bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of Audio Technology of Internet of Things Based on Parallel Storage System in Music Classroom
Authors: Yan Jiang 
Published: April 2023

Abstract
Hard disk not only has powerful storage capacity, but also has highly intelligent interface and convenient application design. In daily life, hard disk is a very suitable tool for data collection and storage. The performance of hard disk is better when the number of samples is not too many, the sampling rate is low, and the number of sampling paths is small. However, when faced with some complex problems with high sampling rate and multiple paths, high-speed data storage will face greater difficulties. Therefore, this paper introduces a parallel storage system, and discusses the basic structure and the implementation of the system the factors that affect the storage rate, the specific structure of the data acquisition system in the system, which is subdivided into the structure of the power supply, data acquisition, caching and sorting and so on. With the support of parallel storage system, this paper summarizes some basic characteristics of audio, and focuses on the decisive role of hard disk in audio interactive system. In the process of research, it is found that the hardware system based on parallel storage system has many advantages, such as low consumption, small volume, high performance and low cost, which can achieve the research goal well. In recent years, the Internet of things has been widely used in many fields. Scientists have long explored the application of the Internet of things technology in the construction of contemporary mobile multimedia audio system, so that the multimedia video communication system can achieve intelligent development, and at the same time to realize its performance optimization, the price of the Internet of things audio technology can be reduced. In this paper, combined with the advantages of parallel storage system, the application of Internet of things audio technology in music classroom will be discussed to improve the efficiency of music teaching and students' music literacy.
Structural and Dimensional Analysis by Computed Tomography of Multi Geometric Template Manufactured by Fused Deposition Modeling
Authors: Aguilar-Duque Julian Israel , Ontiveros Sinue , Baez-Lopez Yolanda , Tlapa Diego 
Published: April 2023

Abstract
During the last decade of the 20th century, there has been significant growth in the applications and development of manufacturing processes associated with Additive Manufacturing (AM). The evolution of production systems has made it possible that today there are more than 20 technologies associated with this production system. As a consequence of the development of AM, strategies have been developed to optimize the printing process focused on reducing manufacturing time, such as using Genetic Algorithms (GA). The effect caused by the modification of the path patterns is an effect of interest in two aspects; on the one hand, the dimensional assurance focused on the compliance of the dimensions of the components in comparison with the digital design of the same, and on the other hand, the structural composition and resistance that the printing process itself can generate. This paper aims to present the effect of optimizing the path of Fused Filament Fabrication (FFF) equipment on the dimensional finish and structural quality of a multi-geometric component. For this purpose, a template composed of 23 geometric elements, printed by FFF technology, using PLA as base material, is used. The dimensional analysis is performed using Geomagic software, and the porosity analysis is performed using VG Studio software concerning the 134 attributes of interest. The results show, on the one hand, a 12% reduction in the total process time required to print the component. On the other hand, using Computed Tomography (CT), it was identified the effect on the dimensional precision of printing three elements with characteristics associated with the angular precision or definition of external angles and the roundness demanded by an unsupported cantilevered arch. In addition, it was possible to ensure that the structural quality of the multi-geometric component was not affected by the modification of the path required by the printing process.
Processing of Chinese Language and Text Information System Under the Background of Speech Recognition
Authors: Cao Huiqin , He Peng , Wang Chengjin 
Published: April 2023

Abstract
With the popularization of computers, artificial intelligence technology has become more and more mature, among which speech recognition technology in artificial intelligence is favored by people. In the past few years, the acoustic model combined with the Gaussian mixture model and the hidden Markov model has always been in the leading position. In the field of speech recognition technology, because the development of speech data has gradually expanded, and the complexity of the data has also increased. The larger the data, the traditional data network model is slowly showing inadequacy. However, the deep neural network model is easy to deal with large and complex data modeling. This article combines the advantages of basic learning theory and speech recognition technology, and launches in-depth research on embedding learning theoretical knowledge into the field of speech recognition. Nowadays, large-scale text information databases relying on computers are becoming more and more important in linguistic research, and a large-scale corpus that fully reflects language facts and contains rich language information has been constructed. The establishment of the text information database system is long, from word segmentation, part-of-speech tagging to syntactic tagging to semantic tagging. Therefore, the characteristic of information system processing is that the systematic description depends on the application environment of understanding vocabulary and reasoning. According to different scenarios, the realization methods of semantic description roles are also different, and the description of semantic roles in correct scenarios is clearer, more detailed and systematic. Therefore, this article is of great significance for solving the semantic problem of using Chinese frame network for Chinese information processing in the context of speech recognition.
ATP modulation of osmotically activated anionic current in the membrane of Phycomyces blakesleeanus sporangiophore
Authors: Stevanović Katarina S. , Čepkenović Bogdana , Križak Strahinja , Pajić Tanja , Todorović Nataša V. , Živić Miroslav Ž. 
Published: April 2023

Abstract
Ion channels are vital components of filamentous fungi signaling in communication with their environment. We exploited the ability of the apical region of growing sporangiophores of Phycomyces blakesleeanus to form membrane-enveloped cytoplasmic droplets (CDs), to examine ion currents in the filamentous fungi native plasma membrane. In hypoosmotic conditions, the dominant current in the CDs is ORIC, an osmotically activated, anionic, outwardly rectified, fast inactivating instantaneous current that we have previously characterized. Here, we examined the effect of ATP on ORIC. We show that CDs contain active mitochondria, and that respiration inhibition by azide accelerates ORIC inactivation. ATP added intracellularly, reduced ORIC run-down and shifted the voltage dependence of inactivation toward depolarized potentials, in a manner that did not require hydrolysis. Notably, ATP led to slowing down of ORIC inactivation, as evidenced by an increased time constant of inactivation, τin, and diminished decreasing of τin during prolonged recordings. Flavonoids (genistein and quercetin) had the effect on ORIC opposite to ATP, acting as current inhibitors, possibly by disrupting the stabilizing effect of ATP on ORIC. The integration of osmotic sensing with ATP dependence of the anionic current, typical of vertebrate cells, is described here for the first time in filamentous fungi.
Overcoming Language Barriers to Environmental Information: A Study of Easy-to-Read Adaptations
Authors: Pujadas-Farreras Marina , McDonagh Sarah Anne 
Published: April 2023

Abstract
Access to clear and scientifically verified information is crucial to understand the scale of the challenge of the climate crisis, allowing policymakers, governments, and individuals to better respond to it. However, for some, including people with intellectual and cognitive disabilities as well as those who have difficulty reading, climate science can be difficult to understand with complex sentence structures and jargon obscuring important environmental information. The aim of this paper is to assess the main linguistic barriers to information about the climate crisis for people with intellectual and cognitive disabilities and reading difficulties. Using the examples of the Greater London Authority’s Environment Strategy Executive Report and the Northern Ireland Executive Discussion Document on a Northern Ireland Climate Change Bill, and their adaptations into Easy-to-Read as our corpus, we will examine the different morphosyntactic and lexical elements of each text. Our results show that both Easy-to-Read versions were generally easier to understand than the standard versions. However, the Northern Ireland Easy-to-Read text was more syntactically complex with longer and more complicated sentence structures, owing to its function as a consultation document. We conclude that the main access barriers in the Northern Ireland Easy-to-Read text are related to its morphosyntactic elements, a conclusion supported by our qualitative analysis of the standard text. More generally, the lexical aspects of both Easy-to-Read texts showed positive results, which suggests that they may be more easily simplified compared to morphosyntactic aspects. However, more systemic and contrastive research is required to confirm our findings, in addition to user testing with people with cognitive and intellectual disabilities and those who have difficulties reading.
Effect of onchocerciasis elimination measures on the incidence of epilepsy in Maridi, South Sudan: a three-year prospective study
Authors: Jada Stephen Raimon , Amaral Luís-Jorge , Lakwo Thomas , Carter Jane Y , Rovarini Jacopo , Bol Yak Yak , Logora Makoy Yibi , Hadermann Amber , Hopkins Adrian , Fodjo Joseph N Siewe , Colebunders Robert 
Published: April 2023

Abstract
Background
High onchocerciasis transmission predisposes endemic communities to a high epilepsy burden. Retrospective studies suggest that adequate onchocerciasis control would decrease the epilepsy burden, but this has never been assessed prospectively. The 4.4% (95% CI: 4.1–4.7%) epilepsy prevalence documented in 2018 in the onchocerciasis focus in Maridi, South Sudan, prompted the strengthening of onchocerciasis elimination measures. We evaluated the effect of these interventions on the incidence of epilepsy, including nodding syndrome (NS).
Methods
Community-directed treatment with ivermectin (CDTi) was implemented annually in 2017, 2018 and 2019, interrupted in 2020 and re-implemented biannually in 2021. Additionally, a community-based “Slash and Clear” vector control method was initiated in 2019 at the Maridi dam, the main blackfly breeding site. Community-based surveys were conducted in Maridi in 2018 (baseline) and 2022 (follow-up) to investigate changes in epilepsy incidence following onchocerciasis elimination interventions. Epilepsy was confirmed via a two-stage approach: the house-to-house screening of all residents followed by confirmation of the epilepsy diagnosis by trained clinicians.
Results
The baseline and follow-up surveys included 17,652 and 14,402 individuals, respectively. When biannual CDTi was initiated in 2021, CDTi coverage rose by 15.7% (95% CI: 14.6–16.8%); still, only 56.6% of the population took ivermectin in 2021. Between 2018 and 2022, epilepsy incidence decreased from 348.8 (95% CI: 307.2–395.8) to 41.7 (95% CI: 22.6–75.0) per 100,000 person-years. Similarly, the incidence of NS decreased from 154.7 (95% CI: 127.6–187.3) to 10.4 (95% CI: 2.7–33.2) per 100,000 person-years. Living closer to the Maridi dam, being aged 6–40 years, not taking ivermectin and being male constituted risk factors for epilepsy.
Conclusions
In onchocerciasis-endemic areas with high epilepsy prevalence, strengthening onchocerciasis elimination interventions can decrease the incidence of epilepsy, including NS. Additional efforts are needed to increase CDTi coverage and sustain blackfly control in Maridi.
Sports Mental Health Monitoring Based on Multiobjective Evolutionary Algorithms in the Internet of Things
Authors: Xiaoyan Li , Yunjing Shi , Qiang Gao 
Published: April 2023

Abstract
With the increasing popularity of sports such as football and basketball, many policy reforms are striving to strengthen the education of sports talents in China. The release of relevant policies can further promote the development of sports and enable more and more people to promote physical and mental health through sports activities. The emergence of the Internet of Things, especially the emergence of intelligent wearable devices, has brought many conveniences to the long-term detection and analysis of human health and motion parameters. By measuring human health and sports information, it is possible to quantitatively monitor the amount of exercise and physical health level of athletes, in order to achieve more effective training effects. In addition, for complex multi-objective problems, multi-objective evolutionary algorithms can effectively solve problems that are difficult to handle, suppress, and balance targets. Therefore, this article uses a multi-objective evolutionary algorithm to complete mental health monitoring based on the Internet of Things. It monitors the impact of sports on students' mental health, compares their mental health before and after the experiment, and analyzes the data changes before and after the experiment to summarize the impact of sports on students' mental health. The main characteristics of multi-objective evolutionary algorithm are excellent convergence and diversity. This article uses its main characteristics to real-time monitor the mental health level of college students during exercise through the Internet of Things, opening up a new way to improve their mental health.
Stability analysis of intelligent English translation system based on model predictive control algorithm
Authors: YANG Fan 
Published: April 2023

Abstract
English translation systems often require manual input to convert speech into text document mode, which leads to poor translation results. In order to improve the intelligence of the intelligent English translation system, based on the machine learning algorithm, this paper constructs an intelligent English translation system based on the model predictive control algorithm, and combines the self-triggering MPC with the robust control to propose a corresponding control solution. That is, a robust self-triggering MPC method is proposed for linear systems with constraints. Moreover, this paper studies the stability and robustness of MPC in continuous time systems and describes the interfaces to be used in the system and the performance requirements of the system. In addition, this paper analyzes and describes the feasibility of the system development plan. Finally, this paper designs experiments to analyze the model performance from the system translation accuracy rate, system login security and system stability. The research results show that the model constructed in this paper has certain practical effects.
Application of data mining based on Improved Ant Colony Algorithm in college students' employment and Entrepreneurship Education
Authors: Zhang Yingnan 
Published: April 2023

Abstract
Under the background of the new era of economy, the employment and entrepreneurship education of college students has also ushered in new problems. In the construction of student employment and entrepreneurship data mining model, data solving efficiency and association rule mining play a key role in the performance of the model. How to optimize and improve the mathematical model and improve the accuracy of student employment and entrepreneurship data analysis needs further research and analysis. This paper constructs the mathematical model of ant colony algorithm, introduces the logical process in solving practical problems, provides setting suggestions for the value of algorithm parameters, and improves the solution efficiency. This paper improves the decision tree classification method and ant colony algorithm. The association rule mining based on ant colony has more perfect reference value. From the combination and interest analysis of College Students' employment and entrepreneurship content, it provides efficient, practical and useful information for the school. Finally, after constructing the prediction model, this paper analyzes the four factors affecting the choice of College Students' homework entrepreneurial intention, which are individual, family, school and society, and puts forward five measures to improve college students' Entrepreneurship and employment education.
Individual and Combined Effects of Alanine Aminotransferase and Hemoglobin on Metabolic Syndrome in the Elderly in Qingdao, China
Authors: Liu Li , Shao Yuhan , Feng Enqiang , Shao Zhugang , Xing Dongming 
Published: April 2023

Abstract
Aims
We aimed to investigate individual and combined effects of alanine aminotransferase(ALT) and hemoglobin(Hb) on metabolic syndrome(MetS) in the elderly.
Methods and Results
Participants came from the health examinations for the elderly in 2021 in Qingdao, China. 34,399 individuals aged 65 years and older were included in the current study. Based on a combination of ALT and Hb levels in the tertile, participants were grouped into nine groups. Logistic regression models were used to analyze individual and combined effects of ALT and Hb on MetS. ALT and Hb were both independently related to MetS and respective ORs(95%CIs) were 1.46(1.42–1.50) and 1.16(1.12–1.19). With the elevation of ALT or Hb levels, risks for MetS and its components increased. Compared to the reference group, ORs (95%CIs) of combined ALT and Hb for MetS were 1.23(1.13–1.35), 1.34(1.23–1.47), 1.59(1.46–1.74), 1.63(1.49–1.78), 1.89(1.72–2.08), 2.41(2.21–2.63) and 2.61(2.39–2.84) in Group 2–9 after adjusting for confounding factors.
Conclusions
ALT and Hb were both independently related to MetS. Combined ALT and Hb levels could increase risks of MetS and its components than an elevation in ALT or Hb alone. Therefore, individuals should take measures to lower their ALT and Hb levels to reduce the morbidity of MetS.
Improved Adaptive Momentum Method
Authors: Kabiri Hichame , Ghanou Youssef , Khalifi Hamid , Casalino Gabriella 
Published: April 2023

Abstract
In this paper, we present a new gradient descent optimization method that overcomes some weaknesses of existing gradient descentoptimization strategies. The proposed optimization technique is basedon the variation of simple gradients and regulates the learning rate inresponse to the need for an efficient learning adjustment mechanism.The memory and hyper-parameter requirements of our algorithm are reduced compared to other algorithms. We provide a convergence analysisof the algorithm. In order to evaluate our algorithm we perform classification tests on the MNIST data collection, IMDB movie review data andCIFAR-10 data, to explore how our proposed method performs againststate-of-the-art optimizers, such as SGD(M), Adam, Adamax, NadamRMSProp, Adagrad and AdaDelta. Our algorithm is computationallyefficient and effective when compared to existing methods.
Golden Ratio Information for Neural Spike Code
Authors: Deng Bo 
Published: April 2023

Abstract
Spike bursting is a ubiquitous feature of all neuronal systems. Assuming the spiking states form an alphabet for a communication system, what is the optimal information precessing rate? and what is the channel capacity? Here we demonstrate that the quaternary alphabet of spike number code gives the maximal processing rate, and that a binary source in Golden Ratio distribution gives rise to the channel capacity. A multi-time scaled neural circuit is shown to satisfy the hypotheses of this neural communication system.
Appropriate Momentum Provision for Numerical Simulations of Horizontally Homogeneous Urban Canopies Using Periodic Boundary Conditions
Authors: Sanemitsu Toshiki , Ikegaya Naoki , Okaze Tsubasa , Finnigan John 
Published: April 2023

Abstract
Turbulent flow over urban-like roughness has been numerically studied for various purposes, such as the clarification of turbulent characteristics over rough walls, visualization of turbulent structures around block arrays, and evaluation of urban ventilation and pedestrian winds. In such simulations, a portion of the developing boundary layer is extracted as a numerical domain, assuming periodic boundary conditions in the horizontal direction to reproduce laterally homogeneous rough surfaces. However, the conditions required to drive the airflow by an artificial momentum source uniquely determine the turbulent statistics, which are different from those in developing boundary layers. Therefore, this study presents a new approach for driving the airflow over urban-like block arrays. The new method is based on spatially averaged Navier–Stokes equations to prove the necessity of height-dependent momentum provision. The turbulent flow over a cubical-block array is determined using large-eddy simulations driven by four different momentum sources. Regardless of the driving force, the vertical profiles of the streamwise velocity components are identical. In contrast, slight differences in the vertical Reynolds stress, variances in the velocity components, and turbulence kinetic energy are appropriately reproduced in the new approach. In addition, the budget equations of the turbulent statistics reveal that a change in the vertical Reynolds stress affects the energy production and its redistribution into variance components. The proposed method can contribute to the reproduction of a realistic turbulent flow and provide a theoretical understanding of the momentum provision.