bluuebunny/crossref_metadata_2025 huggingface dataset:
Scope on Triglyceride Levels in Elderly Dementia Patients Versus Controls: Systematic Review and Meta-Analysis
Authors: Ramadan Heba
Published: May 2024

Introduction
Triglyceride levels show controversial contributions in dementia patients. In this study, triglyceride levels were examined to demonstrate whether they increase or decrease in elderly dementia patients and other elderly individuals, whether there is a difference between elderly individuals with different forms of dementia and controls, and whether that difference is considered significant.
Methods
This analysis was performed via searching in Scopus, Web of Science, and Pubmed. A PRISMA checklist was followed to conduct the systematic review. The quality assessment was checked by the Newcastle-Ottawa for case-control studies. Meta-analysis was performed by SPSS, Version 28.
Results
Twenty-five studies consisting of 18943 cases and 212144 controls were included in the final analysis. Eighteen studies showed that the triglyceride levels in both patients and controls did not exceed the normal range (1.7 mmol/L or 150 mg/dl). A meta-analysis was also performed for the seven studies that revealed that triglyceride levels exceeded the normal range and no significant difference was established between the cases and controls (p-value = 0.18, 95% CI).
Conclusion
Triglyceride levels may not be a serious factor that should be considered in dementia, which differs from other areas of medicine, such as cardiovascular diseases.
Performance of Artificial Intelligence: Does artificial intelligence dream of electric sheep
Authors: Ioku Tomohiro , Kondo Sachihiko , Watanabe Yasuhisa
Published: May 2024

This study investigates the performance of generative artificial intelligence (AI) in evaluating the acceptance of generative AI technologies within higher education guidelines, reflecting on the implications for educational policy and practice. Drawing on a dataset of guidelines from top-ranked universities, we compared generative AI evaluations with human evaluations, focusing on acceptance, performance expectancy, facilitating conditions, and perceived risk. Our study revealed a strong positive correlation between ChatGPT-rated and human-rated acceptance of generative AI, suggesting that generative AI can accurately reflect human judgment in this context. Further, we found positive associations between ChatGPT-rated acceptance and performance expectancy and facilitating conditions, while a negative correlation with perceived risk. These results validate generative AI evaluation, which also extends the application of the Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology framework from individual to institutional perspectives.
Rotation-equivariant graph neural networks for learning glassy liquids representations
Authors: Pezzicoli Francesco Saverio , Charpiat Guillaume , Landes François Pascal
Published: May 2024

The difficult problem of relating the static structure of glassy liquids and their dynamics is a good target for Machine Learning, an approach which excels at finding complex patterns hidden in data. Indeed, this approach is currently a hot topic in the glassy liquids community, where the state of the art consists in Graph Neural Networks (GNNs), which have great expressive power but are heavy models and lack interpretability. Inspired by recent advances in the field of Machine Learning group-equivariant representations, we build a GNN that learns a robust representation of the glass’ static structure by constraining it to preserve the roto-translation (SE(3)) equivariance. We show that this constraint significantly improves the predictive power at comparable or reduced number of parameters but most importantly, improves the ability to generalize to unseen temperatures. While remaining a Deep network, our model has improved interpretability compared to other GNNs, as the action of our basic convolution layer relates directly to well-known rotation-invariant expert features. Through transfer-learning experiments displaying unprecedented performance, we demonstrate that our network learns a robust representation, which allows us to push forward the idea of a learned structural order parameter for glasses.
SmoQyDQMC.jl: A flexible implementation of determinant quantum Monte Carlo for Hubbard and electron-phonon interactions
Authors: Cohen-Stead Benjamin , Costa Sohan Malkaruge , Neuhaus James , Ly Andy Tanjaroon , Zhang Yutan , Scalettar Richard , Barros Kipton , Johnston Steven
Published: May 2024

We introduce the SmoQyDQMC.jl package, a Julia implementation of the determinant quantum Monte Carlo algorithm. SmoQyDQMC.jl supports generalized tight-binding Hamiltonians with on-site Hubbard and generalized electron-phonon (ee-ph) interactions, including non-linear ee-ph coupling and anharmonic lattice potentials. Our implementation uses hybrid Monte Carlo methods with exact forces for sampling the phonon fields, enabling efficient simulation of low-energy phonon branches, including acoustic phonons. The SmoQyDQMC.jl package also uses a flexible scripting interface, allowing users to adapt it to different workflows and interface with other software packages in the Julia ecosystem. The code for this package can be downloaded from our GitHub repository at https://github.com/SmoQySuite/SmoQyDQMC.jl or installed using the Julia package manager. The online documentation, including examples, can be obtained from our document page at https://smoqysuite.github.io/SmoQyDQMC.jl/stable/.
Asymmetrical zinc(II) phthalocyanines conjugated to nanomaterials for degradation of organic pollutants and inactivation of Staphylococcus aureus bacteria
Authors:   , Mgidlana Sithi
Published: May 2024

This thesis reports on the syntheses and characterization of asymmetrical phthalocyanines (Pcs) with different ring substituents (tert-butyl, ester, diimide, trimethoxy, acetophenone, heptanoylphenoxy, perfluorophenoxy, dimethoxy, propanoic acid, acetic acid, carboxylic acid, aminophenoxy, acrylic acid). Several nanoparticles including metal tungstate, capped with glutathione and 1-mercaptohexanol are prepared and characterized using analytical techniques. The synthesized Pcs are covalently linked to various nanoparticles (NPs) through ester and amide bonds to form Pc-NP conjugates, in order to improve their catalytic properties. The Pcs and their conjugates are characterized using different analytical techniques. The photophysics and photochemistry of the MPcs and conjugates are studied. The conjugates T). The complexes and the conjugates with nanomaterials are evaluated for singlet oxygen-generating ability. Conjugates generate higher singlet oxygen in comparison to Pc complexes alone. The photocatalytic activity of the conjugates of ZnPc complexes with NiWO4, Ag2WO4, Bi2WO6, CoWO4, and Ag-Fe3O4-based nanoparticles is evaluated based on photodegradation of methylene blue, tetracycline, and dibenzothiophene. The photocatalytic efficiencies of the synthesized phthalocyanine complexes increased in the presence of nanoparticles. This work also reports on the photodynamic antimicrobial chemotherapy activity of these materials against Staphylococcus aureus (S. aureus) bacteria in DMSO. The results indicated that silver-based nanoconjugates exhibit high antimicrobial activity with high log reductions compared to NiWO4, CoWO4, and Ag-Fe3O4-based materials. The z-scan technique is employed to experimentally test the nonlinear optical response of complexes and nanoconjugates in solution. The nonlinear absorption coefficient, third-order optical susceptibility and optical limiting threshold of the materials are obtained from the Z-scan aperture data. The nonlinear absorption parameters improved in the presence of semiconductor quantum dots, with 1-ethanoic-CdTe/ZnSeS/ZnO giving the best results due to the presence of electron-donating substituents.
The influence of banking liquidity risk on profitability: The moderating role of capital adequacy ratio
Authors: Meliza  , Abu Hasan Norraidah , Saputri Hermilasari
Published: May 2024

The decline in bank liquidity due to slowing economic growth in Indonesia has decreased bank profitability. COVID-19 and the increase in the number of non-performing loans increased the level of bank liquidity risk and decreased capital. Hence, the purpose of this study is to analyze the influence of banking liquidity risk on profitability in the Indonesian banking sector and to examine the role of capital adequacy ratio as a moderating variable. The method section explains panel data analysis using the random-effect model in analyzing the influence of liquidity risk on profitability and the role of capital adequacy ratio as a moderating variable. The results of the analysis show that liquidity risk has a significant positive influence on profitability at the 1% significance level. Moreover, the t-statistic value for capital adequacy ratio as a moderating variable is 2.59 at a 1% significance level. This result shows that the capital adequacy ratio can moderate the relationship between liquidity risk and profitability. Furthermore, the robustness test results show that the deposit risk ratio is a good indicator for estimating liquidity risk. In addition, this study is useful for the banking sector in managing its capital adequacy ratio and as a reference for the government in setting policies related to banking capital.
ESG factors in M&A in India: Performance and market insights from 2010 to 2023
Authors: Panda Manoj , Sharma Pankaj , László Vasa , Kapse Manohar , Sharma Vinod , Mahajan Yogesh
Published: May 2024

This study assesses the impact of mergers and acquisitions on Environmental, Social, and Governance (ESG) performance and market value of acquiring companies operating in India. Data were collected and analyzed from 69 M&A announcements from January 2010 to June 2023, sourced from the Bloomberg database. The analysis reveals a positive correlation between the post-merger market value of acquiring firms and their ESG performance, indicating that an improvement in ESG factors is associated with increased market value after mergers. Additionally, a positive correlation was identified between acquiring companies’ post-merger ESG performance and their target firms’ pre-merger ESG performance. This finding suggests that when acquiring a target firm with high ESG performance, the acquirer is likely to experience an improvement in its own post-merger ESG performance. Moreover, both the post-merger market value and ESG performance of the acquirer are likely to improve with the profitability and size of firms but will have a negative impact based on the leverage components of the acquiring firms. 
Customers’ Purchase Intentions on Herbal Products and Supplements During the COVID-19 Pandemic
Authors: Syafrizal Syafrizal , So Idris Gautama , Vafaei-Zadeh Ali
Published: May 2024

The research aimed to extend the Theory of Planned Behavior (TPB) by including health consciousness and health value as predictors of purchase intention on herbal products and supplements. The research applied quantitative hypothesis testing. Then, the convenience sampling technique was used in collecting research data. The survey was conducted on 260 herbal and supplement customers in West Sumatra. The research instrument was adapted from previous studies. Then, the research data were analyzed using Structural Equation Modelling (SEM) techniques with the software SmartPLS 3.0. The testing of extended TPB in the research finds that health consciousness and health value have a positive and significant effect on customers’ attitudes and purchase intentions. Among the three main predictors of purchase intention in TPB (customer attitude, subjective norm, and behavioral control), only control behavior positively and significantly affects purchase intention. This extended TPB contributes to the theory of purchase intention by including health consciousness and health value as new predictors in customers’ purchase intentions, especially for herbal products and supplements. The research implications are that marketers and other stakeholders need to carry out effective marketing communications about products and events that support the development of healthy patterns and lifestyles and spend some effort to facilitate consumers' access to herbal products and supplements.
Philosophy of Medicine and Its Role in the Formation of the Methodology of Science
Authors:   Sechenov First Moscow State Medical University, Monin Maxim A. ,   Sechenov First Moscow State Medical University,   Sechenov First Moscow State Medical University
Published: May 2024

The article raises the question of how much medical knowledge and its historical evolution, taken as a subject of scientific research, influenced the formation of the theory of science as a whole. Besides, it considers how it is possible, and whether it is possible at all, to build a general theory of scientific knowledge that would combine its cognitive, technological, and social aspects. The methodological programs analyzed in the article by Ludwik Fleck (“The Genesis and Development of a Scientific Fact”), Michel Foucault (“The Birth of the Clinic: An Archaeology of Medical Perception”, “Madness and Civilization: A History of Insanity in the Age of Reason”, and “The birth of Social Medicine”) and Bruno Latour (“Pasteur. War and Peace of Microbes”, “Laboratory Life”, and “Science in Action”) based on the analysis of medical knowledge or knowledge of related fields, not only immerse the process of obtaining new scientific knowledge in a rather complex and contradictory social context, but also show a variety of research perspectives, in which scientific activity can be considered. The analysis carried out on the base of these works made it possible to demonstrate a close connection between the cognitive problems as they are and those historical and social conditions within which these problems arise and find their solution. It is in the works that consider medical problems, this connection manifests itself especially clearly. Thus, it can be assumed that just the works of ‘medical orientation’ had an impact on the fact, that the theory of science in the second half of the twentieth century, in addition to epistemological issues, increasingly began to include consideration of the historical and cultural context of scientific research.
Post-Historicism and the End of the Historicist Project: Оn the Issue of Overcoming Historical Relativism in Analytical Philosophy
Authors:   St. Petersburg State University, Nikonenko Sergei V.
Published: May 2024

The article is devoted to consideration of theories of Post-Historicism in the analytical philosophy of history. It is emphasized that Post-Historicism initially performs a critical position to the linguistically oriented historical relativism. Theorists of Post-Historicism criticized discursive understanding of the subject of history, as well as the view of historian as author. They provide paradigmatic turn from the language of historians to the analysis of historical experience (understood as a special, ‘sublime’ experience). It is noted that in the center of the theories of Post-Historicism there are such categories as ‘narrative’, ‘past’, ‘memory’, ‘metaphor’, ‘representation’, etc. The narrativists approach involves the assumption that the historian does not work with events of the past, but only with the interpretations of it. Main historical method is the reconstruction of historical experience through productive reminiscence. There is a fundamentally new challenge: the creation of many local histories in the form of narratives, but without attempts to create ‘meta-narratives’. Retrospectivism in narrative approach is the desire of the historian to retell certain events of the past in the form of textual integrity. The integrity of the narrative as a historical text is based not according to linguistic but to the ‘aesthetic’ principle: it is rooted in describing some historical events in their unity as an experience of certain actors of those events, and considering historian as their interpreter. In the era of Post-Historicism, analytical philosophy of history seeks to design not discourse, but narrative, because the latter one initially appeals to empathize, not understand or build some linguistic kinship. The concept of metaphors is proposed, involving the symbolic interpretation of historical concepts and generalizations, according to which there is a possibility to establish ‘how’ was the past. From the author’s point of view, it is possible to base historical epistemology on the assumption of a symbolic interpretation of historical experience and narrative.
“Bullshit Job”: The Critic of Capitalism in D. Graeber’s Theory
Authors:   St. Petersburg State University, Naumova Ekaterina I.
Published: May 2024

The article is on the theme of the emergence of nonsensical job as a result of the Neoliberal Capitalism development. American anthropologist D. Graeber, the author of the conception of ‘bullshit jobs’, decided to solve the scholarly problem: why the fast-moving technical development run to the situation, when people start to work more instead to work less. It happens because the new nonsensical posts and jobs are built. Graeber proposes the ‘bullshit job’s’ classification showing that the contemporary capitalism creates the useless working place and pays people for doing nothing contrary to the economical law (minimization of costs and maximization of profit). The term ‘bullshit’ resulted from the word ‘bull’ which is rooted in French ‘bole’ (illusion, swindle). This fact shows that ‘bullshit jobs’ consist of an illusion and fraud: the person, doing some ‘bullshit job’, knows that his/her work is nonsensical and useless but he/she have to make a show (for himself and other people) that this is not the case. Graeber comes to the light that moral and psychical violence are rooted in contemporary labour relationships and it is shown the negative essence of the Neoliberal society. Graeber offers the initiative of the Universal Basic Income as the ‘medicine’ from ‘bullshit jobs’. Article shows that the governmental protection of the basic human needs operates as the Universal Basic Income in Socialist society. There were no ‘bullshit jobs’ in the U.S.S.R.
Proton Therapy: A Ray of Hope for the Cancer Patients
Authors: Khamkat Piyali , Barik Vivek , Mukherjee Swarupananda , Karati Dipanjan
Published: May 2024

Cancer is a life-threatening disease, and there are very few options to treat it almost
completely, with a high percentage of success rates. Proton therapy is a very unique and one of the
latest techniques to treat cancer with a very promising percentage of success rate. In this therapy, a
proton particle with high velocity is used, and it is superior to conventional photon or radiotherapy. In
this review, we have discussed the theoretical aspects of this technique and the latest variant of this
therapy called pencil beam proton therapy, which is a cutting-edge technique to treat cancer. We have
also tried to discuss the applications of proton therapy for different types of cancers.
Support Group WhatsApp Chat Method on Knowledge of Heart Failure Patients at RSUD dr. R. Koesma Tuban
Authors: Fauziansyah Ahmad , Yulian Wiji Utami  , Alfrina Hany  , Mohammad Fahrul Arifin  , Moh. Ubaidillah Faqih
Published: May 2024

Heart failure patients need to gain knowledge of heart failure, one of which is by providing education related to the process of heart failure, its causes and treatment, ways of self-care, how to take medicine, consumption of drinking water and salt intake in food to achieve actual health status. This study aims to determine the effect of group support with the WhatsApp chat method on heart failure patients. This type of research is quasi-experimental, with pretest and posttest control group designs, and it is conducted with a population of 50 patients with heart failure. We had 25 people in the treatment group and 25 people in the control group. Then, the normality test and data analysis were carried out using the Wilcoxon Signed Rank test < 0.05. The results showed that the average respondent was female 33 (66%), farmer occupation 22 (44%), and Killip I functional status was 41 (82%), and the result was p = 0.000 at the level of knowledge of the respondents. From the results of this study, it was concluded that the support group using the WhatsApp chat method can affect knowledge. Still, WhatsApp chat is more appropriate for heart failure patients with higher activities.
Adolescent Verbal Violent Behavior and Emotional Intelligence: A Cross-Sectional Study
Authors: Yunita Rizka , Isnawati Iin Aini
Published: May 2024

In today's world, verbal violence is a prevalent issue, especially among adolescents. Typically, the perpetrators are the victims' peers, and this can have detrimental effects on the victims, including a decrease in emotional intelligence. The purpose of the study was to examine the relationship between peer verbal violence and emotional intelligence in adolescents. The study utilized a cross-sectional design and involved 120 teenage boarding school students, with a sample of 92 active adolescent students selected through simple random sampling. The research instruments included a bullying questionnaire (consisting of 12 questions) adapted from Tower and an emotional intelligence self-assessment tool (comprising 20 questions) adapted from Sterret. Data analysis was conducted using the Spearman Rank Test, which revealed a significant relationship (ρ value of 0.000) between peer verbal violence and emotional intelligence in adolescents. The study highlighted the adverse effects of peer verbal violent behaviour, such as hindering self-development, reducing empathy, and causing anxiety and shame, as well as potentially triggering similar violent behaviour by the perpetrator. As a result, it emphasizes the need for schools to take collaborative action to minimize violent verbal behaviour.
Case Study: Criminal Psychology Analysis and Profile on a Case of the Judge Being Shot
Authors: Zhang Wei , Ye Zhuang
Published: May 2024

This paper provides a comprehensive criminal psychology analysis and profiling of a case involving the shooting of a judge. Two perpetrators, motivated by alleged injustices in divorce property disputes, targeted the judge, her family, and associates of their ex-wives, resulting in two fatalities and two injuries. The perpetrators eventually committed suicide after being cornered by police. The study delves into the psychological entanglements, latent stage, malignant transformation, implementation, and decline phases of the perpetrators’ criminal psychology. The case underscores the complexity of emotional homicides, the role of revenge and jealousy, and the dynamics of joint criminal activity.
Assessing the Key Factors Influencing Renewable Energy Generation in Mozambique: A Structural Equation Modelling Analysis
Authors: YongSheng Zhang , Maposse Carlos Nehemias , Emefa Ami Acorlor Garnet , Possible Okafor Nkechinyere
Published: May 2024

Structural equation modelling analysis was performed to identify various variables that influence the growth of Renewable Energy Production (REG) in Mozambique. The study revealed that the government's policies regarding renewable energy generation in Mozambique are of moderate quality. However, by implementing skillfully crafted policies and plans, there is a possibility for additional progress and growth. The progress of renewable energy initiatives in Mozambique is significantly influenced by the investment climate for such projects. Although the government has established a favourable environment for investors, it primarily caters to foreign investors rather than local and private investors. Environmental considerations significantly influence the growth of renewable energy generation (REG) in Mozambique. This study highlighted the need to consider environmental issues throughout the planning and execution of REG projects. The lack of technical and managerial proficiency in a particular area can be resolved by importing foreign specialists, either on a temporary or permanent basis. Concurrent with the global goal of shifting to clean energy-producing technologies, this study attempts to identify and assess the variables that influence the growth and development of renewable energy businesses in Mozambique. Setting priorities for energy efficiency can uncover several economic prospects, fostering the growth of a market for innovative solutions and facilitating the construction of specialized firms in this field. Consequently, this will entice investment from both domestic business owners and investors from other countries.
Migration, Human Trafficking, Sexploitation and Trauma in Amma Darko’s Beyond The Horizon
Authors: Nyuykighan Mbu Dora
Published: May 2024

Human trafficking and sexploitation have become prevalent migration configurations in Africa that often plunges the victims into harrowing mental, emotional, and physical trauma. This paper aims at portraying African female immigrants’ experiences in Amma Darko’s Beyond the Horizon projecting the female migrant characters as victims of human trafficking, sexual abuse, and economic exploitation in the hands of their selfish and egoistic husbands. Given the complexities of the lives of African women who immigrate to Europe and get caught in a spider’s web of prostitution and pornography, the fictionalized German universe in the text reveals that Europe is not the “Eldorado” where milk and honey flows in abundance as perceived by most Africans. The paper’s analysis employs a feminist analytical framework to examine the objectification and commodification of the black female body. It submits that, despite their traumatic experiences, these African immigrant women assert their sexuality by challenging the status quo thereby obtaining for themselves an emancipated female agency that allows them to take control of their own bodies as well as their financial gains.
A Study on Fiscal Policies for Rural Revitalization
Authors: Chu Jiajing
Published: May 2024

If we want to achieve comprehensive rural revitalization, emphasizing prioritizing agricultural and rural development, consolidating and expanding poverty alleviation achievements, and promoting the revival of rural industries. Rural revitalization has always been a key the people. However, in the current stage of rural revitalization work, there are still urgent issues to be addressed such as uneven development between villages, inadequate allocation of resources in rural areas, and low level of rural development. Therefore, fiscal policies as an important foundation for national governance should play their role by providing targeted support to promote vibrant and healthy development in rural areas.This paper first analyzes the concepts and current situation of fiscal policies and rural revitalization. It then explains the characteristics of existing fiscal policies that support rural revitalization. Finally, it summarizes the problems with current fiscal support for rural revitalization along with corresponding suggestions for improvement.
Evaluation of Severity Index of Road Casualties on Mangawan to Chakghat Section of NH-30 Using Machine Learning Approach
Authors: Khade Alkesh Kumar , Mehar Dr. Rakesh
Published: May 2024

Abstract: Each year, over 1.35 million people die in road accidents, and many more are seriously injured, according to the WHO. Predicting the severity of these accidents is vital for improving prevention and response plans. This paper proposes a new method to predict the severity of road accidents using various factors. This research focuses on road accidents at Sohagi Ghat on NH-30. The study looks at accident types and locations along a 3.67 Kilometer section of steep, challenging terrain. A safety audit was conducted on black spots and it revealed that 324 accidents occurred over five years, making this section particularly dangerous. Special safety measures are needed to reduce the risk in this area. The paper aims at forecasting of upcoming highway accidents through moving average approach, exponential smoothing approach and linear forecasting approach using the previous year’s data sets. With the help of Kaggle Data Directory, precise accident data for visualization is formed and then visualization of road accidents is performed on Python programming language-based Anaconda Navigator’s Jupyter Notebook. While accident severity index of Sohagi Ghat NH-30 is also carried out and some results of machine learning based visualization and some forecasting-based results are driven out and compared with each other. The study calculated accident severity and used Logistic Regression to train a model with 0.85 accuracy value. The precision, recall, and F-1 score of the model were perfect. Injury severity percentages were 10.8% fatal, 48.2% serious, and 41% minor. The Accident Severity Index for the NH-30 Sohagi Ghat location was found to be 0.211.
Implementation of AI-Based Robotic Self Navigation System
Authors: Bhosale Amar
Published: May 2024

Abstract: Artificial intelligence (AI) has revolutionized modern weapon systems, offering increased speed, precision, and capability in military operations. However, the use of AI-based weapon systems increases significant moral legitimate, and operational challenges that need to be satisfied in the development of AI-based weapon systems. Autonomous operation is a key feature of A-I-based weapon systems, posing important questions regarding accountability and the risk of unpremeditated outcomes. This automatic weapon is a remote weapon that is automatically aimed and fired at targets that are detected by sensors. The first of its kind to have an integrated system that includes stewardship, pursuit, and firing. The function of automatically selecting, attacking targets could be available on many platforms such as battle tanks, fighter jets, or ships. human out-of-the-the-scheme system, once activated, can select automatically and engage targets without further interference by a human operator. For example “loitering” weapons that once launched, detect interference and attack their conscious targets over a specified area without any further human interference or weapon systems that autonomously use electronic “cramming ” to confuse communications.
Smart Autonomous Nurse Assistant Robot (SANAR)
Authors: Kushwah Ms. Prema
Published: May 2024

Abstract: In the evolving landscape of healthcare, the integration of innovative technologies has become paramount to enhance efficiency, accessibility, and usability across all sectors, particularly in the medical industry. This project proposes the development of a Smart Autonomous Nurse Assistant Robot (SANAR) aimed at revolutionizing medical care delivery, especially during emergencies and pandemics like Covid-19. SANAR utilizes cutting-edge technology to streamline disease diagnosis, monitor patient health in real-time, and facilitate drug delivery. The core of SANAR's functionality lies in its utilization of a health tracker system-based IoT platform, which continuously analyzes vital patient data, including oxygen levels, pulse rate, and temperature. Through simple text commands and a timer-based medicine scheduler, SANAR ensures timely medication administration, leveraging a cloud server for seamless data access and management with utmost security. Equipped with advanced sensors such as oximeter, heartbeat, ultrasonic sensors, and a voice module, SANAR leverages Internet of Things (IoT) technology to enable data storage and retrieval over HTTP and MQTT protocols, facilitating connectivity and scalability. The primary goal of this project is to democratize smart automation in healthcare, making it accessible and affordable to all segments of society, ultimately empowering medical staff to deliver efficient and effective care.
The Impact of Artificial Intelligence on the Financial Sector
Authors: Thumar Prof. Rahul , Vaghasiya Prof. Ritesh
Published: May 2024

Abstract: Artificial Intelligence (AI) has revolutionized various sectors, with the financial industry being a prominent beneficiary. This review paper explores the multifaceted impact of AI on the financial sector, examining its influence on banking, investment management, fraud detection, customer service, and risk management. It highlights the transformative capabilities of AI technologies such as machine learning, natural language processing, and robotic process automation, while also addressing the associated challenges and future prospects
High-resolution monitoring and simulation of the temperatures in a borehole heat exchanger field over multiple years
Authors: Gebhardt Hannah , Mohammadi Hesam Soltan , Ebert Andreas , Bott Christoph , Visser Adriaan , Bayer Peter
Published: May 2024

Installation and operation of ground source heat pump systems build upon an enormous practical experience. As these systems are operated for decades, their techno-economic tenability strongly depends on the long-term in-situ heat transfer efficiency and thus the altered ambient subsurface temperatures. Imbalanced seasonal heat exchange causes thermal changes in the ground, which need to be understood to reliably predict the performance of a system during its lifetime. Despite extensive research, understanding the interaction between subsurface and borehole heat exchangers (BHEs) remains inconclusive and not thorough enough. This is due to the scarcity of detailed monitored sites and the monitoring time needed, which renders model calibration with data over multiple years or decades barely feasible. This study monitors an operational field over six years to better understand subsurface thermal changes induced by BHE operation. The ground source heat pump system supplies heat and cold for a multi-family house in Lausen, Switzerland, and consists of an array of three double-U tubes of 146 m each, along with one observation borehole. Ground temperatures were measured by distributed temperature sensing (DTS) at a temporal resolution of 20 minutes in each BHE as well as in the observation borehole. The thermal conductivity of different subsurface layers was derived through an enhanced thermal response test before the start of operation. The monitored data at the location of the BHEs reveal an annual cooling trend of around 0.55 Â°C. For the understanding of the controlling factors and processes, these cooling trends and temperature variabilities are reproduced in a numerical model. This is also done to evaluate the predictive capabilities of the model and to ultimately judge the spatial and temporal resolution needed for reliable simulation. Thereby, a three-dimensional U-tube model with heat extraction and free cooling was implemented for the site. Comparison of the simulation against measured data of the three BHEs reveals a fair agreement with a root mean squared error (RMSE) of 0.82 Â°C, whereas the full variability of observation borehole data cannot be reproduced by the model.
IEA ES Task 38: Ground source de-icing and snow melting systems for infrastructure
Authors: Gehlin Signhild , Salciarini Diana , Ghalandar Taha , Andersson Olof , Adl-Zarrabi Bijan
Published: May 2024

Thermal de-icing and snow melting systems offer alternatives to mechanical and chemical methods for clearing snow and ice from roads, bridge decks, ramps, and other transport infrastructure. Snow melting and de-icing systems with hydronic heated pavement (HHP) are utilized in various countries for infrastructure and other applications, often employing district heating return flow, electric heating, or gas boilers as heat sources. Alternatively, the ground can serve as a heat source for HHP systems, with or without the aid of heat pumps. These systems may also utilize the pavement as a solar heat collector in the summer, thereby cooling the road surface and prolonging the lifespan of asphalt roads by preventing rutting. In 2021, the International Energy Agency (IEA) initiated the international collaboration project Task 38 - Ground Source De-Icing and Snow Melting Systems for Infrastructure. Sweden, Turkey, Italy, Germany, France, and Belgium are part of this collaboration project. This paper provides an overview of the work within Task 38 and the current state-of-the-art of ground source de-icing and snow melting systems for infrastructure.
Drake Landing Solar Community: an analysis of different technology scenarios
Authors: Kosteniuk Isabelle , Thornton Jeff , Mesquita Lucio , Boulter Raymond
Published: May 2024

The present work simulates the Drake Landing Solar Community (DLSC) in Okotoks, Alberta, using calibrated borehole heat exchanger models to evaluate the energy performance of different technology scenarios. Four technology scenarios were compared to the existing design, including an updated DLSC solar thermal system with high efficiency collectors, a photovoltaic plus heat pumps and electric boilers system with high temperature seasonal thermal storage, a conventional ground source heat pump system, and a hybrid solar thermal and photovoltaic system with heat pumps, electric boilers and seasonal thermal storage. The ground source heat pump scenario presents the highest SPFnet (seasonal performance factor net) to solar panel area with one caveat: the operation is dependent on ground temperature, which goes down with time, s, and the heat pump operation would experience interruptions after 30 years of operation without heat injection into the ground. The solar thermal + borehole thermal energy storage systems presented the highest SPFs of the options evaluated.
An exploration of a heuristic predictive control strategy for ground source heat pumps coupled to standing column wells
Authors: Tonellato Giulio , Kummert Michaël , Candanedo José , Beaudry Gabrielle , Pasquier Philippe
Published: May 2024

Standing column wells (SCW) have shown to be a cost-effective hybrid ground heat exchanger (GHE) configuration suitable for high-density urban areas as they benefit from groundwater advection while not requiring particularly productive aquifers. However, operating SCWs in cold climates can represent a control challenge since the groundwater can approach freezing conditions while recirculating; on the other hand, submersible pumps can cause a significant power usage. This article explores the potential of a heuristic predictive pumping control strategy built with an accurately calibrated white-box model of a real case study in Mirabel, Quebec, Canada. Results show that it can be used to both contain pumping power and safely operate the SCWs without using an electric boiler as anti-freezing protection. In an exceptionally cold month, the predictive control strategy effectively prevents the boiler intervention, resulting in a 3.25 times reduction in peak power, with a slight increase in energy use (5.75%). In less extreme winter weather, the energy usage difference will be smaller, but the reactive control will likely use the boiler whenever the weather gets particularly cold. This study provides the basis for the development of predictive control rules that may be easily implemented in similar configurations.
Numerical investigation of an energy pile-based solar-assisted ground source heat pump system for space heating and cooling
Authors: Beragama Jathunge Charaka , Adebayo Philip , Dworkin Seth B. , Mwesigye Aggrey
Published: May 2024

While ground source heat pump systems are a sustainable method to climatize buildings, their long-term performance in cold climates may lead to ground overcooling and, thereby, performance deterioration over time, especially when the loads are significantly imbalanced. Solar-assisted ground source heat pump systems are an alternative to mitigate the ground thermal imbalance by injecting solar thermal energy into the ground to balance energy extraction by the heat pump while also improving the heat pump performance. This study numerically evaluates the performance of a solar-assisted ground source heat pump system for three different climate zones and three modes of operation using a thoroughly validated finite volume-based computational model. A 0.139 m diameter helical steel pile installed to a depth of 18.288 m below the ground was used in this study as the ground heat exchanger. Realistic building load profiles were obtained using OpenStudio for residential applications in Calgary, Toronto, and New York and coupled with a computational fluid dynamics solver to evaluate the overall system performance. The results show that the solar-assisted system shows a significant performance improvement of 16.3% over a non-solar enhanced system for the coldest climatic zone studied. Out of the three system operation modes studied (mode 1: solar loop is turned off at low irradiance, mode 2: solar thermal energy is redirected based on the season, mode 3: solar thermal energy is redirected based on the heat pump operating mode), mode 3 yields the best overall heat pump performance for all the locations (COP: 3.72, 3.74, 4.24 for Calgary, Toronto, and New York, respectively). Interestingly, the results indicate the best-suited system operating mode depends on the degree of dominance of the building's heating load.
Effect of the geothermal heat flux on vertical ground heat exchanger performance
Authors: Sabbagh Gabriel , Bernier Michel
Published: May 2024

Ground heat exchangers (GHE) are typically modeled using a simplifying assumption: the mean ground and atmospheric temperatures are assumed to be equal to the ground temperature halfway down the length of the borehole. This paper examines the impact of this assumption on vertical ground heat exchanger performance. A numerical model using a finite volume method is developed to simulate the performance of ground heat exchangers. The model takes into consideration the effect of the geothermal gradient, varying surface temperatures, inlet fluid temperatures or energy extraction loads over long periods of time. Results from the first comparison show that the geothermal heat flux provides more energy to the GHE than the outside environment and that over long periods of operation, the geothermal heat flux establishes itself as the main energy source. Moreover, the existence of a geothermal heat flux diminishes the effect of continuous heat extraction on the natural ground heat flux profile and therefore, infers a more sustainable exploitation of the energy resource. Results from the second comparison show that inadequate GHE dimensioning in both cooling and heating can occur if the geothermal heat flux is not considered. However, using simple approximations to the ground temperature profile that consider the geothermal heat flux can lead to accurate heat exchange calculations.
Biomineralized soil improves wind erosion tolerance of cyanobacterial biocrust
Authors: Kimura Keiichi , Okuro Toshiya
Published: May 2024

Land degradation is a global problem and effective land restoration
techniques are needed. Biocrust introduction has attracted much
attention because biocrust-forming organisms have a high survival rate
in harsh environments and perform various ecological functions. However,
physical disturbances and low nutrients impede biocrust development. In
degraded areas, soil tackifiers and amendments are often applied before
biocrust inoculation, but optimal methods require further investigation.
This study examined whether biomineralization by ureolytic bacteria, one
soil stabilization method, could facilitate the growth of
biocrust-forming cyanobacteria and biocrust development. We also
investigated whether biomineralization and cyanobacterial inoculation
could improve soil stabilization, hydrology, and photosynthesis activity
compared to the only biocrust introduction. We incubated the biocrusts
on biomineralized sand or bare sand. We measured several indicators of
cyanobacterial growth, biocrust structure development, and ecological
functions during the incubation. The results indicate that although the
biomineralized soil did not facilitate cyanobacterial growth,
infiltration, or photosynthesis activity, it improved the biocrust
thickness and wind erosion tolerance. Our findings indicate biocrusts
with biomineralization would form a more stable soil surface in degraded
land. We also show the different influences of biomineralization among
the target ecological functions, which will help to develop land
restoration methods utilizing biocrusts and biomineralization.
Advancing Psychopharmacological Training and Prescriptive Authority for Psychologists in India: A Call for Action
Authors: Das Chandan
Published: May 2024

Proficiency in psychopharmacology is indispensable for a psychologist to
effectively fulfill their professional responsibilities, irrespective of
their intention for prescribing licensure. This commentary makes a call
for psychopharmacology training in clinical psychology and Prescriptive
Authority for Psychologists in India. Without proficiency in
psychopharmacology, one’s capacity to collaborate with medical
prescribers and provide optimal care to patients as a valued member of
the healthcare team is severely constrained.
Machine learning for a heterogeneous water modeling framework
Authors: Frame Jonathan
Published: May 2024

We explore deep learning for the Next Generation Water Resources
Modeling Framework (NextGen). We present results from Random
forest-based multi-model ensembles, Long Short-Term Memory (LSTM) and
differentiable parameter learning hydrological models (δ conceptual
models) and attribute sensitivity for ungauged basins.

This poster was presented at the CIROH Developers Conference May 29 –
June 1, 2024, at the University of Utah in Salt Lake City.
Bayesian Inference of Coupled Groundwater Flow and Radiogenic Helium-4 Production and Transport at the Catchment Scale
Authors: Casillas-Trasvina Alberto , Rogiers Bart , Beerten Koen , Wouters Laurent , Walraevens Kristine
Published: May 2024

Hydrogeological numerical models are crucial for assessing radioactive
waste disposal. State variables are widely used but not quantitatively
during model inversion, except for hydraulic head. This study explores
incorporating radiogenic Helium-4 (4Herad) as an unconventional state
variable in model inversion, addressing parameter solution
non-uniqueness. Employing a formal Bayesian approach, two 3D
physically-based models are used to infer posterior parameter
distributions. Major 4Herad sources include crustal fluxes and in situ
production in the Boom Clay. Coupled inference narrows marginal
posterior distributions, reducing uncertainty in calibration and
prediction of certain parameters. Integrating 4Herad as a state variable
improves model reliability and fidelity, particularly in constraining
solute transport and refining groundwater flow parameters and derived
fluxes. This state-of-the-art study demonstrates the effectiveness of
including 4Herad in combination with classical hydraulic head
observations, showcasing transformative potential for reducing
uncertainties crucial for radioactive waste disposal. It marks the
first-ever attempt at harnessing 4Herad quantitative insights into flow
and transport parameters following a Bayesian approach at a catchment
scale, setting a precedent for future research. The study strongly
advocates for the continued utilization of 4Herad in hydrogeological
modeling, emphasizing its relevance for safety studies.