bluuebunny/crossref_metadata_2025 huggingface dataset:
Mean Platelet Volume Used as a Potential Negative Predictor in Patients with Heart Failure; Hypothesis Based on Statistical Modeling
Authors: Catană Andreea , Andrei Cătălina Liliana , Ceban Octavian , Sinescu Crina Julieta
Published: October 2023

(1) Background: Heart failure (HF) remains one of the most frequent public health problems, with high mortality and hospitalization rates. Identifying an indicator with a prognostic role in patients with HF could represent a salutary solution in the future, as it could identify patients with a negative prognosis. Thus, our study focused on mean platelet volume (MPV) as a possible prognostic factor in patients with HF. (2) Methods: The research was a type of correlational study, which was conducted in a retrospective manner on 260 patients with chronic HF. The statistical analysis assessed whether there was a plausible relationship between the MPV value and several target variables based on a regression model analysis. (3) Results: Using logistic and linear regression models, we estimated the impact of the MPV value on certain events and the probabilities of these events depending on MPV value. The results obtained using regression model analysis were considered statistically significant (α = 0.05) based on a p-value below 0.05. The results showed that patients with class IV NYHA HF or acute pulmonary edema had higher MPV than class II NYHA HF, and that patients with higher MPV had a greater probability of having certain events, represented by 3-month hospitalization, 6-month rehospitalization, 1-year death, and prolonged hospitalization. (4) Conclusions: Using statistical modeling based on regression model analysis, our study showed that certain negative events in HF patients could be predicted based on the MPV value.
Neural Network Learning Algorithms for High-Precision Position Control and Drift Attenuation in Robotic Manipulators
Authors: Mystkowski Arkadiusz , Wolniakowski Adam , Kadri Nesrine , Sewiolo Mateusz , Scalera Lorenzo
Published: October 2023

In this paper, different learning methods based on Artificial Neural Networks (ANNs) are examined to replace the default speed controller for high-precision position control and drift attenuation in robotic manipulators. ANN learning methods including Levenberg–Marquardt and Bayesian Regression are implemented and compared using a UR5 robot with six degrees of freedom to improve trajectory tracking and minimize position error. Extensive simulation and experimental tests on the identification and control of the robot by means of the neural network controllers yield comparable results with respect to the classical controller, showing the feasibility of the proposed approach.
A Poisson Shot Noise Limited MMSE Precoding for Photon-Counting MIMO Systems with Reinforcement Learning
Authors: Li Zihao , Zhou Xiaolin , Wan Chengrui , Du Gang , Wang Yuequan
Published: October 2023

With the development of the Internet of Things (IoT), most communication systems are difficult to implement on a large scale due to their high complexity. Multiple-input multiple-output (MIMO) precoding is a generally used technique for improving the reliability of free-space optical (FSO) communications, which is a key technology in the 6G era. However, traditional MIMO precoding schemes are typically designed based on the assumption of additive white Gaussian noise (AWGN). In this paper, we present a novel MIMO precoding method based on reinforcement learning (RL) that is specifically designed for the Poisson shot noise model. Unlike traditional MIMO precoding schemes, our proposed scheme takes into account the unique statistical characteristics of Poisson shot noise. Our approach achieves significant performance gains compared to existing MIMO precoding schemes. The proposed scheme can achieve the bit error rate (BER) of 10−5 in a strong turbulence channel and exhibits superior robustness against imperfect channel state information (CSI).
Accepting the Digital Challenge: Public Perceptions and Attitudes toward Interactivity in Data Journalism
Authors: Zhang Boning , Zhang Yuxin , Pan Younghwan
Published: October 2023

In the context of digitization, traditional journalism is facing transformation and innovation. Among them, the interactivity of visual graphics in data journalism is crucial for attracting and retaining online users, but few studies have examined public perceptions and attitudes toward it. In this study, we proposed a model to validate the relationship between users’ perceived interactivity and their attitudes toward data journalism, and we included user affective and cognitive factors (enjoyment and engagement) related to this as possible mediating variables in the model for validation. We conducted experiments (n = 75) using data journalism containing map visualizations with three levels of interactivity (low, medium, and high) in China. Furthermore, an exploratory evaluation of the experimental group provided further insights into the differences in interactions between groups, and the emerging five key concepts of data journalism design. Overall, all our hypotheses are supported, with enjoyment and engagement mediating the relationship between perceived interactivity and users’ attitudes toward the news. In addition, the experimental group with higher interaction potential also reported more positive attitudes toward journalism. Therefore, if data journalism and visualization designers want to attract and retain users in the future, enhancing user interaction on news pages will be a proven method.
Prediction and Comparison of In-Vehicle CO2 Concentration Based on ARIMA and LSTM Models
Authors: Han Jie , Lin Han , Qin Zhenkai
Published: October 2023

An increase in the carbon dioxide (CO2) concentration within a vehicle can lead to a decrease in air quality, resulting in numerous adverse effects on the human body. Therefore, it is very important to know the in-vehicle CO2 concentration level and to accurately predict a concentration change. The purpose of this research is to investigate in-vehicle concentration levels of CO2, comparing the accuracy of an autoregressive integrated moving average (ARIMA) model and a long short-term memory (LSTM) model in predicting the change in CO2 concentration. We conducted a field test to obtain in-vehicle original concentration data of CO2 while driving, establishing a prediction model of CO2 concentration with ARIMA and LSTM. We selected mean absolute percentage error (MAPE) and root mean squared error (RMSE) as the evaluation indicators. The findings indicate the following: (1) With the vehicle windows closed and recirculation ventilation mode activated, in-vehicle CO2 concentration increases rapidly. During testing, CO2 accumulation rates were measured at 1.43 ppm/s for one occupant and 3.52 ppm/s for three occupants within a 20 min driving period. Average concentrations exceeded 1000 ppm, so it is recommended to improve ventilation promptly while driving. (2) The MAPE of ARIMA and LSTM prediction results are 0.46% and 0.56%, respectively. The RMSE results are 19.62 ppm and 22.76 ppm, respectively. The prediction results demonstrate that both models effectively forecast changes in a vehicle’s interior environment CO2, but the prediction accuracy of ARIMA is better than that of LSTM. The research findings provide theoretical guidance to traffic safety managers in selecting suitable models for predicting in-vehicle CO2 concentrations and establish an effective in-vehicle ventilation warning control system.
Solid Dispersions of Gefitinib with D-α-Tocopherol Polyethylene Glycol-1000 Succinate and 2-Hydroxypropyl β-Cyclodextrin Complex Improved Their Solubility, Dissolution and Apoptosis against A549 Cells
Authors: Kalam Mohd Abul , Alhowyan Adel Ali , Alhudaithi Sulaiman S. , Khan Mohd Shahnawaz , Alshememry Abdullah K. , Alkholief Musaed
Published: October 2023

This study focuses on the development and characterization of solid dispersions (SDs) of Gefitinib (GEF) to improve its aqueous solubility and therapeutic activity against lung cancer. SDs were prepared by the co-precipitation method with tocopheryl-polyethylene-glycol succinate-1000 (TPGS) (F1), sodium lauryl sulfate (SLS) (F2) and complexation of F1 with hydroxypropyl β-cyclodextrin (HP-β-CD) (F3). Optimal formulations (F1 and F3) were used against A549 cells to determine the apoptosis, expressions of p53 and caspases. F3 has shown the highest solubility (1271.21 µg/mL), followed by F1 (1003.69 µg/mL), F2 (707.81 µg/mL) and GEF pure (303.85 µg/mL) in 0.1N HCl. Dissolution at 1.2 pH significantly enhanced the release from F3 (99.19%), followed by F1 (94.76%), F2 (85.70%) and GEF pure (37.26%) during 120 min. Complexation of GEF–TPGS with HP-β-CD significantly improved drug release with high dissolution efficiency (78.57%) in 24.9 min of mean dissolution time. Differential scanning calorimetry revealed crystalline to amorphous conversion of GEF in SDs, which was confirmed by scanning electron microscopy. Fourier transform infrared and proton nuclear magnetic resonance spectral analysis revealed no interaction between GEF and excipients. The IC50 values were 2.239, 3.135 and 4.471 µM for F3, F1 and GEF pure, respectively, against A549 cells. Increased expressions of p53 (5.9-, 4.6- and 3.04-fold), caspase-3 (5.38-, 3.78- and 3.01-fold) and caspase-9 (5.35-, 3.76- and 2.47-fold) in the case of F3, F1 and GEF pure, respectively, as compared to the untreated A549 cells indicated improved apoptotic potential of the SDs. TPGS SDs and their complexation with HP-β-CD improved the solubility, dissolution and efficacy of GEF against A549 cells. So, they can be a suitable alternative to the conventional GEF formulations against non-small-cell lung cancers.
Deep Learning Logging Sedimentary Microfacies via Improved U-Net
Authors: Cai Hanpeng , Hu Yongxiang , Zhang Liyu , Su Mingjun , Yuan Cheng , Zhao Yuting
Published: October 2023

Well logging data contain abundant information on stratigraphic sedimentology. Artificial identification is usually strongly subjective and time-consuming. Pattern recognition algorithms like SVM may not adequately capture the depth-related variations in logging curve shape. This paper defines logging sedimentary microfacies as unidirectional 2D image segmentation and builds an improved U-net model to meet the requirements of logging sedimentary microfacies acquaintance. The proposed model contains three characteristics: (1) It removes pooling layers to avoid the loss of spatial features; (2) it utilizes multi-scale convolution blocks for mining multi-scale spatial features in logging data; (3) a one dimensional convolution layer is added to achieve deep single-direction segmentation. In this model, a 2D image composed of several standardized logging curves is used as the network’s input. In addition, we propose an effective data enhancement method and calculate the geometric feature attributes of well logging curves to reduce the complexity of the data characteristics. We tested the model on manually annotated validation datasets. Our method automatically measures fine sedimentary microfacies characteristics, improving the accuracy of sedimentary microfacies identification and achieving the desired result. Additionally, the model was tested on unlabeled actual logging data, which shows the generalizability of this deep learning method on different datasets.
Real Fluid Modeling and Simulation of the Structures and Dynamics of Condensation in CO2 Flows Shocked Inside a de Laval Nozzle, Considering the Effects of Impurities
Authors: Bhatia Harshit , Habchi Chaouki
Published: October 2023

Because of the currently changing climate, Carbon Capture and Storage (CCS) is increasingly becoming an important contemporary topic. However, this technique still faces various challenges. For the compression of CO2 to its supercritical condition for efficient transport, one of the important challenges is mastering the two-phase flow in the pump. Indeed, phase changes that appear on the blade tips of an impeller or rotor in such pumps can lead to performance and stability issues. Moreover, these phase change phenomena (vaporization and condensation) can be significantly modified by the presence of impurities (N2, O2, H2S, etc.) whose nature depends on the source of the CO2 production. In this work, we focus on analyzing the high pressure flow behavior of CO2 mixed with varying levels of impurities in a de Laval nozzle, for which experimental results are available. Numerical simulations are performed using a real-fluid model (RFM) implemented in the CONVERGE CFD solver. In this model, a tabulation approach is used to provide the thermodynamic and transport properties of the mixture of CO2 with the impurities. The study is carried out with different inlet conditions, and the results are in good agreement with the available experimental data. In addition, the results provide insights on the interaction of the shock wave with the observed condensation phenomenon, as well as its impact on the amount of condensation and other thermodynamic variables. The research indicates that the presence of impurities mixed with CO2 significantly affects the observed condensation in gas streams, which is a crucial factor that cannot be overlooked when implementing CCS systems.
Research on Multi-Objective Optimization Model of Foundation Pit Dewatering Based on NSGA-II Algorithm
Authors: Ma Zhiheng , Wang Jinguo , Zhao Yanrong , Li Bolin , Wei Yufeng
Published: October 2023

This study focuses on optimizing the foundation pit dewatering scheme using the foundation pit dewatering theory and the principles of multi-objective optimization. It explores the development of a multi-objective optimization model and efficient solution technology for foundation pit dewatering. This research focuses on the foundation pit dewatering project at the inverted siphon section of Xixiayuan canal head, specifically from pile number XZ0+326 to XZ0+500. It establishes an optimized mathematical model for foundation pit dewatering that incorporates three objectives. Additionally, a dewatering optimization program is developed by utilizing the MATLAB optimization toolbox and the multi-objective optimization algorithm program based on the NSGA-II algorithm (Gamultiobj). The multi-objective optimization mathematical model is solved, and a Pareto-optimal solution set with uniform distribution is obtained. The multi-objective optimization evaluation system based on AHP is constructed from the three aspects of dewatering cost, the impact of settlement on the environment, and the safety and stability of the foundation pit. The optimization scheme of the Pareto-optimal solution set is selected as the decision result to provide multiple feasible schemes for the dewatering construction of foundation pits. The optimization scheme is verified by using the GMS software. The simulation results demonstrate that the optimization scheme fulfills the requirements for water level and settlement control. Moreover, the developed optimization program efficiently solves the multi-objective optimization problem associated with foundation pit dewatering. Lastly, an evaluation system incorporating the NSGA-II algorithm and AHP is developed and utilized in the context of dewatering engineering in order to offer multiple viable optimal dewatering schemes.
Shaking Table Testing of Liquefied Soil Layer Located in the Bottom Slab of a Subway Station
Authors: Ming Shi , Tao Lianjin , Wang Zhigang
Published: October 2023

In this study, a shaking table test was conducted to investigate the presence of a liquefied soil layer at a subway station bottom plate. The seismic responses to soil and station structure were investigated by inputting seismic waves of different intensities. The following test results were obtained. As the intensity of the seismic response increases, liquefaction occurs in the soils located at the base of the station. The remainder of the soil liquefies to a lesser degree but still results in soil subsidence and damage to the soils on both sides of the station. In seismic loading conditions, the pore water pressure undergoes a process of “rapid growth and slow dissipation”. As the seismic intensity increases, the main frequency of the soil near the structure develops from a high to a low frequency, and the main frequency of the soil far away from the structure does not change significantly, indicating that the presence of the structure has a significant effect on the working conditions of the soil. The peak acceleration, as well as the peak maximum dynamic strain in the center column of the station, occurs at the bottom of the center column at the platform level, and the maximum dynamic strain in the slab occurs at the bottom slab at the concourse level.
Suitability of Dual-Band, Dual-Polarized Patch Antennas with a Superstrate for the Miniaturization of Ku-Band Antenna Arrays for Automotive Applications
Authors: Francis Roslin , Butt Safwat Irteza , Singh Jasmeet , Guelzow Peter , Eimertenbrink Ralf , Hein Matthias A.
Published: October 2023

The extension of low-earth orbit (LEO) services to non-terrestrial mobile communications has huge potential for eliminating network white spots and providing high-speed, low-latency links with worldwide geographic coverage. State-of-the-art user terminals for mobile platforms are too large for integration into a passenger vehicle. Antenna elements loaded with a dielectric superstrate could potentially lead to a considerable miniaturization of the user terminal. As per link budget calculations, an array with a gain of 27 dBi is necessary to ensure a throughput of 25 Mbps in the downlink at the Ku-band. A conventional array with a gain of 6 dBi per element, assuming a 12 × 12 arrangement with half-wavelength spacing, would require a footprint of 36 λ2 at 10 GHz to achieve this target and appears unsuitable for automotive integration. This paper proposes a low-profile, dual-band, dual-polarized, vertically stacked patch antenna with superstrate loading and shows that the inclusion of the superstrate improves the antenna’s gain by at least 3 dB. Therefore, compared to a conventional array, a superstrate-loaded array would need only half of the number of elements to meet the target gain, thus occupying only half of the surface area, and offers better integration for automotive applications. Requiring half of the number of elements also implies considerably reduced design complexity and cost.
A Study on the Stoichiometry of Casein/Chitosan Gel Complexes as a Delivery System for Quercetin
Authors: Milenkova Sofia , Zahariev Nikolay , Ambrus Rita , Pilicheva Bissera , Marudova Maria
Published: October 2023

As a well-known plant flavanol, quercetin possesses a diverse range of biological properties. These include its ability to act as an antioxidant, reduce inflammation, and exhibit anticancer effects. Consequently, it finds extensive application in numerous models related to wound healing. However, the poor physicochemical characteristics of the molecule (which include low solubility, stability, and permeability) eventually reduce its bioavailability at the targeted sites. A variety of nano formulations with great therapeutic potential have been created in order to get around these obstacles on the way to successful therapy. The current investigation aims to examine the properties of nano- and micro-sized casein/chitosan gel polyelectrolyte complexes (PECs) with respect to their potential for quercetin loading and release. Four different types of hydrogel particles at pH 6 and different casein/chitosan charge ratios were synthesized; namely, 1:1, 2:1, 4:1, and 6:1 in excesses of casein. The attractive electrostatic interactions between the oppositely charged polyelectrolytes were proved by FT-IR spectroscopy. The process yield increased from 37.5% to 72.5% in excesses of casein. The gel particle’s size varied between 377 nm and 5.72 µm depending on the casein/chitosan stoichiometry. The morphology of the obtained gel polyelectrolyte complexes was found to be spherical, based on scanning electron microscopy and atomic force microscopy analysis. The quercetin loading efficiency was above 95% for all investigated hydrogel complexes. Investigation of the physical state of the loaded polyphenol by the differential scanning calorimetry and X-ray powdered diffraction technique suggested the occurrence of partial recrystallization phenomena. The quercetin release test was performed in phosphate buffer (pH 5.5) at 32 °C and permanent stirring at 50 rpm. A zero-order model was used to describe in the best way the release kinetics. The reported casein/chitosan complexes loaded with quercetin may find application in wound healing as a concomitant treatment.
Strengthening Cloud Security: An Innovative Multi-Factor Multi-Layer Authentication Framework for Cloud User Authentication
Authors: Mostafa Ayman Mohamed , Ezz Mohamed , Elbashir Murtada K. , Alruily Meshrif , Hamouda Eslam , Alsarhani Mohamed , Said Wael
Published: October 2023

Cloud multi-factor authentication is a critical security measure that helps strengthen cloud security from unauthorized access and data breaches. Multi-factor authentication verifies that authentic cloud users are only authorized to access cloud apps, data, services, and resources, making it more secure for enterprises and less inconvenient for users. The number of authentication factors varies based on the security framework’s architecture and the required security level. Therefore, implementing a secured multi-factor authentication framework in a cloud platform is a challenging process. In this paper, we developed an adaptive multi-factor multi-layer authentication framework that embeds an access control and intrusion detection mechanisms with an automated selection of authentication methods. The core objective is to enhance a secured cloud platform with low false positive alarms that makes it more difficult for intruders to access the cloud system. To enhance the authentication mechanism and reduce false alarms, multiple authentication factors that include the length, validity, and value of the user factor is implemented with a user’s geolocation and user’s browser confirmation method that increase the identity verification of cloud users. An additional AES-based encryption component is applied to data, which are protected from being disclosed. The AES encryption mechanism is implemented to conceal the login information on the directory provider of the cloud. The proposed framework demonstrated excellent performance in identifying potentially malicious users and intruders, thereby effectively preventing any intentional attacks on the cloud services and data.
An Efficient Maritime Route Planning Method Based on an Improved A* with an Adaptive Heuristic Function and Parallel Computing Structure
Authors: Li Hanlin , Qian Longxia , Hong Mei , Wang Xianyue , Guo Zilong
Published: October 2023

Maritime route planning under minimal-risk conditions plays an important part in the development and utilization of marine resources. High-resolution weather forecasting data places higher demands on the algorithms’ ability to optimize and compute, and existing algorithms are significantly deficient in these aspects. Therefore, we propose a parallel computing-based planning method, segment parallel A* (SPA*), which splits the path into small segments and runs A* separately on CPU cores through a control algorithm. In segment planning, we propose an adaptive heuristic function on A*. It automatically balances the order of magnitude difference between the risk assessment value and the estimated distance, thus significantly reducing the A* expansion useless grid to improve the performance and running speed of the algorithm. Finally, the complete route is obtained by splicing the above segments. In the static planning experiments, the time of SPA* is reduced by about 5~12,425 times compared with 6 traditional and swarm intelligence-based algorithms, i.e., Dijkstra, A*, bidirectional A* (BA*), ant colony optimization (ACO), Harris hawks optimization (HHO), and sparrow search algorithm (SSA). And the abilities to control the risk caused by wind and waves and the comprehensive risk are improved by 7.68%~25.14% and 8.44%~14.38%, respectively; in the dynamic planning experiments, the above results are 4.8~1262.9 times, 3.87%~9.47% and 7.21%~10.36%, respectively. By setting the recommended range of the number of segments for each case, SPA* shows stable performance in terms of the calculation and risk control. SPA* demonstrates a unique structure for using parallel computing in route planning, which is representative and general in both reducing time and improving efficiency.
A Theoretical Method and Model for TBM Tunnelling Trajectory Adjustment
Authors: Wang Ruirui , Zhang Lingli
Published: October 2023

TBM tunnelling trajectory adjustment is a significant issue in guaranteeing a tunnel project. This paper proposes a theoretical method of trajectory adjustment aimed at synchronously reducing bias angle and distance. The proposed method can be divided into three steps. First, the need for manual intervention in the tunnelling trajectory is determined based on the current bias angle and distance. Next, if manual intervention is required, a theoretical relationship is established using the current bias angle and distance as an input and the rotated angle of the TBM main beam as an output. Finally, a series of constraints according to the normal working conditions of the TBM are incorporated into the method. These constraints ensure that the method remains within the acceptable range of TBM operation. Using mechanical parameters such as the cutterhead diameter and cutter spacing of the TBM used in the sixth section of the Qingdao Metro Project, a model suitable for the project is established, and the model is modified by the tunnelling trajectory data collected in the field. This method provides a reference for TBM drivers to use to correct the tunnelling trajectory while considering the specific conditions of the project.
Kinetic, Physiological and Fatigue Level Differences Depending on the Menstrual Cycle Phase and Running Intensity
Authors: Domínguez-Muñoz Carolina , del Campo Juan , García Alberto , Guzmán José , Martínez-Gallego Rafael , Ramón-Llin Jesús
Published: October 2023

Background: Depending on the phase of the menstrual cycle an athlete is in, some kinetic, physiological, and fatigue variables will show differences. The aim of this study is to analyze whether there are changes in these variables over the course of the menstrual cycle. Methods: Eight regularly practicing women runners and triathletes performed a maximal treadmill test and a submaximal test (6′ stages at 50%, 60%, and 80% of maximal aerobic speed) in each of the phases of the menstrual cycle: bleeding phase (day 2.4 ± 0.7), follicular phase (day 10.4 ± 2.2), and luteal phase (day 21.8 ± 2.1). Running dynamics were measured (using RunScribe) at the end of each test, as were lactate concentration, heart rate, and fatigue (evaluated on a scale of 0–5). Results: Higher shock (G) values were recorded in the bleeding phase (η2 = 0.27) and higher vertical spring stiffness (kN/m) was recorded in the follicular phase (η2 = 0.25). The phase of the menstrual cycle had a significant effect on average and peak heart rate, which was significantly higher in the follicular phase (η2 = 0.45 and η2 = 0.48, respectively). Conclusions: Higher vertical spring stiffness was observed in the follicular phase, in addition to higher peak and average heart rate.
Quantification of External Training Load among Elite-Level Goalkeepers within Competitive Microcycle
Authors: Vladovic Jakov , Versic Sime , Foretic Nikola , Morgans Ryland , Modric Toni
Published: October 2023

This study aimed to evaluate the external training load (ETL) of elite-level goalkeepers considering days before match day (MD minus) and playing status in subsequent matches. The ETL of three goalkeepers from the Croatian highest national football competition were analyzed, quantifying goalkeeping-specific physical performance variables (i.e., distances covered, acceleration frequencies, dives, jumps). Data were collected using a 10 Hz global-positioning system and 100 Hz accelerometer technology (Vector G7, Catapult Sports Ltd., Melbourne, Australia) from 67 training sessions. Significant daily differences for almost all physical performance variables were found (all small-to-medium effect sizes (ESs)). Specifically, total distance, total and high-intensity dives, high-intensity accelerations and decelerations, and explosive efforts were greatest on MD-3 and lowest on MD-2 and MD-1. Nonstarters performed more medium jumps on MD-4 (large ES); low jumps on MD-3 (medium ES); total, right-, and left-side dives and low jumps on MD-2 (all small-to-medium ESs); and left-side dives and low and medium jumps on MD-1 (all small-to-medium ESs) compared to the starters. These findings demonstrated that (i) elite-level goalkeepers experienced the greatest ETL on MD-3 and the lowest on MD-2 and MD-1 and that (ii) starters’ and nonstarters’ ETLs were similar on MD-4 and MD-3, while nonstarters compared to the starters presented slightly greater ETLs on MD-2 and MD-1. This study highlighted the differing daily training demands placed on elite-level goalkeepers, offering valuable insights for their preparation.
A Multi-Scale Cross-Fusion Medical Image Segmentation Network Based on Dual-Attention Mechanism Transformer
Authors: Cui Jianguo , Wang Liejun , Jiang Shaochen
Published: October 2023

The U-net network, with its simple and powerful encoder–decoder structure, dominates the field of medical image segmentation. However, convolution operations are limited by receptive fields. They do not have the ability to model long-range dependencies, but Transformer has the capability of long-term modeling thanks to its core self-attention mechanism, which has been widely applied in the field of medical image segmentation. However, both CNNs and Transformer can only perform correlation calculations for a single sample, ignoring the correlation between different samples. To address these problems, we propose a new Transformer, which we call the Dual-Attention Transformer (DAT). This module captures correlations within a single sample while also learning correlations between different samples. The current U-net and some of its variant models have the problem of inadequate feature fusion, so we also improve the skip connection to strengthen the association between feature maps at different scales, reduce the semantic gap between the encoder and decoder, and further improve the segmentation performance. We refer to this structure as DATUnet. We conducted extensive experiments on the Synapse and ACDC datasets to validate the superior performance of our network, and we achieved an average DSC (%) of 83.6 and 90.9 and an average HD95 of 13.99 and 1.466 for the Synapse and ACDC datasets, respectively.
Risk Interdependency Network Model for the Cost and Time of Pile Installation in Saudi Arabia, Using Partial Least Squares Structural Equation Modeling
Authors: Alsanabani Naif M. , Al-Gahtani Khalid S. , Almohsen Abdulmohsen S. , Alsharef Abdullah
Published: October 2023

Pile construction projects cause significant time and expense overruns. The pile installation activity is the primary reason for project underperformance and uncertainties. Additionally, the risks associated with pile installation are mostly considered independent in the overall risk management process, leading to inadequate risk assessment and response. However, few studies have evaluated the risks associated with pile installation. Thus, this study aims to establish the risks of the time and cost of pile installation, using an interdependency network model with a particular emphasis on sand and rocky terrain conditions. In addition, this study introduces a new method for establishing a model that considers the interrelationships among risks via a partial least squares structural equation model (PLS-SEM). The research methodology involves assessing the probability and impact of 53 risk factors of pile installation time and cost. Twelve pile construction experts participated in this assessment. Then, a Monte Carlo Simulation was utilized before the data were integrated into the PLS-SEM. The research findings reveal that the site and economic risks indirectly affect the cost of installing pile in sand through construction risks. Also, the risk group comprising site and equipment risks indirectly affects the cost of installing pile in rock through design risks. This study’s findings will help construction organizations to improve time and cost risk assessments for pile installation projects.
Multi-Axis Laser Interferometer Not Affected by Installation Errors Based on Nonlinear Computation
Authors: Wen Tingrui , Hu Jinchun , Zhu Yu , Hua Guojie
Published: October 2023

Most multi-axis laser interferometers require accurate installation of the lasers and detectors since the position and orientation installation errors of lasers and detectors bring measurement error to the interferometer. In this paper, the multi-axis interferometer based on nonlinear computation is proposed, which avoids the measurement error caused by installation errors by taking the laser position and orientation as unknowns into the measurement model and discussing the solution component uniqueness of a nonlinear equation system. The simulation results show that even when the installation errors are close to 1 μm and 1 μrad, the proposed interferometer can still measure the multi-degree-of-freedom displacement accurately, and the root mean standard error (RMSE) of displacement is 1.884 nm and 5.871 × 10−7 mrad under a reading noise level of 0.1 nm.
Research on the Optimization of Open-Pit Mine Cast Blasting Parameters Based on the Optimal Economy of Dragline Stripping Technology
Authors: Zhang Zhao , Zhang Ruixin , Sun Jiandong
Published: October 2023

As the key technology of high-step stripping and blasting engineering, throwing blasting will be the development trend of the production optimization and benefit maximization of the open-pit mine in the future. In order to break with the research idea of optimizing the cast blasting effect by improving the effective throwing rate for a long period of time, maximizing the economic benefit of the subsequent dragline stripping technology and stabilizing the engineering connection, this paper takes the Heidaigou open-pit mine as the research object. Through data acquisition, analysis, and data fusion of the heaped-up bulk characteristics, the heaped-up bulk profile can be obtained to characterize the cast blasting effect. Secondly, the key factors influencing the cast blasting effect are determined based on the gray relational degree theory. Then, the black box principle of the system control theory is adopted as the guiding principle of the blasting optimization. Based on the production data of field cast blasting, the dynamic change law between the controllable variables of system input and the observable variables of system feedback in the black box system are studied and explored without consideration of the internal structure or the energy transformation relationship of the cast blasting system. Finally, the optimal blasting parameter combination under different working conditions is obtained. If the research results are successfully applied, it is expected that the dragline stripping technology cost of the Heidaigou open-pit mine can be reduced by 5~10%, and the results can also provide new ideas and new ways of optimizing the design of cast blasting.
Optimizing Size Consistency in Batch Roller Production: A Mixed Strategy Approach
Authors: Liu Weifeng , Ren Chengzu
Published: October 2023

The Double-Disk Straight Groove Lapping (DDSGL) technique, a novel approach to batch processing of bearing rollers, achieves high dimensional consistency by removing material through size comparison between multiple rollers in the processing area. To avoid collision between the rollers, the prevalent practice in DDSGL involves circulating the rollers in fixed linear sequences, an approach that impedes comprehensive size comparison throughout the entire batch of rollers. To counter this, we introduce a Dual-Channel Mixing Scheduling (DCMS) strategy that disrupts the roller sequence without triggering collisions. This strategy promotes extensive size comparison and enhances batch size consistency. To elucidate the operational principles of DCMS, we have developed a computational model grounded in DDSGL, designed simulation test plans under different mixing parameters, and summarized the number of direct comparisons, total comparisons, and differences in roller cycle times to determine the optimal combination of mixing parameters. Finally, structural modifications were made in the DDSGL system for validation studies under different mixing parameters. The test results show that the use of DCHS can reduce processing time by up to 50%, and the batch diameter change of the rollers can converge from 1.15 μm to as low as 0.76 μm. The industrial relevance of this research is significant; these improvements can lead to higher efficiency in the manufacturing process and improved quality of bearing rollers.
Advancing Urban Wastewater Management: Optimizing Sewer Performance through Innovative Material Selection for the Armlet with a Wet Circuit Measurement System
Authors: Sionkowski Tomasz , Halecki Wiktor , Chmielowski Krzysztof
Published: October 2023

Rainwater infiltration presents substantial challenges for urban wastewater management systems. This article delves into enhancing the quality of wastewater systems by proposing a novel device designed to tackle this issue comprehensively. The focal point of our research revolves around the conceptualization, construction, rigorous testing, and the potential multifaceted applications of this innovative wastewater device. Our study is dedicated to assessing the viability of a cutting-edge apparatus that empowers municipal entities in swiftly identifying rainwater ingress points within channels during precipitation events. Our findings vividly showcase the device’s remarkable capability to directly measure moisture levels along the channel’s path, eliminating the arduous need for manual data input, extensive data collection, and intricate water analysis procedures. To ensure the seamless flow of both sewage and water within the sewer channel, the use of a relatively slender strap is conventionally favored. However, factoring in the requisite structural robustness, we recommend a minimum thickness of 4 mm for 3D printing applications. For instances where maintaining the channel’s cross-sectional area integrity is paramount, opting for an armlet with a wet circuit measurement thickness of up to 7 mm is vital. In the realm of material selection, our investigation advocates for the utilization of PC/ABS (polycarbonate/Acrylonitrile Butadiene Styrene), ABS, ASA (Acrylonitrile Styrene Acrylate), or HIPS (High Impact Polystyrene) for strap housing. For sewer diameters surpassing 315 mm, the application of thin-walled PVC (Poly Vinyl Chloride) emerges as a practical recommendation. Notably, the incorporation of PVC flat bars is discouraged, as their presence might potentially hinder the fluidity of sewage flow, thereby compromising the precision of wet circuit measurements. The pivotal innovation lies in the armlet with a wet circuit measurement system, harboring immense potential for broad-scale integration across municipal facilities. This solution emerges as a streamlined and efficient strategy, offering a comprehensive avenue for continuously monitoring, fine-tuning, and optimizing the structural soundness and operational efficacy of sewer systems.
Advances in Riblets Design
Authors: Pakatchian Mohammad Reza , Rocha Joana , Li Lucy
Published: October 2023

Continuous evolution in nature has created optimum solutions for creature survival that have inspired many innovative engineering designs. Riblet geometries, passive flow control devices, have been studied, which were inspired by the skin of fast-swimming sharks. Turbulent boundary layer research reveals the positive effect of riblets in reducing drag by manipulating turbulent structures. Reducing drag is an important topic for the aviation industry, as it directly relates to fuel savings and reductions in carbon footprints. Aircraft noise represents another significant area of concern. When riblet designs modify turbulent structures, they can also impact pressure sources within the boundary layer, consequently influencing the generation of self-noise. Earlier research studies have demonstrated the favorable outcomes of riblet configurations on the variations in wall pressure, resulting in reduced levels of noise propagation. The current review paper is mainly devoted to the application of riblets in the aviation industry, focusing on studies that are performed in wind tunnels, flight tests, and using numerical techniques. Proving the desired performance of micro-grooves, their method of fabrication and implementation on aircraft surfaces are important topics that are also discussed. In addition, the effect of durability on the performance and required maintenance intervals was previously investigated and is also presented. Finally, recommendations for future activities in the relevant fields of study are provided.
Cyclic Degradation Parameters of Flow-Controlled Geomaterial for Pile Group Subjected to Torsional Loads
Authors: Mehra Sagar , Trivedi Ashutosh
Published: October 2023

The pile groups support large foundation structures which often experience cyclic torsional loads. Several theoretical and experimental investigations were carried out on pile groups under axial and lateral cyclic loads; however, the study of the response of cyclic torsional loads on pile foundation groups remains elusive. This paper proposes a numerical scheme to capture the behavior of the symmetrical pile group in the flow-controlled geomaterial under cyclic torsional loading. Based on the numerical scheme, three-dimensional finite element analysis was performed to capture the nonlinear response of the pile group using a computational program. The results from the numerical analysis have been compared with the experimental observations. The peak twist and peak shear stress logarithmically decrease and then become asymptotic after a number of cycles of loading for a pile group (2,2) in a flow-controlled geomaterial. A set of cyclic degradation parameters of flow-controlled geomaterial is identified for the pile group and presented as a function of dilation.
Analysis of Peak Ground Acceleration and Seismogenic Fault Characteristics of the Mw7.8 Earthquake in Turkey
Authors: Duan Yushi , Bo Jingshan , Peng Da , Li Qi , Wan Wei , Qi Wenhao
Published: October 2023

A Mw7.8 earthquake struck Turkey on 6 February 2023, causing severe casualties and economic losses. This paper investigates the characteristics of strong ground motion and seismogenic fault of the earthquake. We collected and processed the strong ground motion records of 379 stations using Matlab, SeismoSignal, and Surfer software: Matlab (Version R2016a), SeismoSignal (Version 5.1.0), and Surfer (Version 23.0.15), and obtained the peak ground acceleration (PGA) contour map. We analyzed the near-fault effect, the fault locking segment effect, and the trampoline effect of the earthquake based on the spatial distribution of PGA, the fault geometry, and slip distribution. We found that the earthquake generated a very strong ground motion concentration effect in the near-fault area, with the maximum PGA exceeding 2000 cm/s2. However, the presence of fault locking segments influenced the spatial distribution of ground motion, resulting in four significant PGA high-value concentration areas at a local dislocation, a turning point, and the end of the East Anatolian Fault. We also revealed for the first time the typical manifestation of the trampoline effect in this earthquake, which was characterized by a large vertical acceleration with a positive direction significantly larger than the negative direction. This paper provides an important reference for understanding the seismogenic mechanism, damage mode, characteristics, and strong earthquake law of the Turkey earthquake.
Optimization of Coverage and Capacity Using Smart Antennae
Authors: Ho Min-Che , Song Pin-Yu , Chiou Yi-Shian , Lee Yueh-Tan , Huang Li-Ling
Published: October 2023

In the rural and geographically remote regions of Taiwan, the high cost of establishing information infrastructure has resulted in significantly lower internet penetration and usage rates compared with urban areas. To address the network demands in such remote mountainous areas, the deployment of multiple mobile base stations has become essential. However, the wireless implementation of base stations can lead to signal interference issues. This research aims to enhance the signal reception capabilities of end-user devices by utilizing intelligent directional antennas. This study employs five directional smart antennas, each of which can be independently adjusted to be active or inactive. Unlike traditional omnidirectional antennas that cause interference in overlapping coverage areas for end-user devices, our proposed adaptive directional antenna algorithm optimizes energy consumption by selectively activating directional antennas and concurrently reduces signal interference problems for end-user devices. The results of this research offer valuable insights for improving network connectivity and efficiency in remote and underserved areas. Through experimental simulations conducted in an environment with 10 base stations per square kilometer, the utilization of smart antennas, as opposed to omnidirectional antennas, results in a significant improvement of 33.8% in signal coverage.
The Role of Ultrasound Guidance in Mini-Invasive Musculoskeletal Surgery—A Pictorial Essay
Authors: Paczesny Łukasz , Lorkowski Matthias , Pielak Tomasz , Wójcicki Rafał , Huri Gazi , Zabrzyński Jan
Published: October 2023

In this article, the authors review the role of ultrasound guidance in MSK mini-invasive surgery. Ultrasound imaging has become an important tool in the field of musculoskeletal examination and has advantages over the X-ray guidance traditionally used by orthopaedic surgeons. Ultrasound provides the 3D localization of the area where the instruments are being used, does not require X-ray’s certified personnel, and poses less of a health risk to the patient and the medical staff. This article explores the development and application of ultrasound navigation in mini-invasive surgery, including the use of ultrasound during different stages of arthroscopic procedures or for the entire operation. Ultrasounds can assist in setting access points around the joint, localize the pathology and assure its complete resection, identify vessels and nerves, establish access to and constant control of difficult operating areas with a high potential for neurovascular complications. In this paper, the authors also acknowledge that there are some disadvantages, including the need for additional equipment and personnel, a long learning curve, and the potential elongation of the procedure. To identify all of the essential studies that report relevant information and data concerning the ultrasounds navigation in mini-invasive MSK surgery, an extensive search of the major and significant electronic databases was performed by two authors. An investigation was conducted in January 2023 using the following key terms: ultrasounds navigation, ultrasounds in arthroscopy, ultrasounds in MSK, with no limits regarding the year of publication. The authors focused both on the advantages and disadvantages of ultrasound navigation in MSK mini-invasive surgery, and also on particular techniques in mini-invasive and arthroscopic surgeries. The described techniques are the application of ultrasound in arthroscopy (knee, hip, and shoulder), hallux rigidus surgery, mini-invasive Achilles tendon surgery, gastrocnemius recession, carpal tunnel release, and hematoma evacuation.