bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Influence of Product Price and Service Quality on The Decision to Purchase Iron Steel at Pt Sinar Bangun Tata Semesta in West Jakarta
Authors: Jefri Jefpri Parulian , Carolina F. Sembiring  , Desideria Regina  
Published: August 2024

These studies aim to determining the effects of Products, Prices and Services Quality both simultaneously and simultaneously on Purchases Decision. The independent variable in these studies are Products Quality, Prices, and Services Quality, while dependent variable is Purchases Decision. These studies used a random sampling methods with a total samples of 35 respondent, especially DKI Jakarta. Methods of data analyst used SPSS software versions 25 The result of these studies proves that partially or simultaneously, product quality has a significancy effects on purchasing decisions, while prices have no significancy effects on purchasing decision, and service quality has a significancy effects on purchasing decision.
Keywords: Product Quality, Price, Service Quality, Purchasing Decision
ANALISIS KEBIJAKAN PELAYANAN DOKUMEN KEPENDUDUKAN DAN PENCATATAN SIPIL DI KABUPATEN BANDUNG
Authors: Lubis Bertha 
Published: August 2024

Pelayanan dokumen kependudukan dan pencatatan sipil di Kabupaten Bandung masih mengalami hambatan dan kendala baik dari segi kuantitas dan kualitas sumber daya manusia, sarana ruang server dan masih terbatasnya aplikasi khusus untuk memonitor kinerja jaringan kecamatan. Adapun Tujuan dari penelitian adalah untuk menggambarkan tentang Analisis Kebijakan Pelayanan Dokumen dukcapil di Kabupaten Bandung. Penelitian ini menggunakan metode kualitatif deskriptif dengan pendekatan induktif. Hasil dan simpulan, bahwa saat ini bentuk pelayanan dilakukan dengan mekanisme dan aplikasi secara on-line, yang terkoneksi dengan jaringan internet. Dimana masyarakat tidak perlu datang kekantor Dinas Kependudukan dan Pencatatan Sipil, masyarakat dapat meminta pelayanan dengan mengakses melalui website pada Dinas Kependudukan dan Pencatatan Sipil, model pelayanan ini sangat efektif dan masyarakat merasakan manfaatnya secara langsung. Namun masih ada kendala dalam pelayanan online tersebut sehingga diperlukan upaya nyata dalam mengahadapi hambatan tersebut diantara nya pendidikan dan pelatihan sumber daya manusia dan penguatan jaringan.
Kata Kunci: Analisis; Kebijakan; Pelayanan Publik.
Feasibility of tongue image detection for coronary artery disease: based on deep learning
Authors: Duan Mengyao , Mao Boyan , Li Zijian , Wang Chuhao , Hu Zhixi , Guan Jing , Li Feng 
Published: August 2024

AimClarify the potential diagnostic value of tongue images for coronary artery disease (CAD), develop a CAD diagnostic model that enhances performance by incorporating tongue image inputs, and provide more reliable evidence for the clinical diagnosis of CAD, offering new biological characterization evidence.MethodsWe recruited 684 patients from four hospitals in China for a cross-sectional study, collecting their baseline information and standardized tongue images to train and validate our CAD diagnostic algorithm. We used DeepLabV3 + for segmentation of the tongue body and employed Resnet-18, pretrained on ImageNet, to extract features from the tongue images. We applied DT (Decision Trees), RF (Random Forest), LR (Logistic Regression), SVM (Support Vector Machine), and XGBoost models, developing CAD diagnostic models with inputs of risk factors alone and then with the additional inclusion of tongue image features. We compared the diagnostic performance of different algorithms using accuracy, precision, recall, F1-score, AUPR, and AUC.ResultsWe classified patients with CAD using tongue images and found that this classification criterion was effective (ACC = 0.670, AUC = 0.690, Recall = 0.666). After comparing algorithms such as Decision Tree (DT), Random Forest (RF), Logistic Regression (LR), Support Vector Machine (SVM), and XGBoost, we ultimately chose XGBoost to develop the CAD diagnosis algorithm. The performance of the CAD diagnosis algorithm developed solely based on risk factors was ACC = 0.730, Precision = 0.811, AUC = 0.763. When tongue features were integrated, the performance of the CAD diagnosis algorithm improved to ACC = 0.760, Precision = 0.773, AUC = 0.786, Recall = 0.850, indicating an enhancement in performance.ConclusionThe use of tongue images in the diagnosis of CAD is feasible, and the inclusion of these features can enhance the performance of existing CAD diagnosis algorithms. We have customized this novel CAD diagnosis algorithm, which offers the advantages of being noninvasive, simple, and cost-effective. It is suitable for large-scale screening of CAD among hypertensive populations. Tongue image features may emerge as potential biomarkers and new risk indicators for CAD.
Clinical characteristics and long-term prognosis of female patients with acute coronary syndrome
Authors: Rocamora-Horrach Mar , Peiró Óscar M. , Bardají Alfredo , Flores-Benítez Javier , Ivorra-Cámara Miguel , Carrasquer Anna , Ferreiro José Luis 
Published: August 2024

BackgroundCardiovascular disease has traditionally been studied predominantly in men, but understanding its manifestations in women is crucial for effective management. This study aims to evaluate the long-term prognosis of female patients with acute coronary syndrome (ACS) within a tertiary hospital setting in Spain.MethodsRetrospective observational study based on a cohort of consecutive hospitalized patients with ACS from January 2009 to December 2014. Data on demographics, risk factors, treatment, and outcomes were collected, with a median follow-up of 9.2 years.ResultsWomen with ACS, constituting 27.3% of 2,330 patients, were older and had a higher prevalence of cardiovascular risk factors such as obesity, hypertension, and diabetes mellitus compared to men. They presented with more non-ST-segment elevation myocardial infarction and underwent less coronary angiography. Female patients were also less likely to be treated with acetylsalicylic acid, a second antiplatelet drug, or statins. Despite initial higher mortality rates [hazard ratio (HR) 1.30; 95% confidence interval (CI) 1.13–1.49; p &lt; 0.001], female patients exhibited a more favorable long-term prognosis after adjustments (adjusted HR 0.82; 95% CI 0.71–0.96; p = 0.014), even in the subgroup analysis excluding patients with unstable angina.ConclusionsWomen with ACS are more comorbid, but after adjustments, female sex appears to be a protective factor that confers a better long-term prognosis.
Research on line loss prediction of distribution network based on ensemble learning and feature selection
Authors: Zhang Ke , Zhang Yongwang , Li Jian , Jiang Zetao , Lu Yuxin , Zhao Binghui 
Published: August 2024

IntroductionAccurate prediction of line losses in distribution networks is crucial for optimizing power system planning and network restructuring, as these losses significantly impact grid operation quality. This paper proposes a novel approach that combines advanced feature selection techniques with Stacking ensemble learning to enhance the effectiveness of distribution network loss analysis and assessment.MethodsUtilizing data from 44 substations over an 18-month period, we integrated a Stacking ensemble learning model with multiple feature selection methods, including correlation coefficient, maximum information coefficient, and tree-based techniques. These methods were employed to identify the key predictors of power loss in the distribution network.ResultsThe proposed model achieved a Mean Absolute Percentage Error (MAPE) of 3.78% and a Root Mean Square Error (RMSE) of 1.53, demonstrating a substantial improvement over traditional linear regression-based prediction methods. The analysis revealed that historical line loss and line active power were the most influential predictive variables, while the inclusion of time-related features further refined the model's performance.DiscussionThis study highlights the efficacy of combining multiple feature selection methods with Stacking ensemble learning for predicting power loss in 10 kV distribution networks. The enhanced accuracy and reliability of the proposed model offer valuable insights for electrical engineering applications, potentially contributing to more efficient and sustainable energy distribution systems. Future research could explore the applicability of this approach to other distribution network voltage levels and investigate the incorporation of additional environmental and network-specific factors to further improve power loss prediction.
Efficacy and safety of different regimens of neoadjuvant therapy in patients with hormone receptor-positive, her2-negative breast cancer: a network meta-analysis
Authors: Wu Yongxiao , Huang Shibo , Wei Yanlin , Huang Miaoyan , Li Chunyan , Liang Weiming , Qin Tian 
Published: August 2024

IntroductionThe objective of this systematic review and network meta-analysis (NMA) is to assess the effectiveness and safety of various neoadjuvant treatment protocols in individuals diagnosed with hormone receptor-positive, her2 negative(HR+/HER2-) breast cancer.Materials and methodsA systematic search was conducted in four databases (Medline, Embase, Web of Science, and CENTRAL) from the inception of the databases to January 16, 2024, to identify randomized controlled trials (RCTs) to various neoadjuvant therapy options in patients diagnosed with hormone receptor-positive, HER2-negative breast cancer. A network meta-analysis was conducted to evaluate pathological complete response (pCR).ResultsThere were 17 randomized controlled trials (RCTs) included in the analysis. These trials examined 16 different treatment regimens and involved a total of 5752 participants. The analysis revealed that the six most effective neoadjuvant treatment regimens for HR+/HER2- breast cancer were: CT(A)+olaparib (82.5%), CT(A)+nivolumab (76.5%), Com (74.9%), CT (72.1%), Mono+eribulin (72.0%), and CT(A)+pembrolizumab (70.4%).Paired meta-analysis for pathological complete response (pCR) found no statistically significant distinction between treatment regimens that included both anthracycline and immunosuppressants and regimens that relied solely on anthracycline chemotherapy(OR:1.14, 95%ci 0.79-1.64, I2 = 71%, P=0.50). Similarly, there was no significant difference between platinum-based chemotherapy and anthracycline-basedchemotherapy(OR:1.37, 95%ci 0.53- 3.56, I2 = 11%, P=0.52). With regards to safety, adverse effects of grade 3-5 were observed, which included haematological toxicity, gastrointestinal reactions, skin and mucous membrane reactions, neuropathy, hepatotoxicity, and cardiac disorders.ConclusionsThe CT(A)+Olaparib and CT(A)+nivolumab groups demonstrated superior efficacy in neoadjuvant therapy for HR+/HER2- breast cancer. Furthermore, it is crucial to focus on effectively managing the adverse effects of the treatment plan to enhance patient’s ability to tolerate it. Given the constraints of the current research, additional well-executed and suitable RCTs are necessary to validate the findings of this investigation. Although pCR is valuable in assessing the effect of neoadjuvant therapy in some cases, prognostic prediction and efficacy assessment in patients with HR+/HER2- breast cancer should be based on a combination of broader clinical and biological characteristics.Systematic review registrationPROSPERO https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024534539, CRD42024501740.
Ginsenoside Rg3 targets glycosylation of PD-L1 to enhance anti-tumor immunity in non-small cell lung cancer
Authors: Wang Wei , Kong Min , Shen Fu , Li Ping , Chen Cheng , Li Yueqin , Li Cheng , Qian Zhiqiang , Zhong Aihua , Wang Yuhua , Yang Liang , He Fangkai , Li Weichun 
Published: August 2024

BackgroundReactivate the T cell immunity by PD-1/PD-L1 checkpoint blockade is widely used in non-small cell lung cancer (NSCLC) patients, while the post-translational modification of Programmed death ligand-1 (PD-L1) is commonly existed in various cancer cells, thus increases the complexity and difficulty in therapy development. Ginsenoside Rg3 is an active component of traditional Chinese herb Ginseng with multiple pharmacological effects including immune regulation. However, the effect on the glycosylation of PD-L1 is unknown.MethodsNSCLC cell lines were tested for glycosylation of PD-L1, and the potential mechanisms were investigated. Tumor cell-T cell coculture experiment was conducted and the activation of T cells and cytotoxicity were measured by flow cytometry. In vivo xenograft mouse tumor model was used to investigate the effects of Rg3 on PD-L1-mediated immunosuppression and tumor growth.ResultsHere, we identified PD-L1 is widely N-linked glycosylated in NSCLC cell lines, while Rg3 could inhibit the glycosylation of PD-L1 by downregulating the EGFR signaling and further activate GSK3b-mediated degradation, thus resulted in reduced PD-L1 expression. Moreover, the inhibition of PD-L1 glycosylation promoted the activation and cytotoxicity of T cells under coculture condition. In addition, Rg3 could decrease the tumor volume and enhance anti-tumor T cell immunity as evidence by the upregulated expression of Granzyme B and perforin in CD8+T cells, along with elevated serum IL-2, IFN-g and TNF-a level in Rg3-treated mice.ConclusionsThese results suggest that Rg3 inhibits PD-L1 glycosylation and thus enhance anti-tumor immunity, which provide new therapeutic insight into drug discovery.
Study on the effect factors of discharge readiness of total hip arthroplasty patients
Authors: Liu Pei , Chen Weiqiang , Shan Ying , Dai Liang , Qin Xianglan , Yang Haoze , Ji Xingchen , Tan Zhen , Yu Fei 
Published: August 2024

IntroductionIn order to explore the correlation between discharge readiness and Harris score or self-care ability of patients undergoing total hip arthroplasty (THA) based on the enhanced recovery after surgery (ERAS) concept. We carried out this single center retrospective study.MethodsWe enrolled 331 patients who underwent THA. These patients were divided into the higher score group and the lower score group according to median discharge readiness score. After the baseline data of these patients were compared, the effect factors of discharge readiness of these patients was analyzed through univariate and multivariate logistic regression analyses and mixed effects models.ResultsThe results demonstrated that there was a correlation between discharge readiness and changes in Harris score 30 days after discharge (compared with that before surgery) in these patients. Besides, the Harris score and self-care ability 30 days after discharge were higher than those at the time of discharge. In addition, patients in the higher score group exhibited a higher Harris score compared with those in the lower score group. From the evaluation at different time points after discharge, there was a significant difference in the Harris score between both groups.DiscussionIt can be inferred that the discharge readiness of patients undergoing THA was correlated with the Harris score but not with the self-care ability. These results are expected to provide guidance for the physical and mental recovery of patients undergoing total hip replacement under the ERAS concept. Furthermore, these findings may contribute to higher diagnosis, treatment, and nursing levels of orthopedic medical staff.
The incidence and risk factors of depression across six time points in the perinatal period: a prospective study in China
Authors: Zhu Jue , Ye Youchun , Liu Xuan , Chen Yichen , Chen Lu , Lin Yi , Wang Qiming , Zhang Jing 
Published: August 2024

IntroductionPerinatal depression (PND) affects approximately 15%–20% of women. This study aimed to determine the incidence of PND and identify risk factors.MethodsA prospective study was conducted at the Affiliated People’s Hospital of Ningbo University. The Edinburgh Postnatal Depression Scale (EPDS) was used to screen for PND. Classification models were constructed using Extreme Gradient Boosting (XGBoost), Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM), and the optimal model was selected.ResultsBetween March 2019 and August 2021, a total of 485 participants completed all valid questionnaires. Depression was observed in 75 (15.5%), 47 (9.7%), 25 (5.2%), 94 (19.4%), 85 (17.5%), and 43 (8.9%) cases during the first trimester, the second trimester, the third trimester, 1 week postpartum, 6 months postpartum, and 12 months postpartum, respectively. During the prenatal period, factors such as monthly income, employment status, marital status, and thyroid function significantly impacted depression. Additionally, factors including monthly income, employment status, marital status, parity, and unintended pregnancy were found to affect the likelihood of developing postpartum depression. XGBoost was chosen for its accuracy (0.9097) and precision (0.9005) in predicting prenatal depression, as well as for its accuracy (0.9253) and precision (0.9523) in predicting postpartum depression.DiscussionIn conclusion, the incidence of depression varies throughout the perinatal period, with different factors influencing prenatal and postpartum depression.
Causal effects of gut microbiota on risk of overactive bladder symptoms: a two-sample Mendelian randomization study
Authors: Shen Chaodong , Fang Mengjie , Zhang Xiaolong , Zhu Zhirong , Chen Jiajian , Tang Guiliang 
Published: August 2024

BackgroundClinical observations indicate a correlation between the gut microbiota and overactive bladder (OAB) symptoms. Nevertheless, the causal relationship and mechanisms between gut microbiota and OAB symptoms remain elusive.MethodsTwo-sample Mendelian randomization (MR) analyses were performed to assess the association between gut microbiota and OAB symptoms, including urinary incontinence (UI). Data were obtained from the MiBioGen International Consortium genome-wide association studies (GWAS) dataset and the IEU GWAS database. The inverse variance weighted method was used as the primary approach in the MR analysis, with the weighted median, MR-Egger, and weighted mode methods as supplementary approaches. Sensitivity analyses were employed to assess potential violations of the MR assumptions.ResultsOur analysis identified seven gut bacterial taxa with a causal relationship to OAB and nine gut bacterial taxa associated with UI. Genera Eubacteriumfissicatenumgroup, LachnospiraceaeNK4A136group, and Romboutsia were identified as protective factors against OAB, while genera Barnesiella, FamilyXIIIAD3011group, Odoribacter, and RuminococcaceaeUCG005 were associated with an increased risk of OAB. A higher abundance of the genus Coprococcus3, order Burkholderiales, and phylum Verrucomicrobia predicted a lower risk of UI. Conversely, the class Mollicutes, genus Ruminococcus gauvreauii group, order Mollicutes RF9, and phylum Firmicutes and Tenericutes were positively correlated with UI risk. The sensitivity analysis excluded the influence of potential heterogeneity and horizontal pleiotropy.ConclusionThis study revealed a causal relationship between gut microbiota and OAB symptoms, providing new insights and a theoretical foundation to identify biomarkers and therapeutic targets for patients with OAB symptoms.
Cross comparison of alternative diagnostic protocols including substitution to the clinical sample, RNA extraction method and nucleic acid amplification technology for COVID-19 diagnosis
Authors: Segura-Ulate Ismael , Apú Navilla , Cortés Bernal , Querol-Audi Jordi , Zaldívar Yamitzel , Ortega Carlos Alexander , Flores-Mora Fernando , Gatica-Arias Andrés , Madrigal-Redondo Germán 
Published: August 2024

Backgroundthe gold-standard diagnostic protocol (GSDP) for COVID-19 consists of a nasopharyngeal swab (NPS) sample processed through traditional RNA extraction (TRE) and amplified with retrotranscription quantitative polymerase chain reaction (RT-qPCR). Multiple alternatives were developed to decrease time/cost of GSDP, including alternative clinical samples, RNA extraction methods and nucleic acid amplification. Thus, we carried out a cross comparison of various alternatives methods against GSDP and each other.Methodswe tested alternative diagnostic methods using saliva, heat-induced RNA release (HIRR) and a colorimetric retrotranscription loop-mediated isothermal amplification (RT-LAMP) as substitutions to the GSDP.ResultsRT-LAMP using NPS processed by TRE showed high sensitivity (96%) and specificity (97%), closely matching GSDP. When saliva was processed by TRE and amplified with both RT-LAMP and RT-qPCR, RT-LAMP yielded high diagnostic parameters (88%–96% sensitivity and 95%–100% specificity) compared to RT-qPCR. Nonetheless, when saliva processed by TRE and detected by RT-LAMP was compared against the GSDP, the resulting diagnostic values for sensitivity (78%) and specificity (87%) were somewhat high but still short of those of the GSDP. Finally, saliva processed with HIRR and detected via RT-LAMP was the simplest and fastest method, but its sensitivity against GSDP was too low (56%) for any clinical application. Also, in this last method, the acidity of a large percentage of saliva samples (9%–22%) affected the pH-sensitive colorimetric indicator used in the test, requiring the exclusion of these acidic samples or an extra step for pH correction.Discussionour comparison shows that RT-LAMP technology has diagnostic performance on par with RT-qPCR; likewise, saliva offers the same diagnostic functionality as NPS when subjected to a TRE method. Nonetheless, use of direct saliva after a HIRR and detected with RT-LAMP does not produce an acceptable diagnostic performance.
Predicting radiofrequency thermocoagulation surgical outcomes in refractory focal epilepsy patients using functional coupled neural mass model
Authors: Cai Tianxin , Lin Yaoxin , Wang Guofu , Luo Jie 
Published: August 2024

ObjectiveThe success rate of achieving seizure freedom after radiofrequency thermocoagulation surgery for patients with refractory focal epilepsy is about 20–40%. This study aims to enhance the prediction of surgical outcomes based on preoperative decisions through network model simulation, providing a reference for clinicians to validate and optimize surgical plans.MethodsTwelve patients with epilepsy who underwent radiofrequency thermocoagulation were retrospectively reviewed in this study. A coupled model based on model subsets of the neural mass model was constructed by calculating partial directed coherence as the coupling matrix from stereoelectroencephalography (SEEG) signals. Multi-channel time-varying model parameters of excitation and inhibitions were identified by fitting the real SEEG signals with the coupled model. Further incorporating these model parameters, the coupled model virtually removed contacts destroyed in radiofrequency thermocoagulation or selected randomly. Subsequently, the coupled model after virtual surgery was simulated.ResultsThe identified excitatory and inhibitory parameters showed significant difference before and after seizure onset (p &lt; 0.05), and the trends of parameter changes aligned with the seizure process. Additionally, excitatory parameters of epileptogenic contacts were higher than that of non-epileptogenic contacts, and opposite findings were noticed for inhibitory parameters. The simulated signals of postoperative models to predict surgical outcomes yielded an area under the curve (AUC) of 83.33% and an accuracy of 91.67%.ConclusionThe multi-channel coupled model proposed in this study with physiological characteristics showed a desirable performance for preoperatively predicting patients’ prognoses.