Miracle-dz/UniFAR-FTUs huggingface dataset:
Bactericidal activity of OPC-67683 against drug-tolerant Mycobacterium tuberculosis.

OBJECTIVES There is an urgent need for drugs that hasten sterilization in tuberculosis; however, we presently lack indicators of this activity to guide early drug development. We previously described a novel in vitro assay to study mycobacterial phenotypic drug tolerance, in which sterilizing activity could be assessed. OPC-67,683 is a novel imidazooxazole that accelerates sterilization in the mouse tuberculosis model. The present study was conducted to determine the activity of OPC-67,683 in the in vitro tolerance model using drug-tolerant clinical Mycobacterium tuberculosis strains. METHODS Tolerance was assessed in Bactec radiometric culture as: (i) delayed decline in growth index during 14 days of drug exposure; (ii) shorter time to positivity of subcultures following drug exposure. RESULTS Four isolates were selected from among 16 surveyed, based on delayed killing by isoniazid and OPC-67,683. Unlike isoniazid and rifampicin, whose rates of killing were concentration-independent, OPC-67,683 showed concentration-dependent effects that, at the highest dose levels tested (1.0 microg/mL), were superior to isoniazid and equal to rifampicin. CONCLUSIONS The sterilizing activity of OPC-67683 against drug-tolerant M. tuberculosis in the Bactec model is consistent with its activity in mice. Further studies are warranted to examine the effects of OPC-67683 on mycobacterial persistence in tuberculous patients and to determine the biological basis of tolerance in the model.
Measurement of the spatial distribution of birefringence in optical fibers

We describe a technique for the measurement of the birefringence spatial distribution in a single-mode optical fiber with a resolution of 1 m. This technique is based on a polarization optical time-domain reflectometer using a rotary linear polarizer. We report results performed on different types of fibers: standard step-index and dispersion shifted fibers.
Mechanisms and Mediators of Inflammation: Potential Models for Skin Rejection and Targeted Therapy in Vascularized Composite Allotransplantation

Vascularized composite allotransplantation (VCA) is an effective treatment option for patients suffering from limb loss or severe disfigurement. However, postoperative courses of VCA recipients have been complicated by skin rejection, and long-term immunosuppression remains a necessity for allograft survival. To widen the scope of this quality-of-life improving procedure minimization of immunosuppression in order to limit risks and side effects is needed. In some aspects, the molecular mechanisms and dynamics of skin allograft rejection seem similar to inflammatory skin conditions. T cells are key players in skin rejection and are recruited to the skin via activation of adhesion molecules, cytokines, and chemokines. Blocking these molecules has not only shown success in the treatment of inflammatory dermatoses, but also prolonged graft survival in various models of solid organ transplantation. In addition to T cell recruitment, ectopic lymphoid structures within the allograft associated with chronic rejection in solid organ transplantation might contribute to the strong alloimmune response towards the skin. Selectively targeting the molecules involved offers exciting novel therapeutic options in the prevention and treatment of skin rejection after VCA.
Post-traumatic stress disorder and substance use following traumatic brain injury: a clinical and neuropsychological case study

The present study proposes to investigate the case of a patient with crack-cocaine use disorder from the occurrence of a neurological condition of traumatic brain injury (TBI) and development of Post-Traumatic Stress Disorder (PTSD). It is presumed that this is a case of crack and cocaine use disorder from the occurrence of two predisposing factors : TBI and the appearance of post-traumatic symptoms. Therefore, the present case discusses, clinically and based in neuropsychological assessment, the hypotheses of substance use as self-medication to attenuate the depressive symptoms related to the traumatic experience and/or as a consequence of a neuropsychological framework. Furthermore, the presence of a neurological condition may explain the subsequent progression to crack-cocaine use disorder.
60-GHz CMOS Direct-Conversion Transceiver Using Injection-Lock Oscillators

This paper presents a 60-GHz direct-conversion RF front-end realizing full 4-channel wireless communication. The 65-nm CMOS front-end consumes 319mW and 223mW in transmitting and receiving mode, respectively. It is capable of more than 7-Gb/s 16QAM wireless communication for every channel of the 60-GHz standards, which can be extended up to 10Gb/s.
The Cases of the European Values Study and the European Social Survey: European Constellations of Social Science Knowledge Production

This paper analyses two European social science surveys in a comparative perspective. Some twenty years apart, two groups of scholars launched two European social surveys. In 1981, the first round of the European Values Study (EVS) took place and twenty years later, in 2001, the first round of the European Social Survey (ESS) was launched. From the outset, both surveys were closely connected to national and European social scientific institutions, had ties to the EU and used the most sophisticated survey techniques of their time to address urgent contemporary political and social problems. However, only the ESS has managed to exploit these connections to European political institutions in order to obtain symbolic and monetary resources. The article argues that, in order to explain the trajectory of two social surveys, we need to understand not only the scientific and organizational properties of the two surveys, but just as importantly the constellation of the European field of research policy and the field of social science in Europe. In the twenty years separating the EVS and the ESS, social sciences and not least classical issues like social cohesion and political participation had become a part of issues funded through the EU research policies. In this way, the paper shows that success of social scientific projects are not only a result of the intrinsic qualities of the projects, but need to be understood in relation to and as a consequence of how it relates to of the social institutions and uses opening offers by changes in the settlement.
Graduate Entrepreneurship Incubation Environments

The benchmarking framework developed in this study is specifically designed for higher education institutions to consider when developing environments to encourage entrepreneurship among their students, graduates and staff. The objective of the study was to identify key success factors of Graduate Entrepreneurship Incubator Environments (GEIEs) that nurture, encourage and promote entrepreneurship in higher education. Semi-structured interviews with stakeholders in five leading UK entrepreneurial universities were used to collect data on GEIEs. The framework is a non-prescriptive tool which can be used by universities as a practical mechanism for plotting and monitoring progress towards an enabling environment for entrepreneurial graduates.
Gestational Diabetes Mellitus and Risk of Childhood Overweight and Obesity in Offspring: A Systematic Review

We systematically reviewed research examining the association between gestational diabetes (GDM) and childhood overweight and obesity. We identified studies from three sources: (1) a PubMed search of articles published between January 1990–January 2011, (2) reference lists of publications from the PubMed search, and (3) reference lists of review articles. We included studies that examined GDM separately from pregestational diabetes and childhood overweight or obesity defined as BMI > 85th or 95th percentile. A total of 12 studies were included in the systematic review. Crude odds ratios for the relationship between GDM and childhood overweight or obesity ranged from 0.7 to 6.3; in 8 studies, the associations were not statistically significant. In only 3 studies were results adjusted for any confounders; in the 2 that adjusted for prepregnancy obesity, the GDM and childhood overweight or obesity associations were attenuated and not statistically significant after adjustment. This paper demonstrates inconsistent evidence of an association between GDM and offspring overweight and obesity due to the methodological limitations of existing studies. Recommendations for future research are presented, which address methodological challenges.
Generating Chess Moves using PVM

Game playing is one of the oldest areas of endeavors in artificial intelligence. A chess playing computer is an existence proof of a machine doing something thought to require intelligence. Chess programs have three major components: move generation, search and evaluation. The speed of a chess program depends on the quality of the mechanisms used to prune search of unprofitable continuations. The most reliable pruning method in popular use is the alpha-beta algorithm. This paper presents a parallel alpha-beta searching algorithm and examines the performance of its implementation.
A prediction algorithm with a limited number of particles for state estimation of high-dimensional systems

The ensemble transform Kalman filter (ETKF) is a state estimation algorithm that is widely applied to estimating the state of nonlinear high-dimensional systems, such as data assimilation that combines observations and a numerical simulation model. The ETKF is an efficient algorithm that uses a relatively small number of particles to represent a probability density function for the state of a system. However, the existing methods for obtaining a predictive distribution for the ETKF are not necessarily applicable to general situations. One of the common methods, the Monte Carlo method, can be influenced by random errors if the use of a large number of particles is not allowed due to the computational cost of the simulation model. Another common method, the multiplicative inflation method, does not allow us to make arbitrary choices of the stochasticity of the system. The purpose of this work is to overcome these problems. In this study, we propose a new algorithm for obtaining particles that represent the predictive distribution. The proposed algorithm allows us make a prediction under an arbitrary system noise covariance matrix. Since it does not use random numbers, it well works even when the number of particles is limited.
Computer aided diagnosis for lung CT using artificial life models

With the present paper we introduce a new computer assisted detection method for lung cancer from CT images. The algorithm is based on different algorithms like: 3D region growing, active contour and shape models, centre of maximal balls but we can say that at the core of our approach are the biological models of ants also known as artificial life models. In the first step of the algorithm the images are undergoing a 3D region growing for identifying the ribcage. Once the ribcage is identified an active contour is used in order to build a confined area for the incoming ants that are deployed to make clean and accurate reconstruction of the bronchial and vascular tree. Next the branches of the newly reconstructed trees are checked to see whether they include nodules or not by using active shape models and to also to see if there are any nodules attached to the pleura of the lungs (centre of maximal balls). The next step is to remove the trees in order to provide a cleaner algorithm for localizing the nodules which is achieved by applying snakes and dot enhancement algorithms.
Automatically Exploring How Uncertainty Impacts Goal Satisfaction

A dynamically adaptive system (DAS) monitors itself and its execution environment to assess requirements satisfaction at run time. Unanticipated environmental conditions may cause sensory inputs that alter the self-assessment capabilities of a DAS in unpredictable and undesirable ways. Moreover, it is impossible for a human to know and/or enumerate all possible combinations of system and environmental conditions that a DAS may encounter. This paper introduces Loki, an evolutionary computation-based approach that automatically discovers environmental conditions that lead to requirements violations and latent behaviors in a DAS. As such, Loki facilitates the identification of goals with inadequate obstacle mitigations or insufficient constraints to prevent unwanted behaviors. We apply Loki to an autonomous vehicle system that performs adaptive cruise control, lane keeping, and collision avoidance. Experimental results show that Loki discovers environmental conditions that obstruct goals and detects a significantly larger number of different and unexpected behaviors than randomized search. Keywords-requirements engineering, evolutionary algorithm, novelty search, environmental uncertainty, self-adaptation
The Great Recession Was Not so Great

The Great Recession is characterized by a GDP-decline that was unprecedented in the past decades. This paper discusses the implications of the Great Recession analyzing labor market data from 20 OECD countries. Comparing the Great Recession with the 1980s recession it is concluded that there is a high cross-country correlation of the unemployment rates over the two recessions indicating that some labor markets are more vulnerable to fluctuations in economic growth than others. Young workers are the most affected by the Great Recession both in terms of unemployment rates as well as employment rates. For prime age workers employment rates were also affected but for older workers the Great Recession did not have a large impact. To analyze how economic growth and labor market institutions have affected unemployment two types of models are estimated. The main conclusion is rather straightforward and has a "one size fits all" character: to reduce unemployment and create jobs economic growth is needed.
Trustworthy Storage and Exchange of Theorems

A large e ort is usually required to have a theorem prover establish a complex theorem. Having invested this e ort, how can we store the result for later use, or communicate it to others while preserving our trust in its validity? This paper discusses the use of digital signatures to store and exchange theorems in a secure way.
Fast Algorithms for Online Stochastic Convex Programming

We introduce the online stochastic Convex Programming (CP) problem, a very general version of stochastic online problems which allows arbitrary concave objectives and convex feasibility constraints. Many well-studied problems like online stochastic packing and covering, online stochastic matching with concave returns, etc. form a special case of online stochastic CP. We present fast algorithms for these problems, which achieve near-optimal regret guarantees for both the i.i. d. and the random permutation models of stochastic inputs. When applied to the special case online packing, our ideas yield a simpler and faster primal-dual algorithm for this well studied problem, which achieves the optimal competitive ratio. Our techniques make explicit the connection of primal-dual paradigm and online learning to online stochastic CP.
Security Visualization Survey

Visualization plays a major role in understanding and interpreting security requirements. Security visualization means different things to different people. Some consider it as viewing the state of the environment and system. The purpose of this paper is to review some of the current methods used in security visualization. Index terms – information security, human intuition, administrator experience, visualization, visual analysis
Stability and Stabilization of Differential Nonlinear Repetitive Processes with Applications

Abstract Repetitive processes are a class of two-dimensional systems that arise in the modeling of physical examples and also the control systems theory developed for them has, in the case of linear dynamics, been applied to design iterative learning control laws with experimental verification. This paper gives new results on the stability of nonlinear differential repetitive processes for applications where a linearized model is either very limited or not applicable. The stability results are then applied to the design of iterative learning control laws in the presence of uncertain parameters and to the same problem when random failures occur that are modeled by a homogeneous Markov chain with a finite set of states. In both cases the computations required are expressed as a finite set of linear matrix inequalities.
Automated acceptance testing tools for web applications using Test-Driven Development

In the last years the software engineering community pays a strong interest in agile development methods. Those methods place software testing for example the Test-Driven Development method as an important task of the development process. Agile projects rely on good test automation tools. In this paper we evaluate five test automation tools for their usage in acceptance testing for web applications using Test-Driven Development. Streszczenie. Rozdzial prezentuje analize porownawczą wybranych narzedzi umozliwiających tworzenie zautomatyzowanych testow akceptacyjnych, czyli Fitnesse, Proven! , jfcUnit oraz Selenium. Badana jest mozliwośc stosowania tych narzedzi do testowania aplikacji internetowych wytwarzanych w procesie opierającym sie o podejście programowania przez testy. Aplikacje internetowe są bardzo specyficzną grupą aplikacji. Do ich uruchomienia potrzeba serwera aplikacji. W związku z tym nie kazda aplikacja nadaje sie do przeprowadzania na nich testow akceptacyjnych. Dodatkowe komplikacje pojawiają sie, jezeli wymagac, aby testy powstaly przed napisaniem kodu źrodlowego, co ma miejsce w przypadku programowaniu przez testy. (Zautomatyzowane testy akceptacyjne dla aplikacji internetowych w programowaniu sterowanym testami)
Multi-scale recurrence quantification analysis of heartbeat interval series in healthy vs. Heart failure subjects

Recurrence plot is a useful analysis method for nonlinear time series, and has been widely used in studies of heart rate variability in recent years. In this paper, recurrence plot and corresponding quantification analysis were utilized to analyze the heart rate variability data from healthy people and congestive heart failure sufferers. It was found that the measures for standard recurrence quantification analysis failed to distinguish between the two groups. Therefore, a multi-scale recurrence quantification analysis method was proposed, which is able to implement the quantitative analysis for recurrence structures of coarse-grained heartbeat interval series on multiple time scales. Experiment results showed that, on certain time scales, the recurrence structures of abnormal heart rate fluctuation from subjects with congestive heart failure could be reflected more clearly by multi-scale RQA parameters.
Time Dissociative Characteristics of Numerical Inductive Reasoning: Behavioral and ERP Evidence

Although some preliminary spatial localization results have been reported, the temporal characteristics of human inductive reasoning process have not been investigated. In the present study, event-related potential (ERP) was used to explore the time course of inductive reasoning process. Based on pilot studies and some other related research, we hypothesized that the process of numerical inductive reasoning is composed of number recognition, strategy formation, hypothesis generation and validation, and the above three stages are (partially) dissociable over time. A typical task of inductive reasoning, function-finding, was adopted. Induction tasks and calculation tasks were performed in the experiments, respectively. The mean reaction time of induction tasks was much longer than that of calculation tasks as expected. Statistical analysis revealed that induction showed no significant separations from calculation for the early ERP components and the slow waveforms after about 600ms, while marked dissociations appeared for the late components in the time window of about 250-600ms. It can be preliminarily concluded that, the early components before about 250ms may reflect the process of attention and number recognition, the late components may relate to strategy formation, and hypothesis generation and validation may be performed in about 600-1200ms. On the whole, the results on the behavioral data and ERP data support our hypothesis.
Traffic Modeling in PLC Networks using a Markov Fluid Model with Autocorrelation Function Fitting

In this paper, we present an analysis of VoIP (Voice over IP) traffic and data transfer using PLC (PowerLine Communications) network. We propose a model based on MMFM (Markov Modulated Fluid Models) for data and VoIP traffic in PLC networks. Simulations and comparisons were carried out to verify the efficiency of the proposed traffic model over the Poisson and MMPP (Markov Modulated Poisson Process) models.
Documenting the Emergence of Grassroots Politics on Facebook: the Florida Case

This study analyzed the message characteristics of U.S. high school and college students’ Facebook political groups to explore how young voters produce and reproduce political content on social network sites. Grounded in communication frame analysis, a quantitative content analysis revealed that the majority of Facebook wall posts focused on politics as a game frame rather than as an issue frame, paralleling findings in traditional news media research. Additional results show that within the interactivity frame, hyperlinks and a call for offline interactions are prevalent, as well as the emotional manifestation frame. When accounted for the election type and partisanship in the context of 2008 presidential and 2010 midterm elections, Democrats dominated the discussion during presidential elections, but Republicans were more active during congressional elections. The results of this research contribute to our understanding of the use of social networking sites for political purposes. Most importantly, it adds to the scarce body of knowledge on the grassroots-style of political discourse.
Separating Maximally Violated Comb Inequalities in Planar Graphs

The Traveling Salesman Problem (TSP) is a benchmark problem in combinatorial optimization. It was one of the very first problems used for developing and testing approaches to solving large integer programs, including cutting plane algorithms and branch-and-cut algorithms [16]. Much of the research in this area has been focused on finding new classes of facets for the TSP polytope, and much less attention has been paid to algorithms for separating from these classes of facets. In this paper, we consider the problem of finding violated comb inequalities. If there are no violated subtour constraints in a fractional solution of the TSP, a comb inequality may not be violated by more than 0.5. Given a fractional solution in the subtour elimination polytope whose graph is planar, we either find a violated comb inequality ordetermine that there are no comb inequalities violated by 0.5. Our algorithm runs in O(n + MC(n)) time, where MC(n) is the time to compute all minimum cuts of a planar graph.
Holography and the inverse source problem. Part II: Inhomogeneous media

The inverse source problem for a monochromeatic source imbedded in a nonabsorbing inhomogeneous medium is investigated within the framework of the reduced scalar wave equation. The Porter-Bojarski integral equation previously formulated for sources imbedded in vacuum is generalized to this case, as are the class of nonradiating and minimum-energy sources considered in Part I [ J. Opt. Soc. Am.72, 327 ( 1982)].