bluuebunny/crossref_metadata_2025 huggingface dataset:
Selection of Additive Manufacturing Machines via Ontology-Supported Multi-Attribute Three-Way Decisions
Authors: Huang Meifa , Fan Bing , Chen Long , Pan Yanting , Qin Yuchu
Published: February 2023

Selection of a suitable additive manufacturing (AM) machine to manufacture a specific product is one of the important tasks in design for AM. So far, many selection approaches based on multi-attribute decision making have been proposed within academia. Each of these approaches works well in its specific context. However, the approaches are not flexible enough and could produce undesirable results as they are all based on multi-attribute two-way decisions. In this paper, a selection approach based on ontology-supported multi-attribute three-way decisions is presented. Firstly, an ontology for AM machine selection is constructed according to vendor documents, benchmark data, expert experience, and the Senvol database. Supported by this ontology, a selection approach based on multi-attribute three-way decisions is then developed. After that, four AM machine selection examples are introduced to illustrate the application of the developed approach. Finally, the effectiveness and advantages of the approach are demonstrated via a set of comparison experiments. The demonstration results suggest that the presented approach is as effective as the existing approaches and more flexible than them when the information for decision making is insufficient or the cost for undesirable decision results is high.
Cellular Automata Approach to Topology Optimization of Graded Multi-Material Structures
Authors: Tajs-Zielińska Katarzyna , Bochenek Bogdan
Published: February 2023

Despite decades of progress, structural topology optimization is still one of the most important areas of engineering optimal design. The intensive research within this area has been stimulated by the development of efficient methods and algorithms on one side and the needs and demands of contemporary engineering on the other. Over the years, the practical aspect of topology optimization has become one of the most significant issues within the design community. Simultaneously, the range of design applications has been broadening. Among many research areas where topology optimization is present, attention has been paid to the design of multi-material structures. The gradation of the material properties has a significant influence on the final layout of the structure, so this problem can be treated as an extension of the classical task of the topology optimization of structures made of a material with uniform distributions of properties. While working with multi-material structures, the important role plays an interface between parts made of materials with different properties. In this paper, the implementation of interfaces made of functionally graded materials (FGM) is proposed. A functionally graded interface means that continuous and smooth changes of properties are assigned to a particular direction from one material surface to another. This paper presents the idea of topology optimization of graded multi-material structures using a simple, fast convergent technique based on the Cellular Automata approach. The proposal is to take the advantage of the versatility of efficient professional finite element-based structural analysis software and the simplicity of the original heuristic topology generator, to build a tool for the optimization of FGM structures as well as multi-material structures including the FGM interface.
Modelling Interactions between Three Aquifer Thermal Energy Storage (ATES) Systems in Brussels (Belgium)
Authors: De Paoli Caroline , Duren Thierry , Petitclerc Estelle , Agniel Mathieu , Dassargues Alain
Published: February 2023

Shallow open-loop geothermal systems function by creating heat and cold reserves in an aquifer, via doublets of pumping and reinjection wells. Three adjacent buildings in the center of Brussels have adopted this type of aquifer thermal energy storage (ATES) system. Two of them exploit the same aquifer consisting of Cenozoic sands, and started operation in 2014 and 2017, respectively. A previous hydrogeological model developed by Bulté et al. (2021) has shown how the thermal imbalance of one of the systems jeopardizes the thermal state of this upper aquifer. Here, the interactions with a more recent third ATES system located in the deep aquifer of the Palaeozoic bedrock are studied and modelled. After being calibrated on groundwater flow conditions in both aquifers, a 3D hydrogeological model was used to simulate the cumulative effect of the three geothermal installations in the two exploited aquifers. The results of the simulations showed that although the hydraulic interactions between the two aquifers are very weak (as shown by the different observed potentiometric heads), heat exchanges occur between the two aquifers through the aquitard. Fortunately, these heat exchanges are not sufficient to have a significant impact on the efficiency of the individual geothermal systems. Additionally, this study shows clearly that adding a third system in the lower aquifer with a mean power of 286 kW for heating between October and March and an equivalent mean cooling power between April and September is efficient.
Creation of Signals Database for the Development of Speed Estimation in an Axle Counter System
Authors: Szczeponik Adam , Grzechca Damian
Published: February 2023

The article presents the process of creation of a signals database for the development of a train speed-estimation method for an axle counter system. In the article the authors present the need for information about the train speed on the railway lines and the possible applications for which the information about the train speed may be used, as well as address the concerns related with the evaluation of the information in axle counter systems. The main goal of the paper is to present the creation process of an axle counter signals database and how to emulate the real signals using the laboratory-obtained ones. A database that has been created for a specific wheel detector is available on request. It contains a variety of signals that are necessary for the development and tests of wheel detector algorithms, in particular the estimation of train speed. Signals were generated for the most commonly used rail profile in Europe and the wheels that are defined in the technical specification of interoperability. Furthermore, the signals were transformed to emulate various speeds, the possible accelerations and to include the disturbance observed in the field.
Two-Stage Optimal Task Scheduling for Smart Home Environment Using Fog Computing Infrastructures
Authors: Sharma Oshin , Rathee Geetanjali , Kerrache Chaker Abdelaziz , Herrera-Tapia Jorge
Published: February 2023

The connection of many devices has brought new challenges with respect to the centralized architecture of cloud computing. The fog environment is suitable for many services and applications for which cloud computing does not support these well, such as: traffic light monitoring systems, healthcare monitoring systems, connected vehicles, smart cities, homes, and many others. Sending high-velocity data to the cloud leads to the congestion of the cloud infrastructure, which further leads to high latency and violations of the Quality-of-Service (QoS). Thus, delay-sensitive applications need to be processed at the edge of the network or near the end devices, rather than the cloud, in order to provide the guaranteed QoS related to the reduced latency, increased throughput, and high bandwidth. The aim of this paper was to propose a two-stage optimal task scheduling (2-ST) approach for the distribution of tasks executed within smart homes among several fog nodes. To effectively solve the task scheduling, this proposed approach uses a naïve-Bayes-based machine learning model for training in the first stage and optimization in the second stage using a hyperheuristic approach, which is a combination of both Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). In addition, the proposed mechanism was validated against various metrics such as energy consumption, latency time, and network usage.
Implicit Algorithm of the SBSP-R Model for Predicting the Non-Unique Critical State of Soils
Authors: Kang Xiaosen , Dai Qian , Liao Hongjian , He Yuqi
Published: February 2023

The non-unique critical state represents the distance between the critical state line (CSL) and the isotropic consolidation line (ICL) that significantly varies with stress paths and particle size distribution of soils. A structural bounding surface plasticity model with spacing ratio r (SBSP-R model) was implemented using an explicit algorithm. However, the explicit algorithm did not well capture the non-unique critical state of soils with a large spacing ratio r, which prevented the soil mechanics research on non-unique critical state via finite element analysis. To overcome the limitation, the implicit algorithm of the SBSP-R model is formulated, and it mainly includes elastic prediction and plastic correction. The plastic correction is realized using the Newton–Simpson scheme with a controlling equation set related to consistency condition, plastic flow, hardening parameter, structural bounding surface, plastic modulus, and mapping rule. Case studies indicate that the implicit algorithm of the SBSP-R model is right and stable in predicting non-unique critical states. Comparisons between predicted and tested results indicate that the implicit algorithm of the SBSP-R model not only captures the critical state, stress-strain, and stress paths of various soils but also shows higher computational accuracy and efficiency compared with the previous explicit algorithm. These results indicate that the formulated implicit algorithm of the SBSP-R model is an alternative approach to the previous explicit algorithm.
Experimental Evaluation of Collision Avoidance Techniques for Collaborative Robots
Authors: Neri Federico , Forlini Matteo , Scoccia Cecilia , Palmieri Giacomo , Callegari Massimo
Published: February 2023

This paper presents the implementation of an obstacle avoidance algorithm on the UR5e collaborative robot. The algorithm, previously developed and verified in simulation, allows one to modify in real time the trajectory of the manipulator with three different modalities to avoid obstacles. Some test cases with fixed or dynamic obstacles affecting the robot’s motion were first simulated and then experimented on. The paper describes the hardware/software architecture of the robotic system: an external controller is realized by a standard PC that communicates with the robot controller by a TCP/IP protocol; algorithms and data processing are executed by Python/Matlab software that guarantees a duty cycle of at least 100 Hz. The error analysis between simulated and real data allows one to conclude that the developed algorithms revealed to be effectively applied to a real robotic system, showing behavior similar to what is expected by simulations.
A Method to Determine the Torque Ripple Harmonic Reduction in Skewed Synchronous Reluctance Machines
Authors: Gallardo César , Madariaga Carlos , Tapia Juan A. , Degano Michele
Published: February 2023

In this paper, a discrete skew methodology is presented to understand the effect of skewing angle on electromagnetic torque in SynRM design. A new approach is proposed to estimate the amplitude of each torque ripple component as a function of skewing angle. The reduction factor for each harmonic component is derived in general form, allowing for the determination of overall torque ripple waveform. The validity of the proposed method is evaluated through the examination of two SynRMs, resulting in a torque ripple reduction of up to 70%. The results obtained through the use of a proposed analytical ripple reduction estimator and FEA evaluation showed good agreement. The proposed skewing technique was applied on a previously optimized triple-barrier SynRM with a positive outcome: a consistent torque ripple reduction tackling relevant harmonic components. The analysis of harmonic distribution of torque ripple is mandatory for the selection of the optimal skewing strategy when following the proposed method, with two-step skewing recommended for mostly-purely-sinusoidal torque waveforms, and multi-step skewing recommended for machines with multiple higher-magnitude harmonic components.
Improved Stress Classification Using Automatic Feature Selection from Heart Rate and Respiratory Rate Time Signals
Authors: Iqbal Talha , Elahi Adnan , Wijns William , Amin Bilal , Shahzad Atif
Published: February 2023

Time-series features are the characteristics of data periodically collected over time. The calculation of time-series features helps in understanding the underlying patterns and structure of the data, as well as in visualizing the data. The manual calculation and selection of time-series feature from a large temporal dataset are time-consuming. It requires researchers to consider several signal-processing algorithms and time-series analysis methods to identify and extract meaningful features from the given time-series data. These features are the core of a machine learning-based predictive model and are designed to describe the informative characteristics of the time-series signal. For accurate stress monitoring, it is essential that these features are not only informative but also well-distinguishable and interpretable by the classification models. Recently, a lot of work has been carried out on automating the extraction and selection of times-series features. In this paper, a correlation-based time-series feature selection algorithm is proposed and evaluated on the stress-predict dataset. The algorithm calculates a list of 1578 features of heart rate and respiratory rate signals (combined) using the tsfresh library. These features are then shortlisted to the more specific time-series features using Principal Component Analysis (PCA) and Pearson, Kendall, and Spearman correlation ranking techniques. A comparative study of conventional statistical features (like, mean, standard deviation, median, and mean absolute deviation) versus correlation-based selected features is performed using linear (logistic regression), ensemble (random forest), and clustering (k-nearest neighbours) predictive models. The correlation-based selected features achieved higher classification performance with an accuracy of 98.6% as compared to the conventional statistical feature’s 67.4%. The outcome of the proposed study suggests that it is vital to have better analytical features rather than conventional statistical features for accurate stress classification.
Anthropometric and Kinanthropometric Distinctive Profile of a Sedentary Population Compared with an Amateur Athlete Population
Authors: Navas Harrison Daniel Jonathan , Pérez Pico Ana María , García Blázquez Francisco Manuel , Acevedo Raquel Mayordomo
Published: February 2023

Anthropometry and kinanthropometry are sciences that measure variations in the physical dimensions and composition of the human body. There are studies that analyze these parameters individually, but we believe that it is much better to analyze them globally. We realized a multivariate analysis, to determine which variables could explain the profiles of the subjects depending on sex, lifestyle, and type of sports modality. We analyzed 25 variables in a population of 574 people aged between 18 and 42 years. A multivariate statistical analysis was performed using exploratory factor analysis, and then we obtained five differentiating variables: fat mass, muscle mass, bone mass, skinfolds, and robustness. We classified the population into sedentary lifestyle, amateur athletes with predominance of the upper and lower train, and amateur athletes with predominance mainly of the lower train, in an attempt to analyze the existence of statistical significance between them. Amateur athletes with a predominance of the upper and lower train have a higher Body Mass Index and a lower Relative Index of the Lower Limbs, in addition to greater muscle mass and robustness than those athletes with a predominance mainly of the lower train. The sedentary control group presented higher values in terms of skinfolds and fat mass. This work could help people to choose the best sport according to their morphotype, and also could be used to plan sports training to potentiate different body regions, injury recovery, selection of talented athletes, etc.
Exploration Technology of Adverse Geological Body in Karst Development Area Based on Borehole Multi-Source Data
Authors: Liu Wenlian , Sui Sugang , Xu Hanhua , Wang Jinchao , Wang Feng
Published: February 2023

In view of the current technical difficulties in the detection of unfavorable geological bodies in karst areas, this paper starts with the fine detection of a borehole wall, near-field of the borehole wall rock and far-field of the borehole wall rock, deeply excavates the correlation characteristics between multi-source borehole data, and proposes detection technology for unfavorable geological bodies in karst development areas based on multi-source borehole data. This is used to establish a multi-source data depth mining model. The correlation characteristics between multi-source data are clarified. The borehole multi-source heterogeneous detection technology is proposed to realize the organic fusion between the detection data of different scales, and effectively estimate the extension range of structural planes and cavities. The joint interpretation method of multi-source drilling data can effectively realize the three-dimensional visualization of unfavorable geological bodies in karst development areas. Through a case analysis, it is shown that this technology is a new and effective exploration method in the engineering geological exploration of karst development areas, and can provide more abundant and reliable exploration data for the fine exploration of geological bodies in the exploration area.
Shape Evolution of Indium Sulfide Heterostructures via Carbon Nanotube Scrambling: Towards Reliable Sustainability and Mitigating Leakage Current in Supercapacitors
Authors: Kumar Niraj , Mishra Dhananjay , Kim Seungyeob , Mokurala Krishnaiah , Mishra Rajneesh Kumar , Song Junyoung , Jin Sung Hun
Published: February 2023

For sustainable energy storage devices with long-term endurance, exploring novel electrode materials can be a realistic focus in the areas of robust structures, surface area control, high channel conductivity, and others. A composite of a hierarchical series of single-walled carbon nanotubes (SWNTs) with In2S3 was synthesized by applying a simple one-step solvothermal method. A SWNT scaffold yields a good conductive pathway, leading to the improved electron transportation and catalytic behaviors. This promotes the robust formation of materials and their enhancement in surface activity and specific capacitance. Herein, the nucleated nanocomposites based on SWNT-mediated In2S3 improve the specific capacitance (1268 F·g−1 at 10 mVs−1) to a remarkable 92.4% of its capacitance even after 10,000 cycles, and furthermore, the robust cocoon-like structure of INS5 (5 mL SWNT doped in In2S3) shows an excellent 97.8% of cyclic retention (10,000 cycles). As a conceptual demonstration of system integration, the as-fabricated symmetric supercapacitor (SSC) device is successfully integrated into the Bluetooth/photoplethysmography (BLE/PPG) module for a wireless sensor network. These findings, through indium sulfides with SWNT scrambling, are expected to contribute to the next-generation solid-state-supercapacitor (SSC)-integrated module in the wireless health monitoring system.
Anti-Mutagenic and Immunomodulatory Effects of Astragali Radix Extract on a Cyclophosphamide-Induced Immunosuppressed Mouse Model
Authors: Park Hye-Rim , Kim Joo Wan , Lee Jung-Ok , Ahn Jong-Deuk , Yang Min-Cheol , Bashir Khawaja Muhammad Imran , Choi Jae-Suk , Ku Sae-Kwang
Published: February 2023

Although the immunomodulatory effects of Astragali Radix extract (AR) have been documented, its anti-mutagenic activity, a problem arising from chemotherapeutic agents, is rarely reported. Therefore, the anti-mutagenic and immunomodulatory effects of AR were investigated using a cyclophosphamide (CPA)-induced immunosuppressed mouse model to develop an alternative immunomodulatory agent. The fluid-bed-dried aqueous extract of AR containing 37.5% dextrin and exopolymers purified from Aureobasidium pullulans SM-2001 (EAP) were used in this study. The therapeutic potentials of AR at doses ranging from 100 mg/kg to 400 mg/kg was estimated by a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) based cytotoxicity and splenocyte proliferation assay, body weight and lymphatic organ weight measurements, hematological measurements, serum and spleen cytokine level measurements, natural killer (NK) cell activity measurements, real-time RT-PCR expressions of splenic mRNA, a micronucleus test, histopathological observations, and immunohistochemical measurements. In CPA-treated mice, a clear immunosuppressive effect was observed for all tested parameters. However, the oral administration of AR (100, 200, and 400 mg/kg) showed dose-dependent and favorable inhibitory activities on CPA-induced immunosuppression and mutagenicity as compared to 200 mg/kg EAP. Furthermore, AR (100–400 mg/kg) up-regulated the nuclear factor kappa-light-chain-enhancer of activated B-cells (NF-κB) which are related to NK-, T-, and B-cell activation, with no critical cytotoxicity. The results of this study clearly demonstrate that AR at an appropriate oral dose could act as a potential alternative agent with significant anti-mutagenicity and immunomodulatory properties.
An Open Relation Extraction Method for Domain Text Based on Hybrid Supervised Learning
Authors: Wang Xiaoxiong , Hu Jianpeng
Published: February 2023

Current research on knowledge graph construction is focused chiefly on general-purpose fields, whereas constructing knowledge graphs in vertically segmented professional fields faces numerous difficulties. To solve the problems of complex relation types of domain entities, the lack of a large amount of annotated corpus, and the difficulty of extraction, this study proposed a method for constructing domain-annotated datasets based on publicly available texts on the web, which integrates remote supervision and semi-supervision. For the relational triad extraction of a given core entity (an entity lexicon defined semi-automatically by experts), an inflated gate attention network structure for increasing the perceptual field of the model is proposed. In addition, a relational extraction model, Ro-DGANet, was designed based on this structure, incorporating the idea of a probability graph. The Ro-DGANet model was experimentally evaluated on the publicly available Chinese datasets LIC2019 and CHIP2020 and compared with the mainstream relation extraction models, achieving the best results with F1 values of 82.99% and 66.39%, respectively. Finally, the Ro-DGANet model was applied to the relation extraction task of equipment components in industrial scenarios and to the relation extraction task of core knowledge points of programming languages. The analysis results show that the proposed method is applicable to open relation extraction among core entities in different domains with reliable performance and portability.
Applications MLP and Other Methods in Artificial Intelligence of Fruit and Vegetable in Convective and Spray Drying
Authors: Przybył Krzysztof , Koszela Krzysztof
Published: February 2023

The seasonal nature of fruits and vegetables has an immense impact on the process of seeking methods that allow extending the shelf life in this category of food. It is observed that through continuous technological changes, it is also possible to notice changes in the methods used to examine and study food and its microbiological aspects. It should be added that a new trend of bioactive ingredient consumption is also on the increase, which translates into numerous attempts that are made to keep the high quality of those products for a longer time. New and modern methods are being sought in this area, where the main aim is to support drying processes and quality control during food processing. This review provides deep insight into the application of artificial intelligence (AI) using a multi-layer perceptron network (MLPN) and other machine learning algorithms to evaluate the effective prediction and classification of the obtained vegetables and fruits during convection as well as spray drying. AI in food drying, especially for entrepreneurs and researchers, can be a huge chance to speed up development, lower production costs, effective quality control and higher production efficiency. Current scientific findings confirm that the selection of appropriate parameters, among others, such as color, shape, texture, sound, initial volume, drying time, air temperature, airflow velocity, area difference, moisture content and final thickness, have an influence on the yield as well as the quality of the obtained dried vegetables and fruits. Moreover, scientific discoveries prove that the technology of drying fruits and vegetables supported by artificial intelligence offers an alternative in process optimization and quality control and, even in an indirect way, can prolong the freshness of food rich in various nutrients. In the future, the main challenge will be the application of artificial intelligence in most production lines in real time in order to control the parameters of the process or control the quality of raw materials obtained in the process of drying.
Experimental and Numerical Study on the Fluid Dynamics and Exergetic Performance of the Heat Exchanger in an Industrial Corn Drying System
Authors: Zhang Xuefeng , Li Bin , Li Chengjie , Zhang Ye , Meng Mingang , Wang Han , Li Changyou
Published: February 2023

The heat exchanger is the key component of an industrial drying system. The present work introduced a novel tube heat exchanger into a corn drying system. To fully understand the heat exchange process and optimize the heat exchange performance of the heat exchanger, numerical simulation, exergy analysis and economic analysis methodologies were adopted to analyze the comprehensive performance of the heat exchanger. The fluid dynamics as well as the exergy performance of the heat exchanger under different flue gas velocities (3, 5 and 7m/s) and different ambient air relative humidities (80%, 85% and 90%) were investigated. The results showed that there are two strong turbulences causing the huge pressure drop at the last two stages of the flue gas duct, while there are two insufficient heat exchange areas on both sides of the heat exchanger; thus, the corresponding improvement recommendations were proposed in the present work. The values of the Re and Nu were found to vary in the range of 1256.275–2210.554 and 21.337–32.415, respectively. The average heat transfer coefficients were ascertained to be above 8.274 kW·m−2·K−1, while the pressure drop of the ambient air was ascertained to be under 16.138 Pa. Moreover, the exergy analysis revealed that the heat exchanger experiences sustainable development (SI < 2), and the exergy efficiency is above 11.461%. The main results may provide some references for further optimizing the heat transfer performance of the heat exchanger.
Agent-Based Modelling of the Evolution of Hydro-Sedimentary Connectivity: The Case of Flash Floods on Arable Plateaus
Authors: Rakotoarisoa Mahefa Mamy , Reulier Romain , Delahaye Daniel
Published: February 2023

Land use and landscape structure play an important role in the functioning of flash floods on the arable plateaus of northern France. Landscape structures have changed considerably over the last decades with an increase in runoff-producing surfaces and an enlargement of the plots. This evolution results in an increase in runoff volumes accompanied by an increasingly easy diffusion of runoff on the slopes. There is therefore potentially an increasingly frequent and important spatial connectivity from the plots to the thalwegs, which can lead to the formation of flash floods. This study proposes to model this diachronic evolution of connectivity in a small agricultural basin of Seine Maritime using a multiagent system (MAS) and to develop synthetic indicators characterising these spatial links in the flow processes. The model outputs show that spatial connectivity has been steadily increasing over the past 70 years due to the enlargement of the parcel grid and the growth of runoff surfaces. For example, for the same 20 mm/h rainfall, the connectivity indicator increases from 40.99% (in 1947) to 78.33% (in 2015). This observation is observed for all levels of rainfall intensity, including the lowest. This modelling, carried out for a 116 ha basin in arable farming, can be transposed to all small agricultural basins.
Serotonin Signaling in the Enteric Nervous System and Connection to Autism Spectrum Disorder: A Translational Mathematical Model
Authors: Kareva Irina
Published: February 2023

While the causes of autism spectrum disorder (ASD) remain unclear, some studies have shown that serotonin-mediated effects on the enteric nervous system (ENS) correlate with an ASD-like behavioral phenotype in mice. Introduced here is a mathematical model of interactions between gut serotonin and its impact on the ENS. The model was used to identify three key factors that affect ENS size, namely, serotonin production, its clearance, and its ability to act as a growth factor for the ENS. The model was used to reproduce experimentally reported results from a mouse model by Margolis et al. (2016), which connected serotonin-mediated ENS hypoplasia to an ASD phenotype. The proposed mathematical model was used to scale the quantified relationship from mice to humans to show how the combination of these three factors can translate to a quantifiable metric that could potentially be correlated to the ASD spectrum. A detailed discussion of how ENS hypoplasia could mechanistically affect CNS activity concludes this paper.
Inspection and Structural Rehabilitation of an Existing Masonry Arch Railway Bridge
Authors: Bencardino Francesco , Curto Roberta , Scavelli Vincenzo
Published: February 2023

Masonry arch bridges are important structures of road and rail networks around the world. Over several decades of service life, they suffer deterioration and damage. In order to preserve their functioning, it is necessary to carry out a seismic vulnerability analysis to verify the current level of safety and, if necessary, take action to reach the standard required by current codes. For these reasons, a structural analysis of the existing railway bridge built with masonry arches, located on the San Nicola–Avigliano Lucania line in Potenza, Italy, was carried out. The seismic vulnerability of the bridge was assessed using the Finite Element Analysis (FEA) method by subjecting a properly discretized three-dimensional model of the entire structure to a non-adaptive nonlinear static analysis (pushover). The obtained results do not meet the minimums suggested by current European Standards. Therefore, a traditional structural rehabilitation intervention was designed and modeled. The intrados of the arches and the bridge piers were reinforced with a thin reinforced concrete slab and reinforced concrete jackets, respectively, all connected to the existing structure by steel bar connectors. By re-performing the pushover analysis of the reinforced structure using FEA software, it was observed that the new risk indexes satisfy the seismic vulnerability verification. Thus, the proposed structural rehabilitation is a valid, but not unique, solution to the problem affecting the existing masonry arch bridge analyzed in this study.
Silicone Elastomeric-Based Materials of Soft Pneumatic Actuator for Lower-Limb Rehabilitation: Finite Element Modelling and Prototype Experimental Validation
Authors: Bakeri Hanisah , Hasikin Khairunnisa , Abd Razak Nasrul Anuar , Mohd Razman Rizal , Khamis Abd Alghani , Annuha Muhammad ‘Ammar , Tajuddin Abbad , Reza Darween
Published: February 2023

This study describes the basic design, material selection, fabrication, and evaluation of soft pneumatic actuators (SPA) for lower-limb rehabilitation compression therapy. SPAs can be a promising technology in proactive pressure delivery, with a wide range of dosages for treating venous-related diseases. However, the most effective design and material selection of SPAs for dynamic pressure delivery have not been fully explored. Therefore, a SPA chamber with two elastomeric layers was developed for this study, with single-side inflation. The 3D deformation profiles of the SPA chamber using three different elastomeric rubbers were analyzed using the finite element method (FEM). The best SPA-compliant behavior was displayed by food-grade silicone A10 Shore with a maximum deformation value of 25.34 mm. Next, the SPA chamber was fabricated using A10 Shore silicone and experimentally validated. During the simulation in FEM, the air pressure was applied on the inner wall of the chamber (i.e., the affected area). This is to ensure the applied pressure was evenly distributed in the inner wall while the outer wall of the chamber remained undeformed for all compression levels. During the inflation process, pressure will be applied to the SPA chamber, causing exerted pressure on the skin which is then measured for comparison. The simulation and experimental results show an excellent agreement of pressure transmission on the skin for the pressure range of 0–120 mmHg, as depicted in the Bland–Altman plots. The findings exhibited promising results in the development of the SPA chamber using low-cost and biocompatible food-grade silicone.
Laryngeal Imaging Study of Glottal Attack/Offset Time in Adductor Spasmodic Dysphonia during Connected Speech
Authors: Naghibolhosseini Maryam , Zacharias Stephanie R. C. , Zenas Sarah , Levesque Farrah , Deliyski Dimitar D.
Published: February 2023

Adductor spasmodic dysphonia (AdSD) disrupts laryngeal muscle control during speech and, therefore, affects the onset and offset of phonation. In this study, the goal is to use laryngeal high-speed videoendoscopy (HSV) to measure the glottal attack time (GAT) and glottal offset time (GOT) during connected speech for normophonic (vocally normal) and AdSD voices. A monochrome HSV system was used to record readings of six CAPE-V sentences and part of the “Rainbow Passage” from the participants. Three raters visually analyzed the HSV data using a playback software to measure the GAT and GOT. The results show that the GAT was greater in the AdSD group than in the normophonic group; however, the clinical significance of the amount of this difference needs to be studied further. More variability was observed in both GATs and GOTs of the disorder group. Additionally, the GAT and GOT time series were found to be nonstationary for the AdSD group while they were stationary for the normophonic voices. This study shows that the GAT and GOT measures can be potentially used as objective markers to characterize AdSD. The findings will potentially help in the development of standardized measures for voice evaluation and the accurate diagnosis of AdSD.
Characterization and Differentiation of Wild and Cultivated Berries Based on Isotopic and Elemental Profiles
Authors: Cristea Gabriela , Dehelean Adriana , Puscas Romulus , Covaciu Florina-Dorina , Hategan Ariana Raluca , Müller Molnár Csilla , Magdas Dana Alina
Published: February 2023

The isotopic content (δ13C, δ2H, δ18O) and concentrations of 30 elements (Li, Na, Mg, P, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, As, Rb, Sr, Ag, Cd, Ba, Pb, La, Ce, Pr, Nd, Sm, Eu, Gd, and Tb) were determined in different wild and cultivated berries (raspberry, seaberry, blackberry, cranberry, and blueberry). Partial least squares discriminant analysis (PLS-DA) was applied in order to develop models for differentiating berries according to their botanical origin and growing system. δ13C, δ2H, δ18O, Li, Na, Mg, P, Ca, V, Mn, Co, Ni, Zn, As, Rb, Sr, Ba, and Eu were identified as significant elements for the differentiation of berry species, based on which an 85% PLS-DA model accuracy was obtained. Similarly, the PLS-DA model developed for the growing system differentiation correctly classified 94.4% of the cultivated berries and 77.2% of the wild ones, based on the main predictors: δ13C, δ18O, Li, Na, Ca, Cr, Mn, Ni, Rb, and Ba. The developed PLS-DA model for the discrimination of wild blueberries from cultivated ones showed excellent levels of sensitivity (100%), specificity (100%), and accuracy (100%).
First Characterization of Novel Silicon Carbide Detectors with Ultra-High Dose Rate Electron Beams for FLASH Radiotherapy
Authors: Romano Francesco , Milluzzo Giuliana , Di Martino Fabio , D’Oca Maria Cristina , Felici Giuseppe , Galante Federica , Gasparini Alessia , Mariani Giulia , Marrale Maurizio , Medina Elisabetta , Pacitti Matteo , Sangregorio Enrico , Vanreusel Verdi , Verellen Dirk , Vignati Anna , Camarda Massimo
Published: February 2023

Ultra-high dose rate (UHDR) beams for FLASH radiotherapy present significant dosimetric challenges. Although novel approaches for decreasing or correcting ion recombination in ionization chambers are being proposed, applicability of ionimetric dosimetry to UHDR beams is still under investigation. Solid-state sensors have been recently investigated as a valuable alternative for real-time measurements, especially for relative dosimetry and beam monitoring. Among them, Silicon Carbide (SiC) represents a very promising candidate, compromising between the maturity of Silicon and the robustness of diamond. Its features allow for large area sensors and high electric fields, required to avoid ion recombination in UHDR beams. In this study, we present simulations and experimental measurements with the low energy UHDR electron beams accelerated with the ElectronFLASH machine developed by the SIT Sordina company (IT). The response of a newly developed 1 × 1 cm2 SiC sensor in charge as a function of the dose-per-pulse and its radiation hardness up to a total delivered dose of 90 kGy, was investigated during a dedicated experimental campaign, which is, to our knowledge, the first characterization ever done of SiC with UHDR-pulsed beams accelerated by a dedicated ElectronFLASH LINAC. Results are encouraging and show a linear response of the SiC detector up to 2 Gy/pulse and a variation in the charge per pulse measured for a cumulative delivered dose of 90 kGy, within ±0.75%.
Caraway Oil as a Multimodal Therapy for Neuropathic Pain: Investigating the Mechanisms of Action in Rats with Chronic Constriction Injury
Authors: Alkholifi Faisal K. , Devi Sushma , Alam Aftab , Kamal Mehnaz , Yusufoglu Hasan S.
Published: February 2023

Neuropathic pain, a prevalent concern associated with various pathological conditions, poses a significant public health risk due to its poorly understood pathophysiology and treatment complexities. Multimodal therapy is often the most efficacious approach to managing neuropathic pain, yet it is also highly labour intensive. The exact underlying causes of neuropathic pain are unclear; evidence suggests that cytokines, neuropeptides, and neurotrophic factors may play a role in its pathogenesis. The current study aimed to investigate the anti-neuropathic pain activity of caraway oil and the molecular mechanisms underlying its actions in rats with CCI, a model of neuropathic pain. Behavioural evaluations of cold allodynia, heat hyperalgesia, mechanical allodynia, and mechanical hyperalgesia were conducted using the acetone spray test, hot plate test, Von Frey hair test, and pinprick test, respectively. Additionally, the level of TNF-α in the sciatic nerve was examined as an indicator of inflammation, and NGF and substance P levels were determined in the DRG to identify mechanistic processes. Rats were administered caraway oil orally at doses of 25 and 50 mg/kg for 21 days. Results indicated that caraway oil administration significantly reduced behaviour associated with injury-related pain and elevated TNF levels. After an anti-NGF injection on the 21st day, significant attenuated behavioural effects were observed. Furthermore, caraway oil administration was able to inhibit the upregulation of NGF in DRG caused by CCI and minimize the increase in substance P in DRG. These findings suggest that caraway oil has promising therapeutic potential for managing neuropathic pain by targeting peripheral and secondary sensitization mechanisms.
Use of Spatio-Structural Parameters of the Multiscan Video Signal for Improving Accuracy of Control over Object Geometric Parameters
Authors: Tlach Vladimír , Alies Michael Yurievich , Kuric Ivan , Sága Milan , Shelkovnikov Yuriy Konstantinovich , Arkhipov Igor Olegovic , Korshunov Aleksandr Ivanovich , Meteleva Anastasia Alekseevna
Published: February 2023

In the present paper, we consider the issue of improving the accuracy of measurements and the peculiar features of the measurements of the geometric parameters of objects by optoelectronic systems, based on a television multiscan in the analogue mode in scanistor enabling. It is shown that the convolution of the input signal of the rectangular profile of the light zone with the impulse response of the multiscan explains the smearing of video signal edges. The value of smearing is completely determined by impulse response and does not depend on the zone width. It is established that signals of the action from narrow light zones are smeared out substantially relative to their width, and in this case, the conventional method for determining the zone width by the video signal derivatives stops working. A method is proposed for a full reconstruction of the rectangular profile of a light zone (including a narrow one) in a developed noise-proof optoelectronic measuring device based on a multiscan with the use of spatio-structural parameters, where the width of a light zone corresponds to an extent, illumination of the zone—to brightness, and its coordinate—to centroid. It is shown that the subtraction of the dissipation of the impulse response from the video signal dissipation allows for accounting of the value of the video signal smearing out with high accuracy at the estimation of the width of a light zone, in accordance with the property of the additive accumulation of dissipation. It is established that the use of the spatio-structural video signal model permits the extension of the application of multiscan-based optoelectronic devices for the high-accuracy control and measurement of the geometric parameters of small objects.
Reduction in Drying Shrinkage and Efflorescence of Recycled Brick and Concrete Fine Powder–Slag-Based Geopolymer
Authors: Liu Xiaoming , Liu Erping , Fu Yongtong
Published: February 2023

It is an effective method to prepare geopolymer with recycled brick and concrete fine powder (RP) and slag as main materials for the resource utilization of construction waste. However, its hydration products have large drying shrinkage and high efflorescence risk under normal curing conditions. Until now, the durability of recycled brick and concrete fine powder–slag-based geopolymer (RPSG) has not been well documented, such as drying shrinkage and efflorescence. In this study, the effects of slag content, alkali equivalent and modulus on the durability properties of RPSG were evaluated. The results show: (1) Slag can significantly reduce the drying shrinkage and efflorescence of RPSG. (2) The potential for the efflorescence of RPSG increases with increasing alkali equivalent. The drying shrinkage of RPSG increases with the increase of alkali equivalent in the case of a low alkali equivalent (6 wt.% in this paper) and decreases with the increase of alkali equivalent in the case of a high alkali equivalent. (3) The drying shrinkage of RPSG increases with increasing modulus. In contrast, the degree of efflorescence decreases with increasing modulus. In this study, RP-S45-M1.3N6 (slag content: 45 wt.%; alkali equivalent: 6 wt.%; modulus: 1.3) is the best proportional design for RPSG with excellent durability. Compared to RP-S0-M1.3N6, the drying shrinkage of RP-S45-M1.3N6 is reduced by 76.32%, the capillary porosity is reduced by 60.9%, the visual efflorescence is significantly alleviated, and the early pH value is reduced by approximately 2.0. This paper systematically analyzed the drying shrinkage pattern and the efflorescence pattern of RPSG, which has a positive significance for promoting the recycling of RP from construction waste.
Recognition and Prediction of Pedestrian Hazardous Crossing Intentions in Visual Field Obstruction Areas Based on IPVO-LSTM
Authors: Zhou Jincao , Bai Xin , Hu Wenjie
Published: February 2023

Pedestrians who suddenly cross the street from within the blind spot of a vehicle’s field of view can pose a significant threat to traffic safety. The dangerous pedestrian crossing intentions in view-obscured scenarios have not received as much attention as the prediction of pedestrian crossing intentions. In this paper, we present a method for recognizing and predicting the dangerous crossing intention of pedestrians in a view-obscured region based on the interference, pose, velocity observation–long short-term memory (IPVO-LSTM) algorithm from a road-based view. In the first step, the road-based camera captures the pedestrian’s image. Then, we construct a pedestrian interference state feature module, pedestrian three-dimensional pose feature module, pedestrian velocity feature module, and pedestrian blind observation state feature module and extract the corresponding features of the studied pedestrians. Finally, the pedestrian hazard crossing intention prediction module based on a feature-fused LSTM (ff-LSTM) and attention mechanism is used to fuse and process the above features in a cell state process to recognize and predict the pedestrian hazard crossing intention in the blind visual area. Experiments are compared with current common algorithms in terms of the input parameter selection, intention recognition algorithm, and intention prediction time range, and the experimental results validate our state-of-the-art method.
Stability Index of Surrounding Rock during Deep Rock Excavation Considering Energy Release Speed
Authors: Luo Sheng , Yan Peng , Lu Wenbo , Dong Zhihong , Zhou Chunhua , Yang Zhaowei , Hu Yingguo
Published: February 2023

Rockburst is a kind of dynamic rock failure process that is easily induced by the excavation of a high-stress rock mass. However, from an energy perspective, the existing indexes for rockburst tendency have a limitation in that they do not consider the energy release speed. In this study, energy release effectiveness was proposed based on the local energy release rate while considering the influence of the energy release speed. The index can evaluate the stability of surrounding rock during the excavation of high-stress rock. The index can be obtained by recording the strain energy density of every element in the model during excavation and identifying the maximum strain energy density (Eimax), the minimum strain energy density (Eimin), the maximum time (timax), and the minimum time (timin) to calculate energy release speed and energy release effectiveness. A case study of the excavation of an experimental tunnel, namely, the URL of AECL, was adopted to validate the index. The results indicated that the proposed index can clearly identify the location and strength of the impact tendency area, and it can be effectively applied to the stability analysis during the excavation of deep tunnels.