Miracle-dz/UniFAR-FTUs huggingface dataset:
Tracking in range versus time with application to matched field processing of vertical line array data

Efficient linear three dimensional tracking techniques have been used to improve source localization over that from a single matched-field processing (MFP) ambiguity surface. This paper describes an efficient MFP tracker for data collected by a Vertical Line Array (VLA). The tracker assumes that the source moves at constant speed. Our two dimensional algorithm differs from tracking in three dimensions in that only source range and depth information are required, as would be available for a VLA in an essentially azimuthally independent environment. The source's initial and final range as well as its speed are estimated by the algorithm described in this paper. The method was applied to data which were collected from a VLA as part of PACIFIC SHELF 93. This trial was carried out in the shallow water of the continental shelf and slope off the western coast of Vancouver Island in the north-eastern Pacific Ocean during September 1993. Source track parameters recovered by applying the linear tracker at both 45 and 72 Hz were found to be within the uncertainty associated with the GPS records for the track when the 100 m range uncertainty introduced by the array tether was taken into account. The source level at 45 Hz was typical of a strong line on a merchant vessel while the 72 Hz line was 20 dB lower.
Adaptive Switching Frequency Selection Based on Two-Step Efficiency Optimization for Grid-Connected Inverters

A two-step efficiency optimization of a three-phase voltage source inverter with series R damped LCL filter is proposed. The first optimization step aims to find the optimal parameters of the series R damped LCL filter at rated load conditions. The objective function of step-one is to minimize the values of the passive elements of the filter-stage. Afterward, the magnetic cores of inductors are thoroughly designed using soft magnetic powder materials. This design is proposed to specify the smallest core-size required based on the value of the inductance found in step-one of the optimization. The second optimization step aims to optimally select the switching frequency of the inverter-stage considering load variations. This optimization is based on the optimized filter-stage parameters. The proposed objective function of step-two aims to minimize the power losses in the inverter-stage and filter-stage while limiting the harmonic-levels at the point of common coupling. Detailed loss-formulation including filter-stage core and copper losses is thoroughly presented. Teaching-learning-based optimization algorithm is adopted to perform the optimization problem. Experiment and simulation are done to justify the proposed optimization procedure.
Population genetic structure of a broadcast‐spawning coral across a tropical–temperate transition zone reveals regional differentiation and high‐latitude reef isolation

Genetic connectivity is a key component of species resilience to climate change in terms of recovery capacity following disturbance and capacity to disperse to novel locations as the climate warms and isotherms shift poleward. We aimed to strengthen our understanding of resilience in this context by characterizing patterns of connectivity and genetic diversity in a broadcast spawning coral across a tropical–temperate transition zone. We hypothesize genetic differentiation between tropical and temperate populations and decreasing genetic diversity with higher latitudes.
Modeling and Control of a Hybrid-Electric Vehicle for Drivability and Fuel Economy Improvements

The gradual decline of oil reserves and the increasing demand for energy over the past decades has resulted in automotive manufacturers seeking alternative solutions to reduce the dependency on fossil-based fuels for transportation. A viable technology that enables significant improvements in the overall tank-to-wheel vehicle energy conversion efficiencies is the hybridization of electrical and conventional drive systems. Sophisticated hybrid powertrain configurations require careful coordination of the actuators and the onboard energy sources for optimum use of the energy saving benefits. The term optimality is often associated with fuel economy, although other measures such as drivability and exhaust emissions are also equally important. This dissertation focuses on the design of hybrid-electric vehicle (HEV) control strategies that aim to minimize fuel consumption while maintaining good vehicle drivability. In order to facilitate the design of controllers based on mathematical models of the HEV system, a dynamic model that is capable of predicting longitudinal vehicle responses in the low-to-mid frequency region (up to 10 Hz) is developed for a parallel HEV configuration. The model is validated using experimental data from various driving modes including electric only, engine only and hybrid. The high fidelity of the model makes it possible to accurately identify critical drivability issues such as time lags, shunt, shuffle, torque holes and hesitation. Using the information derived from the vehicle model, an energy management strategy is developed and implemented on a test vehicle. The resulting control strategy has a hybrid structure in the sense that the main mode of operation (the hybrid
Design of Personal Trajectories for Employees’ Professional Development in the Knowledge Society under Industry 5.0

The main feature of Industry 5.0 is “personalization”, linked not only to provide customers with personalized products, but also, in our opinion, to ensure personalization in labor relations with employees, since it increases human value through human–machine collaboration. The human capital quality determines a significant contribution not only to the labor productivity growth, but also to extend a social communication, loyalty and employees’ trust. The study proposes the new methodological approach for corporate human capital assessment and management (CHCM) over new conditions of digital transformation. The CHCM uses methods of system analysis and synthesis, expert assessments, descriptive statistical analysis and survey. The novelty of CHCM is that, firstly, it reflects all the essential features and properties of human capital under emergence of new professions; secondly, it combines and comprehensively uses both quantitative and qualitative methods for human capital assessment, reflecting the subjective and objective aspects of human capital measurement; thirdly, it allows to create warranted management decisions about individual trajectories of professional development of employees, ensuring the continuous growth of individual, corporate and social wealth. It is proved experimentally that the implementation of individual trajectories for employees’ professional development provides 2–3 years’ perspective on companies’ performance growth.
Inhibition of Sphingosine-1-Phosphate Receptor 2 by JTE013 Promoted Osteogenesis by Increasing Vesicle Trafficking, Wnt/Ca2+, and BMP/Smad Signaling

Sphingosine-1-phosphate receptor 2 (S1PR2) is a G protein-coupled receptor that regulates various immune responses. Herein, we determine the effects of a S1PR2 antagonist (JTE013) or a S1PR2 shRNA on osteogenesis by culturing murine bone marrow stromal cells (BMSCs) in osteogenic media with JTE013, dimethylsulfoxide (DMSO), a S1PR2 shRNA, or a control shRNA. Treatment with JTE013 or the S1PR2 shRNA increased alkaline phosphatase and alizarin red s staining, and enhanced alkaline phosphatase, RUNX2, osteocalcin, and osterix mRNA levels in BMSCs compared with the controls. Protein analysis revealed that a high dose of JTE013 (4 or 8 μM) increased vesicle trafficking-associated proteins (F-actin, clathrin, Early Endosome Antigen 1 (EEA1), and syntaxin 6) and Wnt/Ca2+ signaling. On the other hand, a low dose of JTE013 (1 to 2 μM) increased BMP/Smad signaling. In contrast, the S1PR2 shRNA reduced vesicle trafficking-associated proteins and attenuated Wnts and BMP/Smad signaling, but enhanced p-CaMKII compared with the control, suggesting that the S1PR2 shRNA influenced osteogenesis via different signaling pathways. Moreover, inhibiting protein trafficking by brefeldin A in BMSCs suppressed Wnts and BMPRs expressions. These data supported that enhanced osteogenesis in JTE013-treated BMSCs is associated with increased vesicle trafficking, which promotes the synthesis and transport of osteogenic protein and matrix vesicles and enhances matrix mineralization.
DEVELOPING A TOTAL QUALITY MANAGEMENT FRAMEWORK FOR PUBLIC SECTOR UNIVERSITIES IN PAKISTAN

Total Quality Management (TQM) is a management philosophy and practices that aims to harness the human and material resources of an organization in the most effective way to achieve the objectives of the organization. This descriptive study investigated the preparedness of public sector universities in Pakistan for ISO 9001:2008 implementation and proposed a TQM framework. The study was carried out in the backdrop of National Educational Policy 1998-2010 recommendations for implementation of ISO 9000 and Higher Education Commission (HEC) push for enhancing the quality of education. The objectives of the study were to: (a) survey the presence of effective quality assurance processes in HEIs (b) explore the problems faced by HEIs to improve the quality of education (c) explore critical success factors for TQM implementation (d) explore correlation among different management practices in HEIs (e) find out the factors influencing Customer Focus and Satisfaction (f) propose a TQM implementation framework. It studied 25 HEIs through the perceptions of 25 VCs, 25 Registrars, 25 Deans, 500 Teachers and 1500 Students regarding the quality management practices. The study focused on the core activities i.e. teaching, learning and research; and the aspects which had a direct impact on the quality of the educational product. ISO 9001 requirements were used as a survey instrument for Gauging Absence of Prerequisite (GAP) analysis for the implementation of ISO 9001. Descriptive Statistics, Correlation, Regression and ANOVA were performed to analyze the data. The findings indicated that HEIs were strong in the area of measurement, analysis and improvement but weak in resource management and their standing regarding QMS, as a whole, was above average which showed that more need to be done and improved. Customer focus and satisfaction was a dependent variable and a proxy to measure TQM level of implementation. The study revealed management commitment, internal communication, work environment, infrastructure, teaching processes and assessment processes as significant predictors of customer focus and satisfaction. Moreover, all selected TQM factors were positively correlated to one another. The study proposed a TQM implementation framework. It also revealed insufficient financial and physical resources, lack of planning and lack of quality assurance at feeding colleges as top detriments to education quality in HEIs. The study adds to academic knowledge, provides a solid foundation for future research in the area of quality assurance and offers recommendations for quality assurance in HEIs.
Optimization of unit commitment using parallel structures of genetic algorithm

This paper proposes an innovative genetic algorithm (GA) approach to solving the thermal unit commitment (UC) problem using a constraint satisfaction technique. Minimum up-time and down-time constraints on the generating units are embedded in the delicately designed binary strings to represent the on-off states of the units. Ramp rate constraints on the units being started up or shut down are tackled in the economic dispatch subprogram by limiting the associated maximum available capacities for generating. Violations of the other constraints are considered by integrating penalty factors into the cost function. The developed algorithm is further paralleled on an 8-processor transputer network, processors of which are arranged in master-slave and dual-direction ring structures, respectively. The proposed approach is tested on the simple 4 thermal units system and the practical Taiwan Power system of 38 thermal units. Speed-up and efficiency for each structure with different number of processors are compared to those of the sequential GA approach. The proposed approach is shown to be well amenable to parallel implementation.
Information capacity as new figure of merit for Er-doped fiber amplifiers

Information capacity for unsaturated gain regime is proposed as new figure of merit for host glasses for Er-doped fiber amplifiers that are considered as components of optical communication systems. Silicate and phosphate glasses are proved to have the highest total information capacity over the S-, C- and L-bands. In wideband communication systems tellurite glasses are shown to have the maximum capacity.
Beyaz Yeni Zelanda Tavşanlarında Canlı Ağırlıklara Ait Varyans Unsurlarının Farklı Yöntemlerle Tahmini

In this research, it was aimed to determine the variance components of live weights by different methods in New Zeland White Rabbits. In the study, 16 sires, 68 dams and offsprings obtained from these sires and dams were used in the first generation. Second generation was obtained by choosing 22 sires and 84 dams from the first generation offsprings. The variance components and heritabilities of live weight from weaning to 90 th days were estimated by using ANOVA, ML and REML methods in two generations. Estimated heritabilites were found to be low and middle level. In addition, heritabilities estimated from dam variance components were higher than those estimated from sire variance components for all ages.
3D Model Registration-Based Batch Wafer-ID Recognition Algorithm

Wafer identification (ID) is a serial number printed on the surface of wafer, which is used for indexing production process data in manufacture execution system. The automatic recognition of wafer ID is helpful to improve the level of automatic production. However, the existing equipment and methods mainly focus on single wafer-ID recognition, which require wafers to be taken out and placed on a specific platform, resulting in low efficiency. In this paper, we present a batch wafer-ID recognition method based on machine vision, including a specific designed image-acquisition system and recognition algorithms. Based on the priori information, we formulate a 3D model for the cassette and wafers to be registered with the features extracted from the image. Combined with image-processing techniques, the pose of wafers in the cassette is estimated to undistort the perspective deformation of wafer-ID characters, such that we can exploit a classic lightweight convolution neural network for character recognition. The proposed system can capture and recognize the whole image of a cassette of wafers at once, which does not need to take out the wafers from the cassette and avoids the risk of contamination. Extensive experiments were conducted to evaluate the performance of our proposed techniques by collecting the data set of wafer-ID images. The results show that our proposed 3D model-based rectification method can correct the character deformation effectively and enable the lightweight classifier to achieve high speed and high accuracy for batch wafer-ID recognition.
Fault sensitivity and wear-out analysis of VLSI systems

This thesis describes simulation approaches to conduct fault sensitivity and wear-out failure analysis of VLSI systems. A fault-injection approach to study transient impact in VLSI systems is developed. Through simulated fault injection at the device level and subsequent fault propagation at the gate, functional and software levels, it is possible to identify critical bottlenecks in dependability. Techniques to speed up the fault simulation and to perform statistical analysis of fault impact are developed. A wear-out simulation environment is also developed to closely mimic dynamic sequences of wear-out events in a device through time, to localize weak location/aspect of target chip and to allow generation of Time-to-Failure (TTF) distribution of a VLSI chip as whole. First, an accurate simulation of a target chip and its application code is performed to acquire real workload trace data on switch activity. Then, using this switch activity information, wear-out of the each component of the chip is simulated using Monte Carlo techniques.
Removal of Universal Impulse Noise by the Use of Second Order Neighborhood Mean Based Filter

In digital image processing images plays a very vital role as humans can extract meaningful information from it. These images are very often degraded by images. There are various types of noises that affect the quality of digital images. These noises are Gaussian noise, Poisson noise, salt & pepper noise, Impulse noise, Speckle noise etc. But of these the two types of noise that affects the quality of digital images to a large extent are Impulse noise and Gaussian noise. This noiseespecially impulse noiseoccur in the images during image capture, transmission etc. For the detection and removal of impulse noise the mechanism is implemented. This mechanism consists of two stages: In the first stage, detection of noise is performed with the help of impulse detector. The second phase consists of filtering phase where noisy pixels are being repaired with the help of neighborhood mean based filter. This new approach works on both the impulse models – the random valued and /or fixed valued impulse noise models.
Advances in microstrip and printed antennas

Probe-Fed Microstrip Antennas (K. Lee, et al.). Aperture-Coupled Multilayer Microstrip Antennas (K. Luk, et al.). Microstrip Arrays: Analysis, Design, and Applications (J. Huang & D. Pozar). Dual and Circularly Polarized Microstrip Antennas (P. Hall & J. Dahele). Computer-Aided Design of Rectangular Microstrip Antennas (D. Jackson, et al.). Multifunction Printed Antennas (J. James & G. Andrasic). Superconducting Microstrip Antennas (J. Williams, et al.). Active Microstrip Antennas (J. Navarro & K. Chang). Tapered Slot Antenna (R. Lee & R. Simons). Efficient Modeling of Microstrip Antennas Using the Finite-Difference Time-Domain Method (S. Chebolu, et al.). Analysis of Dielectric Resonator Antennas (K. Luk, et al.). References. Index.
Histological and histochemical changes in the peripheral organs of the immune system of dogs in cases of isoniazid poisoning

Most publications on isoniazid poisoning in dogs are devoted to clinical diagnostics, treatment, and prevention of the disease. Histological and histochemical changes are not fully described, though they are important in assessing the toxic effects of isoniazid. Isoniazid is used to treat tuberculosis in humans. Dogs are hypersensitive to this drug. The article highlights the results of macroscopic, histological, and histochemical studies of the dogs’ lymph nodes and spleen in cases of isoniazid poisoning. A pathological examination of 19 corpses of dogs of different ages was performed, during which isoniazid poisoning was posthumously diagnosed, based on anamnesis, clinical signs, pathological autopsy, histological, and histochemical examination. Samples of lymph nodes and spleen were fixed in a 10% aqueous neutral formalin solution, Carnoy’s solution, and Bouin’s fixative. Histoсuts were prepared using a sled microtome and stained with hematoxylin and eosin. Staining was also performed according to the techniques suggested by McManus, Brachet, and Perls. The pathomorphological changes in lymph nodes and spleen were characterized by disorganization of vascular walls and connective tissue fibers of the stroma, dilatation of veins, their overflow with hemolyzed blood, and, in cases of the long clinical course, thrombosis of small vessels. Intravascular hemolysis of erythrocytes resulted in an excessive formation of hemosiderin. Histochemically, the spleen and lymph nodes showed a significant increase in the number of hemosiderophages in the spleen’s red and white pulp and the lymph nodes’ central sinuses and pulp cords. In the spleen, mucoid swelling and necrobiotic changes in the wall structures of the arterioles and arteries progressed with a narrowing of their lumen in dogs suffering from the long clinical course. Increased permeability of the microcirculatory tract vessels of the spleen and lymph nodes, transudate formation, and the destructive changes in the reticular skeleton accompanied hemodynamic violations. A sharp change in blood rheology caused the violation of trophism and metabolism in the immune system. Lymphoid elements of the lymph nodes and white pulp of the spleen were in a state of karyorrhexis and karyolysis. The morphological study of the immune system’s peripheral organs suggests that dogs poisoned by isoniazid demonstrate hemodynamic disorders, changes in the physicochemical properties of blood (hemolysis of erythrocytes and thrombosis). This is the basis of trophic disorders, metabolic malfunctions, and the development of dystrophic processes in all structural elements of the spleen and lymph nodes.
Evaluation of Deep Learning Methods in a Dual Prediction Scheme to Reduce Transmission Data in a WSN

One of the most important challenges in Wireless Sensor Networks (WSN) is the extension of the sensors lifetime, which are battery-powered devices, through a reduction in energy consumption. Using data prediction to decrease the amount of transmitted data is one of the approaches to solve this problem. This paper provides a comparison of deep learning methods in a dual prediction scheme to reduce transmission. The structures of the models are presented along with their parameters. A comparison of the models is provided using different performance metrics, together with the percent of points transmitted per threshold, and the errors between the final data received by Base Station (BS) and the measured values. The results show that the model with better performance in the dataset was the model with Attention, saving a considerable amount of data in transmission and still maintaining a good representation of the measured data.
Supplementary material to "A global open-source database of flood-protection levees on river deltas (openDELvE)"

Abstract. Flood-protection levees have been built along rivers and coastlines globally. Current datasets, however, are generally confined to territorial boundaries (national datasets) and are not always easily accessible, posing limitations for hydrologic models and assessments of flood hazard. Here we present our work to develop a single, open-source global river delta levee data environment (openDELvE) which aims to bridge a data deficiency by collecting and standardising global flood-protection levee data for river deltas. In openDELvE we have aggregated data from national databases as well as data stored in reports, maps, and satellite imagery. The database identifies the river delta land areas that the levees have been designed to protect, and where additional data is available, we record the extent and design specifications of the levees themselves (e.g., levee height, crest width, construction material) in a harmonised format. openDELvE currently contains 5,089 km of levees on deltas, and 44,733.505 km2 of leveed area in 1,601 polygons. For the 152 deltas included in openDELvE, on average 19 % of their habitable land area is confined by verifiable flood-protection levees. Globally, we estimate that between 5 % and 54 % of all delta land is confined by flood-protection levees. The data is aligned to the recent standards of Findability, Accessibility, Interoperability and Reuse of scientific data (FAIR) and is open-source. openDELvE is made public on an interactive platform (www.opendelve.eu), which includes a community-driven revision tool to encourage inclusion of new levee data and continuous improvement and refinement of open-source levee data.