bluuebunny/crossref_metadata_2025 huggingface dataset:
Reflect, not Regret: Understanding Regretful Smartphone Use with App Feature-Level Analysis
Authors: Cho Hyunsung , Choi DaEun , Kim Donghwi , Kang Wan Ju , Choe Eun Kyoung , Lee Sung-Ju
Published: October 2021

Digital intervention tools against problematic smartphone usage help users control their consumption on smartphones, for example, by setting a time limit on an app. However, today's social media apps offer a mix of quasiessential and addictive features in an app (e.g., Instagram has following feeds, recommended feeds, stories, and direct messaging features), which makes it hard to apply a uniform logic for all uses of an app without a nuanced understanding of feature-level usage behaviors. We study when and why people regret using different features of social media apps on smartphones. We examine regretful feature uses in four smartphone social media apps (Facebook, Instagram, YouTube, and KakaoTalk) by utilizing feature usage logs, ESM surveys on regretful use collected for a week, and retrospective interviews from 29 Android users. In determining whether a feature use is regretful, users considered different types of rewards they obtained from using a certain feature (i.e., social, informational, personal interests, and entertainment) as well as alternative rewards they could have gained had they not used the smartphone (e.g., productivity). Depending on the types of rewards and the way rewards are presented to users, probabilities to regret vary across features of the same app. We highlight three patterns of features with different characteristics that lead to regretful use. First, "following"-based features (e.g., Facebook's News Feed and Instagram's Following Posts and Stories) induce habitual checking and quickly deplete rewards from app use. Second, recommendation-based features situated close to actively used features (e.g., Instagram's Suggested Posts adjacent to Search) cause habitual feature tour and sidetracking from the original intention of app use. Third, recommendation-based features with bite-sized contents (e.g., Facebook's Watch Videos) induce using "just a bit more," making people fall into prolonged use. We discuss implications of our findings for how social media apps and intervention tools can be designed to reduce regretful use and how feature-level usage information can strengthen self-reflection and behavior changes.
Co-Designing Personal Health? Multidisciplinary Benefits and Challenges in Informing Diabetes Self-Care Technologies
Authors: Ayobi Amid , Stawarz Katarzyna , Katz Dmitri , Marshall Paul , Yamagata Taku , Santos-Rodriguez Raul , Flach Peter , O'Kane Aisling Ann
Published: October 2021

Co-design is a widely applied design process with well-documented values, including mutual learning and collective creativity. However, the real-world challenges of conducting multidisciplinary co-design research to inform the design of self-care technologies are not well established. We provide a qualitative account of a multidisciplinary project that aimed to co-design machine learning applications for Type 1 Diabetes (T1D) self-management. Through interviews, we identify not only perceived social, technological and strategic benefits of co-design but also organisational, translational and pragmatic design challenges: participants with T1D experienced difficulties in co-designing systems that met their individual self-care needs as part of group activities; HCI and AI researchers described challenges resulting from applying co-design outcomes to data-driven ML work; and industry collaborators highlighted academic data sharing regulations as cross-organisational challenges that can impede co-design efforts. Based on this understanding, we discuss opportunities for supporting multidisciplinary collaborations and aligning individual health needs with collaborative co-design activities.
More than a Modern Day Green Book: Exploring the Online Community of Black Twitter
Authors: Klassen Shamika , Kingsley Sara , McCall Kalyn , Weinberg Joy , Fiesler Casey
Published: October 2021

The Negro Motorist Green Book was a tool used by the Black community to navigate systemic racism throughout the U.S. and around the world. Whether providing its users with safer roads to take or businesses that were welcoming to Black patrons, The Negro Motorist Green Book fostered pride and created a physical network of safe spaces within the Black community. Building a bridge between this artifact which served Black people for thirty years and the current moment, we explore Black Twitter as an online space where the Black community navigates identity, activism, racism, and more. Through interviews with people who engage with Black Twitter, we surface the benefits (such as community building, empowerment, and activism) and challenges (like dealing with racism, appropriation, and outsiders) on the platform, juxtaposing the Green Book as a historical artifact and Black Twitter as its contemporary counterpart. Equipped with these insights, we make suggestions including audience segmentation, privacy controls, and involving historically disenfranchised perspectives into the technological design process. These proposals have implications for the design of technologies that would serve Black communities by amplifying Black voices and bolstering work toward justice.
Dr.Aid: Supporting Data-governance Rule Compliance for Decentralized Collaboration in an Automated Way
Authors: Zhao Rui , Atkinson Malcolm , Papapanagiotou Petros , Magnoni Federica , Fleuriot Jacques
Published: October 2021

Collaboration across institutional boundaries is widespread and increasing today. It depends on federations sharing data that often have governance rules or external regulations restricting their use. However, the handling of data governance rules (aka. data-use policies) remains manual, time-consuming and error-prone, limiting the rate at which collaborations can form and respond to challenges and opportunities, inhibiting citizen science and reducing data providers' trust in compliance. Using an automated system to facilitate compliance handling reduces substantially the time needed for such non-mission work, thereby accelerating collaboration and improving productivity. We present a framework, Dr.Aid, that helps individuals, organisations and federations comply with data rules, using automation to track which rules are applicable as data is passed between processes and as derived data is generated. It encodes data-governance rules using a formal language and performs reasoning on multi-input-multi-output data-flow graphs in decentralised contexts. We test its power and utility by working with users performing cyclone tracking and earthquake modelling to support mitigation and emergency response. We query standard provenance traces to detach Dr.Aid from details of the tools and systems they are using, as these inevitably vary across members of a federation and through time. We evaluate the model in three aspects by encoding real-life data-use policies from diverse fields, showing its capability for real-world usage and its advantages compared with traditional frameworks. We argue that this approach will lead to more agile, more productive and more trustworthy collaborations and show that the approach can be adopted incrementally. This, in-turn, will allow more appropriate data policies to emerge opening up new forms of collaboration.
Why do People Participate in Small Online Communities?
Authors: Hwang Sohyeon , Foote Jeremy D.
Published: October 2021

Many benefits of online communities---such as obtaining new information, opportunities, and social connections---increase with size. Thus, a "successful'' online community often evokes an image of hundreds of thousands of users, and practitioners and researchers alike have sought to devise methods to achieve growth and thereby, success. On the other hand, small online communities exist in droves and many persist in their smallness over time. Turning to the highly popular discussion website Reddit, which is made up of hundreds of thousands of communities, we conducted a qualitative interview study examining how and why people participate in these persistently small communities, in order to understand why these communities exist when popular approaches would assume them to be failures. Drawing from twenty interviews, this paper makes several contributions: we describe how small communities provide unique informational and interactional spaces for participants, who are drawn by the hyperspecific aspects of the community; we find that small communities do not promote strong dyadic interpersonal relationships but rather promote group-based identity; and we highlight how participation in small communities is part of a broader, ongoing strategy to curate participants' online experience. We argue that online communities can be seen as nested niches: parts of an embedded, complex, symbiotic socio-informational ecosystem. We suggest ways that social computing research could benefit from more deliberate considerations of interdependence between diverse scales of online community sizes.
A Human-Centered Systematic Literature Review of the Computational Approaches for Online Sexual Risk Detection
Authors: Razi Afsaneh , Kim Seunghyun , Alsoubai Ashwaq , Stringhini Gianluca , Solorio Thamar , De Choudhury Munmun , Wisniewski Pamela J.
Published: October 2021

In the era of big data and artificial intelligence, online risk detection has become a popular research topic. From detecting online harassment to the sexual predation of youth, the state-of-the-art in computational risk detection has the potential to protect particularly vulnerable populations from online victimization. Yet, this is a high-risk, high-reward endeavor that requires a systematic and human-centered approach to synthesize disparate bodies of research across different application domains, so that we can identify best practices, potential gaps, and set a strategic research agenda for leveraging these approaches in a way that betters society. Therefore, we conducted a comprehensive literature review to analyze 73 peer-reviewed articles on computational approaches utilizing text or meta-data/multimedia for online sexual risk detection. We identified sexual grooming (75%), sex trafficking (12%), and sexual harassment and/or abuse (12%) as the three types of sexual risk detection present in the extant literature. Furthermore, we found that the majority (93%) of this work has focused on identifying sexual predators after-the-fact, rather than taking more nuanced approaches to identify potential victims and problematic patterns that could be used to prevent victimization before it occurs. Many studies rely on public datasets (82%) and third-party annotators (33%) to establish ground truth and train their algorithms. Finally, the majority of this work (78%) mostly focused on algorithmic performance evaluation of their model and rarely (4%) evaluate these systems with real users. Thus, we urge computational risk detection researchers to integrate more human-centered approaches to both developing and evaluating sexual risk detection algorithms to ensure the broader societal impacts of this important work.
Dilemmas in Mutual Aid: Lessons for Crisis Informatics from an Emergent Community Response to the Pandemic
Authors: Soden Robert , Owen Embry
Published: October 2021

In response to the COVID-19 pandemic, networks of community organizers and activists mobilized to support their neighbors as part of mutual aid groups across the United States. Emergent community response is a common phenomenon during crisis, but mutual aid in the pandemic took on a distinct character, drawing on traditions of political and community organizing. Our research into these activities suggests that mutual aid organizing in relation to disaster is growing practice but remains evolving and contested. Drawing on interviews with organizers of mutual aid groups in New York, we identify a series of four dilemmas that mutual aid organizers encountered in their work, with impacts on their organizational strategy and technology choices. We then raise three implications for crisis informatics to support community response to disaster: taking a long view of crises, centering questions of equity, and adopting a transformative vision of emergency response.
Understanding Driver-Passenger Interactions in Vehicular Crowdsensing
Authors: Agarwal Dhruv , Agarwal Srishti , Singh Vidur , Kochupillai Rohita , Pierce-Messick Rosemary , Iyengar Srinivasan , Jain Mohit
Published: October 2021

Smart city projects collect data on urban environments to identify problems, inform policymaking, and boost citizen engagement. Typically, this data is collected by static sensors placed around the city, which is not ideal for spatiotemporal needs of certain sensing applications such as air quality monitoring. Vehicular crowdsensing is an upcoming approach that addresses this problem by utilizing vehicles' mobility to collect fine-grained city-scale data. Prior work has mainly focused on designing vehicular crowdsensing systems and related components, including incentive schemes, vehicle selection, and application-specific sensing, without understanding the motivations and challenges faced by drivers and passengers, one of the two key stakeholders of any vehicular crowdsensing solution. Our work aims to fill this gap. To understand drivers' and passengers' perspectives, we developed Turn2Earn, a generic vehicular crowdsensing system that incentivizes drivers to take specific routes for data collection. Turn2Earn system was deployed with 13 auto-rickshaw drivers for two weeks in Bangalore, India. Our drivers took 709 trips using Turn2Earn covering 79.2% of the city's grid cells. Interviews with 13 drivers and 15 passengers revealed innovative information-based strategies adopted by the drivers to convince passengers in taking alternative routes, and passengers' altruism in supporting the drivers. We uncovered novel insights, including viability of offered routes due to road closure, issues with electric vehicles, and selection bias among the drivers. We conclude with design recommendations to inform the future of vehicular crowdsensing, including engaging and incentivizing passengers, and criticality-based reward structure.
From Theoretical Work to Clinical Translation: Progress in Concentric Tube Robots
Authors: Mitros Zisos , Sadati S.M. Hadi , Henry Ross , Da Cruz Lyndon , Bergeles Christos
Published: October 2021

Continuum robots can traverse anatomical pathways to intervene in regions deep inside the human body. They are able to steer along 3D curves in confined spaces and dexterously handle tissues. Concentric tube robots (CTRs) are continuum robots that comprise a series of precurved elastic tubes that can be translated and rotated with respect to each other to control the shape of the robot and tip pose. CTRs are a rapidly maturing technology that has seen extensive research over the past decade. Today, they are being evaluated as tools for a variety of surgical applications, as they can offer precision and manipulability in tight workspaces. This review provides an exhaustive classification of research on CTRs based on their clinical applications and highlights approaches for modeling, control, design, and sensing. Competing approaches are critically presented, leading to a discussion of future directions to address the limitations of current research and its translation to clinical applications.
Urinary Matrix Metalloproteinase-9 and Nephrin in Idiopathic Membranous Nephropathy: A Cross-Sectional Study
Authors: Gilbert Akankwasa , Changjuan An , Guixue Cheng , Jianhua Liu , Xiaosong Qin
Published: October 2021

Aim. Idiopathic membranous nephropathy (IMN) has a varied clinical course that requires accurate prediction as a prerequisite for treatment administration. Currently, its prognosis relies on proteinuria, a clinical parameter whose onset lags behind kidney injury. Increased urinary excretion of matrix metalloproteinase-9 (MMP-9) and nephrin has been reported in a number of IMN-like glomerular diseases in which they reflected disease severity. However, little or nothing is known of the importance of these biomarkers in IMN, a major cause of adult nephrotic syndrome. To highlight their potential, we measured both biomarkers and assessed their relationships with key parameters of renal function in IMN. Methods. We quantified urinary MMP-9 and nephrin in 107 biopsy-proven IMN patients and 70 healthy subjects by enzyme-linked immunosorbent assay (ELISA). We then compared biomarker levels between patients and healthy subjects and among patients with different clinical features. We also determined the relationship of each biomarker with proteinuria and the estimated glomerular filtration rate (eGFR). Results. Urinary MMP-9 and nephrin were significantly higher in IMN compared to healthy controls. Unlike nephrin, MMP-9 correlated significantly with proteinuria and was significantly higher among patients with nephrotic range proteinuria. Both biomarkers were correlated with eGFR, but only MMP-9 was significantly higher in patients with eGFR less than 90 ml/min/1.73 m2. Conclusion. Our findings suggest that urinary MMP-9 holds a greater potential than urinary nephrin in monitoring the severity of IMN.
Embedded Microprocessor Wireless Communication Data Collection Aids in Early Warning of Default Risk for Internet Finance Bank Customers
Authors: Li Hui
Published: October 2021

Thanks to the maturity and innovation of embedded technology, products based on embedded platforms continue to penetrate people’s lives and play a pivotal role in various fields of society, while the development of data acquisition systems based on wireless communication of embedded microprocessors is one of the frontier directions of embedded development. Modern commercial bank risk management system includes risk control organization, risk measurement techniques (including risk warning), risk avoidance techniques, and total risk management model. In this paper, a multichannel data acquisition system combined with a wireless sensor platform is designed for early warning of default risk of Internet financial bank customers, which can realize real‐time monitoring, acquisition, display, and data storage of DC signals and indoor environment information output from sensor platforms or electronic devices, and for frequent transactions, fund splitting, and mortgage pledging related to complex customers in today’s e‐commerce platform, which triggers when the associated enterprise credit risk presents complexity, continuity, wholeness, multiplicity, volatility, severity, etc., it is used to improve risk judgment and risk warning ability, enhance investment risk response ability, and reduce the related losses caused by marketing risk.
Optimal Administrative Response to Selfish Behaviors in Urban Public Management: The Role of Zero-Determinant Strategies
Authors: Shen Ai Zhong , Gao Xiang , Wang Xiao Ping
Published: October 2021

City management involves complex interactions between the manager (administrator), who supervises urban appearance and environmental sanitation, and the managed (speculator), who works in urban areas and is subject to management ordinances. This article provides an iterated game framework for analyzing the extent to which zero-determinant strategies can be used to optimize the intensity decision of supervisory action against municipal code violations, thus enhancing administrative efficiency. To account for characteristics of the public affairs context, it is assumed that each player in our model chooses from a finite set of discrete and random courses of game strategy. As our model constitutes a major extension to the seminal Press and Dyson (2012) model, we resort to the theory of stochastic process to prove the existence of multiple zero-determinant strategies when players can adopt many strategies in the iterated game. Various numerical examples are presented to validate such strategies’ optimality. Our finding is that, given the probability of adopting a particular strategy, an urban administrator can unilaterally (i) set the speculators’ expected payoff to a level equaling to the opportunity cost of abiding by the law and (ii) let their own expected surplus payoff exceed the speculators. Finally, important policy implications can be derived based on these analyses and conclusions.
[Retracted] Periodontitis Exacerbates Benign Prostatic Hyperplasia through Regulation of Oxidative Stress and Inflammation
Authors: Fang Cheng , Wu Lan , Zhao Ming-Juan , Deng Tong , Gu Jia-Min , Guo Xing-Pei , Li Cheng , Li Weiguang , Zeng Xian-Tao
Published: October 2021

Epidemiological studies demonstrate that men with periodontitis are also susceptible to benign prostatic hyperplasia (BPH) and that periodontal treatment can improve the prostatic symptom. However, molecular links of this relationship are largely unknown. The goal of the current study was to elucidate the effects of experimental periodontitis on the hyperplasia of prostate and whether oxidative stress and inflammation participated in this process. For this purpose, ligature‐induced periodontitis, testosterone‐induced BPH, and the composite models in rats were established. Four weeks later, all the rats were sacrificed and the following items were measured: alveolar bone loss and histological examination of periodontal tissues were taken to assess the establishment of periodontitis model, prostate index and histological examination of prostate tissues were taken to test the establishment of the BPH model, inflammatory cytokines in plasma were assessed, and Bax/Bcl‐2 proteins related to cell apoptosis were analyzed via western blot analysis. To further investigate whether oxidative stress participates in the aggravation of BPH, in vitro models were also conducted to measure the production of intracellular reactive oxygen species (ROS) and hydrogen peroxide (H2O2) concentration. We found that simultaneous periodontitis and BPH synergistically aggravated prostate histological changes, significantly increased Ki67 proliferation, and reduced apoptosis in rat prostate tissues. Also, our results showed that periodontal ligation induced increased Bcl‐2 protein expression, whereas Bax expression was decreased in BPH rats than in normal rats. Compared with the control group, periodontitis and BPH both significantly enhanced inflammatory cytokine levels of TNF‐α, IL‐6, IL‐1β, and CRP. Furthermore, Porphyromonas gingivalis lipopolysaccharide induced enhanced generation of intracellular expression of ROS and H2O2 in BPH‐1 cells. Our experimental evidence demonstrated that periodontitis might promote BPH development through regulation of oxidative stress and inflammatory process, thus providing new strategies for prevention and treatment of BPH.
System Dynamics Modelling for Dynamic Emergency Response to Accidents Involving Transport of Dangerous Goods by Road
Authors: Zhang Guo-sheng , Shen Xiao-yan , Hua Jun , Zhao Jun-wei , Liu Hao-xue
Published: October 2021

For improving the emergency capacities during road transportation accidents of dangerous goods, this paper divides the accident emergency procedure into four subsystems: accident information processing, personnel rescue and evacuation, vehicle evacuation, and rescue materials delivery. On this basis, the causal mechanism and the loop diagrams of the emergency process are established by using the System Dynamics Method and Vensim software. First, six factors including transportation distance, the degree of mechanical modernization, delay time of personnel control, delay time of traffic information release, command level coefficient, and delay time of department arrival are selected as parameters to test the model’s sensitivity analysis. Then, the influences of the abovementioned factors on the observed value, such as the demand gap of on-site materials, number of people in safe area, number of vehicles in safe area, amount of disposal information, and the dynamic evolution behavior of the system, are analyzed. The results show that the transportation distance is shortened by half, and the time to fill the demand gap is reduced by 39%. The level of mechanical modernization is doubled, the peak inventory of materials in transit will increase by 9.2%, and the time to reach the peak will be shortened by 6.8%. If the delay time of personnel control is shortened by 480 s, the number of people to be evacuated in accident area will be reduced by 56. The delay time of traffic information release is shortened by 480 s, the number of vehicles to be evacuated is reduced by 74, and the time when the vehicle stops entering accident area is 1646 s in advance. The command level coefficient increases by 9.5%, and the speed of action execution increases by 9.6%.
Path Planning Method for Electric Vehicles Based on Freeway Network
Authors: Liu Qichao , Wang Wei , Hua Xuedong
Published: October 2021

Recently, electric vehicles (EVs) have received more and more attention, but the problem of the insufficient range is still the main reason that hinders electric vehicles to travel long distances. Under the premise of the battery capacity without technological innovation, the path planning method can ensure the safety and efficiency of electric vehicles in long-distance travel. This paper studies the actual freeway network to optimize the vehicle driving path and give the charging strategy based on the shortest travel time of a single vehicle. In this paper, a path and charging strategy planning model is proposed. In this model, the shortest travel time of a single vehicle is taken as the objective function, and the state of charging equipment in the actual road network and the safe electric quantity are considered as constraints. And the genetic algorithm is used to solve the model. Through case analysis, the rationality and optimization efficiency of the model proposed in this paper are verified. Finally, the sensitivity analysis of the three parameters of traffic volume, temperature, and travel speed is carried out with the Shanghai-Nanjing freeway network. The experimental results can get the nodes with the highest service pressure in the network, which can provide a theoretical basis for charging nodes’ expansion in the freeway network in the future.
[Retracted] Optimization of Personnel Placement Scheme and Big Data Analysis Based on Multilayer Variable Neural Network Algorithm
Authors: Li Haiqiu
Published: October 2021

People usually use the method of job analysis to understand the requirements of each job in terms of personnel characteristics, at the same time use the method of psychological measurement to understand the psychological characteristics of each person, and then put the personnel in the appropriate position by matching them with each other. With the development of the information age, massive and complex data are produced. How to accurately extract the effective data needed by the industry from the big data is a very arduous task. In reality, personnel data are influenced by many factors, and the time series formed by it is more accidental and random and often has multilevel and multiscale characteristics. How to use a certain algorithm or data processing technology to effectively dig out the rules contained in the personnel information data and explore the personnel placement scheme has become an important issue. In this paper, a multilayer variable neural network model for complex big data feature learning is established to optimize the staffing scheme. At the same time, the learning model is extended from vector space to tensor space. The parameters of neural network are inversed by high‐order backpropagation algorithm facing tensor space. Compared with the traditional multilayer neural network calculation model based on tensor space, the multimodal neural network calculation model can learn the characteristics of complex data quickly and accurately and has obvious advantages.
Thermal and Residual Stress Distributions in Inconel 625 Butt‐Welded Plates: Simulation and Experimental Validation
Authors: Vemanaboina Harinadh , Gundabattini Edison , Kumar Kaushik , Ferro Paolo , Sridhar Babu B
Published: October 2021

Thermal and residual stress distributions induced by the gas tungsten arc welding (GTAW) process on Inconel 625 were studied using numerical simulation and experiments. A multi‐pass welding model was developed that uses a volumetric heat source. Thermomechanical analysis is carried out to assess the Thermal and residual stress distributions. Experiments were carried out with 5 mm thick Inconel 625 plates. X‐ray diffraction techniques were used to measure residual stresses, and IR thermometry was employed to capture the temperature values on the welded joints. Simulations were performed with ANSYS numerical code, and a close agreement was found between the predicted and experimentally measured residual stress. Thermal measurements were collected pass by pass from the analysis, and the agreement was 9.08%. The agreement between the measured and analysed residual stress was 11%.
Optimal Allocation of Vaccine and Antiviral Drugs for Influenza Containment over Delayed Multiscale Epidemic Model considering Time-Dependent Transmission Rate
Authors: Abbasi Zohreh , Zamani Iman , Amiri Mehra Amir Hossein , Ibeas Asier , Shafieirad Mohsen
Published: October 2021

In this study, two types of epidemiological models called “within host” and “between hosts” have been studied. The within-host model represents the innate immune response, and the between-hosts model signifies the SEIR (susceptible, exposed, infected, and recovered) epidemic model. The major contribution of this paper is to break the chain of infectious disease transmission by reducing the number of susceptible and infected people via transferring them to the recovered people group with vaccination and antiviral treatment, respectively. Both transfers are considered with time delay. In the first step, optimal control theory is applied to calculate the optimal final time to control the disease within a host’s body with a cost function. To this end, the vaccination that represents the effort that converts healthy cells into resistant-to-infection cells in the susceptible individual’s body is used as the first control input to vaccinate the susceptible individual against the disease. Moreover, the next control input (antiviral treatment) is applied to eradicate the concentrations of the virus and convert healthy cells into resistant-to-infection cells simultaneously in the infected person’s body to treat the infected individual. The calculated optimal time in the first step is considered as the delay of vaccination and antiviral treatment in the SEIR dynamic model. Using Pontryagin’s maximum principle in the second step, an optimal control strategy is also applied to an SEIR mathematical model with a nonlinear transmission rate and time delay, which is computed as optimal time in the first step. Numerical results are consistent with the analytical ones and corroborate our theoretical results.
An Automatic Classification Method of Sports Teaching Video Using Support Vector Machine
Authors: Min-qing Zhang , Wen-ping Li
Published: October 2021

There are many different types of sports training films, and categorizing them can be difficult. As a result, this research introduces an autonomous video content classification system that makes managing large amounts of video data easier. This research provides a video feature extraction approach using a support vector machine (SVM) video classification algorithm and a mix of video and audio dual-mode characteristics. It automates the classification of cartoons, ads, music, news, and sports videos, as well as the detection of terrorist and violent moments in films. To begin, a new feature expression scheme, the MPEG-7 visual descriptor subcombination, is proposed based on an analysis of the existing video classification algorithms, with the goal of addressing the problems in these algorithms. This is accomplished by analyzing the visual differences of the five video classification algorithms. The model was able to extract 9 descriptors from the four characteristics of color, texture, shape, and motion, resulting in a new overall visual feature with good results. The results suggest that the algorithm optimizes video segmentation by highlighting disparities in feature selection between different categories of films. Second, the support vector machine’s multivideo classification performance is improved by the enhanced secondary prediction method. Finally, a comparison experiment with current related similar algorithms was conducted. The suggested method outperformed the competition in the accuracy of video classification in five different types of videos, as well as in the recognition of terrorist and violent incidents.
Anesthesia, Sedation, and Unplanned Extubation of Tracheal Intubation in Children with Severe Pneumonia
Authors: Wang Zengchun , Chen Qiang , Yu Lingshan , Huang Yu , Cao Hua
Published: October 2021

We randomly divided 200 children with severe pneumonia who met the indications for tracheal intubation into 2 groups in this prospective study. One group that received dexmedetomidine for sedation was recorded as the dexmedetomidine group (n = 100), and the group that received midazolam for sedation was recorded as the midazolam group (n = 100). We compared the anesthesia sedation scores, time to fall asleep, time to wake up from anesthesia, related hemodynamic parameters, and adverse reactions between the two groups of children. The failure mode and effect analysis method (FMEA) was also used to investigate the causes of unplanned extubation (UEX) of tracheal intubation in 32 children with severe pneumonia. Our conclusion is as follows: (1) Compared with midazolam, the comprehensive effect of dexmedetomidine on children with severe pneumonia undergoing tracheal intubation for anesthesia and sedation is better, it can effectively shorten the anesthesia induction time and the recovery time after stopping the drug, and there are few adverse reactions, which is worthy of application and promotion. (2) UEX is an important risk factor in the monitoring and nursing of children with severe pneumonia tracheal intubation, and the nursing method of PDCA cycle management is particularly important for them.
Research on Prediction Model of Prestress Loss of Anchor Cable in Soil‐Rock Dual‐Structure Slope
Authors: Gao Xuhe , Tian Weiping , Li Jiachun , Qi Hongliang , Zhang Zhipei
Published: October 2021

The establishment of the prestressed cable loss prediction model is a difficult problem faced by the popularization and use. This article aims at the problem of the loss of anchor cable prestress over time in the soil‐rock dual‐structure slope. We relied on the soil‐rock dual‐structure slope treatment project of section K5 + 220‐K5 + 770 of Jiangwen Expressway and monitored the prestress loss of the anchor cable in the slope through the anchor cable meter with built‐in vibrating wire sensor. Using regression analysis and segmented modelling methods, we established a comprehensive mathematical improvement model, analyzed the applicability of the improved model, and obtained the error range, 0.04%–8.9%. This work offers a new approach for predicting anchor cable prestress loss, which has certain practical value for the use of prestressed anchor cables.
Serial Combination Optimization Method of Packet Transport Network
Authors: Wang Chunzhi , Wang Zaoning , Li Xing , Guan Sha , Wang Ruoxi
Published: October 2021

Packet transport network (PTN) has problems such as waste of resources and low network stability due to the excessive complexity of the existing network or improper network architecture design. The optimization of the transport networks can not only make the network structure more reasonable but also reduce all kinds of unexpected scenarios in the network operation, improving the network efficiency and reducing the failure rate. This research will be optimized from three aspects. (1) In order to solve the problem of the same active and standby routing in the existing network, an optimization algorithm for the same active and standby routing of LSP is proposed. The essence of the optimization algorithm is to search the existing routing using the K‐shortest path (KSP) between two network nodes as protection routing for LSP protection. (2) Aiming at the link with a high CIR bandwidth occupancy rate, a method is completed without adding optical fibers and other physical resources; an optimization method for the committed information rate bandwidth occupancy rate based on the KSP algorithm is proposed. (3) When the PTN ring formation rate is low, the security of the PTN is seriously reduced. In order to solve the problem of low ring formation rate in the network, this paper proposes a ring formation rate optimization scheme for PTN access layer equipment based on network elements accounting income. Through the experimental verification on the mobile PTN in one city, Hubei Province, the combination optimization method can improve the network LSP protection rate by 24%, the CIR bandwidth occupancy rate is reduced by 13.82%, and the nonring forming rate was reduced by 17.9%. This method improved network stability, reducing the risk of failure in service transportation effectively.
Sun Toughness Conditions forP2andP3Factor Uniform and Factor Critical Avoidable Graphs
Authors: Gong Shu , Baskonus Haci Mehmet , Gao Wei
Published: October 2021

The security of a network is closely related to the structure of the network graph. The denser the network graph structure is, the better it can resist attacks. Toughness and isolated toughness are used to characterize the vulnerable programs of the network which have been paid attention from mathematics and computer scholars. On this basis, considering the particularity of the sun component structures, sun toughness was introduced in mathematics and applied to computer networks. From the perspective of modern graph theory, this paper presents the sun toughness conditions of the path factor uniform graph and the path factor critical avoidable graph inP≥2-factor andP≥3-factor settings. Furthermore, examples show that the given boundaries are sharp.
A Case Report of Improved Palmoplantar Pustulosis following Periodontal Treatment and Possible Association with Diminished Systemic Subclinical Inflammation
Authors: Yamashita Akiko , Sano Tomomi , Iwashita Misaki , Nishimura Fusanori
Published: October 2021

Palmoplantar pustulosis (PPP) is a recurrent pustular dermatosis located on the palms and soles. Focal infection may exacerbate the symptoms of PPP, but the etiology is not fully clear. A 56-year-old woman with PPP was diagnosed with severe chronic periodontitis. Initial treatment for periodontitis combined with topical application of antibiotics and surgical treatment was performed. In this case, attention was paid to the relevance of systemic inflammation caused by periodontitis with the clinical symptoms of PPP. With periodontal treatment, the symptoms of PPP and periodontitis, high-sensitivity C-reactive protein (hs-CRP) level, and periodontal inflamed surface area (PISA) improved. This case highlights the importance of comprehensive dental examinations, including those for oral infections, such as periodontitis and other unrecognized sources of infection, and dental treatment in the overall management of PPP.
Effect of Melatonin Administration on Mitochondrial Activity and Oxidative Stress Markers in Patients with Parkinson’s Disease
Authors: Jiménez-Delgado Alicia , Ortiz Genaro Gabriel , Delgado-Lara Daniela L. , González-Usigli Hector Alberto , González-Ortiz Luis Javier , Cid-Hernández Margarita , Cruz-Serrano José Antonio , Pacheco-Moisés Fermín Paul
Published: October 2021

Mitochondrial dysfunction and oxidative stress are extensively linked to Parkinson’s disease (PD) pathogenesis. Melatonin is a pleiotropic molecule with antioxidant and neuroprotective effects. The aim of this study was to evaluate the effect of melatonin on oxidative stress markers, mitochondrial complex 1 activity, and mitochondrial respiratory control ratio in patients with PD. A double‐blind, cross‐over, placebo‐controlled randomized clinical trial study was conducted in 26 patients who received either 25 mg of melatonin or placebo at noon and 30 min before bedtime for three months. At the end of the trial, in patients who received melatonin, we detected a significant diminution of lipoperoxides, nitric oxide metabolites, and carbonyl groups in plasma samples from PD patients compared with the placebo group. Conversely, catalase activity was increased significantly in comparison with the placebo group. Compared with the placebo group, the melatonin group showed significant increases of mitochondrial complex 1 activity and respiratory control ratio. The fluidity of the membranes was similar in the melatonin group and the placebo group at baseline and after three months of treatment. In conclusion, melatonin administration was effective in reducing the levels of oxidative stress markers and restoring the rate of complex I activity and respiratory control ratio without modifying membrane fluidity. This suggests that melatonin could play a role in the treatment of PD.
Prediction and Risk Factors for Prognosis of Cirrhotic Patients with Hepatic Encephalopathy
Authors: Peng Ying , Wei Qinglin , Liu Yun , Wu Zhenyu , Zhang Hongjia , Wu Hongbo , Chai Jin
Published: October 2021

Background and Aims. Hepatic encephalopathy (HE) is characterized by recurrence and poor quality of life. Acute-on-chronic liver failure (ACLF) mainly occurs in patients with chronic liver diseases and often presents with HE. Several predictive models have been proposed to predict the outcomes of these patients. Our study is aimed at identifying associated risk factors and the prognostic accuracies of predictive models in HE patients with or without ACLF. Methods. Patients with liver cirrhosis were retrospectively enrolled. Risk factors were evaluated by multivariate regression analyses. The predictive capabilities of models were calculated using the receiver operating characteristic (ROC) curve analyses and compared by the DeLong tests. Outcomes were defined as in-hospital mortality, HE severity, and ACLF occurrence. Results. In multivariate regression analyses, serum biomarkers neutrophil and total bilirubin (TBIL) were independently correlated with in-hospital death. Alanine aminotransferase (ALT) and blood urea nitrogen (BUN) were independent serum biomarkers associated with HE severity. Hemoglobin, TBIL, BUN, and international normalized ratio (INR) were significant indicators associated with ACLF incidence. For prediction of in-hospital mortality, Child-Pugh was superior to the others in the whole patients, while NLR showed the best capability in the ACLF group. Conclusion. In cirrhotic patients present with HE, BUN is a risk factor associated with HE severity and ACLF incidence. Child-Pugh and NLR scores may be effective prognosticators in patients with HE.
pKAS: A Secure Password-Based Key Agreement Scheme for the Edge Cloud
Authors: Liu Ping , Shirazi Syed Hamad , Liu Wei , Xie Yong
Published: October 2021

For the simplicity and feasibility, password-based authentication and key agreement scheme has gradually become a popular way to protect network security. In order to achieve mutual authentication between users and edge cloud servers during data collection, password-based key agreement scheme has attracted much attention from researchers and users. However, security and simplicity are a contradiction, which is one of the biggest difficulties in designing a password-based key agreement scheme. Aimed to provide secure and efficient key agreement schemes for data collecting in edge cloud, we propose an efficient and secure key agreement in this paper. Our proposed scheme is proved by rigorous security proof, and the proposed scheme can be protected from various attacks. By comparing with other similar password-based key agreement schemes, our proposed scheme has lower computational and communication costs and has higher security.
Research of Surrogate Measure for Freeway Crashes Based on Tire Skid Marks
Authors: Ma Yan , Huang Wenjing , Tian Zong , Li Donghong , Cai Hongzhou , Su Jie
Published: October 2021

Traditional approaches to evaluating and predicting safety issues in traffic systems are via crash records. However, considering the characteristics of scarcity, inconsistency, inaccuracy, and incompleteness of crash records, conclusions and recommendations drawn purely based on crashes have limitations. Tire skid marks are considered an indication of some safety hazards, and it could have good potential to be used as surrogates for crashes. By collecting and analyzing the data based on selected arterial and freeway segments in the Reno-Sparks area in northern Nevada, a methodology was developed to categorize different tire skid marks. Sliding window and linear regression techniques were applied to determine any correlation between tire skid marks and crashes. The analyses indicated that there was a relatively strong linear correlation between skid marks and crashes on freeway segments.
[Retracted] Construction and Simulation of Injury Early Warning Model for Retired Athletes Based on Improved Self‐organizing Neural Network
Authors: Li Deli
Published: October 2021

With the progress of sci‐tech, the interdisciplinary and comprehensive development, and various advanced sci‐tech gradually integrated into the field of sports, it has become possible to study how to reasonably prevent sports injuries, minimize the risk of sports injuries, and maintain the best physical condition of retired athletes. Due to the long‐term high‐load exercise of retired athletes during their sports career, athletes’ physical functions have been damaged to varying degrees, resulting in more injuries. According to the characteristics that many factors need to be considered in the prediction of retired athletes’ injuries, this paper puts forward an improved self‐organizing neural network (SOM) method to predict retired athletes’ injuries. In this paper, an early warning analysis model of retired athletes’ susceptibility to injury based on SOM is proposed, which screens the state of retired athletes’ physical function variables in each stage, considers athletes’ physical function data whose standard deviation is higher than the limit specification of susceptibility to injury as susceptible injury data, quickly judges all vulnerable injury data, and completes the high‐speed early warning analysis of retired athletes’ susceptibility to injury.
Lightweight Design of Solar UAV Wing Structures Based on Sandwich Equivalent Theory
Authors: Liu Hongjun , Zhou Dong , Shen Bing , Ding You
Published: October 2021

In this paper, an equivalent method based on sandwich plate is deduced, and the equivalent parameters of the honeycomb plate are obtained. With these equivalent parameters, the honeycomb plate equivalent FEM simulation model and actual model are established, and three-point bending simulations of the equivalent model and the actual model three-point are completed. Then, a three-point bending test of a real honeycomb sandwich panel was performed for comparison with the simulation result, which agrees well with the test result and shows the effectiveness of the equivalent model. The equivalent model of honeycomb sandwich plate win ribs is established for structural topology optimization and wing static simulation analysis, and a prototype of the solar UAV is made for flight testing according to the topology optimization results. The simulation and prototype test results indicated that the sandwich equivalent theory is suitable for the lightweight design of solar UAV wing structures with honeycomb sandwich plate materials, and this method can provide a reference for the same type of wing structure design.
A Hybrid Power Mean Involving the Dedekind Sums and Cubic Gauss Sums
Authors: Hu Jiayuan , Zhan Yu , Si Qin
Published: October 2021

The main purpose of this paper is using analytic methods and the properties of the Dedekind sums to study one kind hybrid power mean calculating problem involving the Dedekind sums and cubic Gauss sum and give some interesting calculating formulae for it.