Miracle-dz/UniFAR-FTUs huggingface dataset:
Information-Gathering in Latent Bandits

In the latent bandit problem, the learner has access to reward distributions and -- for the non-stationary variant -- transition models of the environment. The reward distributions are conditioned on the arm and unknown latent states. The goal is to use the reward history to identify the latent state, allowing for the optimal choice of arms in the future. The latent bandit setting lends itself to many practical applications, such as recommender and decision support systems, where rich data allows the offline estimation of environment models with online learning remaining a critical component. Previous solutions in this setting always choose the highest reward arm according to the agent's beliefs about the state, not explicitly considering the value of information-gathering arms. Such information-gathering arms do not necessarily provide the highest reward, thus may never be chosen by an agent that chooses the highest reward arms at all times. In this paper, we present a method for information-gathering in latent bandits. Given particular reward structures and transition matrices, we show that choosing the best arm given the agent's beliefs about the states incurs higher regret. Furthermore, we show that by choosing arms carefully, we obtain an improved estimation of the state distribution, and thus lower the cumulative regret through better arm choices in the future. We evaluate our method on both synthetic and real-world data sets, showing significant improvement in regret over state-of-the-art methods.
Optical O2 Sensors Also Respond to Redox Active Molecules Commonly Secreted by Bacteria

When they are closely packed, as in biofilms, colonies, and soils, microbes can consume O2 faster than it diffuses. As such, O2 concentrations in natural environments can vary greatly over time and space, even on the micrometer scale. ABSTRACT From a metabolic perspective, molecular oxygen (O2) is arguably the most significant constituent of Earth’s atmosphere. Nearly every facet of microbial physiology is sensitive to the presence and concentration of O2, which is the most favorable terminal electron acceptor used by organisms and also a dangerously reactive oxidant. As O2 has such sweeping implications for physiology, researchers have developed diverse approaches to measure O2 concentrations in natural and laboratory settings. Recent improvements to phosphorescent O2 sensors piqued our interest due to the promise of optical measurement of spatiotemporal O2 dynamics. However, we found that our preferred bacterial model, Pseudomonas aeruginosa PA14, secretes more than one molecule that quenches such sensors, complicating O2 measurements in PA14 cultures and biofilms. Assaying supernatants from cultures of 9 bacterial species demonstrated that this phenotype is common: all supernatants quenched a soluble O2 probe substantially. Phosphorescent O2 probes are often embedded in solid support for protection, but an embedded probe called O2NS was quenched by most supernatants as well. Measurements using pure compounds indicated that quenching is due to interactions with redox-active small molecules, including phenazines and flavins. Uncharged and weakly polar molecules like pyocyanin were especially potent quenchers of O2NS. These findings underscore that optical O2 measurements made in the presence of bacteria should be carefully controlled to ensure that O2, and not bacterial secretions, is measured, and motivate the design of custom O2 probes for specific organisms to circumvent sensitivity to redox-active metabolites. IMPORTANCE When they are closely packed, as in biofilms, colonies, and soils, microbes can consume O2 faster than it diffuses. As such, O2 concentrations in natural environments can vary greatly over time and space, even on the micrometer scale. Wetting soil, for example, slows O2 diffusion higher in the soil column, which, in concert with microbial respiration, greatly diminishes [O2] at depth. Given that variation in [O2] has outsized implications for microbial physiology, there is great interest in measuring the dynamics of [O2] in microbial cultures and biofilms. We demonstrate that certain classes of bacterial metabolites frustrate optical measurement of [O2] with phosphorescent sensors, but also that some species (e.g., E. coli) do not produce problematic secretions under the conditions tested. Our work therefore offers a strategy for identifying organisms and culture conditions in which optical quantification of spatiotemporal [O2] dynamics with current sensors is feasible.
Complexity of lattice problems - a cryptographic perspective

Preface. 1. Basics. 2. Approximation Algorithms. 3. Closest Vector Problem. 4. Shortest Vector Problem. 5. Sphere Packings. 6. Low-Degree Hypergraphs. 7. Basis Reduction Problems. 8. Cryptographic Functions. 9. Interactive Proof Systems. Index
Towards a Theory of Geometric Graphs

On the complexity of the linkage reconfiguration problem by H. Alt, C. Knauer, G. Rote, and S. Whitesides Falconer conjecture, spherical averages and discrete analogs by G. Arutyunyants and A. Iosevich Turan-type extremal problems for convex geometric hypergraphs by P. Brass The thrackle conjecture for $K_5$ and $K_{3,3}$ by G. Cairns, M. McIntyre, and Y. Nikolayevsky Three-dimensional grid drawings with sub-quadratic volume by V. Dujmovic and D. R. Wood On a coloring problem for the integer grid by A. Dumitrescu and R. Radoicic Separating thickness from geometric thickness by D. Eppstein Direction trees in centered polygons by R. E. Jamison Path coverings of two sets of points in the plane by A. Kaneko, M. Kano, and K. Suzuki Length of sums in a Minkowski space by G. O. H. Katona, R. Mayer, and W. A. Woyczynski A new entropy inequality for the Erdos distance problem by N. H. Katz and G. Tardos Coloring intersection graphs of geometric figures with a given clique number by A. Kostochka Convex quadrilaterals and $k$-sets by L. Lovasz, K. Vesztergombi, U. Wagner, and E. Welzl Distance graphs and rigidity by H. Maehara A Ramsey property of planar graphs by J. Nesetril, J. Solymosi, and P. Valtr A generalization of quasi-planarity by J. Pach, R. Radoicic, and G. Toth Geometric incidences by J. Pach and M. Sharir Large sets must have either a $k$-edge or a $(k+2)$-edge by M. A. Perles and R. Pinchasi Topological graphs with no self-intersecting cycle of length 4 by R. Pinchasi and R. Radoicic A problem on restricted sumsets by I. Z. Ruzsa The gap between crossing numbers and convex crossing numbers by F. Shahrokhi, O. Sykora, L. A. Szekely, and I. Vrto Distinct distances in high dimensional homogeneous sets by J. Solymosi and V. Vu The biplanar crossing number of the random graph by J. Spencer The unit distance problem on spheres by K. J. Swanepoel and P. Valtr Short proof for a theorem of Pach, Spencer, and Toth by L. Szekely.
Android malware detection method based on highly distinguishable static features and DenseNet

The rapid growth of malware has become a serious problem that threatens the security of the mobile ecosystem and needs to be studied and resolved. Android is the main target of attackers due to its open source and popularity. To solve this serious problem, an accurate and efficient malware detection method is needed. Most existing methods use a single type of feature, which can be easily bypassed, resulting in low detection accuracy. In addition, although multiple types of features are used in some methods to solve the drawbacks of detection methods using a single type of feature, there are still some problems. Firstly, due to multiple types of features, the number of features in the initial feature set is extremely large, and some methods directly use them for training, resulting in excessive overhead. Furthermore, some methods utilize feature selection to reduce the dimensionality of features, but they do not select highly distinguishable features, resulting in poor detection performance. In this article, an effective and accurate method for identifying Android malware, which is based on an analysis of the use of seven types of static features in Android is proposed to cope with the rapid increase in the amount of Android malware and overcome the drawbacks of detection methods using a single type of feature. Instead of utilizing all extracted features, we design three levels of feature selection methods to obtain highly distinguishable features that can be effective in identifying malware. Then a fully densely connected convolutional network based on DenseNet is adopted to leverage features more efficiently and effectively for malware detection. Compared with the number of features in the original feature set, the number of features in the feature set obtained by the three levels of feature selection methods is reduced by about 97%, but the accuracy is only reduced by 0.45%, and the accuracy is more than 99% in a variety of machine learning methods. Moreover, we compare our detection method with different machine learning models, and the experimental results show that our method outperforms general machine learning models. We also compare the performance of our detection method with two state-of-the-art neural networks. The experimental results show that our detection model can greatly reduce the training cost and still achieve good detection performance, reaching an accuracy of 99.72%. In addition, we compare our detection method with other similar detection methods that also use multiple types of features. The results show that our detection method is superior to the comparison methods.
Cardiomyocyte maturation and its reversal during cardiac regeneration

Cardiovascular disease is a leading cause of death worldwide. Due to the limited proliferative and regenerative capacity of adult cardiomyocytes, the lost myocardium is not replenished efficiently and is replaced by a fibrotic scar, which eventually leads to heart failure. Current therapies to cure or delay the progression of heart failure are limited; hence, there is a pressing need for regenerative approaches to support the failing heart. Cardiomyocytes undergo a series of transcriptional, structural, and metabolic changes after birth (collectively termed maturation), which is critical for their contractile function but limits the regenerative capacity of the heart. In regenerative organisms, cardiomyocytes revert from their terminally differentiated state into a less mature state (ie, dedifferentiation) to allow for proliferation and regeneration to occur. Importantly, stimulating adult cardiomyocyte dedifferentiation has been shown to promote morphological and functional improvement after myocardial infarction, further highlighting the importance of cardiomyocyte dedifferentiation in heart regeneration. Here, we review several hallmarks of cardiomyocyte maturation, and summarize how their reversal facilitates cardiomyocyte proliferation and heart regeneration. A detailed understanding of how cardiomyocyte dedifferentiation is regulated will provide insights into therapeutic options to promote cardiomyocyte de‐maturation and proliferation, and ultimately heart regeneration in mammals.
Importance of Prosecution Witnesses in Terrible Crimes of Sexual Violence, Abduction, Abuse, Torture, Rape And Killing Against Innocent Women and Children

The cases against innocent women and children are tremendously increasing day by day. The offenders are committing sexual intimidation and harassment accompanied by a high degree of torture and killing. The burglars are also observed in such offenses with rape, torture, and/or killing as modus-operandi. Rape is defined under ‘Hadood Laws’ in Islamic Jurisprudence and suggests strong punishments. The ‘Taazir’ sanctions sanctify emerging and contemporary types of criminality. The majority of Islamic penal law's sentences are ‘Taazir’ in nature. The most popular forms of ‘Taazir’ include imprisonment, whipping, fines, and the death penalty. According to Islamic jurisprudence, society must protect its morals, Apart from other factors, this paper focuses on the importance of prosecution witnesses. The prosecution witnesses are the backbone of a criminal case in the court. The criminals and their alias keep following up with the witnesses to prevent and avert the evidence in court; because they know the related information and knowledge about the offense. The paper probes the psychological and psychiatric reasons, why the offenders have abnormal behavior of this type. Therefore, the protection and safe custody of witnesses is of very high importance, particularly in cases of murder and rape. We highlight the ordinary as well as expert witnesses and their role in the cases, regarding proceedings by the prosecution. The role of witnesses is of immense importance. This paper presents two case studies to justify that prosecution must build up and collect enough substantial evidence to win the case in court.
Data Analysis of Twitter feeds on Google Maps

With increasing popularity in microblogging sites, we are in the era of information explosion. As of June 2011, about 200 million tweets are being generated every day. Spurred by that growth, companies and media organizations are increasingly seeking ways to mine Twitter for information about what people think and feel about their products and services. One advantage of this data, over previously used data-sets, is that the tweets are collected in a streaming fashion and therefore represent a true sample of actual tweets in terms of language use and content. Although Twitter provides a list of most popular topics people tweet about known as trending topics in real time, it is often hard to understand what these trending topics are about and it becomes difficult to classify them based on the emotions that each tweet is trying to portray. Therefore a question arises as to what happens when you combine the social networking power of Twitter with the usefulness of Google Maps? The result can contain some rather innovative and intriguing applications. With Twitter and Google Maps mashup"s here, it"s all about taking advantage of both the Google Maps and Twitter API to create a mashup that"s unique, practical, and highly efficient. The aim of our project is to display real time globally trending tweets on google maps and perform sentiment analysis on the tweets related to the topic.This paper primarily focuses on the trend detection and sentiment analysis techniques and the applications of using a Twitter and Google maps mashup. Further, we analyze the sentiments expressed within a particular sentence, paragraph or document etc. The analysis based on sentiments can pave way for automatic trend analysis, topic recognition and opinion mining etc. Furthermore, we can fairly estimate the degree of positivity and negativity of the opinions and sentiments based on the content obtained from a particular social media.
Architectural drawing : a visual compendium of types and methods / Rendow Yee

Preface to Second Edition. Preface to First Edition. 1. Tool Fundamentals. 2. Lettering, Typography, and Line Types. 3. Representational Sketching. 4. Conventional Orthogonal Terminology. 5. Orthographic and Paraline Drawing. 6. Linear Perspective Drawing. 7. Perspective View Development. 8. Light, Shade, and Shadow. 9. Delineating and Rendering Entourage. 10. Diagramming and Conceptual Sketching. 11. Presentation Formats. Epilogue. Drawing Exercises. Bibliography. About the Author. Subject Index. Contributor Index.
Identification of Obesity and Cardiovascular Risk in Ethnically and Racially Diverse Populations: A Scientific Statement From the American Heart Association

Obesity, defined as excess fat (adipose) tissue accumulation that may impair health,1 is a highly prevalent and serious public health problem. Roughly 35.7% of American adults are obese.2 High rates of obesity are not limited to the United States or even to other highly developed countries. The prevalence of obesity in Mexico, for example, is comparable to that in the United States.3 Not surprisingly, rates of obesity-related illnesses including cardiovascular disease (CVD) are rising quickly worldwide. More than 25 million American adults have been diagnosed with diabetes mellitus.4 India is projected to have >100 million diabetic people by the year 2030.5 CVD is the number 1 cause of death worldwide.6 These grim statistics highlight the need for accurate identification of overweight and obese adults who are at high risk for obesity-related illnesses. Accurate identification of such people allows healthcare professionals, policymakers, and others to target prevention and treatment programs to those at the highest risk of morbidity and mortality. Unfortunately, the tools and measures currently available to identify obesity and associated risks are either impractical, inaccurate, or both. For example, the body mass index (BMI) is easy to calculate, and established cutoffs that define overweight (25 kg/m2) and obesity (30 kg/m2) are readily available and well known. The application of such cutoffs to a diverse population, as will be discussed, however, leads to misclassification of a large number of people. Many people with a normal BMI have high levels of adiposity and also are at high risk for obesity-related illness. Others with a high BMI have relatively normal levels of adiposity and are metabolically healthy. The problem of misclassification is especially important for racial and ethnic minorities, who make up nearly 40% of the American population today and will make up more …
The Psychology of Secrets

Preface. 1. Nature of Secrecy. 2. Individual Differences in Secret Keeping. 3. Explaining Why Secrecy is Linked to Problems. 4. Health Benefits of Revealing. 5. What is it About Revealing Secrets that is Beneficial? 6. Secrecy and Openness in Psychotherapy. 7. Explaining Why Openness May Not be Therapeutic: A Self-Presentational View of Psychotherapy. 8. Dilemmas to Revealing Secrets and the Role of the Confidant. 9. When to Reveal Personal Secrets in a Particular Relationship. Index.
An empirical study of the sensitivity of quality indicator for software module clustering

Recently, there has been a significant progress in applying evolutionary multiobjective optimization techniques to solve software module clustering problem. The results of evolutionary multiobjective optimization techniques for software module clustering problem are a set of many non-dominating clustering solutions. Generally, the quality indicators of clustering solutions produced by these techniques are sensitive to minor variation in the decision variables of the clustering solutions. Researchers have focused on finding software module clustering with better cluster quality indicator; however in practice developers may not always be interested to better quality indicator clustering solutions, particularly if these quality indicators are quite sensitive. Under such situations, developer looks for clustering solutions whose quality indicators are not sensitive to small variations in the decision variables of the candidate clustering solution. The paper performs an experiment for the sensitivity analysis of quality indicator on software module clustering solution with two multiobjective formulations MCA and ECA. To perform the experiment the NSGA-II is used as multi-objective evolutionary algorithm. We evaluate sensitivity of quality indicators for six real-world software and one random problem. Results indicate that the quality indicator for MCA formulation is less sensitive than ECA formulation and hence MCA will be a better choice for multiobjective software module clustering from sensitivity perspective.
Fine needle aspiration of pancreatic masses: the clinical impact

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Mining Virulence Genes Using Metagenomics

When a bacterial genome is compared to the metagenome of an environment it inhabits, most genes recruit at high sequence identity. In free-living bacteria (for instance marine bacteria compared against the ocean metagenome) certain genomic regions are totally absent in recruitment plots, representing therefore genes unique to individual bacterial isolates. We show that these Metagenomic Islands (MIs) are also visible in bacteria living in human hosts when their genomes are compared to sequences from the human microbiome, despite the compartmentalized structure of human-related environments such as the gut. From an applied point of view, MIs of human pathogens (e.g. those identified in enterohaemorragic Escherichia coli against the gut metagenome or in pathogenic Neisseria meningitidis against the oral metagenome) include virulence genes that appear to be absent in related strains or species present in the microbiome of healthy individuals. We propose that this strategy (i.e. recruitment analysis of pathogenic bacteria against the metagenome of healthy subjects) can be used to detect pathogenicity regions in species where the genes involved in virulence are poorly characterized. Using this approach, we detect well-known pathogenicity islands and identify new potential virulence genes in several human pathogens.