bluuebunny/crossref_metadata_2025_split huggingface dataset:
Community Perception of Forest Ecosystem Services to Enhance Environmental Decision-making in the Ifrane National Park (Morocco)
Authors: Ismaili Hassana Alaoui , Brhadda Najiba , Ziri Rabea 
Published: September 2023

Abstract
The concept of ecosystem services is increasingly seen as a tool allowing the achievement of sustainable use of forest resources. However, it is not yet sufficiently integrated into participatory forest management approaches.
For this purpose, a study was conducted to assess the direct and indirect benefits of Forest Ecosystem Services perceived by local communities around Ifrane National Park in Morocco and their involvement in its management. The data are collected from 279 households between April and June 2021 through face-to-face interviews. Perceptions of use, priority, and trends of Forest Ecosystem Services are analyzed using descriptive statistics. The Chi-square test was used to examine significant associations between wealth categories and prioritization of provisioning FES.
Several provisioning Forest Ecosystem Services have been identified as essential for household subsistence and cash uses. The chi-square test shows an association between provisioning forest services for subsistence and cash use and household wealth categories. Regarding the prioritization of FESs, fifteen were prioritized, showing the need for their integration into any future forest management approach. 92.8% of participants perceived change in ecosystem services using the participatory approaches, this change was almost always positive (30.9%) and often negative (27.6%). Provisioning FES experienced the greatest negative change (59.2%), requiring several interventions to ensure their sustainability.
These results confirm the importance of integrating participatory ecosystem service assessment with biophysical evaluations to evaluate the benefits of forest areas for the well-being of users. Lack of involvement in forest management can contribute significantly to unsustainable resource extraction by local communities.
Zio® XT Patches in Pediatrics During the COVID-19 Pandemic: Comparisons Between In-Person and Mail-Home Application
Authors: Khan Mohammad S. , Dawson Angela , Rosenthal Geoffrey , Snyder Christopher 
Published: September 2023

Abstract
The Zio® (Zio) XT Patch is a 14-day continuous ambulatory ECG monitor. During the Covid-19 pandemic, Zios were mailed directly to patients for self-application. The purpose of this study was to compare the percent artifact, a marker for quality, of in-clinic (IC) to mail-home (MH) applications in a pediatric population.
Methods:A single-center, IRB-approved study of patients 0-< 21 years of age with Zios were studied for wear and artifact time filtered out based on iRhythm’s proprietary algorithm.
Results: In total, 284 Zios were randomly selected and analyzed for total wear time and artifact. Of these, 149 were IC prior to 12/31/2019 and 135 MH patches prescribed after 1/1/2020. No significant difference was found for percent artifact between the IC (7.8%) and MH (8.3%) group. Average IC wear-time was 127 hours compared to MH at 99 hours (p = 0.02). In conclusion, application of Zio patches outside of the pediatric cardiology clinic offers equivalent artifact, a marker of quality, as those applied in clinic and should be consideration as a viable alternative.
Analysis of Low Carbon Integrated EnergySystem Considering Multiple Uncertainties
Authors: Wang Lunjie , Chen Shuai , Luo Lin , Cao Yupeng 
Published: September 2023

Abstract
Carbon capture systems and the utilization of renewable energy are key waysto reduce carbon emissions, but their uncertainty seriously affects the stableoperation and economic efficiency of power systems. To tackle this challenge, alow-carbon economic scheduling model for microgrid electric-thermal integratedenergy systems(IES) considering uncertainty is proposed in this paper. The modelsuggests an ideal dispatch of the IES system that accounts for the disruption ofthe carbon capture system’s integration into the grid belt and plans for the carbon capture plant’s low carbon features. Coupling of wind energy with carboncapture power plants employing incentives for system operation and dispatch toincorporate load-side demand response resources. The system’s low carbon performance is increased through cooperative source-load resource optimization. Awell-established industrial automation optimal dispatch model is developed usingYALMIP and CPLEX. The results reveal that the method contributes to the resolution of the system adaptability problem and encourages a balance between lowcarbon and economics for large loads, taking into account that uncertainty raisesthe cost by around 3%, thereby boosting system robustness to an acceptabledegree.
Insights of Bioethics among Healthcare Professionals in All Public and PrivateHospitals of District Haripur, Pakistan
Authors: Ateeb Muhammad , Haq Ijaz ul , Zakki Shahbaz Ahmad , Altaf Ehtisham , Junaid Muhammad , Ali Mustafa , Rehman Atif Ur , Wajid Daniyal , Farid Abdullah , Mehmood Asad 
Published: September 2023

Abstract

Background:Awareness of bioethics among healthcare personnel is essential to ensure ethical practice in healthcare. The study aimed to assess the level of bioethics insights and awareness among healthcare professionals and explore its associations with socio-demographic characteristics, training/teaching of ethics, practice of medical ethics and specific ethical issues.Methods:A cross-sectional study was conducted between March and May of 2023 among healthcare professionals (n = 647) including doctors, nurses, LHV, medical technicians/dispensers and other medical personnel from both the public healthcare facilities (BHU, RHC, THQ, and DHQ) and private hospitals located in the Haripur district, Pakistan. The data was collected through a validated questionnaire, whereby a score was given for each response, and a total score was calculated.Results:The overall mean ± SD awareness scores for ethics in healthcare practice and specific issues in medical ethics were 8.0 ± 2.4 and 32.0 ± 5.2, indicating both physicians and non-physicians need to know more about bioethics. With regard to training and teaching in medical ethics, a significant correlation was found between the duration of the ethical training/teaching and job categories/designations (p< 0.001). Ethical views of healthcare professionals differed greatly by job designation regarding the treatment of children without consent (Cramer’s V = 0.4) and revealing the patient’s condition to relatives (Cramer’s V = 0.39). Specific ethical issues such as accepting gifts from patients and pharmaceutical companies, referral fees, advising specific products to patients, disclosure of medical errors, patient’s confidentiality, not informing patients fully about treatment and performing tasks for financial gain showed significant associations with healthcare professional's designation (p< 0.05). Significant differences were observed in ethical awareness scores based on age, ethnicity, place of posting, professional experience, and the organization's ethical guidelines (p< 0.05).Conclusion:This study highlighted a notable gap in the understanding of certain ethical concerns among healthcare professionals, with nurses showing relatively lower awareness of healthcare practice compared to other professionals. Addressing these issues through targeted training and robust ethical guidelines are critical to improving patient’s care and rights in Pakistan's healthcare system.
Unveiling the Intrinsic Photophysics in Quasi-2D Perovskites
Authors: Ren Zefeng , Li Bo-Han , Di Haipeng , Li Huang , Wang Jia-Cheng , Zeng Wen , Cheng Da-Bing , Zhou Chuanyao , Wang Xingan , Shi Yan , Song Jiangfeng , Zhao Yiying , Yang Xueming 
Published: September 2023

Abstract
The 2D perovskites have drawn intensive attentions due to their unique stability and outstanding optoelectronic properties. However, the debate surrounding the spatial phase distribution and band alignment among different 2D phases in the quasi-2D perovskite has created complexities in understanding the carrier dynamics, hindering material and device development. In this study, we employed highly sensitive transient absoprtion spectroscopy to investigate the carrier dynamics of (BA)2(MA)n−1PbnI3n+1 quasi-2D Ruddlesden-Popper (RP) perovskite thin film, nominally prepared as n = 4. We observed the carrier density dependent electron and hole transfer dynamics between 2D and 3D phases. Under low carrier density within the linear response range, we successfully resolved three ultrafast processes of both electron and hole transfers, spanning from hundreds of fs to several ps, tens to hundreds of ps, and hundreds of ps to several ns, which can be attributed to lateral-epitaxial, partial-epitaxial and disordered-interface heterostructures between 2D and 3D phases. By considering the interplay among phase structure, band alignment and carrier dynamics, we have proposed material synthesis strategies aimed at enhancing the carrier transport. Our results not only provide deep insights into an accurate intrinsic photophysics of quasi-2D perovskites, but also inspire advancements in the practical application of these materials.
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

Abstract
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

Abstract:
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

Abstract:
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

Abstract: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.