bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rethinking water and crops management in the irrigated district of Diyar-Al-Hujjej (Tunisia)
Authors: Daghari Issam , Abouaziza Fatma Bader , Daghari Hedi 
Published: April 2021

Abstract
In Diyar-Al-Hujjej irrigated area, aquifer’s over-exploitation, sea intrusion and abandonment of irrigated areas and wells were took place. A yield decrease for all crops was observed. Average aquifer water electrical conductivity (EC) jumps from 4 dS/m to 6.6 dS/m between 1969 and 2017. A fresh surface water transfer over more than 100 km was launched in 1998 to safeguard this irrigated area but this fresh water supply is not stable, it varies from one year to another (about 1,900,000 m3 in 2015 and only 60,000 m3 in 2018) while annual cops water requirements of the perimeter is about 2,500,000 m3. An adaptation by farmers to this new situation of saline and water stress was observed. The follow-up surveys of the farmer’s practices showed that: (i) new crops with high added-value grown during the rainy season were introduced in association with dry season crops (strawberry-pepper association), (ii) rainfed crops, fallow and water blending are common practices, and (iii) growing of rainy season crops in the aim to reduce water supply. The instability of fresh surface water volume transferred constitutes the main threat for this perimeter. The use of aquifer salt water must be stopped; it is the cause of the large quantities of salts supplied (over 13,000 kg / ha) and also of the low annual net income achieved. Net revenue was less than 2,000 US $/ha under salt water and reached even 8,000 US $/ha when sufficient surface water is available. An agrarian reform policy must be applied for this perimeter; only crops whose water requirements are partially met by rain should be grown. Introduction of another more sustainable water source should be initiated (as desalination) even at private farm level.
The host phenotype and microbiome varies with infection status, parasite origin and parasite microbiome composition
Authors: Hahn Megan , Piecyk Agnes , Jorge Fatima , Cerrato Robert , Kalbe Martin , Dheilly Nolwenn M. 
Published: April 2021

Abstract
Background: A growing literature demonstrates the impact of helminths on their host gut microbiome. However, there is now a need to investigate helminth associated microbes and the complex tripartite interactions between parasite, microbes, and hosts. Methods: We investigated whether the stickleback host microbiome depends on eco-evolutionary variables by testing the impact of exposure to the parasite Schistocephalus solidus, infection success, host genotype, parasite genotype, and parasite microbiome composition. Results: We observed constitutive differences in the microbiome of stickleback of different origin that increased when sticklebacks exposed to the parasite resisted infection. In contrast, the microbiome of successfully infected sticklebacks varies with parasite genotype. More specifically, we reveal that the association between microbiome and immune gene expression increases in infected individuals, and varies with parasite genotype. In addition, we showed that S. solidus hosts a complex endo-microbiome and that the abundance and prevalence of an unknown Chloroflexi in the parasite correlate with expression of host immune genes including foxp3, tnfr1, cd97, stat6 and marco. Conclusions: Within this first comprehensive analysis of a cestode’s interaction with bacteria, we demonstrate that (i) regardless of infection success, parasites contribute to modulating the host microbiome, (ii). when infection is successful, the host microbiome varies with parasite genotype due to genotype-dependent variation in parasite immunomodulation, and (iii) the parasite-associated microbiome is distinct from its host’s and contribute to the host immune response to infection. While a growing number of studies focus on determining the genetic and environmental factors contributing to host microbiome composition, this study reveals that parasites, parasite genetic factors, and parasite microbiomes can contribute regardless of whether the infection was successful.
The Etiologies of Isolated Fourth Cranial Nerve Palsy: A 10-Year Review of 158 Cases
Authors: Lekskul Apatsa , Wuthisiri Wadakarn , Tangtammaruk Phantaraporn 
Published: April 2021

Abstract
MethodsPatients diagnosed with isolated fourth nerve palsy from January 1, 2009, through July 31, 2020 in Ramathibodi Hospital, were included in this retrospective, observational case series. The demographic data of patients, age at presentation, the etiologies of isolated fourth nerve palsy and neuroimaging results (if indicated) were recorded.ResultsWe identified 153 unilateral and 5 bilateral cases of isolated fourth nerve palsy. Mean age at presentation was 38.89 ± 25.71 years old. Most of the unilateral cases were congenital (58.17%), with vasculopathy (27.45%), intracranial neoplasm (8.5%) and other etiologies. Trauma with closed head injury was the most common etiology of bilateral cases (60%), followed by ruptured arterovenous malformation (20%) and vasculopathy (20%). Twenty-one of the 43 (48.84%) patients with vasculopathy-associated fourth nerve palsy underwent neuroimaging, with normal findings, and all patients’ symptoms resolved within 6 months of symptom onset.ConclusionsIn our series, most of the isolated fourth nerve palsy cases were congenital, followed in frequency by vasculopathy and intracranial tumor, as in many studies. In cases of vasculopathy, the clinical signs and symptoms resolved within 6 months in all cases: observation was sufficient, with no necessity for neuroimaging. However, neuroimaging should be considered in cases with atypical presentations, such as headache, periorbital pain, ataxia with positive cerebellar signs, or if there is rapid progression or no recovery.
Northward migration of the boreal forest confirmed by satellite record
Authors: Feng Min , Sexton Joseph , Wang Panshi , Montesano Paul , Calle Leonardo , Carvalhais Nuno , Poulter Benjamin , Wooten Margaret , Wagner William , Elders Akiko , Channan Saurabh , Neigh Christopher 
Published: April 2021

Abstract

The boreal forest is one of Earth’s most climatologically sensitive regions, and changes in the cover and structure of its vegetation pose a positive carbon-climate feedback on atmospheric greenhouse warming. The region has also experienced more than three times climatological warming of any forested biome in recent decades. While ecological models predict a northward shift of boreal tree cover in response to climate change, comprehensive data have not been available to test the hypothesis. Here we report a test of the magnitude, direction, and significance of changes in the boreal canopy based on the longest and highest-resolution record of calibrated satellite maps to date. The boreal canopy increased in density and shifted northward from 1984 to 2020, with the largest and most significant gains in its northern latitudes. Net forest gains occurred despite stable rates of disturbance across all but the region’s southernmost latitudes, implicating widespread release of climatological limitation on growth over changing distribution of fire, harvest, insect, and other disturbances. These new forests will sequester carbon as they mature, increasing its residence time in woody biomass, and will play a key role in how the terrestrial biosphere attenuates atmospheric CO2 increases.
The Effect of the Educational Brochure Versus the Video on Disease Knowledge in Juvenile Idiopathic Arthritis Patients: A Randomized Controlled Trial
Authors: Sunthornsup Waraporn , Soponkanaporn Sirisucha , Vilaiyuk Soamarat 
Published: April 2021

Abstract
Background: Juvenile idiopathic arthritis (JIA) is the most common pediatric rheumatic disease. Patient education plays an important role in the management of such chronic disease. Although JIA educational materials are available, patients may not reach them due to limited health literacy or limited access. This study aimed to compare the effectiveness between a brochure and a video in JIA-related knowledge.Methods: This was a randomized controlled trial study. 100 JIA patients or their caregivers, whose JIA patients were not graduated at least 8thgrade were randomized into two groups with 50 subjects per arms. The intervention groups were reading the brochure (n=50) or watching the content matched video (n=50). Fifteen multiple-choice knowledge questionnaires about JIA were answered before, immediately after intervention and at follow-up 4 weeks later. Demographic data and disease activity were recorded.Results: In this study, age of patients in the brochure and video group were 13.2 ± 4.6 years and 14.3 ± 5.1 years, respectively. Most of them were female (57%), diagnosed systemic JIA (37%) and were in active disease status (48%). There was no difference in all baseline demographic data. About 70% of patients had low average monthly family income per household. More than 50% of JIA graduated below secondary school. The mean correct score rates prior to the intervention were 51% and 56% in the brochure group and video group, respectively (p-value 0.28). Post-test total knowledge scores showed that participants in the video group had better knowledge than participants in the brochure group (p-value 0.003). In four-week post-test, both groups had statistically significantly lower total knowledge scores (the brochure 73%, the video 78%) when compared to the immediate post-test score. Moreover, there was no significant difference in four-week post-test scores between two groups (p-value 0.141).Conclusion: The JIA educational video was more effective than the pictorial brochure in improving immediate JIA related knowledge. However, the long-term retention of JIA related knowledge did not show the significant difference between both educational tools. To maintain JIA disease knowledge, patients should be given the knowledge of JIA disease repeatedly.Trial registration: Thaiclinicaltrials.org 06/03/2020, TCTR20200310004, prospectively registered.
Highly c-axis Oriented ZnO Thin Films by Sol-gel Method
Authors: Kutlu Taner , Erdogan Necdet H. , Sedefoglu Nazmi , Kavak Hamide 
Published: April 2021

Abstract
This study reports the effect of annealing temperature on the structural, morphological, and optical properties of ZnO (Zinc Oxide) thin films deposited on a glass substrate by the sol-gel spin coating method. Those properties of ZnO were examined with UV-Vis, Fourier transform infrared (FTIR) and Raman spectroscopy, Scanning Electron Microscopy (SEM), Atomic Force Microscopy (AFM), and X-ray diffraction (XRD), before and after annealing. XRD results revealed that all the samples had a highly c-axis oriented wurtzite structure. A 1 (LO) mode in Raman spectra also confirmed the highly oriented ZnO films. Optical measurement indicated that transmittance of the films was above %85, and the optical band gap slightly decreased with the increasing annealing temperature from 350 to 550 °C. Morphological analysis displayed that increasing annealing temperature improved surface morphology and enlarged the grain size from 2-3 nm for as-deposited samples to 150 nm for annealed at 550 °C.
Anisotropic and Age-Dependent Elastic Material Behavior of the Human Costal Cartilage
Authors: Weber Matthias , Rothschild Markus Alexander , Niehoff Anja 
Published: April 2021

Abstract
Compared to articular cartilage, the biomechanical properties of costal cartilage have not yet been extensively explored. The research presented addresses this problem by studying for the first time the anisotropic elastic behavior of human costal cartilage. Samples were taken from 12 male and female cadavers and unconfined compression and indentation tests were performed in mediolateral and dorsoventral direction to determine Young’s Moduli EC for compression and Ei5%, Ei10% and Eimax at 5%, 10% and maximum strain for indentation. Furthermore, the crack direction of the unconfined compression samples was determined and histological samples of the cartilage tissue were examined with the picrosirius-polarization staining method. The tests revealed mean Young’s Moduli of EC = 32.9 ± 17.9 MPa (N = 10), Ei5% = 11.1 ± 5.6 MPa (N = 12), Ei10% = 13.3 ± 6.3 MPa (N = 12) and Eimax = 14.6 ± 6.6 MPa (N = 12). We found that the Young’s Moduli in the indentation test are clearly anisotropic with significant higher results in the mediolateral direction (all P = 0.002). In addition, a dependence of the crack direction of the compressed specimens on the load orientation was observed. Those findings were supported by the orientation of the structure of the collagen fibers determined in the histological examination. Also, a significant age-related elastic behavior of human costal cartilage could be shown with the unconfined compression test (P = 0.009) and the indentation test (P = 0.004), but no gender effect could be detected. Those results are helpful in the field of autologous grafts for rhinoplastic surgery and for the refinement of material parameters in Finite Element models e.g. for accident analyses with traumatic impact on the thorax.
Study the Behaviour of Underground Oil Cavern Under Static Loading Condition
Authors: Lokhande Ritesh D , Vamsi Krishna Chimmani 
Published: April 2021

Abstract
The country population is increasing rapidly and the needs to make lives easier daily. Some of the essential needs for this generation are crude oil and electricity. India unfortunately does not possess any oil reserves to meet the needs of the country’s demands. So, India is importing oil from other countries. Whenever there are situations like war, pandemic (COVID-19) and other emergencies, the natural oil reserved countries cannot export the oil to other countries which will lead to great chaos in the country. To avoid this situation storing the crude oil is necessary. Building surface giant structures for storing the oil is difficult and won’t be economical. So, India is constructing giant underground structures called caverns, which will reserve the oil. The present study is focused on the stability of the underground cavern structure and understanding the importance of water curtaining system. To analyze the stresses and displacement 2D modelling has been done. In this, wet and dry models are prepared and analysed based on the available geological and geo-technical data to determine the stresses around the cavern and the displacement which will reach on surface due to excavation.
A machine learning model to predict critical care outcomes in patient with chest pain visiting the emergency department
Authors: Wu Ting Ting , Zheng Ruo Fei , Lin Zhi Zhong , Gong Hai Rong , Li Hong 
Published: April 2021

Abstract
Background: Currently, the risk stratification of critically ill patient with chest pain is a challenge. We aimed to use machine learning approach to predict the critical care outcomes in patients with chest pain, and simultaneously compared its performance with the HEART score. Methods: This was a retrospective, case-control study in patients with acute non-traumatic chest pain who presented to the emergency department (ED) between January 2017 and December 2019. The outcomes included cardiac arrest, transfer to ICU, and death during treatment in ED. In the randomly sampled training set (70%), a LASSO regression model was developed, and presented with nomogram. The performance was measured in both training set (70% participants) and testing set (30% participants), and findings were compared with the HEART score.Results: We proposed a LASSO regression model incorporating mode of arrival, reperfusion therapy, Killip class, systolic BP, SCr, CKMB, and BNP as independent predictors of critical care outcomes in patients with chest pain. Our model significantly outperformed the HEART score with AUC of 0.953 (95%CI: 0.922 - 0.984) and 0.754 (95%CI: 0.675 - 0.832), respectively. Consistently, our model demonstrated better outcomes regarding the metrics of accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1 score. Similarly, the decision curve analysis elucidated a greater net benefit of our model over the full ranges of clinical thresholds.Conclusion: We present a promising model for predicting the critical care outcomes in patients with chest pain, and provide substantial support to its application as a decision-making tool in ED.
Predictive determinants of overall survival among re-infected COVID-19 patients using the elastic-net regularized Cox proportional hazards model: a machine-learning algorithm
Authors: Ebrahimi Vahid , Sharifi Mehrdad , Mousavi-Roknabadi Razieh Sadat , Sadegh Robab , Khademian Mohammad Hossein , Moghadami Mohsen , Dehbozorgi Afsaneh 
Published: April 2021

Abstract
Background: Narrowing a large set of features to a smaller one can improve our understanding of the main risk factors for in-hospital mortality in patients with COVID-19. This study aimed to derive a parsimonious model for predicting overall survival (OS) among re-infected COVID-19 patients using machine-learning (ML) algorithms.Methods: The retrospective data of 283 re-infected COVID-19 patients admitted to twenty-six medical centers (affiliated with Shiraz University of Medical Sciences) from 10 June to 26 December 2020 were reviewed and analyzed. An elastic-net regularized Cox proportional hazards (PH) regression and model approximation via backward elimination were utilized to optimize a predictive model of time to in-hospital death. Then, the model was reduced to its core features to maximize simplicity and generalizability.Results: The empirical in-hospital mortality rate among the re-infected COVID-19 patients was obtained as 9.5%. In addition, the mortality rate among the intubated patients was 83.5%. Using the Kaplan-Meier approach, the OS (95% CI) rates for days 7, 14, and 21 were 87.5% (81.6-91.6%), 78.3% (65.0-87.0%), and 52.2% (20.3-76.7%), respectively. The elastic-net Cox PH regression retained 8 out of 35 candidate features of death. Transfer by Emergency Medical Services (EMS) (HR=3.90, 95% CI: 1.63-9.48), SpO2≤85% (HR=8.10, 95% CI: 2.97-22.00), increased serum creatinine (HR=1.85, 95% CI: 1.48-2.30), and increased white blood cells (WBC) count (HR=1.10, 95% CI: 1.03-1.15) were associated with higher in-hospital mortality rates in the re-infected COVID-19 patients.Conclusion: The results of the ML analysis demonstrated that transfer by EMS, profound hypoxemia (SpO2≤85%), increased serum creatinine (more than 1.6 mg/dL), and increased WBC count (more than 8.5 (×109 cells/L)) reduced the OS of the re-infected COVID-19 patients.
Multimodal Primary Open Angle Glaucoma Early Diagnosing Program Based on Clinical Process
Authors: Ma Jingyi , Lv Bin , Li Yuanyuan , Fan Pan , Zhao Xu , Yuan Huiping , Zhang Yingtao 
Published: April 2021

Abstract
Background: Glaucoma is one of the leading causes of blinding disease. Early detection can improve patients’ quality of vision. Effectively identifying primary open angle glaucoma (POAG) using structural and functional examination is critical. Computer aided diagnosis of glaucoma requires multimodal data to find an accurate model for early glaucoma diagnosis. Methods: This study collected 87 early POAG eyes, 85 suspected POAG eyes, and 129 healthy eyes from the ophthalmology department at Second Affiliated Hospital of Harbin Medical University. Retinal nerve fiber layer thickness (RNFLt), intraocular pressure (IOP) value, visual field examination parameters and age were obtained. A powerful deep learning network segmented the FP and extracted optic nerve head (ONH) features. Machine learning classifiers (MLCs) were adopted to get the final classification results and compared with the diagnosis results of glaucoma specialists and general non-glaucoma ophthalmologists. Result: The program diagnosing early POAG, suspected POAG, and healthy eyes made overall Area Under the Curve of 0.97. Dice of optic disc and optic cup segmentation is 0.9631, 0.8435 respectively. Accuracy of the program (0.9004) is higher than general ophthalmologists (0.8195). Specificity of the program (0.9635) is higher than glaucoma specialists (0.9366).Conclusions: The program delivers superior results in diagnosing early POAG. This study’s hybrid deep learning-machine learning framework can assist with clinical decision for early POAG effectively.
Robust Decadal Variations in ENSO Diversity, and its Impact on Future Scenarios
Authors: Dieppois Bastien , Capotondi Antonietta , Pohl Benjamin , Chun Kwok , Monerie Paul-Arthur , Eden Jonathan 
Published: April 2021

Abstract
El Niño-Southern Oscillation (ENSO) shows a large diversity of events, whose modulation by climate variability and change, and their representation in climate models, limit our ability to predict their impact on ecosystems and human livelihood. Here, we introduce a new framework to analysze probabilistic changes in event-location and -intensity, which overcomes existing limitations in studying ENSO diversity. We find robust decadal variations in event intensities and locations in century-long observational datasets, which are associated with perturbations in equatorial wind-stress and thermocline depth, as well as extra-tropical anomalies in the North and South Pacific. A large fraction of CMIP5 and CMIP6 models appear capable of simulating such decadal variability in ENSO diversity, and the associated large-scale patterns. Projections of ENSO diversity in future climate change scenarios strongly depend on the magnitude of decadal variations, and the ability of climate models to reproduce them realistically over the 21st century.
Identifying Associations Between Health Services Operational Factors and Health Experience for Patients With Type 2 Diabetes in Iran
Authors: Mahdavi Mahdi , Parsaeian Mahboubeh , Borzuei Shiva , Majdzadeh Reza 
Published: April 2021

Abstract
Background. Facing limited health resources, healthcare providers need to rely on health service delivery models that produce the best clinical outcomes and patient experience. We aimed to contribute to developing a patient experience-based type 2 diabetes service delivery model by identifying operational structures and processes of care that were associated with clinical outcome, health experience, and service experience. Methods. We conducted a cross-sectional survey of type 2 diabetes patients between Jan 2019 to Feb 2020. Having adjusted for demand variables, we examined relationships between independent variables (behaviors, services/processes, and structures) and three categories of dependent variables; clinical outcomes (HbA1c and fasting blood glucose), health experience (EuroQol quality of life (EQ-5D), evaluation of quality of life (visual analgene scale of EQ-5D), and satisfaction with overall health status), and service experience (evaluation of diabetes services in comparison with worst and best imaginable diabetes services and satisfaction with diabetes services). We analysed data using multivariate linear regression models. Results. After adjusting for demand variables; structures, diabetes-specific health behaviours, and processes explained up to 22%, 12%, and 9% of variance in the outcomes, respectively. Based on significant associations between the diabetes service operations and outcomes, the components of an experience-based service delivery model included the structural elements (continuity of care, redistribution of task to low-cost resources, and improved access to provider), behaviours (improved patient awareness and adherence), and process elements (reduced variation in service utilization, increased responsiveness, caring, comprehensiveness of care, and shared decision-making). Conclusions. Based on the extent of explained variance and identified significant variables, health services operational factors that determine patient reported outcomes for patients with type 2 diabetes in Iran were identified, which focus on improving continuity of care and access to providers at the first place, improving adherence to care at the second, and various operational process variables at the third place.