Miracle-dz/UniFAR-FTUs huggingface dataset:
Replication Strategies for Data Grids

The distributed and dynamic nature of grids present a number of challenging problems distinguished from conventional distributed computing by its focus on large-scale resource sharing and high-performance computing. Grid technology facilitates data sharing across many organizations in different geographical locations. Grid enabled applications need to manage and process large amount of data distributed across multiple grid nodes and stored in heterogeneous databases. Data replication is an excellent technique to move and cache data close to users. Replication reduces access latency and bandwidth consumption. It also facilitates load balancing and improves reliability by creating multiple data copies. Selecting a site for the placement of replica is attributed to various factors such as number of requests for a particular file, bandwidth, read/write statistics and location of the resources. In this paper, three replication strategies for dynamic data grids namely best replica site, cost effective site and topology based replication have been proposed and compared with no replication and existing methodologies.
Differential Evolution assisted by a surrogate model for bilevel programming problems

Bilevel programming is used to model decentralized problems involving two levels of decision makers that are hierarchically related. Those problems, which arise in many practical applications, are recognized to be challenging. This paper reports a Differential Evolution (DE) method assisted by a surrogate model to solve bilevel programming problems (BLPs). The method proposed is an extension of a previous one, BlDE, developed by the authors, where two DE methods are used to generate and evolve the upper and the lower level variables. Here, the use of a similarity-based surrogate model, and a different stopping criteria, are proposed in order to reduce the number of function evaluations on both levels of the problem. The numerical results show a significant reduction in the number of function evaluations in the lower level of the problem, as well as some improvement in the upper level.
A Novel Low-Cost, Large Curvature Bend Sensor Based on a Bowden-Cable

Bend sensors have been developed based on conductive ink, optical fiber, and electronic textiles. Each type has advantages and disadvantages in terms of performance, ease of use, and cost. This study proposes a new and low-cost bend sensor that can measure a wide range of accumulated bend angles with large curvatures. This bend sensor utilizes a Bowden-cable, which consists of a coil sheath and an inner wire. Displacement changes of the Bowden-cable’s inner wire, when the shape of the sheath changes, have been considered to be a position error in previous studies. However, this study takes advantage of this position error to detect the bend angle of the sheath. The bend angle of the sensor can be calculated from the displacement measurement of the sensing wire using a Hall-effect sensor or a potentiometer. Simulations and experiments have shown that the accumulated bend angle of the sensor is linearly related to the sensor signal, with an R-square value up to 0.9969 and a root mean square error of 2% of the full sensing range. The proposed sensor is not affected by a bend curvature of up to 80.0 m−1, unlike previous bend sensors. The proposed sensor is expected to be useful for various applications, including motion capture devices, wearable robots, surgical devices, or generally any device that requires an affordable and low-cost bend sensor.
The anatomy of an ad: structured indexing and retrieval for sponsored search

The core task of sponsored search is to retrieve relevant ads for the user's query. Ads can be retrieved either by exact match, when their bid term is identical to the query, or by advanced match, which indexes ads as documents and is similar to standard information retrieval (IR). Recently, there has been a great deal of research into developing advanced match ranking algorithms. However, no previous research has addressed the ad indexing problem. Unlike most traditional search problems, the ad corpus is defined hierarchically in terms of advertiser accounts, campaigns, and ad groups, which further consist of creatives and bid terms. This hierarchical structure makes indexing highly non-trivial, as naively indexing all possible "displayable" ads leads to a prohibitively large and ineffective index. We show that ad retrieval using such an index is not only slow, but its precision is suboptimal as well. We investigate various strategies for compact, hierarchy-aware indexing of sponsored search ads through adaptation of standard IR indexing techniques. We also propose a new ad retrieval method that yields more relevant ads by exploiting the structured nature of the ad corpus. Experiments carried out over a large ad test collection from a commercial search engine show that our proposed methods are highly effective and efficient compared to more standard indexing and retrieval approaches.
Performance Analysis of Distributed Opportunistic Incremental Decode-and-Forward Scheme in Cooperative Communication at Arbitrary SNR

In this paper, the outage probability and spectral efficiency of distributed opportunistic incremental decode-and-forward (DOIDF) are investigated. We derive the closed-form expressions for the outage probability and spectral efficiency including direct link at arbitrary SNR (signal to noise ratio) regime over independence-non-identical (inid) fading channels. Computer simulation results show that spectral efficiency of DOIDF outperforms the opportunistic relay scheme.
Brucella abortus Uses a Stealthy Strategy to Avoid Activation of the Innate Immune System during the Onset of Infection

Background To unravel the strategy by which Brucella abortus establishes chronic infections, we explored its early interaction with innate immunity. Methodology/Principal Findings Brucella did not induce proinflammatory responses as demonstrated by the absence of leukocyte recruitment, humoral or cellular blood changes in mice. Brucella hampered neutrophil (PMN) function and PMN depletion did not influence the course of infection. Brucella barely induced proinflammatory cytokines and consumed complement, and was strongly resistant to bactericidal peptides, PMN extracts and serum. Brucella LPS (BrLPS), NH-polysaccharides, cyclic glucans, outer membrane fragments or disrupted bacterial cells displayed low biological activity in mice and cells. The lack of proinflammatory responses was not due to conspicuous inhibitory mechanisms mediated by the invading Brucella or its products. When activated 24 h post-infection macrophages did not kill Brucella, indicating that the replication niche was not fusiogenic with lysosomes. Brucella intracellular replication did not interrupt the cell cycle or caused cytotoxicity in WT, TLR4 and TLR2 knockout cells. TNF-α-induction was TLR4- and TLR2-dependent for live but not for killed B. abortus. However, intracellular replication in TLR4, TLR2 and TLR4/2 knockout cells was not altered and the infection course and anti-Brucella immunity development upon BrLPS injection was unaffected in TLR4 mutant mice. Conclusion/Significance We propose that Brucella has developed a stealth strategy through PAMPs reduction, modification and hiding, ensuring by this manner low stimulatory activity and toxicity for cells. This strategy allows Brucella to reach its replication niche before activation of antimicrobial mechanisms by adaptive immunity. This model is consistent with clinical profiles observed in humans and natural hosts at the onset of infection and could be valid for those intracellular pathogens phylogenetically related to Brucella that also cause long lasting infections.
Understanding the Consequences of Technology for Human Interaction and Health: Gunilla Bradley’s Pioneer Scientific Contribution

I shall give a very personal testimony about Gunilla Bradley’s work. I will not try to make a well balanced review of Gunilla ́s lifelong contribution to science. This is the task of other better positioned colleagues. But it is only natural to be impressed by her formidable list of scientific merits. With a full background in psychology and computer technology, she has developed a research field around the encounter of human behaviour with computer based technology. She has served as a scientist of excellence in this field for several years, first at the Stockholm University Sociology Department, during which time she also was a guest visiting scientist at Stanford University, USA. She also served at the Universities of Umeå and Växjö. Her present appointment and maybe her most important contribution is with the Royal aBSTRaCT
The Return to History and the New Institutionalism in American Political Science

When it emerged as a discipline a century ago, the historical and comparative description of political institutions dominated political science. The self-consciously rigorous analysis of behavior inspired by psychology and the physical sciences began to displace historical analysis in the 1920s. By the 1950s and 1960s the behavioral revolution came to dominate the discipline’s research agendas. Leading practitioners acknowledged that the discipline’s tone was predominantly ahistorical.
K.E.M.Cs: A set of student's characteristics for modeling in adaptive programming tutoring systems

In this paper a set of student's characteristics that have to be considered in an adaptive and/or personalized programming tutoring system is presented. This set is called K.E. M.Cs and includes: knowledge, errors, motivation and cognitive states. It allows the system to identify the variety of backgrounds of prospective learners of programming, their misconceptions, needs and learning pace. The modeling of K.E. M.C. s is performed through a combination of different student modeling techniques: overlay, stereotypes, fuzzy logic and OCC cognitive theory. The gain of this approach is that the particular student model represents a sufficiently large part of the complex dimensions of a real student of programming. Therefore, it can be the base for the improvement of the quality of the learning process.
Hyperspectral image analysis for CARS, SRS, and Raman data

In this work, we have significantly enhanced the capabilities of the hyperspectral image analysis (HIA) first developed by Masia et al. 1 The HIA introduced a method to factorize the hyperspectral data into the product of component concentrations and spectra for quantitative analysis of the chemical composition of the sample. The enhancements shown here comprise (1) a spatial weighting to reduce the spatial variation of the spectral error, which improves the retrieval of the chemical components with significant local but small global concentrations; (2) a new selection criterion for the spectra used when applying sparse sampling2 to speed up sequential hyperspectral imaging; and (3) a filter for outliers in the data using singular value decomposition, suited e.g. to suppress motion artifacts. We demonstrate the enhancements on coherent anti‐Stokes Raman scattering, stimulated Raman scattering, and spontaneous Raman data. We provide the HIA software as executable for public use. © 2015 The Authors. Journal of Raman Spectroscopy published by John Wiley & Sons, Ltd.
A Wireless Revenue Based Scheduler with QoS Support

We propose a revenue based scheduling approach for a time slotted wireless communications system that takes Quality-of-Service (QoS) requirements such as a certain minimum data rate, maximum bit error rate, maximum delay or maximum delay variance into account. The objective function to be optimized is the revenue of the network operator. The QoS requirements are implicitly mapped onto the revenue by utilizing appropriate income functions. The resulting optimization problem is too complex to solve it in closed form. However, by introducing some simplifications it can be transformed into the problem of calculating a metric for each user in each time slot and scheduling the user who has the largest metric. Additionally, we propose an even simpler heuristic scheduler. The performance of the two approaches is evaluated by Monte Carlo simulations and compared with an upper bound of the achievable revenue. It turns out that the analytically derived scheduler achieves 99 % of this upper bound.
Determination of autoregressive model orders for seizure detection

In the present study, a step-wise least square estimation algorithm (SLSA), implemented in a Matlab package called as ARfit, has been newly applied to clinical data for estimation of the accurate Auto-Regressive (AR) model orders of both normal and ictal EEG series where the power spectral density (PSD) estimations are provided by the Burg Method. The ARfit module is found to be usefull in comparison to a large variety of traditional methods such as Forward Prediction Error (FPE), Akaike's Information Criteria (AIC), Minimum Description Lenght (MDL), and Criterion of Autoregressive Transfer function (CAT) for EEG discrimination. According to tests, the FPE, AIC and CAT give the identical orders for both normal and epileptic series whereas the MDL produces lower orders. Considering the resulting PSD estimations, it can be said that the most descriptive orders are provided by the SLSA. In conclusion, the SLSA can mark the seizure, since the estimated AR model orders meet the EEG complexity/regularity such that the low orders indicate an increase of EEG regularity in seizure. Then, the SLSA is proposed to select the accurate AR orders of long EEG series in diagnose for many possible future applications. The SLSA implemented by ARfit module is found to be superior to traditional methods since it is not heuristic and it is less computational complex. In addition, the more reasonable orders can be provided by the SLSA.
Analysis of LDPC code syndrome entropy based on subgraphs

We propose a method to bound the syndrome entropy of linear block codes from their factor graph representation. It is specially suited for sparse graphs such as those of low density parity check codes. It is based on the chain rule decomposition of the entropy and the confinement of dependencies within code subgraphs. After forcing or assuming the subgraphs to have a tree structure, the computation is done by means of density evolution as for a belief propagation analysis. We employ this method to compute upper bounds of the LDPC code syndrome entropy, which allows us to obtain asymptotic MAP upper bounds that match the ones obtained by the generalized area theorem.
Change in angular velocity at the end of the QRS loop aids the electrocardiographic detection of acute inferior myocardial infarction

We developed a new method for determining the QRS end, based on angular velocity (AV) changes around the QRS loop, and compared the method's performance to that of more established methods for determining QRS end in both healthy subjects and patients with acute myocardial infarction (AMI). Specifically, using Frank leads reconstructed from standard 12-lead ECGs, we determined AV in the direction of change raised to the 4th power, d(t). We found that the d(t)-determined AV transition (AVTr) nearly coincided with manually determined QRS end in healthy subjects, and in 27 patients with anterior AMI. However, in 31 patients with inferior AMI, AVTr typically preceded that of QRS end determined by the established methods, and by more than 10 ms in 32% of cases. While this “AVTr precedence” coincided with diagnostic ST elevation in only a minority of patients with recent inferior AMI, the use of AVTr precedence as a complement to more established methods for QRS end determination increased the sensitivity for detecting inferior AMIs from 23% to 42% without notably compromising specificity in healthy subjects (N=1050).
Cloning and expression of bovine p47‐phoxand p67‐phox: comparison with the human and murine homologs

Neutrophils play an essential role in bovine cellular host defense, and compromised leukocyte function has been linked to the development of respiratory and mucosal infections. During the host defense process, neutrophils migrate into infected tissues where they become activated, resulting in the assembly of neutrophil membrane and cytosolic proteins to form a superoxide anion‐generating complex known as the NADPH oxidase. Two of the essential cytosolic components of the NADPH oxidase are p47‐phox and p67‐phox. Currently, only the human and murine homologs of these proteins have been sequenced. Because of the important role neutrophils play in bovine host defense, we carried out studies to clone, sequence, and express bovine p47‐phox and p67‐phox. Using polymerase chain reaction (PCR) cloning techniques and a bovine bone marrow cDNA library, we have cloned both of these bovine NADPH oxidase cytosolic components. Comparison of the bovine sequences with those of the human and murine homologs showed that they were highly conserved, but also revealed important information regarding key structural features of p47‐phox and p67‐phox, including location of putative phosphorylation sites. Functional expression of bovine p47‐phox and p67‐phox showed that these proteins could substitute for the human proteins in reconstituting NADPH oxidase activity in a cell‐free assay system, again demonstrating the high degree of conservation between human and bovine homologs. This study greatly contributes to our understanding of the potential structural/functional regions of p47‐phox and p67‐phox as well as providing information that can be used to study the role of neutrophils in bovine inflammatory diseases. J. Leukoc. Biol. 67: 63–72; 2000.
A trap of optimizing skills use when allocating human resources to a multiple projects environment

Purpose The purpose of this paper is to highlight possible hidden risks when allocating multi-skilled human resources to teams working in a multi-project environment. Are allocation strategies maximizing the use of skills for each project, the only way to improve the chances of all projects being successful? What are the risks in this strategy? What are the available alternatives? Design/methodology/approach Simulation was used for different allocation strategies to evaluate, using two different metrics, the staffing of human resources in different projects. Three categories of companies were studied, and for each typology, virtual companies were created and several scenarios of collaborators, projects and tasks were simulated to evaluate the staffing process. Findings It is shown that for different simulations, different allocation strategies and metrics are possible for evaluation and that there is no golden rule of staffing in organizations with multiple projects and with multiple skills collaborators. The staffing is very much dependent on the context of the company. Practical implications The numerical method provides general managers with a useful tool to enable a better distribution of staff collaborators in teams handling multiple projects that require multi-skilled human resources. This method can also be used to evaluate training needs and hiring strategies, as it presents an overview of all human resources skills and motivations. Originality/value For academics, the methodology developed enables the study of characteristics of human resources, skills and motivations, which are interesting for team formation. To practitioners, the numerical method is a practical tool for staffing in multiple skills and multiple projects. This tool can also diagnose each company situation regarding current collaborators’ skills and motivations, serving as a tool for training and for hiring.
Active Imitation Learning: Formal and Practical Reductions to I.I.D. Learning

In standard passive imitation learning, the goal is to learn a policy that performs as well as a target policy by passively observing full execution trajectories of it. Unfortunately, generating such trajectories can require substantial expert eﬀort and be impractical in some cases. In this paper, we consider active imitation learning with the goal of reducing this eﬀort by querying the expert about the desired action at individual states, which are selected based on answers to past queries and the learner’s interactions with an environment simulator. We introduce a new approach based on reducing active imitation learning to active i.i. d. learning, which can leverage progress in the i.i. d. setting. Our ﬁrst contribution is to analyze reductions for both non-stationary and stationary policies, showing for the ﬁrst time that the label complexity (number of queries) of active imitation learning can be less than that of passive learning. Our second contribution is to introduce a practical algorithm inspired by the reductions, which is shown to be highly eﬀective in ﬁve test domains compared to a number of alternatives.
CS 294 A Toolkit for Algorithms Spring 2010 Lecture 1 : January 20

1. Explore applications of the recent ”Quantum Algorithm for Linear Systems of Equations” by Harrow, Hassidim and Lloyd [5]. This algorithm can solve a linear system of the form Ax = b, in time logarithmic in the dimensions of A, an exponential improvement over classical algorithms. However, the quantum algorithm cannot output the vector solution x explicitly, but only give an approximation to the value of x Mx for an input operator M .
Mice Lacking D5 Dopamine Receptors Have Increased Sympathetic Tone and Are Hypertensive

Dopamine is an important transmitter in the CNS and PNS, critically regulating numerous neuropsychiatric and physiological functions. These actions of dopamine are mediated by five distinct receptor subtypes. Of these receptors, probably the least understood in terms of physiological functions is the D5 receptor subtype. To better understand the role of the D5 dopamine receptor (DAR) in normal physiology and behavior, we have now used gene-targeting technology to create mice that lack this receptor subtype. We find that the D5 receptor-deficient mice are viable and fertile and appear to develop normally. No compensatory alterations in other dopamine receptor subtypes were observed. We find, however, that the mutant mice develop hypertension and exhibit significantly elevated blood pressure (BP) by 3 months of age. This hypertension appears to be caused by increased sympathetic tone, primarily attributable to a CNS defect. Our data further suggest that this defect involves an oxytocin-dependent sensitization of V1 vasopressin and non-NMDA glutamatergic receptor-mediated pathways, potentially within the medulla, leading to increased sympathetic outflow. These results indicate that D5dopamine receptors modulate neuronal pathways regulating blood pressure responses and may provide new insights into mechanisms for some forms of essential hypertension in humans, a disease that afflicts up to 25% of the aged adult population in industrialized societies.