bluuebunny/crossref_metadata_2025 huggingface dataset:
Adaptive Computation Offloading for Mobile Augmented Reality
Authors: Ren Jie , Gao Ling , Wang Xiaoming , Ma Miao , Qiu Guoyong , Wang Hai , Zheng Jie , Wang Zheng
Published: December 2021

Augmented reality (AR) underpins many emerging mobile applications, but it increasingly requires more computation power for better machine understanding and user experience. While computation offloading promises a solution for high-quality and interactive mobile AR, existing methods work best for high-definition videos but cannot meet the real-time requirement for emerging 4K videos due to the long uploading latency. We introduce ACTOR, a novel computation-offloading framework for 4K mobile AR. To reduce the uploading latency, ACTOR dynamically and judiciously downscales the mobile video feed to be sent to the remote server. On the server-side, it leverages image super-resolution technology to scale back the received video so that high-quality object detection, tracking and rendering can be performed on the full 4K resolution. ACTOR employs machine learning to predict which of the downscaling resolutions and super-resolution configurations should be used, by taking into account the video content, server processing delay, and user expected latency. We evaluate ACTOR by applying it to over 2,000 4K video clips across two typical WiFi network settings. Extensive experimental results show that ACTOR consistently and significantly outperforms competitive methods for simultaneously meeting the latency and user-perceived video quality requirements.
Active learning assignment: Legos and coins to explain glucose metabolism
Authors: Terson de Paleville Daniela G. L.
Published: December 2021

This article describes an assignment used in an undergraduate Advanced Exercise Physiology course for seniors. Students’ backgrounds in chemistry varied from adequate to almost nonexistent. This presented several challenges for teaching and students’ understanding of aerobic oxidation of a glucose molecule. This article presents an assignment for an active-learning team-based approach in the classroom and the adapted version for virtual learning. Students in active, team-based learning were asked to create a short video of glucose oxidation using Lego bricks, coins, or other toys to represent the glucose molecule, the by-products, and the enzymes involved in each pathway. During virtual learning, the assignment was modified to create a video independently in both synchronous and asynchronous course sections. Based on students’ responses to an instructor-developed survey on their perceptions of the assignment, 71% reported that the assignment was helpful to understand glucose metabolism.
A Privacy‐Preserving Incentive Mechanism for Data Offloading in Satellite‐Terrestrial Crowdsensing
Authors: Zhu Boxiang , Li Jiarui , Liu Zhongkai , Liu Yang
Published: December 2021

Data offloading algorithm is the foundation of urban Internet of Things, which has gained attention for its large size of user engagement, low cost, and wide range of data sources, replacing traditional crowdsensing in areas such as intelligent vehicles, spectrum sensing, and environmental surveillance. In data offloading tasks, users’ location information is usually required for optimal task assignment, while some users in remote areas are unable to access base station signals, making them incapable of performing sensing tasks, and at the same time, there are serious concerns about users’ privacy leakage about their locations. Until today, location protection for task assignment in data offloading has not been well explored. In addition, existing privacy protection algorithms and data offloading task assignment mechanisms cannot provide personalized protection for different users’ privacy protection needs. To this end, we propose an algorithm known as differential private long‐term privacy‐preserving auction with Lyapunov stochastic theory (DP‐LAL) for data offloading based on satellite‐terrestrial architecture that minimizes the total payment. This not only gives an approximate optimal total payment in polynomial time but also improves the issue of poor signal in remote areas. Meanwhile, satellite‐terrestrial data offloading architecture integrates wireless sensor networks and cloud computing to provide real‐time data processing. What is more, we have considered long‐term privacy protection goals. We employ reverse combinatorial auction and Lyapunov optimization theorem to jointly optimize queue stability and total payment. More importantly, we use Lyapunov optimization theorem to jointly optimize queue stability and total payment. We prove that our algorithm is of high efficiency in computing and has good performance in various economic attributes. For example, our algorithms are personally rational, budget‐balanced, and true to the buyer and seller. We use large‐scale simulations to evaluate the proposed algorithm, and compare our algorithm with existing algorithms, our algorithm shows higher efficiency and better economic properties.
An Improved Bingham Model and the Parameter Identification of Coal (Rock) Containing Water Based on the Fractional Calculus Theory
Authors: He Feng , Yang Song , Ren Tianjiao , Bian Hongjie , Li Haoran
Published: December 2021

The rheological properties of coal (rock) containing water cannot be characterized by the traditional Bingham model. This problem was addressed in this study through theoretical analysis and experimental research. Based on fractional calculus theory, a fractional calculus soft element was introduced into the traditional Bingham model. An improved Bingham model creep equation and a relaxation equation were obtained through theoretical derivations. Triaxial creep experiments of coal (rock) with different moisture contents were conducted. The parameters of the improved Bingham model were obtained by the least‐squares method. Conclusions are as follows: (1) in the improved Bingham model, the stage of nonlinear accelerated creep could be characterized by the creep curves of the soft element; (2) with the increasing moisture content of the coal (rock), the transient strain and the slope of the steady creep stage increased and the total creep time showed a decreasing trend; and (3) the parameters of the creep model were obtained by nonlinear fitting of experimental data, and the fitted curve could better describe the whole creep process. The rationality of the improved creep model was verified. It can provide a theoretical basis for the study and engineering analysis of coal (rock).
Synthesis and Evaluation of the Antibacterial and Antioxidant Activities of Some Novel Chloroquinoline Analogs
Authors: Abdi Bayan , Fekadu Mona , Zeleke Digafie , Eswaramoorthy Rajalakshmanan , Melaku Yadessa
Published: December 2021

Quinoline heterocycle is a useful scaffold to develop bioactive molecules used as anticancer, antimalaria, and antimicrobials. Inspired by their numerous biological activities, an attempt was made to synthesize a series of novel 7-chloroquinoline derivatives, including 2,7-dichloroquinoline-3-carbonitrile (5), 2,7-dichloroquinoline-3-carboxamide (6), 7-chloro-2-methoxyquinoline-3-carbaldehyde (7), 7-chloro-2-ethoxyquinoline-3-carbaldehyde (8), and 2-chloroquinoline-3-carbonitrile (12) by the application of Vilsmeier–Haack reaction and aromatic nucleophilic substitution of 2,7-dichloroquinoline-3-carbaldehyde. The carbaldehyde functional group was transformed into nitriles using POCl3 and NaN3, which was subsequently converted to amide using CH3CO2H and H2SO4. The compounds synthesized were screened for their antibacterial activity against Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, and Streptococcus pyogenes. Compounds 6 and 8 showed good activity against E. coli with an inhibition zone of 11.00 ± 0.04 and 12.00 ± 0.00 mm, respectively. Compound 5 had good activity against S. aureus and P. aeruginosa with an inhibition zone of 11.00 ± 0.03 mm relative to standard amoxicillin (18 ± 0.00 mm). Compound 7 displayed good activity against S. pyogenes with an inhibition zone of 11.00 ± 0.02 mm. The radical scavenging activity of these compounds was evaluated using 1,1-diphenyl-2-picrylhydrazyl (DPPH), and compounds 5 and 6 displayed the strongest antioxidant activity with IC50 of 2.17 and 0.31 µg/mL relative to ascorbic acid (2.41 µg/mL), respectively. The molecular docking study of the synthesized compounds was conducted to investigate their binding pattern with topoisomerase IIβ and E. coli DNA gyrase B. Compounds 6 (−6.4 kcal/mol) and 8 (−6.6 kcal/mol) exhibited better binding affinity in their in silico molecular docking against E. coli DNA gyrase. The synthesized compounds were also found to have minimum binding energy ranging from −6.9 to −7.3 kcal/mol against topoisomerase IIβ. The SwissADME predicted results showed that the synthesized compounds 5–8 and 12 satisfy Lipinski’s rule of five with zero violations. The ProTox-II predicted organ toxicity results revealed that all the synthesized compounds were inactive in hepatotoxicity, immunotoxicity, mutagenicity, and cytotoxicity. The findings of the in vitro antibacterial and molecular docking analysis suggested that compound 8 might be considered a hit compound for further analysis as antibacterial and anticancer drug. The radical scavenging activity displayed by compounds 5 and 6 suggests these compounds as a radical scavenger.
Development and Validation of a Mixed Reality Configuration of a Simulator for a Minimally Invasive Spine Surgery Using the Workspace of a Haptic Device and Simulator Users
Authors: Patel Sneha , Alkadri Sami , Driscoll Mark
Published: December 2021

Most surgical simulators leverage virtual or bench models to simulate reality. This study proposes and validates a method for workspace configuration of a surgical simulator which utilizes a haptic device for interaction with a virtual model and a bench model to provide additional tactile feedback based on planned surgical manoeuvers. Numerical analyses were completed to determine the workspace and position of a haptic device, relative to the bench model, used in the surgical simulator, and the determined configuration was validated using device limitations and user data from surgical and nonsurgical users. For the validation, surgeons performed an identical surgery on a cadaver prior to using the simulator, and their trajectories were then compared to the determined workspace for the haptic device. The configuration of the simulator was determined appropriate through workspace analysis and the collected user trajectories. Statistical analyses suggest differences in trajectories between the participating surgeons which were not affected by the imposed haptic workspace. This study, therefore, demonstrates a method to optimally position a haptic device with respect to a bench model while meeting the manoeuverability needs of a surgical procedure. The validation method identified workspace position and user trajectory towards ideal configuration of a mixed reality simulator.
Acupuncture Delays Cartilage Degeneration through Upregulating SIRT1 Expression in Rats with Osteoarthritis
Authors: Liu Hui , Zhang Tingting , Liu Min , Wang Chunhong , Yan Jinfeng
Published: December 2021

Silent mating type information regulation 2 homolog 1 (SIRT1) has been reported to inhibit osteoarthritic gene expression in chondrocytes. Here, efforts in this study were made to unveil the specific role of SIRT1 in the therapy of acupuncture on cartilage degeneration in osteoarthritis (OA). Specifically, OA was established by the anterior cruciate ligament transection method in the right knee joint of rats, subsequent to which acupuncture was performed on two acupoints. Injection with shSIRT1 sequence–inserted lentiviruses was conducted to investigate the role of SIRT1 in acupuncture-mediated OA. Morphological changes and cell apoptosis in rat OA cartilages were examined by safranin-O staining and terminal deoxynucleotidyl transferase-mediated nick-end labeling (TUNEL) assay, respectively. The serum levels of tumor necrosis factor (TNF)-α and interleukin (IL)-2 in OA rats were assessed by enzyme-linked immunosorbent assay (ELISA). The expressions of SIRT1, cartilage matrix degradation-related proteins (matrix metalloproteinase (MMP)-9 and ADAMTS5), NF-κB signaling-related markers (p-p65/p65 and p-IκBα/IκBα), and cartilage matrix synthesis-related proteins (collagen II and aggrecan) in the OA cartilage were analyzed by western blot. As a result, acupuncture counteracted OA-associated upregulation of TNF-α, IL-2, cartilage matrix degradation-related proteins, and NF-κB signaling-related markers, morphological damage, apoptosis, SIRT1 downregulation, and loss of cartilage matrix synthesis-related proteins in rat articular cartilages. SIRT1 silencing reversed acupuncture-induced counteractive effects on the aforementioned OA-associated phenomena (except apoptosis, the experiment regarding which under SIRT1 silencing was not performed). Collectively, acupuncture inhibited chondrocyte apoptosis, inflammation, NF-κB signaling activation, and cartilage matrix degradation by upregulating SIRT1 expression to delay OA-associated cartilage degeneration.
The Modelling of Digital Twins Technology in the Construction Process of Prefabricated Buildings
Authors: Zhou Yun , Wei Xiao , Peng Ying
Published: December 2021

In the process of building construction, traditional architectural design and construction methods take a long time. The built buildings perform poorly in terms of energy usage and energy conservation. The study expects to explore the potential safety hazards of prefabricated buildings during the construction process. On this basis, a modelling study of the construction process is carried out. The study uses Digital Twins (DTs) technology and prefabricated Building Information Modelling (BIM) to conduct in‐depth modelling research on the building construction process. The prefabricated building construction system oriented to DTs technology can well solve the problems of structural damage and deformation in the production, transportation, and assembly process of building components. Especially in prefabricated buildings, it can monitor and accurately predict the damage of building components that may occur in the entire system due to structural problems and material problems in real time. Regarding the building information model, the study uses third‐party software to transfer the assembly information to the network cloud to further realize the display of the BIM. The study shows that the maximum value of the effective risk cases selected is 130, and its effective rate is 100%; after processing the data, it is found that the initial value is always stable, and its value is 1; the extracted value is always changing, the maximum value is 0.86, and the minimum is 0.75. By this result, the conclusion is that DTs technology and BIM can effectively monitor the indicators of risk problems during the construction of prefabricated buildings and can further reduce potential safety hazards. Through building information modelling, the development of intelligent industrialization of building construction design and the in‐depth study of construction modelling has practical application value.
Occupational Exposure of Health-Care Workers to Blood and Body Fluids in West Shewa Zone, Ethiopia, 2018: A Cross-Sectional Study
Authors: Lemessa Dejene , Solomon Tesfaye
Published: December 2021

Background. Health-care workers are susceptible to acquiring blood and body fluids borne infections due to their occupations involving contact with patients and their body fluids, although studies conducted in Ethiopia are scarce. Therefore, the aim of this study was to investigate the magnitude of exposure to blood and body fluids among health-care workers in governmental health facilities in West Shewa Zone, Ethiopia. Materials and Methods. A facility-based cross-sectional study was conducted from May 19 to June 25, 2018. A total of 381 health-care workers were selected by simple random sampling from 31 sampled governmental health facilities using proportional to size allocation. Data were collected through self-administered questionnaires, entered into Epi Info version 7, and analyzed by SPSS version 21. Adjusted odds ratio (AOR) with 95% confidence intervals (CI) calculated for variables retained in the multivariable logistic regression and significance declared at

p
<
0.05

. Results. Of 377 health-care workers who participated, the study found that 233 (61.2%) were exposed to blood and body fluids in their lifetime. Previous needlestick injury (AOR = 0.30; 95% CI: 0.12–0.75), type of health facility (AOR = 0.42; 95% CI: 0.26–0.68), handwashing practice (AOR = 0.15; 95% CI: 0.07, 0.31), and perceiving at risk (AOR = 0.16; 95% CI: 0.03, 0.98) were protective factors, whereas long work experience (AOR = 1.47; 95% CI: 1.13–1.93) was a risk factor for the exposure. Conclusions. Exposures to blood and body fluids during patient care were common among health-care workers in the study area. Therefore, health-care workers especially those newly hired and working in hospitals should pay due attention to their occupation’s safety and regularly practice handwashing during critical times.
The Psychometric Properties of the Relaxation/Meditation/Mindfulness (RMM) Tracker t Inventory in an Iranian Population
Authors: Malakoutikhah Alireza , Zakeri Mohammad Ali , Salehi Derakhtanjani Ahmad , Dehghan Mahlagha
Published: December 2021

Background. A growing body of research has examined the psychometric properties of popular mindfulness inventories for different population. The present study is aimed at exploring the psychometric properties and factor structure of the Relaxation/Meditation/Mindfulness (RMM) Tracker t Inventory in Iran. Method. This was a cross‐sectional and methodological study that conducted in Kerman, southeast Iran. Fifty, 300, and 163 Iranian adult participants were participated in the pilot, exploratory, and confirmatory phase, respectively. Face, content, and structural validities, Cronbach’s alpha, and Omega coefficient were used to validate the Persian scale. Results. The results showed that the “Persian version of RMM t” had acceptable content and face validities. The Principal Axis Factoring (PAF) with Promax Rotation showed that the P‐RMM t has 3 scales of “Mindful Love, Thankfulness, and Transcendence,” “Relaxation,” and “Mindful Deepening” which further confirmed with confirmatory factor analysis. The internal consistency of all three scales was acceptable (Cronbach’s alpha coefficients > 80). Conclusion. The Persian version of RMM Tracker t seems to be a valid and reliable questionnaire to assess the levels of mindfulness in the Iranian general population.
[Retracted] Comprehensive Evaluation of BIM Calculation Quantity in Domestic Construction Engineering Based on Fuzzy Comprehensive Evaluation
Authors: Deng Yi , Rao Ziyuan , Cai Ling
Published: December 2021

Nowadays, with the leap‐forward development of computer technology and the transformation of information technology management concepts, China’s construction industry is quietly entering the era of refined management. Accurate estimation and cost control have become among the key considerations of the construction industry. For the calculation of engineering quantity, there are already many software devices that can be used for the calculation of engineering structure quantity, which means that the incorrect operation of personnel has been reduced to some extent, improving the work efficiency and measurement accuracy. The purpose of this paper is to solve the problems of computational missing, computational errors, inefficiency, data loss, and repetitive system in traditional computing based on the advantages of BIM computing system, which provide a reliable basis for cost forecasting and control. At the same time, using BMI calculation system to solve the problem of steel reinforcement in construction engineering, as well as the use of personnel, the existing calculation software still needs a lot of time and energy. We proposed a comprehensive evaluation study of reinforcement calculation in domestic construction engineering BIM calculation system based on a fuzzy comprehensive evaluation. This paper first summarizes the BIM calculation system of construction engineering, uses fuzzy comprehensive evaluation system as an important evaluation index system in domestic construction engineering BIM calculation system, through the judgment of various factors affecting the actual effect of the calculation system, and uses the fuzzy evaluation system combined with a case to demonstrate the superiority of the proposed research. Therefore, through the above research and experiments, it is concluded that the research method of this paper solves many problems in the process of engineering structure reinforcement calculation and provides a good reference method for the establishment of comprehensive evaluation system of reinforcement calculation, as well as providing an effective validation for the widespread use of BIM technology in the construction industry. Finally, it is also beneficial for users to comprehensively evaluate the BIM calculation system of the construction industry and provide a basic reference condition for different industries to use and choose BIM calculation systems.
An Iterative Method for Solving Split Monotone Variational Inclusion Problems and Finite Family of Variational Inequality Problems in Hilbert Spaces
Authors: Sriprad Wanna , Srisawat Somnuk
Published: December 2021

The purpose of this paper is to study the convergence analysis of an intermixed algorithm for finding the common element of the set of solutions of split monotone variational inclusion problem (SMIV) and the set of a finite family of variational inequality problems. Under the suitable assumption, a strong convergence theorem has been proved in the framework of a real Hilbert space. In addition, by using our result, we obtain some additional results involving split convex minimization problems (SCMPs) and split feasibility problems (SFPs). Also, we give some numerical examples for supporting our main theorem.
Towards Integration of Domain Knowledge‐Guided Feature Engineering and Deep Feature Learning in Surface Electromyography‐Based Hand Movement Recognition
Authors: Wei Wentao , Hu Xuhui , Liu Hua , Zhou Ming , Song Yan
Published: December 2021

As a machine‐learning‐driven decision‐making problem, the surface electromyography (sEMG)‐based hand movement recognition is one of the key issues in robust control of noninvasive neural interfaces such as myoelectric prosthesis and rehabilitation robot. Despite the recent success in sEMG‐based hand movement recognition using end‐to‐end deep feature learning technologies based on deep learning models, the performance of today’s sEMG‐based hand movement recognition system is still limited by the noisy, random, and nonstationary nature of sEMG signals and researchers have come up with a number of methods that improve sEMG‐based hand movement via feature engineering. Aiming at achieving higher sEMG‐based hand movement recognition accuracies while enabling a trade‐off between performance and computational complexity, this study proposed a progressive fusion network (PFNet) framework, which improves sEMG‐based hand movement recognition via integration of domain knowledge‐guided feature engineering and deep feature learning. In particular, it learns high‐level feature representations from raw sEMG signals and engineered time‐frequency domain features via a feature learning network and a domain knowledge network, respectively, and then employs a 3‐stage progressive fusion strategy to progressively fuse the two networks together and obtain the final decisions. Extensive experiments were conducted on five sEMG datasets to evaluate our proposed PFNet, and the experimental results showed that the proposed PFNet could achieve the average hand movement recognition accuracies of 87.8%, 85.4%, 68.3%, 71.7%, and 90.3% on the five datasets, respectively, which outperformed those achieved by the state of the arts.
Cartesian Products of Some Regular Graphs Admitting Antimagic Labeling for Arbitrary Sets of Real Numbers
Authors: Chang Yi-Wu , Liu Shan-Pang
Published: December 2021

An edge labeling of graph

G

with labels in

A

is an injection from

E

G

to

A

, where

E

G

is the edge set of

G

, and

A

is a subset of

ℝ

. A graph

G

is called

ℝ

-antimagic if for each subset

A

of

ℝ

with

A

=

E

G

, there is an edge labeling with labels in

A

such that the sums of the labels assigned to edges incident to distinct vertices are different. The main result of this paper is that the Cartesian products of complete graphs (except

K

1

) and cycles are

ℝ

-antimagic.
Monitoring Population Phenology of Asian Citrus Psyllid Using Deep Learning
Authors: Bibi Maria , Hanif Muhammad Kashif , Sarwar Muhammad Umer , Khan Muhammad Irfan , Khan Shouket Zaman , Shikali Shivachi Casper , Anees Asad
Published: December 2021

Asian citrus psyllid, Diaphorina citri Kuwayama (Liviidae: Hemiptera) is a menacing and notorious pest of citrus plants. It vectors a phloem vessel‐dwelling bacterium Candidatus Liberibacter asiaticus, which is a causative pathogen of the serious citrus disease known as Huanglongbing. Huanglongbing disease is a major bottleneck in the export of citrus fruits from Pakistan. It is being responsible for huge citrus economic losses globally. In the current study, several prediction models were developed based on regression algorithms of machine learning to monitor different phenological stages of Asian citrus psyllid to predict its population about different abiotic variables (average maximum temperature, average minimum temperature, average weekly temperature, average weekly relative humidity, and average weekly rainfall) and biotic variable (host plant phenological patterns) in citrus‐growing regions of Pakistan. The pest prediction models can be used for proper applications of pesticides only when needed for reducing the environmental and cost impacts of pesticides. Pearson’s correlation analysis was performed to find the relationship between different predictor (abiotic and biotic) variables and pest infestation rate on citrus plants. Multiple linear regression, random forest regressor, and deep neural network approaches were compared to predict population dynamics of Asian citrus psyllid. In comparison with other regression techniques, a deep neural network‐based prediction model resulted in the least root mean squared error values while predicting egg, nymph, and adult populations.
Exploration of the Danggui Buxue Decoction Mechanism Regulating the Balance of ESR and AR in the TP53-AKT Signaling Pathway in the Prevention and Treatment of POF
Authors: Liu Huaiquan , Yang Hong , Qin Zhong , Chen Yunzhi , Yu Haiyang , Li Wen , Zhu Xing , Cai Jingwen , Chen Jing , Zhang Mengzhi
Published: December 2021

Objective. The purpose of this study was to explore the molecular mechanism of Danggui Buxue Decoction (DBD) intervening premature ovarian failure (POF). Methods. The active compounds-targets network, active compounds-POF-targets network, and protein-protein interaction (PPI) network were constructed by a network pharmacology approach: Gene Ontology (GO) function and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis by DAVID 6.8 database. The molecular docking method was used to verify the interaction between core components of DBD and targets. Then, High-Performance Liquid Chromatography (HPLC) analysis was used to determine whether the DBD contained two key components including quercetin and kaempferol. Finally, the estrous cycle, organ index, ELISA, and western blot were used to verify that mechanism of DBD improved POF induced by cyclophosphamide (CTX) in rats. Results. Based on the network database including TCMSP, Swiss Target Prediction, DisGeNET, DrugBank, OMIM, and Malacard, we built the active compounds-targets network and active compounds-POF-targets network. We found that 2 core compounds (quercetin and kaempferol) and 5 critical targets (TP53, IL6, ESR1, AKT1, and AR) play an important role in the treatment of POF with DBD. The GO and KEGG enrichment analysis showed that the common targets involved a variety of signaling pathways, including the reactive oxygen species metabolic process, release of Cytochrome C from mitochondria and apoptotic signaling pathway, p53 signaling pathway, the PI3K-Akt signaling pathway, and the estrogen signaling pathway. The molecular docking showed that quercetin, kaempferol, and 5 critical targets had good results regarding the binding energy. Chromatography showed that DBD contained quercetin and kaempferol compounds, which was consistent with the database prediction results. Based on the above results, we found that the process of DBD interfering POF is closely related to the balance of ESR and AR in TP53-AKT signaling pathway and verified animal experiments. In animal experiments, we have shown that DBD and its active compounds can effectively improve estrus cycle of POF rats, inhibit serum levels of FSH and LH, protein expression levels of Cytochrome C, BAX, p53, and IL6, and promote ovary index, uterine index, serum levels of E2 and AMH, and protein expression levels of AKT1, ESR1, AR, and BCL2. Conclusions. DBD and its active components could treat POF by regulating the balance of ESR and AR in TP53-AKT signaling pathway.
Information Flow from COVID‐19 Pandemic to Islamic and Conventional Equities: An ICEEMDAN‐Induced Transfer Entropy Analysis
Authors: Bossman Ahmed
Published: December 2021

With the steady growth in the data set on the COVID‐19 pandemic, empirical works that employ novel and yet appropriate statistical techniques to corroborate previous findings of the pandemic and its consequences on financial markets are necessary. This paper examined the impact of COVID‐19 information flow on the Islamic and conventional equities within the short‐, mid‐, and long‐term horizons to assess possible diversification prospects in the era of the pandemic. To the studied equities markets, a novel technique based on a denoised frequency‐domain entropy paradigm was applied. The operability of entrenched market dynamics in the long‐term horizon of the COVID‐19 pandemic period is reinforced by the results. The findings divulge diversification opportunities between Islamic and conventional equities in the short‐ and mid‐term periods of the COVID‐19 pandemic. The risks on equities from Japan or Bahrain could be diversified by equities from Jordan in the short‐term, while in the intermediate‐term stocks from Japan could diversify with the UAE and USA equities. The results imply that it is imperative for investors and fund managers to employ portfolio management techniques that show how to use benefits together with risk prevention and management across distinct time scales.
Identifying Coronary Artery Lesions by Feature Analysis of Radial Pulse Wave: A Case‐Control Study
Authors: Zhang Chun-ke , Liu Lu , Wu Wen-jie , Wang Yi-qin , Yan Hai-xia , Guo Rui , Yan Jian-jun
Published: December 2021

Background. Cardiovascular diseases have been always the most common cause of morbidity and mortality worldwide. Health monitoring of high‐risk and suspected patients is essential. Currently, invasive coronary angiography is still the most direct and accurate method of determining the severity of coronary artery lesions, but it may not be the optimal clinical choice for suspected patients who had clinical symptoms of coronary heart disease (CHD) such as chest pain but no coronary artery lesion. Modern medical research indicates that radial pulse waves contain substantial pathophysiologic information about the cardiovascular and circulation systems; therefore, analysis of these waves could be a noninvasive technique for assessing cardiovascular disease. Objective. The objective of this study was to analyze the radial pulse wave to construct models for assessing the extent of coronary artery lesions based on pulse features and investigate the latent value of noninvasive detection technology based on pulse wave in the evaluation of cardiovascular disease, so as to promote the development of wearable devices and mobile medicine. Method. This study included 529 patients suspected of CHD who had undergone coronary angiography. Patients were sorted into a control group with no lesions, a 1 or 2 lesion group, and a multiple (3 or more) lesion group as determined by coronary angiography. The linear time‐domain features and the nonlinear multiscale entropy features of their radial pulse wave signals were compared, and these features were used to construct models for identifying the range of coronary artery lesions using the k‐nearest neighbor (KNN), decision tree (DT), and random forest (RF) machine learning algorithms. The average precision of these algorithms was then compared. Results. (1) Compared with the control group, the group with 1 or 2 lesions had increases in their radial pulse wave time‐domain features H2/H1, H3/H1, and W2 (P < 0.05), whereas the group with multiple lesions had decreases in MSE1, MSE2, MSE3, MSE4, and MSE5 (P < 0.05). (2) Compared with the 1 or 2 lesion group, the multiple lesion group had increases in T1/T (P < 0.05) and decreases in T and W1 (P < 0.05). (3) The RF model for identifying numbers of coronary artery lesions had a higher average precision than the models built with KNN or DT. Furthermore, average precision of the model was highest (80.98%) if both time‐domain features and multiscale entropy features of radial pulse signals were used to construct the model. Conclusion. Pulse wave signal can identify the range of coronary artery lesions with acceptable accuracy; this result is promising valuable for assessing the severity of coronary artery lesions. The technique could be used to development of mobile medical treatments or remote home monitoring systems for patients suspected or those at high risk of coronary atherosclerotic heart disease.
Identification of Cross-Talk and Pyroptosis-Related Genes Linking Periodontitis and Rheumatoid Arthritis Revealed by Transcriptomic Analysis
Authors: Jing Yongbin , Han Dong , Xi Chunyang , Yan Jinglong , Zhuang Jinpeng
Published: December 2021

Background. The current study is aimed at identifying the cross-talk genes between periodontitis (PD) and rheumatoid arthritis (RA), as well as the potential relationship between cross-talk genes and pyroptosis-related genes. Methods. Datasets for the PD (GSE106090, GSE10334, GSE16134) and RA (GSE55235, GSE55457, GSE77298, and GSE1919) were downloaded from the GEO database. After batch correction and normalization of datasets, differential expression analysis was performed to identify the differentially expressed genes (DEGs). The cross-talk genes linking PD and RA were obtained by overlapping the DEGs dysregulated in PD and DEGs dysregulated in RA. Genes involved in pyroptosis were summarized by reviewing literatures, and the correlation between pyroptosis genes and cross-talk genes was investigated by Pearson correlation coefficient. Furthermore, the weighted gene coexpression network analysis (WGCNA) was carried out to identify the significant modules which contained both cross-talk genes and pyroptosis genes in both PD data and RA data. Thus, the core cross-talk genes were identified from the significant modules. Receiver-operating characteristic (ROC) curve analysis was performed to identify the predictive accuracy of these core cross-talk genes in diagnosing PD and RA. Based on the core cross-talk genes, the experimentally validated protein-protein interaction (PPI) and gene-pathway network were constructed. Results. A total of 40 cross-talk genes were obtained. Most of the pyroptosis genes were not differentially expressed in disease and normal samples. By selecting the modules containing both cross-talk genes or pyroptosis genes, the blue module was identified to be significant module. Three genes, i.e., cross-talk genes (TIMP1, LGALS1) and pyroptosis gene-GPX4, existed in the blue module of PD network, while two genes (i.e., cross-talk gene-VOPP1 and pyroptosis gene-AIM2) existed in the blue module of RA network. ROC curve analysis showed that three genes (TIMP1, VOPP1, and AIM2) had better predictive accuracy in diagnosing disease compared with the other two genes (LGALS1 and GPX4). Conclusions. This study revealed shared mechanisms between RA and PD based on cross-talk and pyroptosis genes, supporting the relationship between the two diseases. Thereby, five modular genes (TIMP1, LGALS1, GPX4, VOPP1, and AIM2) could be of relevance and might serve as potential biomarkers. These findings are a basis for future research in the field.
Seismic Behavior of Elliptical Concrete‐Filled Steel Tubular Columns under Combined Axial Compression and Cyclic Lateral Loading
Authors: Xu YouWu , Yao Jian , Hu Feng , Zhou Ying , Jiang Shuai
Published: December 2021

Elliptical concrete‐filled steel tubular (CFST) column is a new form of CFST columns, consisting of an outer elliptical tube filled with concrete. Although the study on mechanical performance of the elliptical CFST members is receiving more and more attention, they have been limited to static behavior. Against this background, an experimental study on elliptical CFST columns was carried out under combined axial compression and cyclic lateral loading. The failure modes, hysteretic curves, skeleton curves, load carrying capacity, deformability, stiffness degradation, and energy dissipation ability was obtained and discussed. The test results indicated that the elliptical CFST columns possess excellent seismic performance and ductility. Valuable experimental data were provided for the formulation of the theoretical hysteresis model of the elliptical CFST columns.
Threshold Dynamics of a Diffusive Herpes Model Incorporating Fixed Relapse Period in a Spatial Heterogeneous Environment
Authors: Lu Yueming , Yang Wei , Ji Desheng
Published: December 2021

In this paper, we aim to establish the threshold‐type dynamics of a diffusive herpes model that assumes a fixed relapse period and nonlinear recovery rate. It turns out that when considering diseases with a fixed relapse period, the diffusion of recovered individuals will lead to nonlocal recovery term. We characterize the basic reproduction number, ℜ0, for the model through the next generation operator approach. Moreover, in a homogeneous case, we calculate the ℜ0 explicitly. By utilizing the principal eigenvalue of the associated eigenvalue problem or equivalently by ℜ0, we establish the threshold‐type dynamics of the model in the sense that the herpes is either extinct or close to the epidemic value. Numerical simulations are performed to verify the theoretical results and the effects of the spatial heterogeneity on disease transmission.
An Empirical Analysis of Oil and Stock Markets’ Volatility Based on the DGC-MSV-t Model
Authors: Zhang Jing , Zhuang Ya-Ming , Liu Jia-Bao
Published: December 2021

We investigate the spillover effect between crude oil future prices, crude oil spot prices, and stock index by using the multivariate stochastic volatility model. These tests between each market show the significant Granger causes of spillover effect. More and more evidences show that the crude oil price has been affected by other financial markets. The oil future played an important role in the energy market. WTI and Brent oil future have more spillover effect than INE oil future. The result shows that S&P stock market is more sensitive to the oil price than Shanghai stock market. The cross-market spillover effect we found can give some advices for the investor of oil and stock market. DIC test shows that DGC-MSV-t is considered effective and more accurate.
High-Capacity Robust Behavioral Steganography Method Based on Timestamp Modulation across Social Internet of Things
Authors: Zhang Mingliang , Luo Xiangyang , Zhang Pei , Li Hao , Zhang Yi , Li Lingling
Published: December 2021

Social Internet of Things (SIoT) is an emerging field that combines IoT and Internet, which can provide many novel and convenient application scenarios but still faces challenges in data privacy protection. In this paper, we propose a robust behavioral steganography method with high embedding capacity across social networks based on timestamp modulation. Firstly, the IoT devices on the sending end modulate the secret message to be embedded into a timestamp by using the common property on social networks. Secondly, the accounts of multiple social networks are used as the vertices, and the timestamp mapping relationship generated by the interaction behaviors between them is used as the edges to construct a directed secret message graph across social networks. Then, the frequency of interaction behaviors generated by users of mainstream social networks is analyzed; the corresponding timestamps and social networks are used to implement interaction behaviors based on the secret message graph and the frequency of interaction behaviors. Next, we analyze the frequency of interaction behaviors generated by users in mainstream social networks, implement the interaction behaviors according to the secret message graph and the frequency of interaction behaviors in the corresponding timestamps and social networks, and combine the redundant mapping control to complete the embedding of secret message. Finally, the receiver constructs the timestamp mapping relationship through the shared account, key, and other parameters to achieve the extraction of secret message. The algorithm is robust and does not have the problem that existing multimedia-based steganography methods are difficult to extract the embedded messages completely. Compared with existing graph theory-based social network steganography methods, using timestamps and behaviors frequencies to hide message in multiple social networks increases the cost of detecting covert communication and improves concealment of steganography. At the same time, the algorithm uses a directed secret message graph to increase the number of bits carried by each behavior and improves the embedding capacity. A large number of tests have been conducted on mainstream social networks such as Facebook, Twitter, and Weibo. The results show that the proposed method successfully distributes secret message to multiple social networks and achieves complete extraction of embedded message at the receiving end. The embedding capacity is increased by 1.98–4.89 times compared with the existing methods SSN, NGTASS, and SGSIR.
Berberine Protects against TNF-α-Induced Injury of Human Umbilical Vein Endothelial Cells via the AMPK/NF-κB/YY1 Signaling Pathway
Authors: Chen Li , Fan Xiao-Di , Qu Hua , Bai Rui-Na , Shi Da-Zhuo
Published: December 2021

Endothelial injury, characterized by an inflammatory response and increased permeability, is an initial stage of atherosclerosis (AS). Adenosine 5′-monophosphate (AMP), activated protein kinase (AMPK), and Nuclear Factor kappa B (NF-κB)/Yin Yang 1(YY1) signaling pathways play important roles in the process of endothelial injury. Berberine (BBR), a bioactive alkaloid isolated from several herbal substances, possesses multiple pharmacological effects, including anti-inflammatory, antimicrobial, antidiabetic, anticancer, and antioxidant activities. Previous studies showed a protective effect of berberine against endothelial injury. However, the underlying mechanism remains unclear. We explored the potential effect of BBR on TNF- (tumor necrosis factor-) α-induced injury of human umbilical endothelial cells (HUVECs) and studied its possible molecular mechanism. In the present study, HUVECs were divided into three groups. HUVEC viability was measured with Cell Counting Kit-8 assay. Extracellular lactic dehydrogenase (LDH) concentration was measured with LDH leakage assay. Endothelial microparticle (EMP) numbers were evaluated by flow cytometry analysis assay. The expression of proinflammatory cytokines was evaluated by Enzyme-Linked Immunosorbent Assay (ELISA). The mRNA expression of NF-κB and YY1 was detected by Real-Time PCR (RT-PCR). The protein expression of NF-κB, YY1, and AMPK was detected by immunofluorescence microscopy assay or western blot analysis. The results showed that LDH concentration, EMPs numbers, and the expression of proinflammatory cytokines (IL-6, IL-8, and IL-1β) increased in TNF-α-induced injured HUVECs, but ameliorated by BBR pretreatment. BBR pretreatment upregulated the expression of phosphorylated AMPK and downregulated the expressions of NF-κB and YY1 in injured HUVECs induced by TNF-α, which were offset by the AMPK inhibitor Compound C (CC). The results indicated that BBR protected against TNF-α-induced endothelial injury via the AMPK/NF-κB/YY1 signaling pathway.
Intraoperative Use of Topical Retropharyngeal Steroids for Dysphagia after Anterior Cervical Fusion: A Systematic Review and Meta-Analysis
Authors: Yu Hang , Dong Hui , Ruan Binjia , Xu Xiaohang , Wang Yongxiang
Published: December 2021

Purpose. The anterior cervical approach is commonly used clinically for cervical spondylosis, but it also results in frequent postoperative dysphagia, which can increase the risk of complications and poor treatment satisfaction in severe cases. Intraoperative local application of retropharyngeal steroids has an impact on reducing the occurrence and severity of dysphagia; however, the results of current studies vary. The meta-analysis of this randomized trial was to evaluate the effectiveness and safety of intraoperative topical retropharyngeal steroids for the control of dysphagia after anterior cervical spine surgery. Methods. Two authors searched electronic databases such as PubMed, MEDLINE, EMBASE, Cochrane Library, and Google Scholar, respectively. The search terms were “Dysphagia,” “Steroids,” “Anterior Cervical Discectomy and Fusion,” etc. A random effects model was used to conduct a meta-analysis based on deviance information criteria. Results. A total of 8 studies were included in this meta-analysis after screening of 792 studies. Bazaz scores were not significantly different in the steroid group at one day postoperatively (

P
=
0.38

), and dysphagia was significantly improved at 14 days postoperatively (95% CI: 0.15 to 0.64;

P
=
0.002

). PSTSI was significantly improved one day (

P
=
0.03

) and 14 days after surgery (

P
<
0.0001

). VAS scores were all lower versus controls (

P
<
0.001

). Conclusion. Perioperative local retropharyngeal steroid administration as an adjunct to anterior cervical spine surgery reduces the incidence and severity of dysphagia compared with placebo control. However, future high-quality randomized controlled studies could incorporate nonsubjective dysphagia measures and long-term follow-up on the occurrence of associated complications or other side effects.
On Analysis of Banhatti Indices for Hyaluronic Acid Curcumin and Hydroxychloroquine
Authors: Wang Wenhu , Naeem Muhammad , Rauf Abdul , Riasat Ayesha , Aslam Adnan , Anoh Yannick Kraidi
Published: December 2021

Topological indices are numerical numbers assigned to the graph/structure and are useful to predict certain physical/chemical properties. In this paper, we give explicit expressions of novel Banhatti indices, namely, first K Banhatti index

B

1

G

, second K Banhatti index

B

2

G

, first K hyper-Banhatti index

HB

1

G

, second K hyper-Banhatti index

HB

2

G

, and K Banhatti harmonic index

H

b

G

for hyaluronic acid curcumin and hydroxychloroquine. The multiplicative version of these indices is also computed for these structures.