Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Barycentric Coordinates in Space Vector PWM Computations

This paper proposes the use of barycentric coordinates in the development and implementation of space-vector pulse-width modulation (SVPWM) methods, especially for inverters with deformed space-vector diagrams. The proposed approach is capable of explicit calculation of vector duty cycles, independent of whether they assume ideal positions or are displaced due to the DC-link voltage imbalance. The use of barycentric coordinates also permits a well-defined and universal approach to the problem of identifying the region in which the reference vector is located. It completely avoids the use of angles, trigonometric functions, and inverse trigonometric functions and is chiefly based on matrix operations which are well suited for digital signal processor implementation. The proposed approach is exposed and validated for the special case of three-level neutral-point clamped (NPC) inverter controlled by a discontinuous space-vector PWM.
An International Survey-based Algorithm for the Pharmacologic Treatment of Irritability in Huntington's Disease

It is generally believed that treatments are available to manage irritability in Huntington’s disease (HD). However, lack of an evidence base prevents the establishment of treatment guidelines for this symptom. The research literature fails to address behavioral intervention strategies, drug selection, drug dosing, management of inadequate response to a single drug, or preferred drugs when additional behavioral symptoms comorbid to irritability are present. In an effort to inform clinical decision-making we surveyed an international group of experts to address these points. The experts consistently endorsed an antipsychotic drug (APD) as first choice for treatment of urgent and aggressive irritability behaviors. However, there was variation in practice patterns for treating less severe symptoms. Serotonin reuptake inhibitors (SSRIs) were first choice drug treatments by most respondents across all geographic regions. However, APDs were also endorsed as first choice for mild or moderate irritability, more frequently in Europe than in North America and Australia. Antiepileptic mood stabilizers (AEDs) were used by fewer respondents as first choice drug. Perceived efficacy for control of mild or moderate irritability was judged somewhat higher for APDs than SSRIs or AEDs. Benzodiazepines were not used as monotherapy, but frequently as an adjunctive drug in the setting of comorbid anxiety. Though many cited lack of experience with mirtazapine, others familiar with its use in HD chose it as an alternative monotherapy, or as adjunctive therapy if insomnia was a comorbid factor. This report presents survey results, reviews available irritability studies, and lastly proposes an algorithm for the treatment of irritability in HD derived from expert preferences obtained through this survey.
Improving performance of NN based electricity price forecasting using sensitivity analysis

This paper focuses on sensitivity analysis of neural network (NN) parameters in order to improve the performance of NN based short-term electricity price forecasting. Sensitivity analysis of NN parameters include back-propagation learning set (BP−set), learning rate (η), momentum (α) and NN learning days (dNN). Presented work is an extended version of previous work done by authors to integrate NN and similar days (SD) method for predicting day-ahead electricity prices. Similar days refer to similar price days, i.e., price data obtained from historical days. Euclidean norm with weighted factors is used for the selection of similar price days. Similar days method adopts the information of the days being similar to that of the forecast day. The similar days parameters, i.e., time framework of similar days (d = 45 days) and number of selected similar price days (N = 5) are kept constant for all the simulated cases. Forecasting performance is carried out by choosing a day from each season of the year 2006 randomly, and for which, the NN parameters for the base case are considered as BP−set = 500, η = 0.8, α = 0.1 and dNN = 45 days. Sensitivity analysis has been carried out by changing the value of BP−set (500, 1000, 1500); η (0.6, 0.8, 1.0, 1.2), α (0.1, 0.2, 0.3) and dNN (15, 30, 45 and 60 days). During the sensitivity analysis, the most favorable value of BP−set is first identified followed by that of η and α, and based on which the best value of dNN is determined. Sensitivity analysis results demonstrate that the best value of mean absolute percentage error (MAPE) is obtained when BP−set = 500, η = 0.8, α = 0.1 and dNN = 60 days for winter season, whereas for spring, summer and autumn, these values are 500, 0.6, 0.1 and 45 days, respectively. Results and discussions from real-world case study based on the PJM electricity market are presented.
Role of Glycosylation in Conformational Stability, Activity, Macromolecular Interaction and Immunogenicity of Recombinant Human Factor VIII

Factor VIII (FVIII) is a multi-domain glycoprotein that is an essential cofactor in the blood coagulation cascade. Its deficiency or dysfunction causes hemophilia A, a bleeding disorder. Replacement using exogenous recombinant human factor VIII (rFVIII) is the first line of therapy for hemophilia A. The role of glycosylation on the activity, stability, protein–lipid interaction, and immunogenicity of FVIII is not known. In order to investigate the role of glycosylation, a deglycosylated form of FVIII was generated by enzymatic cleavage of carbohydrate chains. The biochemical properties of fully glycosylated and completely deglycosylated forms of rFVIII (degly rFVIII) were compared using enzyme-linked immunosorbent assay, size exclusion chromatography, and clotting activity studies. The biological activity of degly FVIII decreased in comparison to the fully glycosylated protein. The ability of degly rFVIII to interact with phosphatidylserine containing membranes was partly impaired. Data suggested that glycosylation significantly influences the stability and the biologically relevant macromolecular interactions of FVIII. The effect of glycosylation on immunogenicity was investigated in a murine model of hemophilia A. Studies showed that deletion of glycosylation did not increase immunogenicity.
Analysis of Different Classifier Using Feature Extraction in Speaker Identification and Verification under Adverse Acoustic Condition for Different Scenario

Speech is one the easiest way of medium for human being to interact and exchange information in this universe. The language may be different and the way of speaking is different of each other because of their region and culture. The voice of human beings dependents on the different parameters like vocal cord diameter, pitch, formants (i.e. resonances of the vocal tract), shape and size of various articulators, vocal folds etc. In this paper, we try to analyze the performance of different mixture model like Hidden Markov model (HMM), Vector Quantization (VQ), Gaussian Mixture Model (GMM), Dynamic Time Wrapping (DTW), Euclidean Distance and Hybrid Hidden Markov Model for different feature extraction technique such as Mel Frequency Cepstral Coefficient (MFCC), Linear Predictive Coding (LPC) and Perceptual Linear Prediction (PLP). The adverse acoustic condition is important to consider as the factor like noise, jitter, reverberation etc. degrades the performance of recognition system to a great extent. So, we put your effort to analyze the performance of different feature extraction technique with their classifier under different scenario for real-time applications.
Bayesian Estimation of Species Richness from Quadrat Sampling Data in the Presence of Prior Information

Summary We consider the problem of estimating the number of species of an animal community. It is assumed that it is possible to draw up a list of species liable to be present in this community. Data are collected from quadrat sampling. Models considered in this article separate the assumptions related to the experimental protocol and those related to the spatial distribution of species in the quadrats. Our parameterization enables us to incorporate prior information on the presence, detectability, and spatial density of species. Moreover, we elaborate procedures to build the prior distributions on these parameters from information furnished by external data. A simulation study is carried out to examine the influence of different priors on the performances of our estimator. We illustrate our approach by estimating the number of nesting bird species in a forest.
Volume Rendering Using Hierarchical Spatial Correlation and Occlusion Sorting

Use of voxels for rendering objects in computer graphics is useful for complex geometries. However the hardware support for such rendering algorithms doesn’t exist. In this paper we present an algorithm, which is bound by the order of image and can support dense processing units as the hardware required is for simple arithmetic and logical operations. Moreover, the algorithm discussed in the paper describes an easy way using logical operations to perform occlusion sorting.
Neonatal heart rate prediction

Technological advances have caused a decrease in the number of infant deaths. Pre-term infants now have a substantially increased chance of survival. One of the mechanisms that is vital to saving the lives of these infants is continuous monitoring and early diagnosis. With continuous monitoring huge amounts of data are collected with so much information embedded in them. By using statistical analysis this information can be extracted and used to aid diagnosis and to understand development. In this study we have a large dataset containing over 180 pre-term infants whose heart rates were recorded over the length of their stay in the Neonatal Intensive Care Unit (NICU). We test two types of models, empirical bayesian and autoregressive moving average. We then attempt to predict future values. The autoregressive moving average model showed better results but required more computation.
Symplekin Specifies Mitotic Fidelity by Supporting Microtubule Dynamics

ABSTRACT Using a pangenomic loss-of-function screening strategy, we have previously identified 76 potent modulators of paclitaxel responsiveness in non-small-cell lung cancer. The top hit isolated from this screen, symplekin, is a well-established component of the mRNA polyadenylation machinery. Here, we performed a high-resolution phenotypic analysis to reveal the mechanistic underpinnings by which symplekin depletion collaborates with paclitaxel. We find that symplekin supports faithful mitosis by contributing to the formation of a bipolar spindle apparatus. Depletion of symplekin attenuates microtubule polymerization activity as well as expression of the critical microtubule polymerization protein CKAP5 (TOGp). Depletion of additional members of the polyadenylation complex induces similar phenotypes, suggesting that polyadenylation machinery is intimately coupled to microtubule function and thus mitotic spindle formation. Importantly, tumor cells depleted of symplekin display reduced fecundity, but the mitotic defects that we observe are not evident in immortalized cells. These results demonstrate a critical connection between the polyadenylation machinery and mitosis and suggest that tumor cells have an enhanced dependency on these components for spindle assembly.
Validation of the Rowland Universal Dementia Assessment Scale for Multicultural Screening in Danish Memory Clinics

Background/Aims: The Rowland Universal Dementia Assessment Scale (RUDAS) is a brief cognitive screening test that was developed to detect dementia in multicultural populations. The RUDAS has not previously been validated in multicultural populations outside of Australia. The aim of this study was to evaluate the diagnostic accuracy of the RUDAS in a multicultural sample of patients referred to Danish memory clinics. Methods: Data were collected from 137 consecutive patients (34 with an immigrant background) in three Danish memory clinics. All patients were given the RUDAS as a supplement to the standard diagnostic workup. Results: Diagnostic accuracy for the RUDAS [area under the curve (AUC) = 0.838] was similar to that of the Mini-Mental State Examination (MMSE; AUC = 0.840). The cutoff score with the best balance of sensitivity, specificity and accuracy was <24/30 for the RUDAS (sensitivity 0.69, specificity 0.80) and <25/30 for the MMSE (sensitivity 0.76, specificity 0.83). In contrast to the MMSE, regression analyses revealed that the RUDAS was unaffected by factors related to the patients' immigrant backgrounds. Conclusion: The RUDAS showed high specificity and proved to be less affected by cultural and linguistic factors than the MMSE, making it a particularly valuable tool when screening for cognitive impairment in elderly multicultural patient populations.
Alzheimer disease and cancer

Cross-sectional studies raise the possibility of protective relationships between, or a common mechanism underlying, the development of dementia of the Alzheimer type (DAT) and cancer. Using a prospective longitudinal design, the authors found that the risk of developing cancer is less among participants with DAT vs nondemented participants (p < 0.001) and that the risk of developing DAT may be less for participants with a history of cancer (p = 0.060).
Characterization of the Interactions within the mazEF Addiction Module of Escherichia coli*

In bacteria, programmed cell death is mediated through the unique genetic system called “addiction module,” which consists of a pair of genes encoding a stable toxin and an unstable antitoxin. The mazEF system is known as an addiction module located on the Escherichia coli chromosome. MazF is a stable toxin, and MazE is a labile antitoxin interacting with MazF to form a complex. MazE and the MazE-MazF complex can bind to the mazEF promoter region to regulate the mazEF expression. Here we show that the binding of purified (His)6MazE to the mazEF promoter DNA was enhanced by MazF. The site-directed mutations at the conserved amino acid residues in MazE N-terminal region (K7A, R8A, S12A, and R16A) disrupted the DNA binding ability of both (His)6MazE and the MazE-MazF-(His)6 complex, suggesting that MazE binds to the mazEF promoter DNA through the N-terminal domain. The ratio of MazE to MazF(His)6 in the MazE-MazF(His)6 complex is about 1:2. Because both MazE and MazF-(His)6 exist as dimers by themselves, the MazE-MazF-(His)6 complex (76.9 kDa) is predicted to consist of one MazE dimer and two MazF(His)6 dimers. The interaction between MazE and MazF was also characterized with the yeast two-hybrid system. It was found that the region from residues 38 to 75 of MazE was required for its binding to MazF. Site-directed mutagenesis at this region revealed that Leu55 and Leu58 play an important role in the MazE-MazF complex formation but not in MazE binding to the mazEF promoter DNA. The present results demonstrate that MazE is composed of two domains, the N-terminal DNA-binding domain and the C-terminal domain interacting with MazF.
Upward Spiral Between Positive Emotions and Vagal Tone How Positive Emotions Build Physical Health : Perceived Positive Social Connections Account for the

The mechanisms underlying the association between positive emotions and physical health remain a mystery. We hypothesize that an upward-spiral dynamic continually reinforces the tie between positive emotions and physical health and that this spiral is mediated by people’s perceptions of their positive social connections. We tested this overarching hypothesis in a longitudinal field experiment in which participants were randomly assigned to an intervention group that self-generated positive emotions via loving-kindness meditation or to a waiting-list control group. Participants in the intervention group increased in positive emotions relative to those in the control group, an effect moderated by baseline vagal tone, a proxy index of physical health. Increased positive emotions, in turn, produced increases in vagal tone, an effect mediated by increased perceptions of social connections. This experimental evidence identifies one mechanism—perceptions of social connections—through which positive emotions build physical health, indexed as vagal tone. Results suggest that positive emotions, positive social connections, and physical health influence one another in a self-sustaining upward-spiral dynamic.
Title : Genetic control of plasticity in root morphology and anatomy of rice in response 5 to water-deficit 6

34 Elucidating the genetic control of rooting behaviour under water-deficit stress is essential to 35 breed climate-robust rice cultivars. Using a diverse panel of 274 indica genotypes grown 36 under control and water-deficit conditions during vegetative growth, we phenotyped 35 traits, 37 mostly related to root morphology and anatomy, involving ~45,000 root scanning images and 38 nearly ~25,000 cross-sections from the root-shoot junction. Phenotypic plasticity of these 39 traits was quantified as the relative change in trait value under water-deficit compared to 40 control conditions. We then carried out a genome-wide association analysis on these traits 41 and their plasticity, using 45,608 high quality SNPs. One hundred four significant loci were 42 detected for these traits under control condition, 106 were detected under water-deficit stress, 43 and 76 were detected for trait plasticity. We predicted 296 (control), 284 (water-deficit stress) 44 and 233 (plasticity) a priori candidate genes within linkage disequilibrium (LD) blocks for 45 these loci. We identified key a priori candidate genes regulating root growth and 46 development and relevant alleles that upon validation can help improve rice adaptation to 47 water-deficit stress. 48
Bounds on Sparsity of One-Hidden-Layer Perceptron Networks

Limitations of one-hidden-layer (shallow) perceptron networks to sparsely represent multivariable functions is investigated. A concrete class of functions is described whose computation by shallow perceptron networks requires either large number of units or is unstable due to large output weights. The class is constructed using pseudo-noise sequences which have many features of random sequences but can be generated using special polynomials. Connections with the central paradox of coding theory are discussed.
DPH5, a methyltransferase gene required for diphthamide biosynthesis in Saccharomyces cerevisiae

A mutant of Saccharomyces cerevisiae defective in the S-adenosylmethionine (AdoMet)-dependent methyltransferase step of diphthamide biosynthesis was selected by intracellular expression of the F2 fragment of diphtheria toxin (DT) and shown to belong to complementation group DPH5. The DPH5 gene was cloned, sequenced, and found to encode a 300-residue protein with sequence similarity to bacterial AdoMet:uroporphyrinogen III methyltransferases, enzymes involved in cobalamin (vitamin B12) biosynthesis. Both DPH5 and AdoMet:uroporphyrinogen III methyltransferases lack sequence motifs commonly found in other methyltransferases and may represent a new family of AdoMet:methyltransferases. The DPH5 protein was produced in Escherichia coli and shown to be active in methylation of elongation factor 2 partially purified from the dph5 mutant. A null mutation of the chromosomal DPH5 gene did not affect cell viability, in agreement with other studies indicating that diphthamide is not required for cell survival. The dph5 null mutant survived expression of three enzymically attenuated DT fragments but was killed by expression of fully active DT fragment A. Consistent with these results, elongation factor 2 from the dph5 null mutant was found to have weak ADP-ribosyl acceptor activity, which was detectable only in the presence of high concentrations of fragment A.
Experimental evaluation of two OpenFlow controllers

Software-Defined Networking (SDN) can help simplify the management of today's complex networks and data centers. SDN provides a comprehensive view of the network, offering flexibility and easing automation. In SDN, traffic management functionality requires a high-performance and responsive controller. In this paper, we conduct an experimental evaluation of two open-source distributed OpenFlow controllers, namely ONOS and OpenDaylight. Specifically, we construct a testbed and use a standard benchmarking tool called Cbench to evaluate their performance. We benchmark the throughput, latency, and thread scalability of these two controllers in both physical and virtualized (OpenStack) environments. The experimental results show that ONOS provides higher throughput and lower latency than OpenDaylight, which suffers from performance problems on larger network models. Additional experiments demonstrate the effects of thread placement on the performance of these two controllers.
Characterization of Luminescent Down-Shifting Materials and Applications for PV Devices

Enhancement in the performance of Silicon solar cell can be achieved via luminescent down-shifting (LDS) of the incident light. Lumogen Violet dye and Tb(ant)3.2H2O complex were characterized to determine their suitability for inclusion in LDS layers. LDS layer characterization techniques are discussed and preliminary results from PV cell/LDS layer devices are presented.
One-Stationary Bistatic Side-Looking SAR Imaging Algorithm Based on Extended Keystone Transforms and Nonlinear Chirp Scaling

One-stationary bistatic side-looking synthetic aperture radar (OS-BiSAR) data are more challenging to process than the translational azimuth-invariant bistatic counterparts because 2-D spatial variances exist in OS-BiSAR. To overcome the problem, extended-keystone-transform (EKT)-nonlinear-chirp-scaling (NLCS) imaging algorithm is proposed in this letter. The key steps of the proposed algorithm are deducing the twice EKTs to deal with the 2-D spatial variance of range cell migrations and equalizing the 2-D spatial variant Doppler FM rates by using the associative NLCS. As a result, raw data of OS-BiSAR can be well focused even with the 2-D spatial variances. The simulations given at the end of this letter verify the effectiveness of this imaging algorithm.
Climate justice in the fossil fuel divestment movement: critical reflections on youth environmental organizing in Canada

The fossil fuel divestment movement is a directed-network campaign1 that strategically uses economic and ethical arguments to challenge the social license of the fossil fuel industry. Fossil fuel divestment campaigns have become an induction point for the youth climate movement in North America (Grady-Benson & Sarathy, 2015; Rowe et. al., 2016). The analytical and operational approaches to social change employed by the fossil fuel divestment movement are having a ripple effect on the political orientation of a new generation of activists and environmental leaders. This thesis explores concepts and practices of climate justice in the fossil fuel divestment movement on Canadian university campuses, as a flashpoint in the shifting terrain of environmentalism. The research uses qualitative methods to analyze three case study campaigns, as well as supplemental interviews from additional campaign members and national coordinating organizations like 350.org and the Canadian Youth Climate Coalition. This project contributes to a growing body of literature concerned with applied political theory (Rowe et. al., 2016; Schifeling & Hoffman, 2017) and the social impacts of fossil fuel divestment (Bratman et al, 2016; Grady-Benson & Sarathy, 2015; Mangat et al., 2018), providing new insight into the potential of divestment organizing to disrupt dominant narratives of mainstream environmentalism. Fossil fuel divestment organizers are articulating climate justice analysis that calls for transformative system change, including critiques of neoliberal capitalism that are predominantly grounded in climate justice approaches.