bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hak dan Kewajiban Suami Istri Dalam Perspektif Tafsir Klasik Dan Kontemporer
Authors: Masruchin Masruchin , Nuraeni Wiwin 
Published: January 2022

<p class="05Abstrak">Abstrak</p><p class="06IsiAbstrak">Memaknai lafadz dalam al-Qur’an membutuhkan sebuah pemahaman yang pasti, terutama dalam memaknai hak dan kewajiban antara suami dan istri dalam berumahtangga. Untuk mencapai harapan dalam berumahtangga, semua pasangan menginginkan bagaimana menciptakan keluarga yang harmonis. Dan untuk itu diperlukan suatu keseragaman pemahaman tentang hak dan kewajiban antara suami dan istri. Melalui tulisan ini, peneliti ingin mengkaji makna hak-hak tersebut melalui kajian tafsir baik tafsir klasik maupun kontemporer. Dengan menggunakan metode deskriptif-komperatif, penulis menerapkan kajian analisis dengan menerapkan beberapa kajian dari mufassir klasik hingga kontemporer. Dari kajian tersebut menghasilkan bahwa untuk menuju kebahagiaan yang harmonil dalam berumahtangga harus saling menghargai agar terjalin kehidupan yang sakinah, mawaddah wa rahmah.</p><p class="07KatakunciKeywords"><strong>Kata kunci</strong>: Hak dan Kewajiban, Sakinah, Mawaddah, Rahmah</p><p class="05Abstrak">Abstract</p><p class="06IsiAbstrak">Interpreting lafadz in the Qur'an requires a definite understanding, especially in interpreting the rights and obligations between husband and wife in marriage. To achieve hope in marriage, all couples want how to create a harmonious family. And for that we need a uniform understanding of the rights and obligations between husband and wife. Through this paper, the researcher wants to examine the meaning of these rights through the study of interpretations of both classical and contemporary interpretations. By using descriptive-comparative method, the author applies an analytical study by applying several studies from classical to contemporary commentators. From this study, it is found that in order to achieve harmonious happiness, mutual respect is needed so that a sakinah, mawaddah wa rahmah life can be established.</p><em>Keywords</em>: Rights and Obligations, Sakinah, Mawaddah, Rahmah
Living a Happy Life and Prosperity for Scavengers
Authors: Hutapea Bonar , Ayun Tasya Qurrata , Cherika Cherika , Natashya Regina , Noviana Ricka , Soedaryo Susanthy 
Published: January 2022

The Social Welfare Issuer (PMKS) is a person or family who, because of an obstacle, difficulty or disruption, can not carry out their social functions and therefore can not establish a harmonious and creative relationship with their environment so that they can not fulfill their (physical, spiritual and social) needs adequate and reasonable (Thamrin, Masril & Sembiring, 2016). This research has a point to find out how an illustration the depth to live happily and prosperous people the scavengers. A method is executed by qualitative narrative, by interview depth and observation. Researchers had conducted interviews with two subjects that work as scavengers. Results in getting is the depth to live happily of both the subject of very simple with the fulfill of needs and there is also social security for them. They could only fulfill their needs by gathering used goods erratic the amounts of each day and it becomes happiness its own for both subject. However in fact what happens is that social services agency and the central administration has not given a guarantee or assistance which could be used by both subject. Researchers advice for governments is to give the assurance that it is set in accordance with law social welfare, so that the scavengers can receive their rights .
INSIGHTS FROM FOSSIL FISH TAPHONOMY INTO THE DEPOSITIONAL ENVIRONMENT OF THE LOWER MILWAUKEE FORMATION (BERTHELET MEMBER, LATEST MIDDLE DEVONIAN)
Authors: RICH ANDREW J. , ZAMBITO JAMES J. 
Published: January 2022

ABSTRACTThe fossiliferous, argillaceous dolostone of the latest Middle Devonian (Givetian) Milwaukee Formation contains abundant disarticulated fish skeletal elements. This study refines depositional environment reconstruction of the Milwaukee Formation through taphonomic analysis of this fish assemblage. Robust skeletal elements of placoderm grinding teeth, fin spines, and armored plating dominate the assemblage. Specimens display variation in taphonomic attributes including color, luster, corrasion (chemical corrosion and/or physical abrasion), presence of pyrite and phosphate permineralization, and epibionts. Rare occurrences of teeth belonging to osteichthyan fish are also taphonomically variable. Associated invertebrates are diverse and include abundant cephalopod internal molds and pyritized brachiopods often randomly oriented in shell hashes. In sum, these observations suggest deposition on a marine shelf between normal and storm wave base. During low-energy background periods, fish plates exposed on the seafloor would undergo initial disarticulation, epibiont attachment, and color- and luster-altering corrasion and phosphatization. Buried skeletal elements were ‘protected' from epibiont attachment and corrasion, but occasional low oxygen conditions in the substrate led to early diagenetic pyrite permineralization. Periodic high-energy storm events were responsible for complete disarticulation as well as reworking and reexposure of buried skeletal elements (and burial of others), resulting in a time-averaged assemblage with a wide range of taphonomic attributes. Robust placoderm skeletal elements were best suited to survive fossilization in this setting and therefore the placoderm-dominated fossil assemblage appears to be an artifact of taphonomic processes and energy of the depositional environment.
AnchoisFert: A New Organic Fertilizer from Fish Processing Waste for Sustainable Agriculture
Authors: Muscolo Adele , Mauriello Francesco , Marra Francesca , Calabrò Paolo Salvatore , Russo Mariateresa , Ciriminna Rosaria , Pagliaro Mario 
Published: January 2022

Abstract
The “AnchoisFert” solid residue comprised of milled anchovy leftovers after fish oil extraction with biobased limonene is a powerful organic fertilizer. Employed to promote the growth of Tropea’s red onion (Allium cepa), the fertilizer turns out to largely superior to commonly used organic (manure) and chemical (NPK) fertilizers. Rich in proteins, organic carbon, flavonoids, magnesium, potassium, phosphate and sulphate, and devoid of antibiotics and antibiotic resistance genes, the new organic fertilizer can replace both conventional organic and inorganic fertilizers. The discovery closes the fishing material cycle for one of the most fished species across the seas opening the route to a new class of organic fertilizers of exceptional performance derived from abundant biowaste via a low-cost, environmentally-friendly circular economy process.
Individual Risk Factors of Mycetoma Occurrence in Eastern Sennar Locality, Sennar State, Sudan: A Case-Control Study
Authors: Hassan Rowa , Deribe Kebede , Simpson Hope , Bremner Stephen , Bakheet Osama Elhadi , Alnour Mustafa , Fahal Ahmed Hassan , Newport Melanie , Bakhiet Sahar 
Published: January 2022

Abstract
Mycetoma is a serious chronic subcutaneous granulomatous inflammatory disease that is endemic in tropical and subtropical regions where it impacts profoundly on patients, families, and communities. Individual-level risk factors for the disease are poorly understood. To address this, a case-control study was conducted based on data collected from 60 villages in Eastern Sennar Locality, Sennar State, Sudan. Based on the presence of swelling in any part of the body, or sinus formation with or without grain discharge evident from the lesion by ultrasound examination, we diagnosed 359 cases of mycetoma. For each case, we included three healthy sex-matched persons, with no evidence of mycetoma, from the same village as the controls group (n=1077). The odds for mycetoma were almost three times higher in individuals in the age group 16-30 years (Adjusted Odds Ratio (AOR) = 2.804, 95% CI= 1.424 – 5.523) compared to those in age group ≤15 years. Other factors odds of mycetoma were history of local trauma (AOR =1.892, 95% CI= 1.425 – 2.513), being unmarried (AOR =3.179, 95% CI= 2.339 – 4.20) and owning livestock (AOR =3.941, 95% CI= 2.874 – 5.405). In conclusion, certain factors found to be associated with mycetoma in this study could inform a high index of suspicion for mycetoma diagnosis, which would improve early case detection. Other factors found to be associated could inform the development of an interventional program for mycetoma control in Sudan, including education on healthy farming practices and the risks of puncture wounds for individuals residing in endemic areas. However, this work was conducted in one endemic state, while mycetoma cases occur in all states of Sudan. Replicating this study over a wider area would give a fuller picture of the situation, providing the control program with more comprehensive information on the risk factors for the disease.
Health-care Supplier Selection using Hybrid Multi-criteria Decision Making Methods : A Case Study from Morocco
Authors: AZIZ layla , ÇALIK Ahmet 
Published: January 2022

Abstract
Several studies have been conducted in the context of selecting the best supplier. In literature, the supplier selection problem has been widely studied using different approaches. Multi Criteria decision making(MCDM) is one of the frequently exploited tools for achieving this study. Health-care sector represents a vital priority for decreasing risks. However, it is rarely treated by the research community. In this work, we present three hybrid multi-criteria methods (Analytic hierarchy process-technique for order preference by similarity to ideal solution) AHP-TOPSIS, ( Pythagorean fuzzy analytic hierarchy process-technique for order preference by similarity to ideal solution (PFAHP-TOPSIS) and Best worst method-technique for order preference by similarity to ideal solution(BWM-TOPSIS)) for making the efficient health-care supplier selection.This study is mainly composed of two stages: the first one consists of calculating of the weight priority of each criterion and sub-criterion using AHP, BWM, and PFAHP methods, while the second stage aims to integrate the weights priorities for making the ranking of the alternatives using TOPSIS method. Moreover, we present the sensitivity analysis for the three integrated tools to evaluate the ranking of suppliers under the variation of the weights of criteria. This study was conducted in a public hospital from Marrakech city
In Silico Mutational Analysis of ACE2 to Check the Susceptibility of Lung Cancer Patients Towards COVID-19
Authors: Khalid Zumama , Khan Abeedha Tu-Allah , Alnajjar Radwan , Santali Eman , Shakoori Abdul Rauf 
Published: January 2022

Abstract
Being the second major cause of death worldwide, lung cancer might pose a significant threat to the health of patients especially during this era of pandemic as they are found to be more prone to COVID-19. Although many recent studies imply a high frequency of COVID-19 infection associated severe outcome, however the molecular studies are still lacking in this respect. Hence the current study is designed to investigate the binding affinities of ACE2 lung cancer mutants with the viral spike protein to find the susceptibility of respective mutants carrying patients in catching the virus. Quite interestingly, our study found lesser binding affinities of all the selected mutants thus implying that these cancer patients might be less affected by the virus than others. These results are opposed to the recent studies’ propositions and open new avenues for more in-depth studies.
Feature Extraction from MRI ADC Images for Brain Tumor Classification Using Machine Learning Techniques
Authors: Vijithananda Sahan M. , Jayatilake Mohan L. , Hewavithana Badra , Gonçalves Teresa , Rato Luis M. , Weerakoon Bimali S. , Kalupahana Tharindu D. , Silva Anil D. , Dissanayake Karuna D. 
Published: January 2022

Abstract
Background: Diffusion-weighted (DW) imaging is a well-recognized magnetic resonance imaging (MRI) technique that is being routinely used in brain examinations in modern clinical radiology practices. This study focuses on extracting demographic and texture features from MRI Apparent Diffusion Coefficient (ADC) images of human brain tumors, identifying the distribution patterns of each feature and applying Machine Learning (ML) techniques to differentiate malignant from benign brain tumors. Methods: This prospective study was carried out using 1599 labeled MRI brain ADC image slices, 995 malignant, 604 benign from 195 patients who were radiologically diagnosed and histopathologically confirmed as brain tumor patients. The demographics, mean pixel values, skewness, kurtosis, features of Grey Level Co-occurrence Matrix (GLCM), mean, variance, energy, entropy, contrast, homogeneity, correlation, prominence and shade, were extracted from MRI ADC images of each patient. At the feature selection phase, the validity of the extracted features were measured using ANOVA f-test. Then, these features were used as input to several Machine Learning classification algorithms and the respective models were assessed. Results: According to the results of ANOVA f-test feature selection process, two attributes: skewness (3.34) and GLCM homogeneity (3.45) scored the lowest ANOVA f-test scores. Therefore both features were excluded in continuation of the experiment. From the different tested ML algorithms, the Random Forest classifier was chosen to build the final ML model since it presented the highest accuracy. The final model was able to predict malignant and benign neoplasms with an 90.41% accuracy after the hyper parameter tuning process. Conclusion: This study concludes that the above mentioned features (except skewness and GLCM homogeneity) are informative to identify and differentiate malignant from benign brain tumors. Moreover, they enable the development of a high-performance ML model that has the ability to assist in the decision-making steps of brain tumor diagnosis process, prior to attempting invasive diagnostic procedures such as brain biopsies.
Increased Risk of Primary Ovarian Insufficiency by High-Fructose Diet: A 90 Day Hormonal and Immunohistochemical Study in Wistar Rats
Authors: Mirzaei Roya , Bidgoli Sepideh Arbabi , Khosrokhavar Roya , Shoeibi Shahram , Ashtiani Hamidreza Ahmadi 
Published: January 2022

Abstract
There is ambiguous evidence that high-fructose diet can induce toxicity in different organ systems but its endocrine disrupting effects by abnormal changes in female reproductive organs is poorly evidenced. This study aimed to address the reproductive safety of high fructose diet through clinical, necropsy biochemical, hormonal, histopathological and immunohistochemical analysis. For this purpose, 5-6 weeks mature female Wistar rats were divided in three groups and each five animals/group exposed to standard chow+ water+ HFCS-55, standard chow+ water +sucrose 75 %w/v and standard chow+ water for 90 days. Remarkable increase in most lipid profile factors and total body weights of HFCS-55 fed rats and sucrose fed rats were detected in similar pattern compared to control .At the same time a battery of differential signs and symptoms in HFCS fed groups including destructive endometrial and ovarian changes , significant increase in FSH and LH levels, meaningful decreased serum testosterone and estradiol levels and strong AR expression in reproductive tissues of HFCS group of animals were recorded compared to other two study groups . These thought-provoking signs and signals of fructose induced reproductive toxicity in this model emphasis the contribution of HFCS-55 to deteriorated ovarian and endometrial health. More human population studies is necessary to find any possible association between fructose-rich diet and growing incidence of Primary Ovarian Deficiency (POI) in reproductive aged women .Further concern on this public health issue is required to revise existing regulatory standards and prevent this possible threat in human society.
The Positive Effects of Arbuscular Mycorrhizal Fungi Inoculation And/Or Additional Aeration On The Purification Efficiency of Combined Heavy Metals In Vertical Flow Constructed Wetlands
Authors: Xu Zhouying , Li Kaiguo , Li Wenxuan , Wu Chen , Chen Xi , Huang Jun , Zhang Xiangling , Ban Yihui 
Published: January 2022

Abstract
The extent to which, and mechanisms by which, arbuscular mycorrhizal fungi (AMF) and additional aeration (AA) purify wetlands polluted by combined heavy metals (HMs) are not well understood. In this study, vertical flow constructed wetlands (VFCWs) with the Phragmites australis (reeds)-AMF/AA were used to treat combined HMs-polluted wastewater. The results showed that (1) AA improved the AMF colonization in VFCWs, and AMF accumulated the combined HMs in their structures; (2) AMF inoculation and/or AA significantly promoted the reeds growth and antioxidant enzymes activities, thereby alleviating oxidative stress; (3) AMF inoculation and AA significantly enhanced the removal rates of Pb, Zn, Cu and Cd under the stress of high combined HMs concentrations comparing to the CK treatment (autoclaved AMF inoculation and no aeration), which increased by 22.72%, 30.31%, 12.64%, and 50.22%, respectively; (4) AMF inoculation and/or AA significantly promoted the combined HMs accumulation in plant roots and substrates, and altered the distribution of HMs at the subcellular level. We therefore conclude that AMF inoculation and/or AA in VFCWs improves the purification of combined HMs-polluted wastewater, and the VFCWs-reeds-AMF/AA associations exhibit great potential for application in remediation of combined HMs-polluted wastewater.
Who’s your data? Primary immune deficiency differential diagnosis prediction via machine learning and data mining of the USIDNET registry
Authors: Barrera Jose Alfredo Mendez , Guzman Samuel Rocha , Cascajares Elisa Hierro , Garabedian Elizabeth K , Fuleihan Ramsay L , Sullivan Kathleen E , Reyes Saul Oswaldo Lugo 
Published: January 2022

Abstract
INTRODUCTION: There are currently more than 450 primary immune deficiency (PID) diseases, and about 7,000 rare diseases that together afflict around 1 in every 17 humans. Computational aids based on data mining and machine learning might facilitate the diagnostic task by extracting rules from large datasets and making predictions when faced with new problem cases. OBJECTIVE: In a proof-of-concept data mining study, we aimed to predict PID diagnoses with a supervised machine learning algorithm based on classification tree boosting. METHODS: Through a data query at the USIDNET registry we obtained a database of 2,396 patients with common diagnoses of PID, including their clinical and laboratory features. We kept 12 diagnoses and 286 features that were included in the model. We used the XGBoost package with parallel tree boosting for the supervised classification model, and SHAP for variable importance interpretation, on Python v3.7. The patient database was split into training and testing subsets, and after boosting through gradient descent, the predictive model provides measures of diagnostic prediction accuracy and individual feature importance. To correct for imbalanced classification, after a baseline performance test, we used the Class Weighting Hyperparameter, or scale_pos_weight. RESULTS: The twelve PID diagnoses were CVID (1,098 patients), DiGeorge syndrome, Chronic granulomatous disease, Congenital agammaglobulinemia, ID not otherwise classified, Specific antibody deficiency, Complement deficiency, Hyper-IgM, Leukocyte adhesion deficiency, ectodermal dysplasia with immune deficiency, Severe combined immune deficiency, and Wiskott-Aldrich syndrome. For CVID, the model found an accuracy on the train sample of 0.80, with an area under the ROC curve (AUC) of 0.80, and a Gini coefficient of 0.60. In the test subset, accuracy was 0.76, AUC 0.75, and Gini 0.51. The positive feature value to predict CVID was highest for upper respiratory infections, asthma, autoimmunity and hypogammaglobulinemia. Features with the highest negative predictive value were high IgE, growth delay, abscess, lymphopenia, and congenital heart disease. For the rest of the diagnoses, accuracy stayed between 0.75 and 0.99, AUC 0.46-0.87, Gini 0.07-0.75, and LogLoss 0.09-8.55. See tables and figures.DISCUSSION: Clinicians should remember to consider the negative predictive features together with the positives. We are calling this a proof-of-concept study to continue with our explorations. A good performance is encouraging, and the feature importance might aid feature selection for future endeavors. In the meantime, we can learn from the rules derived by the model and build a user-friendly decision tree to generate differential diagnoses.
Water Allocation Management Under Scarcity: A Bankruptcy Approach
Authors: Zheng Yang , Sang Xuefeng , Liu Zhiwu , Zhang Siqi , Liu Pan 
Published: January 2022

Abstract
This study hopes to develop multi-criteria decision making (MCDM) method for equitable and efficient allocation water resource under scarcity. Based on the Bankruptcy problems, five classic plus one proposed allocation rules are introduced to generate water distribution alternatives. The "Core" solution of Cooperative Game Theory (CGT) and Security Restriction have been used to select the feasible alternatives. Additionally, five voting methods in Social Choice Theory (SCT) are launched to aggregate preferences and obtain "win" alternative. Apply this model on 2030 water allocation management project of Ezhou City, China, as a case study. Under the proposed rule, adjust minimal overlap rule (AMO), five regions, Urban Area, Gedian DZ and three counties, hold the water deficit rate of 5.9%, 15.8% and 4.7%-6.1%, respectively. By voting technique, AMO wins four fifths of aggregating processes and came in the second for the last, which provides some insights for allocating water in a fair and feasible way.
Industrial co-agglomeration, green technological innovation and total factor energy efficiency
Authors: Yang Haochang , Xu Xiezu , Zhang Faming 
Published: January 2022

Abstract
The double-wheel-driven of manufacturing and producer services industrial co-agglomeration is of great significance for transforming the economic growth mode driven by a single industry, integrating and extending regional resources, and improving energy efficiency. Based on panel data from 2004 to 2019, this paper uses the spatial Dubin model to analyze the impact of industrial co-agglomeration on total factor energy efficiency (TFEE) and its regional heterogeneity; Moreover, the mediating model is employed to examine the mediating effect of green technological innovation in the industrial co-agglomeration affects TFEE. Last but not least, the threshold panel regression model is conducted to verify the nonlinear relationship between industrial co-agglomeration and TFEE. The results show that: There is a U-shaped curve relationship between industrial co-agglomeration and TFEE, namely that industrial co-agglomeration first shows a certain inhibitory effect on TFEE, and then plays a significant role in promoting. Moreover, there are obvious regional heterogeneities in the impact of industrial co-agglomeration on TFEE and its spatial spillover effect. Industrial co-agglomeration has a significant indirect impact on TFEE through green technological innovation. In addition, there is a single threshold effect in the impact of industrial co-agglomeration on TFEE, only when the industrial co-agglomeration degree crosses the threshold value of 0.6329, can it positively promote the improvement of TFEE.