bluuebunny/crossref_metadata_2025 huggingface dataset:
Indicadores higrotérmicos horários nos núcleos de desertificação do estado da Paraíba, Brasil
Authors: Almeida Hermes Alves de , Galvani Emerson
Published: April 2024

Embora a desertificação seja um processo de degradação de terras, não há consenso científico, se as causas sejam ocasionadas pelo clima, por ações antrópicas e/ou resulte de uma interação entre si. Diante disto, procurou-se estabelecer os principais indicadores higrotérmicos do ar atmosférico, nos núcleos de desertificação do Cariri e Seridó da Paraíba, localizados nas regiões geográficas intermediárias de Campina Grande e Patos, sendo essas determinações os objetivos principais. Utilizando-se dados horários de temperatura do ar e umidade relativa, coletados nas estações meteorológicas automáticas, instaladas em Cabaceiras (Cariri) e Santa Luzia (Seridó), entre 01.01.2013 e 31.12.2020, foram determinadas as pressões parcial e de saturação, o déficit de pressão, a temperatura do ponto de orvalho e as umidades absoluta e de saturação. Com as séries climatológicas mensais de chuvas, foram estabelecidos os regimes pluviais. Os principais resultados indicaram que as características higrotérmicas horárias, dos referidos núcleos, diferem entre si. O núcleo de desertificação do Cariri é mais frio e mais úmido do que o do Seridó. A capacidade de retenção de vapor d’água é função direta da temperatura do ar e a umidade relativa ocorre de forma inversa. As ações antrópicas adversas contribuem para aumentar a degradação ambiental, embora os elevados indicadores térmicos, os baixos teores de umidades do ar atmosférico e a irregularidade no regime pluvial contribuam para acelerar o processo de desertificação. Como a temperatura do ar é o principal indicador higrotérmico, ela pode ser usada para estimar os demais indicadores termodinâmicos, com elevada precisão.
Estimativa do uso sazonal da irrigação por pivô central na cultura do milho em nível de oito bacias hidrográficas no Rio Grande do Sul
Authors: Villa Bruna de , Petry Mirta Teresinha , Martins Juliano Dalcin , Melo Giane Lavarda , Tokura Luciene Kazue , Ferrazza Cassio Miguel , Santos Maicon Sérgio Nascimento dos , Silva Clarissa Moraes da
Published: April 2024

A preocupação com o uso dos recursos hídricos (indústrias, uso doméstico e agricultura), tem motivado o uso de ferramentas de modelagens, que visam melhorar a gestão da água na agricultura. Assim, o objetivo deste estudo foi (i) estimar o requerimento hídrico (CWR) e a necessidade líquida de irrigação suplementar (NIR) no milho em nível de Bacia Hidrográfica (BH) no RS, usando o modelo SIMDualKc, e (ii) quantificar o volume bruto de água a ser retirado de recursos hídricos para atender a área irrigada nas diferentes BH no ciclo do milho. As simulações para a demanda hídrica da cultura foram realizadas para as oito bacias hidrográficas que concentram os pivôs, no estado do RS: Alto Jacuí, Apauê, Butuí, Ijuí, Passo Fundo, Piratini, Turvo e Várzea. Os dados de entrada do programa foram: características físico-hídricas do solo, dados da cultura; presença de cobertura do solo (mulch), da irrigação, ascensão capilar e escoamento superficial, entre 2010 e 2022. Os maiores consumos de água para irrigação se deram para as bacias hidrográficas de Alto Jacuí, Ijuí e Piratini. A bacia hidrográfica de Piratini ocupou o maior percentual de vazão, com 7,3% e 7,2%, para as semeaduras de 05/10 e 20/10, respectivamente. A simulação do balanço hídrico se mostrou importante para a quantificação da lâmina de água durante o ciclo de desenvolvimento do milho e posterior quantificação da vazão necessária em nível de bacias hidrográficas. O balanço hídrico sequencial diário facilitou o acesso a conhecimentos sobre as irrigações para agricultores, alunos, pesquisadores e demais usuários.
Aplicações da teriparatida sobre osteonecrose dos maxilares associada ao uso de bifosfanatos na implantodontia: uma revisão integrativa
Authors: Leitão Karoline Bittencourt Mendes , Nemetala Renata Marques da Silva , Bugarin Júnior João Geraldo
Published: April 2024

A odontologia constantemente preocupa-se com a qualidade óssea dos seus pacientes. Tal variável determinará o sucesso clínico de intervenções cirúrgicas, instalação de implantes e manutenção de dentes na cavidade bucal. Nessa perspectiva, pacientes com osteoporose são uma população que exige maior atenção. O tratamento atual da osteoporose acontece por meio do uso de bifosfonatos, todavia, seu uso está associado a quadros de osteonecrose dos maxilares. A teriparatida é um medicamento que passou a ser estudado para controle do metabolismo ósseo e demonstra potencial para uso odontológico. Diante disso, o presente estudo buscou validar o uso da teriparatida em contexto de osteonecrose dos maxilares associada a bifosfanatos e sua influência na Implantodontia. A teriparatida é um fármaco recombinante do hormônio da paratireóide e possui efeitos anabólicos no metabolismo ósseo, estimulando a diferenciação de osteoblastos e aumentando a atividade dos osteócitos. Dessa forma, o anabólico ósseo pode ser pensado para recuperação de quadros clínicos com grandes perdas de tecido mineralizado, auxiliando no processo de reabilitação do paciente. Na odontologia, o uso da teriparatida está associado com maiores e melhores níveis de osseointegração de implantes e efeitos positivos nos tecidos periodontais. Seu uso pode, ainda, ser potencializado pela suplementação de vitamina D e cálcio. Diante dos presentes achados, o uso da teriparatida pode ser uma alternativa para o controle da osteoporose frente aos bifosfonatos no período em que se planeja realizar a instalação de implantes dentários ou cirurgias ósseas na região de cabeça e pescoço, diminuindo os riscos de necrose da região. Todavia, é importante enfatizar que os estudos clínicos ainda carecem de desenhos experimentais mais robustos e com amostras maiores para que a teriparatida seja, de fato, uma escolha válida e segura para os pacientes.
О задачах экстремума и оценках управляющей функции для параболичеcкого уравнения
Authors: Astashova Irina Viktorovna , Lashin Dmitry Aleksandrovich , Filinovskii Aleksei Vladislavovich
Published: April 2024

Рассматривается экстремальная задача, связанная с математической моделью управления температурой, основанная на одномерном несамосопряженном параболическом уравнении общего вида. Определяя оптимальное управление как минимизирующую функцию весового квадратичного функционала, мы доказываем существование решения задачи о повторном минимуме - по управляющим и весовым функциям. Получены также оценки сверху нормы управляющей функции через значение функционала качества, используемые для доказательства существования минимизирующей функции на неограниченных множествах управлений.
Improving Preschool Parenting Practice for a More Equitable Parent Engagement: Findings from a Resource-exhausted City in China
Authors: Li Na , Li Yu , Zhang Hairui , Liu Baotong , Yan Wenfan
Published: April 2024

How to improve preschool parenting practice for a more equitable parent engagement is still a challenge for families and schools, especially for parents in undesirable social and economic environment. We approach this challenge through a case study of H city,  one of the third batch of resource-exhausted cities, in Heilongjiang Province, China. Through analysis of 765 parents’ responses, we find that parents, in such circumstance, appear overprotective of their children. Children of authoritarian parenting have lower psychological bearing capacity, weaker sense of responsibility and self-control. Considerable number of preschoolers have a serious problem of procrastination.
The Internal Mechanism of Reduction of Construction Land driving Rural Industrial Revitalization--Based on dual case studies
Authors: Ma Yao
Published: April 2024

Rural characteristic industry is an important segment of industrial revitalization in the county. Based on the land system reform, this paper takes two national project areas for rural revitalization as the research object, and adopts the vertical exploratory double-case study method to comprehensively present the main paths and common mechanisms in the process of industrial revitalization in the two project areas, and the study finds that: 1. The reduction of construction land has a driving role in the revitalization of rural industries. 2. In the industrial revitalization mode, the reduction policy constructs a new rural framework of "government + enterprise + village community + farmers", which greatly improves the vitality of the collective economy. 3. By comparing the two cases, the core of multisector synergy in industrial revitalization is the distribution of the power structure, and it is only through the implementation of the bottom power and handing over the initiative and beneficiary to the farmers that the effective articulation of the interests of the multiple loops can be achieved. Therefore, the institution-building of reduction should be further improved to realize the inter- and intra-regional revenue feedback mechanism of the reduction target, so as to realize the sustainable income and value-added of the industry in the long term.
Application of Video Teaching in the English Classes of the Military Academy
Authors: Xing Yu , Lu Yurong
Published: April 2024

A stronger capacity in English information acquisition and cross-cultural communication is requisite for naval officers in new times. This paper analyzes the difficulties the midshipmen have met in listening comprehension and speaking. It also expatiated on the advantages of English teaching through videos basing on psychological theories. In this paper, it summarizes the potential problems of the application of this teaching method. At last, it puts forward four suggestions on the effective use of English teaching through videos.
This Paper Discusses the Current Situation and Training Strategies of Primary School Students' Computational Thinking Ability
Authors: Zhu Haiduan , Deng Peng
Published: April 2024

Computational thinking is the key to cultivating students' core literacy in the information age, and it is also an important entry point to promote the reform of information technology curriculum. Acquiring computational thinking becomes a foundation, and it should be a must-have for everyone, just like reading, writing, and arithmetic. As computational thinking has been widely concerned by the international computer and education circles, the cultivation of computational thinking has become more and more important. At the same time, the cultivation of computational thinking is a long-term and systematic process, so it is necessary to carry out research on the cultivation of computational thinking from the primary school stage. Based on this importance, this paper analyzes the current situation of computational thinking cultivation of primary school students and discusses how to cultivate computational thinking of primary school students based on the current research situation.
The Impact of Digital Inclusive Finance on Local Economic Growth
Authors: Chen Ruohan
Published: April 2024

Under the background of the new era, digital inclusive finance has burst into new vitality and become an important driver of local economic growth. This paper empirically examines the impact of digital inclusive finance on local economic growth using 31 provincial panel data from 2013-2022. A two-way fixed effects model is built and the results indicate that digital inclusive finance significantly promotes local economic growth. After the robustness analysis, the conclusion is still valid.The analysis of heterogeneity reveals that digital financial inclusion has a significantly positive impact on per capita GDP in northeast China, while its impact on western and eastern China is relatively weak. In the eastern region, digital inclusive finance has the strongest positive effect on per capita disposable income, while in the central region, it is relatively weak. This paper proposes promoting the development of digital inclusive finance, and differentiated countermeasures should be implemented in various regions.
Research on the Influence Mechanism of E-commerce Virtual Hosts on Consumers' Purchase Intention--Based on perceived value theory
Authors: Peng Jingwen
Published: April 2024

With the advancement of AI technology, virtual anchors have emerged as a new form of e-commerce live broadcasting. This study, based on perceived value theory, investigates the factors influencing consumers' purchase intent in virtual anchor live broadcasts. Through a questionnaire survey with 307 responses and SPSS analysis, it was found that consumers' attitudes toward virtual anchors positively impact purchase intent directly or through perceived benefits. The influence of virtual anchors' language proficiency on purchase intent is fully mediated by perceived benefits. Moreover, the alignment of virtual anchors with product types and their professional competence moderate this process.
Digital Government, New Quality Productive Forces and High-quality Development of State-owned Enterprises: Evidence from Listed Companies in China
Authors: Yao Liyu
Published: April 2024

The establishment of digital government aligns closely with enterprises' need for open and transparent data, providing new opportunities for technological revolution and industrial transformation of state-owned enterprises. This research confirms the positive impact of digital government on the high-quality development of state-owned enterprises, based on reliable data from A-share listed state-owned enterprises. And the more advanced the level of high-quality productive forces is, the more prominent their link becomes. The depletion of major shareholders, investment in enterprise innovation, and the business environment act as intermediaries. The study suggests that state-owned enterprises should leverage information transparency opportunities through digital government initiatives. This entails improving corporate governance practices and utilizing information strengths to increase investments in innovative research, to promote high-quality development.
Research on reservoir dispatching system based on digital technology
Authors: Guo Jianhong
Published: April 2024

With the development of digital technology, the automation and intelligence level of reservoir dispatching systems need to be improved urgently to cope with the challenges brought by complex hydrological conditions and climate change. This study designed a complete reservoir dispatching system based on advanced monitoring and communication technology. The system integrates ultrasonic/radar water level gauges, rainfall gauges and other sensors, and realizes real-time data transmission through GPRS/CDMA/3G/4G networks to ensure the accuracy and timeliness of information. By establishing accurate hydrological models and optimization algorithms, dynamic monitoring and prediction of reservoir water levels and flows are achieved, and dispatching strategies are optimized to achieve efficient coordination of multiple goals such as flood control, irrigation, water supply, and power generation. It is expected that the implementation of this system will significantly improve water resource management efficiency and emergency response capabilities.
Reinforcement and effect evaluation of a middle school in Japan
Authors: Li Liang , Ohkubo Takaaki , Deng Guorui , Cao Jianran , Xu Jinjin
Published: April 2024

In recent years, large earthquakes have occurred around the world frequently. In Japan, one of the world’s most earthquake-prone countries, it is more important to ensure the seismic performance of buildings. School buildings are the refuge after the disaster, so it has an important meaning to improve the safety and seismic performance of existing school buildings. Most of the school buildings in Japan were built before the implementation of a new seismic standard. Reinforcement is the most important method to ensure safety and improve seismic performance. Based on the reinforcement and reconstruction project of a middle school in Japan, this study introduces the reinforcement design method based on the overall reinforcement concept. Because of the lack of effective methods for evaluating the effect of reinforcement, a micro-tremor observation experiment was carried out by using the wireless acceleration sensor vibration system before and after the seismic reinforcement of the school building. The effects can be evaluated by comparing and analyzing the changes in the acceleration response spectrum, natural period, vibration mode and other characteristics before and after reinforcement. Based on the overall reinforcement concept, it is more reasonable to fit the structural characteristics of the building. The application of a wireless vibration measurement system for evaluating the effect of reinforcement is feasible, it can provide scientific reference for reinforcement design and construction.
Advances in Research on the Analysis and Detection of Chemical Components in Heated Tobacco Aerosols
Authors: Cai Jieyun , Gu Jianlong , Long Jie , Wang Chunqiong , Liu Yuchen , Luo Yanbo
Published: April 2024

Compared with traditional cigarettes, heated cigarettes have higher advantages in tar reduction, harm reduction, environmental impact and safety. This article provides an overview of the structure of heated tobacco products and the main chemical components in their aerosols. It also elaborates on methods for detecting these chemical components in aerosols. Furthermore, it discusses potential issues and offers suggestions for quality control in heated tobacco product research. The aim is to provide valuable insights and references for the continued research and development of heated tobacco products.
Research and Optimization of Tubular Column Joint Identification Technology for Intelligent Drilling Platforms
Authors: Niu Ke , Peng Bin , Yang Xiaoliang
Published: April 2024

An improved target detection algorithm based on YOLOv5s is proposed to be applied to identify and localize tubular column joints in The improved SC-YOLOv5s model is obtained by combining SPPF, CBAM and the improved multi-scale feature fusion network BiFPN. The improved SC-YOLOv5s model is obtained by combining SPPF, CBAM and the improved multi-scale feature fusion network BiFPN. The SPPF structure introduces spatial pyramid pooling in the network, which can effectively capture the features of the target at different scales and improve detection precision. different scales and improve the detection precision and recall of the target, while the CBAM attention mechanism can adaptively learn the target's spatial and channel feature relationships. s spatial and channel feature relationships, improving the model's ability to distinguish between targets and anti-interference ability The improved multi-scale feature fusion network BiFPN combines Bottom-up and Top-down feature transfer mechanisms, which can better fuse feature information at different levels, making the model's ability to distinguish between targets and anti-interference ability. information at different levels, making the model better adapted to detection tasks in various complex environments. The experimental results show that the improved algorithm achieves the following results that the improved algorithm achieves significant performance improvement in the pipe-column joint detection task, with a mAP value of 99.44%, a frame rate of 136 FPS, and an accuracy of 98.4%, which is 6.6% higher than the original model. The algorithm also improves sensing capability, accuracy and robustness, and outperforms the original model. The algorithm also improves sensing capability, accuracy and robustness, and outperforms other mainstream models in terms of precision. This provides a reference for automatic processing of tubular columns in intelligent oil rigs.
Research on Model Optimization Method Based on Differential Evolution
Authors: Wang Kai , Hu Zhihua
Published: April 2024

Nowadays, industrial upgrading and transformation continues to deepen, based on the deep neural network model of the integration of the advantages of the application is more and more prominent. Rolling bearings can not be ignored as the existence of mechanical equipment. A convolutional neural network parameter optimization algorithm based on differential evolution is proposed. The loss function of the fault diagnosis model is taken as the objective function of the optimization algorithm, and the optimization model is mainly aimed at optimizing the training parameters such as the number of convolutional kernels, convolutional kernel size, and step size of the 3D convolutional neural network, and the optimal parameter setting values are derived. Compared with the pre-optimization fault diagnostic model, the prediction accuracy of the fault diagnostic model is improved by 0.35%, and the loss rate is decreased by 1.13%, and the obtained fault diagnostic model has higher diagnostic accuracy.
Research on the WTA problem in UAV formation air-to-ground attack
Authors: Jiang Haibo , Pan Bo , Luo Senze
Published: April 2024

In view of the process of UAV formation air-to-ground attack, the characteristics and new requirements of UAV combat were deeply studied and analyzed. A dynamic fire assignment model was established, which mainly included the target assignment, the state transfer of target and fire channel in the dynamic fire assignment model, and the suitability test method was deeply analyzed. Considering the constraints of attack, resource and destruction probability, an optimization algorithm for solving fire allocation was proposed. Finally, the improved particle swarm optimization algorithm is used to solve the target assignment model and the feasibility of the model and algorithm is verified by an actual case.
Joint optimization of repair and ordering of centrifugal compressor key performance spare parts based on gas supply reliability
Authors: Wang Xiao , Huang Yixiang , Peng Shiliang , Su Huai , He Qian , Qiao Lingyun , Yang Zhaoming
Published: April 2024

The development of efficient and economical centrifugal compressor key performance spare parts ordering program is very important to improve the maintenance management efficiency of the equipment and reduce costs, this paper proposes a centrifugal compressor based on the reliability of gas supply key performance spare parts maintenance and ordering joint optimization. First of all, based on the average failure rate of compressor unit and the average time between failures to establish unit reliability mathematical model; secondly, based on the unit reliability mathematical model, the establishment of the compressor key components unit preventive maintenance cost model; finally, based on the ordering of spare parts at various moments of the cost function, the working time of the components to establish the compressor key performance parts ordering optimization model, the use of genetic algorithms to get the optimal ordering of the key performance of the spare parts time and optimal replacement of the components time.
The Synergistic Effect of Panax Notoginseng Saponins and Nicotinamide Mononucleotides on Anticoagulant
Authors: Peng Jia , Hao Xiaohui , Chen Yonggen , Jin Qing
Published: April 2024

Panax notoginseng is a traditional Chinese herbal medicine with rich medicinal value and health care efficacy. Its main active ingredient, panax notoginseng saponins, has pharmacological effects on improving blood circulation and inhibiting platelet aggregation. Nicotinamide mononucleotide has the effect of reducing collagen deposition in blood vessels and reducing vascular obstruction. Method: Compare the thrombolytic efficiency of panax notoginseng saponins and nicotinamide mononucleotide alone and in combination, as well as their effect on prolonging coagulation time, using in vitro anticoagulant experiments and in vitro thrombolysis experiments, to explore the efficacy of panax notoginseng saponins and nicotinamide mononucleotide in combination. The results showed that when combined with a compound drug concentration ratio of 3:1 (PNS: NMN), the coagulation time was 1.2 times that of the PNS liposome single dose group and 1.7 times that of the NMN single dose group. And the optimal dosage for combination therapy is only 50% of the single dose. Conclusion: The combination of PNS and NMN has significant synergistic advantages and saves the dosage, which provides a new drug combination for the development of safe and low-toxic anticoagulant and thrombolytic drugs. It provides a reliable and detailed theoretical basis for the combination of panax notoginseng saponins and nicotinamide mononucleotide.
Interpretable Machine Learning Strategies for Accurate Prediction of Thermal Conductivity in Polymeric Systems
Authors: Lin Chunbo , Zheng Han
Published: April 2024

Polymers, integral to advancements in high-tech fields, necessitate the study of their thermal conductivity (TC) to enhance material attributes and energy efficiency. The TC of polymers obtained by molecular dynamics (MD) calculations and experimental measurements is slow, and it is difficult to screen polymers with specific TC in a wide range. Existing machine learning (ML) techniques for determining polymer TC suffer from the problems of too large feature space and cannot guarantee very high accuracy. In this work, we leverage TCs from accessible datasets to decode the Simplified Molecular Input Line Entry System (SMILES) of polymers into ten features of distinct physical significance. A novel evaluation model for polymer TC is formulated, employing four ML strategies. The Gradient Boosting Decision Tree (GBDT)-based model, a focal point of our design, achieved a prediction accuracy of R2=0.88 on a dataset containing 400 polymers. Furthermore, we used an interpretable ML approach to discover the significant contribution of quantitative estimate of drug-likeness and number of rotatable bonds features to TC, and analyzed the physical mechanisms involved. The ML method we developed provides a new idea for physical modeling of polymers, which is expected to be generalized and applied widely in constructing polymers with specific TCs and predicting all other properties of polymers.
Research progress of transition metals Cu, Fe and Ni as electrode materials for electrocatalytic nitrate reduction to ammonia
Authors: Shang SiHan
Published: April 2024

Nitrate is a common pollutant in surface water and groundwater. Electrocatalytic nitrate reduction method is an electrochemical reduction reaction of nitrate at the cathode by impressed current, and the reduced ammonia generated by the reaction is an important chemical raw material. The main step of this process is the selection of cathode electrocatalytic materials. In this paper, the mechanism of electrocatalytic nitrate reduction to ammonia production is briefly explained, then the research situation of transition metals Cu, Fe and Ni as electrode materials for electrocatalytic nitrate reduction to ammonia production at home and abroad is reviewed, and finally the future direction of electrocatalytic nitrate reduction to ammonia production is summarized.
High-Response, Self-Driving Infrared Photodetection Based on WS2-Graphene Heterostructure and Metal-Oxide-Semiconductor Field Effect Transistor Structure
Authors: Wang Fanxu
Published: April 2024

Two-dimensional materials have garnered increasing attention owing to their exceptional photoelectric properties. Among these materials, WS2 is characterized by its ability to adjust the band gap by altering the number of material layers and to control its Fermi level through external gate voltage. Graphene exhibits an extensive absorption spectrum ranging from ultraviolet to terahertz waves, alongside high carrier mobility and rapid light response. In this study, we made a photodetector based on WS2-graphene heterostructure and metal-oxide-semiconductor field effect transistor structure. Leveraging the van der Waals heterojunction formed by these two materials, we aim to amalgamate their respective advantages. Moreover, the Fermi level of the material is modulated via gate voltage manipulation. Subsequently, the sample was tested using a laser with a wavelength of 830 nm. Our research reveal its outstanding photoresponsivity, which holds significant implications for near-infrared band photoelectric detection. This research not only advances the realm of photoelectric detection but also introduces a novel option for near-infrared photoelectric sensing applications.
A MobileNetV2 model of transfer learning is employed for remote sensing image classification
Authors: Cao Leyu
Published: April 2024

Remote sensing image classification is an important and complicated problem in deep learning field. In order to achieve better classification effect, predecessors have proposed different kinds of models. A transfer learning-based MobileNetV2 model is suggested in this paper. First, we take UC-Merced dataset as input and introduce lightweight network MobileNetV2 for scene identification. Secondly, we combined the transfer learning training method and pre-trained the MobileNetV2 model to realize the high-performance classification of deeper remote sensing images. The UC- Merced dataset was classified with a model that achieved 91.43% accuracy,91.00% kappa index, and 91.50% F1-score. These results demonstrate the model's impressive performance in remote sensing image classification and its potential for practical scene identification applications.
Study on Adsorption Properties of New Sodium Alginate and Chitosan Quaternary Ammonium Salt for Heavy Metal Ions
Authors: Li Chonghua
Published: April 2024

Up against accelerating industrialization, heavy metal pollution has been a global environmental problem. Hence, it is urgent to develop high-efficiency, low-cost and environmentally friendly heavy metal adsorption materials. This study aims to explore sodium alginate and chitosan quaternary ammonium salt (Alg/HTACC), a new biosorption material, and evaluate its adsorbability for heavy metal ions. Alg/HTACC is prepared by solution mixing, with its structure and morphology characterized by Fourier transform infrared spectroscopy and X-ray diffraction. Alg/HTACC is porous in structure, which is beneficial to improving the capture capacity of metal ions. As for the study of adsorption properties, the adsorption behavior of Alg/HTACC for many heavy metal ions such as Cu2+, Cd2+ and Pb2+ is systematically investigated. According to experimental results, Alg/HTACC has a good adsorption effect on these metal ions. The regeneration ability and recycling potential evaluated by desorption experiments on saturated Alg/Alg/HTACC still maintain high adsorption efficiency, which proves its good usability.
Design of Portable Multi-point Temperature Control Cabinet Based on Single Chip Microcomputer
Authors: Zhang Haoming
Published: April 2024

Being widely used in various fields, temperature control cabinet has increasingly higher design requirements. However, single-point temperature measurement is commonly applied in temperature control cabinets now with relatively simple temperature detection, so the temperature measurement results are easily affected by environmental temperature. To meet the demand for precision temperature measurement, this paper not only introduces an 8-bit STC89C52 single-chip microcomputer with low power consumption and high performance as the core, but also adopts multi-point control temperature measurement mode. Bluetooth technology is combined with multi-relay self-switching to realize the overall temperature intelligent control of the temperature control cabinet with 0 to 99 ℃ as the temperature measurement range,  0.125 ℃ as the accuracy, and 100 ms as the refresh duration. The multi-point temperature measurement and control system designed independently in this paper features a simple structure, low cost, high precision, high stability, operability and portability, which can effectively meet the needs of precision temperature measurement of temperature control cabinets.
Machine Learning-Based Non-Orthogonal Frequency Division Multiplexing for Data Overlay Transmission and Reception
Authors: Zhao Zhidong
Published: April 2024

The rapid evolution of mobile communication technologies like 5G and the anticipated emergence of 6G have necessitated enhanced resource utilization and reception efficiency in wireless communication systems. One of the challenges faced in existing systems is the resource competition arising from the overlapped transmission of pilot frequency and data. This paper addresses this issue by proposing a deep learning-based solution that leverages machine learning techniques to decode transmitted data efficiently. Through a combination of non-orthogonal pilot-frequency and data-overlapped transmission schemes, the proposed solution effectively mitigates interference problems, leading to improved resource utilization and reception performance. Experimental and simulation analyses validate the efficacy and feasibility of the proposed approach, showcasing a decoding accuracy of up to 93% under specific conditions.
Numerical Analysis and Reinforcement Management of Slopes
Authors: Chen Zhiqiang
Published: April 2024

In order to manage a roadside landslide, a qualitative and quantitative stability analysis of the main landslide face was carried out based on the ground investigation data; a numerical analysis model was constructed to analyze the stress field, displacement field and stability coefficient change of the main landslide face, which verified the reliability of the results from qualitative and quantitative analyses; a numerical calculation was carried out to analyze the stress field calculation and stability coefficient change of the formulated "Anchor + Drainage" reinforcement scheme; the feasibility and reliability of the reinforcement scheme were also verified. Numerical calculations were used to calculate the stress field, displacement field and stability coefficient changes of the proposed "anchor + cut-off drainage" reinforcement scheme, which verified the feasibility and reliability of the reinforcement scheme. The results show that: (1) the qualitative and quantitative analysis results are relatively reliable, and the stability coefficient of the slope before reinforcement does not meet the requirements of the engineering specification, which indicates that the slope is unstable and there is a risk of deformation damage. (2) The average stress and displacement changes of the slope after reinforcement are significantly reduced, and the average stress and displacement of the anchors are increased, indicating that the reinforcement program effectively prevents the deformation and sliding of the slope. (3) The stability coefficient of the slope after reinforcement is improved by 25.9% relative to that before reinforcement, indicating that the reinforcement scheme is feasible.
The screen panel material for the future
Authors: Wu Dada
Published: April 2024

Nowadays, the screen panel material used on TV, computers and smart phones are various and own different features. But in the future, will there be one material becoming the only choice under the development? In this research, the researcher shows the the current application condition of two main materials and give the forecast of the future.
Classification of ECG Signals Based on Hilbert-Huang Transform and 1D Convolution Neural Network
Authors: Tang Tianyao
Published: April 2024

Arrhythmia is a common phenomenon in cardiovascular diseases and its accurate diagnosis typically relies on a thorough analysis of electrocardiogram (ECG). Therefore, accurate identification and classification of ECG signals play a crucial role in the effective treatment of cardiac diseases. In this study, we propose a deep learning model based on Hilbert-Huang Transform (HHT) and one-dimensional convolutional neural network (1D-CNN), aiming to enhance the accuracy of ECG signal classification. Specifically, we first perform time-frequency analysis and feature extraction of the signal using the Hilbert-Huang Transform, after which we further extract features and classify the signal using 1D Convolutional Neural Network. The experimental results show that the model proposed in this paper performs well in classifying four types of ECG signals, with average classification accuracies of 97.73%, 99.16%, 99.50%, and 99.88%, respectively. This not only proves the effectiveness of our proposed method but also provides important technical support for the diagnosis and treatment of cardiovascular diseases, which has far-reaching clinical application value.
Intelligent Control System of Vacuum Oil Filter Based on PLC
Authors: Hu Man , Liu Yang , Zhao Wentian , Bai Jiahang , Liu Yuhao , Zhang Naiwen , Wang Ziyuan , Li Jie , Gao Yuan , Lv Jingzhi
Published: April 2024

This paper proposed an intelligent control system of vacuum oil filter based on PLC. The system aims to enhance the automatic control and remote monitoring capabilities of Vacuum Oil Filter. With the S7-200 PLC serving as the control center, it incorporates state-sensing and electronic control components into the critical areas of the vacuum oil purifier. This allows for precise control of the degassing hood's liquid level, detection of insulating oil leaks, and automatic control of the condensation tank. Consequently, the system enables unmanned filtering of insulating oil, demonstrating its practicality.
Point annotations for nucleus segmentation in histopathology images via envelope enhancement network
Authors: Hong Han , Qu Aiping , Xue Tongqing
Published: April 2024

Nucleus segmentation in histopathology images holds great clinical value for disease analysis. With the advancements in deep learning and continuous iteration of devices, existing nucleus segmentation algorithms can achieve satisfactory performance. However, these fully supervised nucleus segmentation methods require pixel-level annotation information, which requires a significant amount of time and effort. To ease this burden of annotations, we propose an envelope enhancement segmentation Network (EESNet) for weak supervison nucleus segmentation. Specifically, we first employ a Voronoi diagram and adaptive k-means clustering algorithm to derive two kinds of informative pixel-level pseudo labels,which are used for pixel-wise segmentation. Furthermore, we introduce an envelope enhancement network to provide rich envelope structure information to the segmentation network, which helps mitigate the problem of inaccurate boundary segmentation caused by point annotations. Finally, our network is verified on a mainstream nucleus segmentation datasets (consep) and achieves satisfactory performance.
Carbon-Based-Polypyrrole Composite Nanowires for Portable and Remote Trace Sweat Lactate Detection
Authors: Li Yi , Zhai Zhiqiang , Du Xiaosong , Liao Rui , Wang Yang , Yang Yajie , Long Yin
Published: April 2024

The prompt and remote detection of biomarkers is crucial in personalized medicine and health protection, presenting a significant challenge for current devices. In this context, we introduce a highly sensitive method for remotely analyzing sweat lactate, utilizing carbon nanotube-composite polypyrene with the capability of transmitting data. The sensing mechanism is attributed to the charge transfer of polypyrene during anion doping, enabling the selective detection of lactate anions at specific potentials, while maintaining inertness to neutral and cationic substances found in human sweat. Timed-current studies revealed robust sensing properties for lactate, demonstrating a sensitivity of up to 1.8 mA·mM-1cm-2 and a detection limit of 25 μM. Additionally, CNT-polypyrene nanowires exhibited outstanding selectivity for lactate. This breakthrough overcomes the limitations of traditional electrochemical sensors, offering a direction and theoretical foundation for designing wearable sensors to address various stimulus detection needs.
UNA APROXIMACIÓN A LA TRADICIÓN ARTÚRICA A TRAVÉS DE MYRDDIN Y EL CÓMIC
Authors: Umpiérrez Alonso Roberto
Published: April 2024

El objetivo del trabajo es analizar la aparición de Merlín en un cómic español y comparar cómo se situaba respecto a la tradición literaria hispánica. Para ello, utilizamos un breve corpus de obras donde aparece el mago para tener una visión diacrónica de su evolución, entre las que se incluían materiales medievales y tan distintos como la ópera en el siglo pasado. Pudimos observar los vasos comunicantes que partían del medio del cómic hasta obras del siglo XII, y discutimos la prevalencia de ellos en una reelaboración del mago adecuada para la sensibilidad contemporánea.
CUANDO EL SUBYUGADO SE REBELA: LIBERTAD Y SORORIDAD EN LA OBRA DE MERCEDES PINTO
Authors: Bellido Castro Antonio José
Published: April 2024

El propósito de este artículo es examinar la evolución del subyugado en la obra de Mercedes Pinto, y cómo se rebeló este ante la figura masculina. Para nuestro trabajo hemos recurrido a las dos principales novelas de la autora canaria, Él y Ella, así como a El divorcio como medida higiénica, texto que confirma el inicio de la labor divulgadora feminista de Mercedes Pinto. Los resultados arrojan la construcción de un relato a partir de una situación de maltrato, en donde el distanciamiento con el hombre supone el inicio del empoderamiento y liberación de la protagonista, quien apela a su experiencia vital a lo largo de todos sus textos. El caso de Mercedes Pinto supone un rara avis dentro de la sociedad española de inicios de siglo xx, pues no solo se negó a cumplir con los dogmas sociales, sino que dedicó buena parte de su vida a la lucha por la igualdad entre sexos.
REGIAS DEL DRAG, EL IMPERIO DE ILUSIONES TRANSGRESOR DEL NORTE DE MÉXICO
Authors: Garcia Saavedra Francisco Daniel
Published: April 2024

El siguiente articulo presenta la una parte de la escena drag de Monterey, Nuevo León, México; esta escena es muy amplia a nivel local, nacional e internacional. Sin embargo para fines específicos del artículo se presenta un análisis semiótico y cultural de la competición drag local titulada: Regias del Drag. Dicha investigación busca presentar el impacto que esta competencia drag aporta a la cultura regiomontana y su proceso deconstructivo en miras de una sociedad más tolerante y menos clasista, por mencionar algunas cualidades que las estadísticas mencionan de los ciudadanos de este estado. El análisis de este artículo se basa en una etnografía y un análisis de corte vanguardista, pero con una metodología cualitativa que nos ayude a comprender ciertos signos y símbolos que empoderan a Regias del Drag como un icónico acontecimiento de la cultura Pop regiomontana, pero, al mismo tiempo, cómo esta escena drag no solo busca el sentimiento de estandarizar lo mainstream, sino visibilizar luchas y reclamos a una sociedad cerrada a la empatía, la diversidad y el cambio. Cabe destacar que los resultados de este trabajo son mostrar un ejemplo sobre la propuesta drag en un estado homofóbico que responde a una cultura del miedo y la discriminación; sin embargo, la teoría de Lotman ayudará a comprender cómo esta semiosfera de Regias del Drag crea un paradigma en la cultura regiomontana en la cual se busca la aceptación y el respeto por ser diversos; en conclusión, este articulo nos muestra cómo el drag puede convertirse en la actualidad en una especie de combatiente que ayude a visibilizar las luchas por encontrar espacios seguros, amigables, artísticos y, al mismo tiempo, critico-político para despertar conciencias.
Penitentiary risk factors for suicide by inmates
Authors: Muskała Maciej
Published: April 2024

Although suicide in prisons is considered as relatively rare form of self-injurious behaviour, which is illustrated by statistics, their rates are higher than those in the general population.Thus, as emphasised in the literature, there is something specific about the prison environment or the inmate himself that can be considered a risk factor for suicidal behaviour. Research on suicide in correctional facilities, is important and relevant for a number of reasons. For they attempt to identify these specific factors, providing important information about the phenomenon itself, the conditions and causes, but also about ways of preventing it. In this text, on the basis of data obtained from CZSW, an attempt was made to identify selected risk factors characteristic of the environment of penitentiary isolation, which may be helpful in constructing preventive measures.
Product quality and profitability at Masisa
Authors: Lopez Salazar Geraldine Clarita , Manuelo Medina Miguel Francis , Meneses Claudio Brian Andreé , Zapana Ruiz Jorge Arturo
Published: April 2024

This research work was born to address the problem of the negative impact generated by defective products of Masisa Peru during 2022 on its profitability, given that according to the background researched, it is certain that these defective products generate higher operating costs and customer dissatisfaction, thus resulting in lower profits; The main objective of the study is to determine the influence that the quality of these products has on the company's profits, for which a qua entitative methodology with causal descriptive scope was used, and it was executed through the documentary content analysis technique of the historical records corresponding to the number of defective units per month, the number of good products, total sales, costs and profitability obtained during the period 2022 in order to establish the possible relationship between these variables. The results showed through a linear regression statistical model that defective products have a significant negative correlation that explains almost 80 % of the variability in profitability; however, a strong linear connection between melamine in good condition and sales or operating costs was not found, but this does not eliminate the possibility that in the long term there could be a strong relationship between defective products and costs, if the company continues with its current economic activity and does not implement corrective measures. Therefore, it was concluded that the poor quality represented by defective products causes economic losses by reducing profits, as well as this negative relationship generates an adverse effect on profits, causing economic losses, customer dissatisfaction, bad reputation, and even legal problems
Misleading advertising of the food industry as a strategy to incentivize consumption even in the face of the enactment of the junk food law
Authors: Noguera Cardona Joan Sebastián , Sánchez Castillo Verenice
Published: April 2024

Objective: to know the characteristics of misleading advertising in the food industry as a strategy to encourage consumption even with the enactment of the junk food law - 2021. Method: qualitative, descriptive research is carried out with a family from the municipality from Pitalito in the department of Huila, the instrument used was the interview. Results: the calorie intake of ultra-processed foods is an indicator of nutritional quality, these foods have a lower nutritional quality than fresh or minimally processed foods combined. Discussions: nutrition messages that appear on food labels deserve special attention, due to misinformation and misleading advertising. Junk Food Project 167 of 2019 is aimed at improving this information. Conclusions: It is necessary for the food industry to guarantee the full protection and prevalence of consumer rights. Various sectors of society and the government itself have mobilized in favor of the drafting of more restrictive legislation in relation to the advertising of unhealthy foods and beverages directed at children