Miracle-dz/UniFAR-FTUs huggingface dataset:
Religiosität und psychische Befindlichkeit - Überprüfung von Instrumenten zur Erfassung von Religiosität

Religiousness and well-being – Evaluation of instruments for the assessment of religious attitudes Within the international literature, religious beliefs are discussed as an effective resource for the enhancement of adjustment to chronic and life-threatening illness. The present study investigates relationships between several dimensions of religiosity and mental health. A sample of 151 healthy people as well as a second sample of 191 cancer patients were recruited. English questionnaires were translated into German. The investigation of psychometric properties of the adapted measurements indicate high internal consistencies. The original scales were replicated by factor analysis. A brief instrument ‘religious affiliation’ and ‘well-being’ was developed. Within both samples, gender differences were found in several dimensions of religiosity. Comparing matched samples of healthy people and cancer patients, no differences in the dimensions of religiosity with the exception of prayer frequency were found. There only exist very few correlations between dimensions of religiosity and quality of life.
A Cross-Layer Multicore Architecture to Tradeoff Program Accuracy and Resilience Overheads

To protect multicores from soft-error perturbations, resiliency schemes have been developed with high coverage but high power/performance overheads (~2x). We observe that not all soft-errors affect program correctness, some soft-errors only affect program accuracy, i.e., the program completes with certain acceptable deviations from soft-error free outcome. Thus, it is practical to improve processor efficiency by trading off resilience overheads with program accuracy. We propose the idea of declarative resilience that selectively applies resilience schemes to both crucial and non-crucial code, while ensuring program correctness. At the application level, crucial and non-crucial code is identified based on its impact on the program outcome. The hardware collaborates with software support to enable efficient resilience with 100 percent soft-error coverage. Only program accuracy is compromised in the worst-case scenario of a soft-error strike during non-crucial code execution. For a set of multithreaded benchmarks, declarative resilience improves completion time by an average of 21 percent over state-of-the-art hardware resilience scheme that protects all executed code. Its performance overhead is ~1.38x over a multicore that does not support resilience.
Optimal STRIPS Planning by Maximum Satisfiability and Accumulative Learning

Planning as satisfiability (SAT-Plan) is one of the best approaches to optimal planning, which has been shown effective on problems in many different domains. However, the potential of the SAT-Plan strategy has not been fully exploited. Following the SAT-Plan paradigm, in this paper we formulate a STRIPS planning problem as a maximum SAT (max-SAT) and develop a general two-phase algorithm for planning. Our method first represents a planning problem as a combinatorial optimization in the form of a SAT compounded with an objective function to be maximized. It then uses a goal-oriented variable selection to force goal-oriented search and a accumulative learnt strategy to avoid to learn a learnt clause multiple times. We integrate our new methods with SATPLAN04. We evaluate and demonstrate the efficacy of our new formulation and algorithm with SATPLAN04 on many well-known real-world benchmark planning problems. Our experimental results show that our algorithm significantly outperforms SATPLAN04 on most of these problems, sometimes with an order of magnitude of improvement in running time.
Attachment-Focused Parenting: Effective Strategies to Care for Children

Attachment security and affect regulation have long been buzzwords in therapy circles, but many of these ideas-so integral to successful therapeutic work with kids and adolescents- have yet to be effectively translated to parenting practice itself. Moreover, as neuroscience reveals how the human brain is designed to work in good relationships, and how such relationships are central to healthy human development, the practical implications for the parent-child attachment relationship become even more apparent. Here, a leading attachment specialist with over 30 years of clinical experience brings the rich and comprehensive field of attachment theory and research from inside the therapy room to the outside, equipping therapists and caregivers with practical parenting skills and techniques rooted in proven therapeutic principles. A guide for all parents and a resource for all mental health clinicians and parent-educators who are searching for ways to effectively love, discipline, and communicate with children, this book presents the techniques and practices that are fundamental to optimal child development and family functioning-how to set limits, provide guidance, and manage the responsibilities and difficulties of daily life, while at the same time communicating safety, fun, joy, and love. Filled with valuable clinical vignettes and sample dialogues, Hughes shows how attachment-focused research can guide all those who care for children in their efforts to better raise them.
Mutation of Plekha7 attenuates salt-sensitive hypertension in the rat

Significance Zinc-finger nuclease (ZFN)-mediated mutagenesis has now enabled researchers to manipulate specific genes to test their function in animal models other than mice. Applying ZFNs to rats, we can now test the role of specific human genome-wide association studies (GWAS)-nominated genes for hypertension in a well-characterized hypertensive rat model, the Dahl salt-sensitive rat. This study provides the first functional evidence that the GWAS-nominated gene Plekha7 plays an essential role in blood pressure regulation and cardiovascular function by modulating vascular function. Our results indicate that Plekha7 plays a role in the regulation of intracellular calcium, nitric oxide bioavailability, and the response of the vasculature to increased flow. PLEKHA7 (pleckstrin homology domain containing family A member 7) has been found in multiple studies as a candidate gene for human hypertension, yet functional data supporting this association are lacking. We investigated the contribution of this gene to the pathogenesis of salt-sensitive hypertension by mutating Plekha7 in the Dahl salt-sensitive (SS/JrHsdMcwi) rat using zinc-finger nuclease technology. After four weeks on an 8% NaCl diet, homozygous mutant rats had lower mean arterial (149 ± 9 mmHg vs. 178 ± 7 mmHg; P < 0.05) and systolic (180 ± 7 mmHg vs. 213 ± 8 mmHg; P < 0.05) blood pressure compared with WT littermates. Albumin and protein excretion rates were also significantly lower in mutant rats, demonstrating a renoprotective effect of the mutation. Total peripheral resistance and perivascular fibrosis in the heart and kidney were significantly reduced in Plekha7 mutant animals, suggesting a potential role of the vasculature in the attenuation of hypertension. Indeed, both flow-mediated dilation and endothelium-dependent vasodilation in response to acetylcholine were improved in isolated mesenteric resistance arteries of Plekha7 mutant rats compared with WT. These vascular improvements were correlated with changes in intracellular calcium handling, resulting in increased nitric oxide bioavailability in mutant vessels. Collectively, these data provide the first functional evidence that Plekha7 may contribute to blood pressure regulation and cardiovascular function through its effects on the vasculature.
Force Myography for Monitoring Grasping in Individuals with Stroke with Mild to Moderate Upper-Extremity Impairments: A Preliminary Investigation in a Controlled Environment

There is increasing research interest in technologies that can detect grasping, to encourage functional use of the hand as part of daily living, and thus promote upper-extremity motor recovery in individuals with stroke. Force myography (FMG) has been shown to be effective for providing biofeedback to improve fine motor function in structured rehabilitation settings, involving isolated repetitions of a single grasp type, elicited at a predictable time, without upper-extremity movements. The use of FMG, with machine learning techniques, to detect and distinguish between grasping and no grasping, continues to be an active area of research, in healthy individuals. The feasibility of classifying FMG for grasp detection in populations with upper-extremity impairments, in the presence of upper-extremity movements, as would be expected in daily living, has yet to be established. We explore the feasibility of FMG for this application by establishing and comparing (1) FMG-based grasp detection accuracy and (2) the amount of training data necessary for accurate grasp classification, in individuals with stroke and healthy individuals. FMG data were collected using a flexible forearm band, embedded with six force-sensitive resistors (FSRs). Eight participants with stroke, with mild to moderate upper-extremity impairments, and eight healthy participants performed 20 repetitions of three tasks that involved reaching, grasping, and moving an object in different planes of movement. A validation sensor was placed on the object to label data as corresponding to a grasp or no grasp. Grasp detection performance was evaluated using linear and non-linear classifiers. The effect of training set size on classification accuracy was also determined. FMG-based grasp detection demonstrated high accuracy of 92.2% (σ = 3.5%) for participants with stroke and 96.0% (σ = 1.6%) for healthy volunteers using a support vector machine (SVM). The use of a training set that was 50% the size of the testing set resulted in 91.7% (σ = 3.9%) accuracy for participants with stroke and 95.6% (σ = 1.6%) for healthy participants. These promising results indicate that FMG may be feasible for monitoring grasping, in the presence of upper-extremity movements, in individuals with stroke with mild to moderate upper-extremity impairments.
Incremental call graph reanalysis for AspectJ software

Program call graph representation can be used to support many tasks in compiler optimization, program comprehension, and software maintenance. During software evolution, the call graph needs to remain fairly precise and be updated quickly in response to software changes. In this paper, we present an approach to incremental update, instead of exhaustive analysis of the initially constructed call graph in AspectJ software. Our approach first decomposes the source code edits between the updated and initial software versions into a set of atomic change representations, which capture the semantic differences. Then, we explore the relationship between atomic changes and call graph to incrementally update the initially constructed graph, instead of rebuilding it from the ground up. We implement the reanalysis approach on top of the ajc AspectJ compiler and perform an empirical study on 24 versions of eight AspectJ benchmarks. The experiment result shows that our approach can reduce a large portion of unnecessary reanalysis cost as program changes occur, and significant savings are observed for the incremental reconstruction of AspectJ call graph in comparison with an exhaustive analysis, with no loss in precision.
Joint Blind Source Separation for Multimodality Data Fusion through Subject Co-variations

The abstract should appear at the top of the left-hand column of text, about 0.5 inch (12 mm) below the title area and no mor than 3.125 i ches (80 mm) in length. Leave a 0.5 inch (12 mm) space between the end of the abstract and the beginning of the main text. The abstract should contain about 100 to 150 words, and should be identical to the abstract text submitted electronically along with the paper cover sheet. All manuscripts must be in English, printed in black ink.
Decentralised coordination of low-power embedded devices using the max-sum algorithm

This paper considers the problem of performing decentralised co-ordination of low-power embedded devices (as is required within many environmental sensing and surveillance applications). Specifically, we address the generic problem of maximising social welfare within a group of interacting agents. We propose a novel representation of the problem, as a cyclic bipartite factor graph, composed of variable and function nodes (representing the agents' states and utilities respectively). We show that such representation allows us to use an extension of the max-sum algorithm to generate approximate solutions to this global optimisation problem through local decentralised message passing. We empirically evaluate this approach on a canonical coordination problem (graph colouring), and benchmark it against state of the art approximate and complete algorithms (DSA and DPOP). We show that our approach is robust to lossy communication, that it generates solutions closer to those of DPOP than DSA is able to, and that it does so with a communication cost (in terms of total messages size) that scales very well with the number of agents in the system (compared to the exponential increase of DPOP). Finally, we describe a hardware implementation of our algorithm operating on low-power Chipcon CC2431 System-on-Chip sensor nodes.
LexSemTm: A Semantic Dataset Based on All-words Unsupervised Sense Distribution Learning

There has recently been a lot of interest in unsupervised methods for learning sense distributions, particularly in applications where sense distinctions are needed. This paper analyses a state-of-the-art method for sense distribution learning, and op-timises it for application to the entire vocabulary of a given language. The optimised method is then used to produce L EX S EM TM: a sense frequency and semantic dataset of unprecedented size, spanning approximately 88% of polyse-mous, English simplex lemmas, which is released as a public resource to the community. Finally, the quality of this data is investigated, and the L EX S EM TM sense distributions are shown to be superior to those based on the W ORD N ET ﬁrst sense for lemmas missing from S EM C OR , and at least on par with S EM C OR -based distributions otherwise.
Assessing Local Risk of Rifampicin-Resistant Tuberculosis in KwaZulu-Natal, South Africa Using Lot Quality Assurance Sampling

Background KwaZulu-Natal (KZN) has the highest burden of notified multidrug-resistant tuberculosis (MDR TB) and extensively drug-resistant (XDR) TB cases in South Africa. A better understanding of spatial heterogeneity in the risk of drug-resistance may help to prioritize local responses. Methods Between July 2012 and June 2013, we conducted a two-way Lot Quality Assurance Sampling (LQAS) study to classify the burden of rifampicin (RIF)-resistant TB among incident TB cases notified within the catchment areas of seven laboratories in two northern and one southern district of KZN. Decision rules for classification of areas as having either a high- or low-risk of RIF resistant TB (based on proportion of RIF resistance among all TB cases) were based on consultation with local policy makers. Results We classified five areas as high-risk and two as low-risk. High-risk areas were identified in both Southern and Northern districts, with the greatest proportion of RIF resistance observed in the northernmost area, the Manguzi community situated on the Mozambique border. Conclusion Our study revealed heterogeneity in the risk of RIF resistant disease among incident TB cases in KZN. This study demonstrates the potential for LQAS to detect geographic heterogeneity in areas where access to drug susceptibility testing is limited.
Experimental Ventilator-induced Lung Injury: Exacerbation by Positive End-Expiratory Pressure

Background:Previous experimental studies of ventilator-induced lung injury have shown that positive end-expiratory pressure (PEEP) is protective. The authors hypothesized that the application of PEEP during volume-controlled ventilation with a moderately high tidal volume (VT) in previously healthy in vivo rats does not attenuate ventilator-induced lung injury if the peak airway pressure markedly increases during the application of PEEP. Methods:Sixty healthy, male Sprague-Dawley rats were anesthetized and randomized to be mechanically ventilated for 4 h at (1) VT of 6 ml/kg, (2) VT of 20 ml/kg, or (3) VT of 20 ml/kg plus 10 cm H2O of PEEP. Peak airway pressures, gas exchange, histologic evaluation, mortality, total lung tissue cytokine gene expression, and serum cytokine concentrations were analyzed. Results:Peak airway pressures exceeded 30 cm H2O with high VT plus PEEP. All lungs ventilated with high VT had perivascular edema and inflammatory infiltrates. In addition, those ventilated with PEEP had small hemorrhages foci. Five animals from the high VT plus PEEP group died (P = 0.020). Animals ventilated with high VT (with or without PEEP) had a substantial increase in serum interleukin-6 (P = 0.0002), and those ventilated with high VT plus PEEP had a 5.5-fold increase in systemic levels of tumor necrosis factor-alpha (P = 0.007). Conclusions:In contrast to previous reports, PEEP exacerbated lung damage and contributed to fatal outcome in an in vivo, mild overdistension model of ventilator-induced lung injury in previously healthy rats. That is, the addition of high PEEP to a constant large VT causes injury in previously healthy animals.
Phase I and Pharmacokinetic Study of Prinomastat, a Matrix Metalloprotease Inhibitor

Purpose: Prinomastat is a matrix metalloprotease (MMP) inhibitor with selectivity for MMPs 2, 3, 9, 13, and 14. Inhibition of these MMPs has been postulated to block tumor invasion and metastasis. This Phase I, dose-escalation study was designed to evaluate the acute and chronic toxicities of various doses of prinomastat and to determine prinomastat pharmacokinetics. Experimental Design: Seventy-five patients with advanced cancer were given 1, 2, 5, 10, 25, 50, or 100 mg prinomastat orally twice daily until tumor progression or development of significant toxicities. Prinomastat pharmacokinetics were measured on day 29 of therapy. Results: The primary toxicities identified were joint and muscle-related pain, which were generally reversible with treatment rest and/or dose reduction. No dose-limiting toxicities were noted within the first 4 weeks of treatment, but grade 2–3 arthralgias and myalgias were noted 2–3 months after initiation of therapy in >25% of patients at doses >25 mg twice a day. The frequency and severity of symptoms were dose related. Plasma prinomastat concentrations greater than the Ki for MMPs 2 and 9 were achieved at all of the dose levels. Conclusions: Doses of 5–10 mg bid were recommended for additional trials, because this dose range was well tolerated for a treatment duration of at least 3 months and achieves trough plasma concentrations 10–100-fold greater than the Ki (in vitro inhibition constant) for the targeted MMPs (2 and 9).
Blind sensor calibration using approximate message passing

The ubiquity of approximately sparse data has led a variety of communities to take great interest in compressed sensing algorithms. Although these are very successful and well understood for linear measurements with additive noise, applying them to real data can be problematic if imperfect sensing devices introduce deviations from this ideal signal acquisition process, caused by sensor decalibration or failure. We propose a message passing algorithm called calibration approximate message passing (Cal-AMP) that can treat a variety of such sensor-induced imperfections. In addition to deriving the general form of the algorithm, we numerically investigate two particular settings. In the first, a fraction of the sensors is faulty, giving readings unrelated to the signal. In the second, sensors are decalibrated and each one introduces a different multiplicative gain to the measurements. Cal-AMP shares the scalability of approximate message passing, allowing us to treat large sized instances of these problems, and experimentally exhibits a phase transition between domains of success and failure.
Understanding and Supporting Lightweight Communication in Hospital Work

Informal communication is an essential resource in hospital work; it is used as a means to collaborate and coordinate the way in which work is performed, as well as to locate and gather the artifacts and human resources required for patient care. The need of physical proximity to establish and hold informal communications has motivated the development of tools that support remote informal interaction. However, this kind of technology has not been widely adopted in hospitals, where workers experience intense mobility. In this paper, we present the results of an observational study in a hospital aimed at understanding how local mobility changes the rules in the provision of support for informal communication, and how technology could improve this form of communication. We found that local mobility fosters opportunities for colocated communication; however, it faces some inconveniences related to the affordances of the physical environment. We address these issues through the design of SOLAR, a collaborative application that supports colocated interactions in hospital work through the implementation and integration of five services that form a ubicomp infrastructure. Additionally, we present a discussion about the perception of users related to the usefulness of this tool.
Bioengineering the Lung : Molecules , Materials , Matrix , Morphology , and Mechanics Autophagy plays an essential role in cigarette smoke-induced expression of MUC 5 AC in airway epithelium

Zhou JS, Zhao Y, Zhou HB, Wang Y, Wu YF, Li ZY, Xuan NX, Zhang C, Hua W, Ying SM, Li W, Shen HH, Chen ZH. Autophagy plays an essential role in cigarette smoke-induced expression of MUC5AC in airway epithelium. Am J Physiol Lung Cell Mol Physiol 310: L1042–L1052, 2016. First published April 1, 2016; doi:10.1152/ajplung.00418. 2015. —Mucus hypersecretion is a common pathological feature of chronic airway inflammatory diseases including chronic obstructive pulmonary disease (COPD). However, the molecular basis for this condition remains incompletely understood. We have previously demonstrated a critical role of autophagy in COPD pathogenesis through mediating apoptosis of lung epithelial cells. In this study, we aimed to investigate the function of autophagy as well as its upstream and downstream signals in cigarette smokeinduced mucus production in human bronchial epithelial (HBE) cells and in mouse airways. Cigarette smoke extract (CSE), as well as the classical autophagy inducers starvation or Torin-1, significantly triggered MUC5AC expression, and inhibition of autophagy markedly attenuated CSE-induced mucus production. The CSE-induced autophagy was mediated by mitochondrial reactive oxygen species (mitoROS), which regulated mucin expression through the JNK and activator protein-1 pathway. Epidermal growth factor receptor (EGFR) was also required for CSE-induced MUC5AC in HBE cells, but it exerted inconsiderable effects on the autophagy-JNK signaling cascade. Airways of mice with dysfunctional autophagy-related genes displayed a markedly reduced number of goblet cells and attenuated levels of Muc5ac in response to cigarette smoke exposure. These results altogether suggest that mitoROS-dependent autophagy is essential for cigarette smoke-induced mucus hyperproduction in airway epithelial cells, and reemphasize autophagy inhibition as a novel therapeutic strategy for chronic airway diseases.