bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative Evaluation of Antibacterial and Toxicity Mechanisms of Silver Nanoparticles Biosynthesized by Streptomyces, Lemon, and Chitosan
Authors: Mostafa Islam Yousif , Ahmad Maged Sayed , Aboellil Ayman Hassan , Mohamed Ayman Saber 
Published: September 2024

Background:
Recently, there has been a lot of interest in environmentally friendly
nanoparticle synthesis. Silver nanoparticles (AgNPs) are promising against antibiotic resistance
due to their high surface energy, robust action, and excellent adsorbability.

Aim:
The primary objective of this study was to assess the antibacterial efficacy of AgNPs that
were manufactured using three environmentally friendly methods (lemon, Streptomyces, and
chitosan). Furthermore, the study attempted to investigate the potential toxicity of these nanoparticles
on mice.

Methods:
The synthesis of AgNPs was characterized by XRD, TEM FTIR, and TGA. The antimicrobial
effect of AgNPs was studied using the disc diffusion method and minimum inhibitory
concentration (MIC). The antibacterial mechanism of AgNPs was determined using different
methods, such as released glucose and proteins, respiratory chain inhibition, plasma membrane
fluorescence anisotropy, DNA fragmentation, gel electrophoresis, and cell membrane potential.

Results:
The TEM analysis of Ag NPs showed predominantly spherical particles with a size
distribution of 10–60 nm. AgNPs synthesized by the three green methods showed antibacterial
and fungal activity. The antibacterial mechanisms of AgNPs involved inhibition of LDH activity,
increased protein and glucose leakage, DNA and protein damage, and depolarization and
destabilization of the plasma membrane. AgNPs, on the other hand, increased alanine aminotransferase,
aspartate aminotransferase, urea, creatinine, malondialdehyde, and nitric oxide
levels in mice while decreasing glutathione reduced.

Conclusion:
Our study showed that AgNPs synthesized by Streptomyces, lemon, and chitosan
have powerful antimicrobial properties. Chitosan-AgNPs showed the most pronounced antibacterial
action, although it displayed significant toxicity in mice. Conversely, lemon-AgNPs revealed
the least notable impact.
A TTN-Associated Immunoprognostic Model Based on LASSO-Cox Regression for Cervical Squamous Cell Carcinoma and Endocervical
Adenocarcinoma
Authors: Dai Tianjin , Chen Peng , Zhang Jun , Wang Bing 
Published: September 2024

Background:
TTN mutations are the most common genetic mutations found in cervical
squamous cell carcinoma and endocervical adenocarcinoma. They have been shown to affect the
progression and prognosis of Cervical Endometrial glandular carcinoma (CESC). TTN mutations
may also regulate the immune phenotype of CESC, which could impact its prognosis. Previous studies
have demonstrated that CESC patients with TTN mutations had a significantly higher overall
survival rate than those with wild-type TTN. However, the impact of TTN mutations on the immune
microenvironment of CESC has not been thoroughly investigated.

Methods:
This paper aims to examine the TTN mutation status and RNA expression in the CESC
dataset from TCGA. Two gene features were identified to predict the prognosis of CESC. Consequently,
a CESC Immune Prognosis Model (CIPM) based on a LASSO-Cox regression analysis was
developed for the differential expression of immune-related genes between TTN-WT and TTNMUT
CESC samples.

Results:
The results showed that TTN mutations weaken the immune response in CESCs. Out of the
152 genes associated with the immune response, 21 displayed varying expression levels depending
on the presence or absence of TTN mutations.

Conclusion:
The study suggests that TTN mutations have an impact on the immune response in
CESCs. The CIPM was introduced and validated in 232 CESC patients to distinguish between highand
low-risk patients with an unsatisfactory prognosis, regardless of various clinical features.
A Novel Multitask Association Analysis Model with Deep Selfreconstruction for Diagnosis of Alzheimer’s Disease
Authors: Wu Tian-Ru , Gao Ying-Lian , Ren Qian-Qian , Cui Xinchun , Yuan Sha-Sha , Liu Jin-Xing 
Published: September 2024

Background:
With the development of brain imaging technology and genotyping technology,
the brain imaging genetic method has become a powerful means to investigate the pathogenesis
of Alzheimer's disease (AD). However, AD generally exhibits progression, multiplicity,
and intricacy, and different diagnostic groups may carry different biomarkers. At the same time,
traditional models often ignore the nonlinear relationship and inherent topological characteristics of
brain imaging genetic data.

Objective:
Therefore, developing a more reliable method to identify diagnosis-specific genotypes
and phenotypes is indispensable for exploring the pathogenesis of AD. In this paper, a novel deep
self-reconstruction multitask association analysis (DS-MTAA) method is proposed for AD-related
biomarkers extraction and AD classification.

Methods:
First, a deep neural network is designed to learn the nonlinear relationships between
samples. Also, the self-expression idea based on hypergraph regularization is utilized to perform
subspace clustering on the output of the network. Then, a multitask model consisting of sparse canonical
correlation analysis and regular logistic regression is constructed, in which each task is responsible
for learning a diagnosis-specific genotype-phenotype pattern.

Results:
Finally, the RobustBoost classifier is employed to perform the classification experiments
under 5-fold cross-validations. The experimental results show that DS-MTAA can achieve better
classification performance than other advanced comparison methods and identify more effective
brain biomarkers and genetic markers that are strongly associated with diseases.

Conclusion:
Therefore, it can be concluded that a novel multitask association analysis model with
deep self-reconstruction for the diagnosis of Alzheimer’s Disease can further understand the pathogenesis
of AD.
Predicting Drug-target Binding Affinity Based on Graph Isomorphism Network and iTransformer
Authors: Cui Weirong , Qian Jing , Yao Xiaojun , Hu Guang , Tong Henry H.Y. 
Published: September 2024

Background:
Deep learning models have gained significant traction in predicting drugtarget
binding affinity, primarily focusing on deciphering intricate drug-target relationships. However,
these models often overlook intermediate representations, thus failing to capture the holistic
characteristics of proteins crucial for discerning drug-target interactions.

Methods:
This study proposes a novel deep-learning model that captures comprehensive and longrange
dependencies within protein sequences. Leveraging deep feature engineering and an inverted
Transformer module, it integrates multi-scale chemical information of drug molecules using graph
neural networks and hierarchical attention mechanisms.

Results:
The proposed model achieves state-of-the-art performance across multiple drug-target interaction
datasets. It obtains MSE losses of 0.229 and 0.162 on the Davis and KIBA datasets, respectively,
and AUC scores of 0.982 and 0.985 on the Human and C. elegans datasets.

Conclusion:
These results demonstrate the model's superior efficacy in predicting drug-target affinity
and interactions, showcasing its potential to expedite drug discovery processes.
Implementing Wireless Sensor Network Through Machine Learning Techniques
Authors: Sethi Deepak , GORA MANAV , Jain Shubhi , Kumari Shrishti , Gupta Shraddha , TYAGI TANUSHI 
Published: September 2024

Introduction:
A regional WSN of independent SNs collects environmental and physical
data. Sensors for specific applications measure light, pressure, temperature, humidity, etc. WSNs
can transmit real-time data without infrastructure via radio frequencies. Smart cities, agriculture,
industrial automation, environmental monitoring, and healthcare use WSN data. Many SNs monitor
the network architecture's physical environment.

Method:
This design lets SNs talk to neighbors and base stations. Due to power limits, WSNs must
prioritise energy efficiency. ML enhances data processing, energy efficiency, and WSN performance.
WSN sensors assist ML in predicting events. Machine learning improves data compression,
anomaly detection, adaptive network management, WSN predictive modelling, industrial WSN
performance, energy efficiency, data analysis, etc. In this work, the dataset, which has parameters
such as SN’s positions, energy, distance from cluster head, and SN lifetime is provided as an input
to the following ML models Linear Regression, Random Forest, SVM, Naive Bayes, PCA, K
Nearest Neighbour, XG Boost, and NN.

Result:
The result showed that the Linear Regression, Random Forest, SVM, Naive Bayes Classifier,
PCA, K Nearest Neighbour, and XG Boost were all examined on the training and testing data.

Conclusion:
The training data accuracies are as follows: Linear Regression (46.64%), Random
Forest (99.67%), XG Boost (99.99%), SVM (32.10%), K Nearest Neighbor (98.56%), Naïve Bayes
Classifier (96.45%), Principle Component Analysis (97.88%) and NN (34.86%). The testing data
accuracies are as follows: Linear Regression (22.00%), Random Forest (97.18%), XG Boost
(96.94%), SVM (21.75%), K Nearest Neighbor (97.66%), Naïve Bayes Classifier(64.49%),
PCA(99.38%) and NN(28.94%). Linear Regression, Random Forest, SVM, Naive Bayes Classifier,
PCA, K Nearest Neighbour, and XG Boost were all examined. Results revealed that
A Review on Ocular Nanoformulation Based Formulations with Highlights on Pediatric Ocular Pharmacokinetics
Authors: Verma Ravinder , Bhatia Manisha , Mojumder Mithun , Patel Suraj , Mishra Vivek Kumar , Mathur Pooja , Bhatt Shailendra , Sharma Jai Bharti 
Published: September 2024

Abstract:
The potential use of nanoparticle-based formulations is being explored rapidly for drug
delivery in ocular treatment. Despite having several advancements in the area of ocular therapy,
the pharmacokinetics-based formulation development for pediatric ocular treatment is still not in
proper focus. There are an inadequate number of degenerative ocular ailments with childhood
onset. The purpose of this review is to focus on the pharmacokinetics studies of nanoparticle-
based formulations for treating ocular diseases and problems associated with the ocular treatment
of the pediatric population. Recent studies on pharmaceutical modeling of ocular formulations
have also been discussed. Nanoparticle-based formulations were collected by conducting a
literature survey on PubMed, Science Direct, and other portals. In this review, we have explored
in detail the explanation behind the inequality among available ocular treatment regimens for
youngsters as well as adults by specifically focusing on those diseases that can be distressing for
children. Latest innovative developments and advancements in drug delivery systems and challenges
in their usage particularly for young infant patients were also discussed. It can be concluded
that the bioavailability of ocular formulations and their effect on ocular cells can be further enhanced
manifolds by the development of nanoparticles-based formulations.
Measuring the Impact of the COVID-19 Pandemic on Learning Loss: Evidence from Ho Municipality, Ghana
Authors: Letsu Rose , Bigool Mark , Tchochu Emmanuel 
Published: September 2024

Introduction:
This article investigates the effects of school closures due to the COVID-19
pandemic on the math and science test scores of basic school students in Ho Municipality, Ghana.

Method:
The study used data collected from four schools: two public schools with 286 students and
two private schools with 253 students, for the period 2018–2021. STATA (version 17.0) was used
for the main analysis. Further, the data were analyzed by comparing the pre-COVID-19 years (2018
and 2019) to the COVID-19 years (2020 and 2021). The data collection procedure followed ethical
guidelines and data protection regulations, with permission and authorization granted by the relevant
educational authorities. This study establishes that COVID-19 negatively impacted the test results of
students, reducing math scores by 25% and science scores by 6.8%. Public schools were the most
affected, with a 23% reduction in math scores and a 39% reduction in science scores.

Result:
These findings suggest a drop in student performance due to the increased impact of the pandemic.

Conclusion:
The study recommends that educational institutions invest in and enhance remote learning
programs, such as by developing interactive online platforms, providing learning materials, and
training educators to deliver effective virtual instruction.
Adverse events following immunization (AEFIs) in health workers who receive COVID-19 vaccination at Academic Hospital Universitas Gadjah Mada, Yogyakarta
Authors: Lestari Ade Febrina , Sitaresmi Mei Neni , Haspitaningrum Anjarsari , Rachmasari Kusuma Ayu , Wulandari Ratih , Sari Shinta Kusumalarna , Ridhayani Firda 
Published: September 2024

COVID-19 is a new viral infection that has become a global pandemic, resulting in extremely high mortality and morbidity rates worldwide, including in Indonesia. Vaccination is one of the strategies for preventing COVID-19 infection promoted by the World Health Organization (WHO) to reduce COVID-19 morbidity and mortality. The Indonesian government supports the implementation of vaccination and conducts mass vaccination as a strategy to overcome the pandemic in Indonesia. The high immunization coverage resulted in increased use of vaccines, and events following immunization (AEFI) also increased. Reports on follow-up AEFI are needed as government policy references and information for the public. This study aims to describe the following events after the COVID-19 vaccine immunization and the incidence of the infection post vaccination. The study design was a cross-sectional study using primary and secondary data. The data were analyzed descriptively and statistically using Chi Square method by identifying association between demographic data and AEFI incidence. A total 131 respondents were included. Most respondents experienced AEFI after giving the first (77.1%) or second (71.9%) vaccine with the Sinovac vaccine. However, all reported mild AEFI. Most reported AEFIs were pain (48.8% and 49.6%), hungry (37.4% and 10.0%), and drowsiness (32.1% and 23.7%) after the first and the second vaccine. In conclusion, the prevalence of AEFI in the first and the second dose of inactivated COVID-19 vaccine is higher than that reported in the clinical trial study although the all AEFIs are considered as mild.
MEKANISME PENGAJUAN KLAIM BPJS DI RUMAH SAKIT UMUM SILOAM KUPANG
Authors: Taslim Raditya Kevin Adrianto , Meliala Andreasta 
Published: September 2024

ABSTRACT
Background: According to the Utilization Review from BPJS towards Siloam Hospitals Kupang on August 2022, BPJS claim submission of Siloam Hospitals Kupang is 2 months late. The delays is lowering the hospital score from BPJS, affecting the down payment given by BPJS, and may risk the claim to be expired.
Objective: The research aims to identify the suitability of BPJS claim submission flow, factors that causing delays in BPJS claim submission, and the role of factors associated with delays in BPJS claim submission by Casemix Unit of Siloam Hospitals Kupang.
Methods: The research is an exploratory case study with a single case research design with qualitative data presentation. Purposive Sampling is used to select the subject of this research, while the object of this research is all BPJS claim documents that have been verified by the Internal Verificator.
Results: While the flow of BPJS claim submission in Siloam Hospitals Kupang is suitable with regulation of the Minister of Heath, there are 286 (26%) inpatient claim files yet to be verified up until June 10th, 2023. The delays in BPJS claim submission is affected by the unreadiness of the administrative documents and patient’s medical record, discompliance to make sure of the administrative documents reliability and medical records completeness, discompliance to code and verify on time, higher workforce compared to the staff availability, lack of training, unavailability of SOP regarding the flow and requirement of BPJS claim submission, incomplete medical resume, and computer, network, also working space that need to be more comfortable for working environment.
Conclusion: Delays in BPJS claim submission by Casemix Unit of Siloam Hospitals Kupang is caused by factors such as staff’s compliance, number of staff, staff’s competence, hospital policies, completed BPJS claim files, Casemix unit facilities and infrastructure.

Keywords: Delay submission, BPJS claim, Casemix, Hospital
Khuruj Fi Sabilillah Jama'ah Tabligh: Fulfilment of Alimony, Implications for Household Harmony and Wife Psychology
Authors: Setiawan Agus , Asnawi Habib Shulton Asnawi 
Published: September 2024

This article reveals the household conditions of the Tabligh Jama'ah in the context of fulfilling the husband's livelihood towards his wife. The fulfilment of livelihood in the Tabligh Jama'ah is interesting to study because the followers of Jamâ'ah Tabligh apply a pattern that is often done, namely Khuruj Fi Sabilillah. The purpose of this article is how is the practice of fulfilling husband's alimony to his wife in Tabligh Jama'ah and its impact on the household from the perspective of wife's psychology? The type of this article is qualitative, analysing in depth related to the fulfilment of maintenance and wife psychology with the aim of revealing the practice of fulfilling the husband's maintenance obligations towards the wife of Jamâ'ah Tabligh, this field research was conducted in Metro City, the primary data source of this article is the husband of Jamâ'ah Tabligh followers and the wife left behind by her husband Khurûj f? sab?lillah. The results of the study found that the fulfilment of maintenance for Tabligh followers in Metro City who perform Khuruj Fi Sabilillah to provide maintenance for their wives is divided into three categories; first, well fulfilled, second less fulfilled, and third unfulfilled. However, the practice of Khuruj Fi Sabilillah causes a lot of household disharmony because the maintenance is not fulfilled, this has an impact on the wife's mental psychological burden, because the wife has to play a dual role, taking care of household affairs while earning a living.
Analysis of magnetized bio-convective Ellis nanofluid flow: Impact of viscous dissipation and activation energy
Authors: Akhtar Tayyaba , Abid Muhammad , Awad Mohamed M. , Chaudhry Munaza , Imran Muhammad 
Published: September 2024

This study delves into the complex flow dynamics of magnetized bioconvective Ellis nanofluids, highlighting the critical roles of viscous dissipation and activation energy. By employing a MATLAB solver to tackle the boundary value problem, the research offers a thorough exploration of how these factors, along with oxytactic microorganism’s mobility, shape fluid behavior in magnetized systems. Our findings demonstrate that an increase in the magnetization factor leads to a decrease in both velocity and temperature due to enhanced interparticle resistance from the Lorentz force. Additionally, streamline analysis reveals that higher mixed convection parameters intensify flow concentration near surfaces, while increased slip parameters reduce shear stress and boundary layer thickness. Although isotherm analysis shows that higher Ellis fluid parameters enhance heat conduction, with greater porosity values promoting efficient thermal dissipation. These insights significantly advance our understanding of nanofluid dynamics, with promising implications for bioengineering and materials science, setting the stage for future research in this field.
ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI PARTISIPASI KERJA PENDUDUK LANJUT USIA DI KECAMATAN ABIANSEMAL KABUPATEN BADUNG
Authors: Setia Rahini Ni Luh Putu , Sudibia I Ketut 
Published: September 2024

Penelitan ini bertujuan untuk menganalisis pengaruh status perkawinan, tingkat pendidikan, kesehatan lansia, status kepala keluarga, tunjangan hari tua, pendapatan keluarga, dan jumlah tanggungan secara simultan dan parsial, serta untuk mengetahui apakah jumlah tanggungan berperan dalam memoderasi pengaruh pendapatan keluarga di Kecamatan Abiansemal Kabupaten Badung. Populasi pada penelitian ini adalah penduduk 60 tahun ke atas sebanyak 14.430 orang dengan metode non-probability sampling mengkobinasikan metode purposive sampling dan metode accidental sampling diperoleh sampel sebesar 123 responden. Metode pengumpulan berupa observasi, wawancara terstruktur, dan wawancara mendalam. Teknik analisis data yang digunakan analisis deskriptif dan Moderated Regression Analysis (MRA). Berdasarkan hasil analisis diketahui variabel berpengaruh secara simultan terhadap partisipasi kerja penduduk lanjut usia. Kesehatan lansia dan jumlah tanggungan berpengaruh positif, tingkat pendidikan, dan pendapatan keluarga berpengaruh negatif, status kepala keluarga berpengaruh lebih tinggi, status perkawinan dan tunjangan hari tua berpengaruh lebih rendah secara parsial, dan jumlah tanggungan berperan dalam memperkuat pengaruh pendapatan keluarga terhadap partisipasi kerja penduduk lanjut usia di Kecamatan Abiansemal Kabupaten Badung.
PENGAMANAN TERPADU DALAM PENCEGAHAN KEBERANGKATAN PEKERJA MIGRAN INDONESIA ILEGAL DI PERBATASAN ENTIKONG KALIMANTAN BARAT
Authors: Alunaza Hardi , Ilmah Daris Nurul 
Published: September 2024

Meningkatnya kasus pekerja migran Indonesia secara ilegal membuat pemerintah melakukan berbagai regulasi penanganan. Penelitian ini menggunakan pendekatan deskriptif kualitatif dan teknik pengumpulan data hasil wawancara. Penelitian ini bertujuan untuk mengkaji lebih dalam mengenai upaya pengamanan terpadu dalam mencegah keberangkatan Pekerja Migran Indonesia secara ilegal yang dilakukan pemerintah Indonesia, khususnya pemerintah Kalimantan Barat. Penelitian ini terbagi menjadi empat pembahasan yaitu peningkatan Pekerja Migran Indonesia ilegal, permasalahan Pekerja Migran Indonesia ilegal yang ada di Entikong, regulasi yang dilakukan oleh Tentara Nasional Indonesia (TNI) dan BP2MI serta analisis permasalahan PMI menurut perspektif Human security. Hasil akhir yang didapatkan pada penelitian ini menunjukkan bahwa kinerja yang dilakukan oleh pemerintah terkait dengan permasalahan PMI ilegal ini, khususnya TNI dan BP2MI berusaha memaksimalkan kinerja untuk mengamankan keamanan nasional dari kegiatan ilegal yang membahayakan negara.
Post - Pandemic Crisis Consumption Practices to Frozen Food Products in Indonesia
Authors: Wasik Zainul , Gunawan Sri , Handriana Tanti 
Published: September 2024

Purpose: The objective of this study are to describe the pattern of consumption of frozen food participants from time to time (before, during, and after the pandemic) and to explore reasons participants consume frozen food from time to time (before and after when pandemic) and to predict the pattern of consumption of frozen food post-pandemic based on condition actual practice consumption participants.

Theoritical Reference: Product trends frozen experienced enhancement during the covid pandemic; however, conditions were assumed to be different when situation post-pandemic. In its most recent developments.

Method: Research in a manner qualitative use method studies case (case study) with Multiple Case Study Design with 1 unit analysis for 90 people (cases) customers product frozen food in Indonesia (West et al. regions, 30 people each).

Originality/ Value: To reach the objective study, this illustration was used Yin's approach with positivism to understand what already happened or reality (condition practice natural) related consumption product frozen food.

Result and Conclusion: The results of this study indicate that customers still have an attraction to consume frozen products food even though there is no pandemic.

Implication of Research: During the post-pandemic period, the Frozen Food business is still promising and promising so it can be developed on a broader scale.