bluuebunny/crossref_metadata_2025_split huggingface dataset:
CLASSIFICATION OF FAKE NEWS IN INDONESIAN LANGUAGE USING SUPPORT VECTOR MACHINE METHOD
Authors: Tandiano Andreas Halim , Jollyta Deny 
Published: April 2024

Abstract: Since information and communication technology has become ingrained in our daily lives, it has become easier to access information. However, there are some concerns. One of them is about fake news. The aim of this study is to develop an Indonesian system for detecting false news by utilizing news headlines. The methods used are linear kernel support vector ma- chine and n-gram. According to the findings of the performance test that was carried out, the linear kernel support vector machine model employing the term frequency inverse document frequency unigram feature performs better than utilizing bigram. The precision value generated from the model performance test is 1.00. This means that the degree of accuracy in matching the requested information regarding fake news detection with the answers provided by the system is very good. Then the recall value generated is 0.99. This means the linear kernel support vector machine model using unigram news features is very effective for detecting fake news according to the text classification approach. Keywords: classification; fake news; n-gram; support vector machine Abstrak: Dengan adanya integrasi teknologi informasi dan komunikasi dalam kehidupan mem- buat kemudahan dalam mengakses informasi. Walaupun demikian, terdapat kekhawatiran akan beberapa hal. Salah satu di antaranya adalah berita palsu. Tujuan penelitian ini adalah merancang sistem deteksi berita palsu berbahasa Indonesia berdasarkan judul berita. Metode yang digunakan adalah Support Vector Machine kernel linier dan n-gram. Berdasarkan hasil uji performa, model Support Vector Machine kernel linier yang menggunakan fitur term frequency inverse document frequency unigram menunjukkan kinerja yang lebih baik dibandingkan bi- gram. Nilai precision yang dihasilkan dari uji performa model sebesar 1,00. Ini berarti derajat akurasi dalam mencocokkan informasi yang diminta mengenai deteksi berita palsu dengan ja- waban yang diberikan oleh sistem sangat baik. Kemudian nilai recall yang dihasilkan sebesar 0,99. Ini berarti model Support Vector Machine kernel linier dengan menggunakan fitur berita unigram sangat efektif untuk mendeteksi berita palsu menurut pendekatan teks klasifikasi. Kata kunci: klasifikasi; berita palsu; n-gram; support vector machine
IMPLEMENTATION OF MAUT METHOD GRANTING BUSINESS LICENSES IN TANJUNGBALAI CITY
Authors: Raisita Tanya , Hambali Hambali , Maulana Cecep 
Published: April 2024

Abstract: Establishing a business or industrial location must obtain permission from the government which aims to protect the surrounding community from possible disturbances or pollution resulting from the industry. Therefore, in order to achieve this, it is necessary to have a system that automatically provides accurate and fast decisions in determining which companies or industries are worthy of being granted a business license. The aim of this research is to build a decision support system in determining permits to disturb business or industrial premises using the Multi-Attribute Utility Theory (MAUT) method. The data analysis technique used is the MAUT method to determine the final decision in granting a disturbance permit to a company or industry. The sample or training data consists of 20 names in the Tanjungbalai City area. This system is tested with a black box which aims to find out that all components in the system are running well. Our findings show that the system we have created is appropriate based on the results of the analysis using the MAUT method. Apart from that, the results of black box testing show that all components in this system are valid and functioning well.Keywords: granting business licenses; maut method; web based. Abstrak: Mendirikan tempat usaha atau industri harus mendapatkan izin dari pemerintah yang bertujuan untuk melindungi masyarakat sekitar agar terlindungi dari kemungkinan timbulnya gangguan atau polusi yang diakibatkan dari industry tersebut. Oleh karena itu, demi tercapainya hal tersebut perlu adanya sistem yang secara otomatis memberikan keputusan secara akurat dan cepat dalam menentukan suatu perusahaan atau industry mana yang layak diberikan izin usaha. Tujuan penelitian ini adalah untuk membangun sistem pendukung keputusan dalam menentukan izin gangguan tempat usaha atau industri menggunakan metode Multi-Attribute Utility Theory (MAUT). Teknik analisis data yang digunakan menggunakan metode MAUT untuk menentukan keputusan akhir dalam memberikan izin gangguan kepada perusahaan atau industri. Sampel atau data training yang berjumlah 20 nama di wilayah Kota Tanjungbalai. Sistem ini diuji dengan black box yang bertujuan untuk mengetahui semua komponen pada sistem sudah berjalan dengan baik. Hasil penelitian menunjukkan bahwa sistem yang telah kami buat sudah sesuai berdasarkan hasil analisis menggunakan metode MAUT. Selain itu, hasil black box testing menunjukkan bahwa semua komponen pada sistem ini sudah valid dan berfungsi dengan baik.Kata kunci: berbasis web; metode maut; pemberian izin usaha.
Nanozyme-based sensing of dopamine using cobalt-doped hydroxyapatite nanocomposite from waste bones
Authors: Nishan Umar , Jabeen Nighat , Badshah Amir , Muhammad Nawshad , Shah Mohibullah , Ullah Irfan , Afridi Saifullah , Iqbal Jibran , Asad Muhammad , Ullah Riaz , Ali Essam A. , Ahmed Sarfraz , Ojha Suvash Chandra 
Published: April 2024

Dopamine is one of the most important neurotransmitters and plays a crucial role in various neurological, renal, and cardiovascular systems. However, the abnormal levels of dopamine mainly point to Parkinson’s, Alzheimer’s, cardiovascular diseases, etc. Hydroxyapatite (HAp), owing to its catalytic nature, nanoporous structure, easy synthesis, and biocompatibility, is a promising matrix material. These characteristics make HAp a material of choice for doping metals such as cobalt. The synthesized cobalt-doped hydroxyapatite (Co-HAp) was used as a colorimetric sensing platform for dopamine. The successful synthesis of the platform was confirmed by characterization with FTIR, SEM, EDX, XRD, TGA, etc. The platform demonstrated intrinsic peroxidase-like activity in the presence of H2O2, resulting in the oxidation of 3,3′,5,5′-tetramethylbenzidine (TMB). The proposed sensor detected dopamine in a linear range of 0.9–35 μM, a limit of detection of 0.51 µM, limit of quantification of 1.7 µM, and an R2 of 0.993. The optimization of the proposed sensor was done with different parameters, such as the amount of mimic enzyme, H2O2, pH, TMB concentration, and time. The proposed sensor showed the best response at 5 mg of the mimic enzyme, pH 5, 12 mM TMB, and 8 mM H2O2, with a short response time of only 2 min. The fabricated platform was successfully applied to detect dopamine in physiological solutions.
Design and application of a point-of-care testing system for triple detection of SARS-CoV-2, influenza A, and influenza B
Authors: Yang Huan , Zhang Xiaoming , Li Yating , Deng Jing , Liu Zhongming , Chen Qiyue , Zhang Haiyan 
Published: April 2024

To mitigate the continued impact of SARS-CoV-2, influenza A, and influenza B viruses on human health, a smartphone-based point-of-care testing (POCT) system was designed to detect respiratory pathogens through a nucleic acid test. This compact, light-weight, highly automated, and universal system enables the differential diagnosis of SARS-CoV-2, influenza A, and influenza B in approximately 30 min in a single-tube reaction. Numerous hospitals and disease control and prevention center assessed the triple POCT system’s detection threshold, sensitivity, specificity, and stability, and have concluded that all the assessments were comparable to those of fluorescent quantitative polymerase chain reaction (PCR)-based testing. The triple POCT system is suitable as an onsite rapid-diagnosis device, as well as for pathogen screening at airports and customs.
The integrated microfluidic photocatalytic planar reactor under continuous operation
Authors: Ge Xue-hui , Wei Nanjie , Hu Xinyue , Xie Qinyin , Wang Xiaoda , Li Ling , Qiu Ting 
Published: April 2024

An integrated microfluidic planar reactor is essential for achieving efficient and enhanced photocatalytic water treatment. Optimization of catalysts is an area of intense study owing to the need to enhance the performances of microreactors. A high-efficiency photocatalytic microreactor is presented here by combining a planar microreactor with a high-efficiency photocatalyst. TiO2 nanoparticles doped with Y and Yb were prepared to improve the photocatalytic reaction efficiency. First, better performance is achieved with the Y, Yb/TiO2 and TiO2 microreactors than conventional bulk reactors because of good photodegradation and a high reaction rate. Then, the Y, Yb/TiO2 film microreactor exhibits not only efficient catalytic activity with UV light but also higher photocatalytic activity under visible light irradiation than that achieved by a TiO2 film microreactor. The reaction rate constant of the Y, Yb/TiO2 film microreactor is approximately 0.530 s–1, which is twice that of the TiO2 film microreactor. Moreover, the performances under continuous and intermittent reactions are compared to evaluate the stability of the microreactor, thereby building the foundation for practical application of continuous water treatment in the microreactor.The planar microreactor provides a convenient platform for studying photodegradation under various conditions, such as different temperatures, flow rates, light irradiation (UV and Vis), and reaction modes (continuous and intermittent).
Development of rapid nucleic acid testing techniques for common respiratory infectious diseases in the Chinese population
Authors: Zhi Shenshen , Wu Wenyan , Ding Yan , Zhang Yuanyuan , Pan Liyan , Liu Guo , Li Wei 
Published: April 2024

Background: Most respiratory viruses can cause serious lower respiratory diseases at any age. Therefore, timely and accurate identification of respiratory viruses has become even more important. This study focused on the development of rapid nucleic acid testing techniques for common respiratory infectious diseases in the Chinese population.Methods: Multiplex fluorescent quantitative polymerase chain reaction (PCR) assays were developed and validated for the detection of respiratory pathogens including the novel coronavirus (SARS-CoV-2), influenza A virus (FluA), parainfluenza virus (PIV), and respiratory syncytial virus (RSV).Results: The assays demonstrated high specificity and sensitivity, allowing for the simultaneous detection of multiple pathogens in a single reaction. These techniques offer a rapid and reliable method for screening, diagnosis, and monitoring of respiratory pathogens.Conclusion: The implementation of these techniques might contribute to effective control and prevention measures, leading to improved patient care and public health outcomes in China. Further research and validation are needed to optimize and expand the application of these techniques to a wider range of respiratory pathogens and to enhance their utility in clinical and public health settings.
Factors associated with anxiety about handling contaminated patients during a nuclear disaster among disaster medical assistant teams in Japan: a cross-sectional study
Authors: Shibata Hisami , Yamaguchi Takumi , Yamada Yumiko , Shinkawa Tetsuko , Urata Hideko , Matsunari Yuko 
Published: April 2024

IntroductionJapanese Disaster Medical Assistance Teams (DMATs) are pivotal in disaster response, especially during nuclear crises. The objective of this study was to identify factors associated with anxiety among Japanese DMAT personnel when handling contaminated patients during nuclear disasters.Materials and methodsIn this cross-sectional study, 609 Japanese DMAT members from Kyushu and Okinawa, Japan, were surveyed. Multivariate binomial logistic regression was used to determine anxiety predictors.ResultsOf the 276 respondents, 77.2% expressed anxiety about managing contaminated patients. Women and younger team members expressed the highest level of anxiety associated with handling contaminated patients during nuclear disasters.ConclusionThis study revealed heightened anxiety among female and younger Japanese DMAT personnel regarding the handling of contaminated patients during nuclear disasters. Targeted training addressing these concerns is essential for effective disaster response.
An improved two-beat deadbeat synchronous predictive current control strategy for MMC based on Newton interpolation method
Authors: Cheng Yuan , Zhang Hui , Xing Jing , Xiao Zihan 
Published: April 2024

Modular Multilevel Converter (MMC) is widely used in applications such as High Voltage Direct Current (HVDC) transmission, AC/DC power conversion centers, and large-scale power quality management in electrical grids due to its highly modular structure, strong redundancy and low harmonic content in AC output. The application of the traditional deadbeat predictive current control to MMC enhances the fast tracking ability of the output current, but it still has the problems of low output current accuracy and high dependence on bridge arm inductor. Based on this, this paper proposes an improved two-beat deadbeat synchronous predictive current control based on Newton interpolation method. By improving the two-beat deadbeat synchronous predictive current control strategy, the accuracy of the output current can be further improved and its fast tracking ability can be enhanced. Newton interpolation is introduced to improve the accuracy of the output current while reducing the dependence on the bridge arm inductor. The results show that the control strategy proposed in this paper reduces the output current THD by 2.88% compared with the two-beat deadbeat predictive current control, thus improving the accuracy; the bridge arm inductor value is reduced by 1.28%, thus reducing the dependence; and under the transient environment, the output current can be tracked to its predicted reference value 843 μs in advance, which enhances the fast tracking capability.
Identification of immune-related biomarkers for glaucoma using gene expression profiling
Authors: Wang Dangdang , Pu Yanyu , Tan Sisi , Wang Xiaochen , Zeng Lihong , Lei Junqin , Gao Xi , Li Hong 
Published: April 2024

Introduction: Glaucoma, a principal cause of irreversible vision loss, is characterized by intricate optic neuropathy involving significant immune mechanisms. This study seeks to elucidate the molecular and immune complexities of glaucoma, aiming to improve our understanding of its pathogenesis.Methods: Gene expression profiles from glaucoma patients were analyzed to identify immune-related differentially expressed genes (DEGs). Techniques used were weighted gene co-expression network analysis (WGCNA) for network building, machine learning algorithms for biomarker identification, establishment of subclusters related to immune reactions, and single-sample gene set enrichment analysis (ssGSEA) to explore hub genes’ relationships with immune cell infiltration and immune pathway activation. Validation was performed using an NMDA-induced excitotoxicity model and RT-qPCR for hub gene expression measurement.Results: The study identified 409 DEGs differentiating healthy individuals from glaucoma patients, highlighting the immune response’s significance in disease progression. Immune cell infiltration analysis revealed elevated levels of activated dendritic cells, natural killer cells, monocytes, and immature dendritic cells in glaucoma samples. Three hub genes, CD40LG, TEK, and MDK, were validated as potential diagnostic biomarkers for high-risk glaucoma patients, showing increased expression in the NMDA-induced excitotoxicity model.Discussion: The findings propose the three identified immune-related genes (IRGs) as novel diagnostic markers for glaucoma, offering new insights into the disease's pathogenesis and potential therapeutic targets. The strong correlation between these IRGs and immune responses underscores the intricate role of immunity in glaucoma, suggesting a shift in the approach to its diagnosis and treatment.
Interventions to improve the quality of maternal care in Ethiopia: a scoping review
Authors: Birhane Binyam Minuye , Assefa Yibeltal , Belay Demeke Mesfin , Nibret Gedefaye , Munye Aytenew Tigabu , Liyeh Tewachew Muche , Gelaw Kelemu Abebe , Tiruneh Yenework Mulu 
Published: April 2024

IntroductionQuality improvement interventions have been part of the national agenda aimed at reducing maternal and neonatal morbidities and mortality. Despite different interventions, neonatal mortality and morbidity rates remain steady. This review aimed to map and synthesize the evidence of maternal and newborn quality improvement interventions in Ethiopia.MethodsA scoping review was reported based on the reporting items for systematic reviews and meta-analysis extensions for the scoping review checklist. Data extraction, collation, and organization were based on the Joanna Briggs Institute manual of the evidence synthesis framework for a scoping review. The maternal and neonatal care standards from the World Health Organization and the Donabedian quality of health framework were used to summarize the findings.ResultsNineteen articles were included in this scoping review. The review found that the studies were conducted across various regions of Ethiopia, with the majority published after 2013. The reviewed studies mainly focused on three maternal care quality interventions: mobile and electronic health (eHealth), quality improvement standards, and human resource mobilization. Moreover, the reviewed studies explored various approaches to quality improvement, such as providing training to healthcare workers, health extension workers, traditional birth attendants, the community health development army, and mothers and supplying resources needed for maternal and newborn care.ConclusionIn conclusion, quality improvement strategies encompass community involvement, health education, mHealth, data-driven approaches, and health system strengthening. Future research should focus on the impact of physical environment, culture, sustainability, cost-effectiveness, and long-term effects of interventions. Healthcare providers’ knowledge, skills, attitudes, satisfaction, and adherence to guidelines should also be considered.
Mathematical modeling of endogenous and exogenously administered T cell recirculation in mouse and its application to pharmacokinetic studies of cell therapies
Authors: Nikitich Antonina , Helmlinger Gabriel , Peskov Kirill , Bocharov Gennady 
Published: April 2024

IntroductionIn vivo T cell migration has been of interest to scientists for the past 60 years. T cell kinetics are important in the understanding of the immune response to infectious agents. More recently, adoptive T cell therapies have proven to be a most promising approach to treating a wide range of diseases, including autoimmune and cancer diseases, whereby the characterization of cellular kinetics represents an important step towards the prediction of therapeutic efficacy. MethodsHere, we developed a physiologically-based pharmacokinetic (PBPK) model that describes endogenous T cell homeostasis and the kinetics of exogenously administered T cells in mouse. Parameter calibration was performed using a nonlinear fixed-effects modeling approach based on published data on T cell kinetics and steady-state levels in different tissues of mice. The Partial Rank Correlation Coefficient (PRCC) method was used to perform a global sensitivity assessment. To estimate the impact of kinetic parameters on exogenously administered T cell dynamics, a local sensitivity analysis was conducted. ResultsWe simulated the model to analyze cellular kinetics following various T cell doses and frequencies of CCR7+ T cells in the population of infused lymphocytes. The model predicted the effects of T cell numbers and of population composition of infused T cells on the resultant concentration of T cells in various organs. For example, a higher percentage of CCR7+ T cells among exogenously administered T lymphocytes led to an augmented accumulation of T cells in the spleen. The model predicted a linear dependence of T cell dynamics on the dose of adoptively transferred T cells. DiscussionThe mathematical model of T cell migration presented here can be integrated into a multi-scale model of the immune system and be used in a preclinical setting for predicting the distribution of genetically modified T lymphocytes in various organs, following adoptive T cell therapies.
Efficacy and safety of different immunotherapies combined with chemotherapy as first-line therapy in patients with small cell lung cancer: a network meta-analysis
Authors: Gong Siyao , Li Qian , Yu Xin , Yang Sha 
Published: April 2024

BackgroundThe efficacy and safety of different immunosuppressants combined with chemotherapy in treating patients with small-cell lung cancer (extensive-disease small-cell lung cancer, limited-disease small-cell lung cancer and relapsed small-cell lung cancer) are still unknown, and there are no reports directly comparing the efficacy and safety of other immunotherapies.ObjectiveThis study aimed to compare the efficacy and safety of first-line immunotherapy combined with chemotherapy in patients with small-cell lung cancer.MethodWe searched Pubmed, Embase, Cochrane Library, CNKI, and Wanfang databases for relevant articles published from inception to November 11, 2020. The risk of bias of the included studies was conducted using the Cochrane risk-of-bias (RoB) tool. Multiple Bayesian network meta-analyses were performed. They conducted data analysis using R Studio and STATA version 15.1. The outcomes comprised overall survival (OS), progression-free survival (PFS), stability of response (SOR), duration of response (DOR) and adverse events of grade 3 or higher (AE grade≥3). A 95% confidence interval (CI) was provided for each estimate.ResultsThis meta-analysis included 16 RCT studies with 5898 patients. For OS, relative to chemotherapy (MD=-4.49; 95%CI [-7.97, -1.03]), durvalumab plus tremelimumab (MD=-4.62; 95%CI [-9.08, -0.11]), ipilimumab (MD=-4.26; 95%CI [-8.01, -0.3]) and nivolumab(MD=-5.66; 95%CI [-10.44, -1.11]) and nivolumab plus ipilimumab (MD=-4.56; 95%CI [-8.7, -0.1]), serplulimab can significantly increase the OS of SCLC patients. There was no significant difference between PFS, SOR and DOR. Analysis of AE showed that different immunotherapy combined chemotherapy regimens were similar to single chemotherapy regarding the overall incidence of AE grade≥3. However, after the cumulative ranking of the common symptoms of different adverse reactions, it was found that nivolumab ranked first in the occurrence probability of anemia (99.08%), fatigue (84.78%), and decreased appetite (89.66%). durvalumab was the most likely in nausea (75.4%). Pembrolizumab (76.24%) was most likely to cause pruritus. Chemotherapy combined with immunotherapy caused less diarrhea than chemotherapy alone (80.16%).ConclusionsAccording to our analysis, serplulimab combined with chemotherapy is more likely to show better efficacy with a manageable safety profile for small-cell lung cancer. However, the evidence for this comparison shows some limitations due to the number of literature.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023486053.