bluuebunny/crossref_metadata_2025_split huggingface dataset:
PENINGKATAN KEAKTIFAN DAN HASIL BELAJAR SISWA DENGAN PENERAPAN METODE TUTOR SEBAYA
Authors: Wali Gaspar Naju Kaduwu , Winarko Wignyo , Murniasih Tatik Retno 
Published: March 2021

Permasalahan utama pada penelitian ini adalah rendahnya hasil belajar siswa kelas VIII G SMP Negeri 1 Wagir. Salah satu faktor yang menyebabkan rendahnya hasil belajar tersebut adalah siswa kurang aktif dalam pembelajaran matematika di kelas. Dengan demikian, penelitian bertujuan untuk meningkatkan keaktifan dan hasil belajar siswa kelas VIII SMP Negeri 1 Wagir dengan menerapkan metode tutor sebaya. Penelitian ini terdiri dari empat tahap yaitu perencanaan (plan), pelaksanaan (action), pengumpulan data (observe), dan refleksi (reflection). Prosedur pengumpulan data yang digunakan dalam penelitian ini adalah lembar observasi, lembar keaktifan, tes dan wawancara. Hasil penelitian ini menunjukkan penerapan metode tutor sebaya dapat meningkatkan keaktifan dan hasil belajar siswa kelas VIII G SMP Negeri 1 Wagir. Peningkatan keaktifan dan hasil belajar siswa dilihat dari persentase yang diperoleh pada siklus I dan Siklus II dengan rincian sebagai berikut: (1) persentase keaktifan belajar siswa pada siklus I sebesar 71,67% sedangkan pada siklus II mengalami peningkatan menjadi 83,33% , dan (2) hasil belajar siswa pada siklus I sebesar 60,71% sedangkan pada siklus II mengalami peningkatan menjadi 78,57%. Saran bagi peneliti lain dapat menggunakan metode tutor sebaya untuk diterapkan dalam pembelajaran matematika dengan menggunakan materi yang berbeda.
Named Entity Recognition Model of Chinese Clinical Electronic Medical Record Based on XLNet-BiLSTM
Authors: Feng Shen Zhou , Min Su Qian , Lei Guo Jing 
Published: March 2021

Abstract
The recognition of named entities in Chinese clinical electronic medical records is one of the basic tasks to realize smart medical care. Aiming at the insufficient text semantic representation of the traditional word vector model and the inability of the recurrent neural network (RNN) model to solve the problems of long-term dependence, a Chinese clinical electronic medical record named entity recognition model XLNet-BiLSTM-MHA-CRF based on XLNet is proposed. Use the XLNet pre-training language model as the embedding layer to vectorize the medical record text to solve the problem of ambiguity; use the bidirectional long and short-term memory network (BiLSTM) gate control unit to obtain the forward and backward semantic feature information of the sentence; Then input the feature sequence to the multi-head attention layer (multi-head attention, MHA), use MHA to obtain information represented by different subspaces of the feature sequence, enhance the relevance of context semantics and eliminate noise; finally, input the conditional random field CRF to identify the global maximum 优 sequence. The experimental results show that the XLNet-BiLSTM-Attention-CRF model has achieved good results on the CCKS-2017 named entity recognition data set.
Effect of high nitrate vegetable juice supplementation on plasma nitrate and blood pressure in healthy adults: a pilot randomized crossover intervention in healthy volunteers
Authors: Elsahoryi Nour , Cardwell Christopher , Gilchrist Sarah , Woodside Jayne 
Published: March 2021

Abstract
Background: Beetroot juice has been demonstrated to decrease blood pressure due to the high inorganic nitrate content, but few studies have tested the effect of other high nitrate vegetable juices on blood pressure. Methods: This pilot randomized crossover trial aimed to investigate the effect of two different high nitrate vegetable juices on plasma nitrate concentrations and blood pressure in healthy adults. Eighteen healthy volunteers were randomized to receive 115 ml of beetroot juice or 250 ml of green leafy vegetable juice for seven days. Blood samples were collected, and clinic blood pressure measured at baseline and at the end of each juice consumption. Daily home blood pressure assessment was conducted two hours after juice consumption. Nitrate and nitrite concentrations were analysed using a commercially available kit on a Triturus automated ELISA analyser. Hills and Armitage analysis was used for the two- period crossover design and paired sample t- tests were performed to compare within-group changes. Results: Plasma nitrate and nitrite concentration significantly increased and there was significant reduction in clinic and home SBP mean during the beetroot juice period (P-values 0.004 and 0.002, respectively). Home DBP reduced significantly during green leafy vegetable juice consumption week (P-value 0.03). The difference between groups did not reach statistical significance during the formal crossover analysis adjusted for period effects. Conclusion: Beetroot juice and green leafy vegetable juice may reduce systolic or diastolic blood pressure but there was no statistically significant difference between the two juices, although this was only a pilot study.
Programmable terahertz metamaterials with non-volatile memory
Authors: Chen Benwen , Wu Jingbo , Li Weili , Zhang Caihong , Xue Qiang , Chi Yaojia , Wen Qiye , Jin Biaobing , Chen Jian , Wu P. H. 
Published: March 2021

Abstract
Spatial light modulators (SLMs) exhibited the powerful capability of controlling the electromagnetic wave. They have found numerous applications at terahertz (THz) frequencies, including wireless communication, digital holography, and compressive imaging. However, the development towards large-scale, multi-level and multi-functional THz SLM encounters technical challenges. Here, we present an electrically programmable THz metamaterial consisting of an array of 8⊆8 pixels, in which the phase change material of vanadium dioxide (VO2) is embedded. After successfully suppressing the crosstalk from adjacent pixels, the THz wave could be modulated in a programmable manner. The switching speed of each pixel was on the order of 1 kHz. In particular, utilising the hysteresis effect of VO2, the memory effect is demonstrated. The THz amplitude of each pixel can be written and erased by individual current pulses. Furthermore, multi-state THz images could be generated and stored, with a retention time of more than 5 hours. This programmable metamaterial with memory effect can be extended to other frequency bands and opens a route for electromagnetic information processing.
“Influence of Body Composition Assessed by Computed Tomography on Mortality in Older&nbsp;Adults Undergoing&nbsp;Hematopoietic Stem Cell Transplantation”
Authors: Koch Ludmila , Pereira Andrea Z , Hamerschlak Nelson , Castro Adham do Amaral e , Tachibana Adriano , Victor Elivane da Silva , Filho Reynaldo Jesus Garcia 
Published: March 2021

Abstract
Aim: The incidence of most hematologic malignancies increases with age. Hematopoietic stem cell transplantation (HSCT) provides a potentially life-prolonging or curative option for many patients in this scenario. Limited data is available on muscle mass and density assessed from CT-images on outcomes after HSCT. We aimed to evaluate the influence of body composition on morbidity and mortality in older adults undergoing (HSCT). Methods: Retrospective longitudinal study conducted with 50 patients ≥ 60 years undergoing HSCT at Hospital Israelita Albert Einstein, São Paulo. Body composition was assessed by chest computed tomography and treatment related mortality, graft versus host disease, neutrophil grafting, and overall survival were analyzed.Results: 148 HSCT patients were evaluated, 50 patients were eligible: 60% with autologous and 40% with allogeneic transplantation. Body mass index in patients was (female: 26.9 ± 4.7 kg/m2; 30.1± 4.9 kg/m2) - autologous and (female: 24.3 ± 5.15 kg/m2; male: 26.4 ± 2.0 kg/m2) - allogeneic. In autologous transplant group, we found a positive association between age and death risk with an increase of 63.5% in this risk (p=0.006) and also Karnofsky performance scale with decrease of 11.9% in death risk (p<0.001). A negative association between muscle radiodensity and death risk was observed in allogeneic transplantation patients with risk decrease of 20.1% (p = 0.032). We found a positive association between T4 muscle area and radiodensity with risk of acute graft versus host disease (p= 0.028). Conclusion: In population studied, body composition assessed by chest tomography showed the importance of radiodensity for better prognosis.
The Perceived Social Support by Iranian Women with Breast Cancer: A Qualitative Study
Authors: Mokhtari Leila , Markani Abdollah Khorami , Khalkhali Hamid Reza , Feizi Aram 
Published: March 2021

Abstract
Background: Social support has an importnat role in improving health outcomes and is considered as one of the crucial aspects of the modern care in cancer patients. Therefore this article aims at discovering and describing the dimensions of social support based on the lived experience of women suffering from breast cancer.Methods: In this qualitative study, 22 women with breast cancer were selected through purposive sampling from 7 hospitals affiliated to Urmia University of Medical Sciences. The data were collected through semi-structured interviews and were analyzed by the Conventional Qualitative Content Analysis and Graneheim’s and Lundman’s (2004) approach, using MAXQDA software, version 10.Results: After completion of the analyzing process, 6 categories were appeared including “creating an empathic atmosphere by family and community”, “creating a safe communication network for the patient”, “adaption to disease”, “giving meaning to life”, “the feeling of satisfaction with the healthcare providers for fulfilling their role”, and “accepting the support and help of family and friends in fighting the disease”. Conclusion: According to the findings, good social support during the illness can result in the spiritual, mental, and physical well-being of the patients and is one of the most effective factors in fighting the disease and feeling of recovery. The findings of this study can be used to develop plans to help the patients to achieve more support from the family, healthcare providers and the community and even providing the required supportive care for this group of women.
Grass and Plastic Film Mulching Pattern Improve Soil Organic Carbon Pool, Physical Properties, Fertility and Fruit Quality of Ponkan Orchards
Authors: Dong Zhihao , Xue Zhao-Yu , Chen Qin , Srivas Anoop Kumar , Riaz Muhammad , Liu Xiao-Dong , Cui Heng , Tan Qi-Ling , Sun Xue-Cheng , Wu Song-Wei , Hu Cheng-Xiao 
Published: March 2021

Abstract
Aims: Special fertilizer and soil mulching have been used to improve crop yield worldwide. However, the effects of special fertilizer with mulching on soil characteristics of citrus orchards were not yet fully understood. This study aimed at assessing the effects of different mulch patterns including plastic mulching and grass mulching on improving fruit quality of Ponkan and providing a new insight of mulching development in citrus orchards.Methods: In this study, a two-year field experiment was conducted to investigate the effects of citrus special fertilizer (FR), grass mulching (RGM), and plastic mulching (RPM) on fruit quality, soil organic carbon fractions, physicochemical properties, and plant nutrition in Ponkan citrus orchard.Results: The study resulted showed that special fertilizer treatment and grass mulching treatment increased Total soluble solid contents by 6.76% and 3.97%, while plastic mulching decreased Titratable acid contents by 19.44%, resulting in increases of fruit TSS: TA by 6.14%, 3.61%, and 22.76%, respectively. Correlation analyses showed that citrus fruit quality was associated with soil bulk density, Total porosity, Capillary porosit, Aeration porosity, Total organic carbon, Readily oxidized organic carbon, Microbial biomass carbon and Soil available phosphorus. Soil physical properties were improved by RPM, but FR and RGM had better effects on soil nutrients and organic carbon, as evidenced by the results of principal component analysis and loading matrix plot. Conclusions: This study suggested that the different effects of special fertilizer, plastic mulching, and grass mulching on improving fruit quality were associated with their diverse effects on improving soil characteristics.
Methacrylic Functionalized Hybrid Carbon Nanomaterial for the Selective Adsorption and Detection of Progesterone in Wastewater
Authors: Cui Xia , Shu Hua , Wang Lu , Chen Guoning , Han Jili , Hu Qianqian , Bashir Kamran , Luo Zhimin , Chang Chun , Zhang Jia , Fu Qiang 
Published: March 2021

Abstract
Progesterone, an endocrine-disrupting chemical, has been frequently detected in wastewater for decades, posing a serious threat to ecological and human health. However, it is still a challenge to achieve the effective detection of progesterone in complex matrices water samples. In this study, a novel adsorbent CNT@CS/P(MAA) was prepared by grafting methacrylic polymers on the surface of modified carbon nanomaterials. Compared with other reported materials, the hybrid carbon nanomaterial could selectively identify the progesterone in the complex industrial pharmaceutical wastewater, and its adsorption performance is almost independent of pH and environmental temperature. In addition, this nanomaterial could be reused with a good recovery rate. The prepared nanomaterials were characterized by transmission electron microscopy, Fourier transform infrared spectroscopy, X-ray diﬀraction, nitrogen adsorption and desorption experiments and thermo gravimetric analysis. The results confirmed that the methacrylic polymers and chitosan layer were successfully grafted on the surface of carbon nanotubes. Adsorption isotherms, adsorption kinetics, and selectivity tests showed that CNT@CS/P(MAA) had a high adsorption capacity (44.45 mg·g-1), a fast adsorption rate and a satisfied selectivity for progesterone. Then, CNT@CS/P(MAA) was used as solid phase extraction sorbent and combined with HPLC to enrich progesterone from the wastewater samples. Under the optimum conditions, a good linearity was obtained with the correlation coefficient was 0.9998, and the limit of detection was 0.003 ng·mL-1. Therefore, this method could be used for the selective and effective detection of progesterone in the industrial wastewater with complex substrates, and provided a new method for the detection of progesterone in other environmental waters.
Predicting species distributions and community composition using satellite remote sensing predictors
Authors: Pinto-Ledezma Jesús N. , Cavender-Bares Jeannine 
Published: March 2021

Abstract
Biodiversity is rapidly changing due to changes in the climate and human related activities; thus, the accurate predictions of species composition and diversity are critical to developing conservation actions and management strategies. In this paper, using oak assemblages distributed across the continental United States obtained from the National Ecological Observatory Network (NEON), we assessed the performance of stacked species distribution models (S-SDMs), constructed using satellite remote sensing as covariates and under a Bayesian framework, in order to build the next-generation of biodiversity models. This study represents an attempt to evaluate the integrated predictions of biodiversity models—including assemblage diversity and composition—obtained by stacking next-generation SDMs. We found three main results. First, environmental predictors derived entirely from satellite remote sensing represent adequate covariates for biodiversity modeling. Second, applying constraints to assemblage predictions, such as imposing the probability ranking rule, not necessarily results in more accurate species diversity predictions. Third, independent of the stacking procedure (bS-SDM versus pS-SDM versus cS-SDM), this kind of biodiversity models do not accurately recover the observed species composition at plot level or ecological scales (NEON plots), however, they do return reasonable predictions at macroecological scales, i.e., mid to high correct assignment of species identities at the scale of NEON sites. Our results provide insights for the prediction of assemblage diversity and composition at different spatial scales. An important task for future studies is to evaluate the reliability of combining S-SDMs with direct detection of species using image spectroscopy to build a new generation of biodiversity models to accurately predict and monitor ecological assemblages through time and space.
Estimating Land Expectation Value of Smallholder Farmers’ Eucalyptus Woodlot Products in Wogera District, Northern Ethiopia
Authors: deresse yordanos sete , Assefa Getahun Abreham 
Published: March 2021

Abstract
Background: The area of Eucalyptus plantations has expanded greatly and the species dominates many rural and urban landscapes as it suits the limited resources of smallholder farmers, yields higher income than other tree crops and increasing demand for woodlot products. The study conducted in Wogera District within three purposively selected kebele administrations. Smallholder farmers at the study area are converting their crop land to Eucalyptus plantation. Therefore there should need to deal the pushing factors for the allocation of Eucalyptus. This study aims at identifying the factors influencing decision of land allocation for eucalyptus woodlot production, and estimating the land expectation value. Method: Cross sectional data was collected through semi-structured interview schedule. Data analysis employed descriptive statistics and Faustman formula. Results: The results of the household survey revealed that land degradation and neighbor influence are the main factors for smallholders’ land allocation decision for Eucalyptus plantation. Therefore, as per the results, most of the crop land has been converted to Eucalyptus plantation. However, this a rapid land conversion issue made a threat on most farmers in related to losing of indigenous crops so as it leads them to be food insecured. Conclusion: Farmers in the study area are rational in their land allocation for production of either annual or perennial crops including Eucalyptus woodlots. Finally the study recommends government intervention in the separate land management issue is mandatory to make balance in production of both Eucalyptus and crops.
Embodied Carbon Emissions of Aluminum-Containing Commodities in International Trade: China's Perspective
Authors: Li Qiangfeng , Duan Huabo , Li Tianjiao , Zhou Yanjing , Chen Ying , Zhong Ruoyu 
Published: March 2021

Abstract
In recent years, global climate change has become an increasingly serious problem. Developing countries have assumed excessive responsibilities for carbon emissions under the principle of producer responsibility. A system that considers material flows to establish the responsibility for carbon emissions more accurately and fairly was proposed. In this study, the embodied carbon emissions (ECEs) of aluminum-containing commodities (ACC) in China’s international trade from 2008 to 2017 were analyzed via material flow analysis. The carbon emission coefficients of China’s imported and exported ACC were calculated and discussed. The main conclusions were as follows: (1)The annual imported and exported aluminum in ACC showed a fluctuating growth from 2008 to 2017. Overall, China imported a large amount of alumina and exports a large amount of aluminum-containing end products (ACEP) and semi-products (SP). (2) The imported and exported ECEs of ACC were mainly due to ACEP, which account for 57% and 68% of the imported and exported ECEs of ACC, respectively. (3) The ECEs of ACEP in international trade were mainly associated with vehicles, manufacturing equipment, and aircraft. (4) The share of exported and net exported ACC’s ECEs in domestic carbon emissions (calculated using the principle of producer responsibility) also increased from 1.3 and 0.9% to 2.8 and 1.7%. In addition, a more accurate share of international carbon emission responsibility was discussed, and policy recommendations to reduce carbon emissions and actively respond to global climate change were provided.
Selection of an engineering institution: Students’ perceptions on choice characteristics and suitability under Covid-19 pandemic
Authors: Mahajan Prashant , Patil Vaishali 
Published: March 2021

Abstract
Background: COVID-19 has impacted Indian engineering institutions (EIs) enormously. It has tightened its knot around EIs that forced their previous half-shut shades completely down to prevent the risk of spreading COVID-19. In such a situation, fetching new enrollments on EI campuses is a difficult and challenging task, as students’ behavior and family preferences have changed drastically due to mental stress and emotions attached to them. Historically, during crisis situations, institutions have struggled to return to the normal track. Consequently, it becomes a prerequisite to examine the choice characteristics influencing the selection of EI during the COVID-19 pandemic to make it ‘normal’ for ‘new’ enrollments.The purpose of this study is to critically examine choice characteristics that affect students’ choice for EI and consequently to explore relationships between institutions’ characteristics and the suitability of EI during the COVID-19 pandemic across students’ characteristics. Quantitative research, conducted through a self-reported survey composed of a closed-ended structured questionnaire, was purposefully incorporated into the students who recently were enrolled in EIs (batch years 2020-2021) belonging to the North Maharashtra region of India.Results:The findings of this study revealed dissimilarities across students’ characteristics regarding the suitability of EIs under pandemic conditions. Regression analysis revealed that EI characteristics such as proximity, image and reputation, quality education and curriculum delivery have significantly contributed to suitability under COVID-19. At the micro level, multiple relationships were noted between EI characteristics and the suitability of EI under the pandemic across students’ characteristics.Conclusion:Bringing ‘normality’ to ‘new’ enrollments totally depends on EI’s resilience in meeting the needs of diversity in the COVID-19 pandemic situation, which repositions themselves to govern student-centric strategies instituted for the overall suitability of EI under pandemic conditions. The study has successfully demonstrated how choice characteristics can be executed to regulate the ‘suitability’ of EI under the COVID-19 pandemic for the inclusion of diversity. It is useful for policy makers and academicians to reposition EIs that fetch diversity during the pandemic. This study is the first to provide insights into the performance of choice characteristics and their relationship with the suitability of EIs under a pandemic and can be a yardstick in administering new enrollments.