Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of the Transition to Home Monitoring for the Diagnosis of OSAS on Test Availability, Waiting Time, Patients' Satisfaction, and Outcome in a Large Health Provider System

During 2009, the Haifa district of Clalit Health Services (CHS) has switched from in-lab polysomnography (PSG) to home studies for the diagnosis of obstructive sleep apnea (OSA). We assessed the effects of this change on accessibility, waiting time, satisfaction, costs, and CPAP purchase by the patients. Data regarding sleep studies, CPAP purchase, and waiting times were collected retrospectively from the computerized database of CHS. Patients' satisfaction was assessed utilizing a telephone questionnaire introduced to a randomized small sample of 70 patients. Comparisons were made between 2007 and 2008 (in-lab PSGs) and 2010 and 2011 (when most studies were ambulatory). Of about 650000 insured individuals in the Haifa district of CHS, 1471 sleep studies were performed during 2007-2008 compared to 2794 tests during 2010-2011. The average waiting time was 9.9 weeks in 2007-2008 compared to 1.1 weeks in 2010-2011 (P < 0.05). 597 CPAPs were purchased in 2007-2008 compared to 831 in 2010-2011. The overall patients' satisfaction was similar, but discomfort tended to be higher in the in-laboratory group (4.1 vs 2.7 in a scale of 0–10; P = 0.11). Switching to ambulatory diagnosis improved the test accessibility and reduced the waiting times. Patients' satisfaction remained similarly high. The total direct cost of OSA management was reduced.
Implementation of temperature dependence in small-signal models of microwave transistors including noise

In this paper, the artificial neural network approach is proposed for prediction purposes of temperature behavior of microwave transistors. Neural networks are used for modeling of temperature dependencies of elements of transistor small-signal models including noise. These dependencies are extracted from transistor signal and noise data referred to a set of temperatures, The developed models are valid in the whole operational range of temperatures.
Petr Jancar

In this tutorial we describe general approaches to deciding bisimilarity between vertices of (innnite) directed edge-labelled graphs. The approaches are based on a systematic search following the deenition of bisimilarity. We outline (in decreasing levels of detail) how the search is modiied to solve the problem for nite graphs, BPP graphs, BPA graphs, normed PA graphs, and normed PDA graphs. We complete this by showing the technique used in the case of graphs generated by one-counter machines. Finally, we demonstrate a general reduction strategy for proving undecidability, which we apply in the case of graphs generated by state-extended BPP (a restricted form of labelled Petri nets). The bisimulation game is played on a \board" which consists of a (generally innnite) directed edge-labelled multigraph (several edges can lead between two vertices), simply called a graph in the following. We assume that this graph is labelled from a nite set of labels, and that it is nite-branching: that every vertex has nite out-degree. In particular, it is image-nite: for every vertex E and every label a, the set succ a (E) = fF : E a ! Fg is nite. We also asume that these successor sets are eeectively constructible. A game is deened by two vertices E 0 and F 0 of a graph, as well as a predetermined time limit n 2 N f! g (where N = f0; 1; 2; 3; : : :g); we specify such a game by G n (E 0 ; F 0). We have two players competing in the game whom we refer to as Alice (the \Attacker") and Bob (the \Bisimulator"). Their individual goals are as follows: 1. Alice wants to show that E 0 and F 0 are in some sense \diierent". 2. Bob wants to show that E 0 and F 0 are in the same sense \the same".
[The diagnosis and treatment of autoimmune hepatitis].

自身免疫性肝炎(AIH)是由异常自身免疫反应介导的肝实质炎症性病变,以高丙种球蛋白血症、血清自身抗体阳性和对免疫抑制治疗应答为特点[1]. 在环境因素、免疫耐受失衡和遗传易感状态的共同作用下,机体出现T淋巴细胞介导的针对肝抗原的异常免疫攻击,进而导致肝内进行性炎症坏死和纤维化过程。
Scalable Computing: Practice and Experience

Today one of the most important challenges in HPC is the development of computers with a low power consumption. In this context, recently, new embedded many-core systems have emerged. One of them is Kalray. Unlike other many-core architectures, Kalray is not a co-processor (self-hosted). One interesting feature of the Kalray architecture is the Network on Chip (NoC) connection. Habitually, the communication in many-core architectures is carried out via shared memory. However, in Kalray, the communication among processing elements can also be via Message-Passing on the NoC. One of the main motivations of this work is to present the main constraints to deal with the Kalray architecture. In particular, we focused on memory management and communication. We assess the use of NoC and shared memory on Kalray. Unlike shared memory, the implementation of Message-Passing on NoC is not transparent from programmer point of view. The synchronization among processing elements and NoC is other of the challenges to deal with in the Karlay processor. Although the synchronization using Message-Passing is more complex and consuming time than using shared memory, we obtain an overall speedup close to 6 when using Message-Passing on NoC with respect to the use of shared memory. Additionally, we have measured the power consumption of both approaches. Despite of being faster, the use of NoC presents a higher power consumption with respect to the approach that exploits shared memory. This additional consumption in Watts is about a 50%. However, the reduction in time by using NoC has an important impact on the overall power consumption as well.
Design Hybrid method for intrusion detection using Ensemble cluster classification and SOM network

In current scenario of internet technology security is big challenge. Internet network threats by various cyber-attack and loss the system data and degrade the performance of host computer. In this sense intrusion detection are challenging field of research in concern of network security based on firewall and some rule based detection technique. In this paper we proposed an Ensemble Cluster Classification technique using som network for detection of mixed variable data generated by malicious software for attack purpose in host system. In our methodology SOM network control the iteration of distance of different parameters of ensembling our experimental result show that better empirical evaluation on KDD data set 99 in comparison of existing ensemble classifier.
The impact of subordinate–supervisor similarity in growth‐need strength on work outcomes: the mediating role of perceived similarity

Based on data collected from 205 vertical dyads, we found that subordinate–supervisor similarity in their self-reported growth-need strength (GNS) had a positive effect on subordinate-perceived and supervisor-perceived global similarity. The findings also suggested that subordinate-perceived global similarity mediates the link between similarity in GNS and subordinate's trust in and loyalty to supervisor; whereas supervisor-perceived global similarity mediates the link between similarity in GNS and supervisor-rated in-role/extra-role performances. In addition, we found that subordinate–supervisor similarity in self-reported GNS and perceived global similarity had independent effects on work outcomes for both subordinates and supervisors. Copyright © 2006 John Wiley & Sons, Ltd.
A macro-level study of science in Brazil: seven years later

Following earlier studies by the authors published in 2006, the evolution of publication activity and citation impact in Brazil is studied for more recent years up to 2011. Similarly to these studies, an analysis of publication and citation patterns and of national publication profiles is conducted to make it possible to compare recent trends with patterns found earlier. An attempt is made to find also statistical evidences of the relation between international co-authorship and both research profile and citation impact in the Latin American region. The authors compare their results with finding from other bibliometric studies of BRICS and N-11 countries. The enormous growth of Brazilian publication output forms the largest potential reaching far beyond the Latin American world region.
Peer and Faculty Mentoring for Students Pursuing a PHD in Gerontology

The Graduate Center for Gerontology at the University of Kentucky incorporates three levels of mentoring in its PhD program. This project assessed satisfaction with peer and faculty mentoring and explored their perceived benefits and purposes. Core and affiliate faculty and current and graduated students were surveyed. Participants seemed satisfied with the mentoring they were giving and receiving, although all groups discussed limitations. Peer mentors were seen as social support and advice givers, while faculty mentors were viewed as responsible for direction and skill-building. These results can contribute to the development of new mentorship programs and the modification of existing ones.
Mixing Realities? An Application of Augmented Reality for the Treatment of Cockroach Phobia

Augmented reality (AR) refers to the introduction of virtual elements in the real world. That is, the person is seeing an image composed of a visualization of the real world, and a series of virtual elements that, at that same moment, are super-imposed on the real world. The most important aspect of AR is that the virtual elements supply to the person relevant and useful information that is not contained in the real world. AR has notable potential, and has already been used in diverse fields, such as medicine, the army, coaching, engineering, design, and robotics. Until now, AR has never been used in the scope of psychological treatment. Nevertheless, AR presents various advantages. Just like in the classical systems of virtual reality, it is possible to have total control over the virtual elements that are super-imposed on the real world, and how one interacts with those elements. AR could involve additional advantages; on one side it could be less expensive since it also uses the real world (this does not need to be modeled), and it could facilitate the feeling of presence (the sensation of being there), and reality judgment (the fact of judging the experience as real) of the person since the environment he or she is in, and what he or she is seeing is, in fact the "reality. " In this paper, we present the data of the first case study in which AR has been used for the treatment of a specific phobia, cockroaches phobia. It addresses a system of AR that permits exposure to virtual cockroaches super-imposed on the real world. In order to carry out the exposure, the guidelines of Ost with respect to "one-session treatment" were followed. The results are promising. The participant demonstrated notable fear and avoidance in the behavioral avoidance test before the treatment, and not only was an important decrease in the scores of fear and avoidance observed after the treatment, but also the participant was capable of approaching, interacting, and killing live cockroaches immediately following the treatment. The results are maintained in a follow-up conducted 1 month after the termination of the treatment.
Signals of selection in outlier loci in a widely dispersing species across an environmental mosaic

Local adaptation reflects a balance between natural selection and gene flow and is classically thought to require the retention of locally adapted alleles. However, organisms with high dispersal potential across a spatially or temporally heterogeneous landscape pose an interesting challenge to this view requiring local selection every generation or when environmental conditions change to generate adaptation in adults. Here, we test for geographical and sequence‐based signals of selection in five putatively adaptive and two putatively neutral genes identified in a previous genome scan of the highly dispersing purple sea urchin, Strongylocentrotus purpuratus. Comparing six populations spanning the species’ wide latitudinal range from Canada to Baja California, Mexico, we find positive tests for selection in the putative adaptive genes and not in the putative neutral genes. Specifically, we find an excess of low‐frequency and nonsynonymous polymorphisms in two transcription factors and a transporter protein, and an excess of common amino acid polymorphisms in the two transcription factors, suggestive of spatially balancing selection. We test for a genetic correlation with temperature, a dominant environmental variable in this coastal ecosystem. We find mild clines and a stronger association of genetic variation with temperature than latitude in four of the five putative adaptive loci and a signal of local adaptation in the Southern California Bight. Overall, patterns of genetic variation match predictions based on spatially or temporally balancing selection in a heterogeneous landscape and illustrate the value of geographical and coalescent tests on candidate loci identified in a genome‐wide scan for selection.
Recent Developments of Biological Reporter Technology for Detecting Gene Expression

Abstract Reporter gene assay is an invaluable tool for both biomedical and pharmaceutical researches to monitor cellular events associated with gene expression, regulation and signal transduction. On the basis of the alternations in reporter gene activities mediated by attaching response elements to these reporter genes, one sensitive, reliable and convenient assay can be provided to efficiently report the activation of particular messenger cascades and their effects on gene expression and regulations inside cells or living subjects. In this review, we introduce the current status of several commonly used reporter genes such as chloramphenicol acetyltransferase (CAT), alkaline phos-phatase (AP), β-galactosidase (β-gal), luciferases, green fuorescent protein (GFP), and β-lactamase. Their applications in monitoring gene expression and regulations in vitro and in vivo will be summarized. With the development of advanced technology in gene expression and optical imaging modalities, reporter genes will become increasingly important in real-time detection of the gene expression at the single-cell level. This synergy will make it possible to understand the molecular basis of diseases, track the effectiveness of pharmaceuticals, monitor the response to therapies and evaluate the development process of new drugs.
Success Patterns of Exploratory and Exploitative Innovation

Research has frequently argued that firms need to pursue exploratory and exploitative innovation strategies to be viable in an environment of technological change and intensified competition. However, it remains unclear whether exploratory and exploitative innovations are equally successful in different institutional environments. This meta-analysis synthesizes previous empirical findings to reveal under which institutional conditions firms benefit most from exploratory or exploitative innovation. We distinguish between institutional conditions that affect the success derived from exploratory and exploitative innovations through (a) the availability of resources and (b) attitudes toward innovation and the willingness of stakeholders to allocate resources to both innovation types. Our results show that national culture has a strong impact on the success of exploratory innovations, whereas only uncertainty avoidance influences the benefits derived from exploitative innovations. Socioeconomic conditions are equally important for the success of both innovation types. Our findings are of high practical relevance as due to increasing globalization more and more firms operate internationally and managers have choices regarding the location of their exploratory and exploitative innovation activities.
The application of AdaBoost-neural network in storedproduct insect classification

The classification of stored product insects has been an important and difficult aspect of grain reserve in the world. The existing classification methods cannot acquire excellent performance. AdaBoost, an adaptive boosting algorithm, may improve the classification accuracy of any given classifier. In this paper AdaBoost is adopted to increase the performance of artificial neural network for stored product insect classification, and compared with standard neural network methods. Experiment results show that the new method is efficient and a significant improvement in classification accuracy is obtained.
The Effects of MDCO-2010, a Serine Protease Inhibitor, on Activated Clotting Time in Blood Obtained from Volunteers and Cardiac Surgical Patients

BACKGROUND:The activated clotting time (ACT) is widely used for monitoring heparin anticoagulation during cardiac surgery. Celite-based ACT values are prolonged when aprotinin is administered. MDCO-2010, a novel serine protease inhibitor, is currently being evaluated as a possible alternative to aprotinin. Therefore, we evaluated the in vitro effects of this novel agent on ACT values using 3 different point-of-care instruments with kaolin or celite as an activator. METHODS:The study was performed in 2 parts. In the first part, blood samples were obtained from 15 healthy volunteers. Samples were pipetted into small Eppendorf tubes and 2 concentrations of the MDCO-2010 (100 and 500 nM, final concentration) alone or with heparin (1.2 or 2.4 U/mL) were added. ACTs were measured using Helena (celite), Hemochron (kaolin), and Medtronic (kaolin) devices. In the second part of the study, blood samples were obtained intraoperatively, at 5 time points, from 15 patients undergoing cardiopulmonary bypass. MDCO-2010 at a final concentration of 100 or 500 nM was added and ACT testing was performed as before. Additional coagulation tests included prothrombin time, activated partial thromboplastin time, fibrinogen, antithrombin, prothrombin, and anti-Xa levels. RESULTS:Addition of MDCO-2010 concentration-dependently prolonged ACTs in volunteers' and patients' blood samples regardless of the ACT activator or device used. In volunteer samples (no heparin) and in patient samples (baseline and intensive care unit) percent changes in ACTs due to MDCO-2010 were on average 3.1 ± 1.8 times higher (95% confidence interval 2.6–3.6; P < 0.001) for the celite-based Helena device compared with either Hemochron or Medtronic devices. CONCLUSION:MDCO-2010 causes less ACT prolongation with kaolin than with celite activation.
A current-steering DAC-based CMOS ultra-wideband transmitter with bi-phase modulation

In this paper, the design and simulation of a CMOS ultra-wideband (UWB) transmitter using TSMC 0.18 μm CMOS technology is presented. The operating frequency band of the transmitter is from 3 to 10 GHz for the application of UWB communications. The structure of the transmitter is based on the current-steering digital-to-analog converter (DAC). The design has the feature of high-tunability and easy adoption of modulations. The simulation results show that the output of the transmitter complies with the FCC regulations and has a power consumption of 32 mW at a 50 MHz pulse repetition frequency (PRF).
A New Metaphor for Strategic Fit: All That Jazz

Outlines three metaphors which can be used to help understand the strategy process. These are “the jigsaw puzzle”, “the ice skater” and “the jazz band”. The suggestion is that the first two suffer from a number of limitations which the third attempts to address. The “jazz band” metaphor helps to identify some of the features which might be expected to contribute to effective strategic management. Draws out some pointers for managers are drawn out from the discussion.
Seignorage , Productive Government Spending and Growth in a Lucasian General Equilibrium Model

This paper examines the effects of fiscal and monetary policies in a two-sectorial endogenous growth model with money in the utility function. By focusing on the linkage between monetary and fiscal policy due to the government budget constraint, our model deviates from the literature. We show that the impacts of monetary policy heavily depend on the allocation of the seignorage. While money is superneutral, long-run economic growth depends on the level of government expenditures in the human-capital production sector. Therefore an increase in the rate of money supply growth has real effects if and only if the resulting seignorage is used for human capital investments.
The evaluation of low-density lipoprotein cholesterol goals achieved in patients with established cardiovascular disease and/or hyperlipidaemia receiving lipid-lowering therapy: the South African Not At Goal study (SA-NAG)

Summary Aim Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide. Dyslipidaemia is a major risk factor that leads to the clinical sequelae of CVD. As a result, it has become essential for South Africa to update its guidelines for the management of dyslipidaemia, and the South African scientific community has recently adopted the European guidelines on CVD prevention in clinical practice. The South African Not at Goal study (SA-NAG) was a survey done to determine the percentage of patients on lipid-lowering therapy who were not achieving guideline-specified low-density lipoprotein cholesterol (LDL-C) goals. Methods In this cross-sectional study, dyslipidaemic and/or CVD patients on lipid-lowering therapy for more than four months were enrolled. Volunteers had their demographic data and previous medical history documented. Blood samples from these patients were analysed (using standardised methods) to obtain fasting blood lipid and glucose levels. Results In total, 1 201 patients (age 58 ± 11.4 years) were recruited by physicians and general practitioners from across South Africa. Under the new guidelines, 41% of patients were defined as low risk (LR) and 59% were high risk (HR). Sixty-three per cent of LR patients and 77% of HR patients (71% overall) did not achieve their LDL-C target goals of 2.5 and 3.0 mmol/l, respectively. The LR and HR patients who did not achieve their LDL-C goals were on average 19% (0.7 mmol/l ± 0.5) and 31% (1.1 mmol/l ± 1.1) above their LDL-C target levels, respectively. Conclusions These results suggest that a considerable number of patients fall into the category ‘not at goal’ LDL-C. Patients who failed to achieve goal were also far above their LDL-C target levels. The adoption of the new guidelines will necessitate enhanced disease management to reduce the disease burden.
Measurement practice for knowledge management

Knowledge management (KM) has become part of common vocabulary in academic circles as well as in the business world. Whilst an increasing number of companies have embarked upon knowledge management initiatives, a large proportion of these initiatives remain technically focussed. The problem with this type of focus is that it excludes and neglects the true potential benefits that can be derived from knowledge management. In this paper we present a holistic model of KM which dynamically incorporates both tactical as well as strategic elements. Secondly in this paper we address a very important gap in the field of KM, namely how to measure KM by developing a framework which systematically allows for screening and evaluation. The measurement framework proposed enables leveraging knowledge assets effectively and efficiently. Without a holistic perspective which captures all the key elements and dimensions, KM initiatives will create marginal gains at best and failure at worst.