Arabian Journal for Science and Engineering最新文献

Ochratoxin A (OTA) is a mycotoxin commonly found in improperly stored grains, posing significant risks to food safety. Accurate detection of this mycotoxin in food matrices is crucial for ensuring consumer protection. In this study, we used in silico methods to design new peptides with high affinity and selectivity for recognizing OTA, starting crystal structures of OTA-protein complexes, which served to identify short key peptides within the interaction regions. Through deliberate point mutations, the stability and affinity of these peptides towards OTA were enhanced. To assess their suitability as capture probes for OTA sensing, we investigated the interaction of the selected peptides with OTA in a saline aqueous solution to mimic wet-lab experiments. Molecular docking, molecular dynamics simulations were used to evaluate the affinity and stability of the peptide-OTA complexes. Various parameters, including conformational changes, Molecular Mechanics Poisson–Boltzmann Surface Area energetics, the number of contacts, and the number of hydrogen bonds were analyzed to identify the most promising candidates. Among them, the peptide CWC11 has the highest affinity to OTA. Next, CWC11 peptide was used to functionalize the surfaces of two different carbonaceous nanomaterials: reduced graphene oxide (rGO) and graphene oxide (GO). The performance of the peptide-functionalized surfaces in presence of OTA was evaluated, revealing that GO exhibited superior performance compared to rGO. This study provides valuable insights into the design OTA-binding peptides and their use for the functionalization of carbonaceous surfaces, emphasizing the importance of surface selection to tune the efficiency and sensitivity of the detection.

Inspired by natural swarm systems, robotic swarms aim to solve complicated problems through the emergent behaviour of coordinating robots (agents). Communication among the robots is of paramount importance for their effective coordination, cooperation, and overall performance. This research presents a colour light-based communication system for miniature mobile swarm robots, on which a pre-trained supervised machine learning model runs and is responsible for effective colour recognition, enhancing inter-robot local communication. The performance of various supervised machine learning techniques was examined, and XGBoost performed best overall, with a classification accuracy of 96.66%, an execution time of 0.403 ms, an average sensing distance of 87.38 cm, and an acceptable size of 402.1 kilobytes while running on a 32-bit embedded microcontroller. The current work also demonstrates various swarming behaviours, utilising the developed communication as proof of concept.

Enzyme induced carbonate precipitation (EICP) is a new bio-cementation technique that utilizes plant-sourced urease to catalyze urea degradation and reaction with calcium iron, resulting in the formation of calcium carbonate (CaCO₃) for soil improvement. EICP has considerable promise for novel and sustainable engineering applications such as soil strengthening, pollutant remediation, and other in situ field applications. In this study, the effect of EICP on the geotechnical characteristics of expansive soil is examined. A series of laboratory tests have been performed with an optimal concentration ratio of 0.75 mol/L. The outcomes of the compaction experiment indicated a slight increment in the dry density of the expansive soil from 15.78 to 16.71 kN/m³.Further, it diminished the optimal moisture content of the soil, decreasing it from 22.3 to 18.5%. The utilization of EICP improves the soil mechanical characteristics, reducing swelling pressure by 80% and increasing the UCS, cohesion, friction angle, unsoaked and soaked CBR by 66%, 44%, 49%, 441%, and 430%, approximately. Additionally, it leads to a significant decrease in soil permeability, approximately 63%. Moreover, SEM and XRD analysis confirmed the presence of CaCO₃ content in the treated soil. The experimental findings indicated that the EICP method holds promise in enhancing expansive soil within engineering projects.

People with dysarthric speech face problems communicating with others and voice-based smart devices. This paper presents the development of a spatial residual convolutional neural network (RCNN)-based dysarthric speech recognition (DSR) system to improve communication for individuals with dysarthric speech. The RCNN model is simplified to an optimal number of layers. The system utilizes a speaker-adaptive approach, incorporating transfer learning to leverage knowledge learned from healthy individuals and a new data augmentation technique to address voice hoarseness in patients. The dysarthric speech is preprocessed using a novel voice cropping technique based on erosion and dilation methods to eliminate unnecessary pauses and hiccups in the time domain. The isolated word recognition accuracy improved by nearly 8.16% for patients with very low intelligibility and 4.74% for patients with low intelligibility speech compared to previously reported results. The proposed DSR system gives the lowest word error rate of 24.09% on the UASpeech dysarthric speech datasets of 15 dysarthric speakers.

Traffic congestion has several adverse effects on urban traffic networks. Increased travel times of vehicles, with the addition of excessive greenhouse emissions, can be listed as harmful effects. To address these issues, transportation engineers aim to reduce private car usage, reduce travel times through different control strategies, and mitigate harmful effects on urban networks. In this study, we introduce an innovative approach to optimizing traffic signal control settings. This methodology takes into account both pedestrian delays and vehicular emissions. Non-dominated sorting genetic algorithm-II and Multi-objective Artificial Bee Colony algorithms are adopted to solve the multi-objective optimization problem. The vehicular emissions are modeled through the MOVES3 emission model and integrated into the utilized microsimulation environment. Initially, the proposed framework is tested on a hypothetical test network, followed by a real-world case study. Results indicate a significant improvement in pedestrian delays and lower emissions.

The focus of this study is on the aerodynamic design of a 2000-W airborne wind turbine (AWT) situated 100 m above ground level. AWTs harness higher wind speeds at higher altitudes, making them more efficient than ground-based turbines in generating power. To achieve the desired performance, numerical methods, such as blade element momentum (BEM) and computational fluid dynamics (CFD) were employed for the aerodynamic design and analysis of the AWT system. The rotor cross-section of the three-blade rotor incorporates S223 and S822 airfoils, which are derived from the conventional NREL airfoils. The diffuser section of the AWT has an elliptical curve to accommodate the maximum volume of helium gas. Through simulations using both CFD and BEM, the performance of the bare rotor was assessed, as well as the diffuser-augmented wind turbine (DAWT) under design and off-design conditions. The results demonstrated that the DAWT is capable of meeting the desired power output in all scenarios. Moreover, the findings indicated that using the diffuser enhances the rotor output power coefficient by 18% and prevents significant power loss during off-design conditions. This highlights the effectiveness of the rotor-diffuser assembly in maximizing power generation and ensuring consistent performance of the AWT system.

This paper addresses the tracking control problem associated with the diving motion system of a torpedo-like shape autonomous underwater vehicle (AUV). A decoupled and reduced-order three degrees-of-freedom (3-DOF) nonlinear model is employed to represent the dynamics of the diving motion system for depth position control. The control objective is to track the demanded depth position in the presence of uncertainties and disturbances. A control law based on the immersion and invariance (I &I) technique is synthesized to achieve the control objectives. The proposed control law effectively tracks a stable, lower-order target dynamic system immersed within a three-dimensional manifold. Additionally, the regulation problem is treated as a specialized case of tracking, with a known depth serving as the reference input to be regulated. The performance of the proposed control law is assessed through simulation studies that consider various scenarios. The simulation study evaluates the robustness of the proposed control law resilience against modelling uncertainties and underwater disturbances. The simulations utilize the MAYA AUV, incorporating experimentally validated diving motion parameters. The proposed control law’s quantitative analysis and computational performance show better performance against the benchmark controller.

The Ni-, Co-, and Mo-supported Ni foam (NiF–NiCoMo) was produced via galvanostatic method, and electrooxidation of methanol in alkaline medium was examined. The characterization was achieved using field emission scanning electron microscopy, energy-dispersive X-ray, and X-ray diffraction analysis. The electrochemical behavior was determined via cyclic voltammetry and chronoamperometry analysis. The contribution of each transition metal to electrocatalytic performance of NiF was monitored via mono, binary, and ternary modifications of each transition metal (Ni, Co, and Mo) for several amounts (5, 10, and 15 μg). Experiments were performed to determine the influence of catalyst amounts, methanol concentration, and scan rate parameters. The impacts of independent parameters on methanol electrooxidation were statistically investigated using Design-Expert software. The ability to analyze multiple parameters with a limited number of experimental performances is one of the method’s key benefits. The developed model showed that 9.41 and 14.03 µg catalyst amounts were the appropriate values for NiF–NiMo and NiF–NiCoMo achieving optimal circumstances, respectively.

For the satellite antenna, a large aperture reflector is a contemporary need for space agencies worldwide. The space-borne membrane structures are the promising solution for the compact and lightweight reflector antenna. The objective of the study is to investigate the effect of dimension scaling on tension force with different anchor point configurations of the rectangular membrane reflector. The study also aims towards the development of the generalized tension force relation for the scaled dimensions of planar membrane reflectors. The numerical and experimental investigation for loading analysis of membrane reflector with different scale sizes and anchor point configurations is carried out. The study presents the novel equation for average diagonal stresses with different anchor points configurations of membrane reflector. The numerical results of loading analysis are found consistent with the experimental outcomes. Based on the results, the novel trend-line equation between the tension force and the scaling factor is developed. From the developed trend-line equation, the tension force can be directly calculated for any size of a reflector. The relation between the number of anchor points and the size of the reflector is discussed. The findings of this research provide insights to a novel relation for average diagonal stresses and tension force trend-line equations that can be implemented to any scaled sizes of the rectangular membrane reflector.

This article investigates the effect of various fillets on the performance characteristics of relay electrical contacts. Finite element modeling (FEM) of a relay electrical contact is designed in 3D using the COMSOL Multiphysics simulation tool. Copper material is assigned to the electrical contact pairs. Analysis is carried out for the heights of 0.5 mm and 1 mm. Also, the structure of the contact surface is fine-tuned by using different fillets of 1.5 mm, 1 mm, and 0.5 mm. The voltages of 1 V–10 V are offered, and their performance is evaluated. The key parameters to design the contacts are identified. The electrical, thermal, and mechanical analysis is carried out. The parameters such as current density, contact interface temperature, stress, and pressure are simulated using FEM. The results present the evaluation of relays with different heights through different fillets in various voltage ranges. The results demonstrate that the low fillet radii have a higher contact area and exhibit low current density, low contact pressure, and low stress, which is more reliable and efficient. This study will be highly beneficial for relay and circuit breakers manufacturers.