bluuebunny/crossref_metadata_2025 huggingface dataset:
Special economic zones, export status, and firms’ productivity: Theory and evidence from China
Authors: Liu Yang , Jin Yidan
Published: March 2022

This paper explores the impact of special economic zones (SEZs) policy and export status on firms’ productivity. We first sketch a theoretical model to explain the selection mechanism of different types of exporters and SEZ firms, and provide the productivity ranking of firms. SEZ’s exporters have the highest productivity. Firms facing high imported intermediate tariffs will select themselves into SEZs to avoid imported input tariffs; firms become non‐SEZ’s exporters when their intermediate inputs tariffs are low. Compared with other types of firms, non‐SEZ’s non‐exporters have the lowest productivity. Then, we empirically test the productivity ranking by firm‐level data, and the results are consistent with our theoretical framework. Besides, different SEZ policies are associated with heterogeneous impacts on the firms’ productivity. Our paper further suggests that preferential policies are responsible for the productivity ranking of firms.
Multivariate Hierarchical Analysis of Car Crashes Data Considering a Spatial Network Lattice
Authors: Gilardi Andrea , Mateu Jorge , Borgoni Riccardo , Lovelace Robin
Published: March 2022

Road traffic casualties represent a hidden global epidemic, demanding evidence-based interventions. This paper demonstrates a network lattice approach for identifying road segments of particular concern, based on a case study of a major city (Leeds, UK), in which 5862 crashes of different severities were recorded over an 8-year period (2011–2018). We consider a family of Bayesian hierarchical models that include spatially structured and unstructured random effects to capture the dependencies between the severity levels. Results highlight roads that are more prone to collisions, relative to estimated traffic volumes, in the north-west and south of city centre. We analyse the modifiable areal unit problem (MAUP), proposing a novel procedure to investigate the presence of MAUP on a network lattice. We conclude that our methods enable a reliable estimation of road safety levels to help identify ‘hotspots’ on the road network and to inform effective local interventions.
Current methods to analyze lysosome morphology, positioning, motility and function
Authors: Barral Duarte C. , Staiano Leopoldo , Guimas Almeida Cláudia , Cutler Dan F. , Eden Emily R. , Futter Clare E. , Galione Antony , Marques André R. A. , Medina Diego Luis , Napolitano Gennaro , Settembre Carmine , Vieira Otília V. , Aerts Johannes M. F. G. , Atakpa‐Adaji Peace , Bruno Gemma , Capuozzo Antonella , De Leonibus Elvira , Di Malta Chiara , Escrevente Cristina , Esposito Alessandra , Grumati Paolo , Hall Michael J. , Teodoro Rita O. , Lopes Susana S. , Luzio J. Paul , Monfregola Jlenia , Montefusco Sandro , Platt Frances M. , Polishchuck Roman , De Risi Maria , Sambri Irene , Soldati Chiara , Seabra Miguel C.
Published: March 2022

Since the discovery of lysosomes more than 70 years ago, much has been learned about the functions of these organelles. Lysosomes were regarded as exclusively degradative organelles, but more recent research has shown that they play essential roles in several other cellular functions, such as nutrient sensing, intracellular signalling and metabolism. Methodological advances played a key part in generating our current knowledge about the biology of this multifaceted organelle. In this review, we cover current methods used to analyze lysosome morphology, positioning, motility and function. We highlight the principles behind these methods, the methodological strategies and their advantages and limitations. To extract accurate information and avoid misinterpretations, we discuss the best strategies to identify lysosomes and assess their characteristics and functions. With this review, we aim to stimulate an increase in the quantity and quality of research on lysosomes and further ground‐breaking discoveries on an organelle that continues to surprise and excite cell biologists.
Gobierno corporativo: siete aproximaciones jurídicas
Authors:   Pontificia Universidad Javeriana, Ramírez Zuluaga Camilo
Published: March 2022

Gobierno corporativo: siete aproximaciones jurídicas, por medio del aporte experto de sus autores, brinda una visión jurídica de este y de su incidencia en las distintas temáticas que rodean la realidad empresarial, y abre la discusión para una conversación prolífica sobre el desarrollo regulatorio y autorregulatorio que debe acompañar el futuro de la gobernanza empresarial.
Inactivated SARS-CoV-2 Vaccine Shows Cross-Protection against Bat SARS-Related Coronaviruses in Human ACE2 Transgenic Mice
Authors: Liu Mei-Qin , Jiang Ren-Di , Guo Jing , Chen Ying , Yang Dong-Sheng , Wang Xi , Lin Hao-Feng , Li Ang , Li Bei , Hu Ben , Wang Ze-Jun , Yang Xing-Lou , Shi Zheng-Li
Published: March 2022

The genetic diversity of SARSr-CoVs in wildlife and their potential risk of cross-species infection highlight the necessity of developing wide-spectrum vaccines against infection of various SARSr-CoVs. In this study, we tested the protective efficacy of the SARS-CoV-2 inactivated vaccine (IAV) against two SARSr-CoVs with different spike proteins in human ACE2 transgenic mice.
Metagenome-Assembled Genomes from a Microbiome Converting Xylose to Medium-Chain Carboxylic Acids
Authors: Scarborough Matthew J. , Myers Kevin S. , Fortney Nathaniel W. , Ingle Abel T. , Donohue Timothy J. , Noguera Daniel R.
Published: March 2022

There is growing interest in producing beneficial products from wastes using microbiomes. We previously performed multiomic analyses of a bioreactor microbiome that converted carbohydrate-rich lignocellulosic residues to medium-chain carboxylic acids. Here, we present draft metagenome-assembled genomes from this microbiome, obtained from reactors in which xylose was the primary carbon source.
Draft Genome Sequence of Pediococcus pentosaceus IMI 507024
Authors: Nikodinoska Ivana , Makkonen Jenny , Blande Daniel , Moran Colm
Published: March 2022

We report here the draft genome sequence of
Pediococcus pentosaceus
strain IMI 507024, a lactic acid bacterium isolated from fermented sausage in Kentucky (Nicholasville, KY, USA). The strain is deposited in the Centre for Agriculture and Bioscience International (CABI) Culture Collection with the accession number IMI 507024.
Quantitative Proteomics Reveals Metabolic Reprogramming in Host Cells Induced by Trophozoites and Intermediate Subunit of Gal/GalNAc Lectins from Entamoeba histolytica
Authors: Zhao Yanqing , Li Xia , Zhou Ruixue , Zhang Lei , Chen Lijun , Tachibana Hiroshi , Feng Meng , Cheng Xunjia
Published: March 2022

Metabolic reprogramming is considered a hallmark of some infectious diseases. However, in amoebiasis, a neglected tropical disease caused by protozoan parasite
E. histolytica
, metabolic changes in host cells have yet to be proven.
ClaID: a Rapid Method of Clade-Level Identification of the Multidrug Resistant Human Fungal Pathogen Candida auris
Authors: Narayanan Aswathy , Selvakumar Pavitra , Siddharthan Rahul , Sanyal Kaustuv
Published: March 2022

C. auris
was first isolated in Japan in 2009 as an antifungal drug-susceptible pathogen causing localized infections. Within a decade, it simultaneously evolved in different parts of the world as distinct clades exhibiting resistance to antifungal drugs at varying levels.
Physical Processes Accompanying Laser Ablation in Liquid
Authors: Inogamov N. A. , Zhakhovsky V. V. , Khokhlov V. A.
Published: March 2022

Ablation in liquid is numerically simulated with molecular dynamics and hydrodynamics codes. Laser radiation passes through a transparent liquid, illuminates a metal target, and is absorbed in it and reflected from it. The range of absorbed fluences Fabs about 1 J/cm2 is considered, which is of technological interest: the number of nanoparticles formed per laser pulse below these values is small, whereas the optical breakdown of the liquid occurs above them. A theory is developed to estimate the mass and composition of nanoparticles formed by laser radiation using simulation data and thermodynamic information (equation of state of matter).
Electronic Structure and Properties of Two-Dimensional Silicon Dioxide
Authors: Khachaturova T. A. , But’ko V. G. , Gusev A. A.
Published: March 2022

The electronic structure of two-dimensional silicon dioxide is studied using the projection augmented wave method within the density functional theory. The nonempirical calculations are significantly refined in theGWapproximation. Nanofilms with a thickness of 0.35 to 1.76 nm, where the maximum number of atomic layer is 30, are considered. It is shown that the band gap strongly depends on the thickness of the two-dimensional nanocrystal and demonstrates three different types of behavior. This phenomenon is due to the shift of the Fermi level determined by the ratio of the numbers of Si and O atoms in the unit cell.
Physical and Chemical Mechanisms of Reactions that Proceed at Extremely High Rates in a Propagating Flame and the Detonation of Gas
Authors: Azatyan V. V. , Prokopenko V. M. , Bolodyan I. A. , Gordienko G. M. , Kopylov N. P. , Kopylov S. N.
Published: March 2022

The characteristic periods of the reactions in a propagating flame and the detonation of most gases are found to be less than 10−4 and 10−6 s, respectively. The extreme rates and accelerations of reactions responsible for such short times correspond to the law of the dependence of the rate of the combustion reaction on temperature, which is an exponent containing a Boltzmann factor in a positive power index. The kinetics of the processes is determined mainly by a sharp increase in the concentrations of free atoms and radicals as they approach those of the initial reagents. The conclusions of the theory agree with experimental results.
Data sharing in the age of predictive psychiatry: an adolescent perspective
Authors: Pavarini Gabriela , Yosifova Aleksandra , Wang Keying , Wilcox Benjamin , Tomat Nastja , Lorimer Jessica , Kariyawasam Lasara , George Leya , Alí Sonia , Singh Ilina
Published: March 2022

Background

Advances in genetics and digital phenotyping in psychiatry have given rise to testing services targeting young people, which claim to predict psychiatric outcomes before difficulties emerge. These services raise several ethical challenges surrounding data sharing and information privacy.

Objectives

This study aimed to investigate young people’s interest in predictive testing for mental health challenges and their attitudes towards sharing biological, psychosocial and digital data for such purpose.

Methods

Eighty UK adolescents aged 16–18 years took part in a digital role-play where they played the role of clients of a fictional predictive psychiatry company and chose what sources of personal data they wished to provide for a risk assessment. After the role-play, participants reflected on their choices during a peer-led interview.

Findings

Participants saw multiple benefits in predictive testing services, but were highly selective with regard to the type of data they were willing to share. Largely due to privacy concerns, digital data sources such as social media or Google search history were less likely to be shared than psychosocial and biological data, including school grades and one’s DNA. Participants were particularly reluctant to share social media data with schools (but less so with health systems).

Conclusions

Emerging predictive psychiatric services are valued by young people; however, these services must consider privacy versus utility trade-offs from the perspective of different stakeholders, including adolescents.

Clinical implications

Respecting adolescents’ need for transparency, privacy and choice in the age of digital phenotyping is critical to the responsible implementation of predictive psychiatric services.
Choice of cover crop influences soil fungal and bacterial communities in Prince Edward Island, Canada
Authors: Aiyer Harini , Fofana Bourlaye , Fraser Tandra , Caldwell Claude , McKenzie-Gopsill Andrew , Mills Aaron , Foster Adam
Published: March 2022

Soil fungal and bacterial communities play various roles in agroecosystems and are significantly influenced by agricultural management practices. Currently, little is known about the effects of selected cover crops on soil fungal and bacterial communities in no-till systems. In this study, eight cover crops, three mixed crops, and an unmanaged fallow control were evaluated over 2 years for their effects on the soil microbiome. Internal transcribed spacer (ITS) and 16S rRNA amplicon sequencing was performed to characterize fungal and bacterial communities in the soil during the cover crop growing season, and in the subsequent year. Fungal and bacterial alpha diversity significantly increased over time and were influenced in the subsequent growing season by choice of cover crops. Some fungal and bacterial trophic and functional groups were also affected by crop choice. Fungal pathotroph abundance was positively associated with oilseed radish, alfalfa, and phacelia, but negatively associated with sorghum–sudangrass. Beneficial symbiotrophic fungi and functional nitrification-related bacterial groups were also associated with sorghum–sudangrass and buckwheat. These findings suggest that choice of cover crops influences the soil microbial community composition and may impact plant health in the subsequent crops.
What kind of “complexity” is dual to holographic complexity?
Authors: Yang Run-Qiu , An Yu-Sen , Niu Chao , Zhang Cheng-Yong , Kim Keun-Young
Published: March 2022

It is assumed that the holographic complexities such as the complexity-action (CA) and the complexity-volume (CV) conjecture are dual to complexity in field theory. However, because the definition of the complexity in field theory is still not complete, the confirmation of the holographic duality of the complexity is ambiguous. To improve this situation, we approach the problem from a different angle. We first identify minimal and genuin properties that the filed theory dual of the holographic complexity should satisfy without assuming anything from the circuit complexity or the information theory. Based on these properties, we propose a field theory formula dual to the holographic complexity. Our field theory formula implies that the complexity between certain states in two dimensional CFTs is given by the Liouville action, which is compatible with the path-integral complexity. It gives natural interpretations for both the CA and CV conjectures and identify what their reference states are. When applied to the thermo-field double states, it also gives consistent results with the holographic results in the CA conjecture: both the divergent term and finite term.
The dark side of the torsion: dark energy from propagating torsion
Authors: Benisty D. , Guendelman E. I. , van de Venn A. , Vasak D. , Struckmeier J. , Stoecker H.
Published: March 2022

An extension to the Einstein–Cartan (EC) action is discussed in terms of cosmological solutions. The torsion incorporated in the EC Lagrangian is assumed to be totally anti-symmetric, represented by a time-like axial vector $$S^\mu $$

S
μ

. The dynamics of torsion is invoked by a novel kinetic term. Here we show that this kinetic term gives rise to dark energy, while the quadratic torsion term, emanating from the EC part, represents a stiff fluid that leads to a bouncing cosmology solution. A constraint on the bouncing solution is calculated using cosmological data from different epochs.
Structure transformation and electronic properties of m-aminobenzoic acid under different pressures
Authors: Guo Xu , Chen Limin , Bian Xiang , Liu Chunsheng , Xie Qiyun
Published: March 2022

In this paper, the structural, electronic and optical absorption properties of [Formula: see text]-aminobenzoic acid crystals (hereinafter referred to as [Formula: see text]-amino) in the pressure range of 0–300[Formula: see text]GPa are calculated by density functional theory (DFT). The changing trend of the lattice constant of [Formula: see text]-amino under different pressures is analyzed. We find that the crystal undergoes complex transformation. Furthermore, it can be seen that the structure of [Formula: see text]-amino along the [Formula: see text]-axis is stiffer than that along the [Formula: see text]-axis and [Formula: see text]-axis, suggesting that the crystal has anisotropic compressibility. Through the analysis of the band gap and density of states of [Formula: see text]-amino, it is found that the electronic properties of [Formula: see text]-amino are transformed from semiconductor phase to metal phase at 100[Formula: see text]GPa, then jump into the semiconductor phase and maintain the metal phase again in the pressure range of 150–250[Formula: see text]GPa. Repeated phase transitions indicate that the structure of [Formula: see text]-amino becomes more unstable as the pressure increases. Besides, from the absorption spectra, the optical activity of [Formula: see text]-amino is relatively high with the increase of pressure, and two obvious structural transitions are observed at 70 and 270[Formula: see text]GPa, respectively.
A novel viewpoint of proton decay
Authors: Frampton Paul H.
Published: March 2022

In this paper, we update the standard model [Formula: see text] operators of Weinberg (1979) using a modified notation which accommodates the bilepton extension of the standard model. This may lead to an enhancement of the proton lifetime by orders of magnitude due to mixing first-family with third-family quarks. By contrast, [Formula: see text] operators which can provide Majorana neutrino masses retain the family structure of their counterparts in the standard model.
Multimodal Medical Image Fusion Using Nonsubsampled Shearlet Transform and Smallest Uni-Value Segment Assimilating Nucleus
Authors: Ramlal Sharma Dileepkumar , Sachdeva Jainy , Ahuja Chirag Kamal , Khandelwal Niranjan
Published: March 2022

This paper presents a new fusion scheme for medical (CT-MRI) images which is based on the nonsubsampled shearlet transform (NSST). The various image pairs to be fused are obtained from primary and internet sources. Initially, the images are decomposed through NSST into general and detailed features. The smallest uni-value segment assimilating nucleus (SUSAN) and local sum of Gaussian weighted pixel intensities-based activity measures are proposed to fuse the detailed sub-bands and low-frequency sub-band of NSST, respectively, for faster execution of the algorithm. Visual and parametric comparison of the proposed scheme is done through five traditional fusion algorithms using nine fusion performance parameters. In addition, Wilcoxon signed ranks test is also applied to compare different methods scientifically with the proposed fusion scheme. It is observed that the presented method is better in retaining bone, calcification, cerebrospinal fluid (CSF), edema and tumor details of the source images and is faster than other classical fusion schemes. The fused images of the proposed method are suitable for locating the site of biopsy externally or incision location in the bone of the brain skull with minimum diagnostic time.
SIMULATION OF CELL MOTION IN THE MICROCHANNEL WITH A SQUARE CAVITY
Authors: XUANJUN SONG , LANLAN XIAO , CHENSEN LIN , SHUO CHEN , YANG LIU
Published: March 2022

Isolating circulating tumor cells (CTCs) from the blood plays an important role in the specific treatment of tumor diseases. In this study, a dissipative particle dynamics method combined with a spring-based cell model was employed to simulate the motion of a single or two cells in the microchannel with a square cavity. For a single cell with a small diameter, it will be captured by the square cavity at an appropriate flow rate. For cells whose diameter is not small enough compared to the opening size of the square cavity, they will not be captured at any flow rate. Based on this, cells of different sizes could be successfully separated when passing through this microchannel. Through the analysis of the flow behavior of uncaptured cells, the movement of cells in microchannels is divided into four stages: “guiding,” “rapid,” “slow”, and “ascending” according to the lateral movement speed and centroid position of cells. When the CTC moves together with a red blood cell, as the flow rate decreases, it would be trapped by the microcavity, whereas the RBC is not captured. Thus, CTC can be isolated from blood samples of cancer patients. The method of predicting cell movement behavior through simulation can also provide some reference for the design of microfluidic channels.
Dual Process Theories: Computing Cognition in Context
Authors: Robins Anthony V.
Published: March 2022

This paper explores a major theoretical framework from psychology,
Dual Process Theory (DPT)
, which has received surprisingly little attention in the computing education literature. DPT postulates the existence of two qualitatively different kinds of cognitive systems, a fast, intuitive “System 1” and a slow, reflective “System 2”. System 1 is associated with cognitive factors such as crystallized intelligence, long-term memory and associative learning; System 2 with fluid intelligence, working memory, and rule learning. This paper summarizes DPT and the way it has been expressed and explored in literatures relating to intelligence, memory, learning, attention, cognitive load, and more. It proposes a summary model, the
Dual Process Cycle (DPC)
. It then considers example concepts from computing education within the context of this model. Examples include programming expertise, mental models of programs, the notional machine, code reading and code writing, and the theory of
Learning Edge Momentum (LEM)
. In conclusion, it is argued that the DPC (and the framework of DPTs in general) provides a useful context for defining such concepts more richly and exactly, and for generating interesting questions about them.
Motion Puzzle: Arbitrary Motion Style Transfer by Body Part
Authors: Jang Deok-Kyeong , Park Soomin , Lee Sung-Hee
Published: March 2022

This article presents Motion Puzzle, a novel motion style transfer network that advances the state-of-the-art in several important respects. The Motion Puzzle is the first that can control the motion style of individual body parts, allowing for local style editing and significantly increasing the range of stylized motions. Designed to keep the human’s kinematic structure, our framework extracts style features from multiple style motions for different body parts and transfers them locally to the target body parts. Another major advantage is that it can transfer both global and local traits of motion style by integrating the adaptive instance normalization and attention modules while keeping the skeleton topology. Thus, it can capture styles exhibited by dynamic movements, such as flapping and staggering, significantly better than previous work. In addition, our framework allows for arbitrary motion style transfer without datasets with style labeling or motion pairing, making many publicly available motion datasets available for training. Our framework can be easily integrated with motion generation frameworks to create many applications, such as real-time motion transfer. We demonstrate the advantages of our framework with a number of examples and comparisons with previous work.
H-Container: Enabling Heterogeneous-ISA Container Migration in Edge Computing
Authors: Xing Tong , Barbalace Antonio , Olivier Pierre , Karaoui Mohamed L. , Wang Wei , Ravindran Binoy
Published: March 2022

Edge computing is a recent computing paradigm that brings cloud services closer to the client. Among other features, edge computing offers extremely low client/server latencies. To consistently provide such low latencies, services should run on edge nodes that are physically as close as possible to their clients. Thus, when the physical location of a client changes, a service should migrate between edge nodes to maintain proximity. Differently from cloud nodes, edge nodes integrate CPUs of different Instruction Set Architectures (ISAs), hence a program natively compiled for a given ISA cannot migrate to a server equipped with a CPU of a different ISA. This hinders migration to the closest node.

We introduce H-Container, a system that migrates natively compiled containerized applications across compute nodes featuring CPUs of different ISAs. H-Container advances over existing heterogeneous-ISA migration systems by being (a) highly compatible – no user’s source-code nor compiler toolchain modifications are needed; (b) easily deployable – fully implemented in user space, thus without any OS or hypervisor dependency, and (c) largely Linux-compliant – it can migrate most Linux software, including server applications and dynamically linked binaries. H-Container targets Linux and its already-compiled executables, adopts LLVM, extends CRIU, and integrates with Docker. Experiments demonstrate that H-Container adds no overheads during program execution, while 10–100 ms are added during migration. Furthermore, we show the benefits of H-Container in real-world scenarios, demonstrating, for example, up to 94% increase in Redis throughput when client/server proximity is maintained through heterogeneous container migration.
A New Test for Hamming-Weight Dependencies
Authors: Blackman David , Vigna Sebastiano
Published: March 2022

We describe a new statistical test for pseudorandom number generators (PRNGs). Our test can find bias induced by dependencies among the Hamming weights of the outputs of a PRNG, even for PRNGs that pass state-of-the-art tests of the same kind from the literature, and particularly for generators based on
F
2
-linear transformations such as the dSFMT [
22
],
xoroshiro1024+
 [
1
], and WELL512 [
19
].
Enhanced Connectivity Validity Measure Based on Outlier Detection for Multi-Objective Metaheuristic Data Clustering Algorithms
Authors: Mustafa Hossam M. J. , Ayob Masri
Published: March 2022

Data clustering algorithms experience challenges in identifying data points that are either noise or outlier. Hence, this paper proposes an enhanced connectivity measure based on the outlier detection approach for multi-objective data clustering problems. The proposed algorithm aims to improve the quality of the solution by utilising the local outlier factor method (LOF) with the connectivity validity measure. This modification is applied to select the neighbour data point’s mechanism that can be modified to eliminate such outliers. The performance of the proposed approach is assessed by applying the multi-objective algorithms to eight real-life and seven synthetic two-dimensional datasets. The external validity is evaluated using the F-measure, while the performance assessment matrices are employed to assess the quality of Pareto-optimal sets like the coverage and overall non-dominant vector generation. Our experimental results proved that the proposed outlier detection method has enhanced the performance of the multi-objective data clustering algorithms.
Open-Pit Mine Geological Model Construction and Composite Rock Blasting Optimization Research
Authors: Yang Yuqing , Ding Xiaohua , Zhou Wei , Lu Xiang , Ebelia Manda , An Wen , Li Jinyu , Zhang Xiaonan
Published: March 2022

In this paper, the blasting parameters are designed based on the drilling data of the exploration geological stage, the geophysical and mechanical parameters of the mining area, and the geological age information, and the numerical simulation of the blasting of the layered rock steps is carried out to optimize the blasting parameters. Multiple sets of blasting tests were carried out on-site, and the large block rate, average block size satisfaction rate, large block satisfaction rate, cost satisfaction rate, shovel loading efficiency, and blasting effect satisfaction rate were set as the blasting effect evaluation indicators, which verified the feasibility of the optimized scheme.
Diagnosis of Critical Risk Sources in the Operation Safety of the Central Route Project of South-to-North Water Diversion Based on the Improved FMEA Method
Authors: Nie Xiangtian , Zheng Ye , Zhang Yan , Chen Zihan , Wang Bo
Published: March 2022

For the inaccurate description of the failure level in the traditional failure mode and effects analysis (FMEA) method, the research uses the fuzzy evidence reasoning theory to improve the traditional failure mode and effects analysis (FMEA) method. Based on the subjective weight determined by the analytic hierarchy process and the objective weight determined by the gray correlation degree method, we get the combined weight of risk factors through the principle of minimum discrimination information. Combined with the technique for order of preference by similarity to ideal solution (TOPSIS), an improved risk sequence number (IRPN) method was proposed to diagnose the key risk sources. In the case study on a canal section of the Central Route Project of South-to-North Water Diversion in Henan, the key risk factors for the operation safety of the project are identified as rainstorm and flood, geological conditions, geological disasters, and design safety coefficient, and the corresponding prevention measures are put forward to provide help for the safe operation of the Central Route Project of South-to-North Water Diversion.
Real-Time Monitoring of Intraocular Pressure in Glaucoma Patients Using Wearable Mobile Medicine Devices
Authors: Yuan Xiangwen , Zhang Jiabin
Published: March 2022

Glaucoma is caused by excessive aqueous humor in the eye, resulting in a continuous or intermittent increase of intraocular pressure, which exceeds the tolerance of the eyeball and damages the optic nerve. Existing treatments for glaucoma do not work well or have significant side effects. Intraocular pressure signal is a very important physiological signal that needs real-time and accurate monitoring in glaucoma patients, especially in severe glaucoma patients. Therefore, long-term, real-time, and accurate monitoring of intraocular pressure is of great significance for the diagnosis and treatment of glaucoma patients. The use of wearable devices for real-time ocular diagnosis and treatment of glaucoma patients is an effective approach. However, the current commonly used intraocular pressure measurement and monitoring technology is difficult to meet the diagnosis and monitoring needs of glaucoma patients in terms of size, measurement accuracy, power consumption, and intelligence. Therefore, facing the needs of glaucoma disease treatment, this topic studies an implantable flexible intraocular pressure sensor for long-term continuous monitoring of intraocular pressure in glaucoma patients and mainly focuses on the working principle, structural design, process fabrication, measurement and control system, characterization, and performance test of the intraocular pressure sensor. It is of great significance for personalized and accurate treatment of glaucoma patients.
Evaluation of Multicomponent Changes of Schisandra chinensis Fruits with Different Drying Process by UPLC-QQQ-MS-Based Targeted Metabolomics Analysis
Authors: Sheng Yan-hua , Wang Rui , Wang Yi-kai , Li Meng-meng , Liu Fang-xin , Huang Xin , Chen Chang-bao
Published: March 2022

Schisandra chinensis fruit is a famous tonic traditional Chinese medicine and healthy food. The chemical components of dried fruits may vary with the initial processing methods of fresh fruits. Therefore, in this study, the influence of drying was evaluated based on targeted metabolomics analysis. The ultrahigh performance liquid chromatography-triple quadrupole mass spectrometry (UPLC-QQQ-MS) was applied in determination of multicomponent including lignans, organic acids, and oligosaccharides. The fresh fruits of Schisandra chinensis were processed by natural drying in the sun, hot air drying and vacuum drying at different temperatures, and vacuum freeze drying, respectively. The contents of lignans, organic acids, and oligosaccharides in different fruit samples were quantified and statistically analyzed by partial least squares discriminant analysis (PLS-DA). The variation of totally 10 lignans, 5 organic acids, and 9 oligosaccharides with different drying process were compared. The results showed that the drying time of natural drying method was much longer than the other methods using instrument. For hot air and vacuum drying samples, most of lignans, organic acids, and oligosaccharides gradually decreased with the increase of temperature. And the appearance of fruit drying at higher temperature was dark red. At the same processing temperature, vacuum drying takes longer time than hot air drying. In addition, organic acid and oligosaccharide contents of vacuum freeze drying treated samples were higher than the other processed samples significantly. According to the targeted metabolomics analysis, the lignans, organic acids, and oligosaccharides markers were screened out for holistic quality evaluation of Schisandra chinensis fruits. In comprehensive consideration of multicomponent, drying time, fruit appearance and storage, and production feasibility, hot air drying at 50°C is more suitable for the process of Schisandra chinensis. The result is expected to provide a scientific basis for the selection of proper method for drying process of fresh Schisandra chinensis fruit.
Application of Transfer Learning and Feature Fusion Algorithms to Improve the Identification and Prediction Efficiency of Premature Ovarian Failure
Authors: Zhang Yuanyuan , Hou Jing , Wang Qiaoyun , Hou Aiqin , Liu Yanni
Published: March 2022

Ultrasound imaging technology has the advantages of noninvasiveness, real-time, low price, and easy operation. It is one of the most used diagnostic tools for early detection and classification of premature ovarian failure. Although the rapid development of computer-aided diagnosis has provided a great help to the ultrasound diagnosis of premature ovarian failure, it still has many limitations and shortcomings, so this paper adopts transfer learning and feature fusion algorithms to improve the identification and prediction efficiency of premature ovarian failure. In this study, the POF group and the control group both adopted a unified scale. From the four aspects of sociological characteristics, past medical history, environmental factors, and living habits, a dedicated person asked and filled out the scale face to face. All patients participating in the experiment underwent ultrasound examinations. In this paper, the bottom-level feature fusion method is used to improve classification performance. The experiment uses 100 epochs. After each epoch training is completed, we used all the data and labels of the target domain to test. All experiments were performed five times, and the result is the average of five experiments. All the results of baseline and direct classification without migration use the average of five experimental results as the result. Migrating the features extracted by the InceptionV3 network has the best performance for predicting premature ovarian failure. Its classification accuracy is as high as 85.13%, and the F1 value is 0.78. The results show that the migration learning and feature fusion algorithms used in this paper can provide reliable predictive analysis and decision support for doctors in the diagnosis of premature ovarian failure.
Phytochemical Profiling of the Leaf Extract of Ximenia americana var. caffra and Its Antioxidant, Antibacterial, and Antiaging Activities In Vitro and in Caenorhabditis elegans: A Cosmeceutical and Dermatological Approach
Authors: Bakrim Widad Ben , Nurcahyanti Agustina Dwi Retno , Dmirieh Malak , Mahdi Ismail , Elgamal Abdelbaset M. , El Raey Mohamed A. , Wink Michael , Sobeh Mansour
Published: March 2022

We previously annotated the phytochemical constituents of a root extract from Ximenia americana var. caffra and highlighted its hepatoprotective and hypoglycemic properties. We here extended our study on the leaf extract and identified its phytoconstituents using HPLC-PDA-ESI-MS/MS. In addition, we explored its antioxidant, antibacterial, and antiaging activities in vitro and in an animal model, Caenorhabditis elegans. Results from HPLC-PDA-ESI-MS/MS confirmed that the leaves contain 23 secondary metabolites consisting of condensed tannins, flavonol glycosides, flavone glycosides, and flavonol diglycosides. The leaf extract demonstrated significant antioxidant activity in vitro with IC50 value of 5 μg/mL in the DPPH assay and 18.32 μg/mL in the FRAP assay. It also inhibited four enzymes (collagenase, elastase, hyaluronidase, and tyrosinase) crucially involved in skin remodeling and aging processes with comparable activities to reference drugs along with four pure secondary metabolites identified from the extract. In accordance with the in vitro result, in vivo tests using two transgenic strains of C. elegans demonstrated its ability to reverse oxidative stress. Evidence included an increased survival rate in nematodes treated with the prooxidant juglone to 68.9% compared to the 24.8% in untreated worms and a reduced accumulation of intracellular reactive oxygen species (ROS) in a dose-dependent manner to 77.8%. The leaf extract also reduced levels of the expression of HSP 16.2 in a dose-dependent manner to 86.4%. Nuclear localization of the transcription factor DAF-16 was up to 10 times higher in worms treated with the leaf extract than in the untreated worms. The extract also inhibited the biofilm formation of Pseudomonas aeruginosa (a pathogen in skin infections) and reduced the swimming and swarming mobilities in a dose-dependent fashion. In conclusion, leaves of X. americana are a promising candidate for preventing oxidative stress-induced conditions, including skin aging.
Study on the Relationship between Conspicuous Need and Group Cultural Identity of Fashion Cultural Consumption
Authors: Zhao Liang , Duan Yunze , Wang Qiang , Zhou Ke , Gu Nailin , Li Xiangzhong , Dai Jingyu
Published: March 2022

The consumption of sports and leisure apparel has distinct historical characteristics. It is linked to social fashion and fashion trends, which is an internal expression of college students’ perceptions of sports connotation, aesthetic taste, and community affiliation. Furthermore, it serves as a vital link and conduit for college students’ perceptions of sports fashion. This research includes fieldwork in a sportswear briefing and a thorough interview with 15 interviewees. This research builds an analytical framework for the relationship between sports, leisure clothes, and college students’ consumption behavior based on the conspicuous consumption theory. This article examines the relationship and influence between college students’ consumption behavior and sports and leisure clothing consumption in three categories of community affiliation, perceived value, and consumption behavior. According to the findings, college students’ consuming activity shows off their affluence to a certain extent. But, at its core, college students’ consumption is about understanding society and constructing their self-image. As a result, it reflects the changing value orientation of today’s Chinese college students’ purchasing habits. According to the research, it shows the importance of sports leisure apparel consuming behavior is rooted not only in the clothing but also in community identity.
Exploring the Resistance Mechanisms of Distal D835V Mutation in FLT3 to Inhibitors
Authors: Wang Zhiwei , Hu Baichun , An Yu , Wang Jian
Published: March 2022

Objective. FMS-like tyrosine kinase 3 (FLT3) is an attractive therapeutic target in acute myeloid leukemia. Unfortunately, secondary FLT3 mutations that developed resistance to inhibitors have become a severe problem. Specifically, ASP-835 (D835F/H/V/Y) mutant within the activation loop of FLT3 is the most commonly encountered drug-resistant and observed secondary FLT3 mutations. In this study, we carried out a set of computational approaches to explore how this mutation influenced the conformation and dynamics of DFG motif in a manner altered inhibitors’ susceptibility. Methods. Molecular dynamics (MD) simulation, dynamic cross-correlation (DCC) analysis, surface area (SASA), binding free energy (MM-GBSA), and structural analysis were used to compare the severe and minor D835V mutation-induced impact to sorafenib and crenolanib, respectively. Results. The A-loop of the FLT3 protein may experience conformational change in the presence of the resistant mutation, which were mainly positioned at PHE-830. The protein-inhibitor interactions displayed that the motions of PHE-830 influenced that of sorafenib, but not to crenolanib. Conclusions. These findings indicated that the structural impact brought by D835V mutation should be considered in designing novel drugs to overcome resistance to FLT3-D835V.
Machine Learning Based Distribution of Sports Video Stream Assisting Physical Training
Authors: Wang Yanni , Li Jinhui
Published: March 2022

The rapid development of Olympic Games and the intensification of professional sports events make the competition between excellent athletes and teams become more and more fierce, so the demands on athletes’ psychology, techniques, and physical strength are becoming higher and higher, especially that the demands on physical strength are more prominent. Therefore, physical training is an important part of sports training and the core link of competitive sports, which is widely valued by coaches and athletes all over the world. At the same time, with the influence and penetration of the rapid development of modern information technology and network big data on competitive sports, the scientific and digital process of athletes’ physical training has also been accelerated, and many new ideas, scientific training methods, and advanced sports technology have emerged. During the pandemic, many aggregation activities have been disrupted, as well as physical training. Therefore, this paper improves the quality of physical training through video, so that athletes can do physical training at any time and any place. A cut vertices spanning tree algorithm based on machine learning is proposed to distribute layered multicast streaming and dynamically adjust the number of layers of sports video streaming. The cut vertices spanning tree algorithm is mainly applied to the situation when the network bandwidth resources are relatively scarce. The evaluation results indicate that the proposed method can improve the estimated quality of experience (QoE), packet loss rate, link utilization, and video delay on Mininet simulation platform. Furthermore, it can be seen from the experiments that the proposed method has a good performance on distribution of sports video stream assisting physical training.
Whale Optimization Algorithm-Based LQG-Adaptive Neuro-Fuzzy Control for Seismic Vibration Mitigation with MR Dampers
Authors: Lin Xiufang , Lin Weiqing
Published: March 2022

Design of effective control strategies to protect structural buildings from seismic hazards is gaining increasing attention. In this paper, an intelligent semiactive control strategy, which combines linear-quadratic-Gaussian (LQG), whale optimization algorithm (WOA), and adaptive neuro-fuzzy inference system (ANFIS) strategy is designed to mitigate structural vibration by using magnetorheological (MR) dampers, here known as WLQG-ANFIS control. Firstly, considering that the performance of the LQG control for the structures under seismic excitations strongly depends on skill and experience of the experts in determining the weighting matrix of the feedback gain, a WOA with constraints is adopted to optimally design the LQG control due to the strong ability to avoid local optima. Secondly, the inverse dynamic model of the MR damper is developed with the ANFIS technique which combines the fuzzy system and artificial neural network. Finally, according to the active force estimated by the proposed LQG control, the developed inverse model is utilized to calculate the MR damper command signal. Numerical analyses are conducted for a 10-story structural building installed with MR dampers under earthquake excitation. Through a test called analysis of variance in optimizing the LQG control, the superiority of WOA over other three meta-heuristic algorithms, i.e. GA, DE, and ABC, in terms of convergence performance and robustness is validated. The proposed WLQG-ANFIS control can reduce the maximum displacement, interstory drift and acceleration responses by 64%, 65%, and 53%, respectively, which can achieve better overall performance than on-off control, LQG-ANFIS control, fuzzy control, and H∞-ANFIS control. Moreover, this control strategy exhibits the ability to handle the uncertainties in structural parameters as well as seismic excitations.
A New Malware Detection Method Based on VMCADR in Cloud Environments
Authors: Zheng Luxin , Zhang Jian
Published: March 2022

With the cloud computing technology developing increasingly, malware and privacy protection have become two major challenges for cloud security. At present, the detection methods based on virtualization technology are mainly in-VM and out-of-VM approaches, both of which have high detection rates. However, a lot of relevant researches at present have focused on the accuracy of malware without considering the privacy protection of cloud tenants sufficiently. In this paper, we propose a new cloud-based malware detection method that can detect malware in cloud service platforms without compromising user privacy. In order to protect the privacy of cloud tenants, this method uses relevant virtualization technologies to obtain memory snapshots of cloud tenants. Because the memory snapshot is very large, and the semantics is of low level, it needs to be processed for feature dimensionality reduction. Therefore, we propose visualized memory change area dimensionality reduction (VMCADR) method. This method directly performs malware detection on binary memory snapshots without accessing user system information and files, thereby protecting user privacy. The following are the main steps of VMCADR method. First, we propose memory difference (MDIFF) algorithm to obtain the Memory Changed Area (MCA), which is changed by the test program. Then, in order to better detect the MCA files, we use visualization technology to process it. Next, we convert these MCA files into grayscale images and RGB images, respectively. And we resize the picture pixels uniformly, so that it can be classified using convolutional neural networks. Finally, we propose a Simplified Neural Network (SNN) to classify these images. After experiments, the RGB-dataset accuracy of malware detection is 99.39%.
Effect of Recycled Aggregate Content on Water Permeability and Pore Structure of Pervious Concrete Pavement
Authors: Cheng Yin , Shen Nan , Yu Hao , Feng Lu , Yang Tianjun , Shen Jun
Published: March 2022

The shortage of natural aggregate (NA) and a large amount of construction waste generation bring opportunities for the application of recycled aggregate (RA). To investigate the mechanical properties and permeability of Recycled Aggregate Pervious Concrete (RAPC), this study tested the compressive strength, tensile strength, flexural strength, porosity, permeability coefficient, and water retention of RAPC with different RA contents (0, 25%, 50%, 75%, and 100%) and analyzed the changes of these parameters with RA content. Among them, two methods were used for the calculation of porosity. The results showed that the porosity, permeability, and water retention of RAPC increased with the increase in RA content, but the compressive strength, splitting tensile strength, flexural strength, and uniaxial tensile strength decreased. According to the demand of pavement engineering, RAPC should have good water permeability while meeting the strength requirements, so the optimal RA content is 50%.