Miracle-dz/UniFAR-FTUs huggingface dataset:
Load Balancing for Parallel Computations with the Finite Element Method

In this paper, we give an overview of efforts to improve current techniques of load-balancing and efficiency of finite element method (FEM) computations on large-scale parallel machines and introduce a multilevel load balancer to improve the local load imbalance. FEM is used to numerically approximate solutions of partial differential equations (PDEs) as well as integral equations. The PDEs domain is discretized into a mesh of information and usually solved using iterative methods. Distributing the mesh among the processors in a parallel computer, also known as the mesh-partitioning problem, was shown to be NP- complete. Many efforts are focused on graph- partitioning to parallelize and distribute the mesh of information. Data partitioning is important to efficiently execute applications in distributed systems. To address this problem, a variety of general-purpose libraries and techniques have been developed providing great effectiveness. But the load-balancing problem is not yet well solved. Today's large simulations require new techniques to scale on clusters of thousands of processors and to be resource aware due the increasing use of heterogeneous computing architectures as found in many-core computer systems. Existing libraries and algorithms need to be enhanced to support more complex applications and hardware architectures. We present trends in this field and discuss new ideas and approaches that take into account the new emerging requirements.
An interactive color pre-processing method to improve tumor segmentation in digital medical images

x 1. INTRODUCTION 1 1.1 Medical Imaging 1 1.2 Medical Image Segmentation 4 1.3 Digital Image Processing 7 1.4 Motivation 9 1.5 Thesis Organization 10 2. LITERATURE REVIEW 12 2.1 Segmentation 12 2.1.1 Classical Approaches 13 2.1.2 Advanced Approaches 14 2.1.2.1 Statistical and Probabilistic Approaches 14 2.1.2.2 Deformable Models 15 2.1.2.3 Artificial Neural Networks (ANNs) 16 2.1.2.4 Fuzzy Logic 16 2.1.2.5 Atlas-guided approaches 17 2.1.3 Hybrid Approaches 18 2.2 Colorization 19 2.2.1 Color Fundamentals 19 2.2.2 General Colorization Concepts 22
Emotions in Organizations

There has been an “affective revolution” in organizational behavior since the mid-1990s, focusing initially on moods and affective dispositions. The past decade has seen a further shift toward investigating the complex roles played by discrete emotions in the workplace. Discrete emotions such as fear, anger, boredom, love, gratitude, and pride have their own appraisal antecedents, subjective experiences, and action tendencies that prepare people to respond to their current situation. Emotions have intrapersonal effects on the person experiencing them in terms of attention, motivation, creativity, information processing and judgment, and well-being. Some emotions have characteristic voice tones or facial expressions that serve the interpersonal function of communicating one’s state to interaction partners. For this reason, emotions are integral to social processes in organizations such as leadership, teamwork, negotiation, and customer service. The effects of emotions on behavior can be complex and context-dependent rather than straightforwardly mechanistic. Individuals may regulate the emotions they experience, the extent to which they display what they feel, and the actions they choose in response to how they feel. Research has tended to focus on negative emotions (e.g., anger or anxiety) and their potential negative effects (e.g., aggression or avoidance), but negative emotions can sometimes have positive consequences. Discrete positive emotions have been relatively ignored in organizational research but feeling and expressing positive emotions often have positive consequences. There is considerable scope for investigating the ways in which specific discrete emotions are experienced, regulated, expressed, and acted upon in organizational life. There may also be a case for intentional efforts by organizations and employees to increase the occurrence of positive emotions at work.
Visual Analytics for Epidemiologists: Understanding the Interactions Between Age, Time, and Disease with Multi-Panel Graphs

Background Visual analytics, a technique aiding data analysis and decision making, is a novel tool that allows for a better understanding of the context of complex systems. Public health professionals can greatly benefit from this technique since context is integral in disease monitoring and biosurveillance. We propose a graphical tool that can reveal the distribution of an outcome by time and age simultaneously. Methodology/Principal Findings We introduce and demonstrate multi-panel (MP) graphs applied in four different settings: U.S. national influenza-associated and salmonellosis-associated hospitalizations among the older adult population (≥65 years old), 1991–2004; confirmed salmonellosis cases reported to the Massachusetts Department of Public Health for the general population, 2004–2005; and asthma-associated hospital visits for children aged 0–18 at Milwaukee Children's Hospital of Wisconsin, 1997–2006. We illustrate trends and anomalies that otherwise would be obscured by traditional visualization techniques such as case pyramids and time-series plots. Conclusion/Significance MP graphs can weave together two vital dynamics—temporality and demographics—that play important roles in the distribution and spread of diseases, making these graphs a powerful tool for public health and disease biosurveillance efforts.
A duality between exceptions and states

In this short note we study the semantics of two basic computational effects, exceptions and states, from a new point of view. In the handling of exceptions we dissociate the control from the elementary operation that recovers from the exception. In this way it becomes apparent that there is a duality, in the categorical sense, between exceptions and states.
Leo: A Profile-Driven Dynamic Optimization Framework for GPU Applications

Parallel architectures like GPUs are a tantalizing compute fabric for performance-hungry developers. While GPUs enable order-of-magnitude performance increases in many data-parallel application domains, writing efficient codes that can actually manifest those increases is a non-trivial endeavor, typically requiring developers to exercise specialized architectural features exposed directly in the programming model. Achieving good performance on GPUs involves effort-intensive tuning, typically requiring the programmer to manually evaluate multiple code versions in search of an optimal combination of problem decomposition with architecture- and runtime-specific parameters. For developers struggling to apply GPUs to more general-purpose computing problems, the introduction of irregular data structures and access patterns serves only to exacerbate these challenges, and only increases the level of effort required. This paper proposes to automate much of this effort using dynamic instrumentation to inform dynamic, profile-driven optimizations. In this vision, the programmer expresses the application using higher-level front-end programming abstractions such as Dandelion [18], allowing the system, rather than the programmer, to explore the implementation and optimization space. We argue that such a system is both feasible and urgently needed. We present the design for such a framework, called Leo. For a range of benchmarks, we demonstrate that a system implementing our design can achieve from 1.12 to 27x speedup in kernel runtimes, which translates to 7-40% improvement for end-to-end performance.
Distributed diagnosis for multiprocessor systems using extended local neighborhoods

We show a solution to the characterization, diagnosability, and diagnosis problems with the t-in-L/sub 2/ diagnosability theory for permanently faulty processing elements (PEs). If there are at most t faulty PEs in the local neighborhood set of x, and at most t(m) faulty PEs in the extended-local neighborhood set of x, then we can uniquely diagnose any graph.
Cell Damage-induced Conformational Changes of the Pro-Apoptotic Protein Bak In Vivo Precede the Onset of Apoptosis

Investigation of events committing cells to death revealed that a concealed NH2-terminal epitope of the pro-apoptotic protein Bak became exposed in vivo before apoptosis. This occurred after treatment of human Jurkat or CEM-C7A T-lymphoma cells with the mechanistically disparate agents staurosporine, etoposide or dexamethasone. The rapid, up to 10-fold increase in Bak-associated immunofluorescence was measured with epitope-specific monoclonal antibodies using flow cytometry and microscopy. In contrast, using a polyclonal antibody to Bak, immunofluorescence was detected both before and after treatment. There were no differences in Bak protein content nor in subcellular location before or after treatment. Immunofluorescence showed Bcl-xL and Bak were largely associated with mitochondria and in untreated cells they coimmunoprecipitated in the presence of nonioinic detergent. This association was significantly decreased after cell perturbation suggesting that Bcl-xL dissociation from Bak occurred on exposure of Bak's NH2 terminus. Multiple forms of Bak protein were observed by two dimensional electrophoresis but these were unchanged by inducers of apoptosis. This indicated that integration of cellular damage signals did not take place directly on the Bak protein. Release of proteins, including Bcl-xL, from Bak is suggested to be an important event in commitment to death.
Evolutionary Approach in Development of Intelligent Computer Aided Design Systems

There is a word-wide upsurge of interest from both industry and academia in exciting novel computer technologies that are inspired by biological pr inciples and other natural processes. Evolutionary Computing, Artificial Neural Networks, Fuzzy Systems along with other adaptive techniques constitutes a new scientific domain, which was recently named as Soft or Intelli gent Computing. Nowadays this research area is under intensive investigations. However, Soft Computing based approach to development of the new generation of Computer Aided Design (CAD) systems, which are referred in this paper as Intelli gent CADs (ICAD), has not been well studied yet. This paper describes basic ideas of Genetic and other Evolutionary Algor ithms and their r oles in the frameworks of Soft Computing based approach to ICAD development.
A Systems Level Analysis of Transcriptional Changes in Alzheimer's Disease and Normal Aging

Alzheimer's disease (AD) is a debilitating neurodegenerative disorder affecting millions of elderly individuals worldwide. Advances in the genetics of AD have led to new levels of understanding and treatment opportunities. Here, we used a systems biology approach based on weighted gene coexpression network analysis to determine transcriptional networks in AD. This method permits a higher order depiction of gene expression relationships and identifies modules of coexpressed genes that are functionally related, rather than producing massive gene lists. Using this framework, we characterized the transcriptional network in AD, identifying 12 distinct modules related to synaptic and metabolic processes, immune response, and white matter, nine of which were related to disease progression. We further examined the association of gene expression changes with progression of AD and normal aging, and were able to compare functional modules of genes defined in both conditions. Two biologically relevant modules were conserved between AD and aging, one related to mitochondrial processes such as energy metabolism, and the other related to synaptic plasticity. We also identified several genes that were central, or hub, genes in both aging and AD, including the highly abundant signaling molecule 14.3. 3 ζ (YWHAZ), whose role in AD and aging is uncharacterized. Finally, we found that presenilin 1 (PSEN1) is highly coexpressed with canonical myelin proteins, suggesting a role for PSEN1 in aspects of glial-neuronal interactions related to neurodegenerative processes.
Horner's Syndrome Secondary to Epidural Anaesthesia Following Posterior Instrumented Scoliosis Correction

An 11-year-old girl underwent T4 to L1 posterior instrumented scoliosis correction for adolescent idiopathic scoliosis. Postoperative clinical examination revealed left-sided Horner's syndrome which was preceded by left-sided C8 paraesthesia. The Horner's syndrome resolved after 14 hours following weaning and removal of the epidural catheter. Horner's syndrome following posterior instrumented scoliosis correction associated to epidural use is extremely rare. Surgeons must be aware of the risks of epidural placement and the need for close monitoring of associated complications. Alternative aetiology producing a Horner's syndrome must always be considered because of its devastating long term sequela if missed.
Improvement of P-CUBE: Algorithm education tool for visually impaired persons

As a method of teaching fundamental programming concepts to visually impaired persons and novice programmers, we developed the P-CUBE algorithm education tool, with which users are able to control a mobile robot simply by positioning wooden blocks on a mat. The fundamental programming concepts taught by P-CUBE consist of three elements: sequences, branches and loops. The P-CUBE system consists of a mobile robot, a program mat, programming blocks, and a personal computer (PC). The programming blocks utilize radio frequency identification (RFID) tags alone, and thus require no precision equipment such as microcomputers. Furthermore, since P-CUBE is designed to be operated via tactile information, it can be utilized by visually impaired persons. In this paper, we report on the P-CUBE system configuration and a programming workshop held for visuarlly impaired persons. We then propose P-CUBE device improvements formulated through subjective assessments obtained from workshop participants.
Heterogeneity reduces time to reach consensus in collective decisions

Collective decision processes in multi-agent systems may eventually lead to two diﬁerent kindsof global states: (i) consensus, i.e. all agents have agreed to the same opinion, (ii) coexistence,i.e. not all agents agree to the same opinion, but may coexist with diﬁerent opinions. In thetrivial case, one can observe random distributions of agents coexisting with diﬁerent opinions.More interesting, however, are those cases where larger domains of agents with the same opinioncan be found. These domains may change in the course of time, but coexistence remains as anon-stationary phenomenon.In this paper, we focus only on collective decision processes which lead to consensus. We areparticularly interested in the time to reach consensus (TTC) and explore decision mechanismsto reduce the TTC for certain conditions. Whether or not consensus can be reached, dependsin general both on the spectrum of opinions and the way agents take their decisions. We onlyconsider those models where these decisions result from a local, heterogeneous interaction amongthe agents. Given a ﬂxed set of opinions and an initial spatial distribution of agents with diﬁerentopinions, one is then interested in the following questions: (i) What is the likelihood that a givenopinion is able to take over the whole system? (ii) How long will the process to reach consensustake? These questions have been discussed in diﬁerent context. Assuming a continuous spectrum ofopinions,HegselmannandKrause[2]haveinvestigatedamodel,whereagentsadapttheircurrentopinion in a group interaction. The size of the group depends on the number of \likeminded"agentsinthesystem,i.e.thoseagentswithadiﬁerenceintheiropinionssmallerthanaparameter† (conﬂdence interval). Since agents with too diﬁerent opinions do not interact, the value of †decides about reaching consensus or not. This model does not consider local eﬁects, as we areinterested in, and considers the aggregated opinions of like-minded agents rather than binaryinteractions. In a related model of Weisbuch et al. [7], the decision process is based on binaryinteractionsofrandomlychosenagents.Butinteractionsbetweenagentswithfardistantopinionsare still excluded.We are interested in another model class, the so-called \voter model" (VM), rigorously deﬂnedby Liggett [4]. Here agents decide about their opinion based on the frequency of opinions ofother agents in the neighborhood. In the linear VM, the probability to adopt a given opinion is1/4
Nonequilibrium Thermodynamics and Cosmological Pancake Formation

We investigate the influence of nonequilibrium thermodynamics on cosmological structure formation. In this paper, we consider the collapse of the planar perturbations usually called "Zeldovich pancakes. " We have developed for that purpose a new two-fluid (gas and dark matter) hydrodynamical code, with three different thermodynamical species: electrons, ions, and neutral particles, Te ≠ Ti ≠ Tn. We describe in detail the complex structure of accretion shock waves. We include several relevant processes for a low-density, high-temperature collisional plasma: nonequilibrium chemical reactions, cooling, shock heating, thermal energy equipartition between electrons, ions, and neutral particles, and electronic conduction. We find two different regions in the pancake structure: a thermal precursor ahead of the compression front and an equipartition wave after the compression front, where electron and ion temperatures differ significantly. This complex structure may have two interesting consequences: preheating of unshocked regions in the vicinity of massive X-ray clusters and ion and electron temperature differences in the outer regions of X-ray clusters.
Adverse Selection and Moral Hazard in Joint Liability Loan Contracts: Evidence from an Artefactual Field Experiment

We design an artefactual field experiment to study the relationship between joint-liability lending and adverse selection, moral hazard and risk preferences. While theories concerning joint-liability lending have highlighted its ability to mitigate adverse selection in credit transactions, our experimental results indicate that joint-liability lending may actually induce problems of adverse selection. The results of our experiment, carried on in partnership with a Bolivian microlender, show that borrowers exogenously endowed with a risky project are disproportionately likely to choose jointly-liability contracts over individually-liable contracts. This behavior does not appear to be motivated by risk-diversification, but rather by free-riding, as these subjects disproportionally switch from safe to risky projects when exogenously given a joint-liability contract instead of an individual contract. Thus the results of our experiment offer a possible explanation why joint liability loans have diminished in popularity in recent years among both borrowers and microfinance lenders.
Underwater sensor network: Architectures, challenges and applications

Recent advancements in information and communication technologies have resulted into improvements in wireless sensor networks. Since the human civilization is heading towards being “WIRELESS”, so as the field of communication and networking needs to be speeded in similar fashion. Detailed research at broad ends has been done on terrestrial networks. However, marine sensor networks have received limited attention. This paper focuses on understanding and analyzing the basic architecture of underwater sensor networks along with the types of marine sensors. We further explore their nature when subjected to marine environments. The paper also discusses the features, applications and challenges involved with marine sensor networks.
Astrometric Resolution of Severely Degenerate Binary Microlensing Events

We investigate whether the "close/wide" class of degeneracies in caustic-crossing binary microlensing events can be broken astrometrically. Dominik showed that these degeneracies are particularly severe because they arise from a degeneracy in the lens equation itself rather than a mere "accidental" mimicking of one light curve by another. A massive observing campaign of five microlensing collaborations was unable to break this degeneracy photometrically in the case of the binary lensing event MACHO 98-SMC-1. We show that this degeneracy indeed causes the image centroids of the wide and close solutions to follow an extremely similar pattern of motion during the time when the source is in or near the caustic. Nevertheless, the two image centroids are displaced from one another, and this displacement is detectable by observing the event at late times. Photometric degeneracies therefore can be resolved astrometrically, even for these most severe cases.
Influencia del apoyo familiar y escolar en el compromiso conductual de los estudiantes. Análisis multinivel en un IES de compensación educativa

espanolEl compromiso de los estudiantes con el aprendizaje y la escuela, dada su relacion con el rendimiento y la carrera academica, no deja de ser un reto en cualquier sistema educativo, que mantiene el interes de la investigacion socio-educativa. Esta realidad se ve aumentada cuando se pone el foco en centros educativos de compensacion educativa. Se trata de centros que canalizan curricularmente a aquellos estudiantes que fracasan en otros centros, y que suelen estar en situacion de riesgo de exclusion social. En consecuencia, los factores que influyen en el compromiso academico de los estudiantes, en este tipo de centros pueden identificarse de forma mas evidente. El estudio que se presenta en este articulo se ubica en un IES de estas caracteristicas, siendo sus objetivos: (a) identificar la medida en la que el apoyo familiar/escolar influye sobre el compromiso conductual (CC) de los estudiantes, y (b) ver la medida en la que el nivel educativo de la ESO (NE-ESO) modula esta influencia. En el estudio se implica a la totalidad de los estudiantes del IES, se aplica un cuestionario con una escala tipo Likert, y se realiza un analisis multinivel. Los resultados muestran una fuerte influencia del apoyo del profesorado sobre el compromiso conductual de los estudiantes con el proceso de ensenanza-aprendizaje. Asimismo, aunque en menor medida, resulta significativo el interes y participacion de la familia en los asuntos escolares. EnglishThe commitment of students to learning and school, given their relationship with performance and academic career, is no longer a challenge in any educational system, which maintains the interest of socio-educational research. This reality is increased when the focus is placed on educational compensation educational centers. These are centers that channel curricularly those students who fail in other centers, and who are usually at risk of social exclusion. Consequently, the factors that influence students’ academic commitment in these types of centers can be more clearly identified. The study presented in this article is located in an IES of these characteristics, its objectives being: (a) to identify the extent to which family/school support influences students’ behavioral commitment (CC); and (b) To see the extent to which the educational level of ESO (NE-ESO) modulates this influence. The study involves all students of the IES, a questionnaire is applied with a Likert scale, and a multi-level analysis. The results show a strong influence of teacher support on students’ behavioral commitment to the teaching-learning process. Also, although to a lesser extent, the interest and participation of the family in school matters is significant.