bluuebunny/crossref_metadata_2025 huggingface dataset:
A Study of Quality in Primary Education Combined Disjoint Block Neutrosophic Cognitive Maps (CDBNCM)
Authors:   M.Phil Mathematics, Department of Mathematics, Loyola College, Chennai-34, India, Bellarmin A. Joseph , Devadoss A.Victor ,   Head & Associate Professor, Department of Mathematics, Loyola College, Chennai 34,India, Anand M. Clement Joe ,   Ph.D Research Scholar, Department of Mathematics, Loyola College, Chennai-34, India
Published: February 2023

Quality in primary education has been classified into five factors involving learners, content, processes, environment and outcomes. In this paper we analyzed, quality in primary education in Chennai and find out its solution using Neutrosophic cognitive maps (NCMS), which is the generalization of fuzzy cognitive maps (FCMS) defined by W.B. Vasantha Kandasamy and Florentine Smarandache. This paper has five sections. First section gives information about development of fuzzy cognitive maps and Neutrosophic cognitive maps. Second section gives the preliminaries of FCMS and NCMS. In section three, we give the description of the problem; final section gives the conclusion based on our study.
Enhanced Hand Gesture Recognition In Augmented Reality Using Genetic Algorithm
Authors:   M.Phil. Research Scholar,Department of Computer Applications, Alagappa University, Ms M.Sivaneshwari
Published: February 2023

Hand Gesture recognition is technology which interpret human gestures using various algorithms.Interpreting human hand gestures has various challenges and issues such as image noise,visibility and orientation. There are various kinds of computer based algorithms have been proposed in the literature to overcome these limitations and still needs improvement. Hence in this research work a new Hand Gesture recognition system for augmented reality using Genetic Algorithm and Artificial neural network algorithm has been proposed.This shows that the experiment is successful and gesture recognition system is vigorous against various changes that are made in illumination changes and background changes. Experimental results show that the extracted features are effective, robust, and can cover the entire feature space of the selected gestures. This method satisfactory performance when compared with convensional methods
An Innovative System for Classifying Cervical Cancer Using Features Based ANFIS Classifier
Authors:   Assistant Professor Department of Computer Applications, Alagappa University, Karaikudi, Mr A.Nagarajan
Published: February 2023

Cervical Cancer (CC) is one among the most vulnerable and exceedingly affected diseases among ladies around the globe. Usually, cells develop and divide to deliver more cells just when the body needs them. The proposed model exhibits cost sensitive classifiers that have three primary stages the principal stage is preprocessing the original data to set it up for classification model which is developed based on Adaptive Neuro Fuzzy Inference System (ANFIS) classifier. To enhance the classifying accuracy for determining the cervical cancer threat, we are considering Whale Optimization (WO) to select optimal features like both genetic and natural components. The motivation behind data mining is to discover some data which isnot specifically obvious or retrievable by perusing data or executing simple inquiries to the data. A precise and convenient prediction could maintain a strategic distance from any future issue at a specific level
An Investigation into Brain Tumor Segmentation Techniques
Authors:   Research Co-ordinator & Asst. Professor, PG & Research Dept. of Computer Science, Periyar E.V.R. College, Mr T.N.Ravi
Published: February 2023

A tumor is an anomalous mass in the brain which can be cancerous. Such anomalous growth within this restricted space or inside the covering skull can cause problems. Detecting brain tumors from images of medical modalities like CT scan or MRI involves segmentation (Division into parts) for analysis and can be a challenging task. Accurate segmentation of brain images is very essential for proper diagnosis of tumor and non-tumor areas for clinical analysis. This paper details on segmentation algorithms for brain images, advantages, disadvantages and a comparison of the algorithms
Impacts of Evaluation Methods on Classification Algorithm s Accuracy
Authors:   H.H the Rajah’S College, Pudukkottai, Mr K.Subramanian
Published: February 2023

Decision trees are one of the most powerful and commonly used supervised learning algorithms in the field of data mining. It is important that a decision tree perform accurately when employed on unseen data; therefore, evaluation methods are used to measure the predictive performance of a decision tree classifier. However, the predictive accuracy of a decision tree is also dependent on the evaluation method chosen since training and testing sets of decision tree models are selected according to the evaluation methods. The aim of this paper was to study and understand how using different evaluation methods might have an impact on decision tree accuracies when they are applied to different decision tree algorithms.
Further dietary samples for Eastern Barn Owls Tyto javanica near Tamworth, New South Wales, revealed by habitat clearance
Authors:   Zoology, University of New England, Armidale NSW 2351, Australia, Debus S.J.S. , Tsang L.R. ,   Australian Museum Research Institute, Australian Museum, 1 William Street, Sydney NSW 2010, Australia
Published: February 2023

The diet of the Eastern Barn Owl Tyto javanica was investigated by examination of two samples of pellets (n = 11 and 39), pellet debris and prey remains from: (1) an occupied nest with fledgling in May 2009, and (2) an Owl’s winter roost in August 2009 near Tamworth in the grain belt of New South Wales. The breeding diet consisted, by number, of 91% mammals (90% rodents, including 87% House Mice Mus musculus) and 9% common farmland birds (n = 116 food items). The winter diet consisted of 99% House Mice and 1% bird (n = 188 food items). The fledgling Owl was killed when it failed to flush from its nest hollow as the tree was being felled, during approved clearing of the now Critically Endangered White Box–Yellow Box–Blakely’s Red Gum Grassy Woodland and Derived Native Grassland. Given the dependence of the Barn Owl on House Mice, and the ongoing clearing of hollow trees, we note the potential for (a) secondary poisoning of owls by rodenticides, especially during plagues of the invasive House Mouse in the grain belt, and (b) the Barn Owl’s long-term decline in abundance in New South Wales.
A Critical Analysis of the Quantum Nonlocality Problem: On the Polemic Assessment of What Bell Did
Authors: Lambare Justo Pastor
Published: February 2023

The alleged nonlocal character of quantum mechanics is inextricably related to the formulation of the Bell theorem. That relation, however, is commonly incorrectly assessed. The departure from the clear line of reasoning that John Bell tried to convey has led to a polarization of part of the scientific community into radical irreconcilable positions. We show how the correct appreciation of Bell's work calls for reinterpreting the usual significance given to the Bell theorem yielding a more rational perspective of the problem. We formalize the correct argument sustaining the nonlocal character of quantum mechanics and also comment on alternatives that may justify considering quantum mechanics as a local theory.
A New Algorithm for Estimating Fast Variations in the Heart Rate
Authors: Staderini Enrico Maria , Kambampati Harish , Ramakrishnaiah Amith K. , Mugnaini Stefano , Magrini Andrea , Gentili Sandro
Published: February 2023

Heart rate variability (HRV) is commonly intended as the variation in the heart rate (HR) and it is evaluated in the time and frequency domains with various well known methods. In the present paper, we first consider an abstract model in which the HR is the instantaneous frequency of an otherwise periodic signal such as the electrocardiogram (ECG). Thus the ECG is assumed as a frequency modulated signal, or carrier signal, where HRV or HRVt is a supposed time-domain signal which is frequency modulating the carrier ECG signal around its average frequency. Hence we describe an algorithm able to frequency demodulate the ECG signal to extract a continuous signal HRVt with possibly enough time resolution to analyse fast time-domain variations in the instantaneous HR. After exhaustive testing of the method on simulated frequency modulated sinusoidal signals, we have applied the procedure on actual ECG tracings. The purpose of the work is to eventually use the heart as a kind of biological sensor of the fast activity of the autonomic nervous system (ANS) to study the ANS ultra-short-term event-evoked responses. A few preliminary, not clinical, real examples are also given.
A Generalized Series Expansion of the Arctangent Function Based on the Enhanced Midpoint Integration
Authors: Abrarov Sanjar , Siddiqui Rehan , Jagpal Rajinder , Quine Brendan
Published: February 2023

In this work we derive a generalized series expansion of the acrtangent function by using the enhanced midpoint integration (EMI). Algorithmic implementation of the generalized series expansion utilizes a simple two-step iteration. This approach significantly improves the convergence and requires no surd numbers in computation of the arctangent function.
Linear Predictive Model for Dissolved Oxygen in a Protected Urban Lake using Machine Learning Techniques
Authors: Selim Abu , Shuvo Shah Newaz Alam , Moniruzzaman Mohammad , Islam M. M. , Shah Sakifa , Ohiduzzaman Md
Published: February 2023

The paper portrays a linear model for synchronous prediction of the dissolved oxygen (DO) level in a protected urban lake by using independent variables in real-time monitoring of the water quality parameters. Multi-linear regression and machine learning techniques were applied to the Dissolved Oxygen (DO) using the basic four parameters of Water Quality Index (WQI). Three real-time industry standard sensors PHEHT, CTZN, OPTOD were used for sampling, data was then interpolated through ArcGIS kriging method. 25 correlations were checked through the ML algorithm, a correlation heat map was produced and the top five relations were taken under consideration and validated by r-score and root mean squared error (RMSE) to develop the linear regression model. The performance of the model was validated through the RMSE, mean squared error (MSE), and mean absolute error (MAE) the r2 accuracy came to 0.983 when it is checked against the sample data. The suggested model can be used as a technique for unknown or malfunctioned sensor’s null DO data prediction.
Identification of Technological Effectiveness for Mechanized Harvesting of Red Currant Cultivars Based on Bush Morphology and Mechanical Fruit Parameters
Authors: Panfilova Olga , Kahramanoglu Ibrahim , Ondrasek Gabrijel , Ryago Nelly , Tsoy Mikhail , Seguel Alex , Meier Sebastian , Okatan Volkan , Usanmaz Serhat , Helvacı Murat
Published: February 2023

The cultivation of berry crops by the type of "intensive plantings" is an economic and scientific approach in modern horticulture. The principles of forming a red currant assortment adapted to mechanized harvesting are considered. The bush should be compact for mechanized harvesting and have a straight-growing or slightly spreading shape. The morphological structure of the bush is a feature determined by the genotype. The ripening period of berries and the mechanical parameters of berries assess the effectiveness of the berry harvesting process. With the help of agrotechnical techniques, the mechanical parameters of berries cannot be improved and are de-termined by weather, soil, water, and climatic factors. The present study was conducted in the 2021-2022 season using 14 red currant genotypes of different geographical and genetic origins to assess cultivars' suitability for machine harvesting. In most of the studied cultivars, berry quality indicators, the parameters of separation force (Fs) and crushing force (Fc) decreased by the time of biological maturity of the genotype. Several cultivars have shown a non-simultaneous decrease in Fs and Fc. A minor limiting feature determines the duration of harvesting. The high correlation of Fs and Fc (R=0.75-0.85) allows us to predict the most significant period for the high-quality operation of a mechanized harvester. There was no dependence of the strength of the attachment of berries to the peduncle on the thickness of the skin of the berries. Jonkheer Van Tets, Red Lake, Rovada, Rolan, Vika, Asya, and Niva can be attributed to technological cultivars as sources of compact and erect bush habit, Jonkheer Van Tets, Rovada, Rolan, Vika, and Asya are recommended for mechanized harvesting.
Toward to an Automatic Crack Size Estimation with iFEM for Structural Health Monitoring
Authors: Oboe Daniele , Poloni Dario , Sbarufatti Claudio , Giglio Marco
Published: February 2023

The inverse Finite Element Method (iFEM) is a model-based technique to compute the displacement (and then the strain) field of a structure from strain measurements and a geometrical discretization of the same. Different literature works exploit the error between the numerically reconstructed strains and the experimental measurements to perform damage identification in a Structural Health Monitoring framework. However, only damage detection and localization are performed, without attempting a proper damage size estimation. The latter could be based on machine learning techniques, however, an a priori definition of the damage conditions would be required. To overcome these limitations, the present work proposes a new approach in which the damage is systematically introduced in the iFEM model to minimize its discrepancy with respect to the physical structure. This is performed with a maximum likelihood estimation framework, where the most accurate damage scenario is selected among a series of different models. The proposed approach is experimentally verified on an aluminum plate subjected to fatigue crack propagation, which enables the creation of a Digital-Twin of the structure itself. The strain field fed to the iFEM routine is experimentally measured with an Optical Backscatter Reflectometry fiber and the methodology is validated with independent observations of lasers and the Digital Image Correlation.
Analysis of Adaptive Algorithms Based on Least-Mean-Square Applied to Hand Tremors Suppression Control
Authors: Araújo Rafael Silfarney Alves , Tironi Jessica Cristina , Parreira Wemerson Delcio , Borges Renata Coelho , De Paz Santana Juan Francisco , Leithardt Valderi Reis Quietinho
Published: February 2023

The increase in life expectancy, according to the World Health Organization, is a fact, and with it rises the incidence of age-related neurodegenerative diseases. The most recurrent symptoms are those associated with tremors resulting from Parkinson's Disease (PD) or Essential Tremors (ET). The main alternatives for the treatment of these patients are medication and surgical intervention, which sometimes have restrictions and side effects. Through computer simulations in Matlab software, this work investigates the performance of adaptive algorithms based on least mean squares (LMS) to suppress tremors in upper limbs, especially in the hands. The signals resulting from pathological hand tremors, related to PD, present components at frequencies that vary between 3~Hz and 6~Hz, with the more significant energy present in the fundamental and second harmonics, while physiological hand tremors, referred to as ET, vary between 4~Hz and 12~Hz. We simulated and used these signals as reference signals in adaptive algorithms, Filtered-x Least Mean Square (Fx-LMS), Filtered-x Normalized Least Mean Square (Fx-NLMS), and a hybrid Fx-LMS\&NLMS purpose. Our results showed that the vibration control provided by the Fx-LMS\&LMS algorithm is the most suitable for physiological tremors. For pathological tremors, we have used a proposed algorithm with a filtered sinusoidal input signal, Fsinx-LMS, which presented the best results in this specific case.
Automatic Generation of a Portuguese Land Cover Map with Machine Learning
Authors: Esteves Antonio , Valente Nuno
Published: February 2023

The application of machine learning techniques to satellite imagery has been the subject of interest in recent years. The increase in quality and quantity of images, made available by Earth observation programs, such as the Copernicus program, led to the generation of large amounts of data. Among the various applications of this data is the creation of land cover maps. The present work aimed to create machine learning models capable of accurately segment and classify satellite images, to automatically generate a land cover map of the Portuguese territory. Several experiments were carried out with the spectral bands of the Sentinel-2 satellite, with vegetation indices, and with several sets of land cover classes. Three machine learning architectures were evaluated, which adopt two different techniques for image classification. One of the classification techniques follows an object-oriented approach, and in this case the architecture adopted in our models was a U-Net artificial neural network. The other classification technique is pixel-oriented, and the machine learning models tested were random forest and support vector machine. The overall accuracy of the results obtained ranged from 68.6% to 94.75%, depending strongly on the number of classes into which the land cover is classified. The result of 94.75% was obtained when classifying the land cover only into 5 classes. However, a very interesting accuracy of 92.37% was achieved by the model when trained to classify 8 classes. These results are superior to those reported in the related bibliography.
Membrane Association of the Short Transglutaminase Type 2 Splice Variant (TG2-S) Modulates Cisplatin Resistance in a Human Hepatocellular Carcinoma (HepG2) Cell Line
Authors: Meshram Dipak D. , Fanutti Cristina , Pike Claire V. S. , Coussons Peter J.
Published: February 2023

Hepatocellular carcinoma (HCC) is a heterogeneous malignancy with complex carcinogenesis. Although there has been significant progress in the treatment of HCC over the past decades, drug resistance to chemotherapy remains a major obstacle in its successful management. In this study we were able to reduce chemoresistance in cisplatin-resistant HepG2 cells by either silencing the expression of transglutaminase type 2 (TG2) using siRNA or by pre-treatment of cells with the TG2 enzyme inhibitor cystamine. Further analysis revealed that, whereas the full-length TG2 isoform (TG2-L) was almost completely cytoplasmic in its distribution, the majority of the short TG2 isoform (TG2-S) was membrane-associated in both parental and chemoresistant HepG2 cells. Following induction of cisplatin toxicity in non-chemoresistant parental cells, TG2-S together with cisplatin quickly relocated to the cytosolic fraction. Conversely, no cytosolic relocalisation of TG2-S or nuclear accumulation cisplatin was observed following identical treatment of chemoresistant cells, where TG2-S remained predominantly membrane-associated. This suggests that deficient subcellular relocalisation of TG2-S from membranous structures into the cytoplasm may limit the apoptic response to cisplatin toxicity in chemoresistant cells. Structural analysis of TG2 revealed the presence of binding motifs for interaction of TG-S with the membrane scaffold protein LC3/LC3 homologue that could contribute to a novel mechanism of chemotherapeutic resistance in HepG2 cells.
Oxidation of Aldehydes used as Food Aditives by Peroxinitrite: Organoleptic/Antoixidant Properties
Authors: Olivares Clara I , García-Río Luis , Mejuto Juan C. , Moreno Inmaculada , Poblete Francisco J , Tejeda Juan
Published: February 2023

Benzaldehyde and its derivatives are used as food supplements, due to their properties as anti-oxidants and mainly as organoleptic substances. The degradation of these aldehydes produces benzoic acid and benzyl alcohol derivatives, both of which present high toxicity levels. On the other hand, peroxynitrite acts as an oxidizing agent, thus strategies for its production control during food processing could help to improve food quality parameters such as taste, colour and functional properties. Therefore, the control of these degradative oxidation processes is of great interest to the food industry. In order to know in depth this problem, the present article has fo-cused on the kinetic study of the oxidation of aldehydes by peroxynitrite. The proposed mecha-nism justifies all the experimental results, passing through three competitive pathways were per-oxynitrite acts as a radical, nucleophilic or oxidant species. The possible increase of toxic prod-ucts was analyzed.
Effects of Health Anxiety, Social Support, and Coping on Dis-sociation with Mediating Role of Perceived Stress during the COVID-19 Pandemic
Authors: Kolozsvári László Róbert , Rekenyi Viktor , Garbóczy Szabolcs , Hőgye-Nagy Ágnes , Szemán-Nagy Anita , Sayed-Ahmad Mohamed , Héjja-Nagy Katalin
Published: February 2023

Background: Our study aimed to examine how modulating variables such as social support, health anxiety, coping, gender, being separated from home, and lockdown can modify or amplify the effect of perceived stress as a starting variable in the point of view of the output variable, dissociation. Methods: A cross-sectional survey was conducted in online form at two points in time: the beginning and the later stage of the COVID-19 pandemic. Results: We received a total of 1711 responses. Perceived stress moderately correlated with dissociation in both International and Hungarian samples. Health anxiety showed a strong direct and indirect correlation with dissociation. Regarding social support, the support of family significantly decreased the dissociative experiences in the Hungarian sample through mediating the stress and directly as well. In the international sample, the goal-oriented coping strategy had a strong decreasing effect on all dissociation scales in the first measurement, through mediation of perceived stress. As to the Hungarian sample, positive thinking was found to decrease dissociation through decreasing perceived stress. Conclusion: The cause and effect relationship between stress and dissociation may be tinctured by health anxiety, coping and social support, influencing dissociacion directly and indirectly. Social support, mainly support of the family and problem-focused coping strategies seem to alleviate dissociation-provoking effect of stress.
Stark Broadening of Al IV Spectral Lines
Authors: Dimitrijević Milan S. , Christova Magdalena D.
Published: February 2023

Stark widths for 23 transitions in Al IV have been calculated employing modified semiempirical method. The results are obtained for an electron density of 10^17 cm−3 and temperatures from 10,000 K up to 160,000 K. The results obtained in this investigation are used for the examination of the influence of Stark broadening in Al IV stellar spectra, as well as to check Stark width regular behavior and similarites within Al IV spectrum.
Entomopathogenic Fungi-Mediated Solubilization and Induction of Fe related Genes in Melon and Cucumber Plants
Authors: García-Espinoza Fabián , Quesada-Moraga Enrique , García del Rosal María José , Yousef-Yousef Meelad
Published: February 2023

Endophytic insect pathogenic fungi have a multifunctional lifestyle; in addition to its well-known function as biocontrol agents, it may also help plants respond to other biotic and abiotic stresses, such as iron (Fe) deficiency. This study explores M. brunneum EAMa 01/58-Su strain attributes for Fe acquisition. Firstly, direct attributes include siderophore exudation (in vitro assay) and Fe content in shoots and in the substrate (in vivo assay) were evaluated for three strains of Beauveria bassiana and Metarhizium bruneum. The M. brunneum EAMa 01/58-Su strain showed a great ability to exudate iron siderophores (58.4% surface siderophores exudation) and provided higher Fe content in both dry matter and substrate compared to the control and was therefore selected for further research to unravel the possible induction of Fe deficiency responses, Ferric Reductase Activity (FRA), and relative expression of Fe acquisition genes by qRT-PCR in melon and cucumber plants.. In addi-tion, root priming by M. brunneum EAMa 01/58-Su strain elicited Fe deficiency responses at transcriptional level. Our results show an early up-regulation (24, 48 or 72 h post inoculation) of the Fe acquisition genes FRO1, FRO2, IRT1, HA1, and FIT as well as the FRA. These results highlight the mechanisms involved in the Fe acquisition as mediated by IPF M. brunneum EAMa 01/58-Su strain.
Evaluation of Synthetic Categorical Data Generation Techniques for Predicting Cardiovascular Diseases and Post-hoc Interpretability of the Risk Factors
Authors: García-Vicente Clara , Chushig-Muzo David , Mora-Jiménez Inmaculada , Fabelo Himar , Torhild Gram Inger , Løchen Maja-Lisa , Granja Conceição , Soguero-Ruiz Cristina
Published: February 2023

Machine Learning (ML) methods have become important to enhance the performance of decision-support predictive models. However, class imbalance is one of the main challenges for developing ML models, because it limits the generalization of these models, and biases the learning algorithms. In this paper, we consider oversampling methods for generating synthetic categorical clinical data aiming to improve the predictive performance in ML models, and the identification of risk factors for cardiovascular diseases (CVDs). We performed a comparative study of several categorical synthetic data generation methods, including Generative Adversarial Networks (GANs). Then, we assessed the impact of combining oversampling strategies and linear and nonlinear supervised ML methods. Lastly, we conducted a post-hoc model interpretability based on the importance of the risk factors. Experimental results show the potential of GAN-based models for generating high-quality categorical synthetic data, yielding probability mass functions that are highly close to real data, maintaining relevant insights, and contributing to increase the predictive performance. The GAN-based model and a linear classifier outperforms other oversampling techniques, improving 2\% the area under the curve. These results demonstrate the capability of synthetic data to help both in determining risk factors and building models for CVD prediction.
Group Independent Components Underpin Responses to Items from a Depression Scale
Authors: Stoyanov Drozdstoy , Khorev Vladimir , Paunova Rositsa , Kandilarova Sevdalina , Kurkin Semen , Calhoun Vince D.
Published: February 2023

The aim of the presents study is to further expand the model of translational cross-validation by investigating the brain circuits or networks which underpin the same tasks by means of group independent component analysis for FMRI toolbox (GIFT). We hypothesized that there will be neural network patterns of activation and deactivation, which correspond to real time performance on clinical self-evaluation scales. We recruited 42 subjects: 20 healthy controls and 22 patients with major depressive episode. All subjects underwent functional MRI scanning using paradigm comprised of diagnostic clinical self-assessment depression scale contrasted to neutral scale. The data were processed with group independent component analysis for functional MRI toolbox and statistical parametric mapping. The results have demonstrated that there exist positively or negatively modulated brain networks during processing of diagnostic specific task questions for major depressive disorder. There have also been confirmed differences in the networks processing diagnostic versus off blocks between patients and controls in anterior cingulate cortex and middle frontal gyrus. Diagnostic conditions (depression scale) when contrasted to neutral conditions demonstrate differential activity of right superior frontal gyrus and right middle cingulate cortex in the comparison of patients with healthy controls. It is for the first time when potential neuroimaging state dependent biomarker has been directly linked with clinical assessment self-evaluation scale, administered as stimuli simultaneously with the fMRI acquisition. It may be regarded as further evidence in support of the ability of both methods to concordantly distinguish groups by means of incremental translational cross-validation.
Study of Nonlinear Excitation Circuits for Fluxgate Magnetometer
Authors: Zhang Chenhao , Zhang Yiming , Wang Xuhong
Published: February 2023

This paper presents the common methods and corresponding drawbacks concerning nonlinear analysis of fluxgate excitation circuits and emphasizes the importance of nonlinear analysis for these circuits. With regard to the nonlinearity of the excitation circuit, this paper proposes the use of the core-measured hysteresis curve for mathematical analysis and the use of a nonlinear model that considers the coupling effect of the core and winding and influence of the historical magnetic field on the core for simulation analysis. The feasibility of mathematical calculations and simulation for the nonlinear study of fluxgate excitation circuit is verified via experiments. The results demonstrate that, in this regard, the simulation is better than a mathematical calculation. The simulation and experimental results of the excitation current and voltage waveforms under different excitation circuit parameters and structures are essentially consistent with each other, thereby verifying the effectiveness of the nonlinear excitation analysis method.
Endogenous piRNAs Can Interact with Omicron Variant of the SARS-CoV-2 Genome
Authors: Rakhmetullina Aizhan , Akimniyazova Aigul , Niyazova Togzhan , Pyrkova Anna , Kamenova Saltanat , Kondybayeva Aida , Ryskulova Alma-Gul , Ivashchenko Anatoliy , Zielenkiewicz Piotr
Published: February 2023

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused the COVID-19 pandemic still able to infect the population in many countries. The Omicron strain is the most mutated variant of SARS-CoV-2. The high transmissibility of the strain and the ability to evade immunity require a priority study of its properties in order to quickly create effective means of preventing it. The present work is devoted to the study of in silico interaction of piRNAs with the genome of the SARS-CoV-2 (gRNA) in order to identify endogenous piRNAs and propose synthetic piRNAs with high antiviral activity for drug development. The studies were carried out using proven bioinformatic methods of interaction of the entire SARS-CoV-2 genome with more than eight million piRNAs. Binding sites (BSs) of piRNAs in the 5'UTR were located with overlapping nucleotide sequences called clusters of BSs. Several clusters of BSs were found in the nsp3, nsp7, RNA-dependent RNA polymerase, endoRNAse, S surface glycoprotein, ORF7a and nucleocapsid. 16 synthetic piRNAs have been proposed that interact with gRNA with free binding energy from -170 kJ/mol to -175 kJ/mol, which can be used to create drugs that suppress the reproduction of SARS-CoV-2.
Trening siłowy kończyn górnych jako forma rehabilitacji dzieci i młodzieży z mózgowym porażeniem dziecięcym: systematyczny przegląd piśmiennictwa
Authors:   Klinika Kardiologii Wieku Dziecięcego i Pediatrii Ogólnej WUM, Szkoła Doktorska Warszawski Uniwersytet Medyczny, Walecka Iwona , Ambroziewicz Marta ,   Oddział Fizjoterapii, II Wydział Lekarski, Warszawski Uniwersytet Medyczny, Gąsior Jakub S. ,   Klinika Kardiologii Wieku Dziecięcego i Pediatrii Ogólnej, Warszawski Uniwersytet Medyczny
Published: February 2023

Wstęp: Osłabienie siły mięśniowej jest jednym z kluczowych objawów ograniczających motorykę u pacjentów z mózgowym porażeniem dziecięcym (MPD). Przeprowadzony przegląd piśmiennictwa skupia się na efektach treningu siłowego (TS) kończyn górnych u dzieci z MPD. Materiał i Metody: Przegląd piśmiennictwa przeprowadzono zgodnie z wytycznymi PRISMA Statement. W celu weryfikacji skuteczności TS przeszukano wybrane medyczne bazy danych używając słów kluczowych: mózgowe porażenie dziecięce, trening siłowy, kończyna górna. Badania podzielono na dwie kategorie, te w których występuje sam trening siłowy oraz te, w których trening siłowy jest połączony z inną interwencją terapeutyczną. Wyniki: Znaleziono 19 publikacji, z których do końcowej analizy włączono 9 prac: 4 badania randomizowane, 1 badanie inne niż randomizowane i 4 analizy przypadku. Wyniki przedstawiono w formie tabelarycznej zgodnie z Międzynarodową Klasyfikacją Funkcjonowania, Niepełnosprawności i Zdrowia na poziomach: struktury i funkcji, aktywności oraz partycypacji. W analizowanych badaniach wykorzystywano: TS jako samodzielną interwencję, TS wraz z elektrostymulacją oraz TS w połączeniu z iniekcjami toksyny botulinowej. Wnioski: Na podstawie przeanalizowanych badań nie można określić precyzyjnych wytycznych TS kończyn górnych w grupie dzieci z MPD z powodu zbyt dużej różnorodności badań w zakresie typu treningu, jego intensywności i czasu trwania. Istnieje konieczność ustalenia charakterystyki pacjentów z MPD i protokołu treningowego, które pozwolą na osiągnięcie maksymalnych korzyści płynących z tego rodzaju treningu na płaszczyźnie aktywności i partycypacji w życiu codziennym.
INTO THE SHOES OF VISUALLY IMPAIRED VIEWERS. A DIDACTIC EXPERIMENT TO IMPROVE AUDIOVISUAL TRANSLATION, AUDIO DESCRIPTION AND ENGLISH SKILLS
Authors: Ogea Pozo Maria del Mar
Published: February 2023

Audiovisual accessibility has become, since the beginning of the 21st century, one of the most interesting and promising fields at both academic and professional levels related to audiovisual translation (Pereira and Lorenzo, 2021; Permuy, 2021; Sanz, 2017). Audio describers need to develop, among other skills, social sensitivity, knowledge of film language, fluency in their own language and culture, and an understanding of the semiotics of the image (Díaz-Cintas, 2007; Navarrete, 1997). Moreover, as proved by previous studies, audio description may work as an excellent tool in foreign language learning (Talaván et al., 2022; Vermeulen & Escobar, 2021; Navarrete, 2018). In order to delve into the acquisition of the necessary skills for audio description and, simultaneously, to improve the students’ level of English as a foreign language during a course on AD and didactics of English, a pedagogical experiment was carried out involving the identification of aural and visual elements, and the preparation and delivery of an AD in English. This study reveals the results obtained from this five-stage activity, in terms of the acquisition of specific skills and the raising of awareness of the importance of audio description in today's film industry.
Nuevos datos sobre el Real Convento de San Pablo de Córdoba: la dotación de agua y estudio de la cimentación de su iglesia
Authors: Aparicio Sánchez Laura , Jordano Barbudo Mª de los Ángeles , Alejandre Sánchez Francisco Javier
Published: February 2023

En una reciente actuación arqueológica en el Real Convento de San Pablo de Córdoba hemos podido documentar, de una parte, la cimentación del muro de la fachada principal de la iglesia y, de otra, una importante canalización de agua dulce que abastecía a los dominicos. El monasterio de San Pablo se ubicó en terrenos donados por Fernando III en 1241, concediéndoles el rey un tercio del agua que corría bajo el lienzo este de la muralla de la Villa (antigua Medina).
Remote sensing tools to support ordinary high water mark delineation
Authors: Haring Christopher , Gordon Kyle , Darby Tom
Published: February 2023

This document is a technical note (TN) that describes existing and recently developed tools to support ordinary high water mark (OHWM) identification and delineation. It also presents a case study to demonstrate how utilizing the tools provide supporting lines of evidence in OHWM delineations.
TINJAUAN HISTORIS TEKNOLOGI VARIETAS UNGGUL DAN PROGRAM INTENSIFIKASI DALAM PENINGKATAN PRODUKTIVITAS PADI BERKELANJUTAN
Authors: Swastika Dewa K S , Agustian Adang , Suryana Achmad , Muslim Chairul , Sunarsih NFn , Perdana Resty Puspa
Published: February 2023

The Indonesian Agency for Agricultural Research and Development (IAARD) has created various technology packages, significantly superior rice varieties with high yields and resistance to various pests and diseases. Since 1943 hundreds of superior varieties of rice have been released. However, domestic rice production has yet to be able to meet the national rice needs. One of the main problems is the decrease in fertile land due to continuous land conversion. Hence, the mainstay in increasing rice production is to escalate productivity through technological improvements. Therefore, IAARD continues to create new high-yielding rice varieties through plant breeding. More than 200 high-yielding varieties of rice have been produced to meet the challenge of increasing productivity. This paper aims to examine the historical profile of the creation of superior rice varieties in line with intensification programs and their role in increasing national rice production. The study was conducted using a desk study approach by examining secondary data and literature from various publications. The study results showed that creating high-yielding varieties accompanied by various intensification programs had increased rice productivity sustainably. The challenge for IAARD is the creation of new high-yielding varieties with higher yields than those currently available.
An approach for prioritizing candidate genes from RNA-seq using preclinical cocaine self-administration datasets as a test case
Authors: Vannan Annika , Dell'Orco Michela , Perrone-Bizzozero Nora I. , Neisewander Janet L. , Wilson Melissa A.
Published: February 2023

RNA-sequencing (RNA-seq) technology has led to a surge of neuroscience research using animal models to probe the complex molecular mechanisms underlying brain function and behavior, including substance use disorders (SUDs). However, findings from rodent studies often fail to be translated into clinical treatments. Here, we developed a novel pipeline for narrowing candidate genes from preclinical studies by translational potential and demonstrated utility of this model in three RNA-seq studies of rodent self-administration. This pipeline uses evolutionary conservation and preferential expression of genes across brain tissues to prioritize candidate genes, increasing the translational utility of RNA-seq in model organisms. We found only 1 differentially-expressed gene (DEG) in any dataset after correcting for multiple testing (FDR < 0.05 or < 0.1), raising concerns about false positives and low statistical power that may impact these and other RNA-seq datasets. Thus, we demonstrate the utility of our prioritization pipeline using an uncorrected p-value. Curiously, even with an uncorrected p-value of 0.05 we saw low overlap of DEGs across the 3 selected datasets. Thus, we also advocate for improved RNA-seq data collection, statistical testing, and metadata reporting that will bolster the field’s ability to identify reliable candidate genes and compare results across studies.
Characterization of COVID-19 Vaccine Clinical Trial Discussions on the Social Question-and-Answer Site Quora
Authors: Xu Qing , McMann Tiana J. , Li Jiawei , Wenzel Christine , Mackey Tim Ken
Published: February 2023

Introduction:
Throughout the COVID-19 pandemic underserved populations, such as racial and ethnic minorities, were disproportionately impacted by illness, hospitalization, and death. Equity in clinical trials means that the participants in clinical trials represent the people who are most likely to have the health condition and need the treatment that the trial is testing. Infodemiology approaches examining user conversations on social media platforms have the potential to elucidate specific barriers and challenges related to clinical trial participation.
Methodology:
The study retrospectively collected and analyzed user question and answer posts from Quora in October 2021 using an inductive content coding approach. We also examined user’s publicly available profile metadata to identify racial and ethnic minority populations to capture their experiences, attitudes, topics, and barriers to COVID-19 vaccine trials.
Result
A total of 1,073 questions and 7,479 answers were collected based on structured automated keyword queries and data mining. A total of 763 questions and 2,548 answers were identified as related to COVID-19 vaccine clinical trials. The majority of these online interactions focused on asking questions and sharing knowledge and opinions about COVID-19 vaccine trials, including major topics related to: (a) interpreting whether clinical trial results could be trusted; (b) questions about vaccine efficacy and safety; (c) understanding trial design, regulatory considerations, and vaccine platforms; and (d) questions about trial enrollment, length, and adequate representation. Additionally, four major barriers discussed included: (i) disagreement from users regarding whether clinical trials require representation from different racial and ethnic minorities; (ii) concerns regarding the safety of trials when participating; (iii) lack of knowledge on how to register for a trial; and (iv) whether participants could withdraw from a trial to receive a more rapidly approved COVID-19 vaccine.
Conclusions
Our study found active user discussions related to COVID-19 vaccine clinical trials on Quora, including those specific to minority health topics and posted by self-identified racial and ethnic minority online users. Results from this study can help identify near real-time barriers to participation among underrepresented groups and support the design of future outreach strategies to help with recruitment and inclusive participation.
Childhood Trauma Questionnaire-Short Form: Evaluation of Factor Structure and Measurement Invariance
Authors: Cruz Daniel
Published: February 2023

Childhood trauma is known to put individuals at risk for mental and physical challenges later in life. Retrospective assessment of early abuse and neglect is critical for prevention and intervention efforts targeted at reducing the negative impacts of childhood trauma. The Childhood Trauma Questionnaire-Short Form (CTQ-SF) is a widely used measure to assess trauma among adolescents and adults, though there are some inconsistencies with regard to its factor structure and psychometric properties. The purpose of the current study was twofold: 1) to evaluate the hypothesized five-factor structure of CTQ-SF and 2) to test measurement invariance (equivalence) of the instrument across gender and race in a large, nationally representative sample of US adults (N = 863). Confirmatory factor analysis results indicate that the five-factor model fit the data well after some re-specification. The results also show that the five-factor model is generally invariant by gender and racial/ethnic groups and that the form’s subscales positively correlate with depression, anxiety, and abnormal inflammatory biomarker activity. Assessment is critical for the advocacy and treatment of individuals who have experienced abuse and neglect as children and adolescents. Our findings suggest that the CTQ-SF is a valuable tool for assessing childhood trauma and can be used in advocacy and treatment efforts.
a1,3-fucosylation of MEST promotes embryo implantation by activating translation initiation
Authors: Wang Hao , Cui Xinyuan , Wang Luyao , Fan Ningning , Qin Huamin , liu shuai , yan qiu
Published: February 2023

Embryonic trophoblast implanting into the uterus is the gateway for successful pregnancy. Dysfunctions of trophoblast cause pregnancy failure. Protein glycosylation plays crucial roles in reproduction process. However, it remains unclear if the glycosylation of trophoblasts involves in embryo implantation. By glycomics, proteomics combined with translatomics, our results revealed the that decreased α1,3-fucosylation, especially difucosylated Lewis Y (LeY) glycan, in the villus trophoblast of miscarriage patients compared with normal pregnancy women. Downregulating LeY by silencing key enzyme fucosyltransferase IV (FUT4) inhibited trophoblast implantation potential. Using proteomics analysis, we identified MEST scaffolding LeY at Asn163, and its expression was enhanced trophoblast implantation. We also provided novel evidence showing that decreased LeY modification on MEST dramatically hampered it binding with translation factor eIF4E2, and inhibited implantation-related gene translation initiation, which caused embryo implantation failure. The α1,3-fucosylation of MEST by FUT4 may serves as a new biomarker for evaluating the functional state of pregnancy and target for infertility treatment.
Ferroelectric hafnia as an ionic conductor
Authors: Zhao Guo-Dong , Liu Xingen , Xu Zhongshan , Ren Wei , Zhu Xiaona , Yu Shaofeng
Published: February 2023

The intensively concerned hafnia-based ferroelectric (FE) material has been controversial over whether the origin of its observed ferroelectricity being structural or electrochemical. We revisit the rigorous application of modern theory of polarization on displacive FE-HfO2, and make clear the microscopic mechanism of ionic conductance intertwined with continuous nucleation-and-growth FE switching in HfO2 from first principles. Independent from the involvement of vacancies, active oxygen ions in FE-HfO2 can be collectively conducted along continuous FE uniaxial-connected-paths (UCPs) in a typical nucleation-and-growth manner. The ionic conductance should have a nonlinear electric-field dependence from the Merz’s law, which is consistent with the strongly correlated ionic conductance. Based on our established physical picture, some abnormal experimental observations of HfO2 may be explained beyond the pristine understanding of FE switching within double-well potentials.
Detection and Mitigation of Malicious DDoS Floods in Software Defined Networks
Authors: Ahmad Furqan , Rehman Ubaid ur , Saleem Maham
Published: February 2023

Software-defined networking (SDN) has revolutionized network management by providing modular control and data plane attributes for flexible network management. It implies the concept of separating the control and data plane attributes for flexible network management. However, centralized management due to control plane separation in SDN also exposes it to cyber threats such as Distributed Denial-of-service (DDoS) attacks that can compromise the SDN controllers. In recent research, entropy-based attack detection approaches showed much significance among other detection methods but relying on entropy itself can neglect detection in several variables such as variations in flow specification. Based on these limitations, in this work, we have designed a DDoS attack detection framework inside the SDN control plane by integrating the packet flow initiation and its specifications properties with entropy-based algorithm to ensure correct measures of attack detection. The simulation is performed on Mininet network simulator, for implementing SDN architecture and the testbed is created on UDP flood attacks on commonly used data-centric tree topologies. Based on experimentation, this lightweight framework is designed to mitigate DDoS attacks by detecting its effects in the early stages to prevent SDN controller being hijacked due to immense packet flooding Based on the results, the proposed solution assures the SDN-based DDoS attack detection and mitigation under 150 packets maintaining significantly low detection time and high accuracy.accuracy.