bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of land-use/cover change on water quality in the Mindu Dam drainage, Tanzania
Authors: Gobry Josephine John , Twisa Sekela Simon , Ngassapa Faustin , Kilulya Kessy F. 
Published: April 2023

Abstract
Water pollution caused by land-use/cover change is one of the most pressing problems facing both industrialized and developing countries. Freshwater quality deterioration suggests the collective outcomes of natural courses and alterations in land-use/cover. Understanding the correlation among land-use/cover and water quality parameters is vital for future water quality management. In this work, land-use/cover pattern and its effect on water quality in the Mindu Dam drainage area were analysed using Remote Sensing (RS) and Geographical Information System (GIS) techniques together with cellular automata–Markov model. The land-use/cover images between 1990 and 2020 were used to assess historical and spatial change of land-use/cover change, and projected for 2030 and 2040. We discovered that the dynamics of land use and land cover during the study period were significant. A strong correlation was revealed between changes in the land-use/cover and water quality parameters. Furthermore, a strong correlation exists between cultivated land and measured nutrient (nitrate and phosphate) and chlorophyll-a concentration. The natural vegetation buffer around Mindu Dam should be sufficient to prevent long-term water quality degradation from agricultural runoff in order to manage water quality sustainably. Therefore, land-use/cover management practices must be considered for sustainable resource management and water quality monitoring.
Antibacterial Activity of Origanum vulgare and Rosmarinus officinalis standardized extracts Against Curtobacterium and Xanthomonas
Authors: Vaz Priscila Dias da Silva , Souza Waléria Ramos Nogueira de , Wendland Adriane , Oliveira Matheus Gabriel de , Cirilo Hérica Nubia Cardoso , Cortes Marcio Vinicius de Carvalho Barros , Bara Maria Teresa Freitas 
Published: April 2023

Diseases caused by Curtobacterium and Xantomonnas species represent an agricultural problem in crops and can generate economic impacts on the commercialization of seeds and food. Origanum vulgare L. (oregano) and Rosmarinus officinalis L. (rosemary) have rosmarinic acid and others phenolics that can lead to the control of phytopathogenic bacteria in common bean (Phaseolus vulgaris L.). This study aimed to evaluate the in vitro and in vivo antibacterial activity of O. vulgaris and R. officinalis extracts, standardized in rosmarinic acid, against Curtobacterium flaccumfaciens pv. flaccumfaciens, Xanthomonas axonopodis pv. phaseoli, Xanthomonas fuscans subsp. fuscans and Xanthomonas sp. The antibacterial effect of the extracts in bean seed was also investigated. The content of rosmarinic acid was 8.55 % for O. vulgare and 16.30 % for R. officinalis extract. It was verified the complete in vitro inhibition of the bacteria studied by both extracts at 0.8% (w/w) with exception of Xanthomonas axonopodis pv. phaseoli BRM 025302 that was completely inhibited at 1.2% (w/w) of oregano. In addition, no symptom of phytotoxicity were noted in detached bean leaves treated with them. Under greenhouse conditions, some reduction on severity of Curtobacterium wilt by both extracts at 1% (w/w) was noted to bean cultivars BRS Sublime and BRS Estilo. Under the experimental conditions these extracts were not efficient to control the common bacterial blight caused by X. axonopodis pv. phaseoli. Both extracts are promising in the treatment of seeds, specially in related to contamination by Fusarium spp., whose percentage decreased on average an average from 94% to 10%. In addition, these bean seeds maintained the germination percentage adequate to that required by legislation. Further studies must be conducted to better investigate the potential of these standardized extracts as a bioproduct for agriculture.
A Cyclic Tripeptide-based Human SIRT3 Inhibitor
Authors: Wu Bo , Liu Tianli , Zheng Weiping 
Published: April 2023

Background:
Among the seven human sirtuins SIRT1-7, SIRT3 is not lesser functionally understood.
However, the identification of its inhibitors has not been quite a success.

Objective:
In the current study, we intended to see if we were able to develop cyclic tripeptide-based human
SIRT3 inhibitors that would harbor the catalytic mechanism-based pan-SIRT1/2/3 inhibitory warhead
Ne-thioacetyl-lysine.

Methods:
In the current study, we prepared the corresponding N-terminus-to-side chain cyclic analog of
two of our previously reported linear tripeptidic human SIRT3 inhibitors whose chemical structures both
harbor the catalytic mechanism-based pan-SIRT1/2/3 inhibitory warhead N(epsilon)-thioacetyl-lysine at
the central position and subjected the analogs to the same sirtuin inhibition assay under the same assay
condition as those employed previously in our laboratory for the two parent linear tripeptidic SIRT3 inhibitors.

Results:
We found that analog 2 exhibited an enhanced SIRT3 inhibitory potency than its linear tripeptidic
parent (i.e. compound 2a) and displayed a SIRT3 inhibitory IC50 value of ~340 nM which is smaller
than its inhibitory IC50 values against other sirtuins with the following folds: ~2-fold versus SIRT1, ~7.7-
fold versus SIRT2, and >68-353-fold versus SIRT5-7.

Conclusion:
The successful identification of the human SIRT3 inhibitor 2 in the current study would help
the further functional dissection and pharmacological exploitation of the SIRT3 deacetylation reaction.
Effect of Notch Signal Pathway on Steroid Synthesis Enzymes in TM3 Cells
Authors: Zhang Hongdan , Wang Wei , Wu Zaichao , Zheng Yuxiang , Li Xiao , Han Suo , Wang Jing , Zhang Chunping 
Published: April 2023

Background:
Studies have indicated that the conservative Notch pathway contributes
to steroid hormone synthesis in the ovaries; however, its role in hormone synthesis of the testis
remains unclear. We have previously reported Notch 1, 2, and 3 to be expressed in murine Leydig
cells and that inhibition of Notch signaling caused G0/G1 arrest in TM3 Leydig cells.

Methods:
In this study, we have further explored the effect of different Notch signal pathways on key steroidogenic enzymes in murine Leydig cells. TM3 cells were treated with Notch signaling pathway inhibitor MK-0752, and different Notch receptors were also overexpressed in TM3 cells.

Results:
We evaluated the expression of key enzymes of steroid synthesis, including p450 choles-terol side-chain cleavage enzyme (P450Scc), 3β-hydroxysteroid dehydrogenase (3β-HSD) and steroidogenic acute regulatory protein (StAR), and key transcriptional factors for steroid synthesis, including steroidogenic factor 1 (SF1), GATA-binding protein 4 (GATA4) and GATA6.

Conclusion:
We found the level of P450Scc, 3β-HSD, StAR and SF1 to be decreased after treat-ment with MK-0752, while overexpression of Notch1 up-regulated the expression of 3β-HSD, P450Scc, StAR and SF1. MK-0752 and overexpression of different Notch members had no influ-ence on the expression of GATA4 and GATA6. In conclusion, Notch1 signaling may contribute to the steroid synthesis in Leydig cells through regulating SF1 and downstream steroidogenic en-zymes (3β-HSD, StAR and P450Scc).
Back-propagation ANN to Predict Cleanliness and Quality of Cotton Spinning
Preparatory Output: A Comprehensive Research
Authors: Shaikh Tasnim Nisarahmed , Pujara Hardik 
Published: April 2023

Background:
Modern spinning preparatory has undergone drastic technological changes, but still, individual’s expertise-based decisions govern the complex and non-linear multivariant relationships prevailing amongst raw material (cotton) variables, machine variables, process variables (waste), and product (card sliver) quality. The scientifically precise prediction regarding the cleanliness and quality of card sliver and waste control for the given inputted cotton variables processed on the state-of-the-art machinery setup without waiting for the production and testing of card sliver is still impossible.

Methods:
The present work describes the use of Aritificial Neural Networks (ANN) for ruling out these limitations on scientific grounds. A complex system targeted at ANN was developed using the "newff" function on the mill's five-year database. Single-group ANN was initially designed to determine the influence of inherent variations in raw cotton fibre properties and trash content on blow room and card performance. A multi-group approach of ANN was developed at a later stage to define the influence of complex interactions amongst various fibre properties on three main quality measures considered at blow room and carding, viz., i) influence of blow room and card on fibre length properties, ii) fibre damage at blow room or improvement at card, and iii) degree of cleanliness of the output material.

Results:
Reverse modelling for both groups was also successfully designed to demarcate feed cotton quality and cleanliness requirements for targeted blow room or card cleaning performance.

Conclusion:
A high level of positive endurance was observed for all ANNs. Multigroup networking has proven to be more precise than single group networking.
Review of Recent Patents on Smart Bearing
Authors: Pan Chengyi , Cao Yuanfei , Yan Yubin , Shao Ruinan 
Published: April 2023

Background:
Smart bearing is based on the traditional bearing, which is integrated by sensing devices and control devices, formating a unique bearing structure unit. It uses information processing, automatic control, and other technologies to achieve real-time online monitoring of bearing operating conditions, fault detection, and state control. Compared with ordinary bearings, smart bearings have the characteristics of self-awareness, self-decision, and self-regulation. By analyzing the composition of various types of smart bearings and their working principles, it is beneficial to prospect the future development direction of bearings.

Objective:
We analyze and organize the patents on smart bearings in recent years, summarize the problems encountered in the development of smart bearings, and propose the development direction of smart bearings in the future to provide a reference for future scientific research.

Methods:
This paper reviews the patents related to smart bearings and analyzes the composition and structure of smart bearings. The main smart bearings include rolling bearing, sliding bearing, magnetic bearing, and rubber bearing. The principle and structure of these bearings are analyzed. Their advantages and shortcomings are discussed.

Results:
Through the analysis of relevant patents and papers on smart bearings, the current development status and problems of smart bearings are summarized, the future design of smart bearings is proposed, and the research ideas and directions are proposed.

Conclusion:
The development of smart bearings is conducive to the timely detection of bearing conditions in the operation process. Except for detection, smart bearings have the functions of judgment, feedback, processing, etc. There are many factors that interfere with the accuracy of the smart bearing judgment and information transfer, so it is necessary to improve the structure and working principle of smart bearings through a variety of measures. In the future, more smart bearings will be invented.
Public Awareness and Stigmatizing Attitudes toward People Living with Human Immunodeficiency Virus Acquired Immune Deficiency Syndrome in Saudi Arabia
Authors: Alwazzeh Marwan J. , Kabbani Abdullah H. , Alghamdi Muhannad A. , Alharbi Khalid I. , Qoqandi Abdullah A. , Alsomali Abdulrazaq I. , Fiore Jose Ramon 
Published: April 2023

Background:
Recently, there have been efforts to increase HIV/AIDS education and awareness programs to reduce the stigmatization and discrimination of people living with human immunodeficiency virus/acquired immune deficiency syndrome (PLWHA). However, it is essential to understand that these efforts must be ongoing and sustained to be effective.

Objective:
This study aimed to assess the Saudi population’s awareness and stigmatizing attitudes toward PLWHA.

Methods:
This is a cross-sectional study on individuals (patients or families of patients) who attended “King Fahad Hospital of The University (KFHU)”. The study was conducted between September 1st and December 31st, 2018. Each participant provided informed consent, and data were collected through an informative, validated, anonymous, self-administrated questionnaire. The questionnaire was designed by experts and included all the data regarding demographic information, assessment of knowledge of HIV transmission, general awareness of HIV, assessment of attitudes toward PLWHA, etc. The collected data were analyzed using the SPSS version 22.

Results:
The majority of the participants were aware that HIV might be spread by receiving blood from an infected person, sharing a needle or syringe, and receiving organs from an infected person. There is a strong correlation between HIV transmission knowledge with age (p = 0.001), marital status (p = 0.001), an education level (p = 0.001), and economic status (p = 0.049). The study indicated negative stigmatizing attitudes toward PLWHA.

Conclusion:
This study highlights significant public awareness gaps about HIV/AIDS and stigmatizing attitudes of the public toward HIV/AIDS.
Consensus Guidelines for Teledermatology: Scoping Review
Authors: Cummins Mollie R , Ong Triton , Ivanova Julia , Barrera Janelle F , Wilczewski Hattie , Soni Hiral , Welch Brandon M , Bunnell Brian E 
Published: April 2023

Background
Consensus guidelines and recommendations play an important role in fostering quality, safety, and best practices, as they represent an expert interpretation of the biomedical literature and its application to practice. However, it is unclear whether the recent collective experience of implementing telemedicine and the concurrent growth in the evidence base for teledermatology have resulted in more robust guidance.

Objective
The objective of this review was to describe the extent and nature of currently available guidance, defined as consensus guidelines and recommendations available for telemedicine in dermatology, with guidance defined as consensus or evidence-based guidelines, protocols, or recommendations.

Methods
We conducted a single-reviewer scoping review of the literature to assess the extent and nature of available guidance, consensus guidelines, or recommendations related to teledermatology. We limited the review to published material in English since 2013, reflecting approximately the past 10 years. We conducted the review in November and December of the year 2022.

Results
We identified 839 potentially eligible publications, with 9 additional records identified through organizational websites. A total of 15 publications met the inclusion and exclusion criteria. The guidelines focused on varied topics and populations about dermatology and skin diseases. However, the most frequent focus was general dermatology (8/15, 53%). Approximately half of the telemedicine guidance described in the publications was specific to dermatology practice in the context of the COVID-19 pandemic. The publications were largely published in or after the year 2020 (13/15, 87%). Geographical origin spanned several different nations, including Australia, the United States, European countries, and India.

Conclusions
We found an increase in COVID-19–specific teledermatology guidance during 2020, in addition to general teledermatology guidance during the period of the study. Primary sources of general teledermatology guidance reported in the biomedical literature are the University of Queensland’s Centre for Online Health and Australasian College of Dermatologists E-Health Committee, and the American Telemedicine Association. There is strong evidence of international engagement and interest. Despite the recent increase in research reports related to telemedicine, there is a relative lack of new guidance based on COVID-19 lessons and innovations. There is a need to review recent evidence and update existing recommendations. Additionally, there is a need for guidance that addresses emerging technologies.
Particle Swamp Optimized -Physics-Informed Deep Learning for Heterogeneous Oil and Gas Underground Reservoir Pressure Management.
Authors:   1Department of Computer Science, College of Education, Gidan-Waya Kaduna, Nigeria, 2,3,4,5Department of Computer Science, Kaduna State University, Kaduna, Nigeria, E-mails: thomaslass2002@gmail.com, samson.isaac@kasu.edu.ng, meenatu02@gmail.com, zarasakanau@yahoo.com, hamidatuabdulkadir@gmail.com Phones: +2349128759750, Barna Thomas Lass, ,   +2348035370205,   +2348032880130,   +2348037077346,   +2348169829895, Isaac Samson , Isa Amina , Sakanau Zara , Abdulkadir Hamidatu 
Published: April 2023

In recent years, Particle Swarm Optimization (PSO) has been integrated with machine learning algorithms, such as deep learning, to create powerful hybrid methods that can tackle complex optimization problems more effectively. In the domain of oil and gas reservoir management, underground pressure management is crucial to maximize the yield and efficiency of the reservoir. However, the heterogeneity of the reservoir, along with uncertainties in its properties, makes pressure management a complex and challenging task. To address this issue, researchers have proposed Physics-Informed Deep Learning (PIDL) techniques that incorporate domain-specific knowledge, such as the governing physical equations, into the deep learning framework. Particle Swarm Optimized-Physics-Informed Deep Learning (PSO-PIDL) is a novel hybrid approach that combines PSO with PIDL to optimize the pressure management of heterogeneous oil and gas underground reservoirs. In this approach, the PSO algorithm is used to find the optimal solution for the PIDL-based model that incorporates the governing physical equations of the reservoir. PSO-PIDL can effectively handle the uncertainties and heterogeneity of the reservoir, while also incorporating the physical constraints of the problem. Overall, PSO-PIDL is a promising approach for optimizing the pressure management of oil and gas reservoirs. It can help reduce the operational costs and improve the efficiency of the reservoir, while also ensuring the sustainable use of natural resources. Keywords:	Physics-Informed Deep Learning, Particle Swarm Optimization, Bidirectional Long-Short-Term-Memory, Heterogeneous Reservoir, DuPont Finite Element Heat and Mass Transfer Code
Klasterisasi Puskesmas dengan K-Means Berdasarkan Data Kualitas Kesehatan Keluarga dan Gizi Masyarakat
Authors: Prakoso Bakhtiyar Hadi , Rachmawati Ervina , Mudiono Demiawan Rachmatta Putro , Vestine Veronika , Suyoso Gandu Eko Julianto 
Published: April 2023

One of the fundamental principles followed by the Jember Health Office for decision-making is data. Data plays a crucial role in the decision-making process. Raw data is more difficult to interpret and needs to be analyzed. Clustering is one of the techniques used for analysis. This study discusses using K-Means to cluster Public Health Center data based on AKI, AKB, and stunting prevalence. The data is processed by reducing dimensions and normalizing them. The clustering process is performed using the K-Means method, where the maximum k-value is obtained by calculating WCSS. The clustering process results in three clusters of Public Health Centers in the Jember Regency. These clusters can serve as a reference for the Jember Health Office to formulate family health and community nutrition quality policies.Keywords: data mining, K-Means, clustering, Maternal Mortality Rate, Infant Mortality Rate, the prevalence of stunting

Salah satu dasar pengambilan kebijakan oleh Dinas Kesehatan Jember adalah data. Data memiliki peran dalam proses pengambilan keputusan. Data mentah yang didapatkan lebih sulit untuk diinterpretasikan sehingga diperlukan analisis terhadap data tesebut. Salah satu analisis yang dapat digunakan adalah teknik klasterisasi. Padapenelitian ini akan dibahas penggunaan K-Means untuk klasterisasi data puskesmas berdasarkan AKI, AKB, dan prevalensi stunting. Data diproses dengan melakukan reduksi dimensi dan normalisasi. Proses klasterisasi dilakukan dengan metode K-Means dimana nilai k maksimal diperoleh dengan menghitung WCSS. Adapun hasil proses klasterisasi didapatkan tiga kelompok klaster puskesmas yang terdapat di Kabupaten Jember. Hasil klasterisasi dapat digunakan sebagai referensi Dinas Kesehatan Jember dalam mengambil kebijakan terkait kualitas kesehatan keluarga dan gizi masyarakatKata Kunci: data mining, K-Means, klasterisasi, Angka Kematian Ibu, Angka Kematian Bayi, prevalensi stunting
Implementasi Algoritma K-Nearest Neighbour dalam Menganalisis Sentimen Terhadap Program Merdeka Belajar Kampus Merdeka (MBKM)
Authors: Sartika Dewi 
Published: April 2023

K-Nearest Neighbor Algorithm Implementation in sentiment analysis towards Merdeka Belajar Kampus Merdeka (MBKM) Program. Merdeka Belajar Kampus Merdeka (MBKM) is a program that supports students to improve their skills by having direct experience in the work environment to prepare for competition and a future career. MBKM program has been implemented by Indonesia's Ministry of Education, Culture, Research, and Technology (Kemendikbudristek) since 2020. Every policy needs to be evaluated; a simple evaluation can be done through sentiment analysis to determine public responses to the MBKM program. The results are used as suggestions for program improvement. Sentiment analysis is done by applying the Natural Language Processing (NLP) algorithm to process crawled data from Twitter, then classified using the K-NN Algorithm. Based on the results, the sentiment is neutral. This illustrates that people are only partially interested in the MBKM program policy. The accuracy of the classification model using the K-NN algorithm is 95%, and an F1-score value of 0.96 for the classification model with a ratio of 80% training data and 20% test data.Keywords: MBKM, NLP, K-NN, F1-Score

Program Merdeka Belajar Kampus Merdeka (MBKM) merupakan suatu kebijakan dalam mendukung pemberian kebebasan terhadap mahasiswa untuk mengasah kemampuan dengan merasakan langsung pengalaman di dunia kerja sebagai bekal untuk menghadapi persaingan dan persiapan berkarir di masa mendatang. Program MBKM mulai diberlakukan oleh Kementerian Pendidikan Kebudayaan Riset dan Teknologi (Kemendikbudristek) Republik Indonesia sejak tahun 2020. Setiap kebijakan tentunya perlu dievaluasi, evalusi sederhana dapat dilakukan melalui analisis sentimen untuk mengetahui tanggapan masyarakat mengenai program MBKM. Hasilnya digunakan sebagai saran perbaikan untuk pengembangan program. Analisis sentimen dilakukan dengan menerapkan algoritma Natural Language Processing (NLP) untuk memproses data hasil crawling dari Twitter, selanjutnya diklasifikasikan menggunakan algoritma K-NN. Berdasarkan hasil analisis diperoleh bahwa sentimen masyarakat bersifat netral. Hal ini menggambarkan bahwa masyarakat tidak sepenuhnya tertarik terhadap kebijakan program MBKM, sedangkan untuk tingkat akurasi model klasifikasi menggunakan algoritma K-NN sebesar 95% dan nilai F1-score sebesar 0,96 untuk model klasifikasi dengan perbandingan 80% data latih dan 20% data uji.Kata Kunci: MBKM, NLP, K-NN, F1-Score