bluuebunny/crossref_metadata_2025 huggingface dataset:
Parameters Influence on the Dynamic Properties of Polymer-Matrix Composites Reinforced by Fibres, Particles, and Hybrids
Authors: Murčinková Zuzana , Postawa Przemysław , Winczek Jerzy
Published: July 2022

In this paper, we present an extensive experimental study on the dynamic mechanical properties of composites with polymer matrices, as well as a quantification of the parameters that influence these properties. Polymer-composite matrices make it possible to form any reinforcement arrangement of fibres, particles, and layers, which makes it possible to form composite materials with certain dominant mechanical properties according to the internal arrangement for the application. In this study, we focused on the dynamic properties (i.e., damping parameters, such as the loss factor (tan d), logarithmic decrement (λ), storage modulus (E′), and loss modulus (E″)) of composites with polymer matrices, including parameters such as the fibre material, fabric weaving, fibre orientation, temperature, frequency, particle size, volume of short fibres, and epoxy resin type. If other articles focus on one type of composite and 1–2 parameters, then the benefit of this article lies in our analysis of 8 mentioned parameters in the experimental analysis of 27 different types of composites with polymer matrices. The tested fibre materials were glass, aramid, and carbon; the tested woven fabrics were twill, plain, unidirectional, and satin; the temperature range was from −50 to +230 °C; the frequency was 1 Hz and 10 Hz; the particle size was 0.1–16 mm; the volume percentages of the short fibres were 3, 6, and 12 vol.% of the hybrid polymer composites and the type of polymer matrix. We used the free-damped-vibration method with vibration dynamic signal analysis and the forced-damped vibration of dynamic mechanical thermal analysis for testing. We ranked the parameters that influence the dynamic vibration properties according to the effects. Among sets of results provided in the paper, considering the storage modulus, loss modulus, and loss factor, the best results of the fibre composites were for aramid-fibre-reinforced polymers, regardless of the weave type, with an advantage for unidirectional fabric. The best results of the particle composites were for those with fine filler sizes that incorporated the short fibres.
The Influence of Filler Loading and Alkaline Treatment on the Mechanical Properties of Palm Kernel Cake Filler Reinforced Epoxy Composites
Authors: Cionita Tezara , Siregar Januar Parlaungan , Shing Wong Ling , Hee Cheng Wan , Fitriyana Deni Fajar , Jaafar Jamiluddin , Junid Ramli , Irawan Agustinus Purna , Hadi Agung Efriyo
Published: July 2022

The manufacturing of materials, in conjunction with green technology, emphasises the need to employ renewable resources to ensure long-term sustainability. Re-exploring renewable elements that can be employed as reinforcing materials in polymer composites has been a major endeavour. The research goal is to determine how well palm kernel cake filler (PKCF) performs in reinforced epoxy composites. In this study, PKCF with 100 mesh was mixed with epoxy resin (ER) in various ratios ranging from 10% to 40% by weight. Hand lay-up with an open mould is proposed as a method for fabricating the specimen test. Surface modification of PKCF with varying concentrations of NaOH (5 wt.% and 10 wt.%) will be contrasted with the untreated samples. Using Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC), the effect of alkaline treatment will be examined. The tensile and maximum flexural strength of the untreated PKCF/ER composite were determined in this work, with a 30 wt.% of PKCF having the highest tensile strength of 31.20 MPa and the highest flexural strength of 39.70 MPa. The tensile and flexural strength were reduced to 22.90 MPa and 30.50 MPa, respectively, when the filler loading was raised to 40 wt.%. A 5 wt.% alkali treatment for 1 h improved the composites’ mechanical characteristics. Lastly, an alkali treatment can aid in the resolution of the problem of inadequate matrix and filler interaction. Alkaline treatment is a popular and effective method for reducing the hydroxyl group in fillers and, thus, improving interfacial bonding. Overall, palm kernel cake is a promising material used as a filler in polymer composites.
Optimization of Two-Dimensional Extended Warranty Scheme for Failure Dependence of a Multi-Component System with Improved PSO–BAS Algorithm
Authors: Dong Enzhi , Cheng Zhonghua , Wang Rongcai , Zhao Jianmin
Published: July 2022

Human society is entering the era of Industry 4.0; engineering systems are becoming more complex, which increases the difficulties of maintenance support work. Failure dependence exists widely in multi-component systems. In this work, a model of two-dimensional (2D) warranty decision making was constructed by using a failure-dependence analysis for multi-component systems and by considering the extended warranty cost and the system availability. The decision was to cut the warranty cost as much as possible for manufacturers, while the constraint condition was the minimum acceptable availability for the customer. The model combined preventive maintenance as well as corrective maintenance strategies. Under the condition that the multi-component system is replaced upon the expiration of the extended warranty (EW), the optimal 2D EW duration and preventive maintenance interval could be obtained through the model. In a case analysis, the optimal EW scheme for the gearbox of an electric multiple unit (EMU) system was obtained by using a grid search algorithm, a PSO algorithm, and a PSO–BAS algorithm. Through comparison, the PSO–BAS algorithm obtained a better scheme with lower warranty costs and higher system availability. A comparative analysis and a sensitivity analysis showed that the model provides a theoretical basis for manufacturers to optimize their 2D extended gearbox warranties.
Investigating the Molecular Mechanism of Qianghuo Shengshi Decoction in the Treatment of Ankylosing Spondylitis Based on Network Pharmacology and Molecular Docking Analysis
Authors: Luo Simin , Xiao Xiang , Luo Wenting , Zhang Xuan , Zhang Jian , Tang Songqi
Published: July 2022

Background: Qianghuo Shengshi decoction (QHSSD), a traditional Chinese medicine formula, is used to treat ankylosing spondylitis (AS) in China. The pharmacological mechanism of QHSSD for AS remains to be clarified. In this study, we investigated the molecular mechanisms of QHSSD in the treatment of AS using network pharmacology and molecular docking. Methods: To obtain the chemical components and potential targets of QHSSD, we used the Traditional Chinese Medicine Systematic Pharmacology Database and Analysis Platform (TCMSP) and SwissTargetPrediction. AS potential targets were found in the GeneCards, OMIM, and DisGenets databases. A Venn diagram was used to screen QHSSD and AS common potential targets. The STRING website and Cytoscape software were used to create and analyze protein–protein interactions and component–target networks. The DAVID database was used for the gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Molecular docking was used to visualize drug–target interactions. Results: The component–target network consisted of 119 chemical components and 193 potential targets. QHSSD was implicated in various biological processes, such as inflammation and angiogenesis, and mediated multiple signaling pathways, such as the MAPK signaling pathway. Molecular docking revealed good binding ability between medicarpin, notoptol, vitetrifolin E, and cnidilin and EGFR, TNF-α, ALB, and VEGFA. Conclusions: The chemical compositions, potential targets, and pathways involved in the QHSSD treatment of AS were successfully predicted in this study. This study provides a solid foundation for the selection of drugs to treat AS.
Extraction of Oils and Phytochemicals from Camellia oleifera Seeds: Trends, Challenges, and Innovations
Authors: Li Guihui , Ma Li , Yan Zhipeng , Zhu Qinhe , Cai Jiangtao , Wang Saiyu , Yuan Yuan , Chen Yongzhong , Deng Senwen
Published: July 2022

Camellia seed oil, extracted from the seeds of Camellia oleifera Abel., is popular in South China because of its high nutritive value and unique flavor. Nowadays, the traditional extraction methods of hot pressing extraction (HPE) and solvent extraction (SE) are contentious due to low product quality and high environmental impact. Innovative methods such as supercritical fluid extraction (SCFE) and aqueous extraction (AE) are proposed to overcome the pitfalls of the traditional methods. However, they are often limited to the laboratory or pilot scale due to economic or technical bottlenecks. Optimization of extraction processes indicates the challenges in finding the optimal balance between the yield and quality of oils and phytochemicals, as well as the environmental and economic impacts. This article aims to explore recent advances and innovations related to the extraction of oils and phytochemicals from camellia seeds, and it focuses on the pretreatment and extraction processes, as well as their complex effects on nutritional and sensory qualities. We hope this review will help readers to better understand the trends, challenges, and innovations associated with the camellia industry.
Structured Development of Digital Twins—A Cross-Domain Analysis towards a Unified Approach
Authors: Heindl Wolfgang , Stary Christian
Published: July 2022

Digital Twins (DT) as digital representations are increasingly becoming operational design tools in a variety of contexts. Although a common understanding of the concept and the underlying development procedure would facilitate DT applications, only limited information has been published on the essential stages of development and fundamental development activities. This paper examines the extent to which an abstract, and thus generally applicable model for the development of Digital Twins can be identified. In order to come up with such a reference procedure, a structured analysis of published development experiences has been performed. Three major application domains, namely product lifecycle management, manufacturing, and predictive maintenance, could be detailed and cross-checked. For each of these domains, a contextual development model could be derived from empirically valid design and engineering practices. The data also allowed for the determination of which way each model corresponds to existing Digital Twin concepts. The use of a standard modeling notation enabled the integration of the domain-specific models into a single Digital Twin development model. As a result, developers are guided by domain-independent and -dependent development steps. Due to its generic structure, the model can serve for further domain explorations.
Network Pharmacology and Molecular Docking Based Prediction of Mechanism of Pharmacological Attributes of Glutinol
Authors: Alzarea Sami I. , Qasim Sumera , Uttra Ambreen Malik , Khan Yusra Habib , Aljoufi Fakhria A. , Ahmed Shaimaa Rashad , Alanazi Madhawi , Malhi Tauqeer Hussain
Published: July 2022

Glutinol, a triterpenoid compound, has no documented systematic investigation into its mechanism. Hence, we used network pharmacology to investigate glutinol’s mechanism. The chemical formula of glutinol was searched in the PubChem database for our investigation. The BindingDB Database was utilized to discover probable glutinol target genes after ADMET analysis with the pkCSM software. DAVID tools were also used to perform Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of target genes. We also uploaded the targets to the STRING database to obtain the protein interaction network at the same time. Then, we performed some molecular docking using glutinol and targets. Finally, we used Cytoscape to visualize and evaluate a protein–protein interaction network and a drug-target-pathway network. Glutinol has good biological activity and drug utilization, according to our findings. A total of 32 target genes were discovered. Bioinformatics and network analysis were used, allowing the discovery that these target genes are linked to carcinogenesis, diabetes, inflammatory response, and other biological processes. These findings showed that glutinol can operate on a wide range of proteins and pathways to establish a pharmacological network that can be useful in drug development and use.
Reimagining Prosthetic Control: A Novel Body-Powered Prosthetic System for Simultaneous Control and Actuation
Authors: Nagaraja Vikranth H. , da Ponte Lopes Jhonatan , Bergmann Jeroen H. M.
Published: July 2022

Globally, the most popular upper-limb prostheses are powered by the human body. For body-powered (BP) upper-limb prostheses, control is provided by changing the tension of (Bowden) cables to open or close the terminal device. This technology has been around for centuries, and very few BP alternatives have been presented since. This paper introduces a new BP paradigm that can overcome certain limitations of the current cabled systems, such as a restricted operation space and user discomfort caused by the harness to which the cables are attached. A new breathing-powered system is introduced to give the user full control of the hand motion anywhere in space. Users can regulate their breathing, and this controllable airflow is then used to power a small Tesla turbine that can accurately control the prosthetic finger movements. The breathing-powered device provides a novel prosthetic option that can be used without limiting any of the user’s body movements. Here we prove that it is feasible to produce a functional breathing-powered prosthetic hand and show the models behind it along with a preliminary demonstration. This work creates a step-change in the potential BP options available to patients in the future.
Factors Influencing Household Waste Separation Behavior: Cases of Russia and Finland
Authors: Zaikova Anna , Deviatkin Ivan , Havukainen Jouni , Horttanainen Mika , Astrup Thomas Fruergaard , Saunila Minna , Happonen Ari
Published: July 2022

This paper investigates the factors influencing the behavior of individuals in source-separation of municipal solid waste in an immature system for collection of recyclable waste (Saint Petersburg, Russia) and a more mature waste system (selected urban areas, Finland). Online questionnaires were applied to collect data from citizens of Saint Petersburg and the Finnish urban population. The data were examined within an extended theory of planned behavior using structural equation modeling for the identification of factors affecting waste source-separation behavior. The findings indicate that the factors differed significantly in the two waste systems. In Russia, the inconvenience of waste collection limited waste source-separation behavior, while intentions of individuals and information availability had an almost equal positive effect. In Finland, waste source-separation behavior was mostly affected by people’s intentions. Based on the findings, recommendations for the development of recycling practices were made for practitioners in Russia and possibly other early-stage systems for the collection of recyclable waste. Limitations of the study pinpointed the possibilities for future research.
Religious Devotion to Political Secularism
Authors: Ghobadzadeh Naser
Published: July 2022

By investigating the formation of Twelver Shīʿī theology, this article seeks to show that, despite being political and despite its advocacy of pure theocracy, living in the shadow of a secular state is part of Shīʿī religious doctrine. It is argued that existential threats against Proto-Twelver Shīʿism during its formative centuries led to a messianic conception of the twelfth Imām, the only person whose direct leadership can enable a religiously legitimate state to be formed. Therefore, until his return—which is subject to the will of God—all rulers are usurpers and imposers on the right of the twelfth Imām. Shīʿī leaders are not allowed to seize the institution of government, and non-governmentalism is institutionalized as part of Shīʿī political theology. Instead of focusing on the characteristics of a legitimate ruler and how to form a legitimate government, the founding Shīʿī scholars were concerned with how to co-exist with a usurper. It will be demonstrated that these scholars had differing ideas about the scope and scale of engagement/disengagement with the institution of the state, but none of them discussed the possibility of forming a religiously legitimate government before the return of the twelfth Imām.
Multiple Bonus–Malus Scale Models for Insureds of Different Sizes
Authors: Boucher Jean-Philippe
Published: July 2022

How to consider the a priori risks in experience-rating models has been questioned in the actuarial community for a long time. Classic past-claim-rating models, such as the Buhlmann–Straub credibility model, normalize the past experience of each insured before applying claim penalties. On the other hand, classic Bonus–Malus Scales (BMS) models generate the same surcharges and the same discounts for all insureds because the transition rules within the class system do not depend on the a priori risk. Despite the quality of prediction of the BMS models, this experience-rating model could appear unfair to many insureds and regulators because it does not recognize the initial risk of the insured. In this paper, we propose the creation of different BMSs for each type of insured using recursive partitioning methods. We apply this approach to real data for the farm insurance product of a major Canadian insurance company with widely varying sizes of insureds. Because the a priori risk can change over time, a study of the possible transitions between different BMS models is also performed.
Population of Degrading Small Impact Craters in the Chang’E-4 Landing Area Using Descent and Ground Images
Authors: Hu Teng , Yang Ze , Kang Zhizhong , Lin Hongyu , Zhong Jie , Zhang Dongya , Cao Yameng , Geng Haomin
Published: July 2022

The landing camera (LCAM) of Chang’e-4 lander provides a series of low (46 cm/pixel) to high (2.3 cm/pixel) resolution images, which are suitable for centimeter-scale craters. In this paper, we analyze the degradation of those small-sized craters to provide detailed information on the local geological evolution of the lunar surface. From the mosaicked descent image, 6316 craters were extracted and classified into four degradation levels based on their morphology on the image: fresh, slightly degraded, moderately degraded, and severely degraded. The ground terrain camera (TCAM) image and the DEM of the Yutu-2 panoramic camera (PCAM) validate the crater degradation levels from a qualitative and quantitative perspective, respectively. The results show that the smaller the size of the craters, the more easily they are degraded. The crater populations in equilibrium in the four study areas indicate that the cumulative size–frequency distribution (SFD) slope is different from previous research results, and the smaller the craters, the more difficult to reach an equilibrium state (for craters smaller than a given size, the production rate is exactly balanced by the removal rate), which may be due to secondary cratering and surface resurfacing caused by the burial of ejecta from neighboring craters.
Multi-Dimensional Parameter Estimation in Polarimetric ULA with Cross-Distribution Dipole Pairs
Authors: Zhong Tiantian , Tao Haihong , Lan Lan
Published: July 2022

This paper investigates the estimation of parameters—including the elevation angle, azimuth angle, polarization auxiliary angle, polarization phase difference, frequency and range of near-field sources in a Polarimetric Uniform Linear Array (P-ULA) with defective electromagnetic vector sensors. The cross-distribution dipole pairs are alternately placed in the xoy plane and yoz plane, respectively, and the whole array is divided into two subarrays, where subarray 1 consists of all of the dipole pairs placed in the xoy plane, while the dipole pairs placed in yoz plane are gathered in subarray 2. Specifically, the polarization auxiliary angle and the polarization phase difference, as well as the elevation and azimuth angles of the sources, are firstly estimated based on the Fourth-Order Cumulant (FOC) matrix in each subarray. Moreover, a decoupling method is developed to obtain the elevation and azimuth. Subsequently, the frequency and range are estimated based on the FOC matrix. Then, the parameter pair matching method is performed in order to match the pairs. Finally, an analysis of the Cramér-Rao Bound (CRB) is provided, and comparisons of the root mean square error with respect to the different input signal-to-noise ratios and number of snapshots, among different estimation methods, are implemented in the environment of additive white gaussian noise. The simulation results are provided in order to verify the effectiveness and feasibility of the proposed method for multi-dimensional parameter estimation.
Retrieval of Aged Biomass-Burning Aerosol Properties by Using GRASP Code in Synergy with Polarized Micro-Pulse Lidar and Sun/Sky Photometer
Authors: López-Cayuela María-Ángeles , Herrera Milagros E. , Córdoba-Jabonero Carmen , Pérez-Ramírez Daniel , Carvajal-Pérez Clara Violeta , Dubovik Oleg , Guerrero-Rascado Juan Luis
Published: July 2022

The aim of this study was to analyze the potential of the GRASP code to retrieve optical and microphysical properties vertically-resolved using a synergy of polarized Micro-Pulse Lidar and Sun/sky photometer observations. The focus was on the long-range transport of Canadian aged-smoke plumes observed at El Arenosillo/Huelva (Spain) from 7 to 8 September 2017. Both the columnar and height-resolved microphysical and optical properties were assessed in comparison with AERONET data and vertical lidar-retrieved profiles, respectively. In particular, the vertical properties were also derived using the POLIPHON approach, which serves as a comparison for GRASP retrievals. The retrieved columnar aerosol microphysical properties (volume concentration and effective radius) showed an excellent agreement, with negligible differences, and were within the uncertainties. Nevertheless, for the retrieved columnar optical properties, we could only perform an individual comparison, due to the strong AERONET limitations, and although the agreements were generally good, no conclusions were obtained, due to differences in the real refractive index and due to the large uncertainties obtained in the retrievals. For the vertical profiles, however, we present a large advance that permits obtaining aerosol backscatter and extinction coefficients, plus volume concentrations, without the need for internal assumptions (extinction-to-backscatter ratios and depolarization measurements), due to the very good agreement observed between GRASP and the lidar-derived methodologies. However, the separation of the properties into their fine and coarse modes was not feasible using the one-wavelength elastic lidar measurements with the GRASP retrieval configuration used in this work. Therefore, current studies are being addressed to assessing the introduction of lidar depolarization in the GRASP code as an encouraged added-value, for the improvement of the retrieval of vertical aerosol properties.
Chinese High Resolution Satellite Data and GIS-Based Assessment of Landslide Susceptibility along Highway G30 in Guozigou Valley Using Logistic Regression and MaxEnt Model
Authors: Liu Ying , Zhao Liangjun , Bao Anming , Li Junli , Yan Xiaobing
Published: July 2022

Landslide disasters frequently occur along the highway G30 in the Guozigou Valley, the corridor of energy, material, economic and cultural exchange, etc., between Yili and other cities of China and Central Asia. However, little attention has been paid to assess the detailed landslide susceptibility of the strategically important highway, especially with high spatial resolution data and the generative presence-only MaxEnt model. Landslide susceptibility assessment (LSA) is a first and vital step for preventing and mitigating landslide hazards. The goal of the current study was to perform LSA for the landslide-prone highway G30 in Guozigou Valley, China with the aid of GIS tools and Chinese high resolution Gaofen-1 (GF-1) satellite data, and analyze and compare the performance of the maximum entropy (MaxEnt) model and logistic regression (LR). Thirty five landslides were determined in the study region, using GF-1 satellite data, official data, and field surveys. Seven landslide conditioning factors, including altitude, slope, aspect, gully density, lithology, faults density, and NDVI, were used to investigate their existing spatial relationships with landslide occurrences. The LR and MaxEnt model performance were assessed by the receiver operating characteristic curve, presenting areas under the curve equal to 0.85 and 0.94, respectively. The performance of the MaxEnt model was slightly better than that of the LR model. A landslide susceptibility map was created through reclassifying the landslides occurrence probability with the classification method of natural breaks. According to the MaxEnt model results, 3.29% and 3.82% of the study region is highly and very highly susceptible to future landslide events, respectively, with the highest landslide susceptibility along the highway. The generated landslide susceptibility map could help government agencies and decision-makers to make wise decisions for preventing or mitigating landslide hazards along the highway and design schemes of highway engineering and maintenance in Guozigou Valley, the mountainous areas.
An Overview of Precision Weed Mapping and Management Based on Remote Sensing
Authors: Andujar Dionisio , Martinez-Guanter Jorge
Published: July 2022

Precision Agriculture face the challenge of feeding an increasing population, maximizing yield while optimizing inputs [...]
Aerial Imagery-Based Building Footprint Detection with an Integrated Deep Learning Framework: Applications for Fine Scale Wildland–Urban Interface Mapping
Authors: Huang Yuhan , Jin Yufang
Published: July 2022

Human encroachment into wildlands has resulted in a rapid increase in wildland–urban interface (WUI) expansion, exposing more buildings and population to wildfire risks. More frequent mapping of structures and WUIs at a finer spatial resolution is needed for WUI characterization and hazard assessment. However, most approaches rely on high-resolution commercial satellite data with a particular focus on urban areas. We developed a deep learning framework tailored for building footprint detection in the transitional wildland–urban areas. We leveraged meter scale aerial imageries publicly available from the National Agriculture Imagery Program (NAIP) every 2 years. Our approach integrated Mobile-UNet and generative adversarial network. The deep learning models trained over three counties in California performed well in detecting building footprints across diverse landscapes, with an F1 score of 0.62, 0.67, and 0.75 in the interface WUI, intermix WUI, and rural regions, respectively. The bi-annual mapping captured both housing expansion and wildfire-caused building damages. The 30 m WUI maps generated from these finer footprints showed more granularity than the existing census tract-based maps and captured the transition of WUI dynamics well. More frequent updates of building footprint and improved WUI mapping will improve our understanding of WUI dynamics and provide guidance for adaptive strategies on community planning and wildfire hazard reduction.
Mapping Roads in the Brazilian Amazon with Artificial Intelligence and Sentinel-2
Authors: Botelho Jonas , Costa Stefany C. P. , Ribeiro Júlia G. , Souza Carlos M.
Published: July 2022

This study presents our efforts to automate the detection of unofficial roads (herein, roads) in the Brazilian Amazon using artificial intelligence (AI). In this region, roads are built by loggers, goldminers, and unauthorized land settlements from existing official roads, expanding over pristine forests and leading to new deforestation and fire hotspots. Previous research used visual interpretation, hand digitization, and vector editing techniques to create a thorough Amazon Road Dataset (ARD) from Landsat imagery. The ARD allowed assessment of the road dynamics and impacts on deforestation, landscape fragmentation, and fires and supported several scientific and societal applications. This research used the existing ARD to train and model a modified U-Net algorithm to detect rural roads in the Brazilian Amazon using Sentinel-2 imagery from 2020 in the Azure Planetary Computer platform. Moreover, we implemented a post-AI detection protocol to connect and vectorize the U-Net road detected to create a new ARD. We estimated the recall and precision accuracy using an independent ARD dataset, obtaining 65% and 71%, respectively. Visual interpretation of the road detected with the AI algorithm suggests that the accuracy is underestimated. The reference dataset does not include all roads that the AI algorithm can detect in the Sentinel-2 imagery. We found an astonishing footprint of roads in the Brazilian Legal Amazon, with 3.46 million km of roads mapped in 2020. Most roads are in private lands (~55%) and 25% are in open public lands under land grabbing pressure. The roads are also expanding over forested areas with 41% cut or within 10 km from the roads, leaving 59% of the 3.1 million km2 of the remaining original forest roadless. Our AI and post-AI models fully automated road detection in rural areas of the Brazilian Amazon, making it possible to operationalize road monitoring. We are using the AI road map to understand better rural roads’ impact on new deforestation, fires, and landscape fragmentation and to support societal and policy applications for forest conservation and regional planning.
Evaluation of the Foot Center of Pressure Estimation from Pressure Insoles during Sidestep Cuts, Runs and Walks
Authors: Morin Pauline , Muller Antoine , Pontonnier Charles , Dumont Georges
Published: July 2022

Estimating the foot center of pressure (CoP) position by pressure insoles appears to be an interesting technical solution to perform motion analysis beyond the force platforms surface area. The aim of this study was to estimate the CoP position from Moticon® pressure insoles during sidestep cuts, runs and walks. The CoP positions assessed from force platform data and from pressure insole data were compared. One calibration trial performed on the force platforms was used to localize the insoles in the reference coordinate system. The most accurate results were obtained when the motion performed during the calibration trial was similar to the motion under study. In such a case, mean accuracy of CoP position have been evaluated to 15±4mm along anteroposterior (AP) axis and 8.5±3mm along mediolateral (ML) axis for sidestep cuts, 18±5mm along AP axis and 7.3±4mm along ML axis for runs, 15±6mm along AP axis and 6.6±3mm along ML axis for walks. The accuracy of the CoP position assesment from pressure insole data increased with the vertical force applied to the pressure insole and with the number of pressure cells involved.
Tip-Enhanced Raman Spectroscopy Based on Spiral Plasmonic Lens Excitation
Authors: Gu Kai , Sun Ming , Zhang Yang
Published: July 2022

In this study, we proposed the idea of replacing the traditional objective lens in bottom-illumination mode with a plasmonic lens (PL) to achieve tip-enhanced Raman spectroscopy (TERS). The electric field energy of surface plasmon polaritons (SPPs) of the spiral PL was found to be more concentrated at the focal point without any sidelobe using the finite-difference time domain (FDTD) method compared with that of a symmetry-breaking PL. This property reduces far-field background noise and increases the excitation efficiency of the near-field Raman signal. The disadvantage of only the near-field Raman scattering of samples at the center of the structure being detected when using an ordinary PL in TERS is overcome by using our proposed method of changing only the polarization of the incident light.
Explaining One-Dimensional Convolutional Models in Human Activity Recognition and Biometric Identification Tasks
Authors: Aquino Gustavo , Costa Marly G. F. , Costa Filho Cicero F. F.
Published: July 2022

Due to wearables’ popularity, human activity recognition (HAR) plays a significant role in people’s routines. Many deep learning (DL) approaches have studied HAR to classify human activities. Previous studies employ two HAR validation approaches: subject-dependent (SD) and subject-independent (SI). Using accelerometer data, this paper shows how to generate visual explanations about the trained models’ decision making on both HAR and biometric user identification (BUI) tasks and the correlation between them. We adapted gradient-weighted class activation mapping (grad-CAM) to one-dimensional convolutional neural networks (CNN) architectures to produce visual explanations of HAR and BUI models. Our proposed networks achieved 0.978 and 0.755 accuracy, employing both SD and SI. The proposed BUI network achieved 0.937 average accuracy. We demonstrate that HAR’s high performance with SD comes not only from physical activity learning but also from learning an individual’s signature, as in BUI models. Our experiments show that CNN focuses on larger signal sections in BUI, while HAR focuses on smaller signal segments. We also use the grad-CAM technique to identify database bias problems, such as signal discontinuities. Combining explainable techniques with deep learning can help models design, avoid results overestimation, find bias problems, and improve generalization capability.
Implementation of ISO/IEEE 11073 PHD SpO2 and ECG Device Specializations over Bluetooth HDP following Health Care Profile for Smart Living
Authors: Cristobal-Huerta Alexandra , Torrado-Carvajal Angel , Rodriguez-Sanchez Cristina , Hernandez-Tamames Juan Antonio , Luaces Maria , Borromeo Susana
Published: July 2022

Current m-Health scenarios in the smart living era, as the interpretation of the smart city at each person’s level, present several challenges associated with interoperability between different clinical devices and applications. The Continua Health Alliance establishes design guidelines to standardize application communication to guarantee interoperability among medical devices. In this paper, we describe the implementation of two IEEE agents for oxygen saturation level (SpO2) measurements and electrocardiogram (ECG) data acquisition, respectively, and a smartphone IEEE manager for validation. We developed both IEEE agents over the Bluetooth Health Device Profile following the Continua guidelines and they are part of a telemonitoring system. This system was evaluated in a sample composed of 10 volunteers (mean age 29.8 ± 7.1 y/o; 5 females) under supervision of an expert cardiologist. The evaluation consisted of measuring the SpO2 and ECG signal sitting and at rest, before and after exercising for 15 min. Physiological measurements were assessed and compared against commercial devices, and our expert physician did not find any relevant differences in the ECG signal. Additionally, the system was assessed when acquiring and processing different heart rate data to prove that warnings were generated when the heart rate was under/above the thresholds for bradycardia and tachycardia, respectively.
Characterization of Nuclear Pleomorphism and Tubules in Histopathological Images of Breast Cancer
Authors: Peregrina-Barreto Hayde , Ramirez-Guatemala Valeria Y. , Lopez-Armas Gabriela C. , Cruz-Ramos Jose A.
Published: July 2022

Breast cancer (BC) diagnosis is made by a pathologist who analyzes a portion of the breast tissue under the microscope and performs a histological evaluation. This evaluation aims to determine the grade of cellular differentiation and the aggressiveness of the tumor by the Nottingham Grade Classification System (NGS). Nowadays, digital pathology is an innovative tool for pathologists in diagnosis and acquiring new learning. However, a recurring problem in health services is the excessive workload in all medical services. For this reason, it is required to develop computational tools that assist histological evaluation. This work proposes a methodology for the quantitative analysis of BC tissue that follows NGS. The proposed methodology is based on digital image processing techniques through which the BC tissue can be characterized automatically. Moreover, the proposed nuclei characterization was helpful for grade differentiation in carcinoma images of the BC tissue reaching an 0.84 accuracy. In addition, a metric was proposed to assess the likelihood of a structure in the tissue corresponding to a tubule by considering spatial and geometrical characteristics between lumina and its surrounding nuclei, reaching an accuracy of 0.83. Tests were performed from different databases and under various magnification and staining contrast conditions, showing that the methodology is reliable for histological breast tissue analysis.
Three-Dimensional Lower-Limb Kinematics from Accelerometers and Gyroscopes with Simple and Minimal Functional Calibration Tasks: Validation on Asymptomatic Participants
Authors: Carcreff Lena , Payen Gabriel , Grouvel Gautier , Massé Fabien , Armand Stéphane
Published: July 2022

The use of inertial measurement units (IMUs) to compute gait outputs, such as the 3D lower-limb kinematics is of huge potential, but no consensus on the procedures and algorithms exists. This study aimed at evaluating the validity of a 7-IMUs system against the optoelectronic system. Ten asymptomatic subjects were included. They wore IMUs on their feet, shanks, thighs and pelvis. The IMUs were embedded in clusters with reflective markers. Reference kinematics was computed from anatomical markers. Gait kinematics was obtained from accelerometer and gyroscope data after sensor orientation estimation and sensor-to-segment (S2S) calibration steps. The S2S calibration steps were also applied to the cluster data. IMU-based and cluster-based kinematics were compared to the reference through root mean square errors (RMSEs), centered RMSEs (after mean removal), correlation coefficients (CCs) and differences in amplitude. The mean RMSE and centered RMSE were, respectively, 7.5° and 4.0° for IMU-kinematics, and 7.9° and 3.8° for cluster-kinematics. Very good CCs were found in the sagittal plane for both IMUs and cluster-based kinematics at the hip, knee and ankle levels (CCs > 0.85). The overall mean amplitude difference was about 7°. These results reflected good accordance in our system with the reference, especially in the sagittal plane, but the presence of offsets requires caution for clinical use.
Smartphone-Based Electrochemical Systems for Glucose Monitoring in Biofluids: A Review
Authors: Xu Jie , Yan Zupeng , Liu Qingjun
Published: July 2022

As a vital biomarker, glucose plays an important role in multiple physiological and pathological processes. Thus, glucose detection has become an important direction in the electrochemical analysis field. In order to realize more convenient, real-time, comfortable and accurate monitoring, smartphone-based portable, wearable and implantable electrochemical glucose monitoring is progressing rapidly. In this review, we firstly introduce technologies integrated in smartphones and the advantages of these technologies in electrochemical glucose detection. Subsequently, this overview illustrates the advances of smartphone-based portable, wearable and implantable electrochemical glucose monitoring systems in diverse biofluids over the last ten years (2012–2022). Specifically, some interesting and innovative technologies are highlighted. In the last section, after discussing the challenges in this field, we offer some future directions, such as application of advanced nanomaterials, novel power sources, simultaneous detection of multiple markers and a closed-loop system.
Mussel Inspired Polydopamine as Silica Fibers Coating for Solid-Phase Microextraction
Authors: Aresta Antonella , Cicco Stefania R. , Vona Danilo , Farinola Gianluca Maria , Zambonin Carlo
Published: July 2022

Commercial solid-phase microextraction fibers are available in a limited number of expensive coatings, which often contain environmentally harmful substances. Consequently, several different approaches have been used in the attempt to develop new sorbents that should possess intrinsic characteristics such as duration, selectivity, stability, and eco-friendliness. Herein we reported a straightforward, green, and easy coating method of silica fibers for solid-phase microextraction with polydopamine (PDA), an adhesive, biocompatible organic polymer that is easily produced by oxidative polymerization of dopamine in mild basic aqueous conditions. After FT-ATR and SEM characterization, the PDA fibers were tested via chromatographic analyses performed on UHPLC system using biphenyl and benzo(a)pyrene as model compounds, and their performances were compared with those of some commercial fibers. The new PDA fiber was finally used for the determination of selected PAHs in soot samples and the results compared with those obtained using the commercial PA fiber. Good reproducibility, extraction stability, and linearity were obtained using the PDA coating, which proved to be a very promising new material for SPME.
Deep Learning Beehive Monitoring System for Early Detection of the Varroa Mite
Authors: Voudiotis George , Moraiti Anna , Kontogiannis Sotirios
Published: July 2022

One of the most critical causes of colony collapse disorder in beekeeping is caused by the Varroa mite. This paper presents an embedded camera module supported by a deep learning algorithm for the process of early detecting of Varroa infestations. This is achieved using a deep learning algorithm that tries to identify bees inside the brood frames carrying the mite in real-time. The end-node device camera module is placed inside the brood box. It is equipped with offline detection in remote areas of limited network coverage or online imagery data transmission and mite detection over the cloud. The proposed deep learning algorithm uses a deep learning network for bee object detection and an image processing step to identify the mite on the previously detected objects. Finally, the authors present their proof of concept experimentation of their approach that can offer a total bee and varroa detection accuracy of close to 70%. The authors present in detail and discuss their experimental results.
Biochar Additions Alter the Abundance of P-Cycling-Related Bacteria in the Rhizosphere Soil of Portulaca oleracea L. under Salt Stress
Authors: Egamberdieva Dilfuza , Ma Hua , Shurigin Vyacheslav , Alimov Jakhongir , Wirth Stephan , Bellingrath-Kimura Sonoko Dorothea
Published: July 2022

Numerous reports confirm a positive impact of biochar amendments on soil enzyme activities, nutrient cycles, and, finally, plant growth and development. However, reports explaining the process behind such diverse observations are scarce. The aim of the present study was (1) to evaluate the effect of biochar on the growth of purslane (Portulaca oleracea L.) and nutrients; (2) to determine the response of rhizosphere enzyme activities linked to soil phosphorus cycling after bio-char amendment under non–saline and saline soil conditions. Furthermore, we investigate whether adding biochar to soil alters the abundance of P-cycling-related bacteria. Two rates of biochar (2% and 4%) were applied in pot experiments. Biochar addition of 2% significantly increased plant growth under non-saline and saline soil conditions by 21% and 40%, respectively. Moreover, applying biochar increased soil microbial activity as observed by fluorescein diacetate (FDA) hydrolase activity, as well as phosphomonoesterase activities, and the numbers of colony-forming units (CFU) of P-mobilizing bacteria. Soil amended with 2% biochar concentration increased total soil nitrogen (Nt), phosphorus (P), and total carbon (Ct) concentrations by 18%, 15%, and 90% under non-saline soil conditions and by 29%, 16%, and 90% in saline soil compared the control, respectively. The soil FDA hydrolytic activity and phosphatase strongly correlate with soil Ct, Nt, and P contents. The rhizosphere soil collected after biochar amendment showed a higher abundance of tricalcium phosphate-solubilizing bacteria than the control soil without biochar. Overall, this study demonstrated that 2% maize-derived biochar positively affects halophyte plant growth and thus could be considered for potential use in the reclamation of degraded saline soil.
The Association between Bilateral Deficit and Athletic Performance: A Brief Review
Authors: Železnik Petra , Slak Vita , Kozinc Žiga , Šarabon Nejc
Published: July 2022

An abundance of information can be found in the scientific literature regarding the bilateral deficit (BLD) in different contraction types, including its possible underlying mechanisms. On the other hand, studies on the relationship between BLD and athletic performance have only begun to emerge in recent years. The purpose of this review article is to assemble and analyze the literature on the topic of the relationship between BLD and athletic performance. After a detailed review of the scientific databases, we analyzed 10 relevant scientific articles. BLD calculated from outcomes of vertical jumps was positively related to the ability to change direction quickly in volleyball, basketball, tennis and student population, but not in soccer. Sprint running performance does not seem to be associated with BLD, while one study suggested that a smaller BLD is associated with a more efficient start in a sprint. Apart from the associations with change in direction performance, there is little evidence to support the association between BLD and athletic performance; thus, further research is required in other sports, incorporating sport-specific performance outcomes and multiple tasks to calculate the BLD.
Comparing the Current Training Running Demands of Elite Camogie Players to Competitive Match-Play
Authors: Connors Philip , Browne Declan , Earls Des , Fitzpatrick Paula , Rankin Paula
Published: July 2022

Training to meet match-play demands is a primary objective in an athlete’s preparation for their games. Despite camogie match-play running demands being available, how current training practices compare, specifically individual training components, remains unknown. This study aimed to investigate and compare current elite camogie training to match-play demands. Thirty-three (n = 33) elite camogie players wore 10 Hz Playertek GPS units during twenty-five training sessions and ten competitive matches. Training sessions were analysed using ball-in-play time and split into warm-ups, drills, small-sided games, running, and training matches. Metrics were converted into relative terms (per minute), to allow comparisons. Players cover significantly greater (p < 0.05) total distance (non-parametric standardised effect sizes (r = 0.45)), peak speed (r = 0.45), high-speed running (r = 0.13), sprint distance (r = 0.20), and total decelerations (r = 0.12–0.22) during match-play than training. Relatively, players cover significantly greater distance during running, small-sided games, and training matches compared to match-play (r = 0.21–0.29). Compared with match-play, running results in significantly greater high-speed running and sprint distance (r = 0.18–0.41), with greater accelerations (3–4 m∙s−2) during warm-ups, running, and small-sided games (r = 0.14–0.28). Current total training demands seem to fall behind match-play. However, relatively, training matches and small-sided games match or surpass competitive match-play demands. These findings may be utilised in preparing camogie teams for competition.