Foresight Ventures: Rational Insights into Decentralized Computing Networks
Author: Ian Xu@Foresight Ventures
- The main convergence points of AI + Crypto currently fall into two major categories: Distributed Computing Power and ZKML. For ZKML, you can refer to one of my previous articles. This article will focus on analysis and reflections on the decentralized distributed computing power network.
- Under the trend of the development of large AI models, computing power resources will be the next big battlefield for the coming decade, and it is also the most important thing in the future of human society. It will not only remain in the realm of commercial competition but also become a strategic resource in the game of big countries. Future investments in high-performance computing infrastructure and reserves of computing power will rise exponentially.
- The demand for decentralized distributed computing power networks is greatest in the training of large AI models, but it also faces the greatest challenges and technological bottlenecks, including the need for complex data synchronization and network optimization problems. In addition, data privacy and security are also significant constraints. Although some existing technologies can provide preliminary solutions, they are still not applicable in large-scale distributed training tasks due to the massive computational and communication overheads.
- Decentralized computing power networks have more opportunities to land in model inference, and it can be predicted that the future incremental space is large enough. However, it also faces challenges such as communication delays, data privacy, and model security. Compared with model training, the computation complexity and data interactivity during inference are lower, which is more suitable for execution in a distributed environment.
- Through the case studies of two startups, Together and Gensyn.ai, the overall research direction and specific ideas of decentralized distributed computing power networks are illustrated from the perspectives of technical optimization and incentive layer design.
1. Decentralized Computing Power — Large Model Training
When we discuss the application of distributed computing power during training, we generally focus on training large language models. The primary reason is that the training of small models does not demand significant computing power, and it is not cost-effective to handle data privacy and numerous engineering problems through distribution. Centralized solutions would be more efficient. Large language models, however, require immense computing power, and they are currently in the initial stage of explosive growth. From 2012–2018, the computational requirements of AI approximately doubled every four months. It is currently the focus of computing power demand and is predicted to continue to have enormous incremental demand for the next 5–8 years.
With huge opportunities also come significant challenges. Everyone knows that the field is vast, but where are the specific challenges? Who can target these problems rather than blindly entering the market is the key to identifying excellent projects in this track.
1.1 Overall Training Process
Take the training of a large model with 175 billion parameters as an example. Due to the massive scale of the model, parallel training needs to be carried out on many GPU devices. Suppose there is a centralized server room with 100 GPUs, each with 32GB of memory.
- Data Preparation: First, a large dataset is needed, which includes various data such as Internet information, news, books, etc. These data need to be preprocessed before training, including text cleaning, tokenization, vocabulary building, etc.
- Data Splitting: The processed data is split into multiple batches for parallel processing on multiple GPUs. Assume the batch size chosen is 512, meaning each batch contains 512 text sequences. Then, we divide the entire dataset into multiple batches, forming a batch queue.
- Data Transfer between Devices: At the beginning of each training step, the CPU takes a batch from the batch queue and sends the batch data to the GPU via the PCIe bus. Suppose the average length of each text sequence is 1024 tokens, then the data size of each batch is about 512 * 1024 * 4B = 2MB (assuming each token uses a 4-byte single-precision floating-point number). This data transfer process usually takes only a few milliseconds.
- Parallel Training: After each GPU device receives the data, it begins forward pass and backward pass computations, calculating the gradient of each parameter. Since the model is very large, the memory of a single GPU cannot hold all the parameters, so we use model parallel technology to distribute the model parameters across multiple GPUs.
- Gradient Aggregation and Parameter Update: After the backward pass computation is completed, each GPU obtains the gradients of some parameters. Then, these gradients need to be aggregated among all GPU devices to calculate the global gradient. This requires data transfer through the network. Suppose a 25Gbps network is used, then transferring 700GB of data (assuming each parameter uses a single-precision floating-point number, then 175 billion parameters are about 700GB) takes about 224 seconds. Then, each GPU updates the parameters it stores based on the global gradient.
- Synchronization: After the parameter update, all GPU devices need to synchronize to ensure that they use consistent model parameters for the next step of training. This also requires data transfer through the network.
- Repeat Training Steps: Repeat the above steps until all batches are trained, or a predetermined number of training rounds (epochs) are completed.
This process involves a large amount of data transfer and synchronization, which can become a bottleneck in training efficiency. Therefore, optimizing network bandwidth and latency, as well as using efficient parallel and synchronization strategies, are crucial for large-scale model training.
1.2 Communication Overhead Bottleneck:
It’s worth noting that the bottleneck of communication is also why distributed computing power networks CANNOT currently perform training for large language models.
Nodes need to frequently exchange information to work together, which creates communication overhead. For large language models, due to the enormous number of model parameters, this problem is particularly severe. Communication overhead can be divided into several aspects:
- Data Transfer: During training, nodes need to frequently exchange model parameters and gradient information. This requires the transmission of a large amount of data in the network, consuming a significant amount of network bandwidth. If the network conditions are poor or the distance between computing nodes is large, the delay in data transfer will be high, further increasing the communication overhead.
- Synchronization Issue: Nodes need to work together during training to ensure its correct progress. This requires frequent synchronization operations between nodes, such as updating model parameters, calculating global gradients, etc. These synchronization operations need to transfer a large amount of data in the network and need to wait for all nodes to complete the operation, which leads to a large amount of communication overhead and waiting time.
- Gradient Accumulation and Update: During training, each node needs to calculate its gradient and send it to other nodes for accumulation and update. This requires the transfer of a large amount of gradient data in the network and needs to wait for all nodes to complete the computation and transfer of the gradient, which is another reason for the large communication overhead.
- Data Consistency: It is necessary to ensure that the model parameters of each node remain consistent. This requires frequent data verification and synchronization operations between nodes, which leads to a significant amount of communication overhead.
Although there are some methods to reduce communication overhead, such as parameter and gradient compression, efficient parallel strategies, etc., these methods may introduce additional computational burdens or have negative effects on the training effect of the model. Moreover, these methods cannot completely solve the problem of communication overhead, especially in situations where network conditions are poor or the distance between computing nodes is large.
1.2.1 For instance:
a) Decentralized Distributed Computing Networks
The GPT-3 model contains 175 billion parameters. If we use single-precision floating-point representation (4 bytes per parameter), storing these parameters would require ~700GB of memory. In distributed training, these parameters need to be frequently transmitted and updated between computing nodes.
Assuming we have 100 computing nodes and each node needs to update all parameters at each step, each step would require transmitting about 70TB of data (700GB*100). If we optimistically assume that each step takes 1s, then 70TB of data would need to be transmitted per second. This demand for bandwidth far exceeds the capacity of most networks, and it raises questions of feasibility.
In reality, due to communication latency and network congestion, data transmission time might far exceed 1s. This means that computing nodes might spend most of their time waiting for data transmission rather than performing actual computations. This greatly reduces training efficiency, and this decrease in efficiency isn’t something that can simply be resolved by waiting. It’s the difference between feasibility and infeasibility and can render the entire training process unworkable.
b) Centralized Data Centers
Even within centralized data center environments, training large models still requires intensive communication optimization.
In centralized data center environments, high-performance computing devices form a cluster, sharing computing tasks via a high-speed network. However, even training parameter-intensive models within this high-speed network environment, communication overhead remains a bottleneck because the parameters and gradients of the model need to be frequently transmitted and updated among various computing devices.
As previously mentioned, assume we have 100 computing nodes, each with a network bandwidth of 25Gbps. If each server must update all parameters at each training step, transmitting approximately 700GB of data would take ~224 seconds per training step. Leveraging the advantage of centralized data centers, developers can optimize network topology internally and use technologies like model parallelism to significantly reduce this time.
By contrast, if conducting the same training in a distributed environment, let’s still assume 100 computing nodes, spread globally, with an average network bandwidth of only 1Gbps per node. In this case, transmitting the same 700GB of data would take ~5600 seconds, significantly longer than in a centralized data center. Moreover, due to network latency and congestion, the actual time required might be even longer.
However, compared to a decentralized distributed computing network, optimizing communication overhead in a centralized data center environment is relatively easy. In centralized data centers, computing devices usually connect to the same high-speed network, with relatively good bandwidth and latency. In a distributed computing network, computing nodes might be scattered across the globe, potentially with inferior network conditions, exacerbating the issue of communication overhead.
OpenAI trained GPT-3 using a model parallelism framework called Megatron to solve the problem of communication overhead. Megatron reduces the parameter load and communication overhead for each device by dividing the model’s parameters and processing them in parallel across multiple GPUs. Each device is only responsible for storing and updating a portion of the parameters. At the same time, a high-speed interconnect network is used during training, and network topology is optimized to reduce communication path length.
1.3 Why Decentralized Computing Networks Can’t Achieve These Optimizations
The optimizations could be achieved, but their effectiveness is limited compared to centralized data centers.
- Network Topology Optimization: In a centralized data center, one can directly control network hardware and layout, so network topology can be designed and optimized as needed. However, in a distributed environment, computing nodes are scattered in different geographical locations, say one in China, and one in the U.S., making direct control over their network connections impossible. Though data transmission paths can be optimized via software, it’s less effective than direct hardware network optimization. Besides, due to geographical differences, network latency and bandwidth also vary greatly, further limiting the effect of network topology optimization.
- Model Parallelization: Model parallelization is a technique that splits model parameters across multiple computing nodes, thus improving training speed through parallel processing. This method usually requires frequent data transfer between nodes, hence high network bandwidth and low latency are needed. In centralized data centers where the network bandwidth is high and latency is low, model parallelization can be very effective. However, in distributed environments, due to poor network conditions, model parallelization faces significant constraints.
1.4 Data Security and Privacy Challenges
Almost every step involving data processing and transmission can affect data security and privacy:
- Data Allocation: Training data need to be distributed to various nodes involved in the computation. At this stage, data might be maliciously used or leaked across distributed nodes.
- Model Training: During training, each node uses the data allocated to it to perform calculations and then outputs model parameter updates or gradients. During this process, if the calculation process of a node is compromised or the results are maliciously interpreted, data leakage may occur.
- Parameter and Gradient Aggregation: Outputs from each node need to be aggregated to update the global model. Communication during this aggregation process might also leak information about the training data.
What are the solutions for data privacy issues?
- Secure Multiparty Computation: SMC has been successfully applied in some specific, smaller-scale computational tasks. However, in large-scale distributed training tasks, due to its high computational and communication overhead, it is not yet widely applied.
- Differential Privacy: Used in some data collection and analysis tasks, like Chrome’s user statistics. But in large-scale deep learning tasks, DP can impact the accuracy of the model. Moreover, designing appropriate noise generation and addition mechanisms also poses a challenge.
- Federated Learning: Applied in some edge device model training tasks, like Android keyboard vocabulary prediction. But in larger-scale, distributed training tasks, FL faces issues like high communication overhead and complex coordination.
- Homomorphic Encryption: Already been successfully applied in tasks with smaller computational complexity. However, in large-scale distributed training tasks, due to its high computational overhead, it is not yet widely applied.
Each of the above methods has suitable scenarios and limitations. There is no single method that can entirely solve the data privacy issue in large model training in distributed computing networks.
Can the highly-anticipated ZK solve the data privacy problem during large model training?
In theory, Zero-Knowledge Proof can be used to ensure data privacy in distributed computations, allowing a node to prove that it has performed calculations as stipulated without revealing actual input and output data.
However, actually applying ZKP to large-scale distributed computing network training of large models faces the following bottlenecks:
- Increased computation and communication overhead: Constructing and verifying zero-knowledge proofs require substantial computational resources. Moreover, the communication overhead of ZKP is also high, as the proof itself needs to be transmitted. In the case of large model training, these overheads could become particularly significant. For example, if each mini-batch computation requires generating a proof, this would significantly increase the overall training time and cost.
- Complexity of ZK protocols: Designing and implementing a ZKP protocol suitable for large model training would be very complex. This protocol would need to handle large-scale data and complex computations, and it should be able to deal with potential error reporting.
- Hardware and software compatibility: Using ZKP requires specific hardware and software support, which might not be available on all distributed computing devices.
Applying ZKP to large-scale distributed computing network training of large models would require years of research and development, as well as more focus and resources from the academic community in this direction.
2. Distributed Computing — Model Inference
Another significant scenario for distributed computing is model inference. According to our judgment on the development path of large models, the demand for model training will gradually slow down after reaching a peak as large models mature. However, the need for model inference will exponentially increase with the maturation of large models and Artificial General Intelligence.
In comparison to training tasks, inference tasks generally have lower computational complexity and weaker data interactivity, making them more suitable for a distributed environment.
In a distributed environment, communication between nodes is essential. In a decentralized distributed computing network, nodes might be scattered globally, making network latency a problem, especially for inference tasks that require real-time response.
Model Deployment and Update:
Models need to be deployed to each node. If a model is updated, each node needs to update its model, which can consume a large amount of network bandwidth and time.
Although inference tasks usually only need input data and the model, without needing to send back a large amount of intermediate data and parameters, the input data might still contain sensitive information, such as a user’s personal information.
In a decentralized network, models need to be deployed to untrusted nodes, which could lead to model leakage, raising issues of model property rights and misuse. This could also trigger security and privacy issues, as a node could infer sensitive information by analyzing the behavior of a model that handles sensitive data.
Each node in a decentralized distributed computing network might have different computational capabilities and resources, which could make it challenging to ensure the performance and quality of inference tasks.
During the training phase, models need to iterate repeatedly, and the training process involves calculating forward and backward propagation for each layer, including the computation of activation functions, loss functions, gradients, and weight updates. Thus, the computational complexity of model training is high.
During the inference phase, only a single forward propagation is needed to compute the prediction. For example, in GPT-3, the input text needs to be converted into a vector, which is then propagated forward through each layer of the model (typically Transformer layers), finally producing an output probability distribution used to generate the next word. In Generative Adversarial Networks, the model generates an image based on the input noise vector. These operations only involve forward propagation of the model and do not require computation of gradients or updating of parameters, resulting in lower computational complexity.
During the inference phase, models usually process individual inputs, not large batches of data as in training. Each inference result also depends only on the current input and not on other inputs or outputs, eliminating the need for extensive data interaction and, hence, reducing communication pressure.
Take a generative image model as an example, suppose we use GANs to generate images. We only need to input a noise vector to the model, and the model will generate a corresponding image. In this process, each input generates only one output, and outputs do not depend on each other, eliminating the need for data interaction.
Take GPT-3 as another example; generating each subsequent word only requires the current text input and the model state. There’s no need for interaction with other inputs or outputs, leading to a weaker demand for data interactivity.
Whether it’s large language models or generative image models, inference tasks have relatively low computational complexity and data interactivity, making them more suitable for decentralized distributed computing networks. This is also the direction that most projects are currently focusing on.
3. Projects currently researching in this direction
The technical threshold and breadth of decentralized distributed computing networks are both high, and they also require hardware resource support, so we have not seen too many attempts. For example, let’s look at Together and Gensyn.ai:
Together is a company focusing on open-sourcing large models and dedicated to decentralized AI computing solutions. Their aim is to make AI accessible and usable for anyone, anywhere. Together recently completed a seed round of funding led by Lux Capital, raising 20 million USD.
Together was co-founded by Chris, Percy, and Ce. The initial intention was due to the need for large model training, which requires extensive high-end GPU clusters and significant expenses, with these resources and the capability to train models concentrated in a few large companies.
From my perspective, a reasonable startup planning for distributed computing would be:
Step 1. Open Source Models
To achieve model inference in a decentralized distributed computing network, a prerequisite is that nodes must be able to acquire models at a low cost, which means that models to be used on a decentralized computing network need to be open-source (if the model needs to be used under respective licenses, it will increase the complexity and cost of implementation). For instance, chatgpt, as a non-open-source model, is not suitable for execution on a decentralized computing network.
Therefore, it can be inferred that an invisible barrier for a company providing a decentralized computing network is the need to have a strong capacity for large model development and maintenance. Developing and open-sourcing a powerful base model can to some extent reduce dependence on third-party model open-source, and solve the most basic problem of a decentralized computing network. At the same time, it is also more beneficial to prove that the computing network can effectively carry out the training and inference of large models.
This is what Together has done. The recently released RedPajama, based on LLaMA, is a joint initiative of teams such as Together, Ontocord.ai, ETH DS3Lab, Stanford CRFM, and Hazy Research. Their goal is to develop a series of fully open-source large language models.
Step 2. Implementation of Distributed Computing in Model Inference
As mentioned in the previous two sections, compared to model training, the computation complexity and data interactivity of model inference is lower, which makes it more suitable to be performed in a decentralized distributed environment.
Based on open-source models, the development team of Together has made a series of updates for the RedPajama-INCITE-3B model, such as implementing low-cost fine-tuning using LoRA, making the model run more smoothly on CPUs (especially on MacBook Pros using the M2 Pro processor). At the same time, although the scale of this model is small, its capabilities exceed other models of the same scale, and it has been applied in real-world scenarios such as law and social interactions.
Step3. Implementation of Distributed Computing in Model Training
In the medium and long term, despite facing significant challenges and technical bottlenecks, fulfilling the computing needs for the training of large AI models is definitely the most enticing aspect. At the beginning of its establishment, Together began to layout work on how to overcome communication bottlenecks in decentralized training. They also published a related paper at NeurIPS 2022: “Overcoming Communication Bottlenecks for Decentralized Training”. We can primarily summarize the following directions:
During training in a decentralized environment, since the connections between different nodes have different latencies and bandwidths, it is important to assign tasks that require heavy communication to devices with faster connections. Together has established a model to describe the costs of specific scheduling strategies, better optimizing these strategies to minimize communication costs and maximize training throughput. The Together team also found that even if the network is 100 times slower, the end-to-end training throughput is only 1.7 to 2.3 times slower. Therefore, pursuing the gap between distributed networks and centralized clusters through scheduling optimization is feasible.
Communication Compression Optimization
Together proposed communication compression for forward activation and backward gradients, introducing the AQ-SGD algorithm, which provides strict guarantees for the convergence of stochastic gradient descent. AQ-SGD can fine-tune large base models on slow networks (e.g., 500 Mbps), and compared with the end-to-end training performance in the centralized computing network (e.g., 10 Gbps) under uncompressed conditions, it is only 31% slower. In addition, AQ-SGD can be combined with the most advanced gradient compression techniques (such as QuantizedAdam) to achieve a 10% improvement in end-to-end speed.
The Together team has a comprehensive configuration, and all members have strong academic backgrounds, with industry experts supporting everything from large model development, and cloud computing to hardware optimization. And Together has indeed shown a patient, long-term posture in its path planning, from developing open-source large models to testing idle computing power (like Mac) in distributed computing networks for model inference to the layout of distributed computing power in large model training. It gives a feeling of a big payoff after extensive preparation :)
However, I have not seen many research achievements from Together in the incentive layer. I believe this is as important as technical research and development and is a key factor to ensure the development of the decentralized computing network.
From Together’s technical path, we can roughly understand the process of decentralized computing networks landing on model training and inference, as well as the corresponding R&D focus.
Another crucial aspect that cannot be overlooked is the design of the incentive layer/consensus algorithm for the computing network. For example, an excellent network needs to:
- Ensure that the benefits are attractive enough;
- Ensure that each miner gets the benefits they deserve, including anti-cheating and rewarding more work;
- Ensure tasks are reasonably scheduled and distributed among different nodes, avoiding a large number of idle nodes or overcrowding of some nodes;
- Ensure the incentive algorithm is simple and efficient, without causing excessive system burden and delay.
Let’s see how Gensyn.ai does it:
- Becoming a node
Firstly, in the computing network, solvers compete for the right to handle tasks submitted by users through bidding. Based on the size of the task and the risk of being caught cheating, solvers need to pledge a certain amount.
While updating parameters, the solver generates multiple checkpoints (to ensure the transparency and traceability of the work) and regularly generates cryptographic encrypted inference proofs about the task (proof of work progress).
When the solver completes work and produces some calculation results, the protocol will select a verifier. The verifier also pledges a certain amount (to ensure the verifier honestly performs verification) and decides which part of the computation results needs to be verified based on the provided proofs.
- If there is a disagreement between the solver and the verifier
A data structure based on Merkle trees is used to pinpoint the exact location of disagreement in the computation results. The entire verification operation is on-chain, and cheaters will be deducted the pledged amount.
The design of the incentive and verification algorithms allows Gensyn.ai do not have to replay all results of the entire computation task during the verification process. Instead, it only needs to replicate and verify part of the results based on the provided proofs, which greatly improves the efficiency of verification. At the same time, nodes only need to store part of the computation results, which also reduces the consumption of storage space and computational resources. Additionally, potential cheating nodes cannot predict which parts will be selected for verification, thus reducing the risk of cheating.
This way of verifying disagreements and discovering cheaters can quickly find errors in the computation process without needing to compare the entire computation result (starting from the root node of the Merkle tree, gradually traversing downwards). This is very effective when dealing with large-scale computation tasks.
In summary, Gensyn.ai’s incentive/verification layer design aims for simplicity and efficiency. But currently, this is only at the theoretical level. The specific implementation may still face the following challenges:
- In terms of the economic model, how to set appropriate parameters to effectively prevent fraud without imposing too high a threshold on participants.
- In terms of technical implementation, how to devise an effective periodic cryptographic inference proof is a complex issue requiring advanced cryptographic knowledge.
- On task distribution, how the computing network selects and assigns tasks to different solvers also requires the support of reasonable scheduling algorithms. Simply assigning tasks according to the bidding mechanism seems questionable in terms of efficiency and feasibility. For instance, nodes with strong computing power can handle larger tasks but may not participate in bidding (this involves the incentive issue of node availability), and nodes with low computing power may bid the highest but are not suitable for handling complex large-scale computation tasks.
4. A Bit of Reflection on the Future
The question of who needs a decentralized computational power network has never really been validated. The application of idle computing power in the training of large models, which have a huge demand for computing resources, seems to make the most sense and offers the largest room for imagination. However, constraints like communication and privacy force us to rethink:
Can we truly see hope in the decentralized training of large models?
If we step outside this generally agreed “most logical scenario”, would it not be a large market to apply decentralized computing power to the training of small AI models? From a technical perspective, the current constraints have been solved due to the scale and architecture of the model. Moreover, from the market perspective, we have always thought that the training of large models will be a huge market from now into the future, but does the market for small AI models do not have its allure?
I don’t think so.
Compared to large models, small AI models are easier to deploy and manage, and they are more efficient in terms of processing speed and memory usage. In many application scenarios, users or companies do not need the more universal reasoning capability of large language models but are only focused on a very refined prediction target. Therefore, in most scenarios, small AI models are still a more feasible choice, and should not be overlooked too early in the tide of FOMO on large models.
About Foresight Ventures
Foresight Ventures is dedicated to backing the disruptive innovation of blockchain for the next few decades. We manage multiple funds: a VC fund, an actively-managed secondary fund, a multi-strategy FOF, and a private market secondary fund, with AUM exceeding $400 million. Foresight Ventures adheres to the belief of a “Unique, Independent, Aggressive, Long-Term mindset” and provides extensive support for portfolio companies within a growing ecosystem. Our team is composed of veterans from top financial and technology companies like Sequoia Capital, CICC, Google, Bitmain, and many others.
Disclaimer: All articles by Foresight Ventures are not intended to be investment advice. Individuals should assess their own risk tolerance and make investment decisions prudently.


Carivibe Radio - My DJs. My Music. My Station. Carivibe Radio is the World’s #1 mix show station, featuring the World’s top club DJs. Playing the very best in R&B, Hip Hop, Soca, Reggae, Throwbacks, Rare Grooves, Slow Jams & more…
Listen to 100,000+ live radio stations around the World, on-demand content like podcasts & etc anywhere you go it is with you.


World Party front man Karl Wallenger returns to Austin for this year’s South By Southwest. It’s been a decade since the band released new music, but Wallenger’s showcase will undoubtedly bring out long-time fans and well-wishers.
Wallenger was a member of British band The Waterboys, but left the group in the mid-80s to form World Party, which had a few hits of its own. Check out some videos below.
“Message In The Box”
World Party plays its official SXSW 2011 showcase on Friday, 3.18.11, at 7pm at the Auditorium Shores Stage (Lady Bird Lake). Visit the band online at www.worldparty.net.


Finley Quaye is the brother of prominent guitarist Caleb Quaye. Afterncollaborating with A Guy Called Gerald in Manchester, Finley recordednand co-produced his debut album, Maverick A Strike, in Sheffield withnThe Comsat Angels which was released on Epic Records in 1997. Threenyears after his critically acclaimed debut, Finley resurfaced withnVanguard; a new outlook and musical vision were well rounded and anmaturation marked the result. Vanguard was recorded again in Sheffieldnand released in 2000. Much More Than Much Love was recorded at RAK innLondon, released in 2004 and included the single “Dice”. The songnfeatured contributions from Beth Orton and William Orbit became anminor hit. Although it would be another eight years for a follow-upnalbum, 2008 saw the release of both a new EP, Pound For Pound, and angreatest hits package, The Best Of The Epic Years. A release on thenFrench label Sakifo titled 28th February Road was released in Francenin 2012, followed two years later by a reggae LP called Royal Rasses,nwhich saw Finley working with Norman Grant of the long tenurednJamaican act the Twinkle Brothers, Lloyd Parks, Sly Dunbar and LittlenRoy.


text:
Nepisiguit Centennial Museum/Cultural Centre
Nepisiguit Centennial Building
Édifice centenaire Nepisiguit
Links and documents
Listed on the Canadian Register:
Statement of Significance
Description of Historic Place
The Nepisiguit Centennial Museum/Cultural Centre is a modern international-style building constructed in 1967 as part of Canada’s Centennial celebrations. The building houses the Bathurst Heritage Museum and the Nepisiguit Cultural Centre, and stands on part of the Coronation Park grounds on Douglas Avenue in Bathurst.
The heritage values of the Nepisiguit Centennial Museum/Cultural Centre as a local historic place stem from its architecture, its commemorative significance for the population and for its cultural vocation.
The building’s heritage value can also be found in its architecture and builders. The building was constructed in 1967 as one of the projects commemorating Canada’s Centennial and highlighting the centennial of federalism. Its architecture is typical of the modern international style of that period. The international style is depicted in the sobriety of its lines, its rectangular massing with a flat roof, its horizontal row of windows, and its mix of brick, concrete and steel.
The heritage value is also attributed to the building because it was a community project that brought the two linguistic communities together in a major fundraising campaign for a public library that would serve both groups.
The heritage value of the building also lies in its cultural vocation. Originally built to house the first public library for both linguistic communities, it later became the Nepisiguit Cultural Centre and now houses the Bathurst Heritage Museum.
Source: Bathurst Heritage Trust Commission, Inc.
The character defining elements associated with the location include:
- positioning of the building on a large lot on the Coronation Park grounds;
- proximity of certain institutions such as a school and a church;
- geographic location in the downtown.
The character defining elements associated with the building include:
- rectangular plan;
- flat roof;
- concrete access ramp;
- brick and concrete exterior finish;
- fenestration that wraps around the building;
- integrity of the original interior;
- mezzanines and their varnished wooden railings;
- staircases and banisters.
The character defining elements associated with the building's cultural use include:
- collection of historic and cultural artefacts relating to the Bathurst area.
Local Governments (NB)
Community Planning Act
Theme - Category and Type
- Expressing Intellectual and Cultural Life
- Architecture and Design
- Building Social and Community Life
- Education and Social Well-Being
Function - Category and Type
Architect / Designer
Gavin & Valentine
Location of Supporting Documentation
Bathurst Heritage Trust Commission Inc., 360 Douglas Avenue, Bathurst, NB.
Cross-Reference to Collection

domain: history


text:
Americans are beating cancer in record numbers. Even the number of Americans diagnosed with cancer is down a little. All of that is good news.
In a new report from the National Institutes of Health the findings show increased survival rates for major cancers including lung, colorectal, prostate, and breast cancer. The N.I.H. says the credit goes to more emphasis on prevention, stronger methods of detection, and better treatment options.
The bad news is that minorities are not celebrating these survival rates as much. This includes American Indians and Alaskan natives.
"We still have major differences among different groups of people. There are still disparities in how well patients are going." said Dr. Edward J. Benz Jr., an Oncologist at Dana-Farber Cancer Institute.
There are still concerns that after years of increased community health screenings, the effort is not as frequent now and there is also a drop in research funding. Health experts say that could bring an end to the declining death rate, unless changes are made.

domain: sociology


text:
With over a decade&39;s experience in BPO and contact center operations, Moreno has held increasingly vital leadership positions in the. News, email and search are just the beginning. QB, WR, WR, WR, RB, RB, TE, W/R/T, W/R/T, K, DEF, D, BN, BN, BN, BN, BN. Find Getafe vs Real Betis result on Yahoo Sports. Por Favor, que no sea tan largo, solo de 3 o 4 renglones.
But there is a growing concern that many will be left without as the moratorium on evictions run out at the end of the month. Winds variable at 2 to 6 mph (3. Wearing different colored shoes — one red and one green on Christmas Day — Kamara sprinted for a 40-yard touchdown on the game&39;s opening drive. Public Comment AC96 Risk Based Capital Guidelines State Street Corporation, Boston, MA : Stefan M.
· The vast region of Southern California, much of the San Francisco Bay area and a large francisco pascasio moreno yahoo finance swath of the Central Valley are about to be placed under a sweeping new lockdown in an urgent attempt to slow the rapid rise of coronavirus cases. Find local weather forecasts for Moreno Valley, United States throughout the world. Gavell Executive Vice President and Head of Regulatory and Industry Affairs State Street Corporation 1 Lincoln Street P. com has been visited by 100K+ users in the past month.
Ramon Flying Eagle Gonzalez went missing on Monday, according to a post on the Boone Police Department Facebook page. · The baked structure overlooks the city of San Francisco A mysterious monolith made out of gingerbread appeared in Corona Heights Park in the US city of San Francisco on Christmas Day. Winds variable at 1 to 11 mph (1.
The California Department of Public Health said Saturday the intensive care unit capacity in Southern California and Central Valley hospitals had fallen below a. Note: You are reading this message either because you do not have a standards-compliant browser, or because you can not see our css files. Media coverage of San Francisco’s recent passage of a citywide “wealth tax” has been hard to come by, to say the least. 30 % 63 ° 38 ° Night - Cloudy. After photos were posted on social media, the tall, silver metallic structure drew hikers to the top of the Pine Mountain trail in an Atascadero park, halfway between San. 14 -- Zoox Inc. Francisco Pascasio Moreno BirthdayMonday, BirthplaceBuenos Aires DiedSaturday, Novem pascasio NationalityArgentine Known for Exploration of the Patagonia.
As part of World Connection&39;s continued transformation and growth, President and COO Hui Wu-Curtis has announced the hiring of Guillermo Moreno as Executive Director-Guatemala. Left-hander Alex Claudio agreed to a one-year, . It is unclear who is behind the object, which combines two of &39;s trends - home baking and mysterious structures.
· A Chicago bakery is donating cookies to everyone who donates a coat. Find Pachuca vs Pumas UNAM result on Yahoo Sports. He kicked Moreno in the groin as if he were a punter trying to kick a 60-yard punt. · A walk-on at Auburn University, Greene was a fifth-round draft pick of the Los Angeles Rams in the 1985 NFL draft and went on to play for the Rams, Steelers, Carolina Panthers and San Francisco 49ers. Welcome to Yahoo Fantasy.
The vehicle can carry as many as four passengers, has a motor at each end, travels in either direction and maxes out at 75 miles per hour. · Media coverage of San Francisco’s recent passage of a citywide “wealth tax” has been hard to come by, to say the least. India’s single-day cases have. Yahoo Sports also had it 47-47, giving Figueiredo Rounds 1, 3 and 5. Founder and Chief Technology Officer Jesse Levinson discusses the development of the company&39;s fully autonomous "robotaxi" with no steering wheel that can drive day and night on a single charge. See more results. World Connection Executive francisco pascasio moreno yahoo finance Director-Guatemala Guillermo Moreno. Night - Partly cloudy with a 90% chance of precipitation.
Too many of Britain&39;s companies use formulaic explanations about diversity, climate change policy and leadership that provide little detail for investors, the Financial Reporting Council (FRC) said on Thursday. A record 621 people died of drug overdoses in San Francisco so far this year, a staggering number that far outpaces the 173 deaths from COVID-19 the city has seen thus far. 2 days ago · SAN FRANCISCO (AP) — In true pop-up art fashion, a nearly 7-foot-tall monolith made of gingerbread mysteriously appeared on a San Francisco hilltop on Christmas Day and collapsed the next day. View the latest weather forecasts, maps, news and alerts on Yahoo Weather. The FRC supervises how companies comply with its Stewardship Code of governance best practice, requiring them to explain in a "clear and compelling" way if they choose to ignore some. · Days after the discovery and swift disappearance of two shining metal monoliths half a world apart, another towering structure has popped up and then quickly vanished, this time from the pinnacle of a trail in California.
com&39;s offering. francisco pascasio moreno yahoo finance led to the exposure of 164,683,455 confidential yahoo records, as per the Identity. 1, /PRNewswire/ -- Just in time for the holidays, Holy Grail Steak Co. Like us on Facebook to see similar stories.
Fight of the Year There were a slew of incredible fights in, but the Zhang-Jedrzejczyk fight was just too good to ignore. Find your yodel. That makes Jan Blachowicz the Yahoo Sports MMA Fighter of the Year. Perito Moreno is named for Francisco Pascasio Moreno, whose nickname was Perito. It didn’t matter that Moreno was slinging a sharp jab and. The vast region of Southern California, much of the San Francisco Bay area and a large swath of the Central Valley are about to be placed under a sweeping new lockdown in an urgent attempt to slow the rapid rise of coronavirus cases. The ten richest Americans have a combined wealth of well over half a trillion dollars. Did you miss the UFC 256 main event slugfest between Deiveson Figueiredo and Brandon Moreno from.
It is not just that this bill will do little to provide additional net revenue to a city facing financial ruin; it is that this bill will surely do the exact opposite. Halifax, Nova Scotia--(Newsfile Corp. Francisco P. He played in 228 games, was named to the Pro Bowl five times and is part of the NFL&39;s All-Decade team of the 1990s. Online leader in mail-order luxury proteins introduces Sonoma lamb alongside world-class beef and Korubuta pork portfolio.
UFC 256 result: Deiveson Figueiredo keeps belt after draw with Brandon Moreno. Miami Dolphins running back Myles Gaskin was activated off the COVID-19 reserve list Wednesday. 125 million contract with francisco the Angels, adding the sidearm reliever to their bullpen makeover. Find the francisco pascasio moreno yahoo finance latest Víctor Guzmán news, stats, transfer rumours, photos, titles, clubs, goals scored this season and more. And we might only be beginning to feel the influence of all that buying power in the campaign. The crisis fueled by the powerful painkiller fentanyl could have been far worse if it wasn&39;t for the nearly 3,000 times Narcan was used from January to the beginning of November to save someone from the brink of death, the.
Francisco Pascasio Moreno, también conocido como el Perito Moreno (Buenos Aires, 31 de mayo de 1852 - Buenos Aires 22 de noviembre de 1919), fue un científico, naturalista, conservacionista, político, botánico, explorador y geógrafo de la Generación del Ochenta de la Argentina. 25 % 61 ° 36 ° Cloudy with a high of 62 °F (16. Moreno, Honoris Causa,, he was the first Argentine to travel the area and his son later compiled his Reminiscencias Del Perito Moreno.
· A record 621 people died of drug overdoses in San Francisco so far this year, a staggering number that far outpaces the 173 deaths from COVID-19 the city has seen thus far. 3 °C) and a 90% chance of precipitation. It&39;s no secret that there aren&39;t enough Pfizer vaccine doses for every American who wants one.
To commercialize the technology, Amzon. View Víctor Guzmán profile on Yahoo7 Sports. unfortunately, but tried to make the best. The overnight low will be 40 °F (4. One can be forgiven for wondering if leftist media outlets even see the writing on the city’s wall. francisco pascasio moreno yahoo finance Find local weather forecasts for Banning, United States throughout the world. View full match commentary including video highlights, news, team line-ups, player ratings, stats and more. He spent time on all fours coughing, but got up and continued to fight.
Gaskin is Miami&39;s leading rusher this season even though he hasn&39;t played since Week 4. Apple on Tuesday announced new versions of two of its most popular products: the Apple Watch and the iPad. Box 5225 Boston, com Ma Office of the Comptroller of the Currency Jennifer J. He missed four games because of a knee injury and has been on the COVID list since Dec. The baked structure overlooks the city of San Francisco A mysterious monolith made out of gingerbread appeared in francisco pascasio moreno yahoo finance Corona Heights Park in the US city of San Francisco on Christmas Day. 17, (GLOBE NEWSWIRE) -- The "Cyber Security Market Research Report: By Component, Security Type, Deployment, Enterprise, Use Case, Industry - Global Industry Analysis and Growth Forecast to " report has been added to ResearchAndMarkets.
9 million. More formally known as Dr. The Salvation Army is also putting together a holiday gift drive for kids in need. SAN FRANCISCO, Dec. SAN FRANCISCO (AP) — In true pop-up art fashion, a nearly 7-foot-tall monolith made of gingerbread mysteriously francisco pascasio moreno yahoo finance appeared on a San Francisco hilltop on Christmas Day and collapsed the next day. Like us on Facebook to see similar stories Please give an overall site rating.
Find more questions on United States on Yahoo Answers. See the company profile for America Movil, S. Moreno shrieked in agony and went down. Winds variable at 2 to 9 mph (3. Called the Apple Watch Series 5 and iPad, the devices follow the unveiling of Apple’s latest iPhones, the iPhone 11, 11 Pro and 11 Pro Max.
But there are at least a few million more sitting in a warehouse, waiting for the government to decide where they&39;re headed, Pfizer said. Night - Rain with a 90% chance of precipitation. 25 % 62 ° 42 ° Cloudy with a high of 62 °F (16. Winds variable at 2 to 7 mph (3. · It&39;s no secret that there aren&39;t enough Pfizer vaccine doses for every American who wants one.
· Online leader in mail-order luxury proteins introduces Sonoma lamb alongside world-class beef and Korubuta pork portfolio. Dublin, Nov. NEW ORLEANS — Alvin Kamara tied an NFL record by running for six touchdowns in a game and finished with a career-high 155 yards rushing to help New Orleans beat the Minnesota Vikings 52-33 on Friday and clinch a moreno fourth straight NFC South title.
(AMOV) including business summary, industry/sector information, number of employees, business summary, corporate governance, key. India francisco pascasio moreno yahoo finance is reporting 31,521 newly confirmed coronavirus infections in the past 24 hours, dropping to just over a third of the peak level seen in mid-September. In this role, he. In, 1,473 data breaches in the U. · NEW ORLEANS — Alvin Kamara tied an NFL record by running for six touchdowns in a game and finished with a career-high 155 yards rushing to help New Orleans beat the Minnesota Vikings 52-33 on Friday and clinch a fourth straight NFC South title. From the opening bell, Figueiredo walked Moreno down. So I was pick 9. Christmas comes early: UFC 256, ‘Fight of the Year’ candidate airs Thursday night on ESPN2 MMA Junkie via Yahoo Sports · 2 days ago.
Winds variable at 6 to 12 mph (9. · Initial crash reports indicate the man died from injuries caused by not wearing a seat belt. A (AMX) including business summary, industry/sector information, number of employees, business summary, corporate governance, key. The bout was decided because of a point deduction on Figueiredo in the third round for a low blow. Rain with a high of 56 °F (13. Discover more every day.
welcomes decadently delicious and expertly butchered centerpieces into its portfolio of luxury proteins: Upper Prime Black Angus Prime Rib, Kurobuta Rack of Pork, Kurobuta. - Decem) - ScoZinc Mining Ltd. · Halifax, Nova Scotia--(Newsfile Corp. Find Getafe vs Villarreal result on Yahoo Sports. · Many people are facing evictions and lighting crisis amid the pandemic.
The ten richest Americans have francisco pascasio moreno yahoo finance a combined wealth of well over half a trillion dollars. (TSXV: SZM) ("ScoZinc" or the "Company") is pleased to announce that it has confirmed its gypsum surface rights at the Scotia Mine and is currently proceeding towards a new NI 43-101 Technical Report to determine the additional economics to be added to the Project due to the gypsum potential exploitation. finance Passing Yards 10 yards per point; 1 points at 300 yards; 2 points at 350 yards; 3 points at 400 yards. After receiving emergency use authorization from the Food and Drug Administration last week, Pfizer said Thursday that it has since shipped out the 2. The Dolphins rank 22nd in rushing but ran for 250 yards last week against New England, their highest total since.
-> Trigen investments
-> Wozniak bitcoin gold

domain: news


text:
Sadly the last days of Summer are with us and cooler days and nights are just around the corner so it’s a good time to start thinking about the cost of heating.
Last month our members saved £58.80 per 1000 litres against the average market price, paying just 55.75 pence per litre of heating oil. How did your supplier compare?
Our bulk LPG members are saving between £150 and £260 per annum and we are also able to offer great savings and free delivery on LPG cylinders.
If you would like to find out more about reducing the cost of your heating oil or making a saving on your LPG please email firstname.lastname@example.org or call Sarah on 01789 472611.

domain: finance


I just got two of these. A friend of ours past away and his wife sold them to me. Both have never been fired. I will fire one of them when the time comes.A 1967 Canadian Centennial 30-30 with a 26" octagon barrel. Don't know what it groups but it always hits what I shoot at.


text:
TERRY WILLIAMS MATCH SCORES
For the 100 yard match held
October 9, 2011 at the Springs Rod & Gun Club
Bolt Gun Match
Bart Wineland 03A3 74-1X 85-0X 78-5X 188-0X 423-1X
Steve McQuiston 03A3 87-1X 69-0X 87-2X 172-0X 415-3X
Service Rifle Match
Joe Kanya M1 82-0X 69-0X 73-0X 150-0X 374-0X
What a beautiful day!
We thought the afternoon relay would better Bartís morning score, but nobody showed up so Bart is the winner of the Terry Williams Match for the third year in a row! My wife said: why donít you have Bartís name put on the trophy for three or four years. That way we wonít have to keep going to the trophy shop every year to get it on the trophy. She has an idea there.
Joe Kanya gave his rifle to a young lad to shoot a couple times and ended up only shooting 17 shots at his slow prone target which Joe shot kneeling. He made a nice gesture and the boy really enjoyed the opportunity. He just might become a shooter!
We were disappointed with the turn out. Too nice a day I guess. You guys who wanted to upset Bart blew your chance!
Remember you can check your scores on the Springs Rod & Gun Club web site: www.springsrodandgunclub.org or check out the Gem City Gun club web site: www.gemcitygunclub.org.
Thanks again for coming today.
Pete Mathews (398-4368) Dave Dunkle (398-4052)

domain: hobby


text:
On the surface, there are reasons to believe the Bulls have improved since they fired Fred Hoiberg. The Bulls have won as many times in Jim Boylen’s 14 games as they did in Hoiberg’s 24. The defense has been a good bit better under Boylen’s watch.
The idea that Boylen has improved the Bulls is a flawed one though, for obvious reasons. For starters, Lauri Markkanen and Kris Dunn are back. You try to build a competent defense around Cam Payne and Jabari Parker.
Despite a healthier roster, the Bulls have managed to look noticeably worse offensively. They’ve scored over 100 points just three times under Boylen, regularly electing to take 20 or more seconds off of the shot clock rather than pushing the ball with any semblance of pace.
It would be one thing if Boylen’s strategy of turning back the clock 25 years was leading to wins, but the Bulls have lost nine of the 11 games in which they’ve scored under 100. The atrocious offensive play continued tonight as the Bulls scored just 84 points at home against an under .500 Magic team.
Oh, and the Bulls allowed Orlando, the 6th worst offense in the league, to drop 112 in the United Center.
As badly as we want to watch this young core with hopes of Markkanen, Dunn, Zach LaVine and Wendell Carter one day leading this team back to relevancy, nights like tonight make it hard to stay positive. Nights like tonight don’t benefit anybody.

domain: sports


text:
Resident Trust Funds – Distribution Upon Death
This client alert advises facilities on what to do with the remaining resident trust funds following a resident death. Problems generally arise when the resident, upon admission, fails (or refuses) to designate a named beneficiary.
Avoiding the Issue.
It's important to ensure the resident names a beneficiary for the funds in the event of the
resident’s death. During the admission process, the resident should designate a beneficiary in writing using the Beneficiary Designation Form provided by DHS. A second beneficiary can be named in the event the first beneficiary is unavailable. If the resident does not want to name a friend/relative as a beneficiary, the resident should be encouraged to consider naming a non-profit organization of his/her choice, or even DHS. Remember, the resident’s named beneficiary cannot be an administrator, employee, owner, or representative of the long-term care facility. The facility should document that all beneficiary designations are the result of the resident’s independent choice, and the Beneficiary Designation Form must be completed in
the presence of and signed by two (2) witnesses.
Distribution to the Estate.
Within thirty days of the resident’s death, the facility administrator must provide an accounting, and return all refunds and funds to the personal representative of the deceased resident’s estate. A personal representative is someone appointed by court order to administer the deceased’s estate. If no personal representative has been appointed, which is often the case, then the funds are released to the resident’s named beneficiary or surviving spouse.
What if there is not a personal representative, named beneficiary, or surviving spouse?
If there is no personal representative, named beneficiary, or surviving spouse, or if there is but the person cannot be located, the funds must be deposited into an interest-bearing account in the same county in which the facility is located, if possible. For trust funds of deceased residents that are equal to or over $100, the facility must maintain separate interest-bearing accounts. These accounts must be maintained for five years after the date of the resident’s death unless a probate case is opened sooner. At the expiration of five
years, the funds will need to be returned to the state.
Who needs to be notified when the funds are released?
At the time the funds are disbursed, the nursing facility notifies DHS using the Deceased Resident Personal Trust Fund Form. Beneficiary Receipt Form should be completed and a copy submitted to DHS along with the Deceased Resident Personal Trust Fund Form.
How can Conner & Winters help?
Conner & Winters has experience dealing with a wide variety of day to day and transactional needs for long-term care and other clients. Please contact us if you have any questions or if you would like assistance with this or other matters.

domain: law


text:
« AnteriorContinuar »
THE GREAT TRAGEDIAN.
AMIDST a storm of applause the more than ever-now more than at any curtain fell. The applause continued, period of his long career, during which and the curtain rose once more; and his heart had always throbbed at every the favourite actor, worn out with sound of applause, did he crave more emotion and fatigue, reappeared to and more applause. That man, seemreceive the homage which an enthu- ingly so indifferent, was sick at heart, siastic multitude paid to his genius, and applause alone could cure him !
I saw a proud flush of triumph steal Had he not applause enough ? Did not over his wan face, which lighted it for all Germany acknowledge his greata moment with almost supernaturalness? Did not, Berlin worship him? expression. As he passed behind the True ; but that was not enough: he scenes, amidst the rustling dresses of hungered for more. the rouged and spangled crowd, I I was taken ap to him by Madame observed his face contracted by a pang, Röckel, and introduced as an "Engwhich struck me the more forcibly lish admirer.” Now, for the first time, from its so quickly succeeding the he manifested some pleasure. It was look of triumph. He passed on to his not assuredly what I said—(for alroom without uttering a word—there though, of course, I am always" misto disrobe himself of the kingly gar- taken for a German," so pure is my ments in which he had “ strutted his accent, so correct my diction !)-it brief hour on the stage;" and in a was the fact of my being a foreigner little while again passed me (as I -an Englishman—which made my was hammering out compliments, in praise so acceptable. I was a counyoluble but questionable German, to tryman of Shakspeare's, and, of the pretty little * * *) in his sober- course, a discerning critic of Shaksuited black, and, stepping into his spearian acting. We rapidly passed carriage, drove to the Behren Strasse. over the commonplace bridges of
I knew he was going there, as I conversation, and were soon engaged had been earnestly pressed to meet in a discussion respecting the stage. him that very evening ; so, collecting With nervous energy, and a sort of all my forces, I uttered the happiest feverish irritability, he questioned me thing my German would permit me, about our great actors-our Young, and accompanying it with my most Kean, Kemble, and Macready killing glance, raised the tiny hand of which gave me an opportunity for * * * to my lips and withdrew, per- displaying that nice critical discrimi, fectly charmed with her, and perfectly nation which my friends are kind satisfied with myself.
enough to believe I possess—with There was a brilliant circle that what reason it is not for me to say. night at Madame Röckel's. To use When I told him that, on the whole, the received phrase, “ all Berlin was I was more gratified with the perthere." I found Herr Schoenlein, formances of Shakspeare in Germany, the great actor, surrounded by ad- he turned upon me with sudden quickmirers, more profuse than delicate in ness and askedtheir adulation. He was pale ; looked 6 In what towns ?" wearied. He seemed to heed that " At Berlin and Dresden," I anadmiration so little--and yet, in truth, swered. he needed it so much! Not a muscle “ You have seen Franz, then?” moved-not a smile answered their “ I have." compliments; he received them as if His lip quivered. I saw that I had he had been a statue which a senseless made a mistake. I am not generally crowd adored. Yet, fulsome as the an ass—nay, I am believed to possess compliments were, they were never some little tact; but what demon too fulsome for his greed. He had the could have possessed me to talk of an fever-thirst of praise upon him now actor to an actor?
" Do you think Franz greater than fancy they had not dined, and to see any of your English actors?” he asked them dine next day, you would fancy fretfully.
they had not supped, and breakfasted " Why, I cannot say that exactly. twice. But I was amazingly struck with his Eating is an art. It is also—and performance. My observation, how. this fact we are prone to overlook-a ever, principally applied to the general habit. As a habit it may be enlarged * getting-up.'"
to an indefinite extent; and lisping * But Franz-Franz. I wish to fraüleins have demonstrated the capahear your opinion of him."
city of the human stomach to be such " He is young," I replied ; " has as would make our beauties stare. a fine figure, a noble voice, a grand It must not be supposed that I am carriage, and, although new to the a coxcomb, since nothing can be farstage, and consequently deficient in ther from the truth ; nor must I be some technical matters, yet he has held to share with Lord Byron his that undefinable something which men horror at seeing women eat. In fact call genius."
I like to see the darlings enjoy “Hm!” was the significant an- themselves : but-and I care not who swer.
knows it--to see German women eat, I then saw whither my stupidity is more than I can patiently endure. had led me. This, however, I will Let me cease this digression to resay for myself, if ever I do get into mark that, except myself, the great a dilemma, I have generally readiness tragedian was the only person at of mind enough to extricate myself. I table who was not voracious—and that do not say this out of conceit, for I am because he was unhappy. While not at all conceited—I merely men- knives and forks were playing with tion it as a fact. This is how I turn- reckless energy he talked to me, but ed my blunder to account.
there was a coldness and constraint in 6 Although," said I, “ he has not his manner which plainly told me that your mastery, yet he reminded me a my praises of Franz had deeply morgreat deal of you. I cannot pay him tified him. a higher compliment."
Poor Schoenlein! Unhappy he came To my surprise he did not see the to Madame Röckel's; for, amidst the flattery of this, but moved to another storm of applause which saluted him part of the room; and I did not speak at the theatre, he heard the applause with him again till supper.
which was saluting his rival at DresThis little incident excited my den; and he had left the theatre for a attention. I puzzled my brain for an friendly circle of admirers only to hear explanation of the riddle which his his rival praised by an Englishman. conduct presented, and spoke to seve. All the applause of all Berlin weighed ral of my friends about it, who could as nothing against one compliment only tell me that Schoenlein was jea- paid to Franz! lous of this new actor Franz
It was nearly twelve, and the comDid you ever sup in Berlin, reader? pany had gradually departed. I was If not, let me inform you that supper left alone with Madame Röckel; and, there is a most substantial affair. I as usual, I stayed half-an-hour later had not read Miss Bremer's novels than the others, to have a quiet chat when first I went there; so, not being with her. I wanted to ask her for prepared for the infinite amount of an explanation of Schoenlein's coneating and drinking which is trans- duct. Much as I had seen of the acted in the north, I confess my asto- vanity of actors—well as I knew their nishment was a little mingled with petty jealousy of each other I was disgust to find a supper begin with not prepared for what I had seen that white-beer sonp, (capital soup, by the night. way,) followed by various kinds of Madame Röckel had resumed her fish, amongst them, of course, that knitting-the never-failing accompaneternal hideous carp-roast veal, iment of a German lady-and I drew poultry, pastry, and dessert. To see a chair close to the sofa, and told her the worthy Berliners sup, you would what had passed.
- "His story is a strange one,” she the truth is, he acts because he has said; " and to understand him you an irresistible impulse to act. It is must know it."
a sort of intellectual dram-drinking “ Can you not tell it me?”
which he cannot forego." * Willingly. Schoenlein is a man "To be sure, men are strange bunwell born and well bred, who feels his dles of contradictions; and I suppose profession is a disgrace."
one must give Schoenlein credit for “ A disgrace!"
being sincere." " Very absurd, is it not ? but that “He is his own dupe, for to no is his feeling. At the same time, just one but very intimate friends has he as the opium-eater, knowing the de- ever disclosed his real opinions." gradation of his vice, cannot resist its " Then his life must be a constant fascination-So this actor, with an struggle ?" intense feeling of what he regards as " It is. This it is which has made the sinfulness of the stage, cannot him prematurely old : the struggle of resist its fascination."
his conscience with his passions. But " You astonish me!"
this it is also which gives such touch“He is an austere man-what you ing pathos to his acting-—which makes English would call a puritan-who his voice so mournful that it vibrates looks upon the stage as the theatre through your whole being. As the of vice, and yet cannot quit it because poet's sufferings are sublimed into it is the theatre of his triumphs !" song, and become the delight of man
"But how came he to be an actor!” kind, so from the ground of this
“Why, thrown upon the stage tragedian's despair springs the well when the stage seemed the only of his inspiration, which makes him means of livelihood open to him truly great." forced on it by necessity, success has We were both silent for a few mochained him there. I have heard ments. him say that every time he performs " I have said enough," added Mait is with the conviction that he is dame Rockel, “ to explain how such performing for the last time. But the a man must necessarily be, above all fascination still continues—his heart others, envious-how the success of is still greedy of applause-his mind another must be torture to him. Nostill eager for its accustomed emo- thing but intense vanity could keep tions. He goes on the stage sad, him on the stage. Hitherto he has struggling, and repentant; to leave really had no rival- he has stood alone; it with throbbing pulses and a wild- other tragedians have not been named beating heart. He accepts no en beside him. But now, within the last gagement, he only plays by the night. few weeks, there has arisen this young He has from time to time made Franz, who has only played at Leipsic vigorous efforts to quit the stage, and Dresden, yet whose fame has but at the end of a fortnight he inva- spread all over Germany." riably returns. He once set out for « But I have seen Franz, and I Italy, thinking that if away from assure you he is not so great an actor Germany he should be able to wean as Schoenlein. To be sure, he has himself from the theatre ; but he got youth on his side." no farther than Vienna, and there " It is not his success alone which played for twenty nights."
is so exasperating ; it is because the "But don't you think there must critics, as usual, will do nothing but be a great deal of humbug in all this?" compare the young Franz with the old “Not a bit.”
Schoenlein ; while the public, with its “Do you really believe in his natural inconstancy, begins to discover scruples ?"
that Schoenlein is no longer young. "I know him too well to doubt It is a sad thing,” she pursued, with them. There are many men quite as a faint smile, “ for those who have inconsistent. He deludes himself reigned supreme over audiences to feel with all sorts of sophistry. He per their dynasty is drawing to a close suades himself that he acts only to sad for those who have swayed all realise an independence for his son, hearts, to feel that another is now to and to secure his own old age. But usurp their place. We women know what it is, in a slight degree, when “ Yet, when Franz comes to Berwe grow old. Do we ever grow old, lin, which will be next month, there and know it? When our glass still will then be no possible doubt as to tells us we are young, that the bloom which is the finer actor." is still upon our cheeks, the lustre in "Perhaps not. But the public will our eyes, the witchery in our smiles, nevertheless applaud Franz; and hownow as of yore-and yet what the ever slightly they do so, to the envious glass tells us, what our feelings con- ears of Schoenlein it will sound like firm, we do not see mirrored in the thunder." admiration of those around us! We The clock striking twelve warned also know what it is when we see our me to depart, for in Berlin they keep former adorers pass to newer beauties, early hours; and I went away thinkand we perhaps overhear such a phrase ing of what I had just heard, and spoken of us as, · Yes, she has been feeling no small contempt for Schoenhandsome!' But even we cannot lein's preposterous jealousy: “ What know the actor's triumph or the actor's a contemptible feeling is envy!-as if humiliation. To feel that our presence only one person in the world had a is the signal for applause, that every right to admiration!" word we utter is listened to with At that moment I stepped into a eager interest, that every part we droschke, and was driving to my play is an image which we engrave rooms, when I passed that miserable upon the minds of thousands, there puppy Fürstenberg, whom, I am sorry to abide as a thing of beauty and of to say, little * * * admires so much; wonder--this is beyond us."
though, for the life of me, I never “ But, my dear Madame Röckel, I could see wherefore. Yet this unsee no diminution of admiration for couth German, aping the dandy, Schoenlein in Berlin. Surely no au- usurps all her conversation, even dience can be more enthusiastic. Why when I am by! should he fear a rival?"
It is not that I am jealous, for that " You might as well ask a beauty," is not my character; but I cannot she replied, “why she is jealous of a bear to see so charming a girl so woman less pretty than herself. The miserably deceived in any one as she why is not to be explained by logic, is in Fürstenberg ! for envy does not calculate—it feels."
Schoenlein did not play for a fort- was said, "had all the energy of night, and, as the time of Franz's Schoenlein, with youth, and grace, engagement was drawing near, I and beauty in his favour. The same imagined he was sulking. I commu- power of distinct conception and nicated my suspicions to Madame unexaggerated execution, without Röckel.
Schoenlein's tendency to conventional “I would wager fifty thalers," she points.'” Strangers asked him if replied, "that he has gone to Dresden he had seen Franz. The very waitto see his dreaded rival, and judge for ers at the hotel recommended him to himself."
go and see Franz! It was as Madame Röckel said: Schoenlein never hated his profesgoaded by irresistible jealousy, Schoen- sion so much as at that moment. lein had set off for Dresden to see his Yet, such was his exasperation, that rival play.
he was constantly tempted to appear Arrived there, he was three days on the stage at Dresden, and crush before he could summon resolution to his rival by acting in the same theatre enter the theatre. Franz's name met with him— constantly tempted to him every where. At the table-d'hôte show the fickle public the genius of he heard nothing but praises of Franz: the actor they were fast forgetting. in the newspapers he read nothing but It was the fourth day of his preinvidious comparisons between Franz sence at Dresden. Hamlet was to be and himself, in which the palm was performed that evening, and Schoenawarded to his rival, “ Franz," it lein had resolved to be there. As
the hour drew near, he was seated at as the finest part he had yet a table on that beautiful terrace, which played. no one who has visited Dresden can T hree men seated themselves at ever forget, and which the Hahn Schoenlein's table. In the midst of Hahn has so graphically set before us their enthusiastic criticism one of in her Faustine. He was smoking a them remarkedmeditative cigar, gazing abstractedly “ Well, Franz is certainly very at the promenaders, who, in their gay fine; but it is absurd to compare him dresses, passed to and fro in light happy with Schoenlein." talk, while the sounds of a good orches- "I think him better," said another. tra in the Café came mellowed by the “Nonsense !-you would not say distance, and lent another charm to so if you could see them together. the exhilarating scene. His thoughts You will find that in a little while the were not at all in harmony with that public will come round to my opinion. happy scene-they were fixed mourn. Let them once get over the novelty, fully on his own condition. He felt and they will judge correctly." the sadness of a fallen favourite.
A thrill ran through the actor's There he sat, and saw the sun go frame as he heard this. He called down over the antique bridge-saw the waiter ; paid ; rose; departed. its last rays shimmering on the placid In another instant he was in the bosom of the Elbe, which winds its parterre of the theatre, feverishly undulating course beneath the terrace impatient for the curtain to rise. -saw the groups of promenaders gra- The brief scene between the King dually disappear, and the tables all and Queen, which opens the fourth deserted. The calls for ices, for act, seemed to that impatient man as cigars, for “ light," were becoming if it never would end ; and when rarer and rarer. The music had Rosenkranz was heard within calling, ceased-night had shut in. Still he “Hamlet, Lord Hamlet!" the persat there in the same mournful mood, spiration burst from every pore, and tempted to go to the theatre, so close he trembled like a leaf as Hamlet at hand, but repelled by the idea of appeared, uttering the “Soft--what hearing Franz applauded.
news? Who calls on Hamlet ?" At the conclusion of the third act, Schoenlein heard no more. The several playgoers reappeared upon tones of that voice raised a mist bethe terrace, to cool themselves in the fore his brain--stung and perplexed evening air, and to take an ice. Their him with rage and astonishment. He conversation, of course, turned but heard nothing, saw nothing - his upon one man, and that man was brain was in a whirl. Franz. They spoke of his Hamlet The Hamlet before him-Franz,
the dreaded rival-was his son!
It is necessary here to take a retro- talked about by him were those of spective glance into Schoenlein's his. Shakspeare, Molière, Göthe, and tory, that we may understand the Schiller. These were his household horror wbich possessed him at the gods. Young Franz was early inidiscovery of his son upon the stage. tiated into their beauties, and would
We may readily conceive how his declaim, (in private,) with great gusto, dislike to his profession made him all the long speeches. very sedulous of keeping his child Franz was sent to the university of from all contact with it, lest its fasci. Leipsic, where it was his father's nation should mislead him also. He fond hope he would distinguish himhad never permitted him to see a play self as a student of theology. For the He brought him up strictly, religious. first year he was assiduous enough ; ly, austerely. He had no friends but theology grew inexpressibly weaamong actors : acting was never spo- risome, while poetry became irresisken of in his presence. Yet, by an tibly alluring to him. Göthe's Wilinconsistency easily enough explained, helm Meister fell into his hands, and the works most constantly read and was read with rapture. He fell in

domain: literature


text:
Best of BAM: The End of Woman with Carrie Gress
On today’s Bible Answer Man broadcast, we present an episode of the Hank Unplugged podcast. Hank’s guest is Dr. Carrie Gress, author of The End of Woman: How Smashing the Patriarchy Has Destroyed Us. Hank and Dr. Gress discuss why feminism tried to eradicate the unique femininity of women, how smashing the patriarchy has destroyed women, how our culture can no longer define what a woman is, the ABCs of feminism—abortion, birth control, and casual sex; why feminism hasn’t been challenged, if feminism is the most powerful brand in the world, and the lost girls—the broken women at the roots of feminism.
Download from Google Play
Download from App Store


text:
People have varying opinions on personal style. To some, picking an outfit is more of a chore than a hobby. For others, styling gives the world a sneak peak into your priorities, confidence, and true colors. I teamed up with friend and blogger Vanessa Ulrich of The Primpy Sheep to talk about personal style to discuss finding it, having it, and wearing it!
How would you describe your personal style now?
Taylor: Eclectic, retro, repurposed. My personal style spans decades and stereotypes; and I love using retro/retro-inspired pieces to prove that a look isn’t defined by one piece, but rather, how you style it.
Vanessa: Elegant, chic, thoughtful. I’m very intentional with the looks I style. My husband says I’m an obsessive perfectionist, and maybe I am. I want everything - the color, proportions, textures - to be balanced just so.
How has it evolved over the years?
Taylor: Believe it or not, I had an incredibly preppy style in college. And blonde hair. I thought brand was important for status, but as I’ve grown older, I’ve transitioned to buying clothes/brands for quality, not status.
Vanessa: I used to have a pretty minimalist wardrobe with very little color. But since I started blogging I’ve found I think more like an art director. I always aim to have one focal point in my looks, to draw the eye, and a few unexpected details that you don’t notice until later.
What are you influenced by; what/who inspires you?
Taylor: I draw inspiration from all walks of life - retro advertisements, runway looks, others on social media.
Vanessa: Editorial photography, both in magazines and from photographers I follow on social media.
What does having a personal style mean to you?
Taylor: It means I get to express my confidence and mood through my clothes. Personal style is an art and when I’ve created a look that’s both flattering and authentic, I feel accomplished.
Vanessa: It’s important to how I feel. If I know I’ve done something creative with a look, I feel energized. If I’m wearing something polished, I feel more confident.
What role does fashion play in society today?
Vanessa: It’s a way to have fun, be creative, and say something about yourself to the world. It’s also an indicator of our social tastes and norms. We are less limited by social norms around dressing than we were 50 years ago, or even five years ago. Those walls will only break down more and more.
Taylor: More and more, brands are creating clothes intended to make social statements. Graphic tees, pops of colors, wider size ranges. We are able to shift cultural and social norms through our clothes and the way we wear them.
The fashion industry is often criticized for its unsustainable environmental practices and propagation of a culture of consumption. How do you think the industry will evolve / what needs to change?
Taylor: I think there is an uproar of initiatives for sustainable style. ThredUp, Poshmark, Tradesy, Rent the Runway. To change the industry, I think we need to focus our energy on encouraging sustainability instead of fighting fast fashion.
Vanessa: I see a strong movement towards sustainable production practices, and the use of renewable, biodegradable materials like organic cotton, silk, and wool. I’m also a huge proponent of buying secondhand.
How do you decide what to wear on any given day?
Taylor: During the week, I try to balance practicality with style. My office is always cold so I wear layers; lab safety requires us to wear closed-toed shoes. When I have an event after work, I will usually wear a work-modified version of my planned outfit keeping a change of shoes in my bag.
Vanessa: Five days out of the week I’m dressing for the office, so I usually grab something comfortable without thinking too much about how it looks. Layers are essential to cope with the office air conditioning. I’ll wear flats but bring a change of shoes and a bright lipstick if I have an event after work.
How do you plan the looks you shoot for your blog?
Taylor: Truth is I’m really bad at planning which looks to shoot! I have a lot of pieces I want to capture, and sometimes I’m not sure if I should 1) re-shoot a certain piece styled differently or 2) shoot a new piece entirely. I try on a bunch of things but only wears what feels right in the moment because no matter the look I choose, confidence makes any photo.
Vanessa: The setting is almost as important as the look itself, so I’ll consider the color palette and shapes of where I’m shooting. I usually try on a bunch of different things and take photos, and then review them to see what meshes together best. It’s not effortless!
What’s your go-to piece in your closet right now?
Vanessa: My red Rothy’s flats. They go with everything and they really brighten up a look.
Taylor: Hmm, I would definitely have to say my lilac blazer is a go-to. It brings color, structure, and a chic edge to any minimal look.
What’s going to be trending this summer?
Vanessa: Pink and red. It’s a color palette that has traditionally been a no-no, but I love the power and energy it conveys. Victoria Beckham did a lot with pink and red for her London Fashion Week show back in February, and I’ve been seeing it all over ever since.
Taylor: Piggy-backing on Vanessa’s answer, two-tone and creative forms of asymmetry - asymmetrical jean skirts to two-toned denim - are definitely trending this summer.
Some questions to think about:
Do you have hallmarks of your personal style? What do they say about you?
Are you still in the process of developing your personal style? What has been your biggest challenge?
Are there pieces that you'd consider authentic to your style but you still won't buy/wear?
What do you want your clothes to say about you?
I'd love to hear one or two of your answers in the comments section; and as always, if you have any questions, FEEL FREE TO ASK! My answer is only a comment away!
To see more of Vanessa's style, be sure to check out her Instagram and website, theprimpysheep.com!
Until next time, keep it authentic!

domain: artistic


Say you line up a bunch of people’s heads in a line, all touching one another, and you put the gun on the first guy’s head, how many people will be killed when you fire?
Depends on the gun.
22? Not so many.
50 cal - a whole lot.
Depends on the gun and the specific cartridge you’re using.
A .50 BMG will go through a lot more than a .22LR.
ETA ninja’d by a think alike mind.
If you’re referring to, say, a typical handgun - let’s go with a Glock as the example - I don’t think it would kill any more than 1 person. The bullet would be slowed down too much by the first person’s skull (bear in mind, the bullet has to pass through TWO layers of bone before it gets to the 2nd person) to cause death to the 2nd person.
That’s not even taking into account the fact that the bullet may be deflected within the 1st person’s skull so that it might not even hit the 2nd person.
Shove the bullet down the first guy’s throat until he chokes to death. Then fish it out, and repeat with the second guy, and so on.
The skull is pretty thick, so you’re not going to go very far with a handgun that way. You’d have a much better chance of multiple kills if the bullets go through the chest and manage not to hit ribs along the way.
Here’s a story of a sniper who killed six Taliban with one bullet. To be fair though, he hit a suicide bomber and his explosives detonated, taking out five of his Taliban buddies. That’s probably not what the OP intended.
There’s a scene in Schindler’s List where a death squad lines prisoners up in single file and points a rifle point-blank range. . . maximizing carnage per bullet.
A 9mm FMJ will easily go through one side of a skull and out the other, with plenty of Velocity left to do it again.
It would depend on the bullet type and power factor. A 9mm FMJ certainly can kill more than one person.
On the other hand, a 308 solid steel bullet will pass many.
I suppose if you lined people up behind each other and had them open their mouths and had them lined up in such a way that you could shoot the first one in the mouth so the bullet went through the back of his head and into the next guys mouth and through his head and so on. Then I suppose you could kill more than 1 with a handgun. It would minimize how much skull material the bullet would have to travel through to kill them.
The faster the bullet the more this would be successful is what I think.
First, how are you going to get people to line up for the experiment?
Must we shoot heads? Seems sort of boneheaded to try to penetrate the most bone you can.
Battle ships have big guns, you did not say which guns could be used so I will use one of them.
As was said in a post above, this will kill a lot.
Glad I passed my background check before I posted in this thread.
If you line up the heads sideways you will be shooting through the temporal bones which are thinner than most of the skull . I don’t know what this means in number of heads penetrated
Shooting through an open mouth so the bullet goes through the back of the head is shooting through a minimal amount of bone yet causing maximum damage. Plus, where else on the body could you shoot through one person to hit another with less resistance but still cause instant or near instant death?
Higher probability of kill as its going into the brain easier than thru the teeth/roof of mouth.
It’s a shame Arlen Specter isn’t alive anymore as he was an expertry on single bullets.
I was going with the U-235 bullet in the Thin Man device exploded over Hiroshima … but I think you got me here …
where are Mythbusters when we need them?
The Thin Man was a series of somewhat farcical detective films starring William Powell and Myrna Loy. The bombs dropped on the Japanese cites of Hiroshima and Nagasaki were the “Little Boy” and “Fat Man” respectively.
Thanx for the correction.
The Navy has a fairly new laser gun that is so powerful that they claim, if you put a line of thin people standing closely together they can shoot through 2200 people per mile for a distance of aprox. 900 miles. Adapting for the curvature of the Earth would be necessary.
The Laser Weapon System would not really hurt them with hard nasty projectiles, rather, when shot, it would just put a one foot circular hole in each of their bodies and would just keep moving through.
The NRA is petitioning the US govt to allow the manufacture of, and public gun show sales in the South, and in Chicago.
This human carnage is fast and painless (almost humane), too. This very effective high-energy device can strike “this line of peeps” at the speed of light (186,000 miles per second)!
The cost? Less than a dollar per shot.
My math is suspect…what would therefor be the cost per kill with this weapon?