Miracle-dz/UniFAR-FTUs huggingface dataset:
A Longitudinal Assessment of the Impact of Selected Organizational Influences on Salespeople's Organizational Commitment during Early Employment

To examine the antecedents and consequences of the development of salespeople's organizational commitment during early employment, the authors conducted a longitudinal study. The study focused on how changes in three key antecedents (leadership behavior, role stress, and job satisfaction) influence the development of commitment and how changes in commitment, in turn, affect turnover intentions and behavior. Results suggest that role ambiguity and job satisfaction (but not leadership behavior) are significant contributors to the development of organizational commitment during early employment. The results also show that organizational commitment influences turnover through its significant impact on propensity to leave.
Rac2 is a major actor of Drosophila resistance to Pseudomonas aeruginosa acting in phagocytic cells

Pathogen recognition and engulfment by phagocytic cells of the blood cell lineage constitute the first line of defense against invading pathogens. This cellular immune response is conserved throughout evolution and depends strictly on cytoskeletal changes regulated by the RhoGTPases family. Many pathogens have developed toxins modifying RhoGTPases activity to their own benefit. In particular, the Exoenzyme S (ExoS) toxin of the Gram‐negative bacteria Pseudomonas aeruginosa is directly injected into the host cell cytoplasm and contains a GAP domain (ExoSGAP) targeting RhoGTPases. Searching for the contribution of each RhoGTPases, Rho1, Rac1, Rac2, Mtl (Mig2‐like) and Cdc42 to fly resistance to P. aeruginosa infections, we found that Rac2 is required to resist to P. aeruginosa and to other Gram‐negative or Gram‐positive bacteria. The Rac2 immune‐deficient phenotype is attributable to defective engulfment of pathogens since Rac2‐mutant macrophages exhibited strong reduction in the phagocytosis level of both Gram‐negative and Gram‐positive bacterial particles whereas systemic immune signaling pathways, including Toll, Immune deficiency and Jun kinases, were not affected. Co‐expression of Rac2 and ExoSGAP rescued the increased sensitivity to P. aeruginosa observed in ExoSGAP‐expressing flies suggesting that Rac2 is the main host factor whose function is inhibited by the GAP domain of the ExoS toxin.
Peace Building in Bosnia and Herzegovina: Effects of Ingroup Identification, Outgroup Trust and Intergroup Forgiveness on Intergroup Contact

The current study examines the effects of ingroup identification, outgroup trust, and intergroup forgiveness on intergroup contact quantity in the diverse cities of Sarajevo and Tuzla in Bosnia and Herzegovina. A total of 455 individuals ranging in age from 14 to 102 self-reported as either Muslim, Roman Catholic, Orthodox Christian, or Other completed a questionnaire. Analyses revealed that ingroup identification was significantly and negatively correlated with intergroup contact quantity; however, ingroup identification was not significantly correlated with outgroup trust or intergroup forgiveness. The comparison between groups revealed significant group differences across all predictor and criterion variables. To confirm whether age or community background had a moderating effect on predicting the relation between ingroup identification, outgroup trust, and intergroup forgiveness on intergroup contact quantity, moderated regression analyses were conducted. Results revealed community background, ingroup identification, and outgroup trust were all significant contributors to the model; however, age and forgiveness were not. Taken as a whole, the entire model accounted for approximately 21% of variability in intergroup contact quantity. The results from the current study reinforce the supposition that the two cities of Sarajevo and Tuzla in Bosnia and Herzegovina cannot move towards reconciliation without first understanding the effect that strong ingroup identification has on mixing with the other diverse groups, and implementing proactive measures to enhance outgroup trust and cross-community outreach. Implementing these measures in the two cities of Sarajevo and Tuzla, along with other areas in Bosnia and Herzegovina, may improve future intergroup relations and move the country closer to reconciliation and peace.
Discrete-time series identification of sliding dynamic friction in industrial robotic joints

In this paper, the discrete-time series identification of dynamic friction in actuated robotic joints during the sliding regime is proposed. Considering the friction lag as a first order time delay element behind the static friction nonlinearity a reasonable approximation of friction dynamics in sliding is proposed. The regression signal model is derived based on a discrete-time transformation of motion dynamics with nonlinear friction. A robust identification scheme is formulated in the Least-Squares (LS) sense by using an appropriate set of model-related regressors. Further, the related Recursive-Least-Squares (RLS) formulation is provided. The proposed modeling and identification are evaluated experimentally by the offline and online parameter estimation. For these purposes the first vertical rotary joint of the base of a standard industrial robotic manipulator has been used in laboratory environment.
SGDI: System for Genomic Data Integration

This paper describes a framework for collecting, annotating, and archiving high-throughput assays from multiple experiments conducted on one or more series of samples. Specific applications include support for large-scale surveys of related transcriptional profiling studies, for investigations of the genetics of gene expression and for joint analysis of copy number variation and mRNA abundance. Our approach consists of data capture and modeling processes rooted in R/Bioconductor, sample annotation and sequence constituent ontology management based in R, secure data archiving in PostgreSQL, and browser-based workspace creation and management rooted in Zope. This effort has generated a completely transparent, extensible, and customizable interface to large archives of high-throughput assays. Sources and prototype interfaces are accessible at www.sgdi. org/software.
The Quest for Numeracy: Data and Methods in American Political History

The Quest for Numeracy: Data and Methods in American Political History Since World War II, some American historians have used quantitative evidence in their research with an enthusiasm and rigor that was unequaled in the historical discipline among the members of previous generations of scholars in this country. The tendency became apparent among economic and political historians during the mid-1950s. Within a decade, a different kind of social history had emerged as well. Inspired in large measure by the work of social scientists, the proponents of these "new" histories attempted both to expand the breadth of their approach and to deepen analysis of the economic, political, and social phenomena of the American past. Most American historians of the I930s and I940s acknowledged multicausality in explaining events in history and provided shopping lists of causal factors in their writing. Over the past three decades, historians have emerged who try to measure (albeit tentatively) the specific contribution of particular variables to outcomes under study, emphasizing the use of quantitative methods.1 The quantifiers of the post-World War II generation did, however, have forerunners who were active in the field of American history between I89o and 1940. Currently, most accept Jensen's view that the dominant influence in emphasizing the importance of analyzing quantitative data during those fifty years stemmed from the research, teaching, and students of Frederick Jackson Turner, whose fruitful career at the University of Wisconsin and Harvard University spanned the years I885-I924.2
Slowness learning for curiosity-driven agents

In the absence of external guidance, how can a robot learn to map the many raw pixels of high-dimensional visual inputs to useful action sequences? I study methods that achieve this by making robots self-motivated (curious) to continually build compact representations of sensory inputs that encode different aspects of the changing environment. Previous curiosity-based agents acquired skills by associating intrinsic rewards with world model improvements, and used reinforcement learning (RL) to learn how to get these intrinsic rewards. But unlike in previous implementations, I consider streams of high-dimensional visual inputs, where the world model is a set of compact low-dimensional representations of the high-dimensional inputs. To learn these representations, I use the slowness learning principle, which states that the underlying causes of the changing sensory inputs vary on a much slower time scale than the observed sensory inputs. The representations learned through the slowness learning principle are called slow features (SFs). Slow features have been shown to be useful for RL, since they capture the underlying transition process by extracting spatio-temporal regularities in the raw sensory inputs. However, existing techniques that learn slow features are not readily applicable to curiosity-driven online learning agents, as they estimate computationally expensive covariance matrices from the data via batch processing. The first contribution called the incremental SFA (IncSFA), is a low-complexity, online algorithm that extracts slow features without storing any input data or estimating costly covariance matrices, thereby making it suitable to be used for several online learning applications. However, IncSFA gradually forgets previously learned representations whenever the statistics of the input change. In open-ended online learning, it becomes essential to store learned representations to avoid re-learning previously learned inputs. The second contribution is an online active modular IncSFA algorithm called the curiosity-driven modular incremental slow feature analysis (Curious Dr. MISFA). Curious Dr. MISFA addresses the forgetting problem faced by IncSFA and learns expert slow feature abstractions in order from least to most costly, with theoretical guarantees.
The pathophysiology, diagnosis, and treatment of constipation.

BACKGROUND Constipation is a common condition about which there are many widespread notions that have no basis in fact. The purpose of this article is to summarize current scientific knowledge on the subject. METHODS Selective review of the literature. RESULTS Diagnostic evaluation usually fails to reveal the cause of constipation. It is due to medications in some patients, while endocrine disorders are the cause in only a small minority. Abnormal defecation may be due to dysfunction of the pelvic floor. Most patients complain of abdominal fullness and of needing to strain to pass stool; low stool frequency is a rare symptom. The symptoms alone determine the indication for treatment. Constipation usually poses no threat to health. Some patients are helped by a diet rich in fiber, others by laxatives. A number of laxatives with different modes of action are available; all are safe and generally well tolerated. In some patients, dysfunctional defecation may be an indication for proctological surgery. CONCLUSIONS The Rome criteria are useful for establishing a specific diagnosis of constipation. Most patients can be helped with laxatives and patient education.
Reduced phase space formalism for spherically symmetric geometry with a massive dust shell

We perform a Hamiltonian reduction of spherically symmetric Einstein gravity with a thin dust shell of positive rest mass. Three spatial topologies are considered: Euclidean $({R}^{3})$, Kruskal ${(S}^{2}\ifmmode\times\else\texttimes\fi{}R)$, and the spatial topology of a diametrically identified Kruskal $({\mathrm{RP}}^{3}\$ ${$a point at infinity$})$. For the Kruskal and ${\mathrm{RP}}^{3}$ topologies the reduced phase space is four dimensional, with one canonical pair associated with the shell and the other with the geometry; the latter pair disappears if one prescribes the value of the Schwarzschild mass at an asymptopia or at a throat. For the Euclidean topology the reduced phase space is necessarily two dimensional, with only the canonical pair associated with the shell surviving. A time reparametrization on a two-dimensional phase space is introduced and used to bring the shell Hamiltonians to a simpler (and known) form associated with the proper time of the shell. An alternative reparametrization yields a square-root Hamiltonian that generalizes the Hamiltonian of a test shell in Minkowski space with respect to Minkowski time. Quantization is briefly discussed. The discrete mass spectrum that characterizes natural minisuperspace quantizations of vacuum wormholes and ${\mathrm{RP}}^{3}$ geons appears to persist as the geometrical part of the mass spectrum when the additional matter degree of freedom is added.
A STUDY ON OUT-OF-VOCABULARY WORD MODELING FOR A SEGMENT-BASED KEYWORD SPOTTING SYSTEM

The purpose of a word spotting system is to detect a certain set of keywords in continuous speech. The most common approach consists of models of the keywords augmented with \(cid:12)ller," or \garbage" models, that are trained to account for non-keyword speech and background noise. Another approach is to use a large vocabulary continuous speech recognition sys-tem (LVCSR) to produce the most likely hypothesis string, and then search for the keywords in that string. The latter approach yields much higher performance, but is signi(cid:12)cantly more costly in computation and the amount of training data required. In this study, we develop a number of segment-based word spotting systems in an e(cid:11)ort to achieve performance comparable to the LVCSR spotter, but with only a small fraction of the vocabulary. We investigate a number of methods to model the keywords and background, ranging from a fewcoarse general models to re(cid:12)ned phone representations. The task is to detect sixty-one keywords from continuous speech in the ATIS corpus. We have achieved performance of 89.8% Figure of Merit (FOM) for the LVCSR spotter, 81.8% using phone-words as (cid:12)ller models, and 79.2% using eighteen more general models.
HUGS - A Lightweight Graph Partitioning Approach

The growing interest in graph data lead to increasingly more research in the field of graph data management and graph analytics. Nowadays, even large graphs of upto a size of billions of vertices and edges fit into main memory of big modern multisocket machines, making them a first-grade platform for graph management and graph analytics. High performance data management solutions have to be aware of the NUMA properties of such big machines. A dataoriented architecture (DORA) is a particular solution to that. However, it requires partitioning the data in a way such that inter-partition communication can be avoided. Graph partitioning is a long studied problem and stateof-the-art solutions, such as multilevel k-way partitioning and recursive bisection achieve good results in feasible time. Integrating such solution is a rather difficult task, though. In this paper, we present a more lightweight approach called Hugs. The key idea of Hugs is to reuse the BFS routine present in a graph data management system anyway, since it is the foundation of many analytical graph algorithms. Hugs is not meant to produce a good general-purpose graph partitioning but good runtimes of BFS graph traversals such as reachability queries on DORA systems. In our experiments Hugs showed capable of finding good graph partitionings faster than state-of-the-art approaches. The partitioning found by Hugs also showed shorter runtimes for reachability queries.
Expression of the nidogen-binding site of the laminin γ1 chain disturbs basement membrane formation and maintenance in F9 embryoid bodies

Basement membranes contain two major molecular networks consisting of laminin and collagen IV. Previous antibody perturbation experiments suggest that the interaction between laminin and nidogen-1 is necessary for proper basement membrane formation and epithelial development, whereas results from gene ablation experiments in mice show that both basement membranes and general development are grossly normal in the absence of nidogen-1. To refine the perturbation approach, we produced F9-teratocarcinoma-cell-derived embryoid bodies in the presence of recombinantly expressed nidogen-binding sites localized within the γ1III3-5 laminin fragment. We found basement membranes were disrupted in γ1III3-5-expressing embryoid bodies. As a measurement of basement membrane function, we tested permeability and detected drastically increased diffusion rates in correlation with basement membrane disruption. Furthermore, TROMA-1 localization in embryoid bodies expressing the nidogen-binding site was altered, suggesting separation of epithelium-specific gene expression from the formation of the actual epithelium when occurring in the absence of an organized basement membrane.
Lock-free and scalable multi-version software transactional memory

Software Transactional Memory (STM) was initially proposed as a lock-free mechanism for concurrency control. Early implementations had efficiency limitations, and soon obstruction-free proposals appeared, to tackle this problem, often simplifying STM implementation. Today, most of the modern and top-performing STMs use blocking designs, relying on locks to ensure an atomic commit operation. This approach has revealed better in practice, in part due to its simplicity. Yet, it may have scalability problems when we move into many-core computers, requiring fine-tuning and careful programming to avoid contention. In this paper we present and discuss the modifications we made to a lock-based multi-version STM in Java, to turn it into a lock-free implementation that we have tested to scale at least up to 192 cores, and which provides results that compete with, and sometimes exceed, some of today's top-performing lock-based implementations. The new lock-free commit algorithm allows write transactions to proceed in parallel, by allowing them to run their validation phase independently of each other, and by resorting to helping from threads that would otherwise be waiting to commit, during the write-back phase. We also present a new garbage collection algorithm to dispose of old unused object versions that allows for asynchronous identification of unnecessary versions, which minimizes its interference with the rest of the transactional system.
Identification of miR-34a-target interactions by a combined network based and experimental approach

Circulating miRNAs have been associated with numerous human diseases. The lack of understanding the functional roles of blood-born miRNAs limits, however, largely their value as disease marker. In a systems biology analysis we identified miR-34a as strongly associated with pathogenesis. Genome-wide analysis of miRNAs in blood cell fractions highlighted miR-34a as most significantly up-regulated in CD3+ cells of lung cancer patients. By our in silico analysis members of the protein kinase C family (PKC) were indicated as miR-34a target genes. Using a luciferase assay, we confirmed binding of miR-34a-5p to target sequences within the 3′UTRs of five PKC family members. To verify the biological effect, we transfected HEK 293T and Jurkat cells with miR-34a-5p causing reduced endogenous protein levels of PKC isozymes. By combining bioinformatics approaches with experimental validation, we demonstrate that one of the most relevant disease associated miRNAs has the ability to control the expression of a gene family.
HIE-FDTD Method With PML for 2-D Periodic Structures at Oblique Incidence

For analyzing the oblique incident plane wave on periodic structures with the fine structure only in one direction, a hybrid implicit-explicit finite-difference time-domain (HIE-FDTD) method with the perfectly matched layer (PML) is derived. First, the field transformation technique is adopted to eliminate the time delay, and the PML formulations are derived by using the auxiliary differential equation (ADE) method. Then, by combining the transformed Maxwell's equations with the PML formulations and adopting the locally one-dimensional (LOD) scheme, the proposed method with two substep implementations is obtained, which only needs to solve one implicit equation. The Courant-Friedrichs-Lewy (CFL) condition of the proposed method is more relaxed and no longer limited by the fine grid cell size.
Transforming Abstract Interpretations by Abstract Interpretation New Challenges in Language-based Security

In this paper we exploit abstract interpretation for transforming abstract domains and semantics. The driving force in both transformations is making domains and semantics, i.e. abstract interpretations themselves, complete, namely precise, for some given observation. We prove that a common geometric pattern is shared by all these transformations, both at the domain and semantic level. This pattern is based on the notion residuated closures, which in our case can be viewed as an instance of abstract interpretation. We consider these operations in the context of language-based security, and show how domain and semantic transformations model security policies and attackers, opening new perspectives in the model of information flow in programming languages.
Miniaturized rat-race coupler with bandpass response and good stopband rejection

Coupled-resonator network is applied to the design of a rat-race coupler with bandpass response in this paper. Net-type resonators are used to reduce the circuit size and control the harmonics. As a result, the proposed coupler exhibits not only a compact size but also good stopband rejection. The proposed coupler occupies only one sixth area of the conventional design, while the rejection level in the stopband is better than 30 dB up to 4. 3ƒ0. The measured results are in good agreement with the simulated predictions.
Development of a Multiplex Real-Time PCR Assay with an Internal Amplification Control for the Detection of Total and Pathogenic Vibrio parahaemolyticus Bacteria in Oysters

ABSTRACT Vibrio parahaemolyticus is an estuarine bacterium that is the leading cause of shellfish-associated cases of bacterial gastroenteritis in the United States. Our laboratory developed a real-time multiplex PCR assay for the simultaneous detection of the thermolabile hemolysin (tlh), thermostable direct hemolysin (tdh), and thermostable-related hemolysin (trh) genes of V. parahaemolyticus. The tlh gene is a species-specific marker, while the tdh and trh genes are pathogenicity markers. An internal amplification control (IAC) was incorporated to ensure PCR integrity and eliminate false-negative reporting. The assay was tested for specificity against >150 strains representing eight bacterial species. Only V. parahaemolyticus strains possessing the appropriate target genes generated a fluorescent signal, except for a late tdh signal generated by three strains of V. hollisae. The multiplex assay detected <10 CFU/reaction of pathogenic V. parahaemolyticus in the presence of >104 CFU/reaction of total V. parahaemolyticus bacteria. The real-time PCR assay was utilized with a most-probable-number format, and its results were compared to standard V. parahaemolyticus isolation methodology during an environmental survey of Alaskan oysters. The IAC was occasionally inhibited by the oyster matrix, and this usually corresponded to negative results for V. parahaemolyticus targets. V. parahaemolyticus tlh, tdh, and trh were detected in 44, 44, and 52% of the oyster samples, respectively. V. parahaemolyticus was isolated from 33% of the samples, and tdh+ and trh+ strains were isolated from 19 and 26%, respectively. These results demonstrate the utility of the real-time PCR assay in environmental surveys and its possible application to outbreak investigations for the detection of total and pathogenic V. parahaemolyticus.