Miracle-dz/UniFAR-FTUs huggingface dataset:
Economic Returns to Investment in AIDS Treatment in Low and Middle Income Countries

Since the early 2000s, aid organizations and developing country governments have invested heavily in AIDS treatment. By 2010, more than five million people began receiving antiretroviral therapy (ART) – yet each year, 2.7 million people are becoming newly infected and another two million are dying without ever having received treatment. As the need for treatment grows without commensurate increase in the amount of available resources, it is critical to assess the health and economic gains being realized from increasingly large investments in ART. This study estimates total program costs and compares them with selected economic benefits of ART, for the current cohort of patients whose treatment is cofinanced by the Global Fund to Fight AIDS, Tuberculosis and Malaria. At end 2011, 3.5 million patients in low and middle income countries will be receiving ART through treatment programs cofinanced by the Global Fund. Using 2009 ART prices and program costs, we estimate that the discounted resource needs required for maintaining this cohort are $14.2 billion for the period 2011–2020. This investment is expected to save 18.5 million life-years and return $12 to $34 billion through increased labor productivity, averted orphan care, and deferred medical treatment for opportunistic infections and end-of-life care. Under alternative assumptions regarding the labor productivity effects of HIV infection, AIDS disease, and ART, the monetary benefits range from 81 percent to 287 percent of program costs over the same period. These results suggest that, in addition to the large health gains generated, the economic benefits of treatment will substantially offset, and likely exceed, program costs within 10 years of investment.
Kelvin probe study of laterally inhomogeneous dielectric charging and charge diffusion in RF MEMS capacitive switches

In this paper we use scanning Kelvin probe microscopy (SKPM) to detect charge in the dielectric of RF MEMS capacitive switches. We observe a laterally inhomogeneous distribution. Laterally inhomogeneous dielectric charging leads to a narrowing of the C-V curve [1], and can lead to stiction of the membrane. The measurements show that trapped charges slowly diffuse, which reduces the inhomogeneity and shows that charge is vertically confined. From these measurements we estimate the lateral diffusion coefficient of trapped charges.
An iterative optimization clustering algorithm based on manifold distance

In this study, a novel iterative optimization clustering algorithm is proposed by using a manifold distance based dissimilarity metric which can measure the geodesic distance along the manifold and a criterion function which can express the clustering target, that is the samples in the same cluster being somehow more similar than samples in different one. The steps of the algorithm are discussed in detail. Simulation results on six artificial datasets with different manifold structures show that comparing to k means clustering algorithm, the new algorithm has the ability to identify complex non-convex clusters.
Distorsiones cognitivas: una revisión sobre sus implicaciones en la conducta agresiva y antisocial

espanolEste trabajo presenta una revision sobre las implicaciones de las distorsiones cognitivas en la conducta agresiva y antisocial en jovenes y adolescentes. Por una parte, son muchos los estudios que han puesto de relieve la importancia de la relacion especifica existente entre la agresion juvenil y las denominadas distorsiones cognitivas auto-sirvientes, por lo que este tipo de distorsiones se han propuesto como uno de los factores cognitivos que mas estarian implicados en el riesgo y el mantenimiento de las conductas agresivas y antisociales. No obstante, las denominadas distorsiones cognitivas auto-humillantes, mucho mas relacionadas con problemas internalizantes como la ansiedad y la depresion, tambien parecen estar relacionadas con el comportamiento antisocial. EnglishThis study reviews the implications of cognitive distortions in aggressive and antisocial behaviour in young people and adolescents. Many studies have highlighted the importance of the specific relationship between juvenile aggression and the so-called self-serving cognitive distortions, so that such distortions have been proposed as one of the cognitive factors more strongly involved in the risk and maintenance of aggressive and antisocial behaviour. However, the so-called self-debasing cognitive distortions, much more related to internalizing problems such as anxiety and depression, also appear to be associated with antisocial behaviour.
The Impact of Personal Income Taxation on Executive Compensation

This paper analyzes the effect of personal income taxation on the sensitivity of executive compensation to company performance and the use of stock option and restricted stock grants underlying this sensitivity. The theoretical model predicts that, if a single tax rate applies to the entire compensation package, an increase in the tax rate weakly diminishes the equilibrium level of managerial effort and the after-tax pay-to-performance sensitivity, with the effect on the pre-tax pay-to-performance sensitivity being ambiguous. When salary and option gains are taxed at a higher rate than stock gains, tax changes also induce shifting among the individual compensation instruments. Interestingly, this differential taxation leads to a positive amount of stocks in the compensation contract even in the absence of any desire to incentivize the manager. In addition, an increase in the tax rate applied to salary and option gains may increase the level of managerial effort in equilibrium. On the other hand, an increase in the tax rate applied to stock gains weakly decreases the equilibrium level of managerial effort and strictly decreases the amount of after-tax pay-to-performance sensitivity generated by stock grants. The second part of the paper exploits the variation in the U.S. federal personal income tax rate generated by the Omnibus Budget Reconciliation Act of 1993, as well as variation in the combined federal and state income tax rates during the period 1992-1996 to empirically evaluate the impact of personal income taxation on the pay-to-stock-price sensitivity generated by stock-option and restricted stock grants. The results show that an increase in the ordinary income tax rate decreases the pay-to-stock-price sensitivity generated by option grants when time series variation in the marginal tax rate is utilized in the identification, with the estimates retaining the same sign but being statistically insignificant when only the variation in the marginal tax rate originating from cross-sectional variation in the federal income tax rate and/or state tax rate changes is used in the estimation. On the other hand, stock grant sensitivity is found to be unresponsive to changes in the ordinary income tax rate.
Betting on Exports: Trade and Endogenous Heterogeneity

We study the equilibrium determinants of firm-level heterogeneity in a model in which firms can affect the variance of their productivity draws at the entry stage and explore the implications in closed and open economy. By allowing firms to choose the size of their investment in innovation projects of unknown quality, the model yields a Pareto distribution for productivity with a shape parameter that depends on industry-level characteristics. A novel result is that export opportunities, by increasing the payoffs in the tail, induce firms to invest in bigger projects with more spread-out outcomes. Moreover, when more productive firms also pay higher wages, trade amplifies wage dispersion by making all firms more unequal. These results are consistent with new evidence on how firm-level heterogeneity and wage dispersion vary in a panel of U.S. industries. Finally, we use patent data across U.S. states and over time to provide evidence in support of a specific mechanism of the model, namely, that export opportunities increase firm heterogeneity by fostering innovation.
Physical properties, hygroscopicity and estimated pulmonary retention of various therapeutic aerosols.

The importance of this work centers around four considerations. The above-mentioned alterations in the assay of Stubbs and Kamovsky may lead to the elucidation of principles not possible with less efficient and less accurate methods. A second consideration is the maintenance of resting CPM sufficiently above background levels in order to reflect actual phagocytizing/resting ratios. This may not be possible with less efficient assays. A third consideration is that the improved assay method facilitates calculation of stoichiometric relationships such as quantitative oxygen uptake. Finally, increased efficiency and accuracy should make possible comparison of data produced by different investigators.
Understanding SRAM Stability via Bifurcation Analysis

In the past decades, aggressive scaling of transistor feature size has been a primary force driving higher Static Random Access Memory (SRAM) integration density. Due to technology scaling, nanometer SRAM designs become increasingly vulnerable to stability challenges. The traditional way of analyzing stability is through the use of Static Noise Margins (SNMs). SNMs are not capable of capturing the key nonlinear dynamics associated with memory operations, leading to imprecise characterization of stability. This work rigorously develops dynamic stability concepts and, more importantly, captures them in physically based analytical models. By leveraging nonlinear stability theory, we develop analytical models that characterize the minimum required amplitude and duration of injected current noises that can flip the SRAM state. These models, which are parameterized in key design, technology, and operating condition parameters, provide important design insights and offer a basis for predicting scaling trends of SRAM dynamic stability.
Non-HDL cholesterol is a good predictor of the risk of increased arterial stiffness in postmenopausal women in an urban Brazilian population

OBJECTIVES: Increased arterial stiffness is an important determinant of the risk of cardiovascular disease. Lipid profile impairment, especially hypercholesterolemia, is associated with stiffer blood vessels. Thus, the aim of this study was to determine which of the five circulating lipid components (high-density lipoprotein cholesterol (HDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), low-density lipoprotein cholesterol (LDL), total cholesterol (TC) and triglycerides) is the best predictor of increased arterial stiffness in an urban Brazilian population. METHODS: A random sample of 1,662 individuals from the general population of Vitoria, Brazil (25-64 years), was selected, and lipid components were measured using standard methods. Pulse wave velocity was measured using a non-invasive automatic device, and increased arterial stiffness was defined as a pulse wave velocity ≥10 m/s. RESULTS: In men, only total cholesterol (OR=1.59; CI=1.02 to 2.48, p=0.04) was associated with the risk of increased arterial stiffness. In women, HDL-C (OR=1.99; CI=1.18 to 3.35, p=0.01) and non-HDL-C (OR=1.61; CI=1.01 to 2.56, p=0.04) were good predictors of the risk of increased arterial stiffness. However, these associations were only found in postmenopausal women (OR=2.06; CI=1.00 to 4.26, p=0.05 for HDL-C and OR=1.83; CI=1.01 to 3.33, p=0.04 for non-HDL-C). CONCLUSION: Our findings indicate that both HDL-C and non-HDL-C are good predictors of the risk of increased arterial stiffness in postmenopausal women in an urban Brazilian population and may be useful tools for assessing the risk of arterial stiffness.
Subgraph Enumeration in Massive Graphs

We consider the problem of enumerating all instances of a given pattern graph in a large data graph. Our focus is on determining the input/output (I/O) complexity of this problem. Let $E$ be the number of edges in the data graph, $k=O(1)$ be the number of vertices in the pattern graph, $B$ be the block length, and $M$ be the main memory size. The main results of the paper are two algorithms that enumerate all instances of the pattern graph. The first one is a deterministic algorithm that exploits a suitable independent set of the pattern graph of size $1\leq s \leq k/2$ and requires $O\left(E^{k-s}/\left(BM^{k-s-1}\right)\right)$ I/Os. The second algorithm is a randomized algorithm that enumerates all instances in $O\left(E^{k/2}/\left(BM^{k/2-1}\right)\right)$ expected I/Os; the same bound also applies with high probability under some assumptions. A lower bound shows that the deterministic algorithm is optimal for some pattern graphs with $s=k/2$ (e.g., paths and cycles of even length, meshes of even side), while the randomized algorithm is optimal for a wide class of pattern graphs, called Alon class (e.g., cliques, cycles and every graph with a perfect matching).
The Symbiotic Division of Labour between Heterogeneous Districts. the Development of Ornamental Horticulture in the Netherlands and Italy

This article focuses upon the historical development of three ornamental horticulture districts located in the Netherlands and in Italy. The aim of our investigation is to underline the features of a global division of labour, which is driven by the specialisation of production and retailing. Despite the lack of natural resources and unfavourable climate, the high labour and energy costs, the Dutch district and the horticulture cluster based in Netherlands hold a leading position. The historical development of the three districts is very similar, but the application of science and the role of local institutions are the explanatory factor of the evolutionary path of the cluster located in the Netherlands. The Italian districts analysed, which enjoy better endowed resources are now strongly dependent by the entire Dutch cluster. JEL – classification: Q1; O18; F0; R0.
An overview of hybrid databases

Due to increase of unstructured data most of the companies now shifting towards NoSQL, but still most of the data is perfectly relational. Till date the modeling of various software functionality can only be efficiently done using relational databases. Storing different parts of data in SQL and NoSQL is very cumbersome and requires lot of manual work to manage multiple data sources. Hence, a theoretical framework is discussed to bridge this gap between two technology through an abstraction layer.
Cartels As Rational Business Strategy: New Data Demonstrates That Crime Pays

Cartels have always been the highest concern of antitrust. They overcharge consumers many billions of dollars every year and there is a strong consensus that they should be sanctioned heavily. Yet, until now no one has ever seriously attempted to analyze whether cartel sanctions are at the optimal level. This article is the first to undertake this formidable task. Rather surprisingly, it demonstrates that the combined level of United States cartel sanctions has been only 7% to 17% as large as it should be to protect potential victims of cartelization optimally. To remedy this the average level of United States anti-cartel sanctions should be approximately quintupled.
Metodología para la implementación de IoT

El presente documento contiene un metodo para identificar necesidades y oportunidades para la implementacion de Internet de las cosas (IoT) aplicable a oficinas de trabajo donde permanezcan entre 30 y 70 personas, teniendo en cuenta que actualmente a nivel mundial no existen reglas normas o recomendaciones que regulen que tipos de tecnologias, seguridad, infraestructura, servicios a ofrecer se deben tener en cuenta al realizar implementaciones IoT.
Image dehazing using dark channel prior and the corrected transmission map

Single image dehazing based on dark channel prior may encounter color distortion in bright region (such as sky region). Three methods are proposed to overcome the limitations of original algorithm. A transmission threshold firstly was determined. Then, by using the threshold to correct the transmission map in different ways and make it adaptive to fog, three algorithms can effectively deal with the sky, white object and so on. In order to reduce the complexity of calculation, fast guider filter was applied to refining the transmission map. Experimental results showed that these methods are feasible to eliminate color distortion of out-door image, and visibility can be also enhanced.
Living Spaces, Communal Places: Early Modern Jewish Homes and Religious Devotions

In* the seventeenth century, Juspe Schammes, the sexton of the Worms synagogue, composed a book documenting the various customs of his community, including the details of the synagogue service. On the days when the Torah was read aloud in the synagogue, a set number of men from the community were individually called up by name. Once called up, the man would recite a blessing over the Torah, and remain present next to the Torah scroll at the centre of the synagogue as a section was read aloud. The custom book includes a section listing the occasions on which specific male members of the community were honoured with being called up to the Torah. Communal officials, for example, were honoured with being called to the Torah on particular dates, while other community members celebrating life-cycle events such as marriage or the anniversary of a close relative’s death were called to the Torah on the relevant dates. Included in this list of honourees was a man who moved into a new house.1 This same practice was also observed in Frankfurt am Main, as is reported in the eighteenth-century custom book Minhag ka-tzon Yosef. The author records that: ‘According to the custom in the holy community of Frankfurt, anyone who moves to a different house is obligated [to be called to the Torah] on the first Sabbath [after the move]’. 2 This honour may have had roots in the Bible, which exempted a man who had moved into a new home and had not yet dedicated it from serving as a soldier in wartime.3 Nevertheless, the early modern practice demonstrates that moving into a new home was actively considered a momentous event marked by a sacred ritual. This ritual was a public performance that acknowledged a change in domestic life in the space of the larger community. It underscores that rather than constituting two discrete categories, domestic and communal places overlapped, with religious devotion playing a role in both. Being called to the Torah
Synchronous Automata for Reactive, Real-Time or Embedded Systems

This paper presents Synchronous Automata, a new representation for compiling, verifying and implementing reactive systems. The synchronous programming paradigm is a novel approach for designing reactive, real-time and embedded systems. This new paradigm embraces languages of dramatically di erent styles, imperative languages like Esterel or Argos as well as declarative ones like Lustre or Signal. In response to industrial needs for mixing styles when designing complex applications, we develop a design environment, the Synchronie workbench, which supports multi-style programming within the synchronous paradigm. This multi-style programming facility is semantically based on Synchronous Automata. This paper presents the basics of Synchronous Automata and provides them with a set of operators to ease and improve both veri cation and implementation tools supported by the Synchronie workbench.
Removal of Muscular and Artefacts Noise from the ECG by a Neural Network

The following work presents a system of cancellation muscular and artefacts noise in biomedical signals with a multilayer structure of neural networks. In this study in particular the signal has been analyzed from electrocardiogram (ECG). This system consists in a simple structure similar to the neuronal network MADALINE (Multiple ADAptive LINear Element), which is used like a structure. The proposed system is a growed artificial neuronal network which allows to optimize, the number of nodes of the hidden layer and the matrixes of coefficients. The coefficients matrix are optimized using the algorithm of simultaneous perturbation which requires a smaller computer complexity than the required one by the backpropagation algorithm. The comparison between the different typical methods (filter FIR, biorthogonal wavelet 6,8, filtered adaptive LMS) and the system based on neural multilayer networks proposed, is obtained calculating the cross correlation between the input signal to the system and the exit, in addition for the calculation of the SIR (relation parameter signal interference). The comparison shows that the neural networks method is able to better preserve the signal waveform at system output with an improved noise reduction in comparison with traditional techniques. With this method it is possible to eliminate white, artefacts and muscular noise. The rest of filter systems give worse results.
Analysis of Vector Space Model in Information Retrieval

Information retrieval is great technology behind web search services. In information retrieval, it is common to model index terms and documents as vectors in a suitably defined vector space. The vector space model is one of the classical and widely applied retrieval models to evaluate relevance of web page. The retrieval operation consists of computing the cosine similarity function between a given query vector and the set of documents vector and then ranking documents accordingly. In this paper, we present different approaches of vector space model to compute similarity score of hits from search engine and more importantly, it is felt that this investigation will lead to a clearer understanding of the issues and problems in using the vector space model in information retrieval and our work intends to discuss the main aspects of Vector space models and provide a comprehensive comparison for TermCount model, Tf-Idf model and Vector space model based on normalization.
Investigating the Process of Process Modeling with Cheetah Experimental Platform

When assessing the usability of BPM technologies enter- prises have to rely on vendor promises or qualitative data rather than on empirical or experimental research. To address this need Cheetah Ex- perimental Platform (CEP) has been developed fostering experimental research on business process modeling. CEP provides components that are frequently used in controlled experiments and allows their assem- bly to experimental workows. CEP supports experimental execution by mitigating risks endangering data validity through better user guid- ance. Additionally, CEP provides richer evaluation techniques compared to paper based experiments fostering the experiment's data analysis.
Cyclophilin A Protects Cardiomyocytes against Hypoxia/Reoxygenation-Induced Apoptosis via the AKT/Nox2 Pathway

Hypoxia/reoxygenation (H/R) accelerates the process of cardiomyocyte apoptosis during ischemia-reperfusion. Excessive reactive oxygen species (ROS) are a critical driver of oxidative stress injury. Cyclophilin A (CyPA) is a major ROS-induced factor in atherosclerosis. There is a positive feedback mechanism between CyPA and ROS, which enables the oxidative stress response to continue and expand. However, it is unclear whether this positive feedback mechanism exists in cardiomyocytes. Through western blotting and flow cytometric assays and TUNEL assay, we found that CyPA inhibited the apoptosis of H9c2 cardiomyocytes under H/R conditions. By dihydroethidium (DHE) staining and electron spin resonance (ESR) assays, we demonstrated that CyPA reduced ROS production and suppressed O2− production dependent on reduced nicotinamide adenine dinucleotide phosphate (NADPH) oxidase. By western blotting, we showed that CyPA inhibited the expression of NADPH oxidase 2 (Nox2) protein by the AKT pathway. Through confocal microscopy assay, we found that CyPA reduced the expression of Nox2 membrane-bound subunits. The current study shows that a positive feedback mechanism does not exist in H9c2 cardiomyoblasts. CyPA protects H9c2 cardiomyoblasts against H/R-induced apoptosis via the AKT/Nox2 pathway. This could be a potential target for ischemia-reperfusion injury therapy.