bluuebunny/crossref_metadata_2025 huggingface dataset:
Idiopathic pulmonary hypertension in an adult with patent foramen ovale
Authors: Shumilin A. A. , Pavlov A. I. , Prokhorchik A. A. , Cherniaev A. L. , Samsonova M. V. , Slavetskya M. A.
Published: November 2024

The article is devoted to the clinical case of combined idiopathic pulmonary hypertension with an open foramen ovale of the atrial septum in a young man of 21 years old with progressive decrease in lung ventilation function. The relationship of pulmonary arterial hypertension with an open foramen ovale of the atrial septum is nearly not described in the literature, as it is rarely found in clinical practice. According to the classification, pulmonary hypertension is divided into idiopathic (primary), secondary and pulmonary hypertension caused by other causes. In the pathogenesis of any PAH, an important role belongs to a complex of vascular changes. Verification of vascular changes is carried out histologically. Variants of idiopathic pulmonary hypertension are plexiform and thrombotic arteriopathy, veno-occlusive disease, capillary hemangiomatosis. An open foramen ovale as a structural anomaly of the adult heart (a vestige of embryonic blood circulation) causes a variety of hemodynamic  disorders that can affect the pathogenesis of pulmonary hypertension. Because of this, preclinical observation of a combination of plexiform and thrombotic arteriopathy with a patent foramen ovale of the interatrial septum in a young man of 21 years old and an attempt to determine the role of an open oval window in the progression of pulmonary hypertension and its effect on treatment is of interest. The diagnosis of idiopathic pulmonary hypertension was made based on the clinical picture, laboratory parameters, echocardiography and histological examination of pulmonary vessels. The article discusses the importance of a patent foramen ovale in the pathogenesis of idiopathic pulmonary hypertension.
Decreased vitamin D levels as a factor of deterioration of osseointegration during dental implantation
Authors: Ilovayskaya I. A. , Amkhadova M. A. , Kadiev A. A. , Amkhadov I. S. , Dzhabrailova М. A.
Published: November 2024

Introduction. Decreased vitamin D levels are considered as a possible factor in dental implantation failure. However, there arelack of good quality studies on this topic, some of which were conducted on animal models.

Aim. To identify the possible role of vitamin D levels on osseointegration parameters during dental implantation.

Materials and methods. A retrospective single-sample cohort observational non-interventional study was conducted. 78 female patients who underwent dental implantation were examined, who were divided into 3 groups: up to 44 years old, group 1 (n = 20), 45-60 years old, group 2 (n = 34), 60 years and older, group 3 (n = 24). All patients were examined before implantation: vitamin D, FSH, estradiol, TSH, free T4, computed tomography of the jaw bones, indices of the gums and periodontium condition, also the implant stability quotient (ISQ) was determined at the time of implant placement and at the time of prosthetics.

Results. The concentrations of vitamin D, estradiol, jaw bone density, and ISQ at the time of implantation and at the time of prosthetics were significantly lower in group 3. Vitamin D deficit/insufficiency occurred in 38%, 58%, 88% of patients in groups 1, 2, 3, respectively (p < 0.001). The ratio of chances to detect a decrease in vitamin D was 13.1 (CI 95% 2.9–60.2) in group 3 compared to group 2, and 5.7 (CI 95% 1.4–22.6) compared to group 1. The ratio of the chances for an increase of osseointegration time was 11.6 (CI 95% 2.3–59.1) in case of vitamin D deficiency compared to optimal values, and 5.7 (CI 95% 1.4–24.1) compared to a insufficiency condition. Vitamin D levels significantly inversely correlated with hygienic indices of periodontal condition.

Conclusion. A decrease vitamin D levels can be strongly considered as a factor in the deterioration of osseointegration during dental implantation, since this is associated with an extended period of osseointegration due to a decrease in the bone density of the jaw and a worse periodontal condition.
Water quality estimates using machine learning techniques in an experimental watershed
Authors: Costa David , Bayissa Yared , Barbosa Kargean Vianna , Villas-Boas Mariana Dias , Bawa Arun , Junior Jader Lugon , Neto Antônio J. Silva , Srinivasan Raghavan
Published: November 2024

This study aims to identify the best machine learning (ML) approach to predict concentrations of biochemical oxygen demand (BOD), nitrate, and phosphate. Four ML techniques including Decision tree, Random Forest, Gradient Boosting and XGBoost were compared to estimate the water quality parameters based on biophysical (i.e., population, basin area, river slope, water level, and stream flow), and physicochemical properties (i.e., conductivity, turbidity, pH, temperature, and dissolved oxygen) input parameters. The innovation lies in the combination of on-the-spot variables with additional characteristics of the watershed. The model performances were evaluated using coefficient of determination (R2), Nash-Sutcliffe efficiency coefficient (NSE), Root Mean Squared Error (RMSE) and Kling-Gupta Efficiency (KGE) coefficient. The robust five-fold cross-validation, along with hyperparameter tuning, achieved R2 values of 0.71, 0.66, and 0.69 for phosphate, nitrate, and BOD; NSE values of 0.67, 0.65, and 0.62, and KGE values of 0.64, 0.75, and 0.60, respectively. XGBoost yielded good results, showcasing superior performance when considering all analysis performed, but his performance was closely match by other algorithms. The overall modeling design and approach, which includes careful consideration of data preprocessing, dataset splitting, statistical evaluation metrics, feature analysis, and learning curve analysis, are just as important as algorithm selection.
A groundwater level spatiotemporal prediction model based on graph convolutional networks with a long short-term memory
Authors: Wang Lifang , Jiang Zhengwen , Song Lei , Yu Xi , Yuan Shujun , Zhang Baoyi
Published: November 2024

The performance of regional groundwater level (GWL) prediction model hinges on understanding intricate spatiotemporal correlations among monitoring wells. In this study, a graph convolutional network (GCN) with a long short-term memory (LSTM) (GCN–LSTM) model is introduced for GWL prediction utilizing data from 16 wells located in the northeastern Xiangtan City, China. This model is designed to account for both the hybrid temporal dependencies and spatial autocorrelations among wells. It consists of two parts: the spatial part employs GCNs to extract spatial characteristics from a spatial self-similarity weight matrix and an attribute self-similarity weight matrix among wells; the temporal part utilizes a LSTM module to capture the temporal patterns of GWL sequences, along with monthly precipitation and temperature data. This model dynamically predicts changes in groundwater levels, achieving higher accuracy on average compared to single-well predictions using LSTM. By incorporating both temporal dependencies and spatial autocorrelations, the GCN–LSTM model demonstrated an average improvement in goodness-of-fit of approximately 11.21% over the LSTM-based model for individual wells. Its application holds significant reference value for the sustainable utilization and development of groundwater resources in Xiangtan City.
ENSINO DE BOAS PRÁTICAS DE ESCRITA DA PRESCRIÇÃO DE MEDICAMENTOS NA GRADUAÇÃO EM MEDICINA
Authors: Mariz Batista Almária , Da Silva Gama Zenewton André , Bezerra de Souza Dyego Leandro , De Oliveira Costa Raphael Raniere
Published: November 2024

PROBLEMA: Prescrição é a etapa de maior prevalência de falhas evitáveis no processo de medicação, o que suscita a necessidade de ensino de boas práticas de escrita da prescrição de medicamentos. MÉTODO: Estudo descritivo da construção e aplicação de um método de ensino-aprendizagem de boas práticas de escrita da prescrição de medicamentos para estudantes de graduação em Medicina. O método, intitulado “Ensino de Boas Práticas de Escrita da Prescrição de Medicamentos”, consiste em 8 etapas. Foi desenvolvido por docentes da Universidade Federal do Rio Grande do Norte, Brasil. Tem como premissa os pressupostos da aprendizagem significativa, da aprendizagem baseada em pares e o instrumento QualiPresc, um instrumento validado para avaliar a qualidade da escrita da prescrição de medicamentos na atenção primária. RESULTADOS: Após o desenvolvimento, foi aplicado, na forma de piloto. As percepções preliminares sobre sua implementação apontam para um método de ensino-aprendizagem com potencial para sua implementação e disseminação em cursos de Medicina no Brasil, para a melhoria da qualidade e segurança do processo de medicação. CONCLUSÕES: Em virtude de seu caráter de “piloto”, mais estudos precisam ser desenvolvidos no sentido de aferir a efetividade do método em detrimento de outras estratégias de ensino e aprendizagem utilizadas para a mesma finalidade.
Novel Drug Delivery System for Nutraceuticals
Authors: Sharma Anjali , Sharma Devkant , Bajaj Himani , Yadav Mayank , Sharma Prerna
Published: November 2024

Nutraceuticals have gotten a lot of attention in recent years because of the
health-promoting and disease-prevention properties along with their nutritional value.
The increasing quantity of widely viable nutraceuticals and their wide range of uses
indicate the domination of these products around the world. Nutraceuticals contain a
variety of health advantages and functions; however, most nutraceuticals degrade
quickly in the gastrointestinal tract and have low bioavailability. Different innovative
drug delivery-containing carrier technologies are continually being researched in order
to improve the efficacy and bioavailability of herbal medications. To overcome hurdles
and enable efficient application, a unique carrier system is becoming increasingly
important. This chapter provides an insight into nanoencapsulated nutraceuticals'
physical and gastrointestinal stability, as well as their bioavailability, which are all
taken into account. The existing limitations, synthesis, and applications of different
lipid-based nanocarriers (including niosomes and liposomes) and lipid nanoparticles
(SLNs and NLCs) are examined critically. This study also attempts to document the
most recent advancements and problems in the field of nanonutraceuticals, a cuttingedge subject that uses nanotechnology to encapsulate bioactive substances in order to
enhance their medicinal effectiveness and release profile.
Phytoconstituents as Nutraceuticals
Authors: Deswal Geeta , Chopra Bhawna , Garg Madhukar , Vaid Lavish , Jain Arhat , Dhingra Ashwani K. , Grewal Ajmer Singh , Kriplani Priyanka
Published: November 2024

Nutraceuticals are nutritional supplements exploited for upgrading wellbeing, delayingaging, averting ailments, and supporting the appropriate working of the
human body. At present, nutraceuticals are gaining significant attention owing to their
nourishment as well as therapeutic potential. On the basis of sources, they are classified
into nutritional supplements and biologically active plant-derived molecules. These
nutraceuticals support fighting some of the foremost well-being complications of the
era, including obesity, cardiac ailments, malignancy, osteoporosis, arthritis, diabetes,
etc. Nutraceuticals have benefits over medication since these are devoid of side effects
and are composed of nature-based nutritional supplements. This chapter gives an
overview of various bioactive components obtained from secondary metabolites of
plants with a diverse era of chemical classes that might act as nutraceuticals (i.e.,
anthraquinones, alkaloids, saponins, tannins, essential oils, carotenoids, flavonoids,
bitters, carbohydrates, protein, and vitamins).
Anthocyanins as Nutraceuticals
Authors: Dutt Rohit , Mathur Pooja , Kamboj Sweta , Kamboj Rohit , Guarve Kumar , Kamboj Shikha , Rudrakash  , Devi Tanu , Sharma Prerna
Published: November 2024

Anthocyanins are a group of colored, water-soluble flavonoid chemicals that
are widely distributed in fruits, leaves, roots, and other portions of plants. They belong
to a large group of flavonoids known as glycosides of anthocyanidins. Anthocyanins
are often found in foods including cherries, plums, strawberries, raspberries,
blackberries, grapes, redcurrants, blackcurrants, vegetable roots, legumes, and grains as
colored compounds. Natural foods are known to contain more than 600 anthocyanins.
Anthocyanin, which is consumed by humans, is one of the greatest flavonoids. Dietary
anthocyanins are not very harmful. They are also helpful for polygenic diseases and
managing weight. These actions, which include anti-inflammatory, liver-protective,
analgesic, and anti-cancer properties, have given anthocyanins tremendous economic
potential and driven researchers to concentrate on studying their chemistry, biological
activity, isolation, and quality. Dietary therapies using anthocyanins are being
thoroughly researched for the prevention of numerous chronic diseases, including GI
cancer.Anthocyanins have been used in clinical investigations that have demonstrated a
substantial reduction in oxidative stress and inflammatory indicators, as well as a
positive impact on vascular function and hyperlipidemia by boosting high-density
lipoprotein and lowering low-density lipoprotein levels. Additionally, they may have
an impact on cognitive decline and glucose homeostasis. The most recent research on
anthocyanins as food supplements and nutraceuticals is summarized in this publication.
The general structure of anthocyanins is shown in Fig. (1).
Anthocyanins: Pharmacology and Nutraceutical Importance
Authors: Alam Md Shamshir , Maity Manish Kumar , Nazmi Abdul Salam , Ali Md
Published: November 2024

Anthocyanins are natural, colored, water-soluble plant pigments that belong
to the flavonoid, a subclass of the family polyphenol. Common dietary sources of
anthocyanins include red and purple berries, grapes, apples, plums, cabbage, and other
foods strong in natural colorants. Cyanidin, delphinidin, malvidin, peonidin, petunidin,
and pelargonidin are among the six most prevalent anthocyanidins in nature. Cyanidin3-glucoside, one of the anthocyanin pigments, is the main anthocyanin present in most
of the plants. Following ingestion, anthocyanins are absorbed in the digestive system,
with the distal lower colon meant for the major absorption and metabolism.
Anthocyanins are extensively broken down by microbes in the colon before being
absorbed and used by humans in phase II metabolism. As a result, hybrid microbialhuman metabolites are created, which are then ingested and boost the anthocyanins'
bioavailability. Colored anthocyanin pigments are traditionally used as natural food
colorants. In addition to their usage as natural colors, anthocyanidins and anthocyanins
are potential medicinal components that have a variety of positive health effects.
Anthocyanins provide several health advantages, particularly in the prevention of
oxidative stress-related illnesses, including cardiovascular, metabolic, and neurological
disorders. According to new data, the regulation of gut microbiota may also be linked
to the health-promoting benefits attributed to anthocyanins. Despite the potentially
widespread biological activity of anthocyanins, safety and toxicological concerns are
relatively minor. The advantages of anthocyanins for health have been the focus of
extensive study over the last two decades. This book chapter focuses on a thorough
overview of the most recent research on anthocyanins, their pharmacological properties
and nutraceutical values in human health.
Therapeutic Efficacy of Anthocyanins in Metabolic Disorders
Authors: Dhankhar Sanchit , Chaudhary Kakul , Chalotra Rishabh , Saini Monika , Gupta Sumeet , Chauhan Samrat
Published: November 2024

Metabolic syndrome (MetS) is a chronic disorder developed with cumulative
symptoms of diabetes mellitus, hypertension and dyslipidemia. The etiologic causes of
metabolic syndrome are a sedentary lifestyle, poor dietary choices, and hereditary
factors, which have a negative impact on the health of people by increasing the risk of
cardiovascular problems, organ damage, and additional pathology related to MetS.
Anthocyanins (ANTs) are plant-based biomolecules that promote health and belong to
a polyphenols subclass of flavonoids. Concurrent research reports have found that
plants rich in ANTs may have therapeutic advantages for diabetes, obesity and MetS by
decreasing insulin resistance, poor glucose resistance, dyslipidemia, high cholesterol
levels in serum, hypertension, and inhibiting free radical formation. This chapter
reviews the therapeutic advantage of ANTs in the management of MetS, along with
their pharmacological mechanisms and biopharmaceutical functions. Similarly, the use
of ANT-rich supplements is discussed for their potential in the control of MetS.
Role of Anthocyanins in Neurological Disorders
Authors: Basheer Vajiha Aafrin , Maity Phalguni , Sofalas Prejesh Samuel , Vallinayagam Sugumari , Ravi Sai Nandhini , Babu Packirisamy Azhagu Saravana
Published: November 2024

Anthocyanins, natural pigments abundantly found in various fruits and
vegetables, have attracted increasing attention for their potential role in mitigating
neurological disorders. This review explores the multifaceted neuroprotective effects of
anthocyanins, focusing on their ability to counteract oxidative stress, modulate
neuroinflammatory responses, and influence cognitive function. Drawing on a diverse
range of studies, both In vitro and in vivo, we examine the impact of anthocyanins on
neuronal health and their potential therapeutic applications in neurodegenerative
diseases. The antioxidant properties of anthocyanins play a crucial role in reducing
oxidative damage, while their anti-inflammatory effects contribute to the attenuation of
neuroinflammation, a common feature in neurological disorders. Furthermore,
anthocyanins exhibit promising potential in preserving cognitive function and
preventing neurodegenerative conditions. This comprehensive analysis highlights the
emerging significance of anthocyanins as potential neuroprotective agents and
emphasizes the need for further research to unlock their full therapeutic potential in the
context of neurological disorders.
The Role of 5G in Creating Smart Cities for Achieving Sustainable Goals: Analyzing the Opportunities and Challenges through the MANOVA Approach
Authors: Tripathi Mano Ashish , Singh Sujay Vikram , Rajkumari Yaisna , Geethanjali N. , Kumar Devendra , Aarif Mohd
Published: November 2024

The next generation of mobile technology, known as 5G, poses a huge
challenge to the existing state of the communications industry since it intends to solve
the issues that have plagued the 4G network in its current iteration. This cutting-edge
technology enables the establishment of multiple connections all at once and maintains
network ubiquity even in settings that involve high levels of mobility or densely
populated areas. As a result, smart cities and intelligent transport systems may stand to
benefit from its use. 5G will make it possible for the actual Internet of Things and the
Internet of Vehicles to become a reality if this plan is implemented. The advent of 5G
will herald the beginning of a new era of opportunities for networks and services. It
will help in maintaining an increased data rate, reduced latency, huge simultaneous
connections, and ubiquity of networks around the world. 5G will also be a crucial
enabler for a true Internet of Things because of its capacity to connect a vast number of
sensors and actuators while following severe energy efficiency and transmission limits.The Internet of Things (IoT), a new digital communication paradigm, has made it
possible for things that are often found in daily life to interact with one another as well
as with people [6]. As a result, the objective of the Internet of Things is to expand both
the breadth and depth of the Internet. This will be accomplished by making it easier for
a wide variety of devices, including vehicles, home appliances, security cameras,
industrial actuators, and many more, to interact with one another in an unobtrusive
manner. When 5G is applied to the Internet of Things in cities, it may be able to keep
track of the total amount of energy that is consumed by all of the city's public services
(including lighting, traffic lights, security cameras, and the heating and cooling of
public buildings, amongst other things). Municipalities will, among other things, be
able to manage their energy resources more effectively if they have access to this
information.
Sentiment Analysis of Tweets Related to Russia Ukraine Conflict Using Bi-Directional LSTM Network for Post-Traumatic Stress Disorder Early Detection
Authors: Shlkamy Eman Sedqy , Maher Khaled , Sedky Ahmed Hesham
Published: November 2024

Techniques for sentiment analysis are crucial for examining people's
opinions. People's attitudes are influenced by the constant and rapid growth in the
amount of material provided on social networks. Most research, however, focuses on
sentiment analysis to determine how a war will affect the global economy.
Consequently, when studying international conflicts, national leaders and other
influential figures tend to receive more attention than public opinion and emotions. The
purpose of the article is to discuss the analysis of moods and focus on the analysis of
emotions and social opinions during the Russian-Ukrainian conflict in order to detect
the early signs of post-traumatic stress disorder (PTSD). Post Traumatic Stress
Disorder (PTSD) and realizing Sustainable Development Goals (SDGs) are vital.
PTSD, with its impact on mental health, poses challenges to achieving Goal 3 of Good
Health and Well-being. Additionally, it hampers access to quality education (Goal 4),
especially in formative years, and can disproportionately affect women, hindering
progress towards Goal 5 of Gender Equality. In the context of conflict, PTSD impedes
the establishment of strong institutions (Goal 16) and underscores the importance of
collaborative efforts (Goal 17) to address the complex challenges associated with
trauma for a resilient and sustainable society. This study is the first to propose a model
that reflects the desire to analyze the impact of this war on mental health during the
Russian-Ukrainian armed conflict. This can protect people from mental disorders and
suicide and provide clues for future research in this area. The method used in this work
is a bidirectional LSTM method with a focus-based network approach to analyzing the
sentiment of English tweets, using positive, negative, and neutral classification in a
multiclass approach to detect signs of PTSD. Sentiment analysis is a method for
extracting emotional content from textual information using natural language
processing (NLP). Our study aims to identify people with PTSD using sentiment
analysis by training a deep learning (ML) model on text data. Based on text mood
analysis, trained models can detect post-traumatic stress disorder (PTSD). We attained a 90.02% accuracy by combining the attentional mechanism with a bidirectional shortterm memory layer (Bi-LSTM). The findings of the suggested framework demonstrate
greater accuracy than earlier state-of-the-art investigations. By creating an early
detection model, post-traumatic stress disorder (PTSD) symptoms may be lessened.
Navigating Sustainability in Cyber Security: Challenges and Solutions
Authors: Naik R. Lakshman , Jain Sourabh , Manjula B.
Published: November 2024

Our daily lives are now completely integrated with internet access. The way
we interact with one another, the way we meet new people, the way we communicate
information, the way we have fun, and the way we shop have been transformed as a
result. They have an impact on many of our daily activities. Today's digital
environment has made cybersecurity a requirement rather than a luxury. Cybersecurity
refers to a group of security techniques that can be used to protect user data and the
internet against attack and penetration. A cyber defense system's primary goal is for
data to be confidential, integral, and available.With one of the world's fastest-rising technological hubs comes a heightened danger of
cyberattacks, but India has swiftly emerged as one of them. Indian companies are
dealing with a wide range of security issues, such as financial fraud, data breaches, and
state-sponsored attacks. One of the biggest and most significant forces of sustainable
economic and social growth is information technology.More precisely, cyber security is now viewed as one of the most important components
in guaranteeing global sustainable development. It has been noted that the United
Nations Sustainable Development Goals (UNSDG) have prioritized cyber security to
protect the cyber environment. To achieve the objectives stated in the Nation for
Sustainable Development Goals, trust in ICT is essential. The goals of sustainable
development might be challenging to achieve in the absence of a stable and secure
cyberspace.The chapter highlights the part played in establishing stronger cyber security standards
as an impetus for sustainable development through the state, business, and other nonstate individuals. In addition to improving online security and protecting India from
cyber threats and vulnerabilities, more effective policymaking, improved tools and
techniques, cyber architectural designing, and collaborative efforts of private parties
like media, industry, civil societies, and other nations and international organizations
will also play a vital role towards achieving the global sustainable development goals.Nations, as well as states, need essential cybersecurity that not only protects from the
current threats but also enables proactive protection against emerging and forthcoming
threats to be able to confidently respond to latest challenges as cyberattacks become
more complex.
Enhancement of Crop Yields and Resource Management for Sustainable Farming in Smart Agriculture: A Multi-Modal Approach Using Machine Learning and Deep Learning
Authors: Afaq Yasir , Akram Shaik Vaseem
Published: November 2024

Smart agriculture is a new sector that integrates cutting-edge technologies
for transforming conventional farming methods into sustainable farming methods, such
as increasing crop yields, lower expenses, and conserving natural resources. Machine
learning (ML) and deep learning (DL) are two significant techniques for smart
agriculture that can be used to analyze enormous volumes of data and extract
significant insights to enhance agricultural practices. In this context, ML and DL may
be utilized for a number of tasks, including crop yield prediction, disease and pest
detection, weather pattern monitoring, and irrigation and fertilization management. The
proposed chapter investigates the utilization of ML and DL in smart agriculture and
highlights some of the most promising uses of these technologies. The study addresses
the obstacles and potential of adopting ML and DL in agriculture, such as data quality,
privacy problems, and the requirement for specialized hardware and software. The
study also looks at some of the most important developments in smart agriculture,
including the usage of sensors, drones, and other IoT devices, as well as the integration
of ML and DL with other technologies like precision farming and robotics. Overall, we
believe that ML and DL have the ability to transform the way we produce food and
manage our natural resources by empowering farmers to make better decisions,
decrease waste, and boost production.
The Integration of Robotics in Advancing Smart Health Echo Systems
Authors: Singh Rajesh , Gehlot Anita , Joshi Kapil
Published: November 2024

Healthcare 4.0, often known as the fourth manufacturing revolution, is a new
concept. The concept relies on intelligent robots with access to huge amounts of data
and the ability to make decisions without the assistance of humans. The employment of
robots in healthcare involves the difficulty of integrating new technology into an
already complex, highly regulated system. Although robots have made multiple
activities easier, some unforeseen consequences have changed ethical rules and
pharmacist employment. Lio, a personal assistive robot, was immediately modified
during the COVID-19 pandemic to handle additional functions like disinfection and
remote detection of elevated body temperature. It complies with ISO13482 - personal
care robot safety rules, allowing it to be tested and deployed directly in care facilities.
To keep up with the speed of rapidly changing technologies, a low-cost, highly
efficient localization solution for wireless sensor technologies is critical. The suggested
system provides a solid foundation for future testing and optimization in collaboration
with the user, ensuring a useful and appropriate mix of sensors and technical equipment
with which the user is familiar.
A Conceptual Framework on Migrant Workers: Evaluation of Sustainable Rural Development through MGNREGS
Authors: Rath Jaya Prakash , Kumari Nisha
Published: November 2024

Public policies like the Mahatma Gandhi National Rural Employment
Guarantee Scheme (MGNREGS) are designed to mitigate unwarranted unemployment
and develop rural infrastructure and resources to have sustainable development in rural
India. The pandemics (e.g., flood, drought, and COVID-19) pose the greatest livelihood
challenge for these migrant workers. Does MGNREGS provide them with minimum
support for the sustainability of their familiesthrough wage employment? Does
MGNREGS work to contribute to rural sustainable development? To answer these
questions, this study attempted to have an appraisal of the performance of MGNREGS
both qualitatively as well as quantitatively across the country by taking a five-year
study period (including the COVID-19 period). The study was supported by a focus
group interview of migrant laborers who returned to Odisha during the initial phases of
the pandemic in India. In the second part, the previous five years’ data was collected
from the official website. A comparative cross-sectional analysis of employment
generation through MGNREGS in the pre and post-COVID-19 period was made. An
administrative efficiency index (AEI) of the program was prepared and compared to
the period from April- September 2016 to 2020 for the entire nation. The results
explored that there was a significant employment generation through MGNREGS for
migrant workers during this pandemic. A conceptual model of ‘migrant employment
during the pandemic’ was proposed on the basis of the empirical results. The model has
both theoretical and practical implications.
The Role of Big Data Analytics as a Critical Roadmap for Realizing Green Innovation and Competitive Edge and Ecological Performance for Realizing Sustainable Goals
Authors: Tripathi Mano Ashish , Goswami Indrajit , Haralayya Bhadrappa , Roja M. Parveen , Aarif Mohd , Kumar Devendra
Published: November 2024

Big data analytics (BDA), as an important tool, is now available to
companies who are struggling with problems related to sustainability. However, there
are not many case studies of BDA in the academic literature, despite the fact that it has
the potential to increase the eco-efficiency of manufacturing. This study focuses
specifically on the manufacturing sector to investigate the impact of BDA on green
innovation (GI), competitive advantage (CA), and environmental performance (EP) in
the context of the manufacturing industry. Big data analytics, also known as BDA, is a
relatively new field that has emerged as a result of the growth of contemporary
computers and their various uses. The relatively new subjects of business data analytics
(BDA) and business analytics (BA) have piqued the attention of both working
professionals and academics. The purpose of this article is to conduct an analysis of the influence that Big Data has
had on four important performance indicators: innovation, competitive advantage,
productivity growth, and support with decision-making. Big data may help
organizations obtain vital insights about their consumers, products, and operations,
despite the fact that it does come with a few negatives. Businesses are in a better
position to quickly implement new ideas, provide better service to customers, increase
efficiency, make decisions that are better informed, and ultimately outperform their
rivals when they have access to data insights. The expansion in both the amount andquality of the data that is now accessible has led to improvements in the capacities of
organizations as well as the opening of new doors leading to growth. Businesses are
renouncing established practices in favor of new, inventive, and innovative techniques
in order to redefine creativity, competitiveness, and productivity. It is vital, for the sake
of achieving sustainable objectives, to have an understanding of big data analytics as a
critical component of the road map for green innovation, competitive advantage, and
ecological performance.
Focused Ion Beam Methods and its Applications in Secondary Batteries
Authors: Yang Ni , Li Yali , Wang Lian , Song Tinglu , Su Yuefeng
Published: November 2024

This chapter discusses the major challenges of characterizing the
microstructure and morphology of battery materials, as well as the limitations of
current characterization techniques in lithium-ion batteries. To address these challenges,
the dual-beam system of focused ion beam scanning electron microscopy (FIB-SEM)
emerges as one promising solution. The FIB-SEM system enables accurate
manipulation and analysis of battery materials from both micro- and nano-scale
perspectives, thus providing valuable insights for the development of high-performance
and safe lithium-ion batteries.
X-ray Photoelectron Spectroscopy and its Applications in Secondary Batteries
Authors: Yu Chuguang , Lu Defeng , Xu Fan , Zhao Liyuan , Chen Yan , Zou Meishuai , Song Tinglu
Published: November 2024

As an important surface analysis technique based on the photoelectric effect,
X-ray Photoelectron Spectroscopy (XPS) enables both qualitative and semiquantitative analysis of the elemental composition and chemical state of the solid
material surface, and has thus been widely applied in secondary batteries. In this
chapter, we first delve into a detailed introduction of the working principle, main
functions, analytical capabilities and technical features of XPS. Following this, we
outline various types of XPS spectral peaks and elucidate general principles for data
analysis. Then, the preparation of diverse XPS specimens along with their packaging
and transfer processes are introduced. Last but not least, we comprehensively
summarize and discuss the application of XPS in secondary batteries, including the
characterization of electrode material composition, charge/discharge mechanism, solid
electrolyte interphase (SEI) structure, etc. Additionally, we provide examples of the
insightful information acquired through XPS and demonstrate how this data aids
researchers in achieving a more profound understanding of secondary batteries, which
highlights the increasingly important role of XPS in the development of secondary
batteries.
Ultrasonic Nondestructive Technique and its Applications in Secondary Batteries
Authors: Zhao Liyuan , Zhang Shixiong , Qian Mengmeng , Zhang Jie , Xue Zhaoyu , Tan Guoqiang , Song Tinglu
Published: November 2024

Secondary batteries have been widely studied due to their highly efficient
electrical and chemical energy-converting performance. Further improvement of these
batteries is expected to meet the growing demands of the economy and technology.
Various advanced characterization techniques have been applied in secondary batteries
to gain a deeper understanding of electrochemical evolution and detection in the
discharge/charge process. The ultrasound technique, with its high sensitivity, low cost
and real-time detection ability, shows great potential for the characterization of
secondary batteries. In this chapter, we introduce the fundamental principles of the
ultrasound technique and summarize its applications in secondary batteries.
As Semelhanças e Diferenças Semânticas: Uma Análise contrastiva do Futuro Simples em Português Europeu e o advérbio temporal “jiang” em Chinês
Authors: Cuerva Rafael Francisco Lam
Published: November 2024

This study aims to describe the semantic properties that characterize the Future Simple tense in European Portuguese, considering its complex nature, which encompasses both modal and temporal aspects. In contrast, in the Chinese language, there is not the same compatibility between the use of morphological tense and interphrasal communication. In this regard, we propose to conduct a contrastive analysis with its counterpart in Chinese, the temporal adverb "jiāng" based on corpus comparison, to identify possible convergences and discrepancies, weighting the hypothesis of potential changes in its linguistic behavior. This study contributes to the understanding of semantic nuances between the two languages and to improve the teaching and learning of Portuguese and Chinese.
Factors Contributing to Formation and Existence of Community Identities in Bangkok Metropolis
Authors: Chitchakkol Nutdhapol , Rugwongwan Yanin , Pongsermpol Chotewit
Published: November 2024

In Bangkok, some traditional communities have maintained their identity despite urbanization. This research investigates the factors that influence the formation and existence of identities in three historic communities: Sam Phraeng, Talat Noi, and Soi Prachanaruemit (Wood Street). The research uses surveys, observations, and interviews to examine tangible and intangible elements. The results indicate that community identity originates from tangible elements such as architecture and landmarks, including intangible elements such as economics and society. Participation is essential to maintaining these identities, which requires effective community management, leading to income generation through activities and tourism that reflect the existence of community identities.
Knowledge, Attitude and Practice of Conventional Medicine Among Thalassaemia In Malaysia: Conceptual paper
Authors: Zainuddin Nurdiana , Ismail Wan Ismahanisa , Nalliappan Parameswari , Hidayah Karuniawati
Published: November 2024

Thalassaemia is chronic hereditary blood disorder. Medication has extended patients' lifespans, but research on their quality of life is scarce due to psychological impacts and medication adherence issues. The objective is to develop and validate a survey assessing the knowledge, attitude, and practice of Malaysian thalassaemia patients towards medication. We will use an exploratory mixed-methods approach with ethical approval from UiTM. Phase I involves semi-structured interviews with thalassaemia patients. Phase II focusses on creating and validating KAP instruments with expert panels and pilot testing. The tools will help medical professionals gather data to improve treatment compliance.
Social media, destination framing and its impact on culinary heritage tourism from the traveller's perspective
Authors: Abdul Latip Muhammad Safuan , Tumin Siti Aisyah , Trupp Alexander , Hamali Ahmad Shuhaib
Published: November 2024

The study explores how the framing of culinary heritage destinations influences travellers' perceptions, with a particular focus on social media platforms. Qualitative research was conducted through in-depth, face-to-face, and semi-structured interviews with twelve participants in Malaysia with active social media accounts. The research findings highlighted the significant role of social media and emphasised the importance of utilising effective platforms and strategic framing to promote culinary heritage destinations and traditional foods. The study further suggests that framing culinary heritage destinations within a social media context can influence travellers to visit these destinations for their culinary offerings.
Chinese Teachers’ Perceptions on Perceived Teacher Support and Student Engagement
Authors: Shu Zhan , Mottan Kannamah , Chen Haowei , Pang Yao
Published: November 2024

This qualitative study investigates the perceptions of teachers regarding methods to enhance students' perceived teacher support and engagement at a higher vocational college in Zhengzhou, China. The participants consisted of four instructors, each specializing in different subjects. Data were collected through semi-structured interviews. The findings reveal several effective strategies that participants use to enhance perceived teacher support and suggest ways to boost student engagement. These strategies offer valuable insights for improving both perceived teacher support and student engagement in the context of Chinese higher vocational education. The study also suggests directions for future research.
Exploring Hypertensive Patients' Experiences and Preferences with Online Health Education
Authors: Ab Hamid Mohd Ramadan , Baderol Allam Fatimah Najihah , Majid Norhaini , Ridhwan Muhammad Umar
Published: November 2024

There is a lack of research on patients' experiences and preferences when using such websites among patients with hypertension. This study aimed to explore their experiences and preferences for health education websites. The study employed a qualitative approach using in-depth interviews with 14 participants in Selangor. Patients' experience and preferences of the website were categorised into two main themes, 1) quality of the content, and 2) design and appearance. Patients preferred that the website’s content to be more practical and the design to be more user-friendly. In conclusion, website must be designed tailored to the needs of the target group.
Exploring challenges and demands of practising healthy eating in young adults: a qualitative study
Authors: Mohd Nor Nur Amira Najwa , Ismail Nazrul Hadi , Abdul Hamid Syahrul Bariah , Al Mukhlas Fikri
Published: November 2024

Transitioning from adolescence to adulthood for individuals aged 18 to 29 involves challenges and demands. This research explores the key challenges and needs of the lived experiences of young adults aged 18 to 29 in practising healthy eating. A qualitative research methodology was employed, using a phenomenological approach to investigate personal and subjective experiences. The study revealed five focused topics and 20 themes clustered into thirteen information categories reflecting their challenges and demands. It highlights knowledge of healthy eating practices among young adults and the need for targeted support systems and interventions to assist young adults in managing these challenges.
Understanding of the Transformational Rural Actors’ Behaviors: A Review
Authors: Nurul Alia Nasuha Samsudin  , Mohd Fadzil Abdul Rashid  , Lim Seng Boon , Muhamad Asri Abdullah Kamar  , Muhamad Azrul Azwan Azman  , Wilmar Salim
Published: November 2024

Rural actors’ behavior is crucial to materializing top-down rural development policies, albeit the rural physical planning. However, studies on detailed perspectives of rural actors’ behavior in response to complex stimuli are limited, particularly in the types of transformational rural actors’ behaviors. Specifically, this study aims to understand rural actors’ behaviors in transforming rural development. The systematic literature review methodology was applied. The findings revealed five themes: economy, environment, psychology, social, and technology—as the stimuli perspectives of transformational rural actors’ behaviors (TRAB) that shed light on rural transformation. This study contributes to synthesizing a new framework for conceptualizing transformational actors’ behaviors in rural development initiatives.
Evaluating the Smart City Status and Acceptance of ISO Standards: A Case Study of Malaysian Local Authority
Authors: Aziz Daimatul Syuhudiyah , Lim Seng Boon , Sutriadi Ridwan
Published: November 2024

While most national smart city frameworks outline the urban challenges, local authorities struggle to translate the top-down plan and align the action plan with ISO 37122 indicators, including the case of Majlis Bandaraya Diraja Klang (MBDK), Malaysia. This study aims to evaluate MBDK’s smart city status and examines the acceptance of ISO standards. The quantitative survey findings indicate a positive perception of smart city status, with unanimous agreement on the importance of ISO standards. This research contributed to one of the pioneer studies evaluating the acceptance of ISO indicators in smart city development in Malaysia and beyond.
Video Modelling Module in Improving Self-Help Skills of Children with Autism Spectrum Disorder
Authors: Noor Suhaimi Nor Syafiqa , Ahmad Zamir Che Daud  , Mohamad Qayum Mohamad Sabri  , Saher Al-Sabbah
Published: November 2024

This study aims to validate a video modelling module for children with Autism Spectrum Disorder (ASD) in Malaysia to improve their self-help skills. The module was developed using video modelling techniques to teach these skills successfully. Focus group discussion (FGD) was conducted to gather expert opinions on the module's content and structures. The results were analyzed through content analysis, revealing that the module achieved its objectives with minimal improvements needed before validation. The module can be widely used to improve self-help skills among children with ASD in Malaysia. The study's findings will be used to enhance the module further.