bluuebunny/crossref_metadata_2025 huggingface dataset:
An Investigation on the Opinions of Class and Guidance Teachers About the Challenges in Mainstream Education
Authors: BARAN KARALAR Elvan , BOGENÇ Atlas , KARGIN Tevhide
Published: September 2023

Introduction: One of the most important factors in mainstreaming practices is the teacher. The role of the created class and psychological guidance, such as ensuring social cohesion between students with special educational needs and their peers, and the active inclusion of families throughout their life, cannot be denied. It is expected that the opinions and expectations regarding the inclusion difficulties and experiences of the classroom and guidance teachers working in primary schools in the province of Istanbul are reached.
Method: In the study in which the case study model, which is one of the qualitative research methods, was used; semi-structured interviews were conducted with seven classroom teachers who have inclusion students in their classroom and six psychological counselor/guidance teachers who have inclusion students in their school. By applying content analysis to the data obtained from the interviews, the main themes and sub-themes were formed and the findings were reached.
Findings: Research findings show that classroom teachers prepare the individualized education program (IEP) with the help of the guidance teacher. The school administration does not have enough information about the inclusion practice because the classrooms are crowded. Thus the teachers have difficulty in gaining academic skills, as well as finding and adapting appropriate materials for mainstreaming students. Counselors, on the other hand, state that the IEP development unit remains on paper, that all responsibilities related to IEP are assigned to them, and that the school administration does not cooperate on inclusion. In addition, both classroom teachers and guidance teachers stated that the communication and cooperation they established with the institutions where the student received support education was one-sided and they did not receive any feedback regarding the student. The fact that families do not accept their children's inadequacy, and do not have enough information about inclusion, is another finding that makes cooperation difficult for classroom and guidance teachers.
Discussion: The findings obtained from the research revealed the necessity of the classroom and guidance teachers to be in cooperation with the school, family and stakeholders who provide support education to the students in the inclusive practice. This cooperation will enable the student's educational process to improve their learning better. It is recommended to conduct experimental studies based on school-family cooperation in similar studies.
Prediction of scour hole characteristics caused by water jets using metaheuristic artificial bee colony-optimized neural network and pre-processing techniques
Authors: Kartal Veysi , Emiroglu Muhammet Emin , Katipoglu Okan Mert , Karakoyun Erkan
Published: September 2023

Preventing plunge pool scouring in hydraulic structures is crucial in hydraulic engineering. Although many studies have been conducted experimentally to determine relationship between the scour depth and water jets in several fields, available equations have deficiencies in calculating the exact scour due to complexity of scour process. This study investigated local scour depth in plunge pool using Metaheuristic Artificial Bee Colony-Optimized Feed Forward Neural Network (ABCFFNN), variational mode decomposition (VMD) and ensemble empirical mode decomposition (EEMD) techniques. To set modeling, the input parameters are impact angle, densimetric Froude number, impingement length, and nozzle diameter. The models' training and testing were conducted using data available in the literature. The models' performances were compared with experiments. The results demonstrate that scour depth, length, width, and ridge height can be calculated more accurately than available equations. A rank analysis was also applied to obtain the most critical parameter in predicting scour parameters in water jet scouring. ABC-FFNN, VMD-ABCFFNN and EEMD-VMD-FFNN hybrid models were performed to obtain scour parameters. As a result, ABC-FFNN algorithms produced the best solution to predict the scour due to circular water jets, with the values for training (R2: 0.331 to 0.778) and testing (R2: 0.495 to 0.863).
Big Data and Artificial Intelligence in Drug Discovery for Gastric Cancer: Current Applications and Future Perspectives
Authors: Nguyen Mai Hanh , Tran Ngoc Dung , Le Nguyen Quoc Khanh
Published: September 2023

Gastric cancer (GC) represents a significant global health burden, ranking as the fifth most common malignancy and the fourth leading cause of cancer-related death worldwide. Despite recent advancements in GC treatment, the five-year survival rate for advanced-stage GC patients remains low. Consequently, there is an urgent need to identify novel drug targets and develop effective therapies. However, traditional drug discovery approaches are associated with high costs, time-consuming processes, and a high failure rate, posing challenges in meeting this critical need. In recent years, there has been a rapid increase in the utilization of artificial intelligence (AI) algorithms and big data in drug discovery, particularly in cancer research. AI has the potential to improve the drug discovery process by analyzing vast and complex datasets from multiple sources, enabling the prediction of compound efficacy and toxicity, as well as the optimization of drug candidates. This review provides an overview of the latest AI algorithms and big data employed in drug discovery for GC. Additionally, we examine the various applications of AI in this field, with a specific focus on therapeutic discovery. Moreover, we discuss the challenges, limitations, and prospects of emerging AI methods, which hold significant promise for advancing GC research in the future.
Role of LncRNA MIAT in Diabetic Complications
Authors: Wang Lijun , Wang Hailin , Luo Yiyang , Wu Wei , Gui Yibei , Zhao Jiale , Xiong Ruisi , Li Xueqin , Yuan Ding , Yuan Chengfu
Published: September 2023

Long non-coding RNA (LncRNA) refers to a large class of RNAs with over
200 nucleotides that do not have the function of encoding proteins. In recent years, more
and more literature has revealed that lncRNA is involved in manipulating genes related
to human health and disease, playing outstanding biological functions, which has attracted
widespread attention from researchers. The newly discovered long-stranded non-coding
RNA myocardial infarction-related transcript (LncRNA MIAT) is abnormally expressed
in a variety of diseases, especially in diabetic complications, and has been
proven to have a wide range of effects. This review article aimed to summarize the importance
of LncRNA MIAT in diabetic complications, such as diabetic cardiomyopathy, diabetic
nephropathy, and diabetic retinopathy, and highlight the latest findings on the pathway
and mechanism of its participation in regulating diabetic complications, which may
aid in finding new intervention targets for the treatment of diabetic complications. LncRNA
MIAT competitively binds microRNAs to regulate gene expression as competitive
endogenous RNAs. Thus, this review article has reviewed the biological function and
pathogenesis of LncRNA MIAT in diabetic complications and described its role in diabetic
complications. This paper will help in finding new therapeutic targets and intervention
strategies for diabetes complications.
Medicinal Aspects of PTP1B Inhibitors as Anti-Breast Cancer Agents: An Overview
Authors: Khator Rakesh , Biharee Avadh , Bhatia Neha , Kulkarni Swanand , Singh Yogesh , Karthikeyan Chandrabose , Jain Akhlesh Kumar , Thareja Suresh
Published: September 2023

:

Protein tyrosine phosphatase 1B (PTP1B) has gained interest as a therapeutic target for type 2 diabetes and obesity. Besides metabolic signalling, PTP1B is a positive regulator of signalling pathways linked to ErbB2-induced breast tumorigenesis. Substan-tial evidence proves that its overexpression is involved in breast cancer, which suggests that selective PTP1B inhibition might be effective in breast cancer treatment. Therefore, huge research is being carried out on PTP1B inhibitors and their activity against breast cancer development. To date, only two PTP1B inhibitors, viz. ertiprotafib and tro-dusquemine, have entered clinical trials. The discovery of selective inhibitors of PTP1B could open a new avenue in breast cancer treatment. In this review, we provide an exten-sive overview on the involvement of PTP1B in breast cancer, its pathophysiology, with special attention on the discovery and development of various natural as well as synthetic PTP1B inhibitors. This study will provide significant information to the researchers de-veloping PTP1B inhibitors for breast cancer treatment.
Mitochondrial Lipid Metabolism Genes as Diagnostic and Prognostic
Indicators in Hepatocellular Carcinoma
Authors: Li Xuejing , Tan Ying , Liu Bihan , Guo Houtian , Zhou Yongjian , Yuan Jianhui , Wang Feng
Published: September 2023

Background:

Due to the heterogeneity of Hepatocellular carcinoma (HCC), there is an urgent
need for reliable diagnosis and prognosis. Mitochondria-mediated abnormal lipid metabolism affects
the occurrence and progression of HCC.

Objective:

This study aims to investigate the potential of mitochondrial lipid metabolism (MTLM)
genes as diagnostic and independent prognostic biomarkers for HCC.

Methods:

MTLM genes were screened from the Gene Expression Omnibus (GEO) and Gene Set Enrichment
Analysis (GSEA) databases, followed by an evaluation of their diagnostic values in both The
Cancer Genome Atlas Program (TCGA) and the Affiliated Cancer Hospital of Guangxi Medical University
(GXMU) cohort. The TCGA dataset was utilized to construct a gene signature and investigate
the prognostic significance, immune infiltration, and copy number alterations. The validity of the
prognostic signature was confirmed through GEO, International Cancer Genome Consortium (ICGC),
and GXMU cohorts.

Results:

The diagnostic receiver operating characteristic (ROC) curve revealed that eight MTLM
genes have excellent diagnostic of HCC. A prognostic signature comprising 5 MTLM genes with robust
predictive value was constructed using the lasso regression algorithm based on TCGA data. The
results of the Stepwise regression model showed that the combination of signature and routine clinical
parameters had a higher area under the curve (AUC) compared to a single risk score. Further, a nomogram
was constructed to predict the survival probability of HCC, and the calibration curves demonstrated
a perfect predictive ability. Finally, the risk score also unveiled the different immune and mutation
statuses between the two different risk groups.

Conclusion:

MTLT-related genes may serve as diagnostic and prognostic biomarkers for HCC as well
as novel therapeutic targets, which may be beneficial for facilitating further understanding the molecular
pathogenesis and providing potential therapeutic strategies for HCC.
Early Detection of Dementia using Risk Classification in MCI: Outcomes
of Shanghai Mild Cognitive Impairment Cohort Study
Authors: Zhou Bin , Zhao Qianhua , Kojima Shinsuke , Ding Ding , Higashide Satoshi , Fukushima Masanori , Hong Zhen
Published: September 2023

Introduction:

The purpose of this study is to identify the risk factors and risk classification
associated with the conversion from mild cognitive impairment (MCI) to Alzheimer’s disease
(AD) dementia to facilitate early intervention and the design of clinical trials for AD.

Methods:

The study comprised a prospective cohort study of 400 subjects with MCI who had annual
follow-ups for 3 years.

Results:

During an average follow-up period of 3.5 years, 109 subjects were diagnosed with all
cause of dementia, of whom 104 subjects converted to Alzheimer’s dementia and 5 subjects converted
to other types of dementia. The cumulative conversion rate was 5.5% (95% CI: 3.4, 8.6),
16.3% (95% CI: 12.9, 21.1), and 31.0% (95% CI: 25.4, 36.5) in each of the first 3 follow-up years,
respectively. The factors associated with a greater risk of conversion from MCI to AD included
smoking status, ApoE4 carrier status, right hippocampal volume (rt. HV), left temporal lobe volume,
and scores on the Revised Chinese version of the Alzheimer’s Disease Assessment Scale-Cognitive
Subscale 13 (ADAS-Cog-C). The risk classification of the ADAS-Cog-C or Preclinical
Alzheimer Cognitive Composite (PACC) score combined with the rt. HV showed a conversion difference
among the groups at every annual follow-up.

Conclusion:

A simple risk classification using the rt. HV and neuropsychological test scores, including
those from the ADAS-Cog-C and PACC, could be a practicable and efficient approach to
indentify individuals at risk of all-cause dementia.
Traditional uses, Phytochemistry, Pharmacology, and Toxicology of the GenusArtemisia L. (Asteraceae): A High-value Medicinal Plant
Authors: Hussain Manzoor , Thakur Rakesh Kr , Khazir Jabeena , Ahmed Sajad , Khan Mohammad Imtiyaj , Rahi Praveen , Peer Latif Ahmad , Vppalayam Shanmugam Pragadheesh , Kaur Satwinderjeet , Raina Soom Nath , Reshi Zafar Ahmad , Sehgal Deepmala , Rajpal Vijay Rani , Mir Bilal Ahmad
Published: September 2023

Biologically active secondary metabolites, essential oils, and volatile compounds derived from medicinal and aromatic plants play a crucial role in promoting human health. Within the large family Asteraceae, the genus Artemisia consists of approximately 500 species. Artemisia species have a rich history in traditional medicine worldwide, offering remedies for a wide range of ailments, such as malaria, jaundice, toothache, gastrointestinal problems, wounds, inflammatory diseases, diarrhoea, menstrual pains, skin disorders, headache, and intestinal parasites. The therapeutic potential of Artemisia species is derived from a multitude of phytoconstituents, including terpenoids, phenols, flavonoids, coumarins, sesquiterpene lactones, lignans, and alkaloids that serve as active pharmaceutical ingredients (API). The remarkable antimalarial, antimicrobial, anthelmintic, antidiabetic, anti-inflammatory, anticancer, antispasmodic, antioxidative and insecticidal properties possessed by the species are attributed to these APIs. Interestingly, several commercially utilized pharmaceutical drugs, including arglabin, artemisinin, artemether, artesunate, santonin, and tarralin have also been derived from different Artemisia species. However, despite the vast medicinal potential, only a limited number of Artemisia species have been exploited commercially. Further, the available literature on traditional and pharmacological uses of Artemisia lacks comprehensive reviews. Therefore, there is an urgent need to bridge the existing knowledge gaps and provide a scientific foundation for future Artemisia research endeavours. It is in this context, the present review aims to provide a comprehensive account of the traditional uses, phytochemistry, documented biological properties and toxicity of all the species of Artemisia and offers useful insights for practitioners and researchers into underutilized species and their potential applications. This review aims to stimulate further exploration, experimentation and collaboration to fully realize the therapeutic potential of Artemisia in augmenting human health and well-being.
Antimicrobial Activity of Formulated Origanum and Thyme Essential Oil
Nanoemulsions - A Comparative Study
Authors: Al-Asmari Fahad , Koirala Pankaj , Rathod Nikheel Bhojraj , Alnemr Tareq Morad , Asiri Saeed Amer , Babeker Mohamed Yousif , Li Li , Nirmal Nilesh Prakash
Published: September 2023

Introduction:

This study focused on the formulation processing and antimicrobial activities
of Origanum and Thyme essential oils (OEO) (TEO) and their nanoemulsions (OEON)
(TEON) on gram-positive and gram-negative bacteria and yeast. Optimal nanoemulsion formulation
and stability were achieved through balancing between requisite hydrophilic-lipophilic balance
(rHLB) and surfactant concentration (Smix) of nanoemulsions.

Methods:

The smallest droplet sizes of OEON: (z -185.1 nm ± 0.85) and TEON (z -130.1 nm ±
0.60), were achieved by using 10 g/100 mL of OEO and TEO with 15 g/100 mL Smix at ultrasonication
for 2 min with no phase separation. The size of nanoemulsion droplet and PDI was found to
be influenced by HLB value, treatment time, and Smix concentration. Antimicrobial analyses, including
a zone of inhibition, minimum inhibitory concentration (MIC), minimum bactericidal concentration
(MBC), and time-kill kinetics assay, were performed against Escherichia coli, Staphylococcus
aureus, and Saccharomyces cerevisiae.

Results:

The antimicrobial findings demonstrated that OEO exhibited higher antimicrobial activity
compared to TEO (P<0.05). Meanwhile, the OEON and TEON substantially reduced the MIC and
MBC values, compared to OEO and TEO against all tested microorganisms (P<0.05). Throughout
the time-kill assay, E. coli was reduced by 5 log CFU/ml within 120 minutes, while S. cerevisiae
and S. aureus were eradicated after 60 and 120 minutes of incubation with OEON, respectively.

Conclusion:

In turn, TEON reduced E. coli by 5 log CFU/ml and S. cerevisiae by 4 log CFU/ml
within 120 minutes, while S. aureus was inhibited within the same time of incubation with TEON.
The nanoemulsion formulations of OEO and TEO considerably enhanced the antimicrobial properties,
which provides a promising alternative plant-derived antimicrobial for pharmaceuticals and
food applications.
Arctigenin Suppresses the Proliferation and Metastasis, and Induces Apoptosis and
Cycle Arrest of Osteosarcoma Cells by inhibiting HMOX1 Expression
Authors: Xu Guosong , He Zhensen , Liu Yinping
Published: September 2023

Background:

Osteosarcoma is the most common malignant bone tumor, with highly proliferative and metastatic
properties. Previous studies have reported that arctigenin (Arc), a bioactive lignin compound, showed excellent
anti-tumor activities in a variety of human cancers. However, its role in osteosarcoma has not been studied.

Objective:

We aimed to investigate the anti-tumor effects of Arc on osteosarcoma cell proliferation, migration, invasion,
apoptosis, and cell cycle.

Methods:

Effects of Arc on osteosarcoma cell proliferation were detected by MTT and colony formation assay. Flow
cytometry analysis was performed to assess the cell apoptosis and cycle arrest. Transwell assay was used to evaluate
the capability of migration and invasion. qRT-PCR and Western blot were employed to determine the changes in
mRNA and protein levels.

Results:

Arc could significantly suppress the proliferation, colony formation, and induce cell apoptosis and S phase
cycle arrest of MG63 and U-2 OS cells in a dose-dependent manner. In addition, we also observed an inhibitory effect
of Arc treatment on osteosarcoma cell invasion, migration, and epithelial-mesenchymal transition (EMT). HMOX1,
encoding enzyme heme oxygenase-1, was predicted to be a candidate target of Arc using STITCH. Arc treatment significantly
reduced the mRNA and protein levels of HMOX1. Furthermore, overexpression of HMOX1 could partly
reverse the inhibitory effects of Arc on osteosarcoma cell malignant phenotypes.

Conclusion:

Our results suggest that Arc inhibits the proliferation, metastasis and promotes cell apoptosis and cycle
arrest of osteosarcoma cells by downregulating HMOX1 expression.
Effects of Sublingual Colostrum Application on Oral and Intestinal Flora
of Extremely Low Birth Weight Infants
Authors: Wang Hua , Li Qiu-Fang , Xu Xin-Fen , Hu Xiao-Li
Published: September 2023

Background:

The aim of this study is to analyze the effects of colostrum application on
the establishment of normal flora in the intestinal tracts and oral cavities of extremely low birth
weight infants (ELBWI).

Methods:

A prospective cohort study design was adopted following the STROBE guidelines (Supplementary
File 1). Colostrum was administered immediately after obtaining maternal breast milk
using a special sterile cotton swab. There were no specific treatments for infants who did not receive
colostrum. This experiment was completed on day 5 post-birth and the patients were divided
into the colostrum and control groups, corresponding to whether or not colostrum was administered.
Throat swabs and stool samples were collected on days 1 and 5 post-birth.

Results:

Using the conventional bacteria cultivation technique, the detection rate of bacteria in 98
cases of meconium at birth was 15.31%. On day 5, the detection rates of Staphylococcus in the colostrum
and control groups were 36.54% and 34.78%, with no significant difference between them
(P = 0.856), and that of Enterococcus was 26.92% and 13.04%, respectively, with no statistically
significant difference (P = 0.089). Likewise, at birth, the detection rate of bacteria in 98 cases of
throat swabs was 27.55%. On day 5, the detection rate of Streptococcus in the colostrum and control
groups was 78.85% and 50.00%, respectively, recording a statistically significant difference
this time (P = 0.003).

Conclusion:

Colostrum application had limited effects on intestinal flora colonization but contributes
to physiological oral flora colonization.
Electromotive Force of Spontaneously Polarized Semiconductors
Authors: Kharlamov Vladimir F.
Published: September 2023

Background:

Spontaneously polarized finely dispersed semiconductors can be sources of direct electric current, similar to thermoelectric converters. Their power is low due to the low electrical conductivity of the powders.

Objective:

Theoretical description of the electromotive force of a spontaneously polarized homogeneous semiconductor film with ionized donor centers uniformly distributed over its two surfaces and free electrons in the volume. Establishment of technical characteristics and competitive advantages of using a film as a current source converts the received energy (heat or light) into the work of an electric field.

Methods:

The theory of semiconductors and the laws of thermodynamics are used.

Results:

Analytical expressions are obtained that describe the electronic processes in a metal-semiconductor-metal three-layer film and the technical characteristics of its use as a current source. Estimates are given on the example of a silicon film with arsenic-doped surfaces.

Conclusion:

The universal principles for creating homogeneous solids of macroscopic dimensions are substantiated, with the efficiency of converting heat into the work of an electric field, which is significantly (by an order of magnitude) higher than the efficiency of materials used to create thermo-EMF sources. The heat absorbed by the metal-semiconductor-metal three-layer film serves as an energy source for a direct current in a closed circuit generated by this structure with an efficiency of 100%. The power of the current source 10 - 105 W/m depends on the received heat flow. A semiconductor film with a built-in electric field is an analogue of a p - n junction and does not have its drawbacks.
Stimulatory and Inhibitory Effect of Antipsychotic Agents Including Dopaminergic Neuro-depressants on Dopamine Formation from p-tyramine Mediated by Cytochrome P450 2D6
Authors: Niwa Toshiro , Yamamoto Yuka
Published: September 2023

Background and Objectives:

The effects of antipsychotic agents, including dopamine D2 receptor blocking agents such as haloperidol, chlorpromazine, and sulpiride, and related compounds such as mirtazapine and sertraline, on dopamine formation from p-tyramine cata-lyzed by cytochrome P450 (CYP) 2D6.2 (Arg296Cys;Ser486Thr), CYP2D6.10 (Pro34Ser;Ser486Thr), and CYP2D6.39 (Ser486Thr) were compared with those of CYP2D6.1.

Methods:

Dopamine was determined by high-performance liquid chromatography, and Michaelis constants (Km), maximal velocity (kcat) values for dopamine formation, and inhibition constants (Ki) of psychotropic agents were estimated.

Results:

Km values for all CYP2D6 variants decreased at lower concentrations, and kcat values for CYP2D6 variants except for CYP2D6.10 gradually increased with increasing haloperidol concentrations up to 5 or 10 μM. The kcat/Km values for all CYP2D6 variants increased at under 2.5 μM concentrations. Lower sertraline concentrations decreased Km values for CYP2D6.10. Chlorpromazine at concentrations under 10 µM competitively inhibited the activities catalyzed by all variants; however, the activities for only CYP2D6.10 were increased by chlorpromazine at concentrations over 250 µM. Mirtazapine and sertraline similarly decreased dopamine formation among all variants except for CYP2D6.10. However, CYP2D6.10 inhibition by mirtazapine was weaker than that of the other variants, and sertraline decreased Km values for CYP2D6.10.

Conclusion:

Haloperidol and sertraline, but not sulpiride, decreased the Km and/or increased kcat values for CYP2D6. The present findings suggest that Dopamine D2 receptor-blocking agents and related compounds may polymorphically affect dopamine formation catalyzed by CYP2D6 in the brain.
How COVID-19 Ceases All Older Adult Services & the Way Out for Community-Dwelling Older Adults with Chronic Pain
Authors: Tse Mimi Mun Yee , Ng Shamay Sheung Mei , Lou Vivian , Lo Raymond SK , Cheung Daphne Sze Ki , Lee Paul H , Tang Shuk Kwan , Leung Siu Hang , Tse Percy Poo-See
Published: September 2023

The COVID-19 pandemic started at the beginning of 2020. It significantly impacted the older adults in Hong Kong, with most of the community centers and elderly centers being closed down under various restrictive measures. Thus, community-based health promotion activities were temporarily paused, which decreased older adults’ health-promoting behaviors and motivation to stay active. This research aimed to improve the quality of life and the health of older adults with chronic pain through the pain management program. This study was conducted face-to-face on the campus of Hong Kong Metropolitan University. This dyadic pain management program (DPM) was an 8-week group-based program. The DPM comprised 4 weeks of campus-based activities and 4 weeks of digital-based activities delivered via a WhatsApp group. An 80% participation rate in the campus-based activities was regarded as completing the DPM. The control group only received lesson leaflets. Pain intensity, pain self-efficacy, psychological health of pain victims, caregiver burden inventory, and a semi-structured interview were evaluated at week 1 (T0), week 8 (T1), and week 12 (T2) after randomization. The IBM-SPSS version 22 was used to perform statistical analyses. Using non-pharmacological methods and regular exercise for 12 weeks improved physical health in terms of pain intensity, pain self-efficacy, and psychological health in anxiety, depression, and stress. For caregivers, their burden decreased after the pain management program. These findings indicated that Pender’s Health Promotion Model is helpful to empower the participants and their caregivers with knowledge, skills, and power to manage their chronic pain situations. Utilizing this model as a framework, Researchers can design more effective non-pharmacological interventions for older adults to increase their engagement in health-promoting activities in the community.
A Culturally Adapted Diet and Physical Activity Text Message Intervention to Prevent Type 2 Diabetes Mellitus for Women of Pakistani Origin Living in Scotland: Formative Study
Authors: Krasuska Marta , Davidson Emma M , Beune Erik , Jenum Anne Karen , Gill Jason MR , Stronks Karien , van Valkengoed Irene GM , Diaz Esperanza , Sheikh Aziz
Published: September 2023

Background

Individuals of South Asian origin are at an increased risk of developing type 2 diabetes mellitus (T2DM) compared with other ethnic minority groups. Therefore, there is a need to develop interventions to address, and reduce, this heightened risk.

Objective

We undertook formative work to develop a culturally adapted diet and physical activity text message intervention to prevent T2DM for women of Pakistani origin living in Scotland.

Methods

We used a stepwise approach that was informed by the Six Steps in Quality Intervention Development framework, which consisted of gathering evidence through literature review and focus groups (step 1), developing a program theory for the intervention (step 2), and finally developing the content of the text messages and an accompanying delivery plan (step 3).

Results

In step 1, we reviewed 12 articles and identified 3 key themes describing factors impacting on diet and physical activity in the context of T2DM prevention: knowledge on ways to prevent T2DM through diet and physical activity; cultural, social, and gender norms; and perceived level of control and sense of inevitability over developing T2DM. The key themes that emerged from the 3 focus groups with a total of 25 women were the need for interventions to provide “friendly encouragement,” “companionship,” and a “focus on the individual” and also for the text messages to “set achievable goals” and include “information on cooking healthy meals.” We combined the findings of the focus groups and literature review to create 13 guiding principles for culturally adapting the text messages. In step 2, we developed a program theory, which specified the main determinants of change that our text messages should aim to enhance: knowledge and skills, sense of control, goal setting and planning behavior, peer support, and norms and beliefs guiding behavior. In step 3, we used both the intervention program theory and guiding principles to develop a set of 73 text messages aimed at supporting a healthy diet and 65 text messages supporting increasing physical activity.

Conclusions

We present a theory-based approach to develop a culturally adapted diet and physical activity text message intervention to prevent T2DM for women of Pakistani origin living in Scotland. This study outlines an approach that may also be applicable to the development of interventions for other ethnic minority populations in diverse settings. There is now a need to build on this formative work and undertake a feasibility trial of a text message–based diet and physical activity intervention to prevent T2DM for women of Pakistani origin living in Scotland.
Machine Learning for Early Prediction of Major Adverse Cardiovascular Events After First Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction: Retrospective Cohort Study
Authors: Zhang Pin , Wu Lei , Zou Ting-Ting , Zou ZiXuan , Tu JiaXin , Gong Ren , Kuang Jie
Published: September 2023

Background

The incidence of major adverse cardiovascular events (MACEs) remains high in patients with acute myocardial infarction (AMI) who undergo percutaneous coronary intervention (PCI), and early prediction models to guide their clinical management are lacking.

Objective

This study aimed to develop machine learning–based early prediction models for MACEs in patients with newly diagnosed AMI who underwent PCI.

Methods

A total of 1531 patients with AMI who underwent PCI from January 2018 to December 2019 were enrolled in this consecutive cohort. The data comprised demographic characteristics, clinical investigations, laboratory tests, and disease-related events. Four machine learning models—artificial neural network (ANN), k-nearest neighbors, support vector machine, and random forest—were developed and compared with the logistic regression model. Our primary outcome was the model performance that predicted the MACEs, which was determined by accuracy, area under the receiver operating characteristic curve, and F1-score.

Results

In total, 1362 patients were successfully followed up. With a median follow-up of 25.9 months, the incidence of MACEs was 18.5% (252/1362). The area under the receiver operating characteristic curve of the ANN, random forest, k-nearest neighbors, support vector machine, and logistic regression models were 80.49%, 72.67%, 79.80%, 77.20%, and 71.77%, respectively. The top 5 predictors in the ANN model were left ventricular ejection fraction, the number of implanted stents, age, diabetes, and the number of vessels with coronary artery disease.

Conclusions

The ANN model showed good MACE prediction after PCI for patients with AMI. The use of machine learning–based prediction models may improve patient management and outcomes in clinical practice.
A Culturally Adapted Diet and Physical Activity Text Message Intervention to Prevent Type 2 Diabetes Mellitus for Women of Pakistani Origin Living in Scotland: Formative Study (Preprint)
Authors: Krasuska Marta , Davidson Emma M , Beune Erik , Jenum Anne Karen , Gill Jason MR , Stronks Karien , van Valkengoed Irene GM , Diaz Esperanza , Sheikh Aziz
Published: September 2023

BACKGROUND

Individuals of South Asian origin are at an increased risk of developing type 2 diabetes mellitus (T2DM) compared with other ethnic minority groups. Therefore, there is a need to develop interventions to address, and reduce, this heightened risk.

OBJECTIVE

We undertook formative work to develop a culturally adapted diet and physical activity text message intervention to prevent T2DM for women of Pakistani origin living in Scotland.

METHODS

We used a stepwise approach that was informed by the Six Steps in Quality Intervention Development framework, which consisted of gathering evidence through literature review and focus groups (step 1), developing a program theory for the intervention (step 2), and finally developing the content of the text messages and an accompanying delivery plan (step 3).

RESULTS

In step 1, we reviewed 12 articles and identified 3 key themes describing factors impacting on diet and physical activity in the context of T2DM prevention: knowledge on ways to prevent T2DM through diet and physical activity; cultural, social, and gender norms; and perceived level of control and sense of inevitability over developing T2DM. The key themes that emerged from the 3 focus groups with a total of 25 women were the need for interventions to provide “friendly encouragement,” “companionship,” and a “focus on the individual” and also for the text messages to “set achievable goals” and include “information on cooking healthy meals.” We combined the findings of the focus groups and literature review to create 13 guiding principles for culturally adapting the text messages. In step 2, we developed a program theory, which specified the main determinants of change that our text messages should aim to enhance: knowledge and skills, sense of control, goal setting and planning behavior, peer support, and norms and beliefs guiding behavior. In step 3, we used both the intervention program theory and guiding principles to develop a set of 73 text messages aimed at supporting a healthy diet and 65 text messages supporting increasing physical activity.

CONCLUSIONS

We present a theory-based approach to develop a culturally adapted diet and physical activity text message intervention to prevent T2DM for women of Pakistani origin living in Scotland. This study outlines an approach that may also be applicable to the development of interventions for other ethnic minority populations in diverse settings. There is now a need to build on this formative work and undertake a feasibility trial of a text message–based diet and physical activity intervention to prevent T2DM for women of Pakistani origin living in Scotland.
"Can We Detect Substance Use Disorder?": Knowledge and Time Aware
Classification on Social Media from Darkweb (Preprint)
Authors: Lokala Usha , Phukan Orchid Chetia , Dastidar Triyasha Ghosh , Lamy Francois , Daniulaityte Raminta , Sheth Amit
Published: September 2023

UNSTRUCTURED

Opioid and substance misuse is rampant in the United States today, with the
phenomenon known as the "opioid crisis". The relationship between substance use
and mental health has been extensively studied, with one possible relationship
being: substance misuse causes poor mental health. However, the lack of
evidence on the relationship has resulted in opioids being largely inaccessible
through legal means. This study analyzes the substance use posts on social
media with opioids being sold through crypto market listings. We use the Drug
Abuse Ontology, state-of-the-art deep learning, and knowledge-aware BERT-based
models to generate sentiment and emotion for the social media posts to
understand users' perceptions on social media by investigating questions such
as: which synthetic opioids people are optimistic, neutral, or negative about?
or what kind of drugs induced fear and sorrow? or what kind of drugs people
love or are thankful about? or which drugs people think negatively about? or
which opioids cause little to no sentimental reaction. We discuss how we
crawled crypto market data and its use in extracting posts for fentanyl,
fentanyl analogs, and other novel synthetic opioids. We also perform topic
analysis associated with the generated sentiments and emotions to understand
which topics correlate with people's responses to various drugs. Additionally,
we analyze time-aware neural models built on these features while considering
historical sentiment and emotional activity of posts related to a drug. The
most effective model performs well (statistically significant) with
(macroF1=82.12, recall =83.58) to identify substance use disorder.
Patient Phenotyping for Atopic Dermatitis With Transformers and Machine Learning: Algorithm Development and Validation Study (Preprint)
Authors: Wang Andrew , Fulton Rachel , Hwang Sy , Margolis David J , Mowery Danielle
Published: September 2023

BACKGROUND

Atopic dermatitis (AD) is a chronic skin condition that millions of people around the world live with each day. Performing research into identifying the causes and treatment for this disease has great potential to provide benefits for these individuals. However, AD clinical trial recruitment is not a trivial task due to the variance in diagnostic precision and phenotypic definitions leveraged by different clinicians, as well as the time spent finding, recruiting, and enrolling patients by clinicians to become study participants. Thus, there is a need for automatic and effective patient phenotyping for cohort recruitment.

OBJECTIVE

This study aims to present an approach for identifying patients whose electronic health records suggest that they may have AD.

METHODS

We created a vectorized representation of each patient and trained various supervised machine learning methods to classify when a patient has AD. Each patient is represented by a vector of either probabilities or binary values, where each value indicates whether they meet a different criteria for AD diagnosis.

RESULTS

The most accurate AD classifier performed with a class-balanced accuracy of 0.8036, a precision of 0.8400, and a recall of 0.7500 when using XGBoost (Extreme Gradient Boosting).

CONCLUSIONS

Creating an automated approach for identifying patient cohorts has the potential to accelerate, standardize, and automate the process of patient recruitment for AD studies; therefore, reducing clinician burden and informing the discovery of better treatment options for AD.
Big Data as a Product of the Preparation Plant: Reality and Prospects in the Case of Coal
Authors: Gvishiani Alexei , Nikitina Izabella , Aleshin Igor
Published: September 2023

The article examines the current and future flow of preparation's plant production processes and how they contribute to the generation of Big Data. It is shown that as the level of automation in the plant increases, the data produced becomes more extensive and varied. At the same time, it is possible to achieve a level when the generated information flows meet the criteria of the Big Data. As a basic example, a typical coal processing plant is used. The main sources, volumes, variety and speeds of data transfer to the processing plant are described and analyzed.
Contribution of Additional Glutamic Acid and Fructose in The Formation of Flavor Compounds in Green Tea
Authors: Aris Khaeruddin , Ningrum Andriati , Supriyadi Supriyadi
Published: September 2023

Green tea in Indonesia has an astringent and bitter taste due to its high catechin content. Adding amino acids and reducing sugars in green tea processing will increase the desirable flavor and cover the astringent and bitter flavors by increasing the Maillard reaction. Research on the manufacture of green tea with the addition of glutamate and fructose in fresh tea leaves has never been explored. This study aims to find a combination of glutamic acid (0%, 0.35%, 0.7%, 1.05%, 1.4%) and fructose (0%, 0.13%, 0.26%, 0.39%, 0.52%) to improve the flavor profile in green tea. The samples were evaluated for their antioxidant activity, amino acid, volatile, sensory evaluation, and color analysis. The results showed that adding glutamate and fructose increased the antioxidant activity of amino acid compounds and decreased the catechin content in green tea. Thus, the best treatment obtained was glutamate (1.05%) and fructose (0.26%), which increased the Maillard reaction in the formation of flavor compounds in green tea.
Comprehensive Evaluation of Antifungal Activity of Argania spinosa (L.) Skeels kernels of the Hot and Cold Extraction and the Effect of Solvents Varying Polarities and the Heat Treatment on Yield and Activity Variance
Authors: Lfitat Aziza , Ed-dahmani Imad , Bousraf Fatima Zohra , Belhaj Abdelhaq , Ainane Tarik , Taleb Mustapha , Gourch Abdelkader , Abdellaoui Abdelfattah
Published: September 2023

A comparative antifungal efficacy study of argan kernels was performed using different solvent fractions obtained by the two extraction methods: cold extraction by maceration at room temperature (1) and hot extraction by Soxhlet apparatus (2). Results demonstrated that the two extraction methods induce different yields among each solvent used. Maceration promoted the maximum contents of crude extract in hexane (42.15%), diethyl ether (2.59%), dichloromethane (4.22%), and ethyl acetate (2.52%). Whereas the hot extraction yielded higher extractives in the case of methanol (22.97%) and water (5.88%) compared to cold extraction. The MIC values of the fractionated extracts obtained by maceration were in the range of 0.051 ± 0.002 and 0.223 ± 0.005 g/ml, whilst they were in the range of 0.101 ± 0.002 and 0.286 ± 0.005 g/ml for the Soxhlet extracts. According to total activity (TA) interpretation, dichloromethane was the most effective solvent to extract active antifungal components, revealing the strongest ability to suppress the growth of fungi at much lower MIC values (0.051 ± 0.002 to 0.156 ± 0.005 g/ml) than the rest of fractions. The effect of heating resulted in an increase of the MICs values of the Soxhlet extracts from 10 to 25 times higher than macerated ones, resulting in lower antifungal activity.
ANALISIS SIKAP SISWA TERHADAP IPA DI SMP KABUPATEN MUARO JAMBI PROVINSI JAMBI
Authors: Kurniawan Dwi Agus , Astalini Astalini , Kurniawan Nugroho
Published: September 2023

Tujuan: Sikap berupa ungkapan suka ataupun tidak suka dan ungkapan menerima ataupun menolak suatu objek. Sikap menerima dilambangkan dengan sikap positif dan sikap menolak dilambangakan dengan sikap negatifÂ  Penelitian ini bertujuan mendeskripsikan sikap siswa berdasarkan tiga indikator sikap di SMP di Muaro Jambi. Metode Penelitian: Jenis penelitian ini adalah Penelitian survey. Instrumen yang digunakan berupa angket yang berfokus pada tiga indikator yang terdiri dari 26 pernyataan dan juga wawancara. Sampel pada penelitian ini berjumlah 2815 SMP di Muaro Jambi. Hasil: Hasil penelitaian tiga indikator sikap yang menjadi fokus penelitian dominan pada kategori baik. Imlpkasi sosial dari IPA menunjukkan kategori sangat baik dengan pesentase kategori 53,2%.Â  Kesenangan dalam belajar sains menunjukkan kategori baik dengan persentase 48,1%. Ketertarikan berkarir dibidag fisika berkategori cukup dengan persentase kategori sebesar 41,8 %. Implikasi:Â  Penelitian yang telah dilaksanakan terlihat bahwa sikap siswa di Sekolam Menengah Pertama berkategori baik, karena tiga indikator yang di teliti menunjukkan kategori baik.
Inteligencia emocional de padres de familia y rendimiento académico de niños en plataformas virtuales del primer grado de primaria de una institución educativa privada
Authors: La Torre Orbegoso Jesús Albero
Published: September 2023

El presente trabajo de investigación tuvo como finalidad determinar que existe relación entre la inteligencia emocional de los padres de familia y el rendimiento académico de los niños del primer grado de una institución educativa privada sede Tacna AF 2021, presentando resultados objetivos que arribaron en conclusiones que permitirán sentar las bases para afrontar en caso hubiese, otras etapas de confinamiento. En cuanto a la metodología esta investigación es de tipo básica, de nivel cuantitativo y diseño no experimental, relacional transversal. Se aplicó una encuesta censal donde se evidencia la influencia de la inteligencia emocional sobre el rendimiento académico. Del total de 64 padres de familia de niños que emplearon plataformas virtuales se evidenció que el 91.00% de ellos, con una aplicación adecuada de la inteligencia emocional, conllevaron al mejor rendimiento académico obteniendo logro destacado de los niños del primer grado y siendo el otro 9% quienes alcanzaron el nivel de logro esperado con un 0% de niños con nivel en proceso y en inicio. Con estos resultados se puede afirmar que la inteligencia emocional de padres de familia tiene influencia significativa en el rendimiento académico de niños en plataformas virtuales del primer grado de primaria de una institución educativa privada – sede Tacna AF 2021, logrando un 100% de logro destacado y esperado en esta etapa formativa.
Comprendiendo la dinámica de los conflictos en américa latina
Authors: Villar Roldán Juan José , Martín Álvarez Juan Manuel
Published: September 2023

El presente estudio tiene como finalidad la identificación de patrones en los conflictos de América Latina desde el año 1989 hasta la actualidad. El artículo se basa en el supuesto de que la clusterización puede utilizarse para alcanzar una mayor comprensión sistémica de las correlaciones entre política, economía y conflicto. Se parte del supuesto de que las variables utilizadas forman parte de un sistema interactivo con correlaciones aún por comprender. La clusterización es la herramienta que se utiliza para clasificar entidades en grupos con el fin de buscar explicaciones basadas en características transversales a los objetos en los que están integradas; de este modo, el análisis busca una explicación más tangible de los complejos vínculos entre las variables de desarrollo humano, económicas y las relacionadas con los conflictos. En el análisis se utilizan los datos del Uppsala Conflict Dataset Program para categorizar actores presentes en conflictos en función de una serie de características.
CMMSE: Jacobian-free vectorial iterative scheme to find several solutions simultaneously
Authors: Triguero-Navarro Paula , Cordero Alicia , Torregrosa Juan Ramon
Published: September 2023

This manuscript is devoted to a derivative-free parametric iterative
step to obtain roots simultaneously for both nonlinear systems and
equations. We prove that when it is added to an arbitrary scheme, it
doubles the convergence order of the original procedure and defines a
new algorithm that obtains several solutions simultaneously. Different
numerical experiments are carried out to check the behaviour of the
iterative methods by changing the value of the parameter and the initial
guesses. Also, it is perform a numerical example where the dynamical
planes are carried out to see and compare the basins of attraction.