bluuebunny/crossref_metadata_2025 huggingface dataset:
Fungsi Badan Permusyawaratan Desa Dalam Penyelenggaraan Pemerintahan Desa Long Beluah Kecamatan Tanjung Palas Barat Kabupaten Bulungan
Authors: Feber Wempi , Iskandar Iskandar
Published: October 2023

Secara umum tujuan penelitian ini untuk mengetahui pelaksanaan fungsi Badan Permusyawaratan Desa dalam penyelenggaraan pemerintahan serta faktor - faktor yang mempengaruhi di Desa Long Beluah Kecamatan Tanjung Palas Barat Kabupaten Bulungan. Analisis data yang digunakan dalam penelitian ini menggunakan metode analisis data kualitatif yaitu mendeskripsikan serta menganalisis data yang diperoleh di lokasi penelitian kemudian di interpretasi secara deskriptif dimana penentuan informan penelitian menggunakan Purposive Sampling dan teknik pengumpulan data dengan observasi, wawancara, studi pustaka, dan studi dokumentasi. Hasil penelitian menunjukkan bahwa, pertama fungsi menetapkan peraturan desa tidak terlaksana karena adanya hambatan dalam pelaksanaannya yaitu minimnya partisipasi dan dukungan masyarakat, kedua fungsi menampung dan menyalurkan aspirasi masyarakat kurang terlaksana karena masih terdapat kendala dalam pelaksanaannya,yaitu masyarakat belum sepenuhnya memahami fungsi anggota Badan Permusyawaratan Desa, sehingga dalam proses menampung dan menyalurkan aspirasi masyarakat anggota Badan Permusyawaratan Desa terjun langsung ke tengah masyarakat atau masyarakat langsung menyampaikan aspiransunya kepada Kepala Desa, ketiga pelaksanaan fungsi pengawasan juga belum terlaksana dengan baik. Adapun faktor yang mempengaruhi pelaksanaan fungsi Badan Permusyawaratan Desa diketahui bahwa, pertama masyarakat, kedua pola hubungan kerja sama dengan pemerintah desa, ketiga pendapatan, keempat sistem pemilihan, dan kelima fasilitas operasional atau penunjang kantor.
On the Cost-Effectiveness of Stacking of Neural and Non-Neural Methods for Text Classification: Scenarios and Performance Prediction
Authors: Gomes Christian , Rocha Leonardo , Gonçalves Marcos
Published: October 2023

Nowadays Neural Network algorithms have excelled in Automatic Text Classification (ATC). However, such enhanced performance comes at high computational costs. Stacking of simpler classifiers that exploit algorithmic and representational complementarity has also been shown to produce superior performance in ATC, enjoying high effectiveness and potentially lower computational costs than complex neural networks. In this master’s thesis, we present the first and largest comparative study to exploit the cost-effectiveness of Stacking in ATC, consisting of Transformers and non-neural algorithms. We investigate cost-effective ensemble vs. the best model and propose a low-cost oracle-based prediction method.
Grace: Sistema de Recomendação de Currículos com Inteligência Artificial
Authors: B. Medeiros Ana Clara , V. Franciscon João Fernando , P. Longo Julia Brugnari , R. de Moraes Marcos Vinícius , de O. Macedo Mariana , P. Bonidia Robson
Published: October 2023

O recrutamento e alocação de funcionários são desafios constantes para as empresas. Diante disso, soluções inovadoras baseadas em Inteligência Artificial (IA) têm surgido para otimizar esses processos. No entanto, IAs podem seguir vieses sociais escondidos nos dados, levando a tomada de decisões injustas, danosas e/ou preconceituosas. Com base nisso, esta pesquisa desenvolveu um sistema de recomendação automatizado de candidatos, baseado em IA, chamado Grace, que visa remover o viés exclusivo de candidatos, como exclusão por gênero, cor, etnia, orientação sexual ou qualquer outro que interfira na escolha dos melhores currículos. Espera-se que essa aplicação resulte em uma seleção imparcial de candidatos, com maior precisão e redução significativa de vieses sociais.
Strategies Selection for a Fair Classification in Logistic Regression: A Comparative Analysis
Authors: V. Pinheiro Murilo , M. Silva Maria de Lourdes , Machado Javam C.
Published: October 2023

The increasing use of technology leads society to a new concern: the use of machine learning models on personal data and the potentially biased classification. A new definition, called fairness, emerged to mitigate and combat discrimination in algorithms. Fairness literature includes several techniques to guarantee fair outputs for different demographic groups. There are three phases where an algorithm can achieve fairness. We explore some methods of each stage to construct a comparative analysis that evaluates fairness and utility metrics. Our analysis aims to understand the many ways to achieve fairness using logistic regression in the three most popular datasets in fairness literature. We include several experiments to compare five fairness techniques and select the best for each application.
Ambiente de data warehousing espacial para tomada de decisão sobre dados de crimes
Authors: Bernardes Freitas Juliana , Clarindo João Paulo , Aguiar Cristina D.
Published: October 2023

A ocorrência de crimes é uma realidade preocupante, com inúmeros casos registrados diariamente. A análise dos dados provenientes dos boletins de ocorrência pode fornecer informações valiosas para os gestores de segurança pública, auxiliando na tomada de decisão estratégica para a segurança pública e o combate à criminalidade. Dentro deste contexto, este artigo propõe a criação de um ambiente de data warehousing espacial para auxiliar gestores de segurança pública a identificar padrões, direcionar recursos e tomar decisões mais eficazes para combater a criminalidade. São apresentados exemplos de consultas analíticas espaciais com dados disponibilizados pela Secretaria de Segurança Pública do estado de São Paulo, e como elas podem ser utilizadas na tomada de decisão.
INSTRUCTOR: uma Ferramenta para Análise de Trajetórias Anômalas de Navios por Meio de Algoritmos de Agrupamento
Authors: Ribeiro Cláudio V. , Paes Aline , de Oliveira Daniel
Published: October 2023

Milhares de navios circulam diariamente e a quantidade de incidentes é expressiva, sendo tais ocorrências associadas a trajetórias consideradas anômalas. Os agentes responsáveis pela vigilância marítima precisam ser apoiados por análises visuais da situação para indicação dessas ocorrências, sobretudo de forma antecipada. Neste artigo, apresentamos a ferramenta INSTRUCTOR, que permite a análise visual de trajetórias anômalas de navios usando múltiplos algoritmos de agrupamento (ex. DBSCAN, K-Means, Birch, Spectral Clustering e Ensembles). A INSTRUCTOR pode ser obtida no repositório do GitHub e vem sendo avaliada junto a especialistas da Marinha do Brasil por meio de questionários específicos com roteiros de testes.
Pluv-Web: um Gateway Científico Orientado a Dados para Análise e Monitoramento de Chuvas na Cidade de Niterói
Authors: Victorino Fabio , Amorim Annie , Pereira Kaio , Assis Gabriel , Poustka Arthur , Oliveira Felipe , Frota Yuri , Nemirovsky Andressa , Moura Nathalia , Paes Aline , Lage Marcos , de Oliveira Daniel
Published: October 2023

Uma tarefa fundamental a ser realizada pelos governos é planejar-se para evitar problemas causados por eventos climáticos extremos (e.g., deslizamentos, cheias, etc). Esse planejamento pode ser apoiado por soluções que envolvem áreas da Computação como Gerência de Dados, Visualização e Aprendizado de Máquina. Neste artigo de demonstração, apresentamos o gateway científico Pluv-Web para apoiar a análise e o monitoramento de chuvas e eventos climáticos na cidade de Niterói. O Pluv-Web permite a visualização interativa de dados históricos e de tempo real de chuvas e de ocorrências de enchentes e deslizamentos, além de identificar inundações por meio de imagens de câmeras e gerar rotas otimizadas para atendimento a ocorrências geradas por eventos climáticos.
Os desafios e soluções para a implementação de Big Data Analytics em cidades inteligentes
Authors: F. Vasconcelos Felipe , T. Ramos Vinicius , J. Coutinho Fábio
Published: October 2023

Nos últimos anos, o crescimento das cidades inteligentes tem exigido soluções para a gerência de dados urbanos massivos e heterogêneos com o objetivo de transformar dados brutos em informação. Essas soluções precisam lidar com caracterı́sticas particulares de acesso, formato e manipulação dos dados, requerendo abordagens distintas para o processamento, integração, análise de dados. Neste trabalho, discutimos os aspectos envolvidos na construção de Big Data Analytics em cidades inteligentes, ressaltando as caracterı́sticas das soluções disponı́veis. No intuito de demonstrar as ferramentas discutidas neste trabalho, foi realizado um experimento inicial, que construiu uma pipeline de dados voltada para a análise do tráfego dos ônibus da cidade de São Paulo.
Feature Selection for Remaining Useful Life Prediction in Hard Disk Drives with Missing Data
Authors: Felix Gabriel L. S. , Pereira Francisco L. F. , Praciano Francisco D. B. S. , Gomes João P. P. , Machado Javam C.
Published: October 2023

This paper proposes a two-stage feature selection approach for the problem of Remaining Useful Life (RUL) prediction in Hard Disk Drives (HDDs) with missing data. First, a wrapper method is employed, utilizing a regression estimator to identify the most informative features for RUL prediction. The selected feature set is then evaluated in the second stage using a neural network model, with a focus on assessing the imputation performance for missing data. The goal is to determine a feature subset that enhances RUL prediction accuracy and exhibits robustness in handling missing data scenarios. This approach addresses the challenges of missing data and provides insights into the most relevant features for accurate RUL prediction.
MobApp: A Data Visualization Tool for Trajectory Analysis
Authors: Cruz Michael O. , Neto Fernando , Barbosa Luciano
Published: October 2023

In this paper, we present a demo called MobApp, a data visualization application to facilitate spatio-temporal trajectories analysis. It aims to help domain analysts and practitioners/scientists to analyze and get insights from real-world trajectories. The tool supports: (1) exploratory analysis of trajectories, which allows users to visualize selected trajectories on a map and provides some statistics about trajectories’ points; (2) visualization of anomalous trajectories and the regions where the anomalies occur, detected by an anomaly detection model; and (3) evaluation of anomaly detection models to compare their performance.
Aprendizado Federado Sensível ao Risco em Modelos de Ranqueamento
Authors: Magalhães Gestefane Rabbi , Gonçalves Marcos André , de Sousa Daniel Xavier , França Celso
Published: October 2023

Essa dissertação explora o uso do Aprendizado Federado para Ranqueamento (Federated Learning to Rank - FL2R), uma técnica empregada em sistemas de busca que considera a privacidade dos dados de diversos clientes. O FL2R envolve a construção de um modelo de ranqueamento executado de forma distribuída em vários dispositivos. Após o treino, os parâmetros das redes neurais dos clientes são combinados, resultando em um novo modelo neural que será distribuído aos clientes. Considerado o estado da arte em Federated Learning (FL), o método Federated Averaging (FedAvg) calcula a média de parâmetros para construir o modelo agregado. Contudo, clientes com baixo desempenho podem distorcer a média de forma enviesada, resultando em uma redução na efetividade do modelo global. Para contribuir na solução desse problema, propomos o estudo de técnicas de agregação que superem a simples média aritmética dos pesos, além de aplicar métricas na área de Sensibilidade ao Risco, tentando mitigar a variância dos modelos no lado do cliente. Embora o trabalho esteja em fase inicial, neste artigo foi possível mostrar alguns experimentos fazendo uso de Projeto Fatorial para avaliação de fatores que possam impactar a efetividade dos modelos federados. Os resultados mostram que combinar os valores dos parâmetros não é uma tarefa trivial, mas considerando as perguntas de pesquisa propostas acreditamos que esse trabalho tem forte potencial de contribuição na área de Recuperação de Informação.
Tutorial: Graph-based Methods for Similarity Searches
Authors: Shimomura Larissa C. , Kaster Daniel S.
Published: October 2023

Similarity searches are based on retrieving similar data of one or more data used as reference according to an intrinsic characteristic of the data. Recently, graph-based methods have emerged as a very efficient option to execute similarity queries in metric and non-metric spaces. Graphs model the interconnectivity among data, enabling us to explore relationships and neighbors in an agile way. In this tutorial, we will give an introduction to similarity searches and present graph-based methods for similarity searches, the types of graphs used in such methods, their properties, open challenges, and research opportunities.
Zur Strafbarkeit nach dem Anti-Doping-Gesetz
Authors: Chrobok David
Published: October 2023

Mit dem Gesetz gegen Doping im Sport (Anti-Doping-Gesetz) hat sich der Gesetzgeber dazu entschlossen, die Bekämpfung des Dopings mit einem eigenständigen Regelungswerk anzugehen. Das neue Stammgesetz richtet sich nicht nur an die Hintermänner des Dopings, erstmals sind es durch eine Strafbarkeit des Selbstdopings auch die Athleten, die in den Fokus der Strafverfolgungsbehörden rücken. Die vorliegende Arbeit setzt sich kritisch mit der Notwendigkeit und den einzelnen Strafbarkeitsvoraussetzungen des neuen Anti-Doping-Gesetzes auseinander.

 

Reihe

Neue Juristische Beiträge - Band 116
Important Considerations for Bone Health Management in Systemic Sclerosis Patients
Authors: E. Frech Madeleine , Adeogun Ganiat , Chew Erin , M. Frech Tracy , Bobo Tanner S.
Published: October 2023

Bone health in systemic sclerosis (SSc) is an essential management consideration for rheumatologists caring for these patients. Screening for reduction in bone density includes a detailed health history, which includes SSc disease features such as intestinal malabsorption, patulous esophagus, and calcinosis. The established International Society for Clinical Densitometry (ISCD) guidelines provide an official position statement on important topics in skeletal assessment. Bone health laboratory testing are indicated in all SSc patients, especially if a low serum albumin or vitamin deficiencies are detected. Bone health treatment considerations include adequate weight bearing exercise, calcium, and vitamin D in all SSc patients. The key findings of this chapter is that SSc patients are at increased risk for low bone density and comorbidities may affect choice of treatment such as oral bisphosphonates in SSc patients with significant esophageal disease or renal impairment and osteoanabolic therapies in SSc patients with calcinosis are important.
Fruit Cracking in Melon
Authors: Maryomana Lija , Suhara Beevy Salmabeevi
Published: October 2023

Melon (Cucumis melo L.) is an economically profitable crop in temperate and tropical regions. Melons vary in shape, size, and skin texture; they are classified under different varieties. Fruit cracking is a general problem of melon fruit grown worldwide. This physiological disorder intensively affects the production and marketable value of fruits. Studies revealed that fruit cracking causes a 70% loss in the economy of the melon fruit industry. The cracking becomes more visible when the fruits reach maturity; no single factor is known to prevent it effectively. The severity of fruit cracking depends on the nature of the variety, climate zone, where the variety is grown, fruit growing patterns, and cultural practices. It has also been linked to improper irrigation, environmental factors, and nutritional deficiencies, particularly boron, calcium, zinc, and potassium. Horticultural practices, such as spraying growth promoters, micronutrients, antitranspirant, and regular drip irrigation with mulching, have been recommended to avoid fruit cracking in melon. Although fruit cracking is a significant economic risk, research on its cause and management in melon is limited compared to other fruit crops. Hence, the present chapter summarizes the underlying causes of melon fruit cracking and potential control strategies to reduce melon fruit cracking.
Low-Temperature Combustion in Diesel Engines
Authors: Getachew Tsegaye , Dejene Mesay
Published: October 2023

The growing energy demand for transportation has led to a shift towards eco-friendly combustion or improved diesel engines with increased efficiency, reduced emissions, and sustainability. Low-temperature combustion (LTC) aims to achieve controlled combustion, balancing optimal performance with lower NOx and SO2 emissions. This chapter summarizes the recent trends in LTC strategies under further exploration such as fuel injection techniques, optimized air-fuel mixing, and accurate combustion phasing management, to discern existing literatures in extensive efforts to reduce flame stability and emissions. Subsequently, LTC faces challenges like stable ignition, precise control, and economical fuel choice. Liquefied biogas, methanol, bio-fuels, and thermo-physically enhanced biofuels are among the LTC diesel alternative fuels under investigation. Higher-octane fuels like biodiesels exhibited promising performance at low to medium loads, while natural gases and dual-fuel mode techniques seen promising choices for high-duty applications. Studies revealed that stakeholder collaboration could make cleaner fuel choices, meeting rigorous emissions rules while operating optimal LTC engines. Therefore, Future LTC research should focus on emission reduction, fuel flexibility, optimum performance at various working conditions, combustion stability, and accurate modeling and simulation.
Gun Culture: A Hidden Evil in Indian Society and Its Implications
Authors: Kumar Yogesh
Published: October 2023

India faces a serious issue of gun violence in many states. Despite having strict laws for firearms, there are many loopholes from where criminals and normal citizens acquire guns. Reasons can be many from portraying themselves as powerful to threatening someone or to protecting and even killing someone. Few surveys have revealed that the numbers of licensed firearms are very low as compared to unlicensed firearms. Government and police have taken severe measures to bring an end to the gun culture, but corruption and politics have given hope to the culprits. States like Punjab, Jammu & Kashmir and Uttar Pradesh are the worst affected regions. Art and culture such as the music industry have witnessed the glorification of guns through music videos and lyrics by many singers and artists. Thus, this chapter tries to bring out this situation, reasons and solutions for the prevailing evil form of gun culture in India.
Material and load path appropriate joining techniques for FRP/metal hybrid structures
Authors: Seidlitz Holger , Ulke-Winter Lars , Ost Lucas , Kuke Felix
Published: October 2023

Fiber-reinforced plastics (FRP) offer great lightweight construction potential. However, the anisotropic high-performance materials can only be fully utilized through the development of material-specific joining processes. A literature study shows that conventional methods such as screwing, riveting and bolting are unsuitable, since the load-bearing fibers are severed in the joining region. This leads to high-stress concentrations. To reduce these, a method is presented in which through holes are created in thermoplastic FRP by reorienting the fibers in this area around the point of disruption in accordance with the load path. For this purpose, the polymer matrix is softened locally by applying heat and penetrated with a needle or mandrel. Based on this, a technology for material-specific joining of FRP and metals has been developed in the form of thermomechanical flow drill joining. In this process, a mandrel forms a bush from the metal component and deflects the fibers of the locally softened organic sheet to suit the material. Cold metal transfer (CMT) pin welding is presented as another fully automatable joining process. In this method, the softened plastic component is penetrated with the welding wire, displacing the fibers in the joining area and realigning them to suit the load path.
Geodetic Data Processing Using Soft Computing Techniques
Authors: Habib Maan
Published: October 2023

Geodetic data processing involves using mathematical and computational techniques to analyze and interpret geospatial data about the Earth’s surface and the objects and features that exist on it. This data is collected through satellite imagery, aerial photography, and surveying instruments such as total stations and GPS receivers. The applications of geodetic data processing are diverse and include land surveying, mapping, navigation, environmental monitoring, and disaster management. It is crucial to understand and manage the Earth’s resources and address global challenges such as climate change, natural disasters, and urbanization. In recent years, the information technology industry has undergone a considerable transformation that has significantly impacted the development of various disciplines. Intelligent systems, powerful tools for understanding and solving complex engineering issues, have become increasingly important in this context. Soft computing techniques, including artificial neural networks, fuzzy logic, and evolutionary algorithms, are used more frequently in geodetic data processing due to their ability to handle complex, imprecise, and uncertain data. This study discusses using soft computing techniques in geodetic data processing and examines the challenges and future directions in using soft computing techniques in geodetic data processing.
Perspective Chapter: Crime Scene Investigation in Criminal Behavior Cases – Forensic Biology, Forensic Entomology and Forensic Entomotoxicology
Authors: Açikgöz Ali , Nihal Açikgöz Halide
Published: October 2023

Branches of forensic science are used to determine the samples used in solving suspicious death cases and the criminal behavior of the suspect. Forensic biology, forensic entomology, and forensic entomotoxicology are just three of them exterior surfaces of cars, are of interest to forensic biology. Forensic entomology is an interdisciplinary science that contributes to the solution of forensic cases by examining the life cycles and successions of arthropods on corpses. The first question that forensic entomology seeks to answer is when the person died. Clarifying the questions of how and where the person was killed will shed light on forensic investigations. The field of forensic entomotoxicology is to determine the alcohol, narcotic substances, and poisons used by the person before his death by toxicological analysis of arthropods fed on corpses. In this section, the journey of the samples collected from the crime scene to the laboratory in the fields of forensic biology, forensic entomology, and forensic entomototoxicology will be followed.
Early Reframing of Aging and Intergenerational Relations for Improved Technology Design and Usage
Authors: Thu Nguyen Kim
Published: October 2023

The phenomenon of ageism is learned at an early age and has lifelong implications on technology design, adoption, and fluency. There is ample evidence supporting this statement. This chapter shares related findings from two American studies; a 2021 study sought to understand the experiences of older adults (those 65 years and older) using everyday information and communications technology (ICT). The second study, conducted in 2022 and 2023, gleaned insights from individuals 17–85 years who provided older adults with hands-on technology instruction. As longevity increases and technological solutions increasingly replace those that humans previously handled, it is evident that those who do not have the tools and the skills to use technology are being left behind. While there is general agreement that a problem exists, the topic of older adults and their digital exclusion seems to be deprioritized by the media, policymakers, corporate leaders, and technology manufacturers—the groups best positioned to increase awareness and make meaningful change. Since aging is inevitable, all should care about reframing aging and strengthening intergenerational relations that promote healthy aging.
Arsenic Emission Control from Coal Combustion Flue Gas
Authors: Wu Jiang , Guan Zhenzhen , Ling Yang
Published: October 2023

Arsenic is a highly toxic element in coal and one of the representative toxic trace metals emitted from coal-fired power plants, which is mainly converted into As2O3 vapor during the combustion process of coal. When absorbed by the body, arsenic can cause arsenic poisoning, which not only causes metabolic disorders and subsequent neurotoxicity in the body but also retards growth in young children. Arsenic is of increasing concern due to its bioaccumulation and potential carcinogenicity. This chapter describes the characteristics of arsenic emissions from coal-fired power plants and the various control technologies, including pre-, in-, and post-combustion control technologies. It also provides an outlook on future technological developments and provides theoretical guidance for controlling arsenic in flue gas.
Cloud management of pumping systems using digital twins supported by augmented reality
Authors: David Rueda Martínez Juan , Andrés Moreno Olano Gonzalo , Roa-Prada Sebastian , Darío Mantilla Hernández Hernán , Fernando Saavedra Trujillo Nestor
Published: October 2023

Smart pumping systems of tomorrow will feature pumps and drives that respond to real-time changes downstream to keep operations at high efficiency and meet growing performance demand. A key component of a smart pumping system is its digital twin, an exact 3D digital copy of the facility. A digital twin enhanced with Augmented Reality (AR) encompasses as-built facility data captured with 3D scanning devices, as well as precise measurement data collected on the actual rigs with high precision instruments. An interactive model based on augmented reality allows the autonomous and efficient use of pumping systems. It provides clear instructions for the step-by-step management of the system. In addition, it shows relevant information with the exploded views of the components for a better understanding of the operation of the equipment. This research is about the interconnection of the digital twin of pumping systems with the real-world using automation and augmented reality systems. In this project, a local area network is configured to exert control and monitoring on an industrial PLC. This PLC controls a test bench with two centrifugal pumps by means of a web page. An augmented reality application is also developed in Unity 3D with the Vuphoria SDK integration.
Yoga-nidrā: A State of Mind, Not a Technique
Authors: Parker Stephen
Published: October 2023

Since its introduction to the West in 1969 by Swāmī Rāma through experiments conducted at the U.S. Menninger Foundation, yoga-nidrā has become a popular practice among yoga teachers from many traditions. The result is a patchwork of techniques incorporating a variety of practices and procedures. It has come to be thought of primarily as technique and the variability of techniques across traditions has engendered debate about which technique is right. In fact, yoga-nidrā is defined by Swāmī Rāma, as well as by textual sources, as a state of mind where the practitioner consciously enters a state of deep, dreamless (non-REM) sleep, remaining both inwardly aware and aware of their external surroundings. The more a practitioner has managed to keep the parasympathetic relaxation system continuously activated through moment-to-moment mindfulness practice, the less technique is required to enter that state. The only way to be certain that someone has entered this state is to measure their brain waves with an electro-encephalogram (EEG) for predominance of delta waves and to test their awareness of their surroundings. For purposes of getting to the state of yoga-nidrā, any of the preparatory techniques will serve, although none are a guarantee that the state will be reached.
Fractal and Multifractal Characterization of 3D Video Signals
Authors: Zekovic Amela
Published: October 2023

Video signals are responsible for the largest amount of information in data storage and data transmission systems. Three-dimensional (3D) video formats are the largest in terms of the amount of data, and thus the required bit rate. For the efficient transmission of 3D video in communication systems, a detailed knowledge of the traffic characteristics of the format is necessary. In this research, characterization of 3D video signals is performed by using fractal and multifractal analyses. Codes for analyses are written in MATLAB and Python. Communication network traffic shows self-similar behavior with long-range dependence (LRD). Using visual methods and a rigorous statistical methods, it was shown that video sequences of 3D video formats have fractal self-similar properties with LRD and high Hurst parameter values. It is shown that investigated 3D video formats have multifractal structure by using the histogram method. The research included different 3D video formats, specifically with one video sequence (frame compatible, FC and frame sequential, FS) and with two or more video sequences (multiview, MV). Cases with different signal qualities defined by the quantization parameter, different types of frames, different groups of picture (GoP), and different broadcasting methods were taken into account and separately analyzed.
Corneal Disease and its Impact on Cataract Surgery
Authors: A. Bird Brian , Y. Cheung Albert , D. Sheppard John
Published: October 2023

The primary focus of this book chapter is to investigate and discuss the impact of corneal disease and how various types of corneal pathology can affect the surgeons preop, intraop and post op management when considering cataract surgery for a patient. Cataract surgery is known to exacerbate ocular surface diseases like dry eye, HSV, inflammatory conditions like ocular cicatricial pemphigoid, SJS, peripheral ulcerative keratitis, Moorens ulcer and endothelial disease like Fuch’s dystrophy secondary to intraoperative endothelial cell loss. Preoperative treatment including optimization of the corneal surface, antiviral prophylaxis in HSV keratitis, quiescence of inflammation and preoperative diagnostic evaluation of endothelial cell counts may all play a role in postoperative outcomes. Corneal disease may also impact intraoperative considerations in cataract extraction to include the use of scleral tunnels or even Extracapsular Cataract extraction techniques, for example, in patients with Mooren’s ulcer to decrease corneal melt. More commonly corneal disease consequently provides a poor view for the surgeon and unfavorable post op visual acuity for the patient. Consideration of staged keratoplasty and cataract surgery vs. combined “triple procedure” have both been shown as reasonable treatment options. Postoperative considerations include management of endothelial cell loss during surgery and minimizing postoperative eye drops and medicomentosa.
Bowel Diverticulosis
Authors: Batti Badie , Mohammad Waseem
Published: October 2023

Colonic diverticulosis is the presence of outpouchings of the intestinal walls in the colon. It remains without symptoms in most individuals, but about 25% of individuals will develop symptoms of diverticulosis at some point in time, and this is termed as colonic diverticular disease. The severity of this illness is variable and ranges from symptomatic uncomplicated diverticular disease (SUDD) to symptomatic disease with complications such as inflammation of these outpouchings or occasional bleeding. The diagnosis of diverticular disease depends mainly on radiological studies, such as computed tomography (CT) abdomen pelvis and magnetic resonance imaging (MRI) scan. The management is a multilevel approach that focuses on lifestyle modifications and pharmacotherapies to provide symptomatic relief and reduce progression risks into complicated diseases. Rarely, endoscopic interventions may be needed in some complicated cases.
Characterization of Dismissed Landfills via Geophysical Techniques
Authors: De Carlo Lorenzo , Cassiani Giorgio , Deiana Rita , Piero Deidda Gian , Clementina Caputo Maria
Published: October 2023

In the context of waste landfill management, geophysical methods are a powerful tool for evaluating their impact on public health and environment. Noninvasive and cost-effective geophysical techniques rapidly investigate large areas with no impact on the system. This is essential for the characterization of the waste body and the evaluation of the liner integrity at the bottom of the landfill and leakage localization. Three case studies are described with the purpose of highlighting the potentiality of such techniques in landfill studies. The case studies show different site conditions (capped landfills, controlled closed systems, and unconfined systems) that limit the applicability of any other kind of investigation and, at the same time, highlight the versatility of the geophysical techniques to adapt to several field situations. Electrical and electromagnetic techniques proved to be the most efficient geophysical techniques for providing useful information to develop an accurate site conceptual model.
Dielectric Spectroscopy for the Non-Destructive Characterization of Biomaterials: Fundamentals, Techniques, and Experimentations
Authors: Novas Castellano Nuria , El Khaled Dalia , Maria Garcia Rosa , Portillo Francisco , Fernadez-Ros Manuel , Antonio Gazquez Jose
Published: October 2023

This chapter provides an overview of research on the dielectric properties of fresh food and their applications in assessing food quality and freshness. Non-destructive methods, including dielectric techniques such as dielectric spectroscopy (DS) and bioelectrical impedance spectroscopy (BIS), have gained importance in assessing food quality without damaging the products. The importance of external appearances, such as color, size, brightness, and hardness, in determining the freshness of fruits and vegetables is emphasized. Several dielectric techniques, such as impedance, capacitance, and electrical conductivity measurements, are studied to assess quality at distinct stages of the supply chain. These techniques can detect defects, diseases, and mechanical damage and facilitate storage quality control and processing quality evaluation. Accurate measurements and instrumentation advancements are crucial for effectively implementing these techniques. The study of dielectric properties offers promising prospects for evaluating food quality and ensuring freshness. Further research and technological advances in this field can enhance the monitoring and maintaining optimal conditions for fresh produce throughout the food supply chain, reducing food waste and improving consumer satisfaction.
Multi-Agent Robot Motion Planning for Rendezvous Applications in a Mixed Environment with a Broadcast Event-Triggered Consensus Controller
Authors: Sariff Nohaidda , Hilmi Ismail Zool , Shah Hizam Md Yasir Ahmad , Sooriamoorthy Denesh , Nor Aznie Fahsyar Syed Mahadzir Puteri
Published: October 2023

Finding consensus is one of the most important tasks in multi-agent robot motion coordination research, especially in a communication environment. This justification underlies the use of event-triggered controller in current multi-agent consensus research. However, the communication issue has not been adequately addressed in a broadcast communication environment for rendezvous applications. Therefore, the broadcast event-triggered (BET) controller with a new formulation was designed using the Simultaneous Perturbation Stochastic Algorithm (SPSA). Theorems and relevant proofs were presented. Agent performances with the BET controller were evaluated and compared with the conventional broadcast time-triggered (BTT) controller. The results showed an effective motion generated by a multi-agent robot to reach the rendezvous point based on the Bernoulli distribution and gradient approximation of the agent local controller. The BET controller has proven to work more efficiently than the BTT controller when it reaches convergence in less than 40.42% of time and 21.00% of iterations on average. The utilization of communication channels is slightly reduced for BET, which is 71.09% usage instead of fully utilized by BTT. The threshold value of the event-triggered function (ETF) and SPSA parameters affected agent performances. Future research may consider using an effective and efficient BET controller in a complex communication environment with many variations of graph topology networks.
Coronary atherosclerosis: a neglected cause of sudden cardiac death in the young
Authors: Thiene Gaetano , Rizzo Stefania , Basso Cristina
Published: October 2023

Sudden cardiac death (SCD) in the adult-elderly population is mostly arrhythmic due to acute thrombotic coronary artery occlusion or chronic ischemic heart disease. In the young atherosclerotic coronary artery disease (CAD) is thought to play a negligible role. We reviewed our pathology experience (1980–2016) in 690 consecutive SCDs in the young (≤40 years old, sudden infant death excluded). We found that CAD was the major cause of SCD (18%). It was observed in 125 subjects (mean age 32.3 ± 5.3 years, female 14), with a peak in 31–40 years old age interval. Site, extent, and histologic type of CAD were peculiar: single plaque of the proximal left anterior descending coronary artery, consisting of fibrocellular proliferation, with rare lipid core. The culprit atherosclerotic segment showed critical stenosis in 66% of cases and thrombotic occlusion in 34%, the latter as the consequence of plaque rupture in 47% and plaque erosion in 53%, which occurred even upon noncritical stenosis. An overt histologically acute myocardial infarction was never seen. When SCD took place during Holter monitory, transient myocardial ischemia was recorded, followed by ventricular fibrillation at the time of reperfusion. Atherosclerotic CAD was found to be the major cause of SCD also in the young, precipitated by acute coronary thrombosis in only a third of cases, more frequently upon endothelial erosion. Functional plaque instability with vasospasm, superimposed to a critical coronary plaque with ECG transient myocardial ischemia, was observed to precipitate SCD.
RESEARCH OF MULTIFUNCTIONAL CERAMIC MATERIALS FOR THEIR APPLICATION
Authors: Stoyanova-Ivanova Angelina , Slavov Stanislav
Published: October 2023

A new challenge is obtaining and researching ceramic multifunctional materials containing phases with various properties, as well as Aurivillius phases, which determine their application. They show potential for use in electrochemical applications and ferroelectric and piezoelectric devices, sensors, and non-volatile memories. Presented are our studies of volumetric nonmonophasic ceramics from the RE-Ba-Cu-O (ReBCO, RE = rare-earth; Y, Dy) and Bi-Pb-Sr-Ca-Cu-O (B(Pb) SCCO) systems that are superconductors, obtained via solid phase synthesis. A bulk ceramic composite Y123/BaCuO2 was synthesized with starting stoichiometry of 1:3:4(Y:Ba:Cu) via a one-step procedure. It has superconducting and magnetic properties at low temperatures. DyBCO bulk ceramic with a nano-Fe3O4 additive was synthesized and characterized to identify the phase and elemental composition, the microstructure, and the superconducting transition temperature. The Aurivillius phases were synthesized via solid-phase synthesis and a melt-quench method. B(Pb)SCCO ceramics (2223, 2212, and 2201), with conductive properties, have been used as an addition to the active mass of a Zn electrode. The method of mixing the materials was also investigated. Their behavior in an alkaline environment and positive influence on the properties and longevity of the nickel-zinc battery has been studied. Part of the obtained ceramic systems was patented.
Ethical Considerations in Organizational Conflict
Authors: Hyatt Josh , Gruenglas Jeffrey
Published: October 2023

Ethical considerations are critical to decision-making in any organization. Decisions that impact internal and external stakeholders carry implications that account for employee conduct, personal values, institutional policies, and obligations to customers. Conflicts within an organization present a particularly unique set of dynamics and tensions that require ethical assessment to ensure a fair, equitable, and ethically acceptable work environment. Recognizing these ethical challenges, and ultimately addressing and resolving them, is incumbent upon all stakeholders to ensure the success of the organization and its stated mission to employees, clients, and the community it serves. This chapter explores commonly encountered forms of organizational conflicts with respect to ethical concerns, and the considerations for navigating such conditions through theoretical foundations and a practical lens. The discussion is then followed by a framework for advancing ethical conduct through institutional codes and policies. We conclude with a case study that examines the ethical challenge of fair resource allocation and just distribution of goods.
Technology Self-Efficacy and Mindfulness as Coping Strategies for Technostress in Hybrid Work Settings
Authors: Harunavamwe Martha , Kanengoni Herbert
Published: October 2023

Information technology (IT) has brought a number of benefits in aiding remote work and facilitating hybrid work models. Though individuals are enjoying the benefits, hybrid work settings are characterised by ambiguity and excessive use of technology, which may result in technostress and may influence well-being negatively. Within this hybrid work model, a number of techno-stressors may impede employee efficiency and trigger anxiety. Among the stressors are techno-overload, techno-complexity, techno-unreliability, techno-uncertainty and techno-invasion. These techno-stressors may be exacerbated by other hybrid work model challenges including long working hours, consistent connectivity, emotional exhaustion, demand for higher cognitive abilities, workaholism and overload. Technostress has thus emerged as a critical issue within the realm of management, owing to its propensity to impose pronounced repercussions on employee welfare and work-life equilibrium, in ways that can significantly impact the overall efficiency of organisations. This chapter contributes and expands literature by identifying technology self-efficacy and mindfulness as coping mechanisms that can be applied by organisations to mitigate the negative consequences of techno-stressors. The recommendations offer practical value in developing, planning and implementing targeted interventions that enable individuals to cope. Practising and implementing technology self-efficacy and mindfulness strategies can protect employees from the negative consequences of technostress, enhance well-being and improve the overall performance of the organisation.
Diagnostic Methods for Microvasculopathy in Systemic Sclerosis
Authors: Miziołek Bartosz , Szczepanek Michał , Bergler-Czop Beata
Published: October 2023

A generalized damage to the microcirculation (microvasculopathy) is a cardinal feature of systemic sclerosis and its first manifestation is Raynaud’s phenomenon. Early detection of microvasculopathy enables to establish the right diagnosis at the very early stage of the disease and to identify those patients with the greater risk of internal organ involvement or developmental digital tip ulcers. Dynamic methods help to monitor the response to treatment that influences on the vasomotoric functions of the microcirculation. The gold standard for the assessment of microvascular involvement constitutes nailfold capillaroscopy, which can be performed using stereomicroscopy, videocapillaroscopy, or dermoscopy. Other non-invasive diagnostic methods include sidestream dark field imaging, optical coherence tomography, laser Doppler and laser-related methods, and thermography.
Basic mechanisms of multisystemic inflammatory syndrome and severe acute respiratory syndrome coronavirus 2
Authors: Sandoval Salazar Cuauhtémoc , Trinidad Villalobos Gútierrez Paola , Gútierrez Coronado Oscar , Beltrán Campos Vicente
Published: October 2023

Multisystemic inflammatory syndrome is a condition developed by various factors such as chronic diseases, diverse body traumas, postoperative complications, and hypoxia. Within the main characteristics of this pathological condition, there is an increase in body temperature, free radicals, proinflammatory cytokines, lymphocytes, and even apoptosis. However, gravity depends on each of the organisms, its characteristics, as well as from the presence of other conditions such as overweight, obesity, and in recent years the infection has al severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), etc. With the above, it is essential to mention that the body uses several cell and molecular mechanisms to counteract the effects of inflammation for a long time. Therefore, life expectancy will depend on each patient’s genetic, metabolic, and physiological response characteristics. This chapter describes the basic mechanisms given during the development of multisystemic inflammatory syndrome.
Influence of Chronic Low-Grade Inflammation (Obesity) on the Systemic Inflammatory Response
Authors: Balderas-Peña Luz-Ma.-Adriana , Sat-Muñoz Daniel , Mireles-Ramírez Mario-Alberto , Martínez-Herrera Brenda-Eugenia , Nava-Zavala Arnulfo-Hernán , Cervantes-González Luz-María , Muñoz-García Michelle-Guadalupe , Rubio-Jurado Benjamín , Salazar Páramo Mario , Gómez Sánchez Eduardo , Nuño-Guzmán Carlos-M
Published: October 2023

The chronic inflammatory state is a common condition in obesity. It has become a health problem with pandemic proportions that, in some developing countries, jointly to overweight, affects more than 50% of their population. As a part of the scenario, we observe how a significant proportion of people with overweight or obesity have raised the acute inflammatory response markers. This situation shows us how this chronic condition can trigger aggressive inflammatory phenomena in critically ill patients with other clinical conditions, occasioning torpid clinical evolution, ominous results, and low-rate survival. This chapter pretends to describe the influence of a low-grade inflammatory state on the clinical outcome of patients who develop a systemic inflammatory response.
Oxide-based Resistive RAM Analog Synaptic Behavior Assessment for Neuromemristive systems
Authors: Aziza Hassen
Published: October 2023

Resistive RAM (RRAM) synaptic plasticity behavior is essential to enable future power-efficient brain-inspired accelerators. In oxide-based RAM (so-called OxRAM), synaptic plasticity is reflected in the OxRAM conductance modulation capability, making the technology well suited for neuromorphic applications. This chapter assesses the conductance modulation of HfO2-based RRAM and leverages experimental measurement results to establish the inherent synaptic behavior of the technology. The OxRAM conductance modulation capability is demonstrated based on a 1T1R elementary memory array test chip. The memory array OxRAM cells are operated using two distinct programming schemes. The first one is based on RESET (RST) peak voltage modulation. The second one is based on SET compliance current modulation. Both methods show that OxRAM conductance modulation is highly impacted by the variability of the technology. Hence, variability happens to be one the most challenging limitations for OxRAMs used in neuromorphic applications.
Non-coding RNAs in Lepidoptera
Authors: Li Dandan , Kan Yunchao , Li Zhongwei
Published: October 2023

In the last few years, the amount of genomic sequence data has grown exponentially. A large number of non-coding RNAs (ncRNAs) have been identified from bacteria to humans. ncRNAs are various and multi-faced; they can regulate gene expression through chromosomal, transcriptional, post-transcriptional, and translational levels and then participate in the whole process of development in different organisms. ncRNAs have been identified in the 1980s in Lepidoptera; they can play roles in growth, metamorphosis, metabolism, sex determination, reproduction, and immune response of insects. Now, the use of ncRNAs in pest control of Lepidoptera is also in process. This chapter will review the recent advance of ncRNAs in Lepidoptera and prospect the future studies of ncRNAs in insects.