bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of Multicultural Events Writing Teaching Materials with A Contextual Approach
Authors: Yanti Ritonga Eka
Published: April 2024

This research is motivated by students who lack creative thinking in solving problems in the material, students are required to understand the material, to develop students' thinking skills, researchers develop teaching materials based on teaching modules. This study aims to develop student teaching materials with a contextual approach to class VI news material at SD Negeri 017 Tambusai Utara with valid and practical criteria. This research is a type of research and development (Research and Development) with the ADDIE model. The research location was carried out at SD Negeri 017 Tambusai Utara. The time of the research was carried out in February 2022 - March 2022. The research population was class VI students. The research sample consisted of 20 students. Research data collection techniques using a questionnaire. The results showed that the validation of material experts was 73 with a percentage of 92.40%, media experts were 74 with a percentage of 94.87%, and the results of the validation of linguists were 57 with a percentage of 95%. Assessment of the level of practicality of teaching materials is known from the teacher response questionnaire and student response questionnaire, the results of the teacher response questionnaire were 92% (very practical) and the student response questionnaire was 85.2% (very good). Thus, teaching materials for writing multicultural news events with a contextual approach to class VI news materials meet valid and practical criteria for use in learning.
Implementation of Role of Card Media in Increasing Students' Narrative Writing Skills in Class IV SD Muhammadiyah 20 Medan
Authors: Puspita T. Winda
Published: April 2024

The background of this research is the lack of motivation of students in writing stories, the absence of students' interest in learning to write, the absence of learning media, part of writing skills, namely writing essays. This study aims to apply the role card media in improving writing skills on narrative essay material for Indonesian language subjects in class IV SD Muhammadiyah 20 Medan. This study uses a type of PTK (Classroom Action Research). The location of this research was carried out at SD Muhammadiyah 20 Medan on Jalan Gedung Arca Gang Unity. The time of the research was held in February 2022. The subjects of this classroom action research were 23 students in grade IV at SD Muhammadiyah 20 Medan consisting of 9 boys and 14 girls. The object of this research is the application of role-card media in improving narrative essay writing skills in class IV SD Muhammadiyah 20 Medan. Data Collection Instrument using Observation. The data analysis technique used is Teacher Activity Analysis and Student Activity Analysis. The results of the study showed that the results of students' writing skills in the first cycle were 61% complete. The results of students' writing skills in cycle II which were completed were 87%. Analysis of Teacher Activities in cycle I as many as 80 with criteria B (Good). Teacher Activity Analysis In cycle II there were 90 with criteria A (Very Good). Analysis of Student Activities in the first cycle of students who completed as many as 12 students with a percentage of 52.2%. Analysis of students in the second cycle of students who completed as many as 20 students with a percentage of 86.9%.
Development of Media Puzzle Using Game Based Learning Approach to Improve Learning Outcomes Student Mathematics in Elementary School
Authors: Riskyka  , Lubis Renni Ramadhani , Yusnita Novi Cynthia
Published: April 2024

This study aims to develop media puzzles with a game based learning approach to improve students' mathematics learning outcomes in elementary schools. This research is a research and development (RnD) research, using a 4-D development model, including: 1) define, 2) design, 3) develop and 4) disseminate. The subjects of this study were 25 grade IV students consisting of 9 male students and 16 female students. The research object is puzzle media with a game based learning approach. Data collection techniques are observation, questionnaires, and tests. Based on the validation results of the puzzle media with the game based learning approach, it shows that: (1) the level of validity of the puzzle media with the game based learning approach gets an average score from material and media experts of 4.29 and 4, 17 with the categories "very valid" and "valid", (2) the level of effectiveness was tested through tests with the result that 80% of students could be said to be complete. This means that the puzzle media with a game-based learning approach is very effective in improving student learning outcomes, (3) the practical level of puzzle media with a game-based learning approach through teacher and student response questionnaires with an average score of 4.09 and 3.86 in the "practical" category. Based on these results, it can be concluded that puzzle media with a game based learning approach is feasible and effective for use in elementary schools. (3) the level of practicality of puzzle media with a game based learning approach through a teacher and student response questionnaire with an average score of 4.09 and 3.86 in the "practical" category. Based on these results, it can be concluded that puzzle media with a game based learning approach is feasible and effective for use in elementary schools. (3) the level of practicality of puzzle media with a game based learning approach through a teacher and student response questionnaire with an average score of 4.09 and 3.86 in the "practical" category. Based on these results, it can be concluded that puzzle media with a game based learning approach is feasible and effective for use in elementary schools.
Application of Video Media to Increase Student Motivation and Learning Autcomes in Flat Sided Space (Prism) Material in Class VIII SMPN 2 Pasir Limau Kapas Odd Semester of The 2021-2022 Academic Year
Authors: Siregar Erlina
Published: April 2024

This research aims to increase student motivation in the learning process of building flat-sided spaces about Building Flat-sided Spaces (Prisma) in class VIII students at SMP Negeri 2 Pasir Limau Kapas Semester I of the 2021/2022 academic year. This research was conducted because of student motivation in learning about flat-sided spatial construction about flat-sided spatial construction (Prisma) in class VIII students at SMP Negeri 2 Pasir Limau Kapas Semester I of the 2021/2022 academic year. still relatively lacking. The research subjects were 20 students in class VIII of SMP Negeri 2 Pasir Limau Kapas Semester I of the 2021/2022 academic year. The procedures for carrying out actions and implementation at the research location are divided into 2 cycles. Each cycle consists of four stages, namely: planning, acting, observing and reflecting and is carried out in 4 meetings. Data collection techniques use tests, observations, and documentation of learning activities. Analysis is carried out using techniques data analysis qualitative and technique analysis data qualitative. Results this research shows that the use of the PjBL learning model with video media in learning to build a flat-sided room, material on building a flat-sided room (Prism) capable improve skills students in making innovative works of prism nets in class VIII of SMP N 2 Pasir Limau Kapas Semester I Academic Year 2021/2022.
Application Method Learning Discovery Learning on Eye Lesson Economy in Increase Interest and Results Study Student
Authors: Aslamiah  , Harahap Fitriani
Published: April 2024

This research aims to increase student interest and learning outcomes. This type of research is classroom action research (PTK), with qualitative methods that explore a concept in a research problem. The research location was carried out at SMPN 5 Satu Muara Batang Girls Roof in December- January Research subjects used is a class VII student population of 21 students, with a research sample of 21 student. Student learning outcomes have improved by using the learning modelDiscovery Learning. With the results, the average student score was 84.7619 students who received the value above the KKM has exceeded 75% namely 19 students while students who got marks under KKM as much 2 students with presentations 20. The highest value is 100 and value Lowest 60.
Application of a Problem Based Learning (PBL) Model to Increase Motivation and Learning Outcomes of Class VII Students
Authors: Sisca Lusianna Sirait  , Arifin Yusna
Published: April 2024

Motivation is one of the factors that influences student success. A person will get the desired results in learning if within him there is a desire to learn. Motivation as the main factor in learning functions to create something fundamental to drive learning actions. In helping children improve their learning achievements, educators, especially teachers, must create a climate that stimulates children's creative thinking and skills at school. Factors that influence the learning process are internal factors originating from students or external factors originating from outside within students. Research findings show low student learning motivation, including the following: 1) Teachers' teaching methods and methods are monotonous and unpleasant, 2) Students' economic and socio-cultural background, 3) Most students from weak economic backgrounds do not have strong motivation to study and continue their education to a higher level. 4) Advances in technology and information, 5) Feeling inadequate in certain subjects, such as mathematics and English and 6) Students' personal problems with parents, friends and the surrounding environment. This research aims to determine the effect of learning motivation on student learning achievement in the Integrated Social Sciences subject, Economics class VII. Researchers as teachers apply the problem-based learning (PBL) model in an effort to increase the learning motivation of class VII students.
Development of Animated Videos Based on Character Educationon Learning Indonesian Language is in Low Class
Authors: Amelia Putri  , Lathifa Munawarah
Published: April 2024

This research explores the development of animated character education videos in Indonesian language learning in lower grades. Using development research methods, we design, produce and evaluate animated videos that are integrated with the Indonesian language curriculum. The results showed positive responses from teachers and students, showing the potential of animated videos to improve understanding of the material. These findings highlight the relevance of this innovation in improving the quality of Indonesian language learning in elementary schools. This study provides a basis for further development in integrating character education through animation media in the context of basic education.
Effectiveness of The Constructionist Approach on Economics Learning Achievement in Material Model Diagram Interaction of Economic Actors Class I
Authors: Ahmad Salami
Published: April 2024

Objective study This is 1) for know Performance Study student with Which No using a constructivism approach, 2) to determine students' learning achievements using PBL Model learning, 3) to find out what exists difference on performance Study between Which No use approach constructivism by using a constructivist approach to student economics material class I This research is a quantitative research with a post test only control design design. The place used for this research was SMP N 3 Muarasipongi One Roof . The research population was 15 students from class IX, using simple random sampling techniques. Data collection technique with written tests and documentation. Class I X as an experimental class. Technique analysis data Which used For analyze data in This research is an analysis t-test statistical data. Based on test score results. Student showing post-test average score the experimental class was 80.8 and the average post-test score for the control class was 67.6. For experimental class which means good, based on the analysis results it is known that the significance level is 5% for mark 68 (significant level of 5% or 1% for N = 70 and dk = 68, because dk = 68 does not listed in table distribution t so taken mark 60) Mark t table of et al = 60 is 2.02 And 5.756 which means t count > t table, Ho is rejected and Ha is accepted. So "there is a difference Which significant between approach constructivism And besides use approach constructivism on business economics learning achievement, material on the role of economic actors among students class.
EDUCAÇÃO DIFERENCIADA NAS ESCOLAS DO CAMPO: O CURRÍCULO E O PROJETO PEDAGÓGICO EM DEBATE
Authors: Miléo Irlanda do Socorro de Oliveira
Published: April 2024

The curricular organization and the pedagogical project are discussed as a strategy for the concreteness of a differentiated education in rural schools. We investigated how the rural school can organize its practices from the pedagogical project in the perspective of differentiated education with the intention of meeting the real educational, sociocultural and identity needs of studants in the countryside? How and teachers think about curricular actions that can have an impact on improving the quality of education offered in rural schools? It aims to identify how the curriculum based on respect for diversity can support the production of a pedagogical project as the central axis of differentiated educational practices in rural schools in the Municipality of Gurupá, State of Pará. The research approach is qualitative and was supported by experiences in schools and dialogues with head teachers of rural schools during the supervision activities of Supervised Internships I and IIV of the Rural Education Degree Course. In the reflections elaborated, we highlight the pedagogical project as an identity document for rural schools that needs to be better discussed in the collective of rural communities in Gurupá-PA; regarding the perceptions of education professionals, the necessary relationship they establish between the pedagogical project and the quality of teaching was notorious, as they understand that it is indispensable in the organization of educational actions based on the peasant reality, in order to embody the directions for education of the countryside that forms the value of the subject of the countryside, its traditional knowledge and its place as an educational territory.
Analysis of Beijing Traffic Violations Based on the BERT-CRF Model
Authors: Li Jie , Shi Yuntao , Li Shuqin
Published: April 2024

Traffic violations are a major cause of traffic accidents, yet current research falls short in comprehensively analysing these violations and the  named entity method fails to extract the name of traffic violation events from records, thereby lacking in providing guidance for managing urban traffic violations. By expanding the People’s Daily dataset from 71,456 words to 95,291 words, the BERT-CRF (Bidirectional Encoder Representations from Transformers-Conditional Random Field) model achieves an accuracy rate of 88.53%, a recall rate of 92.90% and an F1 score of 90.66%, successfully identifying event, time and location named entities within traffic violations. The data of traffic violations is then enhanced through forward geocoding and the Bayesian formula, and traffic violations are analysed from time, space, administrative region, gender and weather, to provide support for the dynamic allocation of law enforcement forces on traffic scenes and the precise management oftraffic violations.
Traffic Signal Timing Scheme Based on the Improved Harris Hawks Optimisation
Authors: Zhao Hongluan , Su Mengmeng
Published: April 2024

With the continuous increase of urban vehicles, traffic congestion becomes severe in the metropolitan areas and higher car utilisation areas. The traffic signal timing scheme can effectively alleviate traffic congestion at intersections. We need to make a profound study in the traffic signal timing. An optimisation model is established, which not only takes the average delay time of vehicles, the number of vehicle stops and the traffic capacity, but also takes the exhaust emissions as the evaluation indexes. The model is too complex and involves too many variables to be solved by using multi-objective programming. Thus, the Harris Hawks Optimisation (HHO) with few parameters and high search accuracy was used to solve the model. To avoid the disadvantages of poor search performance and easy to fall into local optimisation of the Harris Hawks Algorithm, multi-strategy improvements were introduced. The experimental effects show that during the peak hours of traffic flow, the improved algorithm can reduce the average vehicle delay by 36.7%, the exhaust emission by 31.2% and increase the vehicle capacity by 41.6%. The above indicators have also been upgraded during the low peak stage.
Spatial Econometric Analysis of Carbon Dioxide Emission – European Case Study
Authors: Szabó Zsombor , Szalmáné Csete Mária , Sipos Tibor
Published: April 2024

The level of greenhouse gas emissions is one of the most important issues today, both professionally and politically, because a lower level of greenhouse gas emission is mandatory for a sustainable economy. Besides industry and households, the transport sector is also responsible for these emissions. For this reason, it may be essential to set up a model with which the amount of CO2 emissions could be estimated or predicted. This article presents a model that examines the extent of economic development and CO2 emissions in European countries. The result is establishing a pattern requiring a longer time series. If the pattern is proven, a clear reassessment of the current relationship between economic development and environmental protection should be made.
A educação musical em cursos de pedagogia do estado de São Paulo
Authors: Henriques Wasti Silvério Ciszevski
Published: April 2024

Poucos cursos paulistas oferecem a disciplina Música em sua grade curricular, embora os documentos nacionais para o curso de Pedagogia apontem pra a inserção de disciplinas artísticas em seu currículo, pois seu “núcleo de estudos básicos” considera “Artes” como um de seus componentes. Esta obra pretende apresentar aspectos referentes à situação do ensino musical em cursos de Pedagogia paulistas, de modo a contribuir com dados específicos às grandes questões ligadas à implantação da Música na educação básica, temática bastante relevante no momento em que o Brasil se encontra, destacando-se, em especial, a questão do conhecimento em música e o papel da música no currículo da escola regular e nos cursos de formação acadêmico-profissional de professores.
Context-Aware Amino Acid Embedding Advances Analysis of TCR-Epitope Interactions
Authors: Zhang Pengfei , Bang Seojin , Cai Michael , Lee Heewook
Published: April 2024

Accurate prediction of binding interaction between T cell receptors (TCRs) and host cells is fundamental to understanding the regulation of the adaptive immune system as well as to developing data-driven approaches for personalized immunotherapy. While several machine learning models have been developed for this prediction task, the question of how to specifically embed TCR sequences into numeric representations remains largely unexplored compared to protein sequences in general. Here, we investigate whether the embedding models designed for protein sequences, and the most widely used BLOSUM-based embedding techniques are suitable for TCR analysis. Additionally, we present our context-aware amino acid embedding models (catELMo) designed explicitly for TCR analysis and trained on 4M unlabeled TCR sequences with no supervision. We validate the effectiveness of catELMo in both supervised and unsupervised scenarios by stacking the simplest models on top of our learned embeddings. For the supervised task, we choose the binding affinity prediction problem of TCR and epitope sequences and demonstrate notably significant performance gains (up by at least 14% AUC) compared to existing embedding models as well as the state-of-the-art methods. Additionally, we also show that our learned embeddings reduce more than 93% annotation cost while achieving comparable results to the state-of-the-art methods. In TCR clustering task (unsupervised), catELMo identifies TCR clusters that are more homogeneous and complete about their binding epitopes. Altogether, our catELMo trained without any explicit supervision interprets TCR sequences better and negates the need for complex deep neural network architectures in downstream tasks.
Quorum-sensing agr system of Staphylococcus aureus primes gene expression for protection from lethal oxidative stress
Authors: Podkowik Magdalena , Perault Andrew I , Putzel Gregory , Pountain Andrew , Kim Jisun , DuMont Ashley L , Zwack Erin E , Ulrich Robert J , Karagounis Theodora K , Zhou Chunyi , Haag Andreas F , Shenderovich Julia , Wasserman Gregory A , Kwon Junbeom , Chen John , Richardson Anthony R , Weiser Jeffrey N , Nowosad Carla R , Lun Desmond S , Parker Dane , Pironti Alejandro , Zhao Xilin , Drlica Karl , Yanai Itai , Torres Victor J , Shopsin Bo
Published: April 2024

The agr quorum-sensing system links Staphylococcus aureus metabolism to virulence, in part by increasing bacterial survival during exposure to lethal concentrations of H2O2, a crucial host defense against S. aureus. We now report that protection by agr surprisingly extends beyond post-exponential growth to the exit from stationary phase when the agr system is no longer turned on. Thus, agr can be considered a constitutive protective factor. Deletion of agr resulted in decreased ATP levels and growth, despite increased rates of respiration or fermentation at appropriate oxygen tensions, suggesting that Δagr cells undergo a shift towards a hyperactive metabolic state in response to diminished metabolic efficiency. As expected from increased respiratory gene expression, reactive oxygen species (ROS) accumulated more in the agr mutant than in wild-type cells, thereby explaining elevated susceptibility of Δagr strains to lethal H2O2 doses. Increased survival of wild-type agr cells during H2O2 exposure required sodA, which detoxifies superoxide. Additionally, pretreatment of S. aureus with respiration-reducing menadione protected Δagr cells from killing by H2O2. Thus, genetic deletion and pharmacologic experiments indicate that agr helps control endogenous ROS, thereby providing resilience against exogenous ROS. The long-lived ‘memory’ of agr-mediated protection, which is uncoupled from agr activation kinetics, increased hematogenous dissemination to certain tissues during sepsis in ROS-producing, wild-type mice but not ROS-deficient (Cybb−/−) mice. These results demonstrate the importance of protection that anticipates impending ROS-mediated immune attack. The ubiquity of quorum sensing suggests that it protects many bacterial species from oxidative damage.
Aberrant cortical activity, functional connectivity, and neural assembly architecture after photothrombotic stroke in mice
Authors: Bandet Mischa Vance , Winship Ian Robert
Published: April 2024

Despite substantial progress in mapping the trajectory of network plasticity resulting from focal ischemic stroke, the extent and nature of changes in neuronal excitability and activity within the peri-infarct cortex of mice remains poorly defined. Most of the available data have been acquired from anesthetized animals, acute tissue slices, or infer changes in excitability from immunoassays on extracted tissue, and thus may not reflect cortical activity dynamics in the intact cortex of an awake animal. Here, in vivo two-photon calcium imaging in awake, behaving mice was used to longitudinally track cortical activity, network functional connectivity, and neural assembly architecture for 2 months following photothrombotic stroke targeting the forelimb somatosensory cortex. Sensorimotor recovery was tracked over the weeks following stroke, allowing us to relate network changes to behavior. Our data revealed spatially restricted but long-lasting alterations in somatosensory neural network function and connectivity. Specifically, we demonstrate significant and long-lasting disruptions in neural assembly architecture concurrent with a deficit in functional connectivity between individual neurons. Reductions in neuronal spiking in peri-infarct cortex were transient but predictive of impairment in skilled locomotion measured in the tapered beam task. Notably, altered neural networks were highly localized, with assembly architecture and neural connectivity relatively unaltered a short distance from the peri-infarct cortex, even in regions within ‘remapped’ forelimb functional representations identified using mesoscale imaging with anaesthetized preparations 8 weeks after stroke. Thus, using longitudinal two-photon microscopy in awake animals, these data show a complex spatiotemporal relationship between peri-infarct neuronal network function and behavioral recovery. Moreover, the data highlight an apparent disconnect between dramatic functional remapping identified using strong sensory stimulation in anaesthetized mice compared to more subtle and spatially restricted changes in individual neuron and local network function in awake mice during stroke recovery.
ATG6 interacting with NPR1 increases Arabidopsis thaliana resistance to Pst DC3000/avrRps4 by increasing its nuclear accumulation and stability
Authors: Zhang Baihong , Huang Shuqin , Guo Shuyu , Meng Yixuan , Tian Yuzhen , Zhou Yue , Chen Hang , Li Xue , Zhou Jun , Chen Wenli
Published: April 2024

Autophagy-related gene 6 (ATG6) plays a crucial role in plant immunity. Nonexpressor of pathogenesis-related genes1 (NPR1) acts as a signaling hub of plant immunity. However, the relationship between ATG6 and NPR1 is unclear. Here, we find that ATG6 directly interacts with NPR1.
ATG6
overexpression significantly increased nuclear accumulation of NPR1. Furthermore, we demonstrate that
ATG6
increases NPR1 protein levels and improves its stability. Interestingly, ATG6 promotes the formation of SINCs (SA-induced NPR1 condensates)-like condensates. Additionally, ATG6 and NPR1 synergistically promote the expression of
pathogenesis-related
genes. Further results showed that silencing
ATG6
in
NPR1-GFP
exacerbates
Pst
DC3000/
avrRps4
invasion, while double overexpression of
ATG6
and
NPR1
synergistically inhibits
Pst
DC3000/
avrRps4
invasion. In summary, our findings unveil an interplay of NPR1 with ATG6 and elucidate important molecular mechanisms for enhancing plant immunity.We unveil a novel relationship in which ATG6 positively regulates NPR1 in plant immunity.
«Du kan ikke overse generasjon Z»
Authors: Borge Baard Herman , Slåtto Lena , Tande Ceila
Published: April 2024

Generasjonsteori som beskriver hvordan boomers, x, y og z skiller seg fra hverandre med hensyn til holdninger og verdier, er blitt en gjenganger i populærkulturen. Diskusjonen dreier seg ofte om hva særtrekk ved nye generasjoner betyr for arbeidslivet. «Du kan ikke overse generasjon Z», slo et norsk ledermagasin nylig fast, for så å presentere råd om håndtering av arbeidstakere født 1995-2010 (Skrede 2020). Både media, konsulenter og forskere er opptatt av hvordan bedrifter nå bør innrette seg for å rekruttere de yngste, og få dem til å yte maksimalt. I flere land er generasjonsbasert ledelse blitt en nisje innen bedriftsrådgivning, der kjernen er at ansatte skal ledes på bestemte måter ut fra sin generasjonstilhørighet. Generasjonsteori forutsetter at det er mulig å isolere effekten av fødselsår på individers holdninger og atferd. Men holdepunktene for en slik sammenheng er usikre. Eksistensen av homogene generasjoner er omstridt, det samme gjelder de vanlige beskrivelsene av dem. I denne artikkelen bruker jeg norske surveydata fra 2021 til å undersøke om et utvalg fra generasjon Z har holdninger til arbeid som a) samsvarer med fem utbredte stereotypier og b) skiller seg signifikant fra svarene til en sammensatt og atskillig eldre kontrollgruppe (40-67 år). De to gruppenes gjennomsnittsvar sammenlignes ved hjelp av t-tester. Funnene viser at generasjon Z bare på enkelte punkter ligner stereotypen, dernest at forskjellene mellom yngre og eldre personer er mindre enn populærvarianter av generasjonsteori skulle tilsi. Spredningen i svarene var kun i få tilfeller signifikant mindre i generasjon Z-gruppen.
An effective transformer based on dual attention fusion for underwater image enhancement
Authors: Hu Xianjie , Liu Jing , Li Heng , Liu Hui , Xue Xiaojun
Published: April 2024

Underwater images suffer from color shift, low contrast, and blurred details as a result of the absorption and scattering of light in the water. Degraded quality images can significantly interfere with underwater vision tasks. The existing data-driven based underwater image enhancement methods fail to sufficiently consider the impact related to the inconsistent attenuation of spatial areas and the degradation of color channel information. In addition, the dataset used for model training is small in scale and monotonous in the scene. Therefore, our approach solves the problem from two aspects of the network architecture design and the training dataset. We proposed a fusion attention block that integrate the non-local modeling ability of the Swin Transformer block into the local modeling ability of the residual convolution layer. Importantly, it can adaptively fuse non-local and local features carrying channel attention. Moreover, we synthesize underwater images with multiple water body types and different degradations using the underwater imaging model and adjusting the degradation parameters. There are also perceptual loss functions introduced to improve image vision. Experiments on synthetic and real-world underwater images have shown that our method is superior. Thus, our network is suitable for practical applications.
Fine grain emotion analysis in Spanish using linguistic features and transformers
Authors: Salmerón-Ríos Alejandro , García-Díaz José Antonio , Pan Ronghao , Valencia-García Rafael
Published: April 2024

Mental health issues are a global concern, with a particular focus on the rise of depression. Depression affects millions of people worldwide and is a leading cause of suicide, particularly among young people. Recent surveys indicate an increase in cases of depression during the COVID-19 pandemic, which affected approximately 5.4% of the population in Spain in 2020. Social media platforms such as X (formerly Twitter) have become important hubs for health information as more people turn to these platforms to share their struggles and seek emotional support. Researchers have discovered a link between emotions and mental illnesses such as depression. This correlation provides a valuable opportunity for automated analysis of social media data to detect changes in mental health status that might otherwise go unnoticed, thus preventing more serious health consequences. Therefore, this research explores the field of emotion analysis in Spanish towards mental disorders. There are two contributions in this area. On the one hand, the compilation, translation, evaluation and correction of a novel dataset composed of a mixture of other existing datasets in the bibliography. This dataset compares a total of 16 emotions, with an emphasis on negative emotions. On the other hand, the in-depth evaluation of this novel dataset with several state-of-the-art transformers based on encoder-only and encoder-decoder architectures. The analysis compromises monolingual, multilingual and distilled models as well as feature integration techniques. The best results are obtained with the encoder-only MarIA model, with a macro-average F1 score of 60.4771%.
A methodological showcase: utilizing minimal clinical parameters for early-stage mortality risk assessment in COVID-19-positive patients
Authors: Yan Jonathan K.
Published: April 2024

The scarcity of data is likely to have a negative effect on machine learning (ML). Yet, in the health sciences, data is diverse and can be costly to acquire. Therefore, it is critical to develop methods that can reach similar accuracy with minimal clinical features. This study explores a methodology that aims to build a model using minimal clinical parameters to reach comparable performance to a model trained with a more extensive list of parameters. To develop this methodology, a dataset of over 1,000 COVID-19-positive patients was used. A machine learning model was built with over 90% accuracy when combining 24 clinical parameters using Random Forest (RF) and logistic regression. Furthermore, to obtain minimal clinical parameters to predict the mortality of COVID-19 patients, the features were weighted using both Shapley values and RF feature importance to get the most important factors. The six most highly weighted features that could produce the highest performance metrics were combined for the final model. The accuracy of the final model, which used a combination of six features, is 90% with the random forest classifier and 91% with the logistic regression model. This performance is close to that of a model using 24 combined features (92%), suggesting that highly weighted minimal clinical parameters can be used to reach similar performance. The six clinical parameters identified here are acute kidney injury, glucose level, age, troponin, oxygen level, and acute hepatic injury. Among those parameters, acute kidney injury was the highest-weighted feature. Together, a methodology was developed using significantly minimal clinical parameters to reach performance metrics similar to a model trained with a large dataset, highlighting a novel approach to address the problems of clinical data collection for machine learning.
Robust 3D object watermarking scheme using shape features for copyright protection
Authors: M. Alhammad Sarah , Ahmed Nada , Abbas Safia , Abulkasim Hussein , Elhadad Ahmed
Published: April 2024

This article utilizes the discrete wavelet transformation to introduce an advanced 3D object watermarking model depending on the characteristics of the object’s vertices. The model entails two different phases: integration and extraction. In the integration phase, a novel technique is proposed, which embeds the secret grayscale image three times using both the encrypted pixels and the vertices’ coefficients of the original 3D object. In the extraction phase, the secret image is randomly extracted and recaptured using the inverse phase of the integration technique. Four common 3D objects (Stanford bunny, horse, cat figurine, and angel), with different faces and different vertices, are used in this model as a dataset. The performance of the proposed technique is evaluated using different metrics to show its superiority in terms of execution time and imperceptibility. The results demonstrated that the proposed method achieved high imperceptibility and transparency with low distortion. Moreover, the extracted secret grayscale image perfectly matched the original watermark with a structural similarity index of 1 for all testing models.
Design of information management model based on multiobjective optimization algorithm in intelligent electric financial system
Authors: Hu Junhui , Cai Hongxiang , Zhang Shiyong , Pei Chuanxun , Wang Zihao
Published: April 2024

The electric power infrastructure is the cornerstone of contemporary society’s sustenance and advancement. Within the intelligent electric power financial system, substantial inefficiency and waste in information management persist, leading to an escalating depletion of resources. Addressing diverse objectives encompassing economic, environmental, and societal concerns within the power system helps the study to undertake a comprehensive, integrated optimal design and operational scheduling based on a multiobjective optimization algorithm. This article centers on optimizing the power financial system by considering fuel cost, active network loss, and voltage quality as primary objectives. A mathematical model encapsulates these objectives, integrating equations and inequality constraints and subsequently introducing enhancements to the differential evolutionary algorithm. Adaptive variation and dynamic crossover factors within crossover, variation, and selection operations are integrated to optimize algorithm parameters, specifically catering to the multiobjective optimization of the electric power system. An adaptive grid method and cyclic crowding degree ensure population diversity and control the Pareto front distribution. They experimentally validated the approach and the comparisons conducted against AG-MOPSO, INSGA-II, and NSDE algorithms across standard test functions: ZDT1, ZDT2, ZDT3, and DTLZ4. The convergence evaluation indices for this study’s scheme on ZDT1 and ZDT2 are 0.000938 and 0.0034, respectively. Additionally, distribution evaluation indices on ZDT1, ZDT2, ZDT3, and ZDT4 stand at 0.0018, 0.0026, 0.0027, and 0.0009, respectively. These indices indicate a robust convergence and distribution, facilitating the optimization of electric power financial information management and the intelligent handling of the electric power financial system’s information, thereby enhancing the allocation of material and financial resources.
Design of sports training information analysis system based on a multi-target visual model under sensor-scale spatial transformation
Authors: Hu Mei , Zhang Ming , Yu Kewei
Published: April 2024

In the contemporary realm of athletic training, integrating technology is a pivotal determinant for augmenting athlete performance and refining training outcomes. The amalgamation of multi-target visual modeling with sensor technology imparts an enriched stratum of sports training data. Subsequently, the sensor scale-space transformation accentuates the comprehensive apprehension of data across diverse scales and angles. Hence, within this manuscript, addressing the multi-target tracking intricacies during sports training and competition, we posit a framework that amalgamates the shortest path elucidated by the K shortest paths (KSP) methodology with the pose information emanating from the Alphapose network. This framework recognizes the athlete’s shortest path through a convolutional neural network and KSP, followed by the amalgamation of these divergent data sources. The fusion unfolds by incorporating the athlete’s pose information grounded in Alphapose, culminating in a comprehensive integration of the two data streams. Consequently, synthesizing alpha-derived athlete information precipitates the ultimate amalgamation of the two information streams. The accomplished fusion, premised on Alphapose, forms the bedrock for multi-target tracking, culminating in a feature-rich synthesis. Empirical results reveal that after integrating these information streams, the Multiple Object Tracking Accuracy (MOTA) index and Global Multiple Object Tracking Accuracy (GMOTA) index surpass those of the solitary information tracking methods, thereby furnishing a technical underpinning and a foundation for information fusion within prospective sports training analysis systems.
Achieving optimal trade-off for student dropout prediction with multi-objective reinforcement learning
Authors: Pan Feng , Zhang Hanfei , Li Xuebao , Zhang Moyu , Ji Yang
Published: April 2024

Student dropout prediction (SDP) in educational research has gained prominence for its role in analyzing student learning behaviors through time series models. Traditional methods often focus singularly on either prediction accuracy or earliness, leading to sub-optimal interventions for at-risk students. This issue underlines the necessity for methods that effectively manage the trade-off between accuracy and earliness. Recognizing the limitations of existing methods, this study introduces a novel approach leveraging multi-objective reinforcement learning (MORL) to optimize the trade-off between prediction accuracy and earliness in SDP tasks. By framing SDP as a partial sequence classification problem, we model it through a multiple-objective Markov decision process (MOMDP), incorporating a vectorized reward function that maintains the distinctiveness of each objective, thereby preventing information loss and enabling more nuanced optimization strategies. Furthermore, we introduce an advanced envelope Q-learning technique to foster a comprehensive exploration of the solution space, aiming to identify Pareto-optimal strategies that accommodate a broader spectrum of preferences. The efficacy of our model has been rigorously validated through comprehensive evaluations on real-world MOOC datasets. These evaluations have demonstrated our model’s superiority, outperforming existing methods in achieving optimal trade-off between accuracy and earliness, thus marking a significant advancement in the field of SDP.
Cost-effort analysis of Baited Remote Underwater Video (BRUV) and environmental DNA (eDNA) in monitoring marine ecological communities
Authors: Clark Alice J. , Atkinson Sophie R. , Scarponi Valentina , Cane Tim , Geraldi Nathan R. , Hendy Ian W. , Shipway J. Reuben , Peck Mika
Published: April 2024

Monitoring the diversity and distribution of species in an ecosystem is essential to assess the success of restoration strategies. Implementing biomonitoring methods, which provide a comprehensive assessment of species diversity and mitigate biases in data collection, holds significant importance in biodiversity research. Additionally, ensuring that these methods are cost-efficient and require minimal effort is crucial for effective environmental monitoring. In this study we compare the efficiency of species detection, the cost and the effort of two non-destructive sampling techniques: Baited Remote Underwater Video (BRUV) and environmental DNA (eDNA) metabarcoding to survey marine vertebrate species. Comparisons were conducted along the Sussex coast upon the introduction of the Nearshore Trawling Byelaw. This Byelaw aims to boost the recovery of the dense kelp beds and the associated biodiversity that existed in the 1980s. We show that overall BRUV surveys are more affordable than eDNA, however, eDNA detects almost three times as many species as BRUV. eDNA and BRUV surveys are comparable in terms of effort required for each method, unless eDNA analysis is carried out externally, in which case eDNA requires less effort for the lead researchers. Furthermore, we show that increased eDNA replication yields more informative results on community structure. We found that using both methods in conjunction provides a more complete view of biodiversity, with BRUV data supplementing eDNA monitoring by recording species missed by eDNA and by providing additional environmental and life history metrics. The results from this study will serve as a baseline of the marine vertebrate community in Sussex Bay allowing future biodiversity monitoring research projects to understand community structure as the ecosystem recovers following the removal of trawling fishing pressure. Although this study was regional, the findings presented herein have relevance to marine biodiversity and conservation monitoring programs around the globe.
Photoactivated disinfection procedure for denture stomatitis in diabetic rats
Authors: Zhang Xiao , Zhao Zirui , Zhang Ruiqi , Liu Juan , Guo Zhijiao , Hu Qiaoyu , Liu Na , Liu Qing
Published: April 2024

Objective

To study the efficacy of PADTM Plus-based photoactivated disinfection (PAD) for treating denture stomatitis (DS) in diabetic rats by establishing a diabetic rat DS model.

Methods

The diabetic rat DS model was developed by randomly selecting 2-month-old male Sprague-Dawley rats and dividing them into four groups. The palate and denture surfaces of rats in the PAD groups were incubated with 1 mg/mL toluidine blue O for 1 min each, followed by a 1-min exposure to 750-mW light-emitting diode light. The PAD-1 group received one radiation treatment, and the PAD-2 group received three radiation treatments over 5 days with a 1-day interval. The nystatin (NYS) group received treatment for 5 days with a suspension of NYS of 100,000 IU. The infection group did not receive any treatment. In each group, assessments included an inflammation score of the palate, tests for fungal load, histological evaluation, and immunohistochemical detection of interleukin-17 (IL-17) and tumor necrosis factor (TNF-α) conducted 1 and 7 days following the conclusion of treatment.

Results

One day after treatment, the fungal load on the palate and dentures, as well as the mean optical density values of IL-17 and TNF-α, were found to be greater in the infection group than in the other three treatment groups (P < 0.05). On the 7th day after treatment, these values were significantly higher in the infection group than in the PAD-2 and NYS groups (P < 0.05). Importantly, there were no differences between the infection and PAD-1 groups nor between the PAD-2 and NYS groups (P > 0.05).

Conclusions

PAD effectively reduced the fungal load and the expressions of IL-17 and TNF-α in the palate and denture of diabetic DS rats. The efficacy of multiple-light treatments was superior to that of single-light treatments and similar to that of NYS.
The impact of skeletal muscle index at the third lumbar spine on nosocomial deterioration and short-term prognosis in acute pancreatitis: a retrospective observational study
Authors: Lin Chuntao , Zhang Junyuan , Wang Chunye , Lian Wei , Liu Yicong
Published: April 2024

Objective

To investigate the impact of the third lumbar skeletal muscle index (L3-SMI) assessed by CT on the in-hospital severity and short-term prognosis of acute pancreatitis.

Methods

A total of 224 patients with severe acute pancreatitis admitted to Yantaishan Hospital from January 2021 to June 2022 were selected as the subjects. Based on the in-hospital treatment outcomes, they were divided into a mortality group of 59 cases as well as a survival group of 165 cases. Upon admission, general information such as the Acute Physiology and Chronic Health Evaluation II (APACHE II) score, along with the abdominal CT images of each patient, were analyzed. The L3-SMI was calculated, and the Modified CT Severity Index (MCTSI) and Balthazar CT grade were used to assess the severity of in-hospital complications of acute pancreatitis. The evaluation value of L3-SMI for the prognosis of severe acute pancreatitis was analyzed, as well as the factors influencing the prognosis of severe acute pancreatitis.

Results

No statistically significant differences in gender, age, BMI, etiology, duration of anti-inflammatory drug use, and proportion of surgical patients between the survival and mortality groups were observed. But the mortality group showed higher proportions of patients with an elevated APACHE II score upon admission, mechanical ventilation, and renal replacement therapy, compared to the survival group, with statistically significant differences (P < 0.001). Furthermore, the mortality group had higher MCTSI scores (6.42 ± 0.69) and Balthazar CT grades (3.78 ± 0.45) than the survival group, with statistically significant differences (P < 0.001). The mortality group also had a lower L3-SMI (39.68 ± 3.25) compared to the survival group (42.71 ± 4.28), with statistically significant differences (P < 0.001). L3-SMI exhibited a negative correlation with MCTSI scores and Balthazar CT grades (r = −0.889, −0.790, P < 0.001). Logistic regression analysis, with mortality of acute pancreatitis patients as the dependent variable and MCTSI scores, Balthazar CT grades, L3-SMI, APACHE II score upon admission, mechanical ventilation, and renal replacement therapy as independent variables, revealed that MCTSI scores and L3-SMI were risk factors for mortality in acute pancreatitis patients (P < 0.001). Logistic regression analysis using the same variables confirmed that all these factors were risk factors for mortality in acute pancreatitis patients.

Conclusion

This study confirmed that diagnosing muscle depletion using L3-SMI is a valuable radiological parameter for predicting in-hospital severity and short-term prognosis in patients with acute pancreatitis.