Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-Way Component Analysis for Structured Tensor Data: A Signal Processing Perspective

Summary: This tutorial article reviews models and associated unsupervised learning algorithms for tensor decompositions (TD) and Multi-Way Component Analysis (MWCA). Our aim is to make the area of tensor decompositions ap-proachable to a wider signal processing reader-ship, and to show how they can be made efﬁcient by incorporating various physically meaningful criteria, constraints and assumptions. We next brieﬂy overview emerging models and approaches for multi-block constrained matrix/tensor decompositions in applications to group-and linked-multiway component analysis, feature extraction, classiﬁcation and clustering. The MWCA is a promising methodology for many “cause-effect” type signal processing problems due to its ability to decompose multiway data through the interaction of multiple factors or components. We illuminate that tensor decompositions are natural (non-trivial) and versatile generalizations of some most commonly used signal processing tools such correlation and component analysis and linear regressions. Following the basics of tensor multi-linear algebra and decompositions models, tensor canonical correlation analysis (CCA) and higher-order partial least squares (PLS) are introduced in an intuitive way are supported by illustrative examples.
GENETIC CHARACTERISTICS OF INFECTIOUS BURSAL DISEASE VIRUS IN EGYPT FROM 2012 TO 2014

Received at: 22/8/2015 Accepted: 17/9/2015 The infectious bursal disease virus (IBDV) is a continuing serious problem facing poultry industry in Egypt. In this study, 24 bursae samples collected from different broiler flocks (from Giza, Dakahleya, Ismailia, Damietta and Alexanderia) experiencing high mortality rate and bursal lesions during 2012 to 2014 were examined. Clear differences in pathotyping between very virulent Infectious bursal disease (vvIBD) and classical IBD were observed in pathological examination. Reverse transcriptase polymerase chain reaction (RT-PCR) was applied for IBD targeting hyper variable region (HVR) of VP2 gene. Genetic analysis revealed that 15 viruses belonged to vvIBD that had amino acids A222, I256, I294 and S299 which are highly conserved among vvIBD starins, while 9 viruses belonged to classical IBDV (similar to vaccine strains). The genotyping of Egyptian vvIBDV indicate progressive evolution compared with previously isolated strains which indicates persistence of vvIBDV in Egyptian poultry environment.
A Double-Step Unscented Kalman Filter and HMM-Based Zero-Velocity Update for Pedestrian Dead Reckoning Using MEMS Sensors

In this paper, we propose a novel method for pedestrian dead reckoning (PDR) using microelectromechanical system magnetic, angular rate, and gravity sensors, which includes a double-step unscented Kalman filter (DUKF) and hidden Markov model (HMM)-based zero-velocity-update (ZVU) algorithm. The DUKF divides the measurement updates of the gravity vector and the magnetic field vector into two steps in order to avoid the unwanted correction for the Euler angle error. The HMM-based ZVU algorithm is developed to recognize the ZVU efficiently. Thus, the proposed PDR method can reduce the position drift caused by the heading error and fault zero-velocity measurement. Experimental results demonstrate that the proposed method achieves better yaw estimate, as well as zero-velocity measurement, and obtains more accurate dead-reckoning position than other methods in the literature.
Policosanol and Human Health

Policosanol (PC) is a mixture of very long chain aliphatic alcohols derived from the wax constituent of plants. Sugar Cane Policosanol (SCP) was used in Cuba as dietary supplement since the early 1990s. Today, Cuban SCP and PC isolated from other sources are widely used in supplements for hypercholesterolemia. The oral absorption and bioavailability of PC are limited and their exact lipidlowering mechanisms have not been adequately elucidated. Cuban authors showed that SCP inhibits hepatic cholesterol synthesis prior to the formation of mevalonate, reducing synthesis and increasing degradation of 3-Hydroxy-3Methylglutaryl-Coenzyme A (HMGCoA). Other studies demonstrated that SCP reduces HMGCoA activity via AMP-kinase phosphorilation. Cuban trials reported that 5 to 20 mg/day of the SCP significantly reduce Total Cholesterol (TC), Low Density Lipoprotein Cholesterol (LDL-C) and LDL peroxidation and are effective in improving endothelial cell dysfunction, platelet aggregation and intermittent claudication and pre-hypertension. Research groups outside of Cuba have failed to validate the cholesterol-lowering and antioxidant efficacy of PC. The lack of independent studies confirming the therapeutic benefits of PC in cardiovascular disease prevention and treatment raises questions regarding their true efficacy.
Multicore fiber transmission system for high-capacity optical transport network

This paper reviews high-capacity space-division multiplexed (SDM) optical transport system technologies that support the evolution of broadband networks. Technologies that offer new spatial degrees of freedom such as core multiplexing and mode multiplexing can be introduced to optical transmission systems, optical switching systems, and optical fibers; they overcome the physical limits of today’s transport systems based on single-mode fibers. The expected features of future SDM-based optical transport networks are achieving both high transmission capacity over 1 Pbit/s and node throughputs above 10 Pbit/s, while reducing the power consumption and the size of transport node equipment.
PSI-CNN: A Pyramid-Based Scale-Invariant CNN Architecture for Face Recognition Robust to Various Image Resolutions

Face recognition is one research area that has benefited from the recent popularity of deep learning, namely the convolutional neural network (CNN) model. Nevertheless, the recognition performance is still compromised by the model’s dependency on the scale of input images and the limited number of feature maps in each layer of the network. To circumvent these issues, we propose PSI-CNN, a generic pyramid-based scale-invariant CNN architecture which additionally extracts untrained feature maps across multiple image resolutions, thereby allowing the network to learn scale-independent information and improving the recognition performance on low resolution images. Experimental results on the LFW dataset and our own CCTV database show PSI-CNN consistently outperforming the widely-adopted VGG face model in terms of face matching accuracy.
Worminator: A platform to enable bio-inspired (C. elegans) robotics

Recent years have seen a renaissance in artiﬁcial intelligence (AI) technology and its applications, including robotics. Many of these solutions focus on solving a particular problem in a particular domain or environment. Creating robust and generalizable AI solutions is an area of great interest with applications to many different problem spaces. Biological organisms and biological nervous systems serve as an existence proof that such a generalized intelligence solution is possible. We develop and explore a framework for the simulation of biological networks and extend these simulations to a real-world robotic platform. We focus our initial exploration on a simple, well-deﬁned and highly stereotyped biological neural network (i.e., connectome) derived from the Caenorhabditis elegans nematode. We implement a reference anatomical connectome on a robotic platform, then perturb the network to study the inﬂuence of the network parameters on output behavior. Target perturbations can be derived from neuroscience, robotics, or machine learning domains. This platform is useful for exploring the relationship between learning and behavior for biological organisms and robots. To foster further discovery, we share an open source, easy to use framework with visualization and simulation capabilities and provide an interface to a TurtleBot using ROS.
Bias stability enhancement in thin-film transistor with a solution-processed ZrO2 dielectric as gate insulator

In this paper, a high-k metal-oxide film (ZrO2) was successfully prepared by a solution-phase method, and whose physical properties were measured by X-ray diffraction (XRD), X-ray reflectivity (XRR) and atomic force microscopy (AFM). Furthermore, indium–gallium–zinc oxide thin-film transistors (IGZO-TFTs) with high-k ZrO2 dielectric layers were demonstrated, and the electrical performance and bias stability were investigated in detail. By spin-coating 0.3 M precursor six times, a dense ZrO2 film, with smoother surface and fewer defects, was fabricated. The TFT devices with optimal ZrO2 dielectric exhibit a saturation mobility up to 12.7 cm2 V−1 s−1, and an on/off ratio as high as 7.6 × 105. The offset of the threshold voltage was less than 0.6 V under positive and negative bias stress for 3600 s.
Suitability Mapping Of Small Farm Reservoirs Using K-Nearest Neighbors And Random Forest Algorithms

The Philippines is highly vulnerable to the impacts of climate change, including, rising temperatures and increased frequency of extreme drought. Small Farm Reservoir (SFR) is a type of rainwater harvesting system used for supplemental irrigation. However, location suitability poses major challenges in implementing SFR. In this study, K-Nearest Neighbors (KNN), and Random Forest (RF) were utilized to conduct site suitability analysis and to identify suitable locations for SFR. The findings of this study indicated that the application of KNN and FR could be suggested for identification of suitable locations for SFR in other regions.
OP-ICVA200312 1..9

OBJECTIVES: Venoarterial extracorporeal life support (ECLS) has emerged as a potentially life-saving treatment option in therapyrefractory cardiocirculatory failure, but longer-term outcome is poorly defined. Here, we present a comprehensive follow-up analysis covering all major organ systems. METHODS: From February 2012 to December 2016, 180 patients were treated with ECLS for therapy-refractory cardiogenic shock or cardiac arrest. The 30-day survival was 43.9%, and 30-day survivors (n = 79) underwent follow-up analysis with the assessment of mediumterm survival, quality of life, neuropsychological, cardiopulmonary and end-organ status. RESULTS: After a median of 1.9 (1.1–3.6) years (182.4 patient years), 45 of the 79 patients (57.0%) were alive, 35.4% had died and 7.6% were lost to follow-up. Follow-up survival estimates were 78.0% at 1, 61.2% at 3 and 55.1% at 5 years. NYHA class at follow-up was <_II for 83.3%. The median creatinine was 1.1 (1.0–1.4) mg/dl, and the median bilirubin was 0.8 (0.5–1.0) mg/dl. No patient required dialysis. M EC H A N IC A L C IR C U LA TO R Y SU P P O R T VC The Author(s) 2020. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved. Interactive CardioVascular and Thoracic Surgery (2020) 1–9 ORIGINAL ARTICLE doi:10.1093/icvts/ivaa312 D ow naded rom http/academ ic.p.com /icvts/advance-art.1093/icvts/ivaa312/6042989 by gest on 24 D ecem er 2020 Overall, 94.4% were free from moderate or severe disability, although 11.1% needed care. Full re-integration into social life was reported by 58.3%, and 39.4% were working. Quality of life was favourable for mental components, but a subset showed deficits in physical aspects. While age was the only peri-implantation parameter significantly predicting medium-term survival, adverse events and functional status at discharge or 30 days were strong predictors. CONCLUSIONS: This study demonstrates positive medium-term outcome with high rates of independence in daily life and self-care but a subset of 10–20% suffered from sustained impairments. Our results indicate that peri-implantation parameters lack predictive power but downstream morbidity and functional status at discharge or 30 days can help identify patients at risk for poor recovery.
Tick-borne pathogens infecting dogs from a highland swamp area

1 Aluno de graduação Universidade Federal do Agreste de Pernambuco ˗ Garanhuns, PE 2 Aluno de pós-graduação Universidade Federal do Agreste de Pernambuco ˗ Garanhuns, PE 3 Aluno de pós-graduação ˗ Department of Veterinary Medicine University of Bari ˗ Valenzano, Italy 4 Faculdade de Medicina Veterinária e Zootecnia ˗ Universidade Federal de Mato Grosso do Sul ˗ Campo Grande, MS 5 Universidade Federal do Agreste de Pernambuco ˗ Garanhuns, PE
Finding Plausible Optimal Solutions in Engineering Problems Using an Adaptive Genetic Algorithm

In engineering, optimization applications are commonly used to solve various problems. As widely known, solution of an engineering problem does not have a unique result; moreover, the solution of a unique problem may totally differ from one engineer to another. On the other hand, one of the most commonly used engineering optimization methods is genetic algorithm that leads us to only one global optimum. As to mention, engineering problems can conclude in different results from the point of different engineers’ views. In this study, a modified genetic algorithm named multi-solution genetic algorithm (MsGA) based on clustering and section approaches is presented to identify alternative solutions for an engineering problem. MsGA can identify local optima points along with global optimum and can find numerous solution alternatives. The reliability of MsGA was tested by using a Gaussian and trigonometric function. After testing, MsGA was applied to a truss optimization problem as an example of an engineering optimization problem. The result obtained shows that MsGA is successful at finding multiple plausible solutions to an engineering optima problem.
Status Externalities and Low Birth Rates in Korea∗

South Korea has been experiencing a very low total fertility rate around 1.2 over the last two decades. A serious concern of the Korean government about low fertility is demonstrated by its billions-dollars worth spending in recent years. In this paper, we aim to understand why the birth rate is so low in Korea and to assess whether there is a reason for the government to be concerned. We ask what, if anything, could and should be done about the low fertility rate. To do so, we propose status externalities as a new reason for inefficiently low fertility. In our model with endogenous fertility, parents care about the education of their children relative to other parent’s children. We find that the equilibrium is characterized by over-investment in education and under-investment in fertility, relative to the first best. We calibrate the model to Korean data to quantify the role of the status externality. We find that without it fertility would be 17% higher. We also find the externality plays a large role in explaining the fertility-income relationship, which is positive in Korea, in contrast to most other countries. We conduct several policy experiment and find that taxing education would not be desirable in welfare terms, even though it reduces the over-investment. Similarly, pronatal transfers do increase the fertility rate but are also not welfare improving. We conclude that more subtle policies are needed to rectify the friction introduced through status concerns.
Integrin subunit mRNAs are differentially expressed in early Xenopus embryos

to tadpole stages. In addition, 3 is expressed in the forebrain region of later stage embryos. These data suggest that integrin-mediated adhesion may be involved in the process of mesoderm involution at gastrulation and the organization of tissues during embryogenesis. Whole-mount in situ hybridization was carried out using albino embryos as described by Harland (1991). Digoxigenin-rUTP- labelled (Boehringer Mannheim Biochemical) integrin a 3 probes were synthesized from Eco RI (antisense) or Kpn I (sense) linearized FF2 D E (Meng, Whittaker, Hens, Ransom and DeSimone, unpublished data) cDNA templates. Embryos were photographed on a Zeiss Axiophot using bright-ﬁeld and differential interfer-ence contrast optics.
ERROR COMPONENTS IN DEMAND ESTIMATION

Models including error components are today at the frontier of application and development in transport modelling. The name Error Component Models is often used indiscriminately with Random Parameters Logit, Models with Stochastic (or Distributed) Preferences (or Coefficients), Logit Kernel Models or Mixed Logit Models. In general the method of Maximum Simulated Likelihood (MSL) is applied, although this only optimises within a given a priori distribution of the error components (EC). Only few of the analyses so far have dealt with the interesting question of correlation between these error components. An alternative method to determine the distributions is to uncover the empirical distribution of the data by repeated estimations. The purpose of the method is to determine the type of distribution, though (for some distributions) it can determine the parameters of the distribution. It was found that it is likely that the error components (random coefficients) are log-normally distributed - and perhaps more interesting, that correlation between the error components is outspoken. The paper compares logit models built, assuming a traditional utility function (linear, without EC), random coefficients (linear, with ECs added to the coefficients); ECs on orthogonal elements (principal components), without linear utility (primarily for reference); and linear utility with ECs on orthogonal elements (whereby independent distributions of EC can be expected). All utility functions with ECs are set up two times, specified as independent distributions and simultaneous distributions. This paper makes a full comparison of models based on the above 7 different utility functions (everything else being equal) with a focus on model fit as well as (potentially different) distribution of error components dependent on the functional form of the utility function. The paper concludes with guidelines on how to include error components in demand estimation. For the covering abstract see ITRD E124693.
Open and Flexible Li-ion Battery Tester Based on Python Language and Raspberry Pi

Technology improvements and cost reduction allow electrochemical energy storage systems based on Lithium-ion cells to massively be used in medium-power applications, where the low system cost is the major constraint. Battery pack maintenance services are expected to be required more often in the future. For this reason, a low-cost instrumentation able to characterize the cells of a battery pack is needed. Several works use low-cost programmable units as Li-ion cell tester, but they are generally based on proprietary-software running on a personal computer. This work introduces an open-source software architecture based on Python language to control common low-cost commercial laboratory instruments. The Python software application is executed on a Raspberry Pi board, which represents the control block of the hardware architecture, instead of a personal computer. The good results obtained during the validation process demonstrate that the proposed cell station tester features measurement accuracy and precision suitable for the characterization of Li-ion cells. Finally, as a simple example of application, the state of health of twenty 40 Ah LiFePO4 cells belonging to a battery pack used in an E-scooter was successfully determined.
Development of Modular Unmanned Surface Vehicle for Research and Education

Mobile robots are used for years as a valuable educational and research tool in form of available open-platform designs and Do-It-Yourself kits. Rapid development and costs reduction of Unmanned Air Vehicles (UAV) and ground based mobile robots in recent years allowed researchers and students to utilize them as an affordable education platform. Despite of recent developments in the area of ground and airborne robotics, only few examples of Unmanned Surface Vehicle (USV) platforms targeted for educational and research purposes can be found. Aim of this paper is to present development of opendesign USV drone with integrated multi-level control hardware architecture. Catamaran type surface drone is planned to be utilized as a research and education platform for students, where various control algorithms, communication interfaces and sensor payloads can be implemented and tested. Proposed USV enables autonomous navigation or direct control over wireless radio link, separate development of algorithms for optimal propulsion control, navigation and communication with the ground-based control station. Whole design is planned to be highly modular, where each component can be replaced or modified according to desired task, payload or environmental conditions. Keywords—unmanned surface vehicle, control system, mobile robotics
Monitoring Tool Wear in Drilling Process Using Spindle Noise Features

The use of worn cutting tools has a detrimental effect on the surface finish of a workpiece, tool precision and internal machine stress. Worn tools also decrease productivity through unplanned stops, tool changes and increase the production of scrap material. This study investigates an inexpensive and non-intrusive method of inferring tool wear by measuring the audible sounds emitted during a drilling process. A microphone was used to record the machining operation sound of S50C steel, which was drilled using a computer numerical control (CNC) milling machine in wet conditions. The audio signature was examined using a spectrogram, and the extracted sound features of the rotating spindle motor in the frequency domain were used to correlate with tool wear. The results indicated that the frequency of spindle noise was unrelated to tool wear, but although the magnitude of spindle noise significantly increased in accordance with tool wear progression.
Journal of Educational Studies and Multidisciplinary Approaches (JESMA) www.jesma.net Perception and knowledge of critical thinking: A qualitative research study with Professors of Higher Education in Oman

Journal of Educational Studies and Multidisciplinary Approaches(JESMA) is an international scientific, high-quality open access, peer viewed scholarly journal that provides a comprehensive range of unique online-only journal submission services to academics, researchers, advanced doctoral students and other professionals in their field. This journal publishes original research papers, theory-based empirical papers, review papers, case studies, conference reports, book reviews, essays and relevant reports twice a year (March and October) in online versions.
Mass Production of Paulownia tomentosa Trees by Micropropagation

This study was carried out in the Tissue Culture Lab (TCL), in Al-Zahriya Garden at the Horticultural Institute of Agricultural Research Center in Giza, Egypt between 2018 to 2020. This study indicates the effect of different water sources and cytokinins during the proliferation stage of in vitro propagation Paulownia tomentosa plant. In this study, we do that by culturing tissues on epiphytic plants obtained from the same laboratory in the Zohriya garden. the first factor was the water source (tap and distilled water) Two different types of water sources were used: distilled water and tap water. Chemical analysis of tap water was carried out from pH TDS, TSS, EC NO3 and Ca, Na, and the second factor was the cytokinin treatments where three different types of cytokinins BA, Kin, and TDZ were used at different concentrations, 1mg/L, 2 mg/L 3mg/L 4mg/L and 5mg/L. At control concentration [0mg/L], The experiment was conducted by this study to find out the best protocol for in vitro micropropagation of Paulownia tomentosa. The results showed that the BA at 2mg/L got the highest rank for shoot length and shoot number and BA at 3mg/L got the highest rank of leaves number and shoot fresh weight while using Kin at 3mg/L got the highest rank for shoot length and total chlorophyll content. Therefore, we recommend using 2mg/L from BA with Kin at 3mg/L to get the highest rate of shoot length and shoot number and the highest rate of chlorophyll content.