Miracle-dz/UniFAR-FTUs huggingface dataset:
Decomposition of Market-Settlement Surplus Using Pseudo-IV-Optimal Power Flow

Within an alternating current (AC) optimal power flow (OPF) market clearing framework, market-settlement surplus (MS) is inevitable due to network losses, congestion, and reactive power. For a general AC-OPF model, decomposition of MS into its constituents is a challenge. Therefore, this paper proposes a solution for decomposing MS into its constituents, i.e., network losses, congestion, and reactive support services, by deriving analytical expressions for each of the components. An optimization problem, named pseudo-IV-OPF, is set up around the existing AC-OPF solution to derive expressions. The central idea involved in current and voltage OPF, that the current flow at sending end is exactly equal and opposite at receiving end, is exploited to derive the elements of MS by using Karush–Kuhn–Tucker conditions of optimality. It is important to note that a converged OPF solution, obtained from the standard AC-OPF model used by the utility, is an input to the proposed model. The efficacy of the proposed expressions is illustrated on various benchmark systems.
Optically coherent image reconstruction in the presence of phase errors using advanced-prior models

Recently developed coherent-imaging algorithms using Model-Based Iterative Reconstruction (MBIR) are robust to noise, speckle, and phase errors. These MBIR algorithms produce useful images with less signal which allows imaging distances to be extended. So far, MBIR algorithms have only incorporated simple image models. Complex scenes, on the other hand, require more advanced image models. In this work, we develop an MBIR algorithm for image reconstruction in the presence of phase errors which incorporates advanced image models. The proposed algorithm enables optically-coherent imaging of complex scenes at extended ranges.
Connected cars — Threats, vulnerabilities and their impact

The growing demand for interoperability between system components within a connected car has led to new security challenges in automotive development. The existing components, based on established technology, are often being combined to form such a connected car. For such established technologies, individual, often sector specific threat and vulnerability catalogs exist. The aim of this paper is to identify blocks of established technologies in a connected car and to consolidate the corresponding threat and vulnerability catalogs relevant for the individual constituent components. These findings are used to estimate the impact on specific system components and subsystems to identify the most crucial components and threats.
Local Coherence and Preemptive Digging-in Effects in German

SOPARSE predicts so-called local coherence effects: locally plausible but globally impossible parses of substrings can exert a distracting influence during sentence processing. Additionally, it predicts digging-in effects: the longer the parser stays committed to a particular analysis, the harder it becomes to inhibit that analysis. We investigated the interaction of these two predictions using German sentences. Results from a self-paced reading study show that the processing difficulty caused by a local coherence can be reduced by first allowing the globally correct parse to become entrenched, which supports SOPARSE’s assumptions.
Bilevel Optimization for Calibrating Point Spread Functions in Blind Deconvolution

Blind deconvolution problems arise in many imaging modalities, where both the underlying point spread function, which parameterizes the convolution operator, and the source image need to be identified. In this work, a novel bilevel optimization approach to blind deconvolution is proposed. The lower-level problem refers to the minimization of a total-variation model, as is typically done in non-blind image deconvolution. The upper-level objective takes into account additional statistical information depending on the particular imaging modality. Bilevel problems of such type are investigated systematically. Analytical properties of the lower-level solution mapping are established based on Robinson's strong regularity condition. Furthermore, several stationarity conditions are derived from the variational geometry induced by the lower-level problem. Numerically, a projected-gradient-type method is employed to obtain a Clarke-type stationary point and its convergence properties are analyzed. We also implement an efficient version of the proposed algorithm and test it through the experiments on point spread function calibration and multiframe blind deconvolution.
Different methods for compensating the transient analysis using the dynamic voltage regulator

In this paper the transient analysis of 132 kv power substation is calculated by using practical and theoretical values. By studying the power system stability it is observed that the transient means the sudden interruption or change occurred in system which caused the system unhealthy and unbalanced. So in this paper by using the dynamic voltage regulator we compensated the transient analysis stability of substation. This paper compare with the actual data of 132kv substation for calculating the stability. By using the algorithm of modified Euler's method we find the steps of initial and final values of fault. The model of 132kv substation is simulated on Matlab software.
A reduced complexity MFCC-based deep neural network approach for speech enhancement

This paper focuses on a regression-based deep neural network (DNN) approach for single-channel speech enhancement. While DNN can lead to improved speech quality compared to classical approaches, it is afflicted by high computational complexity in the training stage. The main contribution of this work is to reduce the DNN complexity by introducing a spectral feature mapping from noisy mel frequency cepstral coefficients (MFCC) to enhanced short-time Fourier transform (STFT) spectrum. This approach requires much fewer input features and consequently lead to reduced DNN complexity. Exploiting the frequency domain speech features obtained from this mapping also avoids the information loss in reconstructing the speech signal back to time domain from its MFCC. Compared to the STFT-based DNN approach, the complexity of our approach for the training phase is reduced by a factor of 4.75. Moreover, experimental results of perceptual evaluation of speech quality (PESQ) and source-to-distortion ratio (SDR) show that the proposed approach outperforms the benchmark algorithms and this for various noise types, and different SNR levels.
An improved duty cycle ZVT two swicth forward converter

In this paper, an isolated dc-dc converter based on an active demagnetization structure is presented in order to demagnetize transformer of a converter. Also, duty cycle limitation of two switch forward converter is improved with using this structure. At the same time, A Zero Voltage Transition (ZVT) cell is integrated into this improved converter and Soft Switching (SS) for the switches is achieved, too. So, the proposed converter has features duty cycle more than %50 and no turn on switching losses. Operation principles, theoretical analyses and design methods are presented. These theoretical analyses are verified with simulation results using PowerSIM (PSIM) programme.
Changes in speed and strength in female volleyball players during and after a plyometric training program

The goal of this article was the validation of a plyometric training program and the evaluation of the changes in monitored speed and explosive power predispositions during and after the end of the training program. The program was applied to a group of female youth volleyball players (n = 11) twice a week during an eight week period. Their actual level of explosive power and locomotor speed was evaluated before, during and after the intervention was completed. The levels were determined with the following tests: the standing vertical jump, the vertical jump with an approach and the shuttle run for 6 × 6 m. There were positive changes in the average values of test scores during the period of testing, but the dynamics of the changes in the explosive power and the speed were diff erent. Other increases in all the characteristics were noticeable when the fi nal measurements were made six weeks after the completion of the training program. Examination of the diff erences in the test scores by the follow up group, before the beginning and six weeks after fi nishing the intervention, was centred on objectively and statistically important changes in the volleyball players’ motor predispositions (p < .05). The results of the program support the opinion that plyometric exercises are eff ective tools in the development of explosive power and speed in young athletes.
Simulations of novel radiometer systems using compressed sensing

In this paper, a novel radiometer system using compressed sensing technique is simulated. Millimeter-wave radiometer is a high-sensitivity noise power receiver that can detect the microwave radiation from objects. Millimeter wave radiometer is one of the key technologies in millimeter wave passive detection and imaging. The novel system this paper proposed using compressed sensing is a focal plane system, which simultaneously receives signals through multiple feeds. Each feed receives the corresponding pixel point of millimeter wave radiation energy. The system achieves the similar function of the dam-board by on-off the switch. The system reduces the number of receiver channels via the use of compressed sensing. The proposed system not only overcomes the shortcomings of the traditional systems, but also recovers the image according to the theory of compressed sensing. The system performance is validated through simulations.
Ethernet Implementation of Fault Tolerant Train Network for Entertainment and Mixed Control Traffic

This paper studies the integration of the control system and entertainment on board of train wagons. Both the control and entertainment loads are implemented on top of Gigabit Ethernet, each with a dedicated controller/server. The control load has mixed sampling periods. It is proven that this system can tolerate the failure of one controller in one wagon. In a two wagon scenario, fault tolerance at the controller level is studied, and simulation results show that the system can tolerate the failure of 3 controllers. The system is successful in meeting the packet end-to-end delay with zero packet loss in all OPNET simulated scenarios. The maximum permissible entertainment load is determined for the fault tolerant scenarios.
Design and implementation of high gain boost converter with voltage-mode control

This paper presents modeling, design and implementation of a high gain boost DC-DC converter and its closed loop control. A simple voltage mode analog controller is designed to regulate the output voltage of the converter. Small signal model of the converter is derived from average state space analysis. The operation of the converter under steady state and transient are validated experimentally. A hardware prototype of 50 Watt, 200V output voltage, 20kHz boost converter with an input of 12V is developed. The output voltage of dc-dc boost converter is regulated with wide load variation (from 56.52% to 108.70% of full load).
Security approach on MQTT based smart home

Smart home technology is the concept of integrating Information and Communication Technology (ICT) into home appliances, which facilitates the simple tasks to be automated and controlled remotely, thus improves the quality of life of smart home inhabitants. In this paper we propose to implement the security among M2M smart home objects over 6LoWPAN networks, with the help of an enhanced mutual authentication and key establishment scheme. In the enhanced mutual authentication, a hybrid cryptography is used for secure authentication and suitable key establishment, for 6LoWPAN resource constrained devices. A handover ticket is generated for secure authentication, when there is mobility among nodes. In addition to it, we propose to use a communication protocol, MQTT (Message Queueing Telemetry Transport), which is a light weight, publish subscribe based protocol and more compatible with resource constrained devices like smart home objects in 6LoWPAN networks and gives better results in M2M communication.
Dexmedetomidine attenuates cerebral ischemia/reperfusion injury in neonatal rats by inhibiting TLR4 signaling

Objective The sedative dexmedetomidine plays a role in multi-organ protection by inhibiting toll-like receptor (TLR) 4 expression in ischemia/reperfusion injury. The present study investigated whether the neuroprotective effects of dexmedetomidine could be blocked by the TLR4 agonist lipopolysaccharide. Methods We established a cerebral ischemia/reperfusion model in neonatal Sprague-Dawley rats through bilateral carotid artery occlusion for 20 minutes followed by a 2-hour reperfusion. Rats were assigned to four groups: Sham operation, ischemia/reperfusion, ischemia/reperfusion preceded by dexmedetomidine treatment (10 µg/kg), and ischemia/reperfusion preceded by dexmedetomidine (10 µg/kg) and lipopolysaccharide (500 µg/kg) treatments. Cerebral tissue injury was assessed by hematoxylin and eosin staining, and cerebral TLR4 expression was evaluated by real-time PCR and western blot. Results Pretreatment with dexmedetomidine reduced ischemia-induced morphological changes in the hippocampal CA3 region and downregulated TLR4 expression, but these neuroprotective effects were partially blocked by co-treatment with the TLR4 agonist lipopolysaccharide. Conclusion Our results indicate that inhibition of cerebral TLR4 expression is related to the neuroprotective effects of dexmedetomidine in this neonatal rat cerebral ischemia/reperfusion model.
Diabetes Mellitus–Induced Long Noncoding RNA Dnm3os Regulates Macrophage Functions and Inflammation via Nuclear Mechanisms

Objective— Macrophages play key roles in inflammation and diabetic vascular complications. Emerging evidence implicates long noncoding RNAs in inflammation, but their role in macrophage dysfunction associated with inflammatory diabetic complications is unclear and was therefore investigated in this study. Approach and Results— RNA-sequencing and real-time quantitative PCR demonstrated that a long noncoding RNA Dnm3os (dynamin 3 opposite strand) is upregulated in bone marrow-derived macrophages from type 2 diabetic db/db mice, diet-induced insulin-resistant mice, and diabetic ApoE−/− mice, as well as in monocytes from type 2 diabetic patients relative to controls. Diabetic conditions (high glucose and palmitic acid) induced Dnm3os in mouse and human macrophages. Promoter reporter analysis and chromatin immunoprecipitation assays demonstrated that diabetic conditions induce Dnm3os via NF-&kgr;B activation. RNA fluorescence in situ hybridization and real-time quantitative PCRs of subcellular fractions demonstrated nuclear localization and chromatin enrichment of Dnm3os in macrophages. Stable overexpression of Dnm3os in macrophages altered global histone modifications and upregulated inflammation and immune response genes and phagocytosis. Conversely, RNAi-mediated knockdown of Dnm3os attenuated these responses. RNA pull-down assays with macrophage nuclear lysates identified nucleolin and ILF-2 (interleukin enhancer-binding factor 2) as protein binding partners of Dnm3os, which was further confirmed by RNA fluorescence in situ hybridization immunofluorescence. Furthermore, nucleolin levels were decreased in diabetic conditions, and its knockdown enhanced Dnm3os-induced inflammatory gene expression and histone H3K9-acetylation at their promoters. Conclusions— These results demonstrate novel mechanisms involving upregulation of long noncoding RNA Dnm3os, disruption of its interaction with nucleolin, and epigenetic modifications at target genes that promote macrophage inflammatory phenotype in diabetes mellitus. The data could lead to long noncoding RNA-based therapies for inflammatory diabetes mellitus complications.
LMS-based leader selection for distributed estimation

In this paper we investigate the distributed leader selection algorithm in a LMS-based (least mean squares) adaptive network. We introduce the modified algorithm and express the MSD (mean squared deviation) performance of the algorithm. The outline of the communication and setting of the problem is given and the LMS-based distributed leader selection algorithm is described. We compare the analytical performance of the algorithm to the diffusion algorithms and illustrate that the leader selection has robust performance compared to the diffusion algorithms. Simulation results show that the diffusion algorithms outperform the leader selection algorithm in most cases. However and interestingly, the results also show that leader selection attains the same or even better network performance than the diffusion algorithms in a scenario where one of the nodes is in better conditions (e.g. lower noise power) than the other nodes in the network.
Lowering the sintering temperature of low-temperature solid oxide fuel cells with Sm3+ and Nd3+ co-doped ceria electrolyte

Low-temperature solid oxide fuel cell with co-doped ceria electrolyte is a promising high efficient and cost-effective power conversion device, which needs rapid progress. One of the main issues is high sintering temperatures (1500–1600°C), increasing difficulty and cost in the cell fabrication process. To lower the sintering temperature, Fe has been evaluated as a sintering aid for Sm<sup>3+</sup> and Nd<sup>3+</sup> co-doped ceria electrolyte. The reduction in sintering temperature between Sm<inf>0.1</inf>Nd<inf>0.1</inf>Ce<inf>0.79</inf>Fe<inf>0.01</inf>O<inf>2-δ</inf> and Sm<inf>0.1</inf>Nd<inf>0.1</inf>Ce<inf>0.8</inf> O<inf>2-δ</inf> is as much as 250°. The Sm<inf>0.1</inf>Nd<inf>0.1</inf>Ce<inf>0.79</inf>Fe<inf>0.01</inf>O<inf>2-δ</inf> sintered at an optimal sintering temperature of 1250 °C exhibits the highest grain-boundary conductivity and relative density, which is much higher than that of Sm<inf>0.1</inf>Nd<inf>0.1</inf>Ce<inf>0.8</inf> O<inf>2-δ</inf>. The doping of Fe increases both bulk conductivity and grain boundary conductivity of the SNDC electrolyte. An integrated single cell with Sm<inf>0.1</inf>Nd<inf>0.1</inf>Ce<inf>0.79</inf>Fe<inf>0.01</inf>O<inf>2-δ</inf> electrolyte exhibits a high maximum power density of 458 mWcm<sup>−2</sup> at 650°C, which is 20–30% higher than previous reports.
Simulation and development of a system for the analysis of pressure ulcers

The following article presents preliminary research concepts on the analysis and prevention of pressure ulcers at different stages using a sensor-based system with the purpose of lowering the occurrence of this condition. The general objective is to reduce incidences in bedded patients by improving the detection in areas at risk of developing pressure ulcers or detecting infected wounds once the ulcers have developed. The aim is to build an electronic system with an adequate sensor capable of analyzing the biomarkers released during infection so as to provide a broad analysis of the state of the pressure ulcer. The device takes a picture of an area of an immobilized patient and runs an optimal analysis of potential and present pressure ulcers along with their symptoms. The method used includes Sensors (Adafruit MiCS-5524 MQ2 and MQ3), Arduino programming techniques and Integration of materials (microcontroller). The results will be displayed in a Matlab GUI which the final user may interact with. The MQ2 sensor specifies that the sensor works 75% with alcohol in an environment of 1000 ppm. The combined technologies will be part of a larger project that will include software and hardware development for the device. We conducted a usability test of the interface among potential users and received an average score of 87.75/100.
Selection of renewable power generation to reduce transmission congestion

Congestion management plays a key role in ensuring system security and stability. This is one of the key issues of restructured power system. In this paper, the analysis of system cost benefit issues by optimal placing and sizing of Distribution Resources (DRs) are presented. A methodology for computing system cost benefit parameters is considered and analyzed in this paper. To enhance the performance of the considered methodology, hourly load curve for different DRs is also considered and based on this curve different load intervals are included in the study. The technique considered in this paper consists of economical parameters like, DR cost, system benefit, benefit cost ratio and total congestion rent reduction. In this paper, the analysis is carried out using composite power system and hybrid system with both solar and wind power generations. The methodology considered is illustrated using three bus system in MATLAB environment.
Globalisation of water resources : international virtual water flows in relation to crop trade

The water that is used in the production process of a commodity is called the ‘virtual water’ contained in the commodity. International trade of commodities brings along international flows of virtual water. The objective of this paper is to quantify the volumes of virtual water flows between nations in the period 1995–1999 insofar related to international crop trade and to analyse national virtual water balances in relation to national water needs and water availability. The basic approach is to multiply international crop trade flows (ton/yr) by their associated virtual water content (m ton ). The calculations show that the global volume of crop-related international virtual water flows between nations was 695Gm yr 1 in average over the period 1995–1999. For comparison: the total water use by crops in the world has been estimated at 5400Gm yr . This means that 13% of the water used for crop production in the world is not used for domestic consumption but for export (in virtual form). This is a conservative estimate because only a limited number of crops––although the most important ones––have been taken into account and because crop products (such as cotton clothes) have been excluded from the study. The countries with the largest net virtual water export are United States, Canada, Thailand, Argentina and India. The largest net import appears to be in Japan, the Netherlands, the Republic of Korea, China and Indonesia. r 2004 Elsevier Ltd. All rights reserved.