Miracle-dz/UniFAR-FTUs huggingface dataset:
Maintaining Distributed Recursive Views Incrementally

Distributed logic programming languages, that allow both facts and programs to be distributed among different nodes in a network, have been recently proposed and used to declaratively program a wide-range of distributed systems, such as network protocols and multi-agent systems. However, the distributed nature of the underlying systems poses serious challenges to developing efficient and correct algorithms for evaluating these programs. This paper proposes an efficient asynchronous algorithm to compute incrementally the changes to the states in response to insertions and deletions of base facts. Our algorithm is formally proven to be correct in the presence of message reordering in the system. To our knowledge, this is the first formal proof of correctness for such an algorithm. Comments University of Pennsylvania Department of Computer and Information Science Technical Report No. MSCIS-11-06. This technical report is available at ScholarlyCommons: http://repository.upenn. edu/cis_reports/950 Maintaining Distributed Recursive Views Incrementally Vivek Nigam UPENN, USA vnigam@math.upenn. edu Limin Jia CMU, USA liminjia@cmu.edu Boon Thau Loo UPENN, USA boonloo@cis.upenn. edu Andre Scedrov UPENN, USA scedrov@math.upenn. edu
Multi-subject fMRI data analysis: Shift-invariant tensor factorization vs. group independent component analysis

Tensor decomposition of fMRI data has gradually drawn attention since it can explore the multi-way data's structure which exists inherently in brain imaging. For multi-subject fMRI data analysis, time shifts occur inevitably among different participants, therefore, shift-invariant tensor decomposition should be used. This method allows for arbitrary shifts along one modality, and can yield satisfactory results for analyzing multi-set fMRI data with time shifts of different datasets. In this study, we presented the first application of shift-invariant tensor decomposition to simulated multi-subject fMRI data with shifts of time courses and variations of spatial maps. By this method, time shifts, spatial maps, time courses, and subjects' amplitudes were better estimated in contrast to group independent component analysis. Therefore, shift-invariant tensor decomposition is promising for real multi-set fMRI data analysis.
Prevalence and Risk Factors for Trachoma in Central and Southern Malawi

Background Trachoma, one of the neglected tropical diseases is suspected to be endemic in Malawi. Objectives: To determine the prevalence of trachoma and associated risk factors in central and southern Malawi. Methodology/Principal Findings A population based survey conducted in randomly selected clusters in Chikwawa district (population 438,895), southern Malawi and Mchinji district (population 456,558), central Malawi. Children aged 1–9 years and adults aged 15 and above were assessed for clinical signs of trachoma. In total, 1010 households in Chikwawa and 1016 households in Mchinji districts were enumerated within 108 clusters (54 clusters in each district). A total of 6,792 persons were examined for ocular signs of trachoma. The prevalence of trachomatous inflammation, follicular (TF) among children aged 1–9 years was 13.6% (CI 11.6–15.6) in Chikwawa and 21.7% (CI 19.5–23.9) in Mchinji districts respectively. The prevalence of trachoma trichiasis (TT) in women and men aged 15 years and above was 0.6% (CI 0.2–0.9) in Chikwawa and 0.3% (CI 0.04–0.6) in Mchinji respectively. The presence of a dirty face was significantly associated with trachoma follicular (TF) in both Chikwawa and Mchinji districts (P<0.001). Conclusion/Significance Prevalence rates of trachoma follicles (TF) in Central and Southern Malawi exceeds the WHO guidelines for the intervention with mass antibiotic distribution (TF>10%), and warrants the trachoma SAFE control strategy to be undertaken in Chikwawa and Mchinji districts.
A few ants are enough: ACO with iteration-best update

Ant colony optimization (ACO) has found many applications in different problem domains. We carry out a first rigorous runtime analysis of ACO with iteration-best update, where the best solution in the each iteration is reinforced. This is similar to comma selection in evolutionary algorithms. We compare ACO to evolutionary algorithms for which it is well known that an offspring size of Ω(log n), n the problem dimension, is necessary to optimize even simple functions like ONEMAX. In sharp contrast, ACO is efficient on ONEMAX even for the smallest possible number of two ants. Remarkably, this only holds if the pheromone evaporation rate is small enough; the collective memory of many ants stored in the pheromones makes up for the small number of ants. We further prove an exponential lower bound for ACO with iteration-best update that depends on a trade-off between the number of ants and the evaporation rate.
Conditional Knockout of Myocyte Focal Adhesion Kinase Abrogates Ischemic Preconditioning in Adult Murine Hearts

Background Our laboratory has previously demonstrated the importance of a cytoskeletal‐based survival signaling pathway using in vitro models of ischemia/reperfusion (IR). However, the importance of this pathway in mediating stress‐elicited survival signaling in vivo is unknown. Methods and Results The essential cytoskeletal signaling pathway member focal adhesion kinase (FAK) was selectively deleted in adult cardiac myocytes using a tamoxifen‐inducible Cre‐Lox system (α‐MHC‐MerCreMer). Polymerase chain reaction (PCR) and Western blot were performed to confirm FAK knockout (KO). All mice were subjected to a 40‐minute coronary occlusion followed by 24 hours of reperfusion. Ischemic preconditioning (IP) was performed using a standard protocol. Control groups included wild‐type (WT) and tamoxifen‐treated α‐MHC‐MerCreMer+/−/FAKWT/WT (experimental control) mice. Infarct size was expressed as a percentage of the risk region. In WT mice IP significantly enhanced the expression of activated/phosphorylated FAK by 36.3% compared to WT mice subjected to a sham experimental protocol (P≤0.05; n=6 hearts [sham], n=4 hearts [IP]). IP significantly reduced infarct size in both WT and experimental control mice (43.7% versus 19.8%; P≤0.001; 44.7% versus 17.5%; P≤0.001, respectively). No difference in infarct size was observed between preconditioned FAK KO and nonpreconditioned controls (37.1% versus 43.7% versus 44.7%; FAK KO versus WT versus experimental control; P=NS). IP elicited a 67.2%/88.8% increase in activated phosphatidylinositol‐3‐kinase (PI3K) p85/activated Akt expression in WT mice, but failed to enhance the expression of either in preconditioned FAK KO mice. Conclusions Our results indicate that FAK is an essential mediator of IP‐elicited cardioprotection and provide further support for the hypothesis that cytoskeletal‐based signaling is an important component of stress‐elicited survival signaling.
Efficient big link allocation scheme in virtualized software-defined networking

We propose an efficient resource allocation scheme for big links in virtualized software-defined networking. Network virtualization based on software-defined networking provides big link concept to facilitate simple network management — big link maps a set of switches and links into a single virtual link. However, this paper reports an issue of the big link in that there is a severe performance degradation in virtualized SDN environments. We find the cause: the existing network hypervisors do not consider the network traffic when allocating physical resources to a big link. To address this issue, we present big link allocation scheme (BAS) that considers network traffic when allocating and reallocating resources to a big link. A prototype implementation is done with OpenVirteX, and experiments demonstrate that the big link with BAS achieves four times greater throughput than that of the big link without BAS. Moreover, by including a timer in OpenVirteX, the BAS decreases unnecessary resource reallocations, which reduces overhead.
Psychological wellness and health-related stigma: a pilot study of an acceptance-focused cognitive behavioural intervention for people with lung cancer

People with lung cancer experience health-related stigma that is related to poorer psychosocial and quality of life outcomes. The present Phase 1 study applied mixed methods to test the acceptability of an acceptance-focused cognitive behavioural intervention targeting stigma for this patient group. Fourteen lung cancer patients completed a 6-week Psychological Wellness intervention with pre- and post-test outcome measures of psychological and cancer-specific distress, depression, health-related stigma and quality of life. In-depth interviews applying interpretative phenomenological analysis assessed participants' experiences of the intervention. Moderate to large improvements were observed in psychological (ηp2 = 0.182) and cancer-specific distress (ηp2 = 0.056); depression (ηp2 = 0.621); health-related stigma (ηp2 = 0.139). In contrast, quality of life declined (ηp2 = 0.023). The therapeutic relationship; self-management of distress; and relationship support were highly valued aspects of the intervention. Barriers to intervention included avoidance and practical issues. The lung cancer patients who completed the Psychological Wellness intervention reported improvements in psychological outcomes and decreases in stigma in the face of declining quality of life with patients reporting personal benefit from their own perspectives. A randomised controlled trial is warranted to establish the effectiveness of this approach.
Reinforcement Learning with Particle Swarm Optimization Policy (PSO-P) in Continuous State and Action Spaces

This article introduces a model-based reinforcement learning RL approach for continuous state and action spaces. While most RL methods try to find closed-form policies, the approach taken here employs numerical on-line optimization of control action sequences. First, a general method for reformulating RL problems as optimization tasks is provided. Subsequently, Particle Swarm Optimization PSO is applied to search for optimal solutions. This Particle Swarm Optimization Policy PSO-P is effective for high dimensional state spaces and does not require a priori assumptions about adequate policy representations. Furthermore, by translating RL problems into optimization tasks, the rich collection of real-world inspired RL benchmarks is made available for benchmarking numerical optimization techniques. The effectiveness of PSO-P is demonstrated on the two standard benchmarks: mountain car and cart pole.
Practical method for blind inversion of Wiener systems

In this paper, firstly we show that the problem of blind inversion of Wiener systems is a special case of blind separation of post-nonlinear instantaneous mixtures approximately, and derive the learning rule for the former problem using this relationship. Secondly, we review the Gaussianization method for blind inversion of Wiener systems. Based on the fact that the convolutive mixture is close to Gaussian, this method roughly approximates the convolutive mixture by a Gaussian variable and constructs the inverse nonlinearity easily. Thirdly, in order to improve the performance, the Cornish-Fisher expansion is exploited to model the latent convolutive mixture, and then the extended Gaussianization method is developed. We show that the performance of our method is insensitive to the nonlinearity in the Wiener system. Experimental results are presented to illustrate the validity and efficiency of our method.
multiple representation of perceptual features for texture classification

Texture Classification plays a vital role in medical image, remote sensing image, pattern analysis for the past three decades. Eventhough it is three decades problem, still having a lot of scope in pattern analysis. Textural features corresponding to visual properties of texture are highly desirable for two reasons; they will be optimum in terms of feature selection and will be applicable to all kinds of textures. Some of the perceptual features are coarseness, contrast,
Author Manuscript, Published in "international Conference on Human Factors in Computing Systems Touchstone: Exploratory Design of Experiments

Touchstone, an open-source experiment design platform, is designed to help establish a solid research foundation for HCI, especially in the area of novel interaction techniques, by providing a repository and a set of tools to design, run and analyze controlled experiments. Touchstone includes a design platform for exploring alternative designs of controlled laboratory experiments, a run platform for running subjects and a limited analysis platform for advice and access to on-line statistics packages. Designed for HCI researchers and their students, the goal is to facilitate the process of replicating and extending experiments in the research literature as well as creating new ones. We tested Touchstone by designing two controlled experiments. One replicates and extends a previous study of multiscale pointing interaction techniques: OrthoZoom was fastest, followed by bi-manual Pan & Zoom; SDAZ and traditional Pan & Zoom were significantly slower. The other illustrates how to create a new experiment.
Periocular Capillary Hemangiomas: Indications and Options for Treatment

Capillary hemangiomas are the most common periocular and orbital tumors of childhood that typically arise in infancy. Though the diagnosis is frequently made on clinical examination, various diagnostic modalities may be helpful in initial evaluation and follow-up. Tests may be necessary in diagnosing suspect cases or aid in the differentiation of potential malignant tumors. In the vast majority of cases these tumors undergo spontaneous involution without sequelae. However, some periocular and orbital capillary hemangiomas require intervention to prevent serious complications. Other tumors require treatment to lessen the surgical burden for cosmetic repair. When treatment is necessary, there are a number of therapeutic options available. As there is no standard, potential risks and benefits must be discussed with the family and treatment should be specific in each case. A complete understanding of the natural history of the tumor, indications for treatment, and response to different therapies is imperative in managing this common lesion.
Using Behavioral Indicators to Help Detect Potential Violent Acts: A Review of the Science Base

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Multilabel Classification with Principal Label Space Transformation

We consider a hypercube view to perceive the label space of multilabel classification problems geometrically. The view allows us not only to unify many existing multilabel classification approaches but also design a novel algorithm, principal label space transformation (PLST), that captures key correlations between labels before learning. The simple and efficient PLST relies on only singular value decomposition as the key step. We derive the theoretical guarantee of PLST and evaluate its empirical performance using real-world data sets. Experimental results demonstrate that PLST is faster than the traditional binary relevance approach and is superior to the modern compressive sensing approach in terms of both accuracy and efficiency.
A wearable sensing framework for improving personal and oral hygiene for people with developmental disabilities

People with developmental disabilities often face difficulties in coping with daily activities and many require constant support. One of the major health issues for people with developmental disabilities is personal hygiene. Many lack the ability, poor memory or lack of attention to carry out normal daily activities like brushing teeth and washing hands. Poor personal hygiene may result in increased susceptibility to infection and other health issues. To enable independent living and improve the quality of care for people with developmental abilities, this paper proposes a new wearable sensing framework to monitoring personal hygiene. Based on a smartwatch, this framework is designed as a pervasive monitoring and learning tool to provide detailed evaluation and feedback to the user on hand washing and tooth brushing. A preliminary study was conducted to assess the performance of the approach, and the results showed the reliability and robustness of the framework in quantifying and assessing hand washing and tooth brushing activities.
A Bayesian Approach to Speaker Recognition Based on GMMs Using Multiple Model Structures

This paper proposes a speaker recognition technique using multiple model structures based on the Bayesian approach. In recent speaker recognition, many sophisticated statistical models have been proposed, e.g., Joint Factor Analysis and i-Vector based method. However, since most of them are based on Gaussian Mixture Models (GMMs), therefore improving estimation accuracy of generative models, i.e. GMMs, with limited amount of training data is still an important problem in speaker recognition. For this purpose, a Bayesian approach which marginalizes all possible model parameters has been applied to the GMM based speaker recognition. This paper extends it to the model structure marginalization. The proposed method can improve the estimation accuracy by integrating multiple GMMs with different numbers of mixtures within the Bayesian framework. Experimental results show that the proposed method improved the identiﬁcation rates from the conventional method using a single model structure.
New polymeric composites based on poly(-caprolactone) and layered double hydroxides containing antimicrobial species.

Benzoate (Bz), 2,4-dichlorobenzoate (BzDC), and p- and o-hydroxybenzoate (p- and o-BzOH) anions with antimicrobial activity have been intercalated into [Zn(0.65)Al(0.35)(OH)(2)](NO(3))(0.35). 0.6H(2)O, layered double hydroxide (LDH), via anion-exchange reactions. The composition of the obtained intercalation compounds, determined by chemical, thermogravimetric, and ion chromatographic analyses, indicates that benzoate and benzoate derivative anions replace the nitrate counteranions, almost completely. Information on the interactions of the intercalated anions with the inorganic layer have been obtained from Fourier transform IR absorption spectroscopy and powder X-ray diffraction of the samples. It has been found that both the nature and the position of the aromatic ring substituents affect the value of the basal distance and the host-guest hydrogen bond network. Knowledge of the chemical composition, basal distance, and van der Waals dimensions of the guests has finally allowed the proposal of structural models of the intercalation compounds that have been used as fillers of poly(caprolactone), a biodegradable polymer. Films of polymeric composites were obtained by hot-pressing the powders of polymer and filler previously milled by a high-energy ball milling procedure. X-ray diffraction analysis and optical and scanning electron microscopy of the composites indicate that the LDH samples containing BzDC anions are delaminated into the polymeric matrix, whereas those containing p-BzOH anions maintain for the most part the crystal packing and give rise to microcomposites. Intermediate behavior was found for LDH modified with Bz and o-BzOH anions because exfoliated and partly intercalated composites were obtained. Preliminary antimicrobial tests indicate that the composites are able to inhibit the Saccharomyces cerevisiae growth of 40% in comparison with the growth in a pure culture medium. The composites can be studied as the model for "active packaging" systems because of the antimicrobial properties of the anions anchored to the LDH layer.
An Efficient Gene Selection Technique based on Fuzzy C-means and Neighborhood Rough Set

Selecting genes from microarray gene expression datasets has become an important research, because such data typically consist of a large number of genes and a small number of samples. Avoiding information loss, neighborhood mutual information is used to evaluate the relevance between genes in this work. Firstly, an improved Relief feature selection algorithm is proposed to create candidate feature subsets. Then, the cohesion degree of the neighborhood of an object and coupling degree between neighborhoods of objects are defined based on neighborhood mutual information. Furthe rmore, a new initialization method of cluster centers for the Fuzzy C-means (FCM) algorithm is proposed. FCM is a method that allows one piece of data to belong to two or more clusters. Moreover, in view of neighborhood rough set is an effective tool to extract and select features, a novel algorithm for gene selection based on FCM algorithm and neighborhood rough set is proposed. Finally, to evaluate the performance of the proposed approach, we apply it to five well-known gene expression datasets. Experimental results show that the proposed approach can select genes effectively, and can obtain high and stable classification performance.
Metallographic preparation of the conventional and new TBC layers

Purpose: Verification of up-to-now used metallographic preparation of the TBC coating thermal barriers and adaptation of them to layers of new types, based on new ceramic compounds, sprayed on conventional high temperature creep resisting alloys by the APS method, is a purpose of this paper. New types of used ceramic powders are so called pyrochlores of a general formula RE2Zr2O7. Design/methodology/approach: A scope of investigations comprised realization of a process of preparation of metallographic micro-sections, beginning from a cutting moment, through mounting, grinding and polishing. A standard method of preparation of micro-sections, typical for conventional layers was used and microstructural observation, from a point of view of presence of artefacts of mechanical origin was carried out. Findings: The carried out analysis allowed to compare methods of preparation of micro-sections and principles of preparation, used to assess the conventional TBC layers and relation them to barrier layers of new types. The carried out investigations showed that up-to-now used methods and procedures for the TBC layers, got by usage of conventional powders, are sufficient for layers of new types. Research limitations/implications: The carried out investigations suggest a necessity to verify the got results in a case of the TBC layers, sprayed by use of powders of pyrochlore structure of another type. Practical implications: The got results show a possibility to use up-to-now metallographic procedures for the TBC layers of new types. Originality/value: Information, concerning basic principles of microstructural assessment of layers of new types, sprayed by the APS method on high temperature creep resisting alloys, is an original value.