bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhancing Lithium-ion Battery Safety: Analysis and Detection of Internal Short Circuit basing on an Electrochemical-Thermal Modeling
Authors: JIA YIQI , BRANCATO LORENZO , GIGLIO MARCO , CADINI FRANCESCO
Published: June 2024

As the main cause of thermal runaway, the prompt identification of Internal Short Circuit (ISC) occurrences in lithium-ion batteries (LIBs) has emerged as a critical priority for ensuring battery safety. To address this critical need, for a comprehensive understanding of ISC behaviors, an electrochemical-thermal-ISC coupled model has been developed in this work to simulate battery performance across various ISC levels. This model is also utilized to validate the efficacy and robustness of the advanced detection approach proposed. By integrating both thermal and electrical aspects using the Pseudo Two-Dimensional (P2D) and Energy Balance Equation (EBE), our model serves as an efficient surrogate for ISC experiments. Key ISC indicators have been analyzed and integrated into the proposed ISC detection algorithm to enhance its effectiveness. The algorithm utilizes an Equivalent Circuit Model (ECM)-based approach for estimating ISC resistance. This research not only advances our understanding of ISC dynamics but also establishes a robust framework for the timely and reliable detection of ISCs. These advancements significantly enhance the overall safety and reliability of LIBs in electric vehicles (EVs).
Simulation-based remaining useful life prediction of rolling element bearings under varying operating conditions
Authors: Hosseinli Seyed Ali , Ooijevaar Ted , Gryllias Konstantinos
Published: June 2024

Remaining useful life (RUL) prediction of rolling element bearings is a complex task in the frame of condition monitoring which brings cost benefits to the industry by reducing unexpected downtimes and failures. Data-driven approaches based on deep learning have demonstrated exceptional performance in estimating RUL effectively. Nevertheless, challenges such as data scarcity for model training and varying operating conditions add more complexity to prognostic tasks using these methods. This study proposes a methodology for simulating the vibration signals during the degradation process of bearings in order to mitigate the need for historical data for training the models. Simulations are realized using a phenomenological model whose free parameters are adapted based on real measurements so that the simulated run-to-failure datasets are under the same influence of speed as the real dataset with almost the same degradation rate. The simulated dataset is used for model training. Moreover, the proposed methodology is able to react to the shaft speed and be flexible at the predictions when the speed of the bearing varies. The proposed model can take extra information regarding the operating speed and the sequential ordering of the measurements to be aware of the working conditions and the dynamics of the damage progression. The positive effect of the extra information is shown in the results. Model training is based on an unsupervised domain adaptation approach to reduce domain discrepancy between the simulated and real feature space. The effectiveness of the proposed method is examined according to bearing run-to-failure tests under varying operating conditions.
Filter-based feature selection for prognostics incorporating cross correlations and failure thresholds
Authors: Loewen Alexander , Wissbrock Peter , Bender Amelie , Sextro Walter
Published: June 2024

Historical condition monitoring data from technical systems can be utilized to develop data-driven models for predicting the remaining useful life (RUL) of similar systems, whereas the Health Index (HI) often is a crucial component. The development of robust and accurate models requires meaningful features that reflect the system’s degradation process, enabling an accurate prediction of the system's HI. Traditionally, the identification of those is supported by one of various feature ranking methods. In literature, feature interdependencies and their transferability across various similar systems are not sufficiently considered in feature selection, exacerbating the challenge of HI prediction posed by the scarcity of data and system diversity in real-world applications. This work addresses this gaps by demonstrating how filter-based feature selection, incorporating failure thresholds and cross correlations, enhances feature selection leading to improved HI prediction. The proposed methodology is applied to a novel dataset* obtained from run-to-failure experiments on geared motors conducted as part of this study, which presents the aforementioned challenges. It is revealed that classical feature selection, consisting of feature ranking only, leaves potential untapped, which is utilized by the proposed selection methodology. It is shown that the proposed feature selection methodology leads to the best result with a RMSE of 0.14 in predicting the HI of a constructive different gearbox, while the features, determined by classical feature selection, lead to a RMSE of 0.19 at best.
Domain Adaptation for Fault Detection in Civil Nuclear Plants
Authors: Wood Henry , Montana Felipe , Kadirkamanathan Visakan , Mills Andy , Jacobs Will
Published: June 2024

Recent domain adaptation approaches have been shown to generalise well between distant data domains achieving high performance in machine fault detection through time series classification. An interesting aspect of this transfer-learning inspired approach, is that the algorithm need not be exposed to fault data from the target domain during training. This promotes the application of these methods to environments in which fault data is unfeasible to obtain, such as the detection of loss-of-coolant accidents (LOCA) in nuclear power plants (NPPs). A LOCA is a failure mode of a nuclear reactor in which coolant is lost due to a physical break in the primary coolant circuit. If undetected, or not managed effectively, a LOCA can result in reactor core damage. Three high-fidelity physics based models were created with divergent behaviour that represent different data domains. The first model is used to generate source domain data by simulating labelled training data under both nominal and LOCA conditions. The second and third models act as surrogates of real plants and are used to generate target domain data, i.e. to simulate nominal data for training and LOCA condition data for validation. Several deep-learning feature encoders (with varying levels of connectivity) were applied to this LOCA detection problem. Among these, a ’Baseline’ encoder was used to quantify the improvement that domain adaptation techniques make to LOCA detection performance under large domain divergences. Classification accuracy for each model is explored within the context of LOCA break size and location within each plant model. The proposed method for LOCA detection demonstrates how the dependence upon sparse accident-specific data can be alleviated through the use of domain adaptation. Detection capability of the LOCA condition is maintained even when no data examples are available in the target domain.
Analytical Modeling of Health Indices for Prognostics and Health Management
Authors: Pierre Dersin , Bajarunas Kristupas , Arias-Chao Manuel
Published: June 2024

Understanding the current health condition of complex systems and their temporal evolution is an important step in prognostics and health management (PHM). However, when managing a fleet of complex systems, variations arising from manufacturing, environmental factors, mission profiles, and maintenance practices result in diverse health index (HI) trajectories. Therefore, in PHM, it is essential not only to identify common fleet-wide trends but also to account for individual asset-level variations when inferring HIs.
While several data-driven approaches exist for inferring individual asset-level HIs from unsupervised run-to-failure degradation data, little research has been devoted to deriving analytical probabilistic representations of HIs that encompass both fleet-level trends and individual asset-level fluctuations. This paper aims to bridge this gap by addressing the research question of how to obtain an analytical representation of probability distributions for the time to reach intermediate degradation levels, using run-to-failure data or incomplete degradation trajectories from a fleet of complex systems.
In this work, it is assumed that suitable, asset-specific HI curves have been inferred through a fusion of deep learning techniques and prior expert knowledge of degradation physics . Given this context, we derive an analytical probabilistic description of the health index (HI) that reflects both fleet-wide trends and asset-specific conditions in the cases of Gamma or Weibull time-to-failure (TTF) distributions. Our approach involves defining HIs with a power law function, enabling the modeling of TTF and time to reach intermediate degradation levels. Moreover, we also detail the procedure for estimating the power law exponent from field data through regression analysis and conduct a sensitivity analysis regarding this exponent.
To illustrate our methodology, we present two case studies based on the N-CMAPPS dataset of turbofan engines and Li-ion batteries, validating the aforementioned assumptions and illustrating our methodology steps
Towards Physics-Informed PHM for Multi-component degradation (MCD) in complex systems
Authors: Barimah Atuahene , Niculita Octavian , McGlinchey Don , Cowell Andrew , Milligan Billy
Published: June 2024

This study seeks to address the challenge of limited degradation data in developing Fault Detection and Isolation (FDI) models for multi-component degradation (MCD) scenarios. Utilizing a small fraction (0.05%) of a previously utilized water distribution testbed dataset in a previous publication, a weighted ensemble hybrid approach is proposed and evaluated against more established modelling approaches used in the previous publication. The proposed approach combines heuristic approximation and Physics-Informed Neural Network (PINN) methods with a recurrent neural network (RNN) model to enhance diagnostic performance for predicting MCD scenarios. The hybrid model generally outperformed other algorithms when tested on an MCD dataset, demonstrating improved diagnostic accuracy in such scenarios. Future research aims to optimize ensemble weights based on model uncertainty, further enhancing diagnostic capabilities.
A Semi-supervised Fault Diagnosis Method Based on Graph Convolution for Few-shot Fault Diagnosis
Authors: Li Yuyan , Wang Tian , Xie Jingsong
Published: June 2024

In practical bearing fault diagnosis, labeled fault data are difficult to obtain, and limited samples will lead to training overfitting. To address the above problems, a semi-supervised fault diagnosis method based on graph convolution is proposed. Firstly, the KNN graph construction method based on Euclidean distance (ED-KNN) is used to achieve label propagation. Then, a graph convolutional network framework based on dot product attention mechanism (GPGAT) was constructed to enhance the weights of high similarity nodes and diagnose bearing faults. The proposed method is validated on a public bearing dataset. The results show that the proposed method can make full use of very few labeled samples for fault diagnosis. Compared with other state-of-the-art methods, the proposed method achieves better diagnosis performance.
False alarm reduction in railway track quality inspections using machine learning
Authors: Durazo-Cardenas Isidro , Namoano Bernadin , Starr Andrew , Dilip Sala Ram , Lai Jichao
Published: June 2024

Track quality geometry measurements are crucial for the railways’ timely maintenance. Regular measurements prevent train delays, passenger discomfort and incidents. However, current fault diagnosis or parameter deviation relies on simple threshold comparison of multiple laser scanners, linear variable differential transformer (LVDT) and camera measurements. Data threshold exceedances enact maintenance actions automatically. However, issues such as measurement error, and sensor failure can result in false positives. Broad localisation resolution prevents trending/ inferencing by comparison with healthy data baseline at the same position over periodic inspections.
False alarms can result in costly ineffective interventions, are hazardous and impact the network availability.  
This paper proposes a novel methodology based on convolutional neural network (CNN) technique for detecting and classifying track geometry fault severity automatically. The proposed methodology comprises an automatic flow of data for quality assessment whereby outliers, missing values and misalignment are detected, restored and where appropriate curated. Improved, “clean” datasets were then analysed using a pretrained CNN model. The method was compared with a suite of machine learning algorithms for diagnosis including k-nearest neighbour, support vector machines (SVM), and random forest (RF).
The analysis results of a real track geometry dataset showed that track quality parameters including twist, cant, gauge, and alignment could be effectively diagnosed with an accuracy rate of 97.80% (CNN model). This result represents a remarkable improvement of 38% in comparison with the traditional threshold-based diagnosis. The benefits of this research are not only associated with maintenance intervention cost savings. It also helps prevent unnecessary train speed restrictions arising from misdiagnosis.
Test-Training Leakage in Evaluation of Machine Learning Algorithms for Condition-Based Maintenance
Authors: Matania Omri , Cohen Roee , Bechhoefer Eric , Bortman Jacob
Published: June 2024

Many articles have been published utilizing machine learning algorithms for condition-based maintenance through the analysis of vibration signals. One extensively researched topic is the classification of fault types in rolling bearings. There is a fairly widespread problem in the evaluation of these learning algorithms, where the separation of examples between the test and training sets is incorrect, leading to an optimistic conclusion about the algorithm's performance even when it is not the case. In this article, we will review this issue and explain how the data should be properly divided between the test and training sets to avoid this occurrence.
Contrastive Metric Learning Loss-Enhanced Multi-Layer Perceptron for Sequentially Appearing Clusters in Acoustic Emission Data Streams
Authors: Laiadi Oualid , Remadna Ikram , Dris El yamine , Drai Redouane , Terrissa Sadek Labib , Zerhouni Noureddine
Published: June 2024

Conventional structural health monitoring methods for interpreting unlabeled acoustic emission (AE) data typically rely on generic clustering approaches. This work introduces a novel approach for analyzing sequential and temporal acoustic emission (AE) data streams by enhancing a Multi-Layer Perceptron (MLP) with a contrastive metric learning loss function (MLP-CMLL)and Time Series K-means (TSKmeans) clustering. This dual approach, MLP-CMLL with TSKmeans, is crafted to refine cluster differentiation significantly. This method is designed to optimize cluster differentiation, bringing similar acoustic patterns closer and distancing divergent ones, thereby improving the MLP's ability to classify acoustic events over time. Addressing the limitations of traditional clustering algorithms in handling the temporal dynamics of AE data, MLP-CMLL with TSKmeans approach provides deeper insights into cluster formation and evolution. It promises enhanced monitoring and predictive maintenance capabilities in engineering applications by capturing the complex dynamics of AE data more effectively, offering a significant advancement in the field of structural health monitoring. Through experimental validation, we apply this method to characterize the loosening phenomenon in bolted structures under vibrations. Comparative analysis with two standard clustering methods using raw streaming data from three experimental campaigns demonstrates that our proposed method not only delivers valuable qualitative information concerning the timeline of clusters but also showcases superior performance in terms of cluster characterization.
Threshold Selection for Classification Models in Prognostics
Authors: Deo Rohit , Desai Swarali , Behra Subhalakshmi , Pulate Chetan , Yadav Aman , Powar Nilesh
Published: June 2024

In this study, we evaluate the performance of a prognostic classification model for NOX sensors in diesel engines over one month by comparing its predictions against actual outcomes. We then construct a validation dataset to assess the model's performance. By analyzing instances where the model's predictions were incorrect, we determine new threshold values that could potentially reduce errors for each false positive (FP) and false negative (FN). Subsequently, we create a dataset where the threshold varies for each observation and train a regression model with the modified threshold as the target variable. Our findings indicate that incorporating this approach, where the model's performance is iteratively refined using the validation dataset, leads to a reduction in both false positives and false negatives.
The Use of Picture-Based English Materials to Improve Students’ Vocabulary Mastery for States Elementary Schools
Authors: Muhsinin  , Arif Rahman  , Ahmad Javed Hassan  , Said Malika Tridane Manu
Published: June 2024

The research aimed to find out improving students’ vocabulary mastery by using pictures. This research was conducted by using Classroom Action Research (CAR). The subject of this research was grade III of MIN 2 Mataram 2023/2024 academic year which consisted of 35 students consisting of 20 female and 15 male. The object of this research was to improve the students’ vocabulary mastery through pictures. This researcher was conducted in two cycles which each consists’ of planning, acting, observing,  and  reflecting.  The  data  were   gathered  through  qualitative  and quantitative  data.  The  qualitative  data  were  gained  by  analyzing  the  test  and observation  result.  Then,  quantitative  data  were  obtained  from  the  students’ vocabulary score of pre-test and post-test. Based on the result of this research showed that there was a development on the students’ vocabulary mastery, it can be seen if the score of students who got >73 grew up. It can be seen from the mean score of pre-test were 61.31, the mean score of post-test 1 was 72.39, and the mean score of pot-test cycle 2 was 82.39. In addition, there were 12 students (31,57%) who passed Minimum Mastery Criterion (KKM) in the post test of cycle 1. Meanwhile, in the cycle 2, there were 23 students (89, 4%) who passed Minimum Mastery Criterion (KKM). so the criteria of success was achieved. Then, from the result of observation it showed that there was improvement of positive responses in the teaching-learning process of vocabulary through pictures as media and it also showed that the students were motivated in teaching-learning process during the implementation of pictures.
Questioning Strategies in the English Classroom Interaction: An Effort in Improving EFL Learners’ Language Skills
Authors: Hulmayadi Rahman  , Arif Rahman  , Lalu Ari Irawan
Published: June 2024

Questioning strategies provide students with necessary springboards for communication. To encourage the students engagement and thinking in English Language learning, teachers’ need use different types of questioning strategies. Therefore, this research aims to explore the teacher’s questioning Strategies use in the English classroom interactions. The current study was focused on identifying the types of questioning strategies used by the English teachers in the English classroom interaction and finding out the teacher and students’ perception on using questioning strategy in the classroom interaction. This research used descriptive qualitative research. The technique of collecting data used by the researcher was observation and interview towards the English teachers. The instrument of this research are taken field note, transcription, interview and observation note. The results of the study shows that teachers employed several questioning strategies in the classroom, including rephrasing, simplification, repetition, decomposition, and probing. These strategies were used for various purposes based on the functions associated with each strategy. This study further indicates that based on the data interview most of the students agree with the implementation of questioning strategy during teaching and learning process.  Moreover, students believe that the uses of this strategy improve their understanding of the materials and recall the previous English material especially in the beginning of the class. In addition, all of teachers give positive response to use of questioning strategies practice in English class. This is because the questions presented in the class by teachers to students are very important to examine the students understand the material provided.
The Communication Strategies to Avoid Conflicts When Speaking to Sasak Speakers: A Language Style Analysis
Authors: Sugianto  , Tawali
Published: June 2024

Sasak language is a language spoken by mostly whole people who live in Lombok Island, West Nusa Tenggara. As a main media of communication in Lombok, the possibility to get interact with them is wide open since Lombok had become a famous place stayed by various person from all around the world. For the sake of maintaining good relationship with people in Lombok who speak sasaknese, it is crucial to find out what kind of conflicts might happen when communicate to them. Therefore, here is the research aimed at  uncovering the conflicts avoidances utilized by speakers of "Sasak," a language belonging to the Austronesian language family, when they converse in "Sasaknese." The study qualitatively describes how Sasak speakers maintain a good relationship and avoid getting involved into possible conflicts through language style and language used. To ensure the accuracy and validity of the data regarding Sasaknese conflict avoiding styles, some relevant literatures on pertinent issues was extensively reviewed to provide supporting data sources. Data collection and analysis followed three stages of analysis: data reduction, data display, and conclusion drawing and verification. Based on the result of analysis, the study showed that communication strategies applied by Sasak speakers include noble language, Commoner language, and conventional language. Noble language applied formal lexicon, intricate grammatical structures, and deferential speech patterns. The commoner language is used among ordinary people in everyday interactions, including among peers, friends, and family members. It is more casual and relaxed compared to noble language, with simpler vocabulary and grammar. Conventional language refers to rude language and is categorized as low status but it contibutes in avoiding conflict.
Cardiac Arrest during Delivery Revealing a Pheochromocytoma: A Case Report
Authors: Hilia Y. , Lahbabi S. , Elachhab N. , Zemrani H. , Elharfaoui Y. , Chajai S. , Ouadghiri N. , Tachinante R.
Published: June 2024

Pheochromocytoma, a rare catecholamine-secreting tumor during pregnancy, poses significant risks but is curable with timely identification and management. We present a case of a 43 year old nulliparous woman who experienced respiratory distress and cardiorespiratory arrest after delivering a stillborn at 38 weeks gestation. Initially diagnosed with amniotic embolism, her condition worsened, revealing hypertensive crises, hypoxia, and alveolar hemorrhage. Suspicion of pheochromocytoma arose, confirmed by positive urinary catecholamines and imaging. The patient underwent left adrenalectomy, and pathology confirmed a benign pheochromocytoma. The complex diagnostic and therapeutic challenges of managing pheochromocytoma during pregnancy are discussed, emphasizing the need for multidisciplinary care and tailored interventions for optimal maternal and fetal outcomes.
توظيف اللغة العربية في كتابات الطاعنين المعاصرين في السنة النبوية في العصر الحديث نماذج نقدية
Authors: علي مصطفى علي صالح
Published: June 2024

اعتمد كثير من الطاعنين المعاصرين في السنة النبوية على علوم اللغة العربية من أجل إثبات أن كثيرا من الأحاديث النبوية الصحيحة دخلتها الموضوعات والأوهام من قبل الرواة؛ فلا تصح نسبتها إلى النبي صلى الله عليه وسلم على الرغم من تخريجها في أصح كتابين من كتب السنة وهما صحيح البخاري وصحيح مسلم. وقد وظّف هؤلاء دلالات حروف المعاني والدلالة المعجمية للكلمات ومستويات الدلالة والسياق لإثبات أن تلك الأحاديث لا يمكن أن تكون وحيا من الله ولا يمكن أن تصدر عن النبي صلى الله عليه وسلم أفصح من نطق بالضاد ما دامت هذه الأحاديث تخالف الأساليب العربية وقواعدها. وفي هذه الدراسة تم استخراج أبرز المواضع التي تظهر مدى قدرة الطاعنين المعاصرين على فهم المفردات اللغوية ومدى قدرتهم على توظيف قواعد العربية وأساليبها في فهم النص ونقده. وتم اعتماد المنهج التحليلي في نقد كلام الطاعنين؛ وذلك بتفسير النصوص الطاعنة في الأحاديث وتفكيك عباراتها لإدراك حقيقة الطعن وسببه والأساس النظري الذي يقوم عليه، ثم تقويم هذه الطعون بمحاكمتها إلى قواعد علم اللغة العربية لبيان الغث والسمين منها، ونقدها على ضوء قواعد البحث العلمي وشروطه. وبعد الدراسة النقدية لهذه النماذج تبين أن الطاعنين يعتمدون على ثقافتهم اللغوية المتواضعة في فهم النص ونقده؛ لذلك لم يحسنوا فهم النص ولا نقده، وخالفوا في دعواهم اللغة العربية التي يزعمون أنهم يعتمدون عليها في رد الأحاديث الصحيحة.
ASSESSMENT OF TECHNICAL CONDITION OF CONTROL SYSTEMS OF AIR COURT AT INVESTIGATION OF AVIATION INCIDENTS
Authors: Попов Юрий Васильевич , Савилов Виктор Петрович , Крючков Леонид Павлович , Уваров Иван Александрович
Published: June 2024

В статье представлен анализ методов исследования систем управления воздушных судов. Приведена классификация систем управления. Показано, что 23,9% случаев причинами авиационных происшествий являются отказы систем управления воздушных судов. Рекомендована последовательность проведения исследование системы управления. Рассмотрены способы диагностики как механических, так и электродистанционной систем управления, устанавливаемых на самолетах. Разрушения и отказы узлов, деталей и агрегатов систем управления воздушного судна существенно влияют на безопасность полетов. Статья проиллюстрированы примерами проведенных исследований деталей и узлов системы управления. Приведены методы исследования систем управления при расследовании авиационных происшествий. Показано применение методики определения вида технического состояния рулевого привода по зарегистрированной информации бортового устройства регистрации.

The analysis of methods of research of control systems of aircrafts is presented in article. Classification of control systems is given. It is shown that 23,9% of cases are the reasons of aviation incidents refusals of control systems of aircrafts. The sequence of carrying out research of a control system is recommended. Ways of diagnostics both mechanical, and electroremote the control systems installed by planes are considered. Destructions and refusals of knots, details and units of control systems of the aircraft significantly influence safety of flights. Article are illustrated with examples of the conducted researches of details and knots of a control system. Methods of research of control systems at investigation of aviation incidents are given. Application of a technique of definition of a degree of product availability of the steering drive according to the registered information of the onboard device of registration is shown.
A emergência do Ceará Científico anunciada nos textos legais
Authors: Rodrigues Maria Aparecida , Pereira Gandra Lucas , Dos Santos Pastoriza Bruno , Cury Soares Alessandro
Published: June 2024

O objetivo deste estudo é compreender o processo de criação e implementação do Ceará Científico, por meio de uma análise dos textos legais da educação. Trata-se de uma pesquisa com abordagem qualitativa de cunho bibliográfico e documental, que busca responder à questão: Como surgiu o Ceará Científico, quais seus alcances e significado? Os corpus analisados são oriundos da União e do estado do Ceará. Os resultados apontam os marcos legais da educação a favor da pesquisa como garantia e princípio, estimulando a institucionalização de projetos, programas e ações estratégicas no âmbito das políticas educacionais de popularização da ciência, cultura e tecnologia no estado do Ceará. Desses programas e projetos, estruturam-se diferentes estratégias que culminam nos eventos anuais de socialização de resultados de práticas educativas, envolvendo a pesquisa nas diferentes áreas do currículo: O Festival de Talentos (Festal) (2000-2003) e as Feiras Estaduais de Ciências e Cultura , (2007-2015). Além disso, desde  2016, emerge o Ceará Científico.
Abstract
This study aims to understand the process of creating and implementing Ceará Científico through an analysis of legal education texts. qualitative bibliographic and documentary study that seeks to answer the question: How did Ceará Científico come about, what are its scope and meaning? The corpus analyzed comes from the Federal Government and the state of Ceará. The results point to the legal frameworks of education in favour of research as a guarantee and principle, stimulating the institutionalization of projects, programs and strategic actions within the scope of educational policies to popularize science, culture, and technology in the state of Ceará. These programs and projects structure different strategies that culminate in annual events to socialize the results of educational practices, involving research in different areas of the curriculum: The Talent Festival (Festal) (2000-2003) and the State Science and Culture Fairs, (2007-2015). In addition,  since 2016 Ceará Científico has emerged.
Efeito de solução de KCl na germinação de sementes de milheto
Authors: Abud Lidianne Lemes Silva , Guerra Neto Rubens , Lima Vinicius Marca Marcelino de
Published: June 2024

O efeito da solução de Cloreto de potássio na germinação de sementes de milheto é um tema de estudo importante devido à influência do potássio no crescimento e desenvolvimento das plantas. O objetivo do presente trabalho é investigar o efeito de diferentes doses da solução de KCl na germinação de sementes de milheto. O delineamento utilizado foi inteiramente casualizado, com 5 tratamentos e quatro repetições, sendo 0, 25, 50 75 e 100 ml ha-1 respectivamente. Foi utilizado 300 g do Cloreto potássio, sendo feita a diluição em 1 litro de água. As concentrações variadas da solução de KCl exerceram impactos significativos na germinação de sementes de milheto, bem como na altura das plantas e no comprimento das raízes. As concentrações mais elevadas de KCl, como 75 ml ha-1 e 100 ml ha-1, mostraram-se inibitórias, com ausência total de germinação. A dosagem de 25 ml ha-1 exibiu efeitos adversos na germinação e no desenvolvimento das plantas.
Aspectos gerais da gestão ambiental do Parque Zé Bolo Flô: um estudo de caso
Authors: Kassar Borges Gabriel Augusto , Charao Leandro Schwertner , Borges Guilherme Augusto Nogueira
Published: June 2024

O Parque Estadual Zé Bolo Flô está situado em uma região predominantemente do Bioma Cerrado, onde há ocorrência de elementos de fauna e flora ligados ao Pantanal e ao Cerrado, assim como também ao contexto amazônico. Com o aumento da consciência ambiental ampliou-se a participação popular em relação à qualidade social e o meio ambiente. Este trabalho surge com uma proposta de investigar e salientar aspectos importantes relacionados à gestão ambiental do Parque Zé Bolo Flô.
Avaliação da cobertura vacinal contra a COVID-19 em uma instituição de ensino superior privada da cidade de João Pessoa – PB
Authors: Beltrão Gheorgia Victória de Medeiros , Lima Yasmin Souza , Santos Vitória Sued Carvalho , Trigueiro Geicyanna Lins , França Anna Kaline Nascimento de , Silva Gissele Beatriz Pereira da , Vasconcelos Romero Henrique Teixeira , Barros Daniela Bomfim de , Ferreira Rafael Carlos , Sousa Aleson Pereira de
Published: June 2024

As imunizações por meio de vacinas têm, entre seus objetivos, o controle e a erradicação de doenças infecciosas, bem como a prevenção de indivíduos ou grupos de riscos. De acordo com o Programa Nacional de Imunização (PNI), estes grupos incluem profissionais de saúde, segurança e educação. A pandemia do Coronavirus disease 2019 (COVID-19), decretada por meio do estado de Emergência de Saúde Pública de Importância Internacional, pela Organização Mundial de Saúde (OMS), em 2020 teve repercussões e impactos globais. O período foi marcado por alguns movimentos contrários à saúde, como campanhas antivacinas e fake news, fazendo com que seja necessária à amplificação de ações voltadas à conscientização sobre a vacinação e educação em saúde. Considerando que um dos maiores desafios da profilaxia vacinal pode ser a adesão da população a esta medida preventiva, o objetivo deste estudo foi analisar a adesão vacinal contra a COVID-19 na comunidade acadêmica do Centro Universitário Maurício de Nassau João Pessoa no ano de 2023, mediante a formulação de um questionário eletrônico. Os dados foram analisados a partir de estatísticas descritivas e os resultados obtidos ressaltam que, dos 200 participantes, 184 pessoas (92,0%), acreditam na eficácia da vacinação, onde 89 (44,5%) se vacinaram até a 4ª dose, enquanto 41 indivíduos (20,5%) se preocupam com os efeitos colaterais causados pelas vacinas. Assim, os dados representam uma maior diversidade de fatores positivos para adesão às vacinas contra a COVID-19, provocados pela ampliação de campanhas públicas, profissionais de saúde e outras ferramentas de comunicação.
Analisis Kepuasan Pengunjung Terhadap Terapan Visitor Management Di Kawasan Candi Prambanan Dengan Metode Importance Performance Analysis
Authors: Novi Irawati
Published: June 2024

Prambanan Temple also known as Roro Jonggrang Temple is the biggest Hinduism temple in Indonesia. It was built in the 9th century AD. This tourism destination has become one of the most popular tourism destinations with high number visitor visits whether local or foreign. With its large site coverage, visitor management analyzes are needed as one of the most important factors to maximize the visitor number and to minimize the negative impact that can be occurred. The purpose of this research is to determine some indicators of visitor management that affects the visitor satisfaction valuation. The research method is by using importance performance analysis. The valuation result will become the basis of the Prambanan temple sustainable development plan in the future. So that, the satisfaction and memorable value of the visitor would be improved as well as the number of the visitor, and also it can educate the visitor about the heritage conservation value at the same time.
Positive Reinforcement Untuk Meningkatkan Kemampuan Membaca Nyaring
Authors: Dyansatithi Nusareshi , Hasanah Muhimmatul
Published: June 2024

Membaca termasuk kemampuan dasar yang harus dimiliki oleh setiap individu. Dengan kemampuan membaca maka individu dapat mengungkapkan pikiran atau gagasan untuk maksud dan tujuannya. Salah satu kemampuan membaca adalah membaca nyaring. Penelitian ini bertujuan untuk menerapkan teknik penguatan positif untuk meningkatkan kemampuan membaca nyaring menggunakan media flashcard. Subjek dalam penelitian ini adalah anak laki-laki kelas IV SD dengan kemampuan membaca nyaring yang kurang. Metode penelitian yang digunakan adalah kuantitatif dengan pendekatan eksperimen. Desain penelitian yang digunakan adalah Single Suject Research (SSR) dengan subjek tunggal. Teknik pengumpulan data menggunakan observasi dan lembar penilaian indikator membaca nyaring. Analisis data yang digunakan adalah deskriptif kuantitatif berupa analisis grafik. Hasil penelitian menunjukkan adanya pengaruh positif teknik penguatan positif menggunakan media flashcard terhadap kemampuan membaca nyaring yang ditunjukkan dari peningkatan skor dari baseline awal (A1) sebanyak 5 menjadi 8 pada baseline akhir (A2).
From Court-Surrogate to Regulatory Tool: Re-Framing the Empirical Study of Employment Arbitration
Authors: Weidemaier W. Mark
Published: June 2024

A growing body of empirical research explores the use of arbitration to resolve employment disputes, typically by comparing arbitration to litigation using relatively traditional outcome measures: who wins, how much, and how quickly. On the whole, this research suggests that employees fare reasonably well in arbitration. Yet there remain sizeable gaps in our knowledge. This Article explores these gaps with two goals in mind. The first and narrower goal is to explain why it remains exceedingly difficult to assess the relative fairness of arbitration and litigation. The outcome research does not account for a variety of 'filtering" mechanisms that influence the relative merits of the cases adjudicated in each system. This Article explores these filters, focusing on one in particular: most employee grievances are resolved within the workplace through relatively informal procedures. Workplace structures thus filter out most employee grievances before they reach arbitration. This fact has significant implications for efforts to interpret the arbitration outcome research. It also highlights the significance of the workplace as a locus of dispute resolution activity. Indeed, a growing body of research focuses directly on workplace compliance and grievance procedures.

Recognizing the significance of workplace dispute resolution leads to this Article's broader goal. That goal is to expose, and hopefully bridge, an artificial conceptual divide that separates the arbitration research from research into workplace dispute resolution. Many researchers view internal compliance and grievance procedures as a means of harnessing the employer's own regulatory capacity. This conception drives a research agenda that explores the role of workplace structures in generating private norms and in implementing (or subverting) public norms like anti-discrimination. By contrast, the arbitration outcome research conceives of arbitration narrowly as a court surrogate, one that should ideally yield equivalent outcomes at lower cost. Although legitimate to a degree, this conception artificially separates arbitration from other employer-structured disputing procedures and yields an empirical agenda that leaves fundamental questions unanswered. This Article closes by discussing two of these questions: First, do arbitrators play a meaningful regulatory role, either by shaping other arbitrators' practices or by shaping the terms of arbitration contracts? Second, under what circumstances do arbitrators effectively generate and enforce norms?
La Follette's Folly: A Critique of Party Associational Rights in Presidential Nomination Politics
Authors: Martinson Alan
Published: June 2024

Every four years, observers of the presidential nomination season decry the undue influence of those states that hold their primaries first, particularly Iowa and New Hampshire. Currently, Democratic Party rules protect the position of these states. In 2008, two states disregarded party rules in order to move their primaries to a more influential position in the primary season. As punishment for disobeying the rules, the national party diluted the influence of the delegates from these states at the national convention. Legislative solutions to the problems of the current nomination process appear unlikely. Moreover, Supreme Court jurisprudence places no limits on a party's choice to refuse to seat delegates. This Note proposes that the Court evaluate state regulation of parties more seriously with respect to presidential nomination conventions by balancing the burden on the party ' associational rights against the state's interest in regulation.
Lessons from Hurricane Katrina: Prison Emergency Preparedness as a Constitutional Imperative
Authors: Robbins Ira
Published: June 2024

Hurricane Katrina was one of the worst natural disasters ever to strike the United States, in terms of casualties, suffering, and financial cost. Often overlooked among Katrina s victims are the 8,000 inmates who were incarcerated at Orleans Parish Prison (OPP) when Katrina struck. Despite a mandatory evacuation of New Orleans, these men and women, some of whom had been held on charges as insignificant as public intoxication, remained in the jail as the hurricane hit, and endured days of rising, toxic waters, a lack of food and drinking water, and a complete breakdown of order within OPP Wien the inmates were finally evacuated from OPP, they suffered further harm, waiting for days on a highway overpass before being placed in other correctional institutions, where prisoners withstood exposure to the late-summer Louisiana heat and beatings at the hands of guards and other inmates. Finally, even as the prison situation settled down, inmates from the New Orleans criminal justice system were marooned in correctional institutions throughout the state, as the judicial system in New Orleans ceased to function.

The resulting effects were both tragic and unconstitutional, as the suffering at OPP could have been prevented. This Article asserts that prison administrators have a constitutional duty to plan for emergencies, and argues that the failures of New Orleans officials to do so violated prisoners' Sixth and Eighth Amendment rights, as well as internationally recognized human rights standards. With the wealth of training and planning materials available to prison officials and the knowledge of possible emergencies, it is unconscionable for prisons to have nonexistent or inadequate plans. Assessing change through litigation and legislation, this Article advocates a mixed approach, using judicial and legislative remedies for the abhorrent violations of well-established prisoners' rights. The Article recommends that states develop mechanisms, such as emergency courts, to enable the administration of justice to resume promptly following serious natural or man-made disasters. Prisons and courts should internalize the lessons of Hurricane Katrina, which demonstrated the consequences of inadequate preparation and planning for prisoners' safety during and after a major emergency.
Study of direct extrusion with active action of friction forces of powdered porous billet of "glass" type
Authors: Ryabicheva L.A. , Kostrub O.M.
Published: June 2024

The results of a study of direct extrusion of a powdered porous blank of the "glass" type using active friction forces obtained by computer simulation are presented. It is found that the shaping of the porous billet of the "glass" part is influenced by active friction forces that increase the flow of metal in the direction of extrusion, and the presence of back pressure, creating a scheme of an uneven stress state of compression. The relative density of the "glass" blank is obtained equal to the density of the compact material. At the same time, the density difference is 2 %. The stress state is uneven. Hydrostatic compression is the same throughout the annular surface, its is small, which is explained by the large magnitude of the tensile stress component. The scheme of the stressed state with the active action of contact friction and back pressure forces ensures a high density of the billet.
Universal prediction concept of recycled powders contamination in selective laser fusion process
Authors: Evgenov A.G. , Shurtakov S.V. , Galushka I.A.
Published: June 2024

A universal prediction concept of the recycled powders contamination by gas impurities on the basis of the empirical contamination factor and exposure time for each of the complex exposure mode component (sub-mode) is presented. A method of contamination factor determination to estimate the powder contamination proportion by gas impurities depending on the energy density of each exposure mode component is proposed and tested use the example of high-chromium nickel-based VZh159 superalloy. Two methods for calculating of the exposure time of the sum of all 3D model(s) cros-sections are developed and tested. The proposed concept allows predicting the gas impurity content increase in the recycled powder regardless of the parts quantity on the build platform and their geometry. To perform the calculation, it is proposed to consider individual 3D models as the sum of exposure time of all constituent sub-modes on all their layers.
TO COMPARE THE EFFECTIVENESS OF KALTENBORN MOBILIZATION TECHNIQUE VERSUS MULLIGAN' S MWM IN PATIENTS WITH ADHESIVE CAPSULITIS OF SHOULDER
Authors: Babu C. Deepika , M. P. Thenmozhi  , Dhasaradharaman D.Kannan , R.Ferdinand  , S.Kohilavani
Published: June 2024

Background: Adhesive capsulitis (AC) is a condition commonly affecting shoulder with 2% of prevalence, causing insidious pain and restriction of active as well as passive gleno-humeral movement. Both male and female populations were affected; however, there is a tendency towards a higher incidence in female patients. Objective of the study is to compare the effectiveness of kaltenborn mobilization technique versus mulligan’s MWM in patients with adhesive capsulitis. Method: 30 patients were selected between the age group of 40to60 years and having a past history of adhesives capsulitis for one month. 15 patients were allocated to each group of experiment. Group I was given Kaltenborn mobilization and scapular stabilization exercise and Group II was given Mulligan's mobilization and scapular stabilization exercise. Evaluation of the subjects were done using the visual analogue scale(VAS) and shoulder pain and disability index scale (SPADI). Result: Data analysis revealed statistically difference between both groups and proved that kaltenborn mobilization and scapular stabilization exercise is more effective than mulligan mobilization and scapular stabilization exercise in Adhesive capusulitis. Conclusion: This study shows that kaltenborn mobilization and scapular stabilization exercise possess a greater effective over mulligan's mobilization and scapular stabilization exercise in treating patients with adhesive capsulitis.
PROXIMATE COMPOSITION AND ACCEPTABILITY OF CASSAVA-BASED PANCAKE FOR COLLEGE STUDENTS
Authors: Alyssa Tabor Fajardo  , Martina Delos Reyes Peñalber
Published: June 2024

This study is an experimental research about the proximate composition and acceptability of Cassava-Based Pancake. The study was conducted on the S.Y. 2023-2024 at Isabela State University-Main Campus, Food Processing Center, College of Education. The products were subjected to sensory evaluation using the 9-point Hedonic Scale acceptability test in terms of color/appearance, odor/aroma, taste/flavor, texture, and general acceptability. A sensory evaluation was conducted to untrained panel composed of fifty (50) individuals, who were randomly selected from among the students, teachers, and staff of Isabela State University-Main Campus, whose age ranges from 18-60 years old. Result showed that in terms of color/appearance, and odor/aroma T1 obtained the highest degree of acceptability. Of the five treatments, T4 had the highest mean score in terms of taste/flavor and general acceptability, and T3 obtained the highest acceptability in texture. The result on the Acceptability Consumer Index (ACI) revealed that setting aside the T1 (control), T4 (25% Cassava-Based Sagip Nutri-Pack Fortified with Cacao Pod Husk (CPH), Malunggay, and Turmeric Powder) got the highest rank among the treatment. The treatments were subjected to nutrient analysis which includes the amount of crude protein, crude fiber, crude fat, moisture, and ash. The reports of analysis show that T2 had the highest percentage in Crude Protein, Crude Fat, and Ash. T5 had the highest Crude fiber content while T4 had the highest Moisture content. The Return-on-Investment per production of the product shows that T1 achieved the highest percentage followed by T4, T3, T2, and T5.
KEYWORDS: Acceptability, Decent Work and Economic Growth, Pancake, Sagip, Zero Hunger