Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of Muscle Fatigue in Diabetic Patients with Peripheral Neuropathy

Diabetic Peripheral Neuropathy (DPN) is one of the most common complications encountered in type-II diabetic patients. DPN causes motor disability, such as nerve damage and muscle weakness, which leads to an increased risk in falling during performance of activities of daily living (ADL). The extent of muscle weakness can be detected via analysis of surface electromyography (EMG) data. The objective of this study was to investigate if DPN patients were at a higher risk of falling when experiencing muscle fatigue during execution of extraneous tasks. A total of 30 participants (15 DPN patients and 15 healthy subjects) were recruited for this study and EMG data was collected from lower extremity muscles during walking. The sEMG data were analyzed for the detection of transition-to-fatigue phase during gait. The onset of muscle fatigue was detected via spectral feature analysis, i.e., mean and median frequency analysis. Independent t-tests were conducted to assess group differences (p<0.05). Our results indicated that DPN patients demonstrated the onset of muscle fatigue quicker as compared to age and gender matched healthy individuals (p<0.05). These results are expected to improve clinical observations of DPN patients and may contribute towards development of novel fall prevention strategies.
Design of 6 switched 3-level inverter with RL load

Bu çalışmada, çok-seviyeli evirici topolojilerine alternatif bir topoloji verilmiştir. Bu evirici topolojisinde 6 adet IGBT yarıiletken anahtar kullanılmış ve eviricinin her bir çıkış uçlarına çift sarımlı bobinler bağlanmıştır. Bobin gerilimleri kullanılarak 6 anahtar ile 3 seviyeli evirici elde edilmiştir. Yapılan simülasyon çalışmasında Proportional Integral (PI) denetleyici kullanılmıştır. Denetleyiciden elde edilen veriler kullanılarak 6 anahtarlı 3-seviyeli eviricideki yarıiletken anahtarların çalışması için gerekli sinyaller üretilmiştir. Bu sinyaller, uzay vektör darbe genişlik modülasyon tekniği ile elde edilmiştir. Bilgisayar ortamında 10 Ω ve 0.2 H değerinde RL yük esas alınarak benzetim çalışmaları yapılmış ve evirici performansı incelenmiştir. In this study, an alternative topology to multilevel inverter topologies is given. 6 IGBT seminconductor switches are used in this topology and coupled inductors are used in the output stage of the inverter. Using coupled inductors voltages, the 6 switched 3-level inverter has been obtained. In the simulation study, Proportional Integral (PI) controller has been used. By using the data taken from controller, the required switching signals have been produced for a 6 switched 3-level inverter. These signals have been taken by using space vector pulse width modulation technique. Using Computer Aided Design (CAD) analysis a RL load that have 10 Ω and 0.2 H values is simulated and inverter performance has been investigated.
The prediction of bus arrival time using automatic vehicle location systems data

The Prediction of Bus Arrival Time Using Automatic Vehicle Location Systems Data. (December 2004) Ran Hee Jeong, B.S., Hong-ik University; M.S., Hong-ik University Co-Chairs of Advisory Committee: Dr. Laurence R. Rilett Dr. Amy Epps Martin Advanced Traveler Information System (ATIS) is one component of Intelligent Transportation Systems (ITS), and a major component of ATIS is travel time information. The provision of timely and accurate transit travel time information is important because it attracts additional ridership and increases the satisfaction of transit users. The cost of electronics and components for ITS has been decreased, and ITS deployment is growing nationwide. Automatic Vehicle Location (AVL) Systems, which is a part of ITS, have been adopted by many transit agencies. These allow them to track their transit vehicles in real-time. The need for the model or technique to predict transit travel time using AVL data is increasing. While some research on this topic has been conducted, it has been shown that more research on this topic is required. The objectives of this research were 1) to develop and apply a model to predict bus arrival time using AVL data, 2) to identify the prediction interval of bus arrival time and the probabilty of a bus being on time. In this research, the travel time prediction model explicitly included dwell times, schedule adherence by time period, and traffic congestion which were critical to predict accurate bus arrival times. The test bed was a bus route running in the downtown of Houston, Texas. A historical based model, regression models, and artificial neural network (ANN) models were developed to predict bus arrival time. It was found that the artificial neural network models performed considerably better than either historical data based models or multi linear regression models. It was hypothesized that the ANN was able to identify the complex non-linear
A STUDY ON FINANCIAL PERFORMANCE OF SOFTWARE INDUSTRIES WITH REFERENCE TO INDIA

The Indian software industry has brought about a tremendous success for the emerging economy. The software industry is the main component of the information technology in India. Presently there are more than 500 software firms in the country which shows the monumental advancement that the Indian software Industry has experienced. In India, the software boom started somewhere in the late 1990’s. Most of the Indian software companies at that moment offered only limited software services such as the banking and the engineering software. The business software boom started with the emergence of Y2K problems, when a large number of skilled personnel were required to fulfill the mammoth database correction demand in order to cope up with the advent of the new millennium. The profile of the Indian IT services has been undergoing a change in the last few years, partly as it moved up the value chain and partly as a response to the market dynamics, ten years ago, most of the US companies would not even consider outsourcing some of their IT projects to outside vendors. Now, ten years later, a vast majority of the US companies use the professional services of Indian Software engineers in some manner, through large, medium or small companies or through individuals recruited directly. The market competition is forcing organizations to cut down on costs of products. The professional IT services on the other hand are becoming increasingly expensive. The offshore software development model is today where onsite professional services were ten years ago. There is high chance (almost a mathematical certainty), that in less then ten years, the vast majority of IT services (software development being just one of them) from developed countries, will be, one, outsourced and two, outsourced to an offshore vendor. The Indian software Industry has grown from a mere US $ 150 million in 1991-92 to a staggering US $ 5.7 billion in 1999-2000. No other Indian
Distributed Cooperative Reinforcement Learning for Wireless Sensor Network Routing

In this work we examine a specific case of wireless sensor networks (WSN) we call peer-to-peer WSN where source and destination are both dynamic and each is subject to constraints of low bandwidth, limited energy storage, and limited computational resources. Peer-to-peer WSN require the consideration of data computation time as a limiting constraint on information availability unlike a standard WSN that can rely on the unconstrained sink to perform the necessary computation of the raw sensor data into usable information. To effectively manage and improve upon peer-to-peer WSN routing, and WSN routing in general, we present a deep reinforcement learning algorithm known as distributed cooperative reinforcement for routing (DCRL-R) which uses a neural network and expanded state space parameters to learn routing policies for WSN. DCRL-R also incorporates an increased action space for determining when and where to perform in-network computation of the raw sensor data. We perform tests of DCRL-R on a physical network utilizing measured node state parametric data and show its viability in future WSN applications compared to a baseline routing algorithm using shortest path decisions with no computational offloading.
Parametric Modeling of Microwave Structure with Customization Responses by Combining RBF Neural Network and Pole-Residue-Based Transfer Functions

This paper proposed a parametric modeling technique for the microwave structures with a customization magnitude response by combining the RBF neural network and pole-residue-based transfer functions. The Latin hypercube sampling method is used for sampling given physical ranges and obtaining the EM behaviors of the microwave structures. A pole sorting process and a modified pole-residues splitting process are proposed to solve the pole sequence chaos and order-changing problems which occur in the modeling process. The pole-residues parameters after the above pre-processing steps are used as the inputs of the RBF neural network and the physical parameters are used as the outputs of RBF network. Then, the known magnitude response of the microwave structure are used as the prior knowledge to guide obtaining the goal pole-residues values corresponding to the giving magnitude response specification. After the training process of the RBF model, the goal pole-residues are input into the trained RBF network and the goal physical parameters corresponding to the customization responses is obtained. Finally, this model technique is illustrated by the two examples of microwave structures.
The Optimization Model of E-Commerce Logistics Distribution Path Based on GIS Technology

The optimization of the e-commerce logistics distribution path has always been an important research object in intelligent control. Based on the geographic information system (GIS) platform, this paper proposes an improved ant colony algorithm for the logistics distribution path optimization model based on the GIS platform. Firstly, ArcGIS software is used to solve the problem of complex networks and realize the selection and output of optional routes. Secondly, the basic ant colony algorithm is improved, and a dynamic path planning method combining global planning information and local planning is proposed. It mainly includes the improvement of the heuristic function and the improvement of the update method of pheromone. Finally, through simulation experiments and case validation experiments, it is concluded that the improved algorithm outperforms the traditional ant colony algorithm. In the case validation part, a local area of Beijing is selected to simulate a natural distribution environment, and the path optimization experiments are validated by building an actual road network model. The results show that the model can plan the optimal path for logistics distribution according to the road congestion. The data analysis shows that the route optimization model proposed in this paper can effectively reduce the distribution cost of enterprises, increase vehicle loading, and increase the profit and industry competitiveness of logistics enterprises.
Robust control of linear systems with random parameters and multiplicative disturbances with application to the investment portfolio management

This work examines discrete-time systems with additive and multiplicative noises and stochastic parameters. The equations of optimal linear quadratic static and dynamic output-feedback regulators for such systems are obtained. The regulators are robust with respect to a kind of distribution of random parameters. The results are applied to the investment portfolio management. The numerical simulation results are presented.
Ultrasoft Porous 3D Conductive Dry Electrodes for Electrophysiological Sensing and Myoelectric Control

Biopotential electrodes have found broad applications in health monitoring, human–machine interactions, and rehabilitation. This article reports the fabrication and applications of ultrasoft breathable dry electrodes that can address several challenges for their long‐term wearable applications—skin compatibility, wearability, and long‐term stability. The proposed electrodes rely on porous and conductive silver nanowire‐based nanocomposites as the robust mechanical and electrical interface. The highly conductive and conformable structure eliminates the necessity of conductive gel while establishing a sufficiently low electrode–skin impedance for high‐fidelity electrophysiological sensing. The introduction of gas‐permeable structures via a simple and scalable method based on sacrificial templates improves breathability and skin compatibility for applications requiring long‐term skin contact. Such conformable and breathable dry electrodes allow for efficient and unobtrusive monitoring of heart, muscle, and brain activities. In addition, based on the muscle activities captured by the electrodes and a musculoskeletal model, electromyogram‐based neural–machine interfaces are realized, illustrating the great potential for prosthesis control, neurorehabilitation, and virtual reality.
Network Slicing for Wireless Networks Operating in a Shared Spectrum Environment

By virtue of being an efficient way to distribute network resources to physical groups of users and to allow the network to provide performance guarantees, network slicing is one of the main features that has been included in 5G wireless networks. Concurrently, 5G networks will improve the spectral efficiency by transmitting over multiple RF bands (carrier aggregation), some potentially shared with other networks. This work presents a novel approach to implement network slicing when a network is sharing some of its spectrum bands with another network, making it first of its kind in addressing network slicing in a spectrum sharing environment. In the proposed technique, graph coloring is used to represent the interference between two networks and to assign spectrum resources to each access. In addition, two mechanisms are introduced to manage interference: "gray zones" and "blurred edges", the latter of which specifically address inter-network interference. Results show that the proposed technique is effectively able to perform resource allocation for network slicing in a shared spectrum environment by meeting throughput requirements for all slices and the isolation of services that is expected from network slicing.
Dracula’s ménagerie: A multispecies occupancy analysis of lynx, wildcat, and wolf in the Romanian Carpathians

Abstract The recovery of terrestrial carnivores in Europe is a conservation success story. Initiatives focused on restoring top predators require information on how resident species may interact with the re‐introduced species as their interactions have the potential to alter food webs, yet such data are scarce for Europe. In this study, we assessed patterns of occupancy and interactions between three carnivore species in the Romanian Carpathians. Romania houses one of the few intact carnivore guilds in Europe, making it an ideal system to assess intraguild interactions and serve as a guide for reintroductions elsewhere. We used camera trap data from two seasons in Transylvanian forests to assess occupancy and co‐occurrence of carnivores using multispecies occupancy models. Mean occupancy in the study area was highest for lynx (Ψwinter = 0.76 95% CI: 0.42–0.92; Ψautumn = 0.71 CI: 0.38–0.84) and wolf (Ψwinter = 0.60 CI: 0.34–0.78; Ψautumn = 0.81 CI: 0.25–0.95) and lowest for wildcat (Ψwinter = 0.40 CI: 0.19–0.63; Ψautumn = 0.52 CI: 0.17–0.78) We found that marginal occupancy predictors for carnivores varied between seasons. We also found differences in predictors of co‐occurrence between seasons for both lynx‐wolf and wildcat‐wolf co‐occurrence. For both seasons, we found that conditional occupancy probabilities of all three species were higher when another species was present. Our results indicate that while there are seasonal differences in predictors of occupancy and co‐occurrence of the three species, co‐occurrence in our study area is high. Terrestrial carnivore recovery efforts are ongoing worldwide. Insights into interspecific relations between carnivore species are critical when considering the depauperate communities they are introduced in. Our work showcases that apex carnivore coexistence is possible, but dependent on protection afforded to forest habitats and their prey base.
Successful Business Intelligence: Secrets to Making BI a Killer App

Praise for Successful Business Intelligence"If you want to be an analytical competitor, you've got to go well beyond business intelligence technology. Cindi Howson has wrapped up the needed advice on technology, organization, strategy, and even culture in a neat package. It's required reading for quantitatively oriented strategists and the technologists who support them. " --Thomas H. Davenport, President's Distinguished Professor, Babson College and co-author, Competing on Analytics"When used strategically, business intelligence can help companies transform their organization to be more agile, more competitive, and more profitable. Successful Business Intelligence offers valuable guidance for companies looking to embark upon their first BI project as well as those hoping to maximize their current deployments. " --John Schwarz, CEO, Business Objects"A thoughtful, clearly written, and carefully researched examination of all facets of business intelligence that your organization needs to know torun its business more intelligently and exploit information to its fullest extent. " --Wayne Eckerson, Director, TDWI Research"Using real-world examples, Cindi Howson shows you how to use business intelligence to improve the performance, and the quality, of your company. " --Bill Baker, Distinguished Engineer & GM, Business Intelligence Applications, Microsoft Corporation"This book outlines the key steps to make BI an integral part of your company's culture and demonstrates how your company can use BI as a competitive differentiator. " --Robert VanHees, CFO, Corporate Express"Given the trend to expand the business analytics user base, organizations are faced with a number of challenges that affect the success rate of these projects. This insightful book provides practical advice on improving that success rate. " --Dan Vesset, Vice President, Business Analytics Solution Research, IDC
Association of Endothelin-Converting Enzyme and Endothelin-1 Gene Polymorphisms with Essential Hypertension in Malay Ethnics

Objectives Endothelin-1 (ET-1), the most potent endogenous vasoconstrictor, generated by enzymatic cleavage catalyzed by an endothelin-converting enzyme (ECE), plays a significant role in the regulation of hypertension. Methods This study investigates the effect of endothelin-1 (Lys198Asn/rs5370) and ECE (rs212526 C/T) gene polymorphisms with essential hypertension (EH) among Malay ethnics. To determine the association of gene polymorphism, 177 hypertensives and controls (196) were genotyped using Taqman method. Results A significant difference was observed in ET-1 rs5370 and ECE rs212526 gene polymorphisms between EH and control subjects (P < 0.001). A significantly high body mass index (BMI), waist-to-hip ratio, fasting plasma glucose, hemoglobin A1c, systolic and diastolic blood pressure, and lipid profiles were observed among the EH patients when compared to controls (P < 0.05). Moreover, T allele (rs5370) carriers in males have a high risk for EH. There was no significant association between gender in ECE C/T polymorphisms (P > 0.05). Conclusion Based on our result, it is evident that the T allele of ET-1 rs5370 polymorphism and C allele of ECE rs212526 have a significant genetic risk factor in EH among Malay subjects, and BMI and age are associated with hypertension.
The role of socioemotional wellbeing difficulties and adversity in the L2 acquisition of first-generation refugee children

Abstract First-generation refugee children often experience pre- and post-migration adversity and display high levels of mental health/wellbeing difficulties, but to date, research has not examined the impact of such factors on refugee children's L2 acquisition. Accordingly, this study examined the influence of externalizing and internalizing problem behaviours (wellbeing), time in refugee camps and low socioeconomic status (SES) (adversity) on the English-L2 abilities of 117 Syrian refugee children (7–14 years) in their third year of residency in Canada. Wellbeing difficulties and adversity factors accounted for variance on L2 vocabulary, morphosyntax, listening comprehension and narrative production tasks, beyond the variance accounted for by age of L2 acquisition and length of L2 exposure. Specifically, externalizing problem behaviours, time in refugee camp, maternal education and maternal employment predicted variance in L2 abilities. It is concluded that refugee children could have influences on their L2 acquisition that are different from those of bilinguals with other backgrounds.
Safety of lacto‐N‐tetraose (LNT) produced by derivative strains of Escherichia coli BL21 (DE3) as a Novel Food pursuant to Regulation (EU) 2015/2283

Abstract Following a request from the European Commission, the EFSA Panel on Nutrition, Novel Foods and Food Allergens (NDA) was asked to deliver an opinion on lacto‐N‐tetraose (LNT) as a novel food (NF) pursuant to Regulation (EU) 2015/2283. The NF is a powdered mixture mainly composed of the human‐identical milk oligosaccharide (HiMO) LNT, but it also contains d‐lactose, lacto‐N‐triose II and para‐lacto‐N‐hexaose, and a small fraction of other related saccharides. The NF is produced by fermentation with two genetically modified strains of Escherichia coli BL21 (DE3), the production strain and the optional degradation strain. The information provided on the manufacturing process, composition and specifications of the NF does not raise safety concerns. The applicant intends to add the NF to a variety of foods, including infant and follow‐on formula, food for infants and young children, food for special medical purposes and food supplements. The target population is the general population. The anticipated daily intake of LNT from the NF at the maximum proposed use levels does not exceed the intake level of naturally occurring LNT in breastfed infants on a body weight basis. The intake of LNT in breastfed infants on a body weight basis is expected to be safe also for other population groups. The intake of other carbohydrate‐type compounds structurally related to LNT is also considered of no safety concern. Food supplements are not intended to be used if other foods with added LNT or human milk are consumed on the same day. The Panel concludes that the NF is safe under the proposed conditions of use.