bluuebunny/crossref_metadata_2025 huggingface dataset:
Identifying Active Substances and the Pharmacological Mechanism of Houttuynia cordata Thunb. in Treating Radiation-Induced Lung Injury Based on Network Pharmacology and Molecular Docking Verification
Authors: Lai Gui-Hua , Wang Fei , Nie Duo-Rui , Lei Shu-Jun , Wu Zhuo-Jun , Cao Jian-Xiong
Published: March 2022

Background. Houttuynia cordata Thunb. is a traditional Chinese herb widely used mainly because of the pharmacological effects related to heat clearance and detoxification. Emerging clinical evidence indicates that the efficacy of Houttuynia cordata Thunb. on RILI is upstanding. Nevertheless, its underlying therapeutic mechanism remains unclear and warrants further elucidation. Methods. The major active components and corresponding targets of Houttuynia cordata Thunb. were retrieved from the traditional Chinese medicine system pharmacology database (TCMSP) and literature review. The related targets of RILI were retrieved from the GeneCards database. Common targets among the active compounds and diseases were identified through Venn diagram analysis. Cytoscape was employed to construct and visualize the network relationship among the drug, active compounds, targets, and disease. The protein interaction network (PPI) was constructed by STRING. The reliability (the binding affinity) of the core targets and active compounds was verified by molecular docking. Results. A search of the TCMSP database and related literature revealed 12 active compounds of Houttuynia cordata Thunb. against RILI. The core active compounds included quercetin, kaempferol, hyperoside, and rutin. Hub nodes including TP53, VEGFA, JUN, TNF, and IL-6 were identified in the PPI network. The GO categories were classified into three functional categories: 112 biological processes, 9 molecular functions, and 32 cellular components of the active compounds of Houttuynia cordata Thunb. The KEGG pathway enrichment analysis demonstrated the enrichment of target genes in several key cancer-related signaling pathways, including the cancer pathways, TNF signaling pathway, PI3K-Akt signaling pathway, and HIF-1 signaling pathway. Molecular docking analysis validated the effective binding capacity of the main active compounds with the core targets. Conclusion. The main active components of Houttuynia cordata Thunb. have a potential pharmacological effect against RILI via the cancer pathways, TNF signaling pathway, and PI3K-Akt signaling pathway.
Protective Mechanism of Leucine and Isoleucine against H2O2-Induced Oxidative Damage in Bovine Mammary Epithelial Cells
Authors: Wu Sainan , Liu Xize , Cheng Long , Wang Duojia , Qin Guixin , Zhang Xuefeng , Zhen Yuguo , Wang Tao , Sun Zhe
Published: March 2022

Leucine and isoleucine possess antioxidative and anti-inflammatory properties. However, their underlying protective mechanisms against oxidative damage remain unknown. Therefore, in this study, the protective mechanism of leucine and isoleucine against H2O2-induced oxidative damage in a bovine mammary epithelial cell lines (MAC-T cells) were investigated. Briefly, MAC-T cells exposed or free to H2O2 were incubated with different combinations of leucine and isoleucine. The cellular relative proliferation rate and viability, oxidative stress indicators, and inflammatory factors were determined by specific commercial kits. The genes related to barrier functions was measured by real-time quantitative PCR. The protein expression differences were explored by 4D label-free quantitative proteomic analyses and validated by parallel reaction monitoring. The results revealed that leucine and isoleucine increased cell proliferation, total antioxidant status (TAS), and the relative mRNA expression of occludin, as well as decreased malondialdehyde (MDA), total oxidant status (TOS)/TAS, IL-6, IL-1β, and TOS. When leucine and isoleucine were combined, MDA, TOS/TAS, and the relative mRNA expression levels of claudin-1, occludin, and zonula occludens-1 increased when compared to leucine or isoleucine alone. Proteomics analyses revealed that leucine significantly upregulated the propanoate metabolism; valine, leucine, and isoleucine degradation; and thermogenesis pathways, whereas isoleucine significantly upregulated the peroxisome and propanoate metabolism pathways. In conclusion, leucine protected MAC-T cells from H2O2-induced oxidative stress by generating more ATP to supplement energy demands, and isoleucine improved the deficit in peroxisome transport and promoted acetyl-CoA production. The findings of this study enhance our understanding of the protective mechanisms of leucine and isoleucine against oxidative damage.
Evaluation of Key Factors of Logistics Risks for Overseas EPC Projects
Authors: He Jingshi , Han Dai
Published: March 2022

Correctly identifying and evaluating the logistics risks of EPC (engineering procurement construction) projects is conducive to strengthening the risk prevention and control of engineering projects. An evaluation index system for the logistics risk factors of overseas EPC projects was established, and the entropy‐DEA (Data Envelopment Analysis) method used to evaluate and sort risk decision‐making unit (DMU) with risk likelihood and risk consequences as decision variables. The risk reduction ratio and improvement space of each risk DMU are obtained, and the risk factor distribution matrix is constructed, pointing out that legal risks, operational risks and management risks are the primary risk DMU, which provide reference decisions for the optimal allocation of resources. Finally, it is proposed to carefully select overseas logistics carriers, conduct in‐depth research before formulating logistics plans, pay attention to logistics process tracking and supervision, and strengthen logistics packaging and bundling technologies.
Nonlinear Seismic Response Based on Different Site Types: Soft Soil and Rock Strata
Authors: Xiao Meng , Cui Jie , Li Ya-dong , Nguyen Van-Quang
Published: March 2022

Site condition is an important part of urban underground space development and construction. The seismic fortification of the site plays an important role in the safety of the whole project. To study the seismic dynamic response of the site under different geological conditions, seismic waves of different intensities (Chichi wave and Kobe wave) were input to a rock site with good geological conditions and a soft soil site, respectively. In this paper, the dynamic responses of these two types of free sites were calculated and analyzed using DEEPSOIL numerical simulation software. The dynamic responses of different types of sites under strong shock and persistent earthquakes are discussed under the equivalent linear and nonlinear conditions, and the related dynamic parameters are studied. The results show that the equivalent linear method is more effective than the nonlinear method, especially in the calculation of the strong nonlinear soft soil response induced by strong earthquakes. The amplification effect is more obvious in rock layer sites under strong earthquakes, and the “weakening” effect of soft soil sites is more obvious. Arias’s strength values show that both types of sites are safe under the incident of the two waves, but soft soil sites have better seismic performance. The results calculated by the equivalent linear method are larger and more unsafe; in particular, in the case of a strong earthquake with a stronger nonlinear Kobe wave, the results are more inaccurate. The purpose of this study is to provide a reference for seismic design and reinforcement measures of underground engineering.
Differential Prognostic Analysis of Higher and Lower PEEP in ARDS Patients: Systematic Review and Meta-Analysis
Authors: Liang Min , Chen Xin
Published: March 2022

Background. Positive end-expiratory pressure (PEEP) refers to the positive pressure in the respiratory tract at the end of the exhalation when we use a ventilator. The differences of higher PEEP and lower PEEP on clinical outcomes in acute respiratory distress syndrome (ARDS) patients are less well known. Methods. A comprehensive literature search of all randomized control trials (RCTs) was conducted using PubMed, Embase, World Health Organization (WHO) Global Index Medicus, WHO clinical trial registry, and Clinicaltrials.gov. Inclusion criteria included RCTs comparing the clinical outcomes of higher and lower PEEP in ARDS patients. Results. Eleven studies were included in the final analysis. In the higher PEEP group, the hospital mortality, 28-day mortality, and ICU mortality showed no significantly lower risk compared to the lower PEEP group (RR = 0.92, 95% CI 0.80–1.05, p = 0.22; RR = 0.88, 95% CI 0.73–1.05, p = 0.15; RR = 0.84, 95% CI 0.67–1.05, p = 0.12; respectively). High certainty could be obtained that there is no significant difference between the clinical outcomes of higher PEEP and lower PEEP in ARDS patients. Conclusions. There is no significant difference of the hospital mortality, 28-day mortality, and ICU mortality between higher and lower PEEP in ARDS patients.
Further Results on Total Edge‐Vertex Domination
Authors: Şahin Abdulgani
Published: March 2022

Total edge‐vertex domination is a new total domination‐type parameter. In this paper, the author shows that determining the total edge‐vertex domination number in bipartite planar graphs is NP‐complete. Also, the author obtains a structural relation between total domination number and total edge‐vertex domination number and characterizes the trees whose total edge‐vertex domination number is equal to total domination number.
Renal and Inflammatory Proteins as Biomarkers of Diabetic Kidney Disease and Lupus Nephritis
Authors: Johnson Nathan H. , Keane Robert W. , de Rivero Vaccari Juan Pablo
Published: March 2022

Current methods for differentiation of kidney disease types are unspecific and may be invasive. Thus, there is a need for development of new biomarkers of kidney disorders that are specific and less invasive. In this study, we analyzed serum samples of diabetic kidney disease (DKD) and lupus nephritis (LN) patients to identify biomarkers of these two disorders. Serum samples were analyzed by Simple Plex assays. We calculated the area under the curve (AUC) as well as receiver operating characteristics (ROC) to obtain the sensitivity and specificity and other biomarker-related variables of apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC), interleukin- (IL-) 18, Lipocalin-2/NGAL, epidermal growth factor (EGF), u-Plasminogen Activator (uPA), and C-reactive protein (CRP) as potential biomarkers. Protein levels of ASC, IL-18, EGF, and Lipocalin-2/NGAL were higher in DKD and LN patients when compared to controls, whereas only uPA was elevated in DKD patients and CRP in LN patients. As determined by the AUC, of the six analytes studied, EGF (

AUC
=
0.9935

), Lipocalin-2/NGAL (0.9554), ASC (0.7666), and uPA (0.7522) are reliable biomarkers of DKD, whereas EGF (1.000), Lipocalin-2/NGAL (0.9412), uPA (0.7443), and IL-18 (0.7384) are more reliable for LN. The biomarkers analyzed can differentiate between healthy and affected individuals. However, there was no difference between the levels of these biomarkers in DKD vs LN. Thus, although these biomarkers cannot be used to categorize patients between DKD and LN, they are useful as biomarkers of renal pathology.
Characterization of Urban Bus Acceleration Cycles for Fatigue Analysis with a Portable Low-Cost Acquisition System
Authors: Pérez JesusAngel , Olazagoitia JoseLuis , Badea Francisco
Published: March 2022

The fatigue design of bus structures is directly dependent on the loads that the vehicle will support throughout its lifespan. The determination of such operational loads, obtained in form of accelerations through vehicle sensing, is usually done with proprietary and expensive acquisition systems. In this paper, a low-cost acquisition system is presented and studied, which is designed, calibrated, and oriented for this purpose, based on an Arduino UNO and a low-cost accelerometer. The acquisitions are adapted to obtain the operational loads of several urban bus lines in the city of Madrid. The obtained data is later processed in order to characterize the acceleration cycles in these structures, which can be used as an input for the appropriate structural design. As a result, it is proved that the low-cost acquisition system is adequate and provides a simple and cheap way to characterize the acceleration of these vehicles during ordinary service.
Assessment of Sperm Viability and Computer-Assisted Motility Analysis in Budgerigars (Melopsittacus undulatus): Effect of Several In Vitro Processing Conditions
Authors: Madeddu Manuela , Marelli Stefano , Abdel Sayed Ahmad , Mosca Fabio , Cerolini Silvia , Zaniboni Luisa
Published: March 2022

In order to preserve endangered psittacine species, more basic and applied research in reproductive biology is required. Assisted reproductive technologies such as artificial insemination play an important role in parrots species conservation programs to overcome the problem of infertile eggs and male infertility. The aim of this study was to define an effective in vitro protocol in order to standardize the sperm quality evaluation in psittacines, studying Melopsittacus undulatus as model species. Semen was collected from twenty adult males by massage technique from May to June. Sperm concentration was measured by the spectrophotometric method. Sperm quality (sperm membrane integrity (SMI), motility, and kinetic parameters) was assessed on fresh semen. Three different experimental protocols were performed to compare the effects of various processing conditions on SMI, motility, and kinetic parameters. In protocol 1, test was performed by Lake extender with three different pH, 7.4 versus 8.2 versus 8.4, and two different equilibration temperatures after dilution of fresh semen (4°C versus 25°C). In protocol 2, two dilution rates of semen after collection were valuated, 1 : 3 versus 1 : 4, as well as three different semen storage temperatures (4°C versus 25°C versus 38°C) before sperm motility analysis with the computer-assisted sperm analysis (CASA). In protocol 3, two different Makler chamber temperatures (38 versus 41°C) during motility analysis were tested. A significant progressive improvement in spermatozoa motility and kinetic parameters was registered with pH 8.4. Progressive motility and all kinetic parameters were higher at 4°C equilibration temperature. Straightness (STR) kinetic parameter was better with 1 : 4 dilution rate. Total motile sperm was higher in 41°C Makler chamber. In this study, for the first time, the effects of different processing protocols on psittacines seminal quality analysis were investigated. Significant differences conditioning the effectiveness of analysis protocols have been described.
Effects of Organic Nano Calcium Carbonate on Aging Resistance of Bio-Asphalt
Authors: Xiao Nianting , Zhang Yongyi , Xia Hongbo , Lei Yu , Luo Yamin
Published: March 2022

To improve the aging resistance of bioasphalt and explore the impact of organic nano calcium carbonate (CaCO3) on the aging resistance of bioasphalt, the thin-film oven test (TFOT), basic property test, rheological test, four components test, and infrared spectrum test were used to study the bioasphalt with different organic nano-CaCO3 contents. The results show that the addition of organic nano-CaCO3 increases the residual penetration, residual ductility, and residual softening point of bioasphalt. Within the range of test dosage, the greater the dosage, the more significant the effect is. With the increase of organic nano-CaCO3 content, the complex modulus aging index (GAI) of bioasphalt gradually decreases, and the colloidal instability index (IC) gradually decreases. When the content is 6%, the GAI of organic nano-CaCO3 modified bioasphalt is less than that of matrix asphalt. The nanoscale super large specific surface area of organic nano-CaCO3 has an adsorption effect on the light components in bioasphalt, which slows down the volatilization loss of light components and the oxidation process of asphalt. The addition of organic nano-CaCO3 helps to reduce the change rate of the carbonyl index and sulfoxide index.
Effect of Different Nursing Interventions on Discharged Patients with Cardiac Valve Replacement Evaluated by Deep Learning Algorithm‐Based MRI Information
Authors: Zhang Jing , Zhou Qiong
Published: March 2022

This study was aimed to explore the application of cardiac magnetic resonance imaging (MRI) image segmentation model based on U‐Net in the diagnosis of a valvular heart disease. The effect of continuous nursing on the survival of discharged patients with cardiac valve replacement was analyzed in this study. In this study, the filling completion operation, cross entropy loss function, and guidance unit were introduced and optimized based on the U‐Net network. The heart MRI image segmentation model ML‐Net was established. We compared the Dice, Hausdorff distance (HD), and percentage of area difference (PAD) values between ML‐Net and other algorithms. The MRI image features of 82 patients with valvular heart disease who underwent cardiac valve replacement were analyzed. According to different nursing methods, they were randomly divided into the control group (routine nursing) and the intervention group (continuous nursing), with 41 cases in each group. The Glasgow Outcome Scale (GOS) score and the Self‐rating Anxiety Scale (SAS) were compared between the two groups to assess the degree of anxiety of patients and the survival status at 6 months, 1 year, 2 years, and 3 years after discharge. The results showed that the Dice coefficient, HD, and PAD of the ML‐Net algorithm were (0.896 ± 0.071), (5.66 ± 0.45) mm, and (15.34 ± 1.22) %, respectively. The Dice, HD, and PAD values of the ML‐Net algorithm were all statistically different from those of the convolutional neural networks (CNN), fully convolutional networks (FCN), SegNet, and U‐Net algorithms (P < 0.05). Atrial, ventricular, and aortic abnormalities can be seen in MRI images of patients with valvular heart disease. The cardiac blood flow signal will also be abnormal. The GOS score of the intervention group was significantly higher than that of the control group (P < 0.01). The SAS score was lower than that of the control group (P < 0.05). The survival rates of patients with valvular heart disease at 6 months, 1 year, 2 years, and 3 years after discharge were significantly higher than those in the control group (P < 0.05). The abovementioned results showed that an effective segmentation model for cardiac MRI images was established in this study. Continuous nursing played an important role in the postoperative recovery of discharged patients after cardiac valve replacement. This study provided a reference value for the diagnosis and prognosis of valvular heart disease.
Survival Analysis and a Novel Nomogram Model for Progression-Free Survival in Patients with Prostate Cancer
Authors: Han Yuefu , Wen Xingqiao , Chen Dong , Li Xiaojuan , Leng Qu , Wen Yuehui , Li Jun , Zhu Weian
Published: March 2022

Background. This study sought to perform a survival analysis and construct a prognostic nomogram model based on the Gleason grade, total prostate-specific antigen (tPSA), alkaline phosphate (ALP), and TNM stage in patients with prostate cancer (PCa). Methods. The progression-free survival (PFS) of 255 PCa patients was analyzed in this study. The prognostic value of tPSA and ALP was evaluated using the Kaplan-Meier survival curves and Cox regression analysis, and a nomogram model based on the Gleason grade, tPSA, ALP, and TNM stage was further established for PFS prediction in PCa patients. Results. PCa patients with different Gleason grades, tPSA and ALP levels, and TNM stages presented distinct PFS. The Gleason grade, tPSA, ALP, and TNM stage were four independent prognostic indicators. The C-index of the established nomogram was 0.705 for PFS in the test cohort and 0.687 for the validation cohort, and the calibration curves indicated a good consistency between predicted and actual PFS in PCa patients. Conclusion. The data of this study demonstrated that the Gleason grade, tPSA, ALP, and TNM stage of PCa patients are independently correlated with PFS, and a nomogram model based on these indicators may be valuable for the PFS prediction in PCa patient.
Implementation of a Teledentistry Platform for Dental Emergencies for the Elderly in the Context of the COVID‐19 Pandemic in Chile
Authors: Beltrán Víctor , von Marttens Alfredo , Acuña-Mardones Pablo , Sanzana-Luengo Cristina , Rueda-Velásquez Sandra J. , Alvarado Eloy , Flores Marco , Cerda Angeline , Venegas Bernardo
Published: March 2022

Objectives. To develop and implement a “semi‐presential” technology platform to support urgent and priority dental care for the elderly in the context of the COVID‐19 pandemic among the Chilean population. Methods. A dental mobile clinic was implemented along with the development of a technological platform designed to support emergency and priority dental procedures, including teleconsultation with specialists. Under strict biosafety protocols, dental care was provided in five Chilean regions between February and May 2021. Sociodemographic, medical, and dental data were recorded. Results. A total of 135 patients over sixty years old, with a mean age of 72 years, were treated, 48 males and 87 females were attended between February and May 2021 in five different regions of Chile. 53.3% required immediate or urgent treatment, and 24.4% were derived to specialists from whom 60.6% needed immediate or urgent treatment. 74.3% of teleconsultations were derived to an oral pathology specialist. Conclusion. It was shown that a “semi‐presential” technology platform implemented in a mobile dental clinic can help elderly people who are impeded to look for traditional dental assistance during a pandemic.
Network Traffic Monitoring and Marketing Strategy of Online Music Products in Multimedia Environment
Authors: Chen Cheng , Shu Ming Hung , Huang Hsiao-Chun , Chen Tung-Chun , Huang Jui-Chan
Published: March 2022

The network traffic monitoring and marketing strategy of online music products in the multimedia environment refers to the use of existing multimedia technologies to analyze the environment of the online music industry, accurately locate the needs of product users, and formulate more practical and effective network traffic monitoring and marketing strategies. This paper firstly gives a comprehensive overview of the concept and characteristics of online music and then analyzes the development status of the online music industry. Then, according to the current situation and marketing direction of the industry, three network traffic monitoring and marketing strategies for online music products are proposed. They are marketing strategy based on big data mining, marketing strategy based on new media platform, and marketing strategy based on O2O model. These three network traffic monitoring and marketing strategies all need to rely on the existing multimedia technology. Finally, the effectiveness and practicability of the proposed network traffic monitoring and marketing strategies are analyzed by comparing the network traffic monitoring and marketing strategies of online music products with the traditional marketing strategies in the multimedia environment. The experimental results show that the number of visits to music products under the multimedia environment marketing strategy is 1.2 times that of the traditional marketing strategy, and the download volume is 1.5 times that of the traditional marketing strategy. This has a very good effect on the marketing of online music products.
An Old Photo Image Restoration Processing Based on Deep Neural Network Structure
Authors: Wang Ruoyan
Published: March 2022

Old photos retain precious historical image information, but today’s existing old photos often have varying degrees of damage. Although these old photos can be digitally processed and then restored, the restoration of old photos involves multiple areas of image restoration and has various types of degradation. Currently, there is no unified model for repairing multiple types of degradation of old photos. Photo restoration technology still has a lot of developments. Traditional image restoration technology mainly repairs the missing areas of the image based on mathematical formulas or thermal diffusion. This technology can only repair images with simple structures and small damaged areas and is difficult to apply in people’s daily lives. The emergence of deep learning technology has accelerated the pace of research on image restoration. This article will discuss the methods of repairing old photos based on deep neural networks. It is aimed at proposing an image restoration method based on deep neural network to enhance the effect of image restoration of old photos and provide more possibilities for restoration of old photos. This article discusses the background significance of image restoration methods, designs an image restoration model based on deep neural networks, and introduces the structure, principle, and loss function of the model. Finally, this article did a comparative experiment to compare the model in this article with other models and draw the conclusion: in the blur repair experiment, the algorithm in this paper is better than other algorithms for the peak signal-to-noise ratio and structure similarity of the repaired image; in the damage repair experiment, the value of the algorithm’ s peak signal-to-noise ratio is 32.34, and the structure similarity under different damage average levels is 0.767, which is also higher than other algorithms. Therefore, the model in this paper has the best effect on image restoration.
Robust Watermarking Algorithm against the Geometric Attacks based on Non-Subsampled Shearlet Transform and Harris-Laplace Detector
Authors: Zhou Ling , Zuo Mei-Juan , Shi Hao , Zhang Ye , Gong Li-Hua
Published: March 2022

With the rapid spread of network information, the information maintenance has become the focus of information security on networks. Digital watermarking is one of the effective methods to protect information security, achieve anticounterfeiting traceability, and protect copyright, and it is an important branch of information hiding technology. However, one of the most challenging questions of digital watermarking is how to present strong robustness in geometric attacks. Nowadays, most watermarking algorithms are relatively weak robustness against geometric attacks. A robust watermarking algorithm against geometric attacks based on the non-subsampled shearlet transform and the Harris-Laplace detector is proposed. The host image is decomposed into subbands with different directions by the shearlet transform, and the Harris-Laplace detector is utilized to obtain the feature regions. Then, the nonoverlapping regions with strong robustness are selected to embed watermark by the fuzzy c-means cluster algorithm. The experimental results indicate that the proposed watermarking scheme can well resist geometric attacks.
Identification of Working Trucks and Critical Path Nodes for Construction Waste Transportation Based on Electric Waybills: A Case Study of Shenzhen, China
Authors: Bi Jun , Sai Qiuyue , Wang Fujun , Chen Yakun
Published: March 2022

Due to the large amount of waste generated by urban construction, the transportation of construction waste has a significant impact on urban traffic. Understanding the transportation trajectory of garbage trucks can improve the management of transportation routes and reduce traffic accidents. This study analyzes electric waybill and state data of garbage trucks to identify hot nodes of construction waste transportation, where the volume of garbage trucks is relatively high. Management should strengthen the hot nodes to reduce traffic accidents. First, several machine learning methods are used to improve the prediction accuracy of electric waybill generation, where the garbage truck recorded on the electric waybill is regarded as a working truck. Second, the transportation trajectory of working trucks is extracted, and its spatiotemporal characteristics are further analyzed. Hot nodes are found based on density clustering. Finally, a case study is conducted based on the Shenzhen construction waste transportation system. The results show that the XGBoost model can improve the accuracy of the generation of waybill to 90.5% compared with the decision tree model, random forest, and GBDT. Moreover, the density clustering model can discover the hot nodes of construction waste transportation. Considering the minimum number of samples and the neighborhood radius, the clustering number is determined as 100. The ratio of noise points is determined as 0.79. The results can provide decision support for the management of electronic waybill and garbage truck transportation.
Stability Analysis of the Crank-Nicolson Finite Element Method for the Navier-Stokes Equations Driven by Slip Boundary Conditions
Authors: Mbehou M. , Haggar M. S. Daoussa , Tahar H. Olei
Published: March 2022

This paper is devoted to the study of numerical approximation for a class of two-dimensional Navier-Stokes equations with slip boundary conditions of friction type. The objective is to establish the well-posedness and stability of the numerical scheme in

L

2

-norm and

H

1

-norm for all positive time using the Crank-Nicholson scheme in time and the finite element approximation in space. The resulting variational structure dealing with is in the form of inequality, and obtaining

H

1

-estimate is more involved because of the presence of the nondifferentiable term appearing at the boundary where slip occurs. We prove that the numerical scheme is stable in

L

2

and

H

1

-norms with the aid of different versions of discrete Grownwall lemmas, under a CFL-type condition. Finally, some numerical simulations are presented to illustrate our theoretical analysis.
Innovation Efficiency Evaluation of China’s High-Tech Industry considering Subindustry with a Parallel Slack-Based Measure Approach
Authors: Liu Ran , Zhang Hao , You Jianxin , Fu Gan
Published: March 2022

Although the performance estimation of technological innovation activities in the Chinese high-tech industry has been discussed continuously in prior literature, few studies analyze the imbalance development of subindustries and regional heterogeneity. Therefore, this study develops a parallel slack-based measure data envelopment analysis approach to estimate the innovation efficiency of the high-tech industry from regional and industrial perspectives. Compared with prior research, the proposed SBM-DEA model can be used to identify the inefficiencies caused by the subindustries via considering internal subindustries as parallel subunits. The proposed model is applied in the Chinese high-tech industry between 2011 and 2014. Empirical results reveal three critical findings. First, there exists an improving potential for innovation efficiency. Second, significant disparities in innovation efficiency are observed at the industrial level and regional level. Third, the inefficiency of the high-tech industry mainly stems from the low performance of the electronic equipment and communication equipment subindustry and computer and office equipment subindustry. Some suggestions for enhancing innovation efficiency are also proposed.
RTA-Assisted Type Well Construction in Montney Tight Gas Reservoir from Western Canada Sedimentary Basin
Authors: Kong Xiangwen , Wang Hongjun , Zhang Chunshu , Wang Ping , Zhang Wenjing
Published: March 2022

Tight gas reservoirs are mainly developed by multistage hydraulic fracturing horizontal wells (MSHFHWs). A type well provides average production profiles based on real well data and can be constructed from multiple wells to investigate the behavior of the reservoir. For unconventional reservoirs, type wells are the key to reserve calculations and medium- and long-term field development planning. Both geological and completion parameters are key factors affecting single well performance of MSHFHWs. Based on the drilling, hydraulic fracturing, and production data for over 1,800 MSHFHWs in the Montney tight gas reservoir in the Groundbirch region of the Western Canada Sedimentary Basin (WCSB), the main hydraulic fracturing factors affecting the production performance of MSHFHWs were investigated. A rate transient analysis- (RTA-) assisted workflow for type well construction is proposed based on existing production data and considering the geological and engineering factors. Based on the field data, the main hydraulic fracturing factors that affect the production performance of the MSHFHWs in Montney are lateral length, proppant tonnage, and the number of stages. Base type wells are predicted from the P50 wells, which are selected from the wells with normalized lateral length and the same fracturing technique and proppant tonnage. The base type well represents the well performance for a specific drilling and completion background. RTA was introduced to scale up the base type well to predict the type well of new completion design. The new workflow predicts both the base type well with a specific drilling and completion background and the upgraded type well, which uses new completion design. It is highly meaningful and provides a valuable reference to practical studies involving type well prediction in unconventional gas reservoirs.
Study on the Efficacy of Electric Acupuncture in the Treatment of Premature Ejaculation Based on Testosterone Level
Authors: Lu Xiangpeng , Han Hao , Zhang Zhibiao , Chen Hao , Huang Xingru , Zhang Rui
Published: March 2022

Objective. To investigate the clinical efficacy and possible mechanism of electroacupuncture in the treatment of premature ejaculation. Methods. 50 cases of premature ejaculation patients who met the diagnostic criteria were randomly divided into 2 groups with 25 cases in each group. The observation group was treated with electroacupuncture, and the control group was treated with Longdan Xiegan decoction. The treatment period was 4 weeks. Ejaculation latency (IELT), sexual satisfaction score of patients, sexual satisfaction score of partners, testosterone test, and drug safety assessment were performed in all 4 groups before and after treatment. Results. IELT was prolonged in all groups after treatment, the difference was statistically significant (

P
<
0.05

). At the same time, the IELT of the observation group was significantly higher than that of the control group after treatment. Life satisfaction scores of patients and spouses in 2 groups were improved after treatment compared with before treatment, the difference was statistically significant (

P
<
0.05

). After treatment, the satisfaction scores of patients and spouses in the observation group were higher than those in the control group, and the difference was statistically significant (

P
<
0.05

). Before treatment, there was no significant difference in serum testosterone levels among all groups (

P
>
0.05

). Serum testosterone levels in all groups were decreased after treatment compared with before treatment, with statistical significance (

P
<
0.05

). After treatment, the serum testosterone level of the observation group was lower than that of the control group, and the difference was statistically significant (

P
<
0.05

). During the treatment, the adverse reactions in each group disappeared after treatment, and no obvious abnormality was observed in the safety indicators. Conclusion. Electroacupuncture can improve the symptoms of premature ejaculation, which may be related to the regulation of serum testosterone by acupuncture.
Different Associated Aspects That Influence Complication Rates on Clinical PKP Surgery Using Smart Medical Big Data
Authors: Fu Bin , Dong Yi , Xiang Fang , Xia Gen , Ning Zhaohao , Ding Huiqiang
Published: March 2022

Osteoporotic vertebral compression fractures are on the rise in modern society due to the aging population, and this often results in painful symptoms and kyphotic abnormalities in patients. Bone cement was injected into the vertebral body to reinforce the vertebral body and restore most of the damaged vertebrae’s natural height. Percutaneous kyphoplasty is the name given to this type of procedure (PKP). Bone cement leakage has been linked to several problems, according to the research. Neurological problems might arise if bone cement leaks into the spinal canal or the nerve root canal during surgery. As a result, PKP surgeons must now deal with the issue of reducing bone cement leakage. Using smart medical big data, this paper examines a sample of PKP operations and then examines different associated aspects that influence complication rates in order to better advice clinical PKP surgery use. There were 172 vertebral bodies in total in 72 patients receiving PKP surgery at a Chinese hospital that were examined by smart medical big data for vertebral degeneration and fusion. Bone cement leakage and variations in preoperative average anterior vertebral column height, preoperative Cobb angle, and the volume of injected bone cement were considered when dividing the patients into leakage and nonleakage groups; then, we figure out what is causing the bone cement to leak. Five patients experienced lung-related problems out of the 18 vertebral bodies with bone cement leaking that were selected for study. That leakage rate was 10.5%. The differences between the two groups in terms of vertebral compression and bone cement injection were statistically significant based on a single-factor analysis. Bone cement leakage in PKP surgery has been linked to the amount of bone cement injected and whether the vertebral body’s peripheral wall was injured, according to multivariate analysis. Lung-related problems are more common in patients with a prior history of illness. Osteoporotic vertebral compression fractures can be successfully treated with percutaneous kyphoplasty. An important risk factor for bone cement extravasation in PKP surgery is the amount of bone cement injected, as well as its viscosity and whether damage to the vertebral body’s peripheral wall has occurred.
Active Equalization Strategy for Lithium-Ion Battery Packs Based on Multilayer Dual Interleaved Inductor Circuits in Electric Vehicles
Authors: Lei Xu , He Jianping , Fan Linqian , Wang Guiping
Published: March 2022

Lithium-ion batteries (LIBs) are widely used in electric vehicles (EVs) due to their superior power performance over other batteries. However, when connected in series, overcharged cells of LIBs face the risk of explosion, and undercharged cells decrease the life cycle of the battery. Eventually, the inconsistency phenomenon between cells resulting from manufacturing tolerance and usage process reduces the overall charging capacity of the battery and increases the risk of explosion after long-time use. Research has focused on synthesizing active material to achieve higher energy density and extended life cycle for LIBs while neglecting a comparative analysis of equalization technology on the performance of battery packs. In this paper, a nondissipative equalization structure is proposed to reconcile the inconsistency of series-connected LIB cells. In this structure, a circuit uses high-level equalization units to enable direct energy transfer between any two individual cells, and dual interleaved inductors in each equalization unit increase the equalization speed of a single cell in one equalization cycle by a factor of two. The circuit is compared with the classical inductor equalization circuit (CIEC), dual interleaved equalization circuit (DIEC), and parallel architecture equalization circuit (PAEC) in the states of standing, charging, and discharging, respectively, to validate the advantages of the proposed scheme. Considering the diversity of imbalance states, the state of charge (SOC) and terminal voltage are both chosen as the equalization criterion. The second-order RC model of the LIB and the adaptive unscented Kalman filter (AUKF) algorithm are employed for SOC estimation. For effective equalization, the adaptive fuzzy neural network (AFNN) is utilized to further reduce energy consumption and equalization time. The experiment results show that the AFNN algorithm reduces the total equalization time by approximately 37.4% and improves equalization efficiency by about 4.89% in contrast with the conventional mean-difference algorithm. Particularly, the experiment results of the equalization circuit verification certify that the proposed equalization structure can greatly accelerate the equalization progress and reduce the equalization loss compared to the other three equalization circuits.
Characteristics of Computed Tomography Images for Patients with Acute Liver Injury Caused by Sepsis under Deep Learning Algorithm
Authors: Wang Huijun , Bao Qianqian , Cao Donghang , Dong Shujing , Wu Lili
Published: March 2022

This study was aimed at exploring the application of image segmentation based on full convolutional neural network (FCN) in liver computed tomography (CT) image segmentation and analyzing the clinical features of acute liver injury caused by sepsis. The Sigmoid function, encoder‐decoder, and weighted cross entropy loss function were introduced and optimized based on FCN. The Dice value, precision, recall rate, volume overlap error (VOE), relative volume difference (RVD), and root mean square error (RMSE) values of the optimized algorithms were compared and analyzed. 92 patients with sepsis were selected as the research objects, and they were divided into a nonacute liver injury group (50 cases) and acute liver injury group (42 cases) based on whether they had acute liver injury. The differences in the proportion of patients with different disease histories, the proportion of patients with different infection sites, the number of organ failure, and the time of admission to intensive care unit (ICU) were compared between the two groups. It was found that the optimized window CT image Dice value after preprocessing (0.704 ± 0.06) was significantly higher than the other two methods (P < 0.05). The Dice value, precision, and recall rate of the optimized‐FCN algorithm were (0.826 ± 0.06), (0.91 ± 0.08), and (0.88 ± 0.09), respectively, which were significantly higher than other algorithms (P < 0.05). The VOE, RVD, and RMSE values were (21.19 ± 1.97), (10.45 ± 1.02), and (0.25 ± 0.02), respectively, which were significantly lower than other algorithms (P < 0.05). The proportion of patients with a history of drinking in the nonacute liver injury group was lower than that in the acute liver injury group (P < 0.05), and the proportion of patients with a history of hypotension was greatly higher than that in the nonacute liver injury group (P < 0.01). CT images of sepsis patients with acute liver injury showed that large areas of liver parenchyma mixed with high‐density hematoma, the number of organ failures, and the length of stay in ICU were significantly higher than those in the nonacute liver injury group (P < 0.05). It showed that the optimization algorithm based on FCN greatly improved the performance of CT image segmentation. Long‐term drinking, low blood pressure, number of organ failures, and length of stay in ICU were all related to sepsis and acute liver injury. Conclusion in this study could provide a reference basis for the diagnosis and prognosis of acute liver injury caused by sepsis.
Hyperspectral Data Classification Algorithm considering Spatial Texture Features
Authors: NanLan Wang , Xiaoyong Zeng
Published: March 2022

As a cutting-edge technology, hyperspectral remote sensing has been widely applied in many fields, including agricultural production, mineral identification, target detection, disaster warning, military reconnaissance, and urban planning. The collected hyperspectral data have high spectral resolution and spatial resolution and are characterized by a large amount of information, redundancy, and high dimension. At the same time, there is a strong correlation between the bands. Therefore, hyperspectral data not only provides rich information but also brings great challenges for subsequent processing. Hyperspectral image classification is a hot issue in remote sensing information processing. Traditional hyperspectral remote sensing image classification methods only use the spectral features of the image without considering the spatial features of each pixel in the hyperspectral remote sensing image. In this paper, a hyperspectral image classification method is proposed not only considering spectral features but also considering texture features. This method jointly considers both these features. Firstly, six texture features contributing a lot to each pixel of hyperspectral remote sensing image are extracted by using a gray level cooccurrence matrix, and then, the spectral features of each pixel in neighbor are combined to form the texture-spectral features. Finally, the classification experiment of the Indian Pines and Pavia University scene is carried out based on a support vector machine and extreme random tree algorithm, and the obtained results show that the proposed method achieves higher classification performance than the traditional method.
Immune Mechanisms of Resistance to Cediranib in Ovarian Cancer
Authors: Gopinathan Ganga , Berlato Chiara , Lakhani Anissa , Szabova Ludmila , Pegrum Colin , Pedrosa Ana-Rita , Laforets Florian , Maniati Eleni , Balkwill Frances R.
Published: March 2022

This article investigates mechanisms of resistance to the VEGF receptor inhibitor cediranib in high-grade serous ovarian cancer (HGSOC), and defines rational combination therapies. We used three different syngeneic orthotopic mouse HGSOC models that replicated the human tumor microenvironment (TME). After 4 to 5 weeks treatment of established tumors, cediranib had antitumor activity with increased tumor T-cell infiltrates and alterations in myeloid cells. However, continued cediranib treatment did not change overall survival or the immune microenvironment in two of the three models. Moreover, treated mice developed additional peritoneal metastases not seen in controls. Cediranib-resistant tumors had intrinsically high levels of IL6 and JAK/STAT signaling and treatment increased endothelial STAT3 activation. Combination of cediranib with a murine anti-IL6 antibody was superior to monotherapy, increasing mouse survival, reducing blood vessel density, and pSTAT3, with increased T-cell infiltrates in both models. In a third HGSOC model, that had lower inherent IL6 JAK/STAT3 signaling in the TME but high programmed cell death protein 1 (PD-1) signaling, long-term cediranib treatment significantly increased overall survival. When the mice eventually relapsed, pSTAT3 was still reduced in the tumors but there were high levels of immune cell PD-1 and Programmed death-ligand 1. Combining cediranib with an anti–PD-1 antibody was superior to monotherapy in this model, increasing T cells and decreasing blood vessel densities. Bioinformatics analysis of two human HGSOC transcriptional datasets revealed distinct clusters of tumors with IL6 and PD-1 pathway expression patterns that replicated the mouse tumors. Combination of anti-IL6 or anti–PD-1 in these patients may increase activity of VEGFR inhibitors and prolong disease-free survival.