bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi-Robot Collaborative Flexible Manufacturing and Digital Twin System Design of Circuit Breakers
Authors: Wang Linghao , Shu Liang , Zhou Hao
Published: February 2023

Circuit breakers (CBs) are mainly designed to interrupt current flow when faults are detected and have been widely used in industrial applications. The existing CBs manufacturing method is semi-automatic and requires a lot of labor. To realize flexible manufacturing, a multi-robot cooperative CBs flexible manufacturing system (CBFMS) is presented in this study. Aiming at the efficiency of the multi-robot cooperative CBFMS key units, a two-arm cooperation robot approach is proposed. The reinforcement learning algorithm is developed to optimize the manufacturing trajectory of the two-arm cooperation robot. To build and optimize the multi-robot cooperative CBFMS, a digital twin (DT) system describing all physical properties of the physical manufacturing plant is constructed for simulation. In the developed DT system, a kinematic control model of the collaboration robot is established. A real-time display of the robot’s trajectory, manufacturing status, and process manufacturing is provided by the data interaction with the physical cell flow between the units. Following this design, a synchronous mapping between the flexible manufacturing DT system of the CBs and the physical workshop is realized, which enables real-time monitoring and management of the physical production line. The experiments’ results show that the manufacturing efficiency, compared with traditional CBs production, is improved by 22%. Moreover, the multi-robot cooperative CBFMS can make process changes according to the production requirements, which can improve the stability of production.
Error Similarity Analysis and Error Compensation of Industrial Robots with Uncertainties of TCP Calibration
Authors: Li Yufei , Li Bo , Zhao Xidong , Cheng Simiao , Zhang Wei , Tian Wei
Published: February 2023

The machining system based on an industrial robot is a new type of equipment to meet the requirements of high quality, high efficiency and high flexibility for large and complex components of aircraft and spacecraft. The error compensation technology is widely used in robotic machining to improve the positioning accuracy of an industrial robot with the intention of meeting the precision requirements of aerospace manufacturing. However, the robot’s positioning accuracy decreases significantly when the orientation of the tool changes dramatically. This stems from the fact that the existing robot compensation methods ignore the uncertainties of Tool Center Point (TCP) calibration. This paper presents a novel regionalized compensation method for improving the positioning accuracy of the robot with calibration uncertainties and large orientation variation of the TCP. The method is experimentally validated through the drilling of curved surface parts of plexiglass using a KUKA KR2830MT robot. Compared with a published error compensation method, the proposed approach improves the positioning accuracy of the robot under the large orientation variation to 0.235 mm. This research can broaden the field of robot calibration technology and further improve the adaptability of robotic machining.
Document-Level Event Role Filler Extraction Using Key-Value Memory Network
Authors: Wang Hao , Li Miao , Duan Jianyong , He Li , Zhang Qing
Published: February 2023

Previous work has demonstrated that end-to-end neural sequence models work well for document-level event role filler extraction. However, the end-to-end neural network model suffers from the problem of not being able to utilize global information, resulting in incomplete extraction of document-level event arguments. This is because the inputs to BiLSTM are all single-word vectors with no input of contextual information. This phenomenon is particularly pronounced at the document level. To address this problem, we propose key-value memory networks to enhance document-level contextual information, and the overall model is represented at two levels: the sentence-level and document-level. At the sentence-level, we use BiLSTM to obtain key sentence information. At the document-level, we use a key-value memory network to enhance document-level representations by recording information about those words in articles that are sensitive to contextual similarity. We fuse two levels of contextual information by means of a fusion formula. We perform various experimental validations on the MUC-4 dataset, and the results show that the model using key-value memory networks works better than the other models.
Research on the Path Planning of Unmanned Sweepers Based on a Fusion Algorithm
Authors: Ma Yongjie , Ping Peng , Shi Quan
Published: February 2023

Path planning is one of the key technologies for unmanned driving. However, global paths are unable to avoid unknown obstacles, while local paths tend to fall into local optimality. To solve the problem of unsmooth and inefficient paths on multi-angle roads in a park which cannot avoid unknown obstacles, we designed a new fusion algorithm based on the improved A* and Open_Planner algorithms (A-OP). In order to make the global route smoother and more efficient, we first extracted the key points of the A* algorithm and improved the node search structure using heap sorting, and then improved the smoothness of the path using the minimum snap method; secondly, we extracted the key points of the A* algorithm as intermediate nodes in the planning of the Open_Planner algorithm, and used the A-OP algorithm to implement the path planning of the unmanned sweeper. The simulation results show that the improved A* algorithm significantly improved the planning efficiency, the nodes are less computed and the path is smoother. The fused A-OP algorithm not only accomplished global planning effectively, but also avoided unknown obstacles in the path.
Sep-RefineNet: A Deinterleaving Method for Radar Signals Based on Semantic Segmentation
Authors: Mao Yongjiang , Ren Wenjuan , Li Xipeng , Yang Zhanpeng , Cao Wei
Published: February 2023

With the progress of signal processing technology and the emergence of new system radars, the space electromagnetic environment becomes more and more complex, which puts forward higher requirements for the deinterleaving method of radar signals. Traditional signal deinterleaving algorithms rely heavily on manual experience threshold and have poor robustness. To address this problem, we designed an intelligent radar signal deinterleaving algorithm that was completed by encoding the frequency characteristic matrix and semantic segmentation network, named Sep-RefineNet. The frequency characteristic matrix can well construct the semantic features of different pulse streams of radar signals. The Sep-RefineNet semantic segmentation network can complete pixel-level segmentation of the frequency characteristic matrix and finally uses position decoding and verification to obtain the position in the original pulse stream to complete radar signals deinterleaving. The proposed method avoids the processing of threshold judgment and pulse sequence search in traditional methods. The results of the experiment show that this algorithm improves the deinterleaving accuracy and has a good against-noise ability of aliasing pulses and missing pulses.
The Influence of Dome Geometry on the Results of Modal and Buckling Analysis
Authors: Radoń Urszula , Zabojszcza Paweł , Sokol Milan
Published: February 2023

The main purpose of this paper is to compare the results of modal analysis for two types of domes. The first one is a low-rise Schwedler dome. The second one is a high-rise geodesic dome. The low-rise Schwedler dome is subjected to large displacement gradients and should be designed according to geometrical nonlinear analysis. In the case of high-rise geodesic dome, linear analysis is sufficient. In the modal analysis, the mass of the bars of the supporting structures was modeled as evenly distributed, while the mass of the covering and roof equipment was concentrated in the nodes. Classic calculations have been enriched with modal analysis taking into account normal forces. Normal forces affect the vibration frequency of the structure. Commonly used modal analysis does not take into account the influence of normal forces. In order to approximate the actual working conditions of the structure, calculations performed in Autodesk Robot Structure Professional 2022 can be performed in accordance with the modal analysis, taking into account the applied normal forces in the modal analysis. Additionally, stability loss was verified using linear or geometrical nonlinear buckling analysis. The exigence of including normal forces in modal analysis for low-rise domes is the novelty and main message of the work.
Optimal Complex Morlet Wavelet Parameters for Quantitative Time-Frequency Analysis of Molecular Vibration
Authors: Li Shuangquan , Ma Shangyi , Wang Shaoqing
Published: February 2023

When the complex Morlet function (CMOR) is used as a wavelet basis, it is necessary to select optimal bandwidth and center frequency. However, the method to select the optimal CMOR wavelet parameters for one specific frequency is still unclear. In this paper, we deeply investigate the essence of CMOR wavelet transform and clearly illustrate the time-frequency resolution and edge effect. Then, the selection method of the optimal bandwidth and center frequency is proposed. We further perform the quantitative time-frequency (QTF) analysis of water molecule vibration based on our method. We find that the CMOR wavelet parameters obtained by our method can not only meet the requirement of frequency resolution but also meet the limit of edge effect. Moreover, there is an uphill energy relaxation in the vibration of the water molecule, which agrees well with the experimental results. These results demonstrate that our method can accurately find the optimal CMOR wavelet parameters for the target frequency.
Biomechanical Analysis of Femoral Stem Features in Hinged Revision TKA with Valgus or Varus Deformity: A Comparative Finite Elements Study
Authors: Bori Edoardo , Innocenti Bernardo
Published: February 2023

Hinged total knee arthroplasty (TKA) is a valid option to treat patients during revision of an implant; however, in case of varus/valgus deformity, the force transmission from the femur to the tibia could be altered and therefore the performance of the implant could be detrimental. To be able to evaluate this, the goal of this study was to investigate, using a validated finite element analysis, the effect of varus/valgus load configurations in the bones when a hinged TKA is used. In detail, short and long stem lengths (50 mm, and 120 mm), were analyzed both under cemented or press-fit fixation under the following varus and valgus deformity: 5°, 10°, 20°, and 30°. The main outputs of the study were average bone stress in different regions of interest, together with tibio-femoral contact pressure and force. Results demonstrated that changes in the varus or valgus deformity degrees induce a change in the medio-lateral stress and force distribution, together with a change in the contact area. The effect of stem length and cement do not alter the tibio-femoral contact biomechanics but its effect is mainly localized in the distal femoral region, and it is negligible in the proximal regions.
Process Optimization of Microwave-Assisted Extraction of Chlorophyll, Carotenoid and Phenolic Compounds from Chlorella vulgaris and Comparison with Conventional and Supercritical Fluid Extraction
Authors: Georgiopoulou Ioulia , Tzima Soultana , Louli Vasiliki , Magoulas Kostis
Published: February 2023

The production of bioactive products from microalgae biomass with efficient and environmentally friendly technologies is a field of great research interest. The present work focuses on the recovery of high-added value bioactive components from Chlorella vulgaris through microwave-assisted extraction (MAE) with aq. ethanol 90% v/v. The effect of extraction temperature (40–60 °C), duration (5–25 min), solvent-to-biomass ratio (20–90 mLsolv/gbiom), and microwave power (300–800 watts) was investigated regarding the extraction yield, extract’s chlorophyll, carotenoid and phenolic content, and antioxidant activity. MAE optimization at 60 °C, 300 watts, 14 min, and 22 mLsolv/gbiom led to 11.14% w/w yield, 63.36 mg/gextr total chlorophylls, 7.06 mg/gextr selected carotenoids of astaxanthin, lutein and β-carotene, 24.88 mg/gextr total carotenoids, 9.34 mgGA/gextr total phenolics, and 40.49 mgextr/mgDPPH IC50 (antioxidant activity indicator). Moreover, the conventional solid-liquid extraction (SLE) with aq. ethanol 90% v/v, the supercritical fluid extraction (SFE) with CO2, as well as SFE with cosolvent addition (10% w/w ethanol), were also performed for comparison purposes. The results revealed that SLE presented the highest yield. However, the non-conventional methods of MAE and SFE led to extracts of competitive or even better quality under significantly shorter extraction duration.
Gap and Force Adjustment during Laser Beam Welding by Means of a Closed-Loop Control Utilizing Fixture-Integrated Sensors and Actuators
Authors: Schricker Klaus , Schmidt Leander , Friedmann Hannes , Bergmann Jean Pierre
Published: February 2023

The development of adaptive and intelligent clamping devices allows for the reduction of rejects and defects based on weld discontinuities in laser-beam welding. The utilization of fixture-integrated sensors and actuators is a new approach, realizing adaptive clamping devices that enable in-process data acquisition and a time-dependent adjustment of process conditions and workpiece position by means of a closed-loop control. The present work focused on sensor and actuator integration for an adaptive clamping device utilized for laser-beam welding in a butt-joint configuration, in which the position and acting forces of the sheets to be welded can be adjusted during the process (studied welding speeds: 1 m/min, 5 m/min). Therefore, a novel clamping system was designed allowing for the integration of inductive probes and force cells for obtaining time-dependent data of the joint gap and resulting forces during welding due to the displacement of the sheets. A novel automation engineering concept allowed the communication between different sensors, actuators and the laser-beam welding setup based on an EtherCAT bus. The subsequent development of a position control and a force control and their combination was operated with a real time PC as master in the bus system and proved the feasibility of the approach based on proportional controllers. Finally, the scalability regarding higher welding speeds was demonstrated.
Evaluation of Engineering Site and Subsurface Structures Using Seismic Refraction Tomography: A Case Study of Abydos Site, Sohag Governorate, Egypt
Authors: Abudeif Abdelbaset M. , Abdel Aal Gamal Z. , Abdelbaky Nessreen F. , Abdel Gowad Ahmed M. , Mohammed Mohammed A.
Published: February 2023

Because of the strategic importance of the Abydos archaeological site in Egypt as a source of wealth for Egyptian tourism, this study was concerned with carrying out geophysical measurements to detect subsurface succession and measure variations in the geotechnical engineering features of the soils/rocks in order to protect this significant area. The findings will assist geologists and seismologists in collaborating with archaeologists for future site development, revitalization, and investment. The primary objectives of this work were to determine the subsurface lithology, evaluate the engineering geotechnical properties of soils/rocks, identify the layer thicknesses, and identify the site class by calculating Vs30. To achieve these goals, seventeen (17) seismic refraction tomography (SRT) P- and S-wave measurements were executed in front of the Osirion location. SeisImager Software was used for the processing and interpretation of the outcomes. The results were the travel time–distance curves, which were used for building the 2D seismic models that exhibited the velocity and the depth of the layered models. These models were validated by our previous works using electric resistivity tomography and borehole data. The results indicated that this site consisted of three geoseismic subsurface layers. The first layer was the surface that was made up of wadi deposits, which were a mixture of gravel, sand, and silt and were characterized by incompetent to slightly competent materials. The second layer corresponded to the sand and muddy sand deposits of competent rock that was of fair to moderate quality. The third layer (clay deposits) had a higher velocity and was more compact and may be employed as a bedrock layer. The elastic moduli, Vs30, petrophysical, and geotechnical properties of the three geoseismic layers were appraised as essential parameters. Integration of petrophysical and geotechnical parameters and elastic moduli revealed that the third layer was composed of competent clays, which were characterized by low values of porosity, void ratio, Poisson ratio, and stress ratio. It also had a high rigidity, Young’s and bulk moduli, concentration and material indexes, N-value, ultimate bearing capacities, and high density values, and vice versa for the first layer. The standard NEHRP site class was B (rocks). These parameters are ordinarily used as key indications and serve as significant inputs for any future work.
Underwater Object Detection Method Based on Improved Faster RCNN
Authors: Wang Hao , Xiao Nanfeng
Published: February 2023

In order to better utilize and protect marine organisms, reliable underwater object detection methods need to be developed. Due to various influencing factors from complex and changeable underwater environments, the underwater object detection is full of challenges. Therefore, this paper improves a two-stage algorithm of Faster RCNN (Regions with Convolutional Neural Network Feature) to detect holothurian, echinus, scallop, starfish and waterweeds. The improved algorithm has better performance in underwater object detection. Firstly, we improved the backbone network of the Faster RCNN, replacing the VGG16 (Visual Geometry Group Network 16) structure in the original feature extraction module with the Res2Net101 network to enhance the expressive ability of the receptive field of each network layer. Secondly, the OHEM (Online Hard Example Mining) algorithm is introduced to solve the imbalance problem of positive and negative samples of the bounding box. Thirdly, GIOU (Generalized Intersection Over Union) and Soft-NMS (Soft Non-Maximum Suppression) are used to optimize the regression mechanism of the bounding box. Finally, the improved Faster RCNN model is trained using a multi-scale training strategy to enhance the robustness of the model. Through ablation experiments based on the improved Faster RCNN model, each improved part is disassembled and then the experiments are carried out one by one, which can be known from the experimental results that, based on the improved Faster RCNN model, mAP@0.5 reaches 71.7%, which is 3.3% higher than the original Faster RCNN model, and the average accuracy reaches 43%, and the F1-score reaches 55.3%, a 2.5% improvement over the original Faster RCNN model, which shows that the proposed method in this paper is effective in underwater object detection.
Robot Assisted THz Imaging with a Time Domain Spectrometer
Authors: Bachmann Dominik , Brönnimann Rolf , Caceres Luis Nicklaus , Gnannt Sofie L. , Hack Erwin , Mavrona Elena , Sacré Daniel , Zolliker Peter
Published: February 2023

THz-Time domain spectroscopic imaging is demonstrated combining a robotic scanning method with continuous signal acquisition and holographic reconstruction of the object to improve the imaging resolution. We apply the method to a metallic Siemens star in order to quantify resolution and to wood samples to demonstrate the technique on a non-metallic object with an unknown structure.
Prediction of the SO2 Hourly Concentration for Sea Breeze and Land Breeze in an Urban Area of Split Using Multiple Linear Regression
Authors: Trošić Lesar Tanja , Filipčić Anita
Published: February 2023

The main goal of this paper is to study pollution during sea breeze days in the Split town center, which is placed near the industrial area with three cement plants and one asbestos cement plant, as well as a harbor with high traffic, and investigate the sources of pollution with SO2 and its relation to atmospheric parameters using stepwise multiple linear regression (MLR). The hourly temperature difference from the time of the sea breeze lull (dT) was considered in evaluating the influence of meteorological parameters on hourly pollutant concentrations. It was found that the wind direction index (WDI) is a significant predictor for the sea breeze, and wind speed, relative humidity, and dT are significant for the land breeze. A very high index of agreement of 0.9 was obtained by the MLR model for the land breeze, and 0.8 for the sea breeze. Low SO2 concentrations are observed at night, and increased values are found between 0800 and 1800 UTC. With WDI being the only predictor during sea breeze, local traffic is found to be the main anthropogenic source of SO2 pollution.
Aczel–Alsina Hamy Mean Aggregation Operators in T-Spherical Fuzzy Multi-Criteria Decision-Making
Authors: Wang Haolun , Xu Tingjun , Feng Liangqing , Mahmood Tahir , Ullah Kifayat
Published: February 2023

A T-spherical fuzzy set is a more powerful mathematical tool to handle uncertain and vague information than several fuzzy sets, such as fuzzy set, intuitionistic fuzzy set, Pythagorean fuzzy set, q-rung orthopair fuzzy set, and picture fuzzy set. The Aczel–Alsina t-norm and s-norm are significant mathematical operations with a high premium on affectability with parameter activity, which are extremely conducive to handling imprecise and undetermined data. On the other hand, the Hamy mean operator is able to catch the interconnection among multiple input data and achieve great results in the fusion process of evaluation information. Based on the above advantages, the purpose of this study is to propose some novel aggregation operators (AOs) integrated by the Hamy mean and Aczel–Alsina operations to settle T-spherical fuzzy multi-criteria decision-making (MCDM) issues. First, a series of T-spherical fuzzy Aczel–Alsina Hamy mean AOs are advanced, including the T-spherical fuzzy Aczel–Alsina Hamy mean (TSFAAHM) operator, T-spherical fuzzy Aczel–Alsina dual Hamy mean (TSFAADHM) operator, and their weighted forms, i.e., the T-spherical fuzzy Aczel–Alsina-weighted Hamy mean (TSFAAWHM) and T-spherical fuzzy Aczel–Alsina-weighted dual Hamy mean (TSFAAWDHM) operators. Moreover, some related properties are discussed. Then, a MCDM model based on the proposed AOs is built. Lastly, a numerical example is provided to show the applicability and feasibility of the developed AOs, and the effectiveness of this study is verified by the implementation of a parameters influence test and comparison with available methods.
The Stereographic Projection in Topological Modules
Authors: García-Pacheco Francisco Javier
Published: February 2023

The stereographic projection is constructed in topological modules. Let A be an additively symmetric closed subset of a topological R-module M such that 0∈int(A). If there exists a continuous functional m*:M→R in the dual module M*, an invertible s∈U(R) and an element a in the topological boundary bd(A) of A in such a way that m*−1({s})∩int(A)=⌀, a∈m*−1({s})∩bd(A), and s+m*bd(A)\{−a}⊆U(R), then the following function b↦−a+2s(m*(b)+s)−1(b+a), from bd(A)\{−a} to (m*)−1({s}), is a well-defined stereographic projection (also continuous if multiplicative inversion is continuous on R). Finally, we provide sufficient conditions for the previous stereographic projection to become a homeomorphism.
Improvement on the Use of Se@C in Batteries by Synergistic Effect of Nano-Confinement and C-Se Bond
Authors: Wu Lijun , Guo Shoujie , Yue Hongwei , Li Hao , Li Wei , Yao Chuan , Li Pinjiang , Fa Wenjun , Song Burong , Li Kai , Zhou Bitao , Yu Qian , Xu Yunjun , Yang Changchun , Zheng Zhi , Gao Yuanhao
Published: February 2023

In order to alleviate the cyclic attenuation caused by the dissolution of poly-selenides in lithium/sodium storage devices, quantitative selenium was slowly evaporated on the surface of sodium citrate derived carbon (SCDC) at low temperature, and simultaneously the element Se was doped. Benefiting from the synergistic effects of the domain-limiting effect of embedded nanopores on Se nanoparticles and the stability of SCDC with Se doped during the embedding and stripping of Na ions, Se@C versus sodium metal exhibits high second specific capacity of 485 mAh·g−1 and unexpected stability at 0.1 A g−1 and 1 A g−1. Se@C versus lithium metal exhibits high second specific capacity of 1185 mAh·g−1 at 0.1 A g−1 and excellent stability. Together with the simple and application of synthesis method, Se@C composite is expected to become an anode material for large sodium/lithium storage devices.
Establishment of an Integrated CRISPR/Cas9 Plasmid System for Simple and Efficient Genome Editing in Medaka In Vitro and In Vivo
Authors: Zhang Zeming , Wang Jie , Li Jianeng , Liu Xiang , Liu Lei , Zhao Changle , Tao Wenjing , Wang Deshou , Wei Jing
Published: February 2023

Although CRISPR/Cas9 has been used in gene manipulation of several fish species in vivo, its application in fish cultured cells is still challenged and limited. In this study, we established an integrated CRISPR/Cas9 plasmid system and evaluated its efficiency of gene knock-out or knock-in at a specific site in medaka (Oryzias latipes) in vitro and in vivo. By using the enhanced green fluorescent protein reporter plasmid pGNtsf1, we demonstrate that pCas9-U6sgRNA driven by endogenous U6 promoter (pCas9-mU6sgRNA) mediated very high gene editing efficiency in medaka cultured cells, but not by exogenous U6 promoters. After optimizing the conditions, the gene editing efficiencies of eight sites targeting for four endogenous genes were calculated, and the highest was up to 94% with no detectable off-target. By one-cell embryo microinjection, pCas9-mU6sgRNA also mediated efficient gene knock-out in vivo. Furthermore, pCas9-mU6sgRNA efficiently mediated gene knock-in at a specific site in medaka cultured cells as well as embryos. Collectively, our study demonstrates that the genetic relationship of U6 promoter is critical to gene editing efficiency in medaka cultured cells, and a simple and efficient system for medaka genome editing in vitro and in vivo has been established. This study provides an insight into other fish genome editing and promotes gene functional analysis.
Role of Altered Metabolism of Triglyceride-Rich Lipoprotein Particles in the Development of Vascular Dysfunction in Systemic Lupus Erythematosus
Authors: Diószegi Ágnes , Lőrincz Hajnalka , Kaáli Eszter , Soltész Pál , Perge Bianka , Varga Éva , Harangi Mariann , Tarr Tünde
Published: February 2023

Background: Impaired lipid metabolism contributes to accelerated inflammatory responses in addition to promoting the formation of atherosclerosis in systemic lupus erythematosus (SLE). We aimed to evaluate the lipid profile, inflammatory markers, and vascular diagnostic tests in active SLE patients to clarify the association between dyslipidemia and early vascular damage. Patients and Methods: 51 clinically active SLE patients and 41 age- and gender-matched control subjects were enrolled in the study. Lipoprotein subfractions were detected by Lipoprint. Brachial artery flow-mediated dilation and common carotid intima-media thickness were detected by ultrasonography. Arterial stiffness indicated by augmentation index (Aix) and pulse wave velocity was measured by arteriography. Results: We found significantly higher Aix, higher VLDL ratio, plasma triglyceride, ApoB100, and small HDL, as well as lower HDL-C, large HDL, and ApoA1 in patients with SLE. There was a significant positive correlation of Aix with triglyceride, VLDL, IDL-C, IDL-B, and LDL1. A backward stepwise multiple regression analysis showed IDL-C subfraction to be the best predictor of Aix. Conclusions: Our results indicate that in young patients with SLE, triglyceride-rich lipoproteins influence vascular function detected by Aix. These parameters may be assessed and integrated into the management plan for screening cardiovascular risk in patients with SLE.
Prostate Ultrasound Image Segmentation Based on DSU-Net
Authors: Wang Xinyu , Chang Zhengqi , Zhang Qingfang , Li Cheng , Miao Fei , Gao Gang
Published: February 2023

In recent years, the incidence of prostate cancer in the male population has been increasing year by year. Transrectal ultrasound (TRUS) is an important means of prostate cancer diagnosis. The accurate segmentation of the prostate in TRUS images can assist doctors in needle biopsy and surgery and is also the basis for the accurate identification of prostate cancer. Due to the asymmetric shape and blurred boundary line of the prostate in TRUS images, it is difficult to obtain accurate segmentation results with existing segmentation methods. Therefore, a prostate segmentation method called DSU-Net is proposed in this paper. This proposed method replaces the basic convolution in the U-Net model with the improved convolution combining shear transformation and deformable convolution, making the network more sensitive to border features and more suitable for prostate segmentation tasks. Experiments show that DSU-Net has higher accuracy than other existing traditional segmentation methods.
Nanobody-Based Sandwich Immunoassay for Pathogenic Escherichia coli F17 Strain Detection
Authors: Dhehibi Asma , Allaoui Abdelmounaaim , Raouafi Amal , Terrak Mohammed , Bouhaouala-Zahar Balkiss , Hammadi Mohamed , Raouafi Noureddine , Salhi Imed
Published: February 2023

Rapid and specific detection of pathogenic bacteria in fecal samples is of critical importance for the diagnosis of neonatal diarrhea in veterinary clinics. Nanobodies are a promising tool for the treatment and diagnosis of infectious diseases due to their unique recognition properties. In this study, we report the design of a nanobody-based magnetofluorescent immunoassay for the sensitive detection of pathogenic Escherichia coli F17-positive strains (E. coli F17). For this, a camel was immunized with purified F17A protein from F17 fimbriae and a nanobody library was constructed by phage display. Two specific anti-F17A nanobodies (Nbs) were selected to design the bioassay. The first one (Nb1) was conjugated to magnetic beads (MBs) to form a complex capable of efficiently capturing the target bacteria. A second horseradish peroxidase (HRP)-conjugated nanobody (Nb4) was used for detection by oxidizing o-phenylenediamine (OPD) to fluorescent 2,3-diaminophenazine (DAP). Our results show that the immunoassay recognizes E. coli F17 with high specificity and sensitivity, with a detection limit of 1.8 CFU/mL in only 90 min. Furthermore, we showed that the immunoassay can be applied to fecal samples without pretreatment and remains stable for at least one month when stored at 4 °C.
A Case of Anti-GAD 65 Autoimmune Encephalitis Associated with Focal Segmental Stiff-Person Syndrome
Authors: Zhang Chen , Dai Yuwei , Han Binhong , Peng Jian , Ma Jie , Tang Qi , Yang Li
Published: February 2023

Glutamic acid decarboxylase (GAD) antibody-related encephalitis is an autoimmune disease associated with intracellular neuronal antigens. We report on a rare case of GAD antibody-associated encephalitis complicated with focal segmental stiffness-person syndrome (SPS) in a middle-aged woman. The disease course lasted for >10 years, initially presenting with drug-resistant epilepsy, followed by stiffness of the right lower limb, and right upper limb involvement. The patient experienced anxiety and depression symptoms due to long-term illness. During hospitalization, serum and cerebrospinal fluid GAD antibodies were positive and no tumor was found. The symptoms were significantly relieved after corticosteroid therapy and intravenous immunoglobulin immunomodulation therapy. To the best of our knowledge, this case is the first to discuss the early recognition and treatment of chronic epilepsy and focal segmental SPS caused by anti-GAD antibody-related encephalitis.
A Neural Network Model Combining [-2]proPSA, freePSA, Total PSA, Cathepsin D, and Thrombospondin-1 Showed Increased Accuracy in the Identification of Clinically Significant Prostate Cancer
Authors: Gentile Francesco , La Civita Evelina , Ventura Bartolomeo Della , Ferro Matteo , Bruzzese Dario , Crocetto Felice , Tennstedt Pierre , Steuber Thomas , Velotta Raffaele , Terracciano Daniela
Published: February 2023

Background: The Prostate Health Index (PHI) and Proclarix (PCLX) have been proposed as blood-based tests for prostate cancer (PCa). In this study, we evaluated the feasibility of an artificial neural network (ANN)-based approach to develop a combinatorial model including PHI and PCLX biomarkers to recognize clinically significant PCa (csPCa) at initial diagnosis. Methods: To this aim, we prospectively enrolled 344 men from two different centres. All patients underwent radical prostatectomy (RP). All men had a prostate-specific antigen (PSA) between 2 and 10 ng/mL. We used an artificial neural network to develop models that can identify csPCa efficiently. As inputs, the model uses [-2]proPSA, freePSA, total PSA, cathepsin D, thrombospondin, and age. Results: The output of the model is an estimate of the presence of a low or high Gleason score PCa defined at RP. After training on a dataset of up to 220 samples and optimization of the variables, the model achieved values as high as 78% for sensitivity and 62% for specificity for all-cancer detection compared with those of PHI and PCLX alone. For csPCa detection, the model showed 66% (95% CI 66–68%) for sensitivity and 68% (95% CI 66–68%) for specificity. These values were significantly different compared with those of PHI (p < 0.0001 and 0.0001, respectively) and PCLX (p = 0.0003 and 0.0006, respectively) alone. Conclusions: Our preliminary study suggests that combining PHI and PCLX biomarkers may help to estimate, with higher accuracy, the presence of csPCa at initial diagnosis, allowing a personalized treatment approach. Further studies training the model on larger datasets are strongly encouraged to support the efficiency of this approach.
Recent Clinical Advances on Long Non-Coding RNAs in Triple-Negative Breast Cancer
Authors: Singh Desh Deepak , Lee Hae-Jeung , Yadav Dharmendra Kumar
Published: February 2023

Triple-negative breast cancer (TNBC) is a more aggressive type of breast cancer due to its heterogeneity and complex molecular mechanisms. TNBC has a high risk for metastasis, and it is difficult to manage clinical conditions of the patients. Various investigations are being conducted to overcome these challenges using RNA, DNA, and proteins for early diagnosis and treatment. Recently, long non-coding RNAs (lncRNAs) have emerged as a novel target to treat the multistep process of TNBC. LncRNAs regulate epigenetic expression levels, cell proliferation and apoptosis, and tumour invasiveness and metastasis. Thus, lncRNA-based early diagnosis and treatment options could be helpful, especially for patients with severe TNBC. lncRNAs are expressed in a highly specific manner in cells and tissues and are involved in TNBC progression and development. lncRNAs could be used as sensitive and specific targets for diagnosis, treatment, and monitoring of patients with TNBC. Therefore, the exploration of novel diagnostic and prognostic biomarkers is of extreme importance. Here, we discuss the molecular advances on lncRNA regulation of TNBC and lncRNA-based early diagnosis, treatment, and drug resistance.
On Classification of Water-in-Oil and Oil-in-Water Droplet Generation Regimes in Flow-Focusing Microfluidic Devices
Authors: Kamnerdsook Ampol , Juntasaro Ekachai , Khemthongcharoen Numfon , Chanasakulniyom Mayuree , Sripumkhai Witsaroot , Pattamang Pattaraluck , Promptmas Chamras , Atthi Nithi , Jeamsaksiri Wutthinan
Published: February 2023

The objective of this research work is to propose a phase diagram that can be used to find a proper operating condition for generating droplets of different types. It is found that the phase diagram of QR versus CaD can effectively classify the droplet generation into three vivid regimes: dripping, jetting and tubing. For the dripping regime, its operating condition is in the range of either CaD < 10−4 and QR < 50 or 10−3 < CaD < 10−4 and QR < 1. For the jetting regime, its operating condition is in the range of either CaD < 1.35 × 10−2 and QR > 100 or CaD > 1.35 × 10−2 and QR > 1. For the tubing regime, its operating condition is in the range of CaD > 1.35 × 10−2 and QR < 1.
First Record of Beauveria varroae, Cordyceps blackwelliae, and Purpureocillium lavendulum from Greece and Their Pathogenicity against Thaumetopoea pityocampa
Authors: Lagogiannis Ioannis , Mantzoukas Spiridon , Eliopoulos Panagiotis , Poulas Konstantinos
Published: February 2023

Entomopathogenic fungi (EPF) consist of a wide range of fungi that can be used as pest control agents, endophytes, and plant growth promoters. In this study of EPF in suburban soils from Achaia, Greece, we used adult beetles as baits for trapping fungal isolates. According to the macroscopic and microscopic traits of the collected isolates, three species corresponded to Beauveria varroae Vuill. (Hypocreales: Cordycipitaceae); Purpureocillium lavendulum Perdomo, Gené, Cano & Guarro (Hypocreales: Ophiocordycipitaceae); and Cordyceps blackwelliae Mongkolsamrit, Noisripoom, Thanakitpipattana, Spatafora & Luangsaard (Hypocreales: Claviceptaceae). Their taxonomic identity was established by ITS-rDNA sequence amplification and sequencing, molecular database comparisons, and phylogenetic analysis. The application of these new EPF species clearly demonstrated remarkable insecticidal action on Thaumetopoea pityocampa (Lepidoptera, Notodontidae) larvae, which increased with the application dose. Our findings are important based on the enhancement of the application of new EPF species as biocontrol agents within the framework of eco-friendly pest management.
Assessment of the Accuracy, Usability and Acceptability of a Rapid Test for the Simultaneous Diagnosis of Syphilis and HIV Infection in a Real-Life Scenario in the Amazon Region, Brazil
Authors: Soares Daniela Cristina , Filho Luciano Chaves Franco , Souza dos Reis Herald , Rodrigues Yan Corrêa , Freitas Felipe Bonfim , de Oliveira Souza Cintya , Damacena Giseli Nogueira , Véras Nazle Mendonça Collaço , Gaspar Pamela Cristina , Benzaken Adele Schwartz , da Felicidade Ribeiro Favacho Joana , Macedo Olinda , Bazzo Maria Luiza
Published: February 2023

We field-assessed the accuracy, acceptability, and feasibility of the SD BIOLINE HIV/Syphilis Duo rapid diagnostic test in three groups: pregnant women, female sex workers (FSW), and men who have sex with men (MSM). Venous blood samples collected in the field were compared with the respective gold standard methods: SD BIOLINE HIV/Syphilis Duo Treponemal Test versus FTA-abs (Wama brand) treponemal laboratory test for syphilis, and SD BIOLINE HIV/Syphilis Duo Test versus the fourth generation Genscreen Ultra HIV Ag-Ag (Bio-Rad brand) laboratory test for HIV. From a total of 529 participants, 397 (75.1%) were pregnant women, 76 (14.3%) FSW and 56 (10.6%) MSM. Sensitivity and specificity parameters of HIV were 100.0% (95% CI: 82.35–100.0%) and 100.0% (95% CI: 99.28–100.0%), respectively. Sensitivity and specificity parameters found for TP antibody detection were 95.00% (95% CI: 87.69–98.62%) and 100.0% (95% CI: 98.18–100.0%), respectively. The SD BIOLINE HIV/Syphilis Duo Test showed high acceptability among participants (85.87%) and health professionals (85.51%), as well as easy usability by professionals (91.06%). The usability of the SD BIOLINE HIV/Syphilis Duo Test kit would not be a barrier to accessing rapid testing, if the product were incorporated into the list of health service supplies.
Meta-Analysis of Cardiovascular Risk Factors in Offspring of Preeclampsia Pregnancies
Authors: Wang Weikai , Lin Ru , Yang Lan , Wang Yanxia , Mao Baohong , Xu Xiaoying , Yu Jing
Published: February 2023

This study aimed to assess cardiovascular risk factors in the offspring of preeclampsia (PE) pregnancies. PubMed, Web of Science, Ovid, and other foreign language databases, as well as SinoMed, China National Knowledge Infrastructure, Wanfang, and China Science and Technology Journal Databases, were searched. The case-control studies on cardiovascular risk factors in the offspring of PE pregnancies from 1 January 2010 to 31 December 2019 were collected. A random-effects model or a fixed-effects model was used, and RevMan 5.3 software was used for meta-analysis to determine the OR value and 95%CI of each cardiovascular risk factor. A total of 16 documents were included in this research, all of which were case-control studies, with a total of 4046 cases in the experimental group and 31,505 in the control group. The meta-analysis that was conducted demonstrated that SBP [MD = 1.51, 95%CI (1.15, 1.88)] and DBP [MD = 1.90, 95%CI (1.69, 2.10)] values in the PE pregnancy offspring group presented an elevation relative to the non-PE pregnancy offspring group. The total cholesterol value in the PE pregnancy offspring group presented an elevation relative to the non-PE pregnancy offspring group [MD = 0.11, 95%CI (0.08, 0.13)]. The low-density lipoprotein cholesterol value in the PE pregnancy offspring group was comparable to that in the non-PE pregnancy offspring group [MD = 0.01, 95%CI (−0.02, 0.05)]. The high-density lipoprotein cholesterol value in the PE pregnancy offspring group presented an elevation relative to the non-PE pregnancy offspring group [MD = 0.02, 95%CI (0.01, 0.03)]. The non-HDL cholesterol value in the PE pregnancy offspring group presented an elevation relative to the non-PE pregnancy offspring group [MD = 0.16, 95%CI (0.13, 0.19)]. The triglycerides [MD = −0.02, 95%CI (−0.03, −0.01)] and glucose [MD = −0.08, 95%CI (−0.09, −0.07)] values in the PE pregnancy offspring group presented a depletion relative to the non-PE pregnancy group. The insulin value in the PE pregnancy offspring group presented a depletion relative to the non-PE pregnancy offspring group [MD = −0.21, 95%CI (−0.32, −0.09)]. The BMI value in the PE pregnancy offspring group presented an elevation relative to the non-PE pregnancy offspring group [MD = 0.42, 95%CI (0.27, 0.57)]. In conclusion, dyslipidemia, elevated blood pressure, and increased BMI occur postpartum with PE, all of which are risk factors for cardiovascular diseases.
Using Word Reading Fluency Curriculum-Based Measurements to Monitor Students’ Reading Progress in Grade 2
Authors: Mahfouz Mayson Abdel Sabour , Mohamed Ahmed Hassan Hemdan
Published: February 2023

The researchers in this study examined the applicability of using an Arabic version of the curriculum-based measurement of word reading fluency (CBM WRF). A sample of 70 second-grade students, 45 average readers and 25 poor readers from a private school in Al Ain, UAE, were randomly selected to participate in this study. A 12-week trial demonstrated the effectiveness of using Arabic CBM WRF in monitoring the reading progress of second-grade students. In addition, Arabic CBM WRF was a good predictor of grade point average in the native language. Moreover, students who were struggling with reading scored significantly lower on CBM WRF probes than did average readers. Results suggest that the Arabic CBM WRF measure may be useful for evaluating and predicting reading performance in Arabic.
The Effect of Virtual Laboratories on Improving Students’ SRL: An Umbrella Systematic Review
Authors: Sapriati Amalia , Suhandoko Astri Dwi Jayanti , Yundayani Audi , Karim Rafidah Abdul , Kusmawan Udan , Mohd Adnan Airil Haimi , Suhandoko Ardiansyah Azhary
Published: February 2023

Virtual laboratory (VLab) has been observed for its function for the merit of online course delivery. It is believed that the existence of VLab may enhance students’ academic achievements. However, the study which researches its impact on the students’ independence is still limited. This systematic review study aims to determine students’ self-regulated learning (SRL) on the use of VLab by implementing PICOS (Population, Intervention, Comparison, Outcome, Study Design). Further, we examined whether the strategies of SRL, such as cognitive, metacognitive, motivational, behavioral, and contextual strategies owned by students at higher education levels, increased because of leveraging the VLab. We identified 267 articles from Scopus and the Web of Science databases, then utilized the PRISMA guidelines to specify the 249 eligible articles. As a result, only 20 articles passed the criteria of the feasibility stage (1) higher education level, (2) informing online learning, (3) containing materials discussing VLab, and (4) representing the concept of SRL. However, the finding showed that all interventions had positively affected students’ performance. Based on the analyzed data, we confirm that VLab can be considered for providing the learning experience since it bridges the gap between students’ prior knowledge and experience and provides an active social experience.
Multi-Objective Optimization Algorithms for a Hybrid AC/DC Microgrid Using RES: A Comprehensive Review
Authors: Nallolla Chinna Alluraiah , P Vijayapriya , Chittathuru Dhanamjayulu , Padmanaban Sanjeevikumar
Published: February 2023

Optimization methods for a hybrid microgrid system that integrated renewable energy sources (RES) and supplies reliable power to remote areas, were considered in order to overcome the intermittent nature of RESs. The hybrid AC/DC microgrid system was constructed with a solar photovoltaic system, wind turbine, battery storage, converter, and diesel generator. There is a steady increase in the utilization of hybrid renewable energy sources with hybrid AC/DC microgrids; consequently, it is necessary to solve optimization techniques. Therefore, the present study proposed utilizing multi-objective optimization methods using evolutionary algorithms. In this context, a few papers were reviewed regarding multi-objective optimization to determine the capacity and optimal design of a hybrid AC/DC microgrid with RESs. Here, the optimal system consisted of the minimum cost of energy, minimum net present cost, low operating cost, low carbon emissions and a high renewable fraction. These were determined by using multi-objective optimization (MOO) algorithms. The sizing optimization of the hybrid AC/DC microgrid was based on the multi-objective grey wolf optimizer (MOGWO) and multi-objective particle swarm optimization (MOPSO). Similarly, multi-objective optimization with different evolutionary algorithms (MOGA, MOGOA etc.) reduces energy cost and net present cost, and increases the reliability of islanded hybrid microgrid systems.