bluuebunny/crossref_metadata_2025 huggingface dataset:
Stochastic resonance of volatility influenced by price periodic information in financial market
Authors: Yang Guo-Hui , Dong Yang , Li Hai-Feng , Li Jiang-Cheng
Published: June 2021

General researches show that all kinds of random risk information and periodic information in the financial system are mainly transmitted to the asset price through influencing the volatility, thus impacting the whole market. So can the periodic information and random factors in the price be transmitted to the volatility in reverse and cause volatility changes? Hence, in this paper, we investigate the stochastic resonance of volatility which is influenced by price periodic information in financial market, based on our proposed periodic Brownian Motion model and absolute return volatility. The parameter estimation of the periodic Brownian Motion model is obtained by minimizing the mean square deviation between the theoretical and empirical return distributions for the CSI300 data set. The good agreements of the probability density functions of the price returns, realized volatility (RV) at 5 minutes, RV at 15 minutes and absolute return volatility between theoretical and empirical calculation are found. After simulating the absolute return volatility and signal power amplification (SPA) of volatility via periodic Brownian Motion model, the results indicated that (i) single and double inverse resonance phenomena can be observed in the function of SPA versus random information intensity or economic growth rate; (ii) multiple inverse resonance phenomena can be also observed for SPA versus frequency of periodic information. The results imply that the transmission of stochastic factors and periodic information is not only from the volatility to the price, but also from the price to the volatility.
Selective Cell-Based Smoothed Finite Element Method Using 10-Node Tetrahedral Element with Radial Element Subdivision
Authors: Onishi Yuki
Published: June 2021

A new optimal formulation of the selective cell-based smoothed finite element method using 10-node tetrahedral elements (SelectiveCS-FEM-T10) is proposed for nearly incompressible large deformation problems. SelectiveCS-FEM-T10 is a generic name for S-FEM formulations that apply the selective reduced integration (SRI) and the cell-based S-FEM (CS-FEM) simultaneously to the 10-node tetrahedral (T10) elements, and thus it has various formulation variations. The conventional SelectiveCS-FEM-T10 naturally subdivides a T10 element into twelve 4-node tetrahedral (T4) subelements with a dummy node at the element center. Meanwhile, the new SelectiveCS-FEM-T10 radially subdivides it into sixteen T4 subelements around the dummy node. Owing to this radial element subdivision, all the edges of the subelements, including the frame edges, are subjected to strain smoothing only via the edge-based S-FEM (ES-FEM) within an element. Besides, SelectiveCS-FEM-T10 can be implemented into general finite element codes as a T10 element because it is a CS-FEM, which only applies intra-element strain smoothing. Our demonstrative analyses reveal that the new SelectiveCS-FEM-T10 is more robust than the best available T10 element against severe large deformation. They also show that the accuracy of the new SelectiveCS-FEM-T10 is almost equal to the conventional T10 elements as it does not cause shear/volumetric locking and pressure checkerboarding.
A Mathematical Analysis Method for Bending Problem of Clamped Shallow Spherical Shell on Elastic Foundation
Authors: Li Shanqing , Yang Chunsheng , Xia Fengfei , Yuan Hong
Published: June 2021

A mathematical analysis method is employed to solve the bending problem of slip clamped shallow spherical shell on elastic foundation. Using the slip clamped boundary conditions, the differential equations of the problem are simplified to a biharmonic equation. Using the [Formula: see text]-function, the fundamental solution and the boundary equation of the biharmonic equation, a function is established. This function satisfies the homogeneous boundary condition of the biharmonic equation. The biharmonic equation of the slip clamped shallow spherical shell bending problem on elastic foundation is transformed to Fredholm integral equation of the second kind by using Green’s formula. The vector expression of the integral equation kernel is derived. Choosing a suitable form of the normalized boundary equation, the singularity of the integral equation kernel is overcome. To obtain the numerical results, the discretization of the integral equation of the bending problem is conducted. The treatment of singular term in the discretization equation is to use the integration by parts. Numerical results of rectangular, trapezoidal, pentagonal, L-shaped and concave shape shallow spherical shells show high accuracy of the proposed method. The numerical results show fine agreement with the ANSYS finite element method (FEM) solution, which shows the proposed method is an effective mathematical analysis method.
Regularized Semi-Supervised Metric Learning with Latent Structure Preserved
Authors: Wang Qianying , Lu Ming , Li Meng , Guan Fei
Published: June 2021

Metric learning is a critical problem in classification. Most classifiers are based on a metric, the simplest one is the KNN classifier, whose outcome is directly decided by the given metric. This paper will discuss semi-supervised metric learning. Most traditional semi-supervised metric learning algorithms preserve the local structure of all the samples (including labeled and unlabeled) in the input space, when making the same labeled samples together and separating different labeled samples. In most existing methods, the local structure is calculated by the Euclidean distance which uses all the features. As we all know, high dimensional data lies on a low dimension manifold, and not all the features are discriminative. Thus, in this paper, we try to explore the latent structure of the samples and use the more discriminative features to calculate the local structure. The latent structure is learned by clustering random forest and cast into similarity between samples. Based on the hierarchical structure of the trees and the split function, the similarity is obtained from discriminant features. Experimental results on public data sets show our algorithm outperforms the traditional similar related algorithms.
A Multi-Swarm ABC Algorithm for Parameters Optimization of SOFM Neural Network in Dynamic Environment
Authors: Jia Dongli , Li Fan , Tu Jun
Published: June 2021

Self-organizing feature map (SOFM) neural network is a kind of competitive unsupervised learning neural network, which has strong self-organizing and self-learning capabilities. It has been widely used in the fields of data classification and data clustering. A crucial step for SOFM neural network is to set its weight parameters correctly because the output accuracy and efficiency of the network depend much on these parameters. Most of current methods for parameter setting are based on static data. However, in a dynamic environment, the statistical characteristics of the generated data will change unpredictably over time. If the SOFM network cannot react to the changes of the environment, its performance will degrade. To deal with this problem, a more powerful multi-swarm artificial bee colony algorithm (MABC) is proposed. In the algorithm, the classic ABC algorithm is improved with multi-swarm and exclusive operation strategies to make it suitable for tracking optimal parameter settings of the SOFM network, so that the SOFM network can be applied to a dynamic environment. Two real data streams, which are regarded as coming from dynamic environments, are used to evaluate the effectiveness of the algorithm. Results show that the proposed algorithm is superior to the classic SOFM algorithm in terms of clustering purity and effectiveness. It is a promising method for the classification of data streams from dynamic environments.
The Use of Principal Component Analysis for the Prediction of Double Halide Perovskites A2BX6
Authors: Boubchir Mohamed , Boubchir Rachid , Aourag Hafid
Published: June 2021

In this paper, we report a comprehensive and systematic study for predicting the formability of double halide perovskites. Besides the tolerance factor, several complementary criteria for the formation and lattice distortion have been developed and compared with a throughout multivariate technique based on the principal component analysis (PCA) and the partial least square (PLS) methods. Some empirical equations expressing the relationships between the different ionic radii and the electronegativities and the lattice constants of double halide perovskites have been found.
Platinum-group element geochemistry of the Panjal Traps: constraints on mantle melting and implications for mineral exploration
Authors: Shellnutt J. Gregory , Pang Kwan-Nang , Qi Liang , Bhat Ghulam M.
Published: June 2021

Forty-two volcanic rocks of the Panjal Traps were analysed for platinum-group elements (PGEs) to investigate the magma genesis, high-temperature behaviour and exploration potential of these elements. The PGE data exhibit substantial variability and show no systematic relation to their low- or high-Ti affinity. Instead, the basalts can be subdivided into a PGE-undepleted group (group 1) that has ΣPGE >10 ppb and Cu/Pd <30 000, and a PGE-depleted group, which consists of a subgroup showing limited (group 2A) or substantial depletion in Ir-series PGEs relative to Ni (group 2B). The group 1 samples indicate an S-undersaturated history, whereas the group 2 samples might have different origins in terms of S-saturation. Fractionation of a tiny amount of sulfide melts (0.075–0.1%) from a representative group 1 sample accounts for the chalcophile element patterns observed in the group 2B samples. The relatively high Cu/Pd, unfractionated Ni/Ir and low PGE abundances observed in the group 2A samples cannot be explained by equilibration of an immiscible sulfide melt alone, and probably require decomposition of residual sulfides into sulfide melt and a monosulfide solid solution in the mantle restite. Our results question the notion that the coexistence of PGE-undepleted and -depleted magmas is prospective in the exploration of magmatic Ni–Cu–(PGE) sulfide mineralization.
ExSol
Authors: Lamp Josephine , Rubio-Medrano Carlos E. , Zhao Ziming , Ahn Gail-Joon
Published: June 2021

No longer just prophesied about, cyber-attacks to Energy Delivery Systems (EDS) (e.g., the power grid, gas and oil industries) are now very real dangers that result in non-trivial economical losses and inconveniences to modern societies. In such a context, risk analysis has been proposed as a valuable way to identify, analyze, and mitigate potential vulnerabilities, threats, and attack vectors. However, performing risk analysis for EDS is difficult due to their innate structural diversity and interdependencies, along with an always-increasing threatscape. Therefore, there is a need for a methodology to evaluate the current system state, identify vulnerabilities, and qualify risk at multiple granularities in a collaborative manner among different actors in the context of EDS. With this in mind, this article presents
ExSol
, a collaborative, real-time, risk assessment ecosystem that features an approach for modeling real-life EDS infrastructures, an ontology traversal technique that retrieves well-defined security requirements from well-reputed documents on cyber-protection for EDS infrastructures, as well as a methodology for calculating risk for a single asset and for an entire system. Moreover, we also provide experimental evidence involving a series of attack scenarios in both simulated and real-world EDS environments, which ultimately encourage the adoption of
ExSol
in practice.
Genetics of Sleep and Insights into Its Relationship with Obesity
Authors: Dashti Hassan S. , Ordovás José M.
Published: June 2021

Considerable recent advancements in elucidating the genetic architecture of sleep traits and sleep disorders may provide insight into the relationship between sleep and obesity. Despite the involvement of the circadian clock in sleep and metabolism, few shared genes, including FTO, were implicated in genome-wide association studies (GWASs) of sleep and obesity. Polygenic scores composed of signals from GWASs of sleep traits show largely null associations with obesity, suggesting lead variants are unique to sleep. Modest genome-wide genetic correlations are observed between many sleep traits and obesity and are largest for snoring. Notably, U-shaped positive genetic correlations with body mass index (BMI) exist for both short and long sleep durations. Findings from Mendelian randomization suggest robust causal effects of insomnia on higher BMI and, conversely, of higher BMI on snoring and daytime sleepiness. In addition, bidirectional effects between sleep duration and daytime napping with obesity may also exist. Limited gene-sleep interaction studies suggest that achieving favorable sleep, as part of a healthy lifestyle, may attenuate genetic predisposition to obesity,but whether these improvements produce clinically meaningful reductions in obesity risk remains unclear. Investigations of the genetic link between sleep and obesity for sleep disorders other than insomnia and in populations of non-European ancestry are currently limited.
Role of the Superior Colliculus in Guiding Movements Not Made by the Eyes
Authors: Cooper Bonnie , McPeek Robert M.
Published: June 2021

The superior colliculus (SC) has long been associated with the neural control of eye movements. Over seventy years ago, the orderly topography of saccade vectors and corresponding visual field locations were discovered in the cat SC. Since then, numerous high-impact studies have investigated and manipulated the relationship between visuotopic space and saccade vector across this topography to better understand the physiological underpinnings of the sensorimotor signal transformation. However, less attention has been paid to the other motor responses that may be associated with SC activity, ranging in complexity from concerted movements of skeletomotor muscle groups, such as arm-reaching movements, to behaviors that involve whole-body movement sequences, such as fight-or-flight responses in murine models. This review surveys these more complex movements associated with SC (optic tectum in nonmammalian species) activity and, where possible, provides phylogenetic and ethological perspective.
Satellite Navigation and Communication Integration Based on Correlation Domain Indefinite Pulse Position Modulation Signal
Authors: Zou Deyue , Ma Shouchuan
Published: June 2021

Ubiquitous signal coverage is a basic demand of Internet of Things (IoT) communications, which meets the feature of satellite communications. Infinite user number is a basic demand of IoT location‐based services, which meets the feature of Global Navigation Satellite System (GNSS). Both of these demands make Satellite Navigation and Communication Integration (SNCI) an important supporting technology for IoT. Inherited from the satellite communications system, GNSS itself has a certain data transmission capacity. Thus, enhancing the communication function of the GNSS is a promising means of achieving SNCI. Considering that a unified signal system cannot currently realize high‐precision positioning and high‐speed data transmission simultaneously in SNCI, this project proposes a Correlation Domain Indefinite Pulse Position Modulation (CDIPPM). A pilot channel and a data channel are introduced in this technology, which are distinguished by Code Division Multiplexing (CDMA). The synchronization function is provided by the pilot channel, thereby freeing the data channel of this function. The phase of the pseudorandom code can then be used as the carrier of information. In order to transmit more information, the transmitter of the proposed technology superimposes on the data channel multiple sets of spread spectrum sequence, which are generated from one set of spread spectrum sequence by different cyclic shifting operations. The receiver will identify the number and location of the correlation function peaks by a detection algorithm and recover the message. It can be seen by theoretical analysis and simulation verification. The technology can significantly improve satellite data transmission rates and maintain the original positioning function while minimizing change in the original GNSS signal. Therefore, the SNCI system based on this technology has the following advantages: a unified signal system, high positioning accuracy, high data transmission rate, and a backward navigation function, and it is easy to promote.
Multiobjective Evaluation of Coevolution among Innovation Populations Based on Lotka–Volterra Equilibrium
Authors: Wang Sheng-Yuan , Chen Wan-Ming , Wang Rong , Wu Xiao-Lan
Published: June 2021

The collaborative evaluation of enterprise innovation populations is a hot issue. The Lotka–Volterra model is a mature method used to evaluate the interaction mechanism of populations and is widely used in innovation ecology research studies. The Lotka–Volterra model mainly focuses on the quantitative characteristics of the interactive populations. The growth mechanisms cannot explain all the synergy mechanisms of the innovative populations. The collaborative evaluation between enterprise innovation populations is a typical multiobjective evaluation problem. The multichoice goal programming model is a mature method to solve multiobjective optimization problems. This paper combines the Lotka–Volterra model and multichoice goal programming method to construct a three-stage multiobjective collaboration evaluation method based on Lotka–Volterra equilibrium. An evaluation example is used to illustrate the application process of this method. The method proposed in this paper has excellent performance in computing, parameter sensitivity analysis, and model stability analysis.
Variability of Bimodal Soil-Water Characteristic Curves under Different Confining Pressures
Authors: Syarifudin Achmad , Satyanaga Alfrendo
Published: June 2021

Soils with two subcurves of Soil-Water Characteristic Curve (SWCC) (dual porosity soils) might be found within various residual soils. Soils located in different depths have different confining pressure. Residual soils are found in the unsaturated zones due to the deep groundwater table. There is a linear correlation between the hydraulic properties of the soil in the unsaturated area and that of its unsaturated properties. This study aims to examine the influence of the confining pressure towards the SWCC of dual porosity soil. The scope of this study involves measurements of the drying and wetting SWCC using Tempe cells, pressure plates, and an advanced triaxial apparatus. In this study, the mathematical equations were developed to explain the effect of confining pressure on SWCC. The experimental results indicated that the dual porosity soil exhibits bimodal characteristics for the drying curve of SWCC and it exhibits unimodal characteristics for the wetting curve of SWCC. As the confining pressure increases, the air entry values, the inflection points, and the standard deviation of drying SWCC increase. In addition, the hysteresis of SWCC is becoming smaller with the increasing confining pressure.
LBPSGORA: Create Load Balancing with Particle Swarm Genetic Optimization Algorithm to Improve Resource Allocation and Energy Consumption in Clouds Networks
Authors: Mirmohseni Seyedeh Maedeh , Javadpour Amir , Tang Chunming
Published: June 2021

Due to the purpose of this study that reducing power consumption in the cloud network is based on load balancing, the fitness function measures the load balance between cloud network and servers (the hosts). This technique is appropriate for handling the resource optimization challenges, due to the ability to convert the load balancing problem into an optimization problem (reducing imbalance cost). In this research, combining the results of the particle swarm genetic optimization (PSGO) algorithm and using a combination of advantages of these two algorithms lead to the improvement of the results and introducing a suitable solution for load balancing operation, because in the proposed approach (LBPSGORA), instead of randomly assigning the initial population in the genetic algorithm, the best result is procured by putting the initial population. The LBPSGORA method is compared with PSO, GA, and hybrid GA-PSO. The execution cost, load balancing, and makespan have been evaluated and our method has performed better than similar methods.
Wellbore Fracture Mode and Fracture Pressure Drilled in Depleted Reservoir
Authors: Zhao Kai , Yuan Junliang , Liu Ming , Yan Chuanliang , Dou Liangbin , Bi Gang , Li Runsen , Gao Wei
Published: June 2021

Drilling fluid loss in depleted reservoir has been an import issue faced by further tapping the potential of old oil fields. Accurate evaluation of the fracture pressure is the foundation to avoid mud loss. Traditional views suggest that tensile failure is the only fracture mode and the fracture pressure should be determined by a tensile failure criterion, which are not suitable for wells drilled in the depleted reservoir. In this paper, the analysis focuses on the fracture mode and fracture pressure in depleted reservoir, and case studies show that three fracture modes may first occur, and the fracture mode will be changed with reservoir depletion which highly depends on reservoir depletion degree, well azimuth and deviation angle, and the in situ stress state; different failure criteria at different stages of reservoir depletion should be selected to accurately evaluate the fracture pressure. For the vertical well, fracture pressure is no longer a single linear reduction with reservoir depletion; instead, a three-step and two-step reduction may appear, and for the directional well, the fracture pressure is not always decreased; the other patterns such as increase and first increase then decrease may also appear for the wells drilled in reverse and strike fault stress regimes.
[Retracted] Privacy‐Oriented Successive Approximation Image Position Follower Processing
Authors: Miao Ying , Shao Danyang , Yan Zhimin
Published: June 2021

In this paper, we analyze the location‐following processing of the image by successive approximation with the need for directed privacy. To solve the detection problem of moving the human body in the dynamic background, the motion target detection module integrates the two ideas of feature information detection and human body model segmentation detection and combines the deep learning framework to complete the detection of the human body by detecting the feature points of key parts of the human body. The detection of human key points depends on the human pose estimation algorithm, so the research in this paper is based on the bottom‐up model in the multiperson pose estimation method; firstly, all the human key points in the image are detected by feature extraction through the convolutional neural network, and then the accurate labelling of human key points is achieved by using the heat map and offset fusion optimization method in the feature point confidence map prediction, and finally, the human body detection results are obtained. In the study of the correlation algorithm, this paper combines the HOG feature extraction of the KCF algorithm and the scale filter of the DSST algorithm to form a fusion correlation filter based on the principle study of the MOSSE correlation filter. The algorithm solves the problems of lack of scale estimation of KCF algorithm and low real‐time rate of DSST algorithm and improves the tracking accuracy while ensuring the real‐time performance of the algorithm.
Construction of a Teaching System Based on Big Data and Artificial Intelligence to Promote the Physical Health of Primary School Students
Authors: Ma Zhonglin , Xin Changcheng , Zheng Huifang
Published: June 2021

In recent years, although the overall physical health of Chinese students has shown an upward trend, the substantial decline in student physical fitness has been basically curbed. Most of the physical health indicators of students are steadily improving, but there are still many problems that need to be vigilant. In order to solve the problem of the decline of the physical health of primary school students, it is very important to construct a teaching system based on big data and artificial intelligence to promote the physical health of primary school students. This article aims to study from the actual situation and find scientific and reasonable methods to improve the physical health of primary school students. This article uses the literature method, questionnaire survey method, mathematical statistics method, and other research methods to analyze and study the current physical condition of the interviewed students and the actual influencing factors by taking students from 5 domestic primary schools as the research object. It is concluded that more than 90% of primary school students in Haidian District, Beijing, have good physique and physical development. The development level of strength and flexibility is gradually improved, but the speed and endurance quality are on the decline, especially the endurance quality of primary school boys has declined the most. Lack of good exercise habits, insufficient exercise time and exercise efficiency, and lack of appropriate exercise volume and necessary exercise intensity are currently the most important factors affecting the physical health of primary school students. The physical problems of primary school students are not caused by a single factor, but the result of multiple factors. This article puts forward a number of suggestions for the above situation and problems to be solved urgently.
Research on the Dynamic Evolution of Scientific and Technological Innovation Efficiency in Universities and Identification of Influencing factors—based on Markov Chain Estimation and GMM Model
Authors: Luo Quanzhi
Published: June 2021

A scientific and comprehensive measurement of the efficiency of scientific and technological innovation activities is the basis and prerequisite for evaluating the existing environment and conditions of universities and is conducive for improving the efficiency and promoting the development of provincial economy. The paper selects the DEA (Data Envelopment Analysis) method to measure the efficiency of scientific and technological innovation in universities of China from 2007 to 2019 and studies its spatial differences. Then, the paper uses Markov chain estimation to describe the dynamic evolution process of the efficiency, and finally uses system GMM (generalized method of moments) model to identify the key influencing factors of its efficiency. The conclusions obtained are as follows: (1) The scientific and technological innovation efficiency in universities presents the highest distribution characteristics in the eastern part, the western part of China has the lowest, and the central part is midway of the two regions. There are significant differences between regions. (2) During the entire observation period, the efficiency in each region showed a path-dependent characteristic. After 2016, the mobility of different levels of technological innovation efficiency of universities in eastern part of China has increased, while in the central and western parts of China it tends to be stable. (3) Economic advantages, location advantages, government support, research and development foundation, and the efficiency of scientific and technological innovation in universities have a significant relationship, and the results are different in different regions.
Innovative Design of Intangible Cultural Heritage Elements in Fashion Design Based on Interactive Evolutionary Computation
Authors: Xu Qi , Liu Hubin , Liu Yulong , Wu Shan
Published: June 2021

The application of intangible cultural heritage cultural elements and traditional crafts in modern design, especially in modern fashion design, is not to flatter the public but to integrate the artistic language of intangible cultural heritage into modern fashion on the basis of deeply understanding the connotation of intangible cultural heritage and mastering its traditional crafts, so as to meet people’s demand for fashion and aesthetics. It can also promote the inheritance and development of traditional intangible cultural heritage culture and technology. The purpose of this study is to analyze the intangible cultural heritage elements in the innovative design of fashion design by using interactive evolutionary computation. According to the composition characteristics of cultural elements, this research uses interactive evolutionary calculation to analyze the current status of intangible cultural heritage elements in clothing design. Then, 30 fashion designers are selected to evaluate the design situation and judge the effect of the method on the design. The results show that the neural network has evaluated 36 generations, that is, 256 times of moderate value. Compared with the general IGA algorithm, adding neural network IGA can reduce the fatigue caused by user reference score and improve the quality of the optimal solution, and the cultural image attributes whose perception frequency is more than 50% are favored. It is concluded that the research method in the intangible cultural heritage elements in fashion design can improve user satisfaction and the effect is good. This research contributes to the application of intelligent algorithm in the field of fashion design.
Development and Validation of a UPLC‐MS/MS Method for the Quantitative Determination and Pharmacokinetic Analysis of Cirsimarin in Rat Plasma
Authors: Zhang En , Wang Ying , Xie Fuyi , Zhuang Xinlei , Wang Xianqin , Yu Xiaomin
Published: June 2021

Cirsimarin is a bioactive antilipogenic flavonoid isolated from the cotyledons of Abrus precatorius and represents one of the most abundant flavonoids present in this plant species. Cirsimarin exhibits excellent antioxidant, lipolysis, and other biological properties; it can effectively trigger lipid movement and demonstrates antiobesity effects. In this work, an ultra‐high‐performance liquid chromatography tandem mass spectrometry (UPLC‐MS/MS) method was developed for the determination of cirsimarin in rat plasma after intravenous administration. A standard curve of cirsimarin in blank rat plasma was generated over the concentration range of 1–3000 ng/mL. Six rats were administered cirsimarin intravenously (1 mg/kg). The method only required 50 μL of plasma for sample preparation, and the plasma proteins were precipitated with acetonitrile to pretreat the plasma sample. The precisions of cirsimarin in rat plasma were less than 14%, while the accuracies varied between 92.5% and 107.3%. In addition, the matrix effect varied between 103.6% and 107.4%, while the recoveries were greater than 84.2%. This UPLC‐MS/MS method was then applied in measuring the pharmacokinetics of cirsimarin in rats. The AUC(0-t) values of cirsimarin from the pharmacokinetic analysis were 1068.2 ± 359.2 ng/mL·h for intravenous administration. The half‐life (t1/2) was 1.1 ± 0.4 h (intravenous), indicating that the metabolism of the compound was quick in the rats. Exploring the pharmacokinetics of cirsimarin in vivo can help better understand its metabolism.
Calculation of the Roadside Clear Zone Width along Highways Based on the Safe Slope
Authors: Cheng Rui , Cheng Guozhu , Pei Yulong , Xu Liang
Published: June 2021

International crash data indicate that roadside characteristics contribute to more than half of all roadside accidents involving serious injury or death. Therefore, research on roadside safety is urgently needed. Based on the vehicle departure speed, pavement height (i.e., the difference between pavement elevation and ground elevation), slope gradient, and horizontal curve radius, this study uses PC-Crash simulation software to carry out tests of trucks and cars exiting a road. A chi-squared automatic interaction detection (CHAID) decision tree is used to explore the causative mechanism of vehicle rollover, and the concept of a “safe slope” to ensure that vehicles do not roll over is proposed. Aiming at straight and curved sections, discriminant functions of vehicle rollover and nonrollover are fitted through Bayesian discriminant analysis, and safe slope calculation models for trucks and cars are then constructed. Based on the obtained safe slope models, calculation methods for the safe slope and the roadside clear zone width involving different traffic compositions are proposed by calibrating the lateral distance from the final position of nonrollover vehicles to the road edge. The results show that the factors affecting vehicle rollover are, in descending order of importance, the slope gradient, pavement height, vehicle type, departure speed, and horizontal curve radius. For a section with a large proportion of cars, the slope gradient should not be steeper than 1:3.5. The horizontal curve radius should not be less than 600 m for a section with a large proportion of trucks and a slope gradient steeper than 1:3.5 or shallower than 1:2.5. Additionally, for a section with a pavement higher than 0.5 m and a slope gradient steeper than 1:2.5, the operating speed limit should be lower than 60 km/h. These research results have theoretical value and practical significance to improve the driving safety level and reducing the risk of roadside accidents.
Juegos de mesa
Authors: Mandiola Marcela
Published: June 2021

En su informe Women in Science del 2019, la UNESCO insiste en la importante brecha de género en la ciencia, indicando que la participación de las mujeres en investigación y desarrollo a nivel mundial alcanza solo el 29,3%. En nuestra América Latina, Chile alcanza el lugar 16 de entre 20 países medidos, con una participación para las mujeres del 33,1% respecto del total de personas empleadas en ámbitos de I+D. Continuar leyendo...
Adult Pulmonary Intensive and Intermediate Care Units: The Italian Thoracic Society (ITS-AIPO) Position Paper
Authors: Renda Teresa , Scala Raffaele , Corrado Antonio , Ambrosino Nicolino , Vaghi Adriano ,   on behalf of the Scientific Group on Respiratory Intensive Care of the Italian Thoracic Society (ITS-AIPO)
Published: June 2021

The imbalance between the prevalence of patients with acute respiratory failure (ARF) and acute-on-chronic respiratory failure and the number of intensive care unit (ICU) beds requires new solutions. The increasing use of non-invasive respiratory tools to support patients at earlier stages of ARF and the increased expertise of non-ICU clinicians in other types of supportive care have led to the development of adult pulmonary intensive care units (PICUs) and pulmonary intermediate care units (PIMCUs). As in other European countries, Italian PICUs and PIMCUs provide an intermediate level of care as the setting designed for managing ARF patients without severe non-pulmonary dysfunction. The PICUs and PIMCUs may also act as step-down units for weaning patients from prolonged mechanical ventilation and for discharging patients still requiring ventilatory support at home. These units may play an important role in the on-going coronavirus disease 2019 pandemic. This position paper promoted by the Italian Thoracic Society (ITS-AIPO) describes the models, facilities, staff, equipment, and operating methods of PICUs and PIMCUs.
Durable Molecular Remission in an Elderly Patient Affected by Relapsed Ph'+ Acute Lymphoblastic Leukemia with T315I and Concomitant p190 and p210 Expression Achieved by Inotuzumab and Ponatinib
Authors: Molica Matteo , Mazzone Carla , Cordone Iole , Divona Mariadomenica , Niscola Pasquale , de Fabritiis Paolo
Published: June 2021

An unmet clinical need currently exists for elderly patients with relapsed/resistant (R/R) Philadelphia (Ph) positive acute lymphoblastic leukemia (ALL), nearly all who have a very poor prognosis. This includes patients already exposed to the first or second generation tyrosine kinase inhibitors (TKIs) and therefore has few treatment options available. New immunotherapies and targeted agents have shown encouraging activity in R/R ALL irrespective of age. Inotuzumab (InO), a humanized anti-CD22 monoclonal antibody, has potentially beneficial clinical effects in patients with resistant and difficult-to-treat disease in whom prior TKIs have failed. However, InO, as a single agent, did not show durable response and longer progression free survival and overall survival in R/R Ph positive ALL patients compared with those treated with standard chemotherapy. We observed a durable molecular remission (7 months) in an elderly patient affected by Ph'+ ALL with T315I and concomitant p190 and p210 expression achieved by concomitant therapy of InO (for 4 cycles) and ponatinib (15 mg/daily) followed by ponatinib (15 mg/daily) only as maintenance therapy. These findings suggest that elderly R/R Ph positive patients who cannot proceed to the transplant might benefit by concomitant immunotherapy and TKIs aimed to deepen the responses and prolong CR and outcomes.
HINT1 (Histidine Triad Nucleotide-Binding Protein 1) Attenuates Cardiac Hypertrophy Via Suppressing HOXA5 (Homeobox A5) Expression
Authors: Zhang Yan , Da Qiang , Cao Siyi , Yan Ke , Shi Zhiguang , Miao Qing , Li Chen , Hu Lulu , Sun Shixiu , Wu Wei , Wu Lingxiang , Chen Feng , Wang Liansheng , Gao Yuanqing , Huang Zhengrong , Shao Yongfeng , Chen Hongshan , Wei Yongyue , Chen Feng , Han Yi , Xie Liping , Ji Yong
Published: June 2021

Background:

Cardiac hypertrophy is an important prepathology of, and will ultimately lead to, heart failure. However, the mechanisms underlying pathological cardiac hypertrophy remain largely unknown. This study aims to elucidate the effects and mechanisms of HINT1 (histidine triad nucleotide–binding protein 1) in cardiac hypertrophy and heart failure.

Methods:

HINT1 was downregulated in human hypertrophic heart samples compared with nonhypertrophic samples by mass spectrometry analysis.
Hint1
knockout mice were challenged with transverse aortic constriction surgery. Cardiac-specific overexpression of HINT1 mice by intravenous injection of adeno-associated virus 9 (AAV9)–encoding
Hint1
under the cTnT (cardiac troponin T) promoter were subjected to transverse aortic construction. Unbiased transcriptional analyses were used to identify the downstream targets of HINT1. AAV9 bearing shRNA against
Hoxa5
(homeobox A5) was administrated to investigate whether the effects of HINT1 on cardiac hypertrophy were HOXA5-dependent. RNA sequencing analysis was performed to recapitulate possible changes in transcriptome profile.Coimmunoprecipitation assays and cellular fractionation analyses were conducted to examine the mechanism by which HINT1 regulates the expression of HOXA5.

Results:

The reduction of HINT1 expression was observed in the hearts of hypertrophic patients and pressure overloaded–induced hypertrophic mice, respectively. In
Hint1
-deficient mice, cardiac hypertrophy deteriorated after transverse aortic construction. Conversely, cardiac-specific overexpression of HINT1 alleviated cardiac hypertrophy and dysfunction. Unbiased profiler polymerase chain reaction array showed HOXA5 is 1 target for HINT1, and the cardioprotective role of HINT1 was abolished by HOXA5 knockdown in vivo. Hoxa5 was identified to affect hypertrophy through the TGF-β (transforming growth factor β) signal pathway. Mechanically, HINT1 inhibited PKCβ1 (protein kinase C β type 1) membrane translocation and phosphorylation via direct interaction, attenuating the MEK/ERK/YY1 (mitogen-activated protein kinase/extracellular signal-regulated kinase kinase/yin yang 1) signal pathway, downregulating HOXA5 expression, and eventually attenuating cardiac hypertrophy.

Conclusions:

HINT1 protects against cardiac hypertrophy through suppressing HOXA5 expression. These findings indicate that HINT1 may be a potential target for therapeutic interventions in cardiac hypertrophy and heart failure.
Racial Disparities in Cardiovascular Complications With Pregnancy-Induced Hypertension in the United States
Authors: Minhas Anum S. , Ogunwole S. Michelle , Vaught Arthur Jason , Wu Pensee , Mamas Mamas A. , Gulati Martha , Zhao Di , Hays Allison G. , Michos Erin D.
Published: June 2021

Women with pregnancy-induced hypertension, defined as gestational hypertension and preeclampsia/eclampsia, are at increased risk of long-term cardiovascular disease, but less is known about the spectrum of acute cardiovascular outcomes, especially across racial/ethnic groups. We evaluated the risk of cardiovascular events at delivery associated with gestational hypertension and preeclampsia/eclampsia, compared with no pregnancy-induced hypertension, overall and by race/ethnicity. We used the 2016 to 2018 National Inpatient Sample data.
International Classification of Diseases
,
Tenth Revision
, Clinical Modification codes identified delivery hospitalizations and clinical diagnoses. Using survey weights, cardiovascular events were examined using logistic regression by pregnancy-induced hypertension status, with subsequent stratification by race/ethnicity. Among 11 304 996 deliveries in 2016 to 2018, gestational hypertension occurred in 614 995 (5.4%) and preeclampsia in 593 516 (5.2%). Black women had higher odds for preeclampsia independent of underlying comorbidities (adjusted odds ratio, 1.45 [95% CI, 1.42–1.49]) and had the highest rates for several complications (peripartum cardiomyopathy, 506; heart failure, 660; acute renal failure, 953; and arrhythmias, 418 per 100 000 deliveries). After adjustment for socioeconomic factors and comorbidities, preeclampsia/eclampsia was associated with increased risk of cardiovascular events in women of all races/ethnicities. However, risk was highest among Asian/Pacific Islander women and lowest among Black women. In sum, while Black women were the most likely to experience preeclampsia, Asian/Pacific women were the most at risk for acute cardiovascular complications during delivery hospitalization.
West Bank Areas A, B and C – How Did They Come into Being?
Authors: Singer Joel
Published: June 2021

This article tells the story of how and why, when negotiating the Israeli-Palestinian Oslo Accords in 1993–95, the author developed the concept of dividing the West Bank into three areas with differing formulas for allocating responsibilities between Israel and the Palestinian Authority in each. The origin of how these areas were named is also discussed. This negotiation demonstrates that parties are prepared to modify ideological positions when detailed and practical options are presented that constitute a hybrid to the parties’ former positions.
Investigating Cattle Procurement at Great Zimbabwe Using 87Sr/86Sr
Authors: House Michelle , Sealy Judith , Chirikure Shadreck , le Roux Petrus
Published: June 2021

At the ancient Shona centre of Great Zimbabwe (1200–1700 CE), cattle (Bos taurus) were centrally important for economic, social, and symbolic purposes. 87Sr/86Sr for modern plants collected in southern Zimbabwe vary from 0.7054 to 0.8780 and ranges differ between some geological substrates. 87Sr/86Sr in serial samples of Bos taurus tooth enamel provides information on where animals consumed at Great Zimbabwe were raised and how herds were managed. The majority of animals sampled were born and remained for their first year of life in a region some 40–120 km south of Great Zimbabwe. Few animals came from geological substrates like that of Great Zimbabwe itself, and none from areas underlain by basalts (> 120 km south of Great Zimbabwe). Earlier hypotheses of transhumance are not supported. These findings will help to build a fuller picture of the role of local commodities (in this case, cattle) in the economic networks that supported the rise and florescence of Great Zimbabwe as a major centre of power.
Raman Spectra of SF6Decomposed Characteristic Products Based on Density Functional Theory
Authors: Zhang Zhen-Yu , Zhang Xue-Dong , Fu Wen-Hua , Yan Han-Bing , Liu Feng-Chun , Zhou Qu
Published: June 2021

SF6decomposition product analysis is one of the most convenient and efficient methods to diagnose the potential faults of SF6insulated electric equipment in the early stage. Based on SF6decomposition characteristic gas analysis, the operation state of SF6insulated power equipment can be judged by on-line monitoring, so as to ensure its normal operation. Raman spectrum analysis technology can realize the nondestructive detection of gas samples with a single wavelength laser. It has excellent applicability and high efficiency for the detection of SF6decomposition characteristic components. In this paper, molecular configurations of CF4, CO, H2S, SO2were obtained by B3LYP functional that based on density functional theory (DFT), and the Raman frequency and intensity characteristics were calculated by 6-31G (2df, p) basis group. The results were compared with National Institute of Standards and Technology (NIST) standard frequencies and it was found that the optimized configuration has no virtual frequency. The characteristic peaks of CO, CF4, SO2and H2S that were identified by Raman spectrum are respectively 2221.11, 908.97, 1175.24 and 2688.82 cm-1, which are basically consistent with the corresponding NIST standard values. This study not only shows that the Raman spectrum of SF6decomposition products calculated by B3LYP functional function is reliable, but provides a reference for the quantitative detection of SF6decomposition products based on Raman spectrum.
A Quasi 2-D Electrostatic Potential and Threshold Voltage Model for Junctionless Triple Material Cylindrical Surrounding Gate Si Nanowire Transistor
Authors: Manikandan S. , Dhanaselvam P. Suveetha , Pandian M. Karthigai
Published: June 2021

A mathematical model used for determining the threshold voltage characteristics and electrostatic potential of a Junctionless Triple Material Cylindrical Surrounding Gate Silicon Nanowire Transistor (JLTMCSGSiNWT) is proposed in this research work and is obtained by resolving the poison
equation. Three materials with dissimilar metal functions are used in the construction of the device gate structure. Device parameters used to determine the electrical characteristics are also included in the model. Behavior of the device is investigated through its vertical electrical field
distribution along the device channel. Higher drain bias conditions leading to DIBL are reduced in the proposed structure by minimal variation of voltages owing to three different gate materials that maintain a steady field distribution along the channel. This model explicitly shows the impact
of various criteria like drain bias voltage, gate bias voltage, thickness of the silicon layer, thickness of the oxide layer, and length of the channel on electrostatic potential and the deterioration of threshold voltage. The proposed analytical model is validated with TCAD simulations and
it could be further extended to study the advanced electrical characteristics of the JL Triple Material CSG Silicon Nanowire Transistor.
Study the Effect of the Volumetric Ratio of Alq3 on the Optical and Structural Properties of the Alq3:NPD Blend for the UV Photodetector Applications
Authors: Y. Mahmoud Alaa
Published: June 2021

The effect of the volumetric ratio of the tris(8-hydroxyquinoline) aluminum (Alq3) on its blend with the N,N'-Di [(1-naphthyl)-N,N'-diphenyl]-(1,1'-biphenyl)-4,4'-diamine (NPD) (Alq3:NPD) is investigated and optimized for the UV photodetectors
fabrication. The optical and structural properties of Alq3:NPD blend with different volumetric ratios 1:1, 2:1, and 3:1 is studied in the context of the absorbance, transmittance, optical energy gap and XRD patterns. Results show that the absorbance is increased by 11% at A = 260
nm with the increase in the volumetric ratio. In contrast, the optical energy bandgap that is extrapolated from the Tauc’s plot is decreased with the increase in the volumetric ratio, and the 2:1 ratio shows the lowest energy in the UV region. In terms of the XRD investigation, the 2:1
volumetric ratio shows the highest intensity for the crystallinity peak at 36.6°. The fabricated photodetector with a different volumetric ratio of the active layer Alq3:NPD blend shows the best performance with the ratio 2:1.