Miracle-dz/UniFAR-FTUs huggingface dataset:
Technical Report Remote Usability Testing Methods a la Carte

Although existing lab-based formative usability testing is frequently and effectively applied to improving usability of software user interfaces, it has limitations that have led developers to turn to remote usability evaluation methods (RUEMs) to collect formative usability data from daily usage by real users in their own real-world task environments. The enormous increase in Web usage, where users can be isolated and the network and remote work setting become intrinsic parts of usage patterns, is strong motivation for supplementing lab-based testing with remote usability evaluation methods. Another significant impetus for remote evaluation is the fact that the iterative development cycle for any software, Web application or not, does not end with initial deployment. We review and informally compare several approaches to remote usability evaluation with respect to quantity and quality of data collected and the effort to collect the data. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee.
Actual Causality

Causality plays a central role in the way people structure the world; we constantly seek causal explanations for our observations. But what does it even mean that an event C "actually caused" event E? The problem of defining actual causation goes beyond mere philosophical speculation. For example, in many legal arguments, it is precisely what needs to be established in order to determine responsibility. The philosophy literature has been struggling with the problem of defining causality since Hume. In this book, Joseph Halpern explores actual causality, and such related notions as degree of responsibility, degree of blame, and causal explanation. The goal is to arrive at a definition of causality that matches our natural language usage and is helpful, for example, to a jury deciding a legal case, a programmer looking for the line of code that cause some software to fail, or an economist trying to determine whether austerity caused a subsequent depression. Halpern applies and expands an approach to causality that he and Judea Pearl developed, based on structural equations. He carefully formulates a definition of causality, and building on this, defines degree of responsibility, degree of blame, and causal explanation. He concludes by discussing how these ideas can be applied to such practical problems as accountability and program verification. Technical details are generally confined to the final section of each chapter and can be skipped by non-mathematical readers.
The Role of the HDDI Collection Builder in Hierarchical Distributed Dynamic Indexing

The global growth in popularity of the World Wide Web has been enabled in part by the availability of browserbased search tools which in turn have led to increased demand for advances in the field of textual data mining. Simultaneously, fully automatic content-based techniques of textual data management have been under development at a number of institutions. The time is thus ripe for the development of scalable knowledge management systems capable of handling extremely large and diverse textual collections distributed across multiple repositories. This paper introduces the HDDI Collection Builder, our custom developed solution for automatic feature extraction from such collections. The HDDI Collection Builder provides input features for several algorithms in distributed textual data mining.
Improved Automatic Discovery of Subgoals for Options in Hierarchical Reinforcement Learning

Options have been shown to be a key step in extending reinforcement learning beyond low-level reactionary systems to higher-level, planning systems. Most of the options research involves hand-crafted options; there has been only very limited work in the automated discovery of options. We extend early work in automated option discovery with a fle xible and robust method.
Self-organizing Fusion Algorithm Applied to Image Segmentation

It presents a novel method called self-organizing fusion (SOF) for performing fast image segmentation. Characteristics of SOF are explored and discussed, both theoretically and empirically. The essence of SOF is that objects are extracted through alternating processes of updating and merging until convergence. Such concurrent updating creates a self-organizing fusion behavior that facilitates identification of regions comprising the same object. The method is computationally efficient as both updating and merging are conducted in parallel fashion, and since parameters selection is done for local regions, it is able to deal with fairly complex images.
A New Construction of Time Capsule Signature

In this paper we introduce a new approach of constructing time capsule signature. Our new construction captures the basic requirements defined by dodis et al., and it is also very straightforward and flexible. The time capsule signature provides an elegant way to produce a “future signature” that becomes valid from a specific future time t, when a trusted third party (called Time Server) publishes some trapdoor information associated with the time t. It also has many other advantages. Our work includes a developed security model of time capsule signature, a novel way of construction based on the bipartite ring signature, which is proven secure in the random oracle model and a concrete realization of the scheme.
MRI segmentation of Medical images using FCM with initialized class centers via genetic algorithm

Image segmentation is a critical stage in many computer vision and image process applications. Accurate segmentation of medical images is very essential in Medical applications but it is very difficult job due to noise and in homogeneity. Fuzzy C-Mean (FCM) is one of the most popular Medical image clustering methods. We noticed that for some images, FCM is sensitive to initialization of centre of clusters. This article introduced a new method based on the combination of genetic algorithm and FCM to solve this problem. The genetic algorithm is used to find initialized centre of the clusters. In this method, the centre is obtained by minimizing an object Function. This object Function specifies sum of distances between each data and their cluster centres. Then FCM is applied with to the case. The experimental result demonstrates the effectiveness of new method by able to initialize centre of the clusters.
Using Genome Wide Estimates of Heritability to Examine the Relevance of Gene-Environment Interplay

We use genome-wide data from the third generation respondents of the Framing-ham Heart Study to estimate heritability in body mass index using different quantities of the measured genotype. Heritability decreases rapidly when SNPs implicated by a genome-wide association study are removed but shows essentially no decline when SNPs implicated by a gene-environment interaction in a second genome-wide analysis are removed. This second result is highlighted by our additional finding that the SNPs which explain heritability amongst a subsample defined by higher educational attainment explain no heritability of the heritability in the lower education group, and vice-versa. Finally, we do find consistent heritability estimates when we compare family-based estimates versus those based on measured genotype.
Microgeographic variation in locomotor traits among lizards in a human-built environment

Microgeographic variation in fitness-relevant traits may be more common than previously appreciated. The fitness of many vertebrates is directly related to their locomotor capacity, a whole-organism trait integrating behavior, morphology, and physiology. Because locomotion is inextricably related to context, I hypothesized that it might vary with habitat structure in a wide-ranging lizard, Podarcis erhardii, found in the Greek Cyclade Islands. I compared lizard populations living on human-built rock walls, a novel habitat with complex vertical structure, with nearby lizard populations that are naive to human-built infrastructure and live in flat, loose-substrate habitat. I tested for differences in morphology, behavior, and performance. Lizards from built sites were larger and had significantly (and relatively) longer forelimbs and hindlimbs. The differences in hindlimb morphology were especially pronounced for distal components—the foot and longest toe. These morphologies facilitated a significant behavioral shift in jumping propensity across a rocky experimental substrate. I found no difference in maximum velocity between these populations; however, females originating from wall sites potentially accelerated faster over the rocky experimental substrate. The variation between these closely neighboring populations suggests that the lizards inhabiting walls have experienced a suite of trait changes enabling them to take advantage of the novel habitat structure created by humans.
Outcomes of patients with spontaneous coronary artery dissection

Background Spontaneous coronary artery dissection (SCAD) is an uncommon but serious condition presenting as an acute coronary syndrome (ACS) or cardiac arrest. The pathophysiology and outcomes are poorly understood. We investigated the characteristics and outcomes of patients presenting with SCAD. Methods In a retrospective study of a large cohort of patients with SCAD, data were collected regarding clinical presentation, patient characteristics, vascular screening, coronary artery involvement and clinical outcomes. Results 40 patients with SCAD (95% women, mean age 45±10 years) were included. At least 1 traditional cardiovascular risk factor was present in 40% of patients. Migraine was reported in 43% of patients. Events preceding SCAD included parturition (8%), physical stress (13%), emotional stress (10%) and vasoconstrictor substance-use (8%). 65% of patients had a non-ST elevation ACS (NSTEACS) at presentation, 30% had an ST elevation myocardial infarction (STEMI) and 13% had a cardiac arrest. The left anterior descending artery was most frequently involved (68% of patients), and 13% had involvement of multiple coronary territories. Fibromuscular dysplasia (FMD) was identified in 7 (37%) of 19 patients screened. 68% of patients were managed medically, 30% had percutaneous coronary intervention and 5% had coronary artery bypass grafting. Over a median 16-month follow-up period, 8% of patients had at least 1 recurrent SCAD event. There were no deaths. Conclusions Patients with SCAD in this study often had multiple coronary territories involved (13%) and extracardiac vascular abnormalities, suggesting a systemic vascular process, which may explain the high incidence of migraine. All patients with SCAD should be screened for FMD and followed closely due to the possibility of recurrence.
Broadening Perspectives on Immigrant Experiences: Secondary Students Study the Absorption Difficulties Faced by Mizrachi Immigrants in Israel

ABSTRACT Over the course of the 2015–2016 academic year, 12th-grade students at a Jewish high school in Canada participated in a research study that assessed how they integrated morally complex narratives in Israel’s past into their own relationship with the country. This article presents material based on how students reacted to learning that some Jewish immigrants were mistreated by the government by way of intentional economic disparity, depiction as grotesque caricatures in standard curricula, and denial of access to funds for cultural expression. The majority of students expressed shock and outrage as this narrative contrasted with the Zionist narrative that they had previously learned.
A Comparison of High-Level Approaches for Speeding Up Pathfinding

Most games being shipped today use some form of high-level abstraction such as a navmesh or waypoint graph for path planning. These structures can generally be represented in a form which is compact enough to meet the tight memory constraints in a game. But, when such a graph grows too large, finding paths can still be a complex task. This challenge was faced in Dragon Age: Origins and solved by adding an additional level of abstraction.In the last few years a variety of novel approaches have been developed for finding optimal paths through graphs with specific design applications for road networks. Currently these techniques cannot be feasibly applied to the lowest detail of movement possible in a game map, but can be applied to the high-level abstractions which are commonly found in games.In this paper we describe the pathfinding challenge faced before shipping the title Dragon Age: Origins and perform a postmortem analysis on the extended abstraction that was used in comparison to building more advanced heuristics or the use of contraction hierarchies. We show that contraction hierarchies and abstractions have similar overhead and performance and are both useful approaches for high-level planning in games.
Classification Calibration Dimension for General Multiclass Losses

We study consistency properties of surrogate loss functions for general multiclass classification problems, defined by a general loss matrix. We extend the notion of classification calibration, which has been studied for binary and multiclass 0-1 classification problems (and for certain other specific learning problems), to the general multiclass setting, and derive necessary and sufficient conditions for a surrogate loss to be classification calibrated with respect to a loss matrix in this setting. We then introduce the notion of classification calibration dimension of a multiclass loss matrix, which measures the smallest 'size' of a prediction space for which it is possible to design a convex surrogate that is classification calibrated with respect to the loss matrix. We derive both upper and lower bounds on this quantity, and use these results to analyze various loss matrices. In particular, as one application, we provide a different route from the recent result of Duchi et al. (2010) for analyzing the difficulty of designing 'low-dimensional' convex surrogates that are consistent with respect to pairwise subset ranking losses. We anticipate the classification calibration dimension may prove to be a useful tool in the study and design of surrogate losses for general multiclass learning problems.
Gradient-free maximum likelihood parameter estimation with particle filters

In this paper we address the problem of on-line estimation of unknown static parameters in non-linear non-Gaussian state-space models. We consider a particle filtering method and employ two gradient-free Stochastic approximation (SA) methods to maximize recursively the likelihood function, the finite difference SA and Spall's simultaneous perturbation SA. We demonstrate how these algorithms can generate maximum likelihood estimates in a simple and computationally efficient manner. The performance of the proposed algorithms is assessed through simulation
Constructing Precise Control Flow Graphs from Binaries

Third-party software is often distributed only in binary form. Precise and scalable binary analysis is an enabling technology for many software engineering and security techniques such as program verification, bug and vulnerability detection, and automated test case generation. One fundamental obstacle to performing binary analysis is the lack of precise control flow information. Existing techniques to construct the control flow of binaries are either static or dynamic. Traditional static techniques disassemble a program’s binary image statically and build the control flow graph (CFG) from the assembly-level representation of the program. They are limited in precision because of difficulty in statically resolving indirect branches. Dynamic techniques, on the other hand, suffer from poor coverage and scalability. Hybrid techniques based on combined dynamic and symbolic path exploration can improve code coverage, but still suffer from poor coverage and scalability because they rely on expensive constraint solving to generate alternative inputs to explore different control flow paths. This paper presents the first practical technique that constructs precise control flow graphs from binaries. Our technique rests on the key observation that the possible targets of most indirect branches are independent of intermediate program states, and thus by systematically forcing a program’s execution to explore both branches of each conditional, we can discover the program’s precise control flow. Specifically, we run the program under analysis in a controlled virtual environment. At each conditional branch, we save the address of the path not taken, and force the execution to explore that path later. In essence, we leverage both dynamic execution to compute the targets of indirect branches (as in traditional dynamic CFG construction) and efficient (since it is forced) systematic exploration specifically targeting the problem of control flow construction from binaries. We also introduce effective optimizations to make our dynamic forced execution scalable and practical. We have implemented our technique in a practical tool FXE for x86 binaries and performed detailed evaluation of its effectiveness. Our results show that FXE constructs highly precise CFGs and scales to real-world programs, significantly outperforming state-of-the-art alternatives.
Is it them? Or is it you? Examining Perceptions of Workplace Incivility Based on Personality Characteristics

Clare Barratt, Advisor Despite a wealth of research on the antecedents and outcomes of workplace incivility, little is known about the effect of individual differences on perceptions of incivility. The current study sought to examine whether personality and additional individual difference characteristics were predictive of perceptions of incivility. A sample of 295 working adults were exposed to vignettes depicting workplace interactions that could be interpreted as uncivil, and were asked to rate the degree to which each of these were perceived as rude, as well as to describe how they would hypothetically respond to a subset of these items. Results indicated that conscientiousness, narcissism, and hostile attribution bias were positively related to perceptions of incivility. Qualitative analysis demonstrated that the majority of participants would not escalate the described situations. Analyses additionally demonstrated that customerand coworkerperpetrated incivility were perceived as more uncivil than supervisor incivility. Theoretical and practical implications of these findings for future incivility research are discussed.
Coding-theoretic methods for reverse engineering of gene regulatory networks

We provide an overview of known modeling approaches for gene regulatory networks, and introduce a new framework for analyzing such networks as probabilistic polynomial dynamical systems. In the latter context, we describe how list decoding methods for Reed-Muller codes can be used to cope with small DNA microarray sample set problems and measurement noise. We also describe possible future research directions at the interface of systems biology and coding theory, pertaining to probabilistic dynamical systems with memory and probabilistic factor graphs with local list-decoding components.
Mixing patterns and communities on bipartite graphs on web-based social interactions

We use bipartite graph representation of interactions between users of Web databases, such as data about art subjects (books, movies, music records), where users interact via posting comments related to a specific subject. We study patterns of clustering which emerge through the common interests of users. We find robust scale-invariant features in several statistical measures, demonstrated with the data about movies, both in the bipartite and monopartite projections. We present evidence of disassortative mixing on the bipartite graphs which applies both for users and movies. With the spectral analysis of suitably projected weighted networks we find variety of communities, which are based on the properties of the subjects of common interests and of the user habits.
Procedure for Rapid Concentration and Detection of Enteric Viruses from Berries and Vegetables

ABSTRACT Several hepatitis A virus (HAV) and norovirus (NV) outbreaks due to consumption of berries and vegetables have been reported during recent years. To facilitate the detection of enteric viruses that may be present on different fresh and frozen products, we developed a rapid and sensitive detection method for HAV, NV, and rotavirus (RV). Initial experiments focused on optimizing the composition of the elution buffer, improving the viral concentration method, and evaluating the performance of various extraction kits. Viruses were extracted from the food surface by a direct elution method in a glycine-Tris (pH 9.5) buffer containing 1% beef extract and concentrated by ultrafiltration. Occasionally, PCR inhibitors were present in the processed berry samples, which gave relatively poor detection limits. However, this problem was overcome by adding a pectinase treatment in the protocol, which markedly improved the sensitivity of the method. After optimization, this concentration method was applied in combination with real-time reverse transcription-PCR (RT-PCR) using specific primers in various types of berries and vegetables. The average detection limits were 1 50% tissue culture infective dose (TCID50), 54 RT-PCR units, and 0.02 TCID50 per 15 g of food for HAV, NV, and RV, respectively. Based on our results, it is concluded that this procedure is suitable to detect and quantify enteric viruses within 6 h and can be applied for surveillance of enteric viruses in fresh and frozen products.
The Novelty of Human Cancer/Testis Antigen Encoding Genes in Evolution

In order to be inherited in progeny generations, novel genes should originate in germ cells. Here, we suggest that the testes may play a special “catalyst” role in the birth and evolution of new genes. Cancer/testis antigen encoding genes (CT genes) are predominantly expressed both in testes and in a variety of tumors. By the criteria of evolutionary novelty, the CT genes are, indeed, novel genes. We performed homology searches for sequences similar to human CT in various animals and established that most of the CT genes are either found in humans only or are relatively recent in their origin. A majority of all human CT genes originated during or after the origin of Eutheria. These results suggest relatively recent origin of human CT genes and align with the hypothesis of the special role of the testes in the evolution of the gene families.
Stem Cell Therapy in the Treatment of Neurological Diseases

Before a half century, regeneration of neurons has been admitted as an impossible event. Thus, neurodegenerative disorders (e.g. Parkinson’s disease, Alzheimer's disease, multiple sclerosis), vascular events (e.g. stroke) and traumatic diseases (e.g. spinal cord injury) have been admitted as incurable diseases. Afterward, tissue reparative and regenerative potential of stem cell researches for these disorders drew attention of the scientist to replacement therapy. Now, there are hundreds of current experimental and clinical regenerative treatment studies. One of the most popular treatment methods is cell transplantation. For this purpose many types of stem cells such as mononuclear stem cells, mesenchymal stem cells, and olfactory ensheathing cells can be used. As a result, cell transplantation has become a promising therapeutic option for these neurologic disorders. In this article, we reviewed stem cell treatment modalities for neurological disorders in the light of current literature.