Miracle-dz/UniFAR-FTUs huggingface dataset:
Reduction of Cogging Torque in Permanent Magnet Flux-Switching Machines

Permanent magnet flux-switching machine (PMFSM) is a relatively new structure. Available literatures mainly focused on its general design procedure and performance analysis. In this paper, Finite Element Method (FEM) is taken to ana-lyze various design techniques to reduce the cogging torque in a prototype 12/10-pole PMFSM.
Steady-state analysis of biased filtered-x algorithms for adaptive room equalization

This paper provides an analysis of the steady-state behavior of two biased adaptive algorithms recently introduced for listening room compensation, the biased filtered-x normalized least mean squares (Fx-BNLMS) and the biased filtered-x improved proportionate NLMS (Fx-BIPNLMS). We give theoretical results that show that the biased algorithms can outperform the unbiased ones in terms of the mean square error, especially in low signal-to-noise ratio (SNR) scenarios. Moreover, for impulse responses exhibiting high sparse-ness, the improved proportionate algorithms achieve faster convergence than the standard NLMS. Thereby, the advantages of the Fx-BIPNLMS algorithm are justified theoretically in terms of the excess mean square error. Simulation results show that there is a relatively good match between theory and practice, especially for low μ values.
Temporary Work in Tuscany: a Multinomial Nested Logit Analysis

In this paper, distinguishing between the choice of the worker and the choice of the firm, we provide a probabilistic evaluation of the transition from temporary to permanent employment in a regional context. Estimating a Multinomial Nested Logit Model, we found that the transition to a permanent job is far from certain, especially for women and older workers.
An efficient data circulation and discovery scheme in VANETs using public transportation systems

Due to recent development in wireless communication networks, researches in Vehicular Ad-hoc Networks (VANETs) have been getting much attention on information sharing and service discovery. However, due to the ever-shifting mobility of vehicle topology, vehicles moving in non-fixed routes may not find suitable next-hop vehicles to pass the data. This paper proposes schemes to effectively circulate and discover service information with the aid of public transportation systems. Bus routes can be used to create a backbone structure and data can be posted and circulated on the structure to avoid the broadcast storm problem. Moreover, by adopting the proposed architecture, the required data can be effectively disseminated and discovered through the traffic infrastructure and mobile vehicles. The experiment results demonstrate that our scheme outperforms other schemes in terms of packet delivery ratio and end-to-end delay. Moreover, the overhead of our scheme outperforms other scheme with an increasing of number of service requests.
Immunization with Pre-Erythrocytic Antigen CelTOS from Plasmodium falciparum Elicits Cross-Species Protection against Heterologous Challenge with Plasmodium berghei

Background The Plasmodium protein Cell-traversal protein for ookinetes and sporozoites (CelTOS) plays an important role in cell traversal of host cells in both, mosquito and vertebrates, and is required for successful malaria infections. CelTOS is highly conserved among the Plasmodium species, suggesting an important functional role across all species. Therefore, targeting the immune response to this highly conserved protein and thus potentially interfering with its biological function may result in protection against infection even by heterologous species of Plasmodium. Methodology/Principal Findings To test this hypothesis, we developed a recombinant codon-harmonized P. falciparum CelTOS protein that can be produced to high yields in the E. coli expression system. Inbred Balb/c and outbred CD-1 mice were immunized with various doses of the recombinant protein adjuvanted with Montanide ISA 720 and characterized using in vitro and in vivo analyses. Conclusions/Significance Immunization with PfCelTOS resulted in potent humoral and cellular immune responses and most importantly induced sterile protection against a heterologous challenge with P. berghei sporozoites in a proportion of both inbred and outbred mice. The biological activity of CelTOS-specific antibodies against the malaria parasite is likely linked to the impairment of sporozoite motility and hepatocyte infectivity. The results underscore the potential of this antigen as a pre-erythrocytic vaccine candidate and demonstrate for the first time a malaria vaccine that is cross-protective between species.
Maternal high-fat diet consumption impairs exercise performance in offspring

The aim of the present study was to scrutinise the influence of maternal high-fat diet (mHFD) consumption during gestation and lactation on exercise performance and energy metabolism in male mouse offspring. Female C3H/HeJ mice were fed either a semi-synthetic high-fat diet (HFD; 40 % energy from fat) or a low-fat diet (LFD; 10 % energy from fat) throughout gestation and lactation. After weaning, male offspring of both groups received the LFD. At the age of 7·5 weeks half of the maternal LFD (n 20) and the mHFD (n 21) groups were given access to a running wheel for 28 d as a voluntary exercise training opportunity. We show that mHFD consumption led to a significantly reduced exercise performance (P < 0·05) and training efficiency (P < 0·05) in male offspring. There were no effects of maternal diet on offspring body weight. Lipid and glucose metabolism was disturbed in mHFD offspring, with altered regulation of cluster of differentiation 36 (CD36) (P < 0·001), fatty acid synthase (P < 0·05) and GLUT1 (P < 0·05) gene expression in skeletal muscle. In conclusion, maternal consumption of a HFD is linked to decreased exercise performance and training efficiency in the offspring. We speculate that this may be due to insufficient muscle energy supply during prolonged exercise training. Further, this compromised exercise performance might increase the risk of obesity development in adult life.
W.A. Lewis, the Plantation School and Dependency: An Interpretation

This paper examines differences and similarities in the approach to economic development of the Plantation School of Caribbean economists and of W.A. Lewis by locating them within their respective theoretical frameworks. By tracing the evolution of Lewis's thinking in three stages from Caribbean industrialisation to the dual economy and then to trade and development, it identified a change in emphasis in Lewis's later work that brought him closer to 'dependency' explanations of underdevelopment, of which the Plantation School was an expression. It draws attention Lewis's own perspective on the dependency thesis and the related thesis that imperialism is the cause underdevelopment. The paper goes on to review the Plantation School's critiques of Lewis's industrialisation model for the Caribbean and its proposals for an alternative theoretical approach in the form of models of Plantation Economy, and compares this to Lewis's analytical framework to show the differences and similarities. The final section discusses the contemporary relevance of the comparison of the approaches of Lewis and the Plantation School.
An image retrieval approach with relevance feedback

An image retrieval approach combined with relevance feedback is proposed. A set of blobs that are generated from image features using clustering can be used to describe an image. Given a training set of images with annotations, we apply probabilistic models to predict the probability of a blob in image according to the query words. For improving the initial query results, we apply a relevance feedback mechanism to bridge the semantic gap, leading to the improved image retrieval accuracy. A support vector machine classifier can be learned from training data of relevance images and irrelevance images labeled by users. Experimental results show that the proposed approach obtains higher retrieval accuracy than a commonly used approach.
Incremental Weight Elicitation for Multiobjective State Space Search

This paper proposes incremental preference elicitation methods for multiobjective state space search. Our approach consists in integrating weight elicitation and search to determine, in a vector-valued state-space graph, a solution path that best fits the Decision Maker's preferences. We first assume that the objective weights are imprecisely known and propose a state space search procedure to determine the set of possibly optimal solutions. Then, we introduce incremental elicitation strategies during the search that use queries to progressively reduce the set of admissible weights until a nearly-optimal path can be identified. The validity of our algorithms is established and numerical tests are provided to test their efficiency both in terms of number of queries and solution times.
Unit Commitment on the Cloud

The advent of High Performance Computing (HPC) has provided the computational capacity required for power system operators (SO) to obtain solutions in the least time to highly-complex applications, i.e., Unit Commitment (UC). The UC problem, which attempts to schedule the least-cost combination of generating units to meet the load, is increasing in complexity and problem size due to deployments of renewable resources and smart grid technologies. The current approach to solving the UC problem consists of in-house HPC infrastructures, which experience issues at scale, and demands high maintenance and capital expenditures. On the other hand, cloud computing is an ideal substitute due to its powerful computational capacity, rapid scalability, and high cost-effectiveness. In this work, the benefits and challenges of outsourcing the UC application to the cloud are explored. A quantitative analysis of the computational performance gain is explored for a large-scale UC problem solved on the cloud and compared to traditional in-house HPC infrastructure. The results show substantial reduction in solve time when outsourced to the cloud.
Feedback Loop Design and Analysis for Iterative Localized Image Deblurring

—This paper considers image deblurring algorithm based on model-based iterative update of the image estimate. The update has two principal terms: (i) integral feedback of blurred image prediction error and (ii) feedback of the past deblurred image estimate. The two feedback terms are computed by applying two FIR operators. The paper shows how these feedback update operators can de designed with a given degree of localization to provide an optimal tradeoff between design objectives such as convergence speed, noise amplification, quality of image restoration, and robustness. The solution to the feedback operator design problem is obtained by Linear Programming optimization. A parallelized implementation of the update algorithm using localized feedback operators is scalable to very large image sizes.
Methods for monitoring influenza surveillance data.

BACKGROUND A variety of Serfling-type statistical algorithms requiring long series of historical data, exclusively from temperate climate zones, have been proposed for automated monitoring of influenza sentinel surveillance data. We evaluated three alternative statistical approaches where alert thresholds are based on recent data in both temperate and subtropical regions. METHODS We compared time series, regression, and cumulative sum (CUSUM) models on empirical data from Hong Kong and the US using a composite index (range = 0-1) consisting of the key outcomes of sensitivity, specificity, and time to detection (lag). The index was calculated based on alarms generated within the first 2 or 4 weeks of the peak season. RESULTS We found that the time series model was optimal in the Hong Kong setting, while both the time series and CUSUM models worked equally well on US data. For alarms generated within the first 2 weeks (4 weeks) of the peak season in Hong Kong, the maximum values of the index were: time series 0.77 (0.86); regression 0.75 (0.82); CUSUM 0.56 (0.75). In the US data the maximum values of the index were: time series 0.81 (0.95); regression 0.81 (0.91); CUSUM 0.90 (0.94). CONCLUSIONS Automated influenza surveillance methods based on short-term data, including time series and CUSUM models, can generate sensitive, specific, and timely alerts, and can offer a useful alternative to Serfling-like methods that rely on long-term, historically based thresholds.
Novel FFT Techniques for Sequence Analysis

Algorithms for computing Fast Fourier Transforms (FFTs) have been employed in the past for sequence analysis. However these techniques had to perform a large number of FFT computations. In this paper we present algorithms for sequence analysis that reduce the number of FFT computations drastically. We also provide experimental evaluation of the new algorithms. The speedups obtained are impressive.
Weight loss practices of college wrestlers.

PURPOSE The purpose of this investigation was to examine the weight management (WM) behaviors of collegiate wrestlers after the implementation of the NCAA's new weight control rules. METHODS In the fall of 1999, a survey was distributed to 47 college wrestling teams stratified by collegiate division (i.e., I, II, III) and competitive quality. Forty-three teams returned surveys for a total of 741 responses. Comparisons were made using the collegiate division, weight class, and the wrestler's competitive winning percentage. RESULTS The most weight lost during the season was 5.3 kg +/- 2.8 kg (mean +/- SD) or 6.9% +/- 4.7% of the wrestler's weight; weekly weight lost averaged 2.9 kg +/- 1.3 kg or 4.3% +/- 2.3% of the wrestler's weight; post-season, the average wrestler regained 5.5 kg +/- 3.6 kg or 8.6% +/- 5.4% of their weight. Coaches and fellow wrestlers were the primary influence on weight loss methods; however, 40.2% indicated that the new NCAA rules deterred extreme weight loss behaviors. The primary methods of weight loss reported were gradual dieting (79.4%) and increased exercise (75.2%). However, 54.8% fasted, 27.6% used saunas, and 26.7% used rubber/plastic suits at least once a month. Cathartics and vomiting were seldom used to lose weight, and only 5 met three or more of the criteria for bulimia nervosa. WM behaviors were more extreme among freshmen, lighter weight classes, and Division II wrestlers. Compared to previous surveys of high school wrestlers, this cohort of wrestlers reported more extreme WM behaviors. However, compared to college wrestlers in the 1980s, weight loss behaviors were less extreme. CONCLUSIONS The WM practices of college wrestlers appeared to have improved compared to wrestlers sampled previously. Forty percent of the wrestlers were influenced by the new NCAA rules and curbed their weight loss practices. Education is still needed, as some wrestlers are still engaging in dangerous WM methods.
A Tensor-Driven Temporal Correlation Model for Video Sequence Classification

The task of video sequence classification plays a critical role in the development of computer vision. Considering this fact, this letter proposes a novel tensor decomposition method called tensor-driven temporal correlation in which general tensors are used as input for video sequence classification. Because distortion and redundancy may exist in the tensor representations of video sequences, we project the original tensor into subspaces spanned by spatial basis matrices in the proposed formulation. Moreover, to better preserve the temporal smoothness between consecutive slices of the tensor, the basis matrices are jointly learned by introducing an autoregressive model. An experiment on the commonly used Cambridge hand-gesture database demonstrates that our proposed method reaches convergence within a small number of iterations during the training stage and achieves promising results compared with state-of-the-art methods.
Performance of Real-Time Traffic in EDCA-BASED IEEE 802.11 b/g WLANS

The IEEE 802.11e draft specification is intended to solve the performance problems of WLANs for real time traffic by extending the original 802.11 medium access control (MAC) protocol and introducing priority access mechanisms in the form of the enhanced distributed channel access mechanism (EDCA) and hybrid coordination channel access (HCCA). The draft standard comes with a lot of configurable parameters for channel access, admission control, etc. but it is not very clear how real time traffic actually performs with respect to capacity and throughput in such WLANs that deploy this upcoming standard. In this report we have provided detailed simulation results on the performance of enterprise-anticipated real time VoIP application and collaborative video conferencing in presence of background traffic in EDCA-based IEEE 802.11 WLANs. We estimate the channel capacity and acceptable load conditions for some important enterprise usage scenarios. Subsequently, admission control limits are experimentally derived for these usage scenarios for voice and video traffic. Our simulations show that admission control greatly helps in maintaining the quality of admitted voice calls and video conferencing sessions that are prioritized as per EDCA mechanisms within acceptable channel load conditions. The use of admission control allows admitted voice calls and video sessions to retain their throughput and delay characteristics while unadmitted traffic (voice/video streams) greatly suffer from poor quality (delays, packet drops, etc.) as the channel load increases
Localization of mobile nodes based on inaccurate round-trip-time measurements using Bayesian inference

In this paper, we present a Bayesian-based localization method to estimate the unknown location of a mobile station (MS) in a network given the known location of a set of base stations. In this study, the MS was covered by a base station if the signal to interference and noise ratio (SINR) was larger than a threshold. By assuming a priori knowledge of the location of the MS and a Gaussian distribution for the round-trip time (RTT) measurements, a posteriori estimation of the unknown location of the MS using Bayesian inference method was obtained. The impact of variation of various variables on the localization accuracy such as number of base stations covering the MS, number of base stations interfering with the communication between the MS and the covering base stations, fading factor between base stations and the MS, SINR threshold and the path-loss coefficient have been studied. In addition, the performance of the developed Bayesian-based method in terms of localization accuracy was evaluated when the MS was inside and outside the convex hull of the base stations. The results of this study showed an improvement in the mean localization error and the localization root mean square error (RMSE) compared to other similar studies.
Identification of novel pathways linking epithelial-to-mesenchymal transition with resistance to HER2-targeted therapy

Resistance to human epidermal growth factor receptor 2 (HER2)-targeted therapies in the treatment of HER2-positive breast cancer is a major clinical problem. To identify pathways linked to resistance, we generated HER2-positive breast cancer cell lines which are resistant to either lapatinib or AZD8931, two pan-HER family kinase inhibitors. Resistance was HER2 independent and was associated with epithelial-to-mesenchymal transition (EMT), resulting in increased proliferation and migration of the resistant cells. Using a global proteomics approach, we identified a novel set of EMT-associated proteins linked to HER2-independent resistance. We demonstrate that a subset of these EMT-associated genes is predictive of prognosis within the ERBB2 subtype of human breast cancers. Furthermore, targeting the EMT-associated kinases Src and Axl potently inhibited proliferation of the resistant cells, and inhibitors to these kinases may provide additional options for the treatment of HER2-independent resistance in tumors.
Relevance Units Latent Variable Model and Nonlinear Dimensionality Reduction

A new dimensionality reduction method, called relevance units latent variable model (RULVM), is proposed in this paper. RULVM has a close link with the framework of Gaussian process latent variable model (GPLVM) and it originates from a recently developed sparse kernel model called relevance units machine (RUM). RUM follows the idea of relevance vector machine (RVM) under the Bayesian framework but releases the constraint that relevance vectors (RVs) have to be selected from the input vectors. RUM treats relevance units (RUs) as part of the parameters to be learned from the data. As a result, a RUM maintains all the advantages of RVM and offers superior sparsity. RULVM inherits the advantages of sparseness offered by the RUM and the experimental result shows that RULVM algorithm possesses considerable computational advantages over GPLVM algorithm.
Solution of Portfolio Optimization under Constraints and with Higher In-terest Rate for Borrowing

It is studied that the stochastic control problem of maxi-mizing expected utility from terminal wealth and/or con-sumption,when the portfolio is constrained to take val-ues in a given closed,convex subset of R,and in the pr-esence of a higher interest rate for borrowing.The set-ting is that of a continuous-time,Ito process model for the underlying asset prices.The existence of portfolio op-timization under constraints and with higher interest ratefor borrowing than for lending is discussed,and the so-lution for logarithmic utility function is presented.
Relationship between Postural Sway and Dynamic Balance in Stroke Patients

[Purpose] The purpose of the current study was to investigate the relationship between postural sway and dynamic balance in post stroke patients. [Subjects] Thirty-one stroke patients (20 men and 11 women; age 64.25 years; stroke duration 12.70 months; MMSE-K score 26.35) participated in this study. [Methods] This study applied a cross-sectional design. A Good Balance system was used for measurement of the postural sway velocity (anteroposterior and mediolateral) and velocity moment of subjects under the eyes open and eyes closed conditions in a standing posture. The postural sway of subjects was measured under two surface conditions (stable and unstable surfaces). [Results] On the unstable surface (foam), no significant correlation was observed between postural sway and dynamic balance except for the berg balance scale (BBS) score and anteroposterior postural sway velocity under the eyes open condition, anteroposterior postural sway velocity under the eyes closed condition, and postural sway velocity moment. In addition, in the stable condition, no significant correlation was observed between postural sway and dynamic balance. [Conclusion] Our results indicate that a decrease in postural sway does not necessarily reflect improvement of dynamic balance ability. We believe that this finding may be useful in balance rehabilitation for prevention of falls after a stroke.