bluuebunny/crossref_metadata_2025_split huggingface dataset:
Overview of Digital Agriculture Technologies in Indonesia: Policies, Implementation, and Covid-19 Relation
Authors: Mangurai Silvia Uthari Nuzaverra Mayang , Octaviani Eti Artiningsih , Anidah Anidah , Solikhin Achmad , Darmawan Refianto Damai , Wulandari Lora Septrianda , Kurniawan Tegar 
Published: October 2022

Abstract
This study was purposed to overview on general application of Indonesia’s digital agriculture technology policies, implementation, and its relation to the Covid-19 pandemic. This study was undertaken through a systematic evidence evaluation complemented with an interactive map and thematic map of digital agriculture application. This study reported that the Government of Indonesia (GoI) has issued national initiatives and policies that support the implementation of digital techologies in food and agriculture sectors. However, a very limited number of both initiatives and policy has mainstreamed the Covid-19 pandemic. An interactive map of digital agriculture companies can be found at this link:https://agriculture40companies.gis.co.id/, and most of the companies are in form of farmers advisory, mechanization platforms, digital marketplace, e-commerce, traceability, food delivery, and peer-to-peer lending. These applications are mostly concentrated in Java island, and and have benefited digital technologies, such as IoT, blockchain, artifical intelligence, smart phone or android, mobile apps, GPS/GIS, and drone. Start-up companies have applied strategic measures to cope with the pandemic implications and some activities of the companies are suspended.
Optimized Feature Extraction and Cross-Lingual Text Reuse Detection using Ensemble Machine Learning Models
Authors: Maqbool Muhammad Sajid , Hanif Israr , Iqbal Sajid , Basit Abdul , Shabbir Aiman 
Published: October 2022

Abstract
With the availability of digital data in different languages, cross-lingual plagiarism (CLP) detection has gained more importance. CLP is difficult to detect because suspicious and source texts can be written in different languages and processing of digitized text in different languages presents varying types of challenges. In this work, we propose a cross-lingual plagiarism detection method using machine learning algorithms. In this work, we have created an ensemble of machine learning algorithms and to evaluate the designed methodology, a corpus focusing Urdu-English language pair titled CLPD-UE-19 (Israr Haneef et al. 2019) is used. The corpus is a collection of 2398 documents where the source text is written in Urdu language and the suspicious text is presented in the English language. Using NLP methods, optimal features are extracted and fed to designed ensemble method for document classification. A number of aggregating techniques are employed which include majority voting, stacking, averaging, boosting, and bagging. Among these models, the stacking has performed the best achieving accuracy of 96 percent.
Covid-19 Vaccine Recommendation Opinions of Nursing/midwifery Students to Women of Reproductive Age
Authors: VAYISOGLU SUMBULE KOKSOY , BESEN MELTEM AYDIN , ONCU EMİNE 
Published: October 2022

Abstract
Nursing and midwifery students are an important resource in increasing COVID-19 vaccine acceptance among women of reproductive age. In this study, it was aimed to determine the thoughts of midwifery and nursing senior students to recommend COVID-19 vaccine to women of reproductive age and related factors. The data of the cross-sectional study were collected from 504 midwifery and nursing senior students across Türkiye between March 15th - April 30th, 2022, using the "Individual Identification Form", "Vaccine Opinion Form" and "Scale of Attitudes towards COVID-19 Vaccine" in the online environment with snowball sampling method. Data were evaluated with t test, chi-square analysis, correlation analysis, ANOVA, logistic regression, and decision tree analysis. Of the students, 84.3% were women, 50.2% were in the nursing department, and 97.6% had at least two doses of COVID-19 vaccine. While 44.4% of the students stated that they would not recommend vaccination to any of the women that pregnant, breastfeeding and planning to pregnancy, 22.6% reported that they could recommend the COVID-19 vaccine to all three groups. Students who thought they could be counselled on vaccines and had received a previous flu shot were more likely to recommend a COVID-19 vaccine, while students who did not find vaccines safe and believed they could be harmful and did not receive adequate training on vaccines were less likely to recommend vaccines. Counselling self-efficacy of students was affected by education and up-to-date information. It is recommended to develop knowledge and counselling skills so that nursing and midwifery students can recommend COVID-19 vaccine to women of reproductive age.
Mental wellbeing and Health-Risk behaviors of University students in Brunei: A cross-sectional study during COVID-19
Authors: Rahman Hanif Abdul , Julaini Nurul Nazurah , Zaim Siti Nurzaimah Nazhirah , Masri Nurfatin Amalina , Abdul-Mumin Khadizah H. 
Published: October 2022

Abstract
Introduction: The coronavirus disease 2019 (COVID-19) has detrimental effects on mental wellbeing and has altered health behaviors of university students. However, little is known about the impact on university students in South-East Asia, particularly in Brunei.
Aim: To estimate the prevalence and factors related to poor mental wellbeing and engaging in health-risk behaviors among university students in Brunei during the COVID-19 pandemic.
Methods: A cross-sectional online survey of students in all public universities. Warwick-Edinburgh Mental Well-being Scale, Global Physical Activity Questionnaire, and WHO STEPs questionnaires were used to measure mental wellbeing, physical activity, and health behaviors, respectively. Logistic regressions were applied.
Results: 1020 university students participated in this study (57% response rate). Prevalence of poor mental wellbeing and physical inactivity were 30% and 42.8%, respectively. Excessive snacking (89.7%), sugar intake (81.7%), and salt intake (53.8%) were the most prevalent health-risk behaviors. Body mass index and participate in sports activities were the most common factors related to mental wellbeing and health-risk behaviors.
Conclusions: Participating in certain sports activities appear to have protective effects against study outcomes. However, high prevalence of physical inactivity and unhealthy diet among university students is a concern as it could be indicative of future non-communicable disease trend.
Development and validation of machine learning based models for predicting distant metastasis in colorectal cancer: a population-level study
Authors: Li Shuofeng , Yu Guanhua , Wei Ran , Wang Xishan , Jiang Zheng 
Published: October 2022

Abstract
Background
Distant metastasis (DM) is an important prognostic factor and determines the following treatments in patients with colorectal cancer (CRC). The purpose of this study was to construct prediction models for DM in patients with CRC based on machine learning.
Methods
CRC patients between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were identified. Prediction models for DM were developed by applying four machine-learning methods including eXtreme Gradient Boost (XGB), decision tree (DT), random forest (RF), and support vector machine (SVM). The performance of models was quantitatively assessed by receiver operating characteristics (ROC) curve, calibration curve and decision curve analysis (DCA) curve. The SHapley Additive exPlanation (SHAP) method was used for visualization analysis to better explain the results of the machine learning models.
Results
A total of 51788 patients were identified in the SEER database. ROC curves exhibited excellent accuracy of machine learning models. Calibration curves for the probability of DM showed good agreement between model prediction and actual observation in both the training and validation cohorts. The DCA demonstrated that each machine learning model can provide net benefits with treat-none and treat-all strategies. In the SHAP summary plot of the RF and XGB models, carcinoembryonic antigen (CEA), N stage, T stage and tumor deposits were identified as the most important risk factors for DM.
Conclusion
The XGB and RF were ideal machine learning models and showed that CEA, N stage, T stage and tumor deposits were the most important DM-related risk factors.
Pyrometallurgy and Electrometallurgy of Rare Earths – Part B: Cell design, construction, rate processes, and unit operation
Authors: Rafique Muhammad Musaddique Ali , Rafique Muhammad Musaddique Ali 
Published: October 2022

Abstract
Production of rare earths by metallothermic reduction and its variants is presented in an earlier study and its analysis is performed indicating major type and sequence of reactions. Diagrams required and procedures to establish them are also described. Their role and importance are also described. A comparison is also made to identify parameters of importance. This study is continuation of a previous study in which cell design to extract metals is described. Parameters to design and construct cell (metallothermic and electrothermic) are determined and used. Rate processes (heat transfer, mass transfer, charge transfer and simultaneous processes) occurring inside a cell, its operation for a specific reaction and sequence for a specific metal (Nd) are described. Outline of calculations outlining cell efficiency, output and yield are enumerated for individual (Nd, Ce, Dy) metal. Optimization and method to achieve is described. Procedures to control and production is also described. Here preliminary graphs are presented.
Irreversibility optimization on chemically reactive in MHD of radiated Powell-Eyring nanofluid flow with Arrhenius activation energy through Peristaltic micro vessel containing Planktonic microorganisms
Authors: Hussein Sameh A. , Arafa Anas A. M. , Almalki Nawal , AL-Essa Lulwah , Elshekhipy Abdelhafeez , Almuaddi Saad , Ghrib Taher , AL-Saleem Nouf , Ibrahim Nehad 
Published: October 2022

Abstract
The amount of energy lost during any irreversible process is called entropy. The focus of this paper is on how to reduce this energy loss in order to improve the capacity of our system, especially in the presence of planktonic microorganisms. To understand the flow physics associated with bolus formation and the impact of reverberation on the micro vessel, a 3D computational fluid dynamic analysis is performed. The effects of binary chemical interaction with nonlinear mixed convection and Arrhenius activation energy are considered in the present analysis. The complexity of the system was achieved through a numerical approach based on the concepts of small Reynolds number and large wavelength. The resulting nonlinear coupled differential equation system is solved numerically using the built-in command in MATHEMATICA (ParametricNDSolve). Some of the investigation's findings are the entropy profile has been improved for incremental values of Hartmann number and Brinkmann number whereas the axial velocity shows a downward trend for the highest values of the Hartmann number and the material parameter "A". The improvement in the flow, heat, and mass transmission properties of hypoxic tumor regions, will provide developing in drug carrier uses in hypoxic carcinoma regions.
Well-posedness and exponential stability of a coupled fluid-thermoelastic plate interaction model with second sound
Authors: Jiang Jian , Liu Wenjun 
Published: October 2022

Abstract
In this paper, we investigate a coupled system modeled by fluid and thermoelastic plate while the heat effects are modeled by the Cattaneo' law giving rise to a ``second sound" effect. By using the semigroup method, we prove the well-posedness of the system. Then, we construct the second order energy to control the term ∥∇θ∥L2(Г0) so as to establish the exponential decay of the solutions by using the modified multipliers method.
2010 Mathematics Subject Classification: 35Q30, 74F05, 74F10.
Deciphering the broadband absorption of eumelanin in solution
Authors: Izgorodina Ekaterina I , Singh Abhishek , Mason Thomas G , Freeman Benny D 
Published: October 2022

Abstract
Melanin, a bio-polymer responsible for visible pigmentation in the human body, works as a protective layer in our skin by absorbing UV radiation and efficiently dissipating it into heat, preventing DNA damage. The primary structure of eumelanin, one of the two main forms of melanin, is presumed to be a co-polymer of 5,6-dihydroxyindole (DHI) and 5,6-dihydroxyindole-2-carboxylic acid (DHICA) monomers, with DHI being the major component. The solution phase investigation into the origin of broadband monotonic absorption spectrum of melanin has been realized through the polymerization of dopamine and L-DOPA, the molecular precursors of DHI and DHICA, respectively, in an ionic liquid (IL). The evolution of the electronic absorption spectrum of polymerized L-DOPA did not mimic the electronic spectrum of eumelanin, which was attributed to their inability to form stable redox states, as elucidated via structural characterization. In contrast, polymerized DA (pDA) mimics the eumelanin absorption spectrum, and the structural characterization of the polymerization process performed with 1H and 13C NMR and DOSY spectroscopy allowed us to identify chromophores responsible for the absorption profile of pDA. Furthermore, the identified chromophores were subjected to quantum chemical calculations, and the predicted absorption spectra not only supported their presence in the experimental UV-Vis spectra but also allowed us to identify their gradual evolution during polymerisation. The knowledge of the chromophores responsible for the optical properties of melanin will undoubtedly result in their increased application in functional materials.
Prevalence of mental, neurological and substance use conditions and case detection at primary healthcare facilities across three districts in Ghana: findings from a cross-sectional health facility survey
Authors: Ae-Ngibise Kenneth A. , Sakyi Lionel , Adwan-Kamara Lyla , Lund Crick , Weobong Benedict 
Published: October 2022

Abstract
Background: Few studies have examined the prevalence of mental, neurological and substance use disorders, case detection and treatment in primary healthcare in rural settings in Africa. We assessed needs and case detection rate at primary healthcare facilities in low-resource settings in Ghana.
Methods: A cross-sectional study was conducted at the health facility level in three demonstration districts situated in Northern, Middle and Southern belts in Ghana. These districts are Bongo (Upper East Region), Asunafo North (Ahafo Region) and Anloga (Volta Region). Data were collected on five priority mental, neurological and substance use conditions of interest including depression, psychosis, suicidal ideation, epilepsy and alcohol use disorders.
Results: Nine hundred and nine (909) people participated in the survey. The prevalence of depression was 15.6% (142/909), psychosis was 12% (109/909), suicidal ideation was 11.8% (107/909), epilepsy was 13.1% (119/909) and alcohol use disorders was 7.8% (71/909). The proportion of missed detection for cases of depression, psychosis, epilepsy and alcohol use disorders (AUD) ranged from 94.4% to 99.2%, and was similar across study districts. Depression was associated with psychosis (RR: 1.68; 95% CI: 1.12-1.54). For psychosis, a reduced risk was noted for being married (RR: 0.62; 95% CI: 0.39-0.98) and having a tertiary level education (RR: 0.12; 95% CI: 0.02-0.84). Increased risk of suicidal ideation was observed for those attending a health facility in Asunafo (RR: 2.31; 95% CI: 1.27-4.19) and Anloga districts (RR: 3.32; 95% CI: 1.93-5.71). Age group of 35 to 44 years (RR: 0.43; 95% CI: 0.20-0.90) and attending a health facility in the Anloga district (RR: 0.43; 95% CI: 0.20-0.90) were associated with reduced risk of epilepsy, but not for those more than 35 years (RR: 3.06; 95% CI:1.14-8.24). Being female (RR: 0.19; 95% CI: 0.12-0.31) and having a tertiary education were associated with reduced risk of AUD (RR: 0.27; 95% CI: 0.08-0.92).
Conclusions: Our study found a relatively high prevalence of MNS conditions, and very low detection and treatment rates in rural primary care settings in Ghana. There is a need to improve the capacity of primary care health workers to detect and manage mental health conditions, together with improved medication supply and referral pathways.
Identifying determinants of sustainable water management at the household level through rainwater harvesting systems in Nepal
Authors: Thapa Anusha , Khanal Ghanashyam , Mahapatra Sushanta Kumar , Devkota Niranjan , Mahato Surendra , Paudel Udaya Raj 
Published: October 2022

Abstract
The urban water supply systems around the world are highly stressed at present due to growing water demand caused by rapid population growth and unplanned urbanization. The growing environmental awareness and water supply restrictions have made rainwater harvesting systems (RWHS) a priority as well as a necessity in many countries. To improve urban water security, the practice of an RWHS is increasingly being adopted in the cities and towns of developing countries. This study aims at identifying the factors affecting the adoption of rainwater harvesting for household uses in the Kathmandu valley (KV) of Nepal. The results were drawn from a survey of 405 respondents who reside in the KV. To explain the determinants of adaptation, structural equation modeling (SEM) was used. Results show that independence for water access and system sophistication are significant for the adaptation of RWHS and relative advantage plays a moderating role that has partial mediation among dependent and independent variables with a significant relationship. Thus, variables like independence for water access, system sophistication, relative advantage and sustainable use should be highlighted for a sustainable supply of water. For this, we recommend effective policy interventions at the local and national level for the adoption of RWHS and its advantages in terms of safeguarding water in the long run at the present changing climate scenario.
Are Monocyte, %M and WBC Biomarkers in the First Trimester Screening
Test?
Authors: Oz Ozlem , Gonel Ataman 
Published: October 2022

Background:
Differences in free beta HCG and PAPP-A values, which are among the biochemical parameters in the double screening test, is frequently used for pregnancy follow-up, allow aneuploidy and triploidy risk to be determined. In recent studies, it’s suggested that the modified hemogram indices have gained importance as a marker in the prognosis of diseases.

Objective:
In this study, we aimed to determine the hematological parameters, which are routinely applied in the first trimester of pregnancy, have any value in predicting the risk increase in the double screening test and in early diagnosis.

Method:
Pregnant women who conceived spontaneously and had double screening tests were included in the study. CBC results that were studied together with the first trimester screening test were reported. The patients were divided into two groups according to the results of the screening test as the combined risk ratio.

Results:
The mean age was found to be significantly higher in the high-risk group than in the low-risk group. Monocyte, % M and WBC values were significantly lower in the high-risk group (0,483±0,140, 5,58±1,44 and 8,75±2,12 , respectively). There was no significant difference in NLR and PLR values compared between the groups. MPV values were lower and PAPP-A, PAPP-A MoM values were significantly lower in high-risk group compared to the low-risk group.

Conclusion:
The findings support low Monocyte, % M and WBC values as a potential marker for the identification of the high risk pregnancy in otherwise healthy pregnant women. The results indicate that CBC parametres commonly used in pregnancy can be used to predict the prognosis.
Effectiveness of Selective Estrogen Receptor Modulators in Breast
Cancer Therapy: An Update
Authors: Das Agnidipta , Lavanya Kanamarlapudi Joshna , Nandini  , Kaur Kamalpreet , Jaitak Vikas 
Published: October 2022

Background:
Breast cancer is considered to be 2nd most common cancer subtype
investigated worldwide. It is mainly prevalent in postmenopausal women. Estrogen
Receptor (ER) is a primary transcription factor for the survival and growth of tumors.
Around 80% BCs of all classes are ER-positive (ER+). Powerful evidence for estrogen
proved to be involved in BC pathogenesis both exogenously and endogenously. It brings
the concept of ER inhibitors to treat BC with distinct mechanisms into focus and ER
PROTACs (Proteolysis-Targeting Chimeras), AIs (Aromatase inhibitors), SERMs (Selective
estrogen receptor modulators), and SERDs (Selective estrogen receptor degrader)
were developed. For over 30 years, Tamoxifen, a triphenylethylene SERM, was the drug
of choice solely to treat ER+BC patients. Although several SERMs got approval by US
FDA after tamoxifen, complicacies remain because of dangerous adverse effects like endometrial
carcinoma, hot flashes, and VTE (Venous thromboembolism). In addition to
that, drug-resistant tumors put a surging need for novel, potent candidates with no or low
adverse effects for ER+ BC prevention.

Objectives:
This article explores the possibilities of SERMs as effective BC agents.

Methods:
A detailed literature survey of the history and recent advancements of SERMs
has been carried out, taking BC as the primary target. This review provides information
about ER structure, signaling, pharmacological action, chemical classification with SAR
analysis, and benefits and adverse effects of SERMs as potential BC agents.

Results:
Exhaustive literature studies suggested that SERMs having an agonistic, antagonistic
or mixed activity to ER could efficiently inhibit BC cell proliferation

Conclusion:
Each chemical class of SERMs comprises some salient features and potentials,
which may be further investigated to obtain novel effective SERMs in BC therapy.
A Revision of Polymeric Nanoparticles as a Strategy to Improve the
Biological Activity of Melatonin
Authors: Franco Pablo Igor Ribeiro , do Carmo Neto José Rodrigues , Rocha Viviane Lopes , Machado Juliana Reis , Amaral Andre Correa , Miguel Marina Pacheco 
Published: October 2022

Abstract:
Drug delivery systems based on nanotechnology exhibit a number of advantages
over traditional pharmacological formulations. Polymeric nanoparticles are commonly
used as delivery systems and consist of synthetic or natural polymers that protect
drugs from degradation in physiological environments. In this context, indolamine melatonin
has been associated with several biological functions, including antioxidant, antitumor,
immunoregulatory, neuroprotective, and cardioprotective effects. However, its availability,
half-life, and absorption depend upon the route of administration, and this can limit
its therapeutic potential. An alternative is the use of polymeric nanoparticle formulations
associated with melatonin to increase its bioavailability and therapeutic dose at sites
of interest. Thus, the objective of this review is to provide a general and concise approach
to the therapeutic association between melatonin and polymeric nanoparticles applied
to different biological disorders and to also highlight its advantages and potential
applications compared to those of the typical drug formulations that are available.