bluuebunny/crossref_metadata_2025_split huggingface dataset:
Kekaburan Norma dalam Pasal 55 Undang-Undang Nomor 24 Tahun 2011 Tentang Badan Penyelenggaraan Jaminan Sosial
Authors: Winarno Andrias , Bambang Sugiri Bambang , Cholil Yuliati 
Published: October 2021

AbstractThe issues that will be examined in this article relate to the vagueness of norms in Article 19 paragraph (1) and paragraph (2) in conjunction with Article 55 of the BPJS Law. The confusion of norms occurs because there are no clear boundaries regarding the elements in the article so that in practice there is some information that can be provided in BPJS contributions. This paper will examine what actually urges criminal acts in the BPJS Law and what the concept of classification should be. This article uses a normative legal research method with a statute approach and a conceptual approach. The results show that the urgency of regulating criminal acts in Article 55 of the BPJS Law includes legal certainty, authority, and legal benefits. The ideal concept of conception can be arranged in the aspect of the table, from light to heavy with a certain time limit.Keywords: Obscurity Norm; BPJS Law; Classification of Crime.AbstrakPermasalahan yang akan dikaji dalam artikel ini berkaitan dengan kekaburan norma dalam Pasal 19 ayat (1) dan ayat (2) juncto Pasal 55 UU BPJS. Kekaburan norma tersebut terjadi karena dianggap tidak adanya batasan yang jelas mengenai unsur-unsur pelanggaran pada pasal tersebut sehingga dalam prakteknya terdapat beberapa pelanggaran keterlambatan perusahaan dalam membayar iuran BPJS. Tulisan ini akan menelaan apa sesunggunya urgensi klasifikasi tindak pidana dalam UU BPJS dan bagaimana konsep ideal klasifikasi yang seharusnya. Artikel ini menggunakan metode penelitian hukum normatif dengan pendekatan perundang-undang dan pendekatan konseptual. Adapun hasil penelitian menunjukkan bahwa urgensi diaturnya klasifikasi tindak pidana dalam Pasal 55 UU BPJS meliputi kepastian hukum, efektivitas norma dan kemanfaatan hukum. Konsep ideal klasifikasi dapat meliputi pengaturan di aspek keterlambatan, mulai dari ringan hingga berat dengan batasan waktu tertentu.Kata Kunci: Kekaburan Norma; UU BPJS; Klasifikasi Tindak Pidana.
Transition Metal-Ions Incorporated PEG300 and TDI Based Hydroxy-Terminated Polyurethanes
Authors: Laxmi  , Shahzaib Adnan , Khan Shabnam , Ghosal Anujit , Zafar Fahmina , Alam Manawwer , Nami Shahab A. A. , Nishat NAHID 
Published: October 2021

Abstract
Present work reports the synthesis of polyethylene glycol, PEG 300 (soft segment) and toluene 2,4-diisocyanate, TDI (hard segment) based hydroxy-terminated polyurethane ligands (HTPU300) for the first time to the best of our knowledge. The effect of 3d transition metal ions with different 3d electrons within HTPU (M(II)-HTPU300, M= Mn, Co, Ni, and Zn) was evaluated by their physical and antibacterial studies of the final complex polymeric unit. M(II) HTPU300 and was conveniently synthesized in appreciable yields following a facile and one-pot addition polymerization reaction scheme. Foremost the thermal stability of all the M(II)-HTPU300 polymeric materials were evaluated using TGA, DSC, and IPDT calculations. FTIR technique was used to ascertain the structure of M(II)-HTPU300, while SEM/EDX and XRD techniques were used to study their morphology, elemental analysis, and crystalline nature of the material, respectively. Further, the in-vitro antimicrobial activity of the PU was investigated against gram-positive (Staphylococcus aureus, Bacillus subtilis) and gram-negative (Escherichia coli and Pseudomonas aeruginosa) bacterial strains. The comparatively moderate efficacy against bacterial stain supports the possible application of such PU as thermally stable bacterial resistant materials constructed out of degradable PEG.
Predicting Suitable Habitats of Melia Azedarach L. Using Data Mining
Authors: Feng Lei , Tian Xiangni , El-Kassaby Yousry A. , Qiu Jian , Feng Ze , Sun Jiejie , Wang Guibin , Wang Tongli 
Published: October 2021

Abstract
Background: Melia azedarach L. is a globally distributed tree species of economic importance; however, it is unclear how the species distribution will respond to future climate changes.Methods: We aimed to select the most accurate one among seven data mining models to predict the species suitable contemporary and future habitats. These models include: maximum entropy (MaxEnt), support vector machine (SVM), generalized linear model (GLM), random forest (RF), naive bayesian model (NBM), extreme gradient boosting (XGBoost), and gradient boosting machine (GBM). A total of 906 M. azedarach locations were identified, and sixteen climate predictors were used for model building. The models’ validity was assessed using three measures (Area Under the Curves (AUC), kappa, and accuracy). Results: We found that the RF provided the most outstanding performance in prediction power and generalization capacity. The top climate factors affecting the species distribution were mean coldest month temperature (MCMT), followed by the number of frost-free days (NFFD), degree-days above 18°C (DD>18), temperature difference between MWMT and MCMT, or continentality (TD), mean annual precipitation (MAP), and degree-days below 18°C (DD<18). We projected that future suitable habitat of this species would increase under both the RCP4.5 and RCP8.5 scenarios for the 2020s, 2050s, and 2080s.Conclusion: Our findings are expected to assist in better understanding the impact of climate change on the species and provide scientific basis for its planting and conservation.
Evolutionary trajectory and origin of SARS-CoV-2 variant
Authors: Wang Anyou 
Published: October 2021

Abstract
Alignment-based quality attributes have identified several variants of SARS-CoV-2(severe acute respiratory syndrome coronavirus 2) that causes COVID-19 pandemic, but they face challenges to provide dynamic trajectory and origin of these variants. This study employs an alignment-free approach combining Fréchet distance (Fr) and artificial recurrent neural network to reveal evolutionary trajectory and origin of SARS-CoV-2 variant. Fr generates a distance matrix of 84 genome features and more than one million of genome sequences. Recurrent neural networks use this Fr matrix to quantitatively identify variants and reveal the evolutionary trajectory and origin of SARS-CoV-2. Total 34 SARS-CoV-2 variants have been identified. All these variants dynamically delete their genome during evolution, but their trajectory and deletion degree varies with individual variants, which can be classified into 3 groups, slight mutation group (13 members), middle level deletion (17 members), and high deletion (4 members). The slight deletion group works like wild type and its trajectory waves only slightly and temporarily, which has very low infection capacity. The high deletion group fluctuates with a rough trajectory characterized as a large loss and it also infects humans lightly. The middle deletion group gradually deletes their genome with a certain rhythm trajectory, corresponding to the pandemic peaks. This group causes most of the global COVID-19 cases. At least 3 mink coronavirus variants pose 56 genome features similar to SARS-CoV-2 and they are predicted to be able to infect human, and thus mink is the most likely origin of SARS-CoV-2, and the origin path follows this order: mink, cat, tiger, mouse, hamster, dog, lion, gorilla, leopard, bat, and pangolin. Therefore, this mink-origin SARS-CoV-2 evolves with a gradual deletion rhythm to infect humans
Risk Factors for Typical Endometrial Polypoid Adenomyoma
Authors: Wang Xinmei , Zhang Hongyuan , Xu Juan , Qu Pengpeng 
Published: October 2021

Abstract
Objective: Typical endometrial polypoid adenomyoma (TPA) is a rare type of lesion in the uterine cavity or cervical canal. Although the clinical and pathologic features of TPA have been described extensively, reports on its pathogenesis and treatment remain inconclusive. This study was conducted to investigate the risk factors for endometrial TPA and recurrence and to further define the pathogenesis and treatment.Study design: This was a retrospective analysis of 488 cases of TPA and 500 cases of normal endometrium. Age, menopausal status, body mass index (BMI), reproductive history, and method of surgery were retrospectively analyzed. Among TPA cases, 360 were treated by conservative surgery. Risk factors for TPA and recurrence were assessed.Results: There was a significant difference in age, menopausal status, BMI, gravidity, and parity between the two groups (P<0.05). Age >50 years, menopause, obesity, gravidity >3, and parity >2 were risk factors for TPA (P<0.05). The incidence rate of endometriosis and adenomyosis in the TPA group was significantly higher than that in the normal endometrium group (P<0.05). Follow-up data (22–77 months) were obtained for 360 patients, revealing gravidity >3, menopause, curettage, and polyp clamp as independent risk factors for the recurrence of TPA (P<0.05). Conclusions: In addition to high estrogen levels, endometrial injury was the main contributor to TPA pathogenesis. Hysteroscopic electrotomy was the preferential treatment for TPA to avoid recurrence, especially for women with risk factors. Increasing the depth of ablation may prevent the recurrence of TPA more efficiently.
Metabolomic Profiling of Five Hulless Barley with Different Seed Coat Colors
Authors: Liang Lijing , Li Wenbo , Tian Min , Pan Jiajia , Feng Zongyun 
Published: October 2021

Abstract
Colored hulless barley (Hordeum vulgare L.) is a high-quality germplasm resource that is rich in nutrients, such as protein, β-glucan, flavonoids, amino acids, vitamins, microelements, and dietary fiber. However, a systematic evaluation of the metabolites present in colored cultivars is lacking. This study employed an untargeted metabolomics approach using ultra-high-performance liquid chromatography-tandem mass spectrometry (LC-MS) to analyze the metabolic profiles of five hulless barley cultivars with different grain colors. Six-hundred and eight metabolites in various chemical categories were detected; ABC transporters, flavonoid biosynthesis, and anthocyanin biosynthesis were found to be the most significant metabolic pathways. Principal component analysis and orthogonal partial least squares-discriminant analysis revealed significant metabolic differences among the samples, and the colored barley cultivars could be separated from white barley. Black, blue, and purple grains rich in natural antioxidants were identified as promising ingredients for the development of cereal-based functional foods. These findings showed that the nutritional function and quality of hulless barley were strongly correlated with its natural color, thereby improving our understanding of the metabolic mechanisms and functional health value associated with different seed coat colors in different hulless barley cultivars. Our results thus provide a theoretical basis for the future study of hulless barley-related products.
Highly Effective Adsorption of Caffeine by a Novel Activated Carbon Prepared From Coconut Leaf
Authors: Oliveira Elvio N. , Meneses Alex T. , de Melo Samara F. , Dias Franciele M. R. , Perazzini Maisa T. B. , Perazzini Hugo , Meili Lucas , Soletti João I. , Carvalho Sandra H. V. , Bispo Mozart D. 
Published: October 2021

Abstract
The disposal of coconut wastes is costly and damaging to the environment, but its uses are advantageous activated carbons production. Coconut leaves waste were used for activated carbon production by pyrolysis at 500º C and activation with potassium carbonate. The activated carbon was used for caffeine removal from aqueous solution. The coconut leaves activated carbon showed a predominantly amorphous structure from X-ray diffraction analysis and a pH at the zero charge point of 7.9. From the N2 adsorption/desorption method, the adsorbent showed a predominance of mesopores, with average pore size of 45.48 ηm and a surface area of 678.03 m2/g. From kinetic studies the data followed the pseudo-second order, where the intraparticle diffusion can be neglected. The adsorption isotherms were satisfactorily adjusted for the Redlich-Peterson model and a type curve L was identified. The thermodynamic parameters showed that adsorption occurred spontaneously, was exothermic and governed by physical adsorption. The artificial neural networks developed were capable of predicting both kinetics and equilibrium adsorption data under different operating conditions and was comparable to the traditional models available in literature in the training experiments, encouraging its use for data generalization when an efficient dataset is used. In conclusion, coconut leaves waste showed to be a promising feedstock to produce activated carbon aiming caffeine removal from water and wastewater.
Removal and Adsorption Mechanism of Tetracycline Using Manganese-modified Cotton Straw Biochar in an Aqueous Solution
Authors: Liu Xiao , Shi Shaoyang , Hu Xuefei , Sun Tao , Zhang Juanxiang , Li Fayong 
Published: October 2021

Abstract
Farming in China’s rural areas leads to antibiotic pollution in waterbodies making it a grave issue. Cotton straw biochar (CSBC) was prepared by oxygen-limited pyrolysis at 400 °C (CSBC400) and 600 °C (CSBC600); and Mn-modified CSBC (MCSBC) was produced by the KMnO4 wrapping method for tetracycline (TC) removal from aqueous solutions. The effects of temperature, initial solution concentration, pH, ion type, and ionic strength on TC adsorption were investigated. The adsorption process of the biochars achieved an equilibrium state after 360 min, and the highest equilibrium adsorption amount (13.254 mg/g) was found for MCSBC. The kinetic adsorption process, which was dominated by chemisorption, was well-described by the pseudo-second-order kinetic model. The adsorption was a non-homogeneous heat absorption process, and the adsorption isotherm data fitting was compatible with the Freundlich model. A better adsorption effect of MCSBC was observed when the pH was < 4. Monovalent cations (Na+, K+, NH4+, and Ca2+) had a facilitative effect on the adsorption process. The adsorption mechanisms of TC by MCSBC included pore diffusion, H bonding, electrostatic interactions, and π–π accumulation. Therefore, MCSBC has a good adsorption capacity for TC and can be used for the treatment of TC-based pollutants in aqueous environments.
Role of Liver Biopsy in Management of Liver Diseases Following End of the Interferon Era: Experience of A Tertiary Referral Centre
Authors: Ehsan Nermine A , Elsabaawy Maha M , Sweed Dina M , Karman Esraa A , Abdelsameea Eman , Mohamed Anwar A 
Published: October 2021

Abstract
Background: Liver biopsy (LB) is the cornerstone in the management of patients with liver diseases. However, a lot of queries had emerged about its role following the end of the interferon era. The aim of this study was to re-evaluate the current role of LB in the diagnosis of liver diseases. Methods: All patients who had underwent LB at the department of Hepatology, National Liver Institute, from January 2015 through December 2018 were recruited. Indications for LB, pathology reports, and medical records of all cases were retrieved, reviewed and statistically analyzed. Results: A total of 275 liver biopsies were collected, 191 males and 84 females with mean age 41.22±13.36 years. Etiological diagnosis made by histopathological evaluation was 48 drug induced liver injury (DILI), 42 Non-alcoholic fatty liver disease (NAFLD), 34 chronic hepatitis B, or C with cholestasis, 29 autoimmune hepatitis, 34 primary sclerosing cholangitis, 13 primary biliary cholangitis, 7 autoimmune overlap syndrome, 13 active bilharziasis, 10 Wilson’s disease. Minor number of cases were diagnosed by different other etiologies. Initial diagnosis was made by liver biopsy and confirmed by clinical response and laboratory findings. Conclusion: Liver biopsy is still considered as the gold standard diagnostic measure of different liver diseases representing an integral component of management decisions in hepatology.
Prediction of Alzheimer Disease Using Pearson Recursive Graph Convolutional Neural Network
Authors: Roobini M.S , Lakshmi M. 
Published: October 2021

Abstract
Alzheimer diseases are very hard to identify at beginning stage and also medication is available. So, the only way to protect those people is to predict the Alzheimer disease before it reaches the peak. More studies in diabetes show that there is a link between Diabetes and Alzheimer. Initially the prediction of diabetes is done using most relevant parameters, which detects the Diabetes. Then the severity level of diabetes is identified using some scoring levels. Based on scoring levels of diabetes, it is classified in to Type1 and Type2 using Machine Learning algorithms. When Diabetes reaches a worst case, it may affect any organs in the human body, whereas Type 2 Diabetes has associated with rare diseases which literally affects the brain and leads to cognitive impairment. After predicting the patients having cognitive impairment by applying classification algorithms are further examined to check whether it leads to Alzheimer disease. For this prediction the most relevant parameters which are common to Diabetes and Alzheimer is identified. Further identified parameters are used for prediction of Alzheimer disease with high accuracy which is helpful for taking precaution measures. In this proposed work, the most relevant features are selected using Pearson correlation-based feature elimination method and the diagnosis of the diabetes are carried using the Graph convolutional neural network (GCN). The measures of performance of the proposed work are calculated with various factors like Sensitivity measure, Recall, Precision, F-Measure. Proposed has achieved highest of 98.91%, 97.01%, 98.62%, 98.91% in above metrics.
Biogeochemical Effects of a Forest Understory Plant Invasion Depend More On Dissimilar Nutrient Economies Than Invader Biomass
Authors: Podzikowski Laura Y , Lee Marissa , Fahey Catherine , Wright Justin , Flory S. Luke , Phillips Richard P. 
Published: October 2021

Abstract
There is an increasing need to better understand how and why invasion impacts differ across heterogeneous landscapes. One hypothesis predicts invader impacts are greatest where the invader is most abundant (the mass ratio hypothesis; MRH). Alternatively, invader impacts may be greatest in communities where the nutrient acquisition strategies of the invader are most dissimilar from those of native species (the nutrient economy dissimilarity hypothesis; NEDH). We tested whether the effects of an invasive grass, Microstegium vimineum, on soil biogeochemistry were best explained by MRH, NEDH, or both. At three locations (Indiana, North Carolina, and Georgia), invaded and reference plots were established across a nutrient economy gradient. Plots varied in the relative abundance of arbuscular mycorrhizal (AM) vs. ectomycorrhizal (ECM) associated overstory trees, reflecting gradients in biotic nutrient acquisition strategies and edaphic factors. At two locations, we found NEDH predicted invader effects on soil conditions. The net effect of M. vimineum homogenized soil properties across the nutrient economy gradient towards conditions consistent with AM-dominated stands; as such, the nutrient economy gradients observed in uninvaded plots were mostly absent in invaded plots. At one location with high N availability and intermediate acidity, both ECM-dominance (NEDH) and invader abundance (MRH) predicted differences in soil moisture, pH, and nitrification rates. Collectively, these results suggest the biogeochemical consequences of M. vimineum depend, in part, on pre-invasion soil nutrient economies. Where pre-invasion conditions are known, we provide a scalable and predictive approach to determine where impacts on biogeochemical cycling of C and N may be greatest.
Analysis of Prognostic Factors Influencing Survival and Recurrence in Breast Cancer: A Hybrid Machine Learning Approach
Authors: Lee Jae Bin , Choi Jihye , An Mi Sun , Kim Jong-Yeup , Kwon Seong Uk , Kim Jungeun , Lee Seunghee , Jeon Seongwoo , Lee ChungChun , Lee Suehyun , Woo Hyekyung 
Published: October 2021

Abstract
Purpose: The present study sought to identify prognostic factors for breast cancer survival and recurrence using a machine learning approach and electronic medical record data.Methods: We used a machine learning technique called feature selection to identify factors influencing breast cancer prognosis, and factors affecting survival and recurrence in a Cox regression model. Results: History of relapse, type of surgery, diagnostic route, SEER stage, and hormone therapy all affected breast cancer survival. Recurrence of breast cancer was affected by age, history of diabetes, breast reconstruction, pain, breast lumps, nipple discharge, and the presence of other symptoms. According to the survival analysis based on feature selection, patients with diabetes had a significantly higher risk of early recurrence of breast cancer (hazard ratio, 4.8; 95% confidence interval, 2.04–11.2, p < 0.05). Conclusions: The present study identified several factors associated with breast cancer prognosis. While survival was affected by the diagnostic route, recurrence was primarily influenced by breast cancer symptoms and other underlying health conditions. A more accurate and standardized model considering time-to-event data could be developed in the future to evaluate prognostic factors and predict prognoses, and for clinical validation
Laparoscopic Anatomical Resection of Liver Segment 8 via a Hepatic Parenchymal Transection-first Approach Guided by the Middle Hepatic Vein
Authors: You Nan , Wu Ke , Li Jing , Zheng Lu 
Published: October 2021

Abstract
Background Although recent technological developments and improved endoscopic procedures have further extended the application of laparoscopic liver resection, pure laparoscopic anatomic resection of liver segment 8 (S8) is still rarely performed due to the lack of an appropriate surgical approach. This article discusses the technical tips and operation methods for laparoscopic anatomical resection of liver S8 via a hepatic parenchymal transection-first approach.Methods Clinical data of 14 patients who underwent laparoscopic anatomical resection of liver segment 8 via a hepatic parenchymal transection-first approach guided by the middle hepatic vein (MHV) in the Second Affiliated Hospital, Third Military Medical University (Army Medical University) from May 2017 to December 2019 were retrospectively analyzed. The operation time, intraoperative blood loss, postoperative complications, and hospitalization duration were observed.Results The operation was successful with no complications. No other abnormality was noted during outpatient follow-up examination.Conclusions Laparoscopic anatomical resection of liver S8 is still quite challenging at present, and it is our goal to design a reasonable procedure with accurate efficacy and high safety. We use hepatic parenchymal transection-first approach guided by the MHV for laparoscopic anatomical resection of liver S8. This technique overcomes the problem of high technical risk, greatly reduces the surgical difficulty and achieves technological breakthroughs, but there are still many problems worth further exploration.