Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of MapReduce Task Re-execution Policy on Job Completion Reliability and Job Completion Time

MapReduce has been a worldwide accepted framework for solving data-intensive applications. To prevent MapReduce jobs from being interrupted by node failures which occur frequently in a large-scale MapReduce cluster, current MapReduce implementations, e.g., Hadoop, employ a task re-execution policy (TR policy for short) for MapReduce jobs, i.e., when a map/reduce task of a job fails due to node failure, this policy reperforms the task on another node. However, the impact of the TR policy on job completion reliability and job completion time have not been studied from a theoretical viewpoint, especially when the job is given different characteristics, e.g., different input data sizes, different numbers of reduce tasks, and different intermediate data sizes. In this study, we derive the job completion reliability (JCR for short) of a MapReduce job based on Poisson distributions and analyze the expected job completion time (JCT for short) based on the universal generation function. We use nine settings of task re-execution factor (TR factor for short) to explore the impact of the TR policy on the JCR and JCT of jobs. The results show that the TR policy can effectively improve JCR without significantly prolonging JCT. But there is no single TR factor with which all jobs can achieve a high JCR.
A survey on elastic resource allocation algorithm for cloud infrastructure

Elasticity is an asset of cloud computing which makes it better or may be best over the other conventional grid and cluster computing. Cloud elasticity is the ability of the cloud infrastructure to rapidly change the amount of resources allocated to a service during runtime in order to meet the actual varying demands on the service while enforcing SLAs. Initially, elasticity being a key feature of clouds is classified based on Scope, Policy, Purpose and Method of elasticity. This completely explains where, how and why elasticity is crucial. Secondly, diversified related work to elasticity is reviewed and discussed in order to define the state of the art of elasticity in clouds. In this paper we have compared various proposed algorithm based on Quality of service and whether they support elasticity of not.
Sensory neurone responses to mucosal noxae in the upper gut: relevance to mucosal integrity and gastrointestinal pain

Abstract The digestive tract is supplied by extrinsic and intrinsic sensory neurones that, together with endocrine and immune cells, form a surveillance network that is essential to gut function. This article focuses on the responses of extrinsic afferent neurones to chemical insults of the gastrointestinal mucosa and their pathophysiological relevance to mucosal integrity and abdominal pain. Within the gastroduodenal region, spinal afferents subserve an emergency function because, in case of alarm by influxing acid, they stimulate mechanisms of mucosal protection via an efferent‐like release of transmitters. Other sensory neurones signal chemical noxae to the brain, a task that is not confined to spinal afferents because vagal afferents communicate gastric acid and peripheral immune challenges to the brainstem and in this way elicit autonomic, endocrine, affective and behavioural reactions. Emerging evidence indicates that hypersensitivity of extrinsic afferent pathways to mechanical and chemical stimuli makes an important contribution to the abdominal hyperalgesia seen in functional dyspepsia and irritable bowel syndrome. Sensitization may be brought about by inflammatory processes that lead to up‐regulation and functional alterations of receptors and ion channels on sensory neurones. Such sensory neurone‐specific molecules, which include vanilloid (capsaicin) receptors, may represent important targets for novel drugs to treat abdominal pain.
Viewpoint Paper: Some Unintended Consequences of Information Technology in Health Care: The Nature of Patient Care Information System-related Errors

Medical error reduction is an international issue, as is the implementation of patient care information systems (PCISs) as a potential means to achieving it. As researchers conducting separate studies in the United States, The Netherlands, and Australia, using similar qualitative methods to investigate implementing PCISs, the authors have encountered many instances in which PCIS applications seem to foster errors rather than reduce their likelihood. The authors describe the kinds of silent errors they have witnessed and, from their different social science perspectives (information science, sociology, and cognitive science), they interpret the nature of these errors. The errors fall into two main categories: those in the process of entering and retrieving information, and those in the communication and coordination process that the PCIS is supposed to support. The authors believe that with a heightened awareness of these issues, informaticians can educate, design systems, implement, and conduct research in such a way that they might be able to avoid the unintended consequences of these subtle silent errors.
Reduced Insulin Exocytosis in Human Pancreatic β-Cells With Gene Variants Linked to Type 2 Diabetes

The majority of genetic risk variants for type 2 diabetes (T2D) affect insulin secretion, but the mechanisms through which they influence pancreatic islet function remain largely unknown. We functionally characterized human islets to determine secretory, biophysical, and ultrastructural features in relation to genetic risk profiles in diabetic and nondiabetic donors. Islets from donors with T2D exhibited impaired insulin secretion, which was more pronounced in lean than obese diabetic donors. We assessed the impact of 14 disease susceptibility variants on measures of glucose sensing, exocytosis, and structure. Variants near TCF7L2 and ADRA2A were associated with reduced glucose-induced insulin secretion, whereas susceptibility variants near ADRA2A, KCNJ11, KCNQ1, and TCF7L2 were associated with reduced depolarization-evoked insulin exocytosis. KCNQ1, ADRA2A, KCNJ11, HHEX/IDE, and SLC2A2 variants affected granule docking. We combined our results to create a novel genetic risk score for β-cell dysfunction that includes aberrant granule docking, decreased Ca2+ sensitivity of exocytosis, and reduced insulin release. Individuals with a high risk score displayed an impaired response to intravenous glucose and deteriorating insulin secretion over time. Our results underscore the importance of defects in β-cell exocytosis in T2D and demonstrate the potential of cellular phenotypic characterization in the elucidation of complex genetic disorders.
Spatial stability in super wideband channel responses

This paper examines the generally accepted multipath model of wideband radio channels. We use a simple multipath model based on paths of unlimited spatial extent, and compare it to a model that allows a finite spatial extent to the paths (that may result, for example, from shadowing). The comparison shows that the introduction of a finite spatial extent improves the accuracy of the model. Both models are fitted with parameters and compared to measurements from an indoor campaign. Our analysis is based on measurements in the 2-18 GHz band; we made static impulse response measurements with the receiving antenna at different positions along a one meter long linear axis.
Indigenous perpetrators of violence: Prevalence and risk factors for offending

The Australian Institute of Criminology was funded by the Australian Crime Commission to undertake research that could inform and complement the work of the National Indigenous Violence and Child Abuse Intelligence Task Force. It was important, given the plethora of government inquiries and initiatives in recent times, to initially review and assess the evidence of victimisation of, and offending by, Indigenous people. The first summary of this evidence on risk factors associated with Indigenous victimisation was released last year. It drew on a range of sources, primarily survey and administrative data, as well as specific studies, to distil the most significant individual and social risk factors. This report is the end result of a similar exercise. It highlights the gaps and limitations in publicly available administrative and survey data and shows that only a small number of empirical studies have been undertaken in this area. This is not to suggest that in-depth, qualitative research and wide-ranging consultations are not important - these document the viewpoints of Indigenous people; their everyday experience of being an Indigenous person and the kinds of violence they experience, witness and are fearful of. Their perceptions of what will prevent and reduce such violence are crucial to all policies and community-based initiatives aimed at tackling violence.
Cuts for circular proofs: semantics and cut-elimination

One of the authors introduced in [Santocanale, FoSSaCS, 2002] a calculus of circular proofs for studying the computability arising from the following categorical operations: finite products, finite coproducts, initial algebras, final coalgebras. The calculus presented [Santocanale, FoSSaCS, 2002] is cut-free; even if sound and complete for provability, it lacked an important property for the semantics of proofs, namely fullness w.r. t. the class of intended categorical models (called mu-bicomplete categories in [Santocanale, ITA, 2002]). In this paper we fix this problem by adding the cut rule to the calculus and by modifying accordingly the syntactical constraint ensuring soundness of proofs. The enhanced proof system fully represents arrows of the canonical model (a free mu-bicomplete category). We also describe a cut-elimination procedure as a a model of computation arising from the above mentioned categorical operations. The procedure constructs a cut-free proof-tree with possibly infinite branches out of a finite circular proof with cuts.
COLING 2014 The 25th International Conference on Computational Linguistics Proceedings of the AHA!-Workshop on Information Discovery in Text

Recent approaches to relation extraction following the distant supervision paradigm have focused on exploiting large knowledge bases, from which they extract substantial amount of supervision. However, for many relations in real-world applications, there are few instances available to seed the relation extraction process, and appropriate named entity recognizers which are necessary for pre-processing do not exist. To overcome this issue, we learn entity filters jointly with relation extraction using imitation learning. We evaluate our approach on architect names and building completion years, using only around 30 seed instances for each relation and show that the jointly learned entity filters improved the performance by 30 and 7 points in average precision.
The Spirit of Our Times: State Constitutions and International Human Rights

States have a direct responsibility to implement the U.S.'s international obligations in many areas governed by existing human rights treaties. This responsibility is drawn from the nature of federalism, the U.S. Constitution and from states' own constitutions. In light of the relatively populist structure of state governmental institutions, this implementation may be appropriately accomplished by state courts as well as the political branches of state governments. International law has a particularly important role to play in this process, particularly when courts construe states' affirmative constitutional grants - for example, for public health, education or welfare - that have no federal analogs. A case study of Article XVII, s. 3 of the New York State Constitution, which mandates that the state legislature provide for the public health, illustrates the concrete ways in which international law should inform state courts' constitutional decision-making.
Investigating adaptive mutation in the generalized generation gap (G3) algorithm for unconstrained global optimization

For function optimization problems in continuous search spaces, one of the main difficulties currently faced is that of locating high quality solutions. This problem is particularly pertinent for continuous multimodal problems where the quality rather than computational efficiency is more important as a test of the solver's ability to escape local optima and finding solutions near the global optimum [3]. Moreover, this difficulty is further compounded when the function involves large numbers of variables, which translates into a highly deceptive fitness landscape with very large numbers of local optima [2].
Adapting branch-target buffer to improve the target predictability of java code

Java programs are increasing in popularity and prevalence on numerous platforms, including high-performance general-purpose processors. The success of Java technology largely depends on the efficiency in executing the portable Java bytecodes. However, the dynamic characteristics of the Java runtime system present unique performance challenges for several aspects of microarchitecture design. In this work, we focus on the effects of indirect branches on branch-target address prediction performance. Runtime bytecode translation, just-in-time (JIT) compilation, frequent calls to the native interface libraries, and dependence on virtual methods increase the frequency of polymorphic indirect branches. Therefore, accurate target address prediction for indirect branches is very important for Java code.This paper characterizes the indirect branch behavior in Java processing and proposes an adaptive branch-target buffer (BTB) design to enhance the predictability of the targets. Our characterization shows that a traditional BTB will frequently mispredict a few polymorphic indirect branches, significantly deteriorating predictor accuracy in Java processing. Therefore, we propose a rehashable branch-target buffer (R-BTB), which dynamically identifies polymorphic indirect branches and adapts branch-target storage to accommodate multiple targets for a branch.The R-BTB improves the target predictability of indirect branches without sacrificing overall target prediction accuracy. Simulations show that the R-BTB eliminates 61% of the indirect branch mispredictions suffered with a traditional BTB for Java programs running in interpreter mode (46% in JIT mode), which leads to a 57% decrease in overall target address misprediction rate (29% in JIT mode). With an equivalent number of entries, the R-BTB also outperforms the previously proposed target cache scheme for a majority of Java programs by adapting to a greater variety of indirect branch behaviors.
A Survey on Input-Queued Scheduling Algorithms in High-Speed IP Routers

Most high-speed IP routers exploit cell-based switching fabrics, whose scalability and performance are mainly affected by queuing scheme and scheduling algorithm. Input-queued router is referred to as an ideal structure in terms of scalability. However, it needs an efficient scheduling algorithm to guarantee throughput and delay. Several input-queued scheduling algorithms are surveyed in this paper. The scheduling algorithms are classified into four classes: maximum size matching, maximum weight matching, stable marriage matching, and deterministic scheduling algorithm. The similarities and the difference of different algorithms in mechanisms of each class are described, and their performances are compared. Finally, the future directions and possible open problems are discussed.
Application of microprogramming to medium scale computer design

The concept of microprogrammable architectures can provide the system designer with a powerful development tool. This paper describes the development process of a medium scale computer system, using a specific microprogrammable processor. The hardware architecture used in this system is referred to as the MPP (microprogrammable processor) while the resulting computer system is referred to as the MP-60. The MPP hardware was designed to accomplish two primary goals; to shorten the lead time for computer system development by establishing a set of hardware building blocks, and to provide a mechanism for computer system emulation.
Zliczanie Ścieżek Kratowych

, której reprezentacja segmentowa to punkt początkowy (0, 0) oraz ciąg segmentów:). Rysunek 1: Ścieżka kratowa z punktu (0, 0) do (8, 0). Literatura dotycząca ścieżek kratowych jest bardzo bogata. Humphreys w swojej pracy przeglądowej [13] wymienia ponad dwieście kluczowych artykułów. Rozważane są ścieżki, które definiuje się poprzez ustalenie: punktu początkowego i końcowego, zbioru segmentów, zbioru punktów kraty oraz długości. Mając ustaloną rodzinę ścieżek, najczęściej pyta się o liczbę takich ścieżek oraz związki z innymi strukturami. Jedną z najbardziej znanych rodzin ścieżek kratowych są te, które składają się jedynie z dwóch typów segmentów: (1, 1) oraz (1, −1). W literaturze nazywane są ścieżkami Dycka. Po raz pierwszy zostały użyte przez Whitwortha [22] w 1878 roku do opisu pewnych problemów kombinatorycznych. W 1887 roku Bertrand sformułował w [3] słynny problem ballotowy (ang. ballot problem), który tłumaczony jest na pytanie o liczbę ścieżek Dycka z punktu (0, 0) do (u + d, u − d), gdzie u > d, które dodatkowo nie zawierają punktów kraty (i, 0) dla i 1. André [1] rozwiązując ten problem pokazał, że ich liczba jest równa (u+d−1 u) (u − d)/d. W szczególnym przypadku, liczba ścieżek Dycka z punktu (0, 0) do (2n, 0), które nie przechodzą przez punkty poniżej osi x jest równa liczbie Catalana C n = (2n n) /(n + 1).
Expert System to Detect and Diagnose the Leaf Diseases of Cereals

This paper presents a proposed expert system to identify the leaf diseases of three cereal crops (rice, maize and wheat). Keeping in view the advances in the field of agriculture and need of farmers, this expert system has been proposed. The identification of plant diseases is usually a difficult task and requires a plant pathologist or well-trained technician to accurately describe the case. Moreover, there are some diseases which have similar symptoms, thus making it difficult for non-experts like farmers to distinguish between diseases correctly. This expert system will use the colored images of the defected cereal plant leaves as well as the textual input to identify the disease. It will enable users/ farmers to identify any disease, makes the right decision and chooses the right treatment.
Human vascular endothelial cell adhesion receptors for Plasmodium falciparum-infected erythrocytes: roles for endothelial leukocyte adhesion molecule 1 and vascular cell adhesion molecule 1

The clinical complications associated with severe and cerebral malaria occur as a result of the intravascular mechanical obstruction of erythrocytes infected with the asexual stages of the parasite, Plasmodium falciparum. We now report that a primary P. falciparum- infected erythrocyte (parasitized red blood cell [PRBC]) isolate from a patient with severe complicated malaria binds to cytokine-induced human vascular endothelial cells, and that this adhesion is in part mediated by endothelial leukocyte adhesion molecule 1 (ELAM-1) and vascular cell adhesion molecule 1 (VCAM-1). PRBC binding to tumor necrosis factor alpha (TNF-alpha)-activated human vascular endothelial cells is partially inhibited by antibodies to ELAM-1 and ICAM-1 and the inhibitory effects of these antibodies is additive. PRBCs selected in vitro by sequential panning on purified adhesion molecules bind concurrently to recombinant soluble ELAM-1 and VCAM-1, and to two previously identified endothelial cell receptors for PRBCs, ICAM-1, and CD36. Post-mortem brain tissue from patients who died from cerebral malaria expressed multiple cell adhesion molecules including ELAM-1 and VCAM-1 on cerebral microvascular endothelium not expressed in brains of individuals who died from other causes. These results ascribe novel pathological functions for both ELAM-1 and VCAM-1 and may help delineate alternative adhesion pathways PRBCs use to modify malaria pathology.
A Massive Generation of IR Runs

In this demo we present a top-level interface for the Terrier platform. Terrier is an open source search engine that implements various indexing and retrieval models from the literature. A search process can be run using various parameters for indexing and retrieval in relation to TREC and INEX collections. However, with Terrier it is difficult to generate a significant number of runs in order to evaluate the influence of the various parameters. The interface we have developed helps the user instantly generate a significant number of runs.
Kernel-based semi-supervised learning for novelty detection

One-class Support Vector Machine (OCSVM) is a well-known method for novelty detection. However, OCSVM regards all negative data samples as a common symbol and thereby not being able to utilize the information carried by them. Furthermore, OCSVM requires a fully labeled data set and cannot work efficiently with data set with both labeled and unlabeled data samples which is very popular nowadays. In this paper, we first extend the model of OCSVM to enable efficiently using the negative data samples. We then propose two methods to integrate the semi-supervised learning paradigm to the extended model for novelty detection purpose.
The Advanced Compact MOSFET (ACM) Model for Circuit Analysis and Design

Most of the new generation compact models for the MOSFET have many commonalities since they are based on the same main approximations: gradual channel, charge-sheet, and depletion charge linearization. In this study we show that if we include some additional physics-consistent conditions for the MOSFET equations we obtain a very compact model that we call the advanced compact MOSFET (ACM) model. The core ACM model, design-oriented equations, parameter extraction, and a design example are presented.
Prediction of priors for communication over arbitrarily varying channels

We consider the problem of communicating over an unknown and arbitrarily varying channel, using feedback. This paper focuses on the problem of determining the input behavior, or more specifically, a prior which is used to randomly generate a codebook. We pose the problem of setting the prior as a sequential universal prediction problem using information theoretic abstractions of the communication channel. For the case where the channel is block-wise constant, we show it is possible to asymptotically approach the best rate that can be attained by any system using a fixed prior. For the case where the channel may change on each symbol, we combine a rateless coding scheme with a prior predictor and asymptotically approach the capacity of the average channel universally for every sequence of channels.