Miracle-dz/UniFAR-FTUs huggingface dataset:
SINGLE CASE STUDY: “Panic Disorder” in Schizophrenia

A patient is described with operationally diagnosed chronic schizophrenia who simultaneously experienced repeated “attacks” during which times he had intense apprehension and autonomic hyperactivity entirely similar to that usually described under the rubric of “panic attacks” in nonschizophrenic patients. Delusional and hallucinatory symptoms were also transiently exacerbated during these episodes. Alprazolam, as an adjunct to fluphenazine decanoate, was effective in ameliorating these symptoms. Diagnostic and treatment implications are discussed.
Relationships between Tests of Visual Memory in Patients with Mild Cognitive Impairment and Alzheimer’s Disease

Alzheimer’s disease (AD) is a degenerative neurological disorder characterized by cognitive and functional impairment (Budson & Solomon, 2011). Its prevalence is expected to rise in the upcoming decades as the world’s population ages (Alzheimer’s Association, 2014). Amnestic mild cognitive impairment (MCI) is a clinical diagnostic entity that may represent very early AD (Morris et al., 2001). Both disorders involve significant impairment in episodic memory, necessitating reliable memory measures when making diagnoses. Although verbal memory is most often impaired in the earliest stages of disease (Budson & Price, 2005), visual memory is also predictor of AD (Kawas et al., 2003). Partly due to a lack of comparative data between visual memory measures, they are often chosen based on clinical rather than psychometric needs. This study compared several commonly-used visual memory measures in order to provide data to which clinicians can refer when choosing between measures when time is limited. Running head: TESTS OF VISUAL MEMORY iv A 2 × 8 mixed within-between groups design was used to compare measures in a group of 20 older adult patients at a memory disorders clinic diagnosed with AD or MCI and in a comparison group 20 normal healthy controls. Subtests from the Wide Range Assessment of Memory and Learning, 2nd Edition (WRAML2; Sheslow & Adams, 2003), the Wechsler Memory Scale, 4th Edition (WMS-IV; Wechsler, 2009), and the Brief Visuospatial Memory Test, Revised Edition (BVMT-R; Benedict, 1997) were administered to each participant as part of a comprehensive test battery. Correlations between measures were stronger in the control group (r =-.335 to .871, mean r = .157) than in the control group (r = -.421 to .825, mean r = .289). Mean scaled scores differed significantly between groups on most measures, with large effect sizes (d = 1.26 to 2.77, mean d = 1.815). Differences in mean scaled scores between some measures were larger in the clinical group than in the control group. Results demonstrate convergent validity between measures despite differences in item content and response format. Certain measures demonstrated psychometric characteristics that may be advantageous depending on the clinical setting. Running head: TESTS OF VISUAL MEMORY v Table of
A Bayesian Approach to Jointly Modeling Toxicity and Biomarker Expression in a Phase I/II Dose‐Finding Trial

Summary In this article, we propose a Bayesian approach to phase I/II dose‐finding oncology trials by jointly modeling a binary toxicity outcome and a continuous biomarker expression outcome. We apply our method to a clinical trial of a new gene therapy for bladder cancer patients. In this trial, the biomarker expression indicates biological activity of the new therapy. For ethical reasons, the trial is conducted sequentially, with the dose for each successive patient chosen using both toxicity and activity data from patients previously treated in the trial. The modeling framework that we use naturally incorporates correlation between the binary toxicity and continuous activity outcome via a latent Gaussian variable. The dose‐escalation/de‐escalation decision rules are based on the posterior distributions of both toxicity and activity. A flexible state‐space model is used to relate the activity outcome and dose. Extensive simulation studies show that the design reliably chooses the preferred dose using both toxicity and expression outcomes under various clinical scenarios.
Ca2+ Homeostasis Regulates Xenopus Oocyte Maturation1

Abstract In contrast to the well-defined role of Ca2+ signals during mitosis, the contribution of Ca2+ signaling to meiosis progression is controversial, despite several decades of investigating the role of Ca2+ and its effectors in vertebrate oocyte maturation. We have previously shown that during Xenopus oocyte maturation, Ca2+ signals are dispensable for entry into meiosis and for germinal vesicle breakdown. However, normal Ca2+ homeostasis is essential for completion of meiosis I and extrusion of the first polar body. In this study, we test the contribution of several downstream effectors in mediating the Ca2+ effects during oocyte maturation. We show that calmodulin and calcium-calmodulin-dependent protein kinase II (CAMK2) are not critical downstream Ca2+ effectors during meiotic maturation. In contrast, accumulation of Aurora kinase A (AURKA) protein is disrupted in cells deprived of Ca2+ signals. Since AURKA is required for bipolar spindle formation, failure to accumulate AURKA may contribute to the defective spindle phenotype following Ca2+ deprivation. These findings argue that Ca2+ homeostasis is important in establishing the oocyte's competence to undergo maturation in preparation for fertilization and embryonic development.
Comparative Analysis of User-generated and Travel agency photo posting in Chinese Microblog

Abstract The development of social media has produced many user-generated photographs, and it has also provided a new platform for tourism agencies to use photographs to promote their tourism products. This study aims to compare usergenerated photo postings and the travel agency photo postings collected from Sina microblog, one of the most popular Chinese social media platforms. Study results reveal differences in posted images between Chinese domestic tourist destination users and travel agencies. This study provides practical information for travel agencies to develop their promotion strategies for use on social media.
Biogeography Based Optimization Technique for Multi-Constrained Economic Load Dispatch Problems

This paper presents Biogeography-Based Optimization (BBO) technique for solving constrained economic dispatch problems in power system. Many nonlinear characteristics of generators, like valve point loading, ramp rate limits, prohibited zone, and multiple fuels cost functions are considered. The technique is applied to two Economic Load Dispatch (ELD) problems with different characteristics. Its solution quality and computation efficiency are compared to the same of Genetic algorithm (GA), Particle swarm optimization (PSO), and other optimization techniques. The simulation results show that the proposed algorithm outperforms other optimization methods.
Lock-based synchronization for GPU architectures

Modern GPUs have shown promising results in accelerating compute-intensive and numerical workloads with limited data sharing. However, emerging GPU applications manifest ample amount of data sharing among concurrently executing threads. Often data sharing requires mutual exclusion mechanism to ensure data integrity in multithreaded environment. Although modern GPUs provide atomic primitives that can be leveraged to construct fine-grained locks, the existing GPU lock implementations either incur frequent concurrency bugs, or lead to extremely low hardware utilization due to the Single Instruction Multiple Threads (SIMT) execution paradigm of GPUs. To make more applications with data sharing benefit from GPU acceleration, we propose a new locking scheme for GPU architectures. The proposed locking scheme allows lock stealing within individual warps to avoid the concurrency bugs due to the SMIT execution of GPUs. Moreover, it adopts lock virtualization to reduce the memory cost of fine-grain GPU locks. To illustrate the usage and the benefit of GPU locks, we apply the proposed GPU locking scheme to Delaunay mesh refinement (DMR), an application involving massive data sharing among threads. Our lock-based implementation can achieve 1.22x speedup over an algorithmic optimization based implementation (which uses a synchronization mechanism tailored for DMR) with 94% less memory cost.
Single Object Tracking with TLD , Convolutional Networks , and AdaBoost

We evaluate the performance of the TLD algorithm using AdaBoost and SVMs with HOG, CNN, and raw features. We improve runtime performance through algorithmic and implementation optimizations and are able to achieve nearrealtime frame rates of over 10 FPS for selected videos. Our SVM-HOG implementation achieves an average overlap of 54% and 60%, and an average MAP of 67% and 66%, on the validation and test set, respectively.
Redesigning with traits: the Nile stream trait-based library

Recently, traits have been proposed as a single inheritance backward compatible solution in which the composing entity has the control over the trait composition. Traits are fine-grained units used to compose classes, while avoiding many of the problems of multiple inheritance and mixin-based approaches. To evaluate the expressiveness of traits, some hierarchies were refactored, showing code reuse. However, such large refactorings, while valuable, may not be facing all the problems, since the hierarchies were previously expressed within single inheritance and following certain patterns. We wanted to evaluate how traits enable reuse, and what problems could be encountered when building a library using traits from scratch, taking into account that traits are units of reuse. This paper presents our work on designing a new stream library named Nile. We present the reuse that we attained using traits, and the problems we encountered.
The impact of mobility patterns on the efficiency of data forwarding in MANETs

One of the most challenging requirements in cutting-edge Mobile Ad hoc Networks is the need for adaptive and efficient routing. Networks capable of adapting their behavior based on current conditions are often characterized as self-organizing networks, which are lately considered very promising for future applications. This work examines the impact of the different mobility properties on the performance of self-organizing networks. For that purpose, a simulator was developed to model different mobility patterns and study the way they affect the effectiveness of the well-known AODV routing protocol. Particularly, this paper focuses on the effect of the different mobility schemes on network topology and consequently to the overall network performance. The results reveal the tight correlations between node mobility characteristics and network metrics.
Does egg competition occur in marine broadcast‐spawners?

When the availability of sperm limits female reproductive success, competition for sperm, may be an important broker of sexual selection. This is because sperm limitation can increase the variance in female reproductive success, resulting in strong selection on females to compete for limited fertilization opportunities. Sperm limitation is probably common in broadcast‐spawning marine invertebrates, making these excellent candidates for investigating scramble competition between broods of eggs and its consequences for female reproductive success. Here, we report our findings from a series of experiments that investigate egg competition in the sessile, broadcast‐spawning polychaete Galeolaria caespitosa. We initially tested whether the order in which eggs encounter sperm affects their fertilization success at two ecologically relevant current regimes. We used a split‐clutch—split‐ejaculate technique to compare the fertilization success of eggs from individual females that had either first access (competition‐free treatment) or second access (egg competition treatment) to a batch of sperm. We found that fertilization success depended on the order in which eggs accessed sperm; eggs that were assigned to the competition‐free treatment exhibited significantly higher fertilization rates than those assigned to the egg competition treatment at both current speeds. In subsequent experiments we found that prior exposure of sperm to eggs significantly reduced both the quantity and quality of sperm available to fertilize a second clutch of eggs, resulting in reductions in fertilization success at high and low sperm concentrations. These findings suggest that female traits that increase the likelihood of sperm‐egg interactions (e.g. egg size) will respond to selection imposed by egg competition.
The journey of liver transplantation: Milestones covered and the road ahead

Liver transplantation has now become an established approach for managing end-stage liver diseases, and the journey in the complex procedure of liver transplantation has come a long way, witnessing many ups and downs. Better understanding of the physiological and pathological changes in the context of end-stage liver disease has made anesthesia, an important denominator for the successful outcome of this complex surgical procedure.
A hierarchical genetic fuzzy rule-based classifier for high-dimensional classification problems

This paper proposes a novel Hierarchical Genetic Fuzzy Rule-Based Classification System (HGFRBCS), targeted at effectively handling high-dimensional classification tasks. A hierarchical fuzzy rule base comprises rules with linguistic terms from a multi-granular fuzzy sets database, whereby lower levels define thicker granularities of the input space fuzzy partition. The proposed system is developed through sequential repeating steps: in each step a fuzzy rule base is created using a given granularity. Subsequently, the best performing rules are inserted in the hierarchical rule base and the process is repeated again, considering a thicker granularity. The whole process is coordinated by a boosting scheme, which localizes new rules in uncovered regions of the feature space. Comparative results for various real-world high-dimensional classification problems indicate the effectiveness of the proposed methodology.
High prevalence of MRSA and ESBL among asylum seekers in the Netherlands

Migration is one of the risk factors for the spread of multidrug-resistant organisms (MDRO). The increasing influx of migrants challenges local health care systems. To provide evidence for both hospital hygiene measure and empirical antibiotic therapy, we analysed all cultures performed in asylum seekers between January 1st 2014 and December 31st 2015 for methicillin resistant Staphylococcus aureus (MRSA) and for multidrug-resistant Enterobacteriaceae (MDRE). We compared these with cultures from the Dutch patient population with risk factors for carriage of MDRO. A total of 7181 patients were screened for MRSA. 7357 S. aureus were isolated in clinical cultures. Of 898 screened asylum seekers, almost 10% were MRSA positive. Of 118 asylum seekers with S. aureus in clinical cultures almost 19% were MRSA positive. The general patient population had a 1.3% rate of MRSA in S. aureus isolates. A higher rate of Panton-Valentine leukocidin (PVL) positive strains (RR: 2.4; 95% CI: 1.6–3.4) was found in asylum seekers compared to the general patient population. In 33475 patients one or more Enterobacteriaceae were obtained. More than 21% of the asylum seekers were carrier of MDRE, most of them producing extended spectrum beta-lactamases (20.3%). 5.1% of the general patient population was MDRE carrier. It can be concluded that asylum seekers present with higher rate of MDRO compared to the general patient population. These results justify continued screening of asylum seekers to anticipate multidrug-resistant organisms during hospital care of patients.
Simulation study of Conventional Control versus MTPA-Based for PMSM Control

− in this paper, an analytical analysis for the permanent magnet synchronous motor (PMSM) control strategies will be provided and verified using the MATLAB program. A comparison between the conventional control (zero direct current) and the Maximum Torque per Ampere (MTPA) will be provided and verified on MATLAB. The target of this study is to verify that using the MTPA method is to be the proper choice for those applications require efficient driver to minimize the total power loss of the system. Electrical vehicle is one of those applications requires efficient motor drive to optimize the overall system performance. Index Terms – PMSM, MTPA, IPMSM.
The emerging role of guanine nucleotide exchange factors in ALS and other neurodegenerative diseases

Small GTPases participate in a broad range of cellular processes such as proliferation, differentiation, and migration. The exchange of GDP for GTP resulting in the activation of these GTPases is catalyzed by a group of enzymes called guanine nucleotide exchange factors (GEFs), of which two classes: Dbl-related exchange factors and the more recently described dedicator of cytokinesis proteins family exchange factors. Increasingly, deregulation of normal GEF activity or function has been associated with a broad range of disease states, including neurodegeneration and neurodevelopmental disorders. In this review, we examine this evidence with special emphasis on the novel role of Rho guanine nucleotide exchange factor (RGNEF/p190RhoGEF) in the pathogenesis of amyotrophic lateral sclerosis. RGNEF is the first neurodegeneration-linked GEF that regulates not only RhoA GTPase activation but also functions as an RNA binding protein that directly acts with low molecular weight neurofilament mRNA 3′ untranslated region to regulate its stability. This dual role for RGNEF, coupled with the increasing understanding of the key role for GEFs in modulating the GTPase function in cell survival suggests a prominent role for GEFs in mediating a critical balance between cytotoxicity and neuroprotection which, when disturbed, contributes to neuronal loss.
Sparse coding-based topic model for remote sensing image segmentation

Land cover segmentation can be viewed as topic assignment that the pixels are grouped into homogeneous regions according to different semantic topics in topic model. In this paper, we propose a novel topic model based on sparse coding for segmenting different kinds of land covers. Different from conventional topic models which generally assume each local feature descriptor is related to only one visual word of the codebook, our method utilizes sparse coding to characterize the potential correlation between the descriptor and multiple words. Therefore each descriptor can be represented by a small set of words. Furthermore, in this paper probabilistic Latent Semantic Analysis (pLSA) is applied to learn the latent relation among word, topic and document due to its simplicity and low computational cost. Experimental results on remote sensing image segmentation demonstrate the excellent superiority of our method over k-means clustering and conventional pLSA model.
How Many Software Metrics Should be Selected for Defect Prediction?

A software practitioner is interested in the solution to “for a given project, what is the minimum number of software metrics that should be considered for building an effective defect prediction model? ” During the development life cycle various software metrics are collected for different reasons. In the case of a metricsbased defect prediction model, an intelligent selection of software metrics prior to building defect predictors is likely to improve model performance. This study utilizes the proposed threshold-based feature selection technique to remove irrelevant and redundant software metrics (a.k.a. features or attributes). A comparative investigation is presented for evaluating the size of the selected feature subsets. The case study is based on software measurement data obtained from a real-world project, and the defect predictors are trained using three commonly used classifiers. The empirical case study results demonstrate that an effective defect predictor can be built with only three metrics; and moreover, model performances improved when over 98.5% of the software metrics were eliminated.
Alternating vigilance states: new insights regarding neuronal networks and mechanisms

Since the discovery of rapid eye movement (REM) sleep (also known as paradoxical sleep; PS), it is accepted that sleep is an active process. PS is characterized by EEG rhythmic activity resembling that of waking with a disappearance of muscle tone and the occurrence of REMs, in contrast to slow‐wave sleep (SWS, also known as non‐REM sleep) identified by the presence of delta waves. Here, we review the most recent data on the mechanisms responsible for the genesis of SWS and PS. Based on these data, we propose an updated integrated model of the mechanisms responsible for the sleep–wake cycle. This model introduces for the first time the notion that the entrance and exit of PS are induced by different mechanisms. We hypothesize that the entrance from SWS to PS is due to the intrinsic activation of PS‐active GABAergic neurons localized in the posterior hypothalamus (co‐containing melanin‐concentrating hormone), ventrolateral periaqueductal gray and the dorsal paragigantocellular reticular nucleus. In contrast, the exit from PS is induced by the inhibition of these neurons by a PS‐gating system composed of GABAergic neurons localized in the ventrolateral periaqueductal gray and just ventral to it, and waking systems such as the pontine and medullary noradrenergic neurons and the hypothalamic hypocretin neurons. Finally, we review human neurological disorders of the network responsible for sleep and propose hypotheses on the mechanisms responsible for REM behavior disorder and narcolepsy.
An Innovation of an Academic Cloud Computing Service

Despite the popularity of cloud computing services, few studies have investigated academic cloud computing services. This study explored the innovation of an academic cloud, the Ming Chuan University Cloud System (MCUCS). A cloud computing service provides numerous benefits to an organization. We conducted a comprehensive review and observation of MCUCS and identified 8 benefits for teachers and 10 for students. Teachers and students agreed that MCUCS consistently provided a service that improved their performance. The most beneficial features of MCUCS were its high usage and user satisfaction. Between April 2010 and April 2012, the usage exceeded 878 300 events. Overall student satisfaction with MCUCS was 79.2%, and teacher satisfaction was 86%. We concluded that MCUCS provides a good model of an academic cloud computing service and a high qualified system.
Non-Hebbian properties of long-term potentiation enable high-capacity encoding of temporal sequences.

A hypothesis commonly found in biological and computational studies of synaptic plasticity embodies a version of the 1949 postulate of Hebb that coactivity of pre- and postsynaptic elements results in increased efficacy of their synaptic contacts. This general proposal presaged the identification of the first and still only known long-lasting synaptic plasticity mechanism, long-term potentiation (LTP). Yet the detailed physiology of LTP induction and expression differs in many specifics from Hebb's rule. Incorporation of these physiological LTP constraints into a simple non-Hebbian network model enabled development of "sequence detectors" that respond preferentially to the sequences on which they were trained. The network was found to have unexpected capacity (e.g., 50 x 10(6) random sequences in a network of 10(5) cells), which scales linearly with network size, thereby addressing the question of memory capacity in brain circuitry of realistic size.