bluuebunny/crossref_metadata_2025 huggingface dataset:
Overview of Various Voltage Control Technologies for Wind Turbines and AC / DC Connection Systems
Authors: Wu Yuan-Kang , Gau Deng-Yue , Tung Trinh Duc
Published: April 2023

Wind power generation is one of the mainstream renewable energy resources. Voltage stability is as important as the frequency stability of a power system with a high penetration of wind power generation. The advantages of high-voltage direct current (HVDC) transmission systems become more significant with the increase of both installed capacity and transmission distance in offshore wind farms. Therefore, this study discusses about various voltage control methods for wind turbines and HVDC transmission systems. First, various voltage control methods of a wind farm were introduced, and they include QV control and voltage droop control. The reactive power of a wind turbine varies with active power, while the active power from each wind turbine may be different owing to wake effects. Thus, QV and voltage droop control with varying gain values were also discussed in this paper. Next, the voltage control methods for a HVDC transmission system, such as power factor control, voltage control, and Vac-Q control, are also summarized and tested in this study. When a three-phase short circuit fault occurs or a suddan reactive power load increases, the system voltage would drop immediately. Thus, various voltage control methods for wind turbines or HVDC can make the system's transient response more stable. Therefore, this study implemented the simulation scenarios, including a three-phase short circuit fault at the point of common coupling (PCC) or a sudden increase of reactive power load, and adopted various voltage control methods, which aims to verify whether additional voltage control methods are effective to improve the performance of transient voltage.
Automated Word-level Lip Reading using Convolutional Neural Networks with New Turkish Dataset
Authors: Pervan-Akman Nergis , Berkol Ali , Erdem Hamit
Published: April 2023

Automated lip reading is a research problem that has developed considerably in recent years. Lip reading is evaluated both visually and audibly in some cases. The lip reading model is a field of use for detecting specific words using images from security cameras, but it is not possible to use audio-visual databases in this situation. It is not possible to obtain the sound input of the pronounced word in all cases. We collected a new Turkish dataset with only the image in this study. The new dataset is produced using Youtube videos, which is an uncontrolled environment. For this reason, images have difficult parameters in terms of environmental factors such as light, angle, color, and personal characteristics of the face. Despite the different features on the human face such as mustache, beard, and make-up, the visual speech recognition problem was developed on 10 classes including single words and two-word phrases using Convolutional Neural Networks (CNN) without any intervention on the data. The proposed study using only-visual data obtained a model which is automated visual speech recognition with a deep learning approach. In addition, since this study uses only-visual data, the computational cost and resource usage is less than in multi-modal studies. It is also the first known study to address the lip reading problem with a deep learning algorithm using a new dataset belonging to the Ural-Altaic languages.
Use of Artificial Intelligence in Processing of COVID-19-Related Scientific Literature
Authors: Ivantysyn Michal , Vaclavikova Dagmar , Musil Peter
Published: April 2023

The COVID-19 pandemic has resulted in an unprecedented acceleration in scientific production across multiple disciplines. The vast number of publications available makes it challenging for healthcare professionals and researchers to keep up with the current state of knowledge regarding COVID-19. This article presents covid19-help.org, a free expert-curated database designed to increase the availability of relevant original data related to COVID-19 treatment and prevention via immunization. To accelerate the process of identifying relevant original scientific publications and to simplify annotation of their content, the database uses our artificial intelligence in medical literature (AIM.lit) tool. The article provides an overview of the covid19-help.org database design, the criteria used to select publications, and the use of the AIM.lit tool. The database allows users to easily search and filter records, provides concise information on individual substances and their mechanisms of action, lists relevant original scientific publications with annotations, and offers links to external resources. The AIM.lit tool increases the speed of publication selection and extraction of basic relevant information, without compromising the validity of the data. The technology and experience gained from creating the covid19-help.org database and its tools could also be useful in other areas where scientific information organization is a challenge.
Survey of Optimization Algorithms in Modern Neural Networks
Authors: Abdulkadirov Ruslan , Lyakhov Pavel , Nagornov Nikolay
Published: April 2023

Creating self-learning algorithms, developing deep neural networks and improving other methods that "learn" for various areas of human activity is the main goal of the theory of machine learning. It helps to replace the human with a machine, aiming to increase the quality of production. The theory of artificial neural networks, which already have replaced the humans in problems of detection of moving objects, recognition of images or sounds, time series prediction, big data analysis and numerical methods remains the most dispersed branch of the theory of machine learning. Certainly, for each area of human activity it is necessary to select appropriate neural network architectures, methods of data processing and some novel tools from applied mathematics. But the universal problem for all these neural networks with specific data is the achieving the highest accuracy in short time. Such problem can be resolved by increasing sizes of architectures and improving data preprocessing, where the accuracy rises with the training time. But there is a possibility to increase the accuracy without time growing, applying optimization methods. In this survey we demonstrate existing optimization algorithms of all types, which can be used in neural networks. There are presented modifications of basic optimization algorithms, such as stochastic gradient descent, adaptive moment estimation, Newton and quasi-Newton optimization methods. But the most recent optimization algorithms are related to information geometry, for Fisher-Rao and Bregman metrics. This approach in optimization extended the theory of classic neural networks to quantum and complex-valued neural networks, due to geometric and probabilistic tools. There are provided applications of all introduced optimization algorithms, what delighted many kinds of neural networks, which can be improved by including any advanced approaches in minimization of the loss function. Afterwards, we demonstrated ways of developing optimization algorithms in further researches, engaging neural networks with progressive architectures. Classical gradient based optimizers can be replaced by fractional order, bilevel and, even, gradient free optimization methods. There is a possibility to add such analogues in graph, spiking, complex-valued, quantum and wavelet neural networks. Besides the usual problems of image recognition, time series prediction, object detection, there are many are other tasks for modern theory of machine learning, such as solving problem of quantum computations, partial differential and integro-differential equations, stochastic processes and Brownian motion, making decisions and computer algebra.
Chromosome 22q11.2 Deletion Syndrome: A Comprehensive Review of Molecular Genetics in the Context of Multidisciplinary Cinical Approach
Authors: Szczawińska-Popłonyk Aleksandra , Schwartzmann Eyal , Chmara Zuzanna , Głukowska Antonina , Krysa Tomasz , Majchrzycki Maksymilian , Olejnicki Maurycy , Ostrowska Paulina , Babik Joanna
Published: April 2023

The 22q11.2 deletion syndrome is a multisystemic disorder characterized by a marked variability of phenotypic features making the diagnosis challenging for clinicians. The wide spectrum of clinical manifestations includes congenital heart defects, most frequently conotruncal cardiac anomalies, thymic hypoplasia and predominating cellular immune deficiency, laryngeal developmental defects, midline anomalies with cleft palate and velar insufficiency, structural airway defects, facial dysmorphism, parathyroid and thyroid gland hormonal dysfunctions, speech delay, developmental delay, neurocognitive and psychiatric disorders. Significant progress has been made in understanding the complex molecular genetic etiology of the 22q11.2 deletion syndrome underpinning the heterogeneity of clinical manifestations. The deletion is caused by chromosomal rearrangements in meiosis and is mediated by non-allelic homologous recombination events between low copy repeats or segmental duplications in the 22q11.2 region. A range of genetic modifiers, environmental factors as well as the impact of hemizygosity on the remaining allele contribute to the intricate genotype-phenotype relationships. This comprehensive review has been aimed at highlighting the molecular genetic background of 22q11.2 deletion syndrome in correlation with a clinical multidisciplinary approach.
Multisensory Stimulation Reverses Memory Impairment in Adrβ3KO Mice
Authors: Ravache Thaís T. , Batistuzzo Alice , Nunes Gabriela G. , Gomez Thiago G. B. , Lorena Fernanda B. , Nascimento Bruna P. P. , Bernardi Maria Martha , Lima Eduarda R.R. , Martins Daniel O. , Campos Ana Carolina P. , Pagano Rosana L. , Ribeiro Miriam O.
Published: April 2023

Norepinephrine plays an important role in modulating memory consolidation and evocation through its beta-adrenergic receptors (Adrβ: β1, β2 and β3), which are expressed in the hippocampus (HC) and amygdala (AMY). Here we hypothesized that multisensory stimulation would reverse the memory impairment caused by the inactivation of the Adrβ3 with consequent inhibition of sustained glial-mediated inflammation and glutamatergic depuration. To test this, 21- and 86-day-old Adrβ3KO mice and respective controls underwent to (i) gustative and olfactive stimuli of positive and negative valence associated with (ii) intellectual challenges to reach the food in addition to (iii) objects in hidden places (iv) foraging for 8 weeks followed by (v) analysis of GFAP, Iba-1 and EAAT2 protein expression in the HC and AMY. While this protocol restored the memory impairment when applied to Adrβ3KO animals immediately after weaning, it had no effect when applied to adult animals. In fact, we observed that aging worsens the memory of Adrβ3KO mice. Although no significant expression of GFAP and Iba1 were observed in HC of young and old mice, Adrβ3KO increased EAAT2 expression HC of old mice, while MS didn’t change EAAT2 in young mice but enhanced it expression in older. Relative to AMY of old mice Adrβ3KO increased GFAP expression compared whit WT mice and MS sustained the GFAP expression and increased the EAAT2 expression compared with WT group. These results suggest that a richer and more diverse environment helps to correct memory impairment when applied right after weaning Adrβ3KO animals, also show that the changes in GFAP, Iba1 and EAAT2 expression levels in young and old mice indicate a functional significance in the process of learning and memory and that the control of neuroinflammation in limbic areas mediates this response. They also reinforce the idea that disruption of noradrenergic signaling could be involved in the cognitive impairment observed later in life.
APPROACHES TO FORECASTING THE LIKELY CONSEQUENCES OF INNOVATIVE TRANSFORMATIONS
Authors: Popov Alexander , Mekhovych Serhiі
Published: April 2023

The article considers the likely consequences of innovative re-engineering and approaches to their forecasting. Among the various variables, the variable states that characterize the current, past or future state of the production and technological system and which are very important for evaluating the effectiveness of innovative transformations are highlighted. It is justified that the normal law of error distribution is often used to predict the behavior of intensity variables. This determines the simplicity and convenience of calculations. The output variables are determined by the forecast model and the degree of its limitations. In order to build effective models for forecasting innovative transformations, initial data are needed, which are a sample of observation results or a posteriori data of other successful enterprises for some time periods (time series). Approaches to forecasting decisions regarding the financing of a general project of technological reengineering of production based on taking risks into account are considered. Critical and catastrophic financial risks are highlighted. It is noted that risks for investors and the company's management may arise in the event of changes in the organizational forms of interaction between partners, which occur with the transfer of intangible assets - temporary or permanent assignment of rights to intellectual property to investors in exchange for investments and return of rights to the owners of the enterprise after payment of the principal debt and profit to the investors. One of the main types of risk after carrying out technological reengineering of production based on innovative transformations is the risk of promoting innovative products created on a new technological base and the unpredictable reaction of potential consumers. The structure of the reserve for covering unforeseen costs is given.
APPLICATION OF ARTIFICIAL NEURAL NETWORKS AND ACHIEVEMENTS OF TECHNOLOGICAL RE-ENGINEERING OF MODERN INDUSTRIAL PRODUCTION
Authors: Mekhovych Serhiі , Popov Olexander , Klepikova Svitlana
Published: April 2023

The article deals with the issue of the justification mechanism for the choice of directions of technological reengineering. It was determined that the effectiveness of the transformations primarily depends on the methods, tools for choosing directions for the radical transformation of the technological basis of the production enterprise and, in general, on the technological policy. The justification of the directions of technological training engineering is connected with a large volume of interdependent variables of innovative transformations and requires a fundamental analysis of their behaviour and impact on production process. Today, neural networks are one of the most famous and effective tools for intelligent data analysis, which is developed thanks to achievements in the field of artificial intelligence theory and computer science. Intelligent systems based on artificial neural networks and fuzzy logic allow solving the tasks of forecasting, optimization, pattern recognition and management. To train the network, it is necessary to have a set of values of input values (factors) and corresponding to each separate set of values of the desired output value. Such an approach completely coincides with the tasks of choosing the directions of technological reengineering at the enterprises of the innovation cluster. For this purpose, significant external and internal factors influencing the effectiveness of the cluster policy have been determined. In contrast to internal, external to the greatest extent allow solving the tasks of forecasting, optimization, pattern recognition and management. In the conditions of an imperfect regional innovation system and taking into account this factor, for the efficiency of solving the tasks of technological reengineering of industrial production, a methodology is proposed that combines foresight forecasting of the prospects of technological reengineering of enterprises with the theory of artificial neural networks. The mechanism of interaction of artificial neural networks and the foresight method in determining directions of technological reengineering based on regional cluster policy are proposed.
Formação de Banca para Concurso Docente e os Princípios da Administração Pública
Authors: Alves Braga Priscilla Even , Santos Oliveira Duarte Maria de Fátima , Araujo Silva Napiê Galvê
Published: April 2023

Objetivo da pesquisa: A pesquisa tem como objetivo analisar a formação de banca de concurso para docente de Instituição Pública Federal de Ensino e identificar possíveis fragilidades no sistema de composição a fim de propor melhorias à luz dos princípios constitucionais da legalidade, impessoalidade, moralidade, publicidade e eficiência, considerando a autonomia universitária.
Enquadramento teórico: A administração pública passou ao longo dos anos por 3 modelos de gestão: patrimonialista, burocrático e gerencial. Dentro desse contexto, as práticas administrativas eram revestidas de conceitos e critérios que sustentavam os modelos. Partindo dessa premissa, construindo uma breve evolução, chega-se aos concursos públicos e aos princípios constitucionais que devem ser observados em todo contexto da administração pública.
Metodologia: A coleta de dados foi realizada através de questionário aplicado via googleforms e a análise foi feita por meio do software Atlas TI, que permitiu a formação de redes, que identificaram a percepção de candidatos e docentes quanto à forma atualmente adotada na formação de bancas.
Resultados: A análise dos dados sinalizou uma possível deficiência nas práticas adotadas para formação de banca, que podem porventura desencadear ofensa aos princípios constitucionais e práticas de patrimonialismo.
Originalidade: A pesquisa expande a literatura sobre concursos públicos para docente das IFES no Brasil e a consagração dos princípios da administração pública nesse tipo de certame, permitindo a identificação de ofensa aos princípios nos elementos de formação das bancas.
Contribuições teóricas e práticas: Os resultados permitem confrontar os critérios de formação de banca para concurso docente com os princípios da administração pública, identificando quais práticas adotadas podem ser consideradas ofensivas a tais princípios. Nesse contexto, identificados os pontos de ofensa, os gestores podem reformular as práticas adotadas, de forma a uniformizar e melhorar os processos seletivos.
 
Palavras-chave:Concurso público, Princípios da administração pública, Formação de banca, Autonomia universitária.
Clinical application value of nomogram model based on clinical and ultrasound features in predicting thyroid C-TI-RADS classification optimization
Authors: liang yu , Xu Tong , Zhang Jing , Song Jun , Huang FuHong , Li Xuan , Fan ErXi , Chen Qin
Published: April 2023

Backgrounds: A nomogram model based on clinical and ultrasound features was constructed to explore its clinical application value in predicting thyroid C-TI-RADS classification optimization. Methods: Clinical data and ultrasound imaging data of 1,234 patients with thyroid nodules collected from January 2021 to February 2022 of Sichuan Provincial People's Hospital were retrospectively analyzed.All patients underwent preoperative thyroid ultrasound examination and retained standard ultrasound images, evaluated the thyroid nodule C-TI-RADS classification, using the postoperative pathological results as the "gold standard". Independent predictors of C-TI-RADS classification optimization were selected by univariate and multivariate logstic regression analysis, and a nomogram prediction model(*C-TI-RADS) was constructed.The internal validation of the model was performed by Bootstrap resampling. ROC curve was drawn to evaluate the discrimination of the model, and calibration curve and decision curve were drawn to evaluate the consistency and clinical practicability of the prediction model. Results: C-TI-RADS classification, size and number of thyroid nodules, abnormal cervical lymph node ultrasonography, sex and age were independent factors for predicting C-TI-RADS classification optimization (all P < 0.05).The C index of the nomogram prediction model(*C-TI-RADS) constructed based on the above factors was 0.790 (95%CI: 0.765–0.815).Under the optimal cut-off value, the sensitivity was 70.8%, the specificity was 74.4%, and the accuracy was 72.2%.The calibration curve and decision curve showed good consistency and clinical practicability of the model. Conclusions: Nomogram model has good accuracy in the prediction of thyroid C-TI-RADS classification optimization, and can assist ultrasound physician to modify C-TI-RADS classification, which has potential clinical application value.
Multiple resonances, fragmented propagation and homogenized attenuation of the beam model coupled with bi-periodic resonators
Authors: Tang Dong , Ran Maohui , Zhang Wei , Ma Zitong , Ding Zihan
Published: April 2023

Wave propagation and attenuation behaviours of beam-resonators coupling model are dominated by the local resonators and the periodicity. Inspired by bi-periodic structures in engineering practice and based on a previous study, beam models coupled with bi-periodic resonators are proposed by introducing a parametric variant resonator into the periodic model. Wavenumber spectrum relation of the bi-periodic coupling system with a parametric variant resonator and several regular resonators is obtained by means of the method of reverberation-ray matrix and solved by numerical techniques. Effects of various parameters of the parametric variant resonator on the wavenumber spectrum characteristics of the bi-periodic models are investigated in numerical examples, which show that the parametric variant resonator results in an additional resonant peak and extra non-local resonant attenuation bands. Bandwidth of the local resonant attenuation band can be broadened by either increasing the translational stiffness or decreasing the mass of the parametric variant resonator. Compared to wavenumber spectrum curves of the beam model coupled with periodic resonators, the introduction of the parametric variant resonator makes the wavenumber spectrum curves of the real part divided into more curved and straight segments in an alternating presentation. The appearance of extra non-local resonant attenuation bands and the decrease of attenuation performance of the original non-local resonant attenuation bands indicates that the attenuation capability of the non-local resonant attenuation bands is homogenized in the frequency domain for the bi-periodic coupling system. The innovative findings and practical suggestions in the whole frequency range could provide potential references for the researchers and engineers in vibration reduction design of bi-periodic structures in engineering practice.
Study on the evaluation of GIS technology on surface water resources in the security intelligence perspective
Authors: Deng Hongwei , Ranchunzhen Ranchunzhen
Published: April 2023

Seeking an efficient and reasonable evaluation method to determine the current evaluation situation of water resources can maximize the protection and utilization of water resources. This paper analyzes the characteristics of previous GIS technology in the evaluation of surface water resources and proposes the establishment of a GIS evaluation optimization model based on security intelligence perspective for the problems of information redundancy and low transmission efficiency of this evaluation method. Firstly, the feasibility and science of constructing a new model under the perspective of security intelligence is discussed, secondly, the development and application of security intelligence theory and the workflow of GIS technology in evaluating surface water resources are reviewed, and finally, the cycle chain of surface water resources evaluation and the optimization model of surface water resources evaluation based on GIS under the perspective of security intelligence are established, and the traditional surface water resources security management system is combined with security intelligence. The security intelligence subsystem and security management subsystem of surface water resources in the intelligence perspective are constructed. The study shows that the surface water resource evaluation model established by GIS technology under the perspective of security intelligence can make up for the deficiencies in information sharing and data standardization of common surface water resource evaluation models, solve the problems of redundancy of massive information and distortion of evaluation results, and provide suggestions for surface water resource evaluation decisions in a certain region or a certain basin.
Nonlinear interactions between vibration modes with vastly different eigenfrequencies
Authors: Shoshani Oriel , Shaw Steven
Published: April 2023

Nonlinear interactions between modes with eigenfrequencies that differ by orders of magnitude are ubiquitous and occur in various fields of physics, ranging from cavity optomechanics to aeroelastic systems. We show that the complex dynamics of these interactions can be distilled into a single generic form, namely, the Stuart-Landau oscillator. We use this model to study lasing in such systems that result in frequency combs that arise from injection locking and frequency pulling of a low-frequency mode that interacts with a blue-detuned high-frequency mode. Our analysis shows that the frequency combs are tunable around both the high and low carrier frequencies. The novelty of our analysis lies in the minimalistic conceptual view that it offers, including an analogy between these complex interactions and a simple mechanical system model and a connection between the injection locking and pulling of the low-frequency mode and the motion of an overdamped particle in a tilted washboard potential. The results are applicable to a wide class of systems and suggest means of generating tunable frequency combs.
Potential health risk of fluoride in groundwater of CKDu endemic areas in Cuttack district of Odisha, India
Authors: MOHANTY SHRADDHA , Nayak Rabindra Kumar , Jena Bandita , Padhan Kshitipati , Dash Prava Kiran , Sahoo Sanjib Kumar , Das Jyotirmayee
Published: April 2023

In Odisha, chronic kidney disease of unknown aetiology (CKDu) has become a major health concern. The disease is particularly prevalent in farming communities and among individuals who rely on groundwater as their primary source of drinking water. Kidney damage is directly associated with excessive fluoride levels in drinking water. The fluoride concentration of 66 typical groundwater samples were analysed throughout 17 gram panchayats in the Narasinghpur block of Cuttack district, Odisha, India, which is considered a hotspot for CKDu. The research area's groundwater fluoride concentration ranged from 0.58 to 4.95 mg/L, with an average of 1.8 mg/L. The content of fluoride in more than 57% of drinking water samples exceeded the WHO recommendation of 1.5 mg/L. The study also assessed the residents' health risks based on exposure pathways through ingestion and dermal contact using the USEPA human health risk assessment model. The values of chronic daily intake (CDI) and Hazard Quotient (HQ) indicated that excessive drinking of fluoride-rich groundwater poses a higher risk of non-carcinogenic health problems to local residents. In the research location, infants and children are more susceptible to the non-carcinogenic health risks of fluoride than adults. This takes place mainly through direct ingestion route where the dominance order of the total hazard index (THI) of population was infants > children > men > women for all sampling locations, suggesting significantly higher risk than the permissible limits (> 1). Based on the results, the area can be classified as a high-risk zone for fluoride-related issues and requires immediate intervention to protect the health and safety of the local population. This study indicates that long-term exposure to fluoride in drinking water may pose harm to human health and disrupt kidney functions. Thus, continuous monitoring and improved management of water supplies in CKDu-affected regions are crucial for determining the contamination load and mitigating the adverse health effects caused by excessive and prolonged exposure to the fluoride found in ground water.
The purpose of weights in excitable brain networks
Authors: Messé Arnaud , Hütt Marc-Thorsten , Hilgetag Claus
Published: April 2023

Nerve fiber networks connecting different brain regions are the structural foundation of brain dynamics and function. Neural connectomes have been frequently described as binary networks, in basic terms of present or absent connections. By contrast, recent approaches have provided more detailed characterizations of connectomes with weighted-strength connections. However, the topological analysis of weighted networks still has methodological limitations. As a consequence, many investigations of neural network are performed on unweighted networks obtained via binarization, and the functional impact of the unweighted versus the weighted neural networks is unclear. Here we show, for the widespread case of excitable dynamics, that the excitation patterns observed in weighted and unweighted networks are nearly identical, if an appropriate threshold is selected. We generalize this observation to different excitable models, and formally predict the network threshold from the intrinsic model features. The network-binarizing capacity of excitable dynamics suggests that neural activity patterns may primarily depend on binary topological properties of neural networks. Moreover, it appears reasonable to assess topological properties of weighted networks with the standard graph-theoretical tools for binarized networks. Our findings have implications for the functional interpretation of connectome data in neuroscience as well as diverse other systems governed by excitable dynamics.
Seasonal and age-related changes in sperm quality of farmed Arctic charr (Salvelinus alpinus)
Authors: Kurta Khrystyna , Jeuthe Henrik , Naboulsi Rakan , Koning Dirk-Jan , Palaiokostas Christos
Published: April 2023

Background
Substantial variation in male fertility is regularly observed in farmed Arctic charr. However, detailed investigations of its fluctuation during a reproductive season and across years are lacking. Furthermore, information about the effect of underlying genetic factors influencing sperm quality is scarce. The current study focused on seasonal and age-related factors that may affect sperm quality characteristics in males reared in natural and delayed photoperiods. Animals were sampled on three occasions for two consecutive years, and sperm quality parameters were recorded using a computer-assisted sperm analysis (CASA) system. Thereafter, high-throughput sequencing technologies were applied, aiming to identify genomic regions related to the variation of sperm quality throughout the reproductive season.
Results
An across-season variation in the recorded sperm quality parameters was evident. Overall, 29% and 42% of males from the natural and delayed spawning groups, respectively, had a highly variable total progressive motility. Males at four years of age showed significantly higher sperm motility and velocities during the early October and November recordings compared to the following year when the same animals were five years of age. On the other hand, the opposite was observed regarding sperm concentration during the last sampling. A genome-wide FST scan detected SNP differentiation among males with high and low variability in total progressive motility (PM) on eight chromosomes (FST > 0.17), Genome wide windows with the highest FST contained SNPs in proximity (within 250 kb up- and downstream distance) to 16 genes with sperm quality biological functions in mammalian species.
Conclusion
Our findings provide a detailed view of seasonal, age-related, and genetic effects on sperm quality and can be used to guide decisions on broodstock selection and hatchery management.
The heterogeneity and clonal evolution analysis of the advanced prostate cancer with castration resistance
Authors: Chen Lu , Liu Ao , Wang Qi , Lin Wenhao , Ma Zhiyang , Yang Xiaoqun , Gao Yi , Xu Danfeng
Published: April 2023

Background
Nowadays, the incidence rate of advanced prostate cancer at the first time of diagnosis grows higher in China yearly. At present, androgen deprivation therapy is the standard first-line treatment of advanced prostate cancer. However, after several years of ADT, most patients will inevitably progress to castration-resistant prostate cancer (CRPC). Previous studies mainly focus on Caucasian and very few on East Asian patients.
Methods
In this study, the pre-and post-androgen deprivation therapy tumor samples were collected from five Chinese patients with advanced prostate cancer. The whole-exome sequencing, tumor heterogeneity, and clonal evolution pattern were analyzed.
Results
The results showed that the gene mutation pattern and heterogeneity changed significantly after androgen deprivation therapy. Tumor Mutational Burden (TMB) and Copy Number Alteration (CNA) were substantially reduced in the post-treatment group, but the Mutant-allele tumor heterogeneity (MATH), Socio-Demographic Index (SDI), Intratumor heterogeneity (ITH), and weighted Genome Instability Index (wGII) had no significant difference. According to the clone types and characteristics, the presence of main clones in five pre-and post-treatment samples, the clonal evolution pattern can be further divided into two sub-groups (the Homogeneous origin clonal model or the Heterogeneous origin clonal model). The Progression-free survival of the patients with the “Homogeneous origin clonal model” was shorter than the “Heterogeneous origin clonal model”. The longer PFS might relate to MUC7 and MUC5B mutations repaired. ZNF91 mutation might contribute to resistance to androgen deprivation therapy.
Conclusion
Our findings revealed potential genetic regulators to predict the castration resistance and provide insights into the castration resistance processes in advanced prostate cancer.
Evaluating The Infinium Human MethylationEPIC v2 BeadChip
Authors: Kaur Diljeet , Lee Solmoe , Goldberg David , Spix Nathan J , Hinoue Toshinori , Li Hong-Tao , Dwaraka Varun B , Smith Ryan , Shen Hui , Liang Gangning , Renke Nicole , Laird Peter W , Zhou Wanding
Published: April 2023

Infinium Methylation BeadChips are widely used to profile DNA cytosine modifications in large cohort studies for reasons of cost-effectiveness, accurate quantification, and user-friendly data analysis in characterizing these canonical epigenetic marks. In this work, we conducted a comprehensive evaluation of the updated Infinium MethylationEPIC v2 BeadChip (EPICv2). Our evaluation revealed that EPICv2 offers significant improvements over its predecessors, including expanded enhancer coverage, applicability to diverse ancestry groups, support for low-input DNA down to one nanogram, coverage of existing epigenetic clocks, cell type deconvolution panels, and human trait associations, while maintaining accuracy and reproducibility. Using EPICv2, we were able to identify epigenome and sequence signatures in cell line models of DNMT and SETD2 loss and/or hypomorphism. Furthermore, we provided probe-wise evaluation and annotation to facilitate the use of new features on this array for studying the interplay between somatic mutations and epigenetic landscape in cancer genomics. In conclusion, EPICv2 provides researchers with a valuable tool for studying epigenetic modifications and their role in development and disease.
Multidimensional Molecular Characteristics of Early-Onset Endometrioid Endometrial Carcinoma, And Potential Predictors Of Response To Fertility Sparing Therapy
Authors: Sun Chaoyang , Hu Zhe , Liu Jingbo , Liu Wei , Ning Yan , Fan Junpeng , Li Wenting , Yang Xiaohang , Dou Yingyu , Wang Wei , Peng Wenju , Lu Funian , Zhuang Xucui , Qin Tianyu , Kang Xiaoyan , Wu Zimeng , Feng Chenzhao , Xu Zhiying , Lv Qiaoying , Wang Qian , Wang Chao , Wang Xinyan , Wang Zhiqi , Jiang Jie , Wang Beibei , Mills Gordon , Chen Gang , Chen Xiaojun
Published: April 2023

Endometrial carcinoma (EC) remains a public health concern with a growing incidence particularly in younger women. Women with early-onset endometrioid EC (EEEC) who wish to maintain fertility are a worldwide concern. To illuminate the molecular characteristics of EEEC, we undertook a large-scale proteogenomic study of 222 EECs encompassing 81 EEEC who were 40 or younger. In contrast to late-onset EEC, integrated multi-omics analysis unexpectedly revealed an exposome-related mutational signature to be associated with EEEC leading to EEEC specific CTNNB1 and SIGLEC10 hotspot mutations and downstream protein pathway disturbance. Interestingly, in EEECs SIGLEC10Q144K mutation resulted in aberrant Siglec-10 protein expression and promoted progestin resistance by interacting with ERα. Collectively, our study provides a unique high-quality proteogenomic resource of EEECs while enabling insights into interactions between exposome and genomic susceptibilities for primary prevention and early detection of EEECs. Furthermore, we identified biomarkers for progestin response in EEEC fertility-sparing treatment.
Use of Artificial Intelligence Software Helpful for Regional Anesthesia Education in Self-Reported Questionnaire in Academic Medical Center Setting
Authors: Scholzen Elizabeth A , Schroeder Kristopher M
Published: April 2023

Background: The field of regional ultrasound has changed drastically in the past few decades with the widespread use of ultrasound and improvement of ultrasound images and enhancement of needle visibility on ultrasound. The field is continuing to improve with novel advancements in artificial intelligence software to enhance the field of regional anesthesia education. However, there has been relatively little research on the use of artificial intelligence software on the provision of regional anesthesia education. This study looked to discover the usability of one artificial intelligence software, the NerveBlox® software, in a self-reported questionnaire in an academic medical center among trainees and faculty anesthesiologists.
Methods: 11 anesthesiologists and 25 anesthesiology residents at the University of Wisconsin used the NerveBlox® software to simulate performing supraclavicular and adductor canal nerve blocks on standardized patients and filled out a survey on the utility and functionality of the AI software.
Results: Both faculty and residents rated the NerveBlox® system as helpful in regards to identifying key anatomical structures during the procurement of a regional ultrasound image. Both groups also highly rated the NerveBlox® software as helpful for trainees to improve education in regional ultrasound.
Conclusion: In this small study, both faculty anesthesiologists and anesthesiology residents found the NerveBlox® software to be helpful in both performing regional anesthesia procedures as well as for improving education of regional anesthesia procedures in trainees. Further study with more learners would be helpful to determine the extent of the usefulness of AI software in regional anesthesia education.
Association between α1-adrenoceptor antagonists and delirium: Analysis of the Japanese Adverse Event Report database
Authors: Kotake Kazumasa , Noritake Yumi , Kawakami Yasuhiro
Published: April 2023

Background: Tamsulosin, an α1-adrenoceptor antagonist, may increase the risk of dementia in older men with benign prostatic hyperplasia. An association between α1-adrenoceptor antagonists and delirium has been suggested, but the details are unclear.
Aims: This study investigated the association between α1-adrenoceptor antagonists and delirium in patients with benign prostatic hyperplasia, using the Japanese Adverse Drug Event Report database.
Method: First, disproportionality analysis compared the frequency of delirium in the α1-adrenoceptor antagonists silodosin, tamsulosin, and naftopidil. Next, multivariate logistic analysis was performed to examine the association between delirium and α1-adrenoceptor antagonists where disproportionality was detected.
Results: A disproportionality in delirium was observed in patients who received tamsulosin (reporting odds ratio 1.85, 95% confidence interval 1.38–2.44, P < 0.01) and naftopidil (reporting odds ratio 2.23, 95% confidence interval 1.45–3.28, P < 0.01). Multivariate logistic analysis revealed that in addition to previously reported risk factors for delirium, delirium in patients who received tamsulosin was significantly increased with concomitant use of anticholinergics (odds ratio 2.73, 95% confidence interval 1.41–5.29, P < 0.01) and delirium in patients who received naftopidil was significantly increased with concomitant use of β3 adrenoceptor agonists (odds ratio 4.19, 95% confidence interval 1.66–10.6, P < 0.01).
Conclusion: We found that concomitant use of anticholinergic or β3 adrenoceptor agonistsused to treat overactive bladder were strongly associated with delirium. Therefore, confirming the medical history and concomitant medications of patients who receive tamsulosin or naftopidil and providing preventive interventions for delirium may contribute to improved patient outcomes.
Attenuated but immunostimulatory Mycobacterium tuberculosis variant bovis strain Ravenel shows variation in T cell epitopes
Authors: Brenner Evan P. , Sreevat Srinand
Published: April 2023

Tuberculosis, caused by Mycobacterium tuberculosis complex (MTBC) organisms, affects a range of humans and animals globally. Mycobacterial pathogenesis involves manipulation of the host immune system, partially through antigen presentation. Epitope sequences across the MTBC are evolutionarily hyperconserved, suggesting their recognition is advantageous for the bacterium. Mycobacterium tuberculosis var. bovis (MBO) strain Ravenel is an isolate known to provoke a robust immune response in cattle, but typically fails to produce lesions and persist. Unlike attenuated MBO BCG strains that lack the critical RD1 genomic region, Ravenel is classic-type MBO genetically, suggesting genetic variation is responsible for defective pathogenesis. This work explores variation in epitope sequences in MBO Ravenel by whole genome sequencing, and contrasts such variation against a fully virulent clinical isolate, MBO strain 10-7428. Validated MTBC epitopes (n=4,818) from the Immune Epitope Database were compared to their sequences in MBO Ravenel and MBO 10-7428. Ravenel yielded 3 modified T cell epitopes, in genes rpfB, argC, and rpoA, with changes not in silico predicted to significantly affect protein stability. In contrast, no T cells epitopes were changed in 10-7428. Considering T cell epitope hyperconservation across MTBC variants, these altered MBO Ravenel epitopes support a contribution to its attenuation. The affected genes may provide clues on basic pathogenesis, and if so, be feasible targets for reverse vaccinology.
Excessive Internet use among Finnish young people between 2017 and 2021 and the effect of COVID-19
Authors: Kiviruusu Olli
Published: April 2023

Purpose
An increase in excessive Internet use (EIU) among adolescents during the COVID-19 pandemic was suggested in many studies. However, these studies were mostly based on cross-sectional and/or unrepresentative samples.
Methods
Using data from a nationwide Finnish school survey in the years 2017, 2019 and 2021 (N=450,864; aged 13–20 years), changes in the prevalence of EIU (EIUS, 5-item) were assessed. The effects of COVID-19 (year 2021 vs. 2017/2019 combined) and linear trend were analyzed in logistic regression models. Models were adjusted for loneliness, depression, anxiety, and sociodemographic factors.
Results
Among males, EIU prevalence varied minimally (7.8–8.1%) from 2017 to 2021. Among females, the prevalence increased from 6.8% to 11.7% and the effect of COVID-19 was significant (OR=1.53; p<0.001). Including the linear trend in the model turned the COVID-19 effect on EIU among females non-significant (p=0.625), whereas the trend was significant (OR=1.17; p<0.001). Adjusting the models with mental health-related factors attenuated the effect of COVID-19 to some extent, but not the effect of linear trend.
Conclusions
There is a sex difference in the way the prevalence of EIU developed from 2017 to 2021 among Finnish adolescents. In males, there was no indication of increased prevalence of EIU and among females, while the effect of COVID-19 was first found, it was also suggested to be a product of a trend already started before the COVID-19 pandemic. These results are in contrast with some earlier studies suggesting an effect of COVID-19 on EIU.
The Effects of Atmospheric Nitrogen Dioxide and Sulphur Dioxide on the Biochemical Factors of Plant Tolerance
Authors: ADAK PRASENJIT , KOUR NAVNEET
Published: April 2023

Atmospheric nitrogen dioxide (NO2) and sulphur dioxide (SO2) enter leaves through stomata and follow the same diffusion pathways as carbon dioxide (CO2). During the exposure of these pollutants the plants experience changes in the levels of their biochemical constituents (such as, ascorbic acid, chlorophyll, leaf extract pH, and relative water content). Biochemical and Physiological changes in plant leaves are studied and quantified using air pollution tolerance index (APTI) formula. A plant with high APTI can be used as a tolerant, while a plant with a low APTI can be used as a crucial bio-monitor to track the level of air pollution. In the present study, APTI of 15 plants species were calculated. The leaves of the selected plants were sampled from six different locations in Punjab India. Simultaneously air quality data was collected from central pollution control board (CPCB) online monitoring portal. Among 15 species collected from Jalandhar, Amritsar, and Ludhiana, the Ficus religiosa has the highest APTI values (144.6, 176.7, and 280 respectively). Similarly in Sector 22, Sector 25 and Sector 53 of Chandigarh, Ficus benghalensis has been reported to have the highest APTI values. Moreover, the present study correlates the APTI and the concentration of gaseous air pollutants (SO2 and NO2) in the atmosphere. The APTI of the studied plant species has been found to have a negative correlation with SO2 but no significant correlation has been found with NO2. The current study provides pollutant-specific information and insights that can potentially contribute in improvement in the APTI formula.
Influence of warming with temperature oscillations on the life history traits of the Aphids Acyrthosiphon pisum and Megoura crassicauda
Authors: Mala Mukta , Hemmings Zac , Andrew Nigel R.
Published: April 2023

Organisms naturally experience diurnal temperature fluctuations and variable extreme environmental events rather than only static thermal regimes. Therefore, experimental studies that use only static mean daily, monthly or yearly temperatures overlook the possible influence of diurnal temperature fluctuations. Exposure to fluctuating temperatures enables an organism to perform more ‘naturally’ as they have a period of recovery, whereas under constant temperature, they do not have thermal recovery periods. This study compares the impacts of fluctuating and constant temperatures on the fitness and demographic parameters of the pea aphid,Acyrthosiphon pisum. We use four fluctuating temperature regimes that are increased by + 0°C, + 2°C, + 4°C and + 5°C from field-recorded, fluctuating base temperatures and four constant temperatures of 19°C, 21°C, 23°C and 24°C as treatments and also use a control temperature of 25°C. We find thatA. pisumexhibited faster development, quicker generation time (GT), lower population doubling time (DT), increased intrinsic rate of increase (rm) and a finite rate (λ) under warming conditions. In contrast, adult longevity, survival period, fecundity, net reproductive rate (R0), age-specific survivorship (lx) and age-specific fecundity (mx) were negatively affected by warming. The fluctuating thermal regimes improved overall fitness and all demographic parameters of both aphid species; therefore, we identify that daily fluctuating temperatures play a vital role in monitoring and predicting natural population dynamics. These results have implications for the experimental forecasting of natural population dynamics under climate change and global warming predictions.