bluuebunny/crossref_metadata_2025 huggingface dataset:
Strength and Microstructure of Geopolymer Based on Fly Ash and Metakaolin
Authors: Barbhuiya Salim , Pang Edmund
Published: May 2022

The production of Portland cement is widely regarded as a major source of greenhouse gas emissions. This contributes to 6–7% of total CO2 emissions, according to the International Energy Agency. As a result, several efforts have been made in recent decades to limit or eliminate the usage of Portland cement in concrete. Geopolymer has garnered a lot of attention among the numerous alternatives due to its early compressive strength, low permeability, high chemical resistance, and great fire-resistant behaviour. This study looks at the strength and microstructure of geopolymer based on fly ash and a combination of metakaolin and fly ash. Compressive strengths were measured at 7, 14, and 28 days, and microstructure was examined using SEM and XRD.
Composite Ski-Resort Registration Method Based on Laser Point Cloud Information
Authors: Wang Wenxin , Zhao Changming , Zhang Haiyang
Published: May 2022

The environment of ski resorts is usually complex and changeable, and there are few characteristic objects in the background, which creates many difficulties for the registration of ski-resort point cloud datasets. However, in the traditional iterative closest point (ICP) algorithm, two points need to have good initial positions, otherwise it is easy to get caught up in local optimizations in registration. Aiming at this problem, according to the topographic features of ski resorts, this paper put forward a ski-resort coarse registration method based on extraction, and matching between feature points is proposed to adjust the initial position of two point clouds. Firstly, the feature points of the common part of the point cloud datasets are extracted based on the SIFT algorithm; secondly, the Euclidean distance between the feature normal vectors is used as the pairing condition to complete the pairing between the feature points in the point cloud datasets; then, the feature point pair is purified by using the included angle of the normal vector; finally, in the process of coarse registration, the rotation matrix and translation vector between point clouds are solved by the unit quaternion method. Experiments demonstrate that the proposed coarse registration method based on the normal vector of feature points is helpful to the smooth completion of the subsequent fine registration process, avoids the phenomenon of falling into local optimization, and effectively completes the ski-resort point cloud registration.
A Discrete Dynamics Approach to a Tumor System
Authors: Saeed Tareq , Djeddi Kamel , Guirao Juan L. G. , Alsulami Hamed H. , Alhodaly Mohammed Sh.
Published: May 2022

In this paper, we present a cancer system in a continuous state as well as some numerical results. We present discretization methods, e.g., the Euler method, the Taylor series expansion method, and the Runge–Kutta method, and apply them to the cancer system. We studied the stability of the fixed points in the discrete cancer system using the new version of Marotto’s theorem at a fixed point; we prove that the discrete cancer system is chaotic. Finally, we present numerical simulations, e.g., Lyapunov exponents and bifurcations diagrams.
Actual Marine Atmospheric Pre-Corrosion Fatigue Performance of 7075-T73 Aluminum Alloy
Authors: Shi Laixin , Xiang Lin , Tao Jianquan , Chen Qiang , Liu Jun , Zhong Yong
Published: May 2022

Actual marine atmospheric pre-corrosion behavior and its effect on the fatigue performance of 7075-T73 aluminum alloy were studied by means of marine atmospheric outdoor exposure testing and fatigue testing. The surface and cross-sectional microstructures of aluminum alloy specimens after different numbers of days of exposure were analyzed. Localized pitting, and intergranular and exfoliation corrosion occurred during the outdoor exposure of aluminum alloy specimens in a marine atmosphere. The degree of severity of atmospheric corrosion increased with increasing duration of exposure. The effects of Fe-rich constituent particles (Al23CuFe4) and grain boundary precipitates (MgZn2) on the marine atmospheric corrosion behavior were discussed. In addition, when the exposure time was increased from 0 days to 15 days, the average fatigue life of aluminum alloy specimens decreased dramatically from about 125.16 × 104 cycles to 16.58 × 104 cycles. As the exposure time was further increased to 180 days, the average fatigue life slowly decreased to about 6.21 × 104 cycles. The fatigue fracture characteristics and the effect mechanism of marine atmospheric pre-corrosion on the fatigue life of 7075-T73 aluminum alloy were also analyzed.
The Multifunctions and Future Prospects of Endophytes and Their Metabolites in Plant Disease Management
Authors: Xia Yandong , Liu Junang , Chen Cang , Mo Xiuli , Tan Qian , He Yuan , Wang Zhikai , Yin Jia , Zhou Guoying
Published: May 2022

Endophytes represent a ubiquitous and magical world in plants. Almost all plant species studied by different researchers have been found to harbor one or more endophytes, which protect host plants from pathogen invasion and from adverse environmental conditions. They produce various metabolites that can directly inhibit the growth of pathogens and even promote the growth and development of the host plants. In this review, we focus on the biological control of plant diseases, aiming to elucidate the contribution and key roles of endophytes and their metabolites in this field with the latest research information. Metabolites synthesized by endophytes are part of plant disease management, and the application of endophyte metabolites to induce plant resistance is very promising. Furthermore, multi-omics should be more fully utilized in plant–microbe research, especially in mining novel bioactive metabolites. We believe that the utilization of endophytes and their metabolites for plant disease management is a meaningful and promising research direction that can lead to new breakthroughs in the development of more effective and ecosystem-friendly insecticides and fungicides in modern agriculture.
Impact of the Introduction of a Two-Step Laboratory Diagnostic Algorithm in the Incidence and Earlier Diagnosis of Clostridioides difficile Infection
Authors: Sopena Nieves , Wang-Wang Jun Hao , Casas Irma , Mateu Lourdes , Castellà Laia , García-Quesada María José , Gutierrez Sara , Llibre Josep M. , Pedro-Botet M. Luisa , Fernandez-Rivas Gema
Published: May 2022

Our aim was to determine changes in the incidence of CD infection (CDI) following the introduction of a two-step diagnostic algorithm and to analyze CDI cases diagnosed in the study period. We retrospectively studied CDI (January 2009 to July 2018) in adults diagnosed by toxin enzyme immunoassay (EIA) (2009–2012) or toxin-EIA + polymerase chain reaction (PCR) algorithm (2013 onwards). A total of 443 patients with a first episode of CDI were included, 297 (67.1%) toxin-EIA-positive and 146 (32.9%) toxin-EIA-negative/PCR-positive were only identified through the two-step algorithm including the PCR test. The incidence of CDI increased from 0.9 to 4.7/10,000 patient-days (p < 0.01) and 146 (32.9%) toxin-negative CDI were diagnosed. Testing rate increased from 24.4 to 59.5/10,000 patient-days (p < 0.01) and the percentage of positive stools rose from 3.9% to 12.5% (p < 0.01). CD toxin-positive patients had a higher frequency of severe presentation and a lower rate of immunosuppressive drugs and inflammatory bowel disease. Mortality (16.3%) was significantly higher in patients with hematological neoplasm, intensive care unit admission and complicated disease. Recurrences (14.9%) were significantly higher with proton pump inhibitor exposure. The two-step diagnostic algorithm facilitates earlier diagnosis, potentially impacting patient outcomes and nosocomial spread. CD-toxin-positive patients had a more severe clinical presentation, probably due to increased CD bacterial load with higher toxin concentration. This early and easy marker should alert clinicians of potentially more severe outcomes.
Comparison of Multivariate ANOVA-Based Approaches for the Determination of Relevant Variables in Experimentally Designed Metabolomic Studies
Authors: Pérez-Cova Miriam , Platikanov Stefan , Stoll Dwight R. , Tauler Romà , Jaumot Joaquim
Published: May 2022

The use of chemometric methods based on the analysis of variances (ANOVA) allows evaluation of the statistical significance of the experimental factors used in a study. However, classical multivariate ANOVA (MANOVA) has a number of requirements that make it impractical for dealing with metabolomics data. For this reason, in recent years, different options have appeared that overcome these limitations. In this work, we evaluate the performance of three of these multivariate ANOVA-based methods (ANOVA simultaneous component analysis—ASCA, regularized MANOVA–rMANOVA, and Group-wise ANOVA-simultaneous component analysis—GASCA) in the framework of metabolomics studies. Our main goals are to compare these various ANOVA-based approaches and evaluate their performance on experimentally designed metabolomic studies to find the significant factors and identify the most relevant variables (potential markers) from the obtained results. Two experimental data sets were generated employing liquid chromatography coupled to mass spectrometry (LC-MS) with different complexity in the design to evaluate the performance of the statistical approaches. Results show that the three considered ANOVA-based methods have a similar performance in detecting statistically significant factors. However, relevant variables pointed by GASCA seem to be more reliable as there is a strong similarity with those variables detected by the widely used partial least squares discriminant analysis (PLS-DA) method.
Insights on the Bioaccessibility of Natural Pigments from Diatom Chaetoceros calcitrans
Authors: Nascimento Tatiele C. do , Pinheiro Pricila N. , Fernandes Andrêssa S. , Caetano Patrícia A. , Jacob-Lopes Eduardo , Zepka Leila Q.
Published: May 2022

This study aimed to investigate the bioaccessibility of carotenoids and chlorophylls from the biomass of microalgae Chaetoceros calcitrans. The samples were submitted to an in vitro digestion protocol, and the compounds were determined by HPLC-PDA-MS/MS. A total of 13 compounds were identified in all tests. After in vitro digestion, the relative bioaccessibility of carotenoids and chlorophylls ranged from 4 to 58%. The qualitative profile of carotenoids reflected the initial sample, with all-E-zeaxanthin (57.2%) being the most bioaccessible compound, followed by all-E-neochrome (31.26%), the latter being reported for the first time in the micellar fraction. On the other hand, among the chlorophylls only pheophytin a (15.01%) was bioaccessible. Furthermore, a chlorophyll derivative (Hydroxypheophytin a’) was formed after in vitro digestion. Considering all compounds, xanthophylls (12.03%) and chlorophylls (12.22%) were significantly (p < 0.05) more bioaccessible than carotenes (11.22%). Finally, the considerable individual bioaccessibilities found, especially for zeaxanthin, demonstrate the bioactive potential of this bioresource. However, the large reduction in the totality of compounds after in vitro digestion suggests that additional technological strategies should be explored in the future to increase the efficiency of micellarization and enhance its bioactive effects.
Extra Virgin Olive Oil Secoiridoids Modulate the Metabolic Activity of Dacarbazine Pre-Treated and Treatment-Naive Melanoma Cells
Authors: Kugić Azra , Dabelić Sanja , Brala Cvijeta Jakobušić , Dabelić Nina , Barbarić Monika
Published: May 2022

Nowadays, many individuals, whether healthy or diagnosed with disease, tend to expose themselves to various easily accessible natural products in hopes of benefiting their health and well-being. Mediterranean populations have traditionally used olive oil not only in nutrition but also in cosmetics, including skincare. In this study, the phenolic profile—composed of twelve compounds altogether, including the secoiridoids oleocanthal (OCAL) and oleacein (OCEIN)—of extra virgin olive oil (EVOO) from autochthonous cultivars from Croatia was determined using 1H qNMR spectroscopy and HPLC-DAD analysis, and its biological activity was investigated in melanoma cell lines. The EVOO with the highest OCEIN content had the strongest anti-cancer activity in A375 melanoma cells and the least toxic effect on the non-cancerous keratocyte cell line (HaCaT). On the other hand, pure OCAL was shown to be more effective and safer than pure OCEIN. Post-treatment with any of the EVOO phenolic extracts (EVOO-PEs) enhanced the anti-cancer effect of the anti-cancerous drug dacarbazine (DTIC) applied in pre-treatment, while they did not compromise the viability of non-cancerous cells. The metastatic melanoma A375M cell line was almost unresponsive to the EVOO-PEs themselves, as well as to pure OCEIN and OCAL. Our results demonstrate that olive oils and/or their compounds may have a potentially beneficial effect on melanoma treatment. However, their usage can be detrimental or futile, especially in healthy cells, due to inadequately applied concentrations/combinations or the presence of resistant cells.
Anti-Inflammatory Effects of Mitrephora sirikitiae Leaf Extract and Isolated Lignans in RAW 264.7 Cells
Authors: Mangmool Supachoke , Limpichai Chayaporn , Han Khine Kyi , Reutrakul Vichai , Anantachoke Natthinee
Published: May 2022

Mitrephora sirikitiae Weeras., Chalermglin & R.M.K. Saunders has been reported as a rich source of lignans that contribute to biological activities and health benefits. However, cellular anti-inflammatory effects of M. sirikitiae leaves and their lignan compounds have not been fully elucidated. Therefore, this study aimed to investigate the anti-inflammatory activities of methanol extract of M. sirikitiae leaves and their lignan constituents on lipopolysaccharide (LPS)-induced inflammation in RAW 264.7 mouse macrophage cells. Treatment of RAW 264.7 cells with the methanol extract of M. sirikitiae leaves and its isolated lignans, including (−)-phylligenin (2) and 3′,4-O-dimethylcedrusin (6) significantly decreased LPS-induced prostaglandin E2 (PGE2) and nitric oxide (NO) productions. These inhibitory effects of the extract and isolated lignans on LPS-induced upregulation of PGE2 and NO productions were derived from the suppression of cyclooxygenase 2 (COX-2) and inducible nitric oxide synthase (iNOS) production, respectively. In addition, treatment with 2-(3,4-dimethoxyphenyl)-6-(3,5-dimethoxyphenyl)-3,7-dioxabicyclo[3.3.0]octane (3) and mitrephoran (5) was able to suppress LPS-induced tumor necrosis factor alpha (TNF-α) secretion and synthesis in RAW 264.7 cells. These results demonstrated that M. sirikitiae leaves and some isolated lignans exhibited potent anti-inflammatory activity through the inhibition of secretion and synthesis of PGE2, NO, and TNF-α.
Computational Modelling and Sustainable Synthesis of a Highly Selective Electrochemical MIP-Based Sensor for Citalopram Detection
Authors: Rebelo Patrícia , Pacheco João G. , Voroshylova Iuliia V. , Seguro Isabel , Cordeiro Maria Natália D. S. , Delerue-Matos Cristina
Published: May 2022

A novel molecularly imprinted polymer (MIP) has been developed based on a simple and sustainable strategy for the selective determination of citalopram (CTL) using screen-printed carbon electrodes (SPCEs). The MIP layer was prepared by electrochemical in situ polymerization of the 3-amino-4 hydroxybenzoic acid (AHBA) functional monomer and CTL as a template molecule. To simulate the polymerization mixture and predict the most suitable ratio between the template and functional monomer, computational studies, namely molecular dynamics (MD) simulations, were carried out. During the experimental preparation process, essential parameters controlling the performance of the MIP sensor, including CTL:AHBA concentration, number of polymerization cycles, and square wave voltammetry (SWV) frequency were investigated and optimized. The electrochemical characteristics of the prepared MIP sensor were evaluated by both cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) techniques. Based on the optimal conditions, a linear electrochemical response of the sensor was obtained by SWV measurements from 0.1 to 1.25 µmol L−1 with a limit of detection (LOD) of 0.162 µmol L−1 (S/N = 3). Moreover, the MIP sensor revealed excellent CTL selectivity against very close analogues, as well as high imprinting factor of 22. Its applicability in spiked river water samples demonstrated its potential for adequate monitoring of CTL. This sensor offers a facile strategy to achieve portability while expressing a willingness to care for the environment.
Antioxidant Properties and Aldehyde Reactivity of PD-L1 Targeted Aryl-Pyrazolone Anticancer Agents
Authors: Leleu-Chavain Natascha , Regnault Romain , Ahouari Hania , Le Biannic Raphaël , Kouach Mostafa , Klupsch Frédérique , Magnez Romain , Vezin Hervé , Thuru Xavier , Bailly Christian , Goossens Jean-François , Millet Régis
Published: May 2022

Small molecules targeting the PD-1/PD-L1 checkpoint are actively searched to complement the anticancer arsenal. Different molecular scaffolds have been reported, including phenyl-pyrazolone derivatives which potently inhibit binding of PD-L1 to PD-1. These molecules are structurally close to antioxidant drug edaravone (EDA) used to treat amyotrophic lateral sclerosis. For this reason, we investigated the capacity of five PD-L1-binding phenyl-pyrazolone compounds (1–5) to scavenge the formation of oxygen free radicals using electron spin resonance spectroscopy with DPPH/DMPO probes. In addition, the reactivity of the compounds toward the oxidized base 5-formyluracil (5fU) was assessed using chromatography coupled to mass spectrometry and photodiode array detectors. The data revealed that the phenyl-pyrazolone derivatives display antioxidant properties and exhibit a variable reactivity toward 5fU. Compound 2 with a N-dichlorophenyl-pyrazolone moiety cumulates the three properties, being a potent PD-L1 binder, a robust antioxidant and an aldehyde-reactive compound. On the opposite, the adamantane derivative 5 is a potent PD-L1 binding with a reduced antioxidant potential and no aldehyde reactivity. The nature of the substituent on the phenyl-pyrazolone core modulates the antioxidant capacity and reactivity toward aromatic aldehydes. The molecular signature of the compound can be adapted at will, to confer additional properties to these PD-L1 binders.
In-Situ Fabricating V2O5/TiO2-Carbon Heterojunction from Ti3C2 MXene as Highly Active Visible-Light Photocatalyst
Authors: Xu Wentao , Shu Guoqiang , Zhang Shihui , Song Lei , Ma Kui , Yue Hairong
Published: May 2022

Titanium dioxide is a mainstream photocatalyst, but it still confronts great obstacles of poor visible light absorption and rapid recombination rate of photogenerated carriers. Herein, we describe the design of a highly active visible-light photocatalytic system of graphited carbon layers anchored V2O5/TiO2 heterojunctions derived from Ti3C2 MXene, which demonstrates about 4.58 and 2.79 times higher degradation activity of MB under visible light (λ > 420 nm) than pure V2O5 and TiO2-carbon. Combined with the characterization results, the formed V2O5/TiO2 heterojunction promotes the separation of photogenerated carriers, while the graphitized carbon derived from MXene acts as an electronic reservoir to enhance the absorption of visible light. The ESR results show that superoxide radicals and hydroxyl radicals are the main active species in the reaction system. Therefore, we propose a possible mechanism model to provide a feasible idea for the subsequent design of high-efficiency photocatalysts for environmental treatment.
Effect of Nanoparticles on the Thermal Stability and Reaction Kinetics in Ionic Nanofluids
Authors: Svobodova-Sedlackova Adela , Huete-Hernández Sergio , Calderón Alejandro , Barreneche Camila , Gamallo Pablo , Fernandez Ana Inés
Published: May 2022

Nowadays, the incorporation of nanoparticles into thermal fluids has become one of the most suitable strategies for developing high-performance fluids. An unconventional improvement of thermo–physical properties was observed with the addition of 1% wt. of nanoparticles in different types of fluids, such as molten salts, allowing for the design of more thermally efficient systems using nanofluids. Despite this, there is a lack of knowledge about the effect that nanoparticles produce on the thermal stability and the decomposition kinetics of the base fluid. The present study performs IR- and UV-vis spectroscopy along with thermogravimetric analysis (TGA) of pure nitrate and nitrate based nanofluids with the presence of SiO2 and Al2O3 nanoparticles (1% wt.). The results obtained support that nanoparticles accelerate the nitrate to nitrite decomposition at temperatures below 500 °C (up to 4%), thus confirming the catalytic role of nanoparticles in nanofluids.
The Effect of Accommodation on Peripheral Refraction under Two Illumination Conditions
Authors: van Ginkel Raquel , Mechó María , Cardona Genis , González-Méijome José M.
Published: May 2022

The clinical importance of peripheral refraction as a function of accommodation has become increasingly evident in the last years with special attention given to myopia control. Low order ocular aberrations were measured with a Hartmann–Shack aberrometer in a sample of 28 young emmetropic subjects. A stationary Maltese cross was presented at 2.5 D and 5.0 D of accommodative demand and at 0°, 10° and 20° of eccentricity in the horizontal visual field under two different illumination conditions (white and red light). Wavefront data for a 3 mm pupil diameter were analyzed in terms of the vector components of refraction (M, J0 and J45) and the relative peripheral refractive error (RPRE) was calculated. M was myopic at both accommodative demands and showed a statistically significant myopic increase with red illumination. No significant change in J0 and J45 was found with accommodation nor between illumination conditions. However, J0 increased significantly with eccentricity, exhibiting a nasal-temporal asymmetry. The RPRE was myopic at both accommodation demands and showed a statistically significant hyperopic shift at 20° in the nasal retina. The use of red light introduced statistically and clinically significant changes in M, explained by the variation of the ocular focal length under a higher wavelength illumination, increasing the experimental accommodative demand. These findings may be of relevance for research exploring peripheral refraction under accommodation, as the choice of target illumination is not trivial.
The Status and Future of Color Transparency and Nuclear Filtering
Authors: Jain Pankaj , Pire Bernard , Ralston John P.
Published: May 2022

Fourty years after its introduction, the phenomenon of color transparency remains a domain of controversial interpretations of experimental data. In this review, present evidence for or against color transparency manifestation in various exclusive hard scattering reactions is presented. The nuclear transparency experiments reveal whether short-distance processes dominate a scattering amplitude at some given kinematical point. We plead for a new round of nuclear transparency measurements in a variety of experimental set-ups, including near-forward exclusive reactions related to generalized parton distribution (GPD) physics and near-backward exclusive reactions related to transition distribution amplitudes (TDA) physics.
A Review on the Possibilities and Challenges of Today’s Soil and Soil Surface Assessment Techniques in the Context of Process-Based Soil Erosion Models
Authors: Epple Lea , Kaiser Andreas , Schindewolf Marcus , Bienert Anne , Lenz Jonas , Eltner Anette
Published: May 2022

To investigate relevant processes as well as to predict the possible impact of soil erosion, many soil erosion modelling tools have been developed. The most productive development of process-based models took place at the end of the 20th century. Since then, the methods available to observe and measure soil erosion features as well as methods to inter- and extrapolate such data have undergone rapid development, e.g., photogrammetry, light detection and ranging (LiDAR) and sediment tracing are now readily available methods, which can be applied by a broader community with lower effort. This review takes 13 process-based soil erosion models and different assessment techniques into account. It shows where and how such methods were already implemented in soil erosion modelling approaches. Several areas were found in which the models miss the capability to fully implement the information, which can be drawn from the now-available observation and data preparation methods. So far, most process-based models are not capable of implementing cross-scale erosional processes and can only in parts profit from the available resolution on a temporal and spatial scale. We conclude that the models’ process description, adaptability to scale, parameterization, and calibration need further development. The main challenge is to enhance the models, so they are able to simulate soil erosion processes as complex as they need to be. Thanks to the progress made in data acquisition techniques, achieving this aim is closer than ever, if models are able to reap the benefit.
State of the Vietnamese Coast—Assessing Three Decades (1986 to 2021) of Coastline Dynamics Using the Landsat Archive
Authors: Lappe Ronja , Ullmann Tobias , Bachofer Felix
Published: May 2022

Vietnam’s 3260 km coastline is densely populated, experiences rapid urban and economic growth, and faces at the same time a high risk of coastal hazards. Satellite archives provide a free and powerful opportunity for long-term area-wide monitoring of the coastal zone. This paper presents an automated analysis of coastline dynamics from 1986 to 2021 for Vietnam’s entire coastal zone using the Landsat archive. The proposed method is implemented within the cloud-computing platform Google Earth Engine to only involve publicly and globally available datasets and tools. We generated annual coastline composites representing the mean-high water level and extracted sub-pixel coastlines. We further quantified coastline change rates along shore-perpendicular transects, revealing that half of Vietnam’s coast did not experience significant change, while the remaining half is classified as erosional (27.7%) and accretional (27.1%). A hotspot analysis shows that coastal segments with the highest change rates are concentrated in the low-lying deltas of the Mekong River in the south and the Red River in the north. Hotspots with the highest accretion rates of up to +47 m/year are mainly associated with the construction of artificial coastlines, while hotspots with the highest erosion rates of −28 m/year may be related to natural sediment redistribution and human activity.
LoRaCog: A Protocol for Cognitive Radio-Based LoRa Network
Authors: Salika Firas , Nasser Abbass , Mroue Maxime , Parrein Benoît , Mansour Ali
Published: May 2022

In this paper, we propose a new protocol called LoRaCog to introduce the concept of Cognitive Radio (CR) in the LoRa network. LoRaCog will enable access to a wider spectrum than that of LoRaWAN by using the unutilized spectrum and thus has better efficiency without impacting the end devices’ battery consumption. LoRa networks are managed by LoRaWAN protocol and operate on the unlicensed Industrial, Scientific and Medical (ISM) band. LoRaWAN is one of thriving protocols for Low-Power Wide-Area Networks (LPWAN) implemented for the Internet of Things (IoT). With the growing demand for IoT, the unlicensed spectrum is expected to be congested, unlike the licensed spectrum, which is not fully utilized. This can be fairly balanced by applying CR to the LoRa network, where the End Devices (EDs) may change the operating channel opportunistically over the free/available licensed spectrum. Spectrum sensing, channel selection and channel availability relevance become essential features to be respected by the proposed protocol. The main objective of adding CR to LoRaWAN is reducing the congestion and maintaining LoRaWAN’s suitability for battery-operated devices. This is achieved by modifying LoRaWAN components such as the ED receive window RX2 rearrangement, spectrum sensing functionality by gateway (GW) for identifying unused channels, and reaching a decision on the unused channels by network server (NS). These changes will create LoRaCog meeting spectrum efficiency and maintain the same level of battery consumption as in LoRaWAN. Numerical simulations show a significant decrease in the rejected packet rate (more than 50%) with LoRaCog when more EDs use cognitive channels. As the results prove, LoRaWAN can reach above 50% rejected packets for the simulated environment versus 24% rejection for LoRaCog using only one additional channel (means total two channels). This means that the system can eliminate rejected packets almost completely when operating over the possible many channels. As well, these results show the flexibility in the system to utilize the available frequencies in an efficient and fair way. The results also reveal that a lower number of GWs is needed for LoRaCog from LoRaWAN to cover the same area.
Detection of Mechanical Failures in Industrial Machines Using Overlapping Acoustic Anomalies: A Systematic Literature Review
Authors: Qurthobi Ahmad , Maskeliūnas Rytis , Damaševičius Robertas
Published: May 2022

One of the most important strategies for preventative factory maintenance is anomaly detection without the need for dedicated sensors for each industrial unit. The implementation of sound-data-based anomaly detection is an unduly complicated process since factory-collected sound data are frequently corrupted and affected by ordinary production noises. The use of acoustic methods to detect the irregularities in systems has a long history. Unfortunately, limited reference to the implementation of the acoustic approach could be found in the failure detection of industrial machines. This paper presents a systematic review of acoustic approaches in mechanical failure detection in terms of recent implementations and structural extensions. The 52 articles are selected from IEEEXplore, Science Direct and Springer Link databases following the PRISMA methodology for performing systematic literature reviews. The study identifies the research gaps while considering the potential in responding to the challenges of the mechanical failure detection of industrial machines. The results of this study reveal that the use of acoustic emission is still dominant in the research community. In addition, based on the 52 selected articles, research that discusses failure detection in noisy conditions is still very limited and shows that it will still be a challenge in the future.
A Dynamic Calibration of Optical Fiber DTS Measurements Using PEST and Reference Thermometers
Authors: Ghafoori Yaser , Vidmar Andrej , Kryžanowski Andrej
Published: May 2022

Temperature measurements are widely used in structural health monitoring. Optical fiber distributed temperature sensors (DTS) are developed, based on Raman spectroscopy, to measure temperature with relatively high accuracy and short temporal and spatial resolutions. DTS systems provide an extensive number of temperature measurements along the entire length of an optical fiber that can be extended to tens of kilometers. The efficiency of the temperature measurement strongly depends on the calibration of the DTS data. Although DTS systems internally calibrate the data, manual calibration techniques were developed to achieve more accurate results. Manual calibration employs reference sections or points with known temperatures and the DTS scattering data to estimate the calibration parameters and calculate temperature along the optical fiber. In some applications, manual calibration is subjected to some shortages, based on the proposed fiber installation configuration and continuity of calibration. In this article, the manual calibration approach was developed using the model-independent Parameters Estimation (PEST), together with the external temperature sensors as references for the DTS system. The proposed method improved manual calibration in terms of installation configuration, continuity of dynamic calibration, and estimation of the calibration parameters.
Cross Deep Learning Method for Effectively Detecting the Propagation of IoT Botnet
Authors: Wazzan Majda , Algazzawi Daniyal , Albeshri Aiiad , Hasan Syed , Rabie Osama , Asghar Muhammad Zubair
Published: May 2022

In recent times, organisations in a variety of businesses, such as healthcare, education, and others, have been using the Internet of Things (IoT) to produce more competent and improved services. The widespread use of IoT devices makes our lives easier. On the other hand, the IoT devices that we use suffer vulnerabilities that may impact our lives. These unsafe devices accelerate and ease cybersecurity attacks, specifically when using a botnet. Moreover, restrictions on IoT device resources, such as limitations in power consumption and the central processing unit and memory, intensify this issue because they limit the security techniques that can be used to protect IoT devices. Fortunately, botnets go through different stages before they can start attacks, and they can be detected in the early stage. This research paper proposes a framework focusing on detecting an IoT botnet in the early stage. An empirical experiment was conducted to investigate the behaviour of the early stage of the botnet, and then a baseline machine learning model was implemented for early detection. Furthermore, the authors developed an effective detection method, namely, Cross CNN_LSTM, to detect the IoT botnet based on using fusion deep learning models of a convolutional neural network (CNN) and long short-term memory (LSTM). According to the conducted experiments, the results show that the suggested model is accurate and outperforms some of the state-of-the-art methods, and it achieves 99.7 accuracy. Finally, the authors developed a kill chain model to prevent IoT botnet attacks in the early stage.
Smart Sensorization Using Propositional Dynamic Logic
Authors: Merino Salvador , Burrieza Alfredo , Guzman Francisco , Martinez Javier
Published: May 2022

The current high energy prices pose a serious challenge, especially in the domestic economy. In this respect, one of the main problems is obtaining domestic hot water. For this reason, this article develops a heating system applied to a conventional water tank in such a way as to minimize the necessary energy supply by converting it, under certain circumstances, into atmospheric. For this purpose, the domotic system has been equipped with sensors that automate the pressurization of the compartment and solenoid valves that regulate the external water supply. This design, to which different level sensors are applied, sends the information in real time to an artificial intelligence system, by means of deductive control, which recognizes the states of the system. This work shows the introduction of an extension of propositional dynamic logic in the field of energy efficiency. Thanks to this formalism, a qualitative control of the program variables is achieved by incorporating qualitative reasoning tools. On the other hand, it solves preventive maintenance systems through the early detection of faults in the installation. This research has led to the patenting of an intelligent domestic hot water system that considerably reduces energy consumption by setting disjointed heating intervals that, powered by renewable or non-renewable sources, are controlled by a propositional dynamic logic.
Real-Time Monitoring of SO2 Emissions Using a UV Camera with Built-in NO2 and Aerosol Corrections
Authors: Xiong Yuanhui , Wu Kuijun , Yu Guangbao , Chen Zhenwei , Liu Linmei , Li Faquan
Published: May 2022

Nitrogen dioxide (NO2) absorption correction of the sulfur dioxide (SO2) camera was demonstrated for the first time. The key to improving the measurement accuracy is to combine a differential optical absorption spectroscopy (DOAS) instrument with the SO2 camera for the real-time NO2 absorption correction and aerosol scattering correction. This method performs NO2 absorption correction by the correlation between the NO2 column density measurement of the DOAS and the NO2 optical depth of the corresponding channel from the SO2 camera at a narrow wavelength window around 310 and 310 nm. The error of correction method is estimated through comparison with only using the second channel of the traditional SO2 camera to correct for aerosol scattering and it can be reduced by 11.3% after NO2 absorption corrections. We validate the correction method through experiments and demonstrate it to be of greatly improved accuracy. The result shows that the ultraviolet (UV) SO2 camera system with NO2 absorption corrections appears to have great application prospects as a technology for visualized real-time monitoring of SO2 emissions.
SRE_BBC: A Self-Adaptive Security Enabled Requirements Engineering Approach for SLA Smart Contracts in Blockchain-Based Cloud Systems
Authors: Singh Irish , Lee Seok-Won
Published: May 2022

Current blockchain-based cloud (BBC) systems have several security vulnerabilities regarding smart contracts (SC), and several attacks have been reported recently. The SC development lacks standard design processes that follow software lifecycle principles to model secure SC. Secondly, the security mechanisms in the SC are not constantly evolved to resist evolving adversary attacks. BBC systems lack self-adaptive security capability to make spontaneous decisions when adversarial attacks are encountered. To build a self-adaptive secure BBC system that follows standard software development lifecycle principles to model secure SC, we propose the so-called self-adaptive security RE_BBC framework. The framework would utilize the MAPE-BBC adaptation loop to make decisions internally based on the threat models, goal models, and service level agreement (SLA) SC security specifications. The framework identifies vulnerabilities and threats and takes precautionary measures using self-adaptive SC agents. We validated the proposed methodology theoretically and empirically, and statistically proved the research questions and hypothesis using the t-test and Mann–Whitney U test. Subsequently, we compare our proposed approach with the Security Quality Requirements Engineering approach (SQUARE). The feasibility results and the replicated study results indicate that the proposed approach outperformed the SQUARE approach in terms of artifacts quality, self-adaptive security evaluation quality, efficiency in response time, complexity, and usefulness of the proposed approach for the Healthcare Data Management (HDM) system. SC security developers can immensely benefit from our proposed methodology. They need not reengineer SC from scratch; depending on their security needs and plan, the contract can be adapted to execute a new plan.
MIS-Like Structures with Silicon-Rich Oxide Films Obtained by HFCVD: Their Response as Photodetectors
Authors: Mendoza Conde Gabriel Omar , Luna López José Alberto , Hernández Simón Zaira Jocelyn , Hernández de la Luz José Álvaro David , García Salgado Godofredo , Gastellou Hernández Erick , Martínez Hernández Haydee Patricia , Flores Méndez Javier
Published: May 2022

MIS-type structures composed of silicon-rich oxide (SRO), thin films deposited by hot filament chemical vapor deposition (HFCVD), show interesting I-V and I-t properties under white light illumination and a response as photodetectors. From electrical measurements, it was found that at a reverse bias of −4 V, the illumination current increased by up to three orders of magnitude relative to the dark current, which was about 82 nA, while the photogenerated current reached a value of 25 μA. The reported MIS structure with SRO as the dielectric layer exhibited a hopping conduction mechanism, and an ohmic conduction mechanism was found with low voltage. I-t measurements confirmed the increased photogenerated current. Furthermore, the MIS structure, characterized by current-wavelength (I-λ) measurements, exhibited a maximum responsivity value at 254 mA/W, specific detectivity (D*) at 2.21 × 1011 cm Hz1/2 W−1, and a noise equivalent power (NEP) of 49 pW at a wavelength of 535 nm. The structure exhibited good switching behavior, with rise and fall times between 120 and 150 ms, respectively. These rise and decay times explain the generation and recombination of charge carriers and the trapping and release of traps, respectively. These results make MIS-type structures useful as photodetectors in the 420 to 590 nm range.
XDMOM: A Real-Time Moving Object Detection System Based on a Dual-Spectrum Camera
Authors: Shi Baoquan , Gu Weichen , Sun Xudong
Published: May 2022

A low-cost and power-efficient video surveillance system, named XDMOM, is developed for real-time moving object detection outdoors or in the wild. The novel system comprises four parts: imaging subsystem, video processing unit, power supply, and alarm device. The imaging subsystem, which consists of a dual-spectrum camera and rotary platform, can realize 360-degree and all-day monitoring. The video processing unit uses a power-efficient NVIDIA GeForce GT1030 chip as the processor, which ensures the power consumption of the whole system maintains a low level of 60~70 W during work. A portable lithium battery is employed to supply power so that the novel system can be used anywhere. The work principle is also studied in detail. Once videos are recorded, the single-stage neural network YOLOv4-tiny is employed to detect objects in a single frame, and an adaptive weighted moving pipeline filter is developed to remove pseudo-targets in the time domain, thereby reducing false alarms. Experimental results show that the overall correct alarm rate of the novel system could reach 85.17% in the daytime and 81.79% at night when humans are monitored in real outdoor environments. The good performance of the novel system is demonstrated by comparison with state-of-the-art video surveillance systems.
DRiPLOF: An RPL Extension for Multi-Interface Wireless Sensor Networks in Interference-Prone Environments
Authors: Elsas Robbe , De Poorter Eli , Hoebeke Jeroen
Published: May 2022

The Routing Protocol for Low-power and Lossy Networks (RPL) is a popular routing layer protocol for multi-hop Wireless Sensor Networks (WSNs). However, typical RPL configurations are based on decade-old assumptions, leading to a mismatch with: (1) advances in wireless hardware; and (2) growing wireless contention. To soften the impact of external stressors (i.e., jamming and interference), we extended RPL to exploit the capabilities of modern multi-interfaced wireless devices. More specifically, our main contribution is the design, development, and evaluation of a novel RPL Objective Function (OF) which, through simulations, is compared to traditional single-interface approaches and a state-of-the-art multi-interface approach. We examine two scenarios, with and without the injection of jamming, respectively. Our proposed OF is shown to outperform, or otherwise perform similar to, all alternatives considered. In normal conditions, it auto-selects the best interface whilst incurring negligible protocol overhead. In our jamming simulations, it provides stable end-to-end delivery ratios exceeding 90%, whereas the closest alternative averages 65% and is considerably less stable. Given we have open-sourced our development codebase, our solution is an ideal candidate for adoption by RPL deployments that expect to suffer interference from competing technologies or are unable to select the best radio technology a priori.
Tire Speckle Interference Bubble Defect Detection Based on Improved Faster RCNN-FPN
Authors: Yang Shihao , Jiao Dongmei , Wang Tongkun , He Yan
Published: May 2022

With the development of neural networks, object detection based on deep learning is developing rapidly, and its applications are gradually increasing. In the tire industry, detecting speckle interference bubble defects of tire crown has difficulties such as low image contrast, small object scale, and large internal differences of defects, which affect the detection precision. To solve these problems, we propose a new feature pyramid network based on Faster RCNN-FPN. It can fuse features across levels and directions to improve small object detection and localization, and increase object detection precision. The method has proven its effectiveness through cross-validation experiments. On a tire crown bubble defect dataset, the mAP [0.5:0.95] increased by 2.08% and the AP0.5 increased by 2.4% over the original network. The results show that the improved network significantly improves detecting tire crown bubble defects.
Deep Q-Learning in Robotics: Improvement of Accuracy and Repeatability
Authors: Sumanas Marius , Petronis Algirdas , Bucinskas Vytautas , Dzedzickis Andrius , Virzonis Darius , Morkvenaite-Vilkonciene Inga
Published: May 2022

Recent industrial robotics covers a broad part of the manufacturing spectrum and other human everyday life applications; the performance of these devices has become increasingly important. Positioning accuracy and repeatability, as well as operating speed, are essential in any industrial robotics application. Robot positioning errors are complex due to the extensive combination of their sources and cannot be compensated for using conventional methods. Some robot positioning errors can be compensated for only using machine learning (ML) procedures. Reinforced machine learning increases the robot’s positioning accuracy and expands its implementation capabilities. The provided methodology presents an easy and focused approach for industrial in situ robot position adjustment in real-time during production setup or readjustment cases. The scientific value of this approach is a methodology using an ML procedure without huge external datasets for the procedure and extensive computing facilities. This paper presents a deep q-learning algorithm applied to improve the positioning accuracy of an articulated KUKA youBot robot during operation. A significant improvement of the positioning accuracy was achieved approximately after 260 iterations in the online mode and initial simulation of the ML procedure.
General Mass Property Measurement Equipment for Large-Sized Aircraft
Authors: Zhang Xiaolin , Yu Hang , Tang Wenyan , Wang Jun
Published: May 2022

The accurate measurement of aircraft mass properties, such as the mass, centroid, and moment of inertia (MOI), plays a key role in the precise control of aircraft. In order to obtain high-precision information on the parameters of the mass, centroid, and MOI of an aircraft using a single instrument, an integrated mass property measurement system was developed in this study by analyzing and comparing the latest technologies, especially the function-switching device, which switches the measurement states between the center of mass and the MOI. The purpose of mass property measurement was achieved through single clamping. In addition, the system has strong versatility and expansion and can be used with different tooling or adapter rings to measure the mass properties of aircraft with different shapes. In this paper, the main mechanical structure of the measurement system, the measurement method of relevant mass parameters, and the solution method of the transformation matrix are introduced, and the standard parts and the aircraft were verified experimentally. The test results showed that the mass measurement accuracy was 0.03%, the centroid measurement error was within ±0.2 mm, and the measurement accuracy of the MOI was within 0.2%, all of which meet the high-precision measurement requirements for the mass properties.