bluuebunny/crossref_metadata_2025_split huggingface dataset:
Learning in Continuous Action Space for Determination of High Dimensional Potential Energy Surfaces
Authors: Sankaranarayanan Subramanian , Manna Sukriti , Loeffler Troy , Batra Rohit , Banik Suvo , Chan Henry , Sasikumar Kiran , Sternberg Michael , Peterka Tom , Cherukara Mathew , Gray Stephen , Sumpter Bobby 
Published: March 2021

Abstract
Reinforcement learning (RL) approaches that combine a tree search with deep learning have found remarkable success in searching exorbitantly large, albeit discrete action spaces, as demonstrated recently in board games like chess, Shogi, and Go. Many real-world materials discovery and design applications, however, involve multi-dimensional search problems and learning domains that have continuous action spaces. Exploring high-dimensional potential energy surfaces (PES) of materials to represent inter- and intra-molecular interactions, for example, involves a continuous action search to find optimal potential parameters or coefficients. Traditionally, these searches are time consuming (often several years for a single system) and have been driven by human intuition and/or expertise and more recently by global/local optimization searches that have issues with convergence and/or do not scale well with the search dimensionality. Here, in a departure from discrete action and other gradient-based approaches, we introduce a RL strategy based on decision trees that incorporates modified rewards for improved exploration, efficient sampling during playouts, and a “window scaling scheme” for enhanced exploitation, to enable efficient and scalable search for continuous action space problems. Using high-dimensional artificial landscapes and control RL problems, we successfully benchmark our approach against popular global optimization schemes and state-of-the-art policy gradient methods, respectively. We further demonstrate its efficacy to perform high-throughput PES search for 54 different elemental systems across the Periodic table, in- including alkali, alkaline-earth, transition metals, metalloids, as well as non-metals. Using a well-sampled (∼165,000 configurations) first-principles derived training and test dataset, we demonstrate that the new class of RL trained bond-order potentials capture the size-dependent energetic landscape from few atom clusters to bulk (energy errors << 200 meV/atom over a 3-6 eV sampled range) as well as their dynamics (force errors << 0.5 eV/A over a 50-100 eV/A range). We analyze the error trends across different
elements in the latent space and trace their origin to elemental structural diversity and the smoothness of the element energy surface. Finally, we run molecular dynamics using these RL trained potentials and perform a comprehensive test of dynamic stability of more than 40,000 clusters sampled for different elements across the Periodic table. Our newly developed high-quality potentials will enable accelerated nanoscale materials design and discovery. Broadly, our RL strategy will be applicable to many other physical science problems involving search over continuous action spaces.
Relationship between Changes in Cerebral Blood Volume During Hypoxic-ischemic Insult and Early Period after Insult
Authors: Mitsuie Tsutomu , Nakamura Shinji , Htun Yinmon , Nakao Yasuhiro , Arioka Makoto , Koyano Kosuke , Morimoto Aya , Wakabayashi Takayuki , Kuroda Yasuhiro , Takashi KUSAKA 
Published: March 2021

Abstract
To achieve better outcomes in hypoxic-ischemic encephalopathy, categorizing the degree of the hypoxia-ischemia (HI) is important for selecting suitable candidates for therapeutic hypothermia and any additional treatment strategies. We previously developed a novel model of asphyxiated piglets with a uniform degree of histopathological brain injuries that survived for 5 days after insult and showed changes in cerebral blood volume (CBV) that reflected the severity of the brain injuries. However, little is known about the relationship between changes in CBV during and after insult. In this study, an HI event was induced by low inspired oxygen in 23 anesthetized newborn piglets, including three sham controls. CBV was measured using near-infrared time-resolved spectroscopy (TRS). Data were collected before, during, and 6 h after insult. The change in CBV was calculated as the difference between the peak CBV value during insult and the value at the end of insult. The decrease in CBV during insult was found to correlate with the increase in CBV within 6 h after insult. Heart rate exhibited a similar tendency to CBV but blood pressure did not. The CBV increment immediately after resuscitation provides a relatively precise prediction of the severity of HI insult.
Fusion Methods and Multi-Classifiers for Improving Land Cover Estimation By Remote Sensing Analysis
Authors: Dibs Hayder , Hasab Hashim Ali , Mahmoud Ammar Shaker , Al-Ansari Nadhir 
Published: March 2021

Abstract
Adopting a low spatial resolution remote sensing imagery to get an accurate estimation of land-use and land-cover (LU/LC) is a very difficult task to perform. Image fusion plays a big role to map the LU/LC. Therefore, This study aims to find out a refining method for the LU/LC estimating by adopting these steps; (1) apply a three pan-sharpening fusion approaches to combine panchromatic (PAN) imagery has high spatial resolution with multispectral (MS) imagery has low spatial resolution, (2) employing five pixel-based classifier approaches on MS and fused images; artificial neural net (ANN), support vector machine (SVM), parallelepiped (PP), Mahalanobis distance (Mah) and spectral angle mapper (SAM), (3) Make a statistical comparison between classification results. The Landsat-8 image was adopted for this research. There are twenty LU/LC thematic maps were created in this study. A suitable and reliable LU/LC method was presented based on the obtained results. The validations of the results were performed by adopting a confusion matrix. A comparison made between the classification results of MS and all fused images levels. It proved that mapping the LU/LC produced by Gram-Schmidt Pan-sharpening (GS) and classified by SVM method has the most accurate result among all other MS and fused images that classified by the other classifiers, it has an overall accuracy about (99.85%) and a kappa coefficient of about (0.98). However, the SAM algorithm has the lowest accuracy compared to all other adopted methods, with overall accuracy of 53.41% and the kappa coefficient of about 0.48. The proposed procedure is useful in the industry and academic side for estimating purposes. In addition, it is also a good tool for analysts and researchers, who could interest to extend the technique to employ different datasets and regions.
Economic Performance of Indonesia amidst CO2 Emissions and Agriculture: A Time Series analysis
Authors: Adebayo Tomiwa Sunday , Akinsola Gbenga Daniel , Kirikkaleli Dervis , Bekun Festus Victor , Umarbeyli Sukru , Osemeahon Oseyenbhin Sunday 
Published: March 2021

Abstract
The research assesses the impact of CO2 emissions and energy use on economic performance and considers trade openness, urbanization, and agriculture in Indonesia utilizing data covering the period from 1965–2019. The current research employed the Dynamic Ordinary Least Square (DOLS), Autoregressive distributed lag (ARDL), and Fully Modified Ordinary Least Squares (FMOLS) methods. Furthermore, the Gradual shift and Wavelet coherence tests are utilized to capture the direction of causality. The ARDL bounds test discloses a long run interaction among the parameters of interest. The empirical evidence depicts that emissions, agriculture, energy use, and urbanization triggers economic growth. Besides, the growth-induced energy hypothesis is confirmed. This result is resonated by the causality analysis where GDP drives energy one-way in Indonesia. This proposes that Indonesia can embark on conservative energy policies, as such actions will not hurt its growth. Furthermore, there is one-way causality from agriculture to GDP. These outcomes have far-reaching significance for GDP growth and the selected variables in Indonesia.
Dissecting the role of genetic modifiers of hemoglobinopathies: A futuristic approach towards precision medicine
Authors: Hariharan Priya , Gorivale Manju , Sawant Pratibha , Mehta Pallavi , Nadkarni Anita 
Published: March 2021

Abstract
Introduction: Hemoglobinopathies though a monogenic disorder, show phenotypic variability. Hence, understanding the genetics underlying the heritable sub-phenotypes of hemoglobinopathies, specific to each population, would be prognostically useful and could inform personalized therapeutics. This study aimed to evaluate the role of genetic modifiers leading to higher HbF production with cumulative impact of the modifiers on disease severity. Materials and methods:200 patients [100 β-thalassemia homozygotes,100 Sickle Cell Anemia], and 50 healthy controls were recruited. Primary screening followed with molecular analysis for confirming the β-hemoglobinopathy was performed. Co-existing α-thalassemia and the polymorphisms located in 3 genetic loci linked to HbF regulation were screened.Results: The most remarkable result was the association of SNPs with clinically relevant phenotypic groups. The γ-globin gene promoter polymorphisms [-158 C→T,+25 G→A],BCL11A rs1427407 G→T,-3 bp HBS1L-MYB rs66650371 and rs9399137 T→C polymorphisms were correlated with higher HbF, in group that has lower disease severity score (P<0.00001), milder clinical presentation, and a significant delay in the age of the first transfusion.Conclusion:Our study emphasizes the complex genetic interactions underlying the disease phenotype that may be a prognostic marker for predicting the clinical severity and assist in disease management.
Machine learning discovered nano-circuitry for nonlinear ion transport in nanoporous materials
Authors: Zhan Hualin , Sandberg Richard , Xiong Zhiyuan , Liang Qinghua , Xie Ke , Zu Lianhai , Li Dan , Liu Jefferson Zhe 
Published: March 2021

Abstract
Connecting physio-chemical theory with electrical model is essential yet difficult for evaluating the impact of nonlinear ion transport on the performance of ionic circuits and electrochemical energy storage devices1-6. Here we demonstrate that machine learning can resolve this difficulty and produce physics-based nano-circuitry. Starting from a physio-chemical perspective, we first reveal an anomalous diffusion-enhanced migration of ions in nanopores, which exhibits a nonlinear electrical response. Using machine learning, we discover its underlying mathematical equation, and produce a dynamically varying ionic resistance for construction of nano-circuitry model. Based on the physio-chemical understanding of nano-circuitry model, we discover in supercapacitors that the nonlinear ion transport can lead to a Faradaic-like current peak in non-Faradaic processes and an asymmetric charging/discharging without ion desolvation, adding new perspectives to physio-chemistry.
Relay-based Cooperation in Mobile Data Offloading
Authors: Sadeghi Rasool , Hamidkhani Mehdi 
Published: March 2021

Abstract
Mobile data offloading has been emerged as a promising solution to manage high data traffic imposed by mobile users. This technique exploits the frequency spectrum of some overlapping networks such as WiFi in cellular networks. Deployment of minimum WiFi access points (APs) is the main challenge in mobile data offloading which leads to the low cost of CAPEX and OPEX. In this letter, we investigate the impact of a relay-based cooperative MAC protocol on the spectrum efficiency of mobile data offloading and consequently on the WiFi APs deployment. Two algorithms are presented to compute the throughput gain and the minimum number of WiFi APs in two modes of cooperative and non-cooperative MAC protocols. The analytical results indicate that the cooperative MAC protocol can provide a reduction of up to 44% in the number of WiFi APs in comparison to non-cooperative mode.
The Effect of Intraoperative Dexmedetomidine on Cognitive Dysfunction After Surgery: A Updated Meta-Analysis
Authors: Yin Qifan , Li Jianli , Xun Xuejiao , He Jinhua , Yu Dongdong , Wang Zhibin , Rong Junfang 
Published: March 2021

Abstract
BackgroundPostoperative cognitive dysfunction (POCD) is one of the most common. Neuroprotective effects of dexmedetomidine(DEX) are reported in previous studies but evidence regarding the POCD is still unclear. In order to gain latest evidence, the present study analyzes the outcomes of randomized controlled trials(RCTs) which utilized DEX with general anaesthesia perioperatively.MethodFour online databases (PubMed, Embase, the Cochrane Library, and CNKI) were used to find relevant RCTs to conduct systematic analysis. All studies comparing the incidence of POCD or MMSE score between the DEX group and the placebo or comparator group in patients undergoing general anaesthetic surgery were eligible for inclusion. Based on the inclusion and exclusion criteria, the studies were selected. This meta-analysis was performed using odds ratios (ORs) with 95% confidence intervals (CIs) for dichotomous data and standardized mean difference (SMD) and 95% CIs for continuous data as effective measures.ResultsIn total of 21 studies were included in this meta-analysis. The results showed that the incidence of POCD in DEX group was significantly lower than the control group on the first (OR=0.36, 95% CI 0.24-0.54),third (OR=0.45,95% CI 0.33–0.61) and seventh (OR=0.40,95% CI 0.26–0.60) postoperative days; the MMSE scores in DEX group were higher than the control group on the first (SMD=1.24, 95% CI 1.08-1.41), third(SMD= 1.09, 95%CI 0.94-1.24) and seventh (SMD=3.28, 95% CI 1.51-5.04) postoperative days. Conclusions﻿Intraoperative DEX use can ameliorate the POCD of patients who received surgical operations under general anesthesia, and effectively reduce the incidence of POCD and improve MMSE score.
Young Men and Young Women in Secure Care: Gender Differences in the Placement of Those With Mental Health Needs
Authors: Bartlett Annie , Smith Jared G , Warner Louise , Hales Heidi 
Published: March 2021

Abstract
Background The system of secure care for young people in England and Wales comprises youth justice, welfare and mental health facilities. Empirical studies have failed to investigate the system as a whole. The National Adolescent Study in 2016 was the first to provide comprehensive system wide information. This paper, derived from that data set, addresses equity of service provision for young men and women in secure care who have mental health problems.MethodsThe detained census population of English young people was 1322 and detailed data were available on 93% of this population, including 983 young men and 290 young women. The descriptive census data were interrogated to identify associations between gender, other sociodemographic and clinical variables, using Chi-square and Fisher’s exact tests. To control for Type 1 errors, the False Discovery rate approach was used. SPSS (V25) was used for statistical analysis.Results Numerically more young men in secure care than young women in secure care warrant a psychiatric diagnosis but young women had a 9 fold increase in the odds of having a diagnosis compared with the young men. The pattern of mental health diagnoses differed significantly by gender as did the pattern of young men and women’s secure care placement. This different pattern of placement continued to differ by gender when the nature of the mental health diagnosis was taken into account.Conclusions No definitive explanation is evident for the significantly different, placement patterns of young men and young women with the same, mental health diagnoses but the anticipated consequences for some, young men and some young women are important. Proper explanation demands an examination of process variables out with the remit of this study. The lack of routine scrutiny and transparent processes across secure settings could be responsible for the development of these differential placement practices; these practices seem at odds with the duty placed on public services by the Equality Act.
Montmorillonite-Based Porous Composites as Adsorbents for Removal of Cr(III)-Organic Complexes in Tannery Wastewater
Authors: Hao Xin , E Tao , Yang Shuyi , Li Yun 
Published: March 2021

Abstract
Montmorillonite-based porous adsorbent prepared by gel casting method was used to adsorb Cr(III)-organic complexes in tanning wastewater with the initial concentration of 10 mg L−1. The as-porous adsorbent exhibited an excellent performance of separation. Meanwhile, its structural and morphology were characterized by TG, BET, XRD, SEM, EDS and XPS, showing that the porous adsorbent was complete hollow ball structure. And the adsorption results showed that the adsorption amount of porous adsorbent rapidly declined from 9.58 to 5.28, and only Cr(III) was adsorbed, when the molar ratio of Cr(III) and citrate was more than 1:5. Increased of pH was beneficial to the adsorption of Cr(III)-citrate in range from 2.46 to 7.12. Furthermore, the best removal efficiency of porous adsorbent for Cr(III)-organic complex used up to 97% and remaining above 84% after five cycles. Finally, the adsorption mechanism of Cr(III) on porous adsorbent is also provided. Therefore, a kind of easy separated porous adsorbent was prepared in this study so as to treat tanning wastewater containing Cr(III)-organic complex following alkali precipitation, as well as solving the problem of difficult recycle.
The Usage of High-Flow Nasal Oxygen (HFNO) for Patients with Covid-19 Outside Intensive Care Units
Authors: issa issa , Soderberg Marten 
Published: March 2021

Abstract
IntroductionThe usage of high-flow nasal oxygen (HFNO) has traditionally been located in intensive care units (ICU). As the Covid-19 pandemic continues to be a challenge to the whole world, health care providers are trying to manage space in the ICU. HFNO is well studied for usage in acute respiratory distress syndrome (ARDS). We tried to study the usage of HFNO in patients with moderate to severe ARDS related to Covid-19 outside the ICU as well as its benefits both for patients and to offload the ICU.MethodsWe started a project to use HFNO in the ward of infectious diseases at Södersjukhuset, Stockholm. Patients with Covid-19 who needed HFNO were transferred to this ward after assessment from anesthesiologists or intensive care doctors. The patients were observed with frequent controls to assess the need of ICU in case of deterioration. The aim was mainly to offload the ICU.ResultsWe studied 41 patients who were admitted for getting HFNO treatment either as primary treatment (Step-Up) or after stabilizing in the ICU (Step-Down). We studied the patients’ characteristics and the treatment’s result and compared it to a subgroup of patients who did not survive this treatment. Most of our patients were men (80%). They had at least one chronic disease (61%). Each patient had on average 5.6 days of treatment with HFNO. 55% of the patients were discharged home or to geriatric rehabilitation. 10% avoided ICU completely and 15% of patients who simultaneously had a DNR orders (Do-Not-Resuscitate) survived by using HFNO and moved to geriatric rehabilitation. The usage of HFNO saved in total 229 days in the ICU. Mortality was higher among elderly patients, and patients with comorbidities (mainly hypertension and obesity). Discussion and conclusionHFNO treatment is feasible and efficient for patients with Covid-19, saving resources in ICU when the need is maximized, and offering additional advantages as waken proning and fewer complications compared to traditional ICU care. It requires however frequent controls as deterioration is recurrent.
A Novel Stable QTL&nbsp;in Chromosome A04 for Salt Tolerance at the Seed Germination Stage of Upland Cotton via a Resequencing-Based High-Density Genetic Map
Authors: Gu Qishen , Ke Huifeng , Liu Chenchen , Lv Xing , Sun Zhengwen , Liu Zhengwen , Rong Wei , Yang Jun , Zhang Yan , Wu Liqiang , Zhang Guiyin , Wang Xingfen , Ma Zhiying 
Published: March 2021

Abstract
Key message Two candidate genes GhGASA1 and GhADC2 playing negative roles by modulating the GA and PA signaling pathway, respectively, were identified in a major QTL for germination under salt stress.The successful transition of a seed into a seedling is the prerequisite for plant propagation and crop yield. Germination is a vulnerable stage in a plant’s life cycle which is strongly affected by environmental conditions, such as salinity. In this study, we identified a novel stable quantitative trait locus (QTL) qRGR-A04-1 associated with relative germination rate (RGR) after treatment with salt stress based on a high-density genetic map under phytotron and filed conditions, with LOD values of 6.65-16.83 and 6.11-12.63% of phenotypic variations in all five environment tests. Two candidate genes with significantly differential expression between two parents were finally identified through RNA-seq and qRT-PCR analyses. Further functional analyses showed that GhGASA1- and GhADC2-overexpression lines were more sensitive to salt stress than wild-type in Arabidopsis through regulating the transcript levels of gibberellic acid (GA) and polyamine (PA) -related genes implicating in GA and PA biosynthesis with reducing the accumulation of GA and PA under salt stress, respectively. Virus-induced gene silencing analysis showed that TRV:GASA1 and TRV:ADC2 displayed more tolerant to salt stress by increasing the expression of GA-synthesis genes and decreasing the H2O2 content, respectively. Taken together, our results suggested that QTL qRGR-A04-1 and its harbored two genes, GhGASA1 and GhADC2, were promising candidates for salt tolerance improvement in cotton.
Texture Grouping and Statistical Optimization Based Mode Prediction Decision Algorithm for Fast HEVC Intra Coding
Authors: Wang Jianhua , Lin Feng , Zhao Jing , Long Yongbing 
Published: March 2021

Abstract
HEVC (High Efficiency Video Coding), as one of the newest international video coding standard, can achieve about 50% bit rate reduction compared with H.264/AVC (Advanced Video Coding) at the same perceptual quality due to the use of flexible CTU(coding tree unit) structure, but at the same time, it also dramatically adds the higher computational complexity for HEVC. With the aim of reducing the computational complexity, a texture grouping and statistical optimization based mode prediction decision algorithm is proposed for HEVC intra coding in this paper. The contribution of this paper lies in the fact that we successfully use the texture information grouping and statistical probability optimization technology to rapidly determine the optimal prediction mode for the current PU, which can reduce many unnecessary prediction and calculation operations of HCost (Hadamard Cost) and RDCost (Rate Distortion Cost) in HEVC, thus saving much computation complexity for HEVC. Specially, in our scheme, firstly we group 35 intra prediction modes into 5 subsets of candidate modes list according to its texture information of edge in the current PU, and each subset only contains 11 intra prediction modes, which can greatly reduce many traversing number of candidate mode in RMD (Rough Mode Decision) from 35 to 11 prediction modes; Secondly we use the statistical probability of the first candidate modes in candidate modes list as well as MPM selected as the optimal prediction mode to reduce the number of candidate modes in RDO(Rate Distortion Optimization), which can reduce the number of candidate modes from 3+MPM or 8+MPM to 2 candidate modes; At last, we use the number of candidate modes determined above to quickly find the optimal prediction mode with the minimum RDCost by RDO process. As a result, the computational complexity of HEVC can be efficiently reduced by our proposed scheme. And the simulation results of our experiments show that our proposed intra mode prediction decision algorithm based on texture information grouping and statistical probability optimization in this paper can reduce about 46.13% computational complexity on average only at a cost of 0.67% bit rate increase and 0.056db PSNR decline compared with the standard reference HM16.1 algorithm.