bluuebunny/crossref_metadata_2025 huggingface dataset:
An SPS-RS Technique for the Fabrication of SrMoO4 Powellite Mineral-like Ceramics for 90Sr Immobilization
Authors: Belov Anton A. , Shichalin Oleg O. , Papynov Evgeniy K. , Buravlev Igor Yu. , Portnyagin Arseniy S. , Azon Semen A. , Fedorets Alexander N. , Vornovskikh Anastasia A. , Kolodeznikov Erhan S. , Gridasova Ekaterina A. , Pogodaev Anton , Kondrikov Nikolay B. , Shi Yun , Tananaev Ivan G.
Published: August 2023

This paper reports a method for the fabrication of mineral-like SrMoO4 ceramics with a powellite structure, which is promising for the immobilization of the high-energy 90Sr radioisotope. The reported method is based on the solid-phase “in situ” interaction between SrO and MoO3 oxides initiated under spark plasma sintering (SPS) conditions. Dilatometry, XRD, SEM, and EDX methods were used to investigate the consolidation dynamics, phase formation, and structural changes in the reactive powder blend and sintered ceramics. The temperature conditions for SrMoO4 formation under SPS were determined, yielding ceramics with a relative density of 84.0–96.3%, Vickers microhardness of 157–295 HV, and compressive strength of 54–331 MPa. Ceramic samples demonstrate a low Sr leaching rate of 10−6 g/cm2·day, indicating a rather high hydrolytic stability and meeting the requirements of GOST R 50926-96 imposed on solid radioactive wastes. The results presented here show a wide range of prospects for the application of ceramic matrixes with the mineral-like composition studied here to radioactive waste processing and radioisotope manufacturing.
Influence of TiN Inclusions and Segregation Bands on the Mechanical Properties and Delayed Crack in Thick NM550 Wear-Resistant Steel
Authors: Sun Haoran , Du Hegang , Tong Keke , Liu Lihua , Yan Qiangjun , Zuo Xiurong
Published: August 2023

The formation mechanism of the delayed crack after flame cutting and mechanical properties in thick NM550 wear-resistant steel are studied by optical microscopy, scanning electron microscopy, energy dispersive spectroscopy, X-ray diffraction, and an electron backscattered diffractometer. The delayed crack is formed at the segregation zone (SZ) located in the center of the 65 mm thick steel plate. The strength of the non-segregation zone (NSZ) with a martensite microstructure is slightly higher than that of SZ with a mixture microstructure of martensite plus bainite, and the plasticity of NSZ is significantly better than that of SZ. There exists a more severe segregation in the SZ, and only a slight segregation in the NSZ. The average grain sizes of the segregation bands in the NSZ and SZ are 15.72 µm and 6.76 µm, respectively. The number density of TiN larger than 5 µm in the NSZ and SZ is 0.031 and 1.156 number/mm2, respectively. Therefore, a high hardness segregation band with fine grains and a high dislocation density, along with the large number of coarse TiN inclusions within it, results in delayed cracking. For TiN inclusions close to the crack, microvoids or microcracks around the TiN are formed, and the delayed crack will propagate along the edge of the TiN or through the TiN inclusions.
Shear Strength Behaviors of Aeolian Sand Solidified by Microbially Induced Calcite Precipitation and Basalt Fiber Reinforcement
Authors: Li Gang , Liu Jia , Zhang Jinli , Yang Yiran , Chen Shufeng
Published: August 2023

Aeolian sand flow is identified as the main factor in the formation of sandstorms. However, conventional sand fixation methods cannot meet the current development requirements of environmental protection. In this paper, the method using Microbially Induced Calcite Precipitation (MICP) combined with basalt fiber reinforcement (BFR) was adopted to solidify the aeolian sand. Consolidated undrained triaxial shear tests were carried out to analyze the influence of fiber content, fiber length, confining pressure, and other factors on stress–strain characteristics, peak strength, brittleness index, and shear strength of aeolian sand. A shear strength model of aeolian sand solidification using MICP-BFR and considering the effect of fiber length and fiber content is established according to the test results. The results show that the peak strength of aeolian sand solidified by MICP-BFR is remarkably higher than that of aeolian sand solidified by MICP alone, and the peak strength rises with the increasing fiber length, fiber content, and confining pressure. The application of fiber can effectively reduce the brittleness index of aeolian sand solidified by MICP and improve the sample ductility. As fiber content and fiber length increase, the cohesion of solidified aeolian sand increases while the internal friction angle changes relatively little. In the limited range set by the test, the fiber length of 12 mm and the fiber content of 1.0% constitute the optimum reinforcement condition. The test results coincide with the model prediction results, indicating that the new model is fitting for predicting the shear strength of aeolian sand solidified by MICP-BFR. The research results provide an important reference value for guiding the practice of wind prevention and sand fixation in desert areas.
Application of Extended Finite Element Method for Studying Crack Propagation of Welded Strip Steel in the Cold Rolling Process
Authors: Chen Jianjun , Wu Chaojie , Ying Jiacong
Published: August 2023

In the cold rolling process, edge cracks, particularly those near the welded zone, can inadvertently lead to strip rupture. This study employed the extended finite element method (XFEM) to analyze the crack propagation behavior in welded strip steel during cold rolling. Various tests such as the tensile test, essential work of fracture (EWF) test, spherical indentation method, and elastoplastic finite element simulations were conducted to determine the maximum principal stress and fracture energy utilized in XFEM for the base metal and weld metal, respectively. A continuous cold rolling model was established to investigate the crack propagation behaviors in the base metal, weld metal, and the interface between the base and weld metal. In the continuous rolling process, the crack propagation and expansion speed in the base metal are much larger than that of the weld zone. In addition, the base metal at the back end of the rolled piece is more prone to fracture than the base metal at the front end.
Cadmium-Based Quantum Dots Alloyed Structures: Synthesis, Properties, and Applications
Authors: Ebrahim Fadia , Al-Hartomy Omar , Wageh S.
Published: August 2023

Cadmium-based alloyed quantum dots are one of the most popular metal chalcogenides in both the industrial and research fields owing to their extraordinary optical and electronic properties that can be manipulated by varying the compositional ratio in addition to size control. This report aims to cover the main information concerning the synthesis techniques, properties, and applications of Cd-based alloyed quantum dots. It provides a comprehensive overview of the most common synthesis methods for these QDs, which include hot injection, co-precipitation, successive ionic layer adsorption and reaction, hydrothermal, and microwave-assisted synthesis methods. This detailed literature highlights the optical and structural properties of both ternary and quaternary quantum dots. Also, this review provides the high-potential applications of various alloyed quantum dots.
Interlocking Evaluation of Mesoscopic Skeleton with the Compaction Degree of Hot-Mix Asphalt
Authors: Gong Xiangbing , Liu Ziming , Qian Guoping , Liu Zhiyang
Published: August 2023

Asphalt mixtures are multi-phase composites composed of aggregates, bitumen, mineral powders, and voids, and various structures are intertwined during the compaction process. Most of the traditional research focuses on the macro-scale domain, and it is difficult to obtain the internal structure of asphalt mixture in different compaction processes. With the continuous development of digital image technology, the influence of the meso-structure of the asphalt mixture on the compaction quality of the asphalt mixture has become a new means to evaluate the performance of the asphalt mixture. In this paper, different numbers of compactions are selected to represent different stages in the compaction process, the digital images of specimens in different compaction stages are obtained by industrial CT scanning technology. Then, the images are processed and reconstructed in three dimensions using improved image segmentation methods, and the position characteristics and geometric information of coarse aggregate are obtained by combining the Oriented Bounding Box (OBB). The meso-response characteristics of the skeleton structure of the asphalt mixture during compaction were studied. The influence of the internal structure of the mixture on the compaction quality of the mixture was obtained, which is of great significance for the study of improving the durability of the pavement. The results show that the “effective coordination number” (the number of aggregate particles that can transmit force in the skeleton structure) is greatly related to the aggregate size. With the compaction process, the centroid of coarse aggregate in the upper layer of the specimen reflects the overall downward movement trend. The inclination angle of the aggregate spindle tends to be in the range of 80°~100°; the anisotropic amplitude of the xy plane increases, and the direction of the aggregate spindle becomes more and more consistent. With the increase in the number of rotational compactions, these four parameters showed obvious rules, indicating that this meso-characteristic index could well characterize the compaction quality of the asphalt mixture in the compaction process.
Improved Rapid-Expanding-Random-Tree-Based Trajectory Planning on Drill ARM of Anchor Drilling Robots
Authors: Zhang Xuhui , Huang Mengyao , Lei Mengyu , Tian Hao , Chen Xin , Tian Chenhui
Published: August 2023

Permanent highway support in deep coal mines now depends on the anchor drilling robot’s drill arm. The drilling arm’s trajectory planning using the conventional RRT (rapid-expanding random tree) algorithm is inefficient and has crooked, rough paths. To improve the accuracy of path planning, we propose an improved RRT algorithm. Firstly, the kinematic model of the drill arm of the drill and anchor robot was established, and the improved DH solution parameters and the positive solution of the drill arm kinematics were solved. The end effector’s attainable working space was calculated using the Monte Carlo approach. Additionally, to address the problem of the slow running speed of the RRT algorithm, an artificial potential field factor was introduced to construct virtual force fields at obstacle and target points and calculate the potential field map for the entire reachable workspace to improve the speed of the sampling points close to the target point. At the same time, the greedy approach and the three-time B-sample curve-fitting method were used simultaneously to remove unnecessary points and carry out smooth path processing in order to improve the quality of the drill arm trajectory. This was carried out in order to solve the issue of rough pathways generated by the RRT algorithm. Finally, 50 time-sampling comparison experiments were conducted on 2D and 3D maps. The experimental results showed that the improved RRT algorithm improved the average sampling speed by 20% and reduced the average path length by 14% compared with the RRT algorithm, which verified the feasibility and effectiveness of this improved RRT algorithm. The improved RRT algorithm generates more efficient and smoother paths, which can improve the intelligence of the support process by integrating and automating drilling and anchoring and providing reliable support for coal mine intelligence.
New Approach for Fertiliser Size Assessment Using Contactless Scanning
Authors: Laucka Andrius , Andriukaitis Darius , Valinevicius Algimantas , Zilys Mindaugas , Navikas Dangirutis , Balasevicius Leonas , Merfeldas Audrius , Sotner Roman , Jerabek Jan , Li Zhixiong , Ritonja Jozef
Published: August 2023

The growing population and lack of change in resources of cultivated land have led to the search for more efficient farming solutions. The recovery of soil is facilitated by using chemicals designed for the enrichment of cultivated soil. Fertilisers are made of a combination of various substances that determine not only the chemical but also the shape characteristics of the fertiliser pellets. The effect of the quality of fertilisation on yield size is related to even distribution. Shape and size are closely related to the quality of the fertilisation process. The intense control of the production process would not be possible without automatised and quick measurements within the production line. Constant control is necessary to ensure that the products meet quality standards. The contactless assessment of pellet sizes allows a quick reaction to changes in production quality and reduces the costs arising from the reprocessing of defective pellets. The results of the assessment of pellet volume using their two-dimensional image are presented in this publication. Pellets must be analysed according to their most characteristic position, which can provide valuable information about their properties. The aim is to determine the placement positions of the equipment based on calculations and to compare the results with those of gold-standard equipment. Correctly calibrated equipment ensures that the measurement results match the results of the control equipment of fertiliser producers. Reliable non-contact measurements can reduce the reaction time to production changes.
Dual Elite Groups-Guided Differential Evolution for Global Numerical Optimization
Authors: Wang Tian-Tian , Yang Qiang , Gao Xu-Dong
Published: August 2023

Differential evolution (DE) has shown remarkable performance in solving continuous optimization problems. However, its optimization performance still encounters limitations when confronted with complex optimization problems with lots of local regions. To address this issue, this paper proposes a dual elite groups-guided mutation strategy called “DE/current-to-duelite/1” for DE. As a result, a novel DE variant called DEGGDE is developed. Instead of only using the elites in the current population to direct the evolution of all individuals, DEGGDE additionally maintains an archive to store the obsolete parent individuals and then assembles the elites in both the current population and the archive to guide the mutation of all individuals. In this way, the diversity of the guiding exemplars in the mutation is expectedly promoted. With the guidance of these diverse elites, a good balance between exploration of the complex search space and exploitation of the found promising regions is hopefully maintained in DEGGDE. As a result, DEGGDE expectedly achieves good optimization performance in solving complex optimization problems. A large number of experiments are conducted on the CEC’2017 benchmark set with three different dimension sizes to demonstrate the effectiveness of DEGGDE. Experimental results have confirmed that DEGGDE performs competitively with or even significantly better than eleven state-of-the-art and representative DE variants.
AI-Enabled Condition Monitoring Framework for Indoor Mobile Cleaning Robots
Authors: Pookkuttath Sathian , Veerajagadheswar Prabakaran , Rajesh Elara Mohan
Published: August 2023

Autonomous mobile cleaning robots are ubiquitous today and have a vast market need. Current studies are mainly focused on autonomous cleaning performances, and there exists a research gap on monitoring the robot’s health and safety. Vibration is a key indicator of system deterioration or external factors causing accelerated degradation or threats. Hence, this work proposes an artificial intelligence (AI)-enabled automated condition monitoring (CM) framework using two heterogeneous sensor datasets to predict the sources of anomalous vibration in mobile robots with high accuracy. This allows triggering proper maintenance or corrective actions based on the condition of the robot’s health or workspace, easing condition-based maintenance (CbM). Anomalous vibration sources are classified as induced by uneven Terrain, Collision with obstacles, loose Assembly, and unbalanced Structure, which causes accelerated system deterioration or potential hazards. Here, an unexplored heterogeneous sensor dataset using inertial measurement unit (IMU) and current sensors is proposed for effective recognition across different vibration classes, resulting in higher-accuracy prediction. A simple-structured 1D convolutional neural network (1D CNN) is developed for training and real-time prediction. A 2D CbM map is generated by fusing the predicted classes in real time on an occupancy grid map of the workspace to monitor the conditions of the robot and workspace remotely. The evaluation test results of the proposed method show that the usage of heterogeneous sensors performs significantly more accurately (98.4%) than previous studies, which used IMU (92.2%) and camera (93.8%) sensors individually. Also, this model is comparatively fast, fit for the environment, and ideal for real-time applications in mobile robots based on field trial validations, enhancing mobile robots’ productivity and operational safety.
Numerical Solution of Transition to Turbulence over Compressible Ramp at Hypersonic Velocity
Authors: Holman Jiří
Published: August 2023

This work deals with the numerical solution of hypersonic flow of viscous fluid over a compressible ramp. The solved case involves very important and complicated phenomena such as the interaction of the shock wave with the boundary layer or the transition from a laminar to a turbulent state. This type of problem is very important as it is often found on re-entry vehicles, engine intakes, system and sub-system junctions, etc. Turbulent flow is modeled by the system of averaged Navier–Stokes equations, which is completed by the explicit algebraic model of Reynolds stresses (EARSM model) and further enhanced by the algebraic model of bypass transition. The numerical solution is obtained by the finite volume method based on the rotated-hybrid Riemann solver and explicit multistage Runge–Kutta method. The numerical solution is then compared with the results of a direct numerical simulation.
Building Up of Fuzzy Evaluation Model of Life Performance Based on Type-II Censored Data
Authors: Chiou Kuo-Ching
Published: August 2023

The semiconductor industry is a rapidly growing sector. As collection technologies for production data continue to improve and the Internet of Things matures, production data analysis improves, thus accelerating progress towards smart manufacturing. This not only enhances the process quality, but also increases product lifetime and reliability. Under the assumption of exponential distribution, the ratio of lifetime and warranty has been proposed as a lifetime performance index for electronic products. As unknown parameters of the index, to use point estimates to assess lifetime performance may cause misjudgment due to sampling errors. In addition, cost and time limitations often lead to small sample sizes that can affect the results of the analysis. Type-II censored data are widely applied in production and manufacturing engineering. Thus, this paper proposes an unbiased and consistent estimator of lifetime performance based on type-II censored data. The 100(1 − α)% confidence interval of the proposed index is derived based on its probability density function. Overly small sample sizes not only make the length estimates of lifetime performance index intervals for electronic products too long, but they also increase sampling errors, which distort the estimation and test results. We therefore used the aforementioned interval to construct a fuzzy test model for the assessment of product lifetime and further help manufacturers to be more prudent and precise to evaluate the performance of product life cycles. A numerical example illustrates the applicability of the proposed model.
DAG: Dual Attention Graph Representation Learning for Node Classification
Authors: Lin Siyi , Hong Jie , Lang Bo , Huang Lin
Published: August 2023

Transformer-based graph neural networks have accomplished notable achievements by utilizing the self-attention mechanism for message passing in various domains. However, traditional methods overlook the diverse significance of intra-node representations, focusing solely on internode interactions. To overcome this limitation, we propose a DAG (Dual Attention Graph), a novel approach that integrates both intra-node and internode dynamics for node classification tasks. By considering the information exchange process between nodes from dual branches, DAG provides a holistic understanding of information propagation within graphs, enhancing the interpretability of graph-based machine learning applications. The experimental evaluations demonstrate that DAG excels in node classification tasks, outperforming current benchmark models across ten datasets.
Two New Matrix Classes Related to the CMP Inverse: CMP and Co-CMP Matrices
Authors: Chen Yinlan , Gao Jiale , Zuo Kezheng
Published: August 2023

This paper focuses on two new matrix classes related to the CMP inverse of a square matrix, called the CMP and co-CMP matrices. Some of their characterizations are identified based on the core-EP decomposition and subspace operations. And, we show an equivalence relationship between the co-CMP matrix set and the intersection of the core matrix set and the co-EP matrix set. The nonsingularity of other matrices closely associated with the co-CMP matrices is considered, and their inverses are presented in a decomposition form.
Ascoli-Type Theorem for Baire 1 Functions
Authors: Holá Ľubica
Published: August 2023

Let X, Y be metric spaces and B1(X,Y) be the space of Baire 1 functions from X to Y. The main purpose of this paper is to study compact subsets of B1(X,Y) equipped with the topology τUC of uniform convergence on compacta and prove Ascoli-type theorem for locally bounded Baire 1 functions. The key notion in our paper is the notion of equi-Lebesgue family of functions from X to Y.
Synchronization of Takagi–Sugeno Fuzzy Time-Delayed Stochastic Bidirectional Associative Memory Neural Networks Driven by Brownian Motion in Pre-Assigned Settling Time
Authors: Wang Chengqiang , Zhao Xiangqing , Wang Can , Lv Zhiwei
Published: August 2023

We are devoted, in this paper, to the study of the pre-assigned-time drive-response synchronization problem for a class of Takagi–Sugeno fuzzy logic-based stochastic bidirectional associative memory neural networks, driven by Brownian motion, with continuous-time delay and (finitely and infinitely) distributed time delay. To achieve the drive-response synchronization between the neural network systems, concerned in this paper, and the corresponding response neural network systems (identical to our concerned neural network systems), we bring forward, based on the structural properties, a class of control strategies. By meticulously coining an elaborate Lyapunov–Krasovskii functional, we prove a criterion guaranteeing the desired pre-assigned-time drive-response synchronizability: For any given positive time instant, some of our designed controls make sure that our concerned neural network systems and the corresponding response neural network systems achieve synchronization, with the settling times not exceeding the pre-assigned positive time instant. In addition, we equip our theoretical studies with a numerical example, to illustrate that the synchronization controls designed in this paper are indeed effective. Our concerned neural network systems incorporate several types of time delays simultaneously, in particular, they have a continuous-time delay in their leakage terms, are based on Takagi–Sugeno fuzzy logic, and can be synchronized before any pre-given finite-time instant by the suggested control; therefore, our theoretical results in this paper have wide potential applications in the real world. The conservatism is reduced by introducing parameters in our designed Lyapunov–Krasovskii functional and synchronization control.
Physics-to-Geometry Transformation to Construct Identities between Reynolds Stresses
Authors: Ryu Sungmin
Published: August 2023

Modeling has become firmly established as a methodology to close the Reynolds-averaged Navier–Stokes (RANS) equations, owing to theoretical and empirical efforts towards a complete formulation of the Reynolds stress tensor and, recently, breakthroughs in data-processing technology. However, mathematical exactness is not generally ensured by modeling, which is an intrinsic reason why the reliability of RANS closure models is not supposed to be consistent for all kinds of turbulent flow. Rather than straightforwardly overcoming this inherent limitation, most of the studies to date were reasonably directed towards broadening the range of turbulent flows, where reliable prediction accuracy can be obtained via modeling. In this paper, we present three identities between components of the Reynolds stress tensor, constructed via spatial mapping on the basis of the differential version of the Gauss–Bonnet formula. Further, we present a constraint condition that gives a set of equations as numerous as the parameters within a RANS model.
From Cells to Environment: Exploring the Interplay between Factors Shaping Bone Health and Disease
Authors: Singh Samradhi , Sarma Devojit Kumar , Verma Vinod , Nagpal Ravinder , Kumar Manoj
Published: August 2023

The skeletal system is an extraordinary structure that serves multiple purposes within the body, including providing support, facilitating movement, and safeguarding vital organs. Moreover, it acts as a reservoir for essential minerals crucial for overall bodily function. The intricate interplay of bone cells plays a critical role in maintaining bone homeostasis, ensuring a delicate balance. However, various factors, both intrinsic and extrinsic, can disrupt this vital physiological process. These factors encompass genetics, aging, dietary and lifestyle choices, the gut microbiome, environmental toxins, and more. They can interfere with bone health through several mechanisms, such as hormonal imbalances, disruptions in bone turnover, direct toxicity to osteoblasts, increased osteoclast activity, immune system aging, impaired inflammatory responses, and disturbances in the gut–bone axis. As a consequence, these disturbances can give rise to a range of bone disorders. The regulation of bone’s physiological functions involves an intricate network of continuous processes known as bone remodeling, which is influenced by various intrinsic and extrinsic factors within the organism. However, our understanding of the precise cellular and molecular mechanisms governing the complex interactions between environmental factors and the host elements that affect bone health is still in its nascent stages. In light of this, this comprehensive review aims to explore emerging evidence surrounding bone homeostasis, potential risk factors influencing it, and prospective therapeutic interventions for future management of bone-related disorders.
ACE2 and a Traditional Chinese Medicine Formula NRICM101 Could Alleviate the Inflammation and Pathogenic Process of Acute Lung Injury
Authors: Lin Cheng-Han , Chen Yi-Ju , Lin Meng-Wei , Chang Ho-Ju , Yang Xin-Rui , Lin Chih-Sheng
Published: August 2023

COVID-19 is a highly transmittable respiratory illness caused by SARS-CoV-2, and acute lung injury (ALI) is the major complication of COVID-19. The challenge in studying SARS-CoV-2 pathogenicity is the limited availability of animal models. Therefore, it is necessary to establish animal models that can reproduce multiple characteristics of ALI to study therapeutic applications. The present study established a mouse model that has features of ALI that are similar to COVID-19 syndrome to investigate the role of ACE2 and the administration of the Chinese herbal prescription NRICM101 in ALI. Mice with genetic modifications, including overexpression of human ACE2 (K18-hACE2 TG) and absence of ACE2 (mACE2 KO), were intratracheally instillated with hydrochloric acid. The acid intratracheal instillation induced severe immune cell infiltration, cytokine storms, and pulmonary disease in mice. Compared with K18-hACE2 TG mice, mACE2 KO mice exhibited dramatically increased levels of multiple inflammatory cytokines (IL-6 and TNF-α) in bronchoalveolar lavage fluid, histological evidence of lung injury, and dysregulation of MAPK and MMP activation. In mACE2 KO mice, NRICM101 could ameliorate the disease progression of acid-induced ALI. In conclusion, the established mouse model provided an effective platform for researchers to investigate pathological mechanisms and develop therapeutic strategies for ALI, including COVID-19-related ALI.
Geometrical Characterisation of TiO2-rGO Field-Effect Transistor as a Platform for Biosensing Applications
Authors: Alim Anis Amirah , Roslan Roharsyafinaz , Nadzirah Sh. , Saidi Lina Khalida , Menon P. Susthitha , Aziah Ismail , Chang Fu Dee , Sulaiman Siti Aishah , Abdul Murad Nor Azian , Hamzah Azrul Azlan
Published: August 2023

The performance of the graphene-based field-effect transistor (FET) as a biosensor is based on the output drain current (Id). In this work, the signal-to-noise ratio (SNR) was investigated to obtain a high-performance device that produces a higher Id value. Using the finite element method, a novel top-gate FET was developed in a three-dimensional (3D) simulation model with the titanium dioxide-reduced graphene oxide (TiO2-rGO) nanocomposite as the transducer material, which acts as a platform for biosensing application. Using the Taguchi mixed-level method in Minitab software (Version 16.1.1), eighteen 3D models were designed based on an orthogonal array L18 (6134), with five factors, and three and six levels. The parameters considered were the channel length, electrode length, electrode width, electrode thickness and electrode type. The device was fabricated using the conventional photolithography patterning technique and the metal lift-off method. The material was synthesised using the modified sol–gel method and spin-coated on top of the device. According to the results of the ANOVA, the channel length contributed the most, with 63.11%, indicating that it was the most significant factor in producing a higher Id value. The optimum condition for the highest Id value was at a channel length of 3 µm and an electrode size of 3 µm × 20 µm, with a thickness of 50 nm for the Ag electrode. The electrical measurement in both the simulation and experiment under optimal conditions showed a similar trend, and the difference between the curves was calculated to be 28.7%. Raman analyses were performed to validate the quality of TiO2-rGO.
Numerical Modeling of Physical Cell Trapping in Microfluidic Chips
Authors: Cardona Sara , Mostafazadeh Nima , Luan Qiyue , Zhou Jian , Peng Zhangli , Papautsky Ian
Published: August 2023

Microfluidic methods have proven to be effective in separation and isolation of cells for a wide range of biomedical applications. Among these methods, physical trapping is a label-free isolation approach that relies on cell size as the selective phenotype to retain target cells on-chip for follow-up analysis and imaging. In silico models have been used to optimize the design of such hydrodynamic traps and to investigate cancer cell transmigration through narrow constrictions. While most studies focus on computational fluid dynamics (CFD) analysis of flow over cells and/or pillar traps, a quantitative analysis of mechanical interaction between cells and trapping units is missing. The existing literature centers on longitudinally extended geometries (e.g., micro-vessels) to understand the biological phenomenon rather than designing an effective cell trap. In this work, we aim to make an experimentally informed prediction of the critical pressure for a cell to pass through a trapping unit as a function of cell morphology and trapping unit geometry. Our findings show that a hyperelastic material model accurately captures the stress-related softening behavior observed in cancer cells passing through micro-constrictions. These findings are used to develop a model capable of predicting and extrapolating critical pressure values. The validity of the model is assessed with experimental data. Regression analysis is used to derive a mathematical framework for critical pressure. Coupled with CFD analysis, one can use this formulation to design efficient microfluidic devices for cell trapping and potentially perform downstream analysis of trapped cells.
Splicing Measurement and Compensation of Straightness Errors for Ultra-Precision Guideways
Authors: Zhou Lian , Zheng Nan , Li Jie , Yuan Zhigang , Wang Jian , Fang Fei , Xu Qiao
Published: August 2023

The straightness error of guideways is one of the key indicators of an ultra-precision machine, which plays an important role in the machining accuracy of a workpiece. In order to measure the straightness error of a long-distance ultra-precision guideway accurately, a splicing measurement for the straightness error of a guideway using a high-precision flat mirror and displacement sensor was proposed in this paper, and the data splicing processing algorithm based on coordinate transformation was studied. Then, comparative experiments on a splicing measurement and direct measurement of the straightness error were carried out on a hydrostatic guideway grinder. The maximum difference between the two measurements was 0.3 μm, which was far less than the straightness error of 5.8 μm. The experiment demonstrated the correctness of the proposed splicing measurement method and data processing algorithm. To suppress the influence of the straightness error on machining accuracy, a straightness error compensation algorithm based on error rotation transformation and vertical axis position correction was proposed, and the grinding experiment of a plane optics with a size of 1400 mm × 500 mm was carried out. Without error compensation grinding, the flatness error of the element was 7.54 μm. After error compensation grinding, the flatness error was significantly reduced to 2.98 μm, which was less than the straightness errors of the guideways. These results demonstrated that the straightness error of the grinding machine had been well suppressed.
A Four-Port MIMO Cylindrical DRA with High Isolation in Ultra-Compact Size for WLAN Applications
Authors: Li Xue-Ping , Ji Jun-Fei , Duan Chang-Jiao , Sun Qian-Qian , Li Wei , Zhang An-Xue
Published: August 2023

A novel ultra-compact four-port multiple-input-multiple-output (MIMO) cylindrical dielectric resonator antenna (DRA) with improved isolation is proposed for WLAN applications in this paper. The antenna is originally radiated with the assistance of two different excitation mechanisms to generate decoupled orthogonal modes. To further diminish the coupling field and improve the isolation, a suitable U-shaped slot is created on the common ground plane. Two additional rectangular slits are also etched to adjust the impedance matching of other ports. To better reveal the operating mechanism of the decoupling scheme, the common mode (CM) and differential mode (DM) impedance analysis methods between DRA ports are presented. The etched U-shaped slot can tune the impedance of CM and DM to be consistent to realize the decoupling. The antenna is simulated, fabricated, and tested to verify the decoupling mechanism. The results demonstrate that the isolation between ports 1 and 2 is enhanced from 5 dB to 23 dB, and other ports exhibit low coupling of better than 12 dB. Moreover, the antenna with the full size of 30 × 30 × 8.1 mm3 can be used either as a four-port DRA with a bandwidth of 300 MHz or as a two-port DRA with a bandwidth of 700 MHz, at a center frequency of 5.6 GHz.
CS-GA-XGBoost-Based Model for a Radio-Frequency Power Amplifier under Different Temperatures
Authors: Wang Jiayi , Zhou Shaohua
Published: August 2023

Machine learning methods, such as support vector regression (SVR) and gradient boosting, have been introduced into the modeling of power amplifiers and achieved good results. Among various machine learning algorithms, XGBoost has been proven to obtain high-precision models faster with specific parameters. Hyperparameters have a significant impact on the model performance. A traditional grid search for hyperparameters is time-consuming and labor-intensive and may not find the optimal parameters. To solve the problem of parameter searching, improve modeling accuracy, and accelerate modeling speed, this paper proposes a PA modeling method based on CS-GA-XGBoost. The cuckoo search (CS)-genetic algorithm (GA) integrates GA’s crossover operator into CS, making full use of the strong global search ability of CS and the fast rate of convergence of GA so that the improved CS-GA can expand the size of the bird nest population and reduce the scope of the search, with a better optimization ability and faster rate of convergence. This paper validates the effectiveness of the proposed modeling method by using measured input and output data of 2.5-GHz-GaN class-E PA under different temperatures (−40 °C, 25 °C, and 125 °C) as examples. The experimental results show that compared to XGBoost, GA-XGBoost, and CS-XGBoost, the proposed CS-GA-XGBoost can improve the modeling accuracy by one order of magnitude or more and shorten the modeling time by one order of magnitude or more. In addition, compared with classic machine learning algorithms, including gradient boosting, random forest, and SVR, the proposed CS-GA-XGBoost can improve modeling accuracy by three orders of magnitude or more and shorten modeling time by two orders of magnitude, demonstrating the superiority of the algorithm in terms of modeling accuracy and speed. The CS-GA-XGBoost modeling method is expected to be introduced into the modeling of other devices/circuits in the radio-frequency/microwave field and achieve good results.
Integration of Capacitive Pressure Sensor-on-Chip with Lead-Free Perovskite Solar Cells for Continuous Health Monitoring
Authors: Abdellatif Sameh O. , Moustafa Afaf , Khalid Ahmed , Ghannam Rami
Published: August 2023

The increasing prevalence of hypertension necessitates continuous blood pressure monitoring. This can be safely and painlessly achieved using non-invasive wearable electronic devices. However, the integration of analog, digital, and power electronics into a single system poses significant challenges. Therefore, we demonstrated a comprehensive multi-scale simulation of a sensor-on-chip that was based on a capacitive pressure sensor. Two analog interfacing circuits were proposed for a full-scale operation ranging from 0 V to 5 V, enabling efficient digital data processing. We also demonstrated the integration of lead-free perovskite solar cells as a mechanism for self-powering the sensor. The proposed system exhibits varying sensitivity from 1.4 × 10−3 to 0.095 (kPa)−1, depending on the pressure range of measurement. In the most optimal configuration, the system consumed 50.5 mW, encompassing a 6.487 mm2 area for the perovskite cell and a CMOS layout area of 1.78 × 1.232 mm2. These results underline the potential for such sensor-on-chip designs in future wearable health-monitoring technologies. Overall, this paper contributes to the field of wearable health-monitoring technologies by presenting a novel approach to self-powered blood pressure monitoring through the integration of capacitive pressure sensors, analog interfacing circuits, and lead-free perovskite solar cells.
Evaluation of Three Serological Tests for Diagnosis of Canine Brucellosis
Authors: Perletta Fabrizia , Di Pancrazio Chiara , Rodomonti Diamante , Di Febo Tiziana , Luciani Mirella , Krasteva Ivanka Marinova , Maggetti Marta , Profeta Francesca , Salini Romolo , De Massis Fabrizio , Sacchini Flavio , Tittarelli Manuela
Published: August 2023

Canine brucellosis caused by Brucella canis, is an infectious disease affecting dogs and wild Canidae. Clinical diagnosis is challenging, and laboratory testing is crucial for a definitive diagnosis. Various serological methods have been described, but their accuracy is uncertain due to limited validation studies. The present study aimed to evaluate the performances of three serological tests for the diagnosis of B. canis in comparison with bacterial isolation (gold standard), in order to establish a protocol for the serological diagnosis of canine brucellosis. A panel of sera from naturally infected dogs (n = 61), from which B. canis was isolated, and uninfected dogs (n = 143), negative for B. canis isolation, were tested using microplate serum agglutination (mSAT), complement fixation performed using the Brucella ovis antigen (B. ovis-CFT), and a commercial immunofluorescence assay (IFAT). The sensitivity and specificity of the three serological methods were, respectively, the following: 96.7% (95% CI 88.8–98.7%) and 92.3 (95% CI 86.7–95.1%) for mSAT; 96.7% (95% CI 88.8–98.7%) and 96.5 (95% CI 92.1–98.2%) for B. ovis-CFT; 98.4% (95% CI 91.3–99.4%) and 99.3 (95% CI 96.2–99.8%) for IFAT. The use in of the three methods in parallel, combined with bacterial isolation and molecular methods, could improve the diagnosis of the infection in dogs.
In Vitro Biofilm-Mediated Biodegradation of Pesticides and Dye-Contaminated Effluents Using Bacterial Biofilms
Authors: Liaqat Iram , Khalid Awais , Rubab Saima , Rashid Farzana , Latif Asma Abdul , Naseem Sajida , Bibi Asia , Khan Bushra Nisar , Ansar Waiza , Javed Arshad , Afzaal Muhammad , Summer Muhammad , Majid Samia , Ali Sikander , Aftab Muhammad Nauman
Published: August 2023

Overuse of pesticides in agricultural soil and dye-polluted effluents severely contaminates the environment and is toxic to animals and humans making their removal from the environment essential. The present study aimed to assess the biodegradation of pesticides (cypermethrin (CYP) and imidacloprid (IMI)), and dyes (malachite green (MG) and Congo red (CR)) using biofilms of bacteria isolated from pesticide-contaminated soil and dye effluents. Biofilms of indigenous bacteria, i.e., Bacillus thuringiensis 2A (OP554568), Enterobacter hormaechei 4A (OP723332), Bacillus sp. 5A (OP586601), and Bacillus cereus 6B (OP586602) individually and in mixed culture were tested against CYP and IMI. Biofilms of indigenous bacteria i.e., Lysinibacillus sphaericus AF1 (OP589134), Bacillus sp. CF3 (OP589135) and Bacillus sp. DF4 (OP589136) individually and in mixed culture were tested for their ability to degrade dyes. The biofilm of a mixed culture of B. thuringiensis + Bacillus sp. (P7) showed 46.2% degradation of CYP compared to the biofilm of a mixed culture of B. thuringiensis + E. hormaechei + Bacillus sp. + B. cereus (P11), which showed significantly high degradation (70.0%) of IMI. Regarding dye biodegradation, a mixed culture biofilm of Bacillus sp. + Bacillus sp. (D6) showed 86.76% degradation of MG, which was significantly high compared to a mixed culture biofilm of L. sphaericus + Bacillus sp. (D4) that degraded only 30.78% of CR. UV–VIS spectroscopy revealed major peaks at 224 nm, 263 nm, 581 nm and 436 nm for CYP, IMI, MG and CR, respectively, which completely disappeared after treatment with bacterial biofilms. Fourier transform infrared (FTIR) analysis showed the appearance of new peaks in degraded metabolites and disappearance of a peak in the control spectrum after biofilm treatment. Thin layer chromatography (TLC) analysis also confirmed the degradation of CYP, IMI, MG and CR into several metabolites compared to the control. The present study demonstrates the biodegradation potential of biofilm-forming bacteria isolated from pesticide-polluted soil and dye effluents against pesticides and dyes. This is the first report demonstrating biofilm-mediated bio-degradation of CYP, IMI, MG and CR utilizing soil and effluent bacterial flora from Multan and Sheikhupura, Punjab, Pakistan.
The Isolation, Genetic Analysis and Biofilm Characteristics of Listeria spp. from the Marine Environment in China
Authors: Mao Pan , Wang Yan , Li Lingling , Ji Shunshi , Li Peijing , Liu Lingyun , Chen Jinni , Sun Hui , Luo Xia , Ye Changyun
Published: August 2023

Listeria monocytogenes is an important pathogen that can cause listeriosis. Despite the growing recognition of Listeria spp. as a foodborne and environmental pathogen, the understanding of its prevalence and characteristics of Listeria spp. in the marine environment remains unknown. In this study, we first investigated the genetic and phenotypic characteristics of Listeria species isolated in a coastal city in China. The findings revealed that the sequence type 87 (ST87) L. monocytogenes, a prevalent clinical and seafood strain in China, dominates in recreational beach sands and possesses a notable biofilm-forming capacity in seawater. The presence of ST87 L. monocytogenes in coastal environments indicates the potential health risks for both recreational activities and seafood consumption. Moreover, the ST121 isolates from sand had a versatile plasmid encoding multifunctional genes, including uvrX for UV resistance, gbuC for salt resistance, and npx for oxidative resistance and multiple transposases, which potentially aid in survival under natural environments. Black-headed gulls potentially facilitate the spread of L. monocytogenes, with similar ST35 strains found in gulls and beach sand. As a reservoir of microbes from marine environments and human/animal excrement, coastal sand would play an important role in the spread of L. monocytogenes and is an environmental risk for human listeriosis.
Decoding the Microbiome’s Influence on Rheumatoid Arthritis
Authors: Coradduzza Donatella , Bo Marco , Congiargiu Antonella , Azara Emanuela , De Miglio Maria , Erre Gian Luca , Carru Ciriaco
Published: August 2023

The aim is better to understand and critically explore and present the available data from observational studies on the pathogenetic role of the microbiome in the development of rheumatoid arthritis (RA). The electronic databases PubMed, Scopus, and Web of Science were screened for the relevant literature published in the last ten years. The primary outcomes investigated included the influence of the gut microbiome on the pathogenesis and development of rheumatoid arthritis, exploring the changes in microbiota diversity and relative abundance of microbial taxa in individuals with RA and healthy controls (HCs). The risk of bias in the included literature was assessed using the GRADE criteria. Ten observational studies were identified and included in the qualitative assessment. A total of 647 individuals with RA were represented in the literature, in addition to 16 individuals with psoriatic arthritis (PsA) and 247 HCs. The biospecimens comprised fecal samples across all the included literature, with 16S rDNA sequencing representing the primary method of biological analyses. Significant differences were observed in the RA microbiome compared to that of HCs: a decrease in Faecalibacterium, Fusicatenibacter, Enterococcus, and Megamonas and increases in Eggerthellales, Collinsella, Prevotella copri, Klebsiella, Escherichia, Eisenbergiella, and Flavobacterium. There are significant alterations in the microbiome of individuals with RA compared to HCs. This includes an increase in Prevotella copri and Lactobacillus and reductions in Collinsella. Collectively, these alterations are proposed to induce inflammatory responses and degrade the integrity of the intestinal barrier; however, further studies are needed to confirm this relationship.