bluuebunny/crossref_metadata_2025 huggingface dataset:
Increased Leaf Bacterial Network Complexity along the Native Plant Diversity Gradient Facilitates Plant Invasion?
Authors: Du Xiang-Deng , Wang Jiang , Shen Congcong , Wang Jichen , Jing Zhongwang , Huang Li-Nan , Luo Zhen-Hao , Ge Yuan
Published: March 2023

Understanding the mechanisms of biological invasion is critical to biodiversity protection. Previous studies have produced inconsistent relationships between native species richness and invasibility, referred to as the invasion paradox. Although facilitative interactions among species have been proposed to explain the non-negative diversity–invasibility relationship, little is known about the facilitation of plant-associated microbes in invasions. We established a two-year field biodiversity experiment with a native plant species richness gradient (1, 2, 4, or 8 species) and analyzed the effects of community structure and network complexity of leaf bacteria on invasion success. Our results indicated a positive relationship between invasibility and network complexity of leaf bacteria of the invader. Consistent with previous studies, we also found that native plant species richness increased the leaf bacterial diversity and network complexity. Moreover, the results of the leaf bacteria community assembly of the invader suggested that the complex bacteria community resulted from higher native diversity rather than higher invader biomass. We concluded that increased leaf bacterial network complexity along the native plant diversity gradient likely facilitated plant invasion. Our findings provided evidence of a potential mechanism by which microbes may affect the plant community invasibility, hopefully helping to explain the non-negative relationship between native diversity and invasibility.
Differences in Physiological Characteristics, Seed Germination, and Seedling Establishment in Response to Salt Stress between Dimorphic Seeds in the Halophyte Suaeda liaotungensis
Authors: Song Jieqiong , Wang Hongfei , Chu Ruowen , Zhao Lantong , Li Xinxin , An Shuo , Qiang Mengke , Du Wanying , Li Qiuli
Published: March 2023

Soil salinization is an increasing agricultural problem around the world, affecting crop productivity and quality. Seed germination and seedling establishment are susceptible to salt stress. Suaeda liaotungensis is a halophyte with strong salt tolerance that produces dimorphic seeds to adapt to the saline environment. Differences in physiological characteristics, seed germination, and seedling establishment in response to salt stress between dimorphic seeds in S. liaotungensis have not been reported. The results showed that brown seeds had significantly higher H2O2 and O2−. levels and betaine content, as well as POD and CAT activities, while they had significantly lower MDA and proline contents and SOD activity than black seeds. Light promoted the germination of brown seeds in a certain temperature range, and brown seeds could reach a higher germination percentage in a wide temperature range. However, light and temperature had no effect on the germination percentage of black seeds. Brown seeds had higher germination than black seeds under the same NaCl concentration. The final germination of brown seeds was significantly decreased as salt concentration increased, whereas this had no effect on the final germination of black seeds. POD and CAT activities, as well as MDA content, in brown seeds were significantly higher than those in black seeds during germination under salt stress. Additionally, the seedlings from brown seeds were more tolerant to salinity than those from black seeds. Therefore, these results will give an in-depth understanding of the adaptation strategies of dimorphic seeds to a salinization environment, and better exploitation and utilization of S. liaotungensis.
Green Biogenic of Silver Nanoparticles Using Polyphenolic Extract of Olive Leaf Wastes with Focus on Their Anticancer and Antimicrobial Activities
Authors: Alowaiesh Bassam F. , Alhaithloul Haifa Abdulaziz Sakit , Saad Ahmed M. , Hassanin Abdallah A.
Published: March 2023

Agro-industrial wastes are rich in polyphenols and other bioactive compounds, and valorizing these wastes is a crucial worldwide concern for saving health and the environment. In this work, olive leaf waste was valorized by silver nitrate to produce silver nanoparticles (OLAgNPs), which exhibited various biological, antioxidant, anticancer activities against three cancer cell lines, and antimicrobial activity against multi-drug resistant (MDR) bacteria and fungi. The obtained OLAgNPs were spherical, with an average size of 28 nm, negatively charged at −21 mV, and surrounded by various active groups more than the parent extract based on FTIR spectra. The total phenolic and total flavonoid contents significantly increased in OLAgNPs by 42 and 50% over the olive leaf waste extract (OLWE); consequently, the antioxidant activity of OLAgNPs increased by 12% over OLWE, recording an SC50 of OLAgNPs of 5 µg/mL compared to 30 µg/mL in the extract. The phenolic compound profile detected by HPLC showed that gallic acid, chlorogenic acid, rutin, naringenin, catechin, and propyl gallate were the main compounds in the HPLC profile of OLAgNPs and OLWE; the content of these compounds was higher in OLAgNPs than OLWE by 16-fold. The higher phenolic compounds in OLAgNPs are attributable to the significant increase in biological activities of OLAgNPs than that of OLWE. OLAgNPs successfully inhibited the proliferation of three cancer cell lines, MCF-7, HeLa, and HT-29, by 79–82% compared to 55–67% in OLWE and 75–79% in doxorubicin (DOX). The preliminary worldwide problem is multi-drug resistant microorganisms (MDR) because of the random use of antibiotics. Therefore, in this study, we may find the solution in OLAgNPs with concentrations of 2.5–20 µg/mL, which significantly inhibited the growth of six MDR bacteria L. monocytogenes, B. cereus, S. aureus, Y. enterocolitica, C. jejuni, and E. coli with inhibition zone diameters of 25–37 mm and six pathogenic fungi in the range of 26–35 mm compared to antibiotics. OLAgNPs in this study may be applied safely in new medicine to mitigate free radicals, cancer, and MDR pathogens.
Variation in the Concentration of Tilia spp. Pollen in the Aeroplankton of Lublin and Szczecin, Poland
Authors: Weryszko-Chmielewska Elżbieta , Piotrowska-Weryszko Krystyna , Wolski Tomasz , Sulborska-Różycka Aneta , Konarska Agata
Published: March 2023

Although lime trees have numerous benefits, they can pose a threat to allergy sufferers during the flowering period, as their pollen exhibits allergenic properties. This paper presents the results of 3 years of aerobiological research (2020–2022) carried out with the volumetric method in Lublin and Szczecin. A comparison of the pollen seasons in both cities revealed substantially higher concentrations of lime pollen in the air of Lublin than of Szczecin. In the individual years of the study, the maximum pollen concentrations were approximately 3-fold higher, and the annual pollen sum was about 2–3 times higher in Lublin than in Szczecin. Considerably higher lime pollen concentrations were recorded in both cities in 2020 than in the other years, which was probably associated with the 1.7–2.5 °C increase in the average temperature in April compared to the other two years. The maximum lime pollen concentrations were recorded during the last ten days of June or at the beginning of July in both Lublin and Szczecin. This period was associated with the greatest risk of pollen allergy development in sensitive subjects. The increased production of lime pollen in 2020 and in 2018–2019 with the increase in the mean temperature in April, reported in our previous study, may indicate a response of lime trees to the global warming phenomenon. Cumulative temperatures calculated for Tilia may serve as a basis for forecasting the beginning of the pollen season.
Polymer Composites Based on Polycarbonate/Acrylonitrile-Butadiene-Styrene Used in Rapid Prototyping Technology
Authors: Bulanda Katarzyna , Oleksy Mariusz , Oliwa Rafał
Published: March 2023

As part of this work, polymer composites based on polycarbonate/acrylonitrile-butadiene-styrene (PC/ABS) were obtained and used in 3D printing technology, particularly Melted Extrusion Modeling (MEM) technology. The influence of selected fillers on the properties of the obtained composites was investigated. For this purpose, modified fillers such as silica modified with alumina, bentonite modified with a quaternary ammonium salt, and hybrid lignin/silicon dioxide filler were introduced into the PC/ABS matrix. In the first part of this work, polymer blends and their composites containing 1.5–3 wt. of the filler were used to obtain the filament using the proprietary technological line. Moldings for testing the performance properties were obtained using additive manufacturing techniques and injection molding. In the subsequent part of this work, rheological properties (mass flow rate (MFR) and viscosity curves) and mechanical properties (Rockwell hardness and static tensile strength with Young’s modulus) were examined. The structures of the obtained composites were also determined by scanning electron microscopy (SEM/EDS). The obtained results confirmed the results obtained from a wide-angle X-ray scattering analysis (WAXS). In turn, the physicochemical properties were characterized on the basis of the results of tests using thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). Based on the obtained results, it was found that the introduced modified additives had a significant impact on the processing and functional properties of the tested composites.
A Short Review on Nanostructured Carbon Containing Biopolymer Derived Composites for Tissue Engineering Applications
Authors: Bartoli Mattia , Piatti Erik , Tagliaferro Alberto
Published: March 2023

The development of new scaffolds and materials for tissue engineering is a wide and open realm of material science. Among solutions, the use of biopolymers represents a particularly interesting area of study due to their great chemical complexity that enables creation of specific molecular architectures. However, biopolymers do not exhibit the properties required for direct application in tissue repair—such as mechanical and electrical properties—but they do show very attractive chemical functionalities which are difficult to produce through in vitro synthesis. The combination of biopolymers with nanostructured carbon fillers could represent a robust solution to enhance composite properties, producing composites with new and unique features, particularly relating to electronic conduction. In this paper, we provide a review of the field of carbonaceous nanostructure-containing biopolymer composites, limiting our investigation to tissue-engineering applications, and providing a complete overview of the recent and most outstanding achievements.
A Numerical Thermo-Chemo-Flow Analysis of Thermoset Resin Impregnation in LCM Processes
Authors: Alotaibi Hatim , Abeykoon Chamil , Soutis Constantinos , Jabbari Masoud
Published: March 2023

This paper presents a numerical framework for modelling and simulating convection–diffusion–reaction flows in liquid composite moulding (LCM). The model is developed in ANSYS Fluent with customised user-defined-functions (UDFs), user-defined-scalar (UDS), and user-defined memory (UDM) codes to incorporate the cure kinetics and rheological characteristics of thermoset resin impregnation. The simulations were performed adopting volume-of-fluid (VOF)—a multiphase flow solution—based on finite volume method (FVM). The developed numerical approach solves Darcy’s law, heat transfer, and chemical reactions in LCM process simultaneously. Thereby, the solution scheme shows its ability to provide information on flow-front, viscosity development, degree of cure, and rate of reaction at once unlike existing literature that commonly focuses on impregnation stage and cure stage in isolation. Furthermore, it allows online monitoring, controlled boundary conditions, and injection techniques (for design of manufacturing) during the mould filling and curing stages. To examine the validity of the model, a comparative analysis was carried out for a simple geometry, in that the numerical results indicate good agreement—3.4% difference in the degree of cure compared with previous research findings.
Damage Monitoring of Composite Adhesive Joint Integrity Using Conductivity and Fiber Bragg Grating
Authors: Shin Chow-Shing , Chen Liang-Wei
Published: March 2023

Adhesive joints possess a number of advantages over traditional joining methods and are widely used in composite structures. Conventional non-destructive examination techniques do not readily reveal joint degradation before the formation of explicit defects. Embedded fiber Bragg grating (FBG) sensors and the resistance of carbon nanotube (CNT)-doped conductive joints have been proposed to monitor the structural integrity of adhesive joints. Both techniques will be employed and compared in the current work to monitor damage development in adhesive joints under tensile and cyclic fatigue loading. Most of the previous works took measurements under an applied load, which by itself will affect the monitoring signals without the presence of any damage. Moreover, most FBG works primarily relied on the peak shifting phenomenon for sensing. Degradation of adhesive and inter-facial defects will lead to non-uniform strain that may chirp the FBG spectrum, causing complications in the peak shifting measurement. In view of the above shortfalls, measurements are made at some low and fixed loads to preclude any unwanted effect due to the applied load. The whole FBG spectrum, instead of a single peak, will be used, and a quantitative parameter to describe spectrum changes is proposed for monitoring purposes. The extent of damage is revealed by a fluorescent penetrant and correlated with the monitoring signals. With these refined techniques, we hope to shed some light on the relative merits and limitations of the two techniques.
Nanotopography of Polystyrene/Poly(methyl methacrylate) for the Promotion of Patient Specific Von Willebrand Factor Entrapment and Platelet Adhesion in a Whole Blood Microfluidic Assay
Authors: Ward Joanna , Dunne Eimear , Schoen Ingmar , Boyd Adrian R. , Kenny Dermot , Meenan Brian J.
Published: March 2023

Platelet function testing is essential for the diagnosis of patients with bleeding disorders. Specifically, there is a need for a whole blood assay that is capable of analysing platelet behaviour in contact with a patient-specific autologous von Willebrand factor (vWF), under physiologically relevant conditions. The creation of surface topography capable of entrapping and uncoiling vWF for the support of subsequent platelet adhesion within the same blood sample offers a potential basis for such an assay. In this study, spin coating of polystyrene/poly (methyl methacrylate) (PS/PMMA) demixed solutions onto glass substrates in air has been used to attain surfaces with well-defined topographical features. The effect of augmenting the PS/PMMA solution with uniform 50 µm PS microspheres that can moderate the demixing process on the resultant surface features has also been investigated. The topographical features created here by spin coating under ambient air pressure conditions, rather than in nitrogen, which previous work reports, produces substrate surfaces with the ability to entrap vWF from flowing blood and facilitate platelet adhesion. The direct optical visualisation of fluorescently-labelled platelets indicates that topography resulting from inclusion of PS microspheres in the PS/PMMA spin coating solution increases the total number of platelets that adhere to the substrate surface over the period of the microfluidic assay. However, a detailed analysis of the adhesion rate, mean translocating velocity, mean translocation distance, and fraction of the stably adhered platelets measured during blood flow under arterial equivalent mechanical shear conditions indicates no significant difference for topographies created with or without inclusion of the PS microspheres.
Fungal Screening for Potential PET Depolymerization
Authors: Malafatti-Picca Lusiane , Bucioli Elaine Cristina , de Barros Chaves Michel Ricardo , de Castro Aline Machado , Valoni Érika , de Oliveira Valéria Maia , Marsaioli Anita Jocelyne , Govone José Silvio , de Franceschi de Angelis Dejanira , Brienzo Michel , Attili-Angelis Derlene
Published: March 2023

Approximately 400 billion PET bottles are produced annually in the world, of which from 8 to 9 million tons are discarded in oceans. This requires developing strategies to urgently recycle them. PET recycling can be carried out using the microbial hydrolysis of polymers when monomers and oligomers are released. Exploring the metabolic activity of fungi is an environmentally friendly way to treat harmful polymeric waste and obtain the production of monomers. The present study addressed: (i) the investigation of potential of strains with the potential for the depolymerization of PET bottles from different manufacturers (crystallinity of 35.5 and 10.4%); (ii) the search for a culture medium that favors the depolymerization process; and (iii) gaining more knowledge on fungal enzymes that can be applied to PET recycling. Four strains (from 100 fungal strains) were found as promising for conversion into terephthalic acid from PET nanoparticles (npPET): Curvularia trifolii CBMAI 2111, Trichoderma sp. CBMAI 2071, Trichoderma atroviride CBMAI 2073, and Cladosporium cladosporioides CBMAI 2075. The fermentation assays in the presence of PET led to the release of terephthalic acid in concentrations above 12 ppm. Biodegradation was also confirmed using mass variation analyses (reducing mass), scanning electron microscopy (SEM) that showed evidence of material roughness, FTIR analysis that showed band modification, enzymatic activities detected for lipase, and esterase and cutinase, confirmed by monomers/oligomers quantification using high performance liquid chromatography (HPLC-UV). Based on the microbial strains PET depolymerization, the results are promising for the exploration of the selected microbial strain.
Effects of Drinking Electrolyzed Alkaline-Reduced Water on Functional Dyspepsia: A Randomized, Double-Blind, Controlled Prospective Trial
Authors: Bajgai Johny , Lee Mihyun , Jang Yeon-Gyu , Lee Kiwon , Sharma Subham , Jeong Yun Ju , Park Hong Jun , Goh Seong Hoon , Kim Cheol-Su , Kim Hyun Il , Lee Kyu-Jae
Published: March 2023

A well-known functional gastrointestinal disorder called functional dyspepsia (FD) is defined by dyspeptic symptoms without any structural abnormalities. In alternative intervention, electrolyzed alkaline-reduced water (EARW) consumption is regarded as a treatment modality for gastrointestinal symptoms despite its mechanism not yet fully understood. The present clinical study aimed to investigate the effects of EARW on gastrointestinal symptoms of patients with FD. Forty-eight participants with FD were screened, and 42 were enrolled. Participants were randomly allocated to the EARW (n = 21) and purified water (PW) (n = 21) groups. The EARW group ingested EARW (10 mL/kg body weight/day) for 6 weeks. The gastrointestinal symptom rating scale (GSRS), functional dyspepsia-related quality of life (FD-QoL), the Korean version of the Nepean Dyspepsia Index (NDI-K) were used as primary outcome measures at baseline and at 6 weeks, and inflammatory markers were measured as the secondary outcome. Two participants dropped out, and 40 participants (EARW = 20 and PW = 20) completed the trial. Total GSRS score was significantly lower in the EARW group (34.27%, p < 0.01) than in the PW (18.16%) group. In the five subcategories of GSRS, the decreased score between baseline and post-intervention for the EARW and PW groups were 43.59% and 21.33% in abdominal pain score, respectively; 38.98% and 18.92% in reflux syndrome, respectively; 25.42% and 20.90% in diarrhea, respectively; 35.87% and 21.48% in indigestion, respectively; and 32.81% and 10.71% in constipation, respectively, and all the parameters were significantly different in the EARW group compared with those in the PW group. The NDI-K score was also lower in the EARW group (p < 0.01) than in the PW group. FD-QoL score decreased significantly more in the EARW group after intervention than in the PW group (p < 0.05). Additionally, inflammatory cytokines (TNF-α and IFN-γ) levels significantly suppressed in the EARW group after 6 weeks of drinking compared with the levels at the baseline. Our clinical study suggests that long-term drinking of EARW (pH 9.5) may improve FD-related symptoms and the quality of life of FD patients through home-based administration.
The Wounded Body of Christ, the Church and Perennial Escalation of Gender-Based Violence and Its Implications for Pastoral Care
Authors: Mukuka Sylvia
Published: March 2023

It is a known fact that gender-based violence is an infringement on human rights. Gender-based violence takes place all over the world in almost every place. It is experienced in homes, workplaces, communities, and in the Church as well. Today, church members, as well as pastors are wounded, fragmented, and hurting as they suffer serious abuses in silence. Christian children have fallen victim to sexual abuse that is perpetrated by their parents. Parents too, have become victims of violence; sometimes maimed by children who have become violent enough to kill their Christian parents in their homes. Furthermore, many Christian couples have continued to experience intra gender violence in their families that is often attributed to marital infidelity. Beyond that, there is also a common secretive kind of abuse in the form of marital sexual violence which is a serious form of violence against women. This is a hidden type of abuse that has been perpetrated behind closed doors for too long by members of the body of Christ. Due to its prevalence sometimes the victims themselves, often pretend that the problem in not present by keeping a deafening silence. This article, therefore, makes an in-depth investigation into the causes of the pervasive forms of gender-based violence that occur in some Zambian Christian homes, with particular emphasis on the ways in which this multifaceted phenomenon is very much hidden. This article expounds on how Christian couples have continued to suffer silently as their voices are suppressed due to fear and shame. In the conclusion of the article, it is suggested that, unless the church, in its pastoral care role, awakens from its slumber and begins to address issues of gender-based violence in the church with sincerity, honesty, and openness by admitting that indeed, the body of Christ is yearning to be healed, gender-based violence shall remain a perennial occurrence.
Towards a General Monitoring System for Terrestrial Primary Production: A Test Spanning the European Drought of 2018
Authors: Bloomfield Keith J. , van Hoolst Roel , Balzarolo Manuela , Janssens Ivan A. , Vicca Sara , Ghent Darren , Prentice I. Colin
Published: March 2023

(1) Land surface models require inputs of temperature and moisture variables to generate predictions of gross primary production (GPP). Differences between leaf and air temperature vary temporally and spatially and may be especially pronounced under conditions of low soil moisture availability. The Sentinel-3 satellite mission offers estimates of the land surface temperature (LST), which for vegetated pixels can be adopted as the canopy temperature. Could remotely sensed estimates of LST offer a parsimonious input to models by combining information on leaf temperature and hydration? (2) Using a light use efficiency model that requires only a handful of input variables, we generated GPP simulations for comparison with eddy-covariance inferred estimates available from flux sites within the Integrated Carbon Observation System. Remotely sensed LST and greenness data were input from Sentinel-3. Gridded air temperature data were obtained from the European Centre for Medium-Range Weather Forecasts. We chose the years 2018–2019 to exploit the natural experiment of a pronounced European drought. (3) Simulated GPP showed good agreement with flux-derived estimates. During dry conditions, simulations forced with LST performed better than those with air temperature for shrubland, grassland and savanna sites. (4) This study advances the prospect for a global GPP monitoring system that will rely primarily on remotely sensed inputs.
Passive Location for 5G OFDM Radiation Sources Based on Virtual Synthetic Aperture
Authors: Zhang Tong , Zhang Xin , Yang Qiang
Published: March 2023

Passive location technology has been greatly developed because of its low power consumption, long detection distance, good concealment, and strong anti-interference ability. Orthogonal frequency-division multiplexing (OFDM) is an efficient multi-carrier transmission technology, which is an important signal form of 5G communication. Researching passive locations for OFDM signals can realize the location of base stations, which is of great significance in the military. Space-borne passive location technology has a contradiction between wide coverage and high precision. Therefore, a single-satellite passive location algorithm for OFDM radiation sources based on the virtual synthetic aperture is proposed. The algorithm introduces virtual synthetic aperture technology, using antenna movement to accumulate data coherently over a long time period and synthesizing a long azimuth virtual aperture. In addition, it utilizes fast Fourier transform (FFT) to extract phase information at a specific frequency based on the multi-carrier modulation technology of the OFDM signal. Pilot technology of the communication system is used for phase compensation and noise reduction. Thus, the azimuth linear frequency modulation (LFM) signal containing the location information of the radiation source is obtained. The radiation source location can be obtained by range searching and azimuth focusing. Simulation results verify the effectiveness of the algorithm and show that the algorithm can realize high-precision and wide-coverage location for the OFDM radiation sources using a single antenna, turning the hardware structure into software to reduce the cost and complexity of the system.
A Real-Time Detecting Method for Continuous Urban Flood Scenarios Based on Computer Vision on Block Scale
Authors: Huang Haocheng , Lei Xiaohui , Liao Weihong , Li Haichen , Wang Chao , Wang Hao
Published: March 2023

Due to the frequent and sudden occurrence of urban waterlogging, targeted and rapid risk monitoring is extremely important for urban management. To improve the efficiency and accuracy of urban waterlogging monitoring, a real-time determination method of urban waterlogging based on computer vision technology was proposed in this study. First, city images were collected and then identified using the ResNet algorithm to determine whether a waterlogging risk existed in the images. Subsequently, the recognition accuracy was improved by image augmentation and the introduction of an attention mechanism (SE-ResNet). The experimental results showed that the waterlogging recognition rate reached 99.50%. In addition, according to the actual water accumulation process, real-time images of the waterlogging area were obtained, and a threshold method using the inverse weight of the time interval (T-IWT) was proposed to determine the times of the waterlogging occurrences from the continuous images. The results showed that the time error of the waterlogging identification was within 30 s. This study provides an effective method for identifying urban waterlogging risks in real-time.
Going Back to Grassland? Assessing the Impact of Groundwater Decline on Irrigated Agriculture Using Remote Sensing Data
Authors: Wang Haoying
Published: March 2023

Climate change has increased agricultural drought risk in arid/semi-arid regions globally. One of the common adaptation strategies is shifting to more drought-tolerant crops or switching back to grassland permanently. In many drought-prone areas, groundwater dynamics play a critical role in agricultural production and drought management. This study aims to help understand how groundwater level decline affects the propensity of cropland switching back to grassland. Taking Union County of New Mexico (US) as a case study, field-scale groundwater level projections and high-resolution remote sensing data on crop choices are integrated to explore the impact of groundwater level decline in a regression analysis framework. The results show that cropland has been slowly but permanently switching back to grassland as the groundwater level in the Ogallala Aquifer continues to decline in the area. Specifically, for a one-standard-deviation decline in groundwater level (36.95 feet or 11.26 m), the average likelihood of switching back to grassland increases by 1.85% (the 95% confidence interval is [0.07%, 3.58%]). The findings account for the fact that farmers usually explore other options (such as more drought-tolerant crops, land idling, and rotation) before switching back to grassland permanently. The paper concludes by exploring relevant policy implications for land (soil) and water conservation in the long run.
A Low-Cost Deep Learning System to Characterize Asphalt Surface Deterioration
Authors: Inácio Diogo , Oliveira Henrique , Oliveira Pedro , Correia Paulo
Published: March 2023

Every day millions of people travel on highways for work- or leisure-related purposes. Ensuring road safety is thus of paramount importance, and maintaining good-quality road pavements is essential, requiring an effective maintenance policy. The automation of some road pavement maintenance tasks can reduce the time and effort required from experts. This paper proposes a simple system to help speed up road pavement surface inspection and its analysis towards making maintenance decisions. A low-cost video camera mounted on a vehicle was used to capture pavement imagery, which was fed to an automatic crack detection and classification system based on deep neural networks. The system provided two types of output: (i) a cracking percentage per road segment, providing an alert to areas that require attention from the experts; (ii) a segmentation map highlighting which areas of the road pavement surface are affected by cracking. With this data, it became possible to select which maintenance or rehabilitation processes the road pavement required. The system achieved promising results in the analysis of highway pavements, and being automated and having a low processing time, the system is expected to be an effective aid for experts dealing with road pavement maintenance.
Continuously Updated Digital Elevation Models (CUDEMs) to Support Coastal Inundation Modeling
Authors: Amante Christopher J. , Love Matthew , Carignan Kelly , Sutherland Michael G. , MacFerrin Michael , Lim Elliot
Published: March 2023

The National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI) generates digital elevation models (DEMs) that range from the local to global scale. Collectively, these DEMs are essential to determining the timing and extent of coastal inundation and improving community preparedness, event forecasting, and warning systems. We initiated a comprehensive framework at NCEI, the Continuously Updated DEM (CUDEM) Program, with seamless bare-earth, topographic-bathymetric and bathymetric DEMs for the entire United States (U.S.) Atlantic and Gulf of Mexico Coasts, Hawaii, American Territories, and portions of the U.S. Pacific Coast. The CUDEMs are currently the highest-resolution, seamless depiction of the entire U.S. Atlantic and Gulf Coasts in the public domain; coastal topographic-bathymetric DEMs have a spatial resolution of 1/9th arc-second (~3 m) and offshore bathymetric DEMs coarsen to 1/3rd arc-second (~10 m). We independently validate the land portions of the CUDEMs with NASA’s Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) observatory and calculate a corresponding vertical mean bias error of 0.12 m ± 0.75 m at one standard deviation, with an overall RMSE of 0.76 m. We generate the CUDEMs through a standardized process using free and open-source software (FOSS) and provide open-access to our code repository. The CUDEM framework consists of systematic tiled geographic extents, spatial resolutions, and horizontal and vertical datums to facilitate rapid updates of targeted areas with new data collections, especially post-storm and tsunami events. The CUDEM framework also enables the rapid incorporation of high-resolution data collections ingested into local-scale DEMs into NOAA NCEI’s suite of regional and global DEMs. Future research efforts will focus on the generation of additional data products, such as spatially explicit vertical error estimations and morphologic change calculations, to enhance the utility and scientific benefits of the CUDEM Program.
Distinguishing Buildings from Vegetation in an Urban-Chaparral Mosaic Landscape with LiDAR-Informed Discriminant Analysis
Authors: Yamashita Thomas J. , Wester David B. , Tewes Michael E. , Young John H. , Lombardi Jason V.
Published: March 2023

Identification of buildings from remotely sensed imagery in urban and suburban areas is a challenging task. Light detection and Ranging (LiDAR) provides an opportunity to accurately identify buildings by identification of planar surfaces. Dense vegetation can limit the number of light particles that reach the ground, potentially creating false planar surfaces within a vegetation stand. We present an application of discriminant analysis (a commonly used statistical tool in decision theory) to classify polygons (derived from LiDAR) as either buildings or a non-building planar surfaces. We conducted our analysis in southern Texas where thornscrub vegetation often prevents a LiDAR beam from fully penetrating the vegetation canopy in and around residential areas. Using discriminant analysis, we grouped potential building polygons into building and non-building classes using the point densities of ground, unclassified, and building points. Our technique was 95% accurate at distinguishing buildings from non-buildings. Therefore, we recommend its use in any locale where distinguishing buildings from surrounding vegetation may be affected by the proximity of dense vegetation to buildings.
RadWet: An Improved and Transferable Mapping of Open Water and Inundated Vegetation Using Sentinel-1
Authors: Oakes Gregory , Hardy Andy , Bunting Pete
Published: March 2023

Mapping the spatial and temporal dynamics of tropical herbaceous wetlands is vital for a wide range of applications. Inundated vegetation can account for over three-quarters of the total inundated area, yet widely used EO mapping approaches are limited to the detection of open water bodies. This paper presents a new wetland mapping approach, RadWet, that automatically defines open water and inundated vegetation training data using a novel mixture of radar, terrain, and optical imagery. Training data samples are then used to classify serial Sentinel-1 radar imagery using an ensemble machine learning classification routine, providing information on the spatial and temporal dynamics of inundation every 12 days at a resolution of 30 m. The approach was evaluated over the period 2017–2022, covering a range of conditions (dry season to wet season) for two sites: (1) the Barotseland Floodplain, Zambia (31,172 km2) and (2) the Upper Rupununi Wetlands in Guyana (11,745 km2). Good agreement was found at both sites using random stratified accuracy assessment data (n = 28,223) with a median overall accuracy of 89% in Barotseland and 80% in the Upper Rupununi, outperforming existing approaches. The results revealed fine-scale hydrological processes driving inundation patterns as well as temporal patterns in seasonal flood pulse timing and magnitude. Inundated vegetation dominated wet season wetland extent, accounting for a mean 80% of total inundation. RadWet offers a new way in which tropical wetlands can be routinely monitored and characterised. This can provide significant benefits for a range of application areas, including flood hazard management, wetland inventories, monitoring natural greenhouse gas emissions and disease vector control.
Drought Disasters in China from 1991 to 2018: Analysis of Spatiotemporal Trends and Characteristics
Authors: Wang Xiaofeng , Luo Pingping , Zheng Yue , Duan Weili , Wang Shuangtao , Zhu Wei , Zhang Yuzhu , Nover Daniel
Published: March 2023

Droughts have emerged as a global problem in contemporary societies. China suffers from different degrees of drought almost every year, with increasing drought severity each year. Droughts in China are seasonal and can severely impact crops. This study used spatiotemporal trend and characteristics analysis of drought disaster data from 1991 to 2018 in Chinese provinces, in addition to the Mann–Kendall test and wavelet analysis. The drought disaster data included the crop damage area, drought-affected area of the crops, and crop failure area. The outputs of the crops decreased by 10%, 30%, and 80%, respectively. The population with reduced drinking water caused by drought, and the domestic animals with reduced drinking water caused by drought, were numbered in the tens of thousands. The results of the study show that the crop damage areas owing to drought disasters, drought-affected areas of crops, and crop failure areas in China were mainly distributed in the northern, eastern, northeaster, and southwestern regions. The number of people and domestic animals with reduced drinking water owing to drought in China were mainly concentrated in the northern and southwestern regions. These indicators showed a general increasing trend. Tibet, Fujian, Shandong, Jiangsu, Anhui, and Henan provinces and autonomous regions also showed a slightly increasing trend. In particular, the number of domestic animals with reduced drinking water caused by drought in the Inner Mongolia Autonomous Region showed a clear increasing trend with a significant Z-value of 2.2629. The results of this research can be used to provide scientific evidence for predicting future trends in drought and for practising the best management of drought prevention and resistance.
Visible Near-Infrared Spectroscopy and Pedotransfer Function Well Predict Soil Sorption Coefficient of Glyphosate
Authors: Akter Sonia , de Jonge Lis Wollesen , Møldrup Per , Greve Mogens Humlekrog , Nørgaard Trine , Weber Peter Lystbæk , Hermansen Cecilie , Mouazen Abdul Mounem , Knadel Maria
Published: March 2023

The soil sorption coefficient (Kd) of glyphosate mainly controls its transport and fate in the environment. Laboratory-based analysis of Kd is laborious and expensive. This study aimed to test the feasibility of visible near-infrared spectroscopy (vis–NIRS) as an alternative method for glyphosate Kd estimation at a country scale and compare its accuracy against pedotransfer function (PTF). A total of 439 soils with a wide range of Kd values (37–2409 L kg−1) were collected from Denmark (DK) and southwest Greenland (GR). Two modeling scenarios were considered to predict Kd: a combined model developed on DK and GR samples and individual models developed on either DK or GR samples. Partial least squares regression (PLSR) and artificial neural network (ANN) techniques were applied to develop vis–NIRS models. Results from the best technique were validated using a prediction set and compared with PTF for each scenario. The PTFs were built with soil texture, OC, pH, Feox, and Pox. The ratio of performance to interquartile distance (RPIQ) was 1.88, 1.70, and 1.50 for the combined (ANN), DK (ANN), and GR (PLSR) validation models, respectively. vis–NIRS obtained higher predictive ability for Kd than PTFs for the combined dataset, whereas PTF resulted in slightly better estimations of Kd on the DK and GR samples. However, the differences in prediction accuracy between vis–NIRS and PTF were statistically insignificant. Considering the multiple advantages of vis–NIRS, e.g., being rapid and non-destructive, it can provide a faster and easier alternative to PTF for estimating glyphosate Kd.
Passive Electro-Optical Tracking of Resident Space Objects for Distributed Satellite Systems Autonomous Navigation
Authors: Hussain Khaja Faisal , Thangavel Kathiravan , Gardi Alessandro , Sabatini Roberto
Published: March 2023

Autonomous navigation (AN) and manoeuvring are increasingly important in distributed satellite systems (DSS) in order to avoid potential collisions with space debris and other resident space objects (RSO). In order to accomplish collision avoidance manoeuvres, tracking and characterization of RSO is crucial. At present, RSO are tracked and catalogued using ground-based observations, but space-based space surveillance (SBSS) represents a valid alternative (or complementary asset) due to its ability to offer enhanced performances in terms of sensor resolution, tracking accuracy, and weather independence. This paper proposes a particle swarm optimization (PSO) algorithm for DSS AN and manoeuvring, specifically addressing RSO tracking and collision avoidance requirements as an integral part of the overall system design. More specifically, a DSS architecture employing hyperspectral sensors for Earth observation is considered, and passive electro-optical sensors are used, in conjunction with suitable mathematical algorithms, to accomplish autonomous RSO tracking and classification. Simulation case studies are performed to investigate the tracking and system collision avoidance capabilities in both space-based and ground-based tracking scenarios. Results corroborate the effectiveness of the proposed AN technique and highlight its potential to supplement either conventional (ground-based) or SBSS tracking methods.
An In-Ear PPG-Based Blood Glucose Monitor: A Proof-of-Concept Study
Authors: Hammour Ghena , Mandic Danilo P.
Published: March 2023

Monitoring diabetes saves lives. To this end, we introduce a novel, unobtrusive, and readily deployable in-ear device for the continuous and non-invasive measurement of blood glucose levels (BGLs). The device is equipped with a low-cost commercially available pulse oximeter whose infrared wavelength (880 nm) is used for the acquisition of photoplethysmography (PPG). For rigor, we considered a full range of diabetic conditions (non-diabetic, pre-diabetic, type I diabetic, and type II diabetic). Recordings spanned nine different days, starting in the morning while fasting, up to a minimum of a two-hour period after eating a carbohydrate-rich breakfast. The BGLs from PPG were estimated using a suite of regression-based machine learning models, which were trained on characteristic features of PPG cycles pertaining to high and low BGLs. The analysis shows that, as desired, an average of 82% of the BGLs estimated from PPG lie in region A of the Clarke error grid (CEG) plot, with 100% of the estimated BGLs in the clinically acceptable CEG regions A and B. These results demonstrate the potential of the ear canal as a site for non-invasive blood glucose monitoring.
A Channel Allocation Method Considering the Asymmetry of Available Channels for Centralized Underwater Cognitive Acoustic Networks
Authors: Yun Changho
Published: March 2023

Due to the unpredictable presence of Non-Cognitive Users (NCUs) in the time and frequency domains, the number of available channels (i.e., channels where no NCUs exist) and corresponding channel indices per Cognitive User (CU) may differ. In this paper, we propose a heuristic channel allocation method referred to as Enhanced Multi-Round Resource Allocation (EMRRA), which employs the asymmetry of available channels in existing MRRA to randomly allocate a CU to a channel in each round. EMRRA is designed to enhance the overall spectral efficiency and fairness of channel allocation. To do this, the available channel with the lowest redundancy is primarily selected upon allocating a channel to a CU. In addition, when there are multiple CUs with the same allocation priority, the CU with the smallest number of available channels is chosen. We execute extensive simulations in order to investigate the effect of the asymmetry of available channels on CUs and compare the performance of EMRRA to that of MRRA. As a result, in addition to the asymmetry of available channels, it is confirmed that most of the channels are simultaneously available to multiple CUs. Furthermore, EMRRA outperforms MRRA in terms of the channel allocation rate, fairness, and drop rate and has a slightly higher collision rate. In particular, EMRRA can remarkably reduce the drop rate compared to MRRA.
Left Ventricle Detection from Cardiac Magnetic Resonance Relaxometry Images Using Visual Transformer
Authors: De Santi Lisa Anita , Meloni Antonella , Santarelli Maria Filomena , Pistoia Laura , Spasiano Anna , Casini Tommaso , Putti Maria Caterina , Cuccia Liana , Cademartiri Filippo , Positano Vincenzo
Published: March 2023

Left Ventricle (LV) detection from Cardiac Magnetic Resonance (CMR) imaging is a fundamental step, preliminary to myocardium segmentation and characterization. This paper focuses on the application of a Visual Transformer (ViT), a novel neural network architecture, to automatically detect LV from CMR relaxometry sequences. We implemented an object detector based on the ViT model to identify LV from CMR multi-echo T2* sequences. We evaluated performances differentiated by slice location according to the American Heart Association model using 5-fold cross-validation and on an independent dataset of CMR T2*, T2, and T1 acquisitions. To the best of our knowledge, this is the first attempt to localize LV from relaxometry sequences and the first application of ViT for LV detection. We collected an Intersection over Union (IoU) index of 0.68 and a Correct Identification Rate (CIR) of blood pool centroid of 0.99, comparable with other state-of-the-art methods. IoU and CIR values were significantly lower in apical slices. No significant differences in performances were assessed on independent T2* dataset (IoU = 0.68, p = 0.405; CIR = 0.94, p = 0.066). Performances were significantly worse on the T2 and T1 independent datasets (T2: IoU = 0.62, CIR = 0.95; T1: IoU = 0.67, CIR = 0.98), but still encouraging considering the different types of acquisition. This study confirms the feasibility of the application of ViT architectures in LV detection and defines a benchmark for relaxometry imaging.
The Validity of Ultra-Short-Term Heart Rate Variability during Cycling Exercise
Authors: Tanoue Yukiya , Nakashima Shihoko , Komatsu Tomohiro , Kosugi Miki , Kawakami Saki , Kawakami Shotaro , Michishita Ryoma , Higaki Yasuki , Uehara Yoshinari
Published: March 2023

Ultra-short-term heart rate variability (HRV) has been validated in the resting state, but its validity during exercise is unclear. This study aimed to examine the validity in ultra-short-term HRV during exercise considering the different exercise intensities. HRVs of twenty-nine healthy adults were measured during incremental cycle exercise tests. HRV parameters (Time-, frequency-domain and non-linear) corresponding to each of the 20% (low), 50% (moderate), and 80% (high) peak oxygen uptakes were compared between the different time segments of HRV analysis (180 s (sec) segment vs. 30, 60, 90, and 120-sec segments). Overall, the differences (bias) between ultra-short-term HRVs increased as the time segment became shorter. In moderate- and high-intensity exercises, the differences in ultra-short-term HRV were more significant than in low intensity exercise. Thus, we discovered that the validity of ultra-short-term HRV differed with the duration of the time segment and exercise intensities. However, the ultra-short-term HRV is feasible in the cycling exercise, and we determined some optimal time duration for HRV analysis for across exercise intensities during the incremental cycling exercise.