bluuebunny/crossref_metadata_2025 huggingface dataset:
La comunicación e interacción en la mediación pedagógica de los entornos virtuales de aprendizaje
Authors: Bonilla Villalobos Verónica , Salazar Chacón Marlon
Published: April 2024

La mediación especialmente en la educación a distancia se genera al reconstruir el esquema de conocimiento desde la interacción y la comunicación docente-estudiante, facilitando la cercanía, confianza y construyendo la autonomía de la persona estudiante. Implica conocimiento a través del lenguaje y la habilidad para emplearla, además, se fortalece por medio de la experiencia social, motivaciones y según necesidades. El objetivo de esta investigación fue determinar la importancia de la comunicación como elemento de la mediación pedagógica para la mejora continua. Esta investigación se desarrolló bajo un enfoque cuantitativo con un diseño no experimental, tipo transversal descriptivo. Se aplicó un cuestionario con 17 preguntas, mediante la herramienta virtual Google forms®, con la escala de medición Likert, donde se midió el grado de acuerdo o desacuerdo sobre la importancia de la comunicación. Se contó con una población de estudio de 57 personas, fue aplicada en dos asignaturas de la Cátedra Producción Sustentable, siendo un grupo de Bachillerato y otro de Licenciatura. Como resultados importantes mencionan que los recursos están disponibles en todo momento y que se accede de manera simple y rápida. Se reflejó la importancia de la empatía y la motivación, que se debe dar en los entornos virtuales de manera intencionada y asertiva. La comunicación presenta una relevancia en el estudiantado por que reconstruye esquemas a partir de la interacción en sus diferentes dimensiones generando cercanía, motivación, autonomía, fortalece las relaciones interpersonales y favorece el aprendizaje colaborativo, entre otros
Analysis learning outcomes of mathematics education student in the online learning
Authors: Sitepu Christina , Gultom Sanggam P. , Hutauruk Agusmanto J. B. , Panjaitan Simon M.
Published: April 2024

This research aims to look at the impact and learning outcomes of using LMS and online learning platforms, so it is necessary to analyze learning outcomes and how they impact students, lecturers, and learning organizing institutions. This research shows that the LMS and online learning platforms used can improve student learning outcomes, which cannot be separated from the readiness of lecturers and students to implement it. This research used factor analysis (CFA), with a total of 150 respondents, students, and 15 lecturers. The impact provided by the use of LMS and online platforms in online learning is in the form of GPA and students' views on the learning process they have gone through. From the research results, several findings were obtained, including the ability to use LMS in online learning is not optimal, the GPA of learning outcomes is relatively high, and the readiness of lecturers and students to use LMS in online learning is still low.
Tether Force Estimation Airborne Kite using Machine Learning Methods
Authors: Gupta Akarsh , Kashyap Yashwant
Published: April 2024

Airborne Wind Energy (AWE) is looking very promising for harnessing
high- altitute winds and aiding in the transition from fossil fuels to
sustainable en- ergy. The ground-based kite system in plays a crucial
role in autonomously estimating tether force, which depends on various
factors such as wind speed, the kite’s orientation relative to the wind
vector in its figure-eight trajectory and Latitute as well as Longitude.
To predict tether force, we have em- ployed testing of four regression
machine learning models which have shown merit in similar fields. The
machine learning models which were tested upon were: Linear Regression
Support Vector Machine Regression Random Forest Regression XGBoost
Regressor Gradient Boosting After getting the metrics which were Mean
Absolute Error(MAE), Root Mean Square Error(RMSE) and R Error, we concluded that XGBoost Re- gressor gave us
the best metrics in all three categories.
Multi-Omics Exploration of ABA Involvement in Identifying Unique Molecular Markers for Single and Combined Stresses in tomato plants
Authors: Rivero Rosa , Pardo-Hernández Miriam , García-Pérez Pascual , Lucini Luigi
Published: April 2024

Over the past decade, our research group has found that plant responses
to combined abiotic stresses are unique and cannot be inferred from
studying plants exposed to individual stresses. Adaptive mechanisms
involve changes in gene expression, ion regulation, hormonal balance,
and metabolite biosynthesis or degradation. Understanding how these
mechanisms integrate from stress perception to biochemical and
physiological adjustments is a major challenge in abiotic stress
signaling studies. Today, vast amounts of -omics data (genomics,
transcriptomics, proteomics, metabolomics, phenomics) are readily
available. Additonally, each –omic level is regulated and influenced by
the others, highlighting the complexity of plant metabolism’s response
to stress. Considering abscisic acid (ABA) as a key regulator in plant
abiotic stress responses, in our study, ABA-deficient plants (flc)
underwent single or combined salinity and heat stresses were evaluated
and different -omics analyses were conducted. Significant changes in
biomass, photosynthesis, ions, transcripts, and metabolites occurred in
mutant plants under single or combined stresses. Exogenous ABA
application in flc mutants did not fully recover plant phenotypes or
metabolic levels but induced cellular reprogramming with changes in
specific markers. Multi-omic analysis aimed to identify ABA-dependent,
ABA-independent, or stress-dependent markers in plant responses to
single or combined stresses. We demonstrated that studying different
-omics together identifies specific markers for each stress condition
not detectable individually. Our findings provide insight into specific
metabolic markers in plant responses to single and combined stresses,
highlighting specific regulation of metabolic pathways, ion absorption,
and physiological responses crucial for plant tolerance to climate
change.
EXAMINING THE ENVIRONMENTAL POLICIES AND SUSTAINABLE DEVELOPMENT INITIATIVES IN INDIA
Authors: CM Selvamuthu , LAVARAJU B.
Published: April 2024

India’s environmental policy framework has undergone significant
transformation since independence, but effective implementation remains
a challenge. This research examines the evolution of environmental
policy in India, focusing on key challenges and promising sustainable
development initiatives. The study adopts a comprehensive approach,
analyzing relevant legal documents, policy reports, scientific
literature, and data from government agencies. It also incorporates
stakeholder perspectives and insights from civil society organizations.
The research identifies air and water pollution, land degradation,
deforestation, and climate change as major environmental challenges
facing India. Promising sustainable development initiatives include
renewable energy, energy efficiency, waste management, and sustainable
agriculture. However, these initiatives face challenges related to
implementation, enforcement, and long-term effectiveness evaluation. The
research proposes a series of recommendations, including policy reforms,
institutional capacity building, innovation and technological
advancements, green financing mechanisms, and international cooperation.
It emphasizes the importance of public participation, inter-agency
collaboration, and leveraging technology for effective environmental
governance. The research concludes that India needs to prioritize
effective implementation of existing policies and explore innovative
approaches to address emerging environmental challenges. By adopting a
holistic strategy that integrates environmental considerations into all
policy domains, empowers communities, leverages technology, and fosters
international collaboration, India can achieve a cleaner, greener, and
more sustainable future.
Compact Wide Single-/Dual- Band Bandpass Filter with Equal Inductance Configuration in Thin Film IPD Technology
Authors: Liu ZhiHao , Liu Bao-Guang , Cheng Chong-Hu , Cheng Yong
Published: April 2024

In this paper, based on thin film integrated passive device (TF-IPD)
technology, compact ultra-wideband (UWB) bandpass filter (BPF) and
dual-band bandpass filter (DBBPF) with equal inductance configuration
are proposed. The configuration of equal inductance in a circuit
contributes to reducing variables, simplifying the physical structure,
and shortening the debugging time in the TF-IPD design process. Despite
all the inductors being equal in value, wide passband can still be
achieved. The measured results show that the center frequency of UBW BPF
is 11.43 GHz, the 3-dB fractional bandwidth (FBW) is 133% (3.87
GHz-18.99 GHz). And the 3-dB FBWs of DBBPF centered at 6.5 GHz and 16.2
GHz are 92% (3.51-9.49 GHz) and 35% (13.33-18.98 GHz), respectively.
The stopband of UBW BPF and DBBPF can be extended to 47.7 GHz and 44.8
GHz in sizes of 321 um × 856 um and 235 um × 846 um, respectively
(excluding measuring pads).
CliniXPromt: Enhancing the Comprehensibility of Electronic Health Records using GPT-3 and Chain of Thought
Authors: Mazumdar Hirak , Das Suparna , MSVPJ Sathvik , Khondakar Kamil Reza
Published: April 2024

This paper presents an innovative method for enhance the
comprehensibility of Electronic Health Records (EHRs), making it
accessible to individuals without specialized clinical knowledge. Our
approach entails predicting medical professionals’ impressions,
identifying intricate medical terminol- ogy, and clarifying these
complex terms. To achieve this, we fine-tuned GPT-3 for predicting
doctors’ impressions and integrated the Chain Of Thought (COT) prompting
technique to identify and elucidate intricate medical terms. The
assessment was conducted using Rouge scores and cosine similarity
scores. The outcomes reveal that our proposed approach yields a cosine
similarity score surpassing 75, indicative of the model’s exceptional
performance. The comparative analysis demonstrates the superiority of
our approach concerning doctors’ impressions, detection of complex
terminology, and provision of explanations. Furthermore, this work is
pioneering in addressing and resolving intricate terminology in EHRs,
marking a novel contribution to the field.
Diagnostic germline genetic variant classification requires more equitable representation in reference databases
Authors: Burstein Shana , Spier Eva , Patel Janki , Jerome William , Sugrañes Thelma Alessandra , Biase Miranda Di , Loeb David M. , Weiser Daniel
Published: April 2024

Germline genetic testing can aid in difficult diagnostic workups but may
reveal variants of unknown significance (VUS), which do not alter
patient management or provide definitive diagnoses and may worsen stress
on patients and families. VUS are more prevalent in underrepresented
populations given their absence in large scale genomic studies. We
describe seven pediatric hematology/oncology patients seen in the highly
diverse Bronx County in New York City in which VUS or novel pathogenic
variant identification influenced clinical management and outcomes.
These cases highlight the importance of incorporating underrepresented
populations into genomic databases to improve variant characterization
and address healthcare disparities.
Prior COVID-19 infection increases degenerated oocytes but does not affect IVF outcomes: A Prospective Cohort Study
Authors: Gong Fei , Chen Huijun , Guo Hongxin , Zhao Qi , Li Yuan , Lin Ge , Kalk Philipp , Hocher Berthold
Published: April 2024

Objective: To investigate whether prior COVID-19 infection and
time interval after infection affect the in vitro fertilization (IVF)
outcomes. Design: A prospective observational cohort.
Setting: Reproductive center in China. Population:
Participants recovered from COVID-19 and healthy controls.
Methods: All participants received normal IVF treatment. The
oocyte and embryo quality as well as pregnancy outcome data were
collected and analyzed. Main outcome measure: Oocytes and
embryo quality, clinical pregnancy outcomes. Results: The
oocyte and embryo quality were comparable between the two groups,
including the number of oocytes, 2PN zygotes, fertilization rate,
cleavage embryos, day 3 good-quality embryos, blastocyst formation rate,
and good-quality blastocysts. Nevertheless, the study group exhibited
more degenerated oocytes (0.15±0.40 vs. 0.10±0.33, P=0.035). Further
regression analysis indicated that prior COVID-19 infection is
positively related to the number of degenerated oocytes (Adjusted β:
0.06, 95% confidential interval (CI): 0 -0.10, P=0.032). No significant
differences were observed in clinical pregnancy rate, implantation rate,
early miscarriage rate, ectopic pregnancy rate, and ongoing pregnancy
rate. Similarly, we observed no difference in oocyte and embryo quality
as well as pregnancy outcomes across various post-infection time
intervals. Conclusions: Preceding COVID-19 could increase the
number of degenerated oocytes. However, it does not affect subsequent
pregnancy outcomes. Additionally, post-infection time interval plays no
significant role in IVF outcomes.
NON-LOCAL CONVOLUTION TYPE OPERATORS WITH POTENTIAL: ESSENTIAL AND INFINITE DISCRETE SPECTRUM
Authors: Piatnitski Andrey , Borisov Denis , Zhizhina Elena
Published: April 2024

The goal of this note is to study the spectrum of a self-adjoint
convolution operator in L 2 ( R d ) with an integrable kernel that is
perturbed by an essentially bounded real-valued potential tending to
zero at infinity. We show that the essential spectrum of such operator
is the union of the spectrum of the convolution operator and of the
essential range of the potential. Then we provide several sufficient
conditions for the existence of a countable sequence of discrete
eigenvalues. For operators having non-connected essential spectrum we
give sufficient conditions for the existence of discrete eigenvalues in
the corresponding spectral gaps.
Defining a New Subtype of Lung Adenocarcinoma (LUAD) and Identifying Prognostic Biomarkers: A Gene Set Variation Analysis Approach
Authors: Zhao wenzheng , Yun Jianxu , Su Lanlan , Liu Kun , Xia Boning , Liu Guangyi , Li Yang
Published: April 2024

[Objective] This study aimed to define a new subtype of
lung adenocarcinoma (LUAD) and identify prognostic biomarkers;
[Method] We obtained the required raw data from the TCGA
and GEO database. Through gene set variation analysis (GSVA) analysis,
the gene expression matrix was transformed into a gene set expression
matrix. Then, the “Cancersubtypes” package in R software was used to
convert the samples into different subtypes, and a LUAD-related
prognosis model was established based on the differentially expressed
gene sets (DEGSs) between each subtype. Finally, functional and pathway
enrichment analysis, as well as a protein-protein interaction (PPI)
network analysis, were performed on prognosis-related DEGSs;
[Result] We obtained 63 DEGSs and constructed a prognostic
model based on 4 significantly prognosis-related DEGSs;
[Conclusion] This study has developed a new classification
method for LUAD and identified 4 prognosis related DEGSs and 15 core
protein, which could provide relevant theoretical basis and guidance for
the update of cancer treatment methods and the development of new drugs.
WDANet: exploring stylized animation via diffusion model for woodcut-style design
Authors: Ou Yangchunxue , Xu Jingjun
Published: April 2024

Stylized animation is often adored for its innovative and daring visual
creativity. Due to the strong visual impact and color contrast inherent
in woodcut style design, it has been applied in animation and comics.
However, traditional woodcuts, hand-drawn, and previous computer-aided
methods have yet to address the issues of dwindling design inspiration,
lengthy production times, and complex adjustment procedures. To tackle
these challenges, we propose a novel network framework, the
Woodcut-style Design Assistant Network (WDANet). Notably, our research
is the first to utilize diffusion models to streamline the woodcut-style
design process. We curate the Woodcut-62 dataset, which features works
from 62 renowned historical artists, to train WDANet in absorbing and
learning the aesthetic nuances of woodcut prints, offering users a
wealth of design references. Our WDANet integrates text and
woodcut-style image features based on a denoising network. WDANet allows
users to input or slightly modify a text description to quickly generate
accurate, high-quality woodcut-style designs, saving time and offering
flexibility. As confirmed by user studies, quantitative and qualitative
analyses show that WDANet outperforms the current state-of-the-art in
generating woodcut-style images and proves its value as a design aid.
Mass Spectrometry Based Proteomic Profiling of Three Feeding Categories of Bats in Tirunelveli, Tamilnadu, South India
Authors: S Balasingh , Sophia Ezhilmathi , S Suthakar Isaac , J Merrylin
Published: April 2024

A comparative protein profile of bat wing-tissue samples for three
feeding categories of bats such as Insectivorous, Hipposiderous speoris;
Carnivorous Megaderma lyra - and Frugivorous Cynopterus sphinx was
studied. All the samples were analyzed using two-dimensional
electrophoresis coupled with mass spectrometry. Totally, 38 protein
spots were paired across all the three categories of samples and 5
differentially expressed proteins were identified. In the present study,
it is reported that proteomics-based analysis for three feeding
categories reveal the presence of five candidate proteins namely 1)
Hemoglobin subunit beta; 2) V(D)J Recombination activating protein 1; 3)
Olfactory receptor; 4) Lysozyme and 5) Brain-derived neurotrophic factor
were identified. Among them, 3 proteins such as Olfactory receptor;
Lysozyme and Brain-derived neurotrophic factor were up- regulated in M.
lyra and C. sphinx compared to H. speoris. Gene ontology analysis
reveals three different functional properties of the identified protein
such as biological process, cellular component, and molecular function.
The present study will shed more light on the importance of chiropteran
fauna in proteomics and long- term conservation planning of bat
populations of the study area. KEYWORDS : protein profile, three feeding
categories, mass spectrometry, Gene ontology
Frontal and parietal activities associated with different inhibitory processes in a Stroop-matching/stop-signal task: a channel-wise fNIRS study
Authors: Jr Armando Afonso , Machado-Pinheiro Walter , Carreiro Luiz Rodrigues
Published: April 2024

Inhibition is an important component of cognitive control that
encompasses multiple processes, such as interference control, inhibition
of prepotent responses and suppression of ongoing responses. Frontal and
temporoparietal regions of the cortex are implicated differently in
inhibitory functions. The Stroop-matching/stop-signal task is a recent
task that uses Stroop stimuli and stop-signals to create conditions that
allow the investigation of the three forms of inhibition aforementioned.
The task provides a way to distinguish the effect of these inhibitions
as well as their interactions using a single task. The present study
used functional near-infrared spectroscopy (fNIRS) to assess frontal and
temporoparietal activations during the Stroop-matching/stop-signal task.
The main objective was to investigate which cortical regions each
inhibitory function would recruit during this task. Fifty-two young
adults (mean age = 21.4, SD = 3.44) participated. Performance results
indicated the effects previously found in the
Stroop-matching/stop-signal task. FNIRS results showed that the left
inferior frontal cortex (IFC) and the bilateral intraparietal sulcus
(IPS) are involved in interference control; the left IFC also showed
activation in inhibition of prepotent responses; and the right IFC was
involved in the suppression of ongoing responses. The interaction
between suppression of responses and the other two forms of inhibition
lead to deactivation of frontal and parietal areas. Thus, each form of
inhibition demanded by the Stroop-matching/stop-signal task seems to
recruit specific cortical regions, supporting the distinction between
inhibitory components at the neurophysiological level.
Comparative Analysis of Three Typical Cantilever Scaffold Supporting Systems
Authors: Geng Dajiang , Zhao Xintao , Zhang De , Jin Xuesheng
Published: April 2024

In order to effectively guide the selection of scaffold in the designing
of cantilever scaffold, a comprehensive analysis of three typical
scaffold supporting systems (including fully cantilever,
bottom-supporting cantilever and pull-up cantilever) is carried out. The
calculation formulas for the internal force of the three scaffold
supporting systems are proposed by theoretical analysis methods, which
are verified by finite element method (FEM). In addition, the force
mechanism and benefits of the three scaffold supporting systems are
compared and analyzed combined with actual engineering. The results
indicate that there are high calculating accuracy for the proposed
internal force and deflection calculation formulas about the scaffold
supporting systems. According to the distribution uniformity of the
internal force and controlling of the deformation of the main girder,
the bottom-supporting cantilever load-bearing system is the best choice.
While the pull-up cantilever supporting system is the best choice
considering the aspects of cost, construction period and social
benefits, which can be popularized in engineering practice.
Deep reinforcement learning-based approach to tackle positive influence maximization in signed social networks
Authors: Song Nuan , Wu Liming , Sun Tianqi , Si Wei , Li Dong
Published: April 2024

The Influence Maximization problem has garnered significant research
interest since its introduction. In 2014, the problem was further
extended to include signed social networks, resulting in the positive
influence maximization problem and negative influence maximization
problem. However, current solutions mainly rely on greedy algorithms
that suffer from the Inefficient shortcoming, which do not leverage deep
reinforcement learning. This paper introduces a novel approach to
maximize the number of positively activated nodes by applying deep
reinforcement learning to signed networks. Specifically, we extend SDGNN
model for network representation learning and design a DQN-based seed
node selection algorithm. The extensive experimental results on two
real-world networks demonstrate our proposed model outperforms greedy
algorithm and CELF algorithm,in terms of both time efficiency and
influence spread quality. To our knowledge,this work is the first to
leverage deep reinforcement learning to solve influence maximization
problem in signed social networks.
Effects of conformational changes in the N-terminal domain of RfaH on domain dissociation and fold switching
Authors: Seifi Bahman , Wallin Stefan
Published: April 2024

RfaH is a two-domain metamorphic protein involved in transcription
regulation and translation initiation. To carry out dual functions, RfaH
relies on two coupled structural changes: domain dissociation and fold
switching. In the free state, the C-terminal domain (CTD) of RfaH adopts
an all- α fold and is tightly associated with the N-terminal
domain (NTD). Upon binding to RNA polymerase (RNAP), the domains
dissociate and the CTD completely transforms into an all- β fold,
while the NTD remains largely, but not entirely, unchanged. We test the
idea that a change in the conformation of an extended β-hairpin (
β3- β4) located on the NTD, helps trigger domain
dissociation. To this end, we use homology modelling to construct a
structure, H 1 , which is similar to free RfaH but with a remodeled
β3- β4 hairpin. We then use an all-atom physics-based
model enhanced with a dual-basin structure-based potential to simulate
domain separation driven by thermal unfolding of the CTD with NTD in a
fixed, folded conformation. We apply our model to both free RfaH and H 1
. For H 1 we find, in line with our hypothesis, that the CTD exhibits a
lower stability and the domains dissociate at a lower temperature (
T), as compared to free RfaH. We do not, however, observe
complete refolding to the all- β state in these simulations,
suggesting that a change in β3- β4 orientation aid in, but
is not sufficient for, domain dissociation. In addition, we study the
reverse fold switch in which RfaH returns from a domain-open all-
β state to its domain-closed all- α state. We observe a
T-dependent transition rate; fold switching is slow at low
T, where the CTD tend to be kinetically trapped in its all-
β state, and at high- T, where the all- α state
becomes unstable. Consequently, our simulations suggest an optimal
T at which fold switching is most rapid. At this T, the
stabilities of both folds are reduced. Overall, our study suggests that
both inter-domain interactions and conformational changes within NTD may
be important for proper functioning of RfaH.
Short-term outcomes of laparoscopic and robotic distal gastrectomy for gastric cancer
Authors: Xu Feng , Yang Xi , Hu Qiang
Published: April 2024

We have read with interest the article published by Hondo N et al.1 At
present, there are several minimally invasive surgical methods for the
treatment of gastric cancer: Endoscopic mucosal resection (EMR) ,
Endoscopic submucosal dissection (ESD), Laparocopy-assisted radial
gastrectomy (LARG), and Robot-assisted radical gastrectomy (RARG). LARG
and RARG can not only be used for early gastric cancer, but also for the
treatment of advanced gastric cancer, and they have the advantage of a
wide range of surgical indications. Laparoscopic surgery also has some
drawbacks, including a two-dimensional surgical field of view and
limited operational freedom. In order to improve the above shortcomings,
the da Vinci robotic surgical system has emerged in response to the
times. The da Vinci surgical robot system is currently the most advanced
high-tech platform for minimally invasive surgery internationally. It
solves the limitations of traditional laparoscopy in terms of field of
view and operational flexibility, and breaks through the bottleneck of
limited development in traditional laparoscopic surgery. Although we
believe it is a very interesting topic, we would like to offer the
following points for your consideration.
On the Coupling of Intracellular K + to Glycolytic Oscillations in Yeast
Authors: Olsen Lars , Lunding Anita
Published: April 2024

We have investigated the interplay between glycolytic oscillations and
intracellular K concentration in the yeast S.
cerevisiae. Intracellular K concentration was
measured using the fluorophore PBFI. We found that K
is an essential ion for the occurrence of glycolytic oscillations and
that intracellular K concentration oscillates
synchronously with other variables such as NADH, intracellular ATP and
mitochondrial membrane potential. We also investigated if glycolysis and
intracellular K concentration oscillate in a number
of yeast strains with mutations in K transporters in
the plasma membrane, mitochondrial membrane and in the vacuolar
membrane. Most of these strains are still capable of showing glycolytic
oscillations, but two strains are not: (i) a strain with a deletion in
the mitochondrial Mdm38p K /H
transporter and (ii) a strain with deletion of the late endosomal Nhx1p
K /H (Na /H
) transporter. In these two mutant strains
intracellular K concentration seems to be low,
indicating that the two transporters may be involved in transport of K
into the cytosol. In the strain Mdm38p Δ
oscillations in glycolysis could be restored by addition of the K
/H exchange ionophore nigericin.
Furthermore, in two non-oscillating mutant strain with a defective
V-ATPase and deletion of the Arp1p protein the intracellular K
is relatively high, suggesting that the V-ATPase is
essential for transport of K out of the cytosol and
that the cytoskeleton may be involved in binding K
to reduce the concentration of free ion in the cytosol. Analyses of the
time series of oscillations of NADH, ATP, mitochondrial membrane
potential and potassium concentration using data-driven modeling
corroborate the conjecture that K ion is essential
for the emergence of oscillations and support the experimental findings
using mutant strains.
Determinants of Academicians’ Mental Health in Higher Education Institutions: A Systematic Literature Review
Authors: Sakarji Siti Rosnita , Othman Abdul Kadir , Narmaditya Bagus Shandy , Mohd Beta Raja Mayang Delima , Mahmud Azuati
Published: April 2024

Due to the nature of the demanding working circumstances, most academicians at higher education institutions have therefore been vulnerable to experiencing mental health issues. This present study aims to investigate the prominent factors that influence academics' mental health in higher education through systematic reviews. In detail, this study is intended to analyze the trends, patterns, and knowledge gaps on the factors affecting mental health. Using the PRISMA protocol to identify and analyze datasets from the Web of Science (WoS), Scopus, Google Scholar, and Science Direct. In this present study, twenty-one papers were selected and analyzed. The findings indicate a robust influence of job demand on mental health among academicians in higher education. These review papers reveal that there is an increasing amount of research on the factors influencing the mental health of academicians in higher education. The findings highlight a worrying pattern of increasing job pressures and an increase in the frequency of mental health issues among academicians. Thus, there is a critical need for focused treatments and academic support networks to mitigate the increasing demands placed on faculty members and protect their mental health. This study contributes to the literature by focusing on mental health, primarily the job demands of academicians in the context of higher education institutions.
Developing Life-long Investment Literacy of Students through Initial Public Offerings (IPO) One-Stop Support Center and Stock Trading Simulation
Authors: Che-Yahya Norliza , Alyasa-Gan Siti Sarah
Published: April 2024

Initial Public Offerings (IPO) One-Stop Support Center website is created to help students, the public and academic researchers. One of the significant features of this website is a stock trading simulation which enables stock trading practice in a simulated or virtual environment. It simulates the experience of trading equities with virtual currency. The main aim of this trading simulation is to offer students and the public (potential retail investors) a risk-free environment to learn and practice trading before entering the real stock market. This study aims to understand the influence of trading simulation as an educational tool in improving students’ lifelong learning skills through the development of investment literacy. This study was conducted using a qualitative approach. To fulfill the objective of this study, an online survey was distributed through a Google Form. A total of 110 respondents consisting of students enrolling in FIN768 (Investment and Portfolio Analysis) course, public, and academics in Universiti Teknologi MARA (UiTM), Shah Alam and Puncak Alam, Selangor took part in the online survey. This study finds that 89.10 percent of the respondents agree that this stock trading simulation is very useful for their life-long learning. This study contributes mainly to the students by providing them with valuable learning experiences and practical skills that extend beyond traditional classroom teachings.
Exploring the Impact of Authentic Personality and Social Media Posting on Self-Interested Charitable Behavior among Millennials Online Community through the Lens of Social Cognitive Theory
Authors: Husin Norhusniyati , Ibrahim Nadhrathul Ain , Abdul Rahim Najihah , Abd Manaf Khamisah , Shafie Intan Syafinaz Mat
Published: April 2024

Various schools of thought within the field of psychology consider authentic personality to be an essential component of overall well-being. Similarly, people's behavior has changed since the advent of social media. Using Social Cognitive Theory as guidance, this conceptual paper aims to explore how authentic personality and social media postings affect individuals' self-interested charitable behavior, this research aims to delve into the person-centered concept of authentic personality. The sense of giving and charitable behavior includes giving to charity and involving in volunteer activity. This model is deemed appropriate because it further explains authentic personality and exposure to social media posting in an online environment. Throughout the entirety of this study, a search was conducted via a variety of literature on the fields of sociology, psychology, and social science. There was a discussion of the conclusions drawn from the research, and options for more research were outlined.
Students Perceptions Towards Relevance of Tertiary Education
Authors: Jamaludin Nor Lelawati , Sani Azurin , Md Sohid Faizah , Mashahadi Faizah , Yusof Nuryusmawati
Published: April 2024

This research examines students' perceptions of higher education's broader benefits beyond job skills. It emphasizes societal advantages like environmental awareness, well-being, and civic engagement. Focused on 98 international business students at UiTM, it aims to understand factors affecting their self-esteem, particularly the link between academic prowess, social skills, and views on higher education's practical value. The study reveals strong ties between academic ability, social skills, and the importance ascribed to higher education, stressing the need for a holistic educational approach. It suggests future research areas to deepen understanding of tertiary education's relevance and societal impact. Additionally, it proposes ways for institutions to enhance students' appreciation of university education, fostering active engagement and community contribution. Overall, the research contributes to understanding the multifaceted significance of higher education, emphasizing the importance of considering academic and social competencies for informed decision-making and effective educational practices.
Examining Grassroot Innovation: A Case Study of the Curry Puff Maker Machine Project from a Socioeconomic Perspective
Authors: Muhamat Amirul Afif , Abd Rashid Muhammad Hafiz , Yusri  , Ibrahim Muhammad Azman , Salleh Sharmila Mohamed , Hilmiyah Nurul , Basri Mohd Faizal
Published: April 2024

Grassroots innovation is a customised innovation programme aimed at empowering the community by demonstrating creativity, resourcefulness, and technological proficiency to tackle issues that impact their daily life. Yayasan Inovasi Malaysia (YIM) is a prominent institution in Malaysia that serves as an anchor for this endeavour. This study examines a project that was awarded an innovation grant to produce curry puff makers and distribute the machines to individuals from marginalised demographics, including single moms, handicapped individuals, and others. The methodology of research for this study involves using a qualitative method, namely a descriptive case study approach, to engage with the grant recipient. The feedback was evaluated using thematic techniques. The project has successfully achieved its objectives across the four examined categories: social, economic, environmental, and technological adoption.
Determinants of Capital Structure from Malaysian Shariah-Compliant Food and Beverages Firms
Authors: Che-Yahya Norliza , Mohd Kassim Nor Akila , M. Rasit Nur Afiqah , Zainal Abidin Nursyazwina , Shahrel Erni Nazirah , Zulkefli Norizzanie Wajihah , Zalani Nurliyana , Abd Latif Atirah , Alyasa-Gan Siti Sarah
Published: April 2024

This paper addresses the dearth of empirical research on the capital structure of Shariah-compliant food and beverage (F&B) firms in Malaysia. Despite the industry's dynamic growth, specific financing needs, and adherence to Shariah principles, a comprehensive investigation into the determinants of their capital structure choices is lacking. By exploring factors such as profitability, tangibility, growth opportunities, liquidity, and firm size, this paper aims to provide valuable insights into the financial strategies of these specific entities and fill crucial knowledge gaps in empirical evidence. The study employs panel data, a combination of cross-sectional and time-series data, with a sample comprising 24 Shariah-compliant F&B firms listed on Bursa Malaysia, totalling 240 observations. Quantitative methods are applied using secondary data sourced from the Eikon database and financial statements in the annual reports of Bursa Malaysia-listed companies from 2013 to 2022. The findings reveal that profitability, tangibility, liquidity, and firm size significantly impact the capital structure choices of Shariah-compliant F&B firms, while growth opportunities emerge as an insignificant factor. These results support the application of the trade-off theory for profitability and the pecking order theory for tangibility, liquidity, and firm size, shedding light on the nuanced financial decision-making processes within this sector.
Exploring the Phenomenon of Selfie-Posting Behavior among Social Media Users
Authors: Mohd Ramli Norsyazwani , Ali Syukrina Alini Mat , Yunus Noorain Mohamad , Jailani Sri Fatiany Abdul Kader , Shobri Nor Diyana Mohammed
Published: April 2024

In the present day, the act of posting self-portraits, also known as selfies, is widely regarded as one of the most prevalent behaviors linked to the use of social media. Taking a selfie opens a new set of windows for activating specific identities, and over time and with readily available technological means, individuals are able to carefully construct online identities by editing their appearance and idealizing their self-portraits.  The research discusses selfie-posting behavior in which to find out what the users are doing or constructing selfies before posting them.  The primary aim of the current research is to examine these steps, specifically the context in motives, pre-occupation, selection of selfies, and selfie editing before posting.  This study intended to focus on the social media users among Malaysians who engage in selfie activities.  This research used a nonprobability sampling design, which is purposive sampling.  The online questionnaire was administered as a cross-sectional survey, with data collected within a few months.  This survey received 150 responses, and PLS SEM 4.0 was used to gather and analyze the data.  Given the Selfie-Stadium Model, the finding showed that all variables are statistically significantly correlated to the following step.  This research provides practical insights for developers to explore novel methods of improving device functionality and leveraging multitasking capabilities. Additionally, social media users can fully utilize device functions and benefit from technological advancements.
Online Shopper Satisfaction: Exploring the Impact of e-Service Quality
Authors: Ahmad Nazatul Shuhida , Bahry Norliza Saiful , Ali Syukrina Alini Mat , Kori Nur Liana , Mat Azmi , Mohd Salleh Mohammad Zaim
Published: April 2024

The advent of online shopping has brought a significant revolution in how individuals exchange goods and services. Online purchasing has gained considerable popularity, especially after the Movement Control Order due to COVID-19. Therefore, this study aims to find the relationship and identify the most dominant factors of e-service quality that affect online shopping. Convenience sampling was used to collect primary data. 250 self-administered questionnaires with four Likert scales were distributed through a social media channel among Klang Valley residents aged 18 years and above. The data was then analyzed using SPPS Version 26. Multiple Regression Analysis was used to investigate the relationship between e-service quality and customer satisfaction. The researcher found a collective significant effect between Customer Satisfaction and all independent variables except Perceived Risk. Convenience was found to be the most dominant factor that influences Customer Satisfaction. Hence, this study can benefit online business owners as they develop appropriate strategies based on the findings to expand their business.
Examining the Influence of Macroeconomic Factors and Corporate Governance on Firm Performance in the ACE Market
Authors: Roslan Nur Hafizah , Saddam Siti Zaitun , Ahmad Muhammad , Amran Muhammad Hafiz Bin
Published: April 2024

This study focused on investigating the impact of macroeconomic factors and corporate governance on the financial performance of firms listed on the ACE Market of Bursa Malaysia. The ACE Market serves as a platform for smaller, emerging companies, providing them with an opportunity to raise capital with less stringent requirements compared to the Main Market. Using a panel data set of 72 companies over the period 2018-2022, the research employed panel-corrected standard errors (PCSE) regression. PCSE is a panel regression model that accounts for contemporaneous correlations, corrects for deviations from spherical errors, and enhances inference from linear models. The analysis revealed that ACE market companies, on average, show a negative return on equity (ROE) but positive numbers of women (NOW) and board meetings (NOM). The PCSE regression results, however, failed to show a statistically significant relationship between NOW and ROE, suggesting that the presence of women on the board of directors does not significantly impact the firm performance. The findings provide valuable insights for the firms in the ACE market companies regarding the consideration of important factors in improving firm performance. The research's broader goal is to inform the development of strategies fostering enhanced overall performance and sustainability in the ACE market. The study also suggests several recommendations such as broadening the scope and inclusion of international trade dynamics variables.
Factors that Influence Malaysian Muslim Travel Preferences
Authors: Hamdan Muhammad Irham , Omar Syed Ashrene Syed , Sani Azurin , Saidon Janiffa , Ishak Mohd Fikri
Published: April 2024

Tourism has become an important industry that contributes to a country’s economy. Currently, the Muslim tourist segment is viewed as one of the important segments in the tourism industry. In addition, there has been a growing interest in understanding the preferences and motivations of Muslim travelers. This is due to the increasing number of Muslim travelers worldwide and the recognition that catering to their specific needs is essential for successful tourism development. The number of Muslim tourists from a Muslim-majority country increases significantly. Muslim travelers are looking for destinations in which the majority of the population are Muslims. This study is aimed to determine the factors that influence Muslim traveler preferences and to determine the most dominant factor that influences Muslim traveler preferences. Therefore, a survey of 100 Malaysian Muslim travelers in Shah Alam Selangor was done to determine the factors that influence Muslim traveler preferences. Statistical Package for Social Science (SPSS) is used to analyze the multiple regression to test hypotheses on the factors that influence Muslim traveler preferences. The result of the survey suggests that halal certification is a significant factor in explaining Muslim traveler preferences. The availability of halal food and Sharia-compliant hotels were found not to have a significant relationship with Muslim travel preferences. This study provides evidence of the detailed needs and preferences of Muslim travelers and enhances the knowledge of tourists, government, and service providers about Islamic tourism
The Impact of Foreign Direct Investment, Green Technology Innovation and GDP on CO2 Emissions in Western China: A Static Panel Data Analysis
Authors: Qiu Yunxiu , Chuah Soo-Cheng , Muda Ruhaini , Goh Theng-Huey
Published: April 2024

This study investigates the impact of FDI, green technology innovation and GDP on CO2 emissions in the western region of China. This study applies the extended STIRPAT model, selects the relevant data of nine provinces in western China from 2000 to 2019, applies the static panel data analysis method, compares and analyses the estimation methods of Pooled OLS, fixed effect and random effect, and finally adopts the robust standard error estimation method of fixed effect. The results of the robust standard error estimation indicate that, in addition to the negative impact of green technology innovation on CO2 emissions, CO2 emissions are positively impacted by FDI, GDP, population, and the proportion of the secondary and tertiary industries. Therefore, reasonable introduction of FDI and improving green technology innovation levels are crucial in reducing CO2 emissions in the western region of China.
Determinants of Smallholder Farmers' Awareness of Crop Insurance in Kedah, Malaysia
Authors: Mohamad Basir Faziatul Amillia , Roslan Azreen , Zakaria Nur Nazurah Binti , Nasron Ooi Noor Qhaireena Binti Mohd , Anggraini Ratna
Published: April 2024

Agriculture is a major source of income for humans and has become an agro-food commodity. However, this industry is vulnerable to a wide range of dangers, including climate change, natural disasters, illnesses, and pests. Crop insurance is not a new concept in advanced economies since it has been recognized as an efficient instrument for mitigating agricultural risks and encouraging farmers to employ modern technology and innovation. This research investigates the determinants of smallholder farmers' awareness of crop insurance in the agricultural landscape of Kedah, Malaysia. Therefore, this study examines the relationship between knowledge, risk attitude and farm size on the farmers' awareness of crop insurance. The study, based on a sample of 100 farmers, utilizes a non-probability sampling technique to collect data through structured questionnaires. The research employs reliability analysis, correlation analysis, and regression analysis to evaluate the raw data and uncover the factors influencing farmers' awareness of crop insurance. The study conclusion shows a strong correlation between farmers' knowledge levels and farm size as important indicators of crop insurance awareness. The analysis emphasizes how crucial it is to increase farmers' understanding through focused educational programs and customized awareness campaigns that take farm size dynamics into account. Policymakers and agricultural extension services can enable smallholder farmers to make well-informed decisions about using crop insurance as a strategy to manage agricultural risks and guarantee financial stability by making information and resources easily accessible.
Trust, Social Influence and Perceived Usefulness: Examining Online Purchase Intentions among Gen Z
Authors: Achim Nur`ain , Mohamed Dayana Batrisya , Miji Sonia Crystal , Zuraini Nasir Nur Alliyah , Idil Muhammad Iqmal Ridhwan , Hilmen Abby Jane Luntek , Anuar Azu Farhana
Published: April 2024

The growing popularity of online shopping collides with user reservations related to trust, social influence, and perceived purchase usefulness, with such concerns acutely observable among Gen Z populations. As digital natives and prolific online users, Gen Z's purchasing patterns offer valuable insights for marketers adjusting their online strategies. This study extends the body of knowledge by examining the determinants of online purchase intentions among Gen Z thereby guiding university administrators, educators, and online retailers in crafting improved online shopping experiences. Utilizing a non-intrusive, naturalistic research setting, the study harnesses an anonymous survey methodology, and data is rigorously analyzed using Statistical Package for Social Science (SPSS). Findings indicate that trust and perceived usefulness are significantly connected to students' online purchasing decisions. This study enhances the theory of online buying habits by emphasizing trust and value in e-commerce. It advises adding trust cues and functional benefits to online portals, the key to influencing Gen Z buyers and boosting market expansion and e-shopper satisfaction.