Miracle-dz/UniFAR-FTUs huggingface dataset:
Grid-Fault Control Scheme for Three-Phase Photovoltaic Inverters With Adjustable Power Quality Characteristics

The power quality of a three-phase photovoltaic (PV) inverter drastically deteriorates in the presence of grid faults with unbalanced voltages. A ripple in the injected power and an increase in the current harmonic distortion are the main noticeable adverse effects produced by this abnormal grid situation. Several grid-fault control schemes are nowadays available for operating under unbalanced grid voltage. These control schemes usually have extreme power quality characteristics. Some of them have been conceived to completely avoid power ripple during unbalanced voltage sags, but at an expense of high current harmonic distortion. With other schemes, the harmonic distortion is totally eliminated but at an expense of high ripple in the injected power. This paper further explores the performance of PV inverters under unbalanced voltage sags. It has three theoretical contributions: 1) a generalized control scheme, which includes the aforementioned grid-fault controllers as particular cases; 2) a control strategy based on the use of continuous values for the control parameters. This original approach gives adjustable power quality characteristics that cannot be achieved with the previous control schemes; 3) three different control algorithms for calculating the continuous values of the control parameters. These contributions are experimentally validated with a digital signal processor-based laboratory prototype.
Managing contamination delay to improve Timing Speculation architectures

Timing Speculation (TS) is a widely known method for realizing better-than-worst-case systems. Aggressive clocking, realizable by TS, enable systems to operate beyond specified safe frequency limits to effectively exploit the data dependent circuit delay. However, the range of aggressive clocking for performance enhancement under TS is restricted by short paths. In this paper, we show that increasing the lengths of short paths of the circuit increases the effectiveness of TS, leading to performance improvement. Also, we propose an algorithm to efficiently add delay buffers to selected short paths while keeping down the area penalty. We present our algorithm results for ISCAS-85 suite and show that it is possible to increase the circuit contamination delay by up to 30% without affecting the propagation delay. We also explore the possibility of increasing short path delays further by relaxing the constraint on propagation delay and analyze the performance impact.
Ischemic emergency?: endothelial cells have their own "adrenaline shot" at hand.

See related article, pp 129–136 Endothelial cells (ECs) constitute the cell layer covering the luminal surface of all of the blood vessels throughout the entire cardiovascular system and, although initially thought of as inert, purely structural components of vessel walls, are now known to play prominent roles in many facets of vascular physiology.1 Among these are angiogenesis and neoangiogenesis, phenomena that rely on EC migration and proliferation, inflammation, immune responses to injury and tissue healing, blood coagulation, regulation of vascular smooth muscle cell proliferation, atherosclerosis, and atherotic plaque rupture, and, last but not least, ECs are critical regulators of vascular tone via release of a vast plethora of vasoactive agents that promote either constriction or relaxation of the arterial wall smooth muscle, thus exerting important control on systemic blood pressure.1,2 EC function is, in turn, fine tuned by several hormones, whose receptors ECs express on their membranes. Among these hormones are the catecholamines (CAs), which have been known to cause vasoconstriction via α1- (and α2-) adrenergic receptors (ARs) and vasodilation via β2ARs present in vascular smooth muscle.3 However, ARs are also present in EC membranes, per se, and presumably respond to circulating norepinephrine (NE) and epinephrine (Epi), because ECs, unlike vascular smooth muscle, are devoid of sympathetic innervation.1 The circulating CAs, dopamine, NE, and Epi, are synthesized from the amino acid precursor l-tyrosine. Tyrosine hydroxylase catalyzes the first and rate-limiting step in CA biosynthesis, converting l-tyrosine to l-dihydroxyphenylalanine, which, in turn, produces dopamine via decarboxylation by aromatic l-amino acid decarboxylase. In (nor)adrenergic neurons and in the adrenal medulla, …
Solute chemistry of snowmelt and runoff in an Alpine Basin, Sierra Nevada

Snowpack runoff contributions to the hydrochemistry of an alpine catchment in the Sierra Nevada were evaluated in 1986 and 1987 by analyzing snowpack, meltwater, and stream water samples for major inorganic ions, conductance, acid neutralizing capacity (ANC), and silicate. An ionic pulse in meltwater with initial concentrations twofold to twelvefold greater than the snowpack average, varying with site and with ion, was measured in lysimeters placed at the base of the snowpack. Maximum concentrations of ions in meltwater were inversely related to the rate of snowmelt; melt-freeze cycles increased the concentration of solutes in meltwater. Hydrogen concentration in meltwater was buffered by ANC produced in part by the dissolution of particulates. The anionic pulse in meltwater was observed in stream waters during the first 30 days of snowpack runoff, with NO3− concentrations in stream waters at this time about 1.6-fold greater than the average NO3− concentration for the time period of snowpack runoff, Cl− about 1.5-fold greater and SO42− about 1.3-fold greater. Maximum H+ concentration during snowpack runoff (increase of 170% over winter concentrations) occurred near maximum discharge. ANC minima occurred at maximum discharge as a result of dilution, with a decrease from winter concentrations of 70% in 1986 and 60% in 1987. Interactions between snowpack runoff and soils were important to the chemistry of stream water. Eighty to ninety percent of the H+ stored in the snowpack was consumed before it reached the base of the catchment. Soils were a sink for NH4+ from snowpack meltwater, with less than 1% of the NH4+ released from snowpack storage exported from the basin as NH4+. Sulfate concentrations in stream waters were less variable than NO3− or Cl− concentrations; sorption processes in soils were a likely cause for the regulation of SO42− concentrations.
Application of a fuzzy neural network combined with a chaos genetic algorithm and simulated annealing to short-term load forecasting

A fuzzy neural network combined with a chaos-search genetic algorithm (CGA) and simulated annealing (SA), hereafter called the FCS method, or simply the FCS, applied to short-term power-system load forecasting as a sample test is proposed in this paper. A fuzzy hyperrectangular composite neural network (FHCNN) is adopted for the initial load forecasting. An integrated CGA and fuzzy system (CGF) and SA is then used to find the optimal FHCNN parameters instead of the ones with the back propagation method. The CGF method will generate a set of parameters for a feasible solution. The CGF method holds good global search capability but poor local search ability. On the contrary, the SA method possesses a good local optimal search capability. We hence propose in this paper to combine the two methods to exploit their advantages and, furthermore, to eliminate the known downside of the traditional artificial neural network. The proposed FCS is next applied to power-system load forecasting as a sample test, which demonstrates an encouraging degree of accuracy superior to other commonly used forecasting methods available. The forecasting results are tabulated and partially converted into bar charts for evaluation and clear comparisons.
Computationals models of bilingual comprehension

This chapter reviews current computational models of bilingual word recognition. It begins with a discussion of the role of computational modeling in advancing psychological theories, highlighting the way in which the choice of modeling paradigm can influence the type of empirical phenomena to which the model is applied. The chapter then introduces two principal types of connectionist model that have been employed in the bilingual domain, localist and distributed architectures. Two main sections then assess each of these approaches. Localist models are predominantly addressed towards explaining the processing structures in the adult bilingual. Here we evaluate several models including BIA, BIMOLA, and SOPHIA. Distributed models are predominantly addressed towards explaining issues of language acquisition and language loss. This section includes discussion of BSN, BSRN, and SOMBIP. Overall, the aim of current computational models is to account for the circumstances under which the bilingual’s two languages appear to interfere with each other during recognition (for better or worse) and those circumstances under which the languages appear to operate independently. Based on the range of models available in the unilingual literature, our conclusion is that computational models have great potential in advancing our understanding of the principal issues in bilingualism, but that thus far only a few of these models have seen extension to the bilingual domain.
Quadrangulations and 2-colorations

Any metric quadrangulation (made by segments of straight line) of a point set in the plane determines a 2-coloration of the set, such that edges of the quadrangulation can only join points with different colors. In this work we focus in 2-colorations and study whether they admit a quadrangulation or not, and whether, given two quadrangulations of the same 2-coloration, it is possible to carry one into the other using some local operations, called diagonal slides and diagonal rotation. Although the answer is negative in general, we can show a very wide family of 2-colorations, called onions 2-coloration, that are quadrangulable and which graph of quadrangulations is always connected.
Ezrin-Dependent Promotion of Glioma Cell Clonogenicity, Motility, and Invasion Mediated by BCL-2 and Transforming Growth Factor-β2

Ezrin belongs to the ezrin–radixin–moesin family proteins, which cross-link actin cytoskeleton and plasma membrane. Malignant glioma cells are paradigmatic for their strong migratory and invasive properties. Here, we report that the expression of dominant-negative ezrins inhibits clonogenicity, migration, and invasiveness of human malignant glioma cells. Furthermore, dominant-negative ezrins block hepatocyte growth factor (HGF)-mediated stimulation of clonogenicity and migration, without altering HGF-induced protein kinase B/Akt and focal adhesion kinase phosphorylation. Glioma cells expressing dominant-negative ezrins exhibit a shift of the BCL-2/BAX rheostat toward apoptosis, reduced αVβ3integrin expression and reduced matrix metalloproteinase (MMP) expression and activity. These changes are associated with a dramatic loss of transforming growth factor β2(TGF-β2) release. Exogenous supplementation of TGF-β2 overcomes the inhibitory effects of dominant-negative ezrins on migration and clonogenicity. A neutralizing TGF-β2 antibody mimics the effects of dominant-negative ezrins on clonogenicity and migration. Exogenous HGF markedly induces TGF-β2 protein levels, and a neutralizing TGF-β2 antibody abolishes the HGF-mediated increase in glioma cell motility. Finally, TGF-β2 does not modulate BCL-2 or BAX expression, but BCL-2 gene transfer increases the levels of latent and active TGF-β2. Intracranial xenografts of U87MG glioma cells transfected with the dominant-negative ezrins in athymic mice grow to significantly smaller volumes, and the median survival of these mice is 50 d compared with 28 d in the control group. These data define a novel pathway for HGF-induced glioma cell migration and invasion, which requires ezrin, changes in the BCL-2/BAX rheostat, and the induction of TGF-β2expression in vitro, and underscore the important role of HGF signaling in vivo.
The Influence of Language Production, Comprehension, and Pragmatic Judgment on Prosocial Behavior in Children with Language Impairment

The Influence of Language Production, Comprehension, and Pragmatic Judgment on Prosocial Behavior in Children with Language Impairment Nicole Yvette Weber Department of Communication Disorders Master of Science The purpose of this study was to examine the relationship between language skills and prosocial behavior in 37 children with language impairment (LI) and 37 typically developing peers matched for age (ranging from 6;11 to 11;1 years). The influence of gender on this relationship was also considered. Three different subtests of the Comprehensive Assessment of Spoken Language (Carrow-Woolfolk, 1999) were used to evaluate language ability in the areas of language comprehension, language production and pragmatic judgment skills. The Teacher Behavior Rating Scale (C. H. Hart & Robinson, 1996) was used to evaluate prosocial behavior. The current study replicated previous research by documenting that children with LI demonstrate significantly poorer prosocial behavior skills than do typically developing peers. Children with LI also performed significantly more poorly on the three language subtests of paragraph comprehension, syntactic construction, and pragmatic judgment skills compared to typical peers. No significant gender differences were noted on any of the comparisons. Multiple regression analyses were used to evaluate the relationship between the three language subtests and prosocial behavior in the group with LI compared to the typical group. Results for both groups indicated that paragraph comprehension, syntactic construction, and pragmatic judgment skills were not significant predictors of prosocial behavior when used in combination or independently. Results suggest that language alone cannot predict prosocial behavior in children with LI or typically developing children.
High Cross-Regulation Multioutput $LLC$ Series Resonant Converter With Magamp Postregulator

A magnetic amplifier (Magamp) postregulator using a time-sharing control strategy is proposed when using a multioutput LLC series resonant converter. The operating principles of the proposed converter and the Magamp postregulator are analyzed in detail. Furthermore, the design criterion for the Magamp core is presented, and the dead-time problem of the Magamp postregulator is analyzed. Compared with a flyback converter, the dead-time impact in the LLC structure is much better for two main reasons. The first one is that there is no reverse-recovery resetting effect for the Magamp postregulator in an LLC topology, and the second is that, when the same dead time is applied in both converters, the effect is better by using an LLC topology than a flyback topology. Finally, an experimental prototype of 310-V input and 24-V/3-A and 18-V/2-A outputs was built and tested to verify the zero-voltage-switching (zero-current-switching) operation and the high cross-regulating ratio. The experimental results prove that the dead-time impact over a Magamp in an LLC converter is much better than that when using a flyback converter, since a high cross-regulating ratio was easily achieved without using complicate resetting methods or large dead load.
Cancer Diagnosis with QUIRE: QUadratic Interactions among infoRmative fEatures

Motivation: Responsible for many complex human diseases including cancers, disrupted or abnormal gene interactions can be identified through their expression changes correlating with the progression of a disease. However, the examination of all possible combinatorial interactions between gene features in a genome-wide case-control study is computationally infeasible as the search space is exponential in nature. Results: In this paper, we propose a novel computational approach, QUIRE, to identify discriminative complex interactions among informative gene features for cancer diagnosis. QUIRE works in two stages, where it first identifies functionally relevant feature groups for the disease and, then explores the search space capturing the combinatorial relationships among the genes from the selected informative groups. Using QUIRE, we explore the differential patterns and the interactions among informative gene features in three different types of cancers, Renal Cell Carcinoma(RCC), Ovarian Cancer(OVC) and Colorectal Cancer (CRC). Our experimental results show that QUIRE identifies gene-gene interactions that can better identify the different cancer stages of samples and can predict CRC recurrence and death from CRC more successfully, as compared to other state-of-the-art feature selection methods. A literature survey shows that many of the interactions identified by QUIRE play important roles in the development of cancer.
Service-Oriented Maintainability Modeling and Analysis for a Cloud Computing

We focus on a cloud computing environment by using open source software such as OpenStack and Eucalyptus because of the unification management of data, and low cost. In this paper, we propose a new approach to software reliability assessment based on a jump diffusion model based on the stochastic differential equations in order to consider the interesting aspect of the numbers of components and users. In particular, we derive the confidence limits of jump range for the proposed jump diffusion model. Also, actual software fault-count data are analyzed in order to show numerical examples of software reliability assessment. Moreover, this paper shows that the proposed method of reliability analysis can assist quality improvement for the cloud computing.
Association Between Anxiety and Depression With Dialysis Adequacy in Patients on Maintenance Hemodialysis

Background Depression and anxiety are common among hemodialysis patients and affect their treatment outcomes. Dialysis adequacy also affects the hemodialysis patients’ survival rates. Objectives This study aimed to evaluate the correlation between anxiety and depression with dialysis adequacy. Patients and Methods In this cross-sectional study, 127 hemodialysis patients (73 males, 57.5%) with the mean age of 55.7 ± 17.5 were enrolled. Demographic and recent laboratory data were collected using self-administered questionnaires and by reviewing medical records. Dialysis adequacy measures including the Kt/V and urea reduction rate (URR) were calculated using standard formulas. The Hospital Anxiety and Depression Scale (HADS) was used to diagnose depression and anxiety. Independent sample t-test and Chi-square test were used to compare the values in different groups. Pearson correlations and linear regression were used to analyze the data using SPSS version 21. Results The prevalence rates of depression and anxiety (HADS score ≥ 8) were 31.5% and 41.7%, respectively. The prevalence of both conditions was significantly higher in women than in men (P < 0.05). The mean values of Kt/V and URR were not different in patients with and without depression or anxiety. The anxiety scores were correlated with age (P = 0.007, r = -0.24) and parathyroid hormone (P = 0.04, r = -0.19). Younger age and lower parathyroid hormone were the only factors that predicted higher scores of anxiety in linear regression. The Kt/V or URR were not significantly correlated with depression and anxiety scores. Conclusions Depression and anxiety are common among hemodialysis patients. There are no statistically significant correlation between depression and anxiety and dialysis adequacy.
Enhancement of human computer interaction with facial electromyographic sensors

In this paper we describe a way to enhance human computer interaction using facial Electromyographic (EMG) sensors. Indeed, to know the emotional state of the user enables adaptable interaction specific to the mood of the user. This way, Human Computer Interaction (HCI) will gain in ergonomics and ecological validity. While expressions recognition systems based on video need exaggerated facial expressions to reach high recognition rates, the technique we developed using electrophysiological data enables faster detection of facial expressions and even in the presence of subtle movements. Features from 8 EMG sensors located around the face were extracted. Gaussian models for six basic facial expressions - anger, surprise, disgust, happiness, sadness and neutral - were learnt from these features and provide a mean recognition rate of 92%. Finally, a prototype of one possible application of this system was developed wherein the output of the recognizer was sent to the expressions module of a 3D avatar that then mimicked the expression.
A precise ΔΣ-based Digitally Controlled Oscillator (DCO) for all-digital PLL

A Digitally Controlled Oscillator (DCO) for the frequency band of 1700-1900 MHz is presented. This architecture achieves a frequency resolution less than 1-kHz. The DCO is a part of an All-Digital Phase-Locked Loop (ADPLL) for GSM-1800 and GSM-900 applications implemented in a 0.18 μm CMOS process. In this architecture an 18-bit delta sigma digital to analog converter and a voltage controlled LC oscillator is used. The used ΔΣ DAC is a fourth order structure with 450 MHz sampling frequency, Over Sampling Ratio (OSR) =128 and 118 dB SNR. The bandwidth of this ΔΣ DAC is about 1.8 MHz. The phase noise of the presented DCO at 500 kHz offset frequency is -115 dBc/Hz.
Adapting strategy choices to situational factors: The effect of time pressure on children's numerosity judgement strategies

The present study investigated the effect of time pressure on 6th graders' (11-12 years old) numerosity judgement strategies under three different time pressure conditions. Time pressure was manipulated by varying the maximum presentation time of the stimuli on three different levels: 5 s in the severe, 10 s in the moderate, and 20 s in the low time pressure condition. Analysis of the results in terms of the theoretical framework of Lemaire and Siegler (1995) revealed an effect of increasing time pressure on several parameters of strategy use such as participants' strategy repertoire, relative frequency of strategy use and efficiency of strategy execution. Unexpectedly, we did not observe a significant decline in the adaptiveness of strategy choices as a function of item characteristics. Taken as a whole, these results indicate that children are already at a young age able to adapt their strategy use to the external demands of a task.
The Effect of Stimulus Modality on Signal Detection: Implications for Assessing the Safety of In-Vehicle Technology

Objective: This study examined the effect of two in-vehicle information systems (IVIS) on signal detection in the visual, auditory, and tactile modalities; established whether the detrimental effects of an IVIS on driving could be quantified by these detection tasks; and examined the effect of stimulus modality on signal detection. Background: The peripheral detection task has been used widely for assessing the effects of an IVIS on driving. However, performance on this task relies on drivers' ability to see a series of LEDs, which can be problematic in field tests (e.g., on sunny days). Method: Participants responded to one of three detection tasks during a simulated driving experiment. The effect of IVIS interaction on these detection tasks was also measured. Reduced performance in the detection tasks was assumed to indicate a decline in drivers' ability to handle sudden events in the driving task. Results: Response time to all detection tasks increased by around 200 ms when drivers performed the IVIS tasks, as compared with baseline driving. Analyses of variance and comparison of effect sizes showed the effects of these two IVISs to be the same across the three detection tasks. Conclusion: These detection tasks are useful for quantifying the safety of an IVIS during driving. The absence of a difference in signal detection by modality suggests that performance on these tasks relies on general attentional resources and is not modality specific. Application: The signal detection tasks employed here should be further investigated for their suitability in assessing the safety of in-vehicle systems.