bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification of Oxindoleacetic Acid Conjugates in Quinoa (Chenopodium quinoa Willd.) Seeds by High-Resolution UHPLC-MS/MS
Authors: Karonen Maarit , Pihlava Juha-Matti
Published: September 2022

Quinoa (Chenopodium quinoa Willd.) has a high nutritional value and it contains a high number and high amounts of specialized metabolites. These metabolites include, for example, phenolic acids, flavonoids, terpenoids and steroids. In addition, it is known to contain N-containing metabolites, such as betalains. Here, we report the presence and identification of 14 new oxindoleacetate conjugates in quinoa by high-resolution ultrahigh-performance liquid chromatography quadrupole-time-of-flight tandem mass spectrometry (UHPLC-QTOF-MS/MS) and ultrahigh-resolution UHPLC-QOrbitrap-MS/MS. The oxindoleacetate conjugates were extracted from dried and ground quinoa seeds using either methanol/water or acetone/water (4:1, v/v) and were further concentrated into aqueous phase and analyzed by UHPLC with reverse-phase chromatography using acetonitrile and 0.1% aqueous formic acid as eluents. High-resolution hybrid LC-MS/MS techniques, including full scan MS with in-source collision, induced dissociation, and data dependent-MS2(TopN) with stepped normalized collision energies using N2 as collision gas and data-independent acquisition (MSE) using ramped collision energies and argon as collision gas enabled their analysis directly from the crude quinoa seed extract. The oxindoleacetate conjugates were found to be present in both conventional and organic farmed seeds. According to our best knowledge, this is the first time hydroxy-oxindoles have been reported in quinoa.
Biopreservation of Chocolate Mousse with Lactobacillus helveticus 2/20: Microbial Challenge Test
Authors: Goranov Bogdan , Teneva Desislava , Denkova-Kostova Rositsa , Shopska Vesela , Oulahal Nadia , Denkova Zapryana , Kostov Georgi , Degraeve Pascal , Pagan Rafael
Published: September 2022

Probiotic bacteria are used for food biopreservation because their metabolic products might contribute to ensuring food microbiological safety and/or increase its shelf life without the addition of chemical preservatives. Moreover, biopreserved foods are excellent vehicles for the delivery of probiotic bacteria. The aim of the study was to investigate the potential of chocolate mousse food matrix for the delivery of the probiotic strain Lactobacillus helveticus 2/20 (Lb. helveticus 2/20) and to investigate its capacity to inhibit the growth of two foodborne pathogenic bacteria (Staphylococcus aureus and Escherichia coli). Therefore, the populations of free or encapsulated in calcium alginate Lb. helveticus 2/20 cells and/or of each pathogen (used to voluntarily contaminate each sample) were monitored both in complex nutrient medium (MRS broth) and in chocolate mousse under refrigeration conditions and at room temperature. Lb. helveticus 2/20 alone in free or encapsulated state effectively inhibited the growth of Escherichia coli ATCC 25922 and Staphylococcus aureus ATCC 25923 in chocolate mousse when stored at 20 ± 2 °C. Practically no viable unwanted bacteria were identified on the 7th day from the beginning of the process. High viable Lb. helveticus 2/20 cell populations were maintained during storage under refrigerated conditions (4 ± 2 °C) and at room temperature. Chocolate mousse is thus a promising food matrix to deliver probiotic Lb. helveticus 2/20 cells, which could also protect it from contamination by unwanted bacteria.
Supramolecular Binding with Lectins: A New Route for Non-Covalent Functionalization of Polysaccharide Matrices
Authors: Montroni Devis , Di Giosia Matteo , Calvaresi Matteo , Falini Giuseppe
Published: September 2022

The chemical functionalization of polysaccharides to obtain functional materials has been of great interest in the last decades. This traditional synthetic approach has drawbacks, such as changing the crystallinity of the material or altering its morphology or texture. These modifications are crucial when a biogenic matrix is exploited for its hierarchical structure. In this work, the use of lectins and carbohydrate-binding proteins as supramolecular linkers for polysaccharide functionalization is proposed. As proof of concept, a deproteinized squid pen, a hierarchically-organized β-chitin matrix, was functionalized using a dye (FITC) labeled lectin; the lectin used was the wheat germ agglutinin (WGA). It has been observed that the binding of this functionalized protein homogenously introduces a new property (fluorescence) into the β-chitin matrix without altering its crystallographic and hierarchical structure. The supramolecular functionalization of polysaccharides with protein/lectin molecules opens up new routes for the chemical modification of polysaccharides. This novel approach can be of interest in various scientific fields, overcoming the synthetic limits that have hitherto hindered the technological exploitation of polysaccharides-based materials.
Ultra-Low Power All-Optically Tuned Hybrid Graphene Ultra Silicon-Rich Nitride Ring Resonator-Based Add-Drop Filter for DWDM Systems
Authors: Rukerandanga Filston , Musyoki Stephen , Ataro Edwin
Published: September 2022

This research work conducted a design and simulation of an ultra-low power all-optically tuned nonlinear ring resonator-based add-drop filter. The purpose of this study is to investigate a CMOS-compatible nonlinear material system for an optical filter with temperature resilience, polarization insensitivity, and fast and energy-efficient tunability. The all-optical tunability was achieved using an optical pump that photo-excites the high nonlinear Kerr effect in the device material system. A three-dimensional multiphysics approach was used, combining the electromagnetics and thermo-structural effects in the filter. Hybrid graphene on an ultra-rich silicon nitride ring resonator-based filter enabled the realization of an ultra-high tuning efficiency (0.275 nm/mW for TE mode and 0.253 nm/mW for TM mode) on a range of 1.55 nm and thermal stability of 0.11 pm/K. This work contributed to the existing literature by proposing (1) the integration of a high Kerr effect layer on a low loss, high index contrast, and two-photon absorption-free core material with an athermal cladding material system and (2) the use of a cross-section shape insensitive to polarization. Moreover, the tuning mechanism contributed to the realization of an all-optical on-chip integrable filter for Dense Wavelength Division Multiplexing systems in the less occupied L band.
Theoretical Search for Gravitational Bound States of Tachyons
Authors: Schwartz Charles
Published: September 2022

The mission here is to see if we can find bound states for tachyons in some gravitational environment. That could provide an explanation for the phenomena called Dark Matter. Starting with the standard Schwarzschild metric in General Relativity, which is for a static and spherically symmetric source, it appears unlikely that such localized orbits exist. In this work, the usual assumption of isotropic pressure is replaced by a model that has different pressures in the radial and angular directions. This should be relevant to the study of neutrinos, especially if they are tachyons, in cosmological models. We do find an arrangement that allows bound orbits for tachyons in a galaxy. This is a qualitative breakthrough. Then we go on to estimate the numbers involved and find that we do have a fair quantitative fit to the experimental data on the Galaxy Rotation Curve. Additionally we are led to look in the neighborhood of a Black Hole and there we find novel orbits for tachyons.
Binding of Natural Inhibitors to Respiratory Complex I
Authors: Schiller Jonathan , Zickermann Volker
Published: September 2022

NADH:ubiquinone oxidoreductase (respiratory complex I) is a redox-driven proton pump with a central role in mitochondrial oxidative phosphorylation. The ubiquinone reduction site of complex I is located in the matrix arm of this large protein complex and connected to the membrane via a tunnel. A variety of chemically diverse compounds are known to inhibit ubiquinone reduction by complex I. Rotenone, piericidin A, and annonaceous acetogenins are representatives of complex I inhibitors from biological sources. The structure of complex I is determined at high resolution, and inhibitor binding sites are described in detail. In this review, we summarize the state of knowledge of how natural inhibitors bind in the Q reduction site and the Q access pathway and how their inhibitory mechanisms compare with that of a synthetic anti-cancer agent.
Impact of Clinical Pharmacist Intervention on Clinical Outcomes in the Critical Care Unit, Taif City, Saudi Arabia: A Retrospective Study
Authors: Althomali Abdullah , Altowairqi Ahmed , Alghamdi Afnan , Alotaibi Musim , Althubaiti Abdulrahman , Alqurashi Abdulaziz , Harbi Adnan Al , Algarni Majed Ahmed , Haseeb Abdul , Elnaem Mohamed Hassan , Alsenani Faisal , Elrggal Mahmoud E.
Published: September 2022

(1) Objectives: Clinical pharmacists are now playing a significant role in hospitals aiming to reduce medication errors, adverse drug reactions, and healthcare costs. Therefore, the main objective of this study was to assess the interventions provided by a clinical pharmacist in the intensive care unit at the King Faisal Hospital in Taif city. (2) Methods: For this single-center retrospective study, patients were included from December 2021 to May 2022. In the present study, all the interventions of clinical pharmacists made over six months were included. The Intensive care unit (ICU) ward was covered by three clinical pharmacists, and the interventions made were categorized into four groups: (1) interventions related to indications; (2) interventions regarding safety; (3) interventions regarding dosing, and (4) miscellaneous. Descriptive statistics was applied to evaluate the results in the form of frequencies and percentages. Analysis was performed using the statistical package SPSS 20.0. (3) Results: Overall, a total of 404 interventions were recommended for 165 patients during the six- month period of study. Among them, 370 interventions (91.5%) were accepted by physicians. Among all the interventions, the majority were suggested regarding ‘indication’ (45.7%), including the addition of drugs, drugs with no indications, and duplication. The acceptance rate of clinical pharmacist intervention was 98.5%. (4) Conclusions: This retrospective study shows that clinical pharmacists played a critical role in optimizing drug therapy which could subsequently help to prevent drug-related issues and lower drug costs. More research is needed to do a thorough cost-benefit analysis.
Ballistic Imaging through Strongly Scattering Media by Using a Combination of Supercontinuum Illumination and Fourier Spatial Filtering
Authors: Tong Junyi , Zheng Yipeng , Tan Wenjiang , Li Cunxia , Si Jinhai
Published: September 2022

Imaging through turbid media is important but has created challenging issues for a long time. Previous research studies have shown that the object hidden in a turbid medium might be seen just by effectively suppressing the speckles by using low-coherent light sources, such as random laser and supercontinuum. However, the image contrast was seriously degraded due to the background noise of scattered photons. In this work, we demonstrate ballistic imaging for an object hidden behind strongly scattering media, in which the speckles are suppressed by the supercontinuum (SC) illumination and lots of scattered photons are simultaneously filtered by the Fourier spatial gate. Compared with speckle-free imaging from using SC illumination and ballistic imaging by Fourier spatial filtering, this method combines their advantages and shows a degree of synergism. When the optical depth of the scattering medium reaches 14, the image using this combined method is able to increase the image identifiability and the relative image contrast by about two times and four times compared to the method using only SC illumination, respectively. Our work offers a way for direct imaging through strongly turbid media without a complex image process.
Deep Deconvolution of Object Information Modulated by a Refractive Lens Using Lucy-Richardson-Rosen Algorithm
Authors: Praveen P. A. , Arockiaraj Francis Gracy , Gopinath Shivasubramanian , Smith Daniel , Kahro Tauno , Valdma Sandhra-Mirella , Bleahu Andrei , Ng Soon Hock , Reddy Andra Naresh Kumar , Katkus Tomas , Rajeswary Aravind Simon John Francis , Ganeev Rashid A. , Pikker Siim , Kukli Kaupo , Tamm Aile , Juodkazis Saulius , Anand Vijayakumar
Published: September 2022

A refractive lens is one of the simplest, most cost-effective and easily available imaging elements. Given a spatially incoherent illumination, a refractive lens can faithfully map every object point to an image point in the sensor plane, when the object and image distances satisfy the imaging conditions. However, static imaging is limited to the depth of focus, beyond which the point-to-point mapping can only be obtained by changing either the location of the lens, object or the imaging sensor. In this study, the depth of focus of a refractive lens in static mode has been expanded using a recently developed computational reconstruction method, Lucy-Richardson-Rosen algorithm (LRRA). The imaging process consists of three steps. In the first step, point spread functions (PSFs) were recorded along different depths and stored in the computer as PSF library. In the next step, the object intensity distribution was recorded. The LRRA was then applied to deconvolve the object information from the recorded intensity distributions during the final step. The results of LRRA were compared with two well-known reconstruction methods, namely the Lucy-Richardson algorithm and non-linear reconstruction.
Chasing QCD Signatures in Nuclei Using Color Coherence Phenomena
Authors: El Fassi Lamiaa
Published: September 2022

Over the last few decades, several experiments have used atomic nuclei as unique laboratories to probe the internal structure of the strongly interacting particles, namely hadrons. Indeed, the nucleus could be used as a revealing medium of the time evolution of elementary configurations of the hadron wave function. One of the ordinary approaches used to probe this picture involves searching for the onset of various phenomena which are naturally predicted by Quantum Chromo-Dynamics (QCD), the theory of strong interactions. One such phenomenon is the color transparency (CT), which refers to the production and propagation of a small size hadron-like configuration that, under specific conditions, stays intact in a transparent nuclear medium. In this paper, I will briefly review the status of the experimental search for CT effects and highlight the upcoming Jefferson Laboratory (JLab) 12 GeV experiment that will study CT at higher momentum transfer using the CLAS12 spectrometer.
Centenary of Alexander Friedmann’s Prediction of the Universe Expansion and the Quantum Vacuum
Authors: Klimchitskaya Galina L. , Mostepanenko Vladimir M.
Published: September 2022

We review the main scientific pictures of the universe developed from ancient times to Albert Einstein and underline that all of them treated the universe as a stationary system with unchanged physical properties. In contrast to this, 100 years ago Alexander Friedmann predicted that the universe expands starting from the point of infinitely large energy density. We briefly discuss the physical meaning of this prediction and its experimental confirmation consisting of the discovery of redshift in the spectra of remote galaxies and relic radiation. After mentioning the horizon problem in the theory of the hot universe, the inflationary model is considered in connection with the concept of quantum vacuum as an alternative to the inflaton field. The accelerated expansion of the universe is discussed as powered by the cosmological constant originating from the quantum vacuum. The conclusion is made that since Alexander Friedmann’s prediction of the universe expansion radically altered our picture of the world in comparison with the previous epochs, his name should be put on a par with the names of Ptolemy and Copernicus.
A Combined CFD-Response Surface Methodology Approach for Simulation and Optimization of Arsenic Removal in a Fixed Bed Adsorption Column
Authors: Solangi Zulfiqar Ali , Bhatti Inamullah , Qureshi Khadija
Published: September 2022

An experimentally validated CFD model was developed for lab-scale arsenic (As) fixed-bed columns using COMSOL Multiphysics. The effects of key factors such as the adsorbent bed depth, the feed flow rate, and the initial As concentration (conc.) on the overall As removal performance were investigated. Subsequently, the CFD was combined with response surface methodology (RSM) to optimize process conditions and examine main and interaction effects of these factors on model responses, i.e., the As removal efficiency and the bed saturation time. The ANOVA results suggested that quadratic regression models were highly significant for both responses. The established regression model equations predicted the response values closer to CFD measurements. It was found that, compared with the initial As conc. and the feed flow rate, the effect of the bed depth was more significant. Moreover, both the As removal efficiency and the bed saturation time were increased reasonably with the increasing bed depth and decreased with the increasing feed flow rate and initial As conc. The optimum conditions for the As removal process were obtained as the bed height of 80 cm, the initial As concentration of 2.7 mmol/m3, and the feed flow rate of 1 L/min. The present combined CFD−RSM approach is a useful guideline in overall design and optimization of various lab-scale and industrial applications for removal of As from wastewater.
Carbon Functionalized Material Derived from Byproduct of Plasma Tar-Cracking Unit on Biomass Gasifier Collected Using Standard Impinger Method
Authors: Soedarsono Harry Poetra , Faizal Ferry , Panatarani Camellia , Joni I Made
Published: September 2022

Reduction of tar concentration in biomass gasification with secondary plasma tar cracking unit remains a challenge to meet the requirement for clean syngas energy applications. Typically, the post-treatment of syngas to reduce the tar from an updraft fixed-bed reactor is using secondary plasma tar cracking unit. In this study, an additional trapping train was introduced as a mechanism to harvest byproducts of the tar decomposition process (byproduct carbon functionalized material or BCFM). The measurement in gravimetric and particle size distribution, supported by photoluminescent (PL) and Fourier transform infrared spectroscopy (FT–IR) of BCFM, were conducted to reveal the BCFM characteristic. The gravimetric analysis showed that the application of the secondary plasma tar cracking unit highly reduced the tar concentration. Similarly, the average particle size also decreased significantly. The peak emission spectra of the suspended BCFM particle under the plasma cracking treatment shifted from around 500 nm to around 400 nm. The significant changes in the BCFM functional group occurred due to the successful cracking process. It was concluded that the byproduct received from the plasma cracking process resulted in very low tar content and was revealed to be a carbon functionalized material with a very small size (16.2 nm) and stable suspension.
Optimization of a Protocol for Protein Extraction from Calcified Aortic Valves for Proteomics Applications: Development of a Standard Operating Procedure
Authors: Trindade Fábio , Ferreira Ana F. , Saraiva Francisca , Martins Diana , Mendes Vera M. , Sousa Carla , Gavina Cristina , Leite-Moreira Adelino , Manadas Bruno , Falcão-Pires Inês , Vitorino Rui
Published: September 2022

The comprehension of the pathophysiological mechanisms, the identification of druggable targets, and putative biomarkers for aortic valve stenosis can be pursued through holistic approaches such as proteomics. However, tissue homogenization and protein extraction are made difficult by tissue calcification. The reproducibility of proteome studies is key in clinical translation of the findings. Thus, we aimed to optimize a protocol for aortic valve homogenization and protein extraction and to develop a standard operating procedure (SOP), which researchers can use to maximize protein yield while reducing inter-laboratory variability. We have compared the protein yield between conventional tissue grinding in nitrogen followed by homogenization with a Potter apparatus with a more advanced bead-beating system. Once we confirmed the superiority of the latter, we further optimized it by testing the effect of beads size, the number of homogenization cycles, tube capacity, lysis buffer/tissue mass ratio, and two different lysis buffers. Optimal protein extraction was achieved with 2.8 mm zirconium dioxide beads, in two homogenization cycles, in the presence of 20 µL RIPA buffer/mg tissue, using 2 mL O-ring cryotubes. As a proof of concept of the usefulness of this SOP for proteomics, the AV proteome of men and women with aortic stenosis was characterized, resulting in the quantification of proteins across six orders of magnitude and uncovering some putative proteins dysregulated by sex.
Quantification of Construction Waste in Early Design Stages Using Bim-Based Tool
Authors: Quiñones Rocío , Llatas Carmen , Montes Maria Victoria , Cortés Isidro
Published: September 2022

Construction and demolition waste represents a growing environmental, social, and economic problem, and has become a priority for European and worldwide policies. The early quantification of construction waste is essential for the minimisation of its production and the improvement of waste management. This requires the development of design-based tools that enable a better understanding of the expected waste produced during the construction phase. Building Information Modelling (BIM) methodologies have gained recognition in the Architecture, Engineering, Construction, and Operations (AECO) sector, largely due to their capacity for data simulation, storage, and management during the building design phase. This study presents a software application, called WE-BIM Add-in, to quantify construction waste (CW) while designing the BIM model in Revit. A validated CW quantification model which enables waste types and quantities per building element to be predicted in detail according to the European List of Waste (LoW) is integrated into the Revit workflow. Design alternatives could be effortlessly simulated in real time to assist practitioners in decision-making during the early design stages. Two alternative structural systems of a Spanish residential building were compared: a reinforced concrete structure, Option 1 (O1), and a steel structure, Option 2 (O2). The results were obtained automatically: O2, in addition to reducing 56% of O1′s waste, would have increased the waste recycling rate by 49%; and displayed in Revit, thereby remaining consistent with those of other studies that compare prefabricated systems with in situ systems. This work provides a basis for future research into the automated estimation of construction waste in BIM which could become a useful tool in waste-prevention policies.
Underwater Image Restoration via Contrastive Learning and a Real-World Dataset
Authors: Han Junlin , Shoeiby Mehrdad , Malthus Tim , Botha Elizabeth , Anstee Janet , Anwar Saeed , Wei Ran , Armin Mohammad Ali , Li Hongdong , Petersson Lars
Published: September 2022

Underwater image restoration is of significant importance in unveiling the underwater world. Numerous techniques and algorithms have been developed in recent decades. However, due to fundamental difficulties associated with imaging/sensing, lighting, and refractive geometric distortions in capturing clear underwater images, no comprehensive evaluations have been conducted with regard to underwater image restoration. To address this gap, we constructed a large-scale real underwater image dataset, dubbed Heron Island Coral Reef Dataset (‘HICRD’), for the purpose of benchmarking existing methods and supporting the development of new deep-learning based methods. We employed an accurate water parameter (diffuse attenuation coefficient) to generate the reference images. There are 2000 reference restored images and 6003 original underwater images in the unpaired training set. Furthermore, we present a novel method for underwater image restoration based on an unsupervised image-to-image translation framework. Our proposed method leveraged contrastive learning and generative adversarial networks to maximize the mutual information between raw and restored images. Extensive experiments with comparisons to recent approaches further demonstrate the superiority of our proposed method. Our code and dataset are both publicly available.
Context for Reproducibility and Replicability in Geospatial Unmanned Aircraft Systems
Authors: Howe Cassandra , Tullis Jason A.
Published: September 2022

Multiple scientific disciplines face a so-called crisis of reproducibility and replicability (R&R) in which the validity of methodologies is questioned due to an inability to confirm experimental results. Trust in information technology (IT)-intensive workflows within geographic information science (GIScience), remote sensing, and photogrammetry depends on solutions to R&R challenges affecting multiple computationally driven disciplines. To date, there have only been very limited efforts to overcome R&R-related issues in remote sensing workflows in general, let alone those tied to unmanned aircraft systems (UAS) as a disruptive technology. This review identifies key barriers to, and suggests best practices for, R&R in geospatial UAS workflows as well as broader remote sensing applications. We examine both the relevance of R&R as well as existing support for R&R in remote sensing and photogrammetry assisted UAS workflows. Key barriers include: (1) awareness of time and resource requirements, (2) accessibility of provenance, metadata, and version control, (3) conceptualization of geographic problems, and (4) geographic variability between study areas. R&R in geospatial UAS applications can be facilitated through augmented access to provenance information for authorized stakeholders, and the establishment of R&R as an important aspect of UAS and related research design. Where ethically possible, future work should exemplify best practices for R&R research by publishing access to open data sets and workflows. Future work should also explore new avenues for access to source data, metadata, provenance, and methods to adapt principles of R&R according to geographic variability and stakeholder requirements.
Development of a GIS-Based Methodology for the Management of Stone Pavements Using Low-Cost Sensors
Authors: Bruno Salvatore , Vita Lorenzo , Loprencipe Giuseppe
Published: September 2022

Stone pavements are present in many cities and their historical and cultural importance is well recognized. However, there are no standard monitoring methods for this type of pavement that allow road managers to define appropriate maintenance strategies. In this study, a novel method is proposed in order to monitor the road surface conditions of stone pavements in a quick and easy way. Field tests were carried out in an Italian historic center using accelerometer sensors mounted on both a car and a bicycle. A post-processing phase of that data defined the comfort perception of the road users in terms of the awz index, as described in the ISO 2631 standard. The results derived from the dynamic surveys were also compared with the corresponding values of typical pavement indicators such as the International Roughness Index (IRI) and the Pavement Condition Index (PCI), measured only on a limited portion of the urban road network. The network’s implementation in a Geographic Information System (GIS) represents the surveys’ results in a graphical database. The specifications of the adopted method require that the network is divided into homogeneous sections, useful for measurement campaign planning, and adopted for the GIS’ outputs representation. The comparisons between IRI-awz (R2 = 0.74) and PCI-awz (R2 = 0.96) confirmed that the proposed method can be used reliably to assess the stone pavement conditions on the whole urban road network.
Anomaly Detection in Traffic Surveillance Videos Using Deep Learning
Authors: Khan Sardar Waqar , Hafeez Qasim , Khalid Muhammad Irfan , Alroobaea Roobaea , Hussain Saddam , Iqbal Jawaid , Almotiri Jasem , Ullah Syed Sajid
Published: September 2022

In the recent past, a huge number of cameras have been placed in a variety of public and private areas for the purposes of surveillance, the monitoring of abnormal human actions, and traffic surveillance. The detection and recognition of abnormal activity in a real-world environment is a big challenge, as there can be many types of alarming and abnormal activities, such as theft, violence, and accidents. This research deals with accidents in traffic videos. In the modern world, video traffic surveillance cameras (VTSS) are used for traffic surveillance and monitoring. As the population is increasing drastically, the likelihood of accidents is also increasing. The VTSS is used to detect abnormal events or incidents regarding traffic on different roads and highways, such as traffic jams, traffic congestion, and vehicle accidents. Mostly in accidents, people are helpless and some die due to the unavailability of emergency treatment on long highways and those places that are far from cities. This research proposes a methodology for detecting accidents automatically through surveillance videos. A review of the literature suggests that convolutional neural networks (CNNs), which are a specialized deep learning approach pioneered to work with grid-like data, are effective in image and video analysis. This research uses CNNs to find anomalies (accidents) from videos captured by the VTSS and implement a rolling prediction algorithm to achieve high accuracy. In the training of the CNN model, a vehicle accident image dataset (VAID), composed of images with anomalies, was constructed and used. For testing the proposed methodology, the trained CNN model was checked on multiple videos, and the results were collected and analyzed. The results of this research show the successful detection of traffic accident events with an accuracy of 82% in the traffic surveillance system videos.
Data Processing Approaches to Measure Velocity of Electromagnetic Gun on Laser Screen in Complex Environment
Authors: Hao Huiyan , Liu Wenyu , Xu Peng , Zhao Hui
Published: September 2022

The exit velocity of the armature is an important indicator in measuring the launching performance of the electromagnetic gun. The non-contact photoelectric detection technology with the use of a laser screen was applied to the measurement of the armature velocity of the electromagnetic gun. By means of taking the signals that pass through the laser screen obtained by the velocity measurement system as the research object, we solved problems such as the harsh test environment of the launch armature velocity of the electromagnetic gun, the interferences on the armature signal passing through the laser screen unavoidably caused by various factors such as vibration, electromagnetic interference, shock wave, flare, smoke and fragments, and even the non-recognition of the signal passing through the laser screen in severe cases. A data-processing algorithm that combines the Ensemble Empirical Mode Decomposition (EEMD) with Correlation Algorithm (CA) was proposed, with the aim of processing the signals passing through the laser screen, while using the maximum slope point as the time passing through the laser screen so as to calculate the velocity of the armature passing the laser screen. This method can effectively reduce the influence of interference on the test results, and the test results from two sets of velocity measuring systems show that the velocity obtained by the proposed approach is highly consistent.
Empowering Intelligent Surfaces and User Pairing for IoT Relaying Systems: Outage Probability and Ergodic Capacity Performance
Authors: Dang Huu-Phuc , Nguyen Minh-Sang Van , Do Dinh-Thuan , Nguyen Minh-Hoa , Pham Minh-Triet , Kim Anh-Tuan
Published: September 2022

The evolution of Internet of Things (IoT) networks has been studied owing to the associated benefits in useful applications. Although the evolution is highly helpful, the increasing day-to-day demands of mobile users have led to immense requirements for further performance improvements such as efficient spectrum utilization, massive device connectivity, and high data rates. Fortunately, reconfigurable intelligent surfaces (RIS) and non-orthogonal multiple access (NOMA) techniques have recently been introduced as two possible current-generation emerging technologies with immense potential of addressing the above-mentioned issues. In this paper, we propose the integration of RIS to the existing techniques (i.e., NOMA and relaying) to further enhance the performance for mobile users. We focus on a performance analysis of two-user group by exploiting two main performance metrics including outage probability and ergodic capacity. We provide closed-form expressions for both performance metrics to highlight how NOMA-aided RIS systems provide more benefits compared with the benchmark based on traditional orthogonal multiple access (OMA). Monte-Carlo simulations are performed to validate the correctness of obtained expressions. The simulations show that power allocation factors assigned to two users play a major role in the formation of a performance gap among two users rather than the setting of RIS. In particular, the strong user achieves optimal outage behavior when it is allocated 35% transmit power.
Dimension Reduction of Digital Image Descriptors in Neural Identification of Damaged Malting Barley Grains
Authors: Boniecki Piotr , Sujak Agnieszka , Pilarska Agnieszka A. , Piekarska-Boniecka Hanna , Wawrzyniak Agnieszka , Raba Barbara
Published: September 2022

The paper covers the problem of determination of defects and contamination in malting barley grains. The analysis of the problem indicated that although several attempts have been made, there are still no effective methods of identification of the quality of barley grains, such as the use of information technology, including intelligent sensors (currently, quality assessment of grain is performed manually). The aim of the study was the construction of a reduced set of the most important graphic descriptors from machine-collected digital images, important in the process of neural evaluation of the quality of BOJOS variety malting barley. Grains were sorted into three size fractions and seed images were collected. As a large number of graphic descriptors implied difficulties in the development and operation of neural classifiers, a PCA (Principal Component Analysis) statistical method of reducing empirical data contained in the analyzed set was applied. The grain quality expressed by an optimal set of transformed descriptors was modelled using artificial neural networks (ANN). The input layer consisted of eight neurons with a linear Postsynaptic Function (PSP) and a linear activation function. The one hidden layer was composed of sigmoid neurons having a linear PSP function and a logistic activation function. One sigmoid neuron was the output of the network. The results obtained show that neural identification of digital images with application of Principal Component Analysis (PCA) combined with neural classification is an effective tool supporting the process of rapid and reliable quality assessment of BOJOS malting barley grains.
A New GNSS Spoofing Signal Power Control Algorithm for Receiver Sensors in Acquisition Phase and Subsequent Control
Authors: Gao Yangjun , Li Guangyun
Published: September 2022

Satellite navigation spoofing technology has become a hotspot of interference technology research because of its significant threat and high concealment. In a spoofing scenario, suppressive interference is typically used to ensure that the target receiver sensor is in the unlocked and reacquisition state, and then spoofing is implemented. This method has a high feasibility, and the power of the spoofing signal affects the concealment and efficiency of spoofing. Currently, there is limited research involving the GNSS spoofing signal power control. Moreover, there is no systematic complete power control scheme, most of which is limited to qualitative or simulation, and the actual application effect is still unclear. Therefore, a new GNSS spoofing signal power control algorithm under the power constraints of the receiver sensor in the acquisition phase and the subsequent control is proposed. The experimental platform is designed to prove that compared with the conventional spoofing signal high power control algorithm, the new GNSS spoofing signal power control algorithm shortens Doppler frequency fluctuation time by 72.2% and reduces the range by 75.9%. The carrier-to-noise ratio of the received signal is less than the threshold of the receiver sensor, and the range of three-dimensional coordinates of Earth-Centered, Earth-Fixed (ECEF) is significantly reduced during the spoofing signal taking over receiver sensor, this shows that the new design of the GNSS spoofing signal power control algorithm can make spoofing behavior more hidden, and it will make it more difficult for the target receiver sensor to detect spoofing behavior. The designed algorithm can take over the receiver sensor stealthily with the help of suppressing interference and then pull the bias positioning results, which has good feasibility and effectiveness.
Refined Appearance Potential Mass Spectrometry for High Precision Radical Density Quantification in Plasma
Authors: Cho Chulhee , Kim Sijun , Lee Youngseok , Jeong Wonnyoung , Seong Inho , Lee Jangjae , Choi Minsu , You Yebin , Lee Sangho , Lee Jinho , You Shinjae
Published: September 2022

As the analysis of complicated reaction chemistry in bulk plasma has become more important, especially in plasma processing, quantifying radical density is now in focus. For this work, appearance potential mass spectrometry (APMS) is widely used; however, the original APMS can produce large errors depending on the fitting process, as the fitting range is not exactly defined. In this research, to reduce errors resulting from the fitting process of the original method, a new APMS approach that eliminates the fitting process is suggested. Comparing the neutral densities in He plasma between the conventional method and the new method, along with the real neutral density obtained using the ideal gas equation, confirmed that the proposed quantification approach can provide more accurate results. This research will contribute to improving the precision of plasma diagnosis and help elucidate the plasma etching process.
Research and Development of Ankle–Foot Orthoses: A Review
Authors: Zhou Congcong , Yang Zhao , Li Kaitai , Ye Xuesong
Published: September 2022

The ankle joint is one of the important joints of the human body to maintain the ability to walk. Diseases such as stroke and ankle osteoarthritis could weaken the body’s ability to control joints, causing people’s gait to be out of balance. Ankle–foot orthoses can assist users with neuro/muscular or ankle injuries to restore their natural gait. Currently, passive ankle–foot orthoses are mostly designed to fix the ankle joint and provide support for walking. With the development of materials, sensing, and control science, semi-active orthoses that release mechanical energy to assist walking when needed and can store the energy generated by body movement in elastic units, as well as active ankle–foot orthoses that use external energy to transmit enhanced torque to the ankle, have received increasing attention. This article reviews the development process of ankle–foot orthoses and proposes that the integration of new ankle–foot orthoses with rehabilitation technologies such as monitoring or myoelectric stimulation will play an important role in reducing the walking energy consumption of patients in the study of human-in-the-loop models and promoting neuro/muscular rehabilitation.
Musculoskeletal Disorders among Agricultural Workers of Various Cultivation Activities in Upper Northeastern Thailand
Authors: Poochada Worawan , Chaiklieng Sunisa , Andajani Sari
Published: September 2022

Musculoskeletal disorders (MSDs) are the most significant work-related health conditions that are experienced by agricultural workers. This cross-sectional study has investigated MSDs among agriculturalists in upper northeastern Thailand. We assessed the types of MSDs, their severity, and their frequency. There were 889 cultivating agriculturalists from four provinces who participated in this study. The majority of the participants reported experiencing mild levels of MSDs (60.48%). Predominantly, the farmers who were working on cassava, vegetable, and sugarcane plantations reported experiencing the most severe MSDs in the knees/calves (22.40%). The rice plantation workers reported the largest number of MSDs complaints. The workers on rubber plantations and in sugarcane fields were more likely to feel knee/calf pain (OR = 1.59, 95% CI = 1.05–2.39) and lower limb pain (OR = 1.97, 95% CI = 1.35–2.89) than those who were working on rice and tobacco plantations. The individuals who were working on cassava, fruit, vegetable, and corn plantations were also more likely to report knee/calf pain (OR = 1.48, 95% CI = 1.01–2.17) and lower limb pain (OR = 1.97, 95% CI = 1.37–2.84) than those who were working on rice and tobacco plantations. The MSDs that were found among those working on agricultural activities affected many parts of their bodies. The ergonomic risk needs to be assessed in order to inform plantation workers of the implications in order to improve their health and well-being and to reduce the risks of MSDs.
Improvement of Salinity Tolerance in Rice Seedlings by Exogenous Magnesium Sulfate Application
Authors: Xuan Tran Dang , Huong Can Thu , Quan Nguyen Van , Anh La Hoang , Khanh Tran Dang , Rayee Ramin
Published: September 2022

This study was conducted to develop the salt tolerance of rice by exogenous application of magnesium sulfate supplement (MgSO4). The salinization was carried out on 7-day-old rice seedlings including BC15 (salinity tolerant) and DT84DB (salinity susceptible) varieties with 0.5 mM MgSO4. The exogenous application of MgSO4 significantly improves the growth of seedlings of both varieties. In addition, antioxidant activities increase in line with the raise of total phenolic and total flavonoid contents. Remarkably, the contents of momilactone B (MB) and phenolic compounds including tricin, ρ-coumaric, salicylic, cinnamic, benzoic, and ferulic acids simultaneously rise in both varieties treated by salinity and 0.5 mM MgSO4. Interestingly, MB was not found in the salt-treated samples but presents with considerable contents in the salt and MgSO4-treated cultivars. The findings imply that MgSO4 may significantly improve the salt tolerance of rice seedlings through the enhancement of secondary metabolic synthesis pathways, of which phenolic acids and momilactone B may play a crucial role in the response of rice to salt stress. In contrast, momilactone A (MA) did not show any contribution in salinity tolerance of examined rice cultivars at the early seedling stage. Further investigations on the effect of MgSO4 exogenous application in improving salinity tolerance of various rice varieties at other growing stages should be carried out.
Including Sustainable Development Goals (SDGs) Transversally in Education
Authors: Zamora-Polo Francisco , Sánchez-Martín Jesús
Published: September 2022

Since mid-last century, the international scientific community has been developing a concept that each day presents more and more varied ramifications: sustainability [...]
Coordination of Retailer-Led Closed Loop Supply Chain Considering Corporate Social Responsibility
Authors: Zhao Huanhuan , Liu Yong , Liu Zhiyang
Published: September 2022

As resource waste and environmental degradation become increasingly serious, closed-loop supply chains have attracted more and more attention from the public. How to effectively undertake corporate social responsibility (CSR) and alleviate the conflict of closed-loop supply chains has become an urgent task for managers and researchers to resolve. With respect to the coordination problems of closed-loop supply chains led by retailers, based on Stackelberg game theory, we establish some models considering manufacturer’s CSR, exploit them to compare the optimal decisions under centralized and decentralized decisions, explore the impact of CSR on supply-chain decisions, then design a coordination mechanism through two-step pricing.
Sustaining Formal and Informal English Language Learning through Social Networking Sites (SNS): A Systematic Review (2018–2022)
Authors: Zainuddin Fatin Najiha , Yunus Melor Md
Published: September 2022

There has been a gradual shift over the years towards the use of social networking sites (SNS) in formal and informal English language learning which was accelerated during the COVID-19 pandemic. Though there is an abundance of articles dedicated to probing into the in-depth use of SNS in English language learning, a clear correlation between the formal and informal application of SNS in English language learning is still scarce. Therefore, this systematic review aims to exhaustively analyse the recent findings regarding the integration of SNS in English language learning in both formal and informal learning contexts. Two databases were employed, which are the Web of Science (WoS) and Educational Resources Information Centre (ERIC) and thirty articles were extracted for further review. These articles were selectively restricted to a five-year (2018–2022) range and have been screened for any contradiction against the research objectives. As an overview, SNS is favoured for different kinds of applications in teaching and learning purposes due to observed improvements in overall language skills, social interactions, motivation and flexibility. It is proposed for future researchers to focus on a specific target group as well as specific SNS platforms which could help the researchers to minimize discrepancies.
Integrating Freight and Public Transport Terminals Infrastructure by Locating Lockers: Analysing a Feasible Solution for a Medium-Sized Brazilian Cities
Authors: Oliveira Leise Kelli de , Oliveira Isabela Kopperschmidt de , França João Guilherme da Costa Braga , Balieiro Gustavo Wagner Nunes , Cardoso Jean Francisco , Bogo Tiago , Bogo Diego , Littig Marco Adriano
Published: September 2022

Integrating freight and public transport infrastructure can lead to providing economic feasibility to public transportation systems and reducing externalities related to urban freight transport. This can be achieved by sharing the infrastructure of freight and public transportation systems. Additionally, failed deliveries represent a major challenge in e-commerce. Lockers can address this problem and promote sustainable urban freight transport. This paper identified a locker network in a public transportation infrastructure. The framework considered scenarios built under the 15-min city concept, and the analysis is based on a case study in Jaraguá do Sul (Brazil, a mid-sized Brazilian city, and its conurbated area. The networks were found by solving a p-median problem, which minimised the maximum distance between the lockers and the population. The findings showed that, in the best scenario with 16 lockers, the population could reach the lockers within a 10-min cycling ride. Additionally, the results showed that the public transportation network provides a locker network to integrate freight and public transportation. The locker network is accessible to public transportation and micromobility users. With this solution, residents play an active role in last-mile deliveries. In addition, lockers can work as mini hubs for crowdshipping services. In addition to reducing urban delivery trips, this solution can encourage public transportation usage, which contributes to more sustainable cities.