Leicester vs Derby live streaming free, team news and more.
The Foxes have not won in the Premier League since the start of the season. However, the team has a good chance of winning the title this season. Leicester is in a good shape and has a strong squad. The team is led by Leicester City’s star player, Riyad Mahrez.
The team has not won the title for a long time, but now it is much easier to follow the results of the team. The Foxes are in a fight for the title, and the players have everything necessary to win the title. The main goal of the Leicester City is to win at the first stage of the championship.
Leicester vs. Derby live stream
The match between the Foxes and Derby County is scheduled for the weekend of August 29 and 30. The match will be held at the home stadium of the Fox. The first match of the series was a draw, but the second one was a lot closer. The game ended with a score of 1:1.
In the last season, the Foxe’rs lost to the team from Derby in the first round of the League 1. The teams met in the League Cup, and Leicester won. The players of the club have a good opportunity to win in the next season.
Derby County vs Leicester live score
The last season of the English Premier League was very successful for the Fox’ers. The club won the championship for the second time in a row, and it is now in the fight for a place in the Champions League zone. The season ended with the victory of the Royal Blues in the EPL.
It was the second victory of Leicester in the season, and this time the team won the first match. The second victory was also a draw. The Royal Blues have a chance to win a place at the Champions league zone.
This season, Leicester has a great opportunity to improve its position in the standings. The current season is the third time the Fox team has won the Premier league.
Live score of the Derby County vs. Leicester
The first match between these teams was a victory for the Royal Blue. The fans of both teams had a lot of emotions. The fight for gold medals was intense, and many of the players were injured.
However, the players managed to win gold medals for the third year in arow. The matches of the Champions cup were also successful for Leicester. The last time the club won this tournament was in the year 2000.
Now, the Royal Club has a chance of getting into the Champions club zone. This is the first time in the club’ history that the team is in the top 4 of the Premier. The next season, it will be even more difficult for the team to get into the zone of the top-4.
As for Derby, the club has a lot to prove. The previous season, they lost to Leicester in both the league and the Champions Cup. The new season promises to be more interesting for the fans.
You can follow the live score of both matches of these teams on the sports statistics website. Here, you will find the latest information about the matches of both clubs.
Leicester City� in the current season
The current season of English Premier league is very interesting for fans. Leicester City has a bright future, and now the club is in great shape. The Leicester City looks more like a team that is ready to fight for trophies.
Many of the problems of the previous season have been solved. Riyad is one of the main stars of the current team. He is a player who is loved by the fans and the team players. The player has a contract with the club for another five years.
Riyad has a very good chance to get to the Champions’ club zone in the future. He has a number of important tasks for the club. Among them are:
1. To win the English championship. The City has not been in the position to win it for a while now.
2. To get into Europe. The squad of the City has an excellent chance to do this.
3. To qualify for the Champions’ club zone for the next year.
All this can be done in the upcoming season. The future of the player is bright, and he will be able to do his best to achieve the goals of the fans of the Club.
Main rivals of Leicester City
The main rivals of the squad of Leicester are: Liverpool, Manchester City, Chelsea, Arsenal, Tottenham Hotspur. Each of them has a decent chance to enter the Champions Club zone. However it is the Fox that is in better shape than its rivals.
Manchester City is the main rival of the King City. The Citizens have a number one star player in Riyad. The midfielder has a long contract with Leicester. He will be paid a lot, and his contract is worth a lot.
Liverpool is the other main rival. The Reds have a great chance to qualify for European cups. However they have a long way to go.
Chelsea is a team of young players, and they have not yet been in a position to fight against the main teams. However the players of Leicester have a bright and promising future ahead of them.
Who will win the Premier?
The Premier league of England is the most popular football championship in the world.
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The catch of the day will be bursting with flavor with these season packets! Great on white fish, salmon, scallops. What will you put on your catch of the day?
Lemon Dill: Not just for fish! This blend brings citrus life to anything -- grilled, baked, sauteed, or fried.
By land or Sea was designed especially to complement the mild flavor of seafood, but perfect pairing for those meats of the land. This seasoning provides a BURST of pepper and herb flavor when used as a rub or marinade.
Parisian Blend is delicate and light, perfect to add a bright flavor of to a dish. A layering flavor for Cornish hens, lentils, soups, flat breads, potatoes, and lamb. Wonderful flavor for dips, and sauces.
Twist: fish marinades, salads, vegetables, potatoes, soups
Ingredients for each 1 oz packet:
Delicious Asian Cuisine brought to life with this set. This gift set includes 3- 60 ml bottles. Flavors consist Honey Ginger and Blackberry Ginger Balsamic Vinegar and Toasted Sesame Oil. No substitutions...
Pop, Pop, Pop goes the kernel! This is a small and tender popped corn. We are pleased to announce this is an Indiana Grown item, distributed by Amish Country...
Breakfast inspiration abounds in this gift set. Butter Olive Oil, Blood Orange Olive Oil, Blueberry Balsamic Vinegar, and Maple Balsamic Vinegar are the flavors in this palate pleasing gift. Gift...
Mama Duck's is a Northeast Indiana owned business that has developed a tasty line-up of jams and jellies. Succulent and tart blackberry notes paired with the the complex rich notes...

domain: food


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Behind the News – June 2019
Jun 3, 2019 | AIJAC staff
Rocket and Terror report
On April 28, a rocket was fired, reportedly by Palestinian Islamic Jihad (PIJ), to disrupt ongoing Egyptian-mediated long-term ceasefire negotiations being held indirectly between Hamas and Israel.
A week later, a major escalation from Gaza erupted following an Islamic Jihad sniper attack on Israeli soldiers. A record 690 rockets, mortars and missiles were fired at Israel over approximately 24 hours on May 4-5.
In response, the Israeli Air Force struck hundreds of Hamas and PIJ targets in Gaza and carried out a targetted assassination of a Hamas official involved in smuggling Iranian funds into Gaza to finance terror.
Approximately 86% of the projectiles launched towards southern Israeli cities from Gaza were intercepted by Israel’s Iron Dome missile defence system, but four Israelis civilians were nonetheless killed – one when his car was targetted by a Kornet anti-tank missile fired from Gaza. Dozens of Israelis were injured. According to an Israeli investigation, of the 27 Palestinians killed, at least 74% were members of terrorist organisations. An unofficial ceasefire between Hamas and Israel, reached with the financial assistance of Qatar and Egyptian mediation, ended the escalation.
The “Great March of Return”-themed border clashes that began in March 2018 continued along the Gaza fence, involving incendiary balloons, improvised explosives devices, gunfire, and burning tyres.
Iran announces plan to breach nuclear deal
On May 8, Iranian President Hassan Rouhani announced that the country would cease observing the elements of the 2015 nuclear deal that limited Iranian possession of enriched uranium and heavy water in response to the tightening grip of US sanctions. Iranian officials also said if European states did not meet Iranian demands to compensate them for the sanctions within 60 days, Iran would begin exceeding the 3.67% cap on enrichment levels under the agreement.
Twelve days later, Behrouz Kamalvandi, the spokesperson for Iran’s nuclear agency, told Iranian news agencies that his country had quadrupled its production of low-enriched uranium, and is now expected to reach the 300kg limit on possession of enriched uranium under the nuclear deal “within weeks”.
Experts: IAEA must investigate Iran’s nuclear archive
A report released on April 4 by an independent panel of experts from Harvard University’s Belfer Center for Science and International Affairs called on the International Atomic Energy Agency (IAEA) to investigate findings from the Iranian nuclear archive, extracted from Teheran by Israel in January 2018, and to address the information it contains in future negotiations with Iran on a nuclear deal.
To research the report, the six experts had visited Israel, been briefed by Israeli intelligence officers and been given access to original documents from the nuclear archive. Their report concluded that Iranian leadership, including current President Hassan Rouhani (who was then Secretary of the Supreme National Security Council), approved the state-sanctioned “Amad Project” to build an atomic bomb and this project continues today under different names, both openly and clandestinely, enabling Iran, if it decides to do so, to immediately resume work towards a bomb. The report also concluded that Iran was much closer to constructing a nuclear weapon than previously assumed, and both IAEA monitoring and intelligence organisations failed to detect the true extent of Iran’s illegal nuclear activities.
US ends oil waivers on Iran
US waivers allowing countries to buy Iranian oil without facing American sanctions expired on May 2, following Washington’s April 22 decision not to renew them.
Countries impacted by the decision include China, Greece, India, Italy, Japan, South Korea, Taiwan and Turkey. White House Press Secretary Sarah Sanders said in a statement, “This decision is intended to bring Iran’s oil exports to zero, denying the regime its principal source of revenue.”
Meanwhile, satellite images have revealed some of the ways Teheran is attempting to circumvent those sanctions, according to several reports.
One method Iran has reportedly used for selling contraband oil is tanker-to-tanker sales while at sea. In one instance, an Iranian tanker reportedly transferred its cargo mid-sea to a Russian vessel it met in the Maldives. The Russian ship then delivered the crude oil to northern China, breaching the sanctions.
Dossier exposes Venezuela-Hezbollah-Iran axis
A dossier compiled by Venezuela’s intelligence agency and handed to the New York Times sheds new light on the intimate and well-established relationship between Hezbollah, Iran, and the Venezuelan regime, overseen by former Venezuelan Vice-President Tareck El Aissami and his family.
According to the report, Aissami’s father is a Syrian Hezbollah liaison and wanted to establish the group in Venezuela for intelligence gathering and drug trafficking. Tareck El Aissami has held several senior positions in Venezuela and in these capacities helped issue false documents to Hezbollah and Iranian operatives to expand their networks in South America, including linking them up with the notorious Columbian narco-terrorist insurgent group FARC, it said.
US offers rewards to stop Hezbollah cash flow
The US is offering rewards of up to US$10 million for information leading to the disruption of the financial mechanisms of the Lebanese terror group Hezbollah. The US State and Treasury departments announced that the money would be paid to people who provide information such as the names of Hezbollah donors and financiers, bank records, customs receipts, or evidence of real estate transactions.
The payments will be made by the State Department’s “Rewards for Justice” program, which offers money for information leading to the location of wanted terrorists, but this is the first time the program has been used to target a financial network.
Hamas money laundering in West Bank
Hamas is exploiting Israel’s humanitarian policy of allowing Gazans to export fish and produce to the West Bank in order to fund its West Bank terror activities, according to Israeli media reports based on interviews with Israeli security officials.
The head of Financial Warfare Branch of the IDF’s Central Command, which identifies and confiscates terrorist money in the West Bank said that, instead of letting Palestinian suppliers and retailers in the West Bank and Gaza interact directly, Hamas demands to act as the middleman, and in doing so reinforces its position on both sides and collects revenue from the transactions.
In related news, the Palestinian Al Mezan Center for Human Rights released a fact sheet on April 23 which slammed Hamas for arbitrarily detaining 742 Gazans for their political affiliations between March 2018 and March 2019.
Bundestag: BDS is antisemitic
On May 17, the German Parliament became the first legislature in the European Union to pass a resolution designating the Boycott, Divestment and Sanctions (BDS) movement against Israel as antisemitic.
While non-binding, the resolution will prevent funding for BDS-related events by the Bundestag and calls upon the Government to “not provide premises and facilities under the administration of the Bundestag to organisations that express themselves in antisemitic terms or question Israel’s right to exist.”

domain: news


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Asda has launched a scholarship scheme for farmers that aims to boost innovation in its beef supply chain.
The scholarships will fund three farmers to carry out research of their choosing anywhere in the world. Any Asda beef farmer is eligible to submit plans, with the successful candidates receiving funds to carry out their ideas as well as financial support to cover their absence. The initiative is part of the Beef Link initiative launched last autumn to boost the relationship between farmers, Anglo Beef Processors and Asda.
Shared findings from the research would bring new ways of working that would benefit British beef producers, said Jim Viggars, Asda meat buyer. "Our farmers are the experts in beef production, and are in the best position to propose research that will result in real improvements to their businesses," he said.
Last year Asda announced the extension of its Buy British policy to increase the amount of British beef it stocked.


1995 年 13 巻 4 号 p. 590-596
The effect of tungsten on the HAZ properties in duplex stainless steel was investigated to obtain the high pitting corrosion resistant duplex stainless steel. The steels tested were the modified 25%Cr SUS329J4L duplex stainless steel with the addition of tungsten. The welded joints produced by gas tungsten arc (GTA) welding and simulated HAZ were evaluated in terms of pitting corrosion resistance, impact toughness and microstructures including analysis of precipitates. As results, the tungsten addition up to 2 mass% was effective to improve the pitting corrosion resistance without remarkable deterioration of impact toughness in the HAZ. However, the tungsten addition exceeding 3 mass% decreased the impact toughness in the HAZ as well as pitting corrosion resistance because of accelerating the precipitation of intermetallic compound during the weld thermal cycles. From these findings it was clarified the corrosion resistance of duplex stainless steel is improved in the HAZ by the alloying of proper content of tungsten as well as in the base metal.


Modeling human cancer-related regulatory modules by GA-RNN hybrid algorithms
© Chiang and Chao; licensee BioMed Central Ltd. 2007
Received: 31 October 2006
Accepted: 14 March 2007
Published: 14 March 2007
Modeling cancer-related regulatory modules from gene expression profiling of cancer tissues is expected to contribute to our understanding of cancer biology as well as developments of new diagnose and therapies. Several mathematical models have been used to explore the phenomena of transcriptional regulatory mechanisms in Saccharomyces cerevisiae. However, the contemplating on controlling of feed-forward and feedback loops in transcriptional regulatory mechanisms is not resolved adequately in Saccharomyces cerevisiae, nor is in human cancer cells.
In this study, we introduce a Genetic Algorithm-Recurrent Neural Network (GA-RNN) hybrid method for finding feed-forward regulated genes when given some transcription factors to construct cancer-related regulatory modules in human cancer microarray data. This hybrid approach focuses on the construction of various kinds of regulatory modules, that is, Recurrent Neural Network has the capability of controlling feed-forward and feedback loops in regulatory modules and Genetic Algorithms provide the ability of global searching of common regulated genes. This approach unravels new feed-forward connections in regulatory models by modified multi-layer RNN architectures. We also validate our approach by demonstrating that the connections in our cancer-related regulatory modules have been most identified and verified by previously-published biological documents.
The major contribution provided by this approach is regarding the chain influences upon a set of genes sequentially. In addition, this inverse modeling correctly identifies known oncogenes and their interaction genes in a purely data-driven way.
A regulatory module is a set of genes that is regulated or co-regulated by one or more common transcription factors (TFs). A TF is a protein that binds to a cis-regulatory element (e.g. an enhancer, a TATA box) and thereby, directly or indirectly, positively or negatively affects the initiation of transcription of regulated genes. A cancer-related regulatory module is a set of genes (oncogenes or tumor suppressor genes) that is regulated by one ore more common TFs. Modeling the cancer-related regulatory modules of the cell division cycle in human cells is a critical and fundamental step toward understanding cancers. The aim of this paper is not only to drive cancer-related regulatory modules, but also to identify the relationships of regulations between genes that fit the feed-forward or feedback influences. A feed-forward regulatory module, contains a TF that controls a second TF at later time points and has the additional feature that both TFs bind to common target genes. Therefore, the major contribution of this study is regarding the chain influences upon a set of genes sequentially. That is, to construct a simple cancer-related regulatory pathway with feedback loop and feed-forward controlled relationships achieved by modified Recurrent Neural Network (RNN) architecture . Combining modified multi-layer RNN with the global searching ability of Genetic Algorithms (GA) , this approach can efficiently select regulated target genes as well. We also provide the solution of analysis time-course gene expression data. For example, one particular TF expressed highly in S/G1 phase may regulate its target genes expressed highly in the M (mitotic) phase. That is, our modified GA-RNN hybrid algorithm has the capability of finding target regulated genes at a later time point (e.g. t + 2) when given a TF at an earlier time point (e.g. t).
Machine learning approaches to microarray analysis
There are many types of gene transcriptional regulatory related approaches which have been proposed in the past. Their nature and composition are categorized by several factors: considering gene expression values [3, 4], the causal relationship between genes, e.g. with Bayesian analysis or Dynamic Bayesian Networks[5, 6], and the time domain e.g. discrete or continuous time [7–10]. The genome-wide transcriptional program during the cell cycle has been investigated in a wide range of organisms, including yeast , bacteria , primary human fibroblasts [13, 14], and human HeLa cells . However, consideration of feedback and feed-forward control in regulatory modules is also important. That is, some genes have unique characteristics, for instance, they regulate themselves or they regulate genes in the following further time points. Unfortunately, constructing regulatory modules with feedback and feed-forward controls is not mentioned by [3–6]. Moreover, genes may have one or more activators or inhibitors which co-regulate the transcription levels of genes in regulatory modules. Lots of the cell's activities are organized as sets of genes co-regulated by some particular TFs to respond to different conditions. Therefore, the present challenge is to understand how transcription factors control global gene expression programs, i.e., specific gene expression programs involve regulated transcription of many other genes in different time points or involve regulated transcription of themselves. Our approach aims to provide a system to construct regulatory modules with feedback and feed-forward control mechanisms that illustrate cancer-related genes and their cause-effect relations to other genes.
Recent approaches to gene expression of human cancers
Gene expression profiling has been widely used for cancer research. The results provided by  and  have shown that co-expression of gene pairs in multiple data sets are correlated with functional relatedness. According to , they seek pairs of genes based on the correlation of their expression profiles in multiple data sets, and define these pairs of genes reliably co-expressed to establish a high-confidence network of more than 8,000 genes connected by co-expression links that are observed in the data sets. However, global co-expression patterns have not been determined for cancer, and it is still unknown what are the key genes or gene groups that have been causing or stabilizing the observed global cancer-related patterns. Likewise, it is of interest to know which genes are the factors that initiate the regulation to another possibly pathological state. Hence, we try to deal with this problem by identifying genes whose regulatory functions have interventions in the global cancer-related gene expression profiles.
Results of human cancer data
The experimental results of GA with RNN for human cell cycle data
The minimum RMSE
Notice that the minimum RMSE for GA generations 2000 and 2500 are 0.17 and 0.16, respectively. Comparing these two experimental results, although the number of GA generations is supplementary, there is no conspicuous diminishing for the value of RMSE. Moreover, the maximum number of GA generations for the yeast data set is less than half of the human data set. Searching for "good" combinations of regulated target genes from the human data set yields much more permutations than yeast.
Compare human cancer data results to yeast cell cycle
An example of periodically expressed gene in human cells but not in yeast is the human CDK7 (homologous of S. cerevisiae KIN28). Yeast KIN28 is not found as a TF at the transcriptional level, but the CDK7 is a TF that regulates MO15. Human gene CDC6 is homologous of S. cerevisiae CDC6, which is identified by our system, and is an auto-regulated and crucial TF to GCN5, pRB, and NICD genes while yeast CDC6 is not. The most interesting and complicated gene of the human data set that system came out is E2F1. It is likely that some of the periodically expressed genes in human cell that do not have periodically expressed correspondents in yeast are subject to multiple layers of regulation. It is also reasonable that, multi-layer regulation in human cell, such as the phosphorylation and proteolysis, are known for some well-studied cell cycle genes. Therefore, the regulatory module starting on E2F1 TF shows the chain processes of the regulatory mechanism, which implies the complication of human cancer-related regulatory manipulations. One known gene, p53, also represents an intriguing consequence. After inputting HDAC3 TF to the GA-RNN algorithm, some negative values are reported by the neural network weight matrix, which indicates inhibitor targets. It appears that there is a similar case, the GATA2, down-regulated by HDAC3 as well, and both are confirmed by Juan et al.  and Ozawa et al. . These listed genes are strongly expressed in proliferative tumors, and have regulatory relationships with other genes. This may further prove to be a useful source of additional drug targets of this kind. On the other hand, most of the genes identified by our system periodically expressed in both species are involved in DNA replication, DNA repair, DNA metabolism and mitosis. In the viewpoint of biology, these genes involved in mitosis or DNA replication, in all probability, have connections with cancer diseases.
The construction of cancer-related regulatory modules from temporal expression data is one of the most important problems in computational biology. It is acknowledged that the causes of heterogeneity genetic-related circumstances, such as the cell cycle, or cancer diseases, are products of complex interactions between genes over time. The analysis of cancer-related gene expression data will thus become increasingly widespread. When appraising approaches for discovery of cancer-related regulatory modules, the amount and type of sources of data must be taken into account. Besides, the approach must be capable of handling noisy and high dimensional gene expression data. The approach described here has been shown to be effective with real-world expression data. The stochastic nature of GA means that the same results can not be expected from each run of the algorithm, and the GA is run for a fixed number of generations for each output of regulatory modules. However, to increase the number of genes that the GA can select from, it could require more GA generations. As a result, increasing the GA generations also increases the computational time, although it does show that results on microarray data can be discovered correctly by the GA used in our approach. In addition, this approach builds modules "piece by piece", that is, regulatory module by regulatory module. Imagine that the network motif described in section 2 is one of the transcriptional regulatory mechanism units with a specific set of genes, including the influences and the targets. We discover all the formed units one by one and eventually join these units by their simultaneously existing TFs. The above-mentioned contents are the advantages of generating smaller but more precise regulatory modules, in that each of the paths or the units (or genes) in the modules can be seen without being masked by other connections. It is not the same as traditional complicated regulatory relationships, which are too many to visualize as a network to yield useful information in a digestible format for biologists.
Compare to related researches
The ordering of regulatory processing can be displayed faithfully by this approach, especially the feed-forward motif, which represents a very simple regulator pathway. The phenomenon of this biology mechanism is often seen but ignored when constructing regulatory modules. Bayesian Networks have been proven to be an efficient methodology to reveal the cause-effect relationships from microarray experimental data, but may be deficient in dealing with the control of feedback or feed-forward issues. A major contribution provided by this approach is the discovery of not only the cause-effect relationships between genes but also the chain influences upon a set of genes sequentially. The mechanism of chain influences is achieved by modified RNN architecture, which includes the nonlinear mapping capability and the ability of time delay in constructing regulatory modules. The other advantage of this study is the power of global searching for regulated target genes provided by GA. Those selected target genes are judged whether they are "true target genes" or not according to the RMSE provided by RNN, and the results substantiate the capability of our hybrid GA-RNN method. Compared to  (see additional file 2), this paper limits potential regulators to those genes with either earlier or simultaneous expression changes (up- or down-regulation) in relation to their target genes, which we also achieve the results. Moreover, we provide feedback and feed-forward regulation control relations between transcription factors and their targets, that is, we contribute more complicated regulatory relationships of regulatory modules.
Compared to Keedwell et al. , which uses a supervised single-layer artificial neural network (ANN) to construct the regulatory connections between genes, the first improvement of our approach is that we use modified multi-layer RNN to complete the feed-forward, feedback, auto-regulate, and multi-input regulatory modules, which means we show clearly the transcriptional regulatory mechanisms. Secondly, Keedwell et al.  provided most of the significant connections in the network by repeated GA. In our approach, we intersect the regulatory modules that output from different GA generations. Take Table 4 as an example, the GA generations for human cell cycle data are 100, 500, 1000, 1500, 2000, and 2500, respectively. We collect the repeated regulatory modules that are appeared in 1000, 1500, 2000, and 2500 generations. It means that the significant regulatory modules are aggregated. Finally, Keedwell et al. construct their regulatory connections by microarray expression values; nevertheless, we also consider the transcription factor binding sites sequences, which consider more biological factors while constructing regulatory modules. We also provide more biological evidences for human cell cycle data, and the results compared with  are listed in additional file 1.
We combine the GA and RNN computing approaches to construct the cancer-related regulatory modules in silico. Upon the microarray data and the sequences of transcription factor binding sites, the approach has been shown to be able to accurately fit the data on which it is trained. We also observe that some TFs play critical roles in various motifs. In other words, some functions of TFs are fit for several kinds of regulatory modules. We then adopt these characteristics by training the RBF classifier  for categorizing TFs. Additionally, the experimental results have proven that the GA-RNN hybrid algorithm has the capability of constructing the feedback and feed-forward regulatory modules. RNNs with diversified architectures indicate varied regulatory mechanisms to construct complete regulatory modules with feedback and feed-forward controls. Combining modified RNN with GA, it provides the global searching capacities to find proper target regulated genes for some TFs. The chromosomes that the GA used are combinations of target genes and the crossover and mutation operators used by GA on all chromosomes alter the choice of output gene combinations. This approach is on the basis of both gene expression data and sequences data, so it is time significant and binding region significant data analysis. Summing up, since this method has been previously shown to also classify TFs as well and then construct regulatory modules, it can be considered a candidate multipurpose tool for microarray expression data analysis.
Human cell cycle microarray data
Microarray time course measurement of genome-wide mRNA expression levels allows genome-wide prediction of cell division cycle regulated genes. In each cell division cycle, cells pass through four phases, namely, M-G2-S-G1, in a fixed order. Each cell division cycle regulates gene expressions in one of these phases, and results in a rise in the possibility that the cell division cycle regulated genes would reveal periodic expressions if they are studied for more than one cycle. This phenomenon is the basis for detecting genes with oscillated expressions in synchronized cell culture to discover the cell division cycle regulated genes. Data from Whitfield et al.  is downloaded from the reference web site. The genome-wide program of gene expression during the cell division cycle in a human cancer cell line (HeLa) is characterized using cDNA microarrays. The goal of human cell cycle analysis from Whitfield et al. is to identify >850 genes periodically expressed during the cell cycle, and to show that most of these genes have been previously associated with the proliferation of tumors during the human cell division cycle as well. The data in this report provide a comprehensive catalog of cell cycle regulated genes that can serve as a starting point for functional discovery. We adopt this data set to construct cancer-related regulatory modules with feedback or feed-forward controlled target genes which are regulated by some specific TFs.
Yeast cell cycle data
The data of Spellman et al.  is downloaded from the reference web site. We use this data set to construct regulatory modules and target genes which are also regulated by some specific TFs. Since this data set has been used to construct regulatory modules by various approaches in the past, we regard it as the testing data set to prove the efficiency of our approach. The experimental results and biological supports are provided in additional file 2 and additional file 3.
Transcription factor binding sites
Our computational method attempts to integrate gene expression data and sequence data. Transcription factors bind short DNA motifs, namely, the transcription factor binding site, which plays a central role in recruiting the transcriptional mechanism at the promoters of genes and leading to the initiation of their transcription. As a result, we collect known transcription factor binding sites sequences from ENSEMBL , TRANSFAC , SGD  and YPD  for human and yeast, which are listed in additional file 4.
The network motifs
The encoded numbers of amino acids
Categorize human cell cycle-related transcription factors by RBF
Some examples of regrouped TFs for Homo sapiens
Encoded catalog number of RBF classifier
Under this approach, the RBF network architecture is one input layer with two kinds of input data, one hidden layer, and one output layer, which is illustrated in additional file 6.
Construction of regulatory modules
RNNs are neural networks with one or more feedback loops. Given a multilayer perceptron as the basic building block, we may have feedback from the output neurons of the multilayer perceptron to the input layer. Similarly, the architectures of gene regulatory modules also have feedback from the target genes to TFs, which represent positive or negative effects on those genes that influence themselves. When the multilayer perceptron has two or more hidden layers, the possible forms of global feedback expand even further, such as the feed-forward motif. We train different RNN architectural layouts for various network modules, as described in the material section.
where the e i (t) is the gene expression level for the i th gene (m + 1 ≤ i ≤ m + n, n is the number of beginning TFs), w ki (m + 1 ≤ i ≤ m + n) represents the effect of the k th gene on the i th gene, and B is the bias. The x i (t) represents the m neurons in the hidden layer that are connected to the feedback nodes in the input layer, and the matrix w ki (1 ≤ i ≤ m) represents the synaptic weights of the m neurons. A negative value of w ki represents the inhibition of the k th gene on the i th gene, while a positive value indicates the activation controls. The ϕ(), is a nonlinear sigmoidal function, usually in the form of ϕ(z) = 1/(1 + exp-z). The symbol B represents the bias, and the matrix w kb contains of the weights that represent bias terms applied to neuron 1 to k. The x k (t + 1) represents the first hidden layer in the gene feed-forward regulated RNN, which stands for biological second ordered TFs (controlled by the starter TFs); the second and third hidden layers are listed as follows, respectively:
where the w' pk is a weight matrix, for 1 ≤ k ≤ m, and B' is the bias for this hidden layer. As in Figure 2, the third hidden layer contains e i (t) and y p (t + 1) to demonstrate the expression values of the starter TFs and TFs controlled by themselves, respectively, and to co-regulate their common target genes described as:
It is logical to assume that the time stamp of target genes is marked as t + 2, t + 1 for controlled TFs, and time stamp t for the starter TFs. In transcriptional progresses, regulatory pathway follows the prescribed order to "turn-on" or "turn-off" some target genes, and that is why we design a gene feed-forward regulated RNN architecture to fit the characteristic of the regulatory module. In the problem of regulatory module inference, the goal is to recover the regulatory interactions w ki , w' pk , w'' qj and w''' sq . The instantaneous sum of squared errors at time t is defined in terms of E(t) by
The objective of the learning process is to minimize a cost function obtained by summing E(t) over all time t; that is,
which measures the deviation of network output O(t) from the measurement (the target) d(t). We use gradient descent to determine the weights of the network and the weights correction of this gene feed-forward regulated RNN in the training phase are as follows:
where the η, η', η'' and η''' represent the learning rate. The first derivative of O s with respect to w ki , w' pk , w qj '' and w sq ''' are listed as follows:
Figures 1(b) and 1(c) demonstrate the RNN architectures for auto-regulate and multi-input motifs, respectively. The major difference between figure 1(b) and 1(c) is that the feedback comes from the output neurons or the hidden neurons of the multilayer perceptron to the input layer. Especially for figure 1(c), the single-input motif can be considered a subclass of the multi-input motif, and that is the reason we use the same RNN architecture to represent single-input and multi-input motifs.
Input: various transcription factors
Output: regulatory modules with feedback and feed-forward control
For each transcription factor
Randomly choose one TF A as the "input" gene, geneA.
If geneA is labeled as "010", then run steps 3 ~ 9 three times, one for the single-input motif RNN architecture, another for the multi-input motif RNN architecture, and the other for the feed-forward motif RNN architecture. It infers that, we have designed several RNN architectures for different motifs that are described in above section.
Use the genetic algorithm (GA) to generate combinations of M genes (gene1, gene2, ..., genem) to represent the target genes that are regulated by geneA. Each combination is a chromosome. The initial set of combinations is composed of the initial population of chromosomes.
The training set, including the initial population of chromosomes and geneA, will consist of the microarray expression values for all the time points, and the initial population of chromosomes will be the target output for the RNN.
Execute the gradient descent algorithm on this training data via the RNN to determine the weights between the input genes and the output genes until stopping criterion is met.
Return the RMSE of RNN to GA. This is the fitted value for a particular chromosome.
Repeat 3, 4, and 5 for each chromosome.
Repeat steps 3~6 as a GA run, using crossover and mutation operators on all chromosomes to alter the choice of output gene combinations.
When some stopping criterion is met, the GA stops. Record the best chromosome and the weights of the RNN.
Change another TF (i.e. geneB), until no TFs are left.
GA and RNN parameter settings
Yeast Cell Cycle Data set
Human Cell Cycle Data set
One Point, crossover rate (0.9)
One Point, crossover rate (0.8)
Random, mutation rate (0.05)
Random, mutation rate (0.1)
50 ~ 250
100 ~ 250
100 ~ 1000
100 ~ 2500
50 ~ 100
100 ~ 200
List of abbreviations
- Genetic Algorithm (GA):
Recurrent Neural Network (RNN), Transcription Factors (TFs), Radial Basis Function (RBF), Dynamic Bayesian Network (DBN)
This research work was supported in part by Research Grant NSC95-2221-E-006-321 from the National Science Council, Taiwan.
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text:
The roles of forests in nature can be listed as cleansing water, stabilizing the soil, cycling nutrients, controlling the climate, absorbing carbon dioxide, and producing oxygen. They are the habitats for the wildlife, and an important segment of the country’s economic wealth [1
]. However, every year millions of acres of forest are lost because of forest fires. The forest fires can be divided into two broad classes; wildfires and prescribed fires. Wildfires are either caused by accidental or malicious acts of human (almost 90% of wildfires in U.S [2
]) or by nature (lightning, etc.) (around 10% of wildfires in USA [2
]). They are not planned by forest managers and do not occur under controlled settings [2
], and pose severe hazards to wildlife and society. According to National Interagency Fire Center, from 1 January to 30 November 2017 there were 56,186 wildfires in U.S. causing around 9.2 million acres of forest loss [3
]. According to Verisk’s 2017 wildfire risk analysis, wildfires caused $
5.1 billion loss to U.S. within last 10 years [4
]. Additionally, 4.5 million U.S. homes are identified at high or extreme risk of wildfire [4
]. It is crucial to detect and suppress the wildfires as early as possible; due to the rapid convection spread and long combustion cycle [1
]. However, early intervention is not usually possible due to terrain that is hard to access and the impact of wind, intensified by various fuel sources contained in the forests. The fuels of wildfires can be listed as understory foliage, small or large branches, upper layers of the forest floor, and treetop residues [2
]. The fuels can also be categorized as surface fuels versus aerial fuels. Surface fuels include combustible material lying on or immediately above the ground, roots and organic soils. Duff, litter, and low-lying vegetative growth are accounted as the principal surface fuels. Duff is composed of layers of partially decomposed organic matter on the forest floor, and has little impact on the forward rate of spread of a fire, but support a slow, smoldering type of combustion [2
]. Litter consists of fallen leaves, needles, twigs, bark, cones, and small branches that have not decayed sufficiently. The low-lying vegetation includes grasses, low shrubs, ferns, seedlings, and other small plants. On the other hand, aerial fuels include all live and dead material not in direct contact with the ground such as tree branches and foliage due to volatile oils and resins [2
]. Besides the possible fuels existing on forests, it is important to understand the wildfire behavior. There are four descriptors of wildfire behaviors: rate of spread (chains/hour), heat per unit area (Btu/ft2
), flame length (feet), and fireline intensity (Btu/ft/s) [5
]. Rate of spread is the forward rate of spread at the head of a surface fire, whereas heat per unit area is a measure of heat released by a square foot of fuel within the flaming zone. Flame length is the length from the midway of active flaming zone to the average position of the flame tip, while fireline intensity is the amount of heat released per second by a foot wide slice of the flaming combustion zone. The latter two descriptors are the basis for the fire suppression interpretation [5
]. Table 1
shows the suppression interpretations based on the flame length and fireline intensity [5
]. Heat per unit area is equal to the fireline intensity divided by the rate of spread. Thus, for a given fireline intensity, the faster the rate of spread, the less heat will be directed to the site. On the other hand, a slow moving fire will concentrate substantial heat on the site [7
The surface fire behavior chart in Figure 1
demonstrates these descriptors. This chart is developed by utilizing the programs “BehavePlus Version 5.0.5 and Fire Characteristics Chart v2.0”. Four vegetation types were considered for this surface model as a replication of the model provided by Andrews, et al. (2011) [6
]. Legend provided on the figure presents the vegetation models. These models represent different regions of the heat per unit area versus rate of spread graph. Therefore, short grass, timber litter, short needle litter, and chapparal vegetations are included in the experimental design of the conceptual model. The main objective of our research is proposing a system to assist wildfire fighting mainly for these four vegetation models, due to the fact that they represent all different regions on the rate of spread versus heat per unit area chart as shown in Figure 1
. For instance, short grass fires, which are coded as number ‘1’ in the chart, resemble the wildfire behavior of high rate of spread (chains/hr) and low heat per unit area (Btu/ft2
). This way, the system could be feasible to be applied for a wide spectrum of vegetation and landscapes.
The conceptual design is based on fire extinguishing balls being released from a small unmanned aircraft system (UAS) to mitigate the risks associated with wildfires to manned crafts, firefighter crew, and society. The proposed remote-sensing technology concept can be used to monitor, detect, diagnose, prognose all categories in Table 1
, whereas the fire-extinguishing balls can be effective for the categories up to 8 feet. It could essentially be applicable in wildland urban interface zone fires rather than large scale forest fires. A fire extinguishing ball is a sphere-shaped product made of Styrofoam filled with environmentally friendly non-toxic chemical powders. The manufacturers claim that the ball self-activates within at least 3 seconds of contact with the fire; explodes and releases the extinguishing agents [8
]. There are currently two main brands of fire extinguishing balls in the marketplace: the Elide and the AFO. Elide is made in Thailand, whereas AFO is made in China. The Elide ball is 1.5 ± 0.2 kg, with a diameter of 147 mm [8
]. AFO balls are available in three different sizes; the smallest ball weighs around 0.5 kg, the medium ball weighs around 0.7 kg, and the largest ball weights around 1.3 kg. The Elide ball is the patented pioneer version with global certifications including ISO 9001:2008. The manufacturers of both brands claim that these balls are effective against fires involving solid burning materials (Class A), flammable liquids and gases (Class B), and energized electrical equipment (Class C) [8
]. However, no information with respect to effectiveness for wildfires are provided by the manufacturers. Thus, the objective of this initial part of the research was to experiment with the use of these balls for building fires and wildfires. Figure 2
shows the Elide and AFO fire extinguishing balls.
There is a growing need to use drones with diverse capabilities and various civilian and military applications including search and rescue missions, environmental protection, mailing and delivery, active weapon engagement, space and marine drones, etc. [10
]. This paper specifically emphasizes the use of drones in firefighting applications. The time to suppress a forest fire is critical with regards to the fire burden consisting of economic, environmental, and social losses [1
]. To decrease the fire burden, currently UASs are used by several fire departments nationwide for search and rescue operations, and for situational awareness assessed by monitoring (finding a potential fire or hot spot), detection (triggering an alarm to inform related operators and personnel), diagnosis (determining the fire’s location and extent and tracking its progress), and prognosis (predicting the future of the fire) [11
] thanks to the remote-sensing capabilities via incorporated sensors and processing units.
Scientific research on the use of drones have been conducted from both technical and non-technical perspectives in the last decade. The non-technical aspect is based mainly on understanding society’s attitudes towards drones. Several survey studies addressed this issue [12
]. The common finding from these studies is that public perception of drones is dependent on the application. Firefighting applications of drones are well supported by the public. Another non-technical aspect is the economic feasibility and justification. For instance, Laszlo et al., studied the economic effectiveness of using drones at forest fires by proposing three approaches [17
]. On the other hand, the technical aspect of using drones for firefighting has focused on remote sensing, simulation studies, and use of various fire suppressants.
UAS-based remote sensing with computer vision is a rapid, mobile, and low-cost alternative or supplement to the traditional sensing technologies; ground-based systems, manned air vehicles, and satellite-based systems. The images retrieved from satellites are not sufficient to create effective firefighting missions due to low temporal and low spatial resolutions, and ineffectiveness in populated areas [18
]. Ground measurement equipment may suffer from restricted surveillance ranges, and manned aircraft are typically expensive [1
]. The firefighters’ need for frequent and high-quality information with regards to fire behavior [20
] could be achieved by autonomous UAS even under low light and high smoke conditions by means of the embedded sensors with low cost. The evolution of using UAS for fire imaging started with using infrared sensors (cameras) detecting the radiation emitted by fires [21
]. Infrared sensors require a direct view of the radiation source for effective results [19
]. Visual cameras, on the other hand, have been used to detect the smoke produced by fire under daylight conditions. Visual cameras can mainly provide flame height and angle, and fire’s location and width. Fire detection with visual cameras is mainly based on contrast, texture, and motion analysis [19
]. Another early method is the use of light detection and ranging (LIDAR) devices to identify the concentration of fire smoke particles [22
There are several simulation studies showing promising results for swarms of UAS to monitor, detect, diagnose, and prognose wildfires. For instance, Merino et al., presented a system of heterogeneous UAS incorporated with infrared and visual cameras to reduce the number of false fire alarms by means of data fusion techniques [23
]. Howden and Hendtlass described an algorithm that performs localized, rather than centralized, control of multiple UASs that surveys complex areas for fires [25
]. Considering the results of the simulation runs, their algorithm is proven to be robust for adapting to loss or addition of one or more UASs. Pham et al. (2017) also developed a decentralized algorithm for a team of UASs to track the fire spreading boundaries [26
]. Their algorithm ensures that collisions are avoided between UASs. Yuan et al. (2017) developed a forest fire detection model using color and motion-based analysis [11
]. The reliability and accuracy of their model in forest fire detection was proven by two experiments; one in a real forest fire video recorded by an aircraft, and one in a real-time indoor fire video gathered by a UAS. Similarly, Alexis et al., (2009) presented a decentralized autonomous system of multiple UASs to monitor the perimeter of the forest fire [27
]. Casbeer et al., in a simulation study, developed path planning algorithms utilizing infrared images to track the perimeter of simulated forest fires for both single UAS and multiple UASs scenarios. Multiple UAS algorithms allowed more frequent and detailed updates to the firefighters with respect to the perimeter and location [1
]. On the other hand, Lee et al., evaluated five deep convolutional neural networks for detection of wildfires [18
]. The majority of the deep convolutional networks were identified to be effective in detecting wildfires by analyzing aerial images. Dios et al., (2011) tested UAS under several scenarios measuring sources of errors in detecting the forest fires with infrared and visual cameras. Their real-time experiments showed promising results for use of UAS incorporating data from several cameras by statistical data fusion methods [19
Although the ongoing research on using UAS to detect wildfires has shown promising progress, the development of such systems, including software, hardware, and applications, is still at a minimum [1
]. Moreover, what we are focusing that is different from the previous researchers’ work is developing a remote-sensing capability that will give an alarm not only for spot fires, but also for the detection of the fire head and flanks’ risk of spreading to a building, fences, or firefighting crew. Thus, the remote sensing will be designed to detect spot fires, buildings or fences, firefighters, fire behavior, and based on that will recognize the risk of the fire spreading to any building, fences, or firefighter and trigger an alarm with precise location parameters. The design of this remote-sensing system is an ongoing project, but it is out of the scope of this particular paper.
Besides the use of UAS for remote sensing, commercial uses for fire suppression has not been possible due to the restricted payload and flight time capacities and the existing research on using UAS to suppress fire is very limited.
The first set of studies used or recommended the use of water as the fire suppressant. One of these studies was conducted by Lockheed Martin by demonstrating a collaborative system including a UAS and a helicopter. The hot spots identified by the UAS were attacked by the helicopter by dropping water [28
]. Several other companies, such as Aerones, Nitrofirex, Singular Aircraft have also been working on developing drone systems that utilize water to suppress building or wild fires [29
]. Phan and Liu (2008) proposed a system including an airship, UAS and unmanned ground vehicles (UGVs). The airship, which is the top level of the hierarchy, generates a mission plan by utilizing wildfire, UAS, and UGV dynamic models. It sends commands to the UASs and UGVs to travel to certain waypoints for them to suppress the fire. This system has not been tested in real life, but simulation tests have been planned albeit not executed yet [32
]. Qin et al. (2017) built a UAS that can autonomously handle the tasks of collecting water, transporting it to the specific fire point, and releasing the water onto the fire. The system was tested in outdoor experiments in both fair and windy conditions successfully [33
]. Yet, considering large scale use of these two concepts in the future, with a theme of dropping water, leaves many doubts on how UASs might find water sources to collect water and respond to a fire in a prompt fashion. Even though their systems work well in theory, we believe they would not be practical unless the fire is in a remote area right next to a large water source. Also, the potential water damage to buildings is not negligible.
There are few studies that considered fire suppressants other than water. In a simulation study, Kumar et al. developed a control model for multiple UASs to detect the fire front and also to fight the fire with limitless fire suppressant fluid [34
]. They tested their model with use of 10 UASs via simulation. Yet, their system has not been tested in a real life scenario. Also, the assumption of limitless suppressant fluid is not practical. As undergraduate design projects at Florida International University (FIU), a student team designed a quadcopter with a ball-throwing mechanism that can shoot a single unit of fire-extinguishing ball by using compressed springs [35
], whereas another team designed a claw mechanism to drop a unit of fire extinguishing ball [36
]. None of the teams tested the mechanism attached to UAS. In another study conducted at FIU, a UAS design and a leader-follower algorithm were proposed to model the use of a swarm of UAS simultaneously dropping fire extinguishing balls to the wildfire [37
]. On the other hand, researchers from the University of Nebraska-Lincoln collaborating with the U.S. Geological Survey propose a system where UASs drop ping pong ball-sized “dragon eggs” of fire. Their goal is to destroy the possible fuels before the wildfire approaches [38
]. Thus, they are actually starting fire with the fire balls to control wildfires. This way the fuel load is decreased. In case of an unintentional wildfire; the fire intensity will remain low, which results in reduced fire spread, more time for intervention, and less fire burden [39
Our approach in this research project is similar to the former three studies that recommended throwing fire extinguishing balls into fire, rather than the latter approach of starting controlled fires. Specifically, the purpose of our study is using three emerging technologies concurrently; the UASs, remote sensing, and the so-called fire extinguishing balls to combat wildfires. The proposed system consists of: (1) scouting UAS to detect spot fires and monitor the risk of wildfire approaching a building, fences or firefighting crew via remote sensing, (2) communication UAS to establish and extend the communication channel between scouting UAS and fire-fighting UAS, and (3) a fire-fighting UAS autonomously traveling to the waypoints to drop fire extinguishing balls (environmental friendly, heat activated suppressants). As aforementioned, development of this proposed system is an ongoing multi-institutional, transdisciplinary research project. This paper illustrates the initial part of the research; controlled experiments to examine the effectiveness and efficiency of fire extinguishing balls.
The AFO ball was efficient in terms of time to activate for both fire classifications, but was not efficient when kept in a wall mount. It took an overall average of 290.9 seconds to explode when on the wall mount. Moreover, no matter if it is directly thrown or kept on a wall mount, it was ineffective with respect to actually extinguishing the building fire. It extinguishes the fire as soon as it explodes, but in a few seconds the fire restarts. Therefore, the firefighters had to extinguish the fire with traditional means in order to avoid complete destruction of the demonstration cell in each experimental run. Further experiments are planned to investigate the Elide fire extinguishing ball under same experimental settings.
The following table (Table 3
) shows the data collected in each trial. As mentioned, the time data are the average recordings of two observers.
Contrary to the building fire experiments, the research team got promising results for the wildfire case. It took around same time for the AFO model to explode, and the short grass fire was completely extinguished in both trials. Figure 4
shows the short grass fire before and after explosions.
The fire was completely extinguished by means of the fire extinguishing ball. Considering the fact that the ball used for this experiment was the cheapest and smallest version of the fire extinguishing balls available at the marketplace, we believe that assisting firefighters during wildfires with fire extinguishing balls looks promising for the future. The 0.5 kg size ball extinguished a circle of 1-m diameter wildfire in our experiments, yet the 1.3 kg balls are claimed to extinguish a radius of 1.3 m.
After the experiments a total of eight questions were asked of two firefighters to obtain subject matter expert feedback. Both firefighters directly participated in the experiments. The questions included building fire and wildfire related questions. Their responses are illustrated next.
5. Subject Matter Experts’ Feedback
Question 1: “Tell me what you think about the effectiveness of these balls with respect to extinguishing building fires.”
In response to question 1, the firefighters strongly recommended use of a larger size fire-extinguishing ball and if possible to shoot multiple balls into a room in case of building fires. They thought that even this size of AFO ball might be effective on slowing down the building fire if thrown in batches. They also commented that if the balls were thrown from a higher elevation the powder might spread in a more circular fashion and might be more effective. This brought the research question of what the optimal elevation of dropping balls should be with the UASs. As it is dangerous to get the UASs close to fire because of the updrafts caused by the fire, it is important to investigate the optimum elevation as well as adjusting dropping strategies for weather (i.e., wind) that keeps the UASs safe, and the balls most effective. This research question is not addressed within the scope of this paper. Another comment from the firefighters was that the ball was obviously not effective against Class B fires.
Question 2: “How would you compare the after fire damage as a result of using these balls versus using water as fire suppressants?”
With respect to after fire damage of using the ball, firefighters thought the balls were very usable. One of them commented that: “…Water damage is devastative, compared to that, these balls won’t cause any damage to the buildings…”. They also commented about the fact that it is going to help save a lot of water. A rule of thumb to calculate the amount of water needed per minute to put out a fire is the area divided by three. Consider the fire demonstration cell, which was built to be 8 ft by 8 ft. That constitutes an area of 64 ft2. Thus, extinguishing the 64 ft2 cell requires more than 20 gallons per minute of water by the rule of thumb.
Question 3: “Tell me how these balls could be used for firefighting specifically for your city?”
The firefighters responded that the driver could throw these balls into rooms with a broken window while the rest of the crews were doing their own duties during a fire. Since the driver mostly sits idle during the fire, it would be an activity for the driver to help the fire extinguishing effort.
Question 4: “Tell me what you think of autonomous UASs shooting these balls into a building fire before you even arrive at the fire scene?”
The firefighters argued that breaking the windows to be able to throw these balls inside might cause the fire to get even worse due to the rapid intake of oxygen into the room. However, they recommended that it would be very beneficial to use them for those rooms with already broken windows. During a fire, a window can be broken by itself, or firefighters break them to change the direction of the fire. Thus, they thought it would be beneficial if UASs shoot these balls into a building through already broken windows or any openings before the first responders arrive at the fire scene. The main contribution would be slowing down the fire.
Question 5: “Tell me what you think of autonomous UASs bringing these balls to the fire scene and giving instructions through an audio system to people on how to use them before you even arrive at the fire scene?”
They did not favor this concept idea, since they thought it might cause liability issues. If a citizen gets injured while following the instructions the UAS is broadcasting, that would cause serious liability concerns. Especially thinking of how the people are under a panic situation while a fire is going on; there is a high risk involved in this concept.
Question 6: “Other than fire-extinguishing balls, tell me what materials or equipment would you like a UAS to bring to the fire scene during the fire and post-fire?”
The firefighters discussed that the most important equipment is thermal cameras. If UASs equipped with thermal sensors arrive at the fire scene before them and provide a live aerial thermal view of the fire; that would help them tremendously in terms of time to control the fire once they arrive on the scene. They also recommended UASs bring medical supplies and even food.
Question 7: “How would you like drones to broadcast the fire scene to you before you arrive at the fire scene via thermal cameras and regular video broadcasting?”
The firefighters partially responded to this question in the previous step as they discussed thermal cameras. Responding to Question 7, they also acknowledged the significance of regular video broadcasting before they arrive.
Question 8: “How could these balls be used during wildfires?”
The firefighters recommended the use of these balls for wildfire, specifically to prevent the fire spreading to buildings or towards significant fuel resources. They thought the ball was effective for the short grass fire, and one firefighter said they would direct the UASs to certain points to drop these balls to mitigate the risk for buildings on the path of fire head.
As mentioned earlier, feedback from two firefighters does not provide any power to draw conclusions, but helped the research team change the main focus from building fires to wildfires. A further study might incorporate a mixed method including a survey and interviews by increasing the number of participating firefighters. This would help the research team to statistically be able to draw generalizations or conclusions with regards to the questions listed above.
Before the experiments, the main research objective was combatting high-rise building fires. Based on the findings of the experiments, the research team changed the key objective to mitigate the risk of wildfires spreading to buildings and potential fuel resources that could worsen the fire.
Consider a swarm of 10 UASs, each carrying 10 of the 1.3 kg fire-extinguishing balls (each extinguishing a radius of 1.3 m). If they fly in a parallel fashion, and each of them drops the balls in a straight line one by one autonomously; that would constitute an area of 676 m2
(=(1.3 * 2 * 10)2
) per sortie. If the UASs could be re-loaded with agile methods, it could be possible to prevent wildfire from spreading to buildings or critical directions, or to extinguish spot fires igniting during the main wildfire with this swarm size. If the swarm size increases and/or the number of balls per UAS increases, the effectiveness of the system can be increased exponentially. The research team is by no means claiming extinguishing a wildfire completely with the current state of the art of the UAS technology. Yet, our foremost objective is designing a system to assist firefighters during wildfires, especially those in wildland–urban interface zones. The conceptual system is as follows: (1) swarm of scouting UAS to detect spot fires and monitor the risk of wildfire approaching a building, fences, or firefighting crew via remote sensing, (2) communication UAS to establish and extend the communication channel between scouting UAS and fire-fighting UAS, and (3) a swarm of fire-fighting UAS autonomously traveling to the waypoints and dropping fire extinguishing balls. An algorithm will be developed and tested on simulation environment. The input from the visual and infrared sensor data from S-UAS, incorporated with wildfire models such as BehavePlus [6
] and FlamMap [40
], will be used to predict the prognosis of the fire behavior. The system will be tested in simulation environment for true alarm rates and timeliness for prediction of fire spread towards a building/fence, or firefighter. The research team has already completed the building of a scouting UAS and also a fire-fighting UAS with payload capacity of around 15 kg and time of flight of around 25 minutes. In addition, a mechanism attachable to the UAS that can carry fire-extinguishing balls has been completed. Figure 5
shows the scouting UAS, while its components are listed on Table 4
. Table 5
shows the components of the fire-fighting UAS.
The battery can supply 200 amps (=20A * 10C) continuous current and 400 amps (=20A * 20C) peak current. Each motor can pull 25 amps (=200A/8) continuously. According to manufacturer’s thrust tests, each motor provides a thrust of 3.01 kg with 1855 carbon propellers, at 22.2 V, 23.1 amps. Overall, eight motors will give a thrust of around 24 kg. Subtracting the weight of the frame, motors, ESCs, and other components of the UAS, there is a room for almost 15 kg to add the fire-extinguishing balls and the ball-dropping mechanism. This means the firefighting UAS can carry up to 10 fire-extinguishing balls if needed. A ball-release mechanism was designed and built as a mechatronic system attachable to the firefighting UAS. The system consists of electronic components such as microcontroller, power supply, sender and receiver, and motor as well as a mechanism to carry and release the ball and its connections to the fire-fighting UAS. Figure 6
shows the built prototype including the ball-releasing mechanism and attached mechatronic components, as well as the remote starter button attached to a signal sender. This mechanism will be attached to the fire-fighting drone to perform the future experiments of the research in order to test the conceptual design with timber litter, short needle litter, and chapparal vegetation-based experimental settings. By taking the observations from the prototype into consideration, another mechanism that would carry at least three balls will be designed and built.

domain: geography


text:
Title: Brandon Colker's How to Make Big Bucks from Big Blogs
Length: 1 hour, 2 min
Listen to another e-book today and this one was not that long of a listen either. From my point of view the author has a holistic point of view. Not only does he discuss the physical steps that need to be taken he also talks about what is needed in order to take that steps. One example of this is when he discusses the frame of mind you need to be in in order to take it. There are also humorous stories used as analogies to further drive home specific points that the author is trying to highlight.
Received this Live Infinitely exercise ball for free/Heavily Discounted for my honest and unbiased review, un-compensated . This product can be purchased at http://www.amazon.com/Brandon-Colkers-Make-Bucks-Blogs/dp/1517756537. For further information about the author go to
http://BrandonColker.com/ . #BrandonColker

domain: literature


text:
Charleston Fashion Week March 2011
Fashion Event Articles Fashion Trade Shows Fashion Shows Fashion Articles Fashion Week Fashion Week News Fashion Article Archive Fashion News Clothes Shopping Articles Fashion Newspaper Fashion Writers Fashion Week Directory Fashion Week Fashion Week Photos Fashion Week Videos Fashion Industry Calendar Fashion Seminars Fashion News Articles Runway Shows Fashion Events
Charleston Fashion Week®, presented by The Art Institute of Charleston, has released the schedule of events, nightly featured designers, retail participants, and roster of celebrity judges confirmed for the March 22-26th event. Celebrating its fifth year, the premier fashion event of the South is set to host some of the most innovative up-and-coming talent on the East Coast, as well as the most influential names in the industry.
New York Fashion Week creator and Former VP of IMG Fashion Fern Mallis will join the CFW Fashion Panel on Saturday, March 26th to select the next Emerging Designer Competition: East winner. Current President of Fern Mallis LLC, Mallis is widely credited for establishing 7th on Sixth, which organized, centralized, and modernized the American runways, allowing American designers to compete head-on with Milan and Paris, and forever changing the global fashion business. Ms. Mallis has led new Fashion Weeks in Miami, Los Angeles, New York, Berlin, and Moscow.
Other front-row fashion headliners on Saturday's finale panel include Elle magazine's Fashion News Director & returning judge Anne Slowey, fashion writer and New York Times best-selling author Derek Blasberg, Gilt Groupe co-founder Alexis Maybank, and Mad Men costume designer Janie Bryant.
Nightly fashion panel judges include Social Primer's K. Cooper Ray (former VP of Bottega Veneta) and Andrea Serrano (costume buyer for Army Wives). CFW alums and designers Mychael Knight and Marysia Dobrzanska Reeves will also help select the four finalists that will move on to showcase their collections for the chance to win the Grand Prize valued at $30,000.
Charleston Fashion Week® 2011 ticket holders will have the opportunity to see nightly runway shows from retail participants, featured designers, and up-and-coming emerging designers. Featured designers for 2011 include David Yoo (2010 Elle/rISD Design Award Winner), April Johnston (Project Runway Season 8 Designer), Troubadour, Hunter Dixon, Barbara Beach, Jamie Lin Snider, and 2010 Emerging Designer Competition Winner Larika Page.
Charleston Fashion Week® organizers have also confirmed that along with the growing list of fashion A-listers in attendance, modeling scouts and buyers will be present. To review the nightly schedule of runway shows; learn more about the featured designers, retail participants, and special guests; or to purchase your VIP weekly pass and tickets; visit www.charlestonfashionweek.com.
About Charleston Fashion Week® Showcasing fashion designers, retailers and models, Charleston Fashion Week® founded in 2007 has fast become one of the premier fashion weeks in North America. Held March 22-26th under the tents in Marion Square in Charleston, SC this five-night celebration will feature more than 40 runway shows, the Spring Bridal Show, Emerging Designer Competition: East, and Rock the Runway Model Competition. Named a Top 20 Event for March by the Southeast Tourism Society, and accredited with launching the careers of numerous up-and-coming designers, this true multimedia event presents high-end runway shows, interactive entertainment, chic after parties and press events. For more information on the fifth annual Charleston Fashion Week®, to review the show schedule, or to complete the media application visit www.charlestonfashionweek.com.
Learn more about international fashion week events.
You are welcome to further discuss these fashion events at the Fashion Industry Network.
Learn about Fashion Weeks.
You may want to read fashion blogs to learn more about fashion events. Fashion bloggers typically do a good job with reporting on fashion events.
|Clothing B2B Women's Fashion Fashion Network|

domain: entertainment


text:
Caught living in a world between fantasy and reality, Carrie, a 13-year-old homeschooled girl, struggles to make sense of loss and new beginnings, seeking comfort in a heart-shaped locket…with a secret. Themes include: family, fantasy, and grief.
About K. Kelley HeyneSee more books from this Author
Having suffered a tragic loss and been forced to leave behind her best friend when her family moves from Washington to Wisconsin seeking a fresh start, home-schooled Carrie retreats into a fantasy world in which her alter ego, Princess Caritas, embarks on a dangerous journey to save her family fr...Feb 28 2013 | Read Full Review of The Locket's Secret
A 13-year-old girl struggles with profound life changes in Heyneâs uneven middle-grade debut. Carrie is crushed to be uprooted from all she knows when her family relocates from Washington to WisconsinMar 18 2013 | Read Full Review of The Locket's Secret
An aggregated and normalized score based on 6 user ratings from iDreamBooks & iTunes

domain: library


text:
THE STORY OF A STRANGE LAND.
|THE STORY OF A STRANGE LAND.|
By DAVID STARR JORDAN.
PRESIDENT OF THE LELAND STANFORD JUNIOR UNIVERSITY.
"In one strange land,
And a long way from home,
I heard a mighty rumbling, and I couldn't tell where."
IT happened a long time ago, it may be fifty thousand years in round numbers, or it may have been twice as many, that a strange thing took place in the heart of the Great Mountains. It was in the middle of the Pliocene epoch, a long, dull time that seemed as if it would never come to an end. There was then on the east side of the Great Divide a deep, rocky basin surrounded by high walls of granite gashed to the base by the wash of many streams. In this basin, we know not how—for the records all are burned or buried—the crust of the earth was broken, and a great outflow of melted lava surged up from below. This was no ordinary eruption, but a mighty outbreak of the earth's imprisoned forces. The steady stream of lava filled the whole mountain basin and ran out over its sides, covering the country all around so deeply that it has never been seen since. More than four thousand square miles of land lay buried under melted rock. No one can tell how deep the lava is, for no one has ever seen the bottom. Within its bed are deep clefts whose ragged walls descend to the depth of twelve hundred feet, and yet give no glimpse of the granite below, while at their side are mountains of lava whose crags tower a mile above the bottom of the ravines.
At last, after many years or centuries—time does not count for much in these Tertiary days—the flow of melted lava ceased. Its surface cooled, leaving a high, uneven plain, black and desolate, a hard, cold crust over a fiery and smoldering interior. About the crater lay great ropes and rolls of the slowly hardening lava, looking like knots and tangles of gigantic reptiles of some horrible extinct sort. There was neither grass nor trees, no life of any sort. Nothing could grow in the coarse, black stone. The rivers and brooks had long since vanished in steam, the fishes were all dead, and the birds had flown away. The whole region wore the desolation of death.
But to let land go to waste is no part of Mother Nature's plan. So even this far-off corner of her domain was made ready for settlement. In the winter she sifted snow on the cold black plain, and in the summer the snow melted into a multitude of brooks and springs. The brooks gradually wore paths and furrows down the large bed, and the sands which they washed from one place


text: Not to be defined by one style, Lorna B’s own personal art of music is a blend of Smooth, Standard, Improvisational Jazz, Soul, Blues and Pop arranged with a Jazz flare. Lorna's training started early at age 3 under the guidance of her father, one of Portland Oregon’s greatest jazz legends, composer & arranger for Billy Eckstine, pianist Warren Bracken . Her father’s contributions in Jazz, Bebop, and Blues as well as exposure to other jazz greats of the time, influenced her to start on her own musical journey. In her youth, her vocal strengths were noticed and led her to be selected as the only child of an all adult choir where she sang from age 12 to 18. Lorna moved out of state and later, out of country to Canada for 14 years. While there she worked on some music projects with other artists. Since returning to her home state of Oregon, her music projects were working with her group, the Lorna B Band playing Pop, Soul Funk & Blues. Lorna has now has come full circle and is showcasing her roots in Jazz, by way of her skills in her unique style and naturally seasoned vocal sound.


text:
Madison owns the house across the street from us. She found a new boyfriend and this weekend, she moved some of her furniture over to his swanky place on Harvard Avenue. We noticed that we hadn’t seen much of her. About three weeks ago when spring surprised us, she was doing some cleaning in her yard. I asked her where she had been hiding herself and she told us about her new boyfriend. She was living with him and she thought that they might get married soon. Her house has been empty since then and this last weekend she was moving.
Next door to her, the house had been for sale. It only stayed on the market for a couple of weeks before the “Sale Pending” sign went up. Last week, the “Sold” sign went up. Last weekend, we watched the old neighbors move out and the new neighbors move in. I still haven’t introduced myself to them yet. I guess I should, but I was worried that they were stressed with the move and in no position to receive visitors. What is the proper etiquette in this situation? Should I have run up to them when they were moving bookcases and chairs and introduced myself?
That’s how we met Rick, our next door neighbor. Back in July, we were trying to get the U-Haul back in time. Rick ran right up to the truck and introduced himself. He wanted to apologize in advance for the barking of his dogs. He had three dogs, Kelly, Wilson and Anna, and he was worried that they would bother us. Wilson is a real barker and will sound off whenever we walk by the house, he fretted. We assured him that we were far more worried about our dog, Sid, than his dogs. If our dog isn’t the loudest in the neighborhood, that made us happy. We became instant friends with Rick.
Rick got a new girlfriend. I don’t know when that big blue SUV started staying overnight at his place. I actually didn’t notice that he had an extra human living with him at all. I didn’t even notice that the barking next door got louder. I noticed that his cats, Pedro and Jahnsie, were a lot friendlier than they had been before. I noticed that their food bowls were out on the front porch, attracting an orange stray tabby. I didn’t notice his new girlfriend until he introduced her to us.
She has moved in with him and brought a dog with her named Stella who hates cats, which explains the exile of Pedro and Jahnsie. I love Pedro so much that I would just steal him from Rick and let him stay with us, but that isn’t neighborly behavior, is it? I watched his new girlfriend take all four dogs into her large SUV on Saturday. She truly is his soul mate to live with his menagerie.
I know that her dog’s name is Stella. I know that she’s Rick’s soul mate. I know that she’s a great gal, but I can’t remember her name. When Rick introduced us, her name got overwritten in my memory by Stella’s. I just imagined Marlon Brando in the rain, screaming at his large, gray dog, “STELLA!”

domain: pet


text:
Prolonged shutdown may hurt veterans
Marcus Clem | editor in chief
Just about everything the federal government does that’s not required to protect life and property is in limbo.
Checks coming, for now
One of the government’s essential services that remain open is the U.S. Department of Veterans Affairs (VA).
The VA regulates G.I. Bill payments and other assistance to 246 Pittsburg State student veterans.
A VA announcement published on Monday, Sept. 30, to address veterans’ anxiety shows a more uncertain future.
“Claims processing and payments in the compensation, pension, education and vocational rehabilitation programs,” the announcement said, “are anticipated to continue through late October.
“However, in the event of a prolonged shutdown … these programs would be suspended when available funding is exhausted.”
Pvt. Andrew Hodson, a student veteran and member of the Kansas Army National Guard, says that fact worries him.
“If I lost that then I don’t know what I would do,” said Hodson, freshman in nursing. “If the government promises you something and then takes it away that’s kind of screwing you right there … I hope that they get going and find a solution.”
Worry not, VA says
Sherry Roberts, administrative specialist for the registrar’s office and Veterans Affairs contact, says that she’s tried to reassure the students who have come to her with concerns.
“I’ve told them that the government can’t close down indefinitely,” she said. “The best way to think about this is to know that it can’t stay closed forever. They have to come to a resolution eventually.”
Roberts says that she’s confident that she’ll be able to continue helping student veterans as much as they need, but it may get harder if the government remains shut down.
“This does make my job more difficult,” she said. “This is people’s income, how they pay their bills, how they eat.
“I don’t know if I could say I’m upset, but I am concerned that my students are concerned about how they are going to pay their bills.”
Troops not affected
The shutdown itself has nothing to do with veterans. In fact, the U.S. Congress passed a new bill in the days before it began to ensure pay for active duty troops for the duration.
All funding that Pitt State’s Reserve Officer Training Corps program depends on is secure for the moment, says Lt. Col. Christopher Lambert, professor of military science.
“It does not affect our scholarship dollars at all,” he said. “Obviously, some funding in place may be affected, and like the rest of the country we’ll be watching the future funding situation. We’re just watching it day by day.”

domain: economics


text:
LOS ANGELES (AP) — Along with Rihanna, Nicki Minaj is the top nominee at Sunday's American Music Awards, but the rapper-singer isn't concerned with her four nominations.
The 29-year-old said in an interview that she doesn't "do music for awards" and that she's more excited to perform her new single "Freedom."
The American Music Awards are all about performances, and Sunday's show will be no exception. Justin Bieber will share the stage with Minaj. Ludacris and Chris Brown will perform with Swizz Beatz. And Stevie Wonder is set to provide the soundtrack for a tribute to Dick Clark.
Taylor Swift, Carrie Underwood, Kelly Clarkson, Usher and Carly Rae Jepsen are also set to sing during the three-hour program, which is to be broadcast live on ABC.
Sunday's show will mark the AMA's 40th anniversary.