bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pengaruh Return on Asset dan NonPerforming Loan Terhadap Capital Adequacy Ratio Pada PT Bank Mega Tbk
Authors: Faisal Faisal 
Published: June 2021

This study aims to determine the effect of the independent variables on the dependent variable. The independent variable used in this study is Return on Assets, Non Performing Loans. While the dependent variable in this study is the Capital Adequacy Ratio. The data used in this study are quarterly data from 2010 to 2018. The sampling technique used in this study was purposive sampling involving Bank Mega Tbk. The analysis technique used is multiple linear regression analysis. Based on the results of data analysis, this study shows that simultaneously (Simultaneous) Return on Assets, Non Performing Loans have a significant effect on Capital Adequacy Ratio. And individually (partial) Net Interest Margin, Non Performing Loans and Return on Assets have a positive effect on CAR, negatively affect CAR. Determination coefficient results indicate the Adjusted R-squared value of 0.714240 means that the independent variable can explain the dependent variable by 71.42% while the rest is explained by other variables not contained in the model.In this study, the researcher wanted to find out whether there was a significant relationship between Return on Assets, Non-Performing Loans had a significant effect on the Capital Adequacy Ratio.

Abstrak
Penelitian ini bertujuan untuk mengetahui pengaruh antara variabel independen terhadap variabel dependen. Variabel independen yang digunakan dalam penelitian ini adalah Return on Asset, Non Performing Loan. Sedangkan variabel dependen dalam penelitian ini adalah Capital Adequacy Ratio. Data yang digunakan dalam penelitian ini adalah data kuartal selama periode 2010 sampai dengan 2018. Teknik sampling yang digunakan dalam penelitian ini adalah purposive sampling yang melibatkan Bank Mega Tbk. Teknik analisis yang digunakan adalah analisis regresi linear berganda. Berdasarkan hasil analisis data penelitian ini menunjukan secara bersama-sama (Simultan) Return on Asset, Non Performing Loan berpengaruh signifikan terhadap Capital Adequacy Ratio. Dan secara individu (Parsial) Net Interest Margin, Non Performing Loan dan Return on Asset berpengaruh positif terhadap CAR, berpengaruh negatif terhadap CAR. Hasil Koefisien Determinasi menunjukan nilai Adjusted R-squared sebesar 0,714240 artinya bahwa variabel independen dapat menjelaskan variabel dependen sebesar 71,42% sedangkan sisanya dijelaskan oleh variabel lain yang tidak terdapat dalam model.Return on Asset, Non Performing Loan berpengaruh signifikan terhadap Capital Adequacy Ratio

KataKunci: Return on Asset, Non Performing Loan, Capital Adequacy Ratio.
Analisis Evaluasi Keberhasilan Inovasi Sistem Aplikasi By Data Pada UKM Minuman Kekinian di Kota Tangerang Selatan(Studi Kasus Minuman "Ngombe”)
Authors: Tumanggor Rahmayanti , Wiyanto Wiyanto 
Published: June 2021

This aims of the study is to analyze the evaluation of innovation successful of by data application system at modern beverage MSMEs (Ngombe) in South Tangerang City. Also to find out influence and benefits of using by data application system to increase sales of modern beverages. Alsoto know how the “by data” application system can help modern beverage business entrepreneursto achieve significant sales and to provide economic benefits.The method used in this study was descriptive analysis of qualitative method. The analysis technique uses observation, interview, documentation, forum group discussion and triangulation. The analysis data method was inductive that based on the accumulation of data, then developed in to hypothesis by organize the data in to category, outline into units, do synthesis, compile in to the pattern to get the conclusion. Based on the SWOT analysis, the EFI and EFE calculations obtained the EFI score of 3.65, meaning that the business has a good internal strength position. While the EFE score is 3.30 indicating that external factors are sufficient to support the business. By using the SPACE matrix, Ngombe is in quadrant III, which is an aggressive condition. The conclusion is that implementation of by data application system gives ease in the service to consumers and provides significant advantage to the owner.
Abstrak
Penelitian ini bertujuan untuk menganalisis evaluasi keberhasilan inovasi sistem aplikasi by data pada UKM minuman kekinian (Ngombe) di Kota Tangerang Selatan. Juga untuk mengetahui pengaruh dan manfaat penggunaan sistem aplikasi by data terhadap peningkatan penjualan minuman kekinian. Bagaimana sistem aplikasi ‘by data” dapat membantu para pelaku usaha minuman kekinian dalam mengembangkan usahanya sehingga tercapai penjualan yang cukup signifikan dan memberi keuntungan ekonomis Metode penelitian yang digunakan adalah kualitatif yang bersifat analisis deskriptif.Teknik pengumpulan data adalah observasi, wawancara, dokumentasi, FGD dan triangulasi. Metode analisis data bersifat induktif, dikembangkan menjadi hipotesis, mengorganisasikan data ke dalam kategori, menjabarkan ke dalam unit-unit, melakukan sintesa, menyusun ke dalam pola, sehingga mendapatkan satu kesimpulan. Hasil penelitian berdasarkan analisis SWOT perhitunganan EFI dan EFE nilai skor tertimbang EFI sebesar 3.65, artinya usaha yang dikembangkan memiliki posisi kekuatan internal baik. Sedangkan skor tertimbang EFE diperoleh nilai 3,30 mengindikasikan bahwa faktor eksternal cukup mendukung usaha yang dilakukan. Denganmenggunakanmatrik SPACE,usaha Minuman Ngombe berada padaposisi kuadran III yaitu kondisi agresif.Kesimpulannya bahwa minuman kekinian yang menggunakan sistem aplikasi‘by data’memberikan kemudahan dalam penjualan, juga memberikan keuntungan yang signifikan bagi pemiliknya.

Kata Kunci:Produk, Profit, Inovasi, Sistem Aplikasi by data
A Voltammetric Perspective of Multi-Electron and Proton Transfer in Protein Redox Chemistry: Insights From Computational Analysis of Escherichia coli HypD Fourier Transformed Alternating Current Voltammetry
Authors: Dale-Evans Alister R. , Robinson Martin J. , Lloyd-Laney Henry O. , Gavaghan David J. , Bond Alan M. , Parkin Alison 
Published: June 2021

This paper explores the impact of pH on the mechanism of reversible disulfide bond (CysS-SCys) reductive breaking and oxidative formation inEscherichia colihydrogenase maturation factor HypD, a protein which forms a highly stable adsorbed film on a graphite electrode. To achieve this, low frequency (8.96 Hz) Fourier transformed alternating current voltammetric (FTACV) experimental data was used in combination with modelling approaches based on Butler-Volmer theory with a dual polynomial capacitance model, utilizing an automated two-step fitting process conducted within a Bayesian framework. We previously showed that at pH 6.0 the protein data is best modelled by a redox reaction of two separate, stepwise one-electron, one-proton transfers with slightly “crossed” apparent reduction potentials that incorporate electron and proton transfer terms (Eapp20&gt;Eapp10). Remarkably, rather than collapsing to a concerted two-electron redox reaction at more extreme pH, the same two-stepwise one-electron transfer model withEapp20&gt;Eapp10continues to provide the best fit to FTACV data measured across a proton concentration range from pH 4.0 to pH 9.0. A similar, small level of crossover in reversible potentials is also displayed in overall two-electron transitions in other proteins and enzymes, and this provides access to a small but finite amount of the one electron reduced intermediate state.
Pre-ischemic Lactate Levels Affect Post-ischemic Recovery in an Isolated Rat Heart Model of Donation After Circulatory Death (DCD)
Authors: Arnold Maria , Segiser Adrian , Graf Selianne , Méndez-Carmona Natalia , Sanz Maria N. , Wyss Rahel K. , Kalbermatter Nina , Keller Nino , Carrel Thierry , Longnus Sarah 
Published: June 2021

Introduction: Donation after circulatory death (DCD) could substantially improve donor heart availability. In DCD, the heart is not only exposed to a period of warm ischemia, but also to a damaging pre-ischemic phase. We hypothesized that the DCD-relevant pre-ischemic lactate levels negatively affect the post-ischemic functional and mitochondrial recovery in an isolated rat heart model of DCD.Methods: Isolated, working rat hearts underwent 28.5′ of global ischemia and 60′ of reperfusion. Prior to ischemia, hearts were perfused with one of three pre-ischemic lactate levels: no lactate (0 Lac), physiologic lactate (0.5 mM; 0.5 Lac), or DCD-relevant lactate (1 mM; 1 Lac). In a fourth group, an inhibitor of the mitochondrial calcium uniporter was added in reperfusion to 1 Lac hearts (1 Lac + Ru360).Results: During reperfusion, left ventricular work (heart rate-developed pressure product) was significantly greater in 0.5 Lac hearts compared to 0 Lac or 1 Lac. In 1 vs. 0.5 Lac hearts, in parallel with a decreased function, cellular and mitochondrial damage was greater, tissue calcium content tended to increase, while oxidative stress damage tended to decrease. The addition of Ru360 to 1 Lac hearts partially abrogated the negative effects of the DCD-relevant pre-ischemic lactate levels (greater post-ischemic left ventricular work and less cytochrome c release in 1 Lac+Ru360 vs. 1 Lac).Conclusion: DCD-relevant levels of pre-ischemic lactate (1 mM) reduce contractile, cellular, and mitochondrial recovery during reperfusion compared to physiologic lactate levels. Inhibition of mitochondrial calcium uptake during early reperfusion improves the post-ischemic recovery of 1 Lac hearts, indicating calcium overload as a potential therapeutic reperfusion target for DCD hearts.
Plasma Testosterone Levels and Atherosclerotic Plaque Gene Expression in Men With Advanced Atherosclerosis
Authors: Groepenhoff Floor , Diez Benavente Ernest , Boltjes Arjan , Timmerman Nathalie , Waissi Farahnaz , Hartman Robin J. G. , Onland-Moret N. C. , Pasterkamp Gerard , Den Ruijter Hester 
Published: June 2021

Aims: Low plasma testosterone levels have been shown to predict worse outcome in men with severe atherosclerotic disease. We hypothesized that a low plasma testosterone level affects disease risk through changes in gene expression in atherosclerotic plaques. Therefore, we studied plasma testosterone levels in relation to gene expression levels in atherosclerotic plaque tissue of men with advanced atherosclerotic disease.Methods: Plasma testosterone levels were measured in 203 men undergoing carotid endarterectomy. The corresponding atherosclerotic plaque tissue was used for RNA sequencing. First, we assessed how often the androgen receptor gene was expressed in the plaque. Second, correlations between plasma testosterone levels and pre-selected testosterone-sensitive genes were assessed. Finally, differences within the RNA expression profile of the plaque as a whole, characterized into gene regulatory networks and at individual gene level were assessed in relation to testosterone levels.Results: Testosterone plasma levels were low with a median of 11.6 nmol/L (IQR: 8.6–13.8). RNA-seq of the plaque resulted in reliable expression data for 18,850 genes to be analyzed. Within the RNA seq data, the androgen-receptor gene was expressed in 189 out of 203 (93%) atherosclerotic plaques of men undergoing carotid endarterectomy. The androgen receptor gene expression was not associated with testosterone plasma levels. There were no significant differences in gene expression of atherosclerotic plaques between different endogenous testosterone levels. This remained true for known testosterone-sensitive genes, the complete transcriptomic profile, male-specific gene co-expression modules as well as for individual genes.Conclusion: In men with severe atherosclerotic disease the androgen receptor is highly expressed in plaque tissue. However, plasma testosterone levels were neither associated with pre-selected testosterone sensitive genes, gene expression profiles nor gene regulatory networks in late-stage atherosclerotic plaques. The effect of testosterone on gene expression of the late-stage atherosclerotic plaque appears limited, suggesting that alternate mechanisms explain its effect on clinical outcomes.
Multi—Proxy Reconstructions of Climate Change and Human Impacts Over the Past 7000 Years From an Archive of Continental Shelf Sediments off Eastern Hainan Island, China
Authors: Huang Chao , Kong Deming , Chen Fajin , Hu Jianfang , Wang Peng , Lin Junchuan 
Published: June 2021

Abrupt climatic events and the history of human activities on Hainan Island are poorly understood, due to the lack of high-resolution records. We present high-resolution multiproxy records from the coastal shelf off eastern Hainan Island in China to investigate abrupt climate change and regional human–environment interaction over the last 7,000 years. A prominent climatic anomaly occurred during 5,400–4,900 cal yr BP. This abrupt monsoon failure has been detected in various paleoclimatic records from monsoonal regions. Anomalous summer monsoon intensity during 5,400–4,900 cal yr BP is probably driven by solar variability, ENSO activity and ice-rafting events in the North Atlantic. Over the past 1,500 years, with the growing population and progress in production technology, human activity has increasingly become the dominant factor controlling the natural environment of Hainan Island.
The Genetics of Adverse Drug Outcomes in Type 2 Diabetes: A Systematic Review
Authors: Baye Assefa M. , Fanta Teferi G. , Siddiqui Moneeza K. , Dawed Adem Y. 
Published: June 2021

Background: Adverse drug reactions (ADR) are a major clinical problem accounting for significant hospital admission rates, morbidity, mortality, and health care costs. One-third of people with diabetes experience at least one ADR. However, there is notable interindividual heterogeneity resulting in patient harm and unnecessary medical costs. Genomics is at the forefront of research to understand interindividual variability, and there are many genotype-drug response associations in diabetes with inconsistent findings. Here, we conducted a systematic review to comprehensively examine and synthesize the effect of genetic polymorphisms on the incidence of ADRs of oral glucose-lowering drugs in people with type 2 diabetes.Methods: A literature search was made to identify articles that included specific results of research on genetic polymorphism and adverse effects associated with oral glucose-lowering drugs. The electronic search was carried out on 3rd October 2020, through Cochrane Library, PubMed, and Web of Science using keywords and MeSH terms.Result: Eighteen articles consisting of 10, 383 subjects were included in this review. Carriers of reduced-function alleles of organic cation transporter 1 (OCT 1, encoded by SLC22A1) or reduced expression alleles of plasma membrane monoamine transporter (PMAT, encoded by SLC29A4) or serotonin transporter (SERT, encoded by SLC6A4) were associated with increased incidence of metformin-related gastrointestinal (GI) adverse effects. These effects were shown to exacerbate by concomitant treatment with gut transporter inhibiting drugs. The CYP2C9 alleles, *2 (rs1799853C&gt;T) and *3 (rs1057910A&gt;C) that are predictive of low enzyme activity were more common in subjects who experienced hypoglycemia after treatment with sulfonylureas. However, there was no significant association between sulfonylurea-related hypoglycemia and genetic variants in the ATP-binding cassette transporter sub-family C member 8 (ABCC8)/Potassium Inwardly Rectifying Channel Subfamily J Member 11 (KCNJ11). Compared to the wild type, the low enzyme activity C allele at CYP2C8*3 (rs1057910A&gt;C) was associated with less weight gain whereas the C allele at rs6123045 in the NFATC2 gene was significantly associated with edema from rosiglitazone treatment.Conclusion: In spite of limited studies investigating genetics and ADR in diabetes, some convincing results are emerging. Genetic variants in genes encoding drug transporters and metabolizing enzymes are implicated in metformin-related GI adverse effects, and sulfonylurea-induced hypoglycemia, respectively. Further studies to investigate newer antidiabetic drugs such as DPP-4i, GLP-1RA, and SGLT2i are warranted. In addition, pharmacogenetic studies that account for race and ethnic differences are required.
A Combined RNA Signature Predicts Recurrence Risk of Stage I-IIIA Lung Squamous Cell Carcinoma
Authors: Sun Li , Li Juan , Li Xiaomeng , Yang Xuemei , Zhang Shujun , Wang Xue , Wang Nan , Xu Kanghong , Jiang Xinquan , Zhang Yi 
Published: June 2021

ObjectiveRecurrence remains the main cause of the poor prognosis in stage I-IIIA lung squamous cell carcinoma (LUSC) after surgical resection. In the present study, we aimed to identify the long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) related to the recurrence of stage I-IIIA LUSC. Moreover, we constructed a risk assessment model to predict the recurrence of LUSC patients.MethodsRNA sequencing data (including miRNAs, lncRNAs, and mRNAs) and relevant clinical information were obtained from The Cancer Genome Atlas (TCGA) database. The differentially expressed lncRNAs, miRNAs, and mRNAs were identified using the “DESeq2” package of the R language. Univariate Cox proportional hazards regression analysis and Kaplan-Meier curve were used to identify recurrence-related genes. Stepwise multivariate Cox regression analysis was carried out to establish a risk model for predicting recurrence in the training cohort. Moreover, Kaplan-Meier curves and receiver operating characteristic (ROC) curves were adopted to examine the predictive performance of the signature in the training cohort, validation cohort, and entire cohort.ResultsBased on the TCGA database, we analyzed the differentially expressed genes (DEGs) among 27 patients with recurrent stage I-IIIA LUSC and 134 patients with non-recurrent stage I-IIIA LUSC, and identified 431 lncRNAs, 36 miRNAs, and 746 mRNAs with different expression levels. Out of these DEGs, the optimal combination of DEGs was finally determined, and a nine-joint RNA molecular signature was constructed for clinical prediction of recurrence, including LINC02683, AC244517.5, LINC02418, LINC01322, AC011468.3, hsa-mir-6825, AC020637.1, AC027117.2, and SERPINB12. The ROC curve proved that the model had good predictive performance in predicting recurrence. The area under the curve (AUC) of the prognostic model for recurrence-free survival (RFS) was 0.989 at 3 years and 0.958 at 5 years (in the training set). The combined RNA signature also revealed good predictive performance in predicting the recurrence in the validation cohort and entire cohort.ConclusionsIn the present study, we constructed a nine-joint RNA molecular signature for recurrence prediction of stage I-IIIA LUSC. Collectively, our findings provided new and valuable clinical evidence for predicting the recurrence and targeted treatment of stage I-IIIA LUSC.
Genomic Landscape of Head and Neck Squamous Cell Carcinoma Across Different Anatomic Sites in Chinese Population
Authors: Ju Yunhe , Wu Xingrao , Wang Huizhen , Li Bin , Long Qing , Zhang Dadong , Chen Hao , Xiao Nianqing , Li Fugen , Zhang Shiwen , Yang Shenggang 
Published: June 2021

BackgroundThe characteristics of head and neck squamous cell carcinoma (HNSCC) across different anatomic sites in the Chinese population have not been studied. To determine the genomic abnormalities underlying HNSCC across different anatomic sites, the alterations of selected cancer-related genes were evaluated.MethodsGenomic DNA samples obtained from formalin-fixed, paraffin-embedded tissues were analyzed using targeted sequencing in a panel of 383 cancer-related genes to determine the genomic alterations.ResultsA total of 317 formalin-fixed, paraffin-embedded HNSCC specimens were collected, and a total of 2,156 protein-coding mutations, including 1,864 single nucleotide variants and 292 insertions and deletions, were identified across more than six different anatomic sites. Mutation loads were distinct across the anatomic sites. Larynx carcinoma was found with the highest mutation loads, whereas nasopharynx carcinoma showed the lowest mutation loads. A total of 1,110 gains and 775 losses were identified in the 317 specimens. Patients who had at least one clinically actionable alteration (levels 1–4 in OncoKB) were identified. One patient had an actionable alteration with level 1 evidence in OncoKB, TEX10-NTRK2 fusion, who may benefit from larotrectinib or entrectinib treatment.ConclusionThe genomic profiling of HNSCC using targeted sequencing can identify rational therapeutic candidate genes suitable for the treatment of the HNSCCs.
Temporal Integration of Text Transcripts and Acoustic Features for Alzheimer's Diagnosis Based on Spontaneous Speech
Authors: Martinc Matej , Haider Fasih , Pollak Senja , Luz Saturnino 
Published: June 2021

Background:Advances in machine learning (ML) technology have opened new avenues for detection and monitoring of cognitive decline. In this study, a multimodal approach to Alzheimer's dementia detection based on the patient's spontaneous speech is presented. This approach was tested on a standard, publicly available Alzheimer's speech dataset for comparability. The data comprise voice samples from 156 participants (1:1 ratio of Alzheimer's to control), matched by age and gender.Materials and Methods:A recently developed Active Data Representation (ADR) technique for voice processing was employed as a framework for fusion of acoustic and textual features at sentence and word level. Temporal aspects of textual features were investigated in conjunction with acoustic features in order to shed light on the temporal interplay between paralinguistic (acoustic) and linguistic (textual) aspects of Alzheimer's speech. Combinations between several configurations of ADR features and more traditional bag-of-n-grams approaches were used in an ensemble of classifiers built and evaluated on a standardised dataset containing recorded speech of scene descriptions and textual transcripts.Results:Employing only semantic bag-of-n-grams features, an accuracy of 89.58% was achieved in distinguishing between Alzheimer's patients and healthy controls. Adding temporal and structural information by combining bag-of-n-grams features with ADR audio/textual features, the accuracy could be improved to 91.67% on the test set. An accuracy of 93.75% was achieved through late fusion of the three best feature configurations, which corresponds to a 4.7% improvement over the best result reported in the literature for this dataset.Conclusion:The proposed combination of ADR audio and textual features is capable of successfully modelling temporal aspects of the data. The machine learning approach toward dementia detection achieves best performance when ADR features are combined with strong semantic bag-of-n-grams features. This combination leads to state-of-the-art performance on the AD classification task.