Miracle-dz/UniFAR-FTUs huggingface dataset:
Vulnerability as a key to authenticity.

PURPOSE Vulnerability is explored as a human trait that gives nurses an opportunity to engage in authentic nursing. Vulnerability in both nurse and patient is necessary for the practice of nursing with caring as its basic premise. ORGANIZING FRAMEWORK Philosophic discourse. SCOPE Vulnerability is explored in terms of its traditional connotation and existential meaning. CONCLUSIONS To be authentic, nurses must be aware of their own vulnerability, recognize themselves in others, and be willing to enter into mutual vulnerability. If nurses deny the opportunity to be vulnerable, they deny the opportunity to participate in humanness and are more likely to dehumanize others.
[A family with exercise-induced paroxysmal dystonia and childhood absence epilepsy].

INTRODUCTION The boundary between epilepsy and paroxysmal dyskinesia appears to be less easy to delineate than previously believed. Reports of families showing both phenomena suggest a shared pathophysiology. PATIENTS AND METHOD A new family with autosomal dominant exercise-induced paroxysmal dystonia is reported. RESULTS Two family members also had childhood absence epilepsy, and one of them suffered from acute transient hemiplegia at age 10. CONCLUSION The association of epilepsy and paroxysmal dyskinesia has been rarely reported in the literature, and several loci have been identified. Absence epilepsy and exercise-induced paroxysmal dystonia appear to be very uncommon, although some reports mentioned the association in sporadic and familial cases. The involvement of ion channel genes in several transient neurological disorders supports the hypothesis of a common pathophysiological process underlying both the childhood absence seizure and the later paroxysmal dystonia.
Low complexity post-ordered iterative decoding for generalized layered space-time coding systems

In this paper we refer to the combination of BLAST and space-time coding (STC) for multi-input multi-output systems as generalized layered space-time coding (GLST). A post-ordered decoding algorithm is introduced based on the generalization of the original BLAST ordering detection algorithm. The performance is analyzed through comparison to that of pre-ordered decoding with and without power allocation. Interleavered GLST with a new iterative process is also proposed. It can efficiently exploit full receive antenna diversity and thus significantly improve the system overall performance. Due to hard interference cancellation (IC) and ML decoder in the iterations, the new iterative decoding is much less complex than conventional turbo processing where soft IC and MAP decoder were applied.
A Multimodal Way of Experiencing and Exploring Music

Abstract Significant digitization efforts have resulted in large multimodal music collections, which comprise music-related documents of various types and formats including text, symbolic data, audio, image, and video. The challenge is to organize, understand, and search musical content in a robust, efficient, and intelligent manner. Key issues concern the development of methods for analysing, correlating, and annotating the available multimodal material, thus identifying and establishing semantic relationships across various music representations and formats. Here, one important task is referred to as music synchronization, which aims at identifying and linking semantically corresponding events present in different versions of the same underlying musical work. In this paper, we give an introduction to music synchronization and show how synchronization techniques can be integrated into novel user interfaces that allow music lovers and researchers to access and explore music in all its different facets thus enhancing human involvement with music and deepening music understanding.
Low-level vision by consensus in a spatial hierarchy of regions

We introduce a multi-scale framework for low-level vision, where the goal is estimating physical scene values from image data-such as depth from stereo image pairs. The framework uses a dense, overlapping set of image regions at multiple scales and a “local model,” such as a slanted-plane model for stereo disparity, that is expected to be valid piecewise across the visual field. Estimation is cast as optimization over a dichotomous mixture of variables, simultaneously determining which regions are inliers with respect to the local model (binary variables) and the correct co-ordinates in the local model space for each inlying region (continuous variables). When the regions are organized into a multi-scale hierarchy, optimization can occur in an efficient and parallel architecture, where distributed computational units iteratively perform calculations and share information through sparse connections between parents and children. The framework performs well on a standard benchmark for binocular stereo, and it produces a distributional scene representation that is appropriate for combining with higher-level reasoning and other low-level cues.
Economic Evaluation of Text-Messaging and Smartphone-Based Interventions to Improve Medication Adherence in Adolescents with Chronic Health Conditions: A Systematic Review

Background The rate of chronic health conditions (CHCs) in children and adolescents has doubled in the past 20 years, with increased health care costs. Technology-based interventions have demonstrated efficacy to improving medication adherence. However, data to support the cost effectiveness of these interventions are lacking. Objective The objective of this study is to conduct an economic evaluation of text-messaging and smartphone-based interventions that focus on improving medication adherence in adolescents with CHCs. Methods Searches included PubMed MEDLINE, Embase, Cochrane Central Register of Controlled Trials, Cumulative Index to Nursing and Allied Health Literature, PsycINFO, Web of Science, and Inspec. Eligibility criteria included age (12-24 years old), original articles, outcomes for medication adherence, and economic outcomes. Results Our search identified 1118 unique articles that were independently screened. A total of 156 articles met inclusion criteria and were then examined independently with full-text review. A total of 15 articles met most criteria but lacked economic outcomes such as cost effectiveness or cost-utility data. No articles met all predefined criteria to be included for final review. Only 4 articles (text messaging [n=3], electronic directly observed therapy [n=1]) described interventions with possible future cost-saving but no formal economic evaluation. Conclusions The evidence to support the cost effectiveness of text-messaging and smartphone-based interventions in improving medication adherence in adolescents with CHCs is insufficient. This lack of research highlights the need for comprehensive economic evaluation of such interventions to better understand their role in cost-savings while improving medication adherence and health outcomes. Economic evaluation of technology-based interventions can contribute to more evidence-based assessment of the scalability, sustainability, and benefits of broader investment of such technology tools in adolescents with CHCs.
Prediction of Cancer Incidence and Mortality in Korea, 2015

Purpose For estimation of Korea’s current cancer burden, this study aimed to report on the projected cancer incidence and mortality rates for the year 2015. Materials and Methods Cancer incidence data from 1999 to 2012 were obtained from the Korea National Cancer Incidence Database, and cancer mortality data from 1993 to 2013 were acquired from Statistics Korea. The cancer incidence in 2015 was projected by fitting a linear regression model to the observed age-specific cancer incidence rates against the observed years and then multiplying the projected age-specific rates by the age-specific population. A similar procedure was used for cancer mortality, except a Joinpoint regression model was used to determine at which year the linear trend changed significantly. Results A total of 280,556 new cancer cases and 76,698 cancer deaths are expected to occur in Korea in 2015. The crude incidence rate per 100,000 of all sites combined will likely reach 551.6 and the age-standardized incidence rate, 347.6. The estimated five leading primary cancer incidence sites are the stomach, colorectum, lung, prostate, and liver in men; and thyroid, breast, colorectum, stomach, and lung in women. The projected crude mortality rate of all sites combined and age-standardized rate is 150.8 and 82.4, respectively. Conclusion Cancer is currently one of the foremost public health concerns in Korea, and as the population ages, the nation’s cancer burden will continue to increase.
Effect of rosuvastatin on hyperuricemic rats and the protective effect on endothelial dysfunction

Endothelial dysfunction plays a key role in the development of cardiovascular diseases, renal injuries and hypertension induced by hyperuricemia. Therapies targeting uric acid (UA) may be beneficial in cardiovascular diseases. In the present study, the effect of rosuvastatin, a 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitor, was investigated to determine whether rosuvastatin improves endothelial dysfunction via the endothelial nitric oxide (NO) pathway and delays the pathogenesis of endothelial dysfunction in hyperuricemic rats. A total of 72 Sprague-Dawley rats (age, 8 weeks) were randomly divided into six groups (12 rats per group), including the control, model, 2.5 mg/kg/day rosuvastatin, 5 mg/kg/day rosuvastatin, 10 mg/kg/day rosuvastatin and 53.57 mg/kg/day allopurinol groups. The model, rosuvastatin and allopurinol rats were subjected to hyperuricemia, induced by the administration of yeast extract powder (21 g/kg/day) and oxonic acid potassium salt (200 mg/kg/day). The hyperuricemic rats were treated with 2.5, 5.0 or 10.0 mg/kg/day rosuvastatin orally for six weeks, while rats treated with allopurinol (53.57 mg/kg/day) were used as a positive control. The serum levels of NO and the gene expression levels of endothelial NO synthase in the aortic tissue increased, whereas the serum levels of UA, endothelin-1 and angiotensin II decreased in the hyperuricemic rats treated with rosuvastatin, particularly at a high rosuvastatin dose (10 mg/kg/day). In addition, the curative effect of the 10 mg/kg/day rosuvastatin group was evidently higher compared with the allopurinol group. Therefore, rosuvastatin may be a novel drug candidate for the treatment of hyperuricemia due to its endothelial protective properties.
A self-adaptive heterogeneous pso for real-parameter optimization

Heterogeneous particle swarm optimizers (HPSO) allow particles to use different update equations, referred to as behaviors, within the swarm. Dynamic HPSOs allow the particles to change their behaviors during the search. These HPSOs alter the exploration/exploitation balance during the search which alters the search behavior of the swarm. This paper introduces a new self-adaptive HPSO and compares it with other HPSO algorithms on the CEC 2013 real-parameter optimization benchmark functions. The proposed algorithm keeps track of how successful each behavior has been over a number of iterations and uses that information to select the next behavior of a particle. The results show that the proposed algorithm outperforms existing HPSO algorithms on the benchmark functions.
Multi-objective optimization of parametric combination of injected slub yarn for producing knitted and woven fabrics with least abrasive damage

Purpose This study aims to optimize the parametric combination of injected slub yarn to achieve least abrasive damage on fabrics produced from it. Design/methodology/approach Single base injected slub yarn structural parameters, vis-a-vis slub length, slub thickness and slub frequency, were varied during preparation of yarn samples under this research work. A total of 17 yarn samples were produced according to the Box and Bhenken design of the experiment. Subsequently knitted and woven (using injected slub yarns in the weft only) fabric samples were prepared from these yarns. Yarn and fabric samples were abraded with standard instruments to see the impact of yarn structural parameters on abrasive damage of fabric in terms of fabric mass loss and appearance deterioration. From the test results, empirical models relating to slub parameters and fabric abrasion behavior were developed through a backward elimination regression approach. Subsequently, a set of optimal parametric combinations was derived with multi-objective evolutionary algorithms by using MATLAB software. This was followed by ranking all optimal solutions through technique for order preference by similarity to idle solution (TOPSIS) score analysis. Findings The injected slub yarn’s structural parameters have a strong influence on the abrasive damage of knitted and woven fabric. It is seen that the best suitable parametric combination of slub parameters for achieving the least abrasive damage is not the same for knitted and woven fabric. Practical implications The spinner can explore this concept to find out the best suitable parametric combination during pattern making of injected slub yarn through MATLAB solution followed by TOPSIS score analysis based on their priority of criteria level to ensure better abrasion behavior of fabric produced. Originality/value Optimization of parametric combination of injected slub yarns will help to ensure production of fabric with most resistance to abrasion for specific applications. The studies showed that the optimal solution for woven and knitted fabrics is different. The result indicates that in the case of knitted fabric, comparatively lesser slub thickness is found to be suitable for getting better fabric abrasion resistance, whereas in the case of woven fabric, comparatively higher slub thickness is found suitable for the same.
Vascular Health and Risk Management Dovepress Treatment Options for Hypertension in High-risk Patients

Patients are considered to be at high risk of cardiovascular events if they have diabetes, chronic kidney disease, stroke, established coronary artery disease, or a coronary artery disease equivalent. Blood pressure-lowering therapy has been shown to reduce cardiovascular events in these patients significantly. Identification of high-risk patients by global risk evaluation is recommended for every hypertensive patient. Treatment of hypertension in high-risk patients with an angiotensin-converting enzyme inhibitor or an angiotensin receptor antagonist, with or without addition of a dihydropyridine calcium channel antagonist, is a reasonable approach based on current clinical trials.
iBoy - Fast System Level Emulation Using Dynamic Binary Translation

Many portable devices are targeted at a mass market that justified to employ low-cost hardware components and highly performance-optimised software to reduce overall costs. Such applications often exhaustively use hardware features without any operating system layer that decouples software from architecture specific peculiarities like address space or interrupt handling. Even with the source code available it is hard to port these applications to new architectures. Ongoing development of processors allows embedded devices to be cheap while providing high performance. This makes it feasible to use performance demanding system level emulation software that enables (binary) legacy applications to run without modifications on new platforms. In this work we evaluate to what extent dynamic binary translation can reduce efficiency losses of system level emulation. We present an exemplary dynamic binary translator that (together with other modifications) is used to speed up the Nintendo Gameboy system level emulator gnuboy on the chosen target architecture: An Apple iPod.
Taxi-Passenger-Demand Modeling Based on Big Data from a Roving Sensor Network

Investigating passenger demand is essential for the taxicab business. Existing solutions are typically based on offline data collected by manual investigations, which are often dated and inaccurate for real-time analysis. To address this issue, we propose Dmodel, employing roving taxicabs as real-time mobile sensors to (i) infer passenger arriving moments by interactions of vacant taxicabs, and then (ii) infer passenger demand by customized online training with both historical and real-time data. Dmodel utilizes a novel parameter called pickup pattern based on an entropy of pickup events (accounts for various real-world logical information, e.g., bad weather) to reduce the size of big historical taxicab data to be processed. We evaluate Dmodel with a real-world 450 GB dataset of 14,000 taxicabs for a half year, and results show that compared to the ground truth, Dmodel achieves 83 percent accuracy and outperforms a statistical model by 42 percent. We further present an application where Dmodel is used to dispatch vacant taxicabs to achieve an equilibrium between passenger demand and taxicab supply across urban regions.
Agent based artificial experiments in social science with jESOF

We introduce here a small set of artificial experim ents in social science and a simplified tool useful to develop them in the perspective of t he analysis of complex systems, with different degrees of cognitive definition of agents ’ behavior. The straightforward way to build this kind of struc t res requires the use of agent based simulation techniques, i.e. models in which small s oftware routines behave representing artificial agents within artificial environments co ntaining (in some case) ecosystems that allow the emergence of institutions such as market, organizations, hierarchal structures. jESOF (java Enterprise Simulation Open Foundations, web.econ.unito.it/terna/jes ) is a tool created to simplify the access to agent based simulation for social scientists, whose competences are not necessarily are the same of hig h level specialized computer scientists. jESof has been developed upon the Swarm ( www.swarm.org) simulation library. The two examples reported in this analysis show tha t it is relatively easy to develop models with jESOF and that we are virtually unconst rained in the definition of the contents of our simulation models. The first model is a test implementation of the wel l known Preys Predators Model (PPM) and allows the introduction of non only two, but th ree or more interacting levels (hyperpredators etc.). PPM uses fixed rules in a determin istic way and complexity comes from the characteristics of the problem and of its envir onment. The second model is based upon two coevolving popul ation: Workers, with their Skills, and Firms (WSF): the two populations have quasi-ind ependent behaviors, based on a bounded rationality paradigm. Despite the relative independence of the two populations, structures emerge, with the shape of industrial dis trict .
Robust MIMO Cognitive Radio Systems Under Interference Temperature Constraints

Cognitive Radio (CR) systems are built on the coexistence of primary users (PUs) and secondary users (SUs), the latter being allowed to share spectral resources with the PUs but under strict interference limitations. However, such limitations may easily be violated by SUs if perfect SU-to-PU channel state information (CSI) is not available at the secondary transmitters, which always happens in practice. In this paper, we propose a distributed design of MIMO CR networks under global interference temperature constraints that is robust (in the worst-case sense) against SU-to-PU channel uncertainties. More specifically, we consider two alternative formulations that are complementary to each other in terms of signaling and system performance, namely: a game-theoretical design and a social-oriented optimization. To study and solve the proposed formulations we hinge on the new theory of finite-dimensional variational inequalities (VI) in the complex domain and a novel parallel decomposition technique for nonconvex sum-utility problems with coupling constraints, respectively. A major contribution of this paper is to devise a new class of distributed best-response algorithms with provable convergence. The algorithms differ in computational complexity, convergence speed, communication overhead, and achievable performance; they are thus applicable to a variety of CR scenarios, either cooperative or non-cooperative, which allow the SUs to explore the trade-off between signaling and performance.
CHROMOSOMAL ABNORMALITIES IN RATS AFTER BAMBOO FLOWERING IN MANIPUR , INDIA

The famine and bamboo flowering are closely related in North-East India. Bamboo flowering causes population explosion of the rat population. The cytological analysis of metaphase from bone marrow cells through karyotype, C-band and Ag-NOR show chromosomal changes like monosomy, trisomy, robertsonian fusion etc. besides 2n=24. How the exploded population gets stabilized is a big question. One hypothesis has been put forward through the chromosomal changes leading to the death or sterility of some or many individuals but the natural or normal population remains more or less constant, as maintained by the unaffected individuals left behind.
Improving Energy Efficiency of GPUs through Data Compression and Compressed Execution

GPU design trends show that the register file size will continue to increase to enable even more thread level parallelism. As a result register file consumes a large fraction of the total GPU chip power. This paper explores register file data compression for GPUs to improve power efficiency. Compression reduces the width of the register file read and write operations, which in turn reduces dynamic power. This work is motivated by the observation that the register values of threads within the same warp are similar, namely the arithmetic differences between two successive thread registers is small. Compression exploits the value similarity by removing data redundancy of register values. Without decompressing operand values some instructions can be processed inside register file, which enables to further save energy by minimizing data movement and processing in power hungry main execution unit. Evaluation results show that the proposed techniques save 25 percent of the total register file energy consumption and 21 percent of the total execution unit energy consumption with negligible performance impact.
Climate Change and Public Health Policy: Translating the Science

Public health authorities are required to prepare for future threats and need predictions of the likely impact of climate change on public health risks. They may get overwhelmed by the volume of heterogeneous information in scientific articles and risk relying purely on the public opinion articles which focus mainly on global warming trends, and leave out many other relevant factors. In the current paper, we discuss various scientific approaches investigating climate change and its possible impact on public health and discuss their different roles and functions in unraveling the complexity of the subject. It is not our objective to review the available literature or to make predictions for certain diseases or countries, but rather to evaluate the applicability of scientific research articles on climate change to evidence-based public health decisions. In the context of mosquito borne diseases, we identify common pitfalls to watch out for when assessing scientific research on the impact of climate change on human health. We aim to provide guidance through the plethora of scientific papers and views on the impact of climate change on human health to those new to the subject, as well as to remind public health experts of its multifactorial and multidisciplinary character.