bluuebunny/crossref_metadata_2025 huggingface dataset:
Carboniferous fusuline Foraminifera: taxonomy, regional biostratigraphy, and palaeobiogeographic faunal development
Authors: Ueno Katsumi
Published: September 2021

This paper proposes a synthesis of the taxonomy, phylogeny, palaeogeographic distribution, regional biostratigraphy, and palaeobiogeographic faunal development of Carboniferous fusuline foraminifers. They appeared in the latest Tournaisian and comprised a small-sized, morphologically conservative taxonomic group during the Mississippian. Fusulines became larger and prevailed in Pennsylvanian foraminiferal assemblages. Carboniferous fusulines consist of Ozawainellidae, Staffellidae, Schubertellidae, Fusulinidae, and Schwagerinidae, in which 95 genera are considered as valid taxonomically. Upsizing their shells throughout the Pennsylvanian is likely related to symbiosis with photosynthetic microorganisms, which was accelerated by the acquisition of a keriothecal wall in Late Pennsylvanian schwagerinids. Regional fusuline succession data from 40 provinces provide a refined biostratigraphy, enabling zonation and correlation with substage- or higher-resolution precision in the Pennsylvanian. Their spatio-temporal faunal characteristics show that fusulines had a cosmopolitan palaeobiogeographic signature in Mississippian time, suggesting unrestricted faunal exchange through the palaeoequatorial Rheic Ocean. After the formation of Pangaea, Pennsylvanian fusulines started to show provincialism, and their distributions defined the Ural–Arctic Region in the Boreal Realm, Palaeotethys, Panthalassa, and North American Craton regions in the Palaeoequatorial Realm, and Western Gondwana and Eastern Peri-Gondwana regions in the Gondwana Realm. The Western Palaeotethys and East European Platform Subregions maintained higher generic diversity throughout the Pennsylvanian.
Enabling Surveillance Cameras to Navigate
Authors: Dong Liang , Xu Jingao , Chi Guoxuan , Li Danyang , Zhang Xinglin , Li Jianbo , Ma Qiang , Yang Zheng
Published: September 2021

Smartphone localization is essential to a wide spectrum of applications in the era of mobile computing. The ubiquity of smartphone
mobile cameras
and surveillance
ambient cameras
holds promise for offering sub-meter accuracy localization services thanks to the maturity of computer vision techniques. In general,
ambient-camera-based
solutions are able to localize pedestrians in video frames at fine-grained, but the tracking performance under dynamic environments remains unreliable. On the contrary,
mobile-camera-based
solutions are capable of continuously tracking pedestrians; however, they usually involve constructing a large volume of image database, a labor-intensive overhead for practical deployment. We observe an opportunity of integrating these two most promising approaches to overcome above limitations and revisit the problem of smartphone localization with a fresh perspective. However, fusing
mobile-camera-based
and
ambient-camera-based
systems is non-trivial due to disparity of camera in terms of perspectives, parameters and incorrespondence of localization results. In this article, we propose iMAC, an integrated mobile cameras and ambient cameras based localization system that achieves sub-meter accuracy and enhanced robustness with zero-human start-up effort. The key innovation of iMAC is a well-designed fusing frame to eliminate disparity of cameras including a
construction of projection map function
to automatically calibrate ambient cameras, an
instant crowd fingerprints model
to describe user motion patterns, and a
confidence-aware matching
algorithm to associate results from two sub-systems. We fully implement iMAC on commodity smartphones and validate its performance in five different scenarios. The results show that iMAC achieves a remarkable localization accuracy of 0.68 m, outperforming the state-of-the-art systems by >75%.
Context-aware Distance Measures for Dynamic Networks
Authors: Zhao Yiji , Lin Youfang , Wu Zhihao , Wang Yang , Wen Haomin
Published: September 2021

Dynamic networks are widely used in the social, physical, and biological sciences as a concise mathematical representation of the evolving interactions in dynamic complex systems. Measuring distances between network snapshots is important for analyzing and understanding evolution processes of dynamic systems. To the best of our knowledge, however, existing network distance measures are designed for static networks. Therefore, when measuring the distance between any two snapshots in dynamic networks, valuable context structure information existing in other snapshots is ignored. To guide the construction of context-aware distance measures, we propose a context-aware distance paradigm, which introduces context information to enrich the connotation of the general definition of network distance measures. A Context-aware Spectral Distance (CSD) is then given as an instance of the paradigm by constructing a context-aware spectral representation to replace the core component of traditional Spectral Distance (SD). In a node-aligned dynamic network, the context effectively helps CSD gain mainly advantages over SD as follows: (1) CSD is not affected by isospectral problems; (2) CSD satisfies all the requirements of a metric, while SD cannot; and (3) CSD is computationally efficient. In order to process large-scale networks, we develop a kCSD that computes top-
k
eigenvalues to further reduce the computational complexity of CSD. Although kCSD is a pseudo-metric, it retains most of the advantages of CSD. Experimental results in two practical applications, i.e., event detection and network clustering in dynamic networks, show that our context-aware spectral distance performs better than traditional spectral distance in terms of accuracy, stability, and computational efficiency. In addition, context-aware spectral distance outperforms other baseline methods.
A Perceptually-Validated Metric for Crowd Trajectory Quality Evaluation
Authors: Daniel Beatríz Cabrero , Marques Ricardo , Hoyet Ludovic , Pettré Julien , Blat Josep
Published: September 2021

Simulating crowds requires controlling a very large number of trajectories and is usually performed using crowd motion algorithms for which appropriate parameter values need to be found. The study of the relation between parametric values for simulation techniques and the quality of the resulting trajectories has been studied either through perceptual experiments or by comparison with real crowd trajectories. In this paper, we integrate both strategies. A quality metric, QF, is proposed to abstract from reference data while capturing the most salient features that affect the perception of trajectory realism. QF weights and combines cost functions that are based on several individual, local and global properties of trajectories. These trajectory features are selected from the literature and from interviews with experts. To validate the capacity of QF to capture perceived trajectory quality, we conduct an online experiment that demonstrates the high agreement between the automatic quality score and non-expert users. To further demonstrate the usefulness of QF, we use it in a data-free parameter tuning application able to tune any parametric microscopic crowd simulation model that outputs independent trajectories for characters. The learnt parameters for the tuned crowd motion model maintain the influence of the reference data which was used to weight the terms of QF.
Diverse Motion Stylization for Multiple Style Domains via Spatial-Temporal Graph-Based Generative Model
Authors: Park Soomin , Jang Deok-Kyeong , Lee Sung-Hee
Published: September 2021

This paper presents a novel deep learning-based framework for translating a motion into various styles within multiple domains. Our framework is a single set of generative adversarial networks that learns stylistic features from a collection of unpaired motion clips with style labels to support mapping between multiple style domains. We construct a spatio-temporal graph to model a motion sequence and employ the spatial-temporal graph convolution networks (ST-GCN) to extract stylistic properties along spatial and temporal dimensions. Through spatial-temporal modeling, our framework shows improved style translation results between significantly different actions and on a long motion sequence containing multiple actions. In addition, we first develop a mapping network for motion stylization that maps a random noise to style, which allows for generating diverse stylization results without using reference motions. Through various experiments, we demonstrate the ability of our method to generate improved results in terms of visual quality, stylistic diversity, and content preservation.
Exotic Ants of the Asia-Pacific: Invasion, National Response, and Ongoing Needs
Authors: Xu Yijuan , Vargo Edward L. , Tsuji Kazuki , Wylie Ross
Published: September 2021

Human activity has facilitated the introduction of many exotic species via global trade. Asia-Pacific countries comprise one of the most economically and trade-active regions in the world, which makes it an area that is highly vulnerable to invasive species, including ants. There are currently over 60 exotic ant species in the Asia-Pacific, with the red imported fire ant, Solenopsis invicta, among the most destructive. Exotic ants pose many economic and ecological problems for the region. Countries in the Asia-Pacific have dealt with the problem of exotic ants in very different ways, and there has been an overall lack of preparedness. To improve the management of risks associated with invasive ants, we recommend that countries take action across the biosecurity spectrum, spanning prevention, containment, and quarantine. The creation of an Asia-Pacific network for management of invasive ants should help prevent their introduction and mitigate their impacts.
What Are the Health Consequences of Upward Mobility?
Authors: Chen Edith , Brody Gene H. , Miller Gregory E.
Published: September 2021

Health disparities by socioeconomic status (SES) have been extensively documented, but less is known about the physical health implications of achieving upward mobility. This article critically reviews the evolving literature in this area, concluding that upward mobility is associated with a trade-off, whereby economic success and positive mental health in adulthood can come at the expense of physical health, a pattern termed skin-deep resilience. We consider explanations for this phenomenon, including prolonged high striving, competing demands between the environments upwardly mobile individuals seek to enter and their environments of origin, cultural mismatches between adaptive strategies from their childhood environments and those that are valued in higher-SES environments, and the sense of alienation, lack of belonging, and discrimination that upwardly mobile individuals face as they move into spaces set up by and for high-SES groups. These stressors are hypothesized to lead to unhealthy behaviors and a dysregulation of biological systems, with implications for cardiometabolic health.
An Analysis of Asymptotic Properties and Error Control under the Exponential Jump-Diffusion Model for American Option Pricing
Authors: Maidoumi Mohamed , Daafi Boubker , Zahid Mehdi
Published: September 2021

Our work is aimed at modeling the American option price by combining the dynamic programming and the optimal stopping time under two asset price models. In doing so, we attempt to control the theoretical error and illustrate the asymptotic characteristics of each model; thus, using a numerical illustration of the convergence of the option price to an equilibrium price, we can notice its behavior when the number of paths tends to be a large number; therefore, we construct a simple estimator on each slice of the number of paths according to an upper and lower bound to control our error. Finally, to highlight our approach, we test it on different asset pricing models, in particular, the exponential Lévy model compared to the simple Black and Scholes model, and we will show how the latter outperforms the former in the real market (Microsoft “MSFT” put option as an example).
Multiple Biomarker‐Combined Screening for Colorectal Cancer Based on Bisulfate Conversion‐Free Detection of Fecal DNA Methylation
Authors: Liu Chong , Xu Lei , Li Wei , Jie Min , Xue Wei , Yu Wenqiang
Published: September 2021

To evaluate the applicability of bisulfate conversion‐free methylation assay based on enzyme digestion in fecal screening for colorectal cancer (CRC). Stool samples were collected from a total of 1142 participants with intestinal abnormalities, including 180 positive cases, 60 advanced adenomas, and 902 negative cases. DNA from reference cell lines and clinical samples was extracted and digested with an enzyme to detect the methylation of CRC markers SEPT9, SDC2, NDRG4, SFRP2, and BMP3 genes. Statistical analysis was then used to determine the ability of the markers, both individually and in combination, to detect CRC and adenoma. Our results showed that the enzyme digestion method could suitably detect DNA marker methylation in as low as 1% of the cell lines. BMP3 had a considerably low detection rate in all clinical samples, with only 6 positive cases detected out of 180 cancer samples. Our findings showed that the combination of SEPT9, SDC2, and SFRP2 had an area under the receiver operation curve of 0.937, sensitivity of 94.11%, and specificity of 89.21% for detecting CRC. Moreover, the detection sensitivity of adenoma can also reach 38.33%. After innovatively utilizing bisulfate conversion‐free methylation assay for CRC screening, this study verified the potential clinical applicability of combining multiple biomarkers for CRC screening in a large number of samples.
Identification of Prognostic Metabolism-Related Genes in Clear Cell Renal Cell Carcinoma
Authors: Chen Yusa , Liang Yumei , Chen Ying , Ouyang Shaxi , Liu Kanghan , Yin Wei
Published: September 2021

Background. Clear cell renal cell carcinoma (ccRCC) is a cancer with abnormal metabolism. The purpose of this study was to investigate the effect of metabolism-related genes on the prognosis of ccRCC patients. Methods. The data of ccRCC patients were downloaded from the TCGA and the GEO databases and clustered using the nonnegative matrix factorization method. The limma software package was used to analyze differences in gene expression. A random forest model was used to screen for important genes. A novel Riskscore model was established using multivariate regression. The model was evaluated based on the metabolic pathway, immune infiltration, immune checkpoint, and clinical characteristics. Results. According to metabolism-related genes, kidney clear cell carcinoma (KIRC) datasets downloaded from TCGA were clustered into two groups and showed significant differences in prognosis and immune infiltration. There were 667 differentially expressed genes between the two clusters, of which 408 were screened by univariate analysis. Finally, 12 differentially expressed genes (MDK, SLC1A1, SGCB, C4orf3, MALAT1, PILRB, IGHG1, FZD1, IFITM1, MUC20, KRT80, and SALL1) were filtered out using the random forest model. The model of Riskscore was obtained by multiplying the expression levels of these 12 genes with the corresponding coefficients of the multivariate regression. We found that the Riskscore correlated with the expression of these 12 genes; the high Riskscore matched the low survival rate verified in the verification set. The analysis found that the Riskscore model was associated with most of the metabolic processes, immune infiltration of cells such as plasma cells, immune checkpoints such as PD-1, and clinical characteristics such as M stage. Conclusion. We established a new Riskscore model for the prognosis of ccRCC based on metabolism. The genes in the model provided several novel targets for the study of ccRCC.
Risk Analysis of Gold Prices in Pakistan Using Extreme Value Theory
Authors: Khan Ghulam Raza , Abdulrahman Alanazi Talal , Alamri Osama , Iqbal Zahid , Ahmad Maqsood
Published: September 2021

Extreme value theory (EVT) is useful for modeling the impact of crashes or situations of extreme stress on investor portfolios. EVT is mostly utilized in financial modeling, risk management, insurance, and hydrology. The price of gold fluctuates considerably over time, and this introduces a risk on its own. The goal of this study is to analyze the risk of gold investment by applying the EVT to historical daily data for extreme daily losses and gains in the price of gold. We used daily gold prices in the Pakistan Bullion Market from August 1, 2011 to July 30, 2021. This paper covers two methods such as Block Maxima (BM) and Peak Over Threshold (POT) modeling. The risk measures which are adopted in this paper are Value at Risk (VaR) and Expected Shortfall (ES). The point and interval estimates of VaR and ES are obtained by fitting the Generalized Pareto (GPA) distribution. Moreover, in this paper, return-level forecasting is also included for the next 5 and 10 years by analyzing the Generalized Extreme Value (GEV) distribution.
iTAGPred: A Two-Level Prediction Model for Identification of Angiogenesis and Tumor Angiogenesis Biomarkers
Authors: Allehaibi Khalid , Daanial Khan Yaser , Khan Sher Afzal
Published: September 2021

A crucial biological process called angiogenesis plays a vital role in migration, growth, and wound healing of endothelial cells and other processes that are controlled by chemical signals. Angiogenesis is the process that controls the growth of blood vessels within tissues while angiogenesis proteins play a significant role in the proper working of this process. The balancing of these signals is necessary for the proper working of angiogenesis. Unbalancing of these signals increases blood vessel formation, which causes abnormal growth or several diseases including cancer. The proposed work focuses on developing a two-layered prediction model using different classifiers like random forest (RF), neural network, and support vector machine. The first level performs in silico identification of angiogenesis proteins based on the primary structure. In the case the protein is an angiogenesis protein, then the second level predicts whether the protein is linked with tumor angiogenesis or not. The performance of the model is evaluated through various validation techniques. The model was evaluated using

k

-fold cross-validation, independent, self-consistency, and jackknife testing. The overall accuracy using an RF classifier for angiogenesis at the first level was 97.8% and for tumor angiogenesis at the second level was 99.5%, ANN showed 94.1% accuracy for angiogenesis and 79.9% for tumor angiogenesis, and the accuracy of SVM for angiogenesis was 78.8% and for tumor angiogenesis was 65.19%.
New Framework of Digital Entrepreneurship Model Based on Artificial Intelligence and Cloud Computing
Authors: Li Jiahui , Yao Meifang
Published: September 2021

With the rapid development of entrepreneurial enterprises and the widespread application of emerging technologies, the commercialization of new technologies for entrepreneurial enterprises is particularly important. This research mainly discusses the new framework of digital entrepreneurship model based on artificial intelligence and cloud computing. Through artificial intelligence technology, the products provided by existing competitors only have the characteristics of one-way value; that is, data is only collected and displayed, and the application of artificial intelligence technology in products makes the value of products develop in two directions; that is, the machine can self-identify faults and errors are resolved and reported. Let customers experience the convenience, accuracy, and safety brought by technology through intelligent acquisition equipment hardware with artificial intelligence algorithm analysis and camera hardware with artificial intelligence image analysis. Customers can pay flexibly according to their needs. This model greatly enhances the high possibility of artificial intelligence companies landing. Use big data analysis and cloud computing technology to provide customers with a series of solutions such as warehouse management, sales forecasting, big data analysis, and financial management. In the SaaS market, in terms of market segmentation, there are no domestic enterprises with scale and brand effect; the incentive and welfare module will focus on the outsourcing and outsourcing of employee benefits. Relevant value-added services and derivative services are the core business, which can give play to the competitive advantages of specialization, scale, and platform. From 2018 to 2020, the cash paid to employees shows a gradual increase, and the taxes and fees paid are also increasing year by year. The cash paid for other operating activities reached a maximum of 12303 million yuan in 2018. This research will promote the innovation of new types of enterprises.
Estimation of Nuclear Medicine Exposure Measures Based on Intelligent Computer Processing
Authors: Wang Junfeng , Wang Fangxiao , Liu Yue , Xu Yuanfan , Liang Jiangtao , Su Ziming
Published: September 2021

This paper provides an in-depth discussion and analysis of the estimation of nuclear medicine exposure measurements using computerized intelligent processing. The focus is on the study of energy extraction algorithms to obtain a high energy resolution with the lowest possible ADC sampling rate and thus reduce the amount of data. This paper focuses on the direct pulse peak extraction algorithm, polynomial curve fitting algorithm, double exponential function curve fitting algorithm, and pulse area calculation algorithm. The detector output waveforms are obtained with an oscilloscope, and the analysis module is designed in MATLAB. Based on these algorithms, the data obtained from six different lower sampling rates are analyzed and compared with the results of the high sampling rate direct pulse peak extraction algorithm and the pulse area calculation algorithm, respectively. The correctness of the compartment model was checked, and the results were found to be realistic and reliable, which can be used for the analysis of internal exposure data in radiation occupational health management, estimation of internal exposure dose for nuclear emergency groups, and estimation of accidental internal exposure dose. The results of the compartment model of the respiratory tract and the compartment model of the digestive tract can be used to calculate the distribution and retention patterns of radionuclides and their compounds in the body, which can be used to assess the damage of radionuclide internal contamination and guide the implementation of medical treatment.
Plasmablastic Lymphoma or Plasmablastic Myeloma: A Case of Post-Transplant Lymphoproliferative Disorder
Authors: Ramadas Poornima , Williams Michael , Duggan David B.
Published: September 2021

Plasmablastic lymphomas and plasmablastic myelomas are malignancies with overlapping clinical and pathological features which pose a diagnostic dilemma and are known to be aggressive with a poor outcome. CD38 is a common immunophenotypic maker for both these malignancies and provides a rationale for using daratumumab-based regimes. We describe a 57-year-old male with a history of end-stage renal disease who underwent a deceased-donor renal transplant maintained on chronic immunosuppression who presented with ascites and was found to have abdominal adenopathy and a lytic lesion in the humerus and diagnosed with a post-transplant lymphoproliferative disorder with features intermediate between plasmablastic lymphoma and plasmablastic myeloma. The patient was subsequently treated with a daratumumab-based regime with an excellent response. This case highlights a rare scenario that poses a diagnostic and therapeutic challenge. As there is no standard of care for the treatment of both these malignancies, this case report also describes the use of daratumumab with a good long-term outcome, especially when the pathological distinction between the two entities is difficult.
Performance Analysis of Clear Sky Global Horizontal Irradiance Models: Simple Models Adapted for Local Conditions
Authors: Kwarikunda Nicholas , Chiguvare Zivayi
Published: September 2021

Evaluation of the maximum solar energy potential of a given area for possible deployment of solar energy technologies requires assessment of clear sky solar irradiance for the region under consideration. Such localized assessment is critical for optimal sizing of the technology to be deployed in order to realize the anticipated output. As the measurements are not always available where they are needed, models may be used to estimate them. In this study, three different models were adapted for the geographical location of the area under study and used to estimate clear sky global horizontal irradiance (GHI) at three locations in the subtropical desert climate of Namibia. The three models, selected on the basis of input requirements, were used to compute clear sky GHI at Kokerboom, Arandis, and Auas. The models were validated and evaluated for performance using irradiance data measured at each of the sites for a period of three years by computing statistical parameters such as mean bias error (MBE), root mean square error (RMSE), and the coefficient of determination (R2), normalized MBE, and normalized RMSE. Comparative results between modelled and measured data showed that the models fit well the measured data, with normalized root mean square error values in the range 4–8%, while the R2 value was above 98% for the three models. The adapted models can thus be used to compute clear sky GHI at these study areas as well as in other regions with similar climatic conditions.
Spatiotemporal Characteristics and Resilience of Urban Network Structure during the Spring Festival Travel Rush: A Case Study of Urban Agglomeration in the Middle Reaches of Yangtze River in China
Authors: Wei Shimei , Pan Jinghu
Published: September 2021

With the increasing trend of globalization, large‐scale and diffuse population flow have become vital carriers characterizing users′ spatial behaviors. Network analysis provides a new perspective to uncover the topology and evolution of the population flow and understand its influence on regional development. By gathering the Autonavi migration index during the Spring Festival travel rush (SFTR) in 2019, 2020, and 2021, the population flow networks among 31 cities of urban agglomeration in the middle reaches of the Yangtze River were constructed to analyze spatiotemporal dynamic characteristics and explore the structure resilience. Results show that although the changing trends of population flow during the 40‐day SFTR of 2019, 2020, and 2021 are consistent, the population floating scale in 2020 and 2021 shows remarkable abnormalities before and after the Spring Festival due to the need for prevention and control of COVID‐19. The intensity of population floating of the regional urban network in 2020 was the weakest, and Changsha became the focus of most population flow, while Wuhan was the most advantageous city in 2019 and 2021. As the third core city in the regional network, the siphon effect of Nanchang was still weak. A situation of tripartite confrontation in the region is formed. However, the higher intensity of population flow in 2021 increased the instability of the regional urban network, potentially exposing the region to higher risks and pressures. Therefore, it is necessary to pay more attention to the peripheral cities to improve regional resilience.
Novel Presentation of Terminal Ileitis Associated with Secukinumab Therapy
Authors: Ahmed Shaheen Aciel , Hader Ismail , Aqel Zakaria
Published: September 2021

Inflammatory bowel disease (IBD) and psoriasis are chronic inflammatory immune-mediated diseases. The interleukin-23- (IL23-) T helper (Th)17 pathway has been implicated in their pathogenesis, with multiple biologic therapies targeting this pathway. IL-17, the main proinflammatory cytokine produced by (TH)17, has been targeted by antibodies and IL-17 receptor blockers with favorable outcomes in treating psoriasis and psoriatic arthritis. However, their role in IBD is unpredictable as studies reported worsening of IBD with agents targeting IL-17 and rare case reports with new-onset IBD. We present a case of Crohn's-like severe terminal ileitis and worsening diverticulitis complicated by intestinal perforation requiring total parenteral nutrition shortly after being started on secukinumab.
Release of HMGB1 in Podocytes Exacerbates Lipopolysaccharide-Induced Acute Kidney Injury
Authors: Gao Zhao , Lu Li , Chen Xinghua
Published: September 2021

Objective. Acute kidney injury (AKI) usually occurs during sepsis. Inflammation factors, such as high-mobility group box 1 (HMGB1), are dramatically upregulated under septic conditions. In our current work, the functions of HMGB1 in AKI were explored. Methods. An AKI model was induced by the lipopolysaccharide (LPS) challenge in C57 mice. Podocytes were challenged by LPS for different durations. Subsequently, podocytes transfected with HMGB1 siRNA were exposed to LPS for 24 h. The expressions of supernatant HMGB1 and cellular active caspase-3 were examined by Western blotting analysis. To explore the effect of HMGB1 on tubular epithelial cells (TECs), HK-2 cells were exposed to HMGB1 at various concentrations for 24 h. Epithelial-mesenchymal transition (EMT) of HK-2 cells was evaluated by Western blotting analysis. Mitochondrial division and apoptosis of HK-2 cells were assessed by MitoTracker Red and Western blotting analysis, respectively. Results. Compared with the sham control group, the expression of HMGB1 was increased in the kidney of AKI mice. Moreover, the expression of supernatant HMGB1 was increased in LPS-challenged podocytes compared with the control group. Knockdown of HMGB1 attenuated LPS-induced podocyte injury. Besides, EMT in TECs was triggered by HMGB1. Mitochondrial damage and apoptosis of HK-2 cells exposed to HMGB1 were markedly elevated compared with the control group. Conclusions. Collectively, HMGB1 release in podocytes was induced by LPS, subsequently leading to exacerbated AKI.
YiQi YangYin Decoction Attenuates Nonalcoholic Fatty Liver Disease in Type 2 Diabetes Rats
Authors: Li Fengjin , Liu Genli , Xue Piliang , Ren Zhen , Dai Peifang , Niu Wenying , Xin Mu
Published: September 2021

Background. YiQi YangYin Decoction (YQ) is a modern Chinese formula composed by the guidance of traditional Chinese medicine theory, which consists of nine traditional Chinese medicines and is applied to treat type 2 diabetes mellitus (T2DM) with nonalcoholic fatty liver in clinic in China for more than a decade. This study aims to evaluate the antidiabetes and lipid-lowering effect of YQ and explore the possible mechanisms of this action. Methods. T2DM rat models were established and given YQ at three different doses for three weeks. Tissues, including pancreas islet and liver, and blood serum were collected. The levels of fasting blood glucose (FBG), fasting insulin (Fins), lipid index, such as total cholesterol (TC), triglyceride (TG), high-density lipoprotein (HDL), and low-density lipoprotein (LDL), and hepatic function index such as alanine aminotransferase (ALT), aspartate aminotransferase (AST), and alkaline phosphatase (ALP) in serum were measured. Pancreas islet damage and liver damage were observed by hematoxylin and eosin staining. The glycogen content and lipid accumulation in liver were determined by periodic acid-Schiff (PAS) staining and Oil Red O staining. The expression levels of insulin receptor substrate 2 (IRS-2), phosphatidylinositol 3 kinase-associated p85alpha (PI3K p85α), AKT, and Glucose Transporter 2 (Glut4) in pancreas islet and AMP-activated protein kinase alpha (AMPKα), sterol regulatory element-binding protein 1c (SREBP1c), acetyl-CoA carboxylase (ACC1), and peroxisome proliferator‐activated receptor-α (PPARα) in liver were determined by western blotting. The relative expressions of ACC1, fatty acid synthase (FAS), stearoyl-CoA desaturase 1 (SCD1), carnitine palmityl transferase-1 (CPT-1), and SREBP-1 mRNA were detected by qRT-PCR. Results. After administering YiQi for three weeks, the levels of fast blood glucose, fasting insulin, TC, TG, LDL, ALT, AST, and ALP were significantly decreased, while HDL significantly increased compared with the model group. YQ could obviously attenuate pancreatic damage and improve islet α- and ß-cell survival compared with the model group. Furthermore, YQ could attenuate hepatic damage caused by lipid accumulation, decrease the content of lipid, and increase the hepatic glycogen content, compared with the model group. In addition, YQ remarkably elevated the proteins expression of p-PI3K, p-AKT, and GLUT4 in pancreas islet and elevated the proteins expression of p-PI3K, p-AKT, GLUT4, p-AMPK, SREBP1, and PPARα and inhibited the expression of p-ACC1 in liver. Besides, YQ reduced the relative expression of ACC1, FAS, SERBP-1c, and SCD mRNA along with the decreased production of CPT-1 mRNA. Conclusions. YQ could attenuate type 2 diabetes mellitus by improving islet α- and ß-cells via IRS-2/AKT/GLUT4 pathway and nonalcoholic fatty liver by ameliorating lipid accumulation via AMPK/PPARα/SREBP1/ACC1 pathway.
Effect of Psychological Care Combined with Traditional Chinese Medicine on Postoperative Psychological Stress Response in Patients with Advanced Cervical Cancer
Authors: Hou Xue , Zhang Huajuan , Nie Yahong , Zhang Yun , Wang Jinhua , Xu Hua
Published: September 2021

Objective. To study the effects of psychological care combined with traditional Chinese medicine treatment on the postoperative psychological stress response and the expression levels of serum C-reactive protein (CRP) and interferon-γ (IFN-γ) in patients with advanced cervical cancer. Method. 232 postoperative advanced cervical cancer patients treated in our hospital from December 2015 to December 2018 were selected as study objects and divided into the control group and study group using the random number table method. The control group was given basic care combined with traditional Chinese medicine treatment, while the study group was given psychological care treatment on the basis of the control group to compare the treatment effect, psychological stress response, pain level, quality of life, and long-term efficacy of the two groups. The serum CRP and IFN-γ levels and their correlation with different psychological stress responses were compared between the two groups before and after treatment. Result. Comparing the clinical efficacy of the two groups, the total effective rate of the study group was higher than that of the control group. VAS scores in the study group were significantly lower than those in the control group 30 and 60 days after treatment. The SCL-90 scores of the study group after treatment were lower than those of the control group. After treatment, the differences between the two groups were statistically significant in the scores of emotional function, social function, and role function. The two-year cumulative survival rate in the study group (82.76%) was significantly increased compared to that in the control group (55.17%). The serum CRP and IFN-γ expression levels in the two groups were significantly decreased after treatment compared to those before treatment, and the serum CRP and IFN-γ expression levels in the study group were significantly decreased compared to those in the control group. Conclusion. Psychological care combined with traditional Chinese medicine in the treatment of advanced cervical cancer patients after surgery was effective in improving patients’ psychological status, reducing their pain level, relieving postoperative negative emotions, increasing compliance, improving the quality of life, helping to prolong survival time, and controlling serum indexes back to normal, which was worth promoting in clinical practice.
The Applications of Blockchain in Artificial Intelligence
Authors: Wang Ruonan , Luo Min , Wen Yihong , Wang Lianhai , Raymond Choo Kim-Kwang , He Debiao
Published: September 2021

There has been increased interest in applying artificial intelligence (AI) in various settings to inform decision-making and facilitate predictive analytics. In recent times, there have also been attempts to utilize blockchain (a peer-to-peer distributed system) to facilitate AI applications, for example, in secure data sharing (for model training), preserving data privacy, and supporting trusted AI decision and decentralized AI. Hence, in this paper, we perform a comprehensive review of how blockchain can benefit AI from these four aspects. Our analysis of 27 English-language articles published between 2018 and 2021 identifies a number of research challenges and opportunities.
Isolated Cysticercosis of Sternocleidomastoid Muscle: Role of Ultrasonography
Authors: Thapa Subash , Lamichhane Norman , Joshi Santosh
Published: September 2021

Cysticercosis is considered a common healthcare problem, especially in developing countries. The invasion of muscle by the larval stage of the pork tapeworm, Taenia solium (i.e., Cysticercus cellulosae) usually occurs in association with CNS cysts, concurrent muscle cysts, or both. Isolated skeletal muscle involvement is rare and presents with nonspecific symptoms resulting in a diagnostic dilemma for the treating physician. We report a 20-year-old female with isolated cysticercosis of right sternocleidomastoid muscle presenting as a right neck swelling and mild pain for 4 months, whose diagnosis was established by ultrasonography (USG) and computed tomogram (CT) scan. She was managed conservatively with oral albendazole therapy for four weeks resulting in complete resolution.
Takagi–Sugeno State Delayed Feedback and Integral Control for PV Systems: Modeling, Simulation, and Control
Authors: El Aiss Hicham , Barbosa Karina A. , Chavez Hector , Rodriguez Carlos
Published: September 2021

The integration of the large-scale photovoltaic systems has experienced significant growth, which is similarly expected to occur with small-scale photovoltaic systems. Since small-scale systems must be simple in cost-effective components, control strategies must be implemented in low complexity circuits. However, current maximum power point tracking (MPPT) algorithms are generally complex and require electronic components to support variable control gains for different irradiance conditions, preventing simple MPPT implementations suitable for small-scale photovoltaic systems. This paper proposes a new control strategy to tackle the power tracking problem of the power systems. First, a dynamic model of the photovoltaic system is described and converted into a Takagi–Sugeno (T-S) model. Then, an MPPT scheme is proposed in series with a fixed integral and a fuzzy gain state delay feedback controller, which avoids the need for a variable control gain, simplifying the electronic implementation of the control strategy. New delay-dependent stabilization conditions based on the Lyapunov-Krasovskii functional are proposed in terms of a convex optimization problem, where the delayed feedback and integral gains are designed simultaneously. Simulation results using Matlab and Simulink are used to validate the proposed method.
Analysis of Propagation Characteristics for Various Subway Tunnel Scenarios at 28 GHz
Authors: Wang Chengjian , Ji Wenli , Zheng Guoxin , Saleem Asad
Published: September 2021

In order to meet the higher data transmission rate requirements of subway communication services, the millimeter wave (mmWave) broadband communication is considered as a potential solution in 5G technology. Based on the channel measurement data in subway tunnels, this paper uses ray-tracing (RT) simulation to predict the propagation characteristics of the 28 GHz millimeter wave frequency band in different tunnel scenarios. A large number of simulations based on ray-tracing software have been carried out for tunnel models with different bending radiuses and different slopes, and we further compared the simulation results with the real time measurement data of various subway tunnels. The large-scale and small-scale propagation characteristics of the channel, such as path loss (PL), root mean square delay spread (RMS-DS), and angle spread (AS), for different tunnel scenarios are analyzed, and it was found that the tunnel with a greater slope causes larger path loss and root mean square delay spread. Furthermore, in the curved tunnel, the angle spread of the azimuth angle is larger than that in a straight tunnel. The proposed results can provide a reference for the design of future 5G communication systems in subway tunnels.
Optimization and Simulation of Atmospheric Environment Monitoring System Based on Wireless Sensor
Authors: Feng Zhenqiang
Published: September 2021

With the acceleration of urbanization, the problems in urban construction are becoming increasingly prominent, especially in air pollution. In order to deal with a series of problems brought by urbanization, the state has formulated the strategic layout of smart city construction. As an important measure and practice for the development of smart city, atmospheric environment monitoring is the premise of controlling atmospheric environment problems and plays a great role in environmental protection. The traditional automatic atmospheric environment monitoring station has complex structure, expensive price, and harsh working conditions, which is difficult to be popularized throughout the country. Aiming at the problems of poor expansibility and low intelligence of atmospheric environment monitoring system, an atmospheric environment monitoring system based on wireless sensor network is proposed. The system designs sensor module, networking module, gateway module, and monitoring interface, studies the accuracy of data collected by the system and the coverage of wireless sensor network, filters the environmental data collected by the sensor module, optimizes the layout of networking module by using improved virtual force algorithm, and finally tests the system. The experimental results show that the system realizes the remote monitoring of temperature, humidity, air pressure, and PM2.5 data, and the monitoring data is real and reliable. The improved virtual force algorithm improves the coverage of wireless sensor networks. Comparing the data collected by the system with the monitoring data of the cause control station, the average relative errors of PM2.5 and other particle parameters and NOx and other gas parameters monitored by the system are 3.81% and 3.48%, respectively; the system can be widely used in various environmental monitoring fields.
Research on Photovoltaic Grid‐Connected Control Strategy Based on Active Disturbance Rejection of Adaptive Extended State Observer
Authors: Liu Dejun , Xu Jinfei , Xue Ruonan , Song Chao , Zhou Zhenxiong
Published: September 2021

In the photovoltaic inverter grid‐connected power generation system, the output power of photovoltaic panels is affected by illumination and temperature. The change of output power of photovoltaic panels will lead to the fluctuation of DC bus voltage. If the control is improper, it will directly affect the regular operation of the system. In order to improve the performance of the grid‐connected inverter system, an active disturbance rejection control method based on adaptive extended state observer (ESO) is proposed. Firstly, a feedforward PI current inner loop controller is designed, which simplifies the structure of the control system and improves the tracking performance of the current. Then, the DC bus voltage outer loop ADRC is designed, and a conversion method that ignores the essential difference between nonlinear/time‐varying and time‐varying/linear is proposed. Through the conversion of time‐invariant nonlinear system and time‐varying linear system, the stability of the extended state observer is proved by the Routh criterion. Secondly, to solve the problem of mutual restriction between the stability and observation accuracy of the extended state observer, an adaptive function online automatic tuning ESO parameter method is proposed. Finally, the simulation results show that the proposed method has better dynamic and static performance, and the grid‐connected voltage and current harmonics are small, which proves the correctness and effectiveness of the proposed method.
Multipeak Emissions and Electrical Properties of ZnO/Si Heterojunctions Based on ZnO Nanoflakes by Spin Coating Technique
Authors: Ma Ya Jun , Ji Peng Fei , Li Yong , Song Yue Li
Published: September 2021

ZnO/Si heterojunctions have been fabricated by spinning ZnO nanoflakes on the p-type single crystal silicon by using the spin coating technique. Photoluminescence spectra of as-grown and annealed ZnO/Si heterojunctions have been recorded under the excitation of 336 nm. Multipeaks between ∼360 nm and ∼430 nm from annealed ZnO/Si heterojunctions have been analyzed, the origins of which have been ascribed to the effects of one or multiple LO phonons. The rectifying effects can be observed from the prototypical devices based on ZnO/Si heterojunctions. Although the parameters obtained by analyzing the current density-voltage characteristics are away from those from the ideal device, it is believed that ZnO/Si heterojunctions in the present work will be a potential candidate in the optoelectronic field through modulating and optimizing the fabrication conditions.
Several Topological Indices of Two Kinds of Tetrahedral Networks
Authors: Liu Jia-Bao , Fang Lu-Lu
Published: September 2021

Tetrahedral network is considered as an effective tool to create the finite element network model of simulation, and many research studies have been investigated. The aim of this paper is to calculate several topological indices of the linear and circle tetrahedral networks. Firstly, the resistance distances of the linear tetrahedral network under different classifications have been calculated. Secondly, according to the above results, two kinds of degree-Kirchhoff indices of the linear tetrahedral network have been achieved. Finally, the exact expressions of Kemeny’s constant, Randic index, and Zagreb index of the linear tetrahedral network have been deduced. By using the same method, the topological indices of circle tetrahedral network have also been obtained.
Clonazepam: An Old “New” Therapy for the Treatment of Phantom Limb Pain—A Brief Report of a Retrospective Study
Authors: Brunelli Stefano , Pratesi Luca , Traballesi Marco
Published: September 2021

The purpose of this study is to describe the results of clonazepam use in the treatment of phantom limb pain (PLP). Although the efficacy of clonazepam on PLP has been reported in 1996, there are no subsequent known studies that confirmed this report. A consecutive sample of 32 patients who suffered from PLP after recent lower limb amputation was studied based on clinical charts. Wilcoxon’s signed rank test was used to compare Numeric Rating Scale (NRS) values before and after the treatment with clonazepam. Twenty‐three amputees were treated only with clonazepam, without adding other drugs or targeted rehabilitation treatments. The median NRS before the treatment with clonazepam was 7 (2), the median NRS after 31 ± 5 days of treatment was 3 (3.5) (p < 0.0001). The average dosage of clonazepam used was 1.5 ± 1 mg per day. The results suggest that clonazepam has to be considered as an alternative drug for PLP treatment.