bluuebunny/crossref_metadata_2025_split huggingface dataset:
Consolidation quantitative analysis on cultivated land fragmentation and its terrain gradient effect in mountainous areas of southwest China: A case study of Caotangxi watershed in the Three Gorges Reservoir Area
Authors: Yang Yongfeng , Li Ruikang 
Published: July 2022

Abstract
Cultivated land fragmentation (CLF) has become the main obstacle restricting rural revitalization and agricultural modernization management in China, especially in southwest mountainous areas. And it’s of great significance to investigate the spatial-temporal evolution law of cultivated land as well as to facilitate regional food security and land management. Taking widely used areas of the Caotangxi River watershed as examples, based on landscape pattern principle, this paper constructs an evaluation system of CLF by landscape metrics. We firstly analyzed the temporal and spatial characteristics of cultivated landscape through the method of cultivated landscape gradient, calculated the value of CLF to reveal its evolution and spatial characteristics, explored the topographic gradient effects of CLF, and further summarized its modes. The results show that the area where arable land is concentrated are often comparatively crushed and distributed in the plain areas along the river banks. CLF in watersheds presented the overall improvement trend by the influence of natural conditions and China’s ecological policies. The overall level of CLF in the watershed is low during the whole study period, and the spatial evolution is uneven. The CLF displays pronounced regional divergence patterns in space, and the value of CLF is comparatively high in terrain Grade 2 and 3, which is the pivotal area for alleviating the fragmentation in the subsequent work. These findings imply that the differences of characteristics of CLF with terrain gradient must be considered in the formulation of targeted policies for land consolidation in the watershed.
Prediction of soil-water thresholds for plant responses
Authors: Chi ChunMing 
Published: July 2022

Abstract
Background It is well known that there is a soil water content threshold (θTHR) for plant growth and physiological processes. It is very import to obtain the θTHR for agriculture water management . However the measurement of θTHR needs specialized and expensive equipment. The θTHR can also be considered as the soil water content of capillary break (θCB). The θTHR can be calculated based on soil water retention curve. But the obtainment of soil water retention curve is time-consuming. Therefore, a simple and rapid prediction of θTHR is the focus of this study. Aims The θTHR can be predicted by estimating the θCB since the θTHR is generally regarded as the θCB. Whether the θCB can be estimated by simple soil parameters such as field capacity (θFC) and soil bulk density (Db)? Is the estimated θCB equal to the measured θTHR? Which of soil or plant is the major factor affecting the θTHR?Methods An formula of B was proposed to estimate θCB. Eight soils from six literature were used to calculate values of θCB. Theses estimated θCB were compared with 16 measured values of θTHR for 12 plant species in the eight soils. The variation in the θTHR and fraction of transpirable soil water (FTSW) with different plant species in the same soil and the same plant species in different soils were analyzed to compare effects of θCB and plant species on θTHR. Results The values of estimated θCB were nearly equal to those of measured θTHR. Highly significant (adjR2=0.9993,p<0.001) linear relationship was found between estimated θCB and measured θTHR with slope of 0.9938 and fixed y intercept of zero. In addition, the values of θTHR for different plant species were close to the same θCB in a soil. The θTHR values for the same plant species were different if θCB were different. Thus, the θTHR varied only with the θCB but not with the plant species. But the threshold FTSW varied due to plant species, not soil. Conclusions The estimated θCB can be considered equal to the measured θTHR. It is the θCB but not the plant that affects majorly the θTHR. Therefore, the θTHR can be predicted simply and quickly based on the estimation of θCB from θFC and Db.
Identification of mutations in SARS-CoV-2 PCR primer regions
Authors: Mentes Anikó , Papp Krisztián , Visontai Dávid , Stéger József , Group VEO Technical Working , Csabai István , Medgyes-Horváth Anna , Pipek Orsolya Anna 
Published: July 2022

Abstract
Due to the constantly increasing number of mutations in the SARS-CoV-2 genome, concerns have emerged over the possibility of decreased diagnostic accuracy of reverse transcription-polymerase chain reaction (RT-PCR), the gold standard diagnostic test for SARS-CoV-2. We propose an analysis pipeline to discover genomic variations overlapping the target regions of commonly used PCR primer sets. We provide the list of these mutations in a publicly available format based on a dataset of more than 600,000 SARS-CoV-2 samples. Our approach distinguishes among mutations possibly having a damaging impact on PCR efficiency and ones anticipated to be neutral in this sense. Samples are categorized as „prone to misclassification” vs. „likely to be correctly detected” by a given PCR primer set based on the estimated effect of mutations present. Samples susceptible to misclassification are always present at a daily rate of 2% or lower, while the daily ratio of samples having a slight chance of misclassification with a particular primer set can reach 90%. As different variant strains may temporarily gain dominance in the worldwide SARS-CoV-2 viral population, the efficiency of a particular PCR primer set may change over time, therefore constant monitoring of variations in primer target regions is highly recommended.
Collapse assessment of high-rise reinforced concrete building under chloride induced pitting corrosion subjected to near-field and far-field ground motions
Authors: Jafary Amirhossein , Zaherbin Pouria , Ghanoonibagha Mohammad , Shayanfar Mohsenali 
Published: July 2022

Abstract
Reinforced concrete structures are vulnerable to corrosion considering its influences on the performance of the structure during the possible earthquakes. Corrosion mostly occurs due to two main reasons: chloride and carbon dioxide penetration into the concrete that leads to the chemical reaction between them and concrete compositions. Chloride diffusion into the concrete brings about rebar pitting, while carbonation-induced corrosion causes uniform corrosion of rebars. In the present study, chloride-induced corrosion was investigated. In this regard, the Haselton 20-story reinforced concrete model was chosen. At first, corrosion initiation time was determined by probabilistic Monte-Carlo Simulation methods for three water to cement ratios of 0.4, 0.45, and 0.5. Next, the effects of corrosion on the mechanical properties of the steel and the concrete were taken into account by using equations available in the literature. Seismic performance of corroded structure was evaluated by conducting Non-linear static and incremental dynamic analysis (IDA). FEMA p695 far-field and near-field ground motions were selected for dynamic analysis. The reduction of overstrength and ductility over 40 years after corrosion initiation was calculated. The results showed that ductility was more affected by corrosion rather than overstrength. The probabilities of the structure being at the four damage states of slight, moderate, extensive, and complete damage were estimated based on fragility curves obtained from IDA. It was observed that ten years after initiation of corrosion there is only a slight difference in the probability of damage states and after that considerable distinction was observed, especially in water to cement ratio of 0.5. Moreover, it was seen that exceeding selected damage states under non-pulse-like near field ground motions is more likely.
Spatio-temporal monitoring of droughts in Iran using remote-sensing indices
Authors: Pouyan Soheila , Bordbar Mojgan , Ravichandran Venkatesh , Tiefenbacher John P. , Pourghasemi Hamid Reza 
Published: July 2022

Abstract
This study monitored spatially drought in Iran country using distance measurement indicators. Five drought indicators measured from 2016 to 2020 were used: temperature condition index (TCI), vegetation condition index (VCI), vegetation health index (VHI), precipitation condition index (PCI), and standardized precipitation index (SPI). The TCI revealed that the largest percentage of the region classified as “severe drought” occurred in 2020. The VCI indicated that the largest portion of the country (73.30%) experiencing “moderate drought” occurred in 2018. The VHI indicated that vegetation stress increased throughout the region, and areas of severe and moderate drought reached their greatest extents in the mentioned years. Although significant droughts have occurred primarily in the central, eastern, and southeastern parts of Iran, mild droughts have occurred in northern Iran as well. The PCI indicated that rainfall amounts have diminished in most of the country during the period of study. The SPI showed that northern Iran received heavy rain, and was the only region classified as “extremely wet.” Most of the rest of Iran were “moderately dry.” The analysis of the VHI index for agricultural plants showed that 27.71% of Iran's agricultural regions experienced “critical drought” conditions, this included the provinces of Razavi Khorasan, Hamadan, and Khozestan. The study can provide a baseline for the selection of the most useful drought-monitoring indicators and can enable a deeper understanding of drought in arid and semi-arid regions.
Low preoperative serum fibrinogen level is associated with postoperative acute kidney injury in patients with in acute aortic dissection
Authors: Guan Xinliang , Li Lei , Jiang Wenjian , Gong Ming , Li Haiyang , Wang Xiaolong , Liu Yuyong , Zhang Hongjia 
Published: July 2022

Abstract
Objective: Acute kidney injury (AKI) after cardiac surgery is associated with serious complication and high risk of mortality. The relationship between hemostatic system and the prognosis of patients with acute type A aortic dissection (ATAAD) has not been evaluated. The purpose of this study was to investigate the association between preoperative serum fibrinogen level and risk of postoperative AKI in patients with ATAAD. Methods: A total of 172 consecutive patients undergoing urgent aortic arch surgery for ATAAD between April 2020 and December 2021 were identified from Beijing Anzhen Hospital aortic surgery database. The primary outcome was postoperative AKI as defined by the Kidney Disease Improving Global Outcomes (KDIGO) criteria. The univariate and multivariate logistic regression analysis was done to assess the independent predictors of risk for postoperative AKI. Receiver operating characteristic (ROC) curve was generated to evaluate the predictive probabilities of risk factors for AKI.Results: In our study, 51.2% (88/172) patients developed postoperative AKI. Multivariate logistic regression analysis identified low preoperative serum fibrinogen level (OR, 1.492; 95% CI, 1.023 to 2.476; p = 0.021) and increased body mass index (BMI) (OR, 1.153; 95% CI, 1.003 to 1.327; p = 0.046) as independent predictors of postoperative AKI in patients with ATAAD. A mixed effect analysis of variance modeling revealed that obese patients with low preoperative serum fibrinogen level had higher incidence of postoperative AKI (p = 0.04). The ROC curve indicated that low preoperative serum fibrinogen level was a significant predictor of AKI [area under the curve (AUC), 0.771; p < 0.001].Conclusions: Low preoperative serum fibrinogen level and obesity were associated with the risk of postoperative AKI in patients with ATAAD. These data suggested that low preoperative serum fibrinogen level was preferred marker for predicting the postoperative AKI, especially in obese patients with ATAAD.
Betting on Forests and Soils to Reach Net Zero
Authors: Smith Harry , Vaughan Naomi E. , Forster Johanna 
Published: July 2022

Abstract
The deployment of Carbon Dioxide Removal (CDR) is essential to reach global and national net-zero emissions targets, but little attention has been paid to their practical deployment by countries. Here we conducted a systematic analysis of CDR in 41 national climate strategies submitted to the UNFCCC. We show that enhancing forest and soil carbon sinks are most advocated (40/41) within strategies but only quantified in 12. Residual emissions in 2050 are only quantified in 19/41 strategies and most of these use forests to reach national net-zero targets. Strategies that quantify residual emissions and assess CDR identify national constraints (e.g., wildfire risks for forests and geology for CO2 storage) and highlight the need for international collaboration. Our analysis also identifies that net-zero targets are often poorly described and, in some cases, misleading. Together these findings underline the need for the UNFCCC to urgently strengthen national reporting requirements for 2050.
Deep Learning Eliminates Massive Dust Storms from Images of Tianwen-1
Authors: Li Hongyu , Li Jia , ren xin , Xu Long 
Published: July 2022

Abstract
Dust storms may remarkably degrade the imaging quality of Martian orbiters and delay the progress of mapping the global topography and geomorphology. To address this issue, this paper presents an approach that reuses the image dehazing knowledge obtained on Earth to resolve the dust-removal problem on Mars. In this approach, we collect remote-sensing images captured by Tianwen-1 and manually select hundreds of clean and dusty images. Inspired by the haze formation process on Earth, we formulate a similar visual degradation process on clean images and synthesize dusty images sharing a similar feature distribution with realistic dusty images. These realistic clean and synthetic dusty image pairs are used to train a deep model that inherently encodes dust irrelevant features and decodes them into dust-free images. Qualitative and quantitative results show that dust storms can be effectively eliminated by the proposed approach, leading to obviously improved topographical and geomorphological details of Mars.
GWNN-HF : Beyond assortativity in Graph Wavelet Neural Network
Authors: Huang BinFeng , Zheng WenJie , Qian Fulan , Zhao Shu , Chen Jie , Zhang Yanping 
Published: July 2022

Abstract
Graph wavelet neural network exerts a powerful learning ability in the assortative network where most of adjacent nodes have the same label as the target node. However, it doesn't perform well in the disassortative network where most of adjacent nodes have different label than the target node. So graph wavelet neural network cannot extract the most useful information based on different types of networks. On the one hand, as a low-pass filter, graph wavelet neural network only obtains the commonality of the same label nodes, it is not capable of obtaining the difference of different label nodes. On the other hand, graph wavelet neural network only aggregates neighbor nodes so that it can't obtain information of nodes which have similar feature with the target node and are far from the target node. To solve the above problems, we propose the GWNN-HF model, which can effectively adapt to different types of networks and get a better node representation. Specifically speaking, firstly, we design low-pass filter and high-pass filter convolution kernels to get low-pass and high-pass signals and then use adaptive fusion method to fuse them, which effectively get commonality of same label nodes and difference of different label nodes. Secondly, we use the Relaxed Minimum-Spanning Tree algorithm to construct a feature correlation graph and use an attention mechanism to fuse the original graph and feature correlation graph representation. Extensive experiments on benchmark datasets clearly indicates that GWNN-HF behaves better than the state-of-the-art GNNs.
Improving the Value and Efficiency of Healthcare Services by Integrated Data Envelopment Analysis and Organizational Structure Design
Authors: Barros Oscar , Diaz Jorge 
Published: July 2022

Abstract
Measuring the efficiency of health services using Data Envelopment Analysis is a common practice nowadays. In addition, some studies use analytical techniques to discover the variables that explain the efficiency level of such services. Nevertheless, few efficiency analyses have resulted in proposals to design organizational health care structures that provide adequate management for actually improving efficiency. Thus, to address the lack of use of Data Envelopment Analysis results in practice, this paper provides a general methodology based on the idea that measuring the efficiency of healthcare services must be complemented with their redesign to obtain potential efficiency improvements. This redesign may include healthcare processes, e.g. clinical flows, analytical techniques to advise processes, e.g. intelligent models, information technology support for processes, and new management structures to facilitate the implementation and operation of the redesigns. Such methodology was applied to a large hospital specialized in cancer to illustrate its use and the results that can be achieved. Results show that the potential cost savings of new designs are about US$ 1.0 million yearly. To generate such savings, new medical and management practices were designed with the MDs’ participation. The implementation of the practices and their continuous evaluation and innovation was possible by a new organizational structure designed for such purpose. This work shows the importance of integrating several methodologies to generate better-founded designs. This integration is lacking in health-service design research, particularly in connection with architecture, processes, and organizational structure; this paper shows that this is a promising line of application.
Metabolic score for visceral fat is associated with prediabetes: based on community-dwelling people prospective cohort study in China
Authors: Liu Guangxu , Dou Jingtao , Wang Meiping , Zuo Yingting , Lu Juming , Ji Linong , Zhan Siyan , He Yan 
Published: July 2022

Abstract
Purpose We aimed to evaluate the association between metabolic score for visceral fat (METS-VF) and prediabetes and to compare the predictive ability among obesity indicators.Methods A total of 4,376 participants (mean age, 55.4±7.1; male, 32.2%) with normal glucose metabolism were recruited in 2011, and were followed up in 2015. The demographic information and anthropometric measurement were collected by standardized procedures. The laboratory test was conducted in local communities. In the follow-up survey, the newly-diagnosed prediabetes incidents were collected. Logistic regression models and receiver operator characteristic curve analysis were used to evaluate the association of obesity indicators and prediabetes.Results During a median follow-up of 3.3 years, 1119 prediabetes participants were identified. After adjusting for all variables, the adjusted odds ratios for the highest, third, second versus lowest METS-VF quartile was 1.56 [95% confidence interval (CI) 1.17-2.08], 1.41 (95% CI 1.09-1.83), 1.25 (95% CI 1.02-1.58), respectively, and elevated with per 1-SD is associated with a 27 % increase in prediabetes risk (OR 1.27, 95% CI 1.17-1.38). A nonlinear relationship of METS-VF with incident prediabetes was observed (P for nonlinear=0.041). In the subgroup analysis stratified by age and sex, similar results were observed. METS-VF showed a better prediction ability for incident prediabetes (AUC 0.623, 95% CI 0.601-0.644).ConclusionMETS-VF is positively associated with the risk of prediabetes, and is a better predictor for prediabetes than all obesity indicators. It has the potential to early identify the risk of prediabetes in future clinical practices or primary health management.
A comparison between micro- and nano-structured compositionally graded layer TBCs: thermal shock and thermal cyclic fatigue behavior
Authors: Sezavar Arezoo , Sajjadi Seyed Abdolkarim , Babakhani Abolfazl , Peng Ru Lin 
Published: July 2022

Abstract

Thermal barrier coating (TBC) technology is used in the process of manufacturing of hot sections of turbine and diesel engines to improve the component life. Performance of micro- and nano-structured compositionally graded layer (CGL) TBCs produced by atmospheric plasma spray (APS) was investigated in thermal shock (TS) and thermal cyclic fatigue (TCF) conditions. Two groups of CGL-TBCs systems consisting of five layers: one bond coat layer with 100% NiCrAlY and four layers of NiCrAlY/YSZ in the weight ratios of 70:30, 50:50, 30:70 and 0:100 as top coat were investigated. In the micro- and nano-structured CGL-TBCs, conventional and nano-structured YSZ were used as TBC powders, respectively. TCF and TS tests were run at 900°C and continued until 1200 cycles. The results of the experimental studies on thermal cyclic behavior and microstructural evolution of micro- and nano-structured CGL-TBCs were compared and discussed. It was shown that after 1200 cycles of TS and TCF tests, no change in the phase composition of coatings is observed. Moreover, in both TS and TCF tests the signs of macroscopic damages appeared in micro CGL-TBC while no significant visible damage was seen in nano-structured one. Microscopic investigation revealed that although in both micro- and nano-structured CGL-TBCs, the integrity of underneath layers (bond coat and the other three gradient layers) up to top coat are preserved, different kinds of damage are seen in top coats. The presence of nanozones in the nano-structured CGL-TBC led to the toughening of the coatings through crack arresting techniques therefore, the nano-structured CGL-TBC showed better resistance than the micro one in the two tests.