bluuebunny/crossref_metadata_2025 huggingface dataset:
Morphology Analysis of Friction Surfaces of Composites Based on PTFE and Layered Silicates
Authors: Kapitonova Iuliia , Lazareva Nadezhda , Tarasova Praskovia , Okhlopkova Aitalina , Laukkanen Samuel , Mukhin Vasiliy
Published: November 2022

In the present study, the tribological behavior of polytetrafluoroethylene (PTFE) composites filled with natural layered silicates (LS) was investigated. The change in the morphology of the friction surface of composites depending on the content and chemical composition of layered silicates has been shown. The friction surface of PTFE composites with layered silicates was investigated by scanning electron microscopy (SEM). The formation on the friction surface of a special layer with a structure different from the bulk of the polymer, which is formed from particles of fillers and wear products, has been established. The thickness of this layer is independent of the content of layered silicates in the polymer. It was indicated that wear debris of PTFE composites was assembled during friction and uniformly cover the friction surface layer by layer, thereby forming a protective layer.
Synthesis and Characterization of Poly(2-vinylpyridine) and Poly(4-vinylpyridine) with Metal Oxide (TiO2, ZnO) Films for the Photocatalytic Degradation of Methyl Orange and Benzoic Acid
Authors: Martínez Iririana , Santillán Ricardo , Fuentes Camargo Iliana , Rodríguez Julia Liliana , Andraca Adame J. Alberto , Gutiérrez Hugo Martínez
Published: November 2022

In this study, composite material films of pyridine-based polymer and metal oxides (ZnO and TiO2) were successfully deposited by spin coating method for environmental remediation. Firstly, the polymers poly(2-vinylpyridine) P(2-VP), and poly(4-vinylpyridine) P(4-VP) were synthesized via solution polymerization. The analysis by grazing incidence X-ray diffraction (GIXRD) reveals semicrystalline nature and scanning electron microscopy (SEM) indicates that the poly(vinylpyridines) clusters of particles were observed on the surface of the films. It was also shown that the morphology of composite materials is completely dependent on the chemical nature of the oxide. In the case of P(2-VP)-TiO2 and P(4-VP)-TiO2, some channels or pathways of TiO2 on the surface of films were observed. However, the surface morphology of the polymer composites formulated with ZnO shows a homogeneous distribution in P(2-VP) and P(4-VP) matrix. The effectiveness of the composite materials in the photodegradation of methyl orange (MO) was evaluated by photocatalysis. According to the results, the P(4-VP)-ZnO composite exhibited the highest photodegradation of MO, allowing the separation of photogenerated species required for the photocatalytic reaction. The P(4-VP)-ZnO composite was also tested in benzoic acid (BA) photodegradation in water. The presence of some scavengers in the reaction system reveals that hydroxyl radicals (OH•), superoxide radicals (O2-•) and holes (h+) are responsible for the BA reduction by photocatalysis.
Evaluation of Mechanical Properties of Porous Chitosan/Gelatin/Polycaprolactone Bone Scaffold Prepared by Microwave Foaming Method
Authors: Wulin Shihan , Shiu Bing-Chiuan , Yuan Qian-Yu , Zhangjian He-qin , Lin Jia-Horng , Lou Ching-Wen
Published: November 2022

Bone tissue may suffer from bone injury and bone defects due to accidents or diseases. Since the demand for autologous bone and allograft tissue far exceeds the supply, bone scaffolds have taken the lead. The use of bone scaffolds is one of the measures to help heal or regenerate bone tissue. Therefore, a new bone scaffold was proposed in this study, which has a simpler preparation process and stronger performance. This study proposes bone scaffolds with an attempt to use polymers that are synthesized separately with three types of minerals as the filler using the microwave foaming method as follows. A 0.1 wt% of montmorillonite (MMT), zinc oxide (ZnO), or titanium dioxide (TiO2) is added to chitosan (CS)/gelatin mixtures, respectively, after which sodium bicarbonate is added as a foaming agent, thereby forming porous gels. The polymer synthesized from three minerals was used as filler. The following microwave foaming method was adopted: 0.1 wt% MMT, ZnO, or TiO2 was added to the CS/gelatin mixture, and then sodium bicarbonate was added as a foaming agent to form a porous gel. Next, porous gels and polycaprolactone were combined in a self-made mold in order to form bone scaffolds. A stereo microscope is used to observe the morphology of bone scaffolds, after which the pore size analysis, pore connectivity, swell property, porosity, and compressive strength are tested, examining the effects of the mineral type on bone scaffolds. The test results indicate that with MMT being the filler and sodium bicarbonate being the foaming agent, the resulting bone scaffolds yield a porous structure with a pore size between 120 μm and 370 μm. Besides, the incorporation of polycaprolactone also provides samples of 1MCG-P, 2MCG-P, and 5MCG-P with a certain compressive strength of 150–170 MPa. To sum up, the test results substantiate that a combination of the microwave foaming method and MMT generates a porous structure for bone scaffolds (1MCG-P, 2MCG-P, and 5MCG-P), involving a porosity of 38%, an inter-connected porous structure, and the compressive strength that exceeds 150 MPa.
Bacterial Cellulose-Based Polymer Nanocomposites: A Review
Authors: Revin Viktor V. , Liyaskina Elena V. , Parchaykina Marina V. , Kuzmenko Tatyana P. , Kurgaeva Irina V. , Revin Vadim D. , Ullah Muhammad Wajid
Published: November 2022

Bacterial cellulose (BC) is currently one of the most popular environmentally friendly materials with unique structural and physicochemical properties for obtaining various functional materials for a wide range of applications. In this regard, the literature reporting on bacterial nanocellulose has increased exponentially in the past decade. Currently, extensive investigations aim at promoting the manufacturing of BC-based nanocomposites with other components such as nanoparticles, polymers, and biomolecules, and that will enable to develop of a wide range of materials with advanced and novel functionalities. However, the commercial production of such materials is limited by the high cost and low yield of BC, and the lack of highly efficient industrial production technologies as well. Therefore, the present review aimed at studying the current literature data in the field of highly efficient BC production for the purpose of its further usage to obtain polymer nanocomposites. The review highlights the progress in synthesizing BC-based nanocomposites and their applications in biomedical fields, such as wound healing, drug delivery, tissue engineering. Bacterial nanocellulose-based biosensors and adsorbents were introduced herein.
A New Modified Exponent Power Alpha Family of Distributions with Applications in Reliability Engineering
Authors: Shah Zubir , Khan Dost Muhammad , Khan Zardad , Shafiq Muhammad , Choi Jin-Ghoo
Published: November 2022

Probability distributions perform a very significant role in the field of applied sciences, particularly in the field of reliability engineering. Engineering data sets are either negatively or positively skewed and/or symmetrical. Therefore, a flexible distribution is required that can handle such data sets. In this paper, we propose a new family of lifetime distributions to model the aforementioned data sets. This proposed family is known as a “New Modified Exponent Power Alpha Family of distributions” or in short NMEPA. The proposed family is obtained by applying the well-known T-X approach together with the exponential distribution. A three-parameter-specific sub-model of the proposed method termed a “new Modified Exponent Power Alpha Weibull distribution” (NMEPA-Wei for short), is discussed in detail. The various mathematical properties including hazard rate function, ordinary moments, moment generating function, and order statistics are also discussed. In addition, we adopted the method of maximum likelihood estimation (MLE) for estimating the unknown model parameters. A brief Monte Carlo simulation study is conducted to evaluate the performance of the MLE based on bias and mean square errors. A comprehensive study is also provided to assess the proposed family of distributions by analyzing two real-life data sets from reliability engineering. The analytical goodness of fit measures of the proposed distribution are compared with well-known distributions including (i) APT-Wei (alpha power transformed Weibull), (ii) Ex-Wei (exponentiated-Weibull), (iii) classical two-parameter Weibull, (iv) Mod-Wei (modified Weibull), and (v) Kumar-Wei (Kumaraswamy–Weibull) distributions. The proposed class of distributions is expected to produce many more new distributions for fitting monotonic and non-monotonic data in the field of reliability analysis and survival analysis.
An Enhanced Evaporation Rate Water-Cycle Algorithm for Global Optimization
Authors: Hussien Abdelazim G. , Hashim Fatma A. , Qaddoura Raneem , Abualigah Laith , Pop Adrian
Published: November 2022

Water-cycle algorithm based on evaporation rate (ErWCA) is a powerful enhanced version of the water-cycle algorithm (WCA) metaheuristics algorithm. ErWCA, like other algorithms, may still fall in the sub-optimal region and have a slow convergence, especially in high-dimensional tasks problems. This paper suggests an enhanced ErWCA (EErWCA) version, which embeds local escaping operator (LEO) as an internal operator in the updating process. ErWCA also uses a control-randomization operator. To verify this version, a comparison between EErWCA and other algorithms, namely, classical ErWCA, water cycle algorithm (WCA), butterfly optimization algorithm (BOA), bird swarm algorithm (BSA), crow search algorithm (CSA), grasshopper optimization algorithm (GOA), Harris Hawks Optimization (HHO), whale optimization algorithm (WOA), dandelion optimizer (DO) and fire hawks optimization (FHO) using IEEE CEC 2017, was performed. The experimental and analytical results show the adequate performance of the proposed algorithm.
Mechanics-Seepage Experimental and Simulation Study of Gas-Bearing Coal under Different Load Paths
Authors: Sun Haibo , Zhang Baoyong , Song Zhijun , Shen Bin , Song Hongyu
Published: November 2022

Mechanics-seepage synchronous tests on gas-bearing coal under three different stress paths were designed and implemented to evaluate how load path affected the mechanical strength and permeability of deep mining-disturbed coal. The cracks-count evolution of coal specimens during instability was observed through DEM numerical simulation. The results showed significant stress-strain and strength variations under different paths. At the time of failure, the specimen deformation and peak strength were Test 1 > Test 2 > Test 3, while the permeability was Test 3 > Test 2 > Test 1, with specimen permeability in Test 3 rising prominently. From numerical simulation, the cracks count was Test 2 > Test 3 > Test 1, with tensile cracks taking the largest proportion in Test 2 and shear cracks taking the largest proportion in Test 3. Our findings shed some light on the research and disaster prevention regarding coal and gas outburst.
Prolonged Disease-Free Survival in a Relapsed Adult Granulosa Cell Tumor of the Ovary Treated by Combined Leuprolide and Letrozole: Case Report
Authors: Garuti Giancarlo , Sagrada Paola Francesca , Delfrati Susanna , Sogaro Lorenzo , Soligo Marco
Published: November 2022

Relapsing ovarian granulosa-cell tumor (GCT) is a challenge for physicians due to the lack of effective therapy. Current strategies did not improve the 80% death rate of recurrent disease. GCTs synthesize estrogens and express follicle-stimulating hormone, gonadotropin-releasing hormone, and estrogen and progesterone receptors. The FOXL2-C134W mutation is shared in all GCTs, and its downregulation of hormone-related apoptosis appears causal in induction of tumor phenotype. On these assumptions, hormone anti-estrogenic therapies have been proposed for recurrent GCTs. A 32-year-old woman suffering from GCT was first treated by surgery in 2004 and staged as IA disease. Two subsequent pelvic relapses were diagnosed in 2006 and 2007, and the patient underwent surgery and chemotherapy to treat both recurrences. Overall, she underwent five subsequent surgical interventions and two chemotherapy instances. A third single pelvic relapse above the vaginal cuff was diagnosed in 2013. Based on the patient’s refusal to undergo further surgery we proposed an anti-estrogen therapy consisting of combined GnRH analogue leuprolide and the aromatase inhibitor letrozole. Complete remission was obtained after 3 months from the start of therapy. Subsequently, we found that disease-free survival was maintained over 9 years of treatment. Although recent reports indicate poor effectiveness of hormone therapy to treat recurrent GCTs, the success of this case indicates that a subset of patients with recurrent GCT maintain a tumor phenotype highly responsive to anti-estrogen drugs.
How to Improve the Reproducibility, Replicability, and Extensibility of Remote Sensing Research
Authors: Kedron Peter , Frazier Amy E.
Published: November 2022

The field of remote sensing has undergone a remarkable shift where vast amounts of imagery are now readily available to researchers. New technologies, such as uncrewed aircraft systems, make it possible for anyone with a moderate budget to gather their own remotely sensed data, and methodological innovations have added flexibility for processing and analyzing data. These changes create both the opportunity and need to reproduce, replicate, and compare remote sensing methods and results across spatial contexts, measurement systems, and computational infrastructures. Reproducing and replicating research is key to understanding the credibility of studies and extending recent advances into new discoveries. However, reproducibility and replicability (R&R) remain issues in remote sensing because many studies cannot be independently recreated and validated. Enhancing the R&R of remote sensing research will require significant time and effort by the research community. However, making remote sensing research reproducible and replicable does not need to be a burden. In this paper, we discuss R&R in the context of remote sensing and link the recent changes in the field to key barriers hindering R&R while discussing how researchers can overcome those barriers. We argue for the development of two research streams in the field: (1) the coordinated execution of organized sequences of forward-looking replications, and (2) the introduction of benchmark datasets that can be used to test the replicability of results and methods.
Infrared Maritime Small Target Detection Based on Multidirectional Uniformity and Sparse-Weight Similarity
Authors: Zhao Enzhong , Dong Lili , Dai Hao
Published: November 2022

Infrared maritime target detection is a key technology in the field of maritime search and rescue, which usually requires high detection accuracy. Despite the promising progress of principal component analysis methods, it is still challenging to detect small targets of unknown polarity (bright or dark) with strong edge interference. Using the partial sum of tubal nuclear norm to estimate low-rank background components and weighted l1 norm to estimate sparse components is an effective method for target extraction. In order to suppress the strong edge interference, considering that the uniformity of the target scattering field is significantly higher than that of the background scattering field in the eigenvalue of the structure tensor, a prior weight based on the multidirectional uniformity of structure tensor eigenvalue was proposed and applied to the optimization model. In order to detect targets with unknown polarity, the images with opposite polarity were substituted into the optimization model, respectively, and the sparse-weight similarity is used to judge the polarity of the target. In order to make the method more efficient, the polarity judgment is made in the second iteration, and then, the false iteration will stop. The proposed method is compared with nine advanced baseline methods on 14 datasets and shows significant strong robustness, which is beneficial to engineering applications.
Urban Flood-Related Remote Sensing: Research Trends, Gaps and Opportunities
Authors: Zhu Wei , Cao Zhe , Luo Pingping , Tang Zeming , Zhang Yuzhu , Hu Maochuan , He Bin
Published: November 2022

As a result of urbanization and climate change, urban areas are increasingly vulnerable to flooding, which can have devastating effects on the loss of life and property. Remote sensing technology can provide practical help for urban flood disaster management. This research presents a review of urban flood-related remote sensing to identify research trends and gaps, and reveal new research opportunities. Based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), the systematic literature search resulted in 347 documents classified as geography, disaster management application, and remote sensing data utilization. The main results include 1. most of the studies are located in high-income countries and territories and inland areas; 2. remote sensing for observing the environment was more popular than observing the building; 3. the most often applied disaster management activities were vulnerability assessment and risk modeling (mitigation) and rapid damage assessment (response); 4. DEM is often applied to simulate urban floods as software inputs. We suggest that future research directions include 1. coastal urban study areas in non-high-income countries/territories to help vulnerable populations; 2. understudied disaster management activities, which often need to observe the buildings in more urban areas; 3. data standardization will facilitate integration with international standard methods for assessing urban floods.
Extracting High-Precision Vehicle Motion Data from Unmanned Aerial Vehicle Video Captured under Various Weather Conditions
Authors: Li Xiaohe , Wu Jianping
Published: November 2022

At present, there are many aerial-view datasets that contain motion data from vehicles in a variety of traffic scenarios. However, there are few datasets that have been collected under different weather conditions in an urban mixed-traffic scenario. In this study, we propose a framework for extracting vehicle motion data from UAV videos captured under various weather conditions. With this framework, we improve YOLOv5 (you only look once) with image-adaptive enhancement for detecting vehicles in different environments. In addition, a new vehicle-tracking algorithm called SORT++ is proposed to extract high-precision vehicle motion data from the detection results. Moreover, we present a new dataset that includes 7133 traffic images (1311 under sunny conditions, 961 under night, 3366 under rainy, and 1495 under snowy) of 106,995 vehicles. The images were captured by a UAV to evaluate the proposed method for vehicle orientation detection. In order to evaluate the accuracy of the extracted traffic data, we also present a new dataset of four UAV videos, each having 30,000+ frames, of approximately 3K vehicle trajectories collected under sunny, night, rainy, and snowy conditions, respectively. The experimental results show the high accuracy and stability of the proposed methods.
Assessing the Reliability of Optimized Residual Feed Intake Measurements in Beef Cattle
Authors: Mononen Jaakko , Kostensalo Joel , Pesonen Maiju , Huuskonen Arto , Manni Katariina
Published: November 2022

Residual feed intake (RFI) is the preferred measurement for feed efficiency in beef cattle, but it is laborious to determine. Data from two experiments of growing bulls (test period durations of 56 and 63 days) were used to examine how a reduction in the number of times the animals were weighed and the shortening of the length of the observation period affect the reliability of the RFI determination. We introduce two easily understandable probability measures for assessing reliability. ‘The consistency of the pair-wise ranks’ gives the probability that the rank of any two animals compared remains the same when the amount of data is reduced. ‘The consistency of the thirds’ gives the probabilities that an individual animal will remain in the same, i.e., the lowest, middle, or highest, third of animals. The reliability of the results was not greatly affected when the weighing interval was reduced from one week to four weeks. However, shortening the test period resulted in a marked reduction in the reliability of RFI. If individual feed intake is automatically measured, the workload required for RFI measurements can most effectively be reduced by reducing the number of weighing times but keeping the duration of the test period long enough.
Bus Violence: An Open Benchmark for Video Violence Detection on Public Transport
Authors: Ciampi Luca , Foszner Paweł , Messina Nicola , Staniszewski Michał , Gennaro Claudio , Falchi Fabrizio , Serao Gianluca , Cogiel Michał , Golba Dominik , Szczęsna Agnieszka , Amato Giuseppe
Published: November 2022

The automatic detection of violent actions in public places through video analysis is difficult because the employed Artificial Intelligence-based techniques often suffer from generalization problems. Indeed, these algorithms hinge on large quantities of annotated data and usually experience a drastic drop in performance when used in scenarios never seen during the supervised learning phase. In this paper, we introduce and publicly release the Bus Violence benchmark, the first large-scale collection of video clips for violence detection on public transport, where some actors simulated violent actions inside a moving bus in changing conditions, such as the background or light. Moreover, we conduct a performance analysis of several state-of-the-art video violence detectors pre-trained with general violence detection databases on this newly established use case. The achieved moderate performances reveal the difficulties in generalizing from these popular methods, indicating the need to have this new collection of labeled data, beneficial for specializing them in this new scenario.
Application of Optical and Rheological Techniques in Quality and Storage Assessment of the Newly Developed Colloidal-Suspension Products: Yogurt-Type Bean-Based Beverages
Authors: Cichońska Patrycja , Domian Ewa , Ziarno Małgorzata
Published: November 2022

The objectives of this study were to compare the properties of the yogurt-type bean-based beverages B and BG produced from the nongerminated and germinated beans, respectively, by high-pressure homogenization (HPH) and fermentation with three starter cultures. Optical techniques were used to evaluate the particle size distribution (PSD), color parameters, and instability during storage, while rheological tests were used to evaluate the shear viscosity, flow behavior, and viscoelastic properties. The BG compared to B, irrespective of the starter culture used, showed a higher mean diameter and Span of PSD (d4,3 ≈ 76.8–84.2, Span ≈ 2.24–2.35 for BG vs. d4,3 ≈ 38.2–47.0, Span ≈ 1.90–2.00 for B). The BG vs. B showed lower viscosity (0.47 Pa·s for BG vs. 0.81 Pa·s for B at shear rate 75 s−1) and slightly lower but satisfactory stability (after 21 days at 6 °C, the Turbiscan Stability Index TSI ≈ 1.3–2.0 for BG vs. TSI ≈ 0.6–0.9 for B). Both B and BG were characterized by light-yellow color and showed the characteristics of a viscoelastic fluid. The HPH and germination mainly affected the properties of the tested plant tissue, which has a direct impact on the properties of the final products.
Compression for Bayer CFA Images: Review and Performance Comparison
Authors: Chung Kuo-Liang , Chen Hsuan-Ying , Hsieh Tsung-Lun , Chen Yen-Bo
Published: November 2022

Bayer color filter array (CFA) images are captured by a single-chip image sensor covered with a Bayer CFA pattern which has been widely used in modern digital cameras. In the past two decades, many compression methods have been proposed to compress Bayer CFA images. These compression methods can be roughly divided into the compression-first-based (CF-based) scheme and the demosaicing-first-based (DF-based) scheme. However, in the literature, no review article for the two compression schemes and their compression performance is reported. In this article, the related CF-based and DF-based compression works are reviewed first. Then, the testing Bayer CFA images created from the Kodak, IMAX, screen content images, videos, and classical image datasets are compressed on the Joint Photographic Experts Group-2000 (JPEG-2000) and the newly released Versatile Video Coding (VVC) platform VTM-16.2. In terms of the commonly used objective quality, perceptual quality metrics, the perceptual effect, and the quality–bitrate tradeoff metric, the compression performance comparison of the CF-based compression methods, in particular the reversible color transform-based compression methods and the DF-based compression methods, is reported and discussed.
Tissue Characterization Using Synchrotron Radiation at 0.7 THz to 10.0 THz with Extended ATR Apparatus Techniques
Authors: Vilagosh Zoltan , Appadoo Dominique , Foroughimehr Negin , Shams Reza , Sly David , Juodkazis Saulius , Ivanova Elena , Wood Andrew W.
Published: November 2022

The attenuated total reflection (ATR) apparatus, with an added partial reflection/partial transmission mode, was used to demonstrate a novel way of characterizing water-based substances at 0.7 to 10.0 THz at the Australian Synchrotron THz-far infrared beamline. The technique utilized a diamond-crystal-equipped ATR to track temperature-dependent changes in reflectance. A “crossover flare” feature in the spectral scan was noted, which appeared to be a characteristic of water and water-dominated compounds. A “quiet zone” feature was also seen, where no temperature-dependent variation in reflectance exists. The variation in these spectral features can be used as a signature for the presence of bound and bulk water. The method can also potentially identify the presence of fats and oils in a biological specimen. The technique requires minimal sample preparation and is non-destructive. The presented method has the promise to provide a novel, real-time, low-preparation, analytical method for investigating biological material, which offers avenues for rapid medical diagnosis and industrial analysis.
Fleet’s Geode: A Breakthrough Sensor for Real-Time Ambient Seismic Noise Tomography over DtS-IoT
Authors: Olivier Gerrit , Borg Braeden , Trevor Lawrence , Combeau Boris , Dales Philippe , Gordon Jonathan , Chaurasia Hemant , Pearson Matthew
Published: November 2022

As most of the outcropping and shallow mineral deposits have been found, new technology is imperative to finding the hidden critical mineral deposits required to transition to renewable energy. One such new technique, called ambient seismic noise tomography, has shown promise in recent years as a low-cost, low environmental impact method that can image under cover and at depth. Wireless and compact nodal seismic technology has been instrumental to enable industry applications of ambient noise tomography, but these devices are designed for the active seismic reflection method and do not have the required sensitivity at low frequencies for ambient noise tomography, and real-time data transmission in remote locations requires significant infrastructure to be installed. In this paper, we show the development and testing of the Geode—a real-time seismic node purpose-built by Fleet Space Technologies for ambient seismic noise tomography on exploration scales. We discuss the key differences between current nodal technology and the Geode and show results of a field trial where the performance of the Geode is compared with a commercially popular nodal geophone. The use of a 2 Hz high sensitivity geophone and low noise digitiser results in an instrument noise floor that is more than 30 dB lower below 5 Hz than nodes that are commonly used in the industry. The increased sensitivity results in signal-to-noise ratios in the cross-correlation functions in the field trial that are more than double that of commercially available nodal geophone at low frequencies. When considering the full bandwidth of retrievable correlations in our study, using the Geode would reduce the required recording time from 75 h to 32 h to achieve an average signal-to-noise ratio in the cross-correlation functions of 10. We also discuss the integration of a real-time direct-to-satellite Internet of Things (DtS-IoT) modem in the Geode, which, together with edge processing of seismic data directly on the Geode, enables us to image the subsurface in real-time. During the field trial, the Geodes successfully transmitted more than 90% of the available preprocessed data packets. The Geode is compact enough so that several devices can be carried and installed by one field technician, whilst the array of stations do not require a base station to transmit data to the cloud for further processing. We believe this is the future of passive seismic surveys and will result in faster and more dynamic seismic imaging capabilities analogous to the medical imaging community, increasing the pace at which new mineral deposits are discovered.
A Non-Convex Compressed Sensing Model Improving the Energy Efficiency of WSNs for Abnormal Events’ Monitoring
Authors: Huang Yilin , Li Haiyang , Peng Jigen
Published: November 2022

The wireless sensor network (WSN), a communication system widely used in the Internet of Things, usually collects physical data in a natural environment and monitors abnormal events. Because of the redundancy of natural data, a compressed-sensing-based model offers energy-efficient data processing to overcome the energy shortages and uneven consumption problems of a WSN. However, the convex relaxation method, which is widely used for a compressed-sensing-based WSN, is not sufficient for reducing data processing energy consumption. In addition, when abnormal events occur, the redundancy of the original data is destroyed, which makes the traditional compressed sensing methods ineffective. In this paper, we use a non-convex fraction function as the surrogate function of the ℓ0-norm, which achieves lower energy consumption of the sensor nodes. Moreover, considering abnormal event monitoring in a WSN, we propose a new data construction model and apply an alternate direction iterative thresholding algorithm, which avoids extra measurements, unlike previous algorithms. The results showed that our models and algorithms reduced the WSN’s energy consumption during abnormal events.
Effect of Linewidth on the Relative Intensity Noise in Random Distributed Feedback Raman Fiber Lasers
Authors: Rota-Rodrigo Sergio , Leandro Daniel , Santarelli Giorgio , Lopez-Amo Manuel , Ania-Castañón Juan Diego
Published: November 2022

We experimentally explore the relation between spectral linewidth and RIN transfer in half-open cavity random distributed feedback Raman lasers, demonstrating for the first time the possibility of adjusting the pump-to-signal RIN transfer intensity and cut-off frequency by using spectral filtering in the reflector section. We apply this approach to a 50-km laser system, operating in the C-Band, reliant on a standard single-mode fiber. We obtained a minimum bandwidth of 13 pm, which translates into a visible RIN cut-off at 800 MHz.
Research on the Physics–Intelligence Hybrid Theory Based Dynamic Scenario Library Generation for Automated Vehicles
Authors: Zhang Yufei , Sun Bohua , Li Yaxin , Zhao Shuai , Zhu Xianglei , Ma Wenxiao , Ma Fangwu , Wu Liang
Published: November 2022

The testing and evaluation system has been the key technology and security with its necessity in the development and deployment of maturing automated vehicles. In this research, the physics–intelligence hybrid theory-based dynamic scenario library generation method is proposed to improve system performance, in particular, the testing efficiency and accuracy for automated vehicles. A general framework of the dynamic scenario library generation is established. Then, the parameterized scenario based on the dimension optimization method is specified to obtain the effective scenario element set. Long-tail functions for performance testing of specific ODD are constructed as optimization boundaries and critical scenario searching methods are proposed based on the node optimization and sample expansion methods for the low-dimensional scenario library generation and the reinforcement learning for the high-dimensional one, respectively. The scenario library generation method is evaluated with the naturalistic driving data (NDD) of the intelligent electric vehicle in the field test. Results show better efficient and accuracy performances compared with the ideal testing library and the NDD, respectively, in both low- and high-dimensional scenarios.
Evaluation of Error-State Kalman Filter Method for Estimating Human Lower-Limb Kinematics during Various Walking Gaits
Authors: Potter Michael V. , Cain Stephen M. , Ojeda Lauro V. , Gurchiek Reed D. , McGinnis Ryan S. , Perkins Noel C.
Published: November 2022

Inertial measurement units (IMUs) offer an attractive way to study human lower-limb kinematics without traditional laboratory constraints. We present an error-state Kalman filter method to estimate 3D joint angles, joint angle ranges of motion, stride length, and step width using data from an array of seven body-worn IMUs. Importantly, this paper contributes a novel joint axis measurement correction that reduces joint angle drift errors without assumptions of strict hinge-like joint behaviors of the hip and knee. We evaluate the method compared to two optical motion capture methods on twenty human subjects performing six different types of walking gait consisting of forward walking (at three speeds), backward walking, and lateral walking (left and right). For all gaits, RMS differences in joint angle estimates generally remain below 5 degrees for all three ankle joint angles and for flexion/extension and abduction/adduction of the hips and knees when compared to estimates from reflective markers on the IMUs. Additionally, mean RMS differences in estimated stride length and step width remain below 0.13 m for all gait types, except stride length during slow walking. This study confirms the method’s potential for non-laboratory based gait analysis, motivating further evaluation with IMU-only measurements and pathological gaits.
Tool Wear Monitoring in Milling Based on Fine-Grained Image Classification of Machined Surface Images
Authors: Yang Jing , Duan Jian , Li Tianxiang , Hu Cheng , Liang Jianqiang , Shi Tielin
Published: November 2022

Cutting tool wear state assessment during the manufacturing process is extremely significant. The primary purpose of this study is to monitor tool wear to ensure timely tool change and avoid excessive tool wear or sudden tool breakage, which causes workpiece waste and could even damage the machine. Therefore, an intelligent system, that is efficient and precise, needs to be designed for addressing these problems. In our study, an end-to-end improved fine-grained image classification method is employed for workpiece surface-based tool wear monitoring, which is named efficient channel attention destruction and construction learning (ECADCL). The proposed method uses a feature extraction module to extract features from the input image and its corrupted images, and adversarial learning is used to avoid learning noise from corrupted images while extracting semantic features by reconstructing the corrupted images. Finally, a decision module predicts the label based on the learned features. Moreover, the feature extraction module combines a local cross-channel interaction attention mechanism without dimensionality reduction to characterize representative information. A milling dataset is conducted based on the machined surface images for monitoring tool wear conditions. The experimental results indicated that the proposed system can effectively assess the wear state of the tool.
On the Stationarity Time of a Vehicle-to-Infrastructure Massive Radio Channel in a Line-of-Sight Suburban Environment
Authors: Dahmouni Nor El Islam , Laly Pierre , Yusuf Marwan , Delbarre Gauthier , Liénard Martine , Simon Eric P. , Gaillot Davy P.
Published: November 2022

Massive multiple-input multiple-output (mMIMO) communication systems are a pillar technology for 5G. However, the wireless radio channel models relying on the assumption of wide-sense stationary uncorrelated scattering (WSSUS) may not always be valid for dynamic scenarios. Nonetheless, an analysis of the stationarity time that validates this hypothesis for mMIMO vehicular channels as well as a clear relationship with the scattering properties is missing in the literature. Here, time-varying single-user mMIMO radio channels were measured in a suburban environment at the 5.89 GHz vehicular band with a strong Line-of-Sight (LOS) to study the non-WSSUS and large scale characteristics of the vehicle-to-infrastructure (V2I) link. The generalized local scattering function (GLSF), computed from the sampled channels, was used to derive (1) the spatial distribution of the stationarity time using the channel correlation function (CCF) and empirical collinearity methods and (2) the root mean square delay/angular spread and coherence time/bandwidth values from the projected power delay profile (PDP) and Doppler power spectra (DPS). The results highlight the high degree of correlation between the spatial distribution of the stationarity time and the scattering properties along the measurement route.
Seed Germination Trials and Ex Situ Conservation of Local Prioritized Endemic Plants of Crete (Greece) with Commercial Interest
Authors: Sarropoulou Virginia , Krigas Nikos , Tsoktouridis Georgios , Maloupa Eleni , Grigoriadou Katerina
Published: November 2022

The in vivo germination course (15, 30, 45, and 60 days) of nine threatened local endemic plants of Crete (Greece) was studied due to conservation concerns and commercial interest in economic sectors. We used seeds directly collected from the wild sown in peat (Terrahum):perlite (1:1 v/v ratio)covered with coarse-grained vermiculite in a greenhouse mist bench with a substrate temperature of 19 ± 2 °C. The onset of in vivo germination was defined by the visible radicle protrusion (6th–9th day from sowing). After 60 days, 100% germination was observed for seeds of Campanula cretica, Dianthus fruticosus subsp. creticus, and Petromarula pinnata, followed by Draba cretica (91%) and Sanguisorba cretica (86%). Average–low germination capacity was observed for seeds of Calamintha cretica (26%), Lomelosia minoana subsp. minoana (38%), and Origanum microphyllum (23%), and very low capacity was observed for Onopordum bracteatum subsp. creticum (1.5%). After keeping seeds at 4–5 °C for three months, pre-treatments were performed (immersion in 50 or 250 ppm of gibberellic acid solution for 24 h) on three taxa with low germination capacity, thus resulting to the germination acceleration of Calamintha cretica seeds and increased germination capacity of Onopordum bracteatum subsp. creticum seeds. Apart from the facilitation of future species-specific conservation actions, the study showcases that the obtained results herein may permit an upgrade in the feasibility and readiness timescale assessments for the sustainable exploitation of studied taxa in different economic sectors.
Test–Retest Reliability and Sensitivity of Common Strength and Power Tests over a Period of 9 Weeks
Authors: Venegas-Carro Maria , Kramer Andreas , Moreno-Villanueva Maria , Gruber Markus
Published: November 2022

This study evaluated the reliability and sensitivity of a set of different common strength and power tests in a healthy adult population in a span of 9 weeks. Seventeen subjects (24.2 ± 2.2 years, 1.75 ± 0.10 m, 68.6 ± 14.2 kg, seven women) participated in the study. We tested countermovement jumps, reactive hops, and the maximal voluntary contraction (MVC) of handgrip and isometric knee extension. The tests were conducted in three separate sessions across a nine-week period, with one week between the first two sessions and eight weeks between the second and the third. Reliability and sensitivity statistics for each test were calculated for both the average of three trials and the best result during each session. The MVC of isometric knee extension and handgrip, as well as the countermovement jump test, demonstrated very high reliability and sensitivity over the nine-week period. The peak force of the reactive hops demonstrated high reliability but high sensitivity only for the average but not for the best result. The average contact time of reactive hops was neither a sensitive nor reliable measurement. In conclusion, isometric maximal knee extension and handgrip tests, as well as countermovement jumps and peak force of reactive hops, can be used as reliable and sensitive measurements of isometric and reactive strength and power over time periods of up to eight weeks. We recommend the use of the average results of three trials instead of the best performance value for longitudinal studies, as this procedure produces more consistent results and a lower measurement error.
Product Recalls in European Textile and Clothing Sector—A Macro Analysis of Risks and Geographical Patterns
Authors: Kumar Vijay
Published: November 2022

Textile and clothing (T&C) products contribute to a substantial proportion of the non-food product recalls in the European Union (EU) due to various levels of associated risks. Out of the listed 34 categories for product recalls in the EU’s Rapid Exchange of Information System (RAPEX), the category ’clothing, textiles, and fashion items’ was among the top 3 categories with the most recall cases during 2013–2019. Previous studies have attempted to highlight the issue of product recalls and their impacts from the perspective of a single company or selected companies, whereas limited attention is paid to understand the problem from a sector-specific perspective. However, considering the nature of product risks and the consistency in a higher number of recall cases, it is important to analyze the issue of product recalls in the T&C sector from a sector-specific perspective. In this context, the paper focuses on investigating the past recalls in the T&C sector reported RAPEX during 2005–2021 to understand the major trends in recall occurrence and associated hazards. Correspondence Analysis (CA) and Latent Dirichlet Allocation (LDA) were applied to analyze the qualitative and quantitative recall data. The results reveal that there is a geographical pattern for the product risk that leads to the recalls. The countries in eastern part of Europe tend to have proportionately high recalls in strangulation and choking-related issues, whereas chemical-related recalls are proportionately high in countries located in western part of Europe. Further, text-mining results indicate that design-related recall issues are more prevalent in children’s clothing.
Novel Biosynthesis of Graphene-Supported Zero-Valent Iron Nanohybrid for Efficient Decolorization of Acid and Basic Dyes
Authors: Samy Mahmoud , Elkady Marwa , Kamal Ayman , Elessawy Noha , Zaki Sahar , Eltarahony Marwa
Published: November 2022

Herein, respiratory nitrate reductases (NAR) were utilized in the biosynthesis of zero-valent iron (ZVI) graphene nanocomposite as a simultaneous reducing and capping agent, for the first time, to efficiently adsorb methylene blue (MB) and direct red-81 (DR-81). Under anaerobic conditions, the greenly synthesized graphene was incubated with iron precursor in the presence of crude-NAR enzyme for 48 h to obtain the ZVI graphene composite followed by characterizing this composite using physiochemical analyses. Scanning and transmission electron microscopy, energy dispersive X-ray spectroscopy and X-ray diffraction techniques assured the chemical composition and the interaction between ZVI and graphene. The influences of operating conditions such as contact time, pH and adsorbent dose on the adsorption efficacy were explored in the case of ZVI graphene, graphene and ZVI. ZVI graphene nanocomposite displayed the highest removal efficiency of MB and DR-81 compared to graphene and ZVI-NPs. The removal percentages of DR-81 and MB by ZVI graphene nanocomposites were 88.3 ± 2.66% and 87.6 ± 2.1%, respectively, at pH 7, adsorbent dose 20 mg/50 mL, initial MB or DR-81 concentration of 10 mg/L and shaking speed of 150 rpm. A pseudo first-order model could describe the adsorption kinetics, and the adsorption mechanism was discussed. The promising results of the current study support the potential of the recruitment of ZVI graphene nanocomposites in eliminating various pollutants from industrial effluents on a larger scale. Further, the prepared nanohybrid can be used in other applications such as photocatalysis, Fenton and persulfate activation processes.
Robust Optimization-Based Optimal Operation of Islanded Microgrid Considering Demand Response
Authors: AlDavood Monir Sadat , Mehbodniya Abolfazl , Webber Julian L. , Ensaf Mohammad , Azimian Mahdi
Published: November 2022

This paper presents a new robust scheduling model for an islanded microgrid (MG) considering demand response. The model is expressed as a min–max bilevel optimization problem that tries to minimize the total costs of MG including operation cost of conventional distributed generators, energy storages, renewable energy sources (RES), cost of load shifting, and interruptible/non-interruptible load shedding in the worst situation of uncertainties. The uncertainties associated with renewable power generations and MG demand are modeled via robust optimization method. A hybrid method based on the genetic algorithm (GA) and mixed-integer programming technique is utilized to solve the bilevel optimization problem. The proposed model is utilized on a typical MG, and the outcomes are analyzed to show the effectiveness of the proposed method.
Blockchain-Based Formal Model for Food Supply Chain Management System Using VDM-SL
Authors: Hameed Hira , Zafar Nazir Ahmad , Alkhammash Eman H. , Hadjouni Myriam
Published: November 2022

In modern society, the food supply chain management system has become an important research area realized nationally and internationally, which has established a collaborative relationship between producers, manufacturers, processors and retailers. Now, consumers are more interested in food quality, safety and the authentication of the products. Food safety has become an important issue in public health in the food market because people of all types and races around the world are affected due its poor quality. The traditional supply chains are centralized and face different issues such as lack of transparency, accountability and audit ability. The general issues in supply chain management include lack of communication, trust among the stakeholders, and interference of entities and wastage of food. A lot of work has been completed by researchers to address the above issues, but still, there is a need for effective mechanisms for the modeling of supply chain management systems. In this paper, a trusted, self-organized, traceable formal system based on blockchain and Internet of Things (IoT) is developed by using wireless sensors networks and finite automata. In the proposed model, smart contracts are designed to assure the automated payment procedures. The proposed model reduced the need for centralized authority. Unified Modeling Language (UML) is used to realize the requirements, and automata is used to capture behavior of the system. A blockchain-based model is used to provides the privacy and security mechanism for the transitions record. Wireless sensors are used to sense the information, and actors are used for decision making in case of any violation in the contact. A lot of work has been completed by researchers on smart contracts. Different smart contracts are designed to achieve the better traceability among producers, transporter/logistics and consumers. Our system provides the smart contract algorithm to show the interaction of entities in the food supply chain management system. Vienna Development Method-Specification Language (VDM-SL) is used to describe the formal system and the VDM-SL toolbox is used for the validation and analysis of the system.