bluuebunny/crossref_metadata_2025 huggingface dataset:
Digital Health Technologies in Vision Care: Transforming Diagnostics and Management
Authors: Gaurav Pfranjpe Et al.
Published: February 2024

A significant change in the diagnosis and treatment of ocular disorders has resulted from the integration of digital health technology in the field of ophthalmology. This thorough analysis looks at the broad influence and uses of digital solutions in vision care, including wearable technology, teleophthalmology, diagnostic tools, and artificial intelligence (AI) algorithms.

With the use of digital imaging methods like fundus photography and optical coherence tomography (OCT), physicians may now see ocular components with previously unheard-of accuracy. These imaging modalities provide early illness identification and customised treatment plans when combined with AI-driven diagnostic tools.

Platforms for teleophthalmology provide remote screenings, consultations, and monitoring, greatly enhancing access to specialised eye care. Artificial intelligence (AI)-powered telemonitoring systems and mobile applications provide real-time data transfer for effective illness management and prompt treatments.
Perioperative Care Innovations: Optimizing Recovery and Reducing Complications in General Surgery
Authors: C.Z. Pardeshi Et al.
Published: February 2024

Significant progress has been made in perioperative care for general surgery with the goal of minimising postoperative complications and improving patient outcomes. This thorough analysis examines developments in the preoperative, intraoperative, and postoperative domains of the perioperative continuum. This article explores the most recent innovations influencing the profession, with a focus on patient-centered tactics, technology improvements, and interdisciplinary approaches.

Within the context of preoperative optimisation, therapies aimed at correcting dietary deficiencies, individualised exercise programmes, and psychological preparedness are critical to improving surgical patient readiness. Improved surgical methods, such as robotics and minimally invasive surgery, revolutionise surgical accuracy while reducing trauma and facilitating a quicker recovery.

Innovations in postoperative care, such improved recovery procedures and remote monitoring devices, speed up recovery and lower complications. Pain treatment and infection control advances in pharmacology have a major positive impact on patient comfort and lower morbidity.

This study emphasises the value of customised treatment plans, collaborative decision-making, and specialised communication while embracing patient-centered methods. It highlights how important it is for patients to be involved in their treatment, how to promote their own autonomy, and how to improve compliance with postoperative instructions.

This study seeks to highlight the combined influence of these breakthroughs on changing general surgery perioperative care paradigms through an examination of these advances. The perioperative setting is driven by the combination of innovative tactics, cooperation across varied healthcare specialties, and technology breakthroughs with the ultimate goal of optimising recovery and minimising problems.
Detection of SSH Password Guessing Attacks using Classification Algorithms
Authors: Golla Giridhara Maanas Et al.
Published: February 2024

The usage of SSH protocol has gained popularity among users due to its secure nature in recent times. Nevertheless, the SSH protocol can be susceptible to exploitation by hackers, who can access SSH servers without permission by exploiting vulnerabilities. SSH attacks cannot be completely detected using state-of-the-art security solutions like Firewall, Intrusion Detec- tion Systems, and so on. Malicious SSH traffic is created by malware and contains password guessing attacks. These attacks can result in compromising the security of servers and lead to the theft of private data. We aim to develop a robust and accurate SSH attack detection system that uses classification algorithms that can effectively differentiate between malicious SSH traffic and legitimate SSH traffic. In this paper, we have selected 14 classification algorithms like CNN, LSTM, Logistic regression, Deep Belief Networks, Auto Encoders, and so on. The process involves organising and preparing the data, extracting relevant features, and application of an ensemble learning approach with the selected classification algorithms. XGBoost is employed for model integration. The ensemble model achieves improved accuracy, successfully classifying between legitimate SSH traffic and SSH password guessing attacks.
Tomato Plant Leaf Disease Detection Using Convolutional Neural Network
Authors: Tejswini S. Danwadkar Et al.
Published: February 2024

Our country is growing country, India is mostly depended on the agriculture field, and Agriculture is pillar of our country’s economy. Because of this India has to improve in agriculture filed, in many of situations’ farmer face difficulties to detect crop disease in a case large area farm, or late in detection of crop disease in such cases farmer lose their all crop and face the huge loss, to avoid this, in agricultural field is detection of plant diseases is very important. And it is very difficult tasks.  In regular normal procedure it requires a more time period and trained person to detect accurate plant disease. In this paper, we proposed effective way for plant disease detection using computer science and machine learning model. Disease transmission from unhealthy plant to all other healthy plants in farm is one of the major damages to crop farm. And these diseases spread like forest fire and have the possible to impact the whole operation if not identified in early on. Now Plant disease detection methods helps to identify infected plants in a very early stage and also help us to identify plant disease in a wide range of area of crops in a cost-effective manner. The aim of this project model is to implement machine learning models, in our proposed system we take a plant leaf image on that leaf images we predict the plant disease using Convolution Neural Networks (CNN) model, in that we build a such a model to predict the plant disease with maximum accuracy and it is for plant disease detection for tomato plant. This machine learning model is analyzing different image metrics pixels data to determine the best performance of network. For that dataset were used around 7around 8016 images we going to use to train the model. We going to use 14 layers CNN models to get better accuracy results. Model consist various layers like convolution, pooling, flatten and dense. Early two layers that is preprocessing and augmentation of images Finally, we get the result of which disease that plant have.
DCNET-DCGAN: A Novel Deep Convolutional Neural Network for COVID-19 Classification
Authors: Sharmila V J Et al.
Published: February 2024

Coronavirus referred to as COVID-19 affects innumerable lives, causing havoc on public health and global economy. The limitation of clinical expertise, medical tools, and testing kits increases the widespread of COVID -19 across the globe. An accurate identification process is necessary for early detection of COVID-19. Recent studies state that the images obtained from the chest X- Rays are highly consistent in diagnosing COVID-19 rather from RT-PCR (Reverse-Transcription-Polymerase-Chain Reaction). Developing an automated CXR image diagnosing method for the accurate prediction is the objective of the proposed model. This objective is achieved by developing a proposed model composed of Deep Convolutional Generative Adversarial Networks (DCGANs) and a Deep Convolutional Neural Network (DCNET) using four distinct datasets (COVID -19 X-ray, COVID-chest X-ray, COVID-19 Radiography, and Corona Hack-chest X-ray). The proposed model exploits the deep learning features of DCNET with four layers of convolution, three layers of max pooling and fully connected layers, thereby achieving a classification accuracy of 98.8% which is better than the pre-existing method. It classifies the result as Normal, COVID-19 and Pneumonia. This model will be an apt solution for facilitating faster screening process for affected patients.
Impact of Artificial Intelligence based Learning Process on Students' Tendency to Involve in Independent Research at the Higher Secondary School
Authors: Mohammad Mazedul Huq Talukdar Et al.
Published: February 2024

The integration of artificial intelligence (AI) has become increasingly essential in implementing innovative instructional approaches at Higher Secondary School (HSS). The demand for advanced education that integrates intelligent technologies to improve the overall educational experience is growing. Individuals that actively study artificial intelligence are more equipped to face future difficulties related to technology, society, and the environment. The Knowledge and Attitudes Survey (KAS) lacks empirical evidence regarding the motivation levels of students in their involvement with the field of AI. The main purpose of this study was to examine how students' self-confidence, peer opinions, and personal beliefs affect their willingness to participate in AI education. A comprehensive longitudinal survey covered a total of 707 students who entered in higher secondary school. The survey examined the subjective norms, intentions, and knowledge of the participants, as well as their acquaintance with AI, their attitude towards acquiring knowledge of AI, their inclination towards AI-based learning, and their self-assurance in studying AI. The participants displayed a primarily optimistic perspective on AI education, with 78.1% expressing positivity. Moreover, an overwhelming majority of 73.1 percent of participants exhibited assurance in their capacity to gain knowledge in the realm of artificial intelligence. The data indicate that a substantial majority of respondents, precisely 82%, recognized the influence of different elements, such as peer pressure, instructors, and families, on their choice to participate in AI courses. The results indicate that students' perception of social norms significantly impacts their motivation to study artificial intelligence. Students must demonstrate a heightened openness to AI learning, especially if they perceive support and approval from their teachers and peers. The desire of pupils to participate in AI learning was discovered to be impacted by their viewpoint, self-assurance, and perceived proficiency in the subject matter. Various tactics can be employed to boost students' motivation to engage in the study of AI at a HSS, as indicated by the research results. These tactics encompass the dissemination of knowledge regarding the importance of AI education, fostering favorable views towards the subject, and nurturing students' self-perception of their abilities and control. This study offers significant insights for government authorities, educators, and other stakeholders in KAS and similar educational settings.
A Proposed Framework for Financial Institutions Using Blockchain Tecnology
Authors: Hossam Mohamed Sherif Et al.
Published: February 2024

Blockchain technology plays a pivotal role in the banking industry, being recognized as one of the most crucial sectors. With the financial market expanding and the demand for banking services on the rise, the need for a robust banking system capable of offering top-notch services to clients is paramount. Regrettably, the current banking system in Egypt falls short of meeting these requirements. However, there is hope on the horizon, as blockchain technology has garnered widespread interest in the global banking community for its potential to mitigate fraud and other threats to banking operations. This study offers a concise overview of various blockchain architectures and trading systems, delving into their types and the popular platforms currently being utilized worldwide., such as Automated Clearing House (ACH).
Exploring Different Sensor Technologies for Infrasonic Cardiac Monitoring: A Review
Authors: S.Vivek Et. al
Published: February 2024

Infrasonic cardiac monitoring is a non-invasive technique used to detect and monitor cardiac activity by analysing infrasound waves produced by the heart. This technique has several advantages over traditional methods, including the ability to detect changes in infrasound waves that may indicate abnormalities in cardiac function. Infrasonic cardiac monitoring has been used in clinical settings, research studies, and emergency situations and has the potential to revolutionize the field of cardiology by providing a non-invasive method of detecting and monitoring cardiac activity. While there are some challenges associated with this technique, ongoing research and technological advancements hold promise for addressing these challenges and improving the accuracy, reliability, and accessibility of infrasonic cardiac monitoring. This paper aims to provide an introductory overview of infrasonic cardiac monitoring, including its principles, methods, challenges, and future prospects.
Cloud System Structure Pre-Warning System and Method for Canal type Reservoir Tributary Bay Water Bloom
Authors: Nagarajan Krishnamurthy Et. al
Published: February 2024

This research proposes a cloud system structure pre-warning system and method for canal type reservoir tributary bay water bloom. The system consists of five modules: monitoring cloud module, information cloud module, application supporting module, water bloom pre-warning module, and discussion decision-making module. The system achieves seamless linkage and operation control based on a cloud system structure, carrying out all-weather monitoring, cloud storage, and water bloom risk pre-warning. The water bloom pre-warning module consists of a risk analysis unit and a pre-warning and forecasting unit. The discussion decision-making module is used for achieving decision-making discussion and information sharing communication in a cloud environment. This study provides a new measure based on the cloud system structure for preventing and reducing water bloom events.
How can Women Working in Mining Achieve a Flourishing Life
Authors: Nabilah Masturah Alifah
Published: February 2024

Mining is a high-risk field of work, especially for women. A work environment that is prone to accidents is the basis for the application of strict work rules. This risk causes concern and has an impact on the individual’s process of achieving a flourishing life. Although, individual personality considerations also play a role in achieving flourishing. This study aims to determine the relationship between the big five personalities and development. This research is nonexperimental quantitative research with a correlational approach. The research respondents were 32 female employees who worked in the mining company. The age of the respondents was in the range of 20–54 years. The majority of respondents had a bachelor’s degree. As many as 68.75% of employees work in the office and 31.25% work in the field. The scale used is the Ten-Item Personality Inventory (TIPI) and the Flourishing Scale (FS). The analysis was performed with multiple linear regression. The results showed that big five personalities simultaneously does not affect flourishing (R = 0.515; P > 0.05). However, partially agreeableness and conscientiousness influence flourishing (R = 0.493; P < 0.05). That is, women who work in mining with agreeableness and conscientiousness tend to flourish more easily than extraversion, emotional stability, and openness to experience. However, the personalities of the big five were not an important consideration in achieveing a flourish life for women who work in mining company.
Keywords: big five personalities, flourishing, mining female employees
Disaster Mitigation for Students with Intellectual Disabilities
Authors: Zulfiana Uun , Achni Fathurrahman Amanda , Normalasari Nadia , Nurul Milah Wahidah
Published: February 2024

Children with intellectual disabilities in Batu still find it difficult to understand the disaster mitigation process. In fact, in Batu itself, natural disasters such as floods, landslides, and tornadoes often occur. Teachers and parents of individuals with intellectual disabilities are the closest people who also experience difficulties when a disaster occurs, especially in the process of education and disaster evacuation. The purpose of this study is to increase understanding of emergency evacuation and early warning of natural disasters for children with intellectual disabilities among parents, teachers, and BPBD using psychoeducation and focus group discussion (FGD) methods. This research was attended by foure people from BPBD Kota Batu, seven teachers from SLBN 1 Kota Batu, and six parents of children with intellectual disabilities. The results of the study showed an increase in parents’ and teachers’ understanding of disaster mitigation. This increased understanding made the subject carry out a process of simulating disaster evacuation activities for individuals with intellectual disabilities.
Keywords: focus group discussion, intellectual disability, mitigation, natural disasters
The Influence of Learning Style on Students' Concentration
Authors: Daly Miqdad Daly Ahmad Miqdad , Putri Andini Apriliani
Published: February 2024

Research between learning styles and learning concentration is rarely done. Learning styles are related to how students can be comfortable with a learning method, so learning styles can be a good indication of influencing learning concentration. This study aims to determine the influence of the three learning styles on learning concentration. The study uses a non-experimental quantitative method with a correlational design. The subjects of this study were 202 undergraduate students. The sampling technique used is convenience sampling. This research uses the Indonesian language learning style scale and the Indonesian language learning concentration scale. The hypothesis testing method used in this research is a multiple regression test. The results of this study found that the three learning styles did not have a significant effect on learning concentration.
Keywords: learning styles, learning concentration
Moral Disengagement Moderates the Relationship Between Anger Rumination and Bullying Behavior in Adolescents
Authors: Imro'atur Rosyidah Fifti
Published: February 2024

Bullying is an act of verbal, nonverbal, and physical violence. The cause is not trusting each other so that they bully each other even though the problem is trivial. In adolescence, individuals begin to have more abstract and reasonable thoughts, as well as the ability to draw conclusions from events. However, at this age emotions are still relatively unstable so that at this stage many are controlled by the emotions that exist in themselves. Teenagers who are victims of bullying tend to reflect on the distress they have experienced. They have a tendency to remember bad things that have happened in their lives and find it difficult to forget them, which is commonly called rumination. Previous research with child and adolescent subjects found that adolescents who experience victimization more often tend to experience rumination that causes anger and sadness. Moral Disengagement is considered a cognitive process that individuals use to justify behavior that they know is wrong. The purpose of this study was to determine the role of Moral Disengagement in moderating the relationship between anger rumination and bullying behavior in adolescents. This research uses a quantitative approach with a research design using ex-post facto which is carried out after a phenomenon occurs. Based on the results of the study, it was found that anger rumination has a significant role in the emergence of bullying behavior in bullying victims (Sig. 0.000 < 0.005). The results of this study support previous research on rumination and anger rumination in the development of bullying behavior. Interaction between variables X and Y is not significant, P = 0.886 (>0.05) which means that anger rumination does not affect bullying. Likewise, the interaction between variables M and Y is also not significant, P = 0.7945 (>0.05) which means that moral disagreement variables do not affect bullying behavior. The results of the research show that anger rumination plays a non-significant role in the emergence of bullying behavior in bullying victims (Sig. 0.8836 < 0.005). The results of this study do not prove the effect of anger rumination on the emergence of bullying behavior. This result is not in accordance with previous research on rumination and anger rumination affecting the emergence of bullying behavior.
Keywords: anger rumination, bullying, moral disengagement
Job Satisfaction and Organizational Citizenship Behavior (OCB): The Moderating Role of Social Identity
Authors: Dhiny Dewantara Nur
Published: February 2024

Organizational citizenship behavior (OCB) is a contribution from individuals who go beyond the role in the workplace from what is assigned and rewarded. Employees who are satisfied with their jobs may be more able to bring out OCB behavior. The relationship can be strengthened by each individual’s social identity. The purpose of this study was to determine the moderating role of social identity on the relationship between job satisfaction and organizational citizenship behavior. The subjects of this study were 75 employees who worked at the Aster Cosmetic company in Malang. The total sampling method was used, wherein the entire population served as the subject. A quantitative research design was used. Data were analyzed using the Hayes PROCESS. The results show that job satisfaction significantly affects OCB behavior. It can be explained that the higher a person’s job satisfaction, the more able the employee will be to show OCB behavior. Meanwhile, social identity is not able to moderate the relationship between job satisfaction and OCB.
Keywords: job satisfaction, OCB, social identity
School Well-being in the Implementation of Inclusive Education in Higher Education
Authors: Meizara Puspita Dewi Eva , . Basti , Tenriawaru Astiti , . Asmiati
Published: February 2024

Inclusive education echoed by the Indonesian government is still limited to elementary and secondary schools. It is now expected that individuals with disabilities must also be provided access to educational services at the tertiary level. This study uses a qualitative method in describing inclusive education that has been applied to four universities in Indonesia, namely: Universitas Brawijaya Malang as the main place of research, and the other three universities (UIN Sunan Kali Jogjakarta, Unika Atmajaya Jakarta, and Padang State University) as a comparison. There were 9 respondents in total comprising: the Manager of the Service Unit Disability, Lecturer, Psychologist, Student and Alumni. The method used is an interview. The results showed that every university that had implemented inclusive education provides services in accordance with the needs of disability through collaboration with various parties on campus so that optimal services are provided to students with disabilities. Moreover, everyone is involved in the process, ranging from the Rector (policy-makers), Deans, Head of Study Program, Lecturers and Students so that all assume their respective roles so that every aspect of school well-being can be achieved optimally. Among the aspects of school well-being, the aspect of loving has a very large role in the creation of welfare for students with disabilities. When students are able to feel understood and accepted, they will exert their utmost effort in maximizing their potential.
Keywords: higher education, inclusive education, school well-being
Moral Intelligence and Bullying At Junior High School
Authors: Yuli Nur Layli Budianti Eka , Firdiyanti Retno
Published: February 2024

There are many cases of bullying at junior high school level. Every school are now inclusive school because of the diverse culture, socioeconomic status, and students with various special needs. The diversity makes students look different. This is actually an opportunity for students to hone tolerance, or as opposite a high risk for occurrence of bullying. Therefore bullying is related to moral intelligence. If students can show empathy, they tend to think wisely and act positive. Coversely, those who bully others are students who lack kindness and act to suppres their peers. The purpose of this study was to determine the relationship between moral intelligence and bullying in junior high school students. The method used is quantitative with a correlational design. The subject were 300 junior high school students, boys and girls. The research used Moral Competency Inventory (MCI) scale and Olweus Bully/Victim Questionnaire (OBVQ) scale to collect the data, and data were analyzed using person product moment correlation. The results show negative and significant relationship between moral intelligence and bullying behavior in junior high school students with a correlation value of –0.633 and a significant value of 0.001.
Keywords: moral intelligence, bullying, junior high school student
Peer Counseling: Addressing Bullying Issues Among Adolescents
Authors: Firizbrilian Purbasafir Trialovena , Suminarti Fasikhah Siti
Published: February 2024

The problem of bullying is a severe issue among adolescents with far-reaching impacts on mental and social well-being. The increasing number of cases is often caused by poor handling and neglect, so victims do not get the psychological assistance they need. Peers have an essential role in adolescent development and can take a role in efforts to deal with bullying at school by becoming counselors for peers who need it. This study aims to improve the understanding and skills of peer counseling on student council cadres as agents of change in schools. This training combines psychoeducational methods to increase understanding of bullying and its implications, as well as providing peer counseling training to provide counseling skills to help peer victims of bullying. The subjects in this study were adolescents aged 13–15 years who were members of the intra-school organization (OSIS) and were taken using a purposive sampling technique totaling 31 subjects. This research is experimental research with a one-group pretest and posttest design. The results showed an increased understanding of bullying and skills in peer counseling. Based on the Wilcoxon test, it was found that the Asymp. Sig (2-tailed) value was 0.000 (sig. <0.05), so it was concluded that peer counseling training interventions were effective in increasing the understanding and skills of bullying and peer counseling.
Keywords: adolescent, bullying, peer counseling training, psychoeducation, school
Coleções em perspectiva
Authors: Sá Ivan Coelho de , Fonseca Maciel Antonio Silveira
Published: February 2024

Este artigo apresenta resultados obtidos a partir da análise do Sistema de Objetos Mineiros Desaparecidos, Recuperados e Restituídos – SOMDAR, ferramenta implantada pelo Ministério Público de Minas Gerais – MPMG, voltada para a recuperação de coleções ou objetos, tidos como bens culturais por sua relevância, subtraídos de instituições e/ou acervos particulares. Foi realizado um levantamento em três importantes bases de dados, responsáveis por mapear objetos desaparecidos e ilegalmente comercializados: o International Observatory on Illicit Traffic in Cultural Goods, vinculado ao ICOM, o Object Identification e a Consulta de Bens Musealizados Desaparecidos, do Instituto Brasileiro de Museus – IBRAM. O objetivo foi o de identificar se, e de que forma, o SOMDAR pode ser entendido como uma ferramenta capaz de apontar e combater as vulnerabilidades de acervos que são vítimas de subtrações criminosas. Os resultados iniciais apontam para a necessidade de que instrumentos semelhantes sejam disseminados nos demais entes da federação, dada a sua potencialidade de ser um aliado da preservação de bens culturais, dentro ou fora de coleções, além de integrar a sociedade civil para o auxílio na tutela do patrimônio cultural.
SOVYET BİRLİĞİ DÖNEMİ’NDE KIRGIZİSTAN’DA GENÇLERİN POLİTİK TOPLUMSALLAŞTIRILMALARI (SOSYALİZASYONU)
Authors: BEŞİRLİ Hayati , ÜNAL Ali
Published: February 2024

Toplumsal yapının sürdürülmesi nüfusa yeni bireylerin katılması ile mümkün olmaktadır. Ancak bu katılımın sadece istatistiksel olması beklenilemez. Bu durum bireylerin toplumsal yapının değerlerini içselleştirmeleri ile mümkündür. Bu süreç toplumsallaşma olarak ifade edilir. Politik sistemlerin de meşruiyetlerini sağlayarak varlıklarını koruyabilmeleri için politik toplumsallaştırma (sosyalizasyon) sürecine önem vermeleri gerekir. Politik kültürün unsuru olacak genç birey aynı zamanda bu sistemin savunucusu hâline de dönüştürülecektir. Sovyetler Birliği Dönemi’nde bireylere, çocukluklarından itibaren hiyerarşik yapı içinde politik sistemin değerlerini içselleştirmeye bağlı olarak yurttaşlık bilinci kazandırılması söz konusudur. Bu kapsamda çocuk ve genç bireylerin yaş ve eğitim durumları itibarıyla dâhil olacakları “oktyabryat”, “pioner” ve “komsomol” teşkilatları oluşturulmuştur. Bu sürecin ideolojik bir aktarım süreci işlevini görmesi ve genç bireylerin Sovyet ideolojisi esasında şekillenmeleri amaçlanmıştır. Bu bağlamda iyi bir yurttaş olma kapsamını, Sovyet ideolojisini benimseme ve bu ideolojiye sadık olma belirlemiş, bunun sağlanması için her alanda ideolojik aktarım esas alınmıştır. Bu makale politik toplumsallaştırma sürecinin Sovyetler Birliği’nde nasıl gerçekleştiğini, Kırgızistan örneğinde orta koymayı amaçlamıştır.
Kajian Penyakit Penyerta Pada Ibu Hamil Terhadap Kejadian Kematian Ibu Di Masa Pandemi COVID-19 : Sebuah Tinjauan Naratif
Authors: Fatiha Tasyakurrisma Adisa , Fauzirra Dhiya Azhar Aghitsa , Rona Elfa , Sylviana Girsang Elizabeth , Sugeri Rauf Azhar , Purnami Cahya Tri , Agushybana Farid , Winarni Sri
Published: February 2024

Latar Belakang : Kasus kematian ibu yang ditemukan dengan covid-19 diakibatkan penyakit penyerta sebelumnya, dengan penyakit penyerta paling umum yaitu obesitas, diabetes gestasional, dan asma. Ibu dengan penyakit penyerta atau komorbid lebih berisiko untuk tertular covid-19 dan dengan komplikasi yang lebih parah bahkan dapat menyebabkan kematian.
Tujuan : untuk mengetahui apakah covid-19 pada ibu hamil dengan penyakit penyerta (komorbiditas) akan meningkatkan keparahan penyakit dan risiko kematian ibu.
Metode : Metode penelitian yang digunakan adalah penelitian naratif dengan menggunakan metode literature review dengan mengumpulkan dan menyimpulkan data dari penelitian sebelumnya. Penelitian dilakukan pada Februari 2022. Penelusuran artikel penelitian sebelumnya dilakukan di portal SINTA, Scopus, PubMed, Elsevier, dengan kata kunci penyakit penyerta (komorbid), ibu hamil, kematian ibu, dan Covid-19.
Hasil : Hasil penelitian menunjukkan usia ibu hamil yang rentan terhadap penyakit penyerta dengan covid-19 pada kelompok usia 25-49 tahun. Terdapat 154 kasus meninggal dengan penyakit penyerta obesitas (RR/OR 2,48), diabetes gestasional (RR/OR 5,71), dan asma (RR/OR 2,05). Kasus lain yang ditemukan adalah pneumonia (RR/OR 1,86) dan preeklamsia (RR/OR 1,77). Obesitas merupakan penyakit penyerta yang paling sering ditemukan di berbagai negara dan diabetes gestasional merupakan penyakit penyerta paling berisiko pada kehamilan dengan risiko kematian tiga kali lipat.
Simpulan : Penyakit penyerta terutama obesitas, diabetes, dan asma berdampak pada tingkat keparahan infeksi covid-19 pada ibu hamil.
Evolution by natural selection is a scientific law and not just a theory
Authors: Crouch Daniel J.M. , Bodmer Walter F.
Published: February 2024

The concept of evolution by natural selection was developed primarily by Darwin and Wallace in the 19th century as an explanation for the diversity and origin of complex organisms. They, however, did not have access to a mechanism of inheritance, which was needed for a proper understanding of how evolution by natural selection could work. Mendel’s discovery of the basic laws of inheritance in diploid sexual organisms enabled Fisher, Haldane, and Wright to provide a theoretical framework for understanding the selective process of evolution by natural selection. The developing knowledge of prokaryotic microorganisms and the discovery of DNA or RNA as the fundamental basis of inheritance in all living organisms, together with Mendel’s laws, now provide the four basic conditions for evolution by natural selection, namely reproduction that is stable, but allows for variation that can increase fitness in the broadest sense. These definitive conditions establish an exponential growth law for evolution by natural selection that applied initially for the longest period of time to the evolution of asexual clonal organisms, and through Mendel's laws, extends to bisexual multicellular organisms. It is mistaking evolution by natural selection to be a scientific theory rather than a law that has led to unnecessary disagreements over its fundamental validity and explanatory power.
Staunch the Age Related Decline into Dementia, Cancer, Autoimmunity (POTS), Obesity, and Other Diseases with a Prebiotic, Probiotic, Postbiotic Triple Play
Authors: Chambers Patrick
Published: February 2024

“All diseases originate in the gut.” Hippocrates (400 BC) A healthy gut microbiome via the gut-brain-axis (GBA) elevates heart rate variability (HRV), a general measure of health and well-being. A dysbiotic gut microbiome, low in biodiversity and butyrate producers, alters tryptophan metabolism with release of proinflammatory cytokines, predominantly TNF-α, IL-6, and IL-1β. These also characterize chronic inflammation, oxidative stress, and a multitude of diseases, all exhibiting low HRV. Gut dysbiosis upregulates IFN-γ and with it IDO (indoleamine 2,3 dioxygenase). Tryptophan pivots from serotonin synthesis to that of IDO induced kynurenine, increasing the kynurenine to tryptophan ratio (KTR). An elevated KTR is positively linked to neurodegenerative and autoimmune diseases and negatively linked to HRV. Elevated IDO activity is not only enzymatic but also an intracellular signal transducer potentiated by TGF-β. This cytokine is the primary determinant of the TME. Also proposed is the gut-lung dysbiosis concept and consequent degradation of ACE2 (richest in lungs and gut). Leaky gut induced autoantibodies related to G-protein coupled receptors (GPCRs) in combination with increased Ang II further potentiate oxidative stress. Aldosterone and paroxysmal orthostatic tachycardia syndrome (POTS) paradoxes are highlighted in the context of GPCR and gut dysbiosis, and the role of Candida is explored. The triple play of a prebiotic (d-mannose), probiotic (bifidobacteria and lactobacilli), and postbiotic (butyrate) might improve intestinal barrier integrity, oppose entry of GPCR antigens, suppress the inflammatory cytokine triad, balance IFN-γ and TGF-β, suppress oxidative stress, depress KTR, elevate HRV, and extend lifespan and its quality.
Natural Environments in University Campuses and Students' Well-being
Authors: Ribeiro Helena , Santana Keila Valente de Souza , Oliver Sofia Lizarralde
Published: February 2024

Most recent university campuses follow the North American model, built on city limits or countryside, with large separate buildings in open green spaces. Studies suggest that prevalence and severity of mental health issues among university students are increasing over the past decade in most countries. University services were created to face this growing problem, however individual based interventions have limited effects on mental health and well-being of a large population. Our aim was to verify if and how the natural environment in Campuses is focused on programs to cope with the issue of mental health and well-being among students. Systematic review of literature was undertaken with search in Scopus and LILACS with the keywords “green areas” AND “well-being” AND “Campus”, following PRISMA guidelines. As a result, 32 articles were selected. Research on the topic is recent, mostly in the USA, Bulgaria, and China. Most studies used objective information on campuses’ greenness and/or university students’ perception. Mental health was usually measured by validated scores. Findings of all the studies indicated positive association between campus greenery and well-being of students. We conclude that there is a large potential for use of university campuses in programs and sites for students´ restoration and stress relief.
Effects of Heat Treatment on the Microstructure and Mechanical Properties of a Dual-Phase High-Entropy Alloy Fabricated via Selective Laser Melting
Authors: Tan Xiaojun , Wang Zihong , Chen Haitao , Peng Xuyun , Zhang Wei , Xiao Haibing , Liu Zhongmin , Hu Yu , Guo Liang , Zhang Qingmao
Published: February 2024

To enhance the applicability of dual-phase high-entropy alloys (HEAs) like Fe32Cr33Ni29Al3Ti3, fabricated via selective laser melting (SLM), a focus on improving their mechanical properties is essential. As part of this effort, heat treatment was explored. This study compares the microstructure and mechanical properties of the as-printed sample with those cooled in water after undergoing heat treatment at temperatures ranging from 1000 to 1200 ℃ for 1 hour. Both pre- and post-treatment samples reveal a dual-phase microstructure comprising FCC and BCC phases. Although heat treatment led to a reduction in tensile and yield strength, it significantly increased ductility compared to the as-printed sample. This strength-ductility trade-off is related to changes in grain sizes with ultrafine grains enhancing strength and micron grains optimizing ductility, also the influence of the content of FCC/BCC phases and dislocation density. In particular, the sample heat-treated at 1000 °C for 1 hour and then water-cooled exhibited a better combination of strength and ductility, a yield strength of 790 MPa, and an elongation of 13%. This research offers innovative perspectives on crafting dual-phase HEA of Fe32Cr33Ni29Al3Ti3, allowing for tailorable microstructure and mechanical properties through a synergistic approach involving SLM and heat treatment.
Disaggregation Model: A Novel Methodology to Estimate Customers Profiles in a Low-Voltage Distribution Grid Equipped With Smart Meters
Authors: Ramos Milis Guilherme Ramos , Gay Christophe , Alvarez-Herault Marie-Cécile , Caire Raphaël
Published: February 2024

In a context of increasingly necessary energy transition, precise modelling of profiles for low-voltage (LV) network consumers is crucial to enhance hosting capacity. Typically, load curves for these consumers are estimated through measurement campaigns conducted by Distribution System Operators (DSO) for a representative subset of customers or through the aggregation of load curves from household appliances within a residence. With the instrumentation of smart meters becoming more common, a new approach to modelling profiles for residential customers is proposed to make the most of the measurements from these meters. The disaggregation model estimates the load profile of customers on a low-voltage network by disaggregating the load curve measured at the secondary substation level. By utilizing only the maximum power measured by Linky smart meters, along with the load curve of the secondary substation, this model can estimate the daily profile of customers. For 48 secondary substations in our dataset, the model obtained an average symmetric mean average percentage error (SMAPE) error of 4.91% in reconstructing the load curve of the secondary substation from the curves disaggregated by the model. This methodology can allow the estimation of the daily consumption behaviors of the low-voltage customers. In this way, we can safely envision solutions that enhance the grid hosting capacity.
Rational Prescribing of Pancreatic Enzymes for Patients with Pancreatic Cancer
Authors: Garcia Mary Acelle , Imam Syed , Braun Ursula K , Jackson Leanne
Published: February 2024

Most patients with pancreatic cancer at some point present with symptoms related to exocrine pancreatic insufficiency (EPI). These include diarrhea, abdominal bloating, indigestion, steatorrhea, weight loss, and anorexia. Even though up to 80% of pancreatic cancer patients eventually present with symptoms related to exocrine pancreatic insufficiency, only 21% are prescribed pancreatic enzyme replacement therapy. This treatment is profoundly underutilized in the palliative care of these patients. The objective of this review is to discuss the pharmacology, pharmacokinetics, side effects, available evidence of effectiveness of pancreatic enzyme use for patients with pancreatic cancer, and challenges along with proposed solutions regarding its use. Pancrelipase is an expensive drug, and it is inactive if not taken correctly. The impact of symptoms of EPI can lead to poorer overall well-being. Pharmacists play a crucial role in properly educating patients on the correct use of pancreatic enzyme replacement therapy. Pancreatic enzyme replacement therapy (PERT) is a key strategy in managing symptoms of EPI and can improve quality of life, which is a central focus in palliative care.
Exercise Alleviates Aging of Adipose Tissue through Adipokine Regulation
Authors: Jia Dandan , Zhang Huijie , Liu Tiemin , Wang Ru
Published: February 2024

Adipose tissue undergoes changes with aging, leading to increased adiposity, inflammatory cell infiltration, reduced angiogenesis, heightened oxidative stress, and alterations in its metabolic function. Regular exercise has been recognized as a powerful intervention that can positively influence adipose tissue health and mitigate the effects of aging. However, the molecular mechanisms underlying the benefits of regular exercise on aging adipose tissue function remain poorly understood. Adipokines released through regular exercise play a potential role in mitigating adipose tissue aging, enhancing the metabolism of glucose and lipids, reducing inflammation and fibrosis, and promoting fat browning and thermogenesis. The goal of this review is to offer a comprehensive overview of the benefits of regular exercise in addressing the age-related decline in adipose tissue function. The significance of regular exercise in mitigating metabolic disorders associated with aged adipose tissue will be discussed.
Performance of High-Resolution WRF Modeling System in Simulation of Severe Tropical Cyclones over the Bay of Bengal Using IMDAA Regional Reanalysis Dataset
Authors: Koteshwaramma Thatiparthi , Singh Kuvar Satya , Nayak Sridhara
Published: February 2024

This study examines the performance of the Indian Monsoon Data Assimilation and Analy-sis (IMDAA) in predicting five extremely severe cyclonic storms (ESCS) over the Bay of Bengal. The Advanced Research version of the WRF (ARW) model is utilized for this analysis over the last two decades. The initial and lateral boundary conditions are derived from the IMDAA datasets with a horizontal resolution of 0.12° × 0.12°. Five ESCSs from the past two decades are considered: Sidr 2007, Phailin 2013, Hudhud 2014, Fani 2019, and Amphan 2020. The model is integrated up to 96 hours using double nested domains of 12 km and 4 km. Model performance is evaluated using the 4 km results, compared with available observational datasets, including the best-fit data from the India Meteorological Department (IMD), The Tropical Rainfall Measuring Mission (TRMM) satellite, and Doppler Weather Radar (DWR). The results indicate that IMDAA provides accurate forecasts for ESCSs Fani, Hudhud, and Sidr in terms of track, intensity, and mean sea level pressure, aligning well with IMD observational datasets. However, Sidr's track deviates more from the observations. The calculated mean absolute maximum sustained wind speed errors range from 8.4 m/s to 10.6 m/s from day-1 to day-4, while mean track errors range from 114 km to 496 km during the same period. Statistical analysis, including bias, mean error, and standard deviation, underscores the significance of ESCS prediction. The discussion also covers rainfall prediction, maximum reflectivity, and the associated structure of the storms.
Creating an Immersive Virtual-Reality Space for Multiuser Synchronous Co-Located Collaboration: Design Considerations and Influencing Factors
Authors: Feng Qinna , Luo Heng , Li Zijian , Liang Jiarong , Li Gege , Yi Yan
Published: February 2024

The last decade has witnessed rapid development of immersive virtual reality (IVR) and its application in various contexts. However, its application in supporting real-time virtual collaboration has been quite rare due to technical barriers and the lack of validated design principles. To address this research gap, this study designed and developed an IVR space to enable multi-user synchronous co-located collaboration. An evaluation study (N = 95) was conducted to explore its useful design considerations and the influencing factors for collaboration experience. The IVR space was enabled by the simultaneous localization and mapping (SLAM)-based inside-out tracking technique and was informed by four essential design considerations for promoting effective collaboration in IVR, namely, the role script, learning task, collaboration mechanism, and communication design. The study results revealed that students in general were satisfied with their collaboration experience in IVR, with social presence and collaboration competency as significant predictors of collective efficacy and social experience. Based on both quantitative and qualitative results, this study proposes four validated principles for designing effective IVR spaces to support synchronous co-located collaboration.
Contribution of Circulating Mfge8 to Human T2DM and Cardiovascular Disease
Authors: Rout Madhusmita , Malone-Perez Megan W. , Park Gilseung , Lerner Megan R. , Frazer J. Kimble , Apple Blair , Vaughan April , Payton Marvin , Stavrakis Stavros , Sidorov Evgeny V. , Fung Kar-Ming A. , Sanghera Dharambir K.
Published: February 2024

MFGE8 is a major exosome (EV) protein known to mediate inflammation and atherosclerosis in type 2 diabetes mellitus (T2DM) in animal studies. However, its role in the pathophysiology of human T2DM, obesity, and cardiovascular disease has been controversial and less explored. Earlier, we reported a rare Asian Indian population-specific missense variant (rs371227978; Arg148His) in the MFGE8 associated with increased circulating Mfge8 and T2DM. Here, we have further investigated the role of Mfge8 with T2DM risk in additional Asian Indians (n=4917) and Europeans and other multiethnic cohorts from UK Biobank (UKBB) (n= 455,808) and the US (n=1150). We also evaluated the exposure of Mfge8-enriched human EVs (with and without mutation) in zebrafish (ZF) for their impact on the cardiometabolic organ system.
Most individual carriers of Arg148His variant not only had high circulating Mfge8 but also showed a positive significant correlation with glucose (r= 0.42; p = 4.9x10-04), while the non-carriers showed a negative correlation of Mfge8 with glucose (r = -0.38; p = 0.001) in Asian Indians. However, the same variant was monomorphic in Europeans and other ethnic groups of UKBB and US cohorts. Even in the absence of Arg148His variant, serum Mfge8 correlated significantly with blood glucose both in Caucasians (r = 0.56; p = 8.4x10-10) and individuals from other ethnicities (African Americans, Hispanics, and others) (r = 0.31; p = 5.8x10-4). Since Mfge8 is an EV marker, the exposure of Mfge8-enriched human EVs to ZF larvae rapidly developed fatty liver disease and heart hypertrophy and exhibited redundant growth with poor muscular architecture with and without the high-fat diet (HFD), while the control group fishes developed fatty liver disease and heart hypertrophy only after the HFD feeding. With strong evidence from animal studies supporting the role of Mfge8 in obesity, insulin resistance, and the development of atherosclerosis in T2DM, the current research suggests that circulating Mfge8 may be a potential marker for preventing or reducing the risk of T2DM and cardiovascular disease.