bluuebunny/crossref_metadata_2025_split huggingface dataset:
Conversion of waste paper sludge into magnetic biochar for activation of peroxydisulfate for tetracycline removal
Authors: Zhang Xin , Zhang Hongtao , Cai Shuhan , Hu Zehong 
Published: October 2024

ABSTRACT

The Fe2+-peroxydisulfate (PDS) process is an effective method to enhance paper sludge dewaterability. However, the generated waste of iron-rich sludge cake needs to be disposed of properly. Converting sludge cake into magnetic biochar catalysts can help to shorten its environmental risks, recover resources, and reduce catalyst costs. In this work, the magnetic sludge biochar (Fe-SBC) was prepared and applied as a PDS activator to remove tetracycline (TC). Results showed that the Fe-SBC pyrolyzed at 600 °C presented excellent catalytic activity for PDS to degrade TC (rate of 74.89%) under the optimum conditions (intrinsic pH, 10 mM PDS, 0.5 g/L Fe-SBC, and 50 mg/L TC). It was found for the first time that the addition sequences of the biochar catalyst and PDS were insignificant on TC removal. Furthermore, the TC removal mechanism was proposed to be free radicals (·OH, SO4·−, and O2−·) and non-radical (1O2) pathways working together for TC removal, for which 1O2 was dominated. In addition, coexisting ions (Cl− and CO32−) had an inhibitory effect on TC degradation. This work will provide a new recycling approach for waste paper sludge in wastewater treatment.
Implementation of an Automated System Using Machine Learning Models to Accelerate the Process of In Silico Identification of Small Molecules As Drug Candidates
Authors: Sevimoglu Tuba 
Published: October 2024

Abstract:
Drugs are commonly utilized to diagnose, cure, or prevent the occurrence of
diseases, as well as to restore, alter, or change organic functions. Drug discovery is a
time-consuming, costly, difficult, and inefficient process that yields very few medicinal
breakthroughs. Drug research and design involves the capturing of structural information
for biological targets and small molecules as well as various in silico methods, such
as molecular docking and molecular dynamic simulation. This article proposes the idea
of expediting computational drug development through a collaboration of scientists and
universities, similar to the Human Genome Project using machine learning (ML) strategies.
We envision an automated system where readily available or novel small
molecules (chemical or plant-derived), as well as their biological targets, are uploaded
to an online database, which is constantly updated. For this system to function, machine
learning strategies have to be implemented, and high-quality datasets and high quality assurance
of the ML models will be required. ML can be applied to all computational drug
discovery fields, including hit discovery, target validation, lead optimization, drug repurposing,
and data mining of small compounds and biomolecule structures. Researchers
from various disciplines, such as bioengineers, bioinformaticians, geneticists, chemists,
computer and software engineers, and pharmacists, are expected to collaborate to establish
a solid workflow and certain parameters as well as constraints for a successful outcome.
This automated system may help speed up the drug discovery process while also
lowering the number of unsuccessful drug candidates. Additionally, this system will decrease
the workload, especially in computational studies, and expedite the process of
drug design. As a result, a drug may be manufactured in a relatively short time.
Determination of pH-Solubility Profile and Development of Prediction Models for pH-Dependent Solubility of Atorvastatin Calcium
Authors: Bodiwala Kunjan B. , Dhameliya Tejas M. , Sureja Dipen K. , Patel Manish P. 
Published: October 2024

Background:
Aqueous solubility is a key parameter in understanding drug transport
in the body and also in the development of analytical methods. Determination of a complete
pH-solubility profile is essential during the pre-formulation stage, and it is also required to define
the class of drug according to the biopharmaceutical classification system.

Objectives:
This study aimed to generate solubility data to obtain a complete pH-solubility
profile for Atorvastatin calcium using the spectrophotometric method and to develop models
for the prediction of aqueous solubility of Atorvastatin calcium at a given combination of the
pH and temperature.

Methods:
The developed pH independent spectrophotometric method was applied to determine
the pH solubility profile of the drug at three different temperatures. Models for the prediction
of solubility were generated by using a full factorial design and validated by determining
solubility experimentally at some combinations of pH and temperature within the design
spaces.

Results:
Solubility of Atorvastatin calcium was found to increase gradually with pH within a
range of pH 1.2-4.0 and pH 9.0-12.0 while increasing drastically with pH within a range of pH
4.0-9.0 at all three temperatures. Experimental values of solubility of Atorvastatin calcium
were found to be in good agreement with predicted values from models.

Conclusion:
Predictive models generated from the experimental values are good indicative of
the solubility of Atorvastatin calcium with respect to temperature and pH of the medium and
can be used for accurate prediction of aqueous solubility within the design space of the models.
Establishment and Validation of a Robust Reversed-Phase HPLC Method for the Determination of Calotropis gigantea in Bulk Material and Marketed Product
Authors: Hebballi Akshata P. , Pujar Basavaraja , Honnalli Suresh S. , Hiremath Sushmita I. , Menasinakai Akshata , Bakale Akash , Nadaf Sahil , M.V. Ashika , Vadavalli Sanjana 
Published: October 2024

Objective:
The objective of the present work is to develop and validate a novel, specific,
precise, and reliable method for the estimation of Calotropis gigantea in bulk and herbal
dosage form using the RP-HPLC method.

Methods:
RP-HPLC analysis was performed using a C18 column of dimension 150×4.6mm, 5
μ. The chromatography system comprised an Agilent 1220 Infinity II LC equipped with a
VWD detector and a 1220 Infinity II LC binary pump, wherein the instrument operation was
managed through Control Panel software at a flow rate of 0.5 ml/min. Methanol: water in the
ratio of 55:45 was used as the mobile phase, and the effluents were analyzed at 275nm. The
proposed method was validated for various parameters like linearity, precision, accuracy, robustness,
ruggedness, selectivity, limit of detection, limit of quantification, and assay as per the
ICH Q2(R1) guidelines.

Results:
Linearity was noted over a concentration range of 50-250 μg/ml with a correlation coefficient
of 0.999. The limit of detection (LOD) and limit of quantification (LOQ) were determined
to be 16.02 and 48.56 μg/mL, respectively. The % RSD for interday and intraday precision
studies was less than 2%, which was within the official RSD limit. Recovery analysis performed
using marketed formulation was found to be in the range of 97-105%.

Conclusion:
The method developed was validated according to the ICH guidelines. Hence, it is
evident that the developed method is novel, sensitive, precise, and reliable, and it can be successfully
applied to estimate Calotropis gigantea in bulk material and its herbal dosage form.
Variación intraespecífica en tolerancia al frío en progenies de Pinus pseudostrobus en dos sitios de evaluación
Authors: Barrera Ramírez Rubén , Vargas Hernández J. Jesús , Escobar Alonso Sebastian , Pérez Luna Alberto , López Upton Javier 
Published: October 2024

La tolerancia al frío tiene valor adaptativo en plantas perennes de clima templado-frío, por lo que es importante detectar variación genética en ella para árboles forestales. En dos ensayos de progenie de Pinus pseudostrobus establecidos en Pueblo Nuevo, Puebla (S1, 2853 m) y Teolocholco, Tlaxcala (S2, 2355 m), se determinó el índice de daño celular (ID) en plantas de cuatro años con una prueba de congelamiento, y se estimó su relación con el crecimiento en altura y variables bioclimáticas del sitio de origen de las familias en la región central de México. La tolerancia a frío se determinó con la pérdida de electrolitos (ID) a -15 °C durante 4 h. El análisis de varianza se realizó con Proc Mixed, usando un diseño de bloques completos al azar. El ID fue diferente (P<0.05) entre sitios y mayor en S1 (60.7%) que en S2 (50%); los parámetros genéticos indicaron que la tolerancia al frío está bajo control genético (h2f ≥0.50). El crecimiento en altura de las plantas en S2 fue mayor que en S1. Las variables bioclimáticas de mayor correlación (r≥0.55) con ID y el crecimiento en altura están relacionadas con la humedad, temperatura y precipitación de otoño-invierno. El daño por heladas en las familias varió entre sitios, lo que demuestra que existe interacción genotipo-ambiente asociada con resistencia al frío para algunas progenies; además de que los factores climáticos asociados con la humedad, la temperatura y precipitación también son importantes en la adaptación y crecimiento de las progenies de P. pseudostrobus
Pelatihan Penyusunan Soal Fisika berbasis Literasi Sains dalam Rangka mendukung Keberhasilan AKM Level 5 untuk Guru Fisika SMA Kabupaten Malang
Authors: Hanatan Ardiana , Khusaini Khusaini , Kusairi Sentot , Sulur Sulur 
Published: October 2024

Kegiatan pengabdian kepada masyarakat yang dilakukan bertujuan untuk memberikan pelatihan penyusunan soal Fisika berbasis literasi sains pada guru Fisika yang tergabung dalam Musyawarah Guru Mata Pelajaran Fisika (MGMP) Kabupaten Malang. Pelatihan tersebut dilakukan untuk mendukung keberhasilan Asesmen Kompetensi Minimum (AKM) untuk jenjang Sekolah Menengah Atas (SMA) atau level 5. Pelatihan dilakukan secara secara blended learning selama 32 jam yang diikuti oleh 40 peserta. Peserta memberikan respon positif terhadap pelatihan yang dilakukan. Adanya pelatihan yang dilakukan membuat para guru memiliki beragam rencana untuk melakukan asesmen pembelajaran Fisika di sekolah. Antusiasme para peserta yang tinggi tercermin dalam feedback yang diberikan bahwa diperlukan adanya pelatihan lanjutan.
Pengayaan Materi dan Pengembangan Kegiatan Praktikum Keanekaragaman Tumbuhan di SMA
Authors: Budiwati Budiwati - , Sudarsono Sudarsono , Ratnawati Ratnawati , Latifa Annisa 
Published: October 2024

AbstrakTujuan dari kegiatan PPM ini adalah untuk meningkatkan pengetahuan dan pengalaman guru dalam mengenali keanekaragaman tumbuhan, meningkatkan pengetahuan guru dalam mengembangkan kegiatan praktikum keanekaragaman tumbuhan, serta meningkatkan kemampuan guru dalam menyusun LKPD keanekaragaman tumbuhan. PPM ini menggunakan metode pretest, tutorial (tatap muka), workshop, dan postest. Kegiatan PPM ini diikuti oleh 14 orang guru Biologi dari MGMP Biologi SMA di Kabupaten Kulon Progo. Produk yang terkumpul sebanyak 14 hasil pretest dan postest yang menunjukkan pengetahuan guru mengenai keanekaragaman tumbuhan serta 9 bahan ajar LKPD yang menunjukkan kemampuan guru dalam menyusun LKPD. Hasil PPM menunjukkan bahwa 57,15% - 71,42% (N=14) peserta telah memahami materi yang diberikan dengan baik dan sebanyak 100% (N=9) peserta telah mampu menyusun bahan ajar LKPD dengan baik. Seluruh peserta memberikan respon positif terhadap kegiatan PPM yang telah dilaksanakan. Kata kunci: pengayaan, LKPD, praktikum, keanekaragaman tumbuhan
Workshop Penyusunan Instructional Design Berbasis Context Untuk Mengoptimalkan Kompetensi Pedagogi Dan Profesional Guru Ipa Di Era Society 5.0
Authors: Hastuti Purwanti Widhy , Wilujeng Insih , Anjarsari Putri , Anantanukulwong Roseleena 
Published: October 2024

Banyak tantangan yang akan dihadapi di era society 5.0, salah satunya adalah di bidang pendidikan yang berkaitan dengan sumber daya manusia. Guru harus melek teknologi untuk mengembangkan proses pembelajaran yang terus mengaktifkan siswa untuk melatih keterampilan yang dibutuhkan di era society 5.0 dan mengintegrasikan sumber belajar yang mengedepankan sumber belajar yang ada di sekitar siswa. Oleh karena itu, guru IPA dituntut untuk mengemas pembelajaran agar dapat mengikuti hakikat pembelajaran IPA dengan tidak mengesampingkan ketercapaian pembelajaran yang sesuai dengan hakikat IPA. Dalam pembelajaran, guru harus memberikan pengalaman belajar kontekstual yang bermakna bagi siswa. Salah satu cara yang dapat dilakukan adalah dengan menerapkan pembelajaran yang membantu siswa memahami materi ajar dan mengaitkannya dengan kehidupan sehari-hari atau yang lebih dikenal dengan pembelajaran berbasis konteks. Workshop ini merupakan diseminasi hasil penelitian tim pengabdian mengenai penerapan produk penelitian tentang pembelajaran berbasis konteks dalam pembelajaran IPA. Kegiatan pelatihan ini bertujuan untuk meningkatkan kompetensi pedagogik dan profesional guru di era society 5.0. Kegiatan yang dilakukan adalah mendiseminasikan hasil penelitian tim pengabdian tentang pengembangan perangkat berbasis konteks, meningkatkan kemampuan guru dalam mengembangkan desain pembelajaran khususnya yang berbasis konteks dan mengintegrasikan teknologi, serta membantu guru menganalisis kebutuhan untuk merancang pembelajaran berbasis konteks. Kegiatan PPM dilakukan melalui tutorial (tatap muka virtual), workshop, penugasan terstruktur, dan konsultasi. Penugasan terstruktur, yaitu penyusunan Desain Instruksional Berbasis Konteks yang mengintegrasikan sumber belajar kontekstual pada mata pelajaran IPA. Konsultasi tugas, yaitu konsultasi yang dilakukan melalui email/WA/HP terutama bagi peserta pelatihan yang mengalami kesulitan dalam menyelesaikan tugas terstruktur dan kegiatan evaluasi melalui angket, observasi, dan pendampingan. Hasil dari kegiatan ini menunjukkan bahwa guru-guru IPA SMP di Kabupaten Sleman Yogyakarta memiliki kompetensi pedagogik dan profesional dalam menyusun Desain Instruksional Berbasis Konteks dalam pembelajaran IPA. Selain itu, hasil kegiatan workshop menjadi bahan kajian, jurnal, atau referensi dalam kegiatan workshop serupa.
Assessing Visitor Expectations of AI Nursing Robots in Hospital Settings: Cross-Sectional Study Using the Kano Model
Authors: Kang Aimei , Wu XiuLi 
Published: October 2024

Abstract

Background
Globally, the rates at which the aging population and the prevalence of chronic diseases are increasing are substantial. With declining birth rates and a growing percentage of older individuals, the demand for nursing staff is steadily rising. However, the shortage of nursing personnel has been a long-standing issue. In recent years, numerous researchers have advocated for the implementation of nursing robots as a substitute for traditional human labor.

Objective
This study analyzes hospital visitors’ attitudes and priorities regarding the functional areas of artificial intelligence (AI) nursing robots based on the Kano model. Building on this analysis, recommendations are provided for the functional optimization of AI nursing robots, aiming to facilitate their adoption in the nursing field.

Methods
Using a random sampling method, 457 hospital visitors were surveyed between December 2023 and March 2024 to compare the differences in demand for AI nursing robot functionalities among the visitors.

Results
A comparative analysis of the Kano attribute quadrant diagrams showed that visitors seeking hospitalization prioritized functional aspects that enhance medical activities. In contrast, visitors attending outpatient examinations focused more on functional points that assist in medical treatment. Additionally, visitors whose purpose was companionship and care emphasized functional aspects that offer psychological and life support to patients.

Conclusions
AI nursing robots serve various functional areas and cater to diverse audience groups. In the future, it is essential to thoroughly consider users’ functional needs and implement targeted functional developments to maximize the effectiveness of AI nursing robots.
Use of AI in Mental Health Care: Community and Mental Health Professionals Survey
Authors: Cross Shane , Bell Imogen , Nicholas Jennifer , Valentine Lee , Mangelsdorf Shaminka , Baker Simon , Titov Nick , Alvarez-Jimenez Mario 
Published: October 2024

Abstract

Background
Artificial intelligence (AI) has been increasingly recognized as a potential solution to address mental health service challenges by automating tasks and providing new forms of support.

Objective
This study is the first in a series which aims to estimate the current rates of AI technology use as well as perceived benefits, harms, and risks experienced by community members (CMs) and mental health professionals (MHPs).

Methods
This study involved 2 web-based surveys conducted in Australia. The surveys collected data on demographics, technology comfort, attitudes toward AI, specific AI use cases, and experiences of benefits and harms from AI use. Descriptive statistics were calculated, and thematic analysis of open-ended responses were conducted.

Results
The final sample consisted of 107 CMs and 86 MHPs. General attitudes toward AI varied, with CMs reporting neutral and MHPs reporting more positive attitudes. Regarding AI usage, 28% (30/108) of CMs used AI, primarily for quick support (18/30, 60%) and as a personal therapist (14/30, 47%). Among MHPs, 43% (37/86) used AI; mostly for research (24/37, 65%) and report writing (20/37, 54%). While the majority found AI to be generally beneficial (23/30, 77% of CMs and 34/37, 92% of MHPs), specific harms and concerns were experienced by 47% (14/30) of CMs and 51% (19/37) of MHPs. There was an equal mix of positive and negative sentiment toward the future of AI in mental health care in open feedback.

Conclusions
Commercial AI tools are increasingly being used by CMs and MHPs. Respondents believe AI will offer future advantages for mental health care in terms of accessibility, cost reduction, personalization, and work efficiency. However, they were equally concerned about reducing human connection, ethics, privacy and regulation, medical errors, potential for misuse, and data security. Despite the immense potential, integration into mental health systems must be approached with caution, addressing legal and ethical concerns while developing safeguards to mitigate potential harms. Future surveys are planned to track use and acceptability of AI and associated issues over time.
Supervised and Unsupervised Screen Time and Its Association With Physical, Mental, and Social Health of School-Going Children in Dhaka, Bangladesh: Cross-Sectional Study
Authors: Kakon Shahria Hafiz , Soron Tanjir Rashid , Hossain Mohammad Sharif , Haque Rashidul , Tofail Fahmida 
Published: October 2024

Abstract

Background
Children’s screen time has substantially increased worldwide, including in Bangladesh, especially since the pandemic, which is raising concern about its potential adverse effects on their physical, mental, and social health. Parental supervision may play a crucial role in mitigating these negative impacts. However, there is a lack of empirical evidence assessing the relationship between parental screen time supervision and health outcomes among school children in Dhaka, Bangladesh.

Objective
We aimed to explore the association between supervised and unsupervised screen time on the physical, mental, and social health of school-going children in Dhaka, Bangladesh.

Methods
We conducted a cross-sectional descriptive study between July 2022 and June 2024. A total of 420 children, aged 6‐14 years, were enrolled via the stratified random sampling method across three English medium and three Bangla medium schools in Dhaka. Data were collected through a semistructured questionnaire; anthropometry measurements; and the Bangla-validated Strength and Difficulties Questionnaire (SDQ), Pittsburgh Sleep Quality Index (PSQI) Scale, and Spencer Children Anxiety Scale (SCAS).

Results
A total of 234 out of 420 students (56%) used digital screen devices without parental supervision. We did not find a substantial difference in the duration of the daily mean use of digital devices among the supervised students (4.5 hours, SD 2.2 hours) and the unsupervised students (4.6 hours, SD 2.4 hours). According to the type of school, English medium school children had a mean higher screen time (5.46 hours, SD 2.32 hours) compared to Bangla medium school children (3.67 hours, SD 2.00 hours). Headache was significantly higher among the unsupervised digital screen users compared to those who used digital screens with parental supervision (175/336 students, 52.1% versus 161/336 students, 47.9%; P<.003). Moreover, students who used digital screens without parental supervision had poor quality of sleep. Behavioral problems such as conduct issues (119/420 students, 28.3%) and peer difficulties (121/420 students, 28.8%) were observed among the participants. However, when comparing supervised and unsupervised students, we found no statistically significant differences in the prevalence of these issues.

Conclusions
The findings of the study showed that the lack of screen time supervision is associated with negative health effects in children. The roles of various stakeholders, including schools, parents, policy makers, and students themselves, are crucial in developing effective guidelines for managing screen use among students. Further research is needed to demonstrate causal mechanisms; identify the best interventions; and determine the role of mediators and moderators in households, surroundings, and schools.