Miracle-dz/UniFAR-FTUs huggingface dataset:
Choice confidence in the webrooming purchase process: The impact of online positive reviews and the motivation to touch

The webrooming purchase process (i.e. searching for information online and then buying the product offline) is the most extended cross-channel shopping behaviour. With the aim of offering a better understanding of this behaviour, this research relies on information processing and uncertainty reduction theories to propose that consumers use the online information to make the offline purchase with a higher degree of confidence. We examine the effects of a previous online interaction with a product on the preferences and decision at the physical store, as well as on the outcomes of the experience. In this path to purchase, we analyse how positive online customer reviews, as a specific form of electronic word of mouth, help the consumer to improve their experience, given their great potential to reduce the consumer's uncertainty in a purchase situation. In addition, the role of the motivation to touch the product is examined. The results of two studies show that the combination of an online search and an offline purchase improves the consumers' purchase experience in pre-choice variables (i.e. purchase intentions), choice and post-choice variables (i.e. search-process satisfaction and choice confidence). Moreover, reading a positive online customer review influences choice confidence, and all the variables considered in the research when it is received at the physical store. Finally, the results stress the importance of the motivation to touch when studying multichannel shopping behaviour, given its direct and moderating effects on the webrooming purchase process. Implications for theory and practice are discussed. Copyright © 2016 John Wiley & Sons, Ltd.
Three-phase inverter with output LC filter using predictive control for UPS applications

The total harmonic distortion (THD) plays a major role in determining the quality of the inverter output waveform. The use of an inverter with an output LC filter allows for generation of sinusoidal voltages with low harmonic distortion. Several control schemes have been proposed for the control of three-phase inverter. This paper presents a new and simple control scheme using predictive control. The controller uses a discrete-time model of the system to predict the behavior of the output voltage for all possible switching states generated by the inverter. Then, a cost function is used as a criterion for selecting the switching state that will be applied during the next sampling interval. A simple estimation of the load-current can be calculated from filter-current and output voltage. Therefore, there is no need of internal current-control loops and no modulators; the gate-drive signals are generated directly by the control. The simulation results under linear and nonlinear loads are presented, using Matlab/Simulink tools, verifying the feasibility and good performance of the proposed control scheme. Finally, the effect of error in system parameters values are presented.
DeftNN: Addressing Bottlenecks for DNN Execution on GPUs via Synapse Vector Elimination and Near-compute Data Fission

Deep neural networks (DNNs) are key computational building blocks for emerging classes of web services that interact in real time with users via voice, images and video inputs. Although GPUs have gained popularity as a key accelerator platform for deep learning workloads, the increasing demand for DNN computation leaves a significant gap between the compute capabilities of GPU-enabled datacenters and the compute needed to service demand. The state-of-the-art techniques to improve DNN performance have significant limitations in bridging the gap on real systems. Current network pruning techniques remove computation, but the resulting networks map poorly to GPU architectures, yielding no performance benefit or even slowdowns. Meanwhile, current bandwidth optimization techniques focus on reducing off-chip band-width while overlooking on-chip bandwidth, a key DNN bottleneck. To address these limitations, this work introduces DeftNN, a GPU DNN execution framework that targets the key architectural bottlenecks of DNNs on GPUs to automatically and transparently improve execution performance. DeftNN is composed of two novel optimization techniques–(l) synapse vector elimination, a technique that identifies non-contributing synapses in the DNN and carefully transforms data and removes the computation and data movement of these synapses while fully utilizing the GPU to improve performance, and (2) near-compute data fission, a mechanism for scaling down the on-chip data movement requirements within DNN computations. Our evaluation of DeftNN spans 6 state-of-the-art DNNs. By applying both optimizations in concert, DeftNN is able to achieve an average speedup of $2.1\times$ on real GPU hardware. We also introduce a small additional hardware unit per GPU core to facilitate efficient data fission operations, increasing the speedup achieved by DeftNN to $2.6\times$CCS CONCEPTS• Computing methodologies $\rightarrow $Neural networks;• Computer systems organization $\rightarrow $Single instruction, multiple data; • General and reference $\rightarrow $Performance;
Predictive information: Status or alert information?

Previous research investigating the efficacy of predictive information for detecting and diagnosing aircraft system failures found that subjects like to have predictive information concerning when a parameter would reach an alert range. This research focused on where the predictive information should be located, and whether the information should be more closely associated with the parameter information or with the alert information. Each subject saw 3 forms of predictive information: (1) none, (2) a predictive alert message, and (3) predictive information on the status display. Generally, subjects performed better and preferred to have predictive information available although the difference between status and alert predictive information was minimal. Overall, for detection and recalling what happened, status predictive information is best; however for diagnosis, alert predictive information holds a slight edge.
Estimating the power of variance component linkage analysis in large pedigrees

Variance component linkage analysis is commonly used to map quantitative trait loci (QTLs) in general pedigrees. Large pedigrees are especially attractive for these studies because they provide greater power per genotyped individual than small pedigrees. We propose accurate and computationally efficient methods to calculate the analytical power of variance component linkage analysis that can accommodate large pedigrees. Our analytical power computation involves the approximation of the noncentrality parameter for the likelihood‐ratio test by its Taylor expansions. We develop efficient algorithms to compute the second and third moments of the identical by descent (IBD) sharing distribution and enable rapid computation of the Taylor expansions. Our algorithms take advantage of natural symmetries in pedigrees and can accurately analyze many large pedigrees in a few seconds. We verify the accuracy of our power calculation via simulation in pedigrees with 2–5 generations and 2–8 siblings per sibship. We apply this proposed analytical power calculation to 98 quantitative traits in a cohort study of 6,148 Sardinians in which the largest pedigree includes 625 phenotyped individuals. Simulations based on eight representative traits show that the difference between our analytical estimation of the expected LOD score and the average of simulated LOD scores is less than 0.05 (1.5%). Although our analytical calculations are for a fully informative marker locus, in the settings we examined power was similar to what could be attained with a single nucleotide polymorphism (SNP) mapping panel (with >1 SNP/cM). Our algorithms for power analysis together with polygenic analysis are implemented in a freely available computer program, POLY. Genet. Epidemiol. 2006. © 2006 Wiley‐Liss, Inc.
Vibration-based localisation of structural deterioration in frame-like civil engineering structures

With the existing trend of minimising material use in typical frame-like civil engineering structures, such as buildings, bridges, and offshore platforms, these structures will typically be subjected to substantial windinduced vibrations. Besides being a source of disturbance for the occupants, these vibrations can potentially lead to an evident risk of structural deterioration. In order to ensure the safety of the structures, it is thus paramount that the potential structural deterioration can be identified before it becomes critical from a structural integrity point of view. One way of facilitating such identification is by use of structural health monitoring (SHM) techniques, which enable remote, typically through pre-installed sensors, diagnosing of the structural health. In the present paper, it is examined whether a vibration-based SHM approach proposed by the authors—and previously applied successfully to other structural systems, for instance, wind turbines— can provide reliable damage localisation in frame-like structures. The performance of the method, which is based on statistical interrogation of changes in a surrogate of the transfer matrix, is tested in a Monte Carlo setting with a numerical steel frame model subjected to white noise excitation.
User Scheduling for the Broadcast Channel Using a Sum-Rate Threshold

In this paper, we present a novel user selection scheme for the broadcast channel (BC) using zero-forcing (ZF) precoding with optimal power control. Our scheme is based on a threshold that sets a minimum acceptable sum-rate. In order to design the threshold, we develop a new approximation of the sum-rate and derive simple design rules for the threshold with complexity constraints. We also extend the scheme so that users with differing quality of service (QoS) demands can be accommodated. Simulations show our scheme performs close to the exhaustive search algorithm, but with significantly reduced complexity. Moreover, it significantly reduces the outages compared to non-threshold based low complexity scheduling schemes.
Accurate Sub-Millimeter Servo-Pneumatic Tracking using Model Reference Adaptive Control (MRAC)

Abstract A model reference adaptive controller (MRAC) for compensating friction and payload uncertainties in a servo-pneumatic actuation system is presented in this paper. A friction model combining viscous and Coulomb friction is formulated within the framework of an adaptive controller. Due to the asymmetric nature of Coulomb friction in pneumatic piston actuators, a bi-directional Coulomb friction model is adopted. An update law is presented to estimate three friction parameters: linear viscous friction, Coulomb friction for positive velocity, and Coulomb friction for negative velocity. The force needed to both overcome the estimated friction forces and to supply the desired pressure-based actuation force to obtain a dynamic model reference position response is then used as the command to a sliding mode force controller. Both the force control loop and the adaptation law are Lyapunov stable by design. To ensure stable interaction between the sliding mode force controller and the adaptive controller, the bandwidth of the parameter update law is designed to be appreciably slower than the force tracking bandwidth. Experimental results are presented showing position tracking with and without an unknown payload disturbance. The steady-state positioning accuracy is shown to be less than 0.05 mm for a 60 mm step input with a rise time of around 200 ms. The tracking accuracy is shown to be within 0.7 mm for a 0.5 Hz sinusoidal position trajectory with an amplitude of 60 mm, and within 1.2 mm for a 1 Hz sinusoidal position trajectory with an amplitude of 60 mm. Both step and sinusoidal inputs are shown to reject a payload disturbance with minimal or no degradation in position or tracking accuracy. The control law generates smooth valve commands with a low amount of valve chatter.
Higher Education and Efficiency in Europe: A Comparative Analysis.

This paper analyses the efficiency of higher education in equalizing the feasible wages obtained for men and women in the labour market. To do that, It is estimated two stochastic frontiers. The first one measures the effect of higher education inside the group of men and women for six European countries. The results indicate that in Denmark, France and Italy men with higher education have higher gains in wages with respect men with the same characteristics with secondary education while for women appears the opposite result. In Germany and Spain, women with higher education experiment higher gains in terms of wages than obtain men. The second frontier shows the wages differentials obtained for women in each country by education level with respect men. Here, women with higher education experiment less wages differentials than do women with primary or secondary education. The data set is the ECHP (European Community Household Panel Data) from 1995 to 2001.
Compression of spatio-temporal networks via point-to-point process models

A point-to-point process describes a dynamic network where a set of edge events are observed, each of which is associated with a time of occurrence and two vertices lying in their state spaces. is study intends to investigate one application of such processes, using NYC Taxi and Limousine Commission dataset that reports taxi trips between two locations at a certain time. Here a pointto-point process is formed with edge events being taxi trips and the vertices adjacent to the edge events are pick-up and drop-o locations, described by latitude and longitude pairs. e intensity of an edge event can have a temporal dependence in addition to being dependent on a latent, spatially-coherent community structure for the vertices. To this end, we have developed a methodology that estimates a spatially smoothed community structure and localizes temporal changepoints for point-to-point processes. By applying this to our dataset, we can explore the spatio-temporal dynamics of the demand of taxi trips. More specically, with reasonable assumptions, the latent community structure is estimated by spectral partitioning based on a low-rank reconstruction of aggregated taxitrip network; and the temporal changepoint localization can be carried out by solving a matrix group fused LASSO program.
Molecular cloning and expression analysis of glucose-regulated protein 78 (GRP78) gene in silkworm Bombyx mori

GRP78 (78 kDa glucose-regulated protein), also known as BiP (immunoglobulin heavy-chain-binding protein), is an essential regulator of endoplasmic reticulum (ER) homeostasis because of its multiple functions in protein folding, ER calcium binding, and controlling of the activation of transmembrane ER stress sensors. In this report, we cloned the full-length cDNA of GRP78 from silkworm Bombyx mori (BmGRP78). It is 2645 bp, including an open reading frame (ORF) of 1977 bp encoding a polypeptide of 658 amino acids. We sequenced the ORF sequence from genomic DNA, and found only one intron (104 bp) existed in Bmgrp78 gene structure. The deduced amino acid sequence of Bmgrp78 carries the ER retention signal KDEL at its C-terminus and is highly homologous to GRP78 of Fenneropenaeus chinensis (83.59%) and Homo sapiens (80.27%). RT-PCR analysis shows that Bmgrp78 is ubiquitously expressed in tissues of silkworm. Heat shock over 35°C notably enhanced the expression of Bmgrp78 in head tissues. In response to starvation, the transcript level of Bmgrp78 in head tissues was 2.8-fold (at WS stage) and 3.2-fold (at SD1 stage) higher than the control level, but it remained stable in the midgut tissues. After silkworms were challenged by bacteria, the relative expression level of Bmgrp78 in midgut was up-regulated and reached maximal level at 24 hour after injection, and remained higher level than that of controls at about 48 hour post challenge. We infer that BmGRP78 may play important roles in chaperoning, protein folding and immune function of silkworm.
Pharmacotherapy and ROP: Going Back to the Basics

Abstract: Retinopathy of prematurity (ROP) is a leading cause of blindness in preterm infants around the world. Through the development of animal models and clinical trials our understanding of the pathophysiology of this disease and approach to therapy has evolved significantly since ROP was first described in the 1940s in the United States. The mainstay of treatment in ROP remains ablative laser therapy to the avascular retina but pharmacologic agents are being more and more commonly used with new targets for pharmacotherapy emerging. This paper summarizes our current understanding of the pathophysiology of ROP based on the data gleaned from animal models and discusses current approaches to pharmacotherapy.
Mice Lacking Catalase Develop Normally but Show Differential Sensitivity to Oxidant Tissue Injury*

Catalase plays a major role in cellular antioxidant defense by decomposing hydrogen peroxide, thereby preventing the generation of hydroxyl radical by the Fenton reaction. The degree of catalase deficiency in acatalasemic and hypocatalasemic mice varies from tissue to tissue. They therefore may not be suitable for studying the function of this enzyme in certain models of oxidant-mediated tissue injury. We sought to generate a new line of catalase null mice by the gene targeting technique. The mouse catalase (Cat or Cas1) gene was disrupted by replacing parts of intron 4 and exon 5 with a neomycin resistance cassette. Homozygous Cat knockout mice, which are completely deficient in catalase expression, develop normally and show no gross abnormalities. Slices of liver and lung and lenses from the knockout mice exhibited a retarded rate in decomposing extracellular hydrogen peroxide compared with those of wild-type mice. However, mice deficient in catalase were not more vulnerable to hyperoxia-induced lung injury; nor did their lenses show any increased susceptibility to oxidative stress generated by photochemical reaction, suggesting that the antioxidant function of catalase in these two models of oxidant injury is negligible. Further studies showed that cortical injury from physical impact caused a significant decrease in NAD-linked electron transfer activities and energy coupling capacities in brain mitochondria of Cat knockout mice but not wild-type mice. The observed decrease in efficiency of mitochondrial respiration may be a direct result of an increase in mitochondrion-associated calcium, which is secondary to the increased oxidative stress. These studies suggest that the role of catalase in antioxidant defense is dependent on the type of tissue and the model of oxidant-mediated tissue injury.
New lipase producing β-proteobacteria strains caldimonas sp. and tepidimonas sp. isolated from a Malaysian hot springs

Microbial lipolytic enzymes have attracted considerable attention owing to their biotechnological potential. In this study, thermophilic bacteria producing lipase were isolated from Bentong and Sungai Lembing hot springs, in Pahang, Malaysia. Out of 25 colonies isolated, 14 samples showed to produce clear zones surrounding the growth on tributyrin and trioelin agar plates. All 14 isolates showed Gram-negative bacteria with short rod morphology. PCR amplification of 16S ribosomal DNA gene showed that these isolates were clustered with subclass β-proteobacteria consisting of thermophilic bacteria that produce lipase. Phylogenetic analysis was carried out with the highly similar species and four isolates (SglA1, BtnC1, BtnC2 and BtnC3) are related to genus Caldimonas and 10 isolates (SglB1, SglB2, SglB3, SglB4, BtnB1, BtnB2 BtnD1, BtnD2, BtnD3 and BtnD4) belonged to genus Tepidimonas. These results indicated that novel lipase-producing thermophilic β-proteobacteria could be isolated from these hot springs
FIRING-RATE MODELS FOR NEURAL POPULATIONSL

I discuss the construction of models that describe the ring rates of excitatory and inhibitory neurons in biological neural networks. A model is presented that incorporates both slow linear and fast nonlinear inhibition. With the appropriate excitatory-to-excitatory couplings this model can act as an associative memory in which pattern recognition is signalled by resonant ring behavior. Stored memories are represented by xed points of the excitatory and fast inhibitory dynamics. After memory recovery, slow inhibition returns the system to the silent, resting state.
A minimal path searching approach for active shape model (ASM)-based segmentation of the lung

We are developing a minimal path searching method for active shape model (ASM)-based segmentation for detection of lung boundaries on digital radiographs. With the conventional ASM method, the position and shape parameters of the model points are iteratively refined and the target points are updated by the least Mahalanobis distance criterion. We propose an improved searching strategy that extends the searching points in a fan-shape region instead of along the normal direction. A minimal path (MP) deformable model is applied to drive the searching procedure. A statistical shape prior model is incorporated into the segmentation. In order to keep the smoothness of the shape, a smooth constraint is employed to the deformable model. To quantitatively assess the ASM-MP segmentation, we compare the automatic segmentation with manual segmentation for 72 lung digitized radiographs. The distance error between the ASM-MP and manual segmentation is 1.75 ± 0.33 pixels, while the error is 1.99 ± 0.45 pixels for the ASM. Our results demonstrate that our ASM-MP method can accurately segment the lung on digital radiographs.
PASQUAL: Parallel Techniques for Next Generation Genome Sequence Assembly

The study of genomes has been revolutionized by sequencing machines that output many short overlapping substrings (called reads). The task of sequence assembly in practice is to reconstruct long contiguous genome subsequences from the reads. With Next Generation Sequencing (NGS) technologies, assembly software needs to be more accurate, faster, and more memory-efficient due to the problem complexity and the size of the data sets. In this paper, we develop parallel algorithms and compressed data structures to address several computational challenges of NGS assembly. We demonstrate how commonly available multicore architectures can be efficiently utilized for sequence assembly. In all stages (indexing input strings, string graph construction and simplification, extraction of contiguous subsequences) of our software Pasqual, we use shared-memory parallelism to speed up the assembly process. In our experiments with data of up to 6.8 billion base pairs, we demonstrate that Pasqual generally delivers the best tradeoff between speed, memory consumption, and solution quality. On synthetic and real data sets Pasqual scales well on our test machine with 40 CPU cores with increasing number of threads. Given enough cores, Pasqual is fastest in our comparison.