bluuebunny/crossref_metadata_2025 huggingface dataset:
WaFFLe
Authors: Chakraborty Shounak , Själander Magnus
Published: September 2021

Managing thermal imbalance in contemporary chip multi-processors (CMPs) is crucial in assuring functional correctness of modern mobile as well as server systems. Localized regions with high activity, e.g., register files, ALUs, FPUs, and so on, experience higher temperatures than the average across the chip and are commonly referred to as hotspots. Hotspots affect functional correctness of the underlying circuitry and a noticeable increase in leakage power, which in turn generates heat in a self-reinforced cycle. Techniques that reduce the severity of or completely eliminate hotspots can maintain functional correctness along with improving performance of CMPs. Conventional dynamic thermal management targets the cores to reduce hotspots but often ignores caches, which are known for their high leakage power consumption.

This article presents
WaFFLe
, an approach that targets the leakage power of the last-level cache (LLC) and hotspots occurring at the cores.
WaFFLe
turns off LLC-ways to reduce leakage power and to generate on-chip thermal buffers. In addition, fine-grained DVFS is applied during long LLC miss induced stalls to reduce core temperature. Our results show that
WaFFLe
reduces peak and average temperature of a 16-core based homogeneous tiled CMP with up to 8.4 ֯ C and 6.2 ֯ C, respectively, with an average performance degradation of only 2.5 %. We also show that
WaFFLe
outperforms a state-of-the-art cache-based technique and a greedy DVFS policy.
Evolution of Thermal Sensitivity in Changing and Variable Climates
Authors: Buckley Lauren B. , Kingsolver Joel G.
Published: September 2021

Evolutionary adaptation to temperature and climate depends on both the extent to which organisms experience spatial and temporal environmental variation (exposure) and how responsive they are to the environmental variation (sensitivity). Theoretical models and experiments suggesting substantial potential for thermal adaptation have largely omitted realistic environmental variation. Environmental variation can drive fluctuations in selection that slow adaptive evolution. We review how carefully filtering environmental conditions based on how organisms experience their environment and further considering organismal sensitivity can improve predictions of thermal adaptation. We contrast taxa differing in exposure and sensitivity. Plasticity can increase the rate of evolutionary adaptation in taxa exposed to pronounced environmental variation. However, forms of plasticity that severely limit exposure, such as behavioral thermoregulation and phenological shifts, can hinder thermal adaptation. Despite examples of rapid thermal adaptation, experimental studies often reveal evolutionary constraints. Further investigating these constraints and issues of timescale and thermal history are needed to predict evolutionary adaptation and, consequently, population persistence in changing and variable environments.
Evolution of Mimicry Rings as a Window into Community Dynamics
Authors: Kunte Krushnamegh , Kizhakke Athulya Girish , Nawge Viraj
Published: September 2021

Mimicry rings are communities of mimetic organisms that are excellent models for ecological and evolutionary studies because the community composition, the nature of the species interactions, the phenotypes under selection, and the selective agents are well characterized. Here, we review how regional and ecological filtering, density- and frequency-dependent selection, toxicity of prey, and age of mimicry rings shape their assembly. We synthesize findings from theoretical and empirical studies to generate the following hypotheses: ( a) the degree of unpalatability and age of mimicry rings increase mimicry ring size and ( b) the degree of unpalatability, generalization of the aposematic signal, and availability of alternative prey are positively related to the breadth of the protection umbrella for an aposematic signal and negatively related to the degree of mimetic resemblance. We also provide a phylogenetic framework in which key aspects of mimicry ring diversification may be studied.
Functional resilience of C57BL/6J mouse heart to dietary fat overload
Authors: Tadinada Satya Murthy , Weatherford Eric T. , Collins Greg V. , Bhardwaj Gourav , Cochran Jesse , Kutschke William , Zimmerman Kathy , Bosko Alyssa , O’Neill Brian T. , Weiss Robert M. , Abel E. Dale
Published: September 2021

Dietary fat overload (DFO) is widely used to model diabetic cardiomyopathy but the utility of this model is controversial. We comprehensively characterized cardiac contractile and mitochondrial function in C57BL6/J mice fed with lard-based or saturated fat-enriched diets initiated at two ages. Despite cardiac hypertrophy, contractile and mitochondrial function is preserved, and molecular adaptations likely limit lipotoxicity. The resilience of these hearts to DFO underscores the need to develop robust alternative models of diabetic cardiomyopathy.
Targeting Parasympathetic Activity to Improve Autonomic Tone and Clinical Outcomes
Authors: Kay Matthew W. , Jain Vivek , Panjrath Gurusher , Mendelowitz David
Published: September 2021

In this review we will briefly summarize the evidence that autonomic imbalance, more specifically reduced parasympathetic activity to the heart, generates and/or maintains many cardiorespiratory diseases and will discuss mechanisms and sites, from myocytes to the brain, that are potential translational targets for restoring parasympathetic activity and improving cardiorespiratory health.
Research on the Establishment and Stability of the Beijing-Tianjin-Hebei Region Air Pollution Cooperative Control Alliance: An Evolutionary Game Approach
Authors: Zhu Wei. , Shan Shaonan. , Shi Xiaohui. , Li Hui.
Published: September 2021

Air pollution control refers to a vital issue in the integrated and coordinated development of the Beijing-Tianjin-Hebei region. As impacted by the fluidity of air pollution, air pollution control cannot be achieved independently by a single local government in the Beijing-Tianjin-Hebei region, and a long-term mechanism should be established for regional coordination and cooperative control. However, in the pursuit of maximising benefits by the participating parties, difficulties in effective coordination between the various control bodies occurred and a dilemma was created in the cooperative control of air pollution in the Beijing-Tianjin-Hebei region. Based on the existing research, this study first builds an evolutionary game model to analyse the evolutionary path and stability of cooperative alliance of air pollution control behaviour in the Beijing-Tianjin-Hebei region. Second, this study explores the core elements of reaching alliances and consolidating cooperative control among cities in the Beijing-Tianjin-Hebei region. Last, in combination with the simulation results, this study compares the feasibility of cooperative control among cities in the Beijing-Tianjin-Hebei region with and without central government constraints. As indicated from the results, without the constraints of the central government, intergovernmental cooperative control is correlated with intercity public benefits, cities’ own benefits, and air pollution losses, whereas it is not effective since it cannot control the phenomenon of “free-riding” by cities in the Beijing-Tianjin-Hebei region. Under the control of the central government, a stable strategy among cities can evolve toward a fast and efficient cooperative management. To achieve air pollution control effectively, the air pollution control alliance should be formed in the Beijing-Tianjin-Hebei region, and the benefits of cooperation lay the basis for reaching cooperative control. The mentioned findings highlight that (1) the benefits of cooperation lay the basis for cooperative control, (2) punitive policies of central government increase the evolutionary rate of cooperative control, and (3) cooperation costs determine the long-term stability of the alliance.
Carbon Dioxide Emission Measurement and Its Spatiotemporal Evolution of Tourism Industry in Heilongjiang Province, China
Authors: Tang Zi , Huang Tianyue
Published: September 2021

This study analyses the composition and evolution of carbon dioxide emissions from the tourism industry in Heilongjiang Province and its 12 regions by the tourism consumption stripping coefficient method and calculates the decoupling relationship between the carbon dioxide emissions and economic growth of tourism from 2010 to 2019. The empirical results are as follows. (1) From 2010 to 2019, carbon dioxide emissions from Heilongjiang Province’s tourism industry and its subsector increased steadily, of which the tourism industry accounted for a relatively large amount of carbon dioxide emissions in “Transport, Storage, and Post.” (2) Time series analysis reveals that the carbon dioxide emissions of tourism basically show an increasing trend and there are still multiple decoupling relationships with economic growth. Expansive decoupling and weak decoupling have occurred more frequently. (3) Spatial analysis reveals that the carbon dioxide emissions of the regional tourism industry show a fluctuating upward trend. The tourism industry in Harbin has significantly higher carbon dioxide emissions than in other regions. In addition, this study provides feasible suggestions and countermeasures for low-carbon tourism development in Heilongjiang Province. The findings are considered useful in future planning of energy conservation and emission reduction in Heilongjiang Province and the regional tourism industry.
Implementation of MCDM-Based Integrated Approach to Identifying the Uncertainty Factors on the Constructional Project
Authors: Bagheri Raana , Borouji Zahra , Razavian Seyed Behnam , Keshvari Mohammad Mahdi , Sharifi Farzad , Sharifi Sara
Published: September 2021

Presently, environmental management for companies emphasizing environmental protection has become one of the most critical issues for customers, shareholders, governments, employees, competitors, and global pressures requiring organizations to produce environmentally-friendly products and services. This challenge has created a new concept called green supply chain management in business, which combines environmental thinking with the supply chain. Selection of suppliers by considering risk criteria is a category that has attracted the attention of a large number of researchers in order to select the best suppliers according to uncertain factors. In this research, we aim to select a green supplier considering risk factors using a new MCDM approach under uncertainty. For this selection problem, HF-MAIRCA, a new multicriteria sorting method for many alternatives, has been developed. This is used for sorting the alternatives into predefined, ordered supplier categories. This sorting method can be applied to different environmental problems that have a large number of alternatives. As a result of Iran’s case study, the result shows that materials flexibility and materials quality are essential criteria for green supplier selection.
Oxidative Stress Genes in Diabetes Mellitus Type 2: Association with Diabetic Kidney Disease
Authors: Roumeliotis Athanasios , Roumeliotis Stefanos , Tsetsos Fotis , Georgitsi Marianthi , Georgianos Panagiotis I. , Stamou Aikaterini , Vasilakou Anna , Kotsa Kalliopi , Tsekmekidou Xanthippi , Paschou Peristera , Panagoutsos Stylianos , Liakopoulos Vassilios
Published: September 2021

Diabetic type 2 patients compared to nondiabetic patients exhibit an increased risk of developing diabetic kidney disease (DKD), the leading cause of end‐stage renal disease. Hyperglycemia, hypertension, oxidative stress (OS), and genetic background are some of the mechanisms and pathways implicated in DKD pathogenesis. However, data on OS pathway susceptibility genes show limited success and conflicting or inconclusive results. Our study is aimed at exploring OS pathway genes and variants which could be associated with DKD. We recruited 121 diabetes mellitus type 2 (DM2) patients with DKD (cases) and 220 DM2, non‐DKD patients (control) of Greek origin and performed a case‐control association study using genome‐wide association data. PLINK and EIGENSOFT were used to analyze the data. Our results indicate 43 single nucleotide polymorphisms with their 21 corresponding genes on the OS pathway possibly contributing or protecting from DKD: SPP1, TPO, TTN, SGO2, NOS3, PDLIM1, CLU, CCS, GPX4, TXNRD2, EPHX2, MTL5, EPX, GPX3, ALOX12, IPCEF1, GSTA, OXR1, GPX6, AOX1, and PRNP. Therefore, a genetic OS background might underlie the complex pathogenesis of DKD in DM2 patients.
A Digital Twin-Based Approach for Optimization and Prediction of Oil and Gas Production
Authors: Shen Fei , Ren Shuang Shuang , Zhang Xiang Yang , Luo Hong Wu , Feng Chao Min
Published: September 2021

The Internet of things technology plays an important role in improving the efficiency of oil and gas production, of which digital twin technology is the most prominent. By effectively using data and organically combining them with a deep understanding of technicians, digital twin technology can improve the efficiency of oil and gas asset systems in the entire life cycle of an oilfield including design, operation control, optimization, etc. Starting with the concept of digital twinning, this paper analyzes the situation of digital twinning in various industries, then obtains the new connotation of digital twinning in oil and gas industry, and at last establishes an optimization model of oil and gas production. Based on the digital twinning of oil and gas and applying the Internet of things, real-time data, and AI, the paper optimizes the oil and gas production process control and applies it to the actual production. Actually, the digital twin technology of oil and gas production includes six parts: entity, model, data collection, intelligent algorithm, service, and interaction control. Meanwhile, each part is interspersed with various data perception and drive, and interactive feedback forms an organic iterative closed-loop control. Digital twin technology can effectively use data and organically combine the deep understanding of technical personnel, so that it can be used in design, operation control, optimization, and other aspects including the entire life cycle of the oilfield from concept to front-end design and out-of-service . And digital twin technology would improve the efficiency of oil and gas asset systems. The example analysis shows that the system efficiency of the oil and gas production model based on digital twinning is improved by 3%. By analyzing the production status, optimizing the design, and fully grasping the production capacity, equipment capacity, and their working conditions of the oil layer, the digital twin-based approach can provide a basis for further formulating reasonable technical measures and make the equipment work normally at high efficiency to ensure high output and efficient production of oil wells.
[Retracted] A Face Recognition System Using ACO‐BPNN Model for Optimizing the Teaching Management System
Authors: Zhu Xiuli
Published: September 2021

The basic idea of face recognition technology is to compare the matching degree between the standard face image marked with identity information and the static or dynamic face collected from the actual scene, which includes two main research contents: face feature extraction and face feature recognition. Traditional identification generally proves who we are through certificates, passwords, or certificates plus passwords. With the development of science and technology, face recognition technology will occupy an increasingly important position. Inspired by the human brain, the artificial neural network (ANN) is an information extraction system based on imitating the basic function and structure of the human brain and abstracted by physical and mathematical research methods. Based on the traditional BP neural network model, this paper proposes an ant colony algorithm‐enabled BP neural network (ACO‐BPNN) model and applies it to face recognition. Experimental results show that, similar to other face recognition techniques, the facial feature location needs to adapt to various changes of faces to the maximum extent, so the recognition and classification effect of the whole face feature extracted from the whole face image on the changes of such partial areas is not good, while the local feature extraction method based on ACO‐BPNN can achieve a good recognition and classification effect.
Viral Coinfection among COVID‐19 Patient Groups: An Update Systematic Review and Meta‐Analysis
Authors: Malekifar Pooneh , Pakzad Reza , Shahbahrami Ramin , Zandi Milad , Jafarpour Ali , Rezayat Sara Akhavan , Akbarpour Samaneh , Shabestari Alireza Namazi , Pakzad Iraj , Hesari Elahe , Farahani Abbas , Soltani Saber
Published: September 2021

Background. Coinfections have a potential role in increased morbidity and mortality rates during pandemics. Our investigation is aimed at evaluating the viral coinfection prevalence in COVID‐19 patients. Methods. We systematically searched scientific databases, including Medline, Scopus, WOS, and Embase, from December 1, 2019, to December 30, 2020. Preprint servers such as medRxiv were also scanned to find other related preprint papers. All types of studies evaluating the viral coinfection prevalence in COVID‐19 patients were considered. We applied the random effects model to pool all of the related studies. Results. Thirty‐three studies including 10484 patients were identified. The viral coinfection estimated pooled prevalence was 12.58%; 95% CI: 7.31 to 18.96). Blood viruses (pooled prevalence: 12.48%; 95% CI: 8.57 to 16.93) had the most frequent viral coinfection, and respiratory viruses (pooled prevalence: 4.32%; 95% CI: 2.78 to 6.15) had less frequent viral coinfection. The herpesvirus pooled prevalence was 11.71% (95% CI: 3.02 to 24.80). Also, the maximum and minimum of viral coinfection pooled prevalence were in AMRO and EMRO with 15.63% (95% CI: 3.78 to 33.31) and 7.05% (95% CI: 3.84 to 11.07), respectively. Conclusion. The lowest rate of coinfection belonged to respiratory viruses. Blood‐borne viruses had the highest coinfection rate. Our results provide important data about the prevalence of blood‐borne viruses among COVID‐19 patients which can be critical when it comes to their treatment procedure.
[Retracted] Identification of Navel Orange Diseases and Pests Based on the Fusion of DenseNet and Self‐Attention Mechanism
Authors: Zhang Yin’e , Liu Yong Ping
Published: September 2021

The prevention and control of navel orange pests and diseases is an important measure to ensure the yield of navel oranges. Aiming at the problems of slow speed, strong subjectivity, high requirements for professional knowledge required, and high identification costs in the identification methods of navel orange pests and diseases, this paper proposes a method based on DenseNet and attention. The power mechanism fusion (DCPSNET) identification method of navel orange diseases and pests improves the traditional deep dense network DenseNet model to realize accurate and efficient identification of navel orange diseases and pests. Due to the difficulty in collecting data of navel orange pests and diseases, this article uses image enhancement technology to expand. The experimental results show that, in the case of small samples, compared with the traditional model, the DCPSNET model can accurately identify different types of navel orange diseases and pests images and the accuracy of identifying six types of navel orange diseases and pests on the test set is as high as 96.90%. The method proposed in this paper has high recognition accuracy, realizes the intelligent recognition of navel orange diseases and pests, and also provides a way for high‐precision recognition of small sample data sets.
Using Pomegranate Peel and Date Pit Activated Carbon for the Removal of Cadmium and Lead Ions from Aqueous Solution
Authors: Al-Onazi Wedad A. , Ali Mohamed H.H. , Al-Garni Tahani
Published: September 2021

Some agricultural byproducts are useful for solving wastewater pollution problems. These byproducts are of low cost and are effective and ecofriendly. The study aim was to investigate the possibility of using pomegranate peel (PP) and date pit (DP) activated carbon (PPAC and DPAC, respectively) as sorbents to remove Cd(II) and Pb(II) from aqueous solutions. Agricultural wastes of DPs and PPs were subjected to carbonization and chemical activation with H3PO4 (60%) and ZnCl2 and used as adsorbents to remove Cd(II) and Pb(II) from their aqueous solutions. The physical characterizations of PPAC and DPAC, including determination of surface area, scanning electron microscopy, energy-dispersive X-ray spectroscopy, and Fourier-transform infrared spectroscopy, were performed. The following factors affected adsorption: solution pH, adsorbent dosage, initial metal ion concentration, and contact time. These factors were studied to identify the optimal adsorption conditions. The results showed that the maximum adsorptions of Cd(II) and Pb(II) were achieved at pH ranging from 6 to 6.5, 90 min contact time, and 0.5 g/L for PPAC and 1 g/L for DPAC dosage. Furthermore, the adsorption efficiencies for both Pb(II) and Cd(II) were higher for PPAC than for DPAC. However, the recorded Qmax values for PPAC were 68.6 and 53.8 mg/g for Pb(II) and Cd(II) and for DPAC were 34.18 and 32.90 mg/g for Pb(II) and Cd(II), respectively. The Langmuir isotherm model fit the adsorption data better than the Freundlich model. Kinetically, the adsorption reaction followed a pseudo-second-order reaction model, with qe ranging from 12.0 to 22.37 mg/g and an R2 value of 0.99.
Effect of Infrastructure Investment and Freight Accessibility on Gross Domestic Product: A Data-Driven Geographical Approach
Authors: Jubiz-Diaz Maria , Saltarin-Molino Maria , Arellana Julian , Paternina-Arboleda Carlos , Yie-Pinedo Ruben
Published: September 2021

Freight transportation can be defined as the movement of goods and services to customers to obtain a monetary reward. Poor quality transport infrastructure implies higher travelling times and costs. This indirectly affects the productivity of a region since transportation costs are directly related to sales prices. Therefore, infrastructure investments become important for improving the competitiveness of a region. The problem with these investments is that they take time and require a large amount of money. Consequently, it is extremely important to prioritise this type of investment. This paper will first explain whether transportation investment or a sustainable transportation method affect the exported freight accessibility and if it also affects regional productivity using a linear regression model with the aid of a data-driven geographical information system. It uses spatial separation, gravity, and cumulative opportunity measures to calculate accessibility. Finally, the paper denotes which regions are highly affected by improvements in road, river, and railway networks using Colombia as a case study. The comparison considers travelling time and costs savings under each scenario. The results indicate that the gravity measure was the most appropriate accessibility measure for analysing the Gross Domestic Product (GDP). The scenario analyses suggest that zones farthest from the seaports are more sensitive to accessibility changes; consequently, they will receive higher improvements in their regional GDP with a national-level implementation of transport infrastructure investments. Thus, project prioritisation should be performed in regions where the investments lead to a decreased travel cost between regions and ports.
Biomarker Extraction Based on Subspace Learning for the Prediction of Mild Cognitive Impairment Conversion
Authors: Li Ying , Fang Yixian , Wang Jiankun , Zhang Huaxiang , Hu Bin
Published: September 2021

Accurate recognition of progressive mild cognitive impairment (MCI) is helpful to reduce the risk of developing Alzheimer’s disease (AD). However, it is still challenging to extract effective biomarkers from multivariate brain structural magnetic resonance imaging (MRI) features to accurately differentiate the progressive MCI from stable MCI. We develop novel biomarkers by combining subspace learning methods with the information of AD as well as normal control (NC) subjects for the prediction of MCI conversion using multivariate structural MRI data. Specifically, we first learn two projection matrices to map multivariate structural MRI data into a common label subspace for AD and NC subjects, where the original data structure and the one‐to‐one correspondence between multiple variables are kept as much as possible. Afterwards, the multivariate structural MRI features of MCI subjects are mapped into a common subspace according to the projection matrices. We then perform the self‐weighted operation and weighted fusion on the features in common subspace to extract the novel biomarkers for MCI subjects. The proposed biomarkers are tested on Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. Experimental results indicate that our proposed biomarkers outperform the competing biomarkers on the discrimination between progressive MCI and stable MCI. And the improvement from the proposed biomarkers is not limited to a particular classifier. Moreover, the results also confirm that the information of AD and NC subjects is conducive to predicting conversion from MCI to AD. In conclusion, we find a good representation of brain features from high‐dimensional MRI data, which exhibits promising performance for predicting conversion from MCI to AD.
Impact of Tunnel Groups on Pupil Diameter of Drivers on Mountainous Freeway in China: A Real-World Driving Study
Authors: Gao Jianping , Zhang Sijie , He Yunyong , Zhang Qi , Sun Lu , Lu Chang , Wu Yi , He Enhuai , Yang Changfeng
Published: September 2021

A real-world driving experiment was performed in the Wen-Ma section of the G4217 Rong-Chang Freeway situated in the Sichuan Province to investigate the impact law of the pupil diameter of drivers in tunnel groups on the mountainous freeway. The eye-movement data of drivers were collected, and the percentage of pupil diameter variable (PPDV) was used as a visual characteristic index. The analysis of the overall change in the PPDV of drivers in the experimental sections demonstrated that the PPDV in tunnel groups differed significantly between the nontunnel sections and single tunnel sections. Subsequently, a related model for the PPDV of drivers and the length of the connecting zone between tunnels was established, its reliability evaluated, and the smooth mutation value obtained on the basis of the mutation theory. Thereafter, a tunnel group definition standard based on the visual effect of drivers was developed. A six-zone approach was devised for the analysis of tunnel groups, and the result revealed that the different zones in the tunnel group have different impact on PPDV of drivers. The results revealed that the different zones of tunnel group have different impact on PPDV of drivers. Furthermore, lighting transition facilities should be set in the exit section of tunnel. The PPDV of drivers was negatively correlated with the length of the connecting zone of tunnel groups, and 100 m is the recommended safety length threshold for the connecting zone of tunnel groups.
Analyzing Drivers’ Distractions due to Smartphone Usage: Evidence from AutoLog Dataset
Authors: Khan Inayat , Rizvi Sanam Shahla , Khusro Shah , Ali Shaukat , Chung Tae-Sun
Published: September 2021

The usage of a smartphone while driving has been declared a global portent and has been admitted as a leading cause of crashes and accidents. Numerous solutions, such as Android Auto and CarPlay, are used to facilitate for the drivers by minimizing driver distractions. However, these solutions restrict smartphone usage, which is impractical in real driving scenarios. This research paper presents a comprehensive analysis of the available solutions to identify issues in smartphone activities. We have used empirical evaluation and dataset-based evaluation to investigate the issues in the existing smartphone user interfaces. The results show that using smartphones while driving can disrupt normal driving and may lead to change the steering wheel abruptly, focus off the road, and increases cognitive load, which could collectively result in a devastating situation. To justify the arguments, we have conducted an empirical study by collecting data using maxed mode survey, i.e., questionnaires and interviews from 98 drivers. The results show that existing smartphone-based solutions are least suitable due to numerous issues (e.g., complex and rich interfaces, redundant and time-consuming activities, requiring much visual and mental attention, and contextual constraints), making their effectiveness less viable for the drivers. Based on findings obtained from Ordinal Logistic Regression (OLR) models, it is recommended that the interactions between the drivers and smartphone could be minimized by developing context-aware adaptive user interfaces to overcome the chances of accidents.
Numerical Study on the Movement Laws of Overlying Strata in Shallow‐Buried Stope Based on the Goaf Compaction Effect
Authors: Zhang Guangchao , Tao Guangzhe , Chen Miao , Li You , Li Pan , Lai Yonghui
Published: September 2021

This study presents an integrated approach including the theoretical analysis and numerical modelling to investigate the failure characteristics of the overlying strata in the shallow‐buried stope. The mechanical characteristics of the caving zone are first revealed and then calibrated by using the double‐yield model. The theoretical results show that the mechanical properties of the collapsed rock mass are closely related to its crushing expansion coefficient and uniaxial compressive strength. The vertical stress of the collapsed rock mass increases slowly with the strain and then increases exponentially after a certain critical strain. The simulation indicates that the fracture zone volume is 1.7‐1.8 times that of the caving zone in the 31108 working face, and the failure volume of the overlying strata is 9‐10 times that of the stope. The simulated height of the caving zone and fracture zone is 9 m and 20 m, respectively. The comparison between the numerical and field measurement results demonstrates that the new evaluation method using shear‐tensile strain behaviors can accurately predicate the height of the two zones. The proposed numerical method could be a viable alternative approach to two zones height calculation.
High-Accuracy Surface Profile Measurement Based on the Vortex Phase-Shifting Interferometry
Authors: Zhao Donge , Jia Chaozheng , Ma Yayun , Yang Xuefeng , Zhang Bin , Chu Wenbo
Published: September 2021

According to the principle of phase-shifting interferometry and spiral phase characteristics of the vortex beam, this article proposes a method for detecting the surface profile of a transparent object, in which the +1 order vortex beam is generated by a spatial light modulator and is taken as the reference light. The influence of the nonlinear phase modulation characteristics of the spatial light modulator on the measurement precision is studied. The results show that nonlinear phase modulation has a great impact on the measurement. Then, the vortex lights with initial phases of 0, π/2, π, and 3π/2 are used to measure the H-type thin film sample based on the Twyman-Green interference system after correcting the nonlinear phase modulation characteristics. The experimental results show that the measurement error of the surface profile to an object with the theoretical value of 20 nm is 1.146 nm, and the feasibility of the optical vortex phase-shifting technique used to measure the surface profile of an object is verified.
Maximum Likelihood Estimation of Parameters for Advanced Continuously Reinforced Concrete Pavement (CRCP) Punchout Calibration Model
Authors: Chen Liangliang , Zhang Feng , Zhou Changjun
Published: September 2021

Pavement performance prediction is the essential part of the pavement design, which is very important for highway agencies for the purpose of budget allocating. This study introduces a model of local calibration for punchout, which is the major structural distress of continuously reinforced concrete pavement (CRCP). It is assumed that the number of equivalent single axle loads’ (ESALs) leads to punchout follows a Weibull distribution. The parameters of Weibull distribution were estimated by maximum likelihood estimation (MLE). Additionally, an approach of estimating the initial value of the parameters was also presented before applying the Newton method for solving the likelihood equations. The regression result was found to fit the performance‐monitoring data from LTPP very well. The proposed calibration model is capable of describing the punchout and can be employed to predict the failure rate and reliability of CRCP in the pavement design and the arrangement of rehabilitation activities.
Validation and Optimization of Suspension Design for Testing Platform Vehicle
Authors: Li Luhang , Xu Lin , Cui Hao , Abdelkareem Mohamed A. A. , Liu Zihao , Chen Jingyu
Published: September 2021

With the application and popularization of the advanced driving assistance system (ADAS), the reliability and stability of ADAS have become its research focus. This article presents a car testing framework for ADAS reliability and stability. Its special suspension has been designed, verified, and optimized in real vehicles according to its working conditions. First, the structure and working principle of the testing platform vehicle are introduced. Then a simulation model is built in MATLAB/Simulink based on the dynamic equation to verify the working characteristics of the suspension. Experimental vehicle tests are conducted for simulation verification purposes. During the analysis, the root‐mean‐square (RMS) values of vehicle body displacement and dynamic tire deflection are considered evaluation indices. The nondominated sorting genetic algorithm (NSGA‐II) is used to optimize the damping, stiffness, and installation position of the suspension system. The findings demonstrate that the specially designed suspension in this article can fulfill the test criteria. Compared with the optimized suspension performance, both the vehicle body displacement and dynamic tire deflection have decreased roughly by 17 and 40%, respectively, which significantly improves the suspension performance and provides a reference for the future designs of testing platform vehicles.
Circular RNA FOXP1 Induced by ZNF263 Upregulates U2AF2 Expression to Accelerate Renal Cell Carcinoma Tumorigenesis and Warburg Effect through Sponging miR-423-5p
Authors: Fang Li , Ye Ting , An Yanmei
Published: September 2021

Renal cell carcinoma (RCC), as one of the most common malignant tumors in the urinary system, is featured with high morbidity and mortality. Although the improvement of clinical intervention, such as surgery technology, chemotherapy, and radiotherapy, has been made, the outcomes of RCC patients are still poor. Novel targets for RCC treatment are urgently needed. Recently, circRNA has been in-depth studied and is considered as a promising direction for gene target therapy. In this study, we explored the function of circFOXP1 in RCC progression and its underlying mechanisms. Firstly, we demonstrated the characterization and expression of circFOXP1 in RCC tissues and cells. Next, by conducting a serial experiment, we found that downregulated circFOXP1 inhibited cell proliferation, migration, invasion, and the Warburg effect. Next, our experiments found that circFOXP1 upregulated U2AF2 expression via sponging miR-423-5p in RCC cells. Moreover, we found that ZNF263 induced circFOXP1 expression in RCC cells. To sum up, our study partially demonstrated that the novel ZNF263/circFOXP1/miR-423-5p/U2AF2 axis has a role in RCC progression. Our results might provide a new direction for RCC therapeutic target exploring.
Application of BigML in the Classification Evaluation of Top Coal Caving
Authors: Wang Meng , Tai Caiwang , Zhang Qiaofeng , Yang Zongwei , Li Jiazheng , Shen Kejun , Wang Kang
Published: September 2021

Longwall top coal caving mining is one of the main methods of mining thick coal seams in China. Therefore, carrying out the classification evaluation of top coal caving is of great significance to ensure mining success and reduce the risk of mining technology. In order to realize the classification evaluation of top coal caving, this article introduces the method of using BigML to establish the classification evaluation model of top coal caving. Furthermore, using the data from the CNKI database as sample data, a classification evaluation model of top coal caving is established on BigML. After training, testing, and optimization, the model is used to evaluate the top coal caving in No. 3 coal seam of Gucheng Coal Mine, and the evaluation result is grade 1, which is consistent with the engineering practice. The final research results show that the application of BigML in the classification evaluation of top coal caving is successful; the evaluation of top coal caving through BigML is reliable; BigML provides another scientific reliability way for the classification evaluation of top coal caving.
Backstepping Control Based on Constrained Command Filter for Hypersonic Flight Vehicles with AOA and Actuator Constraints
Authors: Wei Junbao , Li Haiyan , Guo Ming , Li Jing , Huang Huang
Published: September 2021

An antisaturation backstepping control scheme based on constrained command filter for hypersonic flight vehicle (HFV) is proposed with the consideration of angle of attack (AOA) constraint and actuator constraints of amplitude and rate. Firstly, the HFV system model is divided into velocity subsystem and height subsystem. Secondly, to handle AOA constraint, a constrained command filter is constructed to limit the amplitude of the AOA command and retain its differentiability. And the constraint range is set in advance via a prescribed performance method to guarantee that the tracking error of the AOA meets the constraint conditions and transient and steady performance. Thirdly, the proposed constrained command filter is combined with the auxiliary system for actuator constraints, which ensures that the control input meets the limited requirements of amplitude and rate, and the system is stable. In addition, the tracking errors of the system are proved to be ultimately uniformly bounded based on the Lyapunov stability theory. Finally, the effectiveness of the proposed method is verified by simulation.
Spatial and Temporal Distribution Analysis of Traffic Accidents Using GIS-Based Data in Harbin
Authors: Wang Meina , Yi Jing , Chen Xirui , Zhang Wenhui , Qiang Tiangang
Published: September 2021

Road traffic safety is a social issue of widespread concern. It is important for traffic managers to understand the distribution patterns of road traffic accidents. To this end, this study examines the spatial and temporal patterns of road traffic accidents from both accident frequency and accident severity perspectives. Road traffic accident data from 2016 to 2018 in Harbin, China, were used for the analysis. First, the spatial localization of accidents was completed using geocoding, and the localized accident data were classified by season. Then, density analysis was performed both with and without considering road network density. The results of the density analysis showed that when road network density was considered, accidents were mainly distributed in urban centers, while accidents were more dispersed when road network density was not considered. Third, a cluster analysis considering accident severity found that low-severity accident clusters occurred mostly in urban centers. High-severity accident clusters were mostly present in suburban areas. Finally, the results of these two methods are shown by using the comap technique. Areas of the city with a high frequency and severity of crashes in each season were identified. This study will help traffic management to have a more visual and intuitive understanding of the urban traffic safety situation and to take targeted measures to improve it accordingly.
Research Progress on Shear Characteristics of Rock Joints under Constant Normal Stiffness Boundary Conditions
Authors: Han Guansheng , Xiong Fei , Zhou Yu , Song Leibo , Wang Xingkai
Published: September 2021

The constant normal stiffness (CNS) boundary condition is more representative for the underground engineering, in which the shear‐induced dilation is restricted by surrounding rocks, resulting in an increase in the normal stress. Therefore, the use of CNS boundary conditions in the research of shear‐slip failure of underground rock engineering is more in line with the actual situation. Taking the instability and failure of surrounding rock in underground engineering as the background, the present study introduces the engineering background of CNS boundary conditions and the research progress on shear characteristics of rock joints under CNS boundary conditions. Three key directions for future research are proposed based on the latest research results of shear characteristics of rock joint under CNS boundary conditions: ① developing a rock joint shear test system that can realize the function of “CNS boundary conditions + shear‐seepage test + visualization”; ② carrying out the shear tests of real rock joints under CNS boundary conditions based on 3D scanning and 3D carving technology; and ③ carrying out the shear tests of rock joint network under CNS boundary conditions.
The Positive Role and Mechanism of Herbal Medicine in Parkinson’s Disease
Authors: Yin Rong , Xue Jie , Tan Yanfeng , Fang Chuantao , Hu Chunchun , Yang Qian , Mei Xinyu , Qi Dashi
Published: September 2021

Parkinson’s disease (PD) is a complex neurodegenerative disease, manifested by the progressive functional impairment of the midbrain nigral dopaminergic neurons. Due to the unclear underlying pathogenesis, disease‐modifying drugs for PD remain elusive. In Asia, such as in China and India, herbal medicines have been used in the treatment of neurodegenerative disease for thousands of years, which recently attracted considerable attention because of the development of curative drugs for PD. In this review, we first summarized the pathogenic factors of PD including protein aggregation, mitochondrial dysfunction, ion accumulation, neuroinflammation, and oxidative stress, and the related recent advances. Secondly, we summarized 32 Chinese herbal medicines (belonging to 24 genera, such as Acanthopanax, Alpinia, and Astragalus), 22 Chinese traditional herbal formulations, and 3 Indian herbal medicines, of which the ethanol/water extraction or main bioactive compounds have been extensively investigated on PD models both in vitro and in vivo. We elaborately provided pictures of the representative herbs and the structural formula of the bioactive components (such as leutheroside B and astragaloside IV) of the herbal medicines. Also, we specified the potential targets of the bioactive compounds or extractions of herbs in view of the signaling pathways such as PI3K, NF‐κB, and AMPK which are implicated in oxidative and inflammatory stress in neurons. We consider that this knowledge of herbal medicines or their bioactive components can be favorable for the development of disease‐modifying drugs for PD.
Oncogenic HSP90 Facilitates Metabolic Alterations in Aggressive B-cell Lymphomas
Authors: Calvo-Vidal M. Nieves , Zamponi Nahuel , Krumsiek Jan , Stockslager Max A. , Revuelta Maria V. , Phillip Jude M. , Marullo Rossella , Tikhonova Ekaterina , Kotlov Nikita , Patel Jayeshkumar , Yang Shao Ning , Yang Lucy , Taldone Tony , Thieblemont Catherine , Leonard John P. , Martin Peter , Inghirami Giorgio , Chiosis Gabriela , Manalis Scott R. , Cerchietti Leandro
Published: September 2021

HSP90 is critical for maintenance of the cellular proteostasis. In cancer cells, HSP90 also becomes a nucleating site for the stabilization of multiprotein complexes including signaling pathways and transcription complexes. Here we described the role of this HSP90 form, referred to as oncogenic HSP90, in the regulation of cytosolic metabolic pathways in proliferating B-cell lymphoma cells. Oncogenic HSP90 assisted in the organization of metabolic enzymes into non-membrane–bound functional compartments. Under experimental conditions that conserved cellular proteostasis, oncogenic HSP90 coordinated and sustained multiple metabolic pathways required for energy production and maintenance of cellular biomass as well as for secretion of extracellular metabolites. Conversely, inhibition of oncogenic HSP90, in absence of apparent client protein degradation, decreased the efficiency of MYC-driven metabolic reprogramming. This study reveals that oncogenic HSP90 supports metabolism in B-cell lymphoma cells and patients with diffuse large B-cell lymphoma, providing a novel mechanism of activity for HSP90 inhibitors.

Significance:

The oncogenic form of HSP90 organizes and maintains functional multienzymatic metabolic hubs in cancer cells, suggesting the potential of repurposing oncogenic HSP90 selective inhibitors to disrupt metabolism in lymphoma cells.
Tumor Cell IDO Enhances Immune Suppression and Decreases Survival Independent of Tryptophan Metabolism in Glioblastoma
Authors: Zhai Lijie , Bell April , Ladomersky Erik , Lauing Kristen L. , Bollu Lakshmi , Nguyen Brenda , Genet Matthew , Kim Miri , Chen Peiwen , Mi Xinlei , Wu Jennifer D. , Schipma Matthew J. , Wray Brian , Griffiths John , Unwin Richard D. , Clark Simon J. , Acharya Rajesh , Bao Riyue , Horbinski Craig , Lukas Rimas V. , Schiltz Gary E. , Wainwright Derek A.
Published: September 2021

Purpose:

Glioblastoma (GBM) is an incurable primary brain tumor that has not benefited from immunotherapy to date. More than 90% of GBM expresses the tryptophan (Trp) metabolic enzyme, indoleamine 2,3-dioxygenase 1 (IDO). This observation supported the historical hypothesis that IDO suppresses the antitumor immune response solely through a mechanism that requires intratumoral Trp depletion. However, recent findings led us to investigate the alternative hypothesis that IDO suppresses the anti-GBM immune response independent of its association with Trp metabolism.

Experimental Design:

IDO-deficient GBM cell lines reconstituted with IDO wild-type or IDO enzyme–null cDNA were created and validated in vitro and in vivo. Microarray analysis was conducted to search for genes that IDO regulates, followed by the analysis of human GBM cell lines, patient GBM and plasma, and The Cancer Genome Atlas (TCGA) database. Ex vivo cell coculture assays, syngeneic and humanized mouse GBM models, were used to test the alternative hypothesis.

Results:

Nonenzymic tumor cell IDO activity decreased the survival of experimental animals and increased the expression of complement factor H (CFH) and its isoform, factor H like protein 1 (FHL-1) in human GBM. Tumor cell IDO increased CFH and FHL-1 expression independent of Trp metabolism. Increased intratumoral CFH and FHL-1 levels were associated with poorer survival among patients with glioma. Similar to IDO effects, GBM cell FHL-1 expression increased intratumoral regulatory T cells (Treg) and myeloid-derived suppressor cells while it decreased overall survival in mice with GBM.

Conclusions:

Our study reveals a nonmetabolic IDO-mediated enhancement of CFH expression and provides a new therapeutic target for patients with GBM.