bluuebunny/crossref_metadata_2025 huggingface dataset:
Generalization Enhancement of Artificial Neural Network For Turbulence Closure By Feature Selection
Authors: Zhu Linyang , Zhang Weiwei , Tu Guohua
Published: July 2021

Feature selection targets for selecting relevant and useful features, and is a vital challenge in turbulence modeling by machine learning methods. In this paper, a new posterior feature selection method based on validation dataset is proposed, which is an efficient and universal method for complex systems including turbulence. Different from the priori feature importance ranking of the filter method and the exhaustive search for feature subset of the wrapper method, the proposed method ranks the features according to the model performance on the validation dataset, and generates the feature subsets in the order of feature importance. Using the features from the proposed method, a black-box model is built by artificial neural network (ANN) to reproduce the behavior of Spalart-Allmaras (S-A) turbulence model for high Reynolds number (Re) airfoil flows in aeronautical engineering. The results show that compared with the model without feature selection, the generalization ability of the model after feature selection is significantly improved. To some extent, it is also demonstrated that although the feature importance can be reflected by the model parameters during training process, artificial feature selection is still very necessary.
Generation of Continuous Hybrid Zig-zag and Contour Paths For 3D Printing
Authors: Gomez Gorka , Cortés Camilo , Creus Carles , Amilibia Maialen Zelaia , Moreno Aitor
Published: July 2021

The generation of the printing paths is a decisive step in additive manufacturing (AM). There is a variety of patterns that offer different characteristics, but those that are strictly continuous become especially relevant in certain types of AM by extrusion, with materials like bioinks, carbon or clays, since they do not allow the retraction of the material and travelling movements result in the generation of artefacts. In this work, we present (1) a method that generates continuous paths to fill 2D polygons with a hybrid zig-zag and contour pattern with any direction and line separation,which is based on the extension of an algorithm that decomposes the 2D area to be filled into convex areas, (2) a method to join the subpolygon trajectories such that a continuous path that fills the whole polygon is obtained, and (3) a publicly available dataset of 2D polygons that are relevant to test the performance of the algorithms.
A Novel Grey Power-markov Model for the Prediction of China's Electricity Consumption
Authors: Sun Liqin , Yang Youlong , Ning Tong , Zhu Jiadi
Published: July 2021

The grey prediction models of time series are widely used in demand forecasting because only limited data can be used to build the models and no statistical hypothesis is needed. In this paper, a grey power Markov prediction model (RGPMM(λ,1,1)) with time-varying parameters is proposed. This model is based on the principle of “new information priority”, combined with rolling mechanism and Markov theory, and the prediction residual error is modified to further improve the prediction accuracy. Compared with the classic grey models, the new model not only overcomes the inherent defect of poor adaptability to the original data, but also uses real-time information to better reflect the nonlinear characteristics of the original data, so it can be used to describe and predict the nonlinear development trend of things. In order to verify the validity and applicability of the model, the proposed model is used to forecast the total electric consumption in China. The experimental results show that the proposed model has a better prediction effect than other grey models. The proposed model is used to forecast China’s total electricity consumption in the next six years from 2018 to 2023.
Molecular dynamics simulation of initial thermal decomposition mechanism of DNTF
Authors: Bai Hui , Luo Yiming , Jiang Jun , Gou Rui-jun , Zhang Shuhai , Hu Wenjun
Published: July 2021

In order to understand the thermal decomposition characteristics of 3,4-Bis(3-nitrofurazan-4-yl)furoxan (DNTF), the thermal decomposition reaction of DNTF at 300-4000K temperature programmed and constant temperature of 2000K, 2500K, 3000K, 3500K and 4000K was simulated by ab initio computational molecular dynamics method. The thermal decomposition mechanism of DNTF at different temperatures was analyzed from the aspects of product evolution, cluster, potential energy curve and reaction path. The analysis of products, show that the initial small molecular products are NO, NO2, CO, CO2 and N2, and the final small molecular products are CO2 and N2. In the early stage, the ring-opening reaction of furoxan in DNTF structure is the main trigger reaction, and the C-C bond is broken at the initial stage of reaction. The carbon chain structure produced by decomposition forms various cluster structures in the form of C-N bond. In addition, it was found that temperature significantly affects the decomposition rate of DNTF, but does not change its initial decomposition path.
Global Sensitivity Analysis of a Coupled Hydro-Economic Model and Groundwater Restriction Assessment
Authors: Rodríguez-Flores José M. , Valero-Fandiño Jorge A. , Cole Spencer A. , Malek Keyvan , Karimi Tina , Zeff Harrison B. , Reed Patrick M. , Escriva-Bou Alvar , Medellín-Azuara Josué
Published: July 2021

The modeling of coupled food-water systems to represent the effect of water supply variability as well as shocks that may emerge from changes in policies, economic drivers, and productivity requires an understanding of dominant uncertainties. These uncertainties cascade into forecasts of impacts of water management policies, such as groundwater pumping restrictions. This paper assesses how parametric, crop price, crop yields, surface water price, and electricity price uncertainties shape hydro-economic model estimates for agricultural production through a diagnostic global sensitivity analysis (GSA).The diagnostic GSA explores how the uncertainties in combination with a candidate groundwater pumping restriction influence three metrics of concern: total economic revenue, total land use and groundwater depth change. The hydro-economic model integrates a Groundwater Response Function (GRF) by integrating an Artificial Neural Network (ANN) into a calibrated Positive Mathematical Programming (PMP) production model for the Wheeler Ridge-Maricopa Water Storage District located in Kern County, California. Our results show that in addition to groundwater pumping restriction, performance metrics of the system are highly sensitive to prices and yields particularly of profitable crops. These sensitivities become salient during dry years when there is a higher reliance on groundwater.
B4GALT5 High Expression Associated With Poor Prognosis of Hepatocellular Carcinoma
Authors: Han Yang , Li Zhe , Wu Qi , Liu Hui , Sun Zhiqiang , Wu Yong , Luo Judong
Published: July 2021

Background: B4GALT5 is postulated to be an important protein in sugar metabolism that catalyzes the synthesis of lactosylceramide (LacCer). However, its role in hepatocellular carcinoma (HCC) remains unknown.Method: We characterized the expression of B4GALT5 in HCC tissue compared to normal tissue, and explored its function of B4GALT5 in HCC by enrichment analysis based on its co-expressed gene set. Next, we checked whether B4GALT5 expression is correlated to immune infiltration level and clinical prognosis in hepatocellular carcinoma. Finally, we verified the expression of B4GALT5 using clinical samples evaluated by RT-PCR, and conducted in vitro experiments with B4GALT5-knockdown HCC cells to investigate the function of B4GALT5 in the HCC cell proliferation, migration and invasion.Results: We found B4GALT5 mRNA and protein expression levels were significantly high in HCC tissue compared to normal tissue. The enrichment analysis of the gene sets that co-expressed with B4GALT5 showed specificity in HCC-related pathways and functions. Also, the expression pattern of B4GALT5 was significantly related to the immune infiltration level, especially CD4+ T cell and macrophage cells. B4GALT5 higher mRNA expression was associated with poor overall survival (OS) in HCC patients. Furthermore, In vitro experiments showed that depletion of B4GALT5 significantly inhibited HCC cell proliferation, migration and invasion. This study revealed the function and its mediated pathways of B4GALT5 in HCC, indicating that B4GALT5 may serve as a prognostic biomarker of HCC.
Accurate Spectrophotometric Method for Semitransparent Metallic Thin-film Index Determination Using Interference Enhancement
Authors: Shurvinton Riley , Lemarchand Fabien , Moreau Antonin , Lumeau Julien
Published: July 2021

An accurate spectrophotometric method to determine the refractive index of a semitransparent metallic thin film is presented. This method relies on interference enhancement of the measured spectra, employing an opaque substrate with a dielectric spacer layer beneath the absorbing layer of interest to create interference fringes. The resulting spectral oscillations of the stack are highly sensitive to the properties of the top absorbing layer, allowing precise determination of the refractive index via fitting. The performance of this method is verified using simulations in comparison to the typical method of depositing the absorbing thin film directly onto a transparent substrate. An experimental demonstration is made for titanium thin films over the visible range (370-835 nm). The refractive index of these films is extracted from experimental data using a combination of the Modified Drude and Forouhi-Bloomer models. This method showed high repeatability and accuracy, and is verified for Ti films between 6-70 nm thickness.
Dynamic Variations of Cyanobacterial Blooms And Their Response To Urban Development And Climate Change In Lake Chaohu Based On Landsat Observations
Authors: Qin Xuemin , Xia Wei , Hu Xiaoxuan , Shao Zhen
Published: July 2021

Recurring cyanobacterial blooms have seriously hindered the sustainable development of cities. In this study, the variation trend of cyanobacterial blooms was analyzed by taking Lake Chaohu in China as the study area, and the Normalized Difference Vegetation Index (NDVI) derived from Landsat observations combined with the development index of surrounding cities from 2009 to 2019 was used to quantitatively analyze the response of cyanobacterial blooms to urban development and climate change. The results showed that the NDVI of the Northwest Lake region was significantly higher than that of other regions. Summer and autumn were the main seasons for the outbreak of cyanobacterial blooms. The NDVI of Lake Chaohu and Baohe Lake region showed a significant correlation with the gross domestic product (GDP) growth rate of Hefei city (HF), the districts and counties around the lake (DCL)，Baohe District (BH) and the population (P). As the economic regions gradually focused on BH rather than on HF and DCL, there was an increasing trend correlation between the NDVI of Baohe Lake region and the GDP growth rate. However, the elimination of GDP in BH did not affect the consistency relationship between the economic growth of other regions and the NDVI of Lake Chaohu on a large scale. In addition, the results of relative importance analysis indicated that the GDP growth rate of BH and the area of Hefei except DCL (HF-DCL) accounted for important contribution to the R2 of the regression. This study has momentous reference value for understanding the coupling relationship between urban development and lake environment.
Kinetics And Monte Carlo Simulation of UV Disinfection B. Subtilis Spores And SARS-CoV-2 In Dried Saliva Droplets
Authors: Gibson John , Farnood Ramin , Barbeau Benoit
Published: July 2021

Surfaces can be contaminated by droplets produced coughing or sneezing. In this short, exploratory work, UV disinfection data from B. subtilis spores in dried saliva droplets were fitted to a first-order model. The model has a disinfection rate constant for single organisms, and a smaller one for aggregates (R2 ≥ 0.97). Changes in the fraction of organisms in aggregates (β) alone could account for the effects of different sized droplets in the experimental work. Since a wide spectrum of droplet sizes can be produced and some of the rate constants were uncertain, Monte Carlo simulation was used estimate the UV inactivation performance in dried saliva droplets in a range of conditions. Using conservative lognormal distribution for β, the model was applied to the UV disinfection of SARS-CoV-2 in dried droplets. It was shown that one-log reduction of SARS-CoV-2 was very likely (p>99.9%) and two-log reduction was probable (p=75%) at a dose of 60 mJ/cm2. Aggregates tend to be variable and limit the log reductions that can be achieved at high UV doses.
Synthesis And Characterization of CdS/CeO2 Nanocomposite With Improved Visible-Light Photocatalytic Degradation of Methyl Orange Dye
Authors: Bekele Tigabu Mekonnen
Published: July 2021

In this work, different types of photocatalysts in single (CdS and CeO2) and binary (CdS/CeO2 in different molar ratio: 0.5:1, 1:1 and 1:0.5) systems were synthesized by co-precipitation method. Crystal structure, surface area, morphology, band gap energy, functional groups and optical properties of the as-synthesized photocatalysts were characterized by using XRD, BET, SEM-EDX, UV/Vis, FTIR and PL instruments, respectively. Photocatalytic activities of single and binary nanocomposite were evaluated by using aqueous solution of model pollutant methyl orange dye (MeO). Photocatalytic activities of binary CdS/CeO2 (1:1) nanocomposite were found to be higher than those of single counterparts. The photodegradation efficiencies of the binary system were found to be 53.73%. The reusability of binary photocatalyst was tested and only about 33% decrement was observed after four successive runs. Photocatalytic degradation of MeO dye follows the pseudo first order kinetics for the entire as-synthesized nanocomposite. The results also suggest that in the CdS/CeO2 (1:1) nanocomposite the photoinduced electrons and holes can be effectively separated.
Impacts of Dynamical Downscaling on Circulation type Statistics: Potential added Value in the Euro-CORDEX Ensemble
Authors: Røste Julie , Landgren Oskar A
Published: July 2021

Atmospheric circulation type classification methods were applied to an ensemble of 57 regional climate model simulations from Euro-CORDEX, their 11 boundary models from CMIP5 and the ERA5 reanalysis. We compared frequencies of the different circulation types in the simulations with ERA5 and found that the regional models add value especially in the summer season. We applied three different classification methods (the subjective Grosswettertypes and the two optimisation algorithms SANDRA and distributed k-means clustering) from the cost733class software and found that the results are not particularly sensitive to choice of circulation classification method. There are large differences between models. Simulations based on MIROC-MIROC5 and CNRM-CERFACS-CNRM-CM5 show an over-representation of easterly flow and an under-representation of westerly. The downscaled results retain the large-scale circulation from the global model most days, but especially the regional model IPSL-WRF381P changes the circulation more often, which increases the error relative to ERA5. Simulations based on ICHEC-EC-EARTH and MPI-M-MPI-ESM-LR show consistently smaller errors relative to ERA5 in all seasons. The ensemble spread is largest in the summer and smallest in the winter. Under the future RCP8.5 scenario, more than half of the ensemble shows an increase in frequency of north-easterly flow and decrease in the Central-Eastern European high and south-easterly flow. There is in general a strong agreement in the sign of the change between the regional simulations and the data from the corresponding global model.
Comparative Analysis of Daily and Hourly Temperature Variability in Association with All-Cause and Cardiorespiratory Mortality in 45 US Cities
Authors: Yu Yong , Luo Siqi , Zhang Yunquan , Liu Linjiong , Wang Ke , Hong Le , Wang Qun
Published: July 2021

BackgroundTemperature variability (TV) has been widely associated with increased mortality risk and burden. Extensive researches have used the standard deviations of several days’ daily maximum and minimum temperatures or hourly mean temperatures as daily and hourly TV measures (TVdaily and TVhourly). However, comparative analysis of daily and hourly TV related to cardiorespiratory mortality is still limited.MethodsWe collected daily mortality and meteorological data in 45 US metropolises, 1987–2000. A three-stage analyses were adopted to investigate TV-mortality associations using TVdaily and TVhourly as exposure metrics. We first applied a time-series quasi-Poisson regression to estimate location-specific TV-mortality relationship, which were then pooled using random-effects meta-analysis with maximum likelihood estimation (MLE). We additionally calculated attributable fractions as a reflection of total mortality burden associated with TV. Stratified analyses by age were also performed to identify the susceptible group to TV-related risk.ResultsThere were a total of 15.4 million all-cause deaths, of which 6.1 million were from cardiovascular and 1.2 million were from respiratory causes. Per 1 °C increase in TVdaily and TVhourly was associated with an increase of 0.53% (95% confidence interval: 0.31–0.76%) and 0.52% (0.26–0.79%) in cardiovascular mortality risks, 0.62% (0.26–0.98%) and 0.53% (0.13–0.94%) in respiratory mortality risks. Estimations of cardiovascular attributable fractions for TVdaily and TVhourly were 2.43% (1.42–3.43%) vs 1.63% (0.82–2.43%), whereas respiratory attributable fractions were 3.07% (1.11–4.99%) vs 1.89% (0.43–3.34%). Both daily and hourly indexes showed approximately linear relationships with different mortality categories and similar lag patterns, but greater fractions were estimated using TVdaily than those using TVhourly. People over 75 years old were relatively more vulnerable to TV-induced risks of mortality.ConclusionsBoth TVdaily and TVhourly significantly increased all-cause and cardiorespiratory mortality risks and burden. Daily TV metrics resembled hourly in risk effects, whilst greater mortality burden was found in TVdaily than TVhourly. Our findings may add significance to TV-mortality research and help to promote optimal health management strategies to better mitigate TV-related health effect.
Time Investment of Medical Students during COVID19 Pandemic lockdown
Authors: Hassan Mohajer Ibrahim , Alfatih Mohammed , Taha Mohamed Sharfaldeen Khider , Alhussein Radi Mohd Fawzey Rdi Tofaha , Shaban Mohanned Abdalfdeel Amahie , Ahmed Afra kamal Yahya , Abdalaziz Muaz Hasan , Ahmed Khabab Abbasher Hussien Mohamed , Omer Mohammed Eltahier Abdalla
Published: July 2021

Background: As the world is fighting against the COVID19 outbreak most of the countries closed universities nationwide, impacting nearly 80% of students globally. In order to obtain information and to identify differences between medical students the study has been asset. The primary objective of this survey is to better understand the motivations and obstacles for medical students investing their time during COVID 19 obligatory home stay.Methods: Descriptive cross-sectional survey-based study in 333 medical students in medical college of Alzaeim al Azhari university in Sudan. Data from students was collected by using an online self-design questionnaire. The participants approached by the lead investigator through their social media groups by link enabling the individual willing to participate to access a google form containing the study questionnaire. Analyses was carried out using SPSS statistics package version 24 (IBM).Results: (57.1%) of the participants were females and (42.9%) were males. (37.8%) of medical students who participated in the study think that they make use of their time, while (38.1%) don’t think that and (24.1%) don’t know if they make use of their time or not during staying home due to COVID19 outbreak. Conclusion: There is a considerable variation in time investment (making use of time) during staying home due to COVID 19 outbreak according to medical student’s insight. The research results indicate that medical students need more encouragement and facilities to get benefits from their time during the quarantines and such situation in the future.
Prognostic MicroRNA Panel for HCV-Associated HCC: Integrating Computational Biology and Clinical Validation
Authors: Dabbish Areeg M. , Abdelzaher Hana M. , Abohawya Moustafa , Shamma Samir , Mahmoud Yosra H. , Maged Amr , Manaa Mohamed , Hassany Mohamed , El-Fawal Hassan , Azzazy Hassan , Elnaser Anwar Abd
Published: July 2021

BackgroundEarly detection of hepatocellular carcinoma (HCC) will reduce morbidity and mortality rates of this poorly diagnosed widely-spread disease. Dysregulation in microRNA (miRNAs) expression is associated with HCC progression. MethodsThe objective is to identify a panel of differentially expressed miRNAs (DE-miRNAs) to enhance HCC early prediction in hepatitis C virus (HCV) infected patients. Candidate miRNAs were selected using bioinformatic analysis of microarray and RNA-sequencing datasets, resulting in nine DE- miRNAs (miR-142, miR-150, miR-183, miR-199a, miR-215, miR-217, miR-224, miR-424 and miR-3607). Their expressions were validated in the serum of 44 healthy individuals, 62 non-cirrhotic HCV patients, 67 cirrhotic-HCV and 72 HCV-associated HCC patients using real time PCR (qPCR).ResultsThere was a significant increase in serum concentrations of the nine-candidate miRNAs in HCC and HCV patients relative to healthy individuals. MiR-424, miR-199a, miR-142, and miR-224 expressions were significantly altered in HCC compared to non-cirrhotic patients. While miR-199a and miR-183 showed differential expression in cirrhotic relative to non-cirrhotic patients. A panel of 5 miRNAs improved sensitivity and specificity of HCC detection to 100% and 95.12% relative to healthy controls. Distinguishing HCC from HCV-treated patients was achieved by 70.8% sensitivity and 61.9% specificity using the combined panel, compared to alpha-fetoprotein (51.4% sensitivity and 60.67% specificity).ConclusionMiR-142, miR-183, miR-199a, miR-224 and miR-424 novel panel could serve as non-invasive biomarker for HCC early prediction in chronic HCV patients.
‘… The Elderly are More Comfortable at Home Than at The Health Facility’. Primary Care Provider Notions On Instituting Community-Based Geriatric Support in Uganda
Authors: Ssensamba Jude Thaddeus , Nakafeero Mary , Musana Hellen , Amollo Mathew , Ssenyonjo Aloysius , Kiwanuka Suzanne N
Published: July 2021

Background

Understanding of the most economical and sustainable models of providing geriatric care to Africa’s rising ageing population is critical. In Uganda, the number of old adults (60 years and above) continues to rise against absence of policies and guidelines, and models for providing care to this critical population. Our study explored public primary health care provider views on community-based geriatric support (CBGS) as an adaptable model for delivering geriatric care in Uganda’s resource-limited primary public health care settings.
Methods

We interviewed twenty key informants from four districts of Bukomansimbi, Kalungu, Rakai, and Lwengo in Southern Central Uganda. Respondents were leads (in-charges) of public primary health units that had spent at least six months at the fore said facilities. All interviews were audio-recorded, transcribed verbatim, and analysed based on Hsieh and Shannon’s approach to conventional manifest content analysis.
Results

During analysis, four themes emerged: 1) Structures to leverage for CBGS, 2) How to promote CBGS, 3) Who should be involved in CBGS, and 4) What activities need to be leveraged to advance CBGS? The majority of the respondents viewed using the existing village health team and local leadership structures as key to the successful institutionalization of CBGS; leveraging community education and sensitization using radio, television, and engaging health workers, family relatives, and neighbors. Health outreach activities were mentioned as one of the avenues that could be leveraged to provide CBGS.
Conclusion

Provider notions pointed to CBGS as a viable model for instituting geriatric care in Uganda’s public primary healthcare system. However, this requires policymakers to leverage existing village health team and local governance structures, conduct community education and sensitization about CBGS, and bring onboard health workers, family relatives, and neighbors.
A Blockchain-Based Streaming Data Sharing Scheme with Incentives and Trust Access Control
Authors: Wang Yanping , Hu Teng , Zhong Qi , Zhu Yukun , Song jingcheng , Zhang Xiaosong
Published: July 2021

The fifth-generation of cellular mobile communications (5G) networks promotes the internet of everything, smart devices are setting to penetrate each piece of our life, generating a large amount of data. Data sharing is essential to derive the inherent value, either in the form of social/financial gain or strategic competitive advantage. However, the concerns of security and the deficiency of effective incentive in the Internet of things (IoT) lead to the poor willingness of data sharing. Such considerations call for novel IoT data-sharing protocols that can achieve better data security and provide a more attractive incentive mechanism. In this paper, we exploit smart contracts, re-encryption, and hash-chain to propose a reliable streaming data sharing scheme. Firstly, the incentives to stimulate the owner’s enthusiasm of sharing data is considered, our scheme provides authorized user accessible to the shared data and provides data providers profits to share data. Secondly, a n-time query mechanism that provided flexible data access is designed, in which authorized users can query the data n times within an agreed time. Since the query voucher and every successful query is recorded and verified by smart contract, everyone in the blockchain network can validate it, the trustfulness of data access are ensured. The analysis showed that our scheme has better performance than some of the current data sharing schemes, and the experiment is conducted to demonstrate the effectiveness of our design.
Comparing the Performance of Fuzzy Operators in the Object-based Image Analysis and Support Vector Machine Kernel Functions for the Snow Cover Estimation in Alvand Mountain
Authors: Karampour Mostafa , Halabian Amirhossein , Hosseini Akbar , Mosapoor Mostafa
Published: July 2021

Snow cover is a significant driver in many ecological, climatic, and hydrological processes regarding the mountainous regions and high-latitude areas. Researchers believe that remote-sensing data can provide better estimates of snow cover ranges in comparison with the traditional surveying methods. Therefore, the present study was conducted using Sentinel-2B satellite images to compare the performance of the support vector machine (SVM) kernel functions and object-oriented fuzzy operators in estimating the amount of snow cover in the Alvand Mountain. In this research, the data consists of four Sentinel-2B satellite bands at 10 m spatial resolution (B2, 3, 4 & 8), launched on March 6, 2020. In this research study, the linear, polynomial, radial, and sigmoid SVM kernel functions, as well as the object-oriented fuzzy operators (AND, OR, MGE, MAR, MGWE, and ALP) have been employed. The results indicated that among these algorithms, AND algorithm, which represents the logical commonality, included the lowest return fuzzy value of 98%; therefore, this algorithm seems to provide the overall highest accuracy. Based on these findings, in the digital image classification, the object-oriented processing method can make it possible to achieve the highest accuracy compared to the SVM kernel functions. The reason is that a wide range of information, such as texture, shape, position, content, and bandwidth is associated with the objects in this classification method.
Impact of Digital Game-Based Learning on the Social Competence and Behavior of Pre-Schoolers
Authors: Fang Menglin , Tapalova Olga , Zhiyenbayeva Nadezhda , Kozlovskaya Svetlana
Published: July 2021

Digital gaming has become a regular part of life for today’s pre-schoolers. Hence, there is a need to look at the integration of digital technology into the preschool education. The present study aims to examine the effect digital games have on children's behaviour and their social competence if played to reach an educational purpose (supervised play) and for fun (without educational aim). The study population consists of 54 pre-schoolers (26 girls and 28 boys), aged 4 to 6, who were recruited in Moscow, Russia. All children were divided in two groups: children playing digital games with peers (n = 28) and children playing digital games at home (n = 28). Findings revealed a higher level of social competence in the experimental group (+11.71, p ˂ 0.05) as compared to children playing without being told what they were expected to achieve. The experimental group also scored lower on Anxiety-Withdrawal (-7.94, p ˂ 0.05). A higher Anxiety-Withdrawal score normally means that a child experiences some degree of depression or anxiety, and exhibits overly dependent behaviour. The results of this study may help parents and teachers to use digital learning tools, in particular video games, effectively when working with young children.
Effects of hospice palliative care on medical service utilisation by patients on prolonged mechanical ventilation: A nationwide cohort study
Authors: Liu Chin-Jung , Chu Yeong-Ruey , Chu Chia-Chen , Kung Pei-Tseng , Kuo Wei-Yin , Tsai Wen-Chen
Published: July 2021

Background: Several studies have shown that hospice palliative care interventions for cancer patients can reduce medical utilisation. In Taiwan, 20–25% of mechanical ventilation patients have been on prolonged mechanical ventilation (PMV), but only a few studies have discussed the effectiveness of hospice palliative care on these patients. This study aimed to explore the effectiveness of medical utilisation on patients undergoing PMV in hospice palliative care.Methods: From the Health Insurance database of a nationwide population-based study, we identified patients who had been on mechanical ventilation for over 21 days, were 18 years or older between 2009 to 2017, and had undergone hospice palliative care. The control group was obtained by 1:1 matching using propensity scoring after excluding patients who had participated in palliative care for less than 15 or more than 181 days. Furthermore, we used conditional logistic regression analysis to explore intensive care unit readmission, emergency department presentation, and cardiopulmonary resuscitation incidents, 14 days prior to death.Results: A total of 186,533 new PMV patients aged ≥ 18 years with terminal diseases were admitted between 2009 and 2017. Additionally, the number of patients receiving palliative care increased annually, from 0.6% in 2009 to 41.33% in 2017. The number of prolonged mechanical ventilation during emergency visits (odds ratio [OR]=0.68, 95%CI: 0.63-0.74), intensive care unit hospitalisation (OR=0.59, 95%CI: 0.53-0.46), cardiopulmonary resuscitation (OR=0.40, 95%CI: 0.35-0.46), and total hospitalisation cost (USD 1319.9.57 ± 1821.67 vs. 1544.37 ± 2309.27) was lower in the palliative care group.Conclusion: Patients undergoing PMV whilst in hospice palliative care can significantly reduce total hospitalisation cost, intensive care unit admittance, cardiopulmonary resuscitation utilisation, and medical expenses at ≤14 days prior to death.
Network Pharmacology-Based Prediction and Verification of the Mechanism of Shikonin in the Treatment of Colorectal Cancer
Authors: Wang Zefeng , Cui Qianfei , Shi Ling , Lu Xiaojing , Shi Yongjia , Guo Wenjing , Song Peng
Published: July 2021

Background: Zicao is the dried root of Lithospermum erythrorhizon Sieb, et Zucc, Arnebia euchroma (Royle) Johnst, or Arnebia guttata Bunge and is commonly used to treat viral infection, inflammation, arthritis, and cancer in traditional Chinese medicine. Shikonin (SKN), a naturally occurring naphthoquinone, is a major active chemical component isolated from Zicao and exhibits anticancer activity according to previous research. However, the underlying mechanism has not been elucidated, so further research is necessary to verify its traditional application. The purpose of the present study was to investigate the antitumor mechanism of SKN in colorectal cancer (CRC) through network pharmacology and experiments.Methods: The SymMap database and GeneCards were adopted to predict the potential targets of SKN and CRC, while cotargets were obtained via a Venn diagram. The cotargets were imported from the String and DAVID websites, the protein-protein interaction (PPI) network was constructed, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. With regard to the prediction of KEGG by DAVID, the compound-target-pathway network was generated by connecting potential pathways with the corresponding targets. According to the network pharmacological analysis, cytological experiments, real-time PCR (RT-PCR), and Western blot (WB) were used to verify the key signaling pathway.Results: According to the network pharmacological analysis, the most relevant target of SKN to the treatment of colorectal cancer was IL6. GO and KEGG enrichment analyses indicated that various kinases and the PI3K/AKT signaling pathway were the most enriched molecules and pathways. SKN inhibited CRC cell (HT29 and HCT116) proliferation, migration, and invasion and promoted cell apoptosis by targeting IL6 and inhibiting the IL6R/PI3K/AKT signaling pathway.Conclusions: SKN promotes apoptosis and suppresses CRC cell (HT29 and HCT116) activities through the PI3K-Akt signaling pathway. This research not only provides a theoretical and experimental basis for more in-depth studies but also offers an efficient method for the rational utilization of a series of traditional Chinese medicines as anti-CRC drugs.
Allogeneic Hematopoietic Stem Cell Transplantation in Patients Older than 65 Years with Acute Myeloid Leukemia and Myelodysplastic Syndrome: A 15-Year Experience
Authors: Piemontese Simona , Lazzari Lorenzo , Ruggeri Annalisa , Marcatti Magda , Stanghellini Maria Teresa Lupo , Giglio Fabio , Greco Raffaella , Lorentino Francesca , Clerici Daniela , Assanelli Andrea , Farina Francesca , Mastaglio Sara , Xue Elisabetta , Marktel Sarah , Vago Luca , Gentner Bernhard , Secco Chiara , Corti Consuelo , Carrabba Matteo , Bernardi Massimo , Peccatori Jacopo , Ciceri Fabio
Published: July 2021

Background. Median age of occurrence of acute myeloid leukemias (AML) and myelodisplastc syndromes (MDS) is 65 years and older. Nevertheless, the use of allogeneic stem cell transplant (allo-HCT) has been historically limited to younger population, namely due to excess in non-relapse-mortality (NRM) in olders. Methods. In the present study, we analyzed all consecutive patients aged ≥ 65y diagnosed with AML (71, 81%) or MDS (19, 19%) who received transplants from adult donors at our center from January 2005 to December 2019. Results. Median age was 68.29y (65.02-76.54), 26pts (29%) aged ≥ 70y. Thirty-three (37%) pts received a HLA-matched donor. Conditioning regimen was myeloablative in 46pts (51%). The 3-year overall survival (OS) was 53+/-6%, and disease free survival (DFS) 45+/-6% (Figure 1). Day-100 and 3-year NRM was 17+/-2% and 29+/-2%, respectively. The 3-year CI of relapse was 22+/-2%. Day-100 CI of aGvHD was 21+/-2% for grade II-IV, 14+/-1% for grade III-IV. The 3-year CI of cGvHD was 35+/-3%, extensive 20+/-2%. In multivariate analysis, the Karnofsky Performance Status (KPS) < 90% was associated with lower OS (HR: 2.999, CI: 1.477- 6.691; p=0.002), DFS (HR: 3.155, CI: 1.593 - 6.250; p=0.001) and higher NRM (HR: 2.997, CI: 1.344-6.682; p=0.041). HCT-CI ≥ 3 was also associated with higher NRM (HR: 2.949, CI: 1.166-7.462, p=0.022,). Diagnosis of MDS and receiving a matched donor with PTCy were associated with longer OS (HR: 0.3440, CI: 0.1029-0.915; p=0.033; HR: 0.197, CI: 0.042-0.934; p=0.041).Conclusions. Age alone should not limit transplant eligibility for AML and MDS. KPS and HCT-CI proved to be useful for patient selection among the elderly. The use of HLA-matched donors with PTCy improved OS compared to ATG in our consecutive series.
Sixteenth-century tomatoes in Europe: who saw them, what did they look like, and where did they come from?
Authors: Andel Tinde van , Vos Rutger , Michels Ewout , Stefanaki Anastasia
Published: July 2021

BackgroundSoon after the Spanish conquest of the Americas, the first tomatoes were presented as curiosities to the European royals and drew the attention of sixteenth-century Italian naturalists. Despite of their scientific interest in this New World crop, most Renaissance botanists did not specify where these ‘golden apples’ or ‘pomi d’oro’ came from. The debate on the first European tomatoes and their origin is often hindered by erroneous dating, botanical misidentifications and inaccessible historical sources. The discovery of a tomato specimen in the sixteenth-century ‘En Tibi herbarium’ kept at Leiden, the Netherlands led to claims that its DNA would reveal the ‘original’ taste and pest resistance of early tomatoes.MethodsRecent digitization efforts greatly facilitate research on historic botanical sources. Here we provide an overview of the ten remaining sixteenth-century tomato specimens, early descriptions and 13 illustrations. Several were never published before, revealing what these tomatoes looked like, who saw them, and where they came from.ResultsOur survey shows that the earliest tomatoes in Europe came in a much wider variety of colors, shapes and sizes than previously thought, with both simple and fasciated flowers, round and segmented fruits. Pietro Andrea Matthioli gave the first description of a tomato in 1544, and the oldest specimens were collected by Ulisse Aldrovandi and Francesco Petrollini in c. 1551 from plants grown in the Pisa botanical garden by their teacher Luca Ghini. The oldest illustrations were made in Germany in the early 1550s, but the Flemish Rembert Dodoens published the first image in 1553. The names of early tomatoes in contemporary manuscripts suggest both a Mexican and a Peruvian origin. The ‘En Tibi’ specimen was collected by Petrollini around Bologna in 1558 and thus is not the oldest extant tomato. Although only 1.2% of its DNA was readable, recent molecular research shows that the En Tibi tomato was a fully domesticated, but quite heterozygous individual and genetically close to three Mexican and two Peruvian tomato landraces. Molecular research on the other sixteenth-century tomato specimens may reveal other patterns of genetic similarity and geographic origin. Clues on the ‘historic’ taste and pest resistance of the sixteenth-century tomatoes should not be searched in their degraded DNA, but rather in those landraces in Central and South America that are genetically close to them. The indigenous farmers growing these traditional varieties should be supported to conserve these heirloom varieties in-situ.
Microstructural and Tribological Characterization of API X52 Dual-Phase Steel
Authors: Hamza Gamri , Omar Allaoui , Sami Zidelmel
Published: July 2021

The effect of the morphology and the martensite volume fraction on the microhardness, the tensile, the friction and the wear behavior of API X52 dual phase (DP) steel has been investigated. Three different heat treatments were used to develop dual phase steel with different morphologies and with different amounts of martensite: Intermediate Quenching Treatment/Water (IQ); Step Quenching Treatment (SQ) and direct quenching (DQ). Tribological tests are conducted on DP steels using a ball-on-disc configuration under normal load of 5 N and at a sliding speed of 4 cm/s were used to study the friction and wear behavior of treated samples. Results show that the ferrite–martensite morphology has a great influence on the mechanical properties of dual phase steel. The steel subjected to (IQ) treatment attain superior mechanical properties compared to the SQ and the DQ treatments. On the other hand, it is also found that the friction coefficient and the wear rate (volume loss) decrease when the hardness and the martensite volume fraction increase. The steel with fine fibrous martensite provide good wear resistance.
Essential Features for Antioxidant Capacity of Ascorbic Acid (Vitamin C)
Authors: Santos Kelton L. B. , Bragança Vitor A. N. , Pacheco Larysse V. , Ota Sirlene S. B. , Aguiar Christiane P. O. , Borges Rosivaldo S.
Published: July 2021

Vitamin C or ascorbic acid is an indispensable micronutrient for human health found principally on citrus species such as lemon and orange fruits, and vegetables. It was involved in the production of proteins such as collagen. Its biochemical mechanism is related to its antioxidant capacity, however its function at the cellular level is still unclear. Several theoretical studies about antioxidant and redox mechanisms for ascorbic acid were suggested, however no derivative was proposed. Thereby, an electronic study of antioxidant capacity for ascorbic acid derivatives was performed using theoretical chemistry at the DFT/ B3LYP/6-311++(2d,2p) level of theory. Simplified derivatives show that enol hydroxyls are more important than any other functional group. The vicinal enolic hydroxyl on β-position are more important for antioxidant capacity of ascorbic than hydroxyl on α-position. According to our molecular modifications, the keto-alkene compound showed the best values when compared to ascorbic acid in some molecular characteristics. New promising structural derivatives related to ascorbic acid can be developed in the future.
Efficiency Exploration of Frequency Ratio, Entropy, and Weights of Evidence-Information Value Models in Flood Susceptibility Assessment: A Study of Raiganj Subdivision, Eastern India
Authors: Saha Sunil , Sarkar Debabrata , Mondal Prolay
Published: July 2021

The primary objective of this research was to assess the efficiency of RS and GIS for predicting the flood risk using the Frequency ratio, Entropy index, and Weight of evidence-information Value models. Consequently, for spatial analyses fourteen flood conditioning variables are constructed. The research region is experiencing floods consequently in the past with moderate to high intensities. The assessment demonstrates that parameters such as elevation, LULC, rainfall, distance from rivers, and drainage density contributed significantly to the occurrence of floods. The validation of the results indicates that the success rate of the presently constructed models. Around 33 per cent to 47 per cent of the total area of each block in the subdivision is projected to be in danger of floods. The report's findings will aid planners in designing flood prevention measures as part of regional flood risk management programs and will serve as a platform for future research in the study area.
Research on intelligent analysis of running sports training performance based on artificial intelligence
Authors: Yang Cairu , Liu Yanhua , Zhang Xuzhong
Published: July 2021

With the increasing awareness of human beings in the pursuit of human health, running in sports has become a fashionable and healthy first choice. The research uses artificial intelligence technology to conduct intelligent analysis when running training, and aims at the use of artificial intelligence technology. Artificial intelligence technology can accurately analyze and predict the application requirements of sports training postures. We proposed a set of sports posture analysis and predict system to design in this paper. It uses the running training record data in the watch heart rate and GPS smart sports watch, and uses Recurrent Neural Network (RNN), Long and short-term memory (LSTM) and Gate recursive unit (GRU) that three types of neural network models to predict whether the road race can be in the conference. And confirm it will be completed within the scheduled closing time, and it will also perform intelligent analysis of physical fitness (heart rate, pace) and running technology (cadence, pace). The training and test data for this study are the running training records from (Running distance, time, heart rate, stride frequency, stride length, pace, calories, altitude and other characteristic values) as input parameters to test and compare the running completion time trend of RNN, LSTM, GRU neural network models in the exercise table predictive power. The results show predict accuracy is the best is GRU method, and the worst is LSTM method. After the hidden layers are added to the three predict models, RNN is slightly regressive, LSTM has a significant trend of improvement, and GRU is less obvious.
Development and Validation of Proton Track Structure Model Applicable to Arbitrary Materials
Authors: Ogawa Tatsuhiko , Hirata Yuho , Matsuya Yusuke , Kai Takeshi
Published: July 2021

A novel transport algorithm performing proton track-structure calculations in arbitrary materials was developed. Unlike conventional algorithms, which are based on the dielectric function of the target material, our algorithm uses a total stopping power formula and single-differential cross sections of secondary electron production. The former was used to simulate energy dissipation of incident protons and the latter was used to consider secondary electron production. In this algorithm, the incident proton was transmitted freely in matter until the proton produced a secondary electron. The corresponding ionising energy loss was calculated as the sum of the ionisation energy and the kinetic energy of the secondary electron whereas the non-ionising energy loss was obtained by subtracting the ionising energy loss from the total stopping power. The most remarkable attribute of this model is its applicability to arbitrary materials, i.e. the model utilises the total stopping power and the single-differential cross sections for secondary electron production rather than the material-specific dielectric functions. Benchmarking of the stopping range, radial dose distribution, secondary electron energy spectra in liquid water, and lineal energy in tissue-equivalent gas, against the experimental data taken from literature agreed well. This indicated the accuracy of the present model even for materials other than liquid water. Regarding microscopic energy deposition, this model will be a robust tool for analysing the irradiation effects of cells, semiconductors and detectors.