bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel Pattern Recognition based Kick Detection Method for Offshore Drilling Gas Kick and Overflow Diagnosis
Authors: Xu Yang , Yang Jin , Hu Zhiqiang , Xu Dongsheng , Li Lei , Fu Chao
Published: July 2023

In offshore drilling, accidents such as gas invasion, overflow, and kicks are unavoidable, and they can escalate into blowouts and other catastrophic events, resulting in casualties and significant economic losses. Therefore, ensuring drilling safety requires precise monitoring of gas invasion and overflow. Currently, most overflow monitoring methods used at drilling sites are based on threshold criteria. However, the monitoring parameters obtained during actual drilling operations often contain noise signals, which makes it challenging for threshold-based methods to achieve a balance between improving accuracy and minimizing false positives. This paper proposes a novel method called Pattern-Recognition-based Kick Detection (PRKD) for diagnosing overflow in offshore drilling. The PRKD method utilizes the overflow evolution process by integrating multiphase flow calculations, data filtering theory, pattern recognition theory, the Bayesian framework, and other theoretical models. By analyzing the shape and wave characteristics of the curves, PRKD effectively detects and monitors gas intrusion and overflow based on single parameters. Through case analysis, it is demonstrated that the proposed method achieves high precision in monitoring drilling overflow while maintaining a low false positive rate. By combining advanced computational techniques with pattern recognition algorithms, PRKD improves the accuracy and reliability of kick detection, enabling proactive responses to potential risks, protecting the environment and human lives, and optimizing drilling operations. The case analysis shows that by integrating the probabilistic information of pre-drilling kicks and various characteristic parameters, when the noise amplitude is less than 8 L/s, the PRKD model exhibits superior detection performance. Moreover, when the noise amplitude is 16 L/s, the PRKD model detects the continuous overflow approximately 200 s after the actual overflow occurs and predicts a 95.8% probability of overflow occurrence at the specified location, meeting the on-site requirements. The gas invasion monitoring method proposed in this paper provides accurate diagnostic results and a low false positive rate, offering valuable guidance for gas invasion monitoring in drilling operations.
Dependence of the Bidirectional Reflectance Distribution Function Factor ƒ′ on the Particulate Backscattering Ratio in an Inland Lake
Authors: Zhang Yu , Zhang Lifu , Huang Changping , Cen Yi , Tong Qingxi
Published: July 2023

The bidirectional reflectance distribution function (BRDF) factor ƒ′ provides a bridge between the inherent and apparent optical properties (IOPs and AOPs) of inland waters. The previous BRDF studies focused on ocean waters, while few studies examine inland waters. It is meaningful to improve the theory of remote sensing of water surface and the accuracy of image derivation in inland waters. In this study, radiative transfer simulation was applied to calculate the ƒ′ values using appropriate IOPs based on in situ combined with realistic boundary conditions (N = 11,232). This study shows that ƒ′ factor varied over the range of 0.33–16.64 in Lake Nansihu, a finite depth water, higher than the range observed for the ocean (0.3–0.6). Our results demonstrate that the factor ƒ′ depends on not only solar zenith angle (θs) but also the average number of collisions (n−) and particulate backscattering ratio (b~bp). The ƒ′ factor shows a continuous geometric increase as the solar zenith angle increases at 400–650 nm but is relatively insensitive to solar angle in the 650–750 nm range in which ƒ′ increases as b~bp and n− decreases. To account for these findings, two empirical models for ƒ′ factor as a function of θs, n− and b~bp are proposed in various spectral wavelengths for Lake Nansihu waters. Our results are crucial for obtaining Hyperspectral normalized reflectance or normalized water-leaving radiance and improving the accuracy of satellite products.
Real-Time Semantics-Driven Infrared and Visible Image Fusion Network
Authors: Zheng Binhao , Xiang Tieming , Lin Minghuang , Cheng Silin , Zhang Pengquan
Published: July 2023

This paper proposes a real-time semantics-driven infrared and visible image fusion framework (RSDFusion). A novel semantics-driven image fusion strategy is introduced in image fusion to maximize the retention of significant information of the source image in the fusion image. First, a semantically segmented image of the source image is obtained using a pre-trained semantic segmentation model. Second, masks of significant targets are obtained from the semantically segmented image, and these masks are used to separate the targets in the source and fusion images. Finally, the local semantic loss of the separation target is designed and combined with the overall structural similarity loss of the image to instruct the network to extract appropriate features to reconstruct the fusion image. Experimental results show that the RSDFusion proposed in this paper outperformed other comparative methods on both subjective and objective evaluation of public datasets and that the main target of the source image is better preserved in the fusion image.
Accuracy Improvement of a Compact 85Rb Atom Gravimeter by Suppressing Laser Crosstalk and Light Shift
Authors: Ge Guiguo , Chen Xi , Li Jinting , Zhang Danfang , He Meng , Wang Wenzhang , Zhou Yang , Zhong Jiaqi , Tang Biao , Fang Jie , Wang Jin , Zhan Mingsheng
Published: July 2023

We design and implement a compact 85Rb atom gravimeter (AG). The diameter of the sensor head is 35 cm and the height is 65 cm; the optical and electronic systems are installed in four standard 3U cabinets. The measurement accuracy of this AG is improved by suppress laser crosstalk and light shift. In addition, the angle of the Raman laser reflector is adjusted and locked, and the attitude of the sensing head is automatically adjusted, and the vibration noise is also compensated. The comparison measurement results between this AG and the superconducting gravimeter indicate that its long-term stability is 0.65 μGal @50000 s.
Algorithmic Approach to Virtual Machine Migration in Cloud Computing with Updated SESA Algorithm
Authors: Kaur Amandeep , Kumar Saurabh , Gupta Deepali , Hamid Yasir , Hamdi Monia , Ksibi Amel , Elmannai Hela , Saini Shilpa
Published: July 2023

Cloud computing plays an important role in every IT sector. Many tech giants such as Google, Microsoft, and Facebook as deploying their data centres around the world to provide computation and storage services. The customers either submit their job directly or they take the help of the brokers for the submission of the jobs to the cloud centres. The preliminary aim is to reduce the overall power consumption which was ignored in the early days of cloud development. This was due to the performance expectations from cloud servers as they were supposed to provide all the services through their services layers IaaS, PaaS, and SaaS. As time passed and researchers came up with new terminologies and algorithmic architecture for the reduction of power consumption and sustainability, other algorithmic anarchies were also introduced, such as statistical oriented learning and bioinspired algorithms. In this paper, an indepth focus has been done on multiple approaches for migration among virtual machines and find out various issues among existing approaches. The proposed work utilizes elastic scheduling inspired by the smart elastic scheduling algorithm (SESA) to develop a more energy-efficient VM allocation and migration algorithm. The proposed work uses cosine similarity and bandwidth utilization as additional utilities to improve the current performance in terms of QoS. The proposed work is evaluated for overall power consumption and service level agreement violation (SLA-V) and is compared with related state of art techniques. A proposed algorithm is also presented in order to solve problems found during the survey.
Group Method of Data Handling Using Christiano–Fitzgerald Random Walk Filter for Insulator Fault Prediction
Authors: Stefenon Stefano Frizzo , Seman Laio Oriel , Sopelsa Neto Nemesio Fava , Meyer Luiz Henrique , Mariani Viviana Cocco , Coelho Leandro dos Santos
Published: July 2023

Disruptive failures threaten the reliability of electric supply in power branches, often indicated by the rise of leakage current in distribution insulators. This paper presents a novel, hybrid method for fault prediction based on the time series of the leakage current of contaminated insulators. In a controlled high-voltage laboratory simulation, 15 kV-class insulators from an electrical power distribution network were exposed to increasing contamination in a salt chamber. The leakage current was recorded over 28 h of effective exposure, culminating in a flashover in all considered insulators. This flashover event served as the prediction mark that this paper proposes to evaluate. The proposed method applies the Christiano–Fitzgerald random walk (CFRW) filter for trend decomposition and the group data-handling (GMDH) method for time series prediction. The CFRW filter, with its versatility, proved to be more effective than the seasonal decomposition using moving averages in reducing non-linearities. The CFRW-GMDH method, with a root-mean-squared error of 3.44×10−12, outperformed both the standard GMDH and long short-term memory models in fault prediction. This superior performance suggested that the CFRW-GMDH method is a promising tool for predicting faults in power grid insulators based on leakage current data. This approach can provide power utilities with a reliable tool for monitoring insulator health and predicting failures, thereby enhancing the reliability of the power supply.
Knowledge Development Trajectory of the Internet of Vehicles Domain Based on Main Path Analysis
Authors: Hsieh Tang-Min , Chen Kai-Ying
Published: July 2023

The Internet of vehicles (IoV) is an Internet-of-things-based network in the area of transportation. It comprises sensors, network communication, automation control, and data processing and enables connectivity between vehicles and other objects. This study performed main path analysis (MPA) to investigate the trajectory of research regarding the IoV. Studies were extracted from the Web of Science database, and citation networks among these studies were generated. MPA revealed that research in this field has mainly covered media access control, vehicle-to-vehicle channels, device-to-device communications, layers, non-orthogonal multiple access, and sixth-generation communications. Cluster analysis and data mining revealed that the main research topics related to the IoV included wireless channels, communication protocols, vehicular ad hoc networks, security and privacy, resource allocation and optimization, autonomous cruise control, deep learning, and edge computing. By using data mining and statistical analysis, we identified emerging research topics related to the IoV, namely blockchains, deep learning, edge computing, cloud computing, vehicular dynamics, and fifth- and sixth-generation mobile communications. These topics are likely to help drive innovation and the further development of IoV technologies and contribute to smart transportation, smart cities, and other applications. On the basis of the present results, this paper offers several predictions regarding the future of research regarding the IoV.
Research on Intelligent Monitoring of Boring Bar Vibration State Based on Shuffle-BiLSTM
Authors: Liu Qiang , Li Dingkun , Ma Jing , Bai Zhengyan , Liu Jiaqi
Published: July 2023

Due to its low stiffness, the boring bar used in deep-hole-boring is prone to violent vibration during the cutting process. It is often inaccurate and inefficient to judge the vibration state of the boring bar through artificial experience. To detect the change of the vibration state of the boring bar over time, guide the adjustment of the processing parameters, and avoid wastage of the workpiece and the loss of equipment, it is particularly important to intelligently monitor the vibration state of the boring bar during processing. In this paper, the boring bar is taken as the research object, and an intelligent monitoring technology of the boring bar’s vibration state based on deep learning is proposed. Based on grouping convolution, channel shuffle, and BiLSTM, a shuffle-BiLSTM NET model is constructed, which is both lightweight and has a high classification accuracy. The boring experiment platform is built, and 192 groups of cutting experiments are carried out. The three-way acceleration and sound pressure signals are collected, and the signals are processed by smoothed pseudo-Wigner–Ville distribution. The original signals are transformed into a 256 × 256 × 3 matrix obtained by a two-dimensional time–frequency spectrum diagram. The matrix is input into the model to recognize the boring bar’s vibration state. The final classification accuracy is 91.2%. A variety of typical deep learning models are introduced for performance comparison, which proves the superiority of the models and methods used in this paper.
A Multimode 28 GHz CMOS Fully Differential Beamforming IC for Phased Array Transceivers
Authors: Bhatta Ayush , Park Jeongsoo , Baek Donghyun , Kim Jeong-Geun
Published: July 2023

A 28 GHz fully differential eight-channel beamforming IC (BFIC) with multimode operations is implemented in 65 nm CMOS technology for use in phased array transceivers. The BFIC has an adjustable gain and phase control on each channel to achieve fine beam steering and beam pattern. The BFIC has eight differential beamforming channels each consisting of the two-stage bi-directional amplifier with a precise gain control circuit, a six-bit phase shifter, a three-bit digital step attenuator, and a tuning bit for amplitude and phase variation compensation. The Tx and Rx mode overall gains of the differential eight-channel BFIC are around 11 dB and 9 dB, respectively, at 27.0–29.5 GHz. The return losses of the Tx mode and Rx mode are >10 dB at 27.0–29.5 GHz. The maximum phase of 354° with a phase resolution of 5.6° and the maximum attenuation of 31 dB, including the gain control bits with an attenuation resolution of 1 dB, is achieved at 27.0–29.5 GHz. The root mean square (RMS) phase and amplitude errors are <3.2° and <0.6 dB at 27.0–29.5 GHz, respectively. The chip size is 3.0 × 3.5 mm2, including pads, and Tx mode current consumption is 580 mA at 2.5 V supply voltage.
On the Angular Control of Rotating Lasers by Means of Line Calculus on Hyperboloids
Authors: Penne Rudi , De Boi Ivan , Vanlanduit Steve
Published: July 2023

We propose a new paradigm for modelling and calibrating laser scanners with rotation symmetry, as is the case for lidars or for galvanometric laser systems with one or two rotating mirrors. Instead of bothering about the intrinsic parameters of a physical model, we use the geometric properties of the device to model it as a specific configuration of lines, which can be recovered by a line-data-driven procedure. Compared to universal data-driven methods that train general line models, our algebraic-geometric approach only requires a few measurements. We elaborate the case of a galvanometric laser scanner with two mirrors, that we model as a grid of hyperboloids represented by a grid of 3×3 lines. This provides a new type of look-up table, containing not more than nine elements, lines rather than points, where we replace the approximating interpolation with exact affine combinations of lines. The proposed method is validated in a realistic virtual setting. As a collateral contribution, we present a robust algorithm for fitting ruled surfaces of revolution on noisy line measurements.
Smartphone User Identification/Authentication Using Accelerometer and Gyroscope Data
Authors: Al-Mahadeen Eyhab , Alghamdi Mansoor , Tarawneh Ahmad S. , Alrowaily Majed Abdullah , Alrashidi Malek , Alkhazi Ibrahim S. , Mbaidin Almoutaz , Alkasasbeh Anas Ali , Abbadi Mohammad Ali , Hassanat Ahmad B.
Published: July 2023

With the increasing popularity of smartphones, user identification has become a critical component to ensure security and privacy. This study looked into how smartphone sensors’ data can be utilized to identify/authenticate users and gives suggestions for the best application components. A public smartphone dataset was used to train a deep learning algorithms, conventional classifiers, and voting classifiers, which were then used to identify the users. Feature selection and Pre-processing techniques were investigated to improve the performance. According to the results, Recursive Feature Elimination beat the other feature-selection approaches, and Long Short-Term Memory (LSTM) had the best identification performance, as evidenced by a relatively large number of machine learning performance metrics. Even with a larger number of users, the proposed identification system performed well and outperformed existing approaches, which were primarily designed and tested on the same public smartphone dataset. In terms of user authentication, this study compared the effectiveness of accelerometer data against gyroscope data. According to the findings, the accelerometer data surpassed the gyroscope data in the authentication process. Notably, the study revealed that employing LSTM to combine the accelerometer and gyroscope data resulted in near-perfect user authentication. The insights gained from this study help to develop user identification and authentication approaches that employ smartphone accelerometer data.
Prospects of Mortality Salience for Promoting Sustainable Public Sector Management: A Survey Experiment on Public Service Motivation
Authors: Liu Zhanyu , Ma Zishu , Lei Yuqiong
Published: July 2023

The United Nations has established 17 Sustainable Development Goals (SDGs) as a global initiative to achieve a more sustainable future. Within these goals, SDG16 emphasizes the significance of sustainable public sector management, which profoundly influences the accomplishment of other SDGs. Enhancing public service motivation is a critical element in advancing sustainable public sector management. This study explores the potential of mortality salience as an intervention to bolster public service motivation, aiming to provide valuable insights for SDG16. Specifically, the study investigates the varied effects of mortality salience on public service motivation using a survey experiment and employs machine learning techniques. The findings reveal a significant positive impact of mortality salience on public service motivation. Furthermore, this study highlights that this impact is more prominent in organizations characterized by high levels of servant leadership and extrinsic rewards, as well as low levels of organization-based self-esteem. These findings have practical implications for fostering sustainable public sector management in the post-COVID-19 pandemic era.
An Experimental Approach to Investigating Quasi-Saturation Using Darcy’s Law
Authors: Avzalshoev Zafar , Uchimura Taro
Published: July 2023

Recent trends in abnormal weather patterns leading to sudden and localized heavy rainfall have resulted in an increased frequency of surface landslides. As a result, there is a pressing need for improved prediction and early warning systems. This research focuses on understanding soil behavior under quasi-saturation and elucidating its relationship with pore water pressure and the hydraulic head. In the present study, a mathematical model is formulated to characterize the complex dynamics of quasi-saturation based on established principles. The model demonstrates the correlation between volumetric water content and pore water pressure, considering the influence of the hydraulic gradient. Through two comprehensive model tests, empirical data are generated that highlight the intricate factors influencing quasi-saturation. The findings of this study emphasize the complex interrelationship between volumetric water content, pore water pressure, and the hydraulic head. It is worth noting that under quasi-saturation conditions, the volumetric water content may stabilize over time, indicating an equilibrium between water flow rates driven by the hydraulic gradient and pore water pressure. The present study offers new insights into soil moisture dynamics and lays the foundation for advancements in landslide prediction and mitigation strategies.
Green Energy Generated in Single-Chamber Microbial Fuel Cells Using Tomato Waste
Authors: Rojas-Flores Segundo , De La Cruz-Noriega Magaly , Cabanillas-Chirinos Luis , Benites Santiago M. , Nazario-Naveda Renny , Delfín-Narciso Daniel , Gallozzo-Cardenas Moisés , Diaz Félix , Murga-Torres Emzon , Rojas-Villacorta Walter
Published: July 2023

This research used tomato waste as a substrate (fuel) in Single Chamber-Microbial Fuel Cells (scMFC) on a small scale. The electrochemical properties were monitored, the functional groups of the substrate were analyzed by Fourier Transform Infrared Spectrophotometry (FTIR) and a microbiological analysis was performed on the electrodes in order to identify the microorganisms responsible for the electrochemical process. The results show voltage peaks and an electrical current of 3.647 ± 0.157 mA and 0.957 ± 0.246 V. A pH of 5.32 ± 0.26 was measured in the substrate with an electrical current conductivity of 148,701 ± 5849 mS/cm and an internal resistance (Rint) of 77. 517 ± 8.541 Ω. The maximum power density (PD) displayed was 264.72 ± 3.54 mW/cm2 at a current density (CD) of 4.388 A/cm2. On the other hand, the FTIR spectrum showed a more intense decrease in its peaks, with the compound belonging to the phenolic groups being the most affected at 3361 cm−1. The micrographs show the formation of a porous biofilm where molecular identification allowed the identification of two bacteria (Proteus vulgaris and Proteus vulgaris) and a yeast (Yarrowia lipolytica) with 100% identity. The data found show the potential of this waste as a source of fuel for the generation of an electric current in a sustainable and environmentally friendly way, generating in the near future a mechanism for the reuse of waste in a beneficial way for farmers, communities and agro-industrial companies.
Design of an Equipped Vehicle for In Situ Road Lighting Measurement
Authors: Chen Cheng-Hsien , Hsu Shau-Wei , Yang Tsung-Hsun , Sun Ching-Cherng
Published: July 2023

Sustainable road lighting aims to minimize energy consumption and reduce carbon emissions. Road lighting assessment helps evaluate the energy efficiency of lighting systems, including the selection of appropriate lighting fixtures, efficient lamp technologies (such as LED), and lighting control strategies. Assessments can identify areas for improvement and guide the implementation of energy-saving measures. This study introduces a new technology that utilizes a specially equipped vehicle to efficiently and quickly measure photometric quantities on long, illuminated roads. The measurement ranges for illuminance and luminance are (0.1 to 1000) lx and (0.1 to 100) cd/m2, respectively. The equipped vehicle has a positioning resolution of less than 1 cm. A sampling distance of less than 2 m while traveling at a speed of approximately 20 km/h and a sampling rate of 3 samples/s. To test the system’s applicability, the road used in this study was slightly sloped and curved. The results indicate a strong correlation between the illuminance distributions measured by the new method and those measured by traditional methods, thereby confirming the effectiveness of this innovative approach.
Transitioning to Smart Cities in Gulf Cooperation Council Countries: The Role of Leadership and Organisational Culture
Authors: Mutambik Ibrahim , Lee John , Almuqrin Abdullah , Zhang Justin Zuopeng
Published: July 2023

The concept of Society 5.0, first introduced by Japan in 2016, has become a widely accepted model for the development of social infrastructures across the world. It is a model which is expected to take root globally over the next few years. It is also a model which has smart cities, which are connected and inclusive, at its core. The role of open data is critical to smart cities, and the ability to design and implement strategies for its use is a crucial element in their growth and success. This requires a leadership and organisational culture that embraces the concept of open government data (OGD) and understands its key role in the development of smart cities. In this paper, we examine how the leadership and organisational culture in Gulf Cooperation Council (GCC) Countries has impacted the progress of OGD initiatives and, therefore, the transition to smart cities. This is approached via a re-analysis of data from an earlier study in which semi-structured interviews were used to understand the views and attitudes of a range of senior government department personnel in OGD-related roles, where here a new thematic analysis seeks to identify clearer pointers to attitudes and practices directly relating to smart cities and Society 5.0. The focus on internal factors, such as leadership attitudes and organisational culture, as opposed to external factors, such as technology and resources, differentiates this research from previous studies and adds to our current knowledge. The findings lead to a discussion that identifies a likely gap in the leadership provided by more senior figures. A pilot study of a group of these leaders suggests a generalised problem with communication of policy, objectives and strategies, which is crucial to overcoming cultural impediments to smart city development. While further research is required, a need clearly emerges for significant changes in attitude and application at senior managerial and leadership levels if strategic goals are to be achieved. The paper also makes a number of specific recommendations for activities that could improve progress and indicate areas where more research would be beneficial.
The Influence of Street Components on Age Diversity: A Case Study on a Living Street in Shanghai
Authors: An Dadi , Liu Yan , Huang Yihua
Published: July 2023

Background: Living streets are vital spaces for urban residents to socialise and enjoy leisure activities. Previous research has examined the relationship between street components and residents’ public lives but has overlooked the age composition of residents. To move towards all-age-friendly spaces, it is essential to investigate the preferences of different age groups for public life and to enhance the age diversity of cities. Methods: Based on a literature review, this research selected an index system that consists of four domains (street space, street facilities, street layout, and commercial features) and was suitable for our survey site. The indicators were chosen according to their relevance to street components and measurability. This research then conducted offline surveys and observations to assess the components of small-scale public places on Golden Street in Shanghai. Results: Data analysis showed that street facilities and commercial features strongly correlate with age diversity. However, some indicators did not yield the expected results. Conclusions: Our research demonstrates that specific street components are strongly associated with age diversity. Optimising these components may improve the age diversity of cities. The conclusions suggest that future street construction projects be implemented to assist relevant management departments in creating dynamic streets.
Establishment of a Hydrometallurgical Scheme for the Recovery of Copper, Nickel, and Cobalt from Smelter Slag and Its Economic Evaluation
Authors: Godirilwe Labone Lorraine , Haga Kazutoshi , Altansukh Batnasan , Jeon Sanghee , Danha Gwiranai , Shibayama Atsushi
Published: July 2023

In pursuit of carbon neutrality, the demand for metals that are necessary for the development of clean energy technologies is rapidly increasing. Metallurgical waste, such as slag, presents a promising secondary source of these key metals. This research aims to develop an eco-friendly hydrometallurgical process to recover Cu, Ni, and Co from discarded copper/nickel slag. High-pressure acid leaching (HPAL) was used to selectively leach Ni, Cu, and Co from the fayalite slag, yielding high leaching efficiencies of 99.9%, 89.4%, and 99.9%, respectively, with low Fe and Si tenors to the pregnant leach solution (PLS). The solvent extraction (SX) technique utilizing LIX 984N was used to selectively extract and enrich copper from the dilute PLS to about 23 g/L Cu with a very low Fe concentration of 0.05 g/L. Potassium amyl xanthate (PAX) solution was used to form Ni and Co xanthate complexes from the raffinate solution. Nickel was selectively recovered using ammonia solution, while the cobalt xanthate complex was thermally decomposed and recovered as cobalt oxide solids of about 25 wt.% Co. A comprehensive process flowsheet is presented. Furthermore, to realize the real application of the developed slag cleaning process, a preliminary economic evaluation was performed.
Investigation of Factors Associated with Heavy Vehicle Crashes in Iran (Tehran–Qazvin Freeway)
Authors: Kashani Ali Tavakoli , Zandi Kamran , Okabe Atsuyuki
Published: July 2023

With the growing demand for transportation and cargo between cities, the proportion of heavy vehicles in freeway traffic has been increasing in Iran and worldwide during the past decade. The impact of heavy vehicles on crash severity has long been a concern in the crash analysis literature for the prevalence of crashes in freeway traffic. The purpose of this study is to investigate the contribution of heavy vehicles to freeway crashes and uncover other causal factors. Using the comprehensive crash and traffic data from the Qazvin–Tehran freeway in Iran, from 2013 to 2018, 1350 crashes involving heavy vehicles were extracted regarding the weather conditions, weekday, main cause of the crash, driver gender, and culprit side. Considering crash severity calculation, the applied coefficient weights in this study for a person were considered as 3 for an accident resulting in injury and 5 for a fatal crash. A binary logit model was estimated using the data to determine if there was a significant correlation between recognized factors and the likelihood of the crash. The logit modeling results clearly illustrate important relationships between various risk factors and occupant injury, in which heavy vehicles were recognized as one of the most important factors in this study. Other variables associated with crash severity were weather conditions and driver attention. Results indicate that the number of crashes is simultaneously dependent on the total vehicle volume and average speed of heavy vehicles.
Numerical Investigation of Fractional-Order Fornberg–Whitham Equations in the Framework of Aboodh Transformation
Authors: Noor Saima , Hammad Ma’mon Abu , Shah Rasool , Alrowaily Albandari W. , El-Tantawy Samir A.
Published: July 2023

In this investigation, the fractional Fornberg–Whitham equation (FFWE) is solved and analyzed via the variational iteration method (VIM) and Adomian decomposition method (ADM) with the help of the Aboodh transformation (AT). The FFWE is an important model for describing several nonlinear wave propagations in various fields of science and plasma physics. The AT provides a powerful tool for transforming fractional-order differential equations (DEs) into integer-order ones, making them more amenable to analytical solutions. Accordingly, the main objective of this investigation is to demonstrate the effectiveness and accuracy of ADM and VIM in deriving some approximations for the FFWE. Furthermore, we highlight the advantages and potential applications of these methods in solving other fractional-order nonlinear problems in several scientific fields, especially in plasma physics and some engineering problems.
Solution for Convergence Problem in DEMATEL Method: DEMATEL of Finite Sum of Influences
Authors: Šmidovnik Tjaša , Grošelj Petra
Published: July 2023

Decision-making trial and evaluation laboratory (DEMATEL) is one of the multicriteria decision-making methods based on asymmetric linguistic comparison matrices that has received a great deal of attention, and it is a widely used method in various fields. One of the drawbacks of DEMATEL is a convergence problem that may occur when the infinite sum of normalized influences does not converge. Based on the observations of some examples, the new concept of DEMATEL, the DEMATEL of a finite sum of influences (FSI DEMATEL), is proposed. Instead of an infinite sum, a finite sum of influences is used in FSI DEMATEL so that the convergence problem is avoided. The advantage is that FSI DEMATEL can handle more decision-making problems than the DEMATEL. It can also be used for fuzzy evaluations. FSI DEMATEL can be used as the multicriteria decision-making method to evaluate the relationships between the factors in many different fields.
Efficient Poisson’s Ratio Evaluation of Weft-Knitted Auxetic Metamaterials
Authors: Luan Kun , Newman Zoe , West Andre , Lee Kuan-Lin , Rokkam Srujan
Published: July 2023

Auxetic metamaterials expand transversely when stretched longitudinally or contract transversely when compressed, resulting in a negative Poisson’s ratio (NPR). Auxetic fabrics are 3D textile metamaterials possessing a unique geometry that can generate an auxetic response with respect to tension. In weft-knitted auxetic fabrics, the NPR property is achieved due to the inherent curling effect of the face and back stitches of the knit loops; they contract in an organized knitting pattern. The traditional method used to evaluate NPR is to measure the lateral fabric deformation during axial tensile testing on a mechanical testing machine, which is time-consuming and inaccurate in measuring uneven deformations. In this study, an efficient method was developed to evaluate the NPR of weft-knitted fabric that can also estimate deformation directionality. The elasticity and extension properties of the weft-knitted fabric can be analyzed immediately following removal from the knitting bed. Five fabrics, all with the same stitch densities (including four auxetic patterns and one single jersey pattern), were designed and produced to validate the proposed method. The use of our estimation method to evaluate the Poisson’s ratio of such fabrics showed higher values compared with the traditional method. In conclusion, the deformation directionality, elasticity, and extensionality were examined. It is anticipated that the proposed method could assist in the innovative development and deployment of auxetic knitted metamaterials.
Understanding the Intricacies of Iron Overload Associated with β-Thalassemia: A Comprehensive Review
Authors: Basu Subhangi , Rahaman Motiur , Dolai Tuphan Kanti , Shukla Praphulla Chandra , Chakravorty Nishant
Published: July 2023

β-thalassemia, a congenital genetic hematological disorder characterized by the decrease or absence of β-globin chains, leads to a decrease in levels of Hemoglobin A. The affected individuals can be categorized into two cohorts based on transfusion dependency: transfusion-dependent thalassemia (TDT) and non-transfusion-dependent thalassemia (NTDT). Remarkably, despite the primary pathology lying in β-globin chain depletion, β-thalassemia also exhibits an intriguing association with iron overload. Iron metabolism, a tightly regulated physiological process, reveals a complex interplay in these patients. Over time, both cohorts of β-thalassemic individuals develop iron overload, albeit through distinct mechanisms. Addressing the diverse complications that arise due to iron overload in β-thalassemic patients, the utilization of iron chelators has gained a lot of significance. With varying efficacies, routes of administration, and modes of action, different iron chelators offer unique benefits to patients. In the Indian context, three commercialized iron chelators have emerged, showcasing a high adherence rate to iron chelator-based treatment regimens among β-thalassemic individuals. In this review, we explore the intriguing connection between β-thalassemia and iron overload, shedding light on the intricate mechanisms at play. We delve into the intricacies of iron metabolism, unveiling the distinct pathways leading to iron accumulation in these patients. Additionally, the therapeutic efficacy of different iron chelators in managing iron overload complications is mentioned briefly, along with the guidelines for their usage in India. Through this comprehensive analysis, we aim to deepen our understanding of β-thalassemia and iron overload, paving the way for optimized treatment strategies. Ultimately, our findings provide valuable insights into improving the care and outcomes of individuals affected by β-thalassemia.
Toxicity of Heavy Metals and Recent Advances in Their Removal: A Review
Authors: Abd Elnabi Manar K. , Elkaliny Nehal E. , Elyazied Maha M. , Azab Shimaa H. , Elkhalifa Shawky A. , Elmasry Sohaila , Mouhamed Moustafa S. , Shalamesh Ebrahim M. , Alhorieny Naira A. , Abd Elaty Abeer E. , Elgendy Ibrahim M. , Etman Alaa E. , Saad Kholod E. , Tsigkou Konstantina , Ali Sameh S. , Kornaros Michael , Mahmoud Yehia A.-G.
Published: July 2023

Natural and anthropogenic sources of metals in the ecosystem are perpetually increasing; consequently, heavy metal (HM) accumulation has become a major environmental concern. Human exposure to HMs has increased dramatically due to the industrial activities of the 20th century. Mercury, arsenic lead, chrome, and cadmium have been the most prevalent HMs that have caused human toxicity. Poisonings can be acute or chronic following exposure via water, air, or food. The bioaccumulation of these HMs results in a variety of toxic effects on various tissues and organs. Comparing the mechanisms of action reveals that these metals induce toxicity via similar pathways, including the production of reactive oxygen species, the inactivation of enzymes, and oxidative stress. The conventional techniques employed for the elimination of HMs are deemed inadequate when the HM concentration is less than 100 mg/L. In addition, these methods exhibit certain limitations, including the production of secondary pollutants, a high demand for energy and chemicals, and reduced cost-effectiveness. As a result, the employment of microbial bioremediation for the purpose of HM detoxification has emerged as a viable solution, given that microorganisms, including fungi and bacteria, exhibit superior biosorption and bio-accumulation capabilities. This review deals with HM uptake and toxicity mechanisms associated with HMs, and will increase our knowledge on their toxic effects on the body organs, leading to better management of metal poisoning. This review aims to enhance comprehension and offer sources for the judicious selection of microbial remediation technology for the detoxification of HMs. Microbial-based solutions that are sustainable could potentially offer crucial and cost-effective methods for reducing the toxicity of HMs.
An Integrated GIS and Machine-Learning Technique for Groundwater Quality Assessment and Prediction in Southern Saudi Arabia
Authors: El-Rawy Mustafa , Batelaan Okke , Alshehri Fahad , Almadani Sattam , Ahmed Mohamed S. , Elbeltagi Ahmed
Published: July 2023

One of the most critical stages for developing groundwater resources for drinking water use is assessing the water quality. The use of a Water Quality Index (WQI) is considered an effective method of evaluating water quality. The objective of this research was to evaluate the performance of six multiple artificial intelligence techniques, i.e., linear regression (stepwise), support vector regression SVM (linear and polynomial kernels), Gaussian process regression (GPR), Fit binary tree, and artificial neural network ANN (Bayesian) to predict the WQI in Jizan, Southern Saudi Arabia. A total of 145 groundwater samples were collected from shallow dug wells and boreholes tapping the phreatic aquifer. The WQI was calculated from 11 physicochemical parameters (pH, TDS, Ca2+, Mg2+, Na+, K+, Cl−, SO42−, HCO3−, NO3−, and TH). The spatial distribution results showed that higher values of Cl− and SO42− were recorded in the places close to the coastline, indicating the occurrence of seawater intrusion and salinisation. Seven wells had a WQI of greater than 300, indicating that the water was unfit for consumption. The results showed that the GPR, linear regression (stepwise), and ANN models performed best during the training and testing stages, with a high correlation of 1.00 and low errors. The stepwise fitting model indicated that pH, K+, and NO3− were the most significant variables, while HCO3− was a non-significant variable for the WQI. The GPR, stepwise regression, and ANN models performed best during the training and testing stages, with a high correlation and low errors. In contrast, the SVM and Fit binary tree models performed the worst in the training and testing phases. Based on subset regression analysis, the optimum input combination for WQI model prediction was determined as these eight input combinations with high R2 (0.975–1.00) and high Adj-R2 (0.974–1.00). The resultant WQI model significantly contributes to sustainable groundwater resource management in arid areas and generates improved prediction precision with fewer input parameters.
Fast Prediction of Solute Concentration Field in Rotationally Influenced Fluids Using a Parameter-Based Field Reconstruction Convolutional Neural Network
Authors: Yan Xiaohui , Mohammadian Abdolmajid , Yu Huijuan , Zhang Tianqi , Liu Jianwei , Chang Sheng , Song Hongyi
Published: July 2023

Many high-performance fluid dynamic models do not consider fluids in a rotating environment and often require a significant amount of computational time. The current study proposes a novel parameter-based field reconstruction convolutional neural network (PFR-CNN) approach to model the solute concentration field in rotationally influenced fluids. A new three-dimensional (3D) numerical solver, TwoLiquidMixingCoriolisFoam, was implemented within the framework of OpenFOAM to simulate effluents subjected to the influence of rotation. Subsequently, the developed numerical solver was employed to conduct numerical experiments to generate numerical data. A PFR-CNN was designed to predict the concentration fields of neutrally buoyant effluents in rotating water bodies based on the Froude number (Fr) and Rossby number (Ro). The proposed PFR-CNN was trained and validated with a train-validation dataset. The predicted concentration fields for two additional tests demonstrated the good performance of the proposed approach, and the algorithm performed better than traditional approaches. This study offers a new 3D numerical solver, and a novel PFR-CNN approach can predict solute transport subjected to the effects of rotation in few seconds, and the PFR-CNN can significantly reduce the computational costs. The study can significantly advance the ability to model flow and solute transport processes, and the proposed CNN-based approach can potentially be employed to predict the spatial distribution of any physical variable in the lentic, ocean, and earth system.
Assessing the Possibilities of Backwash Water Reuse Filters in the Water Treatment System—Case Analysis
Authors: Wolska Małgorzata , Urbańska-Kozłowska Halina
Published: July 2023

Due to the worldwide water crisis and diminishing water supplies, it is imperative to reduce water use and reuse it. One possible source of water is the washings created during the purification of drinking water. Backwashing constitutes 2–8% of the treated water used globally; it is more commonly used, primarily for irrigation or to expand surface/groundwater resources. Therefore, recirculating it at the beginning of the water treatment system is reasonable and justifiable, as it can lead to a decrease in the cost of the water that is being used. A study of variations in the content of washings in two water treatment plants revealed the requirement for pollutants to be removed before the water is reused. For the safety of consumers, the presence of microbes in backwashings from both facilities was essential. Variability in the amount and composition of backwashings was higher for surface water treatment in comparison to infiltration water treatment; however, the amount of backwashings was greater in infiltration water. The quantity of microorganisms, including indicator ones, was substantially higher in washings following surface water treatment. On the other hand, in the washings from the infiltration water treatment, large amounts of iron and manganese compounds were present, the recycling of which would reduce the effectiveness of infiltration water treatment. Pre-treatment backwashings from both facilities will be suitable for the suspension separation procedures and disinfection. It is essential to compare the costs connected with water use against the anticipated cost of washing. The potential to purify additional water in the event of a worsening water shortage, however, is the most significant advantage of water reuse. Recycling of the washings will allow to reduce the fees for the use of the environment, even to EUR 150,000 and EUR 250,000 per year for surface and infiltration WTP, respectively.
LONGITUDINAL COMPRESSION OF A ROD WITH AN INITIAL LOSS ACQUIRING INDUCED ANISOTROPY
Authors:   Volgograd State Technical University, KALASHNIKOV S.Y. ,   Central Research and Design Institute of the Ministry of Construction and Housing and Communal Services of the Russian Federation, GUROVA E.V. ,   Volgograd State Technical University, BANDURIN N.G. ,   Volgograd State Technical University
Published: July 2023

A centrally compressed flexible rectilinear steel rod is considered. Due to the existing initial imperfection in the form of a perish, the rod works as a compressed-curved one. The inhomogeneity of the stress state from bending leads to the constraint of deformations that cause a change in the elastic characteristics of the material. To obtain the equation of the rod in the deflected state, the incremental theory of nonlinear deformation of bodies in inhomogeneous stress fields with induced anisotropy of properties proposed earlier by the authors is used. The inhomogeneity of the stress field causes the variability of the elastic characteristics of the material, which, due to the induced incremental curvilinear anisotropy, lead to a change in the design parameters of the structure. The solution is based on the numerical implementation of the curved axis equation using the method of variable elasticity parameter. The growth of deflections at the stages of sequential loading with increasing force is analyzed. Various variants of initial curvatures, including vanishing small ones, are considered. Regardless of the magnitude of the initial deflection, a noticeable increase in the compressive force was found, corresponding to a significant increase in deflections compared to the bifurcation approach.