bluuebunny/crossref_metadata_2025 huggingface dataset:
Instagram of Rivers: Facilitating Distributed Collaboration in Hyperlocal Citizen Science
Authors: Gupta Srishti , Jablonski Julia , Tsai Chun-Hua , Carroll John M.
Published: April 2022

Citizen science project leaders collecting field data in a hyperlocal community often face common socio-technical challenges, which can potentially be addressed by sharing innovations across different groups through peer-to-peer collaboration. However, most citizen science groups practice in isolation, and end up re-inventing the wheel when it comes to addressing these common challenges. This study seeks to investigate distributed collaboration between different water monitoring citizen science groups. We discovered a unique social network application called Water Reporter that mediated distributed collaboration by creating more visibility and transparency between groups using the app. We interviewed 8 citizen science project leaders who were users of this app, and 6 other citizen science project leaders to understand how distributed collaboration mediated by this app differed from collaborative practices of Non Water Reporter users. We found that distributed collaboration was an important goal for both user groups, however, the tasks that support these collaboration activities differed for the two user groups.
Interpersonal Conflicts During Code Review
Authors: Wurzel Gonçalves Pavlína , Çalikli Gül , Bacchelli Alberto
Published: April 2022

Code review consists of manual inspection, discussion, and judgment of source code by developers other than the code's author. Due to discussions around competing ideas and group decision-making processes, interpersonal conflicts during code reviews are expected. This study systematically investigates how developers perceive code review conflicts and addresses interpersonal conflicts during code reviews as a theoretical construct. Through the thematic analysis of interviews conducted with 22 developers, we confirm that conflicts during code reviews are commonplace, anticipated and seen as normal by developers. Even though conflicts do happen and carry a negative impact for the review, conflicts-if resolved constructively-can also create value and bring improvement. Moreover, the analysis provided insights on how strongly conflicts during code review and its context (i.e., code, developer, team, organization) are intertwined. Finally, there are aspects specific to code review conflicts that call for the research and application of customized conflict resolution and management techniques, some of which are discussed in this paper. Preprint: https://arxiv.org/abs/2201.05425 Data and material: https://doi.org/10.5281/zenodo.5848794
Non-literal Communication in Chinese Internet Spaces: A Case Study of Fishing
Authors: Tian Huixin , Ma Xinyao , Bardzell Jeffrey , Patil Sameer
Published: April 2022

In Chinese Internet spaces, "fishing" is a form of non-literal communication that tries to lure or bait others. We conducted a case study of fishing on a Chinese Q&A platform in which we deconstructed the linguistic structure of the fishing language and identified its features by employing analysis techniques informed by Critical Discourse Analysis (CDA). Additionally, we examined the relationship between fishing practices and the specifics of the underlying communication platform. We found that fishing can be characterized as a reaction to rigid norms of politeness and friendliness imposed on users by platform owners. Our analysis reveals that fishing is organically connected with other social interaction within the community and facilitates autonomous and active negotiation of boundaries and linguistic norms for online discussion of controversial topics. We challenge the characterization of non-literal communication as "abnormal," and contribute a more refined understanding of online linguistic norms, community cohesion, and civil engagement.
Power Dynamics and Value Conflicts in Designing and Maintaining Socio-Technical Algorithmic Processes
Authors: Park Joon Sung , Karahalios Karrie , Salehi Niloufar , Eslami Motahhare
Published: April 2022

How do power dynamics and value conflicts affect our ability to design and maintain socio-technical algorithmic processes? In this paper, we study the SIGCHI student volunteer (SV) selection process that uses a weighted semi-randomized algorithm to recruit a desired pool of volunteers. Our interviews with the community members showed that the process is complex and socio-technical; the algorithm's outputs are interpreted and adjusted by the conference organizers to reflect the community values while ensuring the selection of effective volunteers to help with organizing the conference. This provides a stage in which the power dynamics and value conflicts among the stakeholders play salient roles in determining how the process was perceived and envisioned. For instance, non-organizers of the conference found the algorithm used in the selection process to be a power-balancer that places a check on the organizers who oversee the process. However, even with a participatory process to elicit the algorithm's weights, the power dynamics and value conflicts between the participants made it difficult to reach a consensus on what the SV selection process should consider and prioritize. Our findings highlight the importance of value transparency -- the type of transparency that focuses on explaining why a decision was made rather than how it was made -- as a mechanism for resolving such conflicts. Based on our findings, we lay out design recommendations that can guide communities to better design and maintain algorithmic socio-technical processes over time in the face of power dynamics and value conflicts.
Practicing Moderation: Community Moderation as Reflective Practice
Authors: Cullen Amanda L. L. , Kairam Sanjay R.
Published: April 2022

Many types of online communities rely on volunteer moderators to manage the community and maintain behavioral standards. While prior work has shown that community moderators often develop a deep understanding of the goals of their moderation context and sophisticated processes for managing disruptions,less is known about the processes through which moderators develop this knowledge. In this paper, we leverage Donald Schön's concept of reflective practice as a lens for exploring how community moderators develop the 'knowledge-in-action' that they use to perform their work. Drawing on interviews with 18 Twitch moderators, we conceptualize moderators as reflective practitioners, iteratively encountering novel situations and adjusting their practices and mental models. Our findings provide detailed insight into how community moderators reflect-in-action, re-evaluating in real-time their mental models of viewer intent and community goals, and reflect-on-action, conducting post hoc assessments of individual incidents and long-term changes to adjust their practice over time. Moderators working in teams reveal specific aspects of reflection facilitated by cooperative discussion, which we call 'groupwise reflective practice'. By identifying community moderation as a form of reflective practice, we can leverage insights gained from studying practitioners in other fields,providing theoretical and practical implications for the study and support of community moderation.
The Work of Infrastructural Bricoleurs in Building Civic Data Dashboards
Authors: Peer Firaz , DiSalvo Carl
Published: April 2022

The Historic Westside Universities Alliance Data Dashboard was created to meet the data equity needs of a group of resource-constrained communities in the Westside neighborhoods of Atlanta. We observed the development of this dashboard by participating as ethnographers and developers of its public safety module. Our ethnography and subsequent situational analysis of the dashboard's infrastructuring process led us to the work that individual stakeholders do in bringing such a dashboard to fruition. These stakeholders, whom we call infrastructural bricoleurs, operate through principles of situated knowledge, partial perspectives, limited power, and located accountability. Our analysis, which builds on concepts of infrastructures, bricolage, and feminist principles of technology design, helps us add further specificity to the work that infrastructural bricoleurs need to do when building civic data dashboards with resource constrained communities. Our findings benefit other researchers studying data infrastructures as well as administrators and practitioners within programs like DSSG (Data Science for Social Good) who are interested in building data infrastructures under similar constraints.
True or False: Studying the Work Practices of Professional Fact-Checkers
Authors: Micallef Nicholas , Armacost Vivienne , Memon Nasir , Patil Sameer
Published: April 2022

Misinformation has developed into a critical societal threat that can lead to disastrous societal consequences. Although fact-checking plays a key role in combating misinformation, relatively little research has empirically investigated work practices of professional fact-checkers. To address this gap, we conducted semi-structured interviews with 21 fact-checkers from 19 countries. The participants reported being inundated with information that needs filtering and prioritizing prior to fact-checking. The interviews surfaced a pipeline of practices fragmented across disparate tools that lack integration. Importantly, fact-checkers lack effective mechanisms for disseminating the outcomes of their efforts which prevents their work from fully achieving its potential impact. We found that the largely manual and labor intensive nature of current fact-checking practices is a barrier to scale. We apply these findings to propose a number of suggestions that can improve the effectiveness, efficiency, scale, and reach of fact-checking work and its outcomes.
Coarse-to-Fine Output Predictions for Efficient Decoding in Neural Machine Translation
Authors: Chen Qi , Kwong Oi Yee , Li Yinqiao , Xiao Tong , Zhu Jingbo
Published: April 2022

Neural Machine Translation (NMT) systems are undesirably slow as the decoder often has to compute probability distributions over large target vocabularies. In this work, we propose a coarse-to-fine approach to reduce the complexity of the decoding process, using only the information of the weight matrix in the Softmax layer. The large target vocabulary is first trimmed to a small candidate set in the coarse-grained phase, and from this candidate set the final top-
k
results are generated in the fine-grained phase. Tested on an RNN-based NMT system and a Transformer-based NMT system separately, our GPU-friendly method achieved a significant speed-up without harming the translation quality.
Amplification of input differences by dynamic heterogeneity in the spiral ganglion
Authors: Crozier Robert A. , Wismer Zachary Q. , Parra-Munevar Jeffrey , Plummer Mark R. , Davis Robin L.
Published: April 2022

Can changes in intracellular second messenger signaling within primary auditory afferents shift our perception of sound? Results presented herein lead to this conclusion. We found that intracellular cAMP signaling level systematically altered the kinetics and excitability of primary auditory afferents, exemplifying how dynamic heterogeneity can enhance differences between electrophysiological correlates of timing and intensity.
Effect of Apatinib Combined with Seggio on the Expression of Serum AFP and CA724 and Long-Term Survival Rate in Patients with Advanced Gastric Cancer Undergoing Comfortable Nursing Intervention
Authors: Ren Dawei , Feng Mi , Zhang Shengmin , Zhang Yun , Li Ji
Published: April 2022

Objective. To study the effect of apatinib combined with seggio on the expression of serum AFP and CA724 and the long-term survival rate in advanced gastric cancer patients undergoing comfort nursing intervention. Methods. 98 advanced gastric cancer patients were divided into single-drug group and joint group. Both groups of patients were given comfort nursing intervention, the single-drug group was treated with seggio, and the joint group was treated with apatinib and seggio. The clinical efficacy, survival rate, relationship between the tumor markers and the survival time, serum tumor markers levels (CA724 and AFP), inflammatory factors (IL-4, IL-10) levels, quality-of-life scores, and immunity function were measured after treatment. Results. The clinical efficacy in the joint group was better than that in the single-drug group. The three-year survival time in the joint group was upregulated relative to the single-drug group. The patients with high expression of CA724 or AFP had a lower survival time than the patients with low expression of CA724 or AFP. After treatment, IL-10 and IL-4 levels were obviously decreased, and the joint group showed a more obvious decrease compared with the single-drug group. The quality-of-life scores were significantly upregulated after treatment, and compared with the joint group, the scores in the single drug-group were obviously higher. The CD4+/CD8+, CD4+, and CD3+ levels were increased, while CD8+ levels were decreased after treatment, and the changes of each index in the joint group were more significant than those in the single-drug group. The content of CA724 and AFP were significantly decreased after treatment, and the joint group showed a more significant decrease than the single-drug group. Conclusion. Apatinib combined with seggio for advanced gastric cancer patients’ treatment based on comfort nursing intervention can improve the clinical efficacy and survival time, reduce inflammatory factors and serum tumor markers levels, enhance patients’ immune function, and quality of life.
Role of Moringa oleifera on Green Synthesis of Metal/Metal Oxide Nanomaterials
Authors: Jadhav Vikram , Bhagare Arun , Ali Ismat H. , Dhayagude Akshay , Lokhande Dnyaneshwar , Aher Jayraj , Jameel Mohammed , Dutta Mycal
Published: April 2022

Being an environmentally benign method biosynthesis of nanomaterial paying much more attention to researchers, it has many advantages over other routes, such as one pot, facile synthesis, and cost‐effective; synthesized material can have good affinity due to surface modification and hence became a most attractive candidate for medicinal and biological applications. Moreover, biosynthesis creates a bridge of interdisciplinary research. Biosynthesis can be done by using bacteria, microbes, plant extracts, etc. In this study, we focus on the synthesis of some metal and metal oxide nanomaterials (M/MO NMs) by using an extract of parts from the Moringa oleifera plant. It is a natural source that can serve as a capping, stabilizing, and reducing/oxidizing agent due to the presence of some of the phytochemical parameters. Moreover, it is a rich source of antioxidants, including quercetin and chlorogenic acids, such as flavonoids, phenolics, astragalin, anthocyanins, cinnamates, and carotenoids, as well as a good source of carotene, iron, potassium, calcium, terpenes, quinines, saponins, alkaloids, proteins, tannins, and vitamin. These components produce smaller particles and give a compelling impact on the activities of M/MO NMs nanoparticles. Here, we discuss nanoparticles such as FeO, CuO, ZnO, NiO, MgO, Ag, and Au.
A Deep Learning Based Traffic State Estimation Method for Mixed Traffic Flow Environment
Authors: Ding Fan , Zhang Yongyi , Chen Rui , Liu Zhanwen , Tan Huachun
Published: April 2022

Traffic state estimation plays a fundamental role in traffic control and management. In the connected vehicles (CVs) environment, more traffic-related data perceived and interacted by CVs can be used to estimate traffic state. However, when there is a low penetration rate of CVs, the data collected from CVs would be inadequate. Meanwhile, the representativeness of the collected data is positively correlated with the penetration rate. This article presents a traffic state estimation method based on a deep learning algorithm under a low and dynamic CVs penetration rate environment. Specifically, we design a K-Nearest Neighbor (KNN) data filling model integrating acceleration data to solve the problem of insufficient data. This method can fuse the time feature of speed by acceleration modification and mine the distribution features of speed by KNN. In addition, to reduce the estimation error caused by penetration rate, we design a Long Short-Term Memory (LSTM) model, which uses penetration rate estimated by Macroscopic Fundamental Diagram (MFD) as one of the input factors. Finally, we use the concept of operational efficiency for reference, dividing traffic state into three categories according to the estimated speed: free flow, optimal flow, and congestion. SUMO is used to simulate traffic cases under different penetration rates to evaluate our scheme. The results suggest that our data filling model can significantly improve filling accuracy under a low penetration rate; there is also a better performance of our estimation model than that of other comparison models in both low and dynamic penetration rates.
Biomechanical Research on Special Ability of Long Jump Take-Off Muscle Based on Multisource Information Fusion
Authors: Ren Yue , Luo Bingquan , Chu Jun
Published: April 2022

For athletes of different sports, their muscle activities in different sports will show different special characteristics according to different sports. The purpose of this paper is to study the technology of multi-information fusion and to study the athletes of the long jump competition. The relevant research on the muscle specific ability test methods of the athletes in the long jump competition is of great significance to the study of the long jump. This paper proposes a long jumper’s special muscle ability experiment, using the now very popular multi-information fusion technology, to conduct in-depth research on the biomechanics of the long jumper’s special ability of the take-off muscle, which can provide an effective scientific basis for the special ability level and special strength of the long jumper’s take-off sports. The results of the study show that the hip joint of the take-off leg produces greater hip extensor torque during the take-off action of long jump, and the active contraction ability of the knee flexor group is very important for taking off and avoiding damage to the posterior femoral muscle group. The change range of the pressure center is between 51.26% and 74.35%, which has great application value in actual training.
Multiview Volume and Temporal Difference Network for Angle-Closure Glaucoma Screening from AS-OCT Videos
Authors: Hao Luoying , Hu Yan , Higashita Risa , J. Q. Yu James , Zheng Ce , Liu Jiang
Published: April 2022

Background. Precise and comprehensive characterizations from anterior segment optical coherence tomography (AS-OCT) are of great importance in facilitating the diagnosis of angle-closure glaucoma. Existing automated analysis methods focus on analyzing structural properties identified from the single AS-OCT image, which is limited to comprehensively representing the status of the anterior chamber angle (ACA). Dynamic iris changes are evidenced as a risk factor in primary angle-closure glaucoma. Method. In this work, we focus on detecting the ACA status from AS-OCT videos, which are captured in a dark-bright-dark changing environment. We first propose a multiview volume and temporal difference network (MT-net). Our method integrates the spatial structural information from multiple views of AS-OCT videos and utilizes temporal dynamics of iris regions simultaneously based on image difference. Moreover, to reduce the video jitter caused by eye movement, we employ preprocessing to align the corneal part between video frames. The regions of interest (ROIs) in appearance and dynamics are also automatically detected to intensify the related informative features. Results. In this work, we employ two AS-OCT video datasets captured by two different devices to evaluate the performance, which includes a total of 342 AS-OCT videos. For the Casia dataset, the classification accuracy for our MT-net is 0.866 with a sensitivity of 0.857 and a specificity of 0.875, which achieves superior performance compared with the results of the algorithms based on AS-OCT images with an obvious gap. For the Zeiss AS-OCT video dataset, our method also gets better performance against the methods based on AS-OCT images with a classification accuracy of 0.833, a sensitivity of 0.860, and a specificity of 0.800. Conclusions. The AS-OCT videos captured under changing environments can be a comprehended means for angle-closure classification. The effectiveness of our proposed MT-net is proved by two datasets from different manufacturers
Analysis of Toilet Scale of Freeway Service Areas Based on Crowd Gatherings
Authors: Li Xufeng , Xu Jinliang , Dong Yaping , Gao Sunjian , Han Shuo
Published: April 2022

On fully enclosed freeways, the service area is the only key node for certain crowd activities such as resting, toileting, and dining. In these activities, using the toilet is the most important purpose for people to enter the service area. A reasonable toilet location and size in the service area is the basis for its efficient operation. This study conducts field surveys on several service areas, including Meicun, Tai’an, and Qianxian, through video recording and crowd tracking questionnaires. We summarize and analyze the characteristics of population flow in Chinese freeway service areas. The key data obtained through field surveys are reported, such as the priority and length of stay of customers in the facilities during peak hours at weekends, to analyze the characteristics of pedestrian traffic in the service areas. Finally, based on a large number of pedestrian simulation methods used in studies on the layout of subways and airport facilities, the AnyLogic simulation software is applied to establish a crowd movement model for these areas. The study not only obtained the pedestrian characteristics of the service area but also showed that only changing the location of toilets has no effect on the efficiency of toilet use without changing the level of service, whereas changing the number of toilets has a significant impact on the efficiency. Most importantly, this paper establishes a relationship model between the toilet size of the service area and the service area pedestrians flow; when the toilet seats 266/158/148 people, the maximum flow of people in the service area is about 3,115/2200/2000 p/h, which can provide help for the scale design of the service area.
Decreased Interhemispheric Functional Connectivity and Its Associations with Clinical Correlates following Traumatic Brain Injury
Authors: Song Yu , Han Xi , Li Gaoyi , Tong Wusong , Fan Mingxia , Chen Xianzhen , Yin Jia , Chen Songyu , Huang Jingrong , Gao Dongming , Gao Liang , Dong Yan
Published: April 2022

Objective. To explore the interhemispheric functional coordination following traumatic brain injury (TBI) and its association with posttraumatic anxiety and depressive symptoms. Methods. This was a combination of a retrospective cohort study and a cross‐sectional observational study. We investigated the functional coordination between hemispheres by voxel‐mirrored homotopic connectivity (VMHC). Grey matter volumes were examined by voxel‐based morphometry (VBM), and microstructural integrity of the corpus callosum (CC) was assessed by diffusion tension imaging (DTI). The anxiety and depressive symptoms were evaluated with the Hospital Anxiety and Depression Scale. Results. The VMHC values of the bilateral middle temporal gyrus (MTG) and orbital middle frontal gyrus (MFG) were significantly decreased in TBI patients versus the healthy controls. Weakened homotopic functional connectivity (FC) in the bilateral orbital MFG is moderate positively correlated with anxiety and depressive symptoms. The white matter integrity in the CC was extensively reduced in TBI patients. In the receiver operating characteristic analysis, the VMHC value of the orbital MFG could distinguish TBI from HC with an area under the curve of 0.939 (sensitivity of 1 and specificity of 0.867). Conclusion. TBI disrupts the interhemispheric functional and structural connection, which is correlated with posttraumatic mood disorders. These findings may serve as a clinical indicator for diagnosis.
Resource Optimization Technology Using Genetic Algorithm in UAV-Assisted Edge Computing Environment
Authors: Sun Huijuan , Xi Hongqi
Published: April 2022

As fixed edge computing systems can hardly meet the demand of mobile users for massive data processing, a computational resource allocation strategy using the genetic algorithm in UAV-assisted edge computing environment is proposed. First, a UAV-assisted mobile edge computing (MEC) system is designed to help users execute computation tasks through the UAV or relaying to the ground base station. Then, a communication model and a computation model are constructed to minimize the total system energy consumption by jointly optimizing the UAV offloading ratio, user scheduling variables, and UAV trajectory. Finally, the minimization of total system energy consumption is modeled as a nonconvex optimization problem and solved by introducing an improved genetic algorithm, so as to achieve a rational allocation of computational resources. Based on the experimental platform, the simulation of the proposed method is carried out. The results show that the total energy consumption is 650 J when the execution time is 110 s and the execution time is 17.5 s when the number of users is 50, which are both better than other comparison methods.
Pilot Allocation and Data Power Optimization Based on Access Point Selection in Cell-Free Massive MIMO
Authors: Duan Zhiwen , Zhao Feng
Published: April 2022

Focusing on the pilot contamination problem of cell-free massive multi-input multi-output (MIMO), a pilot allocation algorithm based on access point (AP) selection is proposed. To improve the system performance further, data power optimization is carried out. First, the AP that serves each user is selected through the user-centered idea and the large-scale fading matrix. Use the same service AP numbers between users to measure the pilot contamination intensity and then assign orthogonal pilots to strong potential pilot contamination users. A spectrum efficiency (SE) scheme to maximize the minimum user is proposed for the fairness problem in data power optimization. It is proved that the objective function of data power optimization accords with linear programming, and a dichotomy is given to solve the problem. Simulation results show that the pilot allocation algorithm based on AP selection can significantly improve the total SE of the system and reduce the computational complexity of the system. At the same time, the data power optimization algorithm improves minimum SE for users in the system.
Isoflavones from Semen Sojae Preparatum Improve Atherosclerosis and Oxidative Stress by Modulating Nrf2 Signaling Pathway through Estrogen-Like Effects
Authors: Guo Jinzhou , Ma Jingxin , Cai Kun , Chen Haining , Xie Ke , Xu Binren , Quan Desen , Du Jingyan
Published: April 2022

Atherosclerosis (AS) often occurs in cardiovascular disease, which is a chronic vascular disease and is harmful to human health. Oxidative stress is involved in its etiology. This study aimed to determine the effectiveness of Isoflavones from semen sojae preparatum (ISSP) in inhibiting oxidative stress and its important molecular mechanisms through in vivo and in vitro experiments. ApoE−/− mice were used to establish atherosclerosis models through a high-fat diet, and endothelial cells were used to establish oxidative stress injury models through ox-LDL induction. The degree of oxidative stress damage was assessed by detecting changes in ET-1, LDH, SOD, and MDA indicators. It was observed that after ISSP treatment, the oxidative stress damage of mice and endothelial cells was improved. The Nrf2/AER signaling pathway is an important antioxidant pathway that has attracted our attention. Western blotting and qRT-PCR were used to detect the expression of Nrf2, HO-1, and NQO1 in mice aortae and endothelial cells. The results showed that the Nrf2 signaling pathway was activated after ISSP intervention. In addition, in this study, after preantagonizing the estrogen receptors GPR30 and ERβ, it was observed that the effects of ISSP in treating endothelial cell oxidative damage and activating the Nrf2 signaling pathway were weakened. After silencing Nrf2 by Nrf2-siRNA transfection, the effect of ISSP in treating endothelial cell oxidative damage was inhibited. This study shows that ISSP may reduce oxidative stress damage and atherosclerosis through the Nrf2 signaling pathway, and this effect may involve the GPR30 and ERβ estrogen receptors.
Comprehensive Analysis of Potential Biomarkers of Acute Lymphoblastic Leukemia in Children by Using a Competing Endogenous RNA Network
Authors: Lin Xiao-Ying , Yuen Ka-Yuk , Chen Hai-Lei , Shen Miao-Na , Huang Yan , Huang Qian-Wen , Liu Yong , Xu Lu-Hong
Published: April 2022

Acute lymphoblastic leukemia (ALL) is the most serious hematological carcinoma in adolescents. The significance of long noncoding RNAs (lncRNAs) and their regulative role in the proliferation and differentiation of myeloid cells in cancer has been recently reported. Nevertheless, key RNAs and the regulatory mechanism of competitive endogenous RNA (ceRNA) network affected by pediatric ALL are not fully illustrated. In this study, phase 2 and 3 pediatric ALL RNA profiles were extracted from the TARGET database and used to identify lncRNAs, microRNAs, and messenger RNAs in high-risk ALL and reconstruct the sponge ceRNA regulatory network. Results indicated that 44 lncRNAs, 25 miRNAs, and 115 mRNA were up/downregulated. Functional analysis with differentially expressed RNAs (DERNAs) showed enriched significant signaling pathways, including PI3K-Akt and p53 signaling cascades and other pathways associated with the tumor. Seventeen differential hub RNAs, including LINC00909, BZRAP1-AS1, C17orf76-AS1, HCG11, MIAT, SNHG5, SNHG15, and TP73-AS1, were identified. The Cox model of correlation indicated that 14 of these RNAs were associated with the progression of pediatric ALL. These findings would help clarify the regulatory role of several lncRNAs as well as provide insights into the leukemogenesis of pediatric ALL to further explore novel prognostic markers/therapeutic targets for ALL.
The Analysis of Sharing Economy on New Business Model Based on BP Neural Network
Authors: Cai Gang , Ni Chunmei
Published: April 2022

The development of social economy and Internet information technology has made the development of the sharing economy relatively rapid. This article aims to study how to promote the sharing economy based on neural networks to play a role in new business models. This article proposes that the sharing economy and the new business model are inseparable. It also discusses how to analyze the relationship between the sharing economy and the new business model based on the BP neural network. With the development of the economy and society, new economic development models have developed, and the sharing economy model has risen. The sharing economy model has brought an impact to the traditional economic development model, affecting the business model. The results show that with the development of society and enterprises, the development of the sharing economy is getting faster and faster. Today, some sharing economy companies are bound to face various obstacles in the process of copying other business models and development. Sharing economy enterprises have made various adjustments and responses to various problems, but they have not found a better model to adapt to the modern social market and environment. Therefore, the business model of the sharing economy requires further analysis and investigation.
Research on Furniture Design Integrating Ming-Style Furniture Modeling Elements and Image Sensor Data: Taking Suitable Old Furniture as an Example
Authors: Chen Wei
Published: April 2022

Ming-style furniture, adhering to the excellent traditional Chinese history and culture, is the pinnacle of traditional Chinese-style furniture, which vividly embodies the cultural essence of Chinese-style furniture. However, with the current popularity of smart home products, there are many obstacles for elderly users to use smart home products. Voice interaction is one of the main interaction methods of smart home products. The design strategy of voice user interface for aging smart home products is studied to improve the experience of elderly users in operating smart home products. Based on image sensing technology, combining Ming-style furniture modeling elements, and based on context theory research, this paper proposes four types of smart home contexts for elderly users, including user context, task context, time context, and environmental context, so as to propose a specific smart home product voice user interface design strategy. According to the user’s situational characteristics, a multichannel interaction design of voice user interface is proposed, an emotional and personalized voice user interface is constructed, and a design strategy of context memory assisting the dialogue process is constructed. According to the task, time, and environmental situation of elderly users, it proposes design strategies such as active interactive voice user interface design and provides continuous behavioral service experience. Conclusion. The research results provide a method and strategy reference for the design and development of the voice user interface of smart home products and provide a more natural and comfortable experience of using smart home products for elderly users.
A Nomogram for Predicting the Mortality of Patients with Acute Respiratory Distress Syndrome
Authors: Wang Zhenqing , Xing Lihua , Cui Hongwei , Fu Guowei , Zhao Hui , Huang Mingjun , Zhao Yangchao , Xu Jing
Published: April 2022

Acute respiratory distress syndrome (ARDS) is an acute lung injury associated with high morbidity and mortality. This study aimed to establish an accurate prediction model for mortality risk in ARDS. 70% of patients from the Medical Information Mart for Intensive Care Database (MIMIC-III) were selected as the training group, and the remaining 30% as the testing group. Patients from a Chinese hospital were used for external validation. Univariate and multivariate regressions were used to screen the independent predictors. The receiver operating characteristic curve (ROC) analysis, the Hosmer–Lemeshow test, and the calibration curve were used for evaluating the performance of the model. Age, hemoglobin, heart failure, renal failure, Simplified Acute Physiology Score II (SAPS II), immune function impairment, total bilirubin (TBIL), and PaO2/FiO2 were identified as independent predictors. The algorithm of the prediction model was: ln (Pr/(1 + Pr)) = −3.147 + 0.037 ∗ age − 0.068 ∗ hemoglobin + 0.522 ∗ heart failure (yes) + 0.487 ∗ renal failure (yes) + 0.029 ∗ SAPS II + 0.697 ∗ immune function impairment (yes) + 0.280 ∗ TBIL (abnormal) − 0.006 ∗ PaO2/FiO2 (Pr represents the probability of death occurring). The AUC of the model was 0.791 (0.766–0.816), and the internal and the external validations both confirmed the good performance of the model. A nomogram for predicting the risk of death in ARDS patients was developed and validated. It may help clinicians early identify ARDS patients with high risk of death and thereby help reduce the mortality and improve the survival of ARDS.
Neospora caninum SRS2 Protein: Essential Vaccination Targets and Biochemical Features for Next‐Generation Vaccine Design
Authors: Asghari Ali , Kordi Bahareh , Maleki Bahman , Majidiani Hamidreza , Shams Morteza , Naserifar Razi
Published: April 2022

Vaccination is a standout preventive measure to combat neosporosis among cattle herds. The present in silico study was done to evaluate the physicochemical properties and potent immunogenic epitopes of N. caninum SRS2 protein as a possible vaccine candidate. Web‐based tools were used to predict physicochemical properties, antigenicity, allergenicity, solubility, posttranslational modification (PTM) sites, transmembrane domains and signal peptide, and secondary and tertiary structures as well as intrinsically disordered regions, followed by identification and screening of potential linear and conformational B‐cell epitopes and those peptides having affinity to bind mouse major histocompatibility complex (MHC) and cytotoxic T lymphocyte (CTL). The protein had 401 residues with a molecular weight of 42 kDa, representing aliphatic index of 69.35 (thermotolerant) and GRAVY score of ‐0.294 (hydrophilic). There were 53 PTM sites without a signal peptide in the sequence. Secondary structure comprised mostly by extended strand, followed by helices and coils. The Ramachandran plot of the refined model showed 90.2%, 8.8%, 0.5%, and 0.5% residues in the favored, additional allowed, generously allowed, and disallowed regions, correspondingly. Additionally, various potential B‐cell (linear and conformational), CTL, and MHC‐binding epitopes were predicted for N. caninum SRS2. These epitopes could be further utilized in the multiepitope vaccine constructs directed against neosporosis.
Preventive Effects of Ilex Cornuta Aqueous Extract on High-Fat Diet-Induced Fatty Liver of Mice
Authors: Liu Meifang , Jia Haoxin , He Yang , Huan Yu , Kong Zhe , Xu Nuo , Cao Xiangju , Duan YueTong , Li Zhaoliang , Yang Luyuan , Wei Wen-Ping , Wang Lifang , Li Li
Published: April 2022

Objective. To investigate the preventive effects of Ilex cornuta aqueous extract (ICAE) on high-fat diet (HFD)-induced fatty liver of mice and its mechanisms. Materials and Methods. Twenty-six male KM (Kunming) mice were divided into 3 groups, including the control group (n = 9), fed with normal diet; HFD group (n = 9), fed with HFD; ICAE + HFD group (n = 8), fed with HFD and administered with ICAE (3 g·kg−1·d−1) at the same time for 10 weeks. Body weight, liver weight, intra-abdominal and subcutaneous fat weight, serum triglyceride (TG), total cholesterol (TC), and blood glucose were determined to evaluate the preventive effects of ICAE on obesity. The average 24 h food consumption of the mice was monitored for 5 times in the 9th week of the experiment to investigate the effects of ICAE on food intake. Serum alanine transaminase (ALT) and aspartate aminotransferase (AST) were assayed to observe the influences of HFD and ICAE on liver function. HE staining was adopted to observe the influence of ICAE on the morphology of adipose tissue and liver tissue. Hepatic TG and TC content assay and oil red O staining were used to evaluate the influences of ICAE on HFD-induced fatty liver, and the protein expression of peroxisome proliferator-activated receptors γ (PPARγ) and adipose differentiation-related protein (ADRP) in liver were examined by immunoblotting. Results. ICAE treatment significantly reduced the increase of body weight, intra-abdominal, and subcutaneous fat and liver weight induced by HFD (

P
<
0.001

), but has no influence on food intake; ICAE treatment attenuated the elevation of serum TG, TC, and glucose, as well as serum ALT and AST (

P
<
0.01

,

P
<
0.05

,

P
<
0.001

) and dramatically decreased the content of TG in liver (

P
<
0.01

), but has no influence on hepatic TC content. HE staining and oil red O staining showed that ICAE significantly reduced HFD-induced white adipocyte hypertrophy and significantly inhibited lipid accumulation in liver. Immunoblotting showed that the protein levels of PPARγ and ADRP were significantly increased by HFD induction, which can be dramatically reduced by ICAE treatment (

P
<
0.05

,

P
<
0.0001

). Conclusion. ICAE has preventive effects on HFD-induced obesity and fatty liver in mice, exerted beneficial effects upon HFD-induced hepatic injury. The preventive effects of ICAE on fatty liver are concerned with the downregulation of PPARγ and ADRP protein expression in liver.
Prediction of Linalool Content in Osmanthus fragrans Using E-Nose Technology
Authors: Zhou Chenchen , Fan Junjun , Tan Ruinan , Peng Qin , Cai Junhuo , Zhang Wangxiang
Published: April 2022

Linalool is a well-known volatile compound. It is usually extracted from plants or synthesized by chemical methods. However, there is still no rapid screening method for plants with high linalool content. Therefore, we aimed to establish a method determining linalool content in Osmanthus fragrans by electronic nose (E-nose). The volatile gases of three cultivars of O. fragrans were characterized by gas chromatography-mass spectrometry (GC-MS) and E-nose. Different concentrations of linalool were measured by E-nose. Then, the E-nose data were subjected to principal component analysis (PCA) and linear discriminant analysis (LDA) to establish a discriminant model for determining linalool concentrations. Prediction models based on principal component regression (PCR) and multiple linear regression (MLR) were developed from all sensors and feature sensors to determine linalool concentrations in the three cultivars of O. fragrans flowers. Finally, the linalool concentrations determined by gas chromatography were used to verify the accuracy of the prediction model. The results show that linalool had the highest abundance among the volatile compounds of O. fragrans, and the MLR prediction model had an

R

2

of 0.992 in calibration sets and an

R

2

of 0.895 in prediction sets using 10 sensors. This study describes a rapid and accurate method for the detection and quantification of linalool concentrations.
COVID-19 and Mucormycosis Coinfection: How Challenging It Is
Authors: Nayak Niranjan , Khan Erum , Panigrahi Debadatta
Published: April 2022

Recently, cases of rhinoorbital mucormycosis in people diagnosed with COVID-19 have been reported from India particularly. Diabetes mellitus though happens to be an independent risk factor both for severe COVID-19 and mucormycosis, administration of steroids is attributed as a precipitating factor for acquiring the comorbid condition. This opportunistic fungal infection is highly angioinvasive in nature because of which, clinical outcome of infection is invariably poor, especially with rhinocerebral or rhinoorbitocerebral variety of mucormycosis. However, effective management depends upon timely and accurate diagnosis and parenteral administration of amphotericin B. At the same time, judicious use of steroids is a key factor. In addition, glycemic control in those who are severely diabetic is strongly advocated. Exenteration of an eyeball may be indicated if cavernous sinus and intracranial spread are anticipated. Therefore, in order to facilitate faster healing and better penetration of antifungal drugs, surgical debridement of the paranasal sinus cavities and removal of dead tissue from the sinuses are recommended.
Active Management of Labor Process under Smart Medical Model Improves Vaginal Delivery Outcomes of Pregnant Women with Preeclampsia
Authors: Xin Siming , Liu Xianxian , Zheng Jiusheng , Lai Hua , Zhou Jiao , Zhang Feng , Wu Xiaoying , Shen Ting , Xu Lin , Zeng Xiaoming
Published: April 2022

Background. In a global environment of increasing cesarean delivery rate, promoting vaginal delivery, reducing the rate of first cesarean section, and the incidence of vaginal delivery complications are the objectives of obstetric medical quality and safety in China. As a common obstetric complication, preeclampsia affects the safety of many pregnant women. It is the obstetrician’s great responsibility to promote vaginal delivery and improve delivery outcomes in preeclampsia. To this end, we explored the roles of active labor management under the smart medical model in improving the outcomes of vaginal delivery for pregnant women with preeclampsia. Methods. The clinical data of 219 cases of preeclampsia pregnant women who delivered vaginally in our hospital from January 2017 to December 2020 were retrospectively analyzed. According to different labor process management, they were divided into study group (active labor process management group) and control group (normal labor process management group). Active labor process management methods included intrapartum ultrasound, central fetal heart rate monitoring, Doula delivery, labor analgesia, and quality of life care. The differences in delivery process, delivery outcome, bleeding causes, and hemostatic measures were compared between the two groups. Results. (1) The incidence of preeclampsia in our hospital showed an increasing trend in recent four years; (2) in smart hospitals, the active management of labor process reduced the probability of transferring to the cesarean section in preeclampsia pregnant women with vaginal trial failure; and (3) active labor process management reduced the rate of lateral episiotomy, decreased the postpartum hemorrhage volume within two hours, and improved the vaginal delivery outcome of preeclampsia pregnant women. Conclusions. In the era of the rapid development of the Internet, vigorously promoting the construction of smart hospitals and actively managing the delivery process can reduce the failure rate of vaginal trial delivery and improve the outcomes of vaginal delivery in preeclampsia women.
Effects of Operating Conditions during Three-Layered Polymeric Balloon Catheter Extrusion
Authors: Jin G. B. , Wang K. S. , Hua W. J. , Jin Y. F. , Qin P. , Bian J. Y. , Dai G. H. , Zhang Q. Q.
Published: April 2022

Multilayered balloon catheters are attracting more attention in recent years. Multilayered balloon catheters have some unique properties such as meso-/microscale dimensions, small wall thickness, and strict requirements of dimensional accuracy. In this study, three-layered polymeric balloon catheters composed of polyamide, ethylene vinyl acetate, and polypropylene (PA/EVA/PP) are successfully fabricated using a three-layered coextrusion die and the polymer melt flowing behavior through the extrusion die are analyzed. Both the diameter and wall thicknesses have been selected as the targeted structural parameters to investigate the effects of pulling speed, air injection volume rate, and screw speed on the quality of the extrudates. The optimal combination of these three operating conditions has been achieved. It is found that pulling speed can significantly affect the diameters of the extruded balloon catheters. The variation interval values of outer profile diameter and inner cavity diameter with the extrusion experiments are 20.95% and 13.04%, respectively. The screw speed of each layer has a great influence on the wall thickness of each layer. Through the influence of outer screw speed, middle screw speed and inner screw speed, the variation interval values for outer layer wall thickness, middle layer wall thickness, and inner layer wall thickness are 31.06%, 35.69%, and 31.35%, respectively. The air injection volume rate has negligible effect.
Autoencoder for Design of Mitigation Model for DDOS Attacks via M-DBNN
Authors: Agrawal Ankit , Singh Rajiv , Khari Manju , Vimal S. , Lim Sangsoon
Published: April 2022

Distributed Denial of Service (DDoS) attacks pose the greatest threat to the continued and efficient operation of the Internet. It can lead to website downtime, lost time and money, disconnection and hosting issues, and website vulnerability. Conventional machine learning methodologies are being harmed by reduced recognition rates and greater false-positive rates due to the emergence of new threats. As a result, high-performance machine learning classifiers with low false-positive rates and high prediction accuracy are required for the DDoS detection system. Here, a deep belief neural network is preferred, upgraded to the modified deep neural network (M-DBNN) to accurately detect DDoS attacks from the network. Enable the database to change a specific format and range, which helps the M-DBNN classifier easily predict the class. An advanced Chimp Optimization Algorithm (ChOA) is used to minimize the error to find the best weight of the M-DBNN classifier; this leads to accurate DDOS attack detection and predict the classes effectively. The proposed method is evaluated for CAIDA “DDoS Attack 2007” dataset. The accuracy of the proposed method is 0.87%, and the outcome is compared with those of other existing methods of deep neural network (DNN), support vector machine (SVM), artificial neural network (ANN), and neural network (NN). The proposed method demonstrates great detection accuracy with a low error.