bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Interstage Pipeline on the Performance of Two-Stage Centrifugal Compressors for Automotive Hydrogen Fuel Cells
Authors: Wang Huaiyu , Yang Dengfeng , Zhu Zhengcan , Zhang Hongjie , Zhang Qian
Published: January 2023

At present, two-stage centrifugal compressors based on air bearing and high-speed motor technology are widely used in automotive hydrogen fuel cells. The low-pressure stage and high-pressure stage of the compressor are directly connected through an interstage pipeline, thus the structure of the interstage pipeline has an important influence on the aerodynamic performance of the compressor. In this work, a two-stage compressor with three different interstage pipelines were investigated experimentally and numerically. Results show that affected by the interstage pipeline bend section, the flow distortion will be induced at the impeller inlet of the high-pressure stage, and the distortion intensity changes with the pipeline structure. Among the three models, the EPC (elbow pipe change) model induces the most intense total pressure distortion at the condition of 80 kr/min and 130% mass flow rate, resulting in an efficiency reduction of 2 and 1.5 percentage points compared with the SPC (straight pipe change) and the TPC (total pipe change) model, respectively. Further research indicates that the upstream distortion has obvious influence on the downstream rotor blades. As the blade height decreases, the load becomes more uniform on the main blades, while the load extremum migrates to the trailing edge on the splitter blades. Finally, three models are tested, and their performance is compared at three typical rotational speeds., It is recommended that interstage pipelines similar to SPC models should be chosen to improve the two-stage compressor efficiency in the design.
Optimization of Physical Parameters and Analysis of Rock Movement and Deformation Patterns in Deep Strip Mining
Authors: Dong Yue , Luan Yuanzhong , Ji Zhaolei , Luan Hengxuan
Published: January 2023

China’s shallow coal resources are gradually diminishing, and deep coal resources have slowly become the main energy source. However, the destruction mechanism and evolution of deep rock formation structure are not clear, which seriously restricts the exploitation and utilization of deep energy. Here, the optimization of the physical parameters and the deformation law of the overlying rock in a deep mine in Shandong Province were studied with an integrated approach including similar simulation, mechanical analysis, numerical simulation, and measurement verification, etc. First, the paper simplified the rock formation and developed a numerical model using the field exploration data; second, we analyzed the mechanical properties of each rock formation, obtaining the key rock formation that affects the surface deformation of the mining area. Furthermore, we tested the physical parameters of rock formation by using the orthogonal test, optimizing the physical parameters of rock formation with the extreme difference, and variance analysis of the orthogonal test results. Then, using FLAC3D, we conducted numerical calculations for strip mining of deep wells with numerous working faces, analyzing the maximum surface subsidence value, the maximum horizontal movement value of ground surface at different mining depths, and the change in the subsidence coefficient. By analyzing the linkage relationship between the surface phenomenon and deep mining, we obtained the optimal mathematical model of the three and the coal seam mining depth, which revealed the linkage law of “deep formation–earth surface”. Finally, the model relationships of the influence boundary value, maximum subsidence value, maximum horizontal movement value, and mining depth for each rock layer were separately established.
Analysis of Breath-Holding Capacity for Improving Efficiency of COPD Severity-Detection Using Deep Transfer Learning
Authors: Rout Narendra Kumar , Parida Nirjharinee , Rout Ranjeet Kumar , Sahoo Kshira Sagar , Jhanjhi N. Z. , Masud Mehedi , AlZain Mohammed A.
Published: January 2023

Air collection around the lung regions can cause lungs to collapse. Conditions like emphysema can cause chronic obstructive pulmonary disease (COPD), wherein lungs get progressively damaged, and the damage cannot be reversed by treatment. It is recommended that these conditions be detected early via highly complex image processing models applied to chest X-rays so that the patient’s life may be extended. Due to COPD, the bronchioles are narrowed and blocked with mucous, and causes destruction of alveolar geometry. These changes can be visually monitored via feature analysis using effective image classification models such as convolutional neural networks (CNN). CNNs have proven to possess more than 95% accuracy for detection of COPD conditions for static datasets. For consistent performance of CNNs, this paper presents an incremental learning mechanism that uses deep transfer learning for incrementally updating classification weights in the system. The proposed model is tested on 3 different lung X-ray datasets, and an accuracy of 99.95% is achieved for detection of COPD. In this paper, a model for temporal analysis of COPD detected imagery is proposed. This model uses Gated Recurrent Units (GRUs) for evaluating lifespan of patients with COPD. Analysis of lifespan can assist doctors and other medical practitioners to take recommended steps for aggressive treatment. A smaller dataset was available to perform temporal analysis of COPD values because patients are not advised continuous chest X-rays due to their long-term side effects, which resulted in an accuracy of 97% for lifespan analysis.
A Rapid Verification System for Automatic Emergency Braking Control Algorithm of Passenger Car
Authors: Xu Jun , Li Liangyu , Zhao Ran , Deng Feng , Li Gangyan
Published: January 2023

The automatic emergency braking (AEB) system of the passenger car is responsible for auxiliary braking judgment and decision-making in an emergency. Due to the inevitable pressure response delay of passenger car pneumatic braking systems, a large number of verification tests should be carried out to propose appropriate strategies and algorithms. To realize the rapid verification of the AEB control algorithm, a verification system integrating software-in-the-loop (SIL) and hardware-in-the-loop (HIL) was proposed for a two-axle passenger car. It can verify the logic feasibility of the control algorithm through SIL testing, and can verify the implementation effect of the control algorithm through HIL testing. The verification system is composed of IPG, dSPACE, and a pneumatic braking bench. Considering the influence of pneumatic braking delay, it is well-matched with the actual vehicle AEB system. The AEB hierarchical control algorithm was verified under three typical test conditions. The results show that the SIL testing results of speed and relative distance are in good agreement with the HIL testing results, and the average relative deviation of relative distance is only 1.7 m. The single test time of the SIL testing is about 228 s, which can meet the requirements of rapid verification of the AEB control algorithm of the passenger car.
Study on Highway Alignment Optimization Considering Rollover Stability Based on Two-Dimensional Point Collision Dynamics
Authors: Wu Xinye , Fu Shude , Guo Liangrong
Published: January 2023

In order to reduce the influence of unreasonable road alignment design on vehicle driving safety, a study on road alignment optimization and vehicle driving safety based on two-dimensional point collision dynamics was carried out. First, through the two-dimensional point collision dynamics model, the relationship of the kinematic parameters before and after vehicle collision was deduced. Second, according to the vehicle–road coupling dynamic model analysis after collision, the safety threshold between the radius of the circular curve and the road superelevation was derived by taking vehicle rollover as the critical condition. Next, the road alignment optimization scheme based on vehicle rollover stability after collision was proposed. Finally, the rationality of the optimization scheme was verified by PC-Crash simulation. The simulation results showed that the proposed optimization scheme of the minimum radius and superelevation of the circular curve meets the safety requirements of vehicle rollover. This study optimized the relevant indicators of the road alignment under the premise of ensuring vehicle rollover stability and provides a reference for the improvement and optimization of road alignment design. It also has important guiding significance for the formulation of vehicle driving safety management measures.
A Novel Pressure Relief Hole Recognition Method of Drilling Robot Based on SinGAN and Improved Faster R-CNN
Authors: Liang Bin , Wang Zhongbin , Si Lei , Wei Dong , Gu Jinheng , Dai Jianbo
Published: January 2023

The drilling robot is the key equipment for pressure relief in rockburst mines, and the accurate recognition of a pressure relief hole is the premise for optimizing the layout of pressure relief holes and intelligent drilling. In view of this, a pressure relief hole recognition method for a drilling robot, based on single-image generative adversarial network (SinGAN) and improved faster region convolution neural network (Faster R-CNN), is proposed. Aiming at the problem of insufficient sample generation diversity and poor performance of the traditional SinGAN model, some improvement measures including image size adjustment, multi-stage training, and dynamically changing iteration times are designed as an improved SinGAN for the generation of pressure relief hole images. In addition, to solve the problem that the traditional depth neural network is not ideal for small-size target recognition, an improved Faster R-CNN based on multi-scale image input and multi-layer feature fusion is designed with the improved SqueezeNet as the framework, and the sample data collected from ground experiments are used for comparative analysis. The results indicate that the improved SinGAN model can improve the diversity of generated images on the premise of ensuring the quality of image samples, and can greatly improve the training speed of the model. The accuracy and recall rate of the improved Faster R-CNN model were able to reach 90.09% and 98.32%, respectively, and the average detection time was 0.19 s, which verifies the superiority of the improved Faster R-CNN model. To further verify the practicability of the proposed method, some field images were collected from the underground rockburst relief area in the coal mine, and a corresponding test analysis was carried out. Compared with three YOLO models, the accuracy and recall rate of improved Faster R-CNN model improved significantly, although the training time and recognition time increased to a certain extent, which proves the feasibility and effectiveness of the proposed method.
An Improved Stereo Matching Algorithm Based on Joint Similarity Measure and Adaptive Weights
Authors: Lai Xiangjun , Yang Bo , Ma Botao , Liu Mingzhe , Yin Zhengtong , Yin Lirong , Zheng Wenfeng
Published: January 2023

Stereo matching is the operation of obtaining the parallax value between two images by matching all the corresponding image points in the two images, thus obtaining the dense parallax image between the two images. How to obtain accurate disparity images has always been a key point in the field of stereo vision. Presently, in the research of 3D reconstruction technology based on binocular stereo vision, the main research direction of domestic and foreign scholars is to improve the efficiency and accuracy of stereo matching, and there is research literature on soft tissues. This paper proposes an improved stereo matching algorithm based on joint similarity measures and adaptive weights. The algorithm improves the matching cost calculation based on the joint similarity measure to fit the color image of the heart soft tissue. At the same time, the algorithm uses the idea of graph cutting to improve the adaptive weight. The experimental results show that both the improved joint similarity measure and the improved adaptive weight can effectively reduce the mismatch rate. In addition, the corresponding matching effect is better than using only one of the improved joint similarity measures.
An Analytical Method Evaluating the Evolution of Group Effect for Vertically Loaded Pile Groups Subjected to Tunnel Excavation
Authors: Fan Yifei , Cai Jing , Wang Jianhua
Published: January 2023

Tunnel excavations near existing vertically loaded pile groups are frequently encountered in urban areas, and most available studies have focused on the additional deformation and stress induced in the pile group, lacking in consideration of the variation in the pile-soil interaction (PSI) in the process, which plays an important role in pile group behavior with close pile spacing. In addition, for vertically loaded pile groups subjected to excavations in their proximity, the combined actions of the overlapping stress and shielding effect can lead to complicated variations in the group effect, which in turn results in difficulty in evaluating the PSI relationship and the pile group response. Thus, the modified Poulos method is extended in this paper to account for the effects of tunneling, and the variations in the group effect, load redistributions and pile settlements are also investigated. The validity of the proposed method is firstly verified by an available centrifuge model test with tunneling near a 2 × 2 fixed-head pile group. Further, the influences of the pile spacing and relative distance between the pile group and the tunnel are analyzed, and the most unfavorable working condition could be a tunnel excavated near the soil surface, close to a pile group with a small pile spacing.
Energy Cost Minimization with Hybrid Energy Storage System Using Optimization Algorithm
Authors: Rafał Krzysztof , Radziszewska Weronika , Grabowski Oskar , Biedka Hubert , Verstraete Jörg
Published: January 2023

The purpose of this study is to develop an effective control method for a hybrid energy storage system composed by a flow battery for daily energy balancing and a lithium-ion battery to provide peak power. It is assumed that the system operates behind the meter, the goal is to minimize the energy cost in the presence of a PV installation (as an example of a local renewable source) and energy prices are determined by 3-zone tariffs. The article presents the application of an optimization method to schedule the operation of each battery in the system. The authors have defined an optimization method aimed at minimizing the total cost of the system, taking into account energy costs and batteries depreciation. The techno-economical model of the system, including battery degradation, is constructed and the cost optimization methods are implemented in Python. The results are validated with real energy and price profiles and compared with conventional control strategies. The advantages of optimization in terms of energy cost are discussed. The experiment shows that not only is a hybrid energy system successful in lowering the total operation cost and in increasing self-consumption but also that the implemented methods have slightly different properties, benefits and issues.
Two-Dimensional Modelling Approach for Electrokinetic Water Transport in Unsaturated Kaolinite
Authors: López-Vizcaíno Rubén , Navarro Vicente , Yustres Ángel
Published: January 2023

Although electrokinetic treatments for soil remediation and ground improvement have gradually undergone significant experimental development, one of the most important physical phenomena has received very little attention in recent years. Electroosmotic flow, especially in unsaturated conditions, has not been simulated in domains of more than one dimension. In the present work, a modification of the M4EKR code was used to study water movement in partially saturated soils under electrokinetic treatments. Two different configurations were studied: electrodes placed in electrolyte wells and electrodes directly inserted into the soil, and the treatment was started under unsaturated conditions for both. Due to the unrestricted availability of fluid in the first case, soil saturation is inevitable, but in the second case, only a spatial redistribution of water content can be observed. A detailed analysis of a variety of configurations involving several electrolyte wells showed that the number of electrodes, the distance between them and, above all, the ratio between the two magnitudes determines the efficiency of soil saturation and the energy consumed in the process.
Improved Evaluation of Cultivation Performance for Maize Based on Group Decision Method of Data Envelopment Analysis Model
Authors: Huang Wei , Li Han , Chen Kaifeng , Teng Xiaohua , Cui Yumeng , Yu Helong , Bi Chunguang , Huang Meng , Tang You
Published: January 2023

Maize cultivation performance, including the efficiency of the input and output of maize, which reflect the allocation and utilization of resources in the process of maize cultivation, is crucial for evaluating and improving maize cultivation. This paper adopts the method of quadratic regression orthogonal rotation combination experimental design to explore the effects of four main cultivation measures (planting density, nitrogen fertilizer, phosphorus fertilizer and potassium fertilizer) on maize yield at five levels (−2, −1, 0, 1; 2). The CCR (A. Charnes, W. Cooper and E. Rhodes) model, which is the basic model of data envelopment analysis (DEA), was used to evaluate the 36 groups of cultivation measures. The results show that 9 groups are CCR-effective cultivation measures, but the performance of these cultivation measures cannot be further evaluated. To improve the evaluation of cultivation performance, a novel method termed as the group decision method of DEA (GDM-DEA) is proposed to detect the improvement of evaluation performance and is tested using the measurements of maize cultivation. The results suggest that the GDM-DEA method can classify and sort the performance of all the cultivation measures, which is more sensitive and accurate than the CCR method. For the effective cultivation measures that meet the requirements of GDM-DEA, the optimal cultivation measures could be determined according to the ranking of yield. This method determined the most effective cultivation measure. Further independent validation showed that the final optimal cultivation measures fall in the range of the expected cultivation measures. The GDM-DEA model is capable of more effectively evaluating cultivation performance.
Special Issue “Urban Sustainability and Resilience of the Built Environments”
Authors: Nastase Ilinca , Bode Florin Ioan
Published: January 2023

Urbanization and the development of urban areas are profoundly altering the relationship between society and the environment [...]
Task-Specific Grasp Planning for Robotic Assembly by Fine-Tuning GQCNNs on Automatically Generated Synthetic Data
Authors: Károly Artúr István , Galambos Péter
Published: January 2023

In modern robot applications, there is often a need to manipulate previously unknown objects in an unstructured environment. The field of grasp-planning deals with the task of finding grasps for a given object that can be successfully executed with a robot. The predicted grasps can be evaluated according to certain criteria, such as analytical metrics, similarity to human-provided grasps, or the success rate of physical trials. The quality of a grasp also depends on the task which will be carried out after the grasping is completed. Current task-specific grasp planning approaches mostly use probabilistic methods, which utilize categorical task encoding. We argue that categorical task encoding may not be suitable for complex assembly tasks. This paper proposes a transfer-learning-based approach for task-specific grasp planning for robotic assembly. The proposed method is based on an automated pipeline that quickly and automatically generates a small-scale task-specific synthetic grasp dataset using Graspit! and Blender. This dataset is utilized to fine-tune pre-trained grasp quality convolutional neural networks (GQCNNs). The aim is to train GQCNNs that can predict grasps which do not result in a collision when placing the objects. Consequently, this paper focuses on the geometric feasibility of the predicted grasps and does not consider the dynamic effects. The fine-tuned GQCNNs are evaluated using the Moveit! Task Constructor motion planning framework, which enables the automated inspection of whether the motion planning for a task is feasible given a predicted grasp and, if not, which part of the task is responsible for the failure. Our results suggest that fine-tuning GQCNN models can result in superior grasp-planning performance (0.9 success rate compared to 0.65) in the context of an assembly task. Our method can be used to rapidly attain new task-specific grasp policies for flexible robotic assembly applications.
An 8kb RRAM-Based Nonvolatile SRAM with Pre-Decoding and Fast Storage/Restoration Time
Authors: Yin Jiayu , Liao Wenli , Zhang Yuyan , Jiang Jianhua , Chen Chengying
Published: January 2023

Combining the advantages of low-power consumption of static random access memory (SRAM) with high stability and nonvolatile of resistive memory (RRAM), an improved 8T2R nonvolatile SRAM (nvSRAM) memory cell was proposed in this paper. In order to solve the problem that data cannot be stored when SRAM is powered off, RRAM technology was introduced into SRAM to realize an SRAM with nonvolatile function. The differential mode was adopted to improve the data restoration speed. Meanwhile, a pre-decoding technology was proposed to realize fast address decoding, and a voltage-mode sensitive amplifier was used to achieve fast amplification of two bit lines, so as to improve the reading speed of the memory. An 8kb nvSRAM was implemented with a CMOS 28 nm 1P9M process. The simulation results show that when the power supply voltage was 0.9 V, the static/read/write noise margin was 0.35 V, 0.16 V and 0.41 V, respectively. The data storage time was 0.21 ns, and restoration time was 0.18 ns. The time for the whole system to read 1 bit of data was 5.2 ns.
The Use of Wireless Networks and Mobile Applications in the Control of Electric Machines
Authors: Muc Adam , Bielecka Agata , Iwaszkiewicz Jan
Published: January 2023

The paper presents the implementation possibilities of remote control by use of wireless communication and mobile application dedicated to controlling systems of power electronics converters. The article focuses on Bluetooth and Wi-Fi technologies as they are currently the most commonly used in modern mobile devices. The authors wanted to check the usefulness of those methods in the application of a classic drive set with a DC motor. The MIT App Inventor programming environment, which allows quick prototyping of the mobile graphical interface, was used to develop the mobile application. The developed prototype of the mobile application is the second thread of the article, the aim of which is to propose a mobile application interface that enables safe control of the electric drive in an open loop. By repeated testing of the graphical structure of the application and the controls used, the authors obtained the final form of the interface, which, in their opinion, is absolutely required when developing such programs. The evaluated control strategy has been also used to control the rotational speed of a permanent magnet DC motor supplied by a three-phase thyristor rectifier. This paper’s research results have shown the proposed solutions’ advantages and disadvantages.
Theoretical Model of Self-Magnetic Flux Leakage and Its Application in Estimating the Depth Direction of a Fatigue Crack
Authors: Lee Jinyi , Wang Dabin , Dharmawan I Dewa Made Oka
Published: January 2023

In this study, theoretical models were proposed to explain the changes in self-magnetic flux density (SMFD) due to fatigue cracks in the presence and absence of external magnetic fields. Three theoretical models were proposed: rotation domain model (RDM), concentration domain model (CDM), and vertical domain model (VDM), considering the deformation and non-deformation possibilities. To prove the theoretical model, fatigue cracks with different depth angles were fabricated through fatigue testing and EDM processing on the CT specimens. In addition, tunnel magnetoresistance (TMR) sensors were used to evaluate the 3-axis distribution of SMFD. Comparing the simulation and experimental results, similar tendencies of the occurrence and depth angle of fatigue cracks and their effect on the distribution of SMFD were observed. According to the RDM, the distribution of SMFD occurs in the direction of the crack length (y-direction), while the CDM explains that the SMFD does not occur if the fatigue crack is in a direction perpendicular to the surface. In addition, the VDM shows that SMFDs occur in a direction perpendicular to the crack length (x-direction) and the specimen surface (z-direction). Interestingly, these trends agree with the experimental results, which confirms the validity of the theoretical model and thus can be used to estimate the depth direction of a fatigue crack.
In Vitro Evaluation of a Non-Invasive Photoplethysmography Based Intracranial Pressure Sensor
Authors: Abay Tomas Y. , Phillips Justin P. , Uff Christopher , Roldan Maria , Kyriacou Panicos A.
Published: January 2023

Intracranial pressure (ICP) is an important measurement in the treatment of Traumatic Brain Injury (TBI). Currently, ICP can only be measured invasively, which exposes patients to operative risk and can only be performed by neurosurgeons. Hence, there is a significant need for a non-invasive ICP technology. This paper describes the evaluation of a novel non-invasive intracranial pressure (nICP) monitor which uses the Photoplethysmogram (PPG) to measure the ICP. The monitor was evaluated in an in vitro model that simulated cerebral haemodynamics and allowed the controlled manipulation of ICP. A number of features from the PPG were extracted and utilised in a machine learning model to estimate ICP. Three separate measurements in which the ICP was varied were performed, and the estimated ICP (nICP) was compared with reference (invasive) ICP measurements. The ICP estimated by the nICP monitor was highly correlated with reference ICP measurements (Pearson’s correlation coefficient between 0.95 and 0.98). The nICP monitor also showed a low Root Mean Square Error from the reference ICP measure (3.12, 1.48, and 1.45 mmHg). Analysis of agreement by Bland and Altman also revealed good agreement between the two techniques. The optical nICP monitor was able to estimate the ICP non-invasively from an in vitro model simulating intracranial hypertension. The non-invasive ICP monitor showed very promising results which can set the base for further investigations. This work contributes significantly to the quest for non-invasive ICP monitoring in Traumatic Brain Injury (TBI), and paves the way for further research in this field.
A Review Study on Total Ankle Replacement
Authors: Noori Naudereh B. , Ouyang Jessica Yi , Noori Mohammad , Altabey Wael A.
Published: January 2023

Total ankle replacement (TAR) is the replacement of a damaged arthritic ankle joint with a prosthetic implant to eliminate the source of resultant pain and swelling. Historically, however, the ankle joint has been one of the most difficult joints to analyze and replicate for successful replacement due to its complex anatomy and multiplanar motion. Ankle fusion, the standard of care for end stage ankle arthritis, has excellent functional outcomes but results in loss of motion at the joint. TAR was first attempted in the 1970s and by the early 1990s, prosthesis designs more closely mirrored the natural anatomy of the ankle and TAR was no longer considered an experimental procedure. Although the outcomes of TAR have significantly improved over this short period of time, there are still many areas that warrant further investigation including (1) optimal patient selection, (2) number of prosthesis components, (3) bearing type, (4) revision rates and causes and (5) comprehensive finite element models (FEM) of the ankle. The main goal of this paper is to present a literature review on the background and evolution of TAR, the current state of practice and prosthesis types and challenges and directions for future improvement.
Polarformer: Optic Disc and Cup Segmentation Using a Hybrid CNN-Transformer and Polar Transformation
Authors: Feng Yaowei , Li Zhendong , Yang Dong , Hu Hongkai , Guo Hui , Liu Hao
Published: January 2023

The segmentation of optic disc (OD) and optic cup (OC) are used in the automatic diagnosis of glaucoma. However, the spatially ambiguous boundary and semantically uncertain region-of-interest area in pictures may lead to the degradation of the performance of precise segmentation of the OC and OD. Unlike most existing methods, including the variants of CNNs (Convolutional Neural Networks) and U-Net, which limit the contributions of rich global features, we instead propose a hybrid CNN-transformer and polar transformation network, dubbed as Polarformer, which aims to extract discriminative and semantic features for robust OD and OC segmentation. Our Polarformer typically exploits contextualized features among all input units and models the correlation of structural relationships under the paradigm of the transformer backbone. More specifically, our learnable polar transformer module optimizes the polar transformations by sampling images in the Cartesian space and then mapping them back to the polar coordinate system for masked-image reconstruction. Extensive experimental results present that our Polarformer achieves superior performance in comparison to most state-of-the-art methods on three publicly available datasets.
Mechanical and Conductive Behavior of Graphite Filled Polysulfone-Based Composites
Authors: Mohammad Hussam , Stepashkin Andrey A. , Laptev Alexander I. , Tcherdyntsev Victor V.
Published: January 2023

Polysulfone-based composite materials filled with artificial, natural, or thermally expanded graphite have been investigated. Composite materials with filling degrees between 30 and 70 wt.% were prepared using solution technology. High filling levels with graphite fillers allowed for the achievement of thermal conductivity of 7.35 W/m · K and electrical conductivity of 52.9 S/cm. The use of natural graphite has been found to have the greatest impact on thermal and electrical characteristics, while materials with dispersed artificial graphite exhibit the best mechanical properties. Evolution of samples’ density and porosity with the filling degree as well as the effect of these parameters on the conductive properties have been analyzed and discussed.
Research on the Mechanism of the Passive Reinforcement of Structural Surface Shear Strength by Bolts under Structural Surface Dislocation
Authors: Tang Yinfeng , Jiang Donghai , Wang Tongxu , Luan Hengjie , Liu Jiangwei , Zhang Sunhao
Published: January 2023

In order to study the local deformation of an anchor bolt and the improvement in the shear strength of a structural surface under the misalignment of an anchorage structure surface, FLAC3D software was used to simulate granite, sandstone, and coal specimens with anchorage angles of 90° to analyze the damage of the anchoring agent and the changes in the local axial and shear forces of the anchor bolts with the misalignment of the structural surface. The results show that the anchor bolt near the structural surface had significant local characteristics with the misalignment of the structural surface; that is, the length of the local deformation area of the bolt was approximately equal to the length of the damaged area of the anchoring agent, and the stress on the anchor bolt was in a coupled tensile–shear stress state when the bolt reached the yield state. For the fully grouted bolts, it was this significant local feature that made the shear strength of the structural surface increase rapidly under a small shear displacement so that the structural surface reached a stable state. The improvement in the shear strength of the anchoring structural surface was caused by the misalignment of the structural surface. This is referred to as the passive improvement of the shear strength of the anchoring structural surface, which is the mechanism of the bonding section anchor to control the shear displacement of the structural surface and realize the stability of the rock mass.
Adhesive Bonding of an Aluminum Alloy with and without an Oxide Layer in Atmospheres with Different Oxygen Contents
Authors: Gerland Sandra , Raatz Annika
Published: January 2023

Aluminum surfaces in a normal atmosphere are always coated with a native oxide layer. To prevent a new layer from forming after this oxide layer has been removed, an environment without oxygen must be created. This work uses a new method of doping an inert gas atmosphere with highly reactive silane to ensure technical freedom from oxygen. The influence of the surrounding atmosphere and the influence of the oxide layer on the tensile strength of an aluminum-aluminum joint are investigated. For this purpose, 2-component adhesives are used whose curing mechanisms are fundamentally not based on the reaction with the surrounding atmosphere. The tests are carried out in normal, pure argon, and an oxygen-free argon/silane atmosphere. The experiments show that the surrounding atmosphere influences the strength of the bonded joint. Compared to the oxidized surfaces, the joints of the deoxidized surfaces show a higher tensile strength under constant ambient conditions.
Integrated Optimization of Stop Planning and Timetabling for Demand-Responsive Transport in High-Speed Railways
Authors: Li Yawei , Han Baoming , Yang Ruixia , Zhao Peng
Published: January 2023

The high-speed railways have made rapid developments in recent years. Fulfilling passenger demand and providing precise train services are the core problems to be solved in railway operation. This paper proposes an optimization strategy for demand-responsive transport to integrate train-stop planning and timetabling in high-speed railways. Passenger travel information, including their origins, destinations and expected departure times is taken as input. A mixed integer linear programming model is established to obtain an effective service plan, which consists of train stop pattern, passenger ride plan and train arrival/departure times at all stations. The optimization objective is to minimize the remaining passenger demand and train travel time. Finally, the proposed method is applied to a real-world case, and a series of several experiments are conducted to prove the efficiency and validity of the proposed model. The results suggest that the proposed approach could generate efficient service plans which are responsive to passenger demand.
Consistency of Imperfections in Steel Eurocodes
Authors: Baláž Ivan , Koleková Yvona , Agüero Antonio , Balážová Pavla
Published: January 2023

The second-order theory was used to analyze the flexural buckling of an individual member simply supported on both member ends, with a uniform double symmetric cross-section under a uniform axial force in an elastic state. The purpose was to show the influence of four different amplitudes of initial imperfections on the shape of the elastic buckling mode ηcrx used in the current EN 1993-1-1 and its new draft, prEN 1993-1-1. Three methods were followed for the analysis: the equivalent member (EM) method, the unique global and local initial (UGLI) imperfection method, and second-order theory with the initial imperfection having an initial local bow imperfection e0. For the relevant quantities, simple formulae were derived and their distribution was drawn on diagrams to represent their graphical interpretations for the first time ever. The formulae and diagrams were valid for the ultimate limit state, which means NEd=Nb,Rd. The influence of four different amplitude values was evaluated: (a) e0,k, proposed for the UGLI imperfection method in the draft EN 1993-1-1; (b) the initial local bow imperfection e0, utilized in the current EN 1993-1-1; (c) the other one employed in its draft; and (d) e0,d, used in the UGLI imperfection method in the current EN 1993-1-1, the current EN 1999-1-1, and the draft prEN 1999-1-1. The main conclusion was that e0,k must not be used in the draft EN 1993-1-1. The UGLI imperfection method was also applied to the column fixed at one end and simply supported at the other end. This example showed the geometrical interpretation of relevant amplitudes. The historical development of the UGLI imperfection method is also presented. All the relations are illustrated in two numerical examples, and the geometrical interpretations of formulae were used in the diagrams. The partial results were verified by the independent computer programs FE-STAB and IQ 100.
Antibacterial Activity of Crude Extract and Purified Acetogenins from Annona muricata Seeds
Authors: Aguilar-Hernández Gabriela , López-Romero Brandon A. , Pérez-Larios Alejandro , Ruvalcaba-Gómez José M. , Castellanos-Huerta Inkar , Tellez-Isaias Guillermo , Petrone-García Victor M. , Anaya-Esparza Luis M. , Montalvo-González Efigenia
Published: January 2023

Currently, several biological activities are attributed to the acetogenins (ACGs) of Annonaceae (including Annona muricata); among these is antimicrobial activity. The main focus of this experiment was to evaluate the antimicrobial effect of the crude extract (CE) and purified acetogenins (P-ACGs) from the endosperm of A. muricata seeds using agar disk diffusion, lethality, sub-lethal, and potential damage membrane tests against Gram-positive and Gram-negative microorganisms. According to the results, P-ACGs present the highest antibacterial effect (12.5–4000 µg/mL) against Enterococcus faecalis (11–15.67 mm), Listeria monocytogenes (12–18 mm), Aeromonas hydrophila (10.33–11.67 mm), Bulkholderia cenocepacia (11–12 mm), and Salmonella paratiphy (11–15.67 mm), and a minimum inhibitory concentration ranging from 0.009 to 12.50 µg/mL. Measurement of the membrane potential shows that, in the presence of P-ACGs, the number of viable cells is reduced, with a significant logarithmic reduction observed (0.38, 1.27, and 1.81 CFU/mL) and a significant sub-lethal lesion (57.78, 96.14, and 98.42%) in Escherichia coli, E. faecalis, and L. monocytogenes, respectively. According to this study, the results demonstrate that P-ACGs from A. muricata seeds are potent and effective antibacterial compounds with potential pharmaceutical applications.
Maturity Status, Relative Age and Constituent Year Effects in Young Iberian Kayakers
Authors: Fernandes Rui António , Gomes Beatriz Branquinho , Alacid Fernando
Published: January 2023

Like in other sports systems, in kayaking, young athletes are commonly grouped by their birth years. This study analyzed maturity status, relative age, and constituent age effects in young Under 14 (U14) and 16 (U16) Iberian male kayakers. One hundred and thirty (U14: n =80; U16: n = 50) young kayakers aged 14.10 ± 1.06 years were assessed for anthropometry, performance, maturity, and sport experience. The year was divided into four birth quarters (BQ). There were no significant differences in the kayaker’s distribution by BQ in both categories (U14, p = 0.348; U16, p = 0.709) or total sample (p = 0.783). Six of the ten best kayakers in the U14 category were born in the year’s first half, and eight were among the U16 kayakers. Talent detection and selection systems based solely on the young kayakers’ performances may imply some bias. One of the ways to get around this situation would be to adopt a grouping system similar to bio-banding, allowing the maximum number of practitioners to experience the possibility of obtaining competitive success.
New Frontiers in Sustainable Geotechnics
Authors: Jastrzębska Małgorzata , Kazimierowicz-Frankowska Krystyna , Chiaro Gabriele , Rybak Jarosław
Published: January 2023

With increasing ecological awareness, the idea of balanced development has become more popular [...]
Configuring Reconfigurable Intelligent Surface for Parallel MIMO Visible Light Communications with Asymptotic Capacity Maximization
Authors: Wu Qi , Zhang Jian , Zhang Yanyu , Xin Gang , Guo Jianing
Published: January 2023

As an emerging technology, reconfigurable intelligent surface (RIS) has attracted increasing attention due to the ability to configure the wireless propagation environment. Parallel multiple-input multiple-output (MIMO) visible light communication (VLC) is suitable for some scenarios, e.g., multi-user time-division multiple access for indoor VLCs. The application of RIS in VLC is a promising trend in the future, and this paper investigates the employment of RIS in a parallel MIMO VLC system with asymptotic capacity maximization. To this end, the RIS-aided parallel MIMO VLC channel model is derived in this paper under the point source assumption, and then, as for the non-convex optimization problem, instead of searching exhaustively for the optimal solution, we propose a low-complexity near-optimal relaxing particle swarm optimization (RPSO) algorithm to optimize the RIS parameters. Meanwhile, we discover that the convex relaxation is an effective method for the optimization problems. Finally, numerical results indicate the effectiveness of the proposed design of RIS, and meanwhile, the asymptotic capacity can be improved to a great degree by adopting RIS in the parallel MIMO VLC system.
Fiber-Reinforced Polymer Confined Concrete: Data-Driven Predictions of Compressive Strength Utilizing Machine Learning Techniques
Authors: Sofos Filippos , Papakonstantinou Christos G. , Valasaki Maria , Karakasidis Theodoros E.
Published: January 2023

Accurate estimation of the mechanical properties of concrete is important for the development of new materials to lead construction applications. Experimental research, aided by empirical and statistical models, has been commonly employed to establish a connection between concrete properties and the resulting compressive strength. However, these methods can be labor-intensive to develop and may not always produce accurate results when the relationships between concrete properties, mixture composition, and curing conditions are complex. In this paper, an experimental dataset based on uniaxial compression experiments conducted on concrete specimens, confined using fiber-reinforced polymer jackets, is incorporated to predict the compressive strength of confined specimens. Experimental measurements are bound to the mechanical and physical properties of the material and fed into a machine learning platform. Novel data science techniques are exploited at first to prepare the experimental dataset before entering the machine learning procedure. Twelve machine learning algorithms are employed to predict the compressive strength, with tree-based methods yielding the highest accuracy scores, achieving coefficients of determination close to unity. Eventually, it is shown that, by carefully manipulating experimental datasets and selecting the appropriate algorithm, a fast and accurate computational platform is created, which can be generalized to bypass expensive, time-consuming, and susceptible-to-errors experiments, and serve as a solution to practical problems in science and engineering.
Accuracy of Hidden Markov Models in Identifying Alterations in Movement Patterns during Biceps-Curl Weight-Lifting Exercise
Authors: Peres André , Espada Mário , Santos Fernando , Robalo Ricardo , Dias Amândio , Muñoz-Jiménez Jesús , Sancassani Andrei , Massini Danilo , Pessôa Filho Dalton
Published: January 2023

This paper presents a comparison of mathematical and cinematic motion analysis regarding the accuracy of the detection of alterations in the patterns of positional sequence during biceps-curl lifting exercise. Two different methods, one with and one without metric data from the environment, were used to identify the changes. Ten volunteers performed a standing biceps-curl exercise with additional loads. A smartphone recorded their movements in the sagittal plane, providing information on joints and barbell sequential position changes during each lift attempt. An analysis of variance revealed significant differences in joint position (p < 0.05) among executions with three different loads. Hidden Markov models were trained with data from the bi-dimensional coordinates of the joint positional sequence to identify meaningful alteration with load increment. Tests of agreement tests between the results provided by the models with the environmental measurements, as well as those from image coordinates, were performed. The results demonstrated that it is possible to efficiently detect changes in the patterns of positional sequence with and without the necessity of measurement and/or environmental control, reaching an agreement of 86% between each other, and 100% and 86% for each respective method to the results of ANOVA. The method developed in this study illustrates the viability of smartphone camera use for identifying positional adjustments due to the inability to control limbs in an adequate range of motion with increasing load during a lifting task.
Quality of Tomato Juice as Influenced by Non-Thermal Air Plasma Treatment
Authors: Starek-Wójcicka Agnieszka , Sagan Agnieszka , Terebun Piotr , Kwiatkowski Michał , Osmólska Emilia , Krajewska Marta , Grządka Elżbieta , Matsuyama Narumol , Hayashi Nobuya , Pawlat Joanna
Published: January 2023

This paper presents the results of an experiment based on using a Glide-arc type plasma reactor operating at atmospheric pressure for the quality of fresh pressed tomato juice, variety Bekas. The impact of after-glow plasma gas (air) on the physicochemical, microbiological properties and morphology of the product’s samples was investigated. Five groups of juices characterized by different exposure times (30, 60, 120, 300 and 600 s), as well as untreated juice (as control) were used. The juice quality was assessed on days 1, 3, 5, and 10 of refrigerated storage. Significant increases were observed when Cold Atmospheric Plasma (CAP)-treated tomato juice was tested against total soluble solids, pH, lycopene, and vitamin C in comparison to the control treatments. Moreover, changes in the tested physicochemical values during the storage of juice subjected to the action of cold plasma did not progress as quickly as in the case of the control juice. A significant decrease was observed in total plate count, yeast, and mold after 300–600 s CAP treatment. The findings of the current study suggested that CAP treatment is a promising technique that could provide improved quality and stability during the processing of tomato juice with better physicochemical properties and bioavailable nutrients.