bluuebunny/crossref_metadata_2025 huggingface dataset:
Unveiling Clinical Relevance: Investigating Placentas Submitted for Histological Examination and Their Correlation with Clinical Indications and Histological Findings
Authors: Strahler Luisa , Horky Alexander , Spahn Stephan , Bahlmann Franz , Gradhand Elise
Published: July 2024

In Germany, there is currently no official guideline for the submission of placentas for histopathological examination. Placentas are sent for histological examination by obstetricians according to locally defined indications, which leads to different practices in different centers. In this study, two cohorts of placentas were compared to assess the clinical relevance of placental examination. One cohort consisted of placentas with a clinical indication for histologic examination and the other of placentas with a clinically healthy pregnancy and a healthy infant. In this study, a placenta request form based on established international guidelines was used. Placentas from singleton and twin pregnancies with and without clinical indications were histopathologically examined. Clinical information was extracted from the request form and later correlated with histological findings. A total of 236 placentas were examined, including 127 (53.8%) with clinical indications and 109 (46.2%) without. The concordance between submission reasons and histopathological findings was higher in singleton pregnancies with clinical indications (90.9%) compared to twin pregnancies (62.97%). Placentas from singleton and twin pregnancies with clinical indications exhibited significantly more pathological findings than their respective healthy control groups. Histopathological examination of the placenta can confirm or reveal placenta pathologies and therefore improve the care of the mother, child and future pregnancies.
Novel Aging Warm-Forming Process of Al-Zn-Mg Aluminum Alloy Sheets and Influence of Precipitate Characteristics on Warm Formability
Authors: Chen Wan-Ling , Lee Rong-Shean
Published: July 2024

Concurrently improving the formability and post-formed strength of Al-Zn-Mg alloy sheets is crucial for producing high-strength parts with complex shapes. A novel process of aging warm-forming (AWF) to form solution heat-treated and water-quenched aluminum alloy sheets is proposed in this paper. The as-quenched AA 7075 sheet was first pre-aged and then formed at the desired temperature. The automotive paint–bake process was then utilized as the second aging step to achieve the target strength of the formed part. Additionally, the post-formed strength and warm formability of specimens under the AWF process conditions, as well as the warm-forming of various heat-treated Al-Zn-Mg alloy sheets proposed in previous studies, were compared through tensile and limit dome height tests. Precipitate characteristics of specimens subjected to different warm-forming process conditions were examined to understand their impact on warm formability. The warm formability of Al-Zn-Mg alloy sheets was significantly enhanced, and the post-formed strength achieved was more than 90% of the strength of as-received AA 7075-T6 sheets under the AWF process condition. The results demonstrated the feasibility of this novel AWF process to manufacture Al-Zn-Mg alloy stamped parts for improved spring-back, formability, and good overall post-formed strength. The results also indicate that microstructural characteristics in Al-Zn-Mg alloy sheets under different warm-forming process conditions have a noticeable influence on warm formability and final mechanical properties.
Finite Element Simulation of Multi-Pass Rolling of a Pure Aluminum Target under Different Rolling Routes and Methods
Authors: Qiu Chaoxin , Xu Rui , Xu Xin , Ma Shengcan
Published: July 2024

By coordinating the rolling direction and mode, a multi-rolling plastic deformation process for an aluminum (Al) sputter target is proposed to achieve multiple excellent properties, including a uniform and fine grain structure and low defect risk, which are significant in producing high-quality sputtered films. In this work, therefore, DEFORM 3D 10.2 software is adopted to establish three strategies, clock-synchronous rolling, cross-synchronous rolling, and clock–snake rolling. The effect of different rolling routes and modes on the metal flow velocity (MFV), effective strain distribution (ESD), grain size distribution (GSD), damage, and rolling force (RF) are comparatively investigated. The simulation results show that clock–snake rolling can increase the MFV and effective strain by producing a deeper deformation than the others. It provides sufficient energy for dynamic recrystallization to promote grain refinement. In combination with the microstructure homogeneity promoted by the clock rolling route, the GSD from 6.5 to 44.3 μm accounts for about 80.5% of all the grains because of the fact that a randomly oriented grain region is full of high-angle grain boundaries. Compared with the synchronous rolling mode, the decrement in RF maximum reaches up to 51% during the asynchronous rolling process because component energy is consumed to form cross-sheering stress. It remarkably reduces the risk of defects, with a damage value of less than 73%, and simultaneously improves energy efficiency owing to smaller and uniform grains caused by less RF. The results obtained in this work are of great significance as they can guide practical production in the metal target industry.
The Action Mechanism of Rolling Texture on the Anisotropic Behavior of a Pure Titanium Plate
Authors: Wang Sanzhong , Li Wei , Huang Ziteng , Li Songsong , Zhang Genmao , Yu Hui
Published: July 2024

This work combined theoretical calculation with experimental characterization to methodically study the anisotropy mechanism and evolution of the plastic behavior of pure titanium. Initially, a constant-strain uniaxial tensile test was used to measure the anisotropy of the yield behavior along the rolling direction (RD) and transverse direction (TD). Subsequently, the information of crystal orientation both before and after deformation was statistically characterized using electron backscatter diffraction (EBSD). Ultimately, the main deformation mechanism was determined by combining Schmid law with an analysis of the variation of SF values of each deformation mode with the angular relationship between the loading axis and the grain’s c-axis. The findings demonstrate that, for each slip system, the variation trend and value of the SF are influenced by the angle formed by the loading axis and the grain’s c- and a-axes. The primary result of dislocation slip activation is the change of the tilt angle of the grain c-axis from ND to TD, but this has little effect on the tilt angle of the grain c-axis from ND to RD. Prismatic  slip dominates the tensile deformation along the RD. Pyramidal  slip and pyramidal  slip will be activated during the subsequent hardening, whereas basal  slip is difficult to activate. The prismatic  slip in the soft-oriented grain will be preferentially activated during the tensile deformation along the TD, and the prismatic  slip and pyramidal  slip will become the dominant deformation modes during the subsequent hardening. Some soft-oriented grains could activate basal  slip and pyramidal  slip, but dislocation slip is restricted and coordinated by {10-12}ET.
Cultivation of Fungal Endophytes with Tissue Culture Grapevine Seedlings Reprograms Metabolism by Triggering Defence Responses
Authors: Pan Xiaoxia , Liu Huizhi , Li Yiqian , Guo Lirong , Zhang Yunuo , Zhu Youyong , Yang Mingzhi
Published: July 2024

In this study, the transcriptome profiles of tissue–cultured grapevine (Vitis vinifera L. × Vitis labrusca L.: Rose Honey) seedlings inoculated with fungal endophytes Epicoccum layuense R2-21 (Epi R2-21) and Alternaria alternata XHYN2 (Alt XHYN2), were analyzed at three different time points (6 h, 6 d, and 15 d). A total of 4783 differentially expressed genes (DEGs) was found, of which 1853 (6 h), 3878 (6 d), and 4732 (15 d) were differentially expressed relative to those of the control in endophyte Epi R2-21 treatments, while a total of 5898 DEGs, of which 2726 (6 h), 4610 (6 d), and 3938 (15 d) were differentially expressed in endophyte Alt XHYN2 treatments. DEGs enriched in secondary metabolic pathways, plant–pathogen interaction, and hormone signalling were further analysed. The upregulated DEGs in the Epi R2-21 and Alt XHYN2 treatments, both enriched in the Kyoto Encyclopedia of Genes and Genomes (KEGG), were mainly involved in flavonoid biosynthesis, phenylpropanoid biosynthesis, stilbenoid, diarylheptanoid and gingerol biosynthesis, phenylalanine metabolism, and circadian rhythms–plant and plant–pathogen interactions, similar to the trend observed in our previous study conducted on the cultivar ‘Cabernet Sauvignon’ (Vitis vinifera L.). Taken together with the results obtained from the cultivar ‘Cabernet Sauvignon’, it was found that tissue-cultured seedlings of the cultivar ‘Rose Honey’ induced a stronger defence response to fungal endophyte infection than that of the cultivar ‘Cabernet Sauvignon’, and inoculation with the endophyte Alt XHYN2 triggered a stronger response than inoculation with the endophyte Epi R2-21. In addition, the protein–protein interaction (PPI) network revealed that the genes VIT_16s0100g00910, encoding CHS, and VIT_11s0065g00350, encoding CYP73A, were involved in secondary metabolism and thus mediated in the resistance mechanism of grapevine on both the cultivars. The results showed that inoculation with the endophytes Epi R2-21 and Alt XHYN2 had a great ability to induce defence responses and reprogram the gene expression profiles in different grapevine cultivars, which deepens our knowledge of the interaction between fungal endophytes and grapevine and gives hints for grape quality management in viticulture using candidate fungal endophytes.
Dual-Model Derailment Detection Algorithm Based on Variational Bayesian Kalman Filtering
Authors: Fan Shiwei , Gao Xu , Zhang Ya , Chen Huhe , Yi Guoxing , Hao Qiang
Published: July 2024

A derailment detection algorithm for railway freight cars based on micro inertial measurement units was designed to address the complex issue of the disassembly and assembly of derailment braking devices. Firstly, a horizontal attitude measurement model for freight cars was established, and attitude measurement algorithms based on gyroscopes and accelerometers were introduced. Subsequently, a high-precision attitude measurement algorithm based on variational Bayesian Kalman filtering was proposed, which used acceleration information as the observation data to correct attitude errors. In order to improve the accuracy of derailment detection, a dual-model instantaneous attitude difference measurement technique was further proposed. In order to verify the effectiveness of the algorithm, offline data from simulation experiments and in-vehicle experiments were used to validate the proposed algorithm. The results showed that the proposed algorithm can effectively improve the measurement accuracy of horizontal attitude changes, reducing the error by 89% compared to pure inertial attitude calculation, laying a technical foundation for improving the accuracy of derailment detection.
Comprehensive Analysis of Laser Peening Forming Effects on 5083 Aluminum Alloy
Authors: Kong Chuijiang , Zhang Xiaojun , Chen Gongling , Yuan Xiamin , Liu Bing , Zhu Ran
Published: July 2024

In order to investigate the laws of the laser peening forming process and the effects of laser peening on the surface quality and tensile properties of 5083 aluminum alloy, experiments were conducted utilizing various laser peening paths, energies, and plate thicknesses. Subsequently, laser peening forming experiments were performed on S-shaped and different shapes of aluminum alloy substrates. The impact of different laser peening durations on surface morphology and tensile properties was then analyzed. Results indicated that the largest bending deformation perpendicular to the laser peening path reached 12.5 mm. In cases where the laser peening path was inclined relative to the horizontal direction, torsional deformations were observed in the aluminum alloy plate. For laser energy levels of 5 J, 6 J, and 7 J, deformation amounts were 3.8 mm, 4.9 mm, and 5.4 mm, respectively. Plates with thicknesses of 4 mm exhibited convex deformation, while those with 2 mm thickness showed concave deformation. Furthermore, following one and two laser peening cycles, the residual stresses in the alloy plates were −80 MPa and −107 MPa, the surface hardness increased by 16 HV and 31 HV, the roughness increased by 2.495 μm and 3.615 μm, and the tensile strength increased by 9.5 MPa and 18.5 MPa, respectively.
Glass-Ceramic Materials with Luminescent Properties in the System ZnO-B2O3-Nb2O5-Eu2O3
Authors: Aleksandrov Lyubomir , Yordanova Aneliya , Milanova Margarita , Iordanova Reni , Tzvetkov Peter , Markov Pavel , Petrova Petia
Published: July 2024

In this paper, the crystallization behavior of 50ZnO:47B2O3:3Nb2O3:0.5Eu2O3 (G-0 h) glass has been investigated in detail by DSC, XRD and TEM analysis. The luminescent properties of the resulting glass-ceramics were also investigated. By XRD and TEM analysis, crystallization of several crystalline phases has been proved (α-Zn3B2O6, β-Zn3B2O6 and ZnNb2O6). By calculating crystal parameters, it was found that europium ions are successfully incorporated in the β-Zn3B2O6. Photo-luminescent spectra showed increased emission in the resulting glass-ceramic samples compared to the parent glass sample due to higher asymmetry of Eu3+ ions in the obtained crystalline phases. It was established that the optimum emission intensity is registered for glass-ceramic samples obtained after 25 h heat treatment of the parent glass.
Preparation of BN Nanoparticle with High Sintering Activity and Its Formation Mechanism
Authors: Li Qun , Zhang Kuo , Che Xiangming , Gao Tengchao , Wang Shuhuan , Ni Guolong
Published: July 2024

Hexagonal boron nitride (h-BN) nanoparticles have attracted increasing attention due to their unique structure and properties. However, it is difficult to synthesize h-BN nanoparticles with uniform spherical morphology due to their crystal characteristic. The morphology control by tuning their precursor synthesis is a promising and effective strategy to solve this problem. Especially, the treatment temperature of precursors plays an important role in the morphology and surface area of h-BN nanoparticles. Herein, h-BN nanoparticles with different morphologies were synthesized via regulating the treatment temperature of precursors. The result shows that treatment temperature will affect the microstructure and state of precursor and further influence the morphology of h-BN products. Benefiting from the unique structure, the h-BN obtained using 250 °C precursors shows higher specific surface area (61.1 m2 g−1) than that of 85 °C (36.5 m2 g−1) and 145 °C (27.9 m2 g−1). h-BN products obtained using 250 °C precursors show higher specific surface area than that of 85 °C and 145 °C. The optimal condition for obtaining high-quality spherical h-BN is the pretreatment temperature of 250 °C and sintering temperature of 1300 °C. Importantly, compared with commercial h-BN nanoparticles, the synthesized h-BN nanoparticles show more uniform structure and larger specific surface area, indicating that sintering activity will be greatly improved. Furthermore, the reaction pathway and formation mechanism of h-BN was revealed by DFT calculations. The result shows that the five stationary states and five transition states exist in the reaction pathway, and the energy barrier can be overcome at high temperatures to form a ring h-BN. In view of its simplicity and efficiency, this work is promising for designing and guiding the synthesis of h-BN nanoparticles with uniform morphology.
A Mechanistic Study on Iron-Based Styrene Aziridination: Understanding Epoxidation via Nitrene Hydrolysis
Authors: Lakk-Bogáth Dóra , Török Patrik , Pintarics Dénes , Kaizer József
Published: July 2024

Transition-metal-catalyzed nitrene transfer reactions are typically performed in organic solvents under inert and anhydrous conditions due to the involved air and water-sensitive nature of reactive intermediates. Overall, this study provides insights into the iron-based ([FeII(PBI)3](CF3SO3)2 (1), where PBI = 2-(2-pyridyl)benzimidazole), catalytic and stoichiometric aziridination of styrenes using PhINTs ([(N-tosylimino)iodo]benzene), highlighting the importance of reaction conditions including the effects of the solvent, co-ligands (para-substituted pyridines), and substrate substituents on the product yields, selectivity, and reaction kinetics. The aziridination reactions with 1/PhINTs showed higher conversion than epoxidation with 1/PhIO (iodosobenzene). However, the reaction with PhINTs was less selective and yielded more products, including styrene oxide, benzaldehyde, and 2-phenyl-1-tosylaziridine. Therefore, the main aim of this study was to investigate the potential role of water in the formation of oxygen-containing by-products during radical-type nitrene transfer catalysis. During the catalytic tests, a lower yield was obtained in a protic solvent (trifluoroethanol) than in acetonitrile. In the case of the catalytic oxidation of para-substituted styrenes containing electron-donating groups, higher yield, TON, and TOF were achieved than those with electron-withdrawing groups. Pseudo-first-order kinetics were observed for the stoichiometric oxidation, and the second-order rate constants (k2 = 7.16 × 10−3 M−1 s−1 in MeCN, 2.58 × 10−3 M−1 s−1 in CF3CH2OH) of the reaction were determined. The linear free energy relationships between the relative reaction rates (logkrel) and the total substituent effect (TE, 4R-PhCHCH2) parameters with slopes of 1.48 (MeCN) and 1.89 (CF3CH2OH) suggest that the stoichiometric aziridination of styrenes can be described through the formation of a radical intermediate in the rate-determining step. Styrene oxide formation during aqueous styrene aziridination most likely results from oxygen atom transfer via in situ iron oxo/oxyl radical complexes, which are formed through the hydrolysis of [FeIII(N•Ts)] under experimental conditions.
Chemical Orderings in CuCo Nanoparticles: Topological Modeling Using DFT Calculations
Authors: Neyman Konstantin M. , Alemany Pere
Published: July 2024

The orderings of atoms in bimetallic 1.6–2.1 nm-large CuCo nanoparticles, important as catalytic and magnetic materials, were studied using a combination of DFT calculations with a topological approach. The structure and magnetism of Cu50Co151, Cu101Co100, Cu151Co50, and Cu303Co102 nanoparticles; their resistance to disintegrating into separate Cu and Co species; as well as the exposed surface sites, were quantified and analyzed, showing a clear preference for Cu atoms to occupy surface positions while the Co atoms tended to form a compact cluster in the interior of the nanoparticles. The surface segregation of Co atoms that are encapsulated by less-active Cu atoms, induced by the adsorption of CO molecules, was already enabled at a low coverage of adsorbed CO, providing the energy required to displace the entire compact Co species inside the Cu matrices due to a notable adsorption preference of CO for the Co sites over the Cu ones. The calculated adsorption energies and vibrational frequencies of adsorbed CO should be helpful indicators for experimentally monitoring the nature of the surface sites of CuCo nanoparticles, especially in the case of active Co surface sites emerging in the presence of CO.
Proteins and Peptides Studied In Silico and In Vivo for the Treatment of Diabetes Mellitus: A Systematic Review
Authors: Medeiros Isaiane , Gomes Ana Francisca Teixeira , Oliveira e Silva Emilly Guedes , Bezerra Ingrid Wilza Leal , da Silva Maia Juliana Kelly , Piuvezam Grasiela , Morais Ana Heloneida de Araújo
Published: July 2024

Bioinformatics has expedited the screening of new efficient therapeutic agents for diseases such as diabetes mellitus (DM). The objective of this systematic review (SR) was to understand naturally occurring proteins and peptides studied in silico and subsequently reevaluated in vivo for treating DM, guided by the question: which peptides or proteins have been studied in silico for the treatment of diabetes mellitus? The RS protocol was registered in the International Prospective Register of Systematic Reviews database. Articles meeting the eligibility criteria were selected from the PubMed, ScienceDirect, Scopus, Web of Science, Virtual Health Library (VHL), and EMBASE databases. Five studies that investigated peptides or proteins analyzed in silico and in vivo were selected. Risk of bias assessment was conducted using the adapted Strengthening the Reporting of Empirical Simulation Studies (STRESS) tool. A diverse range of assessed proteins and/or peptides that had a natural origin were investigated in silico and corresponding in vivo reevaluation demonstrated reductions in glycemia and/or insulin, morphological enhancements in pancreatic β cells, and alterations in the gene expression of markers associated with DM. The in silico studies outlined offer crucial insights into therapeutic strategies for DM, along with promising leads for screening novel therapeutic agents in future trials.
Enhanced Stability and Compatibility of Montelukast and Levocetirizine in a Fixed-Dose Combination Monolayer Tablet
Authors: Yun Tae Han , Kim Moon Jung , Lee Jung Gyun , Bang Kyu Ho , Kim Kyeong Soo
Published: July 2024

The purpose of this study was to enhance the stability of montelukast and levocetirizine for the development of a fixed-dose combination (FDC) monolayer tablet. To evaluate the compatibility of montelukast and levocetirizine, a mixture of the two drugs was prepared, and changes in the appearance characteristics and impurity content were observed in a dry oven at 60 °C. Excipients that contributed minimally to impurity increases were selected to minimize drug interactions. Mannitol, microcrystalline cellulose, croscarmellose sodium, hypromellose, and sodium citrate were chosen as excipients, and montelukast–levocetirizine FDC monolayer tablets were prepared by wet granulating the two drugs separately. A separate granulation of montelukast and levocetirizine, along with the addition of sodium citrate as a pH stabilizer, minimized the changes in tablet appearance and impurity levels. The prepared tablets demonstrated release profiles equivalent to those of commercial products in comparative dissolution tests. Subsequent stability testing at 40 ± 2 °C and 75 ± 5% RH for 6 months confirmed that the drug content, dissolution rate, and impurity content met the specified acceptance criteria. In conclusion, the montelukast–levocetirizine FDC monolayer tablet developed in this study offers a potential alternative to commercial products.
“Continental Philosophy and Christian Beliefs”: Truth in Being
Authors: Morrison Glenn Joshua
Published: July 2024

The mystery of being touches upon the depths of God’s truth articulated as love [...]
Large-Scale Solar Potential Analysis in a 3D CAD Framework as a Use Case of Urban Digital Twins
Authors: Shirinyan Evgeny , Petrova-Antonova Dessislava
Published: July 2024

Solar radiation impacts diverse aspects of city life, such as harvesting energy with PV panels, passive heating of buildings in winter, cooling the loads of air-conditioning systems in summer, and the urban microclimate. Urban digital twins and 3D city models can support solar studies in the process of urban planning and provide valuable insights for data-driven decision support. This study examines the calculation of solar incident radiation at the city scale in Sofia using remote sensing data for the large shading context in a mountainous region and 3D building data. It aims to explore the methods of geometry optimisation, limitations, and performance issues of a 3D computer-aided design (CAD) tool dedicated to small-scale solar analysis and employed at the city scale. Two cases were considered at the city and district scales, respectively. The total face count of meshes for the simulations constituted approximately 2,000,000 faces. A total of 64,379 roofs for the whole city and 4796 buildings for one district were selected. All calculations were performed in one batch and visualised in a 3D web platform. The use of a 3D CAD environment establishes a seamless process of updating 3D models and simulations, while preprocessing in Geographic Information System (GIS) ensures working with large-scale datasets. The proposed method showed a moderate computation time for both cases and could be extended to include reflected radiation and dense photogrammetric meshes in the future.
Seasonal Variability in the Relationship between the Volume-Scattering Function at 180° and the Backscattering Coefficient Observed from Spaceborne Lidar and Biogeochemical Argo (BGC-Argo) Floats
Authors: Sun Miao , Chen Peng , Zhang Zhenhua , Li Yunzhou
Published: July 2024

The derivation of the particulate-backscattering coefficient (bbp) from Lidar signals is highly influenced by the parameter χp(π), which is defined by χp(π) = bbp/(2πβp(π)). This parameter facilitates the correlation of the particulate-volume-scattering function at 180°, denoted βp(π), with bbp. However, studies exploring the global and seasonal fluctuations of χp(π) remain sparse, largely due to measurement difficulties of βp(π) in the field conditions. This study pioneers the global data collection for χp(π), integrating bbp observations from Biogeochemical Argo (BGC-Argo) floats and βp(π) data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) spaceborne lidar. Our findings indicate that χp(π) experiences significant seasonal differences globally, peaking during summer and nadiring in winter. The global average χp(π) was calculated as 0.40, 0.48, 0.43, and 0.35 during spring, summer, autumn, and winter, respectively. The daytime values of χp(π) slightly exceeded those registered at night. To illuminate the seasonal variations in χp(π) in 26 sea regions worldwide, we deployed passive ocean color data MODIS bbp and active remote sensing data CALIOP βp(π), distinguishing three primary seasonal change patterns—the “summer peak”, the “decline”, and the “autumn pole”—with the “summer peak” typology being the most common. Post recalibration of the CALIOP bbp product considering seasonal χp(π) variations, we observed substantial statistical improvements. Specifically, the coefficient of determination (R2) markedly improved from 0.84 to 0.89, while the root mean square error (RMSE) declined from 4.0 × 10−4 m−1 to 3.0 × 10−4 m−1. Concurrently, the mean absolute percentage error (MAPE) also dropped significantly, from 31.48% to 25.27%.
Influence of Spotted Lanternfly (Lycorma delicatula) on Multiple Maple (Acer spp.) Species Canopy Foliar Spectral and Chemical Profiles
Authors: Joll Elisabeth G. , Ginzel Matthew D. , Hoover Kelli , Couture John J.
Published: July 2024

Invasive species have historically disrupted environments by outcompeting, displacing, and extirpating native species, resulting in significant environmental and economic damage. Developing approaches to detect the presence of invasive species, favorable habitats for their establishment, and predicting their potential spread are underutilized management strategies to effectively protect the environment and the economy. Spotted lanternfly (SLF, Lycorma delicatula) is a phloem-feeding planthopper native to China that poses a severe threat to horticultural and forest products in the United States. Tools are being developed to contain the spread and damage caused by SLF; however, methods to rapidly detect novel infestations or low-density populations are lacking. Vegetation spectroscopy is an approach that can represent vegetation health through changes in the reflectance and absorption of radiation based on plant physiochemical status. Here, we hypothesize that SLF infestations change the spectral and chemical characteristics of tree canopies. To test this hypothesis, we used a full range spectroradiometer to sample canopy foliage of silver maple (Acer saccharinum) and red maple (Acer rubrum) trees in a common garden in Berks County, Pennsylvania that were exposed to varying levels of SLF infestation. Foliar spectral profiles separated between SLF infestation levels, and the magnitude of separation was greater for the zero-SLF control compared with higher infestation levels. We found the red-edge and portions of the NIR and SWIR regions were most strongly related to SLF infestation densities and that corresponding changes in vegetation indexes related to levels of chlorophyll were influenced by SLF infestations, although we found no change in foliar levels of chlorophyll. We found no influence of SLF densities on levels of primary metabolites (i.e., pigments, nonstructural carbohydrates, carbon, and nitrogen), but did find an increase in the phenolic compound ferulic acid in response to increasing SLF infestations; this response was only in red maple, suggesting a possible species-specific response related to SLF feeding. By identifying changes in spectral and chemical properties of canopy leaves in response to SLF infestation, we can link them together to potentially better understand how trees respond to SLF feeding pressure and more rapidly identify SLF infestations.
Exploiting Soil and Remote Sensing Data Archives for 3D Mapping of Multiple Soil Properties at the Swiss National Scale
Authors: Stumpf Felix , Behrens Thorsten , Schmidt Karsten , Keller Armin
Published: July 2024

Soils play a central role in ecosystem functioning, and thus, mapped soil property information is indispensable to supporting sustainable land management. Digital Soil Mapping (DSM) provides a framework to spatially estimate soil properties. However, broad-scale DSM remains challenging because of non-purposively sampled soil data, large data volumes for processing extensive soil covariates, and high model complexities due to spatially varying soil–landscape relationships. This study presents a three-dimensional DSM framework for Switzerland, targeting the soil properties of clay content (Clay), organic carbon content (SOC), pH value (pH), and potential cation exchange capacity (CECpot). The DSM approach is based on machine learning and a comprehensive exploitation of soil and remote sensing data archives. Quantile Regression Forest was applied to link the soil sample data from a national soil data base with covariates derived from a LiDAR-based elevation model, from climate raster data, and from multispectral raster time series based on satellite imagery. The covariate set comprises spatially multiscale terrain attributes, climate patterns and their temporal variation, temporarily multiscale land use features, and spectral bare soil signatures. Soil data and predictions were evaluated with respect to different landcovers and depth intervals. All reference soil data sets were found to be spatially clustered towards croplands, showing an increasing sample density from lower to upper depth intervals. According to the R2 value derived from independent data, the overall model accuracy amounts to 0.69 for Clay, 0.64 for SOC, 0.76 for pH, and 0.72 for CECpot. Reduced model accuracies were found to be accompanied by soil data sets showing limited sample sizes (e.g., CECpot), uneven statistical distributions (e.g., SOC), and low spatial sample densities (e.g., woodland subsoils). Multiscale terrain covariates were highly influential for all models; climate covariates were particularly important for the Clay model; multiscale land use covariates showed enhanced importance for modeling pH; and bare soil reflectance was a major driver in the SOC and CECpot models.
Acquisition and Analysis of Facial Electromyographic Signals for Emotion Recognition
Authors: Kołodziej Marcin , Majkowski Andrzej , Jurczak Marcin
Published: July 2024

The objective of the article is to recognize users’ emotions by classifying facial electromyographic (EMG) signals. A biomedical signal amplifier, equipped with eight active electrodes positioned in accordance with the Facial Action Coding System, was used to record the EMG signals. These signals were registered during a procedure where users acted out various emotions: joy, sadness, surprise, disgust, anger, fear, and neutral. Recordings were made for 16 users. The mean power of the EMG signals formed the feature set. We utilized these features to train and evaluate various classifiers. In the subject-dependent model, the average classification accuracies were 96.3% for KNN, 94.9% for SVM with a linear kernel, 94.6% for SVM with a cubic kernel, and 93.8% for LDA. In the subject-independent model, the classification results varied depending on the tested user, ranging from 91.4% to 48.6% for the KNN classifier, with an average accuracy of 67.5%. The SVM with a cubic kernel performed slightly worse, achieving an average accuracy of 59.1%, followed by the SVM with a linear kernel at 53.9%, and the LDA classifier at 41.2%. Additionally, the study identified the most effective electrodes for distinguishing between pairs of emotions.
Node Localization Method in Wireless Sensor Networks Using Combined Crow Search and the Weighted Centroid Method
Authors: Sankaranarayanan Suresh , Vijayakumar Rajaram , Swaminathan Srividhya , Almarri Badar , Lorenz Pascal , Rodrigues Joel J. P. C.
Published: July 2024

Node localization is critical for accessing diverse nodes that provide services in remote places. Single-anchor localization techniques suffer co-linearity, performing poorly. The reliable multiple anchor node selection method is computationally intensive and requires a lot of processing power and time to identify suitable anchor nodes. Node localization in wireless sensor networks (WSNs) is challenging due to the number and placement of anchors, as well as their communication capabilities. These senor nodes possess limited energy resources, which is a big concern in localization. In addition to convention optimization in WSNs, researchers have employed nature-inspired algorithms to localize unknown nodes in WSN. However, these methods take longer, require lots of processing power, and have higher localization error, with a greater number of beacon nodes and sensitivity to parameter selection affecting localization. This research employed a nature-inspired crow search algorithm (an improvement over other nature-inspired algorithms) for selecting the suitable number of anchor nodes from the population, reducing errors in localizing unknown nodes. Additionally, the weighted centroid method was proposed for identifying the exact location of an unknown node. This made the crow search weighted centroid localization (CS-WCL) algorithm a more trustworthy and efficient method for node localization in WSNs, with reduced average localization error (ALE) and energy consumption. CS-WCL outperformed WCL and distance vector (DV)-Hop, with a reduced ALE of 15% (from 32%) and varying communication radii from 20 m to 45 m. Also, the ALE against scalability was validated for CS-WCL against WCL and DV-Hop for a varying number of beacon nodes (from 3 to 2), reducing ALE to 2.59% (from 28.75%). Lastly, CS-WCL resulted in reduced energy consumption (from 120 mJ to 45 mJ) for varying network nodes from 30 to 300 against WCL and DV-Hop. Thus, CS-WCL outperformed other nature-inspired algorithms in node localization. These have been validated using MATLAB 2022b.
Taste Sensor Assessment of Bitterness in Medicines: Overview and Recent Topics
Authors: Uchida Takahiro
Published: July 2024

In recent decades, taste sensors have been increasingly utilized to assess the taste of oral medicines, particularly focusing on bitterness, a major obstacle to patient acceptance and adherence. This objective and safe method holds promise for enhancing the development of patient-friendly medicines in pharmaceutical companies. This review article introduces its application in measuring the intensity of bitterness in medicine, confirming the achievement of taste masking, distinguishing taste differences between branded and generic medicines, and identifying substances to suppress bitterness in target medicines. Another application of the sensor is to predict a significant increase in bitterness when medicine is taken with certain foods/beverages or concomitant medication. Additionally, to verify the sensor’s predictability, a significant correlation has been demonstrated between the output of a bitter-sensitive sensor designed for drug bitterness (BT0) and the bitterness responses of the human taste receptor hT2R14 from BitterDB (huji.ac.il). As a recent advancement, a novel taste sensor equipped with lipid/polymer membranes modified by 3-Br-2,6-dihydroxybenzoic acid (2,6-DHBA), based on the concept of allostery, is introduced. This sensor successfully predicts the bitterness of non-charged pharmaceuticals with xanthine skeletons, such as caffeine or related compounds. Finally, the future prospects of taste sensors are discussed.
ABDGAN: Arbitrary Time Blur Decomposition Using Critic-Guided TripleGAN
Authors: Lee Tae Bok , Heo Yong Seok
Published: July 2024

Recent studies have proposed methods for extracting latent sharp frames from a single blurred image. However, these methods still suffer from limitations in restoring satisfactory images. In addition, most existing methods are limited to decomposing a blurred image into sharp frames with a fixed frame rate. To address these problems, we present an Arbitrary Time Blur Decomposition Triple Generative Adversarial Network (ABDGAN) that restores sharp frames with flexible frame rates. Our framework plays a min–max game consisting of a generator, a discriminator, and a time-code predictor. The generator serves as a time-conditional deblurring network, while the discriminator and the label predictor provide feedback to the generator on producing realistic and sharp image depending on given time code. To provide adequate feedback for the generator, we propose a critic-guided (CG) loss by collaboration of the discriminator and time-code predictor. We also propose a pairwise order-consistency (POC) loss to ensure that each pixel in a predicted image consistently corresponds to the same ground-truth frame. Extensive experiments show that our method outperforms previously reported methods in both qualitative and quantitative evaluations. Compared to the best competitor, the proposed ABDGAN improves PSNR, SSIM, and LPIPS on the GoPro test set by 16.67%, 9.16%, and 36.61%, respectively. For the B-Aist++ test set, our method shows improvements of 6.99%, 2.38%, and 17.05% in PSNR, SSIM, and LPIPS, respectively, compared to the best competitive method.
Electronic Noses: From Gas-Sensitive Components and Practical Applications to Data Processing
Authors: Zhai Zhenyu , Liu Yaqian , Li Congju , Wang Defa , Wu Hai
Published: July 2024

Artificial olfaction, also known as an electronic nose, is a gas identification device that replicates the human olfactory organ. This system integrates sensor arrays to detect gases, data acquisition for signal processing, and data analysis for precise identification, enabling it to assess gases both qualitatively and quantitatively in complex settings. This article provides a brief overview of the research progress in electronic nose technology, which is divided into three main elements, focusing on gas-sensitive materials, electronic nose applications, and data analysis methods. Furthermore, the review explores both traditional MOS materials and the newer porous materials like MOFs for gas sensors, summarizing the applications of electronic noses across diverse fields including disease diagnosis, environmental monitoring, food safety, and agricultural production. Additionally, it covers electronic nose pattern recognition and signal drift suppression algorithms. Ultimately, the summary identifies challenges faced by current systems and offers innovative solutions for future advancements. Overall, this endeavor forges a solid foundation and establishes a conceptual framework for ongoing research in the field.
A Survey of Autonomous Vehicle Behaviors: Trajectory Planning Algorithms, Sensed Collision Risks, and User Expectations
Authors: Xia Taokai , Chen Hui
Published: July 2024

Autonomous vehicles are rapidly advancing and have the potential to revolutionize transportation in the future. This paper primarily focuses on vehicle motion trajectory planning algorithms, examining the methods for estimating collision risks based on sensed environmental information and approaches for achieving user-aligned trajectory planning results. It investigates the different categories of planning algorithms within the scope of local trajectory planning applications for autonomous driving, discussing and differentiating their properties in detail through a review of the recent studies. The risk estimation methods are classified and introduced based on their descriptions of the sensed collision risks in traffic environments and their integration with trajectory planning algorithms. Additionally, various user experience-oriented methods, which utilize human data to enhance the trajectory planning performance and generate human-like trajectories, are explored. The paper provides comparative analyses of these algorithms and methods from different perspectives, revealing the interconnections between these topics. The current challenges and future prospects of the trajectory planning tasks in autonomous vehicles are also discussed.
Uncertain Knowledge: The Medicalisation of Intersex People and the Production of Ignorance
Authors: Raz Michal
Published: July 2024

Ignorance is produced through mechanisms related to power relations and socio-cultural context. This article examines whether the theoretical conceptualisation of agnotology may be useful when exploring intersex and the way it has been erased socially and physically. Specifically, based on the work of a PhD in Sociology and History of Science, it proposes categorising three types of mechanisms of ignorance production—cultural, epistemological and physical—with the aim of providing a greater understanding of how medicine, science and technology participate in a continuous process of erasing intersex bodies and lived experiences. Using medical literature, interviews and observations, the article focuses on a specific area of biomedical knowledge and intervention: the prenatal ‘treatment’ of Congenital Adrenal Hyperplasia (CAH) with dexamethasone or ‘prenatal DEX’. It shows how this procedure was pioneered by French doctors and how it continues to be practised in France despite numerous uncertainties and controversies inside and outside of the medical sphere.
Vehicle Stock Numbers and Survival Functions for On-Road Exhaust Emissions Analysis in India: 1993–2018
Authors: Guttikunda Sarath K.
Published: July 2024

Road transport plays a crucial role in sustaining all the personal and freight movement needs of residential, commercial, and industrial activities, and in Indian cities, big and small, vehicle exhaust emissions and dust from vehicle movement on the roads contribute to as much as 50% of particulate matter pollution in a year. Therefore, effective management of vehicle exhaust emissions is vital not only for improving current air quality but also for ensuring the long-term benefits from efforts to reduce air pollution. In the approved clean air action plans for 131 cities under the national clean air program (NCAP), more than 50% of the implementable actions are transport-centric. Having a reliable and replicable vehicle exhaust emissions inventory is essential for effective planning, which can help establish a baseline, support scenario analysis, and allow for tracking progress in the sector. This process begins with accessing accurate vehicle stock numbers, typically obtained from vehicle registration databases, traffic surveys, and other governmental records. Often, in low- and middle-income countries like India, these numbers require extensive data cleaning before they can be used for emissions and pollution analysis. This paper presents a cleaned, open-access vehicle stock database for India and outlines a methodology to build and maintain an in-use vehicle age-mix database for future years. The database covers the years 1993 to 2018 for the entire country and individual states, along with estimates of the age distribution of vehicles using survival functions. By offering a comprehensive and reliable data source, this paper aims to support sustainable national and urban air quality management efforts, helping policymakers and stakeholders make informed decisions to improve air quality and public health.
The Use of Grass Typology in Diagnosing and Sustainably Managing Permanent Grasslands
Authors: Ciprian Stroia , Ioan Sarac , Petrescu Irina , Onisan Emilian , Marius Stroia
Published: July 2024

Permanent grasslands are characterized by herbaceous flora adapted to local conditions, with deep root systems that facilitate resource uptake and provide resistance to anthropogenic and abiotic stresses. This study aimed to develop and implement efficient diagnostic and agronomic management tools for farmers. In order to demonstrate the methodology, we selected five diverse grasslands with different characteristics. The research tested the grass typology method to diagnose these areas and establish optimal management practices based on floristic composition. The method was applied to achieve the rational management of the grasslands studied. The results provided valuable data on floristic composition, species frequency, and specific functional indices. The characterization of the five grasslands in Moșnița Nouă in Timiș County enabled us to recognize optimal grassland strategies for each area, maximizing production based on the grass typology. Thus, the study demonstrated the impact of using simplified tools to improve grassland diagnosis and management, significantly contributing to the more sustainable maintenance of the permanent grasslands for farmers.
Exploring Sustainable Leisure Farm with Intelligent of Things (IoT) Technology Solution for Aging
Authors: Kuo Chun-Min , Wang Ching-Hsin , Tseng Chin-Yao , Lo Ying-Chen
Published: July 2024

Amid the increasingly severe challenges faced by traditional agricultural development, it has become necessary for farms to undergo operational transformations. In considering the direction of this transformation, the growing proportion of older adults in the population and the maturation of modern smart technologies applied to industries must be taken into account. By integrating intelligent Internet of Things (IoT) solutions to aid business operations, leisure farms are expected to provide significant benefits to both operators and visitors. Taiwan, which has long been a leader in precision agriculture, serves as a benchmark in Asia for the successful transformation of traditional farms into leisure farms, becoming a model for neighboring countries. This study investigates the transformative potential of intelligent IoT technology solutions on leisure farms, highlighting their capacity to attract senior citizens and create sustainable business models in competitive, homogeneous markets. The primary objective of this research is to uncover the advantageous factors associated with the adoption of intelligent IoT technology solutions in leisure farms. Employing a grounded theory approach, this research conducted face-to-face semi-structured interviews with 40 leisure farm operators to gain insights into the innovative and sustainable value propositions of leisure farms. This study identifies six key advantageous factors and six constraint factors. This research provides forward-looking insights into the application of intelligent IoT technology solutions in leisure farms, emphasizing strategic directions for operators. The integration of these solutions presents a unique opportunity for leisure farms to meet the demands of elderly individuals seeking safe, natural environments without compromising their interests. By offering tailored leisure activities and entertainment, these solutions enhance the quality of life of seniors and promote rural lifestyles, positioning leisure farms as innovative and competitive players in the market. The insights provided in this study can also inform government policymakers and serve as a foundation for future researchers to extend related studies from a customer perspective.