bluuebunny/crossref_metadata_2025 huggingface dataset:
Molecular Dynamics Study on the Welding Behavior in Dissimilar TC4-TA17 Titanium Alloys
Authors: Ou Peng , Cao Zengqiang , Rong Ju , Yu Xiaohua
Published: August 2022

Titanium alloys have become the material of choice for marine parts manufacturing due to their high specific strength and excellent resistance to seawater corrosion. However, it is still challenging for a single titanium alloy to meet the comprehensive specifications of a structural component. In this study, we have applied a molecular dynamics approach to simulate the aging phase transformation, K-TIG welding process, and mechanical properties of the TC4-TA17 (Ti6Al4V-Ti4Al2V) alloy. The results show that during the aging phase transformation process, changes in the structure of the titanium alloys are mainly manifested in the precipitation of a new phase from the sub-stable β-phase, and after the state stabilization, the α-phase content reaches 45%. Moreover, during the melting and diffusion process of TC4-TA17, aluminum atoms near the interface diffuse, followed by titanium atoms, while relatively few vanadium atoms are involved in the diffusion. Finally, the results of tensile simulations of the TC4-TA17 alloy after welding showed that stress values can reach up to 9.07 GPa and that the mechanical properties of the alloy in the weld zone are better than those of the single alloys under the same conditions. This study will provide theoretical support for the optimization of process parameters for TC4-TA17 alloy welding.
Experimental Study on PVA-MgO Composite Improvement of Sandy Soil
Authors: Li Zhongyao , Zhao Zhewei , Shi Haiping , Li Jiahuan , Zhao Cheng , Wang Peiqing
Published: August 2022

Materials with violent hydration reaction such as cement are used to solidify sandy soil slopes, which will cause destructive damage to the ecology of the slopes. In this paper, polyvinyl alcohol (PVA) and activated magnesium oxide (MgO) are used to improve sandy soil, and the effects of the dosage and curing age of modifiers on the mechanical properties of solidified sandy soil are studied. The dry–wet durability of the composite improved sandy soil is analyzed using a dry–wet cycle test, and the improvement mechanism of PVA and activated magnesium oxide is revealed using an electron microscope. The results show that the curing effect of polyvinyl alcohol and activated magnesium oxide on sand particles is better than that of polyvinyl alcohol alone. The compressive strength of improved soil samples increases with the increase of curing time, and magnesium oxide as an improved material needs appropriate reaction conditions to give full play to its role. The compressive strength of composite improved samples increases first and then decreases during the dry–wet cycle. Through the observation of microstructure, it can be seen that the cementing material wraps and connects the sand particles, and the cementing material of the sample after the dry–wet cycle develops more completely; if the magnesium oxide content is high, cracks may appear inside the sample.
Adaptive Band Extraction Based on Low Rank Approximated Nonnegative Tucker Decomposition for Anti-Friction Bearing Faults Diagnosis Using Measured Vibration Data
Authors: Wen Haobin , Zhang Long , Sinha Jyoti K.
Published: August 2022

Condition monitoring and fault diagnosis are topics of growing interest for improving the reliability of modern industrial systems. As critical structural components, anti-friction bearings often operate under harsh conditions and are contributing factors of system failures. Efforts have been cast on bearing diagnostics under the sensor fusion and machine learning framework, whilst challenges remain open on the identification of incipient faults. In this paper, exploiting multi-way representations and decompositions of measured vibration data, a novel band separation method based on the factorization of spectrogram tensors using the low rank approximated nonnegative Tucker decomposition (LRANTD) is proposed and applied to identify detailed fault signatures from the spectral, temporal, and spatial dimensions, flexible for extracting multi-sensor features and multi-dimensional correlations. With the proposed method, informative frequency bands of the latent vibrational components can be automatically extracted, in accordance with the inherent temporal patterns that can be conveniently fed for spectral analysis and fault discrimination. Furthermore, an improved cross-spectrum can be calculated from multi-channel vibrations via LRANTD with enhanced fault features. Based on the real-world vibration data of the accelerated bearing life tests, detailed experimental studies and thorough comparisons to the conventional benchmarks have verified the effectiveness of the reported diagnostic methodology. The proposed method significantly improves the presence of the bearing frequency peaks distinctly over the background noises in the spectrum and hence improves the bearing defect detection process.
A Nonlinear Multigrid Method for the Parameter Identification Problem of Partial Differential Equations with Constraints
Authors: Liu Tao , Yu Jiayuan , Zheng Yuanjin , Liu Chao , Yang Yanxiong , Qi Yunfei
Published: August 2022

In this paper, we consider the parameter identification problem of partial differential equations with constraints. A nonlinear multigrid method is introduced to the process of parameter inversion. By keeping the objective functions on coarse grids consistent with those on fine grids, the proposed method reduces the dimensions of objective functions enormously and mitigates the risk of trapping in local minima effectively. Furthermore, constraints significantly improve the convergence ability of the method. We performed the numerical simulation based on the porosity identification of elastic wave equations in the fluid-saturated porous media, which suggests that the nonlinear multigrid method with constraints decreases the computational expenditure, suppresses the noise, and improves the inversion results.
Multi-Objective Robust Optimization for the Sustainable Location-Inventory-Routing Problem of Auto Parts Supply Logistics
Authors: Lv Ao , Sun Baofeng
Published: August 2022

A great loss of transportation capacity has been caused in auto parts supply logistics due to the independent transportation from auto parts suppliers (APSs) to the automobile production line (APL). It is believed that establishing distribution centers (DCs) for centralized collection and unified distribution is one effective way to address this problem. This paper proposes a unified framework simultaneously considering the location-inventory-routing problem (LIRP) in auto parts supply logistics. Integrating the idea of sustainable development, a multi-objective MIP model is developed to determine the location and inventory capacity of DCs and routing decisions to minimize the total system cost and carbon emissions while concerning multi-period production demand. In addition, a robust optimization model is developed further in the context of uncertain demand. Numerical experiments and sensitivity analyses are conducted to verify the effectiveness of our proposed deterministic and robust models. The results show that synergistically optimizing the location and capacity of DCs and routing decisions are beneficial in reducing total system cost and carbon emissions. The analysis can provide guidelines to decision-makers for the effective management of auto parts supply logistics.
Mathematical Model for Analyzing the Dynamics of Tungro Virus Disease in Rice: A Systematic Literature Review
Authors: Amelia Rika , Anggriani Nursanti , Supriatna Asep K. , Istifadah Noor
Published: August 2022

One of the main obstacles in rice cultivation is the tungro virus disease caused by Rice tungro spherical virus (RTSV) and Rice tungro bacilliform virus (RTBV). These viruses are transmitted by green leafhopper (Nephotettix virescens) vector, semi-persistently after sucking infected plants. Subsequently, the vectors migrate and suck susceptible plants, but they can be controlled chemically and biologically. Mathematical modeling is one of the tools that can be used to analyze the spread of disease in plants. A literature review was conducted regarding the mathematical model of the spread of tungro virus disease in rice plants with the data sourced from scholarly references available in the dimension database, Google Scholar, and Scopus in 2012–2021. The steps followed include conducting a literature analysis and examining the mathematical model of the transmission of tungro virus disease in rice plants to identify gaps for future research. The results show that since 2016, few studies have analyzed mathematical models of the spread of tungro virus disease in rice plants. This is evident from the data search results, which show that only four articles were acquired through the option of duplication and visualization using VOSviewer software.
Molecular Epidemiology of Penicillin-Susceptible Staphylococcus aureus Bacteremia in Australia and Reliability of Diagnostic Phenotypic Susceptibility Methods to Detect Penicillin Susceptibility
Authors: Coombs Geoffrey W. , Yee Nicholas W. T. , Daley Denise , Bennett Catherine M. , Robinson James O. , Stegger Marc , Shoby Princy , Mowlaboccus Shakeel
Published: August 2022

Background: Defined by the emergence of antibiotic resistant strains, Staphylococcus aureus is a priority bacterial species with high antibiotic resistance. However, a rise in the prevalence of penicillin-susceptible S. aureus (PSSA) bloodstream infections has recently been observed worldwide, including in Australia, where the proportion of methicillin-susceptible S. aureus causing bacteremia identified phenotypically as penicillin-susceptible has increased by over 35%, from 17.5% in 2013 to 23.7% in 2020. Objectives: To determine the population structure of PSSA causing community- and hospital-onset bacteremia in Australia and to evaluate routine phenotypic antimicrobial susceptibility methods to reliably confirm penicillin resistance on blaZ-positive S. aureus initially classified as penicillin-susceptible by the Vitek® 2 automated microbiology system. Results: Whole genome sequencing on 470 PSSA collected in the 2020 Australian Group on Antimicrobial Resistance Australian Staphylococcus aureus Sepsis Outcome Programme identified 84 multilocus sequence types (STs), of which 79 (463 isolates) were grouped into 22 clonal complexes (CCs). The dominant CCs included CC5 (31.9%), CC97 (10.2%), CC45 (10.0%), CC15 (8.7%), and CC188 (4.9%). Many of the CCs had multiple STs and spa types and, based on the immune evasion cluster type, isolates within a CC could be classified into different strains harboring a range of virulence and resistance genes. Phylogenetic analyses of the isolates showed most CCs were represented by one clade. The blaZ gene was identified in 45 (9.6%) PSSA. Although multiclonal, approximately 50% of blaZ-positive PSSA were from CC15 and were found to be genetically distant from the blaZ-negative CC15 PSSA. The broth microdilution, Etest® and cefinase, performed poorly; however, when the appearance of the zone edge was considered; as per the EUCAST and CLSI criteria, disc diffusion detected 100% of blaZ-positive PSSA. Conclusions: In Australia, PSSA bacteremia is not caused by the expansion of a single clone. Approximately 10% of S. aureus classified as penicillin-susceptible by the Vitek® 2 harbored blaZ. Consequently, we recommend that confirmation of Vitek® 2 PSSA be performed using an alternative method, such as disc diffusion with careful interpretation of the zone edge.
In Silico Evaluation of Bioactive Compounds of Artemisia pallens Targeting the Efflux Protein of Multidrug-Resistant Acinetobacter baumannii (LAC-4 Strain)
Authors: Suvaithenamudhan Suvaiyarasan , Ananth Sivapunniyam , Mariappan Vanitha , Dhayabaran Victor Violet , Parthasarathy Subbiah , Ganesh Pitchaipillai Sankar , Shankar Esaki Muthu
Published: August 2022

Acinetobacter baumannii (A. baumannii) is one of the major representative aetiologies of recalcitrant nosocomial infections. Genotypic and phenotypic alterations in A. baumannii have resulted in a significant surge in multidrug resistance (MDR). Of all the factors responsible for the development of antimicrobial resistance (AMR), efflux protein pumps play a paramount role. In pursuit of a safe alternative for the prevention and control of A. baumannii infections, bioactive compounds from the aerial parts of the medicinal plant Artemisia pallens were studied. GC-MS analysis of the ethanol extract of A. pallens detected five major compounds: lilac alcohol A, spathulenol, lilac alcohol C, n-hexadecanoic acid, and vulgarin. In silico examinations were performed using the Schrödinger suite. Homology modelling was performed to predict the structure of the efflux protein of A. baumannii-LAC-4 strain (MDR Ab-EP). The identified bioactive compounds were analysed for their binding efficiency with MDR Ab-EP. High binding efficiency was observed with vulgarin with a glide score of −4.775 kcal/mol and stereoisomers of lilac alcohol A (−3.706 kcal/mol) and lilac alcohol C (−3.706 kcal/mol). Our molecular dynamic simulation studies unveiled the stability of the ligand–efflux protein complex. Vulgarin and lilac alcohol A possessed strong and stable binding efficiency with MDR Ab-EP. Furthermore, validation of the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of the ligands strongly suggested that these compounds could serve as a lead molecule in the development of an alternate drug from A. pallens.
2-Arachidonoylglycerol Synthesis: Facile and Handy Enzymatic Method That Allows to Avoid Isomerization
Authors: Ottria Roberta , Casati Silvana , Rota Paola , Ciuffreda Pierangela
Published: August 2022

A simple and practical synthesis of 2-arachidonoyl glycerol (2-AG), an endogenous agonist for cannabinoid receptors, based on a two-step enzymatic process and a chemical coupling, was achieved with a good yield and negligible amount of the isomerization product 1-AG. Commercial preparation of immobilized lipase from Mucor miehei (MML) was selected as the most suitable enzyme to catalyze the efficient protection of glycerol using vinyl benzoate as an acyl transfer reagent in tetrahydrofuran. The same enzyme was used to remove the protective groups in positions 1 and 3. Owing to the mild neutral conditions and easy suitability of the method, 2-AG was obtained without any isomerization to the more stable 1-AG and air oxidation of acid chain. The synthetic method proposed here allows us to easily obtain 2-AG from the protected precursor in a one-step reaction without purification requirement.
Bacopa Protects against Neurotoxicity Induced by MPP+ and Methamphetamine
Authors: Ferrucci Michela , Busceti Carla Letizia , Lazzeri Gloria , Biagioni Francesca , Puglisi-Allegra Stefano , Frati Alessandro , Lenzi Paola , Fornai Francesco
Published: August 2022

The neurotoxins methamphetamine (METH) and 1-methyl-4-phenylpyridinium (MPP+) damage catecholamine neurons. Although sharing the same mechanism to enter within these neurons, METH neurotoxicity mostly depends on oxidative species, while MPP+ toxicity depends on the inhibition of mitochondrial activity. This explains why only a few compounds protect against both neurotoxins. Identifying a final common pathway that is shared by these neurotoxins is key to prompting novel remedies for spontaneous neurodegeneration. In the present study we assessed whether natural extracts from Bacopa monnieri (BM) may provide a dual protection against METH- and MPP+-induced cell damage as measured by light and electron microscopy. The protection induced by BM against catecholamine cell death and degeneration was dose-dependently related to the suppression of reactive oxygen species (ROS) formation and mitochondrial alterations. These were measured by light and electron microscopy with MitoTracker Red and Green as well as by the ultrastructural morphometry of specific mitochondrial structures. In fact, BM suppresses the damage of mitochondrial crests and matrix dilution and increases the amount of healthy and total mitochondria. The present data provide evidence for a natural compound, which protects catecholamine cells independently by the type of experimental toxicity. This may be useful to counteract spontaneous degenerations of catecholamine cells.
Increasing Sugar Content in Source for Biofuel Production Using Agrochemical and Genetic Approaches at the Stages of BioMass Preharvesting and Harvesting
Authors: Zolotareva Darya , Zazybin Alexey , Belyankova Yelizaveta , Dauletbakov Anuar , Tursynbek Saniya , Rafikova Khadichahan , Ten Assel , Yu Valentina , Bayazit Sarah , Basharimova Anna , Aydemir Murat
Published: August 2022

In order to optimize biofuel (including bioethanol) production processes, various problems need to be solved, such as increasing the sugar content of raw materials/biomass to gain a higher yield of the product. This task can be solved in several ways, with their own advantages and disadvantages, and an integrated approach, such as using a combination of ripening agents and phytohormones or application of a superabsorbent polymer with at least one sugar-enhancing agent, can be applied as well. Here, we reviewed several methods, including pre- and postharvest factors (light, temperature, partial replacement of potassium with magnesium, etc.), genetic modifications (traditional breeding, phytohormones, etc.), chemical ripening methods (Ethephon, Moddus, etc.), and some alternative methods (DMSO treatment, ionic liquids, etc.). The aim of this review was to provide a comprehensive, up-to-date summary of methods of increasing the carbohydrate level in plants/biomass for bioethanol production.
Mathematical Perspectives in the Variable Texture Products Cutting Process
Authors: Panainte-Lehăduș Mirela , Moșneguțu Emilian , Bârsan Narcis , Andrioai Gabriela , Tomozei Claudia , Irimia Oana
Published: August 2022

The methods utilized to construct and identify the mathematical equation that characterizes the cutting of items with varied textures are presented in this work. Using laboratory equipment, the cutting process was carried out experimentally. The cutting energy was calculated based on the experimental results. The energy required to perform this process is directly influenced by the textural characteristics of the products used, as per the analysis of the experimental results obtained after the cutting process (density, humidity, products with or without peel). The gathered information was used to develop a general equation that would properly describe the process. Table Curve 3D software was used to create mathematical equations that define the relationship between input parameters, the type of product being cut, cutting speed, and output parameters, i.e., cutting energy. The equations that have the same correlation coefficient were discovered using the working methodology; it was specifically designed for this purpose.
Variation of Salvia officinalis L. Essential Oil and Hydrolate Composition and Their Antimicrobial Activity
Authors: Aćimović Milica , Pezo Lato , Čabarkapa Ivana , Trudić Anika , Stanković Jeremić Jovana , Varga Ana , Lončar Biljana , Šovljanski Olja , Tešević Vele
Published: August 2022

This study aimed to investigate the chemical composition of steam distillate essential oil and corresponding hydrolate obtained from S. officinalis grown in Serbia, as well as the influence of weather conditions (temperature and precipitations) on their chemical profiles. Furthermore, their antimicrobial activity was investigated in vitro. The main compounds in essential oil were cis-thujone, followed by camphor, trans-thujone, and 1,8-cineole, while hydrolate was slightly different from the essential oil, with camphor, cis-thujone, and 1,8-cineole as the main compounds. Among the eight respiratory-associated microorganisms, Klebsiella oxytoca was the most sensitive to the tested EOs (minimum inhibitory concentration (MIC)/minimal bactericidal/fungicidal concentration (MBC/MFC) were 14.20 and 28.4 μL mL−1, respectively). MIC and MBC values of other tested bacteria ranged between 28.40 and 227.25 μL mL−1 while for Candida albicans MIC/MFC ranged from 28.40/56.81 to 56.81–113.63 μL mL−1. Antibiotic susceptibility patterns for the analyzed eight respiratory-associated microorganisms showed an intermediate level of resistance to commonly used antibiotics such as ampicillin, levofloxacin, and ciprofloxacin. As a preliminary approach to the antimicrobial profiling of the tested EO, the obtained results revealed that the tested samples possess remarkable antibacterial activities and could be used to develop pharmaceutical formulations as an alternative to conventional antibiotic therapy.
Neuromodulatory and Protective Effects Induced by the Association of Herbal Extracts from Valeriana officinalis, Ziziphus jujuba, and Humulus lupulus with Melatonin: An Innovative Formulation for Counteracting Sleep Disorders
Authors: Chiavaroli Annalisa , Di Simone Simonetta , Acquaviva Alessandra , Nilofar  , Libero Maria , Brunetti Luigi , Recinella Lucia , Leone Sheila , Orlando Giustino , Zengin Gokhan , Mazzone Antonella , Menghini Luigi , Ferrante Claudio
Published: August 2022

Background: The use of herbal extracts could represent an advantageous approach for treating sleeping disorders, especially in mild-to-moderate conditions, before the onset of a specific therapy with first-line drugs. Specifically, the focus was posed about the use of extracts from Valeriana officinalis, Ziziphus jujuba, and Humulus lupulus. Multiple studies demonstrated the efficacy of these medicinal plants to positively manage insomnia symptoms. Additionally, their efficacy in the treatment of sleeping disorders could also be improved by their pharmacological association. In the present study, extracts from Valeriana officinalis, Ziziphus jujuba, Humulus lupulus, melatonin, and their pharmacological association, Vagonotte® MEL, were studied for potential application in the treatment of insomnia. Methods: The extracts and melatonin were tested on hypothalamic neurons and tissue for evaluating biocompatibility and protective and neuromodulatory effects. The neuromodulatory effects were evaluated as orexin A gene expression and serotonin steady state level, in the hypothalamus. Results: The extracts and melatonin, although with evident differences, were effective as antioxidant and anti-inflammatory agents; additionally, they were also able to reduce the hypothalamic gene expression of orexin A and the steady state level of serotonin, playing master roles in wakefulness. It is noteworthy that the formulation displayed all the effects of the single ingredients, without any sign of toxicity and pharmacological interference in the hypothalamus. Conclusions: Concluding, the present study explored the biological effects of melatonin and herbal extracts with phytotherapy interest in V. officinalis, Z. jujuba, and H. lupulus. The study demonstrated their intrinsic scavenging/reducing activity, together with protective and neuromodulatory effects in the hypothalamus, with a significant reduction of both orexin A gene expression and serotonin steady state level. Additionally, the study also considered their pharmacological association, which displayed an overall pharmacological spectrum mirroring, including all the effects of the single ingredients, without showing any sign of toxicity in the brain and interference between the extracts and melatonin.
Lessons Learnt from Götz of the Iron Hand
Authors: Otte Andreas
Published: August 2022

Recently, we reported the three-dimensional computer-aided design (3D-CAD) reconstruction of the first “Iron Hand” of the famous Franconian knight, Götz von Berlichingen (1480–1562), who lost his right hand by a cannon ball splinter injury in 1504 in the War of the Succession of Landshut [...]
Analyzing Polyethylene Terephthalate Bottle Waste Technology Using an Analytic Hierarchy Process for Developing Countries: A Case Study from Indonesia
Authors: Amirudin Akhmad , Inoue Chihiro , Grause Guido
Published: August 2022

PET bottle waste is easy to recycle because it is easy to separate, abundant, and competitively priced. Technologies for the treatment of PET bottle waste have been evaluated to date by using life cycle assessment (LCA), but this does not take into account all of the aspects that policymakers consider necessary when selecting an acceptable technology. Aspects such as society, economics, policies, and technical applicability need to be considered along with the environment and resource consumption to complement the LCA results for PET bottle waste. These aspects were selected as criteria for the analytical hierarchy process (AHP), and stakeholders were invited to make a comparison evaluation of the criteria and sub-criteria. Academics were involved to compare the technology options. The results show that society is the highest priority because it is the main actor that ensures the application of the technology, and that job creation is the most important indicator for the selection of the technology in society criteria. After comparing open landfills, sanitary landfills, incineration with energy recovery, pelletizing, glycolysis, and hydrolysis for the utilization of PET bottle waste, this study suggests pelletizing as the acceptable technology for Indonesia because pelletizing is dominant in all the criteria and sub-criteria which support sustainability in waste management. This is the first time that a single plastic fraction that is easy to collect and recycle has been studied with the AHP. The results show that this type of plastic could also be reused in developing countries through mechanical recycling.
Strength and Microstructure of Coffee Silverskin Blended Mortar
Authors: Yusuf Moruf Olalekan , Mohammed Zeyad M. A. , Adewumi Adeshina A. , Shaban Mutasem Taisir , AlBaqawi Meshrif Omar Meshrif , Mohamed Hatim Dafalla
Published: August 2022

This study pertains to incorporation of coffee silverskin (CSS) in partial replacement for ordinary Portland cement (OPC) in mortar, by investigating its fresh properties (setting and workability), compressive strength (3, 7, 14 and 28-day), absorption and microstructural characteristics. The objectives were to reduce environmental solid wastes and achieve cost efficiency in the use of construction materials. The CSS was expressed as a ratio of total binder (CSS/(OPC + CSS)) and varied from 0 to 5%. The findings revealed that CSS could reduce workability, setting time and early strength. It could also enhance the absorption of the CSS-blended mortar (CBM). The cause of reduction in workability was due to its contribution to the viscosity of the mixture due to the emulsification of the fat component (acetate) and aromatic compounds, as observed in the Fourier Transform Infrared (FTIR) spectroscopy and X-ray diffraction techniques. The presence of these compounds also caused microstructural disintegration that resulted in the lower strength. In addition, the presence of other organic compound in CSS but absent in OPC enhanced microstructural disintegration and porosity in CBM. The 28-day strength of 25 MPa could be achieved in CSS-blended mortar if the CSS/(CSS + OPC) ratios were kept below 3%. The maximum compressive strength of 38.5 MPa was obtained with the optimum CSS content of 1 wt%. The relative density (water) of CSS was 0.345; therefore, it could also be used to produce lightweight concrete. This study promotes the valorization of raw CSS waste as construction material which could be used for subgrade in the construction of road pavement.
Mobility Management of Unmanned Aerial Vehicles in Ultra–Dense Heterogeneous Networks
Authors: Alshaibani W. T. , Shayea Ibraheem , Caglar Ramazan , Din Jafri , Daradkeh Yousef Ibrahim
Published: August 2022

The rapid growth of mobile data traffic will lead to the deployment of Ultra–Dense Networks (UDN) in the near future. Various networks must overlap to meet the massive demands of mobile data traffic, causing an increase in the number of handover scenarios. This will subsequently affect the connectivity, stability, and reliability of communication between mobile and serving networks. The inclusion of Unmanned Aerial Vehicles (UAVs)—based networks will create more complex challenges due to different mobility characterizations. For example, UAVs move in three–dimensions (3D), with dominant of line–of–sight communication links and faster mobility speed scenarios. Assuring steady, stable, and reliable communication during UAVs mobility will be a major problem in future mobile networks. Therefore, this study provides an overview on mobility (handover) management for connected UAVs in future mobile networks, including 5G, 6G, and satellite networks. It provides a brief overview on the most recent solutions that have focused on addressing mobility management problems for UAVs. At the same time, this paper extracts, highlights, and discusses the mobility management difficulties and future research directions for UAVs and UAV mobility. This study serves as a part of the foundation for upcoming research related to mobility management for UAVs since it reviews the relevant knowledge, defines existing problems, and presents the latest research outcomes. It further clarifies handover management of UAVs and highlights the concerns that must be solved in future networks.
Detection of Oil in Seawater Based on the Fluorometric Index during the Winter Season in the Baltic Sea—The Case of the Gulf of Gdansk
Authors: Baszanowska Emilia , Otremba Zbigniew
Published: August 2022

This study is a continuation of analyses of the fluorometric index (FI), based on the fluorescence of substances of oil origin, as an indicator of oil in a seawater column. The effectiveness of the FI in the cold season (late autumn, winter and early spring) for the coastal water in the southern Baltic Sea was assessed. FI was tested for seawater polluted with a mixture of crude oils, lubricating oils and fuels. Laboratory analyses of oil–water systems for low (reaching the limit of detection) oil content in seawater were performed. The influences of the natural components of seawater that disrupt oil detection are discussed. The ability to detect oil in a seawater column regardless of the season was confirmed.
An Investigation of the Reliability of Different Types of Sensors in the Real-Time Vibration-Based Anomaly Inspection in Drone
Authors: Ghazali Mohamad Hazwan Mohd , Rahiman Wan
Published: August 2022

Early drone anomaly inspection is vital to ensure the drone’s safety and effectiveness. This process is often overlooked, especially by amateur drone pilots; however, some faulty conditions are difficult to notice by the naked eye or discover, even though the drone inspection process has been conducted; therefore, a real-time early drone inspection approach based on vibration data is proposed in this study. Firstly, the reliability of several microelectromechanical systems (MEMS) sensors, namely the ADXL335 accelerometer, ADXL 345 accelerometer, ADXL377 accelerometer, and SW420 vibration sensor in detecting faulty conditions, were tested and compared. The experimental results demonstrated that the vibration parameter measured using ADXL335 and ADXL345 accelerometers are the best choice as most of the faulty conditions can be detected, in contrast to other MEMS sensors. The output produced from the anomaly inspection algorithm is then converted to the “Healthy” or “Faulty” state, which is displayed in a mobile application for easy monitoring.
Monitoring Breathing and Heart Rate Using Episodic Broadcast Data Transmission
Authors: Janik Paweł , Janik Małgorzata A. , Pielka Michał
Published: August 2022

The paper presents a wearable sensor for breath and pulse monitoring using an inertial sensor and episodic broadcast radio transmission. The data transmission control algorithm applied allows for the transmission of additional information using the standard PDU format and, at the same time, goes beyond the Bluetooth teletransmission standard (BLE). The episodic broadcast transmission makes it possible to receive information from sensors without the need to create a dedicated radio link or a defined network structure. The radio transmission controlled by the occurrence of a specific event in the monitored signal is combined with the reference wire transmission. The signals from two different types of sensors and the simulated ECG signal are used to control the BLE transmission. The presented results of laboratory tests indicate the effectiveness of episodic data transmission in the BLE standard. The conducted analysis showed that the mean difference in pulse detection using the episodic transmission compared to the wire transmission is 0.038 s, which is about 4% of the mean duration of a single cycle, assuming that the average adult human pulse is 60 BPM.
Development of a Framework for Generating Driving Safety Assessment Scenarios for Automated Vehicles
Authors: Ko Woori , Park Sangmin , Yun Jaewoong , Park Sungho , Yun Ilsoo
Published: August 2022

Despite the technological advances in automated driving systems, traffic accidents involving automated vehicles (AVs) continue to occur, raising concerns over the safety and reliability of automated driving. For the smooth commercialization of AVs, it is necessary to systematically assess the driving safety of AVs under the various situations that they potentially face. In this context, these various situations are mostly implemented by using systematically developed scenarios. In accordance with this need, a scenario generation framework for the assessment of the driving safety of AVs is proposed by this study. The proposed framework provides a unified form of assessment with key components for each scenario stage to facilitate systematization and objectivity. The performance of the driving safety assessment scenarios generated within the proposed framework was verified. Traffic accident report data were used for verification, and the usefulness of the proposed framework was confirmed by generating a set of scenarios, ranging from functional scenarios to test cases. The scenario generation framework proposed in this study can be used to provide sustainable scenarios. In addition, from this, it is possible to create assessment scenarios for all road types and various assessment spaces, such as simulations, proving grounds, and real roads.
An Automated Optical Strain Measurement System for Estimating Polymer Degradation under Fatigue Testing
Authors: Bogdanov Alexey A. , Panin Sergey V. , Lyubutin Pavel S. , Eremin Alexander V. , Buslovich Dmitry G. , Byakov Anton V.
Published: August 2022

(1) Background: this study deals with design of an automated laboratory facility based on a servo-hydraulic testing machine for estimating parameters of mechanical hysteresis loops by means of the digital image correlation (DIC) method. (2) Methods: the paper presents a description of the testing facility, describes the grounds for calculating the elastic modulus, the offset yield strength (OYS) and the parameters of the mechanical hysteresis loops by the DIC method. (3) Results: the developed hardware-software facility was tested by studying the fatigue process in neat polyimide (PI) under various amplitude tension-tension loadings. It was found that the damage accumulation was accompanied by the decrease in the loop areas, while failure occurred when it reduced by at least ~5 kJ/m3. (4) Conclusions: it was shown that lowering the loop area along with changing the secant modulus value makes it possible to estimate the level of the scattered damage accumulation (mainly at the stresses above the OYS level). It was revealed that fractography data, namely the pattern and sizes of the fatigue crack initiation and propagation zones, did not correlate well with the dependences of the parameters of the hysteresis loops.
Long-Short Term Memory Network-Based Monitoring Data Anomaly Detection of a Long-Span Suspension Bridge
Authors: Zhang Jianliang , Zhang Jian , Wu Zhishen
Published: August 2022

Structural health monitoring (SHM) systems have been widely applied in long-span bridges and a large amount of SHM data is continually collected. The harsh environment of sensors installed at structures causes multiple types of anomalies such as outlier, minor, missing, trend, drift, and break in the SHM data, which seriously hinders the further analysis of SHM data. In order to achieve anomaly detection from a large amount of SHM data, this paper proposes a long-short term memory (LSTM) network-based anomaly detection method. Firstly, the proposed method reduces the workload for preparing training sets. Secondly, the purpose of real-time anomaly detection can be met. Thirdly, the problem of high alarm rate can be avoided by utilizing double thresholds. To validate the effectiveness of the proposed method, a case study of finite element model simulation is firstly introduced, which illustrates the detailed implementation process. Finally, acceleration data from the SHM system of a long-span suspension bridge located in Jiangyin, China is employed. The results show that the proposed method can detect anomaly with high accuracy and identify abnormal accidents such as a ship collision quickly.
Using Sparse Patch Annotation for Tumor Segmentation in Histopathological Images
Authors: Liu Yiqing , He Qiming , Duan Hufei , Shi Huijuan , Han Anjia , He Yonghong
Published: August 2022

Tumor segmentation is a fundamental task in histopathological image analysis. Creating accurate pixel-wise annotations for such segmentation tasks in a fully-supervised training framework requires significant effort. To reduce the burden of manual annotation, we propose a novel weakly supervised segmentation framework based on sparse patch annotation, i.e., only small portions of patches in an image are labeled as ‘tumor’ or ‘normal’. The framework consists of a patch-wise segmentation model called PSeger, and an innovative semi-supervised algorithm. PSeger has two branches for patch classification and image classification, respectively. This two-branch structure enables the model to learn more general features and thus reduce the risk of overfitting when learning sparsely annotated data. We incorporate the idea of consistency learning and self-training into the semi-supervised training strategy to take advantage of the unlabeled images. Trained on the BCSS dataset with only 25% of the images labeled (five patches for each labeled image), our proposed method achieved competitive performance compared to the fully supervised pixel-wise segmentation models. Experiments demonstrate that the proposed solution has the potential to reduce the burden of labeling histopathological images.
Robust PPG Peak Detection Using Dilated Convolutional Neural Networks
Authors: Kazemi Kianoosh , Laitala Juho , Azimi Iman , Liljeberg Pasi , Rahmani Amir M.
Published: August 2022

Accurate peak determination from noise-corrupted photoplethysmogram (PPG) signal is the basis for further analysis of physiological quantities such as heart rate. Conventional methods are designed for noise-free PPG signals and are insufficient for PPG signals with low signal-to-noise ratio (SNR). This paper focuses on enhancing PPG noise-resiliency and proposes a robust peak detection algorithm for PPG signals distorted due to noise and motion artifact. Our algorithm is based on convolutional neural networks (CNNs) with dilated convolutions. We train and evaluate the proposed method using a dataset collected via smartwatches under free-living conditions in a home-based health monitoring application. A data generator is also developed to produce noisy PPG data used for model training and evaluation. The method performance is compared against other state-of-the-art methods and is tested with SNRs ranging from 0 to 45 dB. Our method outperforms the existing adaptive threshold, transform-based, and machine learning methods. The proposed method shows overall precision, recall, and F1-score of 82%, 80%, and 81% in all the SNR ranges. In contrast, the best results obtained by the existing methods are 78%, 80%, and 79%. The proposed method proves to be accurate for detecting PPG peaks even in the presence of noise.
Smart E-Textiles: Overview of Components and Outlook
Authors: Ruckdashel Rebecca R. , Khadse Ninad , Park Jay Hoon
Published: August 2022

Smart textiles have gained great interest from academia and industries alike, spanning interdisciplinary efforts from materials science, electrical engineering, art, design, and computer science. While recent innovation has been promising, unmet needs between the commercial and academic sectors are pronounced in this field, especially for electronic-based textiles, or e-textiles. In this review, we aim to address the gap by (i) holistically investigating e-textiles’ constituents and their evolution, (ii) identifying the needs and roles of each discipline and sector, and (iii) addressing the gaps between them. The components of e-textiles—base fabrics, interconnects, sensors, actuators, computers, and power storage/generation—can be made at multiscale levels of textile, e.g., fiber, yarn, fabric, coatings, and embellishments. The applications, current state, and sustainable future directions for e-textile fields are discussed, which encompasses health monitoring, soft robotics, education, and fashion applications.
Recent Progress in Long-Range Brillouin Optical Correlation Domain Analysis
Authors: Wang Yahui , Zhang Mingjiang
Published: August 2022

Distributed optical fiber sensing technology has been widely applied in the areas of infrastructure health monitoring, national defense security, etc. The long-range high-spatial-resolution Brillouin optical correlation domain analysis (BOCDA) has extensive development and application prospects. In this paper, long-range BOCDAs are introduced and summarized. Several creative methods underpinning measurement range enlargement, including the interval enhancement of the adjacent correlation peak (CP), improvements in the signal-to-noise ratio, and the concurrent interrogation of multiple CPs, are discussed and experimentally verified, respectively. The main drawbacks in the present BOCDA schemes and avenues for future research and development have also been prospected.
A Novel Approach to Multi-Provider Network Slice Selector for 5G and Future Communication Systems
Authors: da Silva Douglas Chagas , Batista José Olimpio Rodrigues , de Sousa Marco Antonio Firmino , Mostaço Gustavo Marques , Monteiro Claudio de Castro , Bressan Graça , Cugnasca  Carlos Eduardo , Silveira Regina Melo
Published: August 2022

The Network Slice Selection Function (NSSF) in heterogeneous technology environments is a complex problem, which still does not have a fully acceptable solution. Thus, the implementation of new network selection strategies represents an important issue in development, mainly due to the growing demand for applications and scenarios involving 5G and future networks. This work presents an integrated solution for the NSSF problem, called the Network Slice Selection Function Decision-Aid Framework (NSSF DAF), which consists of a distributed solution in which a part is executed on the user’s equipment (for example, smartphones, Unmanned Aerial Vehicles, IoT brokers) functioning as a transparent service, and another at the Edge of the operator or service provider. It requires a low consumption of computing resources from mobile devices and offers complete independence from the network operator. For this purpose, protocols and software tools are used to classify slices, employing the following four multicriteria methods to aid decision making: VIKOR (Visekriterijumska Optimizacija i Kompromisno Resenje), COPRAS (Complex Proportional Assessment), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and Promethee II (Preference Ranking Organization Method for Enrichment Evaluations). The general objective is to verify the similarity among these methods and applications to the slice classification and selection process, considering a specific scenario in the framework. It also uses machine learning through the K-means clustering algorithm, adopting a hybrid solution in the implementation and operation of the NSSF service in multi-domain slicing environments of heterogeneous mobile networks. Testbeds were conducted to validate the proposed framework, mapping the adequate quality of service requirements. The results indicate a real possibility of offering a complete solution to the NSSF problem that can be implemented in Edge, in Core, or even in the 5G Radio Base Station itself, without the incremental computational cost of the end user’s equipment, allowing for an adequate quality of experience.
A New Phased-Array Magnetic Resonance Imaging Receive-Only Coil for HBO2 Studies
Authors: Mareyam Azma , Shank Erik , Wald Lawrence L. , Qin Michael K. , Bonmassar Giorgio
Published: August 2022

The paper describes a new magnetic resonance imaging (MRI) phased-array receive-only (Rx) coil for studying decompression sickness and disorders of hyperbaricity, including nitrogen narcosis. Functional magnetic resonance imaging (fMRI) is noninvasive, is considered safe, and may allow studying the brain under hyperbaric conditions. All of the risks associated with simultaneous MRI and HBO2 therapy are described in detail, along with all of the mitigation strategies and regulatory testing. One of the most significant risks for this type of study is a fire in the hyperbaric chamber caused by the sparking of the MRI coils as a result of high-voltage RF arcs. RF pulses at 128 MHz elicit signals from human tissues, and RF sparking occurs commonly and is considered safe in normobaric conditions. We describe how we built a coil for HBO2-MRI studies by modifying an eight-channel phased-array MRI coil with all of the mitigation strategies discussed. The coil was fabricated and tested with a unique testing platform that simulated the worst-case RF field of a three-Tesla MRI in a Hyperlite hyperbaric chamber at 3 atm pressure. The coil was also tested in normobaric conditions for image quality in a 3 T scanner in volunteers and SNR measurement in phantoms. Further studies are necessary to characterize the coil safety in HBO2/MRI.