bluuebunny/crossref_metadata_2025 huggingface dataset:
First-principles study on the effects of V, Nb, Cd, Ag, Ge and Sb doped in Al2CuMg phase of Al–Zn–Mg–Cu alloy
Authors: Li Bingkang , Wang Junkai , Zhang Chuan-Hui
Published: September 2021

The [Formula: see text] phase (Al2CuMg) is an important strengthening phase for the Al–Zn–Cu–Mg alloys, which are widely used in the aerospace and transportation industries. First-principles calculations based on the density functional theory were used to investigate the effects of doping V, Nb, Cd, Ag, Ge and Sb elements on the [Formula: see text] phase. The results demonstrate that Ag atom can spontaneously dope into the [Formula: see text] phase. Ge and Sb doping can improve the toughness and plasticity of the [Formula: see text] phase. And doping Ge, V or Nb can reduce the anisotropy of the Al2CuMg phase. The hardness of the Nb, V, Cd and Ag doped structures become larger than that of the pristine structure. The results of orbital hybridization in the partial density of states (PDOS) and the distribution in electron density difference (EDD) confirmed that the effect of doping elements and Al atoms has the greatest impact on the performance of the system, and the strength of the covalent bond of the system affects the main aspects of brittleness. This study provides a better theoretical understanding of the doped [Formula: see text] phase, providing guidance for improved composition design and performance optimization of Al–Zn–Cu–Mg alloys.
Rational solutions of the (2+1)-dimensional cmKdV equations
Authors: Yuan Feng
Published: September 2021

The order-[Formula: see text] periodic solutions for the (2+1)-D complex modified Korteweg–de Vries (cmKdV) equations are investigated with the aid of Darboux transformation (DT) method. By using Taylor expansion considering the limits [Formula: see text], order-n rational solutions are obtained, among which the order-1 and order-2 solutions are analyzed in detail. By varying different parameter [Formula: see text], two kinds of rational solutions are deduced, namely, the line rogue wave solutions and the lump solutions. Dynamical properties of these solitons, including speed, amplitude, and extreme values, are investigated. It is shown that the line rogue wave solutions appear and disappear, while the lump solutions are localized traveling wave solutions.
SOME FURTHER EXTENSIONS CONSIDERING DISCRETE PROPORTIONAL FRACTIONAL OPERATORS
Authors: RASHID SAIMA , SULTANA SOBIA , KARACA YELIZ , KHALID AASMA , CHU YU-MING
Published: September 2021

In this paper, some attempts have been devoted to investigating the dynamic features of discrete fractional calculus (DFC). To date, discrete fractional systems with complex dynamics have attracted the most consideration. By considering discrete [Formula: see text]-proportional fractional operator with nonlocal kernel, this study contributes to the major consequences of the certain novel versions of reverse Minkowski and related Hölder-type inequalities via discrete [Formula: see text]-proportional fractional sums, as presented. The proposed system has an intriguing feature not investigated in the literature so far, it is characterized by the nabla [Formula: see text] fractional sums. Novel special cases are reported with the intention of assessing the dynamics of the system, as well as to highlighting the several existing outcomes. In terms of applications, we can employ the derived consequences to investigate the existence and uniqueness of fractional difference equations underlying worth problems. Finally, the projected method is efficient in analyzing the complexity of the system.
Multifractal Fluctuation Analysis of Correlations between Agricultural Futures Markets in China and the US Based on MF-X-DFA and MF-DPXA Methods
Authors: Feng You-Shuai , Cao Bao-Ming
Published: September 2021

The fluctuation characteristics of the correlations between China and the US agricultural futures markets have attracted extensive attention from academic circles and government departments. As the main factor that affects the agricultural futures price, the impact of international crude oil futures price on the correlations of the Sino-US agricultural futures markets is also worth discussing. Therefore, this paper adopts the multifractal detrended cross-correlation analysis (MF-X-DFA) and multifractal detrended partial cross-correlation analysis (MF-DPXA) to explore the fluctuation characteristics of cross-correlations for China and the US agricultural futures markets before and after removing the West Texas Intermediate (WTI) crude oil futures price as well as the impact on the cross-correlations. The results show that the fluctuation characteristics of the cross-correlations and partial cross-correlations between the corresponding varieties of China and the US agricultural futures markets as well as among the varieties within the markets are multifractal. The cross-correlation behaviors and the cross-market risks are all affected to varying degrees by the West Texas Intermediate (WTI) crude oil futures. The West Texas Intermediate (WTI) crude oil futures weaken the cross-market risk of the Sino-US soybean futures, while strengthening the cross-market risk of the Sino-US corn and wheat futures. In addition, the impact of the West Texas Intermediate (WTI) crude oil futures on the cross-market risks among China agricultural futures is greater than those among the US corresponding agricultural futures.
Decoupled Iterative Deep Sensor Fusion for 3D Semantic Segmentation
Authors: Duerr Fabian , Weigel Hendrik , Beyerer Jürgen
Published: September 2021

One of the key tasks for autonomous vehicles or robots is a robust perception of their 3D environment, which is why autonomous vehicles or robots are equipped with a wide range of different sensors. Building upon a robust sensor setup, understanding and interpreting their 3D environment is the next important step. Semantic segmentation of 3D sensor data, e.g. point clouds, provides valuable information for this task and is often seen as key enabler for 3D scene understanding. This work presents an iterative deep fusion architecture for semantic segmentation of 3D point clouds, which builds upon a range image representation of the point clouds and additionally exploits camera features to increase accuracy and robustness. In contrast to other approaches, which fuse lidar and camera features once, the proposed fusion strategy iteratively combines and refines lidar and camera features at different scales inside the network architecture. Additionally, the proposed approach can deal with camera failure as well as jointly predict lidar and camera segmentation. We demonstrate the benefits of the presented iterative deep fusion approach on two challenging datasets, outperforming all range image-based lidar and fusion approaches. An in-depth evaluation underlines the effectiveness of the proposed fusion strategy and the potential of camera features for 3D semantic segmentation.
Co-adaptive Human–Robot Cooperation: Summary and Challenges
Authors: Ahlberg Sofie , Axelsson Agnes , Yu Pian , Cortez Wenceslao Shaw , Gao Yuan , Ghadirzadeh Ali , Castellano Ginevra , Kragic Danica , Skantze Gabriel , Dimarogonas Dimos V.
Published: September 2021

The work presented here is a culmination of developments within the Swedish project COIN: Co-adaptive human-robot interactive systems, funded by the Swedish Foundation for Strategic Research (SSF), which addresses a unified framework for co-adaptive methodologies in human–robot co-existence. We investigate co-adaptation in the context of safe planning/control, trust, and multi-modal human–robot interactions, and present novel methods that allow humans and robots to adapt to one another and discuss directions for future work.
Mathematical Modeling and Designing a Heavy Hybrid-Electric Quadcopter, Controlled by Flaps
Authors: Isaac Mohammad Sadeq Ale , Ragab Ahmed Refaat , Garcés Enrique Caballero , Luna Marco Andres , Peña Pablo Flores , Cervera Pascual Campoy
Published: September 2021

Systematic hybrid-electric unmanned aerial vehicles (UAVs) and, especially, quadcopters are so promising due to their long flight endurance and their usage in patrol and rescue missions which gain a high interest to be under examination and test scope by researchers; however, a complete mathematical design is required to fulfill theoretical complexities such as aerodynamic analysis and flight dynamics models related. This paper investigates salient sections from hypothesis to implementation. Researchers at Drone Hopper company have conducted various calculations to perform a precise novel platform called Duty-Hopper (DH). The benefit of this design is to control the attitude by flap vanes and electrical ducted fans (EDFs) when using gasoline engines; while, the principle propellers only lift the drone. This paper examines the attitude control system of DH, once using only flaps, then by only EDFs, and eventually, by compounding both. During this research, the scientific software used is ANSYS-Fluent and MATLAB-SimScape to analyze the entire body of the DH. Furthermore, a robust fault-tolerant controller is designed to immune the DH against internal and external errors. Our research reveals that using flaps is a feasible way to control attitude when it is augmented by EDFs.
Automated Playbook for UAV Traffic Management Based on Spatiotemporal Scenario Data
Authors: He Chenyuan , Wan Yan , Xie Junfei
Published: September 2021

This paper develops a decision framework to automate the playbook for UAS traffic management (UTM) under uncertain environmental conditions based on spatiotemporal scenario data. Motivated by the traditional air traffic management (ATM) which uses the playbook to guide traffic using pre-validated routes under convective weather, the proposed UTM playbook leverages a database to store optimal UAS routes tagged with spatiotemporal wind scenarios to automate the UAS trajectory management. Our perspective is that the UASs, and many other modern systems, operate in spatiotemporally evolving environments, and similar spatiotemporal scenarios are tied with similar management decisions. Motivated by this feature, our automated playbook solution integrates the offline operations, online operations and a database to enable real-time UAS trajectory management decisions. The solution features the use of similarity between spatiotemporal scenarios to retrieve offline decisions as the initial solution for online fine tuning, which significantly shortens the online decision time. A fast query algorithm that exploits the correlation of spatiotemporal scenarios is utilized in the decision framework to quickly retrieve the best offline decisions. The online fine tuning adapts to trajectory deviations and subject to collision avoidance among UASs. The solution is demonstrated using simulation studies, and can be utilized in other applications, where quick decisions are desired and spatiotemporal environments play a crucial role in the decision process.
The importance of early data collection in quarry development consent applications; linking hydrogeological assessment to the decision makers’ legal framework, a case study
Authors: Butler Anna K. , Lloyd Adam , Jefferies Daniel , Mitchener Richard G. R. , Thorn Peter
Published: September 2021

The working of superficial deposits frequently interacts with the groundwater table and thus may affect surface water and groundwater dependent terrestrial ecosystems. The Habitats Directive and the Water Framework Directive require detailed consideration of these potential effects during any application for planning consent or other authorizations and during periodic reviews. These assessments need to consider water resources impacts, the potential for pollution and whether the natural water chemistry may be changed in a way that could change ecological conditions. Early recognition of these challenges, and a well-structured hydrogeological investigation programme to properly characterize the site, is essential to facilitate timely progress through the planning process. This case study presents the approach to hydrogeological characterization and assessment used at the proposed Upwood Quarry, Oxfordshire, which is adjacent to a calcareous wetland protected at European level. Through careful characterization and stakeholder engagement, planning consent was obtained. We consider lessons that may be applied to other sites especially with increased regulation of dewatering abstractions and consider the potential impacts of recent court decisions.
Static Analysis: An Introduction
Authors: Thomson Patrick
Published: September 2021

Modern static-analysis tools provide powerful and specific insights into codebases. The Linux kernel team, for example, developed Coccinelle, a powerful tool for searching, analyzing, and rewriting C source code; because the Linux kernel contains more than 27 million lines of code, a static-analysis tool is essential both for finding bugs and for making automated changes across its many libraries and modules. Another tool targeted at the C family of languages is Clang scan-build, which comes with many useful analyses and provides an API for programmers to write their own analyses. Like so many things in computer science, the utility of static analysis is self-referential: To write reliable programs, we must also write programs for our programs. But this is no paradox. Static-analysis tools, complex though their theory and practice may be, are what will enable us, and engineers of the future, to overcome this challenge and yield the knowledge and insights that we practitioners deserve.
Designing UIs for Static Analysis Tools
Authors: Tiganov Daniil , Nguyen Quang Do Lisa , Ali Karim
Published: September 2021

Static-analysis tools suffer from usability issues such as a high rate of false positives, lack of responsiveness, and unclear warning descriptions and classifications. Here, we explore the effect of applying user-centered approach and design guidelines to SWAN, a security-focused static-analysis tool for the Swift programming language. SWAN is an interesting case study for exploring static-analysis tool usability because of its large target audience, its potential to integrate easily into developers' workflows, and its independence from existing analysis platforms.
Communication—Proving the Importance of Pt-Interlayer Position in PEMWE Membranes for the Effective Reduction of the Anodic Hydrogen Content
Authors: Martin Agate , Abbas Dunia , Trinke Patrick , Böhm Thomas , Bierling Markus , Bensmann Boris , Thiele Simon , Hanke-Rauschenbach Richard
Published: September 2021

Gas crossover through the membrane poses a significant challenge to proton exchange membrane water electrolysers. This work investigates the influence of the position of platinum-based recombination interlayers integrated in the membrane on the anodic hydrogen in oxygen content. The results show that all interlayer positions reduce the anodic hydrogen content without performance losses compared to the reference without interlayer. However, an interlayer positioned closer to the anode is more effective than closer to the cathode. Further, the effect of the interlayer is more pronounced with increasing anode pressure.
Impact of successive exertional heat injuries on thermoregulatory and systemic inflammatory responses in mice
Authors: Caldwell Aaron R. , Oki Kentaro , Ward Shauna M. , Ward Jermaine A. , Mayer Thomas A. , Plamper Mark L. , King Michelle A. , Leon Lisa R.
Published: September 2021

Mice undergoing repeated exertional heat injuries, within 1 wk of an initial heat injury, appear to have some protective adaptations. During the second exertional heat injury, mice were able to run longer and sustain higher body temperatures before collapse. Despite this, the mice undergoing a second exertional heat injury were more resilient to the heat as evidenced by attenuated minimum body temperature, higher HPS70 (serum and liver), lower corticosterone, and lower FABP2.
Predicting critical closing pressure in children with obstructive sleep apnea using fluid-structure interaction
Authors: Mylavarapu Goutham , Gutmark Ephraim , Shott Sally , Fleck Robert , Mahmoud Mohamed , McConnell Keith , Szczesniak Rhonda , Hossain Md Monir , Huang Guixia , Tadesse Dawit G. , Schuler Christine L. , Khosla Sid , Amin Raouf
Published: September 2021

We present a noninvasive method for estimating critical closing pressure (Pcrit) using fluid-structure interaction (FSI) simulations and magnetic resonance imaging (MRI) scans in patients with obstructive sleep apnea (OSA). We used patient-specific stiffness measures in our FSI model to account for any individual variability in the elasticity of soft tissues surrounding the upper airway. We validated this model by measuring the degree of agreement between measured and estimated Pcrit.
Fungal Infections among Psoriatic Patients: Etiologic Agents, Comorbidities, and Vulnerable Population
Authors: Chadeganipour Mostafa , Shadzi Shahla , Mohammadi Rasoul
Published: September 2021

Background. Psoriasis is a chronic inflammatory disorder of the skin and joint, affecting nearly 2-3% of the general population. It is assumed that imbalance between the types of natural microflora can accelerate the onset of the disease. Some fungi can play the role of superantigens and prolong chronic inflammation in the skin of psoriatic patients. The aim of the present investigation was to identify fungal species isolated from patients with psoriasis. Methods. From March 2016 to May 2019, 289 patients with prior diagnosis of psoriasis were included in this survey. Direct microscopy with potassium hydroxide (KOH 10%), culture, urea hydrolysis, hair perforation test, and growth on rice grains were used to identify clinical isolates, phenotypically. For molecular identification of Candida species and Malassezia species, PCR-RFLP and PCR-sequencing were used, respectively. Results. Forty-six out of 289 psoriatic patients had fungal infections (15.9%). Dermatophytes (54.3%), Candida spp. (19.5%), Malassezia spp. (15.2%), Aspergillus spp. (6.5%), and Fusarium spp. (4.3%) were the causative agents of fungal infections. Among Malassezia and Candida species, M. restricta (10.8%) and C. glabrata (8.7%) were the most prevalent species, respectively. Conclusion. Our findings suggested that fungal pathogens, particularly dermatophytes, may play an important role in the pathogenicity of psoriasis. Also, due to the high rate of yeast colonization in the clinical samples of psoriatic patients, concomitant use of anti-inflammatory drugs and antifungals may represent an effective therapeutic approach for better management of chronic lesions among these patients. Mycological tests should be applied to indicate the incidence of fungal diseases in psoriatic patients.
[Retracted] Research on Webcast Supervision Based on Convolutional Neural Network and Wireless Communication
Authors: Sun Zhidong , Sun Jie , Li Xueqing
Published: September 2021

Action recognition is the technology of understanding people’s behavior and classification from video or image sequences. This thesis uses the deep learning approach for action recognition to realize webcast supervision. This paper uses the convolutional neural network (CNN) and the Gaussian Mixture Model (GMM) to establish the webcast supervision system. At the same time, streaming‐based wireless communication network technology is adopted to ensure video transmission speed and quality. Results show that the average detection speed of the system can reach 11.86 frame/s, and the average recognition accuracy is 92.16%, and the missed detection rate is lower than 5%. The design of this system can fully meet the requirements of webcast supervision.
Visual Fatigue Alleviating in Stereo Imaging of Anaglyphs by Reducing Retinal Rivalry and Color Distortion Based on Mobile Virtual Reality Technology
Authors: Qi Min , Cui Shanshan , Du Qianmin , Xu Yuelei , McAllister David F.
Published: September 2021

Stereoscopic display is the means of showing scenes in Virtual Reality (VR). As a type of stereo images, anaglyphs can be displayed not only on the screen, but are currently the only solution of stereo images that can be displayed on paper. However, its deficiencies, like retinal rivalry and color distortion, could cause visual fatigue. To address this issue, an algorithm is proposed for anaglyph generation. Unlike previous studies only considering one aspect, it considers both retinal rivalry and color distortion at the same time. The algorithm works in the CIE L∗a∗b∗ color space and focuses on matching the perceptual color attributes especially the hue, rather than directly minimizes the sum of the distances between the perceived anaglyph color and the stereo image pair. In addition, the paper builds a relatively complete framework to generate anaglyphs so that it is more controllable to adjust the parameters and choose the appropriate process. The subjective tests are conducted to compare the results with several techniques which generate anaglyphs including empirical methods and computing methods. Results show that the proposed algorithm has a good performance.
[Retracted] Construction and Drug Evaluation Based on Convolutional Neural Network System Optimized by Grey Correlation Analysis
Authors: Teng Hui
Published: September 2021

Incidence rate of mental illness is increasing year by year with the development of city. The amount of modern medical data is huge and complex. In many cases, it is difficult to realize the rational allocation of resources, which puts forward an urgent demand for the artificial intelligence of modern medicine and brings great pressure to the development of the medical industry. The purpose of this study is to develop and construct a grey correlation analysis and related drug evaluation system of mental diseases based on deep convolution neural network. The establishment of the system can effectively improve the automation and intelligence of modern psychiatric treatment process. In this article, the grey correlation analysis of patient data is carried out, and then, the optimized deep convolution neural network is constructed. Combined with the medical knowledge base, the analysis of disease results is realized, and on this basis, the efficacy of related drugs in the treatment of mental diseases is evaluated. The results show that the advantage of the deep convolution neural network system is to effectively improve the induction rate. What’s more, compared with other algorithms, this algorithm has higher accuracy and efficiency. It improves the comprehensiveness and informatization of disease screening methods, improves the accuracy of screening, reduces the consumption of doctors’ human resources, and provides a theoretical basis for the digitization of the medical industry in the future.
Target Recognition and Trajectory Planning of Apple Harvesting Robot considering Color Multimedia Image Segmentation Algorithm
Authors: Wang Ya
Published: September 2021

For the purpose of significantly reducing the processing time of the apple harvesting robot during the harvesting process, it is highly necessary to carry out the corresponding studies on the methods for rapid recognition and trajectory planning. Through the comprehensive application of information relevance, the image processing area can be reduced. For image recognition and trajectory planning, the related template matching algorithm for removing the mean value and normalization product can be adopted, and segmentation methods based on different threshold values can be used for the realization of the effect. Subsequently, the comparative experiments are properly carried out to verify the effectiveness of the method used.
Viscoelastoplastic Displacement Solution for Deep Buried Circular Tunnel Based on a Fractional Derivative Creep Model
Authors: Gao Yi-Hang , Zhou Zhou , Zhang Hang , Jin Shuang , Yang Wen , Meng Qing-Hua
Published: September 2021

Time‐dependent deformation of surrounding rock is a common phenomenon for tunnels situated in soft rock stratum or hard rock stratum with high geo‐stress. To describe this phenomenon, a creep model combining the Abel dashpot and a non‐Newton viscous element was adopted, and the analytical solution about the viscoelastoplastic deformation for circular tunnel was obtained based on this creep model. Then, the auxiliary tunnel of Jinping II hydropower station was taken as an example to reveal the influence of creep parameters on the creep deformation. The research shows that (1) the creep model can well describe the whole creep stage of rocks, that is, the decay, constant, and accelerated creep stages, (2) the creep deformation has a positive relation with the value of fractional order of Abel dashpot and the order of the non‐Newton viscous element, and (3) the creep curves between test results and analytical solutions are well consistent with each other, which demonstrate the validity of the analytical solution.
Comparative Efficacy of Haizao Yuhu Decoction Composed of Different Varieties of Glycyrrhiza in Goiter Rats
Authors: Chen Feng , Li Na , Xiu Linlin , Liu Haiyan , Chen Shaohong , He Cheng , Fan Angran , Yu Xue , Wang Xin , Ge Chaoran , Huo Min , He Jia , Zhong Gansheng
Published: September 2021

In traditional Chinese medicine, Glycyrrhiza and Sargassum are one pair of the “18 incompatible medicaments,” which in theory cannot be used together. However, since ancient times, many reports have described using compounds containing both Glycyrrhiza and Sargassum to treat diseases. Haizao Yuhu Decoction (HYD), which contains both ingredients, is mainly used to treat goiter. Chinese Pharmacopoeia officially recorded three varieties of Glycyrrhiza: Glycyrrhiza uralensis, Glycyrrhiza inflata, and Glycyrrhiza glabra. These three varieties have certain differences in chemical composition and pharmacological effects. The purpose of the present study was to investigate whether the HYD containing different varieties of Glycyrrhiza and Sargassum had different therapeutic effects in rats with goiter and to elucidate the underlying mechanism of any difference. In this study, propylthiouracil (PTU) was used to replicate the goiter model, then HYDs containing different varieties of Glycyrrhiza were used for treatment for four weeks, and then the relevant indicators were tested. The results demonstrated that HYD had antigoiter effects, alleviated the pathological changes in the thyroid tissue, and restored the abnormal serum levels of hormones related to thyroid function induced by PTU. HYD containing Glycyrrhiza uralensis had the best therapeutic effect in rats with PTU-induced goiter. The antigoiter effect of HYD may function through the hypothalamic-pituitary-thyroid (HPT) axis, inhibit the expression of the Tg and NIS genes, and regulate the synthesis of thyroid hormones, thereby reducing the excessive stimulation of TSH in thyroid cells. In addition, HYD also prevented goiter by promoting thyroid cell apoptosis and inhibiting the ERK/RSK1 pathway of cell proliferation. In conclusion, three types of HYD had different therapeutic effects in rats with goiter, which might be caused by the compatibility of different varieties of Glycyrrhiza and Sargassum.
Revenue Distribution of Hybrid Channel Supply Chain Based on Modified Shapley Value with Cost
Authors: Sha Jin , Zheng Sisi
Published: September 2021

The reasonable distribution of revenue determines not only the coordination but also the development of supply chain. A hybrid channel supply chain model composed of manufacturer and traditional and online retailers was identified as the object of study, decision models under different cooperation modes were built, different revenues of supply chain members and overall were analyzed, satisfaction of characteristic function required by the Shapley value was proved, and the Shapley values of revenue distribution were calculated. In view of the shortcoming of the Shapley value method which takes contribution margin as the only consideration and ignores the impact of other factors such as cost on revenue distribution, the cost correction model was built by using production and sales cost to modify the traditional Shapley value; the reasonable distribution of individual benefits under the premise of maximizing the overall revenue of hybrid channel supply chain was realized.
Model Construction of Enterprise Financial Early Warning Based on Quantum FOA-SVR
Authors: Pan Wen-Tsao , Liu Yi , Jiang Huan , Chen Ya-Ting , Liu Ting , Qing Yan , Huang Guo-Hui , Li Rong
Published: September 2021

The sudden outbreak of COVID-19 has a great impact on human life security and global economic development. To deal with the rampant pandemic, many countries have taken strict control measures, including restricting gathering in public places and stopping the production of enterprises; as a result, many enterprises suffered great challenges in survival and development during the pandemic. In order to help enterprises monitor their own financial situation and realize their healthy development under the pandemic, this paper constructs an Enterprise Financial Early Warning Model, in which Quantum Rotation Gate is used to optimize four algorithms, namely, Fruit Fly Optimization Algorithm (QFOA), Bee Colony Optimization Algorithm (QABC), Particle Swarm Optimization (QPSO), and Ant Colony Optimization (QACO). The results show that the ability of the prediction model can be greatly improved by using the Quantum Rotation Gate to optimize these four algorithms.
[Retracted] Analysis of English Multitext Reading Comprehension Model Based on Deep Belief Neural Network
Authors: Tang Qiaohui
Published: September 2021

In order to solve the problems of low accuracy and low efficiency of answer prediction in machine reading comprehension, a multitext English reading comprehension model based on the deep belief neural network is proposed. Firstly, the paragraph selector in the multitext reading comprehension model is constructed. Secondly, the text reader is designed, and the deep belief neural network is introduced to predict the question answering probability. Finally, the popular English dataset of SQuAD is used for test analysis. The final results show that, after the comparative analysis of different learning methods, it is found that the English multitext reading comprehension model has a strong reading comprehension ability. In addition, two evaluation methods are used to score the overall performance of the model, which shows that the overall score of the English multitext reading comprehension model based on the deep confidence neural network is more than 90, and the efficiency will not be reduced because of the change of the number of documents in the dataset. The above results show that the use of the deep belief neural network to improve the probability generation performance of the model can well solve the task of English multitext reading comprehension, effectively reduce the difficulty of machine reading comprehension in multitask reading, and has a good guiding significance for promoting human convenient Internet knowledge acquisition.
Remote Diagnosis and Triaging Model for Skin Cancer Using EfficientNet and Extreme Gradient Boosting
Authors: Khan Irfan Ullah , Aslam Nida , Anwar Talha , Aljameel Sumayh S. , Ullah Mohib , Khan Rafiullah , Rehman Abdul , Akhtar Nadeem
Published: September 2021

Due to the successful application of machine learning techniques in several fields, automated diagnosis system in healthcare has been increasing at a high rate. The aim of the study is to propose an automated skin cancer diagnosis and triaging model and to explore the impact of integrating the clinical features in the diagnosis and enhance the outcomes achieved by the literature study. We used an ensemble‐learning framework, consisting of the EfficientNetB3 deep learning model for skin lesion analysis and Extreme Gradient Boosting (XGB) for clinical data. The study used PAD‐UFES‐20 data set consisting of six unbalanced categories of skin cancer. To overcome the data imbalance, we used data augmentation. Experiments were conducted using skin lesion merely and the combination of skin lesion and clinical data. We found that integration of clinical data with skin lesions enhances automated diagnosis accuracy. Moreover, the proposed model outperformed the results achieved by the previous study for the PAD‐UFES‐20 data set with an accuracy of 0.78, precision of 0.89, recall of 0.86, and F1 of 0.88. In conclusion, the study provides an improved automated diagnosis system to aid the healthcare professional and patients for skin cancer diagnosis and remote triaging.
The Least Eigenvalue of the Complement of the Square Power Graph of G
Authors: Gul Lubna , Ali Gohar , Waheed Usama , Nasir Sumiya
Published: September 2021

Let G(n, m) represent the family of square power graphs of order n and size m, obtained from the family of graphs F(n, k) of order n and size k, with m ≥ k. In this paper, we discussed the least eigenvalue of graph G in the family G(n, m)c. All graphs considered here are undirected, simple, connected, and not a complete Kn for positive integer n.
Enhanced Recovery Pathway in Adults Undergoing Elective Posterior Thoracolumbar Fusion Surgery: Outcomes Compared with a Traditional Care Pathway
Authors: AlSaleh Khalid , Murrad Khalid , AlZakri Abdulmajeed , Alrehaili Osama , Awwad Waleed
Published: September 2021

Introduction. Spine fusion surgery is an increasingly popular procedure, but the patient experience is variable and the cost is high. Enhanced recovery after surgery (ERAS) pathways can provide a standardized plan for spine fusion cases, improving quality of care and reducing costs. We report an early attempt at the implementation of such a pathway and compare it to a historical cohort. Methods. All adult patients undergoing elective posterior thoracolumbar spine fusion in 2019 and 2020 were included in the study. The ERAS protocol implementation started in January 2020. The study cohort was all cases performed in 2020—after implementation of ERAS—while the historical cohort was cases from 2019. Demographic and clinical data were collected and compared between the groups. Results. Ninety-three patients were included in the study. The study cohort (ERAS) included 42 patients, while the comparison group (pre-ERAS) included 51 patients. Demographic and preoperative clinical data were similar between the two groups. However, postoperative clinical data showed that ERAS resulted in less reliance on analgesics, earlier mobilization, and a reduced length of stay. Complication and readmission rates were unchanged. Conclusion. ERAS can reduce costs while maintaining or improving clinical outcomes for spinal fusion surgery.
Ropivacaine‐Loaded Poloxamer Binary Hydrogels for Prolonged Regional Anesthesia: Structural Aspects, Biocompatibility, and Pharmacological Evaluation
Authors: Mariano Kelli Cristina Freitas , Papini Juliana Zampoli Boava , de Faria Naially Cardoso , Heluany Daniele Nicoli Cabral , Botega Ana Luiza Lourençoni , Cereda Cíntia Maria Saia , de Paula Eneida , Tófoli Giovana Radomille , de Araujo Daniele Ribeiro
Published: September 2021

This study reports the development of thermosensitive hydrogels for delivering ropivacaine (RVC), a wide clinically used local anesthetic. For this purpose, poloxamer‐ (PL‐) based hydrogels were synthesized for evaluating the influence of polymer concentration, hydrophilic‐lipophilic balances, and binary system formation on biopharmaceutical properties and pharmacological performance. Transition temperatures were shifted, and rheological analysis revealed a viscoelastic behavior with enhanced elastic/viscous modulus relationship (G’/G” = 1.8 to 22 times), according to hydrogel composition and RVC incorporation. The RVC release from PL407 and PL407/338 systems followed the Higuchi model (R2 = 0.923–0.989), indicating the drug diffusion from hydrogels to the medium. RVC‐PL hydrogels were potentially biocompatible evoking low cytotoxic effects (in fibroblasts and Schwann cells) and mild/moderate inflammation signs on sciatic nerve nearby histological evaluation. In vivo pharmacological assays demonstrated that PL407 and PL407/338 evoked differential analgesic effects, by prolonging the sensory blockade duration up to ~340 and 250 min., respectively. All those results highlighted PL407 and PL407/338 as promising new strategies for sustaining analgesic effects during the postoperative period.
Qi-Regulating and Blood Circulation-Promoting Therapy Improves Health Status of Stable Angina Pectoris Patients with Depressive Symptoms
Authors: Wang Xiao-Reng , Song Dan-Dan , Tao Tian-Qi , He Tao , Wu Xu-Dong , Li Xue-Mei , Liu Xiu-Hua
Published: September 2021

Depressive symptoms have been found to be highly prevalent among patients with coronary heart disease (CHD) and seriously affect the patients’ quality of life. However, most psychotropic drugs have warnings about potential side effects. Accordingly, safer effective alternatives are urgently demanded. Angina pectoris of CHD is considered as “chest stuffiness and heartache syndrome” in traditional Chinese medicine, with the major syndrome type named Qi stagnation and blood stasis. Qi-regulating and blood circulation-promoting therapy has increasingly shown unique advantages in CHD patients. This study investigated the efficacy of Xuefu Zhuyu decoction, a representative prescription of Qi-regulating and blood circulation-promoting therapy, on angina pectoris patients with depressive symptoms. Depressive symptoms were stratified at baseline in 30 patients with stable angina pectoris who participated in both baseline and 12-week follow-up studies. After performing a stratified analysis, the angina pectoris-specific health status and traditional Chinese medicine “chest stuffiness and heartache syndrome” were evaluated by self-reports using the associated questionnaire scales, respectively. We measured serum concentrations of serotonin, brain-derived neurotrophic factor, and ATP, which are associated with the development of depression. We found that the Xuefu Zhuyu granule significantly improved the angina pectoris-specific health status in patients after 12 weeks of treatment; specifically, it had a better curative effect on patients with depressive symptoms. Xuefu Zhuyu granule also significantly improved the chest stuffiness and heartache syndrome in patients with depressive symptoms (efficacy index is 61.24%,

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versus baseline). Interestingly, Xuefu Zhuyu granule has been found to be more susceptible to improving ATP levels in patients with depressive symptoms, indicating that the improvement in serum ATP levels might account for the better efficacy of Xuefu Zhuyu granule in patients with depressive symptoms. Our data provide prospective evidence that Xuefu Zhuyu granule improves angina pectoris-specific health status through regulating Qi and promoting blood circulation. This trial is registered with ChiCTR-IOR-15006989.
Security-Oriented Indoor Robots Tracking: An Object Recognition Viewpoint
Authors: Yang Yaoqi , Wei Xianglin , Xu Renhui , Peng Laixian , Liao Yunliang , Ge Lin
Published: September 2021

Indoor robots, in particular AI-enhanced robots, are enabling a wide range of beneficial applications. However, great cyber or physical damages could be resulted if the robots’ vulnerabilities are exploited for malicious purposes. Therefore, a continuous active tracking of multiple robots’ positions is necessary. From the perspective of wireless communication, indoor robots are treated as radio sources. Existing radio tracking methods are sensitive to indoor multipath effects and error-prone with great cost. In this backdrop, this paper presents an indoor radio sources tracking algorithm. Firstly, an RSSI (received signal strength indicator) map is constructed based on the interpolation theory. Secondly, a YOLO v3 (You Only Look Once Version 3) detector is applied on the map to identify and locate multiple radio sources. Combining a source’s locations at different times, we can reconstruct its moving path and track its movement. Experimental results have shown that in the typical parameter settings, our algorithm’s average positioning error is lower than 0.39 m, and the average identification precision is larger than 93.18% in case of 6 radio sources.
Stability Analysis of Host Claystone under T-M Coupling of HLW Disposal Repository in China: Experiments and Numerical Simulation
Authors: Liang Haian , Tang Tan , Zhang Longpeng , Liu Xiaodong , Liu Shuai , Yang Ting , Cheng Xinjun , Zhang Juan
Published: September 2021

This paper focuses on the stability of the high-level radioactive waste (HLW) in the proposed clay rock in Tamusu area of China. The in-situ stress as well as the variational characteristics of ambient temperature caused by nuclide decay during HLW storage should be noticeable. A series of thermal property tests and thermo-mechanical coupled strength (T-M) tests of rock samples in the target formation are carried out. Then the stability of surrounding rock of an HLW under the combination of heat release from HLW and in-situ stress is simulated and analyzed by numerical method. Thermal properties of Tamusu clay rock samples are obtained by testing their thermal conductivity. In order to obtain the characteristics and the failure modes of rock samples at different temperatures, the T-M coupling experiments in the temperature range of 100°C are conducted. Numerical model for simulating the state of operation of the nuclear waste tank buried in the tunnel within 100 years is constructed. A thermal boundary by the heat release equation of HLW and the real in-situ stress level in Tamusu area are considered in the model. While, the variation law of surrounding rock’s temperature, stress, and deformation corresponding to the embedding time is obtained from the numerical calculation. Finally, the stability of the deep geological repository is comprehensively evaluated. The results show that the temperature has a significant impact on the T-M coupling characteristics of Tamusu clay rock, and the proposed repository numerical model has no large deformation and failure problems in 100 years. However, the temperature of the surrounding rock of the repository may exceed the safety standard value during the operation period.
Associations of Air Pollution and Pediatric Asthma in Cleveland, Ohio
Authors: Khatri Sumita B. , Newman Cynthia , Hammel Jeffrey P. , Dey Tanujit , Van Laere Jeffrey J. , Ross Kristie A. , Rose Jerri A. , Anderson Timothy , Mukerjee Shaibal , Smith Luther , Landis Matthew S. , Holstein Ann , Norris Gary A.
Published: September 2021

Air pollution has been associated with poor health outcomes and continues to be a risk factor for respiratory health in children. While higher particulate matter (PM) levels are associated with increased frequency of symptoms, lower lung function, and increase airway inflammation from asthma, the precise composition of the particles that are more highly associated with poor health outcomes or healthcare utilization are not fully elucidated. PM is measured quantifiably by current air pollution monitoring systems. To better determine sources of PM and speciation of such sources, a particulate matter (PM) source apportionment study, the Cleveland Multiple Air Pollutant Study (CMAPS), was conducted in Cleveland, Ohio, in 2009–2010, which allowed more refined assessment of associations with health outcomes. This article presents an evaluation of short-term (daily) and long-term associations between motor vehicle and industrial air pollution components and pediatric asthma emergency department (ED) visits by evaluating two sets of air quality data with healthcare utilization for pediatric asthma. Exposure estimates were developed using land use regression models for long-term exposures for nitrogen dioxide (NO2) and coarse (i.e., with aerodynamic diameters between 2.5 and 10 μm) particulate matter (PM) and the US EPA Positive Matrix Factorization receptor model for short-term exposures to fine (<2.5 μm) and coarse PM components. Exposure metrics from these two approaches were used in asthma ED visit prevalence and time series analyses to investigate seasonal-averaged short- and long-term impacts of both motor vehicles and industry emissions. Increased pediatric asthma ED visits were found for LUR coarse PM and NO2 estimates, which were primarily contributed by motor vehicles. Consistent, statistically significant associations with pediatric asthma visits were observed, with short-term exposures to components of fine and coarse iron PM associated with steel production. Our study is the first to combine spatial and time series analysis of ED visits for asthma using the same periods and shows that PM related to motor vehicle emissions and iron/steel production are associated with increased pediatric asthma visits.
Factors Affecting Recidivism of Drunk Driving for Car and Motorbike Users
Authors: Jou Rong-Chang , Lu Yi-Hao
Published: September 2021

This study explored the important factors affecting the recidivism rate of drunk driving for car and motorbike users. The respondents were students of Taiwan’s road safety training course, which was required for all drunk drivers who were suspended from driving due to the violation of regulations. The characteristics of the drunk car and motorbike drivers, such as socioeconomic variables, alcohol consumption changes, family life cycle, and changes in the number of trips, were investigated. This study estimated the models affecting the recidivism rate of drunk driving for car and motorbike users with the logistic regression model. The main variables included drivers with a university degree or above who tend not to be recidivists compared to the drivers without one. Such respondents are more willing to avoid the risk of becoming drunk driving recidivists. Moreover, the variables of alcohol use disorders’ identification test (AUDIT), breath alcohol concentration, and frequency of drunk driving all significantly affect the possibility of recidivism. In terms of family life cycle, married respondents with children aged between 1 and 5 are less likely to become drunk driving recidivists. Those who take motorbikes as an alternative vehicle after being suspended from driving cars are more likely to become drunk driving recidivists. This study suggests the measures of suspending or withdrawing car and motorbike driver’s licenses at the same time, using alcolocks to restrict the right to drive, and increasing the frequency of drunk driving crackdowns. In addition, in terms of alcohol consumption behaviors, drinkers with high risks and drunk drivers with high breath alcohol concentrations should be regarded as the key targets for future tracking in order to avoid drunk driving recidivism.
Ruxolitinib in CMML: A Case Study of Innovative Trial Design in a Rare Cancer
Authors: Shastri Aditi , Adrianzen-Herrera Diego A.
Published: September 2021

Alternative statistical designs cannot fully mitigate the limitations of traditional clinical trials in rare cancers. Creative study designs that integrate early clinical data and correlative outcomes from concomitant translational and laboratory models to evaluate the efficacy of druggable targets can potentially expedite access to novel therapies for these patients.

See related article by Hunter et al., p. 6095