bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deterministic Weight Modification-based Extreme Learning Machine for
Stock Price Prediction
Authors: Kalaiselvi K. , David Vasantha Kalyani 
Published: December 2023

Background:
The prediction of the stock price is considered to be one of the most fascinating
and important research and patent topics in the financial sector.

Aims:
Making more accurate predictions is a difficult and significant task because the financial
industry supports investors and the national economy.

Objectives:
The DWM is used to adjust the connection weights and biases to enhance prediction
precision and convergence rate. DWM was proposed as a method to reduce system error by
changing the weights of various levels. The methods for predictable changes in weight were provided
together with the computational difficulty.

Methods:
An extreme learning machine (ELM) is a fast-learning method for training a singlehidden
layer neural network (SLFN). However, the model's learning process is ineffective or incomplete
due to the randomly chosen weights and biases of the input's hidden layers. Hence, this
article presents a deterministic weight modification (DWM) based ELM called DWM-ELM for
predicting the stock price.

Results:
The calculated results showed that DWM-ELM had the best predictive performance,
with RMSE (root mean square error) of 0.0096, MAE (mean absolute error) of 0.0563, 0.0428,
MAPE (mean absolute percentage error) of 1.7045, and DS (Directional Symmetry) of 89.34.

Conclusion:
The experimental results showed that, in comparison to other well-known prediction
algorithms, the suggested DWM+ELM prediction model offers better prediction performance.
Comparative Study among MAPE, RMSE and R Square over the Treatment Techniques Undergone for PCOS Influenced Women
Authors: Shanmugavalli M. , Ignatia K. Majella Jenvi 
Published: December 2023

Background:
Among the various statistical measures, Root Mean Square Error
(RMSE), Mean absolute Percentage Error (MAPE), and R-squared (Coefficient of determination)
are the most widely used methods. The significance of the R square approach in the medical field
was extensively discussed in the current review. Furthermore, we compared a number of statistical
metrics for potential applications in the treatment of various disorders. In addition, the pertinent
patents of R square for the consequences of testosterone and the enzymes aspartate dehydrogenase
(AST) and alanine transaminase (ALT) on Polycystic Ovary Syndrome (PCOS) treated patients
have been developed.

Method:
We study in this paper the detailed comparative study on the biological system using
RMSE, MAPE, and R Squared, which consists of 29 PCOS-influenced women against 20 healthy
women and followed by the obesity verification model over the Sprague Dawley rats.

Results:
R Square provides the best results among all mathematical regression analytical methods
in PCOS-influenced patients.

Conclusion:
In this study, we provide the strong conclusion that aspartate dehydrogenase (AST)
with testosterone treated on PCOS influenced women to have a greater chance of getting affected
by Non-alcoholic fatty liver disease (NAFLD) rather than alanine transaminase (ALT) with testosterone-
treated patients. Furthermore, this study extends their mathematical regression analysis
through R squared for the obesity verification over rat model. It confirms that letrozole-treated
rats are inhibited in obese compared with control rats, which results in a chance of NAFLD.
Therefore, AST combined with testosterone creates a major chance for liver dysfunction.
Current Advancement and Future Prospects: Biomedical Nanoengineering
Authors: Singh Sonia , Sahani Hrishika 
Published: December 2023

Abstract:
Recent advancements in biomedicine have seen a significant reliance on nanoengineering,
as traditional methods often fall short in harnessing the unique attributes of biomaterials.
Nanoengineering has emerged as a valuable approach to enhance and enrich the performance
and functionalities of biomaterials, driving research and development in the field. This
review emphasizes the most prevalent biomaterials used in biomedicine, including polymers,
nanocomposites, and metallic materials, and explores the pivotal role of nanoengineering in developing
biomedical treatments and processes. Particularly, the review highlights research focused
on gaining an in-depth understanding of material properties and effectively enhancing
material performance through molecular dynamics simulations, all from a nanoengineering
perspective.
Composite and Nanocomposite Thin-film Structures Based on Chitosan Succinamide
Authors: Salikhov Renat , Zilberg Rufina , Mullagaliev Ilnur , Salikhov Timur , Teres Yuliya , Bulysheva Elena , Ostaltsova Anastasia 
Published: December 2023

Aim:
Currently, developing composite and nanocomposite materials based on natural polymers is attracting the growing attention of scientists. In particular, chitosan succinamide, a modified biopolymer, has good biocompatibility, biodegradability, and electrical conductivity, allowing it to be used as a functional material for creating various electronic devices, including sensors for use in medicine and pharmaceuticals. Composite sensors based on chitosan deriva-tives have found application for the recognition and determination of enantiomers of tryptophan, tyrosine, naproxen, and propranolol in human urine and blood plasma in tablet forms of drugs without a preliminary active substance.

Methods:
This article discusses the studies on composite and nanocomposite thin-film structures based on chitosan succinamide obtained using various fillers, such as graphene oxide, single-walled carbon nanotubes, and carbon adsorbents.

Result:
The studies used cyclic voltammetry, electrochemical impedance spectroscopy, and atom-ic force microscopy. The results created field-effect transistors based on the films in question as the transport layer.

Conclusion:
The mobility of charge carriers was estimated, and the following values were ob-tained: μ(SCTS) = 0.173cm2/V·s; μ(SCTS-GO) = 0.509 cm2/V·s; μ(SCTS-CP) = 0.269 cm2/V·s; μ(SCTS-CB) = 0.351cm2/V·s; μ(SCTS-SWCNT) = 0.713 cm2/V·s.
Analysis of Anti-Cancer Effects in Grapefruit-based Drug Development:
A Narrative Review
Authors: Gupta Jeetendra Kumar , Singh Kuldeep , Kumar Shivendra , Khandelwal Girdhar 
Published: December 2023

Abstract:
Cancer remains a significant global health concern, and natural compounds found in
fruits and vegetables have shown potential anti-cancer effects. Grapefruit (Citrus paradisi) has
gained attention due to its rich phytochemical composition and biological activities, including
anti-cancer properties. This narrative review analyzes the literature on grapefruit-based drug
development and its potential as an adjunctive or alternative therapeutic strategy for cancer
treatment. Grapefruit-derived compounds have been extensively studied for their anti-cancer
effects, with preclinical studies showing promising outcomes in inhibiting cancer cell growth
and proliferation. Compounds made from grapefruit also have anti-cancer effects. They do this
in a number of ways, such as by affecting the cell cycle, apoptosis, angiogenesis, metastasis,
and key signalling pathways. Petrified grapefruit compounds have potential synergistic effects
with conventional chemotherapy drugs, enhancing cytotoxic effects while reducing adverse
side effects. They have shown promising results in overcoming drug resistance, a major obstacle in cancer treatment. However, challenges such as bioavailability, drug interactions, and
variability in compound composition remain. Overall, grapefruit-derived compounds possess
significant anti-cancer properties and warrant further investigation for clinical application.
Development of Aged Skin Equivalent Model
Authors: Brand Luiza Meurer , Lamers Marcelo Lazzaron , Franzen Matte Bibiana 
Published: December 2023

Background:
Skin aging is a result of the aging process and also intrinsic and extrinsic
factors. In order to better understand this process and evaluate anti-aging products, it is necessary
to develop in vitro models that can recapitulate the biological process of aged skin. Therefore, the
aim of this study was to develop an aged skin equivalent model to evaluate these properties.

Methods:
Human fibroblasts were incorporated into the collagen matrix and keratinocytes were
added and cultured in an air-liquid interface for 21 days. During this period, the matrices were
exposed to UV or EX527 to trigger biological aging processes.

Results:
The two protocols evaluated demonstrated reduced expression of genes related to longevity and regulation of cellular redox homeostasis, and it was confirmed with histological analysis. Also, the model demonstrated the anti-aging potential of resveratrol.

Conclusion:
The model developed is a promising platform for reproducing aged skin and evaluating rejuvenating agents.
Exploring Effective Therapeutic Approaches for COVID-19: A Review on
Progress and Prospects
Authors: Okeowo Oritoke M. , Olung Nzube F. , Ijomone Omamuyovwi M. , Adeagbo Ayotunde S. 
Published: December 2023

:
Global health and economy have been severely impacted by the COVID-19 pandemic that
was brought on by the SARS-CoV-2 coronavirus. This makes the creation of potent medications for
the treatment of COVID-19 disease a top goal. In clinical trials, several medications that have been
repurposed for the treatment of COVID-19 have shown promise. Nevertheless, there are a lot of obstacles to overcome in the creation of COVID-19 pharmacological therapy. The inability to pinpoint
prospective treatment targets is one difficulty caused by the unclear etiology of COVID-19. Another
difficulty is the virus' quick evolution, which can result in the creation of drug-resistant variants.
Furthermore, the quick start of clinical trials has been prompted by the strong demand for effective
therapies. A lack of reliable data on the safety and efficacy of medications can result from the early
start of clinical trials that have been prompted by the strong demand for effective medicines. Despite
these obstacles, the development of various promising pharmacological treatments for COVID-19
has advanced. These include immune-modulating medications, like dexamethasone and tocilizumab,
as well as antiviral medicines, like remdesivir and favipiravir. Combination therapies using several
medications may also be useful in enhancing outcomes for COVID-19 patients. Despite some encouraging advancements, there are still a lot of obstacles to be addressed in the development of
pharmacological therapy for COVID-19. Further research is needed to identify the most effective
treatment approaches for this disease.
Maternal and Neonatal Outcomes after Vaccination with SARS-CoV-2: A
Systematic Review and Meta-analysis of Cohort Studies
Authors: Basutkar Roopa Satyanarayan , Murugan Sugash , Priyan Shanmuga , Sagadevan Shonitha , Sri Hari Oorvashree , Palur Ramakrishnan Anand Vijayakumar 
Published: December 2023

:
SARS-CoV-2 infection among pregnant women causes maternal and neonatal complications. Professional societies endorse the vaccination among pregnant women. This review of the
cohort studies aims to assess the short-term maternal and neonatal outcomes among vaccinated vs.
non-vaccinated pregnant women with SARS-CoV-2 vaccination. We searched Cochrane Central
Registry of Controlled Trials, Scopus, Google Scholar, and PubMed databases. The observational
cohort studies published from July 2021 to December 2022 were included. The eligibility criteria
were assessed. The studies documenting maternal and neonatal outcomes and the relative risk, and
95% confidence interval were considered. Joanna Briggs Institute data extraction form was used,
and the quality assessment of the included study was conducted using the Newcastle-Ottawa quality assessment scale. The quality of the grading was summarised with GradePro software. Data
from the five cohort studies are considered. 56% of the un-vaccinated pregnant women experience
composite adverse maternal outcomes (RR: 3.97; 95% CI:0.73,21.49; p-value: ˂0.11). There was a
reduced risk of occurrence of the meconium-stained amniotic fluid who are vaccinated (RR: 0.89;
95% CI:0.71, 1.12; p value=0.33). The unvaccinated group is 3.16 times more likely to take infertility treatment (RR: 3.54; 95% CI:2.04, 6.12; p-value: ˂0.00001). There was no significant difference concerning neonatal outcomes between both groups. The pregnant women who were not vaccinated against SARS-CoV had an increased risk for a composite adverse maternal outcome and
meconium-stained amniotic fluid. The vaccine has effectively prevented the disease in the first six
months. Additional studies are needed to understand the safety of the SARS-CoV vaccine.
Associations Between Patient-Reported Outcome Measures of Physical and Psychological Functioning and Willingness to Share Social Media Data for Research Among Adolescents With a Chronic Rheumatic Disease: Cross-Sectional Survey
Authors: Weitzman Elissa R , Minegishi Machiko , Cox Rachele , Wisk Lauren E 
Published: December 2023

Abstract

Background
Social media data may augment understanding of the disease and treatment experiences and quality of life of youth with chronic medical conditions. Little is known about the willingness to share social media data for health research among youth with chronic medical conditions and the differences in health status between sharing and nonsharing youth with chronic medical conditions.

Objective
We aimed to evaluate the associations between patient-reported measures of disease symptoms and functioning and the willingness to share social media data.

Methods
Between February 2018 and August 2019, during routine clinic visits, survey data about social media use and the willingness to share social media data (dependent variable) were collected from adolescents in a national rheumatic disease registry. Survey data were analyzed with patient-reported measures of disease symptoms and functioning and a clinical measure of disease activity, which were collected through a parent study. We used descriptive statistics and multivariate logistic regression to compare patient-reported outcomes between youth with chronic medical conditions who opted to share social media data and those who did not opt to share such data.

Results
Among 112 youths, (age: mean 16.1, SD 1.6 y; female: n=72, 64.3%), 83 (74.1%) agreed to share social media data. Female participants were more likely to share (P=.04). In all, 49 (43.8%) and 28 (25%) participants viewed and posted about rheumatic disease, respectively. Compared to nonsharers, sharers reported lower mobility (T-score: mean 49.0, SD 9.4 vs mean 53.9, SD 8.9; P=.02) and more pain interference (T-score: mean 45.7, SD 8.8 vs mean 40.4, SD 8.0; P=.005), fatigue (T-score: mean 49.1, SD 11.0 vs mean 39.7, SD 9.7; P<.001), depression (T-score: mean 48.1, SD 8.9 vs mean 42.2, SD 8.4; P=.003), and anxiety (T-score: mean 45.2, SD 9.3 vs mean 38.5, SD 7.0; P<.001). In regression analyses adjusted for age, sex, study site, and Physician Global Assessment score, each 1-unit increase in symptoms was associated with greater odds of willingness to share social media data, for measures of pain interference (Adjusted Odds Ratio [AOR] 1.07, 95% CI 1.001-1.14), fatigue (AOR 1.08, 95% CI 1.03-1.13), depression (AOR 1.07, 95% CI 1.01-1.13), and anxiety (AOR 1.10, 95% CI 1.03-1.18).

Conclusions
High percentages of youth with rheumatic diseases used and were willing to share their social media data for research. Sharers reported worse symptoms and functioning compared to those of nonsharers. Social media may offer a potent information source and engagement pathway for youth with rheumatic diseases, but differences between sharing and nonsharing youth merit consideration when designing studies and evaluating social media–derived findings.
Machine Learning–Based Asthma Attack Prediction Models From Routinely Collected Electronic Health Records: Systematic Scoping Review
Authors: Budiarto Arif , Tsang Kevin C H , Wilson Andrew M , Sheikh Aziz , Shah Syed Ahmar 
Published: December 2023

Background
An early warning tool to predict attacks could enhance asthma management and reduce the likelihood of serious consequences. Electronic health records (EHRs) providing access to historical data about patients with asthma coupled with machine learning (ML) provide an opportunity to develop such a tool. Several studies have developed ML-based tools to predict asthma attacks.

Objective
This study aims to critically evaluate ML-based models derived using EHRs for the prediction of asthma attacks.

Methods
We systematically searched PubMed and Scopus (the search period was between January 1, 2012, and January 31, 2023) for papers meeting the following inclusion criteria: (1) used EHR data as the main data source, (2) used asthma attack as the outcome, and (3) compared ML-based prediction models’ performance. We excluded non-English papers and nonresearch papers, such as commentary and systematic review papers. In addition, we also excluded papers that did not provide any details about the respective ML approach and its result, including protocol papers. The selected studies were then summarized across multiple dimensions including data preprocessing methods, ML algorithms, model validation, model explainability, and model implementation.

Results
Overall, 17 papers were included at the end of the selection process. There was considerable heterogeneity in how asthma attacks were defined. Of the 17 studies, 8 (47%) studies used routinely collected data both from primary care and secondary care practices together. Extreme imbalanced data was a notable issue in most studies (13/17, 76%), but only 38% (5/13) of them explicitly dealt with it in their data preprocessing pipeline. The gradient boosting–based method was the best ML method in 59% (10/17) of the studies. Of the 17 studies, 14 (82%) studies used a model explanation method to identify the most important predictors. None of the studies followed the standard reporting guidelines, and none were prospectively validated.

Conclusions
Our review indicates that this research field is still underdeveloped, given the limited body of evidence, heterogeneity of methods, lack of external validation, and suboptimally reported models. We highlighted several technical challenges (class imbalance, external validation, model explanation, and adherence to reporting guidelines to aid reproducibility) that need to be addressed to make progress toward clinical adoption.
Efektivitas Metode Ekstraksi DNA pada Daun Segar dan Kering dari Tanaman Obat
Authors: Sembiring Enny Rimita , Terryana Rerenstradika Tizar , Anggraheni Yuliana Galih Dyan , Prihaningsih Amalia , Batubara Irmanida , Nurcholis Waras , Ridwan Taopik , Harmoko Rikno 
Published: December 2023

Tanaman obat merupakan salah satu tanaman yang sering menjadi target studi molekuler. Pada studi molekuler, ekstraksi dan purifikasi DNA genom merupakan tahap awal yang akan menentukan analisis selanjutnya. Oleh sebab itu, dibutuhkan metode ekstraksi DNA yang mampu menghasilkan DNA dengan kuantitas dan kualitas yang baik. Tujuan penelitian ini adalah untuk mengetahui efektivitas metode ekstraksi DNA dari daun segar maupun daun yang dikeringkan dari tanaman obat. Sebanyak sembilan genotip tanaman obat yang digunakan pada penelitian ini yaitu tiga genotip Justicia gendarussa, dua genotip Orthosiphon aristatus, dan masing-masing satu genotip Adenostemma lavenia, Adenostemma platyphyllum, Adenostemma madurense, dan Curcuma xanthorrhiza. Metode ekstraksi DNA genom yang digunakan adalah metode CTAB dengan beberapa modifikasi. Hasil penelitian DNA genom dari daun segar dan kering menunjukkan kuantitas, kualitas, dan dapat teramplifikasi dengan baik menggunakan primer RAPD dan penanda DNA.
Dampak Interferensi Gulma terhadap Kualitas dan Hasil Bawang Merah (<i>Allium cepa</i> L. Aggregatum Group)
Authors: Handayani Valentina Dwi Suci , Sulistyaningsih Endang 
Published: December 2023

Produktivitas bawang merah nasional masih di bawah potensi hasil yang diharapkan. Tidak optimalnya produktivitas bawang merah disebabkan interferensi gulma. Interferensi gulma dapat menjadi penyebab kehilangan hasil pada proses budidaya karena adanya kompetisi dan dampak dari alelopati. Penelitian ini bertujuan untuk melihat dampak interferensi gulma terhadap kualitas dan hasil bawang bawang merah. Penelitian menggunakan Rancangan Acak Kelompok Lengkap (RAKL) dengan tiga blok sebagai ulangan. Perlakuan yang diujikan adalah pengendalian gulma dan tanpa pengendalian. Hasil penelitian menunjukkan pengendalian gulma pada lahan pertanian menyebabkan perubahan kelimpahan dan keragaman komunitas gulma. Pengendalian gulma pada saat 3 dan 6 minggu setelah tanam (mst) menyebabkan perbedaan kelimpahan gulma dan perubahan dominasi gulma yaitu dari rumputan menjadi daun lebar yang terjadi pada pengamatan 6 mst dan 9 mst. Kelimpahan dan dominansi gulma berdampak pada penurunan diameter umbi, bobot segar umbi dan bobot umbi bawang merah kering jemur (susut bobot). Pengendalian gulma pada lahan pertanian dapat mencegah kehilangan hasil bawang merah dengan rerata 3 ton/ha dibandingkan lahan tanpa pengendalian.
PENGARUH AKUNTANBILITAS, PROFESIONALISME DAN PENGALAMAN TERHADAP KUALITAS PADA KANTOR AKUNTAN PUBLIK DI DENPASAR
Authors: Triwulani Ni Komang Ayu , Wianto Putra I Made , Sanjaya I Ketut Puja Wirya 
Published: December 2023

Penelitian ini bertujuan dalam penelitian ini untuk mengetahui pengaruh akuntabilitas, profesionalisme dan pengalaman kerja terhadap kualitas auditor. Populasi dalam penelitian adalahauditor di Kantor Akuntan Publik di Denpasar dengan sampel yang digunakan yaitu sebanyak 95orang responden. Teknik analisis data yang digunakan dalam penelitian ini adalah Regresi Linier Berganda, Koefisien F, Uji Determinasi dan Uji t.Berdasarkan hasil penelitian dapat dilihat bahwa: (1) akuntabilitas berpengaruh positif dan signfikan terhadap kualitas auditor, dimana diperoleh koefisien regresi 0,330 dan sig 0,002. (2) profesionalisme berpengaruh positif signifikan terhadap kualitas auditor, dimana diperoleh koefisien regresi sebesar 0,342 dan sig 0,004. (3) pengalaman kerja berpengaruh positif signifikan terhadap kualitas auditor, dimana diperoleh koefesien regresi 0,252 dan sig 0,021. Besarnya pengaruh variabel bebas terhadap akuntabilitas adalah 58,5%. Saran yang dapat diberikan oleh peneliti adalah Kantor Akuntan Publik di Denpasar dalam meningkatkan kualitas auditor dapat dilakukan dengan meningkatkan akuntabilitas, profesionalisme dan pengalaman kerja.
PENGARUH SANKSI, PELAYANAN FISKUS, SOSIALISASI, DAN KESADARAN PAJAK TERHADAP KEPATUHAN WPOP
Authors: Sriary Bhegawati Desak Ayu , Yuesti Anik , Sari I Gusti Ayu Agung Janur Ratna 
Published: December 2023

Kepatuhan Wajib Pajak adalah suatu bentuk kepatuhan terhadap undang-undang dan/atau kepatuhan terhadap undang-undang dan/atau peraturan perpajakan yang berlaku, tetapi diwajibkan untuk memenuhi kewajiban perpajakan. Dalam sistem self assessment, wajib pajak memiliki kebebasan untuk menghitung, mempertimbangkan dan melaporkan sendiri kewajiban perpajakannya. Sanksi, celah hukum, informasi dan kesadaran perpajakan merupakan faktor-faktor yang mempengaruhi pemenuhan kewajiban wajib pajak. Tujuan dari penelitian ini adalah untuk mengetahui pengaruh sanksi, pelayanan tilang, perpajakan dan sosialisasi terhadap kepatuhan wajib pajak orang pribadi di KPP Pratama Denpasar Timur. Metode penentuan pola yang digunakan dalam pengujian ini adalah sampel acak yang terdiri dari total seratus sampel yang sebagian besar diperoleh dari komponen Slovin. Teknik analisis data yang digunakan dalam penelitian ini lebih menyerupai analisis regresi linier yang didahului dengan uji hipotesis klasik. Berdasarkan hasil evaluasi disimpulkan bahwa sanksi , layanan fiscus, dan kesadaran perpajakan berpengaruh signifikan terhadap kepatuhan wajib pajak orang pribadi, sedangkan sosialisasi perpajakan tidak berpengaruh signifikan terhadap kepatuhan wajib pajak orang pribadi.