Miracle-dz/UniFAR-FTUs huggingface dataset:
Implicit Contracting Close to Anonymity

Implicit contracts enforced by repeated interaction or reputation both require stability in the economic environment that simply is not present in a large number of transactions that exhibit limited reliance on external enforcement. Although instability of the environment forces contractual arrangements that are closer to the anonymity of market exchange, this instability leaves open an important avenue for contractual enforcement. This paper presents one class of such environments and shows how a simple mechanism can give rise to Paretoimproving implicit contracting. The key assumption is that in oneperiod relationships benets and costs can arise which are extremely asymmetric; minimal cost to one party can cause large increases in the value of the transaction to the other party. We provide several motivating examples, such as new product development, the relationship between the journal editor/researcher and the expansion of trade to new, potentially unknown, partners.
If you build it, will they come? Lessons learned in recruiting students for randomized controlled trials in postsecondary settings

ABSTRACT Randomized controlled trials (RCTs) are considered the most methodologically sound methods of conducting empirical research, but a successful RCT is contingent on the recruitment of subjects into the intervention and study. Few research articles and evaluations in education discuss recruitment, and even fewer discuss challenges in recruitment. This is worrisome, given that recruitment can jeopardize internal and external validity – the most valuable aspects of RCTs. This paper initiates a conversation about planning and carrying out a successful recruitment campaign, specifically in postsecondary settings where students are more autonomous, programmes are likely to be voluntary, the flow of information is disparate, and incentives are often misaligned for external evaluation. We also share our challenges and lessons learned in recruiting students for a student support programme and its evaluation. We also advocate that more researchers devote attention to, and sufficiently plan for the recruitment of subjects into RCTs.
A Survey on Utilization of Data Mining Approaches for Dermatological (Skin) Diseases Prediction

 Abstract— Due to recent technology advances, large volumes of medical data is obtained. These data contain valuable information. Therefore data mining techniques can be used to extract useful patterns. This paper is intended to introduce data mining and its various techniques and a survey of the available literature on medical data mining. We emphasize mainly on the application of data mining on skin diseases. A categorization has been provided based on the different data mining techniques. The utility of the various data mining methodologies is highlighted. Generally association mining is suitable for extracting rules. It has been used especially in cancer diagnosis. Classification is a robust method in medical mining. In this paper, we have summarized the different uses of classification in dermatology. It is one of the most important methods for diagnosis of erythemato-squamous diseases. There are different methods like Neural Networks, Genetic Algorithms and fuzzy classifiaction in this topic. Clustering is a useful method in medical images mining. The purpose of clustering techniques is to find a structure for the given data by finding similarities between data according to data characteristics. Clustering has some applications in dermatology. Besides introducing different mining methods, we have investigated some challenges which exist in mining skin data. Index Terms— Erythemato-squamous diseases, Data mining, Dermatology, Medical data mining.
Augmented telexistence in smart space

In this paper, we present the new environment for telexistence using our smart space which we have built for interactive space. We've developed several component modules for telexistence, such as display module for large scale display system, interaction module for multimodal interaction, video module for streaming and rendering module for augmented composition in our smart space. Those systems are well-integrated and allow for augmented telexistence functionality which is more natural and also give a beyond face-to-face communication between remote users. Based on our proposed environment, we can create new possibilities for immersive and interactive communication across the space.
Horizontal transport and dispersion in the surface layer of a medium‐sized lake

Lagrangian GPS drifter experiments, carried out in the surface layer of stratified Lake Kinneret (Israel), are presented. Differential kinematic properties and Lagrangian statistics were calculated and used to estimate the dominant mechanisms for horizontal dispersion. On time scales smaller than a few internal wave periods, internal waves lead to strong divergence and convergence events, causing instantaneous apparent horizontal growth rates that were larger, by up to an order of magnitude, than the actual mean dispersion coefficient. It is shown that the internal wave field modulated the vorticity field so as to satisfy conservation of potential vorticity. On time scales larger than a few internal wave periods, unbounded horizontal shear dispersion was of the same order as the actual mean observed dispersion coefficient (Kxy = 17.1 m2 s−1), while vertical shear dispersion was negligible.
Directed paths on hierarchical lattices with random sign weights

We study sums of directed paths on a hierarchical lattice where each bond has either a positive or negative sign with a probability $p$. Such path sums $J$ have been used to model interference effects by hopping electrons in the strongly localized regime. The advantage of hierarchical lattices is that they include path crossings, ignored by mean field approaches, while still permitting analytical treatment. Here, we perform a scaling analysis of the controversial ``sign transition'' using Monte Carlo sampling, and conclude that the transition exists and is second order. Furthermore, we make use of exact moment recursion relations to find that the moments $ $ always determine, uniquely, the probability distribution $P(J)$. We also derive, exactly, the moment behavior as a function of $p$ in the thermodynamic limit. Extrapolations ($n\to 0$) to obtain $ $ for odd and even moments yield a new signal for the transition that coincides with Monte Carlo simulations. Analysis of high moments yield interesting ``solitonic'' structures that propagate as a function of $p$. Finally, we derive the exact probability distribution for path sums $J$ up to length L=64 for all sign probabilities.
Tweets Language Identification using Feature Weighting

This paper describes the language identification method presented in Twitter Language Identification Workshop (TweetLID-2014). The proposed method represents tweets by weighted character-level trigrams. We employed three different weighting schemes used in Text Categorization to obtain a numerical value that represents the relation between trigrams and languages. For each language, we add up the importance of each trigram. Afterward, tweet language is determined by simple majority voting. Finally, we analyze the results.
A Distributed Algorithm in WDM Network to Increase Network Capacity and Minimize Conversion Range

A distributed wavelength assignment technology has been investigated in this work. The Distributed Static Highest Number of Destination (DSHND) algorithm is analysed and compared with two other distributed algorithms. The tree network investigated in this work is a binary tree instead of random trees assumed in other works. The main purpose of the proposed algorithm is to increase network capacity, minimize number of converters and reduce conversion range between the input and output wavelength.
Development of the A-DIVA Scale:

AbstractPlacement of a peripheral intravenous catheter is a routine procedure in clinical practice, but failure of intravenous cannulation regularly occurs. An accurate and reliable predictive scale for difficult venous access creates the possibility to use other techniques in an earlier time frame.We aimed to develop a predictive scale to identify adult patients with a difficult intravenous access prospectively: the A-DIVA scale.This prospective, observational, cross-sectional cohort study was conducted between January 2014 and January 2015, and performed at the department of anesthesiology of the Catharina Hospital (Eindhoven, The Netherlands). Patients 18 years or older were eligible if scheduled for any surgical procedure, regardless ASA classification, demographics, and medical history.Experienced and certified anesthesiologists and nurse anesthetists routinely obtained peripheral intravenous access. Cannulation was performed regarding standards for care.A failed peripheral intravenous cannulation on the first attempt was the outcome of interest.A population-based sample of 1063 patients was included. Failure of intravenous cannulation was observed in 182/1063 patients (17%). Five variables were associated with a failed first attempt of peripheral intravenous cannulation: palpability of the target vein (OR = 4.94, 95% CI [2.85–8.56]; P < 0.001), visibility of the target vein (OR = 3.63, 95% CI [2.09–6.32]; P < 0.001), a history of difficult peripheral intravenous cannulation (OR = 3.86, 95% CI [2.39–6.25]; P < 0.001), an unplanned indication for surgery (OR = 4.86, 95% CI [2.92–8.07]; P < 0.001), and the vein diameter of at most 2 millimeters (OR = 3.37, 95% CI [2.12–5.36]; P < 0.001). The scoring system was applied in 3 risk groups: 36/788 patients (5%) suffered from a failed first attempt in the low-risk group (A-DIVA score 0 or 1), whereas the medium (A-DIVA score 2 or 3) and high-risk group (A-DIVA score 4 plus), included 72/195 (37%) and 74/80 (93%) patients with a failed first attempt of inserting a peripheral intravenous catheter, respectively.The additive 5-variable A-DIVA scale is a reliable predictive rule that implies the probability to identify patients with a difficult intravenous access prospectively.Dutch Trial Register (ref: 4595).
Using Multicast FEC to Solve the Midnight Madness Problem

“Push” technologies to large receiver sets often do not scale due to large amounts of data replication and limited network bandwidth. Even with improvements from multicast communication, scaling challenges persist. Diverse receiver capabilities still result in a high degree of resends. To combat this drawback, we combine multicast with Forward Error Correction. In this paper we describe an implementation of this approach that we call filecasting (Fcast) because of its direct application to multicast bulk data transfers. We discuss a variety of uses for such an application, focusing on solving the Midnight Madness problem, where congestion occurs at Web sites when a popular new resource is made available.
Design and Development of a Flexible Strain Sensor for Textile Structures Based on a Conductive Polymer Composite

The aim of this work is to develop a smart flexible sensor adapted to textile structures, able to measure their strain deformations. The sensors are “smart” because of their capacity to adapt to the specific mechanical properties of textile structures that are lightweight, highly flexible, stretchable, elastic, etc. Because of these properties, textile structures are continuously in movement and easily deformed, even under very low stresses. It is therefore important that the integration of a sensor does not modify their general behavior. The material used for the sensor is based on a thermoplastic elastomer (Evoprene)/carbon black nanoparticle composite, and presents general mechanical properties strongly compatible with the textile substrate. Two preparation techniques are investigated: the conventional melt-mixing process, and the solvent process which is found to be more adapted for this particular application. The preparation procedure is fully described, namely the optimization of the process in terms of filler concentration in which the percolation theory aspects have to be considered. The sensor is then integrated on a thin, lightweight Nylon fabric, and the electromechanical characterization is performed to demonstrate the adaptability and the correct functioning of the sensor as a strain gauge on the fabric. A normalized relative resistance is defined in order to characterize the electrical response of the sensor. Finally, the influence of environmental factors, such as temperature and atmospheric humidity, on the sensor performance is investigated. The results show that the sensor's electrical resistance is particularly affected by humidity. This behavior is discussed in terms of the sensitivity of the carbon black filler particles to the presence of water.
Particle method: an efficient tool for direct numerical simulations of a high Schmidt number passive scalar in turbulent flow

In this work, an efficient way to predict the dynamics of a scalar at high Schmidt numbers, advected by a turbulent flow, is presented. For high Schmidt numbers, the spatial resolution required for the scalar field has to be finer than the resolution required for the velocity field, leading to a significant computational cost due to the Courant-Friedrichs-Lewy (CFL) constraint. We propose here a remeshed particle method coupled to a spectral flow solver to overcome this computational cost limitation. This allows us to perform a systematic analysis of flows over a wide range of Reynolds and Schmidt numbers. For high enough Reynolds and Schmidt numbers, the results presented here recover the spectral behavior predicted by theory. First, the classic k−5/3 law (where k is the wave number) is found for the inertial-convective range. At intermediate scales, the viscous-convective range exhibits a k−1 law for Schmidt numbers higher than unity. Finally, the numerical results indicate that the dissipation range agree well with the Kraichnan model for high Schmidt numbers.
Organizational Application Managing Employee Retention as a Strategy for Increasing Organizational Competitiveness

Research indicates that the total cost of employee turnover is about 150% of an employee’s salary. Because of this high cost of turnover, the organization that is the focus of this article sought to understand their employee’s turnover intentions and the reasons for the potential turnover. Through a series of surveys, observations, and interviews, it was determined that the location of the company and its compensation package were the most common factors in remaining with the company and that compensation and lack of challenge and opportunity were the most common factors in contemplating leaving the organization. Purpose of the Study The purpose of this study was to determine the factors that most significantly influence employees’ decisions to remain employed at a particular organization and possible reasons for choosing to leave. In addition, the study sought to describe the importance of retaining critical employees and developing strategies to enhance employee retention practices. The importance of this issue is demonstrated by the finding that 86% of employers experience difficulty attracting new employees and 58% experience difficulty retaining their employees (Hale, 1998). The results of the current study can be used by organizations to develop policies, practices, and strategies that would enable higher levels of employee retention and create greater efficiencies in meeting strategic business objectives.
Governing teacher learning: understanding teachers’ compliance with and critique of standardization

Abstract This paper examines how policy pressure for increased performance on standardised measures of student achievement influenced the teacher learning practices that arose in a school setting in Queensland, Australia. Drawing upon research and theorising of governing by numbers, and applications to the governance of education, and particularly teachers’ learning, the research analyses how a group of Year 3 teachers collaborated to better inform themselves about the nature of their students’ learning. The research reveals that the governance of teachers’ learning under current policy conditions was manifest through both teachers’ compliance with and critique of a strong focus upon school, regional, state and national data – specifically, students’ attainment in ‘leveled’ readers and other school-based standardised measures of reading and mathematics, and school, state and regional results on national literacy and numeracy tests. There is little research that highlights the tensions around these numbers as governing technologies in relation to specific formal, ongoing instances of teacher professional development practices. The research cautions against the influence of such governing processes for how they potentially narrow teachers’ attention to more standardized measures of students’ learning, even as teachers may critique these more reductive effects.
Growth phase-dependent production of a cell wall-associated elastinolytic cysteine proteinase by Staphylococcus epidermidis

Abstract Staphylococcus epidermidis, a Gram-positive, coagulase-negative bacterium is a predominant inhabitant of human skin and mucous membranes. Recently, however, it has become one of the most important agents of hospital-acquired bacteriemia, as it has been found to be responsible for surgical wound infections developed in individuals with indwelling catheters or prosthetic devices, as well as in immunosupressed or neutropenic patients. Despite their medical significance, little is known about proteolytic enzymes of S. epidermidis and their possible contribution to the bacteriums pathogenicity; however, it is likely that they function as virulence factors in a manner similar to that proposed for the proteases of Staphylococcus aureus. Here we describe the purification of a cell wall-associated cysteine protease from S. epidermidis, its biochemical properties and specificity. A homology search using N-terminal sequence data revealed similarity to staphopain A (ScpA) and staphopain B (SspB), cysteine proteases from S. aureus. Moreover, the gene encoding S. epidermidis cysteine protease (Ecp) and a downstream gene coding for a putative inhibitor of the protease form an operon structure which resembles that of staphopain A in S. aureus. The active cysteine protease was detected on the bacterial cell surface as well as in the culture media and is apparently produced in a growth phase-dependent manner, with initial expression occurring in the midlogarithmic phase. This enzyme, with elastinolytic properties, as well as the ability to cleave α1PI, fibrinogen and fibronectin, may possibly contribute to the invasiveness and pathogenic potential of S. epidermidis.
Beta Combination Graphs

Let G(V,E) be a graph with p vertices and q edges.A graph G(p,q) is said to be a Beta combination graph if there exist a bijection f: V(G)  {1,2 . , p } such that the induced function Bf: E(G)N, N is a natural number, given by Bf (uv)= f(v)! f(u)! f(v)]! + [f(u) ,every edges uv G and are all distinct and the function f is called the Beta combination labeling.In this paper, we proved the Petersen graph , Complete graph Kn (n≤ 8),Ladder Ln (n 2), fan fn (n≥ 2), wheel Wn(n≥ 3), path Pn , cycle Cn(n≥3),friendship graph Fn (n≥1),complete bipartite graph Kn,n (n≥ 2), Tree Tn , triangle snake , n-bistar graph Bn,n and Star graph K1,n (n>1) are the Beta combination graphs.Also we proved Complete graph Kn (n>8) is not a Beta combination graph. General Terms Mathematical subject classification(2010) 05C78.
An Extension of Semantic Proximity for Fuzzy Multivalued Dependencies in Fuzzy Relational Database

Following the development of fuzzy logic theory by Lotfi Zadeh, its applications were investigated by researchers in different fields. Presenting and working with uncertain data is a complex problem. To solve for such a complex problem, the structure of relationships and operators dependent on such relationships must be repaired. The fuzzy database has integrity limitations including data dependencies. In this paper, first fuzzy multivalued dependency based semantic proximity and its problems are studied. To solve these problems, the semantic proximity's formula is modified, and fuzzy multivalued dependency based on the concept of extension of semantic proximity with \alpha degree is defined in fuzzy relational database which includes Crisp, NULL and fuzzy values, and also inference rules for this dependency are defined, and their completeness is proved. Finally, we will show that fuzzy functional dependency based on this concept is a special case of fuzzy multivalued dependency in fuzzy relational database.
4-Way Handshake Solutions to Avoid Denial of Service Attack in Ultra Wideband Networks

ECMA-368 (European Computer Manufacturers Association) Standard specifies the ultra wideband MAC(Medium Access Control) sublayer for a high-speed short range wireless network. This Standard specifies a 4-way handshake mechanism to guarantee secure data transmission; however, it also provides opportunities for hackers to produce DoS(Denial of Service) or DDoS(Distributed DoS) attacks. The paper outlines two scenarios where it is possible to produce DoS and DDoS attacks to 4-way handshake of ECMA-368 standard while two solutions are given respectively. The first DoS attack will consume system’s resources such as CPU and memory resources. The solution successfully prevents the first DoS attack. The second attack deprives the legitimate device of the possibilities to build secure relationship and the solution suppresses the hackers’ behavior. The solutions increase the security of ECMA-368.
The Major Histocompatibility Complex in Transplantation

The transplant of organs is one of the greatest therapeutic achievements of the twentieth century. In organ transplantation, the adaptive immunity is considered the main response exerted to the transplanted tissue, since the principal target of the immune response is the MHC (major histocompatibility complex) molecules expressed on the surface of donor cells. However, we should not forget that the innate and adaptive immunities are closely interrelated and should be viewed as complementary and cooperating. When a human transplant is performed, HLA (human leukocyte antigens) molecules from a donor are recognized by the recipient's immune system triggering an alloimmune response Matching of donor and recipient for MHC antigens has been shown to have a significant positive effect on graft acceptance. This paper will present MHC, the innate and adaptive immunities, and clinical HLA testing.
Linear filtering of image subbands for low complexity postprocessing of decoded color images

In reference 1, image adaptive linear minimum mean squared error (LMMSE) filtering was proposed as an enhancement layer color image coding technique that exploited the statistical dependencies among the luminance/chrominance or Karhunen Loeve Transform (KLT)coordinate planes of a lossy compressed color image to enhance the red, blue, green (RGB) color coordinate planes of that image. In the current work, we propose the independent design and application of LMMSE filters on the subbands of a color image as a low complexity solution. Towards this end, only the coordinates of the neighbors of the filtered subband coefficient, that are sufficiently correlated with the corresponding coordinate of the filtered subband coefficient, are included in the support of the filter for each subband. Additionally, each subband LMMSE filter is selectively applied only on the high variance regions of the subband. Simulation results show that, at the expense of an insignificant increase in the overhead rate for the transmission of the coefficients of the filters and with about the same enhancement gain advantage, subband LMMSE filtering offers a substantial complexity advantage over fullband LMMSE filtering.