bluuebunny/crossref_metadata_2025_split huggingface dataset:
KLASIFIKASI KATEGORI CITRA DIGITAL DENGAN METODE BAG OF VISUAL WORDS
Authors: Prawira Tanjung Mahardika Abdi 
Published: February 2021

Abstract: The human eye can distinguish objects from digital images, however, computers do not have the ability as human eyes that can directly distinguish objects from digital images. Therefore the bag of visual words method was created. Bag of visual words is a method for presenting digital images based on local features. Bag of visual words illustrates how an image can be taken its characteristics, so that computers can distinguish objects on digital images. The test results show that the bag of visual words are still not maximal in classifying digital image categories, especially the chair category, which is only able to produce the most accurate accuracy of 75%. To improve the performance quality of bag of visual words in classifying digital image categories, especially the chair category, you can add an approach to determine the good number of K in clustering the visual words pattern. Keywords: Bag Of Visual Words, Classification, Digital Image, Speed-Up Robust Feature, Support Vector Machine Abstrak: Secara kasat mata manusia bisa membedakan objek pada citra digital, namun, komputer tidak memiliki kemampuan sebagai mata manusia yang dapat secara langsung membedakan objek pada citra digital. Maka dari itu diciptakanlah metode bag of visual words. Bag of visual words adalah metode untuk menyajikan citra digital berdasarkan fitur lokal. Bag of visual words menggambarkan bagaimana suatu gambar dapat diambil karakteristiknya, sehingga komputer dapat membedakan objek pada citra digital. Hasil pengujian menunjukkan bag of visual words masih belum maksimal dalam mengklasifikasi kategori citra digital khususnya kategori chair, yang hanya mampu menghasilkan akurasi paling akurat sebesar 75 %. Untuk meningkatkan kualitas kinerja bag of visual words dalam mengklasifikasi kategori citra digital khususnya kategori chair, dapat menambahkan pendekatan untuk menentukan jumlah K yang baik dalam mengkluster pola visual words. Kata kunci: Bag Of Visual Words, Klasifikasi, Citra Digital, Speed-Up Robust Feature, Support Vector Machine
PAYROLL INFORMATION SYSTEM AT PT. ASTRO NIAGA JAYA (SIPESTRO)
Authors: Muthia Dinda Ayu , Budi Setiawan Anip , Waliyyuddin Waliyyuddin , Syahrul Gunawan Muhammad 
Published: February 2021

Abstract: Payroll is an acceptance in return from the employer to the employee for a job or service that has been done and is expressed or valued in the form of money determined on the basis of an agreement or legislation and is paid on the basis of an employment agreement between the employer and the employee including benefits, both for the employees themselves and for the family. This research takes place at PT. Astro Niaga Jaya. The payroll process at PT. Astro Niaga Jaya is still conventional. Salary calculations are based on different details that hinder the performance process of the human resources department. Errors in calculating salaries can be fatal because it will affect the preparation of financial statements. Therefore, it is necessary to have an employee payroll information system so that the human resources department is not wrong in collecting employee payroll data. The purpose of this paper is to design employee attendance and payroll information systems at PT. Astro Niaga Jaya using Waterfall method in order to produce information that is fast, precise and accurate. The Waterfall method is often used in designing an information system. Payroll Information System can work effectively and efficiently. Keywords: payroll, information, system
Alterations in Dynamic Functional Connectivity in Individuals With Subjective Cognitive Decline
Authors: Chen Qian , Lu Jiaming , Zhang Xin , Sun Yi , Chen Wenqian , Li Xin , Zhang Wen , Qing Zhao , Zhang Bing 
Published: February 2021

Purpose: To investigate the dynamic functional connectivity (DFC) and static parameters of graph theory in individuals with subjective cognitive decline (SCD) and the associations of DFC and topological properties with cognitive performance.Methods: Thirty-three control subjects and 32 SCD individuals were enrolled in this study, and neuropsychological evaluations and resting-state functional magnetic resonance imaging scanning were performed. Thirty-three components were selected by group independent component analysis to construct 7 functional networks. Based on the sliding window approach and k-means clustering, distinct DFC states were identified. We calculated the temporal properties of fractional windows in each state, the mean dwell time in each state, and the number of transitions between each pair of DFC states. The global and local static parameters were assessed by graph theory analysis. The differences in DFC and topological metrics, and the associations of the altered neuroimaging measures with cognitive performance were assessed.Results: The whole cohort demonstrated 4 distinct connectivity states. Compared to the control group, the SCD group showed increased fractional windows and an increased mean dwell time in state 4, characterized by hypoconnectivity both within and between networks. The SCD group also showed decreased fractional windows and a decreased mean dwell time in state 2, dominated by hyperconnectivity within and between the auditory, visual and somatomotor networks. The number of transitions between state 1 and state 2, between state 2 and state 3, and between state 2 and state 4 was significantly reduced in the SCD group compared to the control group. No significant differences in global or local topological metrics were observed. The altered DFC properties showed significant correlations with cognitive performance.Conclusion: Our findings indicated DFC network reconfiguration in the SCD stage, which may underlie the early cognitive decline in SCD subjects and serve as sensitive neuroimaging biomarkers for the preclinical detection of individuals with incipient Alzheimer's disease.
A Feasibility Study of Expanded Home-Based Telerehabilitation After Stroke
Authors: Cramer Steven C. , Dodakian Lucy , Le Vu , McKenzie Alison , See Jill , Augsburger Renee , Zhou Robert J. , Raefsky Sophia M. , Nguyen Thalia , Vanderschelden Benjamin , Wong Gene , Bandak Daniel , Nazarzai Laila , Dhand Amar , Scacchi Walt , Heckhausen Jutta 
Published: February 2021

Introduction:High doses of activity-based rehabilitation therapy improve outcomes after stroke, but many patients do not receive this for various reasons such as poor access, transportation difficulties, and low compliance. Home-based telerehabilitation (TR) can address these issues. The current study evaluated the feasibility of an expanded TR program.Methods:Under the supervision of a licensed therapist, adults with stroke and limb weakness received home-based TR (1 h/day, 6 days/week) delivered using games and exercises. New features examined include extending therapy to 12 weeks duration, treating both arm and leg motor deficits, patient assessments performed with no therapist supervision, adding sensors to real objects, ingesting a daily experimental (placebo) pill, and generating automated actionable reports.Results:Enrollees (n= 13) were median age 61 (IQR 52–65.5), and 129 (52–486) days post-stroke. Patients initiated therapy on 79.9% of assigned days and completed therapy on 65.7% of days; median therapy dose was 50.4 (33.3–56.7) h. Non-compliance doubled during weeks 7–12. Modified Rankin scores improved in 6/13 patients, 3 of whom were &gt;3 months post-stroke. Fugl-Meyer motor scores increased by 6 (2.5–12.5) points in the arm and 1 (−0.5 to 5) point in the leg. Assessments spanning numerous dimensions of stroke outcomes were successfully implemented; some, including a weekly measure that documented a decline in fatigue (p= 0.004), were successfully scored without therapist supervision. Using data from an attached sensor, real objects could be used to drive game play. The experimental pill was taken on 90.9% of therapy days. Automatic actionable reports reliably notified study personnel when critical values were reached.Conclusions:Several new features performed well, and useful insights were obtained for those that did not. A home-based telehealth system supports a holistic approach to rehabilitation care, including intensive rehabilitation therapy, secondary stroke prevention, screening for complications of stroke, and daily ingestion of a pill. This feasibility study informs future efforts to expand stroke TR.Clinical Trial Registration:Clinicaltrials.gov, # NCT03460587.
Machine-Learning vs. Expert-Opinion Driven Logistic Regression Modelling for Predicting 30-Day Unplanned Rehospitalisation in Preterm Babies: A Prospective, Population-Based Study (EPIPAGE 2)
Authors: Reed Robert A. , Morgan Andrei S. , Zeitlin Jennifer , Jarreau Pierre-Henri , Torchin Héloïse , Pierrat Véronique , Ancel Pierre-Yves , Khoshnood Babak 
Published: February 2021

Introduction: Preterm babies are a vulnerable population that experience significant short and long-term morbidity. Rehospitalisations constitute an important, potentially modifiable adverse event in this population. Improving the ability of clinicians to identify those patients at the greatest risk of rehospitalisation has the potential to improve outcomes and reduce costs. Machine-learning algorithms can provide potentially advantageous methods of prediction compared to conventional approaches like logistic regression.Objective: To compare two machine-learning methods (least absolute shrinkage and selection operator (LASSO) and random forest) to expert-opinion driven logistic regression modelling for predicting unplanned rehospitalisation within 30 days in a large French cohort of preterm babies.Design, Setting and Participants: This study used data derived exclusively from the population-based prospective cohort study of French preterm babies, EPIPAGE 2. Only those babies discharged home alive and whose parents completed the 1-year survey were eligible for inclusion in our study. All predictive models used a binary outcome, denoting a baby's status for an unplanned rehospitalisation within 30 days of discharge. Predictors included those quantifying clinical, treatment, maternal and socio-demographic factors. The predictive abilities of models constructed using LASSO and random forest algorithms were compared with a traditional logistic regression model. The logistic regression model comprised 10 predictors, selected by expert clinicians, while the LASSO and random forest included 75 predictors. Performance measures were derived using 10-fold cross-validation. Performance was quantified using area under the receiver operator characteristic curve, sensitivity, specificity, Tjur's coefficient of determination and calibration measures.Results: The rate of 30-day unplanned rehospitalisation in the eligible population used to construct the models was 9.1% (95% CI 8.2–10.1) (350/3,841). The random forest model demonstrated both an improved AUROC (0.65; 95% CI 0.59–0.7; p = 0.03) and specificity vs. logistic regression (AUROC 0.57; 95% CI 0.51–0.62, p = 0.04). The LASSO performed similarly (AUROC 0.59; 95% CI 0.53–0.65; p = 0.68) to logistic regression.Conclusions: Compared to an expert-specified logistic regression model, random forest offered improved prediction of 30-day unplanned rehospitalisation in preterm babies. However, all models offered relatively low levels of predictive ability, regardless of modelling method.
Uncovering the Pharmacological Mechanism of 2-Dodecyl-6-Methoxycyclohexa-2,5 -Diene-1,4-Dione Against Lung Cancer Based on Network Pharmacology and Experimental Evaluation
Authors: Wang Lihui , Yang Xin , Song Qiong , Fu Jiejun , Wang Wenchu , Du Kechen , Chen Shuai , Cao Jinjin , Huang Renbin , Zou Chunlin 
Published: February 2021

Background: 2-Dodecyl-6-Methoxycyclohexa-2, 5-Diene-1,4-Dione (DMDD) was purified from the roots of Averrhoa carambola L. Previous research demonstrated that DMDD is a small molecular compound with significant therapeutic potential for tumors. However, the potential targets and pharmacological mechanism of DMDD to treat lung cancer has not been reported.Methods: We employed network pharmacology and experimental evaluation to reveal the pharmacological mechanism of DMDD against lung cancer. Potential therapeutic targets of DMDD were screened by PharmMapper. Differentially expressed genes (DEGs) in The Cancer Genome Atlas (TCGA) lung cancer data sets were extracted and analyzed by GEPIA2. The mechanism of DMDD against lung cancer was determined by PPI, gene ontology (GO) and KEGG pathway enrichment analysis. Survival analysis and molecular docking were employed to obtain the key targets of DMDD. Human lung cancer cell lines H1975 and PC9 were used to detect effects of DMDD treatment in vitro. The expression of key targets after DMDD treated was validated by Western Blot.Results: A total of 60 Homo sapiens potential therapeutic targets of DMDD and 3,545 DEGs in TCGA lung cancer datasets were identified. Gene ontology and pathway analysis revealed characteristic of the potential targets of DMDD and DEGs in lung cancer respectively. Cell cycle and pathways in cancer were overlapping with DMDD potential targets and lung cancer DEGs. Eight overlapping genes were found between DMDD potential therapeutic targets and lung cancer related DEGs. Survival analysis showed that high expression of DMDD potential targets CCNE1 and E2F1 was significantly related to poor patient survival in lung cancer. Molecular docking found that DMDD exhibited significant binding affinities within the active site of CCNE1 and E2F1. Further tests showed that DMDD inhibited the proliferation, migration and clone formation in lung cancer cell lines (H1975 and PC9) in a dose and time dependent manner. Mechanistically, DMDD treatment decreased the expression of CDK2, CCNE1, E2F1 proteins and induced cell cycle arrest at the G1/S phase in H1975 and PC9 cells.Conclusion: These results delineated that DMDD holds therapeutic potential that blocks tumorigenesis by cell cycle regulation in lung cancer, and may provide potential therapies for lung cancer.
Individual and Community Social Determinants of Health Associated With Diabetes Management in a Mexican American Population
Authors: Zhang Kehe , Reininger Belinda , Lee Miryoung , Xiao Qian , Bauer Cici 
Published: February 2021

Background: Diabetes is a major health burden in Mexican American populations, especially among those in the Lower Rio Grande Valley (LRGV) in the border region of Texas. Understanding the roles that social determinants of health (SDOH) play in diabetes management programs, both at the individual and community level, may inform future intervention strategies.Methods: This study performed a secondary data analysis on 1,568 individuals who participated in Salud y Vida (SyV), a local diabetes and chronic disease management program, between October 2013 and September 2018 recruited from a local clinic. The primary outcome was the reduction of hemoglobin A1C (HbA1C) at the last follow-up visit compared to the baseline. In addition to age, gender, insurance status, education level and marital status, we also investigated 15 community (census tract) SDOH using the American Community Survey. Because of the high correlation in the community SDOH, we developed the community-level indices representing different domains. Using Bayesian multilevel spatial models that account for the geographic dependency, we were able to simultaneously investigate the individual- and community-level SDOH that may impact HbA1C reduction.Results: After accounting for the diabetes self-management education classes taken by the participants and their length of stay in the program, we found that older age at baseline, being married (compared to being widowed or divorced) and English speaking (compared to Spanish) were significantly associated with greater HbA1C reduction. Moreover, we found that the community level SDOH were also highly associated with HbA1C reduction. With every percentile rank decrease in the socioeconomic advantage index, we estimated an additional 0.018% reduction in HbA1C [95% CI (−0.028, −0.007)]. Besides the socioeconomic advantage index, urban core opportunity and immigrant's cohesion and accessibility indices were also statistically associated with HbA1C reduction.Conclusion: To our knowledge, our study is the first to utilize Bayesian multilevel spatial models and simultaneously investigate both individual- and community-level SDOH in the context of diabetes management. Our findings suggest that community SDOH play an important role in diabetes control and management, and the need to consider community and neighborhood context in future interventions programs to maximize their overall effectiveness.
Urban Rail Transportation and SARS-Cov-2 Infections: An Ecological Study in the Lisbon Metropolitan Area
Authors: Severo Milton , Ribeiro Ana Isabel , Lucas Raquel , Leão Teresa , Barros Henrique 
Published: February 2021

Introduction:The large number of passengers, limited space and shared surfaces can transform public transportation into a hub of epidemic spread. This study was conducted to investigate whether proximity to railway stations, a proxy for utilization, was associated with higher rates of SARS-CoV-2 infection across small-areas of the Lisbon Metropolitan Area (Portugal).Methods:The number of SARS-CoV-2 confirmed infections from March 2 until July 5, 2020 at the parish-level was obtained from the National Epidemiological Surveillance System. A Geographic Information System was used to estimate proximity to railway stations of the six railway lines operating in the area. A quasi-Poissongeneralized linear regression model was fitted to estimate the relative risks (RR) and corresponding 95% confidence intervals (95%CI).Results:Between May 2 and July 5, 2020, there were a total of 17,168 SARS-CoV-2 infections in the Lisbon Metropolitan Area, with wide disparities between parishes. Overall, parishes near any of the railway stations of theSintraline presented significantly higher SARS-CoV-2 infection rates (RR= 1.42, 95%CI 1.16, 1.75) compared to parishes located farther away from railway stations, while the opposite was observed for parishes near other railway stations (SadoandFertaguslines), where infection rates were significantly lower than those observed in parishes located farther away from railway stations (RR= 0.66, 95%CI 0.50, 0.87). The associations varied according to the stage of the epidemic and to the mitigation measures enforced. Regression results also revealed an increasing influence of socioeconomic deprivation on SARS-CoV-2 infections.Conclusions:No consistent association between proximity to railway stations and SARS-CoV-2 infection rates in the most affected metropolitan area of Portugal was observed, suggesting that other factors (e.g., socioeconomic deprivation) may play a more prominent role in the epidemic dynamics.
ANALISIS YURIDIS PENEMUAN HUKUM TERHADAP PUTUSAN MAHKAMAH KONSTITUSI NOMOR 46/PUU-VIII/2010 TERHADAP ANAK YANG DILAHIRKAN DI LUAR PERKAWINAN YANG SAH
Authors: Risa Yulia 
Published: January 2021

Putusan Nomor 46/PUU-VIII/2010 tanggal 17 Februari 2012, telah melakukan terobosan hukum dengan memutuskan bahwa Pasal 43 ayat (1) UU No. 1 Tahun 1974 tentang Perkawinan bertentangan dengan UUD 1945. Dalam amar putusannya, MK menyatakan Pasal 43 ayat (1) UU Perkawinan tersebut bertentangan dengan UUD 1945 sepanjang dimaknai menghilangkan hubungan dengan laki-laki yang dapat dibuktikan melalui ilmu pengetahuan dan teknologi dan/atau alat bukti lain ternyata mempunyai hubungan darah sebagai ayahnya. Berdasarkan Putusan Mahkamah Konstitusi yang demikian itu menimbulkan konsekuensi hukum yang cukup mendasar dalam kehidupan masyarakat disebabkan putusan Mahkamah Konstitusi tersebut telah merubah konstruksi hukum ketentuan anak luar kawin sebagaimana dimaksud Pasal 43 ayat (1) UU Perkawinan menjadi diperluas tidak hanya anak yang lahir diluar perkawinan yang tidak dicatatkan saja tetapi juga anak yang lahir dari suatu hubungan yang tanpa ikatan atau hubungan yang insidentil, termasuk anak zina dan anak sumbang.
Keyword: Penemuan Hukum, Putusan Mahkamah Konstitusi Tentang Status Anak Luar Kawin.
Forage Advantages of the Eastern Galega Green Mass Depending on the Cuttings
Authors: Степаненко А.В. , Зенькова Н.Н. 
Published: February 2021

Представлены данные по урожайности и качественному составу зелёной массы галеги восточной. Установлено, что культура является высокоурожайной и в почвенно-климатических условиях северного региона Республики Беларусь обеспечивает три полноценных укоса, сформировав урожайность 484 ц/га зелёной массы. Максимальная урожайность зелёной массы (230 ц/га) была получена в первом укосе, что составило 47,5% от общей урожайности. Во втором укосе галега восточная по урожайности уступила первому укосу на 34,8% и сформировала 150 ц/га (31% от общей урожайности). Третий укос обеспечил 104 ц/га зелёной массы, или 21,5% от общей урожайности. Всего за три укоса галега восточная обеспечила общий сбор кормовых единиц с 1 га посева 98,1 ц/га: в первом укосе – 50,6 ц/га, во втором – 28,8 ц/га и в третьем укосе – 18,7 ц/га. Третий укос уступил второму на 54,0%, первому – в 2,7 раза. Общий сбор переваримого протеина с 1 га зелёной массы галеги восточной составил 15,6 ц /га: в первом укосе – 8,6 ц/га, во втором – 4,2 ц/га и в третьем – 2,8 ц/га. Сбор переваримого протеина в первом укосе составил 74% от общего сбора. Обеспеченность 1 корм. ед. зелёной массы галеги восточной переваримым протеином в среднем за вегетационный период составила 159 г, что превысило зоотехническую норму на 39–54 г. В первом укосе она составила 169 г, что выше, чем во втором укосе (146 г) на 16% и в третьем укосе (149) – на 13%.
Data on yield and quality composition of the Eastern galega green mass are presented. It has been established that the crop is high-yielding and in the soil-climatic conditions of the northern region of the Republic of Belarus provides three complete cuttings having formed a yield of 484 c/ha of green mass. The maximum yield of green mass (230 c/ha) was obtained in the first growth which amounted to 47.5% of the total yield. In the aftergrass the Eastern galega in terms of yield gave way to the first growth by 34.8% and formed 150 c/ha (31% of the total yield). The third hay crop provided 104 c/ha of green mass or 21.5% of the total yield. Just in three cuttings the Eastern galega provided the total harvest of fodder units from 1 hectare of sowing 98.1 c/ha: in the first growth - 50.6 c/ha, in the second – 28.8 c/ha and in the third cutting – 18.7 c/ha. The third cutting yielded to the second by 54.0%, to the first – 2.7 times. The total harvest of digestible protein from 1 hectare of the green mass of the Eastern galega was 15.6 c/ha: in the first growth – 8.6 c/ha, in the second - 4.2 c/ha and in the third – 2.8 c/ha. The digestible protein harvest in the first growth was 74% of the total harvest. Availability of 1 fodder unit of green mass of the Eastern galega by digestible protein averaged 159 g over the growing season which exceeded the zootechnic norm by 39–54 g. In the first growth it amounted to 169 g which is 16% higher than in the second aftergrass (146 g) and in the third cutting (149) – by 13%.