bluuebunny/crossref_metadata_2025 huggingface dataset:
Energy-Aware Predictive Control for the Battery Thermal Management System of an Autonomous Off-Road Vehicle
Authors: Sundar Anirudh , Ghate Atharva , Zhu Qilun , Prucka Robert , Korivi Vamshi , Ruan Yeefeng
Published: April 2024

Off-road vehicles are increasingly adopting hybrid and electric powertrains for improved mobility, range, and energy efficiency. However, their cooling systems consume a significant amount of energy, affecting the vehicle’s operating range. This study develops a predictive controller for the battery thermal management system in an autonomous electric tracked off-road vehicle. By analyzing the system dynamics, the controller determines the optimal preview horizon and controller timestep. Sensitivity analysis is conducted to evaluate temperature tracking and energy consumption. Compared to an optimal controller without preview, the predictive controller reduces energy consumption by 55%. Additionally, a relationship between cooling system energy consumption and battery size is established. The impact of the preview horizon on energy consumption is examined, and a tradeoff between computational cost and optimality is identified. The findings at the system level are also shown to be applicable at the vehicle level.
Heat Dissipation Performance Analysis of Liquid-Cooled Plate in Battery Package System
Authors: Li Ze-Hui , Chen Zhen-Hai , Zhou Fu-Peng , Zhao Xue-Zhi , Shangguan Wen-Bin
Published: April 2024

A liquid-cooled plate is an important component for cooling batteries inside a battery package system. The structure of the liquid-cooling plate significantly affects the temperature conditions of power batteries and the energy consumption of the liquid-cooling system. However, there is a lack of precise knowledge regarding the specific factors that contribute to these impacts. In this study, the influence of structural parameters of flow channel on the heat dissipation performance is studied to solve above problems. A test bench for measuring battery pack cooling performances was built, and pressure drop of liquid-cooled plate and maximum temperature of battery were measured. A CFD model for liquid-cooled plate performance calculations was developed. Using the established model, pressure drop, and maximum temperature were calculated. The measured data are compared with the calculated date, which validate the proposed model. Using DOE with 3-factors 3-levels and using Analysis of Variance, the factors for influencing ‘S’-shaped liquid-cooled plate heat dissipation performance were analyzed. Prioritize the temperature characteristics of the liquid-cooled plate to get the best parameter combinations. Using the best parameter combinations of A3B1C3, a new liquid-cooled plate is designed. Under different discharge rates and inlet flow rates, the heat dissipation performance of initial liquid-cooled plate and the new designed liquid-cooled plate is compared. The calculation results show that the volume of channel and the length of channel have a great influence on the flow resistance. The length of the channel has a great influence on temperature uniformity. The length and the aspect ratio of channel have a great influence on the heat dissipation capacity. Compared with the initial liquid-cooled plate, although the flow resistance of the new liquid-cooled plate is greater resulting in more energy consumption, the temperature uniformity and heat dissipation capacity are improved, under different discharge rates and inlet flow rates. This study serves as a valuable reference for designing liquid-cooled plates.
Research on the Oscillation Reduction Control During Gearshift in Hybrid Electric Vehicles
Authors: Jing Junchao , Zhang Junzhi , Liu Yiqiang , Huang Weishan , Dai Zhengxing
Published: April 2024

In order to realize the shift control of dual-motor hybrid electric vehicle (HEV), a non-power interruption shift control method based on three-power source coordination control was proposed by analyzing the shift process of dual-motor hybrid configuration. The shift control process was divided into three stages: oil-filling self-learning stage, torque exchange stage and inertia control stage. In the torque exchange stage, the characteristics of the speed stage and torque stage were analyzed, which was different from the traditional method's dependence on pressure sensor, longitudinal acceleration sensor and engine torque accuracy. A shift clutch gain self-learning strategy based on shift time and input shaft speed soaring problem was proposed. In the shift process, the parameters were adjusted by self-learning, and the shift time after learning could gradually approach the set target value, and the input shaft speed soaring phenomenon could be gradually eliminated, and the shift quality was significantly improved, which ensured the consistency of shift quality after different vehicles, different engines and different transmissions were integrated, as well as the consistency of driving performance of the vehicle in the product life cycle. In the inertia control stage, The torque intervention strategy has been used in this paper to shorten the inertia phase time to meet the driver's intention quickly. The results show that the time of inertial phase can be greatly shorten by the intervention control of shifting inertial phase and the adaptive method in this paper can effectively detect the shift time too long or too short and flare shift anomalies during the shift process.
Machine Learning Approach for Open Circuit Fault Detection and Localization in EV Motor Drive Systems
Authors: Arsalan Ali , Papari Behnaz , Rahman S M Imrat , Timilsina Laxman , Moghassemi Ali , Muriithi Grace , Ozkan Gokhan , Edrington Christopher , Buraimoh Elutunji
Published: April 2024

Semiconductor devices in electric vehicle (EV) motor drive systems are considered the most fragile components with a high occurrence rate for open circuit fault (OCF). Various signal-based and model-based methods with explicit mathematical models have been previously published for OCF diagnosis. However, this proposed work presents a model-free machine learning (ML) approach for a single-switch OCF detection and localization (DaL) for a two-level, three-phase inverter. Compared to already available ML models with complex feature extraction methods in the literature, a new and simple way to extract OCF feature data with sufficient classification accuracy is proposed. In this regard, the inherent property of active thermal management (ATM) based model predictive control (MPC) to quantify the conduction losses for each semiconductor device in a power converter is integrated with an ML network. This recurrent neural network (RNN)-based ML model as a multiclass classifier localizes the faulty switch based on the dynamics associated with conduction losses as reliable and feature-rich data. The presented approach utilizes the controller data with no additional computational load to compute the feed-in data for the ML model and no extra hardware requirements. The proposed data-driven approach, with an accuracy of 99% for distinct hyperparameters and testing datasets, proves to be a promising solution for OCF DaL.
From Idle to 7.5 Bar IMEPg – Using Fuel Stratification to Control LTGC with Next-Cycle Capability
Authors: Lopez Pintor Dario , MacDonald James , Lee Sanguk
Published: April 2024

Low-temperature gasoline combustion (LTGC) engines can provide high efficiencies with very low NOx and soot emissions, but rapid control of the combustion timing remains a challenge. Partial Fuel Stratification (PFS) was demonstrated to be an effective approach to control combustion in LTGC engines. PFS is produced by a double-direct injection (DI) strategy with most of the fuel injected early in the cycle and the remainder of the fuel supplied by a second injection at a variable time during the compression stroke to vary the amount of stratification. Adjusting the stratification changes the combustion phasing, and this can be done on cycle-to-cycle basis by adjusting the injection timing.

In this paper, the ability of PFS to control the combustion during wide engine load sweeps is assessed for regular gasoline and gasoline doped with 2-ethylhexyl nitrate (EHN). For PFS, the load control range is limited by combustion instability and poor combustion efficiency at low loads. However, late single-DI stratification was demonstrated to allow robust control at low loads with good combustion efficiency by concentrating the fuel in the middle of the chamber, avoiding overly lean regions. Stratification is more effective with EHN-doped gasoline than with straight gasoline because EHN enhances the reactivity and φ–sensitivity of the fuel. Thus, lower intake temperatures and less stratification are required when working with EHN-doped gasoline. The combination of PFS at higher loads and late single-DI at lower loads allows load control ranges from 1.0 to 4.8 bar IMEPg using regular gasoline and from idle to 5.6 bar IMEPg using EHN-doped gasoline at naturally aspirated conditions. Combustion control using only stratification is also demonstrated at boosted conditions, allowing the IMEPg to be varied from idle to 7.5 bar by combining two boost levels (1.3 and 1.0 bar intake) and two EHN flow levels.
Cylinder Head Insulation Plate, Design, Analysis and Testing for an Extreme High Efficiency Internal Combustion Engine
Authors: Ortolani Paolo , Evans Katie , Treccarichi Fabrizio
Published: April 2024

The main objective of this paper is to describe the design, analysis and testing of a novel method of insulating the combustion chamber, which is key for efficiency demonstration on a new class of internal combustion engine (ICE). A recuperated split cycle engine (RSCE) has unique demands for heat loss reduction. In particular during the combustion event, to minimize the heat losses is a must to achieve high efficiency.

The insulation is provided by a metal plate that is assembled into the cylinder head to line the combustion chamber surface. The design has been focused on reducing heat transfer surface area and exploiting contact gap thermal resistance between the upper surface of the plate and the cylinder head, thus reducing heat wasted to the coolant circuit.

In this paper, the plate requirements, functions, design, analysis and test results from a research and development (R&D) program of a heavy duty (HD) recuperated split cycle engine are reported. This includes novelties in plate design, technology and the materials used. This work is based on requirements, hypotheses and problem simplifications, supported by virtual validation, FEM analyses, spreadsheet calculations, component specifications and 1D simulations. Development has also been done by suppliers to satisfy the project requirements, alongside a compromise between technology selection and the pressing need to respect an extremely short time frame for component procurement.

Summary and conclusions are drawn from; test results, particularly in comparison with parallel testing of ceramic coatings, suitability for hydrogen combustion, and further development and potential implementation on existing cylinder heads.
A Deviation-Based Centroid Displacement Method for Combustion Parameters Acquisition
Authors: Wei Zengchun , Yao Zhuoxiao , Su Qingpeng , Lian Xuetong , Zhao Hua
Published: April 2024

The absence of combustion information continues to be one of the key obstacles to the intelligent development of engines. Currently, the cost of integrating cylinder pressure sensors remains too high, prompting attention to methods for extracting combustion information from existing sensing data. Mean-value combustion models for engines are unable to capture changes of combustion parameters. Furthermore, the methods of reconstructing combustion information using sensor signals mainly depend on the working state of the sensors, and the reliability of reconstructed values is directly influenced by sensor malfunctions. Due to the concentration of operating conditions of hybrid vehicles, the reliability of priori calibration map has increased. Therefore, a combustion information reconstruction method based on priori calibration information and the fused feature deviations of existing sensing signals is proposed and named the "Deviation-based Centroid Displacement Method" (DCDM). The method based on priori calibration information, extract features of crankshaft transient angular velocity and knock signals. Using the parameter identification method, it acquires transient values of combustion parameters reconstructed based on various signal features. The fused deviation between transient values and calibration values is calculated using the Kalman filter and employed to adjust the priori values, realizing the computation of transient combustion parameters. A test platform for reconstructing combustion information is established in conjunction with an engine bench. The DCDM model is verified under 11 operating conditions, with the maximum error between the CA10, CA50 and CA90 computed by the DCDM model and experimental values being less than 2 °CA and the average error being less than 1 °CA, indicating high accuracy of the model. The Minkowski distance is less than 0.7, and the model distance is less than 0.3, demonstrating a good real-time performance and consistency of changes.
RIO-Vehicle: A Tightly-Coupled Vehicle Dynamics Extension of 4D Radar Inertial Odometry
Authors: Zhu Jiaqi , Zhuo Guirong , Xiong Lu , zihang he , Leng Bo
Published: April 2024

Accurate and reliable localization in GNSS-denied environments is critical for autonomous driving. Nevertheless, LiDAR-based and camera-based methods are easily affected by adverse weather conditions such as rain, snow, and fog. The 4D Radar with all-weather performance and high resolution has attracted more interest. Currently, there are few localization algorithms based on 4D Radar, so there is an urgent need to develop reliable and accurate positioning solutions. This paper introduces RIO-Vehicle, a novel tightly coupled 4D Radar/IMU/vehicle dynamics within the factor graph framework. RIO-Vehicle aims to achieve reliable and accurate vehicle state estimation, encompassing position, velocity, and attitude. To enhance the accuracy of relative constraints, we introduce a new integrated IMU/Dynamics pre-integration model that combines a 2D vehicle dynamics model with a 3D kinematics model. Then, we employ a dynamic object removal process to filter out dynamic points from a single 4D Radar scan and perform scan-to-scan matching to obtain 4D Radar odometry. Furthermore, we introduce ground plane constraints to eliminate vertical error drift. In the backend, we add the IMU/Dynamics factor, ground plane factor, and 4D Radar odometry factor to the factor graph and obtain estimation results through sliding window-based optimization. Real-vehicle experiments confirm the reliability and accuracy of our proposed method.
Springback Control through Post-stretching Using Different Hybrid Bead Designs with Tonnage Consideration
Authors: Nazari Sobhan T. , Zhu Feng , Makrygiannis John , Zhang Jimmy , Wang Yu-Wei
Published: April 2024

Multiple hybrid bead designs were investigated in this study to control the springback on DP780 samples using post-stretching technique. The performance of the four different hybrid bead designs was evaluated by measuring the minimum blank-lock tonnage required to control the springback during a U-channel stamping process. A finite element (FE) model of the U-channel stamping process was developed to simulate the process and predict the minimum blank-lock tonnage required for springback control using each of the hybrid bead designs. It is shown that the developed FE model predicts both the required minimum blank-lock tonnage for post-stretching, and the springback profile, with good accuracy.
AI-based EV Range Prediction with Personalization in the Vast Vehicle Data
Authors: Joo Kihyung , kim Lina
Published: April 2024

It is an important factor in electric vehicles to show customers how much they can drive with the energy of the remaining battery. If the remaining mileage is not accurate, electric vehicle drivers will have no choice but have to feel anxious about the mileage. Additionally, the potential customers have range anxiety when they consider Electric Vehicles. If the remaining mileage to drive is wrong, drivers may not be able to get to the charging station and may not be able to drive because the battery runs out. It is important to show the remaining available driving range exactly for drivers. The previous study proposed an advanced model by predicting the remaining mileage based on actual driving data and based on reflecting the pattern of customers who drive regularly. The Bayesian linear regression model was right model in previous study. In addition, in order to improve performance, the driver's regular driving pattern is recognized in advance before driving and it is reflected in the remaining driving mileage model with Bayesian regression. It could be seen that the performance of the model in previous study was improved 10% better compared to the remaining driving mileage existed in vehicle function. The purpose of this study confirms the robust performance with vast data of the more vehicles in long mileage. The big data are from that almost vehicles took drive for 10k mile range. The vehicles had various experience in location, driving time rage, mileages, driving pattern, charge pattern, and so on. Moreover, the personalized model gets improved in big data to get higher accuracy. This study proposes personalized algorithm enable to embed in vehicles.
Signal Control of Urban Expressway Ramp Based on Reinforcement Learning
Authors: Ouyang Chen , Zhan Zhenfei , Qian Liuzhu , Zou Jie
Published: April 2024

With economic development and the increasing number of vehicles in cities, urban transport systems have become an important issue in urban development. Efficient traffic signal control is a key part of achieving intelligent transport. Reinforcement learning methods show great potential in solving complex traffic signal control problems with multidimensional states and actions. Most of the existing work has applied reinforcement learning algorithms to intelligently control traffic signals. In this paper, we investigate the agent-based reinforcement learning approach for the intelligent control of ramp entrances and exits of urban arterial roads, and propose the Proximal Policy Optimization (PPO) algorithm for traffic signal control. We compare the method controlled by the improved PPO algorithm with the no-control method. The simulation experiments used the open-source simulator SUMO, and the results showed that the reinforcement learning control ramp technique increases the average speed by 7% and reduces the lane occupancy rate by 15% compared to the no-control method, which proves the effectiveness of the proposed method.
Analysis of the Event Data Recorder (EDR) Function of a GM Active Safety Control Module (EOCM3 LC)
Authors: Bare Cleve , Skiera Jason , Smyth Brian , Beetham Tommy , Floyd Donald , Koo Winston , Newell Devin
Published: April 2024

The Advanced Driver Assistance System (ADAS) is a comprehensive feature set designed to aid a driver in avoiding or reducing the severity of collisions while operating the vehicle within specified conditions. In General Motors (GM) vehicles, the primary controller for the ADAS is the Active Safety Control Module (ASCM). In the 2013 model year, GM introduced an ASCM utilizing the GM internal nomenclature of External Object Calculation Module (EOCM) in some of their vehicles produced for the North American market. Similar to the Sensing and Diagnostic Module (SDM) utilized in the restraints system, the EOCM3 LC contains an Event Data Recorder (EDR) function to capture and record information surrounding certain ADAS or Supplemental Inflatable Restraint (SIR) events. The ASCM EDR contains information from external object sensors, various chassis and powertrain control modules, and internally calculated data. This event data includes date and time, GPS location, driver inputs and vehicle responses, and information regarding ADAS objects of interest.

This paper addresses the operation and accuracy of the EDR data recorded by an ASCM, specifically the GM EOCM3 LC, and its utilization of the GM Vehicle Intelligence Platform (VIP) inter-module serial communication bus.

A series of vehicle Automatic Emergency Braking (AEB) test maneuvers were conducted, triggering the ASCM EDR function. The vehicle dynamic state was independently monitored and recorded by onboard instrumentation and compared to the ASCM recorded data. Evaluation of these data provides a better understanding of the accuracy and timing of this event data recorded by the General Motors' ASCM.
The Role of Bromelain and Papain Proteolytic Potential Binding to Crystalline P23T Γd Protein in Congenital Cataracts
Authors:   Ophthalmology Department of Medical Faculty Jember University, Indonesia, Cahyana Nugraha Wahyu
Published: April 2024

Background: Congenital cataracts can cause permanent vision loss. The etiology of congenital cataracts varies widely. The exact etiology can’t be identified, but usually there an autosomal dominant inheritance. Objective: To assess the proteolytic potential of Bromelain and Papain enzymes against Crystalline P23T γD. Methods: This study is a pre-experimental study with a computer-based one shot case study approach. Papain enzyme data using 9PAP code and bromelain enzyme data using 1BI6 were obtained from the National Center of Biotechnology Information database (NCBI: www.ncbi.nlm.nih.gov/). Assessment of the proteolytic potential of Bromelain and Papain enzymes against Crystalline P23T D data using 2KFB code cluspro www.cluspro.bu.edu/home.php and data analysis. Results: The binding affinity of bromelain is -735.1 KCal/Mol and papain is -730.4 KCal/Mol. Conclusion: The bromelain enzyme has a lower binding affinity value than the papain enzyme, so it has the ability to form stable bond to the crystalline P23T D protein better than papain enzyme.
Macroeconomics Determinants of Interest Rate Spreads Among Commercial Banks in Kenya
Authors:   Department of Economics, Moi University, 2024, Alim Liban Muhudin , Onyango James ,   Department of Economics, Moi University, 2024
Published: April 2024

The determination of interest rate spread in commercial banks is influenced by various macroeconomic variables, market microstructure features and the policy environment. However, studies on factors that contribute to the interest rate spreads among commercial banks in Kenya have produced mixed results that calls for further research. This study aimed to assess the determinants of interest rate spread in commercial banks in Kenya. Specifically, the study sought to establish the effect of inflation rate, domestic borrowing, credit risk and exchange rate risk on the interest rate spreads among commercial banks in Kenya. The study was anchored on fisher hypothesis, classical theory of interest and loanable fund theories. Explanatory research design was adopted to establish the causal relationship between the study’s variables. Secondary data of the study for the period between 1970 -2022 was extracted from annual financial statements of commercial banks targeted by the study and Central bank of Kenya annual reports. Data was analyzed through descriptive and inferential statistics. The study adopted the regression model to obtain results. Based on the regression results, the study found that domestic borrowing had a significant positive effect on interest rate spreads among commercial banks in Kenya. Additionally, the study found that inflation rate, credit risk and exchange rate risk had a significant positive effect on interest rate spreads among commercial banks in Kenya. The study concluded that macroeconomic variables such as inflation rate, domestic borrowing, credit risk and exchange rate risks are key determinants of interest rate spread among commercial banks in Kenya. The study made the following recommendations to regulators and policy makers. First, ensure that the central bank's monetary policy actions effectively influence interest rates throughout the banking system and also Implement mechanisms to improve the transmission of changes in the central bank's policy rates to commercial banks' lending and deposit rates. Secondly, establish a framework for monitoring key macroeconomic indicators such as inflation, economic growth, exchange rates, and fiscal policies to identify potential factors impacting interest rate spreads and use the monitoring results to formulate timely and appropriate policy responses. The study recommends that future studies should conduct studies across different countries which could provide a more comprehensive understanding of the subject matter.
“We could perform much better if we had specific training for girls” – Impacts of the embodiment of tradition for elite-level karateka women
Authors: Turelli Fabiana Cristina , Kirk David , Vaz Alexandre Fernandez
Published: April 2024

Despite several struggles to achieve equality in society, a fight embraced first and foremost by feminist movements, women remain being seen, addressed, and treated as other in sport. Women who practice martial arts and combat sports to some extent disrupt the normative social and sportive order. But to be able to remain in environments where their presence is challenging, they are also challenged in their disruptive acting. They end up embodying the internal dynamics of dojos, adapting to and often reproducing the traditional teachings that discipline practitioners. It is not enough to became equal. Some athletes who can be reflexive and critical of their experiences may start a movement of raising their voices to advocate for equity instead of, or in combination with equality. We carried out a study with the Spanish women’s squad in preparation to attend the unique, to date, Olympic Games that karate was included into, Tokyo 2020 (2021), seeking to understand how they were subjectively dealing with overlapping issues that compose karate. In this paper, we focus on the gendered embodiment that women high-level athletes make of the so-called tradition in their practice of karate and how they reproduce or oppose to such tradition. Their possible resistance is configured as a claim for transformation of the environment through equity and respect for their own fighters’ and personal features, however, the process is challenging. They may reproduce and continue the stream of tradition; face personal confusion in trying to understand the contradictions of resisting domination and just remain in the team or as karateka; they still can be challenged by being named traitors and be conflicted with feminist positionalities; and yet some seem to start a movement of new internal disruption, making it loud that women are ignored, and posing a claim for more women in sport, showing that change has not been achieved enough.
Key words: gender, equity, challenges, change, social justice.
Unpacking Technostress: A Systematic Review on its Effects and Mitigation
Authors: Kupang Genevieve Balance , Ballangan Maribel G. , Carantes Ferdinand T. , Yanes Jr. Pablito S.
Published: April 2024

The exponential growth of technology in everyday life has given rise to technostress, a condition marked by negative psychological and physiological effects. This systematic review synthesizes current research on technostress, examining its global definition, regional variations, impacts, opportunities and mitigation strategies. Drawing on established theories such as the Technostress Model, Job Demands-Resources Model, and Person-Environment Fit Model, the review explores the complex interplay between technology use and stress. The technostress model posits that technostress arises from negative reactions to technology use, fueled by information overload, task demands, and lack of control. The job demands-resource model views technology as either a stressor or a resource, impacting well-being based on organizational context and individual traits, while the person-environment fit model links technostress to capability-demand mismatches. Studies link technostress to anxiety, depression, and physical health problems. The review underscores the importance of tailored interventions, emphasizing organizational support, user-centered design, and individual coping mechanisms in managing technostress, especially in regions with high prevalence rates. In addition to these interventions, the review emphasizes the need for ongoing education and awareness campaigns to promote digital literacy and healthy technology habits. By equipping individuals with the knowledge and skills to navigate the complexities of the digital landscape, these initiatives can empower them to make informed decisions and effectively manage technostress in their daily lives. Highlighting the significance of culturally-tailored interventions, future research aims to refine mitigation strategies and investigate the potential benefits of technology use, ultimately fostering a balanced relationship with technology to minimize drawbacks and maximize advantages.
The Influence of Internal Corporate Social Responsibility Factors on the Innovation Climate of Employees in the Healthcare Industry
Authors: Younas Asifa
Published: April 2024

This study examined the relationship between employee innovation and employee-initiated corporate social responsibility (CSR) elements in medical diagnostic enterprises in Pakistan during the coronavirus disease 2019 pandemic. The research identified nine variables of employee-driven CSR, including communication, empowerment, and work satisfaction. The theoretical framework of the study was based on the theory of CSR and the expectancy theory of motivation. It evaluated their effects on the atmosphere for employee innovation using statistical analysis by using Statistical Package for the Social Sciences and after collecting data by using a survey questionnaire. The study population was employees working in the healthcare industry in Pakistan. The findings showed that employee-driven CSR and innovation were significantly correlated, with work satisfaction having the most impact. Overall, this quantitative study provides important insights for both theoretical understanding and practical application in fostering innovation through CSR initiatives. It emphasizes the critical role of job satisfaction as a key motivating factor for innovation within the framework of employee-driven CSR in the medical diagnostic sector.
 
Received: 12 December 2023 | Revised: 4 March 2024 | Accepted: 1 April 2024
 
Conflicts of Interest
The author declares that he has no conflicts of interest to this work.
 
Data Availability Statement
The data that support this work are available upon reasonable request to the corresponding author.
relevância da teoria de derrotabilidade da norma jurídica na análise das exceções imprevisíveis
Authors: Miranda Ana Valéria de Jesus Ribeiro , Santos Cinthya Amaral , Fleury João Felipe da Silva
Published: April 2024

Esse artigo tem como tema principal a solução de conflitos, seus princípios e a teoria da derrotabilidade da norma envolvida na mediação e conciliação. Através da pesquisa bibliográfica buscou-se entender o como como a teoria acima citada pode ser utilizada pelo intérprete do direito, em caso de resoluções pacíficas das lides. Ao longo do desenvolvimento do estudo considerou-se a possibilidade de aplicação direta desse princípio da derrotabilidade quanto ao surgimento de exceções das regras referentes a solução de conflitos presentes no Código de Processo Civil, o que afastaria a obrigatoriedade da mesma. Foram utilizados os mais renomados doutrinadores, entre nacionais e estrangeiros que tratam do assunto em questão. Entre os internacionais, destaca-se Hart, que idealizou a derrotabilidade, especificando que pode deixar de ser aplicada em determinados casos concretos, que sejam exceções a norma considerada. Ao concluir o presente trabalho buscou-se verificar de forma sucinta e breve, se há compatibilidade entre essa teoria e a mediação e conciliação, inclusive com amostragem de algumas decisões judiciais referentes ao assunto proposto. Assim se percebeu que há possibilidade de utilização para afastar o uso dos meios de solução de conflitos, mesmo que sejam considerados instrumentos hábeis para resolver inúmeros casos
PERFIL EPIDEMIOLÓGICO DO TRAUMA CRANIOENCEFÁLICO NA REGIÃO SUL DO BRASIL
Authors: Koerich Amanda Hedel , Volino Giovanni Cândido , Vicari Gustavo Batistella
Published: April 2024

Introdução: O trauma cranioencefálico (TCE) é definido como qualquer agressão externa que acarrete lesão anatômica ou funcional do crânio, das meninges ou do encéfalo, classificado em leve, moderado ou grave de acordo com a Escala de Coma de Glasgow. Apesar de o TCE demonstrar incidência e taxas de mortalidade elevadas no Brasil, estudos de caráter epidemiológico, sobretudo que abordem especificidades regionais acerca do tema, ainda se mostram escassos. Metodologia: A presente investigação tem como objetivo traçar o perfil epidemiológico do TCE na Região Sul do Brasil nos últimos cinco anos por meio de uma comparação entre seus estados. Trata-se de um estudo transversal e descritivo que utiliza dados do Sistema de Informações Hospitalares do SUS, abrangendo os estados do Rio Grande do Sul, Santa Catarina e Paraná de outubro de 2018 a outubro de 2023. Variáveis incluíram sexo e faixa etária. Além disso, a taxa de mortalidade, média de permanência hospitalar e valores gastos no período decorrentes da patologia também foram alvos da pesquisa. Resultados: O estado do Paraná evidenciou o maior impacto na Região Sul em termos absolutos, registrando 49.288 internações hospitalares e 3.075 óbitos por TCE. Analisando a distribuição por gênero, os indivíduos do sexo masculino apresentaram os maiores percentuais de hospitalizações e óbitos, com 35.474 (72%) e 2.395 (78%), respectivamente. No que se refere à faixa etária, observou-se que sujeitos com idade entre 20 e 29 anos foram os mais frequentemente internados, totalizando 7.305 admissões (15%). Entretanto, em relação aos óbitos, a faixa etária de 80 anos ou mais foi a mais afetada, registrando 514 (17%) notificações. Conclusão: O perfil epidemiológico frequentemente acometido por TCE é composto por indivíduos do sexo masculino entre 20 e 29 anos, seguidos pela faixa etária de 50 a 59 anos. Ainda, o estado do Paraná evidenciou o maior número absoluto de internações e a menor taxa de mortalidade da Região Sul; já o estado do Rio Grande do Sul apresentou as maiores taxas de hospitalização por habitante e mortalidade por TCE da região. Por fim, faz-se necessária uma atenção direcionada a esses grupos.
Impacto de condiciones familiares en las medidas antropométricas y la dieta de niños de primaria durante la pandemia: un estudio en una institución educativa en Perú
Authors: Cerna-Montoya José Estanislao
Published: April 2024

La evolución de los seres humanos se ve moldeada por su entorno, siendo la familia la entidad primordial con una identidad y características que influyen de manera fundamental en cada miembro. Este impacto es particularmente notable en los niños de primaria, quienes están directamente vinculados a las condiciones de vida familiares, donde la calidad nutricional constituye elemento condicionante en sus medidas antropométricas. En estas características, indagamos sobre la relación entre las condiciones familiares, las medidas antropométricas y la dieta alimentaria de niños pertenecientes a la Institución Educativa Los Constructores del Saber durante la pandemia en 2020. El objetivo trascendental fue examinar la conexión entre estos elementos, abordando aspectos económicos, sociales, culturales y educativos. 90 estudiantes se emplearon en la pesquisa, dentro de lo descriptivo correlacional, identificando condiciones familiares, analizando medidas antropométricas y explorando la dieta alimentaria y contrariamente a las expectativas, no hubo una relación significativa entre las variables, evidenciando una relación medianamente comprometida entre una y otra variable.
Palabras clave: Alimentación, antropometría, escolares y familia
MÍNIMO EXISTENCIAL E RESERVA DO POSSÍVEL
Authors: Oliveira Neto Nery Batista de
Published: April 2024

This article sought to discuss the control of constitutionality in financial and budgetary terms, highlighting the applicability of constitutional principles and nuances. The correct allocation of resources that flow into fundamental rights, linked to the existential minimum, are only possible when the objectives proposed by the Public Power are developed in accordance with the constitutional plan. This study had as general objective to discuss the reserve of the possible and minimum existential with emphasis on constitutionality control and social inclusion under the financial/budgetary perspective. The methodology used was a literature review, which searched for material databases already published on the subject. Thus, this study concludes by making clear the importance of the theme and suggesting that more research should be done in order to go deeper into the subject.
AS VISITAS DOS AGENTES DE ENDEMIAS DURANTE A PANDEMIA DA COVID-19 NO MUNICÍPIO DE SANTANA DO IPANEMA- AL
Authors: França Sebastião da Rocha , Costa Loane Márzia Lopes
Published: April 2024

The focus of this study is to address the new forms and work habits of Endemic Agents in the municipality of Santana do Ipanema, located in the hinterland of Alagoano. The main objective of this study was to register the difficulties that agents of endemic diseases faced during visits during the covid-19 pandemic period. Addressing the visits of endemic agents during the covid-19 pandemic in the municipality and Santana do Ipanema-AL, it is justified because this is a current issue, which involves public health, control, and combat of endemic diseases. The present study consists of applied research, of an exploratory nature, with results treated in a qualitative and quantitative way, bringing together a literature review based on academic productions and content published by experts, for secondary data collection and surveys to support the theoretical framework, and a survey of primary data that was done through a semi-structured questionnaire, elaborated through Google Forms, and made available to the target audience. With the gathering of information throughout the research and analysis of the information, it was possible to conclude that during the Covid-19 pandemic, new challenges appeared during the routine and work of Endemic Agents, changing daily habits and adhering to prevention measures against Covid-19, preserving their health and that of the residents of the homes visited.
Level of digital competencies in students of Information and Communication Technologies (ICT) at an Ecuadorian university
Authors: Rentería Macías Henry
Published: April 2024

The present research consists of an exploratory study on student digital competencies. The objective is to analyze the level in its five areas: information, communication, content creation, security and problem solving, in students of the subject 'Computer Projects' of the ninth cycle of the systems engineering career of the Technical University "Luis Vargas Torres" of Esmeraldas. The research had a quantitative approach, with a non-experimental design and two intact groups. As an instrument, a test called "Ikanos", for testing digital competencies of universal character and validated in university students in Europe and Latin America. The results showed that the two groups are not equivalent and have an Intermediate level. This indicated that, despite being students of the ICT career, they could not be placed mostly in Advanced and Expert level. It is concluded about the need to include the development of digital competence as a fundamental element throughout the academic curriculum, from the beginning of the career of Information and Communication Technologies of UTLVTE, implementing strategies, from the first academic cycle, in the career.
Comparative outcome of single versus two double-pigtail stents for endoscopic drainage of pancreatic fluid collections with minimal necrosis: a retrospective analysis
Authors: Giri S , Bhrugumalla S , Gangadhar S , Angadi S
Published: April 2024

Background: Endoscopic ultrasound (EUS)-guided cystogastrostomy is the treatment of choice for managing symptomatic pancreatic fluid collections (PFC). However, studies on the number of stents for optimal drainage of PFCs are limited. Hence, the present study was conducted to compare the outcome of single versus two double-pigtail stents for endoscopic drainage of PFCs.

Methods: This is a single-center, retrospective analysis of patients undergoing endoscopic drainage of PFCs with minimal necrosis (pseudocyst or walled-off necrosis with <30% solid content) at a tertiary center in South India from October 2020 to October 2022. Post-procedure, patients were followed up for clinical improvement, and stents were removed after documentation of cyst size reduction on imaging.

Results: Sixty-three patients (82.5% males, median age: 34 years) fulfilling the selection criteria were included. For single stent placement (n = 47), stents of size 8.5 Fr or 10 Fr were used, while for placement of two stents (n = 16), 7 Fr stents were used. The technical success rate was 100%. Intraprocedural and early postprocedural adverse events (all mild to moderate) were comparable between the groups (17.0% with single stent vs. 25.0% with two stents, p = NS). Clinical success was achieved in 93.6% of patients, with no difference between both groups. Three patients in the single stent group required additional procedures. All patients underwent successful stent removal after a median follow-up of 14 weeks. Conclusion: A single pigtail stent of 8.5 Fr or 10 Fr size for EUSguided cystogastrostomy provides efficacy and safety similar to that of two stents.

Conclusion: A single pigtail stent of 8.5 Fr or 10 Fr size for EUSguided cystogastrostomy provides efficacy and safety similar to that of two stents.
Reanalysis of NOAA H2 observations: implications for the H2 budget
Authors: Paulot Fabien , Pétron Gabrielle , Crotwell Andrew M. , Bertagni Matteo B.
Published: April 2024

Abstract. Hydrogen (H2) is a promising low-carbon alternative to fossil fuels for many applications. However, significant gaps in our understanding of the atmospheric H2 budget limit our ability to predict the impacts of greater H2 usage. Here we use NOAA H2 dry air mole fraction observations from air samples collected from ground-based and ship platforms during 2010–2019 to evaluate the representation of H2 in the NOAA GFDL-AM4.1 atmospheric chemistry-climate model. We find that the base model configuration captures the observed interhemispheric gradient well but underestimates the surface concentration of H2 by about 10 ppb. Additionally, the model fails to reproduce the 1–2 ppb yr−1 mean increase in surface H2 observed at background stations. We show that the cause is most likely an underestimation of current anthropogenic emissions, including potential leakages from H2-producing facilities. We also show that changes in soil moisture, soil temperature, and snow cover have most likely caused an increase in the magnitude of the soil sink, the most important removal mechanism for atmospheric H2, especially in the Northern Hemisphere. However, there remains uncertainty due to fundamental gaps in our understanding of H2 soil removal, such as the minimum moisture required for H2 soil uptake, for which we performed extensive sensitivity analyses. Finally, we show that the observed meridional gradient of the H2 mixing ratio and its seasonality can provide important constraints to test and refine parameterizations of the H2 soil sink.
Comment on “The Volyn biota (Ukraine) – indications of 1.5 Gyr old eukaryotes in 3D preservation, a spotlight on the `boring billion' ” by Franz et al. (2023)
Authors: Head Martin J. , Riding James B. , O'Keefe Jennifer M. K. , Jeiter Julius , Gravendyck Julia
Published: April 2024

Abstract. Franz et al. (2023) report a diverse and three-dimensionally preserved suite of mid-Proterozoic microfossils from miarolitic cavities within the granitic Volyn pegmatite field, a major granitic plutonic complex in NW Ukraine. The biota is dated at between ∼ 1.76 and ∼ 1.5 Ga and includes fungus-like objects. This biota is reported as evidence of organisms living within the continental lithosphere, illuminating part of a ∼ 1.8–0.8-billion-year interval of the Proterozoic Eon characterised by relatively low climatic variability and slow biological evolution. We show that at least some of this putative diversity represents modern contamination including plant hairs, a distinctive pollen grain assignable to the extant conifer genus Pinus, and likely later fungal growth. Comparable diversity is shown to exist in modern museum dust, presented as an example of potential airborne contamination and calling into question whether any part of the Volyn “biota” is biological in origin. We emphasise the need for scrupulous care in collecting, analysing, and identifying Precambrian microfossils.
Parameterizations for global thundercloud corona discharge distributions
Authors: Soler Sergio , Gordillo-Vázquez Francisco J. , Pérez-Invernón Francisco J. , Jöckel Patrick , Neubert Torsten , Chanrion Olivier , Reglero Victor , Østgaard Nikolai
Published: April 2024

Abstract. Four parameterizations have been developed to simulate global distributions of thundercloud streamer corona discharges (also known as Blue LUminous Events or BLUEs) mainly producing bluish optical emissions associated to the second positive system of N2 accompanied by no (or hardly detectable) 777.4 nm light emission. BLUEs occur globally between about 7 and 12 times less frequently (Soler et al., 2022) than lightning flashes. The four schemes are based on nonlinear functions of the cloud top height (CTH), the product of the convective available potential energy (CAPE) and total precipitation (TP), the product of CAPE and specific cloud liquid water content (CLWC), and the product of CAPE and specific cloud snow water content (CSWC). Considering that thunderstorms occur on hourly timescales, these parameterizations have been tested using ERA5 hourly data (except for CTH, not available in ERA5) for the meteorological variables considered, finding that the proposed BLUE schemes work fine and are consistent with observations by ASIM. Moreover, the parameterizations have been implemented in a global chemistry-climate model that generates annual and seasonal global distributions for present day and end of 21st century climate scenarios. Present day predictions are in good agreement with recent observations by the Atmosphere Space Interaction Monitor (ASIM).