bluuebunny/crossref_metadata_2025 huggingface dataset:
“Click-to-Clear”: A Strategy to Minimize Radioactivity from the Blood Pool Utilizing Staudinger Ligation
Authors: Soni Nisarg , Sarkar Swarbhanu , Bhise Abhinav , Ha Yeong Su , Park Wonchoul , Yu A-Ram , Kumar Virendra , Lim Jeong Eun , Yoon Young-Ran , Yoo Jeongsoo
Published: February 2023

The availability of several bioorthogonal reactions that can proceed selectively and efficiently under physiologically relevant conditions has garnered the interest of biochemists and organic chemists alike. Bioorthogonal cleavage reactions represent the latest innovation in click chemistry. Here, we employed the Staudinger ligation reaction to release radioactivity from immunoconjugates, improving target-to-background ratios. In this proof-of-concept study, model systems, including the anti-HER2 antibody trastuzumab, radioisotope I-131, and a newly synthesized bifunctional phosphine, were used. Staudinger ligation occurred when biocompatible N-glycosyl azides reacted with this radiolabeled immunoconjugate, leading to cleavage of the radioactive label from the molecule. We demonstrated this click cleavage in vitro and in vivo. Biodistribution studies in tumor models showed that radioactivity was eliminated from the bloodstream, thereby improving tumor-to-blood ratios. SPECT imaging revealed that tumors could be visualized with enhanced clarity. Our simple approach represents a novel application of bioorthogonal click chemistry in the development of antibody-based theranostics.
High Stability and Low Irritation of Retinol Propionate and Hydroxypinacolone Retinoate Supramolecular Nanoparticles with Effective Anti-Wrinkle Efficacy
Authors: Bai De , Hu Fan , Xu Huixian , Huang Jiahong , Wu Chengyu , Zhang Jiaheng , Ye Rui
Published: February 2023

Gravi-A nanoparticles, composed of retinyl propionate (RP) and hydroxypinacolone retinoate (HPR), were prepared by encapsulating the two using the high-pressure homogenization technique. The nanoparticles are effective in anti-wrinkle treatment with high stability and low irritation. We evaluated the effect of different process parameters on nanoparticle preparation. Supramolecular technology effectively produced nanoparticles with spherical shapes with an average size of 101.1 nm. The encapsulation efficiency was in the 97.98–98.35% range. The system showed a sustained release profile for reducing the irritation caused by Gravi-A nanoparticles. Furthermore, applying lipid nanoparticle encapsulation technology improved the transdermal efficiency of the nanoparticles, thereby allowing these to penetrate deep into the dermis layer to achieve precise and sustained release of active ingredients. Gravi-A nanoparticles can be extensively and conveniently used in cosmetics and other related formulations by direct application.
Unexpected Effects of Sulfate and Sodium Chloride Application on Yield Qualitative Characteristics and Symmetry Indicators of Hard and Soft Wheat Kernels
Authors: Aniskina Tatiana S. , Baranova Ekaterina N. , Lebedev Svyatoslav V. , Reger Nelli S. , Besaliev Ishen N. , Panfilov Alexander A. , Kryuchkova Viktoriya A. , Gulevich Alexander A.
Published: February 2023

The heterogeneity of grain quality can lead to limited predictability of qualitative and quantitative characteristics of the wheat yield, especially with an increase in the importance of drought and salinity caused by climate change. This study was undertaken with the aim of creating basic tools for phenotyping and assessing the sensitivity of genotypes to salt effects at the level of some wheat kernel attributes. The study considers 36 variants of the experiment, including four wheat cultivars—Zolotaya, Ulyanovskaya 105, Orenburgskaya 10, Orenburgskaya 23; three treatment variants—control (without salt) and two salts exposure (NaCl at a concentration of 1.1 g L−1 and Na2SO4 at a concentration of 0.4 g L−1); as well as three options for the arrangement of kernels in a simple spikelet—left, middle, and right. It has been established that the salt exposure had a positive effect on the percentage of kernel fulfilling in the cultivars Zolotaya, Ulyanovskaya 105, and Orenburgskaya 23 compared to control. The kernels of the Orenburgskaya 10 variety matured better in the experiment with Na2SO4 exposure, while the control variant and NaCl gave the same effect. When exposed to NaCl, significantly greater values of weight, transverse section area, and transverse section perimeter of the kernel were noted in the cv Zolotaya and Ulyanovskaya 105. Cv Orenburgskaya 10 responded positively to the use of Na2SO4. This salt caused an increase in the area, length, and width of the kernel. The fluctuating asymmetry of the left, middle, and right kernels in the spikelet was calculated. In the cv Orenburgskaya 23 the salts affected only the kernel perimeter among parameters examined. The indicators of the general (fluctuating) asymmetry were lower in the experiments with the use of salts, i.e., kernels were more symmetrical than in the control variant, both for the cultivar as a whole and when compared taking into account the kernel location in spikelet. However, this result was unexpected, since salt stress inhibited a number of morphological parameters: the number and average length of embryonic, adventitious, and nodal roots, flag leaf area, plant height, dry biomass accumulation, and plant productivity indicators. The study showed that low concentrations of salts can positively affect the fulfilling of kernels (the absence of a cavity inside the kernel) and the symmetry of the left and right sides of the kernel.
Festuca pratensis-like Subgenome Reassembly from a “Chromosomal Cocktail” in the Intergeneric Festulolium (Poaceae) Hybrid: A Rare Chromoanagenesis Event in Grasses
Authors: Pašakinskienė Izolda
Published: February 2023

Festuca and Lolium grass species are used for Festulolium hybrid variety production where they display trait complementarities. However, at the genome level, they show antagonisms and a broad scale of rearrangements. A rare case of an unstable hybrid, a donor plant manifesting pronounced variability of its clonal parts, was discovered in the F2 group of 682 plants of Lolium multiflorum × Festuca arundinacea (2n = 6x = 42). Five phenotypically distinct clonal plants were determined to be diploids, having only 14 chromosomes out of the 42 in the donor. GISH defined the diploids as having the basic genome from F. pratensis (2n = 2x = 14), one of the progenitors of F. arundinacea (2n = 6x = 42), with minor components from L. multiflorum and another subgenome, F. glaucescens. The 45S rDNA position on two chromosomes also corresponded to the variant of F. pratensis in the F. arundinacea parent. In the highly unbalanced donor genome, F. pratensis was the least represented, but the most involved in numerous recombinant chromosomes. Specifically, FISH highlighted 45S rDNA-containing clusters involved in the formation of unusual chromosomal associations in the donor plant, suggesting their active role in karyotype realignment. The results of this study show that F. pratensis chromosomes have a particular fundamental drive for restructuring, which prompts the disassembly/reassembly processes. The finding of F. pratensis “escaping” and rebuilding itself from the chaotic “chromosomal cocktail” of the donor plant points to a rare chromoanagenesis event and extends the view of plant genome plasticity.
Developmental, Reproduction, and Feeding Preferences of the Sitobion avenae Mediated by Soil Silicon Application
Authors: Wang Xiaoru , Li Weiwei , Yan Jia , Wang Yi , Zhang Xingyan , Tan Xiaoling , Chen Julian
Published: February 2023

Silicon occupies an important position in the nutrient requirements of wheat. It has been reported that silicon enhances plant resistance to phytophagous insects. However, only limited research has been carried out on the effects of silicon application to wheat and Sitobion avenae populations. In this study, three silicon fertilizer concentrations were treated for potted wheat seedlings, including 0 g/L, 1 g/L, and 2 g/L of water-soluble silicon fertilizer solution. The effect of silicon application on the developmental period, longevity, reproduction, wing pattern differentiation, and other vital life table parameters of the S. avenae were determined. The cage method and the Petri dish isolated leaf method were used to determine the effect of silicon application on the feeding preference of the winged and wingless aphid. The results showed silicon application had no significant effect on the aphid instar of 1–4; although, 2 g/L silicon fertilizer prolonged the nymph stage and 1 and 2 g/L of silicon application all shortened the adult stage and reduced the longevity and fertility of the aphid. Two instances of silicon application reduced the net reproductive rate (R0), intrinsic rate of increase (rm), and finite rate of increase (λ) of the aphid. A 2 g/L silicon application prolonged the population doubling time (td), significantly reduced the mean generation time (T), and increased the proportion of winged aphids. The results also demonstrated that the selection ratio of winged aphids in wheat leaves treated with 1 g/L and 2 g/L silicon was reduced by 8.61% and 17.88%, respectively. The number of aphids on leaves treated with 2 g/L silicon was significantly reduced at 48 and 72 h of aphids released, and the application of silicon to wheat was detrimental to the feeding preference of S. avenae. Therefore, the application of silicon at 2 g/L to wheat has an inhibitory effect on the life parameters and feeding preference of S. avenae.
Genome-Wide Analysis of the Rhododendron AP2/ERF Gene Family: Identification and Expression Profiles in Response to Cold, Salt and Drought Stress
Authors: Guo Zhenhao , He Lisi , Sun Xiaobo , Li Chang , Su Jiale , Zhou Huimin , Liu Xiaoqing
Published: February 2023

The AP2/ERF gene family is one of the most conserved and important transcription factor families mainly occurring in plants with various functions in regulating plant biological and physiological processes. However, little comprehensive research has been conducted on the AP2/ERF gene family in Rhododendron (specifically, Rhododendron simsii), an important ornamental plant. The existing whole-genome sequence of Rhododendron provided data to investigate the AP2/ERF genes in Rhododendron on a genome-wide scale. A total of 120 Rhododendron AP2/ERF genes were identified. The phylogenetic analysis showed that RsAP2 genes were classified into five main subfamilies, AP2, ERF, DREB, RAV and soloist. Cis-acting elements involving plant growth regulators, response to abiotic stress and MYB binding sites were detected in the upstream sequences of RsAP2 genes. A heatmap of RsAP2 gene expression levels showed that these genes had different expression patterns in the five developmental stages of Rhododendron flowers. Twenty RsAP2 genes were selected for quantitative RT-PCR experiments to clarify the expression level changes under cold, salt and drought stress treatments, and the results showed that most of the RsAP2 genes responded to these abiotic stresses. This study generated comprehensive information on the RsAP2 gene family and provides a theoretical basis for future genetic improvement.
Role of Hydrophobic Associations in Self-Healing Hydrogels Based on Amphiphilic Polysaccharides
Authors: Nichifor Marieta
Published: February 2023

Self-healing hydrogels have the ability to recover their original properties after the action of an external stress, due to presence in their structure of reversible chemical or physical cross-links. The physical cross-links lead to supramolecular hydrogels stabilized by hydrogen bonds, hydrophobic associations, electrostatic interactions, or host-guest interactions. Hydrophobic associations of amphiphilic polymers can provide self-healing hydrogels with good mechanical properties, and can also add more functionalities to these hydrogels by creating hydrophobic microdomains inside the hydrogels. This review highlights the main general advantages brought by hydrophobic associations in the design of self-healing hydrogels, with a focus on hydrogels based on biocompatible and biodegradable amphiphilic polysaccharides.
The Role of Polymers in Halide Perovskite Resistive Switching Devices
Authors: Thien Gregory Soon How , Chan Kah-Yoong , Marlinda Ab Rahman
Published: February 2023

Currently, halide perovskites (HPs) are gaining traction in multiple applications, such as photovoltaics and resistive switching (RS) devices. In RS devices, the high electrical conductivity, tunable bandgap, good stability, and low-cost synthesis and processing make HPs promising as active layers. Additionally, the use of polymers in improving the RS properties of lead (Pb) and Pb-free HP devices was described in several recent reports. Thus, this review explored the in-depth role of polymers in optimizing HP RS devices. In this review, the effect of polymers on the ON/OFF ratio, retention, and endurance properties was successfully investigated. The polymers were discovered to be commonly utilized as passivation layers, charge transfer enhancement, and composite materials. Hence, further HP RS improvement integrated with polymers revealed promising approaches to delivering efficient memory devices. Based on the review, detailed insights into the significance of polymers in producing high-performance RS device technology were effectively understood.
Development, Simulation of Temperatures, and Experimentation in Injection Molds Obtained through Additive Manufacturing with Photocurable Polymeric Resins
Authors: Benitez-Lozano Adrian , Vargas-Isaza Carlos , Montealegre-Rubio Wilfredo
Published: February 2023

Additive manufacturing (AM) is a relatively new option in mold manufacturing for rapid tooling (RT) in injection processes. This paper presents the results of experiments with mold inserts and specimens obtained by stereolithography (SLA), which is a kind of AM. A mold insert obtained by AM and a mold produced by traditional subtractive manufacturing were compared to evaluate the performance of the injected parts. In particular, mechanical tests (in accordance with ASTM D638) and temperature distribution performance tests were carried out. The tensile test results of specimens obtained in a 3D printed mold insert were better (almost 15%) than those produced in the duralumin mold. The simulated temperature distribution closely matched its experimental counterpart—the difference in average temperatures was merely 5.36 °C. These findings support the use of AM in injection molding and RT as an excellent alternative for small and medium-sized production runs in the global injection industry.
Geopolymer Materials for Bone Tissue Applications: Recent Advances and Future Perspectives
Authors: Ricciotti Laura , Apicella Antonio , Perrotta Valeria , Aversa Raffaella
Published: February 2023

With progress in the bone tissue engineering (BTE) field, there is an important need to develop innovative biomaterials to improve the bone healing process using reproducible, affordable, and low-environmental-impact alternative synthetic strategies. This review thoroughly examines geopolymers’ state-of-the-art and current applications and their future perspectives for bone tissue applications. This paper aims to analyse the potential of geopolymer materials in biomedical applications by reviewing the recent literature. Moreover, the characteristics of materials traditionally used as bioscaffolds are also compared, critically analysing the strengths and weaknesses of their use. The concerns that prevented the widespread use of alkali-activated materials as biomaterials (such as their toxicity and limited osteoconductivity) and the potentialities of geopolymers as ceramic biomaterials have also been considered. In particular, the possibility of targeting their mechanical properties and morphologies through their chemical compositions to meet specific and relevant requirements, such as biocompatibility and controlled porosity, is described. A statistical analysis of the published scientific literature is presented. Data on “geopolymers for biomedical applications” were extracted from the Scopus database. This paper focuses on possible strategies necessary to overcome the barriers that have limited their application in biomedicine. Specifically, innovative hybrid geopolymer-based formulations (alkali-activated mixtures for additive manufacturing) and their composites that optimise the porous morphology of bioscaffolds while minimising their toxicity for BTE are discussed.
Introducing Semi-Interpenetrating Networks of Chitosan and Ammonium-Quaternary Polymers for the Effective Removal of Waterborne Pathogens from Wastewaters
Authors: Neblea Iulia E. , Chiriac Anita-L. , Zaharia Anamaria , Sarbu Andrei , Teodorescu Mircea , Miron Andreea , Paruch Lisa , Paruch Adam M. , Olaru Andreea G. , Iordache Tanta-V.
Published: February 2023

The present work aims to study the influence of ammonium-quaternary monomers and chitosan, obtained from different sources, upon the effect of semi-interpenetrating polymer network (semi-IPN) hydrogels upon the removal of waterborne pathogens and bacteria from wastewater. To this end, the study was focused on using vinyl benzyl trimethylammonium chloride (VBTAC), a water-soluble monomer with known antibacterial properties, and mineral-enriched chitosan extracted from shrimp shells, to prepare the semi-IPNs. By using chitosan, which still contains the native minerals (mainly calcium carbonate), the study intends to justify that the stability and efficiency of the semi-IPN bactericidal devices can be modified and better improved. The new semi-IPNs were characterized for composition, thermal stability and morphology using well-known methods. Swelling degree (SD%) and the bactericidal effect assessed using molecular methods revealed that hydrogels made of chitosan derived from shrimp shell demonstrated the most competitive and promising potential for wastewater (WW) treatment.
Identification of Transgenic Agricultural Products and Foods Using NIR Spectroscopy and Hyperspectral Imaging: A Review
Authors: Zhang Jun , Liu Zihao , Pu Yaoyuan , Wang Jiajun , Tang Binman , Dai Limin , Yu Shuihua , Chen Ruqing
Published: February 2023

Spectroscopy and its imaging techniques are now popular methods for quantitative and qualitative analysis in fields such as agricultural products and foods, and combined with various chemometric methods. In fact, this is the application basis for spectroscopy and spectral imaging techniques in other fields such as genetics and transgenic monitoring. To date, there has been considerable research using spectroscopy and its imaging techniques (especially NIR spectroscopy, hyperspectral imaging) for the effective identification of agricultural products and foods. There have been few comprehensive reviews that cover the use of spectroscopic and imaging methods in the identification of genetically modified organisms. Therefore, this paper focuses on the application of NIR spectroscopy and its imaging techniques (including NIR spectroscopy and hyperspectral imaging techniques) in transgenic agricultural product and food detection and compares them with traditional detection methods. A large number of studies have shown that the application of NIR spectroscopy and imaging techniques in the detection of genetically modified foods is effective when compared to conventional approaches such as polymerase chain reaction and enzyme-linked immunosorbent assay.
Investigation of Formation Process and Intensity of Coal and Gas Outburst Shockwave
Authors: Sun Dongling , Cao Jie , Dai Linchao , Li Rifu , Liu Yanbao
Published: February 2023

The shock wave of a coal and gas outburst is a high-pressure and high-speed impact airflow formed rapidly after the outburst. The propagation destroys the ventilation facilities and causes the destruction of the ventilation system. The theoretical research on the outburst shock wave is of great significance. In order to deeply understand the formation mechanism of the outburst shock wave, this paper draws on the shock wave theory to theoretically analyze the microscopic formation process of the outburst shock wave. The main difference between the formation process of a coal and gas outburst shock wave and the formation process of a general shock wave is that the outburst shock wave has a solid–gas flow zone in the high-pressure zone. The calculation formulas of pressure, density, temperature and other parameters before and after the outburst shock wave are derived. After the outburst shock wave passes through, the pressure, temperature and density of the roadway air will change suddenly. The relationship expression between outburst gas pressure and outburst shock wave intensity is derived, which can reflect the role of pulverized coal in the formation process of a shock wave. In order to facilitate the understanding and calculation, the concept of equivalent sound velocity of coal-gas flow is proposed, and the direct calculation of the impact strength of a coal and gas outburst is attempted. This paper is helpful to improve the understanding of the essence of a coal and gas outburst shock wave. It is also of great significance to outburst disaster relief.
Local Quantum Theory with Fluids in Space-Time
Authors: Waegell Mordecai
Published: February 2023

In 1948, Schwinger developed a local Lorentz-covariant formulation of relativistic quantum electrodynamics in space-time which is fundamentally inconsistent with any delocalized interpretation of quantum mechanics. An interpretation compatible with Schwinger’s theory is presented, which reproduces all of the standard empirical predictions of conventional delocalized quantum theory in configuration space. This is an explicit, unambiguous, and Lorentz-covariant “local hidden variable theory” in space-time, whose existence proves definitively that such theories are possible. This does not conflict with Bell’s theorem because it is a local many-worlds theory. Each physical system is characterized by a wave-field, which is a set of indexed piece-wise single-particle wavefunctions in space-time, each with its own coefficient, along with a memory which contains the separate local Hilbert-space quantum state at each event in space-time. Each single-particle wavefunction of a fundamental system describes the motion of a portion of a conserved fluid in space-time, with the fluid decomposing into many classical point particles, each following a world-line and recording a local memory. Local interactions between two systems take the form of local boundary conditions between the differently indexed pieces of those systems’ wave-fields, with new indexes encoding each orthogonal outcome of the interaction. The general machinery is introduced, including the local mechanisms for entanglement and interference. The experience of collapse, Born rule probability, and environmental decoherence are discussed, and a number of illustrative examples are given.
Some Insights about the Applicability of Logistic Factorisation Machines in Banking
Authors: Slabber Erika , Verster Tanja , de Jongh Riaan
Published: February 2023

Logistic regression is a very popular binary classification technique in many industries, particularly in the financial service industry. It has been used to build credit scorecards, estimate the probability of default or churn, identify the next best product in marketing, and many more applications. The machine learning literature has recently introduced several alternative techniques, such as deep learning neural networks, random forests, and factorisation machines. While neural networks and random forests form part of the practitioner’s model-building toolkit, factorisation machines are seldom used. In this paper, we investigate the applicability of factorisation machines to some binary classification problems in banking. To stimulate the practical application of factorisation machines, we implement the fitting routines, based on logit loss and maximum likelihood, on commercially available software that is widely used by banks and other large financial services companies. Logit loss is usually used by the machine learning fraternity while maximum likelihood is popular in statistics. Depending on the coding of the target variable, we will show that these methods yield identical parameter estimates. Often, banks are confronted with predicting events that occur with low probability. To deal with this phenomenon, we introduce weights in the above-mentioned loss functions. The accuracy of our fitting algorithms is then studied by means of a simulation study and compared with logistic regression. The separation and prediction performance of factorisation machines are then compared to logistic regression and random forests by means of three case studies covering a recommender system, credit card fraud, and a credit scoring application. We conclude that logistic factorisation machines are worthy competitors of logistic regression in most applications, but with clear advantages in recommender systems applications where the number of predictors typically outnumbers the number of observations.
Assessing the Performance of a Handheld Laser Scanning System for Individual Tree Mapping—A Mixed Forests Showcase in Spain
Authors: Tupinambá-Simões Frederico , Pascual Adrián , Guerra-Hernández Juan , Ordóñez Cristóbal , de Conto Tiago , Bravo Felipe
Published: February 2023

The use of mobile laser scanning to survey forest ecosystems is a promising, scalable technology to describe the 3D structure of forests at a high resolution. We use a structurally complex, mixed-species Mediterranean forest to test the performance of a mobile Handheld Laser Scanning (HLS) system to estimate tree attributes within a forest patch in central Spain. We describe the different stages of the HLS approach: field position, ground data collection, scanning path design, point cloud processing, alignment between detected trees and measured reference trees, and finally, the assessment of main tree structural attributes diameter at breast height (DBH) and tree height considering species and tree size as control factors. We surveyed 418 reference trees to account for omission and commission error rates over a 1 ha plot divided into 16 sections and scanned using two different scanning paths. The HLS-based approach reached a high of 88 and 92% tree detection rate for the best combination of scanning path and point cloud processing modes for the HLS system. The root mean squared errors for DBH estimates varied between species: errors for Pinus pinaster were below 2 cm for Scan 02. Quercus pyrenaica, and Alnus glutinosa showed higher error rates. We observed good agreement between ALS and HLS estimates for tree height, highlighting differences to field measurements. Despite the complexity of the mixed forest area surveyed, our results show that HLS is highly efficient at detecting tree locations, estimating DBH, and supporting tree height measurements as confirmed with airborne laser data used for validation. This study is one of the first HLS-based studies conducted in the Mediterranean mixed forest region, where variability in tree allometries and spacing and the presence of natural regeneration pose challenges for the HLS approach. HLS is a feasible, time-efficient, scalable technology for tree mapping in mixed forests with potential to support forest monitoring programmes such as national forest inventories lacking three-dimensional, remote sensing data to support field measurements.
Linear and Nonlinear Land Use Regression Approach for Modelling PM2.5 Concentration in Ulaanbaatar, Mongolia during Peak Hours
Authors: Enkhjargal Odbaatar , Lamchin Munkhnasan , Chambers Jonathan , You Xue-Yi
Published: February 2023

In recent decades, air pollution in Ulaanbaatar has become a challenge regarding the health of the citizens of Ulaanbaatar, due to coal combustion in the ger area. Households burn fuel for cooking and to warm their houses in the morning and evening. This creates a difference between daytime and nighttime air pollution levels. The accurate mapping of air pollution and assessment of exposure to air pollution have thus become important study objects for researchers. The city center is where most air quality monitoring stations are located, but they are unable to monitor every residential region, particularly the ger area, which is where most particulate matter pollution originates. Due to this circumstance, it is difficult to construct an LUR model for the entire capital city’s residential region. This study aims to map peak PM2.5 dispersion during the day using the Linear and Nonlinear Land Use Regression (LUR) model (Multi-Linear Regression Model (MLRM) and Generalized Additive Model (GAM)) for Ulaanbaatar, with monitoring station measurements and mobile device (DUST TRUK II) measurements. LUR models are frequently used to map small-scale spatial variations in element levels for various types of air pollution, based on measurements and geographical predictors. PM2.5 measurement data were collected and analyzed in the R statistical software and ArcGIS. The results showed the dispersion map MLRM R2 = 0.84, adjusted R2 = 0.83, RMSE = 53.25 µg/m3 and GAM R2 = 0.89, and adjusted R2 = 0.87, RMSE = 44 µg/m3. In order to validate the models, the LOOCV technique was run on both the MLRM and GAM. Their performance was also high, with LOOCV R2 = 0.83, RMSE = 55.6 µg/m3, MAE = 38.7 µg/m3, and GAM LOOCV R2 = 0.77, RMSE = 65.5 µg/m3, MAE = 47.7 µg/m3. From these results, the LUR model’s performance is high, especially the GAM model, which works better than MRLM.
Analysis of the Difference between Climate Aridity Index and Meteorological Drought Index in the Summer Monsoon Transition Zone
Authors: Zhang Hongli , Zhang Liang , Zhang Qiang , Liu Qian , You Xiaoni , Wang Lixia
Published: February 2023

The summer monsoon transition zone (SMTZ) in China represents an unusual land type with an agro-pasture ecotone, and it is a climate-sensitive region. Changes in climate aridity and changes in meteorological drought are mutually related yet fundamentally different. In this study, potential evapotranspiration (ETO) is calculated using Penman–Monteith, based on China’s national meteorological stations data from 1961 to 2013. An ETO-based climate aridity index (IAI) and ETO-based standardized precipitation evapotranspiration index (SPEI) are used as the metrics for climate aridity and meteorological drought, respectively. The result shows a significant difference between climate aridity and meteorological drought in the SMTZ, compared with the monsoon and non-monsoon zone. This difference varies on different time scales (1–48 months), and the greatest differences between IAI and SPEI are on seasonal and monthly scales (1–12 months), but lower at longer time scales (>12 months). The first reason for the difference is the desynchronicity of meteorological drought and the background climate. After the background climate becomes a relatively arid state (such as 0.96 < IAI < 1) from a semi-arid state (0.50 < IAI < 0.80), the continued arid state with weak IAI fluctuations eventually results in increasingly severe meteorological droughts, or the recurrence of equally severe droughts with drastic reduction. Consequently, the onset of the most severe climate aridity is two to seven months (mostly three to four months) ahead of the onset of the most severe drought events, until the climate returns to a semi-arid state. Second, climate aridity represents the average state of the background climate over a long time period and changes gently, while meteorological droughts are stochastic climate events and change drastically. These findings indicate that IAI can serve as a predictor of the onset of meteorological drought events, especially in the SMTZ, but it fails to characterize the progression of meteorological drought events well. Therefore, this result is of great significance for drought prediction and early warning.
An Intercomparison of Sentinel-1 Based Change Detection Algorithms for Flood Mapping
Authors: Tupas Mark Edwin , Roth Florian , Bauer-Marschallinger Bernhard , Wagner Wolfgang
Published: February 2023

With its unrivaled and global land monitoring capability, the Sentinel-1 mission has been established as a prime provider in SAR-based flood mapping. Compared to suitable single-image flood algorithms, change-detection methods offer better robustness, retrieving flood extent from a classification of observed changes. This requires data-based parametrization. Moreover, in the scope of global and automatic flood services, the employed algorithms should not rely on locally optimized parameters, which cannot be automatically estimated and have spatially varying quality, impacting much on the mapping accuracy. Within the recently launched Global Flood Monitoring (GFM) service, we implemented a Bayes-Inference (BI)-based algorithm designed to meet these ends. However, whether other change detection algorithms perform similarly or better is unknown. This study examines four Sentinel-1 change detection models: The Normalized Difference Scattering Index (NDSI), Shannon’s entropy of NDSI (SNDSI), Standardized Residuals (SR), and Bayes Inference over Luzon in the Philippines, which was flood-hit by a typhoon in November 2020. After parametrization assessment against an expert-created Sentinel-1 flood map, the four models are inter-compared against an independent Sentinel-2 classification. The obtained findings indicate that the Bayes change detection profits from its scalable classification rules and shows the least sensitivity to parametrization choices while also performing best in terms of mapping accuracy. For all change detection models, a backscatter seasonality model for the no-flood reference delivered best results.
Topological Navigation for Autonomous Underwater Vehicles in Confined Semi-Structured Environments
Authors: Rossi Claudio , Caro Zapata Adrian , Milosevic Zorana , Suarez Ramon , Dominguez Sergio
Published: February 2023

In this work, we present the design, implementation, and simulation of a topology-based navigation system for the UX-series robots, a spherical underwater vehicle designed to explore and map flooded underground mines. The objective of the robot is to navigate autonomously in the 3D network of tunnels of a semi-structured but unknown environment in order to gather geoscientific data. We start from the assumption that a topological map has been generated by a low-level perception and SLAM module in the form of a labeled graph. However, the map is subject to uncertainties and reconstruction errors that the navigation system must address. First, a distance metric is defined to compute node-matching operations. This metric is then used to enable the robot to find its position on the map and navigate it. To assess the effectiveness of the proposed approach, extensive simulations have been carried out with different randomly generated topologies and various noise rates.
New Perspective on Planar Inductive Sensors: Radio-Frequency Refractometry for Highly Sensitive Quantification of Magnetic Nanoparticles
Authors: Marqués-Fernández José Luis , Salvador María , Martínez-García José Carlos , Fernández-Miaja Pablo , García-Arribas Alfredo , Rivas Montserrat
Published: February 2023

We demonstrate how resonant planar coils may be used as sensors to detect and quantify magnetic nanoparticles reliably. A coil’s resonant frequency depends on the adjacent materials’ magnetic permeability and electric permittivity. A small number of nanoparticles dispersed on a supporting matrix on top of a planar coil circuit may thus be quantified. Such nanoparticle detection has application detection to create new devices to assess biomedicine, food quality assurance, and environmental control challenges. We developed a mathematical model for the inductive sensor response at radio frequencies to obtain the nanoparticles’ mass from the self-resonance frequency of the coil. In the model, the calibration parameters only depend on the refraction index of the material around the coil, not on the separate magnetic permeability and electric permittivity. The model compares favourably with three-dimensional electromagnetic simulations and independent experimental measurements. The sensor can be scaled and automated in portable devices to measure small quantities of nanoparticles at a low cost. The resonant sensor combined with the mathematical model is a significant improvement over simple inductive sensors, which operate at smaller frequencies and do not have the required sensitivity, and oscillator-based inductive sensors, which focus on just magnetic permeability.
Prioritization Based Task Offloading in UAV-Assisted Edge Networks
Authors: Kalinagac Onur , Gür Gürkan , Alagöz Fatih
Published: February 2023

Under demanding operational conditions such as traffic surges, coverage issues, and low latency requirements, terrestrial networks may become inadequate to provide the expected service levels to users and applications. Moreover, when natural disasters or physical calamities occur, the existing network infrastructure may collapse, leading to formidable challenges for emergency communications in the area served. In order to provide wireless connectivity as well as facilitate a capacity boost under transient high service load situations, a substitute or auxiliary fast-deployable network is needed. Unmanned Aerial Vehicle (UAV) networks are well suited for such needs thanks to their high mobility and flexibility. In this work, we consider an edge network consisting of UAVs equipped with wireless access points. These software-defined network nodes serve a latency-sensitive workload of mobile users in an edge-to-cloud continuum setting. We investigate prioritization-based task offloading to support prioritized services in this on-demand aerial network. To serve this end, we construct an offloading management optimization model to minimize the overall penalty due to priority-weighted delay against task deadlines. Since the defined assignment problem is NP-hard, we also propose three heuristic algorithms as well as a branch and bound style quasi-optimal task offloading algorithm and investigate how the system performs under different operating conditions by conducting simulation-based experiments. Moreover, we made an open-source contribution to Mininet-WiFi to have independent Wi-Fi mediums, which were compulsory for simultaneous packet transfers on different Wi-Fi mediums.
A Cluster-Based 3D Reconstruction System for Large-Scale Scenes
Authors: Li Yao , Qi Yue , Wang Chen , Bao Yongtang
Published: February 2023

The reconstruction of realistic large-scale 3D scene models using aerial images or videos has significant applications in smart cities, surveying and mapping, the military and other fields. In the current state-of-the-art 3D-reconstruction pipeline, the massive scale of the scene and the enormous amount of input data are still considerable obstacles to the rapid reconstruction of large-scale 3D scene models. In this paper, we develop a professional system for large-scale 3D reconstruction. First, in the sparse point-cloud reconstruction stage, the computed matching relationships are used as the initial camera graph and divided into multiple subgraphs by a clustering algorithm. Multiple computational nodes execute the local structure-from-motion (SFM) technique, and local cameras are registered. Global camera alignment is achieved by integrating and optimizing all local camera poses. Second, in the dense point-cloud reconstruction stage, the adjacency information is decoupled from the pixel level by red-and-black checkerboard grid sampling. The optimal depth value is obtained using normalized cross-correlation (NCC). Additionally, during the mesh-reconstruction stage, feature-preserving mesh simplification, Laplace mesh-smoothing and mesh-detail-recovery methods are used to improve the quality of the mesh model. Finally, the above algorithms are integrated into our large-scale 3D-reconstruction system. Experiments show that the system can effectively improve the reconstruction speed of large-scale 3D scenes.
Opera 2015 Project: Accurate Measurement Equipment for Earthquake Electromagnetic Emissions and Radio Seismic Indicator
Authors: Romero Renato , Feletti Luca , Re Claudio , Mariscotti Andrea
Published: February 2023

Electromagnetic emissions from earthquakes are known as precursors and are of considerable importance for the purpose of early alarms. The propagation of low-frequency waves is favored, and the range between tens of mHz to tens of Hz has been heavily investigated in the last thirty years. This work describes the self-financed Opera 2015 project that initially consisted of six monitoring stations over Italy, equipped with electric and magnetic field sensors, among others. Insight of the designed antennas and low-noise electronic amplifiers provides both characterization of performance (similar to the best commercial products) and the elements to replicate the design for our own independent studies. Measured signals through data acquisition systems were then processed for spectral analysis and are available on the Opera 2015 website. Data provided by other world-known research institutes have also been considered for comparison. The work provides examples of processing methods and results representation, identifying many exogenous noise contributions of natural or human-made origin. The study of the results occurred for some years and led us to think that reliable precursors are confined to a short area around the earthquake due to the significant attenuation and the effect of overlapping noise sources. To this aim, a magnitude-distance indicator was developed to classify the detectability of the EQ events observed during 2015 and compared this with some other known earthquake events documented in the scientific literature.
Inline NMR via a Dedicated V-Shaped Sensor
Authors: Schmid Eric , Rondeau Simon , Rudszuck Thomas , Nirschl Hermann , Guthausen Gisela
Published: February 2023

Process monitoring and control require dedicated and reliable measures which reflect the status of the process under investigation. Although nuclear magnetic resonance is known to be a versatile analytical technique, it is only seldomly found in process monitoring. Single-sided nuclear magnetic resonance is one well known approach for being applied in process monitoring. The dedicated V-sensor is a recent approach that allows the inline investigation of materials in a pipe non-destructively and non-invasively. An open geometry of the radiofrequency unit is realized using a tailored coil, enabling the sensor to be applied for manifold mobile applications in in-line process monitoring. Stationary liquids were measured, and their properties were integrally quantified as the basis for successful process monitoring. The sensor, in its inline version, is presented along with its characteristics. An exemplary field of application is battery production in terms of anode slurries; thus, the first results on graphite slurries will demonstrate the added value of the sensor in process monitoring.
The Virtual Sleep Lab—A Novel Method for Accurate Four-Class Sleep Staging Using Heart-Rate Variability from Low-Cost Wearables
Authors: Topalidis Pavlos , Heib Dominik P. J. , Baron Sebastian , Eigl Esther-Sevil , Hinterberger Alexandra , Schabus Manuel
Published: February 2023

Sleep staging based on polysomnography (PSG) performed by human experts is the de facto “gold standard” for the objective measurement of sleep. PSG and manual sleep staging is, however, personnel-intensive and time-consuming and it is thus impractical to monitor a person’s sleep architecture over extended periods. Here, we present a novel, low-cost, automatized, deep learning alternative to PSG sleep staging that provides a reliable epoch-by-epoch four-class sleep staging approach (Wake, Light [N1 + N2], Deep, REM) based solely on inter-beat-interval (IBI) data. Having trained a multi-resolution convolutional neural network (MCNN) on the IBIs of 8898 full-night manually sleep-staged recordings, we tested the MCNN on sleep classification using the IBIs of two low-cost (<EUR 100) consumer wearables: an optical heart rate sensor (VS) and a breast belt (H10), both produced by POLAR®. The overall classification accuracy reached levels comparable to expert inter-rater reliability for both devices (VS: 81%, κ = 0.69; H10: 80.3%, κ = 0.69). In addition, we used the H10 and recorded daily ECG data from 49 participants with sleep complaints over the course of a digital CBT-I-based sleep training program implemented in the App NUKKUAA™. As proof of principle, we classified the IBIs extracted from H10 using the MCNN over the course of the training program and captured sleep-related changes. At the end of the program, participants reported significant improvements in subjective sleep quality and sleep onset latency. Similarly, objective sleep onset latency showed a trend toward improvement. Weekly sleep onset latency, wake time during sleep, and total sleep time also correlated significantly with the subjective reports. The combination of state-of-the-art machine learning with suitable wearables allows continuous and accurate monitoring of sleep in naturalistic settings with profound implications for answering basic and clinical research questions.
An Effective Sensor Architecture for Full-Attitude Determination in the HERMES Nano-Satellites
Authors: Colagrossi Andrea , Lavagna Michèle , Bertacin Roberto
Published: February 2023

The High Energy Rapid Modular Ensemble of Satellites (HERMES) is a constellation of 3U nano-satellites for high energy astrophysics. The HERMES nano-satellites’ components have been designed, verified, and tested to detect and localize energetic astrophysical transients, such as short gamma-ray bursts (GRBs), which are the electromagnetic counterparts of gravitational wave events, thanks to novel miniaturized detectors sensitive to X-rays and gamma-rays. The space segment is composed of a constellation of CubeSats in low-Earth orbit (LEO), ensuring an accurate transient localization in a field of view of several steradians exploiting the triangulation technique. To achieve this goal, guaranteeing a solid support to future multi-messenger astrophysics, HERMES shall determine its attitude and orbital states with stringent requirements. The scientific measurements bind the attitude knowledge within 1 deg (1σa) and the orbital position knowledge within 10 m (1σo). These performances shall be reached considering the mass, volume, power, and computation constraints of a 3U nano-satellite platform. Thus, an effective sensor architecture for full-attitude determination was developed for the HERMES nano-satellites. The paper describes the hardware typologies and specifications, the configuration on the spacecraft, and the software elements to process the sensors’ data to estimate the full-attitude and orbital states in such a complex nano-satellite mission. The aim of this study was to fully characterize the proposed sensor architecture, highlighting the available attitude and orbit determination performance and discussing the calibration and determination functions to be implemented on-board. The presented results derived from model-in-the-loop (MIL) and hardware-in-the-loop (HIL) verification and testing activities and can serve as useful resources and a benchmark for future nano-satellite missions.