Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanism and Suppression of Frequency-Decrease Effect Related to the Low Modulation Frequency Ratio in a High-Ratio MMC-Based DC Transformer

The high-ratio MMC-based DC transformer is the crucial device for the interconnection between different DC distribution networks. Compared to the typical MMC, the transformer has a similar structure and low modulation frequency ratios (FR). Thus, it also has the severe frequency-decrease effect and similar operating performance deterioration. However, because of the extremely lower FRs that are close to 1, the feature of the frequency-decrease effect in the transformer has different manifestations. And because of the two-stage structure which combines the MMC and rectifiers, more factors emerged in the transformer to determine the frequency-decrease effect. Therefore, this study further develops the theory and elaborates the frequency effect's mechanism that is originally from the MMC to adapt to the more complex structure of the transformer. A quantitative analysis of the frequency-decrease effect is then provided, demonstrating that because of the transformer's two-stage structures, two types of FRs and concomitant factors exist in the transformer, thus having a combined effect on the harmonic distributions of capacitor voltages and causing more proportional voltages' harmonics distorting into the slope harmonics. Based on the analysis, the study entirely redesigns the FRs and regulates the modulation strategy of the transformer to fundamentally eliminate the frequency-decrease effect. The study also confirms that the FRs in the two sides cannot be set to the same, and their decimal part cannot cause extra low-frequency harmonics. The frequency-decrease effect, the deteriorations, and the efficiency and comparisons of the proposed methods are finally demonstrated via simulations and experiments.
MITOCHONDRIAL DISORDERS AND THEIR CORRECTION IN NEUROLOGICAL DISEASES

Mitochondria are cellular organelles that produce energy in the form of ATP. For this reason, they are called "power stations" or "energy factories". Mitochondria have their DNA. Part of mitochondrial DNA in the process of phylogenesis moved into nuclear DNA. There are 4 types of metabolism in mitochondria: a) Transfer of electrons in the respiratory chain with the formation of ATP and oxygen, b) Fat metabolism with the participation of carnitine, c) Amino acid metabolism, d) Carbohydrate metabolism. There are 2 groups of mitochondrial pathology: Primary mitochondrial pathology is hereditary syndromes caused by mutations in genes responsible for mitochondrial proteins (Kearns-Sayre syndrome, Pearson syndrome, MELAS syndrome, MERRF syndrome, and others). Secondary mitochondrial pathology includes dysfunction of mitochondria as an important link in pathogenesis. Primary mitochondrial diseases are caused by mutations in mitochondrial DNA or nuclear DNA that affect the respiratory chain or mtDNA homeostasis. Secondary mitochondrial disorders have been identified in common sporadic neurological diseases, including Alzheimer's disease, Parkinson's disease, and other pathologies. ASEAN Journal of Psychiatry, Vol. 23(1) January, 2022; 1-9.
Output feedback control of stochastic nonlinear systems based on extended state observer

In this article, we study the controller design and stability analysis for a class of stochastic cascade nonlinear systems with external disturbances. The unmeasurable external disturbance is viewed as an extended state. In order to estimate the unmeasurable system states and the external disturbance, a new extended state observer (ESO) based on the Riccati differential equation is constructed. The stochastic inverse dynamics, the error dynamics of observer, and the ESO constitute new stochastic nonlinear systems. Based on these new systems, an adaptive output feedback controller is proposed by combining stochastic input‐to‐state stability with backstepping design technique. In stability analysis, it has been shown that the designed controller can guarantee that all closed‐loop system signals are almost surely bounded and the original system states are globally asymptotically stable in probability. Finally, a simulation example is given to the validity of the proposed method.
Klasifikasi Video Olahraga Berdasarkan Citra Berbasis Konten Menggunakan Segmentasi Superpixel

– Type of sport has a large number and its number is always increasing as the time goes by. Many people like to watch sports competitions or tournaments on the field live. Nowadays, sports tournaments can now be watched digitally via video without the need to watch them live on the field by technological advances. Video classification needs to be done to differentiate the number of sports videos currently into the sports category according to the content. This study classifies sports videos of the types of Baseball, Basketball, Boxing, Gymnastic, Hockey, Swimming, Tennis, Volleyball
Research_9869734 1..15

State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China Department of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
BooVI: Provably Efficient Bootstrapped Value Iteration

Despite the tremendous success of reinforcement learning (RL) with function approximation, efﬁcient exploration remains a signiﬁcant challenge, both practically and theoretically. In particular, existing theoretically grounded RL algorithms based on upper conﬁdence bounds (UCBs), such as optimistic least-squares value iteration (LSVI), are often incompatible with practically powerful function ap-proximators, such as neural networks. In this paper, we develop a variant of bootstrapped LSVI, namely BooVI, which bridges such a gap between practice and theory. Practically, BooVI drives exploration through (re)sampling, making it compatible with general function approximators. Theoretically, BooVI inherits the worst-case (cid:101) O ( √ d 3 H 3 T ) -regret of optimistic LSVI in the episodic linear setting. Here d is the feature dimension, H is the episode horizon, and T is the total number of steps.
Understanding how video games playing affects individuals

This study addresses the important and recurring question of whether playing video games is detrimental to the socio-economic development of a person. It does this by using novel data from the Taking Part Survey in England to establish whether games playing is associated with particular socio-economic characteristics and/or other forms of cultural participation. The results do not indicate any obviously negative effects of video games playing: rather, those who play are typically better educated and no less wealthy, and games players are also more likely than non-games players to participate in other forms of culture, particularly active forms of participation. These findings are reinforced when comparing the characteristics of individuals who did and did not play video games when younger. Did you really take a hit? Understanding how video games playing affects individuals
Lecture 6: NTK for Deep Networks and the Convolutional NTK (CNTK)

Thus far, we have presented tools to compute the NTK/NNGP for fully connected networks with 1 hidden layer. We now present a derivation of the NTK/NNGP for fully connected networks of arbitrary depth. Namely, the NTK/NNGP of infinitely wide fully connected networks of depth L can be written concisely as a recursion in terms of the NTK/NNGP of networks of depth L− 1. In order to showcase the flexibility of the NTK framework, we introduce the NTK for a 1 hidden layer convolutional network, i.e. the CNTK. Importantly, we will show that the CNTK involves computing a kernel across all pairs of pixels over all pairs of images unlike the NTK, which only involves computing a kernel across all pairs of images. We lastly present experiments utilizing the Neural Tangents library [6] demonstrating the effectiveness of the NTK/CNTK in practice.
Original Contribution Functional Variants in the Catalase and Myeloperoxidase Genes, Ambient Air Pollution, and Respiratory-related School Absences: An Example of Epistasis in Gene-Environment Interactions

The individual effect of functional single nucleotide polymorphisms within the catalase and myeloperoxidase genes (CAT and MPO) has been studied in relation to asthma; however, their interrelationship with ambient air pollution exposures has yet to be determined. The authors investigated the interrelationships between variants in CAT and MPO, ambient air pollutants, and acute respiratory illness. Health information, air pollution, and incident respiratory-related school absences were ascertained in January–June 1996 for 1,136 Hispanic and non-Hispanic white US elementary schoolchildren as part of the prospective Children’s Health Study. Functional and tagging single nucleotide polymorphisms for the CAT andMPO loci were genotyped. The authors found epistasis between functional polymorphisms in the CAT/MPO loci, which differed by levels of oxidant-stress-producing air pollutants. Risk of respiratory-related school absences was elevated for children with the CAT (G/G) and MPO (G/A or A/A) genes (relative risk 1⁄4 1.35, 95% confidence interval: 1.03, 1.77; P-interaction 1⁄4 0.005). The epistatic effect ofCAT and MPO variants was most evident in communities exhibiting high ambient ozone levels (P-interaction 1⁄4 0.03). The association of respiratory-illness absences with functional variants in CAT and MPO that differ by air pollution levels illustrates the need to consider genetic epistasis in assessing gene-environment interactions.
Productivity , shocks , and management practices

We examine the links between productivity and shocks, particularly exchange rate fluctuations on firm productivity, with data from Ethiopia and Uganda. These two countries offer a useful comparison: they are two small land-locked economies with different exchange-rate regimes. Uganda has a floating exchange-rate regime in contrast to the crawling peg regime effective in Ethiopia. We focus on currency shocks to the costs of imported inputs:using matched customs and firm-level data to examine the impact of currency shocks and input shortages. A particular advantage is that we use the actual currency of invoicing rather than the bilateral exchange rate to construct the measure of currency shocks. For Ethiopia, where we have detailed data on management practices, we also ask whether management affects productivity. We find that depreciations raise productivity, potentially through increased competition in Ethiopia but leave Ugandan productivity unaffected. Good management matters for firm productivity in Ethiopia but does not mitigate the effects of shocks. ∗We are grateful to Dr Adam Mugume and Dr Louis Kasekende for their help and their interest in this project. We are very grateful to Meredith Crowley whose collaboration on the project to examine exchange rates has helped refine this paper. We thank Jacob Raushendorfer, the Country Economist for the IGC in Uganda and David Henning for his excellent research assistance with the data on Uganda used here and Rahel Solomon for her valuable help with the data on Ethiopia. We gratefully acknowledge support from the International Growth Centre’s special grant call for this project (project 32424). The views expressed in this article are those of the authors. †IGC=International Growth Centre ‡University of Oxford §University of Oxford and CEPR ¶Ethiopian Development research Institute
LoS/NLoS Identification Based on Double-Polarized Antenna and Convolutional Neural Networks

5G New Radio has a unique value in improving positioning capabilities, which can achieve centimeter-level indoor positioning. This not only brings convenience to our daily life, but also will play an important role in the industrial field. At present, the Industrial Internet of Things (IIoT) based on 5G private network has emerged. However, none-line-of-sight (NLoS) and line-of-sight (LoS) channel states have a great influence on the accuracy of indoor positioning. If the LoS/NLoS channel propagation states cannot be distinguished, the quality and efficiency of industrial production will be affected. In this paper, we innovatively use the characteristics of dual polarized antennas between the transmitter and receiver, and combine Convolutional Neural Networks (CNN) to propose a LoS / NLoS identification method. We use the Quadriga channel model which conforms to the channel standard of The 3rd Generation Partnership Project Technical Report 38.901 for simulation, and the simulation results show that the accuracy rate of selecting 3 base stations with LoS path can reach 98.5% and 99% respectively in the two IIoT baseline scenarios. Therefore, the proposed algorithm has good classification performance.
Aboul Azm et.al. Characterization Evaluation Osseointegration PEEK Implants Using Nano-Hydroxyapatite Characterization and Evaluation of Osseointegration of Modified PEEK Implants Using Nano-hydroxyapatite Particles: Laboratory and Experimental Study

INTRODUCTION: Polyetherether ketone (PEEK) is a semicrystalline thermoplastic polymer that has been proposed as a substitute for metals in dental implants biomaterials because of its mechanical and biological properties. OBJECTIVES: This study was aimed to prepare and characterize PEEK implant materials modified by different methods using nanoparticles of hydroxyapatite to overcome its limited bioactivity. The study also evaluated the ability of the modified PEEK implant to enhance osseointegration in a rabbit model. METHODS: Four groups of PEEK specimens were prepared. Group1: specimens were constructed from untreated PEEK (control group), group2: specimens were coated with nanoparticles of hydroxyapatite (nHA) after etching the PEEK surfaces with sulfuric acid (98%) for one minute, group3: specimens were be coated with nanoparticles of hydroxyapatite (nHA) after PEEK surfaces treatment with Nd: YAG laser and group4: specimens were be constructed from melt-blended PEEK powder with nanoparticles of hydroxyapatite (nHA/PEEK). Each of the four groups were characterized by scanning electron microscope (SEM), Energy-dispersive X-ray (EXD), Fourier-transformed infrared spectroscopy (FTIR), X-ray Diffraction (XRD), contact angle measuring device and flexural strength test. The ability of each of the four groups to enhance bone osseointegration was evaluated in a rabbit model, by using histomorphometrical analysis. RESULTS: Data was collected, summarized and statistically analyzed using the suitable methods. CONCLUSION: PEEK biocompatibility and its chemical inertness can be improved with coating the surface with nano sized HA or mix blended of PEEK with nHA which does not affect its mechanical strength.
Narrative Educational Games for New-Normal Preschool Education: A Case Study in TK Lintang, Surabaya

Educational games are a state-of-the-art method for education in the 21st century. However, they have not been applied for new-normal education in preschools. To contribute to the matter, we developed an educational game to help TK Lintang, a preschool institution in Surabaya, conduct "Jari Aritmetika" or "Magic Fingers" learning and teaching. We chose the visual novel as the game's genre, and the game presented Jari Aritmetika through storytelling and cartoon visuals. We developed the game in two iterations by considering "ease of use" as its nonfunctional requirement. Our results are two versions of the game (mobile and desktop) and an information system for modifying the game’s arithmetic questions. Our game acquired a 4.79, out of 5, mean value in a testing process involving four students and their parents, proving the game’s effectiveness for entertainment and education. We have also extracted five principles of educational game applications in new-normal preschool education, including facilitating "family time" between students and their parents.
Iterating on multiple collections in synchrony

Abstract Modern programming languages typically provide some form of comprehension syntax which renders programs manipulating collection types more readable and understandable. However, comprehension syntax corresponds to nested loops in general. There is no simple way of using it to express efficient general synchronized iterations on multiple ordered collections, such as linear-time algorithms for low-selectivity database joins. Synchrony fold is proposed here as a novel characterization of synchronized iteration. Central to this characterization is a monotonic isBefore predicate for relating the orderings on the two collections being iterated on and an antimonotonic canSee predicate for identifying matching pairs in the two collections to synchronize and act on. A restriction is then placed on Synchrony fold, cutting its extensional expressive power to match that of comprehension syntax, giving us Synchrony generator. Synchrony generator retains sufficient intensional expressive power for expressing efficient synchronized iteration on ordered collections. In particular, it is proved to be a natural generalization of the database merge join algorithm, extending the latter to more general database joins. Finally, Synchrony iterator is derived from Synchrony generator as a novel form of iterator. While Synchrony iterator has the same extensional and intensional expressive power as Synchrony generator, the former is better dovetailed with comprehension syntax. Thereby, algorithms requiring synchronized iterations on multiple ordered collections, including those for efficient general database joins, become expressible naturally in comprehension syntax.
Accelerating Deep Learning for Shared Facility Centers Using Tensorflow Framework Analysis Based on IBM POWER Platform

In the present paper, the effectiveness of using various versions of the TensorFlow framework on the OpenPOWER platform IBM S822LC is discussed. Special emphasis is given to the conditions of shared facility centers that influence the possible solutions for deep learning research hardware and software. Different versions of TensorFlow were tested, including one specially compiled for the IBM POWER platform. It is shown that TensorFlow version 1.1. 0 from Anaconda repositories is 23% less effective than the version from the IBM PowerAI package. At the same time, TensorFlow 1.2. 1 surpasses all considered versions due to the efficient disposal of hardware. Thus, we may conclude that the novelty of the version of a deep learning framework is a significant factor and may surpass the special optimization techniques in terms of computing performance.
Overview of Oil and Gas Pipeline Failure Database

Oil and gas pipeline failure database comprises many failure cases. Through failure information gathering and analyzing, pipeline operators can find out the trend of failure occurrences and evaluate the performance of pipeline management. There are a number of institutions involve failure data management. Databases can be categoried as three types according to their managers: 1) owned by one company, who collects and analyzes failure informations in their own company, such as PetroChina; 2) managed by authoritative management department, who collects and analyzes failure informations of companies under their responsibility, such as PHMSA (Pipeline & Hazardous Materials Safety Administration); 3) managed by an international group formed through cooperation agreement between several countries and international companies, who collects and analyzes failure informations of companies in the group, such as EGIG (European Gas Pipeline Incident Data Group). Failure defining and information gathering by different database managers are disscussed in this paper, which compares their failure rates and trends that newly announced as well. The failure database management of PetroChina is emphasized by the author. Improvement of failure database can be technically supportive for pipeline engineering critical assessments, and would be important references for risk assessment, as the determination of failure probability and consequence are based on the statistical results. Failure incidents are precious wealth for companies, which can reveal the shortages of pipeline management and emergency rescue and enhance the operation safety.
POTENTIAL INFLUENCES OF INDONESIAN CORPORATE ARCHITECTURAL DESIGN STANDARDS ON CHARACTER OF PLACE

Corporate Architectural Design (CorpAD) has been playing a significant role in shaping the faces of Indonesian cities. This paper aims to identify the features of twelve Indonesian CorpAD standards and their potential influences on local character of place. This research applies content analysis and spatial configuration analysis to twelve Indonesian companies’ CorpAD standards manuals. Four considerations, twelve elements of CorpAD and spatial arrangements characters were identified. The CorpAD standards potentially influence on local characters of place in terms of visual quality of the surroundings, social interactions and street life.
ANALYSIS OF THE GENOTYPE 6 ENVIRONMENT INTERACTION IN MUSA TRIALS By I. DE CAUWER and R. ORTIZ{

Plantain hybrids and landraces, and banana cultivars (Musa spp. L.) were evaluated for three years in the plant and ratoon crops at three locations in the humid lowland forest (Mbalmayo and Onne) and derived savanna (Ibadan) agro-ecozones of sub-Saharan Africa. Additive main eects and multiplicative interaction (AMMI) models accounted for a signi®cant percentage of the genotype6 environment interaction (GE) aecting bunch weight (kg plant) and yield potential (t ha a). Obino l'Ewai, a plantain landrace, showed little GE for bunch weight, whereas the exotic cooking banana cultivar Cardaba had the most stable yield potential as revealed by the biplots of the GE analysis (AMMI-2 biplots). Plantain hybrids achieved high yield potential due to their short growth cycle. The high yield potential of the cooking bananas was mainly the result of their fast sucker development.
The Use of Educational Technology at Tertiary Level Eğitim Teknolojisinin Üniversitede Kullanimi

* ABSTRACT: This study examined the use of educational technology at tertiary level at one of the newly established (i.e. 2007) universities in the eastern part of Turkey in the spring of 2012. The study examined the tertiary teaching staffs" (a) personal and computer related characteristics, (b) their computer self-efficacy perceptions, (c) their computer-using level in certain software, (d) their frequency of computer use for teaching, administrative and communication objectives, and (e) their use of educational technology preferences for preparation and teaching purposes. In this study, all teaching staffs were given the questionnaires to complete. 194 participants (n= 194) completed and returned them. The study was mostly quantitative and partly qualitative. The quantitative results were analysed with SPSS (i.e. mean, Std. Deviation, frequency, percentage, ANOVA). The qualitative data was analysed with examining the participants" responses gathered from the open-ended questions and focussing on the shared themes among the responses. The results reveal that the participants have high computer self-efficacy perceptions, their level in certain programs is good, and they often use computers for a wide range of purposes. There are also statistical differences between (a) their computer self-efficacy perceptions, (b) frequency of computer use for certain purposes, and (c) computer level in certain programs in terms of different independent variables.