bluuebunny/crossref_metadata_2025 huggingface dataset:
Analytical Analysis of Interaction Between a Heavy Vehicle and a Simply Supported Light Bridge Based on Frequency Modulation
Authors: Zhang Yao , Tan Kang Hai
Published: February 2021

This paper analyzes the interaction between a heavy vehicle and a simply supported light bridge based on frequency modulation technique, in which variations of instantaneous frequencies of both bridge and heavy vehicle are considered. The bridge is modeled as a simply supported Euler beam and the heavy vehicle is simplified as a spring-mass system. The variation of instantaneous frequencies of both bridge and vehicle induced by the moving vehicle is usually neglected in classical analysis to decouple the pair of governing equations. However, the coupled vehicle–bridge interaction (VBI) system becomes time-varying and the pair of governing equations cannot be decoupled when the vehicle/bridge mass ratio cannot be neglected. The instantaneous frequencies of both bridge and heavy vehicle including their higher vibration modes are investigated herein. An analytical solution describing the dynamic response of the time-varying VBI system is developed by using the frequency modulation technique. Both Finite Element (FE) method and published experimental data are used for comparison purpose. The predictions of the proposed method match better with those obtained from the FE simulations and experimental measurements than the classical method. Five numerical examples have been adopted to compare the performance of the proposed model and the classical method: the former performs generally well, especially when the vehicle is heavy, or the vehicle frequency is near to the bridge frequency. The classical method is only a special case of the proposed model if either the mass or the stiffness of the vehicle is relatively small compared to the corresponding terms of the bridge. The performance of the proposed method has also been examined in four typical scenarios, where vehicle damping, multi-degree-of-freedom (MDOF) vehicle, road surface roughness, and two-span continuous bridge are involved.
Beyond Tests
Authors: Gao Xiang , Wang Bo , Duck Gregory J. , Ji Ruyi , Xiong Yingfei , Roychoudhury Abhik
Published: February 2021

Automated program repair is an emerging technology that seeks to automatically rectify program errors and vulnerabilities. Repair techniques are driven by a correctness criterion that is often in the form of a test suite. Such test-based repair may produce overfitting patches, where the patches produced fail on tests outside the test suite driving the repair. In this work, we present a repair method that fixes program vulnerabilities without the need for a voluminous test suite. Given a vulnerability as evidenced by an exploit, the technique extracts a constraint representing the vulnerability with the help of sanitizers. The extracted constraint serves as a proof obligation that our synthesized patch should satisfy. The proof obligation is met by propagating the extracted constraint to locations that are deemed to be “suitable” fix locations. An implementation of our approach (E
xtract
F
ix
) on top of the KLEE symbolic execution engine shows its efficacy in fixing a wide range of vulnerabilities taken from the ManyBugs benchmark, real-world CVEs and Google’s OSS-Fuzz framework. We believe that our work presents a way forward for the overfitting problem in program repair by generalizing observable hazards/vulnerabilities (as constraint) from a single failing test or exploit.
Sampling Sparse Representations with Randomized Measurement Langevin Dynamics
Authors: Wang Kafeng , Xiong Haoyi , Bian Jiang , Zhu Zhanxing , Gao Qian , Guo Zhishan , Xu Cheng-Zhong , Huan Jun , Dou Dejing
Published: February 2021

Stochastic Gradient Langevin Dynamics (SGLD) have been widely used for Bayesian sampling from certain probability distributions, incorporating derivatives of the log-posterior. With the derivative evaluation of the log-posterior distribution, SGLD methods generate samples from the distribution through performing as a thermostats dynamics that traverses over gradient flows of the log-posterior with certainly controllable perturbation. Even when the density is not known, existing solutions still can first learn the kernel density models from the given datasets, then produce new samples using the SGLD over the kernel density derivatives. In this work, instead of exploring new samples from kernel spaces, a novel SGLD sampler, namely,
Randomized Measurement Langevin Dynamics
(RMLD) is proposed to sample the high-dimensional sparse representations from the spectral domain of a given dataset.

Specifically, given a random measurement matrix for sparse coding, RMLD first derives a novel likelihood evaluator of the probability distribution from the loss function of LASSO, then samples from the high-dimensional distribution using stochastic Langevin dynamics with derivatives of the logarithm likelihood and Metropolis–Hastings sampling. In addition, new samples in low-dimensional measuring spaces can be regenerated using the sampled high-dimensional vectors and the measurement matrix. The algorithm analysis shows that RMLD indeed projects a given dataset into a high-dimensional Gaussian distribution with Laplacian prior, then draw new sparse representation from the dataset through performing SGLD over the distribution. Extensive experiments have been conducted to evaluate the proposed algorithm using real-world datasets. The performance comparisons on three real-world applications demonstrate the superior performance of RMLD beyond baseline methods.
The Fair Division of Hereditary Set Systems
Authors: Li Z. , Vetta A.
Published: February 2021

We consider the fair division of indivisible items using the maximin shares measure. Recent work on the topic has focused on extending results beyond the class of additive valuation functions. In this spirit, we study the case where the items form a hereditary set system. We present a simple algorithm that allocates each agent a bundle of items whose value is at least 0.3666 times the maximin share of the agent. This improves upon the current best known guarantee of 0.2 due to Ghodsi et al. The analysis of the algorithm is almost tight; we present an instance where the algorithm provides a guarantee of at most 0.3738. We also show that the algorithm can be implemented in polynomial time given a valuation oracle for each agent.
A Survey on Distributed Graph Pattern Matching in Massive Graphs
Authors: Bouhenni Sarra , Yahiaoui Saïd , Nouali-Taboudjemat Nadia , Kheddouci Hamamache
Published: February 2021

Besides its NP-completeness, the strict constraints of subgraph isomorphism are making it impractical for graph pattern matching (GPM) in the context of big data. As a result, relaxed GPM models have emerged as they yield interesting results in a polynomial time. However, massive graphs generated by mostly social networks require a distributed storing and processing of the data over multiple machines, thus, requiring GPM to be revised by adopting new paradigms of big graphs processing, e.g., Think-Like-A-Vertex and its derivatives. This article discusses and proposes a classification of distributed GPM approaches with a narrow focus on the relaxed models.
Systematic Mutation-Based Evaluation of the Soundness of Security-Focused Android Static Analysis Techniques
Authors: Ami Amit Seal , Kafle Kaushal , Moran Kevin , Nadkarni Adwait , Poshyvanyk Denys
Published: February 2021

Mobile application security has been a major area of focus for security research over the course of the last decade. Numerous application analysis tools have been proposed in response to malicious, curious, or vulnerable apps. However, existing tools, and specifically, static analysis tools, trade soundness of the analysis for precision and performance and are hence sound
y
. Unfortunately, the specific unsound choices or flaws in the design of these tools is often not known or well documented, leading to misplaced confidence among researchers, developers, and users. This article describes the
Mutation-Based Soundness Evaluation
(μSE) framework, which systematically evaluates Android static analysis tools to discover, document, and fix flaws, by leveraging the well-founded practice of mutation analysis. We implemented μSE and applied it to a set of prominent Android static analysis tools that detect private data leaks in apps. In a study conducted previously, we used μSE to discover 13 previously undocumented flaws in FlowDroid, one of the most prominent data leak detectors for Android apps. Moreover, we discovered that flaws also propagated to other tools that build upon the design or implementation of FlowDroid or its components. This article substantially extends our μSE framework and offers a new in-depth analysis of two more major tools in our 2020 study; we find 12 new, undocumented flaws and demonstrate that all 25 flaws are found in more than one tool, regardless of any inheritance-relation among the tools. Our results motivate the need for systematic discovery and documentation of unsound choices in soundy tools and demonstrate the opportunities in leveraging mutation testing in achieving this goal.
Conference reports
Authors: Dennis Louise A.
Published: February 2021

This section features brief reports from recent events sponsored or run in cooperation with ACM SIGAI.
Function of Renal Nerves in Kidney Physiology and Pathophysiology
Authors: Osborn John W. , Tyshynsky Roman , Vulchanova Lucy
Published: February 2021

Renal sympathetic (efferent) nerves play an important role in the regulation of renal function, including glomerular filtration, sodium reabsorption, and renin release. The kidney is also innervated by sensory (afferent) nerves that relay information to the brain to modulate sympathetic outflow. Hypertension and other cardiometabolic diseases are linked to overactivity of renal sympathetic and sensory nerves, but our mechanistic understanding of these relationships is limited. Clinical trials of catheter-based renal nerve ablation to treat hypertension have yielded promising results. Therefore, a greater understanding of how renal nerves control the kidney under physiological and pathophysiological conditions is needed. In this review, we provide an overview of the current knowledge of the anatomy of efferent and afferent renal nerves and their functions in normal and pathophysiological conditions. We also suggest further avenues of research for development of novel therapies targeting the renal nerves.
PEMFC Anode Durability: Innovative Characterization Methods and Further Insights on OER Based Reversal Tolerance
Authors: Bentele D. , Aylar K. , Olsen K. , Klemm E. , Eberhardt S. H.
Published: February 2021

Durability is a major lever for commercial success of proton exchange membrane fuel cells (PEMFCs). The introduction of OER catalyst to the PEMFC anode has been established as a material based mitigation strategy for reversal events caused by gross fuel (i.e. H2) starvation. We investigated the degradation of two different OER based reversal tolerant anodes during short-term recurring reversal operation to mimic field occurrence of reversal events realistically. PEMFC failure during normal operation can be observed whereas OER activity during reversal operation is unaffected. This result is in contrast to findings for commonly applied prolonged reversal accelerated stress tests (ASTs) and indicates an OER catalyst recovery effect for short and recurring reversal events. Combining the developed AST with cyclic voltammetry, electrochemical impedance spectroscopy and hydrogen pump, tests failures during normal operation is mainly assigned to hydrogen oxidation mass transfer increase indicating carbon corrosion and structural change within the anode catalyst layer. Consequently, the developed combination of AST and further characterization methods enables in situ distinction between catalyst and structural degradation, highlighting to be a good basis to investigate future aspects regarding anode degradation caused by cell reversal.
AAV Induced Expression of Human Rod and Cone Opsin in Bipolar Cells of a Mouse Model of Retinal Degeneration
Authors: McClements Michelle E. , Staurenghi Federica , Visel Meike , Flannery John G. , MacLaren Robert E. , Cehajic-Kapetanovic Jasmina
Published: February 2021

Vision loss caused by inherited retinal degeneration affects millions of people worldwide, and clinical trials involving gene supplementation strategies are ongoing for select forms of the disease. When early therapeutic intervention is not possible and patients suffer complete loss of their photoreceptor cells, there is an opportunity for vision restoration techniques, including optogenetic therapy. This therapy provides expression of light‐sensitive molecules to surviving cell types of the retina, enabling light perception through residual neuronal pathways. To this end, the bipolar cells make an obvious optogenetic target to enable upstream processing of visual signal in the retina. However, while AAV transduction of the bipolar cells has been described, the expression of human opsins in these cell types within a model of retinal degeneration (rd1) has been less successful. In this study, we have expanded the optogenetic toolkit and shown successful expression of human rhodopsin driven by an ON‐bipolar cell promoter (Grm6) in the rd1 mouse model using modified AAV capsids (AAV2.4YF, AAV8.BP2, and AAV2.7m8) delivered via intraocular injection. We also show the first presentation of ectopic expression of human cone opsin in the bipolar cells of rd1 mice. These data provide evidence of an expansion of the optogenetic toolkit with the potential to restore useful visual function, setting the stage for future trials in human patients.
Correlation Analysis of Sprint Performance and Reaction Time Based on Double Logarithm Model
Authors: Zhang Jing , Lin Xin-Yu , Zhang Su
Published: February 2021

In sprint track events, the starting reaction time is an important professional capacity of the athletes, and it is closely related to their performance. This study examines the reaction time and the results of the male and female sprinters participating in the World Athletics Championships from 2011 to 2019 in the 100 m, 200 m, 100 m, and 110 m hurdles. The researchers used least squares estimation, multivariate analysis of variance, and other methods and theories to construct a double logarithmic model and a multivariate analysis of a variance model. The researchers used Econometrics Views and SPSS software programs to analyze the correlation between the performance and the starting reaction time, as well as the patterns in the changes of the reaction time of athletes of both genders in different types of and rounds in the competitions. Research results show that there is a direct correlation between the reaction time and the performance, and the degrees of correlation vary depending on the gender of the athlete, year of competition, type of competition, and round of competition. There is a correlation between the foul types and the type of competition, but there is no correlation between foul types and the gender of the athlete. The research results are science‐based and are of practical value and thus can be used as a reference by coaches in sprint running to offer more professional guidance to the athletes.
How Has Intervention Fidelity Been Assessed in Smoking Cessation Interventions? A Systematic Review
Authors: Begum Suhana , Yada Ayumi , Lorencatto Fabiana , DiGiacomo Michelle
Published: February 2021

Introduction. Intervention fidelity concerns the degree to which interventions are implemented as intended. Fidelity frameworks propose fidelity is a multidimensional concept relevant at intervention designer, provider, and recipient levels; yet the extent to which it is assessed multidimensionally is unclear. Smoking cessation interventions are complex, including multiple components, often delivered over multiple sessions and/or at scale in clinical practice; this increases susceptibility variation in the fidelity with which they are delivered. This review examined the extent to which five dimensions from the Behaviour Change Consortium fidelity framework (design, training, delivery, receipt, and enactment) were assessed in fidelity assessments of smoking cessation interventions (randomised control trials (RCTs)). Methods. Five electronic databases were searched using terms “smoking cessation,” “interventions,” “fidelity,” and “randomised control trials.” Eligible studies included RCTs of smoking cessation behavioural interventions, published post 2006 after publication of the framework, reporting assessment of fidelity. The data extraction form was structured around the framework, which specifies a number of items regarding assessment and reporting of each dimension. Data extraction included study characteristics, dimensions assessed, data collection, and analysis strategies. A score per dimension was calculated, indicating its presence. Results. 55 studies were reviewed. There was a wide variability in data collection approaches used to assess fidelity. Fidelity of delivery was the most commonly assessed and linked to the intervention outcomes (73% of the studies). Fidelity of enactment scored the highest according to the framework (average of 92.7%), and fidelity of training scored the lowest (average of 37.1%). Only a quarter of studies linked fidelity data to outcomes (27%). Conclusion. There is wide variability in methodological and analytical approaches that precludes comparison and synthesis. In order to realise the potential of fidelity investigations to increase scientific confidence in the interpretation of observed trial outcomes, studies should include analyses of the association between fidelity data and outcomes. Findings have highlighted recommendations for improving fidelity evaluations and reporting practices.
Antidiabetic Activity of Widely Used Medicinal Plants in the Sri Lankan Traditional Healthcare System: New Insight to Medicinal Flora in Sri Lanka
Authors: Wasana Keddagoda Gamage Piyumi , Attanayake Anoja Priyadarshani , Jayatilaka Kamani Ayoma Perera Wijewardana , Weerarathna Thilak Priyantha
Published: February 2021

The use of medicinal plant extracts and their isolated bioactive compounds for the management of diabetes mellitus has been tremendously increased in recent decades. The present study aimed at providing in-depth information on medicinal flora that has been widely used in the Sri Lankan traditional healthcare system for the management of diabetes mellitus. The data of this review article were obtained from published articles from January 2000 to September 2020 in scientific databases of PubMed, Web of Science, and Google Scholar. In this review, a total number of 18 medicinal plants with the antidiabetic activity were expressed, and their isolated antidiabetic active compounds were highlighted as new drug leads. Results of the reported studies revealed that medicinal plants exert a potent antidiabetic activity via both in vitro and in vivo study settings. However, bioactive compounds and antidiabetic mechanism (s) of action of many of the reported medicinal plants have not been isolated/elucidated the structure in detail, to date. Reported antidiabetic medicinal plants with other properties such as antioxidant and antihyperlipidemic activities deliver new entities for the development of antidiabetic agents with multiple therapeutic targets. This is a comprehensive review on potential antidiabetic activities of the Sri Lankan medicinal plants that have been widely used in the traditional healthcare system. The information presented here would fill the gap between the use of them by traditional healers in the traditional medicine healthcare system in Sri Lanka and their potency for development of new drug entities in future.
A Staging Auxiliary Diagnosis Model for Nonsmall Cell Lung Cancer Based on the Intelligent Medical System
Authors: Wu Jia , Gou Fangfang , Tan Yanlin
Published: February 2021

At present, human health is threatened by many diseases, and lung cancer is one of the most dangerous tumors that threaten human life. In most developing countries, due to the large population and lack of medical resources, it is difficult for doctors to meet patients’ needs for medical treatment only by relying on the manual diagnosis. Based on massive medical information, the intelligent decision-making system has played a great role in assisting doctors in analyzing patients’ conditions, improving the accuracy of clinical diagnosis, and reducing the workload of medical staff. This article is based on the data of 8,920 nonsmall cell lung cancer patients collected by different medical systems in three hospitals in China. Based on the intelligent medical system, on the basis of the intelligent medical system, this paper constructs a nonsmall cell lung cancer staging auxiliary diagnosis model based on convolutional neural network (CNNSAD). CNNSAD converts patient medical records into word sequences, uses convolutional neural networks to extract semantic features from patient medical records, and combines dynamic sampling and transfer learning technology to construct a balanced data set. The experimental results show that the model is superior to other methods in terms of accuracy, recall, and precision. When the number of samples reaches 3000, the accuracy of the system will reach over 80%, which can effectively realize the auxiliary diagnosis of nonsmall cell lung cancer and combine dynamic sampling and migration learning techniques to train nonsmall cell lung cancer staging auxiliary diagnosis models, which can effectively achieve the auxiliary diagnosis of nonsmall cell lung cancer. The simulation results show that the model is better than the other methods in the experiment in terms of accuracy, recall, and precision.
Phylogenetic Analysis of ALV-J Associated with Immune Responses in Yellow Chicken Flocks in South China
Authors: Zhang Qihong , Mo Guodong , Xie Tingting , Zhang Zihao , Fu Huali , Wei Ping , Zhang Xiquan
Published: February 2021

The aim of this study was to better understand the sequence characteristics and immune responses in avian leukosis virus subgroup J (ALV-J) infected yellow chicken flocks in South China. We isolated four strains of ALV-J virus from these flocks, which were then identified by several methods, including subtype-specific polymerase chain reaction (PCR), enzyme-linked immunosorbent assay (ELISA), and immunofluorescence assay (IFA). All four viruses were sequenced for their complete genomes and named GD19GZ01, GD19GZ02, GD19GZ03, and GD19GZ04. In comparison with the reference sequence, the homology analysis showed that the gag and pol genes were relatively conserved, whereas env contained much variation. Both GD19GZ01 and GD19GZ02 almost entirely lacked the rTM region and E element, while the latter was retained in GD19GZ03 and GD19GZ04. Moreover, the virus replication levels in GD19GZ03 and GD19GZ04were much higher than those in GD19GZ01 and GD19GZ02. And three virus recombination events in GD19GZ01 and GD19GZ02 were revealed by the results of PDR5 and SimPlot software analysis. Additionally, we found that some interferon-stimulating genes (CH25H, MX, PKR, OAS, and ZAP) and inflammatory mediators (IL-4, IL-6, IL-10, IL-12, 1L-18, and TNF-α) were significantly upregulated in the immune system organs of clinical chickens. Taken together, these findings clarify and reveal the sequence characteristics and trends in the variation of ALV-J infection in yellow chicken flocks of South China.
Numerical Simulation Study on the Distribution Law of Deviatoric Stress of Floor under the Influence of Mining
Authors: Liu Hongtao , Huo Tianhong , Li Yongen , Luo Ming , Zhou Guangdong , He Zengji
Published: February 2021

The Zhaogu No. 2 coal mine is a single thick coal seam mining mine with high gas content. Due to the lack of protective layer mining conditions, we can only arrange the floor gas extraction roadway (FGER) to extract the gas from the overlying coal seam of the FGER to ensure safe production. However, improper placement of FGER will cause water inrush from the floor of FGER. Given above contradictions, this paper analyzes the stress-strain relationship of the fractured rock mass in the caving zone and the stress-recovery characteristics of the goaf from the perspective of the structural characteristics of the overlying strata above goaf. Based on this, a FLAC3D numerical model of equivalent delayed filling of caving rock mass was established by using the double-yield model filling method. The distribution of floor stress under the influence of mining is obtained after the model calculation, i.e., with the increase of the distance from the floor, the ratio of bidirectional stress to the peak value, and the stability value decrease, but the decrease amplitude becomes smaller and smaller. Therefore, floor roadway used for gas extraction should be located 10-15 m below the floor. Combined with the distribution of floor strata in 11060 working face, it is finally determined that FGER should be located 13 m below the floor. Such arrangement of FGER can not only ensure the effect of gas drainage but also prevent the occurrence of water inrush from floor.
Fine Characterization of Sand Body in the Front of the Fluvial Delta: Taking the VII Oil Group of N21 Reservoir in Gasikule Oilfield as an Example
Authors: Sheng Jun , Liu Jincheng , Qi Qingshan , Li Xin , Tan Wulin , Chai Xin , Guo Bin , Yang Xiaojing , Yi Debin , Lu Shanshan , Li Yanan , Zhang Caiyan
Published: February 2021

Taking the VII oil group of N21 reservoir in Gasikule Oilfield as an example, the sedimentary time unit was divided into the barrier layer, interbed, and sand bed by analyzing the sedimentary system and sand body development model in this paper. The single sand body was analyzed for the sand bed time unit. The residual muddy intercalation period division theory was proposed for the first time to divide the sedimentary periods of the sedimentary time unit of the sand bed. Finally, a new “sandwich” layer point coincidence modeling technology was proposed to characterize the sedimentary time units of a barrier layer accurately and interbed and finely describe the sedimentary time unit of the multiperiod sand bed.
Predicting Molecular Subtypes of Breast Cancer with Mammography and Ultrasound Findings: Introduction of Sono-Mammometry Score
Authors: Shaikh Sana , Rasheed Afshan
Published: February 2021

We studied the correlation of sonographic and digital mammographic features with molecular classification of breast cancer. Imaging features from 313 patients with preliminary ultrasound and digital mammogram between November 2017 and May 2020 were compared with histopathology and immunohistochemical analysis for the prediction of molecular classification of breast cancer. We also devised a score called “sono-mammometry” score consisting of few simple imaging features which can easily be performed in outpatient settings. We studied that non-triple-negative breast cancers are predominantly hypoechoic and strongly correlate with the presence of irregular spiculated margins along with peripheral echogenic halo, posterior shadowing, and microcalcifications, while there is considerable variation in imaging features of TNBC as some of its imaging features overlap with those of typical benign tumors. Although imaging characteristics are helpful in the prediction of molecular classification, the prognostication value of these imaging features is still weak. There is considerable variation in imaging features which warrants vigilance towards improved diagnostic performance. To help better understand these features, our sono-mammometry score can serve as straightforward test which is assumed to be functional and productive in resource-limited settings.
Logarithmic Generalization of the Lambert
W
Function and Its Applications to Adiabatic Thermostatistics of the Three-Parameter Entropy
Authors: Corcino Cristina B. , Corcino Roberto B.
Published: February 2021

A generalization of the Lambert

W

function called the logarithmic Lambert function is introduced and is found to be a solution to the thermostatistics of the three-parameter entropy of classical ideal gas in adiabatic ensembles. The derivative, integral, Taylor series, approximation formula, and branches of the function are obtained. The heat functions and specific heats are computed using the “unphysical” temperature and expressed in terms of the logarithmic Lambert function.
Clinically Available Optical Imaging Technologies in Endoscopic Lesion Detection: Current Status and Future Perspective
Authors: He Zhongyu , Wang Peng , Liang Yuelong , Fu Zuoming , Ye Xuesong
Published: February 2021

Endoscopic optical imaging technologies for the detection and evaluation of dysplasia and early cancer have made great strides in recent decades. With the capacity of in vivo early detection of subtle lesions, they allow modern endoscopists to provide accurate and effective optical diagnosis in real time. This review mainly analyzes the current status of clinically available endoscopic optical imaging techniques, with emphasis on the latest updates of existing techniques. We summarize current coverage of these technologies in major hospital departments such as gastroenterology, urology, gynecology, otolaryngology, pneumology, and laparoscopic surgery. In order to promote a broader understanding, we further cover the underlying principles of these technologies and analyze their performance. Moreover, we provide a brief overview of future perspectives in related technologies, such as computer-assisted diagnosis (CAD) algorithms dealing with exploring endoscopic video data. We believe all these efforts will benefit the healthcare of the community, help endoscopists improve the accuracy of diagnosis, and relieve patients’ suffering.
Identification of Influential Nodes via Effective Distance‐based Centrality Mechanism in Complex Networks
Authors: Ullah Aman , wang Bin , Sheng Jinfang , Long Jun , Khan Nasrullah
Published: February 2021

Efficient identification of influential nodes is one of the essential aspects in the field of complex networks, which has excellent theoretical and practical significance in the real world. A valuable number of approaches have been developed and deployed in these areas where just a few have used centrality measures along with their concerning deficiencies and limitations in their studies. Therefore, to resolve these challenging issues, we propose a novel effective distance‐based centrality (EDBC) algorithm for the identification of influential nodes in concerning networks. EDBC algorithm comprises factors such as the power of K‐shell, degree nodes, effective distance, and numerous levels of neighbor’s influence or neighborhood potential. The performance of the proposed algorithm is evaluated on nine real‐world networks, where a susceptible infected recovered (SIR) epidemic model is employed to examine the spreading dynamics of each node. Simulation results demonstrate that the proposed algorithm outperforms the existing techniques such as eigenvector, betweenness, closeness centralities, hyperlink‐induced topic search, H‐index, K‐shell, page rank, profit leader, and gravity over a valuable margin.
Arch Antislide Pile-Wall Structure System: Model and Optimization
Authors: Li Heng , Wang Hui , Yue Gaowei , Zhao Fasuo , Li Wenzhe
Published: February 2021

For the problems of unreasonable force and large deformation of traditional antislide structure system, three new arch antislide pile-wall structure systems are designed for a loess landslide treatment project in Northern Shanxi province. The working performances of four kinds of antislide structures are numerically simulated and analyzed to realize the optimization of the antislide structure system. The results show that the arch antislide pile-wall structure system is a rigid connection between the piles and cap beam, and the antislide pile, cap beam, and sliding bed soil form a spatial nearly rigid structure. Cap beam can better transfer the bending moment generated by the larger thrust in the landslide middle to the piles with less force on both sides of the landslide, so that the stress and deformation of the whole antislide system tend to be uniform, which makes the antislide system “joint operation.” And this structural form increases the overall stiffness and bending capacity and reduces the possibility that the middle pile is destroyed first and loses its working capacity due to large thrust. Compared with the traditional antislide structure system (Model-1), the average displacement of the pile head is reduced by about 60%, and the total control bending moment of the system is reduced by about 6%. The purpose of Model-3 and Model-4 (anchorage arch antislide pile-wall structure system and pull-rod arch antislide pile-wall structure system) is to restrict the deformation of cap beam in both positive and negative directions of x-axis in arch antislide pile-wall structure system, which plays a certain role in coordinating the deformation of antislide structure and better coordinating the stress of each pile. The arch antislide pile-wall structure system (Model-2), anchorage arch antislide pile-wall structure system (Model-3), and pull-rod arch antislide pile-wall structure system (Model-4) can better adapt and adjust the unbalanced thrust between the landslide piles; therefore, they have higher structural robustness than that of traditional antislide structure system. When achieving the management target with a 95% structural reliability probability of the same landslide, the structural robust degrees of Model-1, Model-2, and Model-4 are 0.58, 0.76, and 0.81, respectively. Therefore, the pull-rod arch antislide pile-wall structure system (Model-4) has the best performance among the other antislide structures. These studies lay a foundation for the engineering structural optimization of arch antislide pile-wall structure system.
Behavioral Assessment of Unilateral Spatial Neglect with the Catherine Bergego Scale (CBS) Using the Kessler Foundation Neglect Assessment Process (KF-NAP) in Patients with Subacute Stroke during Rehabilitation in Japan
Authors: Nishida Daisuke , Mizuno Katsuhiro , Tahara Masatoshi , Shindo Shiori , Watanabe Yuki , Ebata Hiroki , Tsuji Tetsuya
Published: February 2021

The Kessler Foundation Neglect Assessment Process (KF-NAP) is an assessment tool for unilateral spatial neglect (USN), which is the scoring method for the Catherine Bergego Scale (CBS) based on detailed instructions. This study is aimed at determining the reliability and validity of the Japanese version of the KF-NAP (KF-NAP-J), evaluating the improvement of neglect assessment with KF-NAP-J, and comparing it with the original CBS for subacute stroke patients. We assessed subacute stroke patients admitted to our intensive rehabilitation hospital. Two KF-NAP-trained occupational therapists (OTs) assessed 22 patients. Before implementing the KF-NAP at the hospital, two other OTs assessed the other 23 patients using the CBS. We evaluated the interrater reliability of the KF-NAP and CBS using intraclass correlation coefficients (ICC) for the total scores, weighted kappa statistics for each subscale, and internal consistency using Cronbach’s alpha. We assessed the validity of the KF-NAP against the Behavioral Inattention Test (BIT) and Functional Independence Measure (FIM) using Spearman’s correlation coefficient. The reliability of both the KF-NAP and CBS was excellent. The weighted kappa results demonstrated that each subscale was in better agreement with the KF-NAP than with the CBS. In the KF-NAP, all eight subscales in which weighted kappa could be calculated were in significant agreement, and two were almost in perfect agreement. The KF-NAP moderately correlated with the subscales of BIT and FIM representing USN and activities of daily living. The USN detection rates of KF-NAP and BIT in the KF-NAP group were 63.6% and 22.7%, respectively. These results suggest that the KF-NAP, as well as the CBS, is useful to assess USN, which strongly impacts the rehabilitation outcomes in subacute stroke patients.
Effect of Duyun Compound Green Tea on Gut Microbiota Diversity in High-Fat-Diet-Induced Mice Revealed by Illumina High-Throughput Sequencing
Authors: Zhou Caibi , Zhou Xiaolu , Wen Zhirui , Yang Zaibo , Mu Ren , Song Yuyan , Mei Xin , Rothenberg Dylan O’Neill
Published: February 2021

Intake of a high-fat diet (HFD) is closely related to disorders of the intestinal microbiota, which plays a key role in the pathogenesis of obesity. Duyun compound green tea, an ancient Chinese drink, is widely consumed to reduce weight, although the mechanism is not clear. In this study, 50 mice were randomly divided into 5 groups: normal control group (CK), HFD model control group (NK), positive control group with medicine (YK), low-dose compound tea group (DL), and high-dose compound tea group (DH). After 4 weeks of intervention, the feces of mice were taken under sterile conditions and evaluated using Illumina high-throughput sequencing technology. The results showed that the diversity of intestinal microbiota was the highest in the CK group, the lowest in the NK group, and relatively increased in the compound tea treatment group. Second, there were differences in intestinal microbiota in each group, among which the beneficial bacteria in the intestinal tract of the CK group were higher than those in the other groups, while the beneficial bacteria in each compound tea treatment group were more abundant than those in the NK group, in which harmful bacteria in the intestinal tract were found to be the highest. These results suggest that compounds in tea may be able to attenuate imbalances of intestinal microbiota induced by poor diet, acting as a therapeutic agent in obesity or other diseases associated with gut dysbiosis.
Passive Mechanical Properties of Human Medial Gastrocnemius and Soleus Musculotendinous Unit
Authors: Wang Ruoli , Yan Shiyang , Schlippe Marius , Tarassova Olga , Pennati Gaia Valentina , Lindberg Frida , Körting Clara , Destro Antea , Yang Luming , Shi Bin , Arndt Anton
Published: February 2021

The in vivo characterization of the passive mechanical properties of the human triceps surae musculotendinous unit is important for gaining a deeper understanding of the interactive responses of the tendon and muscle tissues to loading during passive stretching. This study sought to quantify a comprehensive set of passive muscle‐tendon properties such as slack length, stiffness, and the stress‐strain relationship using a combination of ultrasound imaging and a three‐dimensional motion capture system in healthy adults. By measuring tendon length, the cross‐section areas of the Achilles tendon subcompartments (i.e., medial gastrocnemius and soleus aspects), and the ankle torque simultaneously, the mechanical properties of each individual compartment can be specifically identified. We found that the medial gastrocnemius (GM) and soleus (SOL) aspects of the Achilles tendon have similar mechanical properties in terms of slack angle (GM: −10.96° ± 3.48°; SOL: −8.50° ± 4.03°), moment arm at 0° of ankle angle (GM: 30.35 ± 6.42 mm; SOL: 31.39 ± 6.42 mm), and stiffness (GM: 23.18 ± 13.46 Nmm-1; SOL: 31.57 ± 13.26 Nmm-1). However, maximal tendon stress in the GM was significantly less than that in SOL (GM: 2.96 ± 1.50 MPa; SOL: 4.90 ± 1.88 MPa, p = 0.024), largely due to the higher passive force observed in the soleus compartment (GM: 99.89 ± 39.50 N; SOL: 174.59 ± 79.54 N, p = 0.020). Moreover, the tendon contributed to more than half of the total muscle‐tendon unit lengthening during the passive stretch. This unequal passive stress between the medial gastrocnemius and the soleus tendon might contribute to the asymmetrical loading and deformation of the Achilles tendon during motion reported in the literature. Such information is relevant to understanding the Achilles tendon function and loading profile in pathological populations in the future.
miR‐193a‐3p Promotes the Invasion, Migration, and Mesenchymal Transition in Glioma through Regulating BTRC
Authors: Zhou Dan-Dan , Li Hong-Li , Liu Wei , Zhang Li-Ping , Zheng Quan , Bai Jun , Hu Ya-Qiong , Yin Chong-Gao , Lv Shi-Jun , Zhang Bao-Gang
Published: February 2021

Background. The present study is aimed at exploring the specific expression of miR‐193a‐3p and the mechanism underlying miR‐193a‐3p‐mediated mesenchymal transition (MT), invasion, and migration in glioma. Methods. The gene expression profile datasets of GSE39486 and GSE25676 were downloaded from the National Center for Biotechnology (NCBI). Data regarding the expression of miR‐193a‐3p and survival curves were derived from Chinese Glioma Genome Atlas (CGGA). Online websites including miRWalk, DIANA, and starbase were employed to predict the target genes for miR‐193a‐3p. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by the Omicsbean online software. Module analysis of the protein‐protein interaction (PPI) networks was performed by the plug‐in Molecular Complex Detection (MCODE), and the degrees of genes were calculated by CytoHubba plug‐in of Cytoscape. Survival curves were based on the Gene Expression Profile Interaction Analysis (GEPIA). Transwell, wound healing, and Western blot experiments were performed to investigate the effects of miR‐193a‐3p and beta‐transducin repeat containing E3 ubiquitin protein ligase (BTRC) on the invasion, migration, and MT of glioma. Results. miR‐193a‐3p was highly expressed in glioma tissues and significantly correlated with poor survival in patients with glioma. The target genes for miR‐193a‐3p were involved in many cancer‐related signaling pathways. The PPI showed 11 genes with both high degrees and MCODE scores in the network. Survival analysis demonstrated that the expression of BTRC was significantly correlated with the prognosis of patients with glioma. The results from the transwell, wound healing, and Western blot analyses suggested that miR‐193a‐3p promoted the invasion, migration, and MT of glioma cells, which could be reversed by BTRC. Conclusions. miR‐193a‐3p was upregulated in patients with glioma and could affect the invasion, migration, and MT of glioma by regulating BTRC.
Pleuropulmonary Blastoma with Hotspot Mutations in RNase IIIb Domain of DICER 1: Clinicopathologic Study of 10 Cases in a Single-Institute Experience
Authors: Lee Miseon , Kim Tae-im , Jang Se Jin , Cho Kyung-Ja , Lee Sang Min , Kim Hyeong Ryul , Song Joon Seon
Published: February 2021

Introduction: Pleuropulmonary blastoma (PPB) is a rare sarcomatous malignancy involving the lung and pleura which occurs in early childhood. Cystic PPB in the early stage can be misdiagnosed as other cystic diseases. Early detection of this entity is important for appropriate treatment and prevention of disease progression. Hotspot mutations in the ribonuclease IIIb (RNase IIIb) domain of DICER1 have been reported to have a crucial role as genetic factors of PPB and DICER1 familial syndrome. We reviewed the clinicopathologic findings of PPB and the status of DICER1 hotspot mutation and patients’ clinical course. Methods: We retrospectively reviewed all patients with histologically confirmed PPB at Asan Medical Center between 2000 and 2017. Ten cases were identified in the database, and their clinicopathologic parameters were evaluated. PPB was classified into the following 3 pathologic subtypes: type I (purely cystic), type II (mixed cystic and solid), and type III (entirely solid). The status of DICER1 mutation in 2 hotspot regions of the RNase IIIb domain was evaluated by Sanger sequencing. Results: The most frequent PPB type was II (6 cases), followed by I and III (2 cases each). The age at diagnosis ranged from 16 months to 15 years. All patients underwent surgery, and all patients received adjuvant or neoadjuvant chemotherapy. Four of 7 patients had missense mutations in the RNase IIIb hotspot; the base and predicted corresponding amino acid changes were c.5113 G>A (p.E1705K), c.5407 G>A (p.E1803K), c.5425 G>A (p.G1809R), and c.5428 G>T (p.D1810Y). There was no particular association between the presence of the hotspot mutation and histologic type. Nine patients survived with no evidence of disease for a median interval of 93 (range, 13–199) months. Only 1 patient diagnosed with type III PPB at the age of 18 years had recurrence after 20.8 months and eventually died 66 months after the initial diagnosis. Conclusions: Late detection of solid PPB is associated with poor prognosis. Considering the rarity of PPB disease and the importance of DICER1 hotspot mutation in pathogenesis, DICER1 hotspot mutation testing and identification in the early cystic stage can improve patient outcomes.
Identification of Influential Variants in Significant Aggregate Rare Variant Tests
Authors: Blumhagen Rachel Z. , Schwartz David A. , Langefeld Carl D. , Fingerlin Tasha E.
Published: February 2021

Introduction: Studies that examine the role of rare variants in both simple and complex disease are increasingly common. Though the usual approach of testing rare variants in aggregate sets is more powerful than testing individual variants, it is of interest to identify the variants that are plausible drivers of the association. We present a novel method for prioritization of rare variants after a significant aggregate test by quantifying the influence of the variant on the aggregate test of association. Methods: In addition to providing a measure used to rank variants, we use outlier detection methods to present the computationally efficient Rare Variant Influential Filtering Tool (RIFT) to identify a subset of variants that influence the disease association. We evaluated several outlier detection methods that vary based on the underlying variance measure: interquartile range (Tukey fences), median absolute deviation, and SD. We performed 1,000 simulations for 50 regions of size 3 kb and compared the true and false positive rates. We compared RIFT using the Inner Tukey to 2 existing methods: adaptive combination of p values (ADA) and a Bayesian hierarchical model (BeviMed). Finally, we applied this method to data from our targeted resequencing study in idiopathic pulmonary fibrosis (IPF). Results: All outlier detection methods observed higher sensitivity to detect uncommon variants (0.001 < minor allele frequency, MAF > 0.03) compared to very rare variants (MAF <0.001). For uncommon variants, RIFT had a lower median false positive rate compared to the ADA. ADA and RIFT had significantly higher true positive rates than that observed for BeviMed. When applied to 2 regions found previously associated with IPF including 100 rare variants, we identified 6 polymorphisms with the greatest evidence for influencing the association with IPF. Discussion: In summary, RIFT has a high true positive rate while maintaining a low false positive rate for identifying polymorphisms influencing rare variant association tests. This work provides an approach to obtain greater resolution of the rare variant signals within significant aggregate sets; this information can provide an objective measure to prioritize variants for follow-up experimental studies and insight into the biological pathways involved.