Miracle-dz/UniFAR-FTUs huggingface dataset:
DTC with adaptive stator flux observer and stator resistance estimator for induction motors

This paper describes a robust full-order adaptive stator flux observer is designed for a speed sensorless DTC system and a new speed-adaptive law and a stator resistance adaptive law are given. Furthermore, dynamic neural network is used to design the observer gain matrix and the gain matrix can be adjusted on-line. The stability of observer is guaranteed by the gain matrix in the whole speed range. Finally, the effectiveness and validity of the proposed control approach is verified by computer simulation results.
SmartFridge: Demand Side Management for the device level

With the evolving technologies smart metering, or generalized the smart grid, it becomes reasonable to think about integrating household devices into a Demand Side Management (DSM) network. This paper gives an overview about the state of the art in the area of DSM. Subsequently, it is shown what is needed to convert a standard, commercial-off-the-shelf refrigerator into a networked smart fridge. Following this, a simulation model and a basic algorithm for load control of a refrigerator is presented and analyzed. Finally, possible improvements of hardware and the algorithms are proposed.
Therapeutic Efficacy of p53 Restoration in Mdm2-Overexpressing Tumors

The p53 (TP53) tumor suppressor is the most frequently mutated gene in human cancers. Restoring expression of wild-type p53 has led to tumor growth suppression in a variety of tumor models that are p53 deficient. Other mechanisms, for example, upregulation of Mdm2, exist in tumors to inactivate the p53 pathway. Mdm2, an E3 ubiquitin ligase that targets p53 for proteasomal degradation, is present at high levels in many tumors with wild-type p53. In this study, the effects of restoring p53 activity were probed in Mdm2-overexpressing tumors genetically using animal models. Here, it was demonstrated that elevated levels of Mdm2 and decreased levels of p53 act additively to dampen p53 activity in DNA damage response and tumor development. Our data further indicate that restoration of wild-type p53 expression in Mdm2-overexpressing angiosarcomas results in tumor stasis and regression in some cases. Finally, it was determined that restored p53 suppressed cell proliferation but did not elicit apoptosis in the Mdm2-overexpressing angiosarcomas. Implications: Restoration of wild-type p53 expression in Mdm2-overexpressing tumors suppresses tumor growth, which represents a potential clinical strategy to treat tumors with high levels of Mdm2. Visual Overview: http://mcr.aacrjournals. org/content/12/6/901/F1.large. jpg. Mol Cancer Res; 12(6); 901–11. ©2014 AACR. Visual Overview
Personalized video summarization based on group scoring

In this paper an expert-based model for generation of personalized video summaries is suggested. The video frames are initially scored and annotated by multiple video experts. Thereafter, the scores for the video segments that have been assigned the higher priorities by end users will be upgraded. Considering the required summary length, the highest scored video frames will be inserted into a personalized final summary. For evaluation purposes, the video summaries generated by our system have been compared against the results from a number of automatic and semi-automatic summarization tools that use different modalities for abstraction.
Multi-dimensional Resource Allocation for Data-intensive Large-scale Cloud Applications

Large scale applications are emerged as one of the important applications in distributed computing. Today, the economic and technical benefits offered by the Cloud computing technology encouraged many users to migrate their applications to Cloud. On the other hand, the variety of the existing Clouds requires them to make decisions about which providers to choose in order to achieve the expected performance and service quality while keeping the payment low. In this paper, we present a multi-dimensional resource allocation scheme to automate the deployment of data-intensive large scale applications in Mutli-Cloud environments. The scheme applies a two level approach in which the target Clouds are matched with respect to the Service Level Agreement (SLA) requirements and user payment at first and then the application workloads are distributed to the selected Clouds using a data locality driven scheduling policy. Using an implemented Multi-Cloud simulation environment, we evaluated our approach with a real data-intensive workflow application in different scenarios. The experimental results demonstrate the effectiveness of the implemented matching and scheduling policies in improving the workflow execution performance and reducing the amount and costs of Intercloud data transfers.
Set-based vector model: An efficient approach for correlation-based ranking

This work presents a new approach for ranking documents in the vector space model. The novelty lies in two fronts. First, patterns of term co-occurrence are taken into account and are processed efficiently. Second, term weights are generated using a data mining technique called association rules. This leads to a new ranking mechanism called the set-based vector model. The components of our model are no longer index terms but index termsets, where a termset is a set of index terms. Termsets capture the intuition that semantically related terms appear close to each other in a document. They can be efficiently obtained by limiting the computation to small passages of text. Once termsets have been computed, the ranking is calculated as a function of the termset frequency in the document and its scarcity in the document collection. Experimental results show that the set-based vector model improves average precision for all collections and query types evaluated, while keeping computational costs small. For the 2-gigabyte TREC-8 collection, the set-based vector model leads to a gain in average precision figures of 14.7% and 16.4% for disjunctive and conjunctive queries, respectively, with respect to the standard vector space model. These gains increase to 24.9% and 30.0%, respectively, when proximity information is taken into account. Query processing times are larger but, on average, still comparable to those obtained with the standard vector model (increases in processing time varied from 30% to 300%). Our results suggest that the set-based vector model provides a correlation-based ranking formula that is effective with general collections and computationally practical.
Characterisation of equine satellite cell transcriptomic profile response to β-hydroxy-β-methylbutyrate (HMB)

Abstract β-Hydroxy-β-methylbutyrate (HMB) is a popular ergogenic aid used by human athletes and as a supplement to sport horses, because of its ability to aid muscle recovery, improve performance and body composition. Recent findings suggest that HMB may stimulate satellite cells and affect expressions of genes regulating skeletal muscle cell growth. Despite the scientific data showing benefits of HMB supplementation in horses, no previous study has explained the mechanism of action of HMB in this species. The aim of this study was to reveal the molecular background of HMB action on equine skeletal muscle by investigating the transcriptomic profile changes induced by HMB in equine satellite cells in vitro. Upon isolation from the semitendinosus muscle, equine satellite cells were cultured until the 2nd day of differentiation. Differentiating cells were incubated with HMB for 24 h. Total cellular RNA was isolated, amplified, labelled and hybridised to microarray slides. Microarray data validation was performed with real-time quantitative PCR. HMB induced differential expressions of 361 genes. Functional analysis revealed that the main biological processes influenced by HMB in equine satellite cells were related to muscle organ development, protein metabolism, energy homoeostasis and lipid metabolism. In conclusion, this study demonstrated for the first time that HMB has the potential to influence equine satellite cells by controlling global gene expression. Genes and biological processes targeted by HMB in equine satellite cells may support HMB utility in improving growth and regeneration of equine skeletal muscle; however, the overall role of HMB in horses remains equivocal and requires further proteomic, biochemical and pharmacokinetic studies.
Design and performance assessment for the V shaped magnet IPM synchronous motor

In this paper a V shaped magnet concentrated winding 12 slot 8 pole Interior Permanent Magnet Synchronous Motor (IPMSM) is investigated as a suitable candidate for operation with a wide Constant Power Speed Region (CPSR). Specific physical changes are applied to the initial design in order to study impacts of these changes on the machine CPSR, inductance values, cogging torque and induced voltage harmonic spectrum. Each of these are assessed using Finite Element Models (FEM). In addition to physical design changes, three different types of lamination steel are applied to the structure of the final improved IPMSM, and loss and efficiency analysis are carried out. A final design is presented, along with explanation of the impact of design choices on performance.
Information›seeking agent dialogs with permissions and arguments

Many distributed information systems require agents to have appropriate authorization to obtain access to information. For some applications, such as those in medicine, authorization may be granted in exceptional cases even to agents without the necessary permissions, provided they can provide an appropriate justication for having access. We may consider these agent interactions to be information-seeking dialogs with the agent seeking the information and the agent controlling access to it engaged in argument together over data access. We present a denotational semantics for such dialogs, drawing on Tuple Centers (programmable Tuple Spaces). We illustrate our approach with an example in medicine, and describe an implementation we have created using TuCSoN. ACM CATEGORIES AND SUBJECT DESCRIPTORS: I.2. 11 [Articial Intelligence] Distributed Articial Intelligence: Coherence and co-ordination; Languages and Structures; Multiagent systems.
Graphical Models and Exponential Families

We provide a classification of graphical models according to their representation as subfamilies of exponential families. Undirected graphical models with no hidden variables are linear exponential families (LEFs), directed acyclic graphical models and chain graphs with no hidden variables, including Bayesian networks with several families of local distributions, are curved exponential families (CEFs) and graphical models with hidden variables are stratified exponential families (SEFs). An SEF is a finite union of CEFs satisfying a frontier condition. In addition, we illustrate how one can automatically generate independence and non-independence constraints on the distributions over the observable variables implied by a Bayesian network with hidden variables. The relevance of these results for model selection is examined.
Perspectives on Open Data: Issues and Opportunties

Open data has become an important new direction in information technology. Governments are releasing data so as to be more transparent and also claiming that open data has substantial economic value. However, there appear to be many issues about open data that are not being discussed. This paper uses several practical examples in an attempt to illustrate many of these issues and allied opportunities, and through them to suggest the beginning of a research agenda around open data.
On Simple Multiple Access Networks

We investigate a simple multiple access network (SMAN) where k independent sources of unit rates multicast their information to a set of sinks, via n commonly shared relays. All links are assumed to have unit capacity. Given such a SMAN, a coding scheme for the relays is called optimal if each sink can retrieve all information from the sources under at most ⌊n-k+1/2⌋ node/link errors. We study the problem of designing the sparsest SMAN, i.e., the SMAN that has the least number of edges, that supports an optimal coding scheme for the relays. Additionally, the SMAN must satisfy either of the following constraints: 1) Connection Constraint: Each relay can be connected only to a given subset of sources or 2) Balance Constraint: Each relay must be connected to approximately the same number of sources. We provide two polynomial time algorithms to identify the cases where such a SMAN exists together with its optimal coding scheme designed over sufficiently large fields. One algorithm is based on a nontrivial modification of the well-known Gale-Ryser algorithm, whereas the other is based on a novel generalization of the famous Hall's marriage theorem. We also propose a combinatorial approach to construct optimal coding schemes over small fields and settle the problem for a special case.
Stability-Indicating HPLC Determination of Trandolapril in Bulk Drug and Pharmaceutical Dosage Forms

A rapid, simple, accurate, precise, economical, robust, and stability indicating reverse phase HPLC-PDA procedure has been developed and validated for the determination of trandolapril. The trandolapril was separated isocratically on Hypersil-Gold C18 column (250 mm × 4.6 mm, 5 μm) with a mobile phase consisting of 50% acetonitrile and 50% water (containing 0.025% triethylamine, pH 3.0 ± 0.1), at 25 ± 2°C. Retention time of the drug was ~4.6 min. The eluted compounds were monitored and identified at 210 nm. The linearity of the method was excellent (r 2 > 0.9999) over the concentration range of 1–24 μg/mL; the limit of detection (LOD) and limit of quantitation (LOQ) were 0.0566 μg/mL and 0.1715 μg/mL, respectively. The overall precision was less than 2%. Mean recovery of trandolapril was more than 99%; no interference was found from the component present in the preparation. Stability studies indicate that the drug was stable to sunlight and UV light. The drug gives 6 different oxidative products on exposure to hydrogen peroxide. Slight degradation was observed in acidic condition. Degradation was higher in the alkaline condition compared to other conditions. The robustness of the method was studied using factorial design experiment.
A declarative decision support framework for supply chain problems

The author presents a novel declarative approach to modeling, solving and decision support for supply chain problems as a declarative decision support framework. The proposed framework makes it possible to ask different types of questions (general, specific, logical etc.). The implementation of the framework was performed in the CLP (Constraint Logic Programming) environment. To increase the efficiency of the framework, particularly in the area of optimization made its integration with MP (Mathematical Programming) environment. The paper also presents the implementation of illustrative model, using the proposed framework. In addition, an efficiency analysis of the presented solution in relation to the application of mathematical programming have been conducted.
Effects of a group exercise program on strength, mobility, and falls among fall-prone elderly men.

OBJECTIVES This randomized controlled trial studied the effects of a low- to moderate-intensity group exercise program on strength, endurance, mobility, and fall rates in fall-prone elderly men with chronic impairments. METHODS Fifty-nine community-living men (mean age = 74 years) with specific fall risk factors (i.e., leg weakness, impaired gait or balance, previous falls) were randomly assigned to a control group (n = 28) or to a 12-week group exercise program (n = 31). Exercise sessions (90 minutes, three times per week) focused on increasing strength and endurance and improving mobility and balance. Outcome measures included isokinetic strength and endurance, five physical performance measures, and self-reported physical functioning, health perception, activity level, and falls. RESULTS Exercisers showed significant improvement in measures of endurance and gait. Isokinetic endurance increased 21% for right knee flexion and 26% for extension. Exercisers had a 10% increase (p < .05) in distance walked in six minutes, and improved (p < .05) scores on an observational gait scale. Isokinetic strength improved only for right knee flexion. Exercise achieved no significant effect on hip or ankle strength, balance, self-reported physical functioning, or number of falls. Activity level increased within the exercise group. When fall rates were adjusted for activity level, the exercisers had a lower 3-month fall rate than controls (6 falls/1000 hours of activity vs 16.2 falls/1000 hours, p < .05). DISCUSSION These findings suggest that exercise can improve endurance, strength, gait, and function in chronically impaired, fall-prone elderly persons. In addition, increased physical activity was associated with reduced fall rates when adjusted for level of activity.
The effect of excess cobalt on milk fatty acid profiles and transcriptional regulation of SCD, FASN, DGAT1 and DGAT2 in the mammary gland of lactating dairy cows.

The main objective of this study was to investigate the effect of excess cobalt (Co) on gene expression of stearoyl-CoA desaturase (SCD), fatty acid synthase (FASN), diacylglycerol acyltransferase 1 (DGAT1) and diacylglycerol acyltransferase 2 (DGAT2) of lactating dairy cows in relation to milk fatty acid profile. Seven multiparous cows of the Norwegian Red cattle breed (NRF) had their basal diet supplemented with 1.4 g Co as a 24 g/l solution of Co-acetate per os twice daily for 7 days followed by a 9-day depuration period. Udder biopsies were performed prior to the treatment period, after 1 week of treatment and immediately after the depuration period. Excess Co reduced the proportion of all cis-9 monounsaturated fatty acids and increased the proportion of 18:0 in milk. However, gene expression levels of SCD, DGAT1, DGAT2 and FASN were not significantly altered. Our results indicate that the effect of Co on milk fatty acid profile is mediated at the post-transcriptional level by reduced activity of SCD in the mammary gland. Potential mechanisms explaining how Co might reduce stearoyl-CoA desaturation are discussed.
Spatial Diversity for IEEE 802.11p Post-Crash Message Dissemination in a Highway Environment

In this paper, we evaluate the performance of broadcast safety applications in a vehicular-to-vehicular (V2V) communication scenario using a BER-based reception model from a detailed IEEE 802.11p physical layer simulator for a more accurate interpretation of the vehicular communication system, instead of the prebuilt SNR threshold model available in a typical network simulators. Our main contribution is the spatial diversity analysis provided using MIMO-STBC, that is specific to modulation types, vehicular speeds and range of SNR values. To further improve the accuracy of the analysis, realistic vehicular traces from a bidirectional highway are used as the mobility model. Finally, we included post-crash warning message prioritization over periodic status updates by enabling a hybrid EDCA MAC. Our analysis shows that MIMO-STBC achieves up to 80% range extension of the 1-hop safety broadcast in a V2V when compared against single antenna system.
Service Entity Placement for Social Virtual Reality Applications in Edge Computing

While social Virtual Reality (VR) applications such as Facebook Spaces are becoming popular, they are not compatible with classic mobile-or cloud-based solutions due to their processing of tremendous data and exchange of delay-sensitive metadata. Edge computing may fulfill these demands better, but it is still an open problem to deploy social VR applications in an edge infrastructure while supporting economic operations of the edge clouds and satisfactory quality-of-service for the users. This paper presents the first formal study of this problem. We model and formulate a combinatorial optimization problem that captures all intertwined goals. We propose ITEM, an iterative algorithm with fast and big “moves” where in each iteration, we construct a graph to encode all the costs and convert the cost optimization into a graph cut problem. By obtaining the minimum s-t cut via existing max-flow algorithms, we can simultaneously determine the placement of multiple service entities, and thus, the original problem can be addressed by solving a series of graph cuts. Our evaluations with large-scale, real-world data traces demonstrate that ITEM converges fast and outperforms baseline approaches by more than 2 × in one-shot placement and around 1.3 × in dynamic, online scenarios where users move arbitrarily in the system.
The influence of processor architecture on the design and the results of WCET tools

The architecture of tools for the determination of worst case execution times (WCETs) as well as the precision of the results of WCET analyses strongly depend on the architecture of the employed processor. The cache replacement strategy influences the results of cache behavior prediction; out-of-order execution and control speculation introduce interferences between processor components, e.g., caches, pipelines, and branch prediction units. These interferences forbid modular designs of WCET tools, which would execute the subtasks of WCET analysis consecutively. Instead, complex integrated designs are needed, resulting in high demand for memory space and analysis time. We have implemented WCET tools for a series of increasingly complex processors: SuperSPARC, Motorola ColdFire 5307, and Motorola PowerPC 755. In this paper, we describe the designs of these tools, report our results and the lessons learned, and give some advice as to the predictability of processor architectures.
Quantizer design for interconnected feedback control systems

In this paper, we consider the design of interconnected H-infinity feedback control systems with quantized signals. We assume that a decentralized static output feedback has been designed for an interconnected continuous-time LTI system so that the closed-loop system is stable and a desired H-infinity disturbance attenuation level is achieved, and that the subsystems’ measurement outputs are quantized before they are passed to the local controller. We propose a localoutput-dependent strategy for updating the quantizers’ parameters, so that the overall closed-loop system is asymptotically stable and achieves the same H-infinity disturbance attenuation level. Both the pre-designed controllers and the quantizers’ parameters are constructed in a decentralized manner, depending on local information.
Demonstrating the value of credibility modeling for trust-based approaches to online message recommendation

This paper presents a validation of CredTrust, a multiagent trust model aimed at addressing the problem of folklore in online social networks: strong similarity among mis-guided peers should be ignored, at the expense of valuable advice provided by less similar credible peers. A series of simulations provides measured validation of the value of our approach in coping with a wide variety of messages, recommending those with high predicted benefit and avoiding those with low predicted benefit; we quantify our improvements in comparison with an established trust-based system (which fails to incorporate credibility).