bluuebunny/crossref_metadata_2025 huggingface dataset:
Cotton Chronology: Convolutional Neural Network Enables Single-Plant Senescence Scoring with Temporal Drone Images
Authors: DeSalvio Aaron J. , Arik Mustafa A. , Murray Seth C. , García-Ramos Oriana , DeSalvio Serina M. , Stelly David M.
Published: February 2024

Senescence is a degenerative biological process that affects most organisms. Timing of senescence is critical for annual and perennial crops and is associated with yield and quality. Tracking time-series senescence data has previously required expert annotation and can be laborious for large-scale research. Here, a convolutional neural network (CNN) was trained on unoccupied aerial system (UAS, drone) images of individual plants of cotton (Gossypium hirsutum L.), an early application of single-plant analysis (SPA). Using images from 14 UAS flights capturing most of the senescence window, the CNN achieved 71.4% overall classification accuracy across six senescence categories, with class accuracies ranging between 46.8–89.4% despite large imbalances in numbers of images across classes. For example, the number of images ranged from 109 to 1,129 for the lowest-performing class (80% senesced) to the highest-performing class (fully healthy). The results demonstrate that minimally pre-processed UAS images can enable translatable implementations of high-throughput phenotyping using deep learning methods. This has applications for understanding fundamental plant biology, monitoring orchards and other spaced plantings, plant breeding, and genetic research.
Automatic Assume-Guarantee Reasoning for Safety andLiveness Using Passive Learning
Authors: Sankur Ocan
Published: February 2024

We present circular assume-guarantee reasoning rules automated by an appropriate use of passive learning algorithms for automata and LTL formulas. Both algorithms directly apply to systems made of not just two but multiple components. Moreover the algorithms are modular in the sense that they can be instantiated by any external learning algorithm and model checker. We present experiments showing the feasability of our approach.
Effects of Speed Dependent Treadmill Training on Dual Task Performance in Patients With Parkinson’s Disease
Authors: Hameed Rahma , shahid Wajiha , Pervez Maira , Batool Uzra
Published: February 2024

BACKGROUND:
Parkinson’s disease is progressive disorder, which cause rigidity, balance impairment and tremors. In Parkinson disease patients, the dual task decreases the speed of walking and there is high risk of fall.
OBJECTIVE:
To determine the effects of speed dependent treadmill training on dual task performance in patients with Parkinson’s disease.
METHODOLOGY:
Multicenter randomized clinical trial conducted from January to July 2023 among 24 participants with mild to moderate Parkinson’s disease in 2 outpatient hospitals in Pakistan. The subjects were randomly allocated into two groups. Experimental group received 5weeks treatment on moderate speed for 4 min×4 times for 3 sessions per week. While control group received 5weeks treatment on slow speed for 4 min×4 times for 3 sessions per week. Dual task testing, BBS, and the UPDRS-III were administered at baseline and after the five-week period. Data analyzed on SPSS 25.
RESULTS:
Experimental group had 91.7% male and 8.3% female, while control group had 83.3% male and 16.7% female. The mean and standard deviation of BBS, UPDRS-III and dual-tasking test was decreased in experimental group as compared to control group. Significant difference was found for BBG (p≤0.005), dual-testing test (p≤0.000) and walking speed while dual-tasking (p≤.039) among both groups.
CONCLUSION:
Speed dependent treadmill training improves the dual task performance in Parkinson patient. Slow speed treatment showed more promising result as compared to the moderate treatment in BBS and dual tasking. Additionally, the moderate speed group outperformed the slow speed group in UPDRS-III.
An evaluation of collagen peptide for transdermal delivery using Strat-M ® membrane and excised mouse skin
Authors: Yan Zheng , Dong Peng , Jiang Bin , Zhang Xiao-Qing , Liu Li-Ge , Wang Hai-Yan
Published: February 2024

In the field of medicine and cosmetics, transdermal experiments commonly used to evaluate the transdermal absorption of topical formulations. In this study, we applied Strat-M® membrane to study the in vitro transdermal properties of collagen peptide with different average molecular weight, and compared them with the transdermal absorption through excised mouse skin in vitro. The results showed that the transdermal rate of collagen peptide through Strat-M® and excised mouse skin increased linearly with time, and the different concentrations of collagen peptide solutions affected the final cumulative transmission. The cumulative transmission per unit area and transdermal rate of CP500 were both the highest among the four CPs. The cumulative transmission per unit area of collagen peptides through Strat-M® has a good correlation with that through excised mouse skin, R2 > 0.98. Strat-M® can replace the excised mouse skin in vitro to carry out the transdermal experiment of collagen peptide. Our results can be used to guide formulators in selecting vehicles in early development in the pharmaceutical, personal care and cosmetic industries.
WITHDRAWN: Effects of dietary Bacillus pumilus on the growth performance, intestinal health, lipid metabolism, and mTOR signaling pathway of juvenile Coho salmon (Oncorhynchus kisutch)
Authors: Guo Mengjie , Meng Liuqing , Li Fanghui , Liu Yongqiang , Zhang Ziqi , Zhang Qin , Kong Weiguang
Published: February 2024

This study explored and evaluated the addition of the probiotic Bacillus pumilus Rf8 to Coho salmon (Oncorhynchus kisutch) feed. A total of 360 juvenile Coho salmon with an initial body weight of 130.45 ± 1.11 g were randomly divided into four treatment groups, with three replicates per group and 30 fish per replicate. Different concentrations of B. pumilus were added to the feed of the four treatment groups: 0 (control group), 2 × 106, 4 × 108, and 8 × 1010 cfu/g. The experiment lasted 70 days. Growth performance parameters, nutritional metabolism, immune-related serum biochemical indicators, enzyme activity, gene expression, and muscle composition were evaluated. Furthermore, intestinal histology and intestinal flora were assessed. The findings indicated that relative to the control group, B. pumilus Rf8 notably enhanced the growth performance, protein and fat metabolism, and immune status of the fish, effectively bolstering the structure and function of the intestinal microbiota. The “4 × 108 cfu/g concentration” group demonstrated a substantial advantage in juvenile fish. The B. pumilus strains identified in this study exhibit promising potential as probiotic feed supplements in Coho salmon aquaculture.
Correlation Avoidance in Single-Photon Detecting Quantum Random Number Generators by Dead Time Overestimation
Authors: Solymos Balázs , Schranz Ágoston , Telek Miklós
Published: February 2024

In the case of quantum random number generators based on single photon arrivals, the physical properties of single-photon detectors, such as time-tagger clocks and dead time, influence the stochastic properties of the generated random numbers. This can lead to unwanted correlations among consecutive samples.
We present a method based on extending the insensitive periods after photon detections. This method eliminates the unwanted stochastic effects at the cost of reduced generation speed. We calculate performance measures for our presented method and verify its correctness with computer simulations and measurements conducted on an experimental setup. Our algorithm has low complexity, making it convenient to implement in QRNG schemes, where the benefits of having uncorrelated output intervals exceed the disadvantages of the decreased rate.
Draft genome of Brasenia schreberi, a worldwide distributed and endangered aquatic plant
Authors: Wu Lin-Fang , Zhu Wei-Guang , Yu En-Ping , Cao Hong-Lin , Wang Zheng-Feng
Published: February 2024

Objectives
Brasenia is a monotypic genus in the family of Cabombaceae. The only species, B. schreberi, is a macrophyte distributed worldwide. Because it requires good water quality, it is endangered in China and other countries due to the deterioration of aquatic habitats. The young leaves and stems of B. schreberi are covered by thick mucilage, which has high medical value. As an allelopathic aquatic plant, it can also be used in the management of aquatic weeds. Here, we present its assembled and annotated genome to help shed light on medial and allelopathic substrates and facilitate their conservation.
Data description:
Genomic DNA and RNA extracted from B. schreberi leaf tissues were used for whole genome and RNA sequencing using a Nanopore and/or MGI sequencer. The assembly was 1,055,148,839 bp in length, with 92 contigs and an N50 of 22,379,495 bp. The repetitive elements in the assembly were 555,442,205 bp. A completeness assessment of the assembly with BUSCO and compleasm indicated 88.4 and 90.9% completeness in the Eudicots database and 95.4 and 96.6% completeness in the Embryphyta database. Gene annotation revealed 67,747 genes that coded for 73,344 proteins.
Empowering and Equipping Parents with the Basic Intervention Skills in Handling their Children with Special Learning Needs
Authors: V. Catama Bryan , Ann B. Domalanta Mary , L. Balmeo Marilyn , Dinoc Ignacio Teresita , Marie C. Magat Sheila
Published: January 2024

Parents of children with special learning needs face challenges balancing family needs without sacrificing care. For remote communities, difficulty accessing support compounds struggles. This qualitative phenomenological study explored an extension intervention program's effectiveness empowering parents of children with special needs. Through interviews with participating parents, thematic analysis revealed the program helped in three key empowerment dimensions. Firstly, parents transitioned from limited disability understanding to increased knowledge through educational resources. Secondly, feelings of isolation changed to supportive social networks via connections. Finally, the program equipped parents with resilience skills/mindsets moving from hopelessness towards effective coping. The multidimensional model addressed interrelated cognitive, social and emotional issues impacting parenting. Findings provide valuable insights how holistic, community programs successfully empower/support these families. Further research understands long term impacts and relationships to child outcomes. Keywords: Coping skills, Disability intervention, Family-centered care, Parental empowerment, Resilience, Special needs children.
Research Output and Knowledge Translation Among Faculty Members of University of Technology, Jamaica
Authors: Garba Usman Abubakar
Published: January 2024

Universities are very important assets to produce research knowledge. The three major responsibilities of university faculty members are teaching, research, and community service. Balancing these three responsibilities is often very challenging, and the work that suffers most is research. The government of every nation looks up to its universities to produce research knowledge. The goal is to investigate the research output and knowledge translation among faculty members at Jamaica’s national university. A descriptive quantitative cross-sectional design was used for this study. This design was used to collect data from faculty members at one point in time. Most of the respondents (56.3%) perceived a lack of protected time for research as a barrier to research productivity. Seventy-five percent of the respondents reported having published one research article as the first author in the last two years. The majority (75%) of the respondents have concerns about the research policy of the university. The most common perceived barrier to knowledge translation (KT) was a lack of awareness of the concept of KT. The faculty members are experiencing challenges in conducting research and translating research findings. Keywords: Knowledge translation, Research output.
Evaluating Smartphone Ownership and Usage for Maternal and Child Health in a Ugandan Slum
Authors: Mukiibi Michael , Maghanga Mshilla
Published: January 2024

This research explores smartphone ownership and usage among Ugandan slum-dwelling women, assessing their readiness for mobile health maternal and child health interventions. A mixed-methods approach was employed, including a survey of 200 women and in-depth interviews with 23 participants. Findings reveal significant smartphone usage and a positive disposition towards receiving health information digitally. Women valued the informative nature and convenience of health messages on their phones. Challenges identified include costs and technological literacy. The study underscores the potential of mHealth solutions in low-income settings, highlighting the necessity for accessible and user-friendly technology. Keywords: mHealth, Maternal Health, Smartphone Ownership, Slum Settings, Technology Acceptance, User Attitude, Uganda.
A Machine Learning approach to predict Length of Stay of vehicles in an inbound logistics operation
Authors: Pereira Victor Hugo , Alves Kaike , Aguiar Eduardo
Published: January 2024

A large steel plant receives up to millions of tons of scrap metal through road transportation each year in its inbound logistics process. The Length of Stay (LOS) of vehicles is one of the most critical metrics that represent the performance of the unloading operation of raw materials. Accurately predicting this metric enables managers to make data-driven decisions at operational, tactical, and strategic levels. This study proposes implementing a Machine Learning (ML) approach for predicting the LOS of vehicles loaded with scrap metal in the inbound operation of a large Brazilian steel plant. The performance of five ML models – Linear Model Ridge, k-nearest neighbors Regressor, Gradient Boosting Regressor, Decision Tree Regressor, and ePL-KRLS-DISCO – was evaluated in terms of Root Mean Squared Error (RMSE), Mean Average Error (MAE), and execution time. The results are compared with the current method of prediction and statically validated through an Analysis of Variance (ANOVA) test. The ML approach applied in this study achieved better accuracy, reducing by 64% the RMSE, and has the potential to enable more reliable data-driven decisions for the company.
Armature fault diagnosis of universal motors using time-series data in neural networks
Authors: Silva Guilherme , Silva Bernard , Bertol Douglas
Published: February 2024

A common issue of DC and universal motors is the quality of the armature circuit and the commutation process. Some faults that could happen during the final assembly process, such as a short circuit between two segments or a broken segment in the armatures commutator, may not be detected by a visual inspection or the regular no-load end-of-line test. A more detailed analysis, using the feedback of various auxiliary sensors, usually requires implementing systems with more complex and expensive hardware. It also may take longer to get a precise analysis, which may not be suitable for the production process. As a method to do a fast and accurate detection and classification of faults in the armatures circuit of universal motors, this paper suggests the analysis of the armature voltage and current waveform by an artificial neural network (ANN). The current and voltage signals acquired during the no-load test formed a time-series waveform that was applied to an ANN trained to classify the signal in three possible outcomes: healthy armature, armature with shortcircuited segments, and armature with a broken part. The results achieve effectiveness above 98% in the task of detection and classification of faults. The solution was tested in the production line of universal motors and proved to be fast, reliable, and efficient for the usual no-load test, proving to be suitable in an industrial context.
Detectores de Intrusão Baseados em Random Forest Aplicados a Smart Grids
Authors: Cartucho Igor , Santos Lima Markus Vinícius
Published: February 2024

O smart grid e um modelo de rede elétrica inteligente que, ao integrar tecnologias da informação e de comunicação com sistemas de energia, apresenta diversas melhorias em relação ao modelo convencional. Por depender fortemente de tecnologias da informação, esse novo modelo est a sujeito a ameaças digitais, o que pode levar ao comprometimento de seus principais subsistemas. A Advanced Metering Infrastructure (AMI) e um desses subsistemas de vital importância para seu funcionamento, que é vulnerável a ciberataques e, por isso, precisa estar integrada a eficazes sistemas de segurança. Nesse sentido, este trabalho tem como objetivo apresentar uma solução de segurança para a AMI que emprega sistemas de detecção de intrusão distribu ídos e estudar tres modelos de detector de intrusão baseados em random forest. Para as etapas de treinamento e teste desses detectores, é utilizado o conjunto de dados NSL-KDD, amplamente utilizado para o estudo de detecção de ataques cibernéticos. Dentre os modelos propostos, o detector 3, que combina random forests com K-means, revelou-se um otimo candidato a ser utilizado para a proteção da AMI, apresentando acur acia, taxa de falsos positivos e taxa de verdadeiros positivos de 94,6%, 9,6% e 97,8%, respectivamente.
Classificação de doenças respiratórias a partir de imagens Raios-X de tórax usando redes neurais
Authors: França Aldenis , Torres Carolina , Cabral Luciano
Published: January 2024

A detecção precoce e precisa de doenças respiratórias, como COVID-19 e pneumonia, é de extrema importância para o tratamento eficaz e controle da disseminação dessas doenças. Com avanços recentes em técnicas de aprendizado de máquina, particularmente redes neurais convolucionais (CNNs), tornou-se possível utilizar imagens de raios-X para auxiliar na detecção dessas doenças. Neste artigo, exploramos a aplicação de redes neurais na detecção de COVID-19 e pneumonia usando imagens de raios-X, discutindo os desafios, abordagens e resultados alcançados até agora.
EU-Türkiye Relations with a Special Focus on Syrian Migrants: Readmission Agreement and the 18 March Agreement
Authors: ŞEHİTOĞLU Recep
Published: January 2024

After the start of the Syrian civil war in March 2011, millions of Syrians were forced to flee their country. As other effects of the war and the intensity of migration increased, the situation developed into a humanitarian crisis. In response, Türkiye, as a neighbor of Syria, implemented an open-door policy towards Syrian migrants; and as of 2023, the number of Syrians under temporary protection in Türkiye reached approximately 3.5 million. This number is not only the highest number of Syrians but also is incomparably higher than the number of Syrians in other countries. However, the migration flow towards Türkiye facilitated an influx of migrants to the borders of the European Union (EU). As a result of this influx, the EU needed to join hands with Türkiye. This research analyses EU-Türkiye relations as regards migrating Syrians. In brief, the two actors signed the Readmission Agreement and the 18 March Memorandum of Understanding to prevent the flow of Syrians to the EU. In the actuality created by these texts, the process observed is considered to have yielded a result in favor of the EU. In other words, the flow of migration to the EU through Türkiye has been largely prevented. However, from the Turkish perspective, Türkiye has had to bear the huge expense of hosting approximately 3.5 million Syrians but by and large, has not received the expected support from the EU.
Estimating groundwater recharge rates in the Upper Awash Basin, Ethiopia under different combinations of model complexity and objective functions
Authors: Redda Muauz Amare , Kebede Seifu , Birhanu Behailu , Hussien Bediru
Published: February 2024

This study addresses the critical need for reliable groundwater recharge quantification by investigating the uncertainty associated with recharge estimation based on various combinations of model complexity and objective functions. Focusing on the Hombele catchment in the upper Awash Basin, Ethiopia, the research aims to analyze parameter sensitivity under different model complexities and objectives while estimating groundwater recharge for the period 1986–2013. Employing a Monte-Carlo-based calibration scheme, the study fine-tunes model parameters using objective functions like KGE, NSE, LogNSE, R2, and VE across 10 combinations of model complexity and objective functions. Results identify FC, LP, and BETA as highly sensitive parameters, while UZL, K0, and MAXBAS show limited influence in all model complexity and objective function scenarios. The semi-distributed HBV-light model achieves calibration, validation, and overall period KGE (NSE) values of 0.89 (0.80), 0.80 (0.73), and 0.87 (0.77), respectively. Sensitivity analyses reveal significant impacts on model parameters and recharge estimation based on the chosen objective function and model complexity levels. Average annual recharge rates range from 185.9–280.5 mm when the HBV-light model is semi-distributed, contrasting with 185.3–321.7 mm under lumped model conditions, emphasizing the importance of considering these factors in groundwater resource assessments.
Ecosistema Sierra Nevada de Santa Marta: reflexiones desde la ciencia y la tecnología
Authors: Aguirre Forero Sonia Esperanza , Piraneque Gambasica Nelson Virgilio , Robles Algarín Carlos Arturo
Published: January 2024

Ecosistema Sierra Nevada de Santa Marta: reflexiones desde la ciencia explora la importancia de la Sierra Nevada de Santa Marta (SNSM) como un ecosistema estratégico para la sostenibilidad ambiental y su impacto en las comunidades locales en dos apartados. El primero destaca la relevancia del ecosistema a nivel global y en su entorno, al tiempo que reconoce los conflictos sociales y de uso del territorio. Asimismo, resalta las contribuciones de la investigación y la tecnología para cerrar brechas en las comunidades que la habitan. El segundo se centra en dos estudios de caso. El inicial examina la validación de la cosecha asistida de café en la SNSM y cómo la adopción de tecnologías, como derribadoras selectivas, puede mejorar la producción de café, reducir costos y adaptarse al cambio climático. El segundo se enfoca en la implementación de un sistema renovable híbrido solar-eólico y una planta de tratamiento de agua potable en la comunidad académica de la Institución Educativa Distrital La Revuelta, en Guachaca, Santa Marta. Este proyecto buscó proporcionar energía y agua potable a una comunidad rural promoviendo el uso de energías renovables, cerrando brechas tecnológicas en la región.
Recent Advances in Synthetic Routes for Biologically Active Tetrahydroquinoxalines
and Derivatives: A Comprehensive Review
Authors: Sahoo Ashis Kumar , Bhattacharyya Aditya
Published: February 2024

Tetrahydroquinoxalines are found in many biologically and pharmacologically active small molecules.
In the past two decades, significant progress has been made in the development of novel synthetic routes
for the preparation of biologically active tetrahydroquinoxalines and their derivatives. This synthetic review
aims to provide a comprehensive overview of the advancements in the field of various synthetic strategies and
methodologies employed for the synthesis of tetrahydroquinoxaline scaffolds during this period. The review
emphasizes the diverse synthetic approaches employed, including cycloaddition reactions, condensation reactions,
intramolecular cyclization reactions, ring expansion reactions, hydrogenation reactions, and other miscellaneous
methods.
TPD52 as a Potential Prognostic Biomarker and its Correlation with Immune Infiltrates in Uterine Corpus Endometrial Carcinoma: Bioinformatic Analysis and Experimental Verification
Authors: Miao Lu , Chen Buze , Jing Li , Zeng Tian , Chen Youguo
Published: February 2024

Background:

Aberrant expression of tumor protein D52 (TPD52) is associated with
some tumors. The role of TPD52 in uterine corpus endometrial carcinoma (UCEC) remains uncertain.

Objective:

We aimed to investigate the involvement of TPD52 in the pathogenesis of UCEC.

Methods:

We employed bioinformatics analysis and experimental validation in our study.

Results:

Our findings indicated that elevated TPD52 expression in UCEC was significantly associated
with various clinical factors, including clinical stage, race, weight, body mass index
(BMI), histological type, histological grade, surgical approach, and age (p < 0.01). Furthermore,
high TPD52 expression was a predictor of poorer overall survival (OS), progress-free survival
(PFS), and disease-specific survival (DSS) (p = 0.011, p = 0.006, and p = 0.003, respectively).
TPD52 exhibited a significant correlation with DSS (HR: 2.500; 95% CI: 1.153-5.419; p =
0.02). TPD52 was involved in GPCR ligand binding and formation of the cornified envelope in
UCEC. Moreover, TPD52 expression was found to be associated with immune infiltration, immune
checkpoints, tumor mutation burden (TMB)/ microsatellite instability (MSI), and mRNA
stemness indices (mRNAsi). The somatic mutation rate of TPD52 in UCEC was 1.9%. A ceRNA
network of AC011447.7/miR-1-3p/TPD52 was constructed. There was excessive TPD52
protein expression. The upregulation of TPD52 expression in UCEC cell lines was found to be
statistically significant.

Conclusion:

TPD52 is upregulated in UCEC and may be a useful patent for prognostic biomarkers
of UCEC, which may have important value for clinical treatment and supervision of
UCEC patients.
Regulating Lipid Metabolism via Mitochondrial Dynamics in Tongue Squamous Cell Carcinoma Cancer Stem Cells
Authors: Wu Fan , Chen Suling , Ren Siqi , Wang Ruixin , Tan Yongmei , Chen Rongxi , Li Bowen , Cao Haotian , Li Jinsong
Published: February 2024

Background:

Cancer stem cells (CSCs) are a sub-population of cancer cells present
in many kinds of malignant tumors that have the potential for self-proliferation and differentiation.
These cells have been demonstrated as the main cause of tumor recurrence and metastasis.
Strong evidence indicates that CSCs prefer reprogrammed fatty acid β-oxidation over oxidative
phosphorylation for sustaining energy supply. Although mitochondrial dynamics participate in
the regulation of cancer stemness, the correlation between the inhibition of mitochondrial fission
and the regulation of lipid metabolism in CSCs remains poorly understood.

Methods:

The human tongue squamous cell carcinoma (TSCC) cell lines CAL27 and SAS were
used to obtain the CSCs by 3D Spheroid Culture. Then,western blot methods, RT-PCR and flow
cytometry analysis were used to identify the TSCC CSCs. Next, Immunofluorescence method,
transmission electron microscopy detection and western blot methods were used to evaluate the mitochondrial
morphology and the quantity of lipid droplets (LDs). Lastly, lipidomic analysis was applied
to explored the lipidomic alterations of TSCC CSCs with different mitochondrial morphology.

Results:

Here, we show that the quantity of lipid droplets containing intracellular triglyceride
(TG) can be decreased by regulating mitochondrial morphology. Lipidomic analysis using ultraperformance
liquid chromatography-mass spectrometry (UPLC-MS) also compared alterations
in lipid metabolites in tongue squamous cell carcinoma (TSCC) CSCs, TSCC cells (non-CSCs),
and CSCs with different mitochondrial morphology. Discriminant lipids of statistical significance
were successfully annotated, including phosphatidylcholines (PCs), phosphatidylethanolamines
(PEs), sphingomyelins (SMs), triacylglycerols (TGs), phosphatidylglycerols (PGs), phosphatidylserines
(PSs), lysophosphatidylcholines (LPCs), and lysophosphatidylethanolamines (LPEs).

Conclusion:

This study provides a deeper insight into the alterations of lipid metabolism associated
with TSCC CSCs, non-CSCs and CSCs regulated by mitochondrial dynamics and thus
serves as a guide toward novel targeted therapies.
Hierarchical Virtual Screening of SARS-CoV-2 Main Protease Potential
Inhibitors: Similarity Search, Pharmacophore Modeling, and Molecular
Docking Study
Authors: Mando Huda , Allous Iyad
Published: February 2024

Background:

The outbreak of COVID-19 caused by severe acute respiratory syndrome
coronavirus2 (SARS-CoV-2) resulted in a widespread pandemic. Various approaches involved
the repositioning of antiviral remedies and other medications. Several therapies, including
oral antiviral treatments, represent some approaches to adapting to the long existence of the
COVID-19 pandemic. In silico studies provide valuable insights throughout drug discovery and
development in compliance with global efforts to overcome the pandemic. The main protease is
an essential target in the viral cycle. Computer-aided drug design accelerates the identification
of potential treatments, including oral therapy.

Aims:

This work aims to identify potential SARS-CoV-2 main protease inhibitors using different
aspects of in silico approaches.

Methods:

In this work, we conducted a hierarchical virtual screening of SARS-CoV-2 main protease
inhibitors. A similarity search was conducted to screen molecules similar to the inhibitor
PF-07321332. Concurrently, structure-based pharmacophores, besides ligand-based pharmacophores,
were derived. A drug-likeness filter filtered the compounds retrieved from similarity
search and pharmacophore modeling before being subjected to molecular docking. The candidate
molecules that showed higher affinity to the main protease than the reference inhibitor were
further filtered by absorption, distribution, metabolism, and excretion (ADME) parameters.

Results:

According to binding affinity and ADME analysis, four molecules (CHEMBL218022,
PubChem163362029, PubChem166149100, and PubChem 162396459) were prioritized as
promising hits. The compounds above were not reported before; no previous experimental studies
and bioactive assays are available.

Conclusion:

Our time-saving approach represents a strategy for discovering novel SARS-CoV-
2 main protease inhibitors. The ultimate hits may be nominated as leads in discovering novel
SARS-CoV-2 main protease inhibitors.
Cyber Security Challenges and Effective Security Measures for IOT-based Intelligent Healthcare Systems
Authors: Somnathea Abhijit T. , Gopinath N. , Deena G. , Anandh R. , kumar Santosh , Tiwari Kanchan S.
Published: February 2024

Aims and Background:

In order to keep up with the rapid development of technology,
cities must enhance their offerings in the areas of public security, medical care, transportation,
and citizen well-being. Healthcare systems rely heavily on patient care. Patients' life and the services
offered by doctors, nurses, clinicians, pharmaceutical companies, and governments stand to
benefit from the implementation of Healthcare IoT. There has been a change in the medical industry,
marked by the widespread adoption of wireless healthcare-monitoring-systems (HMS) in
hospitals.

Objectives and Methodology:

However, the Internet-of-Things(IoT) concept frequently ignores
security-privacy for linked things. Security and privacy protections must be implemented systematically
throughout the entire healthcare and remote health monitoring system, from the creation
of equipment to their interconnection, communication, storage, and eventual destruction.
This research investigates the risks associated with using smart health devices and provides recommendations
for addressing those risks. The present security and privacy of IoT devices in
healthcare systems, as well as the difficulties in adopting security frameworks, are discussed, and
recommendations for addressing these issues are offered.

Results and Conclusions:

This study also contributes in two ways to the ongoing effort to investigate
security-privacy concerns in the circumstance of smart cities for healthcare purposes.
Moreover, this article provides a summary of the many Internet of Things applications and the
cyber threats they face. On the other hand, thorough assessments of methods to reduce cyber
threats to 60% are presented.
Emulgel: A Cutting Edge Approach for Topical Drug Delivery System
Authors: Jain Anjali , Kumar Prashant , Verma Anurag , Mohanta Bibhash Chandra , Ashique Sumel , Pal Radheshyam , Kumar Shubneesh , Mishra Neeraj
Published: February 2024

Emulgel is considered an advanced leading form of topical drug delivery system. It
possesses the quality of a dual control drug mechanism for drug release as it holds the properties
of both gel as well as emulsion. Emulgel is capable of overcoming the problems of the conventional
route of topical drug delivery, like low spreadability and stickiness with the delivery
of hydrophobic drugs, enhanced bioavailability at the local site of action, no greasy texture, and
ensuring patient compliance. An emulsion is used either w/o or o/w, and the drug can be incorporated
into the suitable phase of the emulsion. After that, the emulsion is incorporated into the
gel phase. Several factors like oil phase, gelling agent, and emulsifier can affect the efficacy and
stability. This advancement is beneficial not only for dermatology but also for cosmetology as
well. Currently, emulgel-based formulations are used for the delivery of anti-inflammatory, analgesic,
anti-acne, and antifungal drugs with a wide array of exploration.
From Scraps to Solutions: Harnessing the Potential of Vegetable and Fruit
Waste in Pharmaceutical Formulations
Authors: Mittal Vishnu , Sharma Anjali
Published: February 2024

Background::

Food waste is a major worldwide problem due to the increasing population
and imbalances in supply chains. Waste from fruits and vegetables are a substantial proportion of
the overall food waste generated, accounting for approximately 42% of the waste produced. Methane,
a strong greenhouse gas with a significant potential for global warming, is produced when
these waste products are typically dumped in landfills.

Objectives::

The study's goal is to present a thorough overview of the most recent findings and developments
in the use of vegetable and fruit waste for creating therapeutic formulations. Recognizing
the opportunities and challenges in this developing area of study, as well as the promise that
vegetable and fruit waste contains for the creation of environmentally friendly and economically
advantageous pharmaceutical formulations.

Methods::

A comprehensive review of existing literature on the utilization of vegetable and fruit
waste in pharmaceutical formulations was conducted. The review included studies on the chemical
composition and bioactive compounds present in various types of vegetable and fruit waste, their
extraction methods, and their potential applications in pharmaceutical formulations. Additionally,
current waste management practices and challenges associated with waste disposal were also analyzed.

Conclusion::

The review highlights the significant potential of vegetable and fruit waste in the development
of pharmaceutical formulations. Fruit and vegetable waste offer a wide range of bioactive
compounds, such as antioxidants, antimicrobials, and antiinflammatory agents, which could be
utilized in drug formulation. Moreover, this approach can promote environmental sustainability by
reducing waste generation and enhancing waste utilization. Further research and development efforts
should focus on optimizing extraction methods, evaluating the efficacy and safety of wastederived
compounds, and addressing regulatory requirements for integrating vegetable and fruit
waste into pharmaceutical products. Harnessing the potential of vegetable and fruit waste in pharmaceutical
formulations can lead to sustainable advancements in the pharmaceutical industry while
addressing environmental concerns.
Bioactive Compounds from Kinnow Processing Waste and their Associated
Benefits: A Review
Authors: Pulparambil Adethi , Rasane Prasad , Singh Jyoti , Kaur Sawinder , Bakshi Manish , Mahato Dipendra Kumar , Kaur Jaspreet , Gunjal Mahendra , Bhadariya Vishesh
Published: February 2024

We have explored the expansive possibilities of kinnow peel, a frequently ignored
by-product of the fruit processing industry, in this thorough analysis. The production of kinnow
generates a significant amount of waste, including peel, seeds, and pulp. The disposal of this
waste is a major environmental issue, as it can lead to pollution and greenhouse gas emissions.
Due to the presence of bioactive substances that may be used in a variety of sectors, kinnow
processing waste has the potential to provide a number of advantages. In the culinary, pharmaceutical,
and cosmetic industries, the peel, seeds, and pulp from kinnow can be used as natural
sources of antioxidants, aromatics, pectin, and dietary fibre. Utilizing kinnow waste promotes
eco-innovation, increases sustainability, and aids in waste reduction. The development of a circular
economy can be sped up with more study and commercialization of kinnow waste products.
This analysis emphasises how important it is to understand and utilise the unrealized potential
of agricultural byproducts, like kinnow peel.
Fever-Induced Brugada-Pattern Electrocardiogram
Authors: Yudha Nugraha Tria , Prasetya Indra , Martini Heny , Rizal Ardian
Published: January 2024

Background: The Brugada syndrome is a type of cardiac arrhythmia frequently overlooked because of the dynamic character of the condition. Because it tends to progress into ventricular arrhythmias, it is a disorder that, if left untreated, carries the risk of being deadly. Not only is it essential for the practicing clinician to understand the situations that can disclose the concealed Brugada syndrome, but it is also essential for patients to understand these circumstances so that they can be educated to seek medical assistance quickly. This study aimed to describe the diagnosis and management of fever-induced Brugada pattern electrocardiogram Case presentation: Male in his 42-year-old with a history of intermittent fever for four days before hospital admission. High-degree fever was only relieved by taking antipyretics and was accompanied by nausea and muscle and joint pain. Upon arrival at the emergency department, he denied any complaints of chest pain or discomfort, shortness of breath, orthopnea, PND, leg swelling, palpitation, or syncope. A chest radiograph showed normal cardiac and pulmo (Figure 1); a first electrocardiogram showed Sinus Rhythm, HR 112 bpm, regular, FA normal, HA normal, P wave normal, PR interval 160 msec, QRS 80 msec, QTc 326 msec, Coved ST elevation at lead V1 (1 mm), V2 (3 mm), T inversion at lead V1-V2, suggesting sinus tachycardia with type II Brugada pattern. Conclusion: A Brugada pattern can be exposed to several stimuli, but fever is particularly potent. To assist urgent or emergency follow-up in cardiology, Emergency physicians must be informed of specific ECG findings based on the patient's clinical risk factors. The emergency doctor must be able to tell the difference between this pattern and a typical variation of RBBB, as a delayed diagnosis can have dire consequences.
Status of People with Hearing Loss in Korea: Findings of from the 2000 to 2020 Nationwide Survey of People with Disabilities
Authors: Oh Soo Hee
Published: February 2024

The purpose of this study is to understand the status of people with hearing loss in Korea based on findings from a nationwide survey of people with disabilities. The study investigated the statistics of people with hearing loss among the nationwide survey of people with disabilities from 2000 to 2020. Hearing loss population has been increased for the past 20 years and more than 70% of registered people with hearing loss in this study were over the age of 60. Cost issue was the main reason for not purchasing assistive devices (54%). Forty-seven point seven percent of respondents reported that communication difficulty was the reason for discomfort in outdoor activities. People with hearing loss reported that the highest the highest rate of discrimination experience (40.4%) from their peers during their school lives. They also felt that they did not receive much national support after registering their disability. 37% of the respondents used the national medical insurance in Korea for their assistive devices. National support for hearing loss should be considered from multiple aspects.
Neural Mechanism Theories: Dissecting Mismatch Negativity and Stimulus-Specific Adaptation for a Deeper Understanding of Auditory Processing
Authors: An HyunJung
Published: February 2024

The ability to automatically detect signal changes is essential to the survival for any organism. For example, an animal living in the forest can distinguish a relatively constant sound background, such as leaves blowing in the wind, from a sudden novel sound, such as a cracking branch, which might indicate the presence of a nearby predator. Distinct brain responses to novel sounds (as opposed to expected sounds) are known as mismatch negativity (MMN) in humans or stimulus-specific adaptation in animal. It is found that the neural response was attenuated by the repetitive stimulation of sound sequences, while the presentation of an unexpected stimulus enhances the neural responses. Three main hypotheses have been proposed concerning the this neural mechanisms: the model adjustment hypothesis, the neural adaptation hypothesis and predictive coding theory. The purpose of this study is to introduce theoretical perspectives within a fundamental scientific approach in order to elucidate MMN mechanisms. Additionally, we will review the literature that explains MMN from an audiological perspective through these theories.
Automated Category and Trend Analysis of Scientific Articles on Ophthalmology Using Large Language Models: Development and Usability Study
Authors: Raja Hina , Munawar Asim , Mylonas Nikolaos , Delsoz Mohammad , Madadi Yeganeh , Elahi Muhammad , Hassan Amr , Abu Serhan Hashem , Inam Onur , Hernandez Luis , Chen Hao , Tran Sang , Munir Wuqaas , Abd-Alrazaq Alaa , Yousefi Siamak
Published: February 2024

Background

In this paper, we present an automated method for article classification, leveraging the power of large language models (LLMs).

Objective

The aim of this study is to evaluate the applicability of various LLMs based on textual content of scientific ophthalmology papers.

Methods

We developed a model based on natural language processing techniques, including advanced LLMs, to process and analyze the textual content of scientific papers. Specifically, we used zero-shot learning LLMs and compared Bidirectional and Auto-Regressive Transformers (BART) and its variants with Bidirectional Encoder Representations from Transformers (BERT) and its variants, such as distilBERT, SciBERT, PubmedBERT, and BioBERT. To evaluate the LLMs, we compiled a data set (retinal diseases [RenD] ) of 1000 ocular disease–related articles, which were expertly annotated by a panel of 6 specialists into 19 distinct categories. In addition to the classification of articles, we also performed analysis on different classified groups to find the patterns and trends in the field.

Results

The classification results demonstrate the effectiveness of LLMs in categorizing a large number of ophthalmology papers without human intervention. The model achieved a mean accuracy of 0.86 and a mean F1-score of 0.85 based on the RenD data set.

Conclusions

The proposed framework achieves notable improvements in both accuracy and efficiency. Its application in the domain of ophthalmology showcases its potential for knowledge organization and retrieval. We performed a trend analysis that enables researchers and clinicians to easily categorize and retrieve relevant papers, saving time and effort in literature review and information gathering as well as identification of emerging scientific trends within different disciplines. Moreover, the extendibility of the model to other scientific fields broadens its impact in facilitating research and trend analysis across diverse disciplines.
Eco-Innovation for Sustainability in Traditional Herbal (Jamu) Agroindustry: OGSM-Gap Analysis Based on Employee Perception
Authors: Irawan Norbertus Citra
Published: February 2024

This research is motivated by the importance of eco-innovation in traditional herbal medicine agroindustry by using local ethnobotanical raw materials to support sustainability and answer increasingly stringent market demands. This research aims to identify gaps between objectives, goals, strategies, and performance measurements related to eco-innovation in the traditional herbal medicine agroindustry based on employee perceptions. The data analysis method used is the OGSM-Gaps model by collecting data through questionnaires distributed to traditional herbal medicine agroindustry employees at the research location, namely Solo Raya. The research population was employees of the traditional herbal medicine agroindustry. The research sample was taken using a simple random sampling method of 100 respondents. The research results highlight the need for improvement in several aspects of the organization. First, organizations need to focus on providing education and training for salespeople or store staff so that they can provide accurate information about traditional herbal medicine products. Second, increasing the promotion and branding of traditional herbal medicine products is needed to broaden public understanding. Furthermore, increasing the competitiveness of traditional herbal medicine products in the market is a priority, with an emphasis on market research and product innovation. Finally, operational efficiency needs to be improved through operational audits, adopting more efficient technology, and involving employees in these improvement efforts. These improvement efforts will support the organization in achieving sustainability goals and sustainable business growth.
Intellectual property synergies: merging halal certification with Indonesian communal intellectual property rights laws
Authors: Disemadi Hari Sutra , Alhakim Abdurrakhman , Silviani Ninne Zahara , Febriyani Emiliya
Published: February 2024

Indonesia possesses significant potential to enhance and expand its halal industry, leveraging its unique cultural assets from many of its indigenous communities. One of the ways to ensure the growth of the halal industry is the facilitation of IPR protection through the legal framework. Using a normative method supported by a statutory approach, this research analyzed the challenges and potentials of integrating halal certification into the communal IPR system in Indonesia. The analysis found many restrictions within the existing positive laws which can prevent the integration of halal certification into the communal IPR system. This research proposed a model of communal IPR according to the challenges identified, along with the normative construction needed to establish it. This model mainly focused on providing normative spaces for the integration of sharia compliance while also making sure that the purposes of IPR protection are fulfilled.
Reciprocated knowledge sharing and individual creative performance
Authors: Kim Hyunjee Hannah , Chung Yichia , Choi Jin Nam
Published: January 2024

Drawing on the norm of reciprocity from social exchange theory, we proposed that a focal team member's knowledge sharing would predict their own creativity to the extent that other members reciprocate such behaviors. We also expected that the focal member's social values would moderate
this reciprocation process. Empirical analysis of data collected from 169 team members and 50 leaders revealed that the relationship between a focal member's knowledge sharing and creativity was explained by other members' reciprocated knowledge sharing. This knowledge-reciprocation process
was strengthened by collectivistic values but weakened by individualistic values of the focal member. The present study reveals when and how individuals can gain creative benefits from their own knowledge-sharing behavior in work-based team settings.