Miracle-dz/UniFAR-FTUs huggingface dataset:
Pseudo-stable models for logic programs

For a general logic program, a set of n+ 1 logic values is considered and an unde ned value denoted u. Partial multi-valued interpretations are also de ned. A general logic program P may contain the constants that are de ned for every logic value. A pseudo-negation denoted eh is de ned for every integer h, where 0 h < n. A partial ordering denoted h is de ned between multi-valued interpretations. Using an operator de ned for a program P , a multi-valued pseudo-stable semantics for the program P is introduced. The pseudo-stable models which satisfy certain properties are minimal elements of the set of all models for the program P having those properties. The class of pseudo-stable models for a program P contains strictly the class of 3-valued stable models for P .
Microbial Community Composition Impacts Pathogen Iron Availability during Polymicrobial Infection

Iron is an essential nutrient for bacterial pathogenesis, but in the host, iron is tightly sequestered, limiting its availability for bacterial growth. Although this is an important arm of host immunity, most studies examine how bacteria respond to iron restriction in laboratory rather than host settings, where the microbiome can potentially alter pathogen strategies for acquiring iron. One of the most important transcriptional regulators controlling bacterial iron homeostasis is Fur. Here we used a combination of RNA-seq and chromatin immunoprecipitation (ChIP)-seq to characterize the iron-restricted and Fur regulons of the biofilm-forming opportunistic pathogen Aggregatibacter actinomycetemcomitans. We discovered that iron restriction and Fur regulate 4% and 3.5% of the genome, respectively. While most genes in these regulons were related to iron uptake and metabolism, we found that Fur also directly regulates the biofilm-dispersing enzyme Dispersin B, allowing A. actinomycetemcomitans to escape from iron-scarce environments. We then leveraged these datasets to assess the availability of iron to A. actinomycetemcomitans in its primary infection sites, abscesses and the oral cavity. We found that A. actinomycetemcomitans is not restricted for iron in a murine abscess mono-infection, but becomes restricted for iron upon co-infection with the oral commensal Streptococcus gordonii. Furthermore, in the transition from health to disease in human gum infection, A. actinomycetemcomitans also becomes restricted for iron. These results suggest that host iron availability is heterogeneous and dependent on the infecting bacterial community.
Core Community Detection Algorithm based on Edge Removal Learning

In this work, we contribute to solve the community detection problem by proposing an algorithm for the detection of disjoint communities' cores considering unweighted and undirected social graphs. The proposed algorithm is based on the removal of non-essential edges and induced isolated nodes from networks (graphs). To this purpose; we have built a model for predicting edges removal using Weighted Support Vector Machines (WSVM) trained on real-life social network datasets. The training phase was carried out by means of an appropriate proposed heuristic to label edges, and discriminating features extracted from both edges end-point nodes and network structure characteristics. Our designed algorithm shows promising results for communities' cores detection.
Integrating chronic care with primary care activities: enriching healthcare staff knowledge and skills and improving glycemic control of a cohort of people with diabetes through the First Line Diabetes Care Project in the Philippines

Background This study investigated the effects of integrating primary chronic care with current healthcare activities in two local government health units (LGHU) of the Philippines on knowledge and skills of the LGHU staff and clinical outcomes for people with diabetes. Design Integration was accomplished through health service reorganization, (re)distribution of chronic care tasks, and training of LGHU staff. Levels of the staff's pre- and post-training diabetes knowledge and of their self-assessment of diabetes care-related skills were measured. Primary diabetes care with emphasis on self-care development was provided to a cohort of people with diabetes. Glycosylated hemoglobin (HbA1c) and obesity measures were collected prior to and one year after full project implementation. Results The training workshop improved diabetes knowledge (p<0.001) and self-assessed skills (p<0.001) of the LGHU staff. Significant reductions in HbA1c (p<0.001), waist–hip ratio (p<0.001) and waist circumference (p=0.011) of the cohort were noted. Although the reduction in HbA1c was somewhat greater among those whose community-based care providers showed improvement in knowledge and self-assessed skills, the difference was not statistically significant. Conclusions Primary care for chronic conditions such as diabetes may be integrated with other healthcare activities in health services of low-to-middle-income countries such as the Philippines, utilizing pre-existing human resources for health, and may improve clinical endpoints.
A supersymmetric type IIB Randall–Sundrum realization

We show that an earlier domain wall solution of type IIB supergravity provides a supersymmetric realization of the Randall–Sundrum brane-world, and give its ten-dimensional interpretation in terms of IIB 3-branes. We also explain how previous no-go theorems are circumvented. In particular, whereas D=5 supergravity scalars have AdS5 energy E0⩽4 and are unable to support a D=5 positive tension brane, our scalar has E0=8, and is the breathing mode of the S5 compactification. Another essential element of the construction is the implementation of a Z2 symmetry by patching together compactifications with opposite signs for their 5-form field strengths. This is thus a IIB analog of a previous D=5 3-brane realization of the Hořava–Witten orbifold. A mode-locking phenomenon avoids the appearance of negative energy zero-modes in spite of the necessity of a D=10 negative tension brane-source.
Automated image analysis with the potential for process quality control applications in stem cell maintenance and differentiation

The translation of laboratory processes into scaled production systems suitable for manufacture is a significant challenge for cell based therapies; in particular there is a lack of analytical methods that are informative and efficient for process control. Here the potential of image analysis as one part of the solution to this issue is explored, using pluripotent stem cell colonies as a valuable and challenging exemplar. The Cell‐IQ live cell imaging platform was used to build image libraries of morphological culture attributes such as colony “edge,” “core periphery” or “core” cells. Conventional biomarkers, such as Oct3/4, Nanog, and Sox‐2, were shown to correspond to specific morphologies using immunostaining and flow cytometry techniques. Quantitative monitoring of these morphological attributes in‐process using the reference image libraries showed rapid sensitivity to changes induced by different media exchange regimes or the addition of mesoderm lineage inducing cytokine BMP4. The imaging sample size to precision relationship was defined for each morphological attribute to show that this sensitivity could be achieved with a relatively low imaging sample. Further, the morphological state of single colonies could be correlated to individual colony outcomes; smaller colonies were identified as optimum for homogenous early mesoderm differentiation, while larger colonies maintained a morphologically pluripotent core. Finally, we show the potential of the same image libraries to assess cell number in culture with accuracy comparable to sacrificial digestion and counting. The data supports a potentially powerful role for quantitative image analysis in the setting of in‐process specifications, and also for screening the effects of process actions during development, which is highly complementary to current analysis in optimization and manufacture. © 2015 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers, 32:215–223, 2016
Mining Individual Mobile User Behavior on Location and Interests

With the ubiquitous Internet applications brought by widespread popularity of smart device, an exhaustive understanding of user behavior is becoming essential for Internet Service Providers (ISPs) to implement network management and resource optimization. Existing researches on mobile user behavior principally focus on studying people's application interests and mobility properties, especially characterizing relationship between the two perspectives. In this paper, distinct from prior work, we propose a new idea to model and predict mobile user behavior after extracting the behavior with strong correlation between browsing interests and location. Initially, improved Apriori algorithm is applied to find the association rule and estimate the strength of correlation between user's location and application. On that basis, behavior pattern with close correlation between two features is extracted. Subsequently, we use HMM (Hidden Markov Model) to model aforementioned behavior and predict applications used in given location. The effectiveness and accuracy of our method are verified by real data traffic collected from mobile Internet covering 4.51 million people in a large metropolitan area of China over a week.
Rethinking the Paternalist Paradigm in Japanese IndustriM Management

Observers on both sides of the Pacific have long identified paternalism as a distinguishing characteristic of industrial management inJapan. Paternalistic practices the provision of welfare facilities by employers, the articulation of familial corporate ideologies, the use of personnel policies which emphasize job security and foster worker loyalty have been seen as the hallmarks of a distinctively Japanese approach to managing industrial labor. Both mainstream scholarship and journalistic accounts have almost invariably assumed that this paterealistic proclivity was a natural outgrowth of Japan's cultural heritage, reflecting a unique accommodation f traditional values to the impersonal dictates of modern industry. Moreover, it has generally been supposed that paternalism formed the core of Japanese management practice both before and after World War II, and that alternate paradigms of labor management floundered in Japan because of the culturally-conditioned appeal of the paterealistic model. According to Hazama Hiroshi, the most influential analyst of Japanese paternalism, Japan's prewar industrialists made "creative" use of tradition "groupism, feelings of dependency, and a high regard for harmony" in the creation of a singularly Japanese corporate welfare system. With such deep indigenous roots, Hazama concludes, paternalism has reigned supreme in Japan's industrial workshops while other approaches notably Frederick Taylor's Scientific Management have proven unable to penetrate Japanese industry [Hazama, 1979, p. 104; Hazama, 1969; Hazama, 1978]. Although Western scholarship has generally endorsed these views, in recent years some historians have begun to question the received wisdom about paternalism in prewar Japan. Andrew Gordon, for example, has suggested that paterealistic rhetoric was ineffective in swaying worker sentiment and that corporate welfarism was only one device in Japanese industry's arsenal of labor management strategies [Gordon, 1985; Gordon, 1989]. Sheldon Garon and William Dean Kinzley have similarly questioned the monolithic nature of Japanese paternalism and noted the extent to which Japanese managers were influenced by foreign models [Garon, 1987; Kinzley, 1991]. A number of historians have
DeepLearningKit - an GPU Optimized Deep Learning Framework for Apple's iOS, OS X and tvOS developed in Metal and Swift

In this paper we present DeepLearningKit - an open source framework that supports using pretrained deep learning models (convolutional neural networks) for iOS, OS X and tvOS. DeepLearningKit is developed in Metal in order to utilize the GPU efficiently and Swift for integration with applications, e.g. iOS-based mobile apps on iPhone/iPad, tvOS-based apps for the big screen, or OS X desktop applications. The goal is to support using deep learning models trained with popular frameworks such as Caffe, Torch, TensorFlow, Theano, Pylearn, Deeplearning4J and Mocha. Given the massive GPU resources and time required to train Deep Learning models we suggest an App Store like model to distribute and download pretrained and reusable Deep Learning models.
Regret Theory and Salience Theory: Total Strangers, Distant Relatives or Close Cousins?

Two non-expected-utility-theory approaches to model decision making under risk are regret theory (Loomes and Sugden, 1982; Bell, 1982) and salience theory (Bordalo, Gennaioli, and Shleifer, 2012). While the psychological underpinning of these two approaches is different, the models share the assumption that within-state comparisons of outcomes across choice options are a key determinant of choice behavior. We investigate the overlap between the two theories and show that salience theory is a special case of regret theory. Moreover, we trace out the relationship be- tween diminishing sensitivity of the salience function and concavity of the choiceless utility function with regard to behavioral implications.
Signal dependent noise removal from a single image

State-of-the-art image denoising algorithms usually assume additive white Gaussian noise (AWGN), although they have achieved outstanding performance, modeling and removing real signal dependent noise from a single image still remains a challenging problem. In this paper we propose a segmentation-based image denoising algorithm for signal dependent noise. Incorporating a noise identification algorithm, we integrate these two modules into a full blind, end-to-end denoising algorithm for signal dependent noise. First, we identify the noise level function for a given single noisy image. Then, after initial denoising, segmentation is applied to the pre-filtered image. Assuming the noise level of each segment is constant, we apply AWGN denoising algorithm to each segment. We obtain a final de-noised image by composing the denoised segments. Various experimental results on synthetic and real noisy images show that our algorithm outperforms state-of-the-art denoising algorithms in removing real signal dependent noise.
Pathologischer Internet- und Medienkonsum –psychodynamische Erkundungen

Aufgrund der weitgehenden Legalisierung, der ständigen Verfügbarkeit, der Ano-nymität und des geringen Preises sind über den PC, das Smartphone und andere elektronische Medien vermittelte Verhaltenssüchte ein Thema der Gegenwart und der Zukunft im Bereich der Prävention, Diagnostik und Intervention. Sie stellen einerseits eine neue Herausforderung dar und entwickeln sich andererseits entlang bekannter Entwicklungs- und Konfliktthemen von Kindern und Jugendlichen, die sich in den neuen Medien und den neuen Verhaltenssüchten zeigen. Der tiefenpsychologischen Be-trachtungsweise dieser Phänomene kommt grundlegende Bedeutung zu, da Kinder und Jugendliche stets durch Spielen und Interagieren ihre Beziehungsmuster, Konflikte und strukturellen Themen ausagiert und in die Persönlichkeit integriert haben. Diejenigen, die aufgrund von Risikofaktoren und Komorbidität diese moderne Entwicklungsaufgabe nicht allein meistern können, bedürfen eines interdisziplinären Zugangs auf dem Boden einer biografischen Herleitung und eines psychodynamischen Verständnisses. Kindern, und Umgang den sog. neuen elektronischen interaktiven Medien Phänomen letzten zehn Jahre. frühen Phase Intranets, praktischen
The role of social expenditures in budget consolidations - an analysis of the fiscal and macroeconomic effects

This paper reviews and summarizes the literature that has concentrated on budget consolidations and their fiscal and economic effects. The issue of fiscal adjustments has again gained importance due to the recent economic crisis and the resulting fiscal imbalances. The existing literature shows that there may be some factors that influence the fiscal and economic impact depending on the methods used and the underlying assumptions. Referring to the fiscal impact of consolidations, this paper concludes that the composition of the adjustment is the most influential factor in reducing public deficits and debt. This result is in line with other recent literature surveys. Other factors mentioned in the underlying studies include the specialization in certain expenditure areas like public administration and social security, the size of the adjustment, the initial state of public finances and the economy before consolidation, fiscal rules, political and monetary institutions. In contrast to the fiscal effects, the results of the studies concentrating on economic effects vary substantially. Since the early 90's there has been a lively debate about the possibility of non-Keynesian effects after consolidations. Despite the fact that there is no consensus about possible expansive effects of consolidations, this paper concludes that a substantial share of the previous work finds that large negative effects do not necessarily have to prevail. Whether these reversed effects are strong enough to turn restrictive effects into expansive ones depends on different factors, which are similar to those mentioned before in the fiscal effects context. (author's abstract)
On the Design and Evaluation of Producer Mobility Management Schemes in Named Data Networks

Information-centric Networks (ICNs) offer a promising paradigm for the future Internet to cope with an ever increasing growth in data and shifts in access models. Different architectures of ICNs, including Named Data Networks (NDNs) are designed around content distribution, where data is the core entity in the network instead of hosts. One of the main challenges in NDNs is handling mobile content providers and maintaining seamless operation. Accordingly, attempts at handling mobility in NDNs have been proposed in the literature are mostly studied under simplistic and/or special cases. There is a lack of benchmarking tools to analyze and compare such schemes. This paper introduces a comprehensive assessment framework for mobility management schemes in NDNs, under varying topologies, heterogeneous producers and consumers, and different mobility models. We develop a generic and modular simulation environment in ns-3 that is made available for NDN researchers to evaluate their mobility management proposals. We implement and compare the performance of three mainstream Producer mobility management schemes, namely, the Mobility Anchor, Location Resolution and Hybrid approaches in NDNs. We demonstrate how mobility impacts NDN operation, specifically in terms of latency and delivery ratio. We also argue for the superior operation of the hybrid approach to handling mobility in NDNs, yet highlight its high control overhead.
New parallel optimal‐parameter fast multipole method (OPFMM)

The three key translation equations of the fast multipole method (FMM) are deduced from the general polypolar expansions given earlier. Simplifications are introduced for the rotation‐based FMM that lead to a very compact FMM formalism. The optimum‐parameter searching procedure, a stable and efficient way of obtaining the optimum set of FMM parameters, is established with complete control over the tolerable error (ε). This new procedure optimizes the linear scaling with respect to the number of particles for a given ε. In addition, a new parallel FMM algorithm, which requires virtually no internode communication, is suggested that is suitable for the parallel construction of Fock matrices in electronic structure calculations. © 2001 John Wiley & Sons, Inc. J Comput Chem 22: 1484–1501, 2001
General brane cosmologies and their global spacetime structure

Starting from a completely general standpoint, we find the most general brane-universe solutions for a 3-brane in a five-dimensional spacetime. The brane can border regions of spacetime with or without a cosmological constant. Making no assumptions other than the usual cosmological symmetries of the metric, we prove that the equations of motion form an integrable system, and find the exact solution. The cosmology is indeed a boundary of a (class II) Schwarzschild-AdS spacetime, or a Minkowski (class I) spacetime. We analyse the various cosmological trajectories focusing particularly on those bordering vacuum spacetimes. We find, not surprisingly, that not all cosmologies are compatible with an asymptotically flat spacetime branch. We comment on the role of the radion in this picture.
Localization and separation of concurrent talkers based on principles of auditory scene analysis and multi-dimensional statistical methods

This work focuses on 'statistical cocktail party processing': localization, tracking, and enhancement of voices in concurrent speech or in high levels of nonstationary noise. Key strategies are to link binaural and spectro-temporal information, to combine cues across frequency and time by a probabilistic approach, and to treat speech as a multidimensional stochastic signal, using a priori knowledge about it. To implement these, Bayesian estimation, sequential Monte Carlo methods, and statistical evaluation of speech databases are used. Three on-line algorithms are developed and tested, which run partly in real-time. They allow for a robust, efficient and exact sound localization even at low signal-to-noise ratios (SNRs), and successful tracking and separation of voices with convergence times between 50 and 200 ms. The multidimensional statistical approach allows to analyze acoustical scenes at low SNR, showing that the described strategies might help to interpret auditory processing.
Thiostrepton interacts covalently with Rpt subunits of the 19S proteasome and proteasome substrates

Here, we report a novel mechanism of proteasome inhibition mediated by Thiostrepton (Thsp), which interacts covalently with Rpt subunits of the 19S proteasome and proteasome substrates. We identified Thsp in a cell‐based high‐throughput screen using a fluorescent reporter sensitive to degradation by the ubiquitin–proteasome pathway. Thiostrepton behaves as a proteasome inhibitor in several paradigms, including cell‐based reporters, detection of global ubiquitination status, and proteasome‐mediated labile protein degradation. In vitro, Thsp does not block the chymotrypsin activity of the 26S proteasome. In a cell‐based IκBα degradation assay, Thsp is a slow inhibitor and 4 hrs of treatment achieves the same effects as MG‐132 at 30 min. We show that Thsp forms covalent adducts with proteins in human cells and demonstrate their nature by mass spectrometry. Furthermore, the ability of Thsp to interact covalently with the cysteine residues is essential for its proteasome inhibitory function. We further show that a Thsp modified peptide cannot be degraded by proteasomes in vitro. Importantly, we demonstrate that Thsp binds covalently to Rpt subunits of the 19S regulatory particle and forms bridges with a proteasome substrate. Taken together, our results uncover an important role of Thsp in 19S proteasome inhibition.
Combining LSI with other Classifiers to Improve Accuracy of Single-label Text Categorization

This paper describes the combination of k-NN and SVM with LSI to improve their performance in single-label text categorization tasks, and the experiments performed with six datasets to show that both k-NN-LSI (the combination of k-NN with LSI) and SVM-LSI (the combination of SVM with LSI) outperform the original methods for a significant fraction of the datasets. Overall, both combinations present an average Accuracy over the six datasets used in this work that is higher than the average Accuracy of each original method. Having in mind that SVM is usually considered the best performing classification method, it is particularly interesting that the combinations perform even better for some datasets.