bluuebunny/crossref_metadata_2025 huggingface dataset:
Operational Amplifier Design Employing DTMOS Technique with Dual Supply Voltages
Authors: Alaybeyoglu Ersin , Ozenli Deniz
Published: August 2021

An operational amplifier (OPAMP) for portable devices with dual supply voltage is presented in this work. The design is realized with a 600[Formula: see text]mV supply for the core design and a 1.8[Formula: see text]V supply for the biasing circuit to improve input common mode range (ICMR), gain, and common mode rejection ratio (CMRR). The designed amplifier is implemented with dynamic threshold voltage MOSFET (DTMOS) transistors to decrease power consumption and increase the performance of the design. The power consumption of the core design is obtained as 2[Formula: see text][Formula: see text]W while the biasing circuitry consumes 7.38[Formula: see text][Formula: see text]W. The application of different supply voltages has greatly increased the gain of the circuit, where the circuit exhibits 100.2[Formula: see text]dB DC gain and 3.41[Formula: see text]MHz gain bandwidth product (GBW). CMRR of the designed circuit is 84.22[Formula: see text]dB. The simulations are performed in Cadence environment with 0.18[Formula: see text][Formula: see text]m CMOS technology.
Information Source, Media Credibility, and Epidemic Control in COVID-19 Pandemic
Authors: Liu Yuanyuan , Li Xiaojing
Published: August 2021

Based on classic media theories and typical case studies, this paper analyzed the main media types and information sources in COVID-19 infections and the impacts on media trust and social trust, as well as the effects on public health prevention and national epidemic control. It found that news media, social media, aggregated media, medical media, and government media were the five main media types people used in this pandemic. News media performed well on professionalism, timeliness, closeness to public, and social support. Aggregated media and medical media also deserved public trust on error recovery, closeness to public, unselfishness, etc. The fake news on social media, inconsistent data, and information disclosure lag impaired public trust on media. Medical media promoted the health preventive behavior of the public. News media greatly influenced the agenda setting, public opinion, and national epidemic control in the COVID-19 pandemic.
Recurrent Video Deblurring with Blur-Invariant Motion Estimation and Pixel Volumes
Authors: Son Hyeongseok , Lee Junyong , Lee Jonghyeop , Cho Sunghyun , Lee Seungyong
Published: August 2021

For the success of video deblurring, it is essential to utilize information from neighboring frames. Most state-of-the-art video deblurring methods adopt motion compensation between video frames to aggregate information from multiple frames that can help deblur a target frame. However, the motion compensation methods adopted by previous deblurring methods are not blur-invariant, and consequently, their accuracy is limited for blurry frames with different blur amounts. To alleviate this problem, we propose two novel approaches to deblur videos by effectively aggregating information from multiple video frames. First, we present
blur-invariant motion estimation learning
to improve motion estimation accuracy between blurry frames. Second, for motion compensation, instead of aligning frames by warping with estimated motions, we use a
pixel volume
that contains candidate sharp pixels to resolve motion estimation errors. We combine these two processes to propose an effective recurrent video deblurring network that fully exploits deblurred previous frames. Experiments show that our method achieves the state-of-the-art performance both quantitatively and qualitatively compared to recent methods that use deep learning.
Artificial Intelligence–based Computed Tomography Processing Framework for Surgical Telementoring of Congenital Heart Disease
Authors: Xie Wen , Yao Zeyang , Ji Erchao , Qiu Hailong , Chen Zewen , Guo Huiming , Zhuang Jian , Jia Qianjun , Huang Meiping
Published: August 2021

Congenital heart disease (CHD) is the most common birth defect, accounting for one-third of all congenital birth defects. As with complicated intracardiac structural abnormalities, CHD is usually treated with surgical repair, and computed tomography (CT) is the main examination method for diagnosis of CHD and also provides anatomical information to surgeons. Currently, there exists a serious shortage of professional surgeons in developing countries. Compared with developed countries where large hospitals and cardiovascular disease centers have professional surgical teams with rich treatment experience, surgeons in developing countries and remote areas suffer from lack of professional surgical skills resulting with low surgical quality and high mortality. Recently, surgical telementoring has been popular to tackle the above problems, in which less-skilled surgeons can get real-time guidance from skilled surgeons remotely through audio and video transmission. However, there still exists difficulties in applying telementoring to CHD surgeries including high resource consumption on medical data transmission and storage, large image noise, and inconvenient and inefficient discussion between surgeons on CT. In this article, we proposed a framework with an image compression module, an image denoising module, and an image segmentation module based on CT images in CHD. We evaluated the above three modules and compared them with existing works, respectively, and the results show that our methods achieve much better performance. Furthermore, with 3D printing, VR technology, and 5G communications, our framework was successfully used in a real case study to treat a patient who needed surgical treatment.
Entity Recommendation for Everyday Digital Tasks
Authors: Jacucci Giulio , Daee Pedram , Vuong Tung , Andolina Salvatore , Klouche Khalil , Sjöberg Mats , Ruotsalo Tuukka , Kaski Samuel
Published: August 2021

Recommender systems can support everyday digital tasks by retrieving and recommending useful information contextually. This is becoming increasingly relevant in services and operating systems. Previous research often focuses on specific recommendation tasks with data captured from interactions with an individual application. The quality of recommendations is also often evaluated addressing only computational measures of accuracy, without investigating the usefulness of recommendations in realistic tasks. The aim of this work is to synthesize the research in this area through a novel approach by (1) demonstrating comprehensive digital activity monitoring, (2) introducing entity-based computing and interaction, and (3) investigating the previously overlooked usefulness of entity recommendations and their actual impact on user behavior in real tasks. The methodology exploits context from screen frames recorded every 2 seconds to recommend information entities related to the current task. We embodied this methodology in an interactive system and investigated the relevance and influence of the recommended entities in a study with participants resuming their real-world tasks after a 14-day monitoring phase. Results show that the recommendations allowed participants to find more relevant entities than in a control without the system. In addition, the recommended entities were also used in the actual tasks. In the discussion, we reflect on a research agenda for entity recommendation in context, revisiting comprehensive monitoring to include the physical world, considering entities as actionable recommendations, capturing drifting intent and routines, and considering explainability and transparency of recommendations, ethics, and ownership of data.
Intermittent Control as a Model of Mouse Movements
Authors: Martín J. Alberto Álvarez , Gollee Henrik , Müller Jörg , Murray-Smith Roderick
Published: August 2021

We present Intermittent Control (IC) models as a candidate framework for modelling human input movements in Human–Computer Interaction (HCI). IC differs from continuous control in that users are not assumed to use feedback to adjust their movements continuously, but only when the difference between the observed pointer position and predicted pointer positions becomes large. We use a parameter optimisation approach to identify the parameters of an intermittent controller from experimental data, where users performed one-dimensional mouse movements in a reciprocal pointing task. Compared to previous published work with continuous control models, based on the Kullback–Leibler divergence from the experimental observations, IC is better able to generatively reproduce the distinctive dynamical features and variability of the pointing task across participants and over repeated tasks. IC is compatible with current physiological and psychological theory and provides insight into the source of variability in HCI tasks.
Fine Wrinkling on Coarsely Meshed Thin Shells
Authors: Chen Zhen , Chen Hsiao-Yu , Kaufman Danny M. , Skouras Mélina , Vouga Etienne
Published: August 2021

We propose a new model and algorithm to capture the high-definition statics of thin shells via coarse meshes. This model predicts global, fine-scale wrinkling at frequencies much higher than the resolution of the coarse mesh; moreover, it is grounded in the geometric analysis of elasticity, and does not require manual guidance, a corpus of training examples, nor tuning of ad hoc parameters. We first approximate the coarse shape of the shell using tension field theory, in which material forces do not resist compression. We then augment this base mesh with wrinkles, parameterized by an amplitude and phase field that we solve for over the base mesh, which together characterize the geometry of the wrinkles. We validate our approach against both physical experiments and numerical simulations, and we show that our algorithm produces wrinkles qualitatively similar to those predicted by traditional shell solvers requiring orders of magnitude more degrees of freedom.
“Citizens Too”: Safety Setting Collaboration Among Older Adults with Memory Concerns
Authors: Mcdonald Nora , Mentis Helena M.
Published: August 2021

Designing technologies that support the cybersecurity of older adults with memory concerns involves wrestling with an uncomfortable paradox between surveillance and independence and the close collaboration of couples. This research captures the interactions between older adult couples where one or both have memory concerns—a primary feature of cognitive decline—as they make decisions on how to safeguard their online activities using a Safety Setting probe we designed, and over the course of several informal interviews and a diary study. Throughout, couples demonstrated a collaborative mentality to which we apply a frame of citizenship in opensource collaboration, specifically (a)
histories of participation
, (b)
lower barriers to participation, and
(c)
maintaining ongoing contribution.
In this metaphor of collaborative enterprise, one partner (or member of the couple) may be the service provider and the other may be the participant, but at varying moments, they may switch roles while still maintaining a collaborative focus on preserving shared assets and freedom on the internet. We conclude with a discussion of what this service provider-contributor mentality means for empowerment through citizenship, and implications for vulnerable populations’ cybersecurity.
Predictable Robots for Autistic Children—Variance in Robot Behaviour, Idiosyncrasies in Autistic Children’s Characteristics, and Child–Robot Engagement
Authors: Schadenberg Bob R. , Reidsma Dennis , Evers Vanessa , Davison Daniel P. , Li Jamy J. , Heylen Dirk K. J. , Neves Carlos , Alvito Paulo , Shen Jie , Pantić Maja , Schuller Björn W. , Cummins Nicholas , Olaru Vlad , Sminchisescu Cristian , Dimitrijević Snežana Babović , Petrović Sunčica , Baranger Aurélie , Williams Alria , Alcorn Alyssa M. , Pellicano Elizabeth
Published: August 2021

Predictability is important to autistic individuals, and robots have been suggested to meet this need as they can be programmed to be predictable, as well as elicit social interaction. The effectiveness of robot-assisted interventions designed for social skill learning presumably depends on the interplay between robot predictability, engagement in learning, and the individual differences between different autistic children. To better understand this interplay, we report on a study where 24 autistic children participated in a robot-assisted intervention. We manipulated the variance in the robot’s behaviour as a way to vary predictability, and measured the children’s behavioural engagement, visual attention, as well as their individual factors. We found that the children will continue engaging in the activity behaviourally, but may start to pay less visual attention over time to activity-relevant locations when the robot is less predictable. Instead, they increasingly start to look away from the activity. Ultimately, this could negatively influence learning, in particular for tasks with a visual component. Furthermore, severity of autistic features and expressive language ability had a significant impact on behavioural engagement. We consider our results as preliminary evidence that robot predictability is an important factor for keeping children in a state where learning can occur.
A Comprehensive Approach to On-board Autonomy Verification and Validation
Authors: Bozzano Marco , Cimatti Alessandro , Roveri Marco
Published: August 2021

Deep space missions are characterized by severely constrained communication links. To meet the needs of future missions and increase their scientific return, future space systems will require an increased level of autonomy on-board. In this work, we propose a comprehensive approach to on-board autonomy. We rely on model-based reasoning, and we consider many important (on-line and off-line) reasoning capabilities such as plan generation, validation, execution and monitoring, runtime diagnosis, and fault detection, identification, and recovery. The controlled platform is represented symbolically, and the reasoning capabilities are seen as symbolic manipulation of such formal model. We have developed a prototype of our framework, and we have integrated it within an on-board Autonomous Reasoning Engine. Finally, we have evaluated our approach on three case-studies inspired by real-world projects and characterized it in terms of reliability, availability, and performance.
Desmosomal Cadherins in Health and Disease
Authors: Hegazy Marihan , Perl Abbey L. , Svoboda Sophia A. , Green Kathleen J.
Published: August 2021

Desmosomal cadherins are a recent evolutionary innovation that make up the adhesive core of highly specialized intercellular junctions called desmosomes. Desmosomal cadherins, which are grouped into desmogleins and desmocollins, are related to the classical cadherins, but their cytoplasmic domains are tailored for anchoring intermediate filaments instead of actin to sites of cell–cell adhesion. The resulting junctions are critical for resisting mechanical stress in tissues such as the skin and heart. Desmosomal cadherins also act as signaling hubs that promote differentiation and facilitate morphogenesis, creating more complex and effective tissue barriers in vertebrate tissues. Interference with desmosomal cadherin adhesive and supra-adhesive functions leads to a variety of autoimmune, hereditary, toxin-mediated, and malignant diseases. We review our current understanding of how desmosomal cadherins contribute to human health and disease, highlight gaps in our knowledge about their regulation and function, and introduce promising new directions toward combatting desmosome-related diseases.
Recent Challenges in Actuarial Science
Authors: Embrechts Paul , Wüthrich Mario V.
Published: August 2021

For centuries, mathematicians and, later, statisticians, have found natural research and employment opportunities in the realm of insurance. By definition, insurance offers financial cover against unforeseen events that involve an important component of randomness, and consequently, probability theory and mathematical statistics enter insurance modeling in a fundamental way. In recent years, a data deluge, coupled with ever-advancing information technology and the birth of data science, has revolutionized or is about to revolutionize most areas of actuarial science as well as insurance practice. We discuss parts of this evolution and, in the case of non-life insurance, show how a combination of classical tools from statistics, such as generalized linear models and, e.g., neural networks contribute to better understanding and analysis of actuarial data. We further review areas of actuarial science where the cross fertilization between stochastics and insurance holds promise for both sides. Of course, the vastness of the field of insurance limits our choice of topics; we mainly focus on topics closer to our main areas of research.
A Reliable Network Intrusion Detection Approach Using Decision Tree with Enhanced Data Quality
Authors: Guezzaz Azidine , Benkirane Said , Azrour Mourade , Khurram Shahzada
Published: August 2021

Due to the recent advancements in the Internet of things (IoT) and cloud computing technologies and growing number of devices connected to the Internet, the security and privacy issues are important to be resolved and protect the data and computer network. To provide security, a real-time monitoring of the network data and resources is needed. Intrusion detection systems have been used to monitor, detect, and alert an intrusion event in real time. Recently, the intrusion detection systems (IDS) incorporate several machine learning (ML) techniques. One of the techniques is decision tree, which can take reliable network measures and make good decisions by increasing the detection rate and accuracy. In this paper, we propose a reliable network intrusion detection approach using decision tree with enhanced data quality. Specifically, network data preprocessing and entropy decision feature selection is carried out for enhancing the data quality and relevant training; then, a decision tree classifier is built for reliable intrusion detection. Experimental study on two datasets shows that the proposed model can reach robust results. Actually, our model achieves 99.42% and 98.80% accuracy with NSL-KDD and CICIDS2017 datasets, respectively. The novel approach gives many advantages compared to the other models in term of accuracy (ACC), detection rate (DR), and false alarm rate (FAR).
Motion Reliability Analysis of Unlocking Trigger Device Based on CPSO-BR-BP Neural Network with Uncertain Parameters
Authors: Tian Yun , Fan Hongtao , Zhang Yuliang , Liu Licheng , Gong Kang
Published: August 2021

Aiming at overcoming the problem that the mechanism function of the unlocking trigger device is difficult to obtain and the corresponding reliability analysis cannot be performed, a motion reliability analysis method based on the CPSO-BR-BP neural network proxy model is proposed. Firstly, the particle swarm algorithm is optimized through the chaotic sequence, and the back-propagation (BP) neural network is optimized using Chaos Particle Swarm Optimization (CPSO) and Bayesian Regularization (BR) algorithm. The CPSO-BR-BP neural network proxy model is established, and the reliability of shape memory alloys (SMA) wire unlocking based on the structural function is calculated. Moreover, according to the structural function of the separation process, the motion reliability based on the proxy model and the improved membership function is calculated. Finally, a series reliability model is established based on the unlocking process and the separation process to calculate the reliability of the whole machine. The reliability of the unlocking trigger device is analyzed by the proposed method. Results show that the proposed method is computationally efficient with the calculated reliability of 0.9987.
An Optimal Algorithm for Planning Shearer Trailing Drum Cutting Path
Authors: Zhang Hong , Hou Yunbing , Sun Zhenming , Li Zhen , Mao Shanjun , Li Mei , Wang Jinzheng
Published: August 2021

The intelligent adaptive cutting of the shearer is one of the key technologies to realize the intelligent working face. However, since the “memory cut” technology is the mainstream technology, which cannot actively adapt to the coal seam variations, the trailing drum usually cuts at a fixed height without a planned cutting path. This paper analyzes the shearer’s location characteristics before and after the advancement to propose a complete calculation method for the advancing path of the shearer, which simulates all of its possible advancing paths for subsequent n cuttings. The multitree and depth‐first search algorithms are utilized to filter out the optimal advance path under different mining requirements. Simultaneously, this paper indicates that the vertical curvature of the armored face conveyor (AFC) should be considered in the calculation process of the optimal advancing path at different positions of the working face to obtain the shearer’s planned cutting path for subsequent n cuttings. The proposed algorithm in this paper has apparent advantages over the “memory cut” technology and provides a good solution for the intelligent planning of cutting and pitch steering of the shearers.
The Top 100 Cited Articles in Osteonecrosis of the Femoral Head: A Bibliometric Analysis
Authors: Zhang Yumin , Wang Yakang , Chen Juan , Cheng Qianyue , Zhang Binfei , Hao Linjie , Ma Tao , Qin Siqing , Song Wei , Wen Pengfei
Published: August 2021

Background. The number of articles of clinical and basic research for osteonecrosis of the femoral head (ONFH) is increasing, yet, to our knowledge, there is still a lack of bibliometric analysis on ONFH articles. The purpose of this study was to identify the top 100 cited (T100) articles related to ONFH research and to analyze the characteristics and qualities of these articles. Methods. The T100 articles on ONFH were retrieved from the Web of Science database. The information about each article including citations, titles, authors, journals, countries, institutions, and keywords was recorded for bibliometric analysis. Results. The T100 articles related to ONFH were mainly published from 1991 to 2010 (n = 70) and were originated from 24 countries. The USA, China, and Japan were the most productive countries in this regard. The most prolific institution was the University of Pennsylvania from the USA with 6 publications and 742 citations. The most cited article was published in 1995 by Professor Steinberg ME. The five most frequently occurring keywords were “femoral head,” “osteonecrosis,” “core decompression,” “total hip arthroplasty,” and “follow up.” The keywords like “bone tissue engineering” and “extracorporeal shock wave” have emerged in recent years. Conclusions. The USA, China, and Japan contributed greatly in terms of the T100 articles. The outcomes of core decompression and total hip arthroplasty gathered the most research interests. In recent years, bone tissue engineering and extracorporeal shock wave have become new trends. However, the mechanism of ONFH is still unclear.
A Study on Axial Compression Performance of Large Diameter‐Thickness Ratio Concrete‐Filled Gas Drainage Steel Pipe
Authors: Liu Zi-Lu , Ma Zhan-Guo , Li Ye , Gong Peng , Li Ke-Long , Liu Wang
Published: August 2021

A large number of gas drainage pipes are obsoleted in the coal mine gas drainage system, and it causes serious waste. If concrete is poured into the discarded gas drainage pipes as components for underground roadway support, it is very significant for sustainable development of mine. Therefore, it is necessary to study the mechanical properties of the concrete‐filled gas drainage steel pipe. Most frequently used gas drainage pipes are spiral welded steel pipe (SSP‐I) and spiral external rib steel pipe (SSP‐II). In this study, three different concrete‐filled steel pipes are taken as the research object: SSP‐I concrete‐filled steel pipes, SSP‐II concrete‐filled steel pipes, and RSP concrete‐filled ordinary round steel pipes. Through the axial compression test, the failure mode and relationship between stress‐strain of concrete‐filled steel pipes were obtained. Subsequently, the ultimate bearing capacity of three types of specimens was calculated based on the unified strength theory, limit equilibrium theory, and superposition theory. The test results show that both the SSP‐I concrete‐filled pipe columns and RSP concrete‐filled pipe have good post‐peak load‐bearing capacity and ductility, and the second peak load reaches 70.38% and 81.92% of the ultimate load, respectively. The load‐bearing capacity of SSP‐II concrete‐filled pipe columns is dropped sharply after bearing ultimate load, and the second peak load reaches only 36.47% of the ultimate load. The failure characteristics of concrete‐filled gas drainage pipe columns show that the core concrete is compressed to powder and explain that the gas drainage pipe has fully exerted its restraint on the concrete. The FE method was used to simulate the compression test of three types of concrete‐filled steel pipes, and the numerical simulation results show good agreement with the experimental results. Theoretical calculations show that the calculation of concrete‐filled gas drainage pipe columns based on the superposition theory EC4‐2004 is the closest to the measured value. Therefore, the EC4‐2004 standard is recommended to calculate the ultimate bearing capacity of concrete‐filled gas drainage pipe columns.
Thinking and Prospect of Power Chip Specificity
Authors: Ma Fuqi , Li Min , DONG Xuzhu , WANG Bo , ZHOU Yinyu , Li Jincan , FENG Lei , Mohamed Mohamed A.
Published: August 2021

The contradiction between the demand of massive intelligent scene caused by the interconnection of things in power system and the bottleneck of the chip itself is becoming more and more serious. How to realize the self-controllable and domestic substitution of power chips has been widely concerned in the power field. Therefore, this paper analyzes the demand for power chips in power system and discusses the scene specificity of power chips. Then, it combs the design architecture of power chips and discusses the application scenarios and research focuses of power chips. Finally, the key scientific problems and major technical bottlenecks of power chips are prospected.
A Systematic Approach to Formal Analysis of QUIC Handshake Protocol Using Symbolic Model Checking
Authors: Zhang Jingjing , Gao Xianming , Yang Lin , Feng Tao , Li Dongyang , Wang Qiang
Published: August 2021

As a newly proposed secure transport protocol, QUIC aims to improve the transport performance of HTTPS traffic and enable rapid deployment and evolution of transport mechanisms. QUIC is currently in the IETF standardization process and will potentially carry a significant portion of Internet traffic in the emerging future. An important safety goal of QUIC protocol is to provide effective data service for users. To aim this safety requirement, we propose a formal analysis method to analyze the safety of QUIC handshake protocol by using model checker SPIN and cryptographic protocol verifier ProVerif. Our analysis shows the counterexamples to safety properties, which reveal a design flaw in the current protocol specification. To this end, we also propose and verify a possible fix that is able to mitigate these flaws.
Injuries in Left Corticospinal Tracts, Forceps Major, and Left Superior Longitudinal Fasciculus (Temporal) as the Quality Indicators for Major Depressive Disorder
Authors: Liu Ziwei , Kang Lijun , Zhang Aixia , Yang Chunxia , Liu Min , Wang Jizhi , Liu Penghong , Zhang Kerang , Sun Ning
Published: August 2021

At present, the etiology and pathogenesis of major depressive disorder (MDD) are still not clear. Studies have found that the risk of first-degree relatives of MDD is 2–3 times that of the general population. Diffusion tensor imaging (DTI) has been previously used to explore the pathogenesis of MDD. The purpose of this study is to explore the etiology of MDD by DTI and further to explore the correlation between its clinical characteristics and the structural changes of white matter in the brain. The study included 27 first-episode, drug-naive patients with MDD, 16 first-degree relatives without MDD, and 28 healthy control subjects with no family history of MDD (HC). Results showed that the fractional anisotropy (FA) differences among the three groups were mainly in the left anterior thalamic radiation (LATR), right anterior thalamic radiation (RATR), left corticospinal tracts (LCST), forceps major (FMa), right inferior longitudinal fasciculus (RILF), and left superior longitudinal fasciculus (temporal) (LSLF(T)). Among the 6 sites, LCST, FMa, and LSLF(T) showed significant differences between MDD and First-degree relatives compared to HC. MDD patients had significant emotional symptoms, somatic symptoms, and cognitive impairment. FMa FA was significantly positively correlated with delayed memory score (

r
=
0.43

,

P
=
0.031

), and RILF FA was significantly negatively correlated with the FSS score (

r
=
−
0.42

,

P
=
0.028

). These results revealed that the white matter characteristics of MDD-susceptible patients were LCST, FMa, and LSLF(T) lesions, all of which may be quality indicators of MDD.
Quantitative Characterization of Heterogeneity in Different Reservoir Spaces of Low‐Permeability Sandstone Reservoirs and Its Influence on Physical Properties
Authors: Dong Fengjuan , Liu Na , Sun Zhen , Wei Xiaolong , Wang Haonan , Nan Junxiang , Ren Dazhong
Published: August 2021

The complex pore structure of low‐permeability sandstone reservoir makes it difficult to characterize the heterogeneity of pore throat. Taking the reservoir of Sanjianfang formation in QL oilfield as an example, the fractal dimension of different storage spaces is calculated by using fractal theory based on casting thin section, scanning electron microscope, and high‐pressure mercury injection, and the correlation between porosity, permeability, and contribution of different storage space permeabilities is analyzed. The results show that the reservoir of Sanjianfang formation in QL oilfield mainly develops small pores, fine pores, and micropores, and the fractal dimension of micropore structure is between 2.6044 and 2.9982, with an average value of 2.8316. The more complex the pore structure is, the stronger the microheterogeneity is. The higher the fractal dimension, the more complex the pore structure and the smaller the porosity and permeability. The fractal dimensions of small pores, fine pores, and micropores increase successively with the decrease in pore radius, and the microstructure heterogeneity of large pores is weaker than that of small pores. It provides a theoretical basis for the exploration and development of low‐permeability sandstone reservoirs.
Nanopore Confinement Effect on the Phase Behavior of CO2/Hydrocarbons in Tight Oil Reservoirs considering Capillary Pressure, Fluid-Wall Interaction, and Molecule Adsorption
Authors: Zheng Zhixue , Di Yuan , Wu Yu-Shu
Published: August 2021

The pore sizes in tight reservoirs are nanopores, where the phase behavior deviates significantly from that of bulk fluids in conventional reservoirs. The phase behavior for fluids in tight reservoirs is essential for a better understanding of the mechanics of fluid flow. A novel methodology is proposed to investigate the phase behavior of carbon dioxide (CO2)/hydrocarbons systems considering nanopore confinement. The phase equilibrium calculation is modified by coupling the Peng-Robinson equation of state (PR-EOS) with capillary pressure, fluid-wall interaction, and molecule adsorption. The proposed model has been validated with CMG-Winprop and experimental results with bulk and confined fluids. Subsequently, one case study for the Bakken tight oil reservoir was performed, and the results show that the reduction in the nanopore size causes noticeable difference in the phase envelope and the bubble point pressure is depressed due to nanopore confinement, which is conductive to enhance oil recovery with a higher possibility of achieving miscibility in miscible gas injection. As the pore size decreases, the interfacial tension (IFT) decreases whereas the capillary pressure increases obviously. Finally, the recovery mechanisms for CO2 injection are investigated in terms of minimum miscibility pressure (MMP), solution gas-oil ratio, oil volume expansion, viscosity reduction, extraction of lighter hydrocarbons, and molecular diffusion. Results indicate that nanopore confinement effect contributes to decrease MMP, which suppresses to 650 psi (65.9% smaller) as the pore size decreases to 2 nm, resulting in the suppression of the resistance of fluid transport. With the nanopore confinement effect, the CO2 solution gas-oil ratio and the oil formation volume factor of the oil increase with the decrease of pore size. In turn, the oil viscosity reduces as the pore size decreases. It indicates that considering the nanopore confinement effect, the amount of gas dissolved into crude oil increases, which will lead to the increase of the oil volume expansion and the decrease of the viscosity of crude oil. Besides, considering nanopore confinement effect seems to have a slightly reduced effect on extraction of lighter hydrocarbons. On the contrary, it causes an increase in the CO2 diffusion coefficient for liquid phase. Generally, the nanopore confinement appears to have a positive effect on the recovery mechanisms for CO2 injection in tight oil reservoirs. The developed novel model could provide a better understanding of confinement effect on the phase behavior of nanoscale porous media in tight reservoirs. The findings of this study can also help for better understanding of a flow mechanism of tight oil reservoirs especially in the case of CO2 injection for enhancing oil recovery.
Artesunate Restrains Maturation of Dendritic Cells and Ameliorates Heart Transplantation-Induced Acute Rejection in Mice through the PERK/ATF4/CHOP Signaling Pathway
Authors: Chen Yuanyang , Zheng Sihao , Wang Zhiwei , Cai Xin , Che Yanjia , Wu Qi , Yuan Shun , Zhong Xiaohan
Published: August 2021

Background. Heart transplantation (HT) is the only effective treatment for end-stage heart failure because it can effectively improve the survival rate and quality of life of patients with heart failure. Artesunate (ART) is an artemisinin derivative, with good water solubility and higher oral bioavailability. The main aim of this study was to determine the role of ART in HT mice. Methods. In animal experiments, mice were divided into the control group, HT group, low ART+HT group, and high ART+HT group. Next, inflammatory cell infiltration, oxidative stress injury, and myocardial cell apoptosis were determined in heart tissue. The proportion of multiple lymphocytes in spleen and lymph nodes was then determined using flow cytometry. In addition, cell experiments were conducted to determine the changes in expression of surface maturation markers of BMDC and changes in intracellular reactive oxygen species after LPS stimulation. Finally, western blot analysis was performed to determine the levels of endoplasmic reticulum stress-related proteins (CHOP/ATF4/PERK). Results. The survival time of mice in the ART treatment group was significantly prolonged and was positively correlated with the dose. In animal experiments, ART significantly reduced inflammatory cell infiltration in heart tissue and the proportion of CD4+CD8+ T cells in spleens and lymph nodes. Moreover, ART treatment lowered the 8-OHdg in hearts and myocardial apoptosis. In cell experiments, ART treatment slowed down the development and maturation of BMDCs by inhibiting the expression of endoplasmic reticulum stress-related proteins. Furthermore, the treatment alleviated the oxidative stress damage of BMDCs. Conclusion. ART can inhibit maturation of dendritic cells through the endoplasmic reticulum stress signaling pathway, thereby alleviating acute rejection in mice after heart transplantation.
Water, Sanitation, and Hygiene Risk Factors on the Prevalence of Diarrhea among Under-Five Children in the Rural Community of Dangila District, Northwest Ethiopia
Authors: Hailu Bizuayehu , Ji-Guo Wu , Hailu Tadesse
Published: August 2021

Background. Under-five diarrhea is one of the major causes of morbidity and mortality in developing countries. Despite the tremendous achievement in reducing child mortality and morbidity in the last two decades, diarrhea is still the major causes of morbidity and mortality in resource-limited countries like Ethiopia due to the absence of clean water and poor sanitation and hygiene. Objective. This study aimed to assess the association of water, sanitation, and hygiene on the prevalence of diarrhea among under-five children in the rural community of Ethiopia. Methods. A cross-sectional study was conducted among randomly selected 419 under-five children from October to December 2021 in Dangila district, Northwest Ethiopia. A structured questionnaire was used to collect sociodemographic, environmental, and behavioral data. Data were entered into Epi Info and analyzed using SPSS software. Descriptive analysis was used to calculate the prevalence of diarrhea. Univariate and multivariate logistic regression were used to compute the association of water, sanitation, and hygiene with diarrhea. Statistical significance was considered if

P
<
0.05

. Results. Among 419 participants, the prevalence of diarrhea was 106 (25.3%). The absence of handwashing habit of children (AOR = 7.70; 95% CI: 2.71–21.79) and caregivers after toilet (AOR = 19.10; 95% CI: 5.46–66.52), absence of latrine (AOR = 3.87; 95% CI: 1.24–12.08), playing with soil (AOR = 8.40; 95% CI: 4.58–36.66), and eating soil (AOR = 6.24; 95% CI: 1.99–19.78) were significantly associated with under-five diarrhea. Children who drink unprotected water were 2.21 times (AOR = 2.21; 95% CI: 0.51–9.69) more exposed to under-five diarrhea than who drink protected water, but it is not statistically significant (

P
=
0.29

). Conclusion. The prevalence of under-five diarrhea is high in Dangila district. The absence of clean water and poor handwashing practice and the absence of latrine are the main factors associated with diarrhea. Therefore, strengthening water, sanitation, and hygiene strategy in the rural community should be prioritized.
Construction on the Degenerate Poly-Frobenius-Euler Polynomials of Complex Variable
Authors: Muhiuddin Ghulam , Khan Waseem Ahmad , Al-Kadi Deena
Published: August 2021

In this paper, we introduce degenerate poly-Frobenius-Euler polynomials and derive some identities of these polynomials. We give some relationships between degenerate poly-Frobenius-Euler polynomials and degenerate Whitney numbers and Stirling numbers of the first kind. Moreover, we define degenerate poly-Frobenius-Euler polynomials of complex variables and then we derive several properties and relations.
Analysis and Classification of Mitigation Tools against Cyberattacks in COVID-19 Era
Authors: Iakovakis George , Xarhoulacos Constantinos-Giovanni , Giovas Konstantinos , Gritzalis Dimitris
Published: August 2021

The COVID-19 outbreak has forced businesses to shift to an unprecedented “work from home” company environment. While this provides advantages for employees and businesses, it also leads to a multitude of shortcomings, most prevalent of which is the emergence of additional security risks. Previous to the outbreak, company computer networks were mainly confined within its facilities. The pandemic has now caused this network to “spread thin,” as the majority of employees work remotely. This has opened up a variety of new vulnerabilities, as workers’ cyber protection is not the same at home as it is in office. Although the effects of the virus are now subsiding, working remotely has embedded itself as the new normal. Thus, it is imperative for company management to take the necessary steps to ensure business continuity and be prepared to deal with an increased number of cyber threats. In our research, we provide a detailed classification for a group of tools which will facilitate risk mitigation and prevention. We also provide a selection of automated tools such as vulnerability scanners, monitoring and logging tools, and antivirus software. We outline each tool using tables, to show useful information such as advantages, disadvantages, scalability, cost, and other characteristics. Additionally, we implement decision trees for each category of tools, in an attempt to assist in navigating the large amount of information presented in this paper. Our objective is to provide a multifaceted taxonomy and analysis of mitigation tools, which will support companies in their endeavor to protect their computer networks. Our contribution can also help companies to have some type of cyber threat intelligence so as to put themselves one step ahead of cyber criminals.
Study on the Influence of In Situ Stress Distribution on the Stability of Roadway Surrounding Rock
Authors: Li Tao , Gong Hao , Xu Guoliang
Published: August 2021

In order to understand the instability characteristics of surrounding rock in the process of deep roadway excavation, a three‐dimensional numerical model was established by FLAC3D to systematically analyze the influence of roadway surrounding rock stability under different in situ stress distribution forms, and the environmental coefficient of mining‐induced stress η was defined, the larger the environmental coefficient of mining‐induced stress is, the larger the surrounding rock stress environment is, and the range where the η coefficient is greater than 0.2 is called with the destruction‐danger zone. When the initial vertical stress is maximum principal stress and minimum principal stress, by comparing the roadway along the middle ground stress direction and minimum or maximum in‐situ stress direction, the variation characteristics of displacement, failure zone and failure hazard zone of roadway surrounding rock are obtained, which provides theoretical basis for the treatment of disaster accidents such as roadway surrounding rock instability and rock burst caused by deep high in‐situ stress.
Experimental and Numerical Study on Air Flow Behavior for a Novel Retractable Reverse Circulation Drill Bit of Casing-while-Drilling (CwD)
Authors: Qi Bo , Cao Pinlu , Yang He , He Wenbo , Wang Mengke , Chen Baoyi , Bo Kun , Zheng Zhichuan
Published: August 2021

A reverse circulation Down-The-Hole (DTH) hammer drill bit in Casing-while-Drilling (CwD) processes is designed and applied to drilling under complicated formation. The drill bit is a special retractable drill bit with an exclusive reverse circulation gas channel. Using numerical simulations and experiments, the influence of the gas channel structure parameters of the drill bit, including the inner jet nozzles, flushing nozzles, suction channel, and other parameters, on its reverse circulation performance is analyzed, and the optimal gas channel structure parameters of the drill bit are determined to improve the reverse circulation effect. The results show that the flushing nozzles and inner jet nozzles have an important influence on entrainment performance. The entrainment rate

η

decreases as the flushing nozzle diameter increases and decreases as the inner jet nozzle diameter increases. An increase in the suction channel diameter can improve the reverse circulation effect of the drill bit. The spiral slot drill bit is more conducive to air being sucked into the central channel in the form of spiral flow, so it can improve the entrainment performance. The entrainment rate

η

can reach 23.4% with the optimum structured drill bit.
Design and Implementation of High‐Skilled Talent Information Management System Based on Multisensor Information Fusion
Authors: Liu Shui
Published: August 2021

With the rapid development of science and technology, the global network and informatization process is changing people’s lives, and it has also brought profound changes to the management of enterprises. Traditional management still relies heavily on offline management and paper delivery of information. The traditional management model in the past cannot meet the needs of the continuous development of enterprises. The purpose of this article is to design a high‐skilled talent information management system to meet the needs of users and enterprises. This paper combines the BP multisensor information fusion algorithm to screen and process the data and designs a multisensor information fusion‐based competency evaluation model for highly skilled talents. A high‐skilled talent information management system has been established with modules such as basic personnel information, skills identification information, high‐skilled talent management, competence, key research teams, common reports, comprehensive query, and system maintenance. In the test of the system’s usability, 156 users rated the system above 3 points, accounting for 78% of the survey population, indicating that the system has a certain ease of use. This system realizes the electronicization of the basic information of skilled personnel, which plays an important role in regulating the professional management of skilled personnel and improving the management efficiency of skilled personnel.
A Fact-Finding Procedure Integrating Machine Learning and AHP Technique to Predict Delayed Diagnosis of Bladder Patients with Hematuria
Authors: Lo Chia-Lun , Yang Ya-Hui , Tseng Hsiao-Ting
Published: August 2021

Bladder cancer, the ninth most common cancer worldwide, requires fast diagnosis and treatment to prevent disease progression and improve patient survival. However, patients with bladder cancer often experience considerable delays in diagnosis. One reason for such delays is that hematuria, a major symptom of bladder cancer, has a high probability of also being a warning sign for urinary tract diseases. Another reason is that the sensitivity of the body parts affected by bladder cancer deters patients from undergoing cystoscopy and influences patients’ “physician shopping” behavior. In this study, the analytic hierarchy process was used to determine critical variables influencing delayed diagnosis; moreover, the variables were used to construct models for predicting delayed diagnosis in patients with hematuria by using several machine learning techniques. Furthermore, the critical variables associated with delayed diagnosis of bladder cancer in patients with hematuria were evaluated using GainRatio technology. The study sample was selected from a population-based database. The model evaluation results indicated that the prediction model established using decision tree algorithms outperformed the other models. The critical risk factors for delayed diagnosis of bladder cancer were as follows: (1) cystoscopy performed 6 months after hematuria diagnosis and (2) physician shopping.