bluuebunny/crossref_metadata_2025 huggingface dataset:
Patient’s and Consultant’s Views and Perceptions on Switching from an Originator Biologic to Biosimilar Medication: A Qualitative Study
Authors: Rosembert D. C. , Twigg M. J. , Wright D. J.
Published: April 2024

The aim of this study was to describe the opinions of patients undergoing treatment with originator biologics and medical consultants managing their conditions and identify the barriers and enablers to transitioning from originator biologics to equivalent biosimilars. This study was undertaken prior to biosimilar switching at a large teaching hospital in the United Kingdom. Five gastroenterology, rheumatology, and dermatology consultants were interviewed. Two focus groups were conducted with patients prescribed infliximab (n = 2) and etanercept originators (n = 7). Four main themes emerged, as follows: (1) ‘Benefit to the NHS’; (2) ‘Evidence for efficacy and safety’; (3) ‘Team roles’; and (4) ‘Effective communication during switching’, with sub-themes such as (4a) ‘What patients want to know’ and (4b) ‘How it should be communicated’. Recognition of the ability to save NHS money was an enabler for both patients and consultants, with patients wanting to be reassured that the money saved would be used to benefit other patients. Consultants did not always believe that biosimilars had similar efficacy as the originators or that the manufacturing standards were the same. Effective interventions to address these concerns are required. Offering patients the opportunity to revert back to their originator if necessary was seen as an enabler, as was the provision of readily available mechanisms for reporting suspected adverse events resulting from switching. The role of pharmacy in the process of switching from originator biologics to biosimilars can range from educating consultants regarding the safety and efficacy of biosimilars, explaining the rationale for switching patients, and providing a route for reporting adverse events.
Low Diversity and High Genetic Structure for Platonia insignis Mart., an Endangered Fruit Tree Species
Authors: Garcia Caroline Bertocco , Silva Allison Vieira da , Carvalho Igor Araújo Santos de , Nascimento Wellington Ferreira do , Ramos Santiago Linorio Ferreyra , Rodrigues Doriane Picanço , Zucchi Maria Imaculada , Costa Flaviane Malaquias , Alves-Pereira Alessandro , Batista Carlos Eduardo de Araújo , Amaral Dario Dantas , Veasey Elizabeth Ann
Published: April 2024

Platonia insignis is a fruit tree native to Brazil of increasing economic importance, with its pulp trading among the highest market values. This study aimed to evaluate the structure and genomic diversity of P. insignis (bacurizeiro) accessions from six locations in the Brazilian States of Roraima, Amazonas, Pará (Amazon biome), and Maranhão (Cerrado biome). A total of 2031 SNP markers were obtained using genotyping-by-sequencing (GBS), from which 625 outlier SNPs were identified. High genetic structure was observed, with most of the genetic variability (59%) concentrated among locations, mainly between biomes (Amazon and Cerrado). A positive and significant correlation (r = 0.85; p < 0.005) was detected between genetic and geographic distances, indicating isolation by distance. The highest genetic diversity was observed for the location in the Cerrado biome (HE = 0.1746; HO = 0.2078). The locations in the Amazon biome showed low genetic diversity indexes with significant levels of inbreeding. The advance of urban areas, events of burning, and expansion of agricultural activities are most probably the main factors for the genetic diversity reduction of P. insignis. Approaches to functional analysis showed that most of the outlier loci found may be related to genes involved in cellular and metabolic processes.
The Combination of Low-Cost, Red–Green–Blue (RGB) Image Analysis and Machine Learning to Screen for Barley Plant Resistance to Net Blotch
Authors: Leiva Fernanda , Dhakal Rishap , Himanen Kristiina , Ortiz Rodomiro , Chawade Aakash
Published: April 2024

Challenges of climate change and growth population are exacerbated by noticeable environmental changes, which can increase the range of plant diseases, for instance, net blotch (NB), a foliar disease which significantly decreases barley (Hordeum vulgare L.) grain yield and quality. A resistant germplasm is usually identified through visual observation and the scoring of disease symptoms; however, this is subjective and time-consuming. Thus, automated, non-destructive, and low-cost disease-scoring approaches are highly relevant to barley breeding. This study presents a novel screening method for evaluating NB severity in barley. The proposed method uses an automated RGB imaging system, together with machine learning, to evaluate different symptoms and the severity of NB. The study was performed on three barley cultivars with distinct levels of resistance to NB (resistant, moderately resistant, and susceptible). The tested approach showed mean precision of 99% for various categories of NB severity (chlorotic, necrotic, and fungal lesions, along with leaf tip necrosis). The results demonstrate that the proposed method could be effective in assessing NB from barley leaves and specifying the level of NB severity; this type of information could be pivotal to precise selection for NB resistance in barley breeding.
Phytoremediation Performance with Ornamental Plants in Monocultures and Polycultures Conditions Using Constructed Wetlands Technology
Authors: Marín-Muñiz José Luis , Zitácuaro-Contreras Irma , Ortega-Pineda Gonzalo , López-Roldán Aarón , Vidal-Álvarez Monserrat , Martínez-Aguilar Karina E. , Álvarez-Hernández Luis M. , Zamora-Castro Sergio
Published: April 2024

The assessment of constructed wetlands (CWs) has gained interest in the last 20 years for wastewater treatment in Latin American regions. However, the effects of culture systems with different ornamental species in CWs for phytoremediation are little known. In this study, some chemical parameters such as total suspended solids (TSS), chemical oxygen demand (COD), phosphate (PO4-P), and ammonium (NH4-N) were analyzed in order to prove the removal of pollutants by phytoremediation in CWs. The environmental impact index based on eutrophication reduction (EI-E) was also calculated to estimate the cause-effect relationship using CWs in different culture conditions. C. hybrids and Dieffenbachia seguine were used in monoculture and polyculture (both species mixed) mesocosm CWs. One hundred eighty days of the study showed that CWs with plants in monoculture/polyculture conditions removed significant amounts of organic matter (TSS and COD) (p > 0.05; 40–55% TSS and 80–90% COD). Nitrogen and phosphorous compounds were significantly lower in the monoculture of D. seguine (p < 0.05) than in monocultures of C. hybrids, and polyculture systems. EI-E indicator was inversely proportional to the phosphorous removed, showing a smaller environmental impact with the polyculture systems (0.006 kg PO₄3− eq removed) than monocultures, identifying the influence of polyculture systems on the potential environmental impacts compared with the phytoremediation function in monocultures (0.011–0.014 kg PO₄3− eq removed). Future research is required to determine other types of categories of environmental impact index and compare them with other wastewater treatment systems and plants. Phytoremediation with the ornamental plants studied in CWs is a good option for wastewater treatment using a plant-based cleanup technology.
Structure and Properties of Exopolysaccharide Produced by Gluconobacter frateurii and Its Potential Applications
Authors: Ning Yingying , Cao Huiying , Zhao Shouqi , Gao Dongni , Zhao Dan
Published: April 2024

An exopolysaccharide (EPS)-producing bacterium was isolated from apricot fermentation broth and identified as Gluconobacter frateurii HDC-08 (accession number: OK036475.1). HDC-08 EPS is a linear homopolysaccharide mainly composed of glucose linked by α-(1,6) glucoside bonds. It contains C, H, N and S elements, with a molecular weight of 4.774 × 106 Da. Microscopically, it has a smooth, glossy and compact sheet structure. It is an amorphous noncrystalline substance with irregular coils. Moreover, the EPS showed surface hydrophobicity and high thermal stability with a degradation temperature of 250.76 °C. In addition, it had strong antioxidant properties against DPPH radicals, ABPS radicals, hydroxyl radicals and H2O2. The EPS exhibited high metal-chelating activity and strong emulsifying ability for soybean oil, petroleum ether and diesel oil. The milk solidification test indicated that the EPS had good potential in fermented dairy products. In general, all the results demonstrate that HDC-08 EPS has promise for commercial applications as a food additive and antioxidant.
Effect of Biodegradable Nonwoven Mulches from Natural and Renewable Sources on Lettuce Cultivation
Authors: Marasovic Paula , Kopitar Dragana , Peremin-Volf Tomislava , Andreata-Koren Marcela
Published: April 2024

Numerous research showed that mulching with conventional agro foils elevates soil temperature and promotes plant growth, but negatively influences soil health and brings environmental concerns. Most of the published research on nonwoven mulches for plant cultivation includes nonwoven fabrics produced by extrusion processes providing nonwoven fabric structures similar to films. A limited number of studies investigate the impact of nonwoven mulches produced by a mechanical process on the cards and bonded by needling on plant cultivation. For this study, nonwoven mulches of mass per unit area of 400 g m−2 made from jute, hemp, viscose (CV), and polylactide (PLA) fibers were produced on the card bonded by needle punching. The field experiment was conducted two consecutive years in a row, in spring 2022 and 2023, by planting lettuce seedlings. The nonwoven mulches maintain lower temperatures and higher soil moisture levels compared to agro foil and the control field. The fibrous structure and their water absorption properties allow natural ventilation, regulating temperatures and retaining moisture of soil, consequently improving soil quality, lettuce yield, and quality. The fiber type from which the mulches were produced, influenced soil temperature and humidity, soil quality, and lettuce cultivation. The nonwoven mulches were successful in weed control concerning the weediness of the control field. Based on the obtained results, the newly produced mulches are likely to yield better results when used for the cultivation of vegetables with longer growing periods. Newly produced biodegradable nonwoven mulches could be an eco-friendly alternative to traditional agro foil, minimizing environmental harm during decomposition. The obtained results suggest that the newly produced mulches would be even more suitable for growing vegetables with longer growing seasons.
Microbially Mediated Rubber Recycling to Facilitate the Valorization of Scrap Tires
Authors: Kabir Sk Faisal , Sundar Skanda Vishnu , Robles Aide , Miranda Evelyn M. , Delgado Anca G. , Fini Elham H.
Published: April 2024

The recycling of scrap tire rubber requires high levels of energy, which poses challenges to its proper valorization. The application of rubber in construction requires significant mechanical and/or chemical treatment of scrap rubber to compatiblize it with the surrounding matrix. These methods are energy-consuming and costly and may lead to environmental concerns associated with chemical leachates. Furthermore, recent methods usually call for single-size rubber particles or a narrow rubber particle size distribution; this, in turn, adds to the pre-processing cost. Here, we used microbial etching (e.g., microbial metabolism) to modify the surface of rubber particles of varying sizes. Specifically, we subjected rubber particles with diameters of 1.18 mm and 0.6 mm to incubation in flask bioreactors containing a mineral medium with thiosulfate and acetate and inoculated them with a microbial culture from waste-activated sludge. The near-stoichiometric oxidation of thiosulfate to sulfate was observed in the bioreactors. Most notably, two of the most potent rubber-degrading bacteria (Gordonia and Nocardia) were found to be significantly enriched in the medium. In the absence of added thiosulfate in the medium, sulfate production, likely from the desulfurization of the rubber, was also observed. Microbial etching increased the surface polarity of rubber particles, enhancing their interactions with bitumen. This was evidenced by an 82% reduction in rubber–bitumen separation when 1.18 mm microbially etched rubber was used. The study outcomes provide supporting evidence for a rubber recycling method that is environmentally friendly and has a low cost, promoting pavement sustainability and resource conservation.
“Their End Is Destruction”: Reading Philippians as Philosophical Dialogue
Authors: Covington Eric
Published: April 2024

Paul’s address to the ekklesia in Philippi evidences an ideological conflict within the community. The letter encourages the community to persevere in a prescribed philosophy while simultaneously recognizing the presence of “opponents” (Phil 1:28) and “enemies” (Phil 3:18) against whom the community must “stand firm” (Phil 4:1). Building on Pierre Hadot’s work in identifying ancient philosophy as a “way of life”, this article examines the nature of this ideological conflict by reading Philippians in light of the conventions of ancient philosophical dialogue. While the letter does not take the strict literary structure of a formal dialogue, it can rightly be understood as a philosophical text that is engaging in a critical conversation about competing philosophical “ways of life”. In this philosophical dialogue, Paul critiques the alternative way of life on offer to the Philippian ekklesia by portraying it as an insufficient way of life that will lead to destruction. He simultaneously presents his own philosophy as the one that is consistent with the appropriate “goal,” the right “mind,” and a consistent “way of life” that will help the community attain their ultimate telos.
Combined Contaminant Levels from Local Harvested Food Items in the Norwegian–Finnish–Russian Border Region
Authors: Nalbandyan-Schwarz Anna , Bondo Pedersen Kristine , Evenset Anita , Heimstad Eldbjørg , Sandanger Torkjel M. , Myllynen Päivi , Rautio Arja
Published: April 2024

This paper presents the results of a multidisciplinary study with the aim of assessing the potential combined risk from consuming locally harvested food products in the Euro-Arctic region of Norway, Finland, and Russia. The three important contaminant groups—radioactive substances, heavy metals, and persistent organic pollutants (POPs)—were measured in food samples such as berries, mushrooms, fish, birds, reindeer, and moose; they were sampled in 2013–2015. To assess the combined pollution levels and investigate the trends, similarities, and variations between different contaminant groups, subsequent multivariate statistical analysis was performed. The results showed that, in general, the levels of radioactive substances, toxic elements, and POPs were below the permitted EU maximum content in food products. However, statistical analysis revealed some correlations, similarities, and peculiarities between the accumulation of different contaminants in various species, which allowed for a better understanding of the mechanisms of accumulation and interaction between different contaminant groups. It also gave a better insight into the possible added risks and helped pinpoint species that could serve as reference markers for the accumulation of different contaminants in food. Mushrooms, fish, and reindeer were found to be important markers in the combined risk assessments for the contents of metals and radioactive substances. Further research, as well as the development of methodologies for combined assessments, are recommended.
Production and Quality Characteristics of Royal Jelly in Relation to Available Natural Food Resources
Authors: Kanelis Dimitrios , Liolios Vasilios , Rodopoulou Maria-Anna , Papadopoulou Fotini , Tananaki Chrysoula
Published: April 2024

Royal jelly is a secretion produced from the hypopharyngeal glands of worker bees, which requires significant pollen reserves to stimulate gland secretion. The natural sources of food available to the hive during beekeeping season can greatly affect the quantity and quality of produced royal jelly. In this study, samples of royal jelly were collected throughout the beekeeping season, and their physical and chemical characteristics were analyzed to understand how natural variations in bee diet affect royal jelly production. Before each sample collection, the bees’ food reserves were removed from the experimental colonies so that the royal jelly was produced solely from natural sources. The results showed that the production was significantly lower during the summer months compared with spring and autumn. Additionally, the moisture, protein, fructose, and glucose content of fresh royal jelly also showed significant changes in the summer, and all physical and chemical characteristics decreased when the fresh samples were converted into dry matter. It seems that the quality of pollen entering the hives has a direct impact on the physical and chemical properties of the final product, highlighting the crucial role of available resources in stimulating bees to produce royal jelly.
A Framework for Modeling, Optimization, and Musculoskeletal Simulation of an Elbow–Wrist Exosuit
Authors: KhalilianMotamed Bonab Ali , Chiaradia Domenico , Frisoli Antonio , Leonardis Daniele
Published: April 2024

The light weight and compliance of exosuits are valuable benefits not present rigid exoskeleton devices, yet these intriguing features make it challenging to properly model and simulate their interaction with the musculoskeletal system. Tendon-driven exosuits adopt an electrical motor combined with pulleys and cable transmission in the actuation stage. An important aspect of the design of these systems for the load transfer efficacy and comfort of the user is the anchor point positioning. In this paper, we propose a framework, whose first purpose is as a design methodology for the synthesis of an exosuit device, achieved by optimizing the anchor point location. The optimization procedure finds the best 3D position of the anchor points based on the interaction forces between the exosuit and the upper arm. The computation of the forces is based on the combination of a mathematical model of a wrist–elbow exosuit and a dynamic model of the upper arm. Its second purpose is the simulation of the kinematic and physiological effects of the interaction between the arm, the exosuit, and the complex upper limb musculoskeletal system. It offers insights into muscular and exoskeleton loading during operation. The presented experiments involve the development and validation of personalized musculoskeletal models, with kinematic, anthropometric, and electromyographic data measured in a load-lifting task. Simulation of the exosuit operation—coupled with the musculoskeletal model—showed the efficacy of the suit in assisting the wrist and elbow muscles and provided interesting highlights about the impact of the assistance on shoulder muscles. Finally, we provide a possible design of an elbow and wrist exosuit based on the optimized results.
Sub-Hourly Variations of Wind Shear in the Mesosphere-Lower Thermosphere as Observed by the China Meteor Radar Chain
Authors: Long Chi , Yu Tao , Zhang Jian , Yan Xiangxiang , Yang Na , Wang Jin , Xia Chunliang , Liang Yu , Ye Hailun
Published: April 2024

Wind shear has important implications for Kelvin–Helmholtz instability (KHI) and gravity waves (GWs) in the mesosphere–lower thermosphere (MLT) region where its momentum transport process is dominated by short-period (<1 h) GWs. However, the sub-hourly variation in wind shear is still not well quantified. This study aims to improve current understanding of vertical wind shear by analyzing multi-year meteor radar measurements at the Mohe (MH, 53.5°N, 122.3°E), Beijing (BJ, 40.3°N, 116.2°E), Wuhan (WH, 30.5°N, 114.6°E), and Fuke (FK, 19.5°N, 109.1°E) stations in China. The wind field is estimated by a new algorithm, e.g., the damped least squares fitting. Taking the wind shear estimated by normal products as a criterion, the shear produced by the new algorithm has more statistical convergence as compared to the traditional algorithm, e.g., the least squares fitting. Therefore, we argue that the 10 min DLSA wind probably produces a more reasonable vertical shear. Both intensive wind shears and GW kinetic energy can be simultaneously captured during the 0600–1600 UTs of May at MH and during the 1300–2400 UTs of March at FK, possibly implying that the up-propagation of GWs could contribute to the production of large wind shears. The sub-hourly variation in wind shears is potentially valuable for understanding the interrelationship between shear (or KHI) and GWs.
Introducing the Azimuth Cutoff as an Independent Measure for Characterizing Sea-State Dynamics in SAR Altimetry
Authors: Altiparmaki Ourania , Amraoui Samira , Kleinherenbrink Marcel , Moreau Thomas , Maraldi Claire , Visser Pieter N. A. M. , Naeije Marc
Published: April 2024

This study presents the first azimuth cutoff analysis in Synthetic Aperture Radar (SAR) altimetry, aiming to assess its applicability in characterizing sea-state dynamics. In SAR imaging, the azimuth cutoff serves as a proxy for the shortest waves, in terms of wavelength, that can be detected by the satellite under certain wind and wave conditions. The magnitude of this parameter is closely related to the wave orbital velocity variance, a key parameter for characterizing wind-wave systems. We exploit wave modulations exhibited in the tail of fully-focused SAR waveforms and extract the azimuth cutoff from the radar signal through the analysis of its along-track autocorrelation function. We showcase the capability of Sentinel-6A in deriving these two parameters based on analyses in the spatial and wavenumber domains, accompanied by a discussion of the limitations. We use Level-1A high-resolution Sentinel-6A data from one repeat cycle (10 days) globally to verify our findings against wave modeled data. In the spatial domain analysis, the estimation of azimuth cutoff involves fitting a Gaussian function to the along-track autocorrelation function. Results reveal pronounced dependencies on wind speed and significant wave height, factors primarily determining the magnitude of the velocity variance. In extreme sea states, the parameters are underestimated by the altimeter, while in relatively calm sea states and in the presence of swells, a substantial overestimation trend is observed. We introduce an alternative approach to extract the azimuth cutoff by identifying the fall-off wavenumber in the wavenumber domain. Results indicate effective mitigation of swell-induced errors, with some additional sensitivity to extreme sea states compared to the spatial domain approach.
CDEST: Class Distinguishability-Enhanced Self-Training Method for Adopting Pre-Trained Models to Downstream Remote Sensing Image Semantic Segmentation
Authors: Zhang Ming , Gu Xin , Qi Ji , Zhang Zhenshi , Yang Hemeng , Xu Jun , Peng Chengli , Li Haifeng
Published: April 2024

The self-supervised learning (SSL) technique, driven by massive unlabeled data, is expected to be a promising solution for semantic segmentation of remote sensing images (RSIs) with limited labeled data, revolutionizing transfer learning. Traditional ‘local-to-local’ transfer from small, local datasets to another target dataset plays an ever-shrinking role due to RSIs’ diverse distribution shifts. Instead, SSL promotes a ‘global-to-local’ transfer paradigm, in which generalized models pre-trained on arbitrarily large unlabeled datasets are fine-tuned to the target dataset to overcome data distribution shifts. However, the SSL pre-trained models may contain both useful and useless features for the downstream semantic segmentation task, due to the gap between the SSL tasks and the downstream task. To adapt such pre-trained models to semantic segmentation tasks, traditional supervised fine-tuning methods that use only a small number of labeled samples may drop out useful features due to overfitting. The main reason behind this is that supervised fine-tuning aims to map a few training samples from the high-dimensional, sparse image space to the low-dimensional, compact semantic space defined by the downstream labels, resulting in a degradation of the distinguishability. To address the above issues, we propose a class distinguishability-enhanced self-training (CDEST) method to support global-to-local transfer. First, the self-training module in CDEST introduces a semi-supervised learning mechanism to fully utilize the large amount of unlabeled data in the downstream task to increase the size and diversity of the training data, thus alleviating the problem of biased overfitting of the model. Second, the supervised and semi-supervised contrastive learning modules of CDEST can explicitly enhance the class distinguishability of features, helping to preserve the useful features learned from pre-training while adapting to downstream tasks. We evaluate the proposed CDEST method on four RSI semantic segmentation datasets, and our method achieves optimal experimental results on all four datasets compared to supervised fine-tuning as well as three semi-supervised fine-tuning methods.
Changes in Vegetation NDVI and Its Response to Climate Change and Human Activities in the Ferghana Basin from 1982 to 2015
Authors: Zhang Heli , Li Lu , Zhao Xiaoen , Chen Feng , Wei Jiachang , Feng Zhimin , Hou Tiyuan , Chen Youping , Yue Weipeng , Shang Huaming , Wang Shijie , Hu Mao
Published: April 2024

Exploring the evolution of vegetation cover and its drivers in the Ferghana Basin helps to understand the current ecological status of the Ferghana Basin and to analyze the vegetation changes and drivers, with a view to providing a scientific basis for regional ecological and environmental management and planning. Based on GIMMS NDVI3g and meteorological data, the spatial and temporal evolution characteristics of NDVI were analyzed from multiple perspectives with the help of linear trend and Mann–Kendall (MK) test methods using arcgis and the R language spatial analysis module, combined with partial correlation coefficients and residual analysis methods to analyze the impacts of climate change and human activities on the regional vegetation cover of the Ferghana Basin from 1982 to 2015. NDVI driving forces. The results showed the following: (1) The growing season of vegetation NDVI in the Ferghana Basin showed an increasing trend in the 34-year period, with an increase rate of 0.0044/10a, and the spatial distribution was significantly different, which was high in the central part of the country and low in the northern and southern parts of the country. (2) Temperature and precipitation simultaneously co-influenced the vegetation NDVI growth season, with most of the temperature and precipitation contributing in the spring, most of the temperature in the summer being negatively phased and the precipitation positively correlated, and most of the temperature and precipitation in the fall inhibiting vegetation NDVI growth. (3) The combined effect of climate change and human activities was the main reason for the overall rapid increase and great spatial variations in vegetation NDVI in China, and the spatial distribution of drivers, namely human activities and climate change, contributed 44.6% to vegetation NDVI in the growing season. The contribution of climate change and human activities to vegetation NDVI in the Ferghana Basin was 62.32% and 93.29%, respectively. The study suggests that more attention should be paid to the role of human activities and climate change in vegetation restoration to inform ecosystem management and green development.
Weighted Differential Gradient Method for Filling Pits in Light Detection and Ranging (LiDAR) Canopy Height Model
Authors: Zhou Guoqing , Li Haowen , Huang Jing , Gao Ertao , Song Tianyi , Han Xiaoting , Zhu Shuaiguang , Liu Jun
Published: April 2024

The canopy height model (CHM) derived from LiDAR point cloud data is usually used to accurately identify the position and the canopy dimension of single tree. However, local invalid values (also called data pits) are often encountered during the generation of CHM, which results in low-quality CHM and failure in the detection of treetops. For this reason, this paper proposes an innovative method, called “pixels weighted differential gradient”, to filter these data pits accurately and improve the quality of CHM. First, two characteristic parameters, gradient index (GI) and Z-score value (ZV) are extracted from the weighted differential gradient between the pit pixels and their eight neighbors, and then GIs and ZVs are commonly used as criterion for initial identification of data pits. Secondly, CHMs of different resolutions are merged, using the image processing algorithm developed in this paper to distinguish either canopy gaps or data pits. Finally, potential pits were filtered and filled with a reasonable value. The experimental validation and comparative analysis were carried out in a coniferous forest located in Triangle Lake, United States. The experimental results showed that our method could accurately identify potential data pits and retain the canopy structure information in CHM. The root-mean-squared error (RMSE) and mean bias error (MBE) from our method are reduced by between 73% and 26% and 76% and 28%, respectively, when compared with six other methods, including the mean filter, Gaussian filter, median filter, pit-free, spike-free and graph-based progressive morphological filtering (GPMF). The average F1 score from our method could be improved by approximately 4% to 25% when applied in single-tree extraction.
Construction of Aerosol Model and Atmospheric Correction in the Coastal Area of Shandong Peninsula
Authors: Shan Kunyang , Ma Chaofei , Lv Jingning , Zhao Dan , Song Qingjun
Published: April 2024

Applying standard aerosol models for atmospheric correction in nearshore coastal waters introduces significant uncertainties due to their inability to accurately represent aerosol characteristics in these regions. To improve the accuracy of remote sensing reflectance (Rrs) products in the nearshore waters of the Shandong Peninsula, this study develops an aerosol model based on aerosol data collected from the Mu Ping site in the coastal area of the Shandong Peninsula, enabling tailored atmospheric correction for this specific region. Given the pronounced seasonal variations in aerosol optical properties, monthly aerosol models were developed. The monthly aerosol model is derived using the average values of aerosol microphysical properties. Compared to the standard aerosol model, this model is more effective in characterizing the absorption and scattering characteristics of aerosols in the study area. Corresponding lookup tables for the aerosol model were created and integrated into the NIR-SWIR atmospheric correction algorithm. According to the accuracy evaluation indexes of RMSD, MAE, and UPD, it can be found that the atmospheric correction results of the aerosol model established in this paper are better than those of the standard aerosol model, especially in the 547 nm band. It demonstrates that the new aerosol model outperforms the standard model in atmospheric correction performance. With the increasing availability of aerosol observational data, the aerosol model is expected to become more accurate and applicable to other satellite missions.
Cyber–Physical Systems for High-Performance Machining of Difficult to Cut Materials in I5.0 Era—A Review
Authors: Gohari Hossein , Hassan Mahmoud , Shi Bin , Sadek Ahmad , Attia Helmi , M’Saoubi Rachid
Published: April 2024

The fifth Industrial revolution (I5.0) prioritizes resilience and sustainability, integrating cognitive cyber-physical systems and advanced technologies to enhance machining processes. Numerous research studies have been conducted to optimize machining operations by identifying and reducing sources of uncertainty and estimating the optimal cutting parameters. Virtual modeling and Tool Condition Monitoring (TCM) methodologies have been developed to assess the cutting states during machining processes. With a precise estimation of cutting states, the safety margin necessary to deal with uncertainties can be reduced, resulting in improved process productivity. This paper reviews the recent advances in high-performance machining systems, with a focus on cyber-physical models developed for the cutting operation of difficult-to-cut materials using cemented carbide tools. An overview of the literature and background on the advances in offline and online process optimization approaches are presented. Process optimization objectives such as tool life utilization, dynamic stability, enhanced productivity, improved machined part quality, reduced energy consumption, and carbon emissions are independently investigated for these offline and online optimization methods. Addressing the critical objectives and constraints prevalent in industrial applications, this paper explores the challenges and opportunities inherent to developing a robust cyber–physical optimization system.
Improved Catalytic Activity of Spherical Nucleic Acid Enzymes by Hybridization Chain Reaction and Its Application for Sensitive Analysis of Aflatoxin B1
Authors: Wang Wenjun , Li Xuesong , Zeng Kun , Lu Yanyan , Jia Boyuan , Lv Jianxia , Wu Chenghao , Wang Xinyu , Zhang Xinshuo , Zhang Zhen
Published: April 2024

Conventional spherical nucleic acid enzymes (SNAzymes), made with gold nanoparticle (AuNPs) cores and DNA shells, are widely applied in bioanalysis owing to their excellent physicochemical properties. Albeit important, the crowded catalytic units (such as G-quadruplex, G4) on the limited AuNPs surface inevitably influence their catalytic activities. Herin, a hybridization chain reaction (HCR) is employed as a means to expand the quantity and spaces of G4 enzymes for their catalytic ability enhancement. Through systematic investigations, we found that when an incomplete G4 sequence was linked at the sticky ends of the hairpins with split modes (3:1 and 2:2), this would significantly decrease the HCR hybridization capability due to increased steric hindrance. In contrast, the HCR hybridization capability was remarkably enhanced after the complete G4 sequence was directly modified at the non-sticky end of the hairpins, ascribed to the steric hindrance avoided. Accordingly, the improved SNAzymes using HCR were applied for the determination of AFB1 in food samples as a proof-of-concept, which exhibited outstanding performance (detection limit, 0.08 ng/mL). Importantly, our strategy provided a new insight for the catalytic activity improvement in SNAzymes using G4 as a signaling molecule.
Effective Energy Efficiency under Delay–Outage Probability Constraints and F-Composite Fading
Authors: Qasmi Fahad , Muhammad Irfan , Alves Hirley , Latva-aho Matti
Published: April 2024

The paradigm of the Next Generation cellular network (6G) and beyond is machine-type communications (MTCs), where numerous Internet of Things (IoT) devices operate autonomously without human intervention over wireless channels. IoT’s autonomous and energy-intensive characteristics highlight effective energy efficiency (EEE) as a crucial key performance indicator (KPI) of 6G. However, there is a lack of investigation on the EEE of random arrival traffic, which is the underlying platform for MTCs. In this work, we explore the distinct characteristics of F-composite fading channels, which specify the combined impact of multipath fading and shadowing. Furthermore, we evaluate the EEE over such fading under a finite blocklength regime and QoS constraints where IoT applications generate constant and sporadic traffic. We consider a point-to-point buffer-aided communication system model, where (1) an uplink transmission under a finite blocklength regime is examined; (2) we make realistic assumptions regarding the perfect channel state information (CSI) available at the receiver, and the channel is characterized by the F-composite fading model; and (3) due to its effectiveness and tractability, application data are found to have an average arrival rate calculated using Markovian sources models. To this end, we derive an exact closed-form expression for outage probability and the effective rate, which provides an accurate approximation for our analysis. Moreover, we determine the arrival and required service rates that satisfy the QoS constraints by applying effective bandwidth and capacity theories. The EEE is shown to be quasiconcave, with a trade-off between the transmit power and the rate for maximising the EEE. Measuring the impact of transmission power or rate individually is quite complex, but this complexity is further intensified when both variables are considered simultaneously. Thus, we formulate power allocation (PA) and rate allocation (RA) optimisation problems individually and jointly to maximise the EEE under a QoS constraint and solve such a problem numerically through a particle swarm optimization (PSO) algorithm. Finally, we examine the EEE performance in the context of line-of-sight and shadowing parameters.
Exploring Aesthetic Perception in Impaired Aging: A Multimodal Brain—Computer Interface Study
Authors: Clemente Livio , La Rocca Marianna , Paparella Giulia , Delussi Marianna , Tancredi Giusy , Ricci Katia , Procida Giuseppe , Introna Alessandro , Brunetti Antonio , Taurisano Paolo , Bevilacqua Vitoantonio , de Tommaso Marina
Published: April 2024

In the field of neuroscience, brain–computer interfaces (BCIs) are used to connect the human brain with external devices, providing insights into the neural mechanisms underlying cognitive processes, including aesthetic perception. Non-invasive BCIs, such as EEG and fNIRS, are critical for studying central nervous system activity and understanding how individuals with cognitive deficits process and respond to aesthetic stimuli. This study assessed twenty participants who were divided into control and impaired aging (AI) groups based on MMSE scores. EEG and fNIRS were used to measure their neurophysiological responses to aesthetic stimuli that varied in pleasantness and dynamism. Significant differences were identified between the groups in P300 amplitude and late positive potential (LPP), with controls showing greater reactivity. AI subjects showed an increase in oxyhemoglobin in response to pleasurable stimuli, suggesting hemodynamic compensation. This study highlights the effectiveness of multimodal BCIs in identifying the neural basis of aesthetic appreciation and impaired aging. Despite its limitations, such as sample size and the subjective nature of aesthetic appreciation, this research lays the groundwork for cognitive rehabilitation tailored to aesthetic perception, improving the comprehension of cognitive disorders through integrated BCI methodologies.
A Wireless Gamma-Ray Monitoring System for Cemented Radwaste Drums
Authors: Romoli Mauro , Di Giovanni Michele , Di Meo Paolo , Pandalone Antonio , Principe Claudio , Sabbarese Carlo , D’Onofrio Antonio , Prchal Karel , Záruba Jakub , Finocchiaro Paolo
Published: April 2024

In the framework of the PREDIS EU project, a wireless battery-operated gamma-ray detection system was developed in order to provide a medium-to-long-term monitoring system for radioactive waste drums. It was initially proposed to monitor the gamma radioactivity outcoming from steel drums containing cemented radwaste, even though it could be usefully employed in a wider range of applications. Gamma rays are penetrating and convey information from the drum's internal structure, as the count rate measured on the surface depends on the thickness and density of the crossed materials. A number of sensors arranged around a drum, typically four units, provide indications of the emission anisotropy, and any sensitive change in the measured count rate would hint at some anomaly, thus triggering a suitable inspection by operators.
A Novel Spider Monkey Optimization for Reliable Data Dissemination in VANETs Based on Machine Learning
Authors: Gupta Deepak , Rathi Rakesh
Published: April 2024

The growth in linked and autonomous vehicles has led to the emergence of vehicular ad hoc networks (VANETs) as a means to enhance road safety, traffic efficiency, and passenger comfort. However, VANETs face challenges in facilitating trustworthiness and high-quality services due to communication delays caused by traffic, dynamic topology changes, variable speeds, and other influencing factors. Hence, there is a need for a reliable data dissemination scheme capable of reducing communication delays among hops by identifying effective forwarder nodes. In this paper, we propose a novel, weighted, estimated, spider monkey-based, nature-inspired optimization (w-SMNO) method to generate a set of efficient relays. Additionally, we introduce a dynamic weight assignment and configuration model to enhance system accuracy using a neural network based on backpropagation with gradient descent optimization techniques to minimize errors in the machine learning model. The w-SMNO also incorporates a distinct algorithm for effective relay selection among multiple monkey spider groups. The simulation results demonstrate substantial improvements in w-SMNO, with a 35.7% increase in coverage, a 41.2% reduction in the end-to-end delay, a 36.4% improvement in the message delivery rate, and a 38.4% decrease in the collision rate compared to the state-of-the-art approaches.
Direction-of-Arrival Estimation via Sparse Bayesian Learning Exploiting Hierarchical Priors with Low Complexity
Authors: Li Ninghui , Zhang Xiaokuan , Lv Fan , Zong Binfeng
Published: April 2024

For direction-of-arrival (DOA) estimation problems in a sparse domain, sparse Bayesian learning (SBL) is highly favored by researchers owing to its excellent estimation performance. However, traditional SBL-based methods always assign Gaussian priors to parameters to be solved, leading to moderate sparse signal recovery (SSR) effects. The reason is Gaussian priors play a similar role to l2 regularization in sparsity constraint. Therefore, numerous methods are developed by adopting hierarchical priors that are used to perform better than Gaussian priors. However, these methods are in straitened circumstances when multiple measurement vector (MMV) data are adopted. On this basis, a block-sparse SBL method (named BSBL) is developed to handle DOA estimation problems in MMV models. The novelty of BSBL is the combination of hierarchical priors and block-sparse model originating from MMV data. Therefore, on the one hand, BSBL transfers the MMV model to a block-sparse model by vectorization so that Bayesian learning is directly performed, regardless of the prior independent assumption of different measurement vectors and the inconvenience caused by the solution of matrix form. On the other hand, BSBL inherited the advantage of hierarchical priors for better SSR ability. Despite the benefit, BSBL still has the disadvantage of relatively large computation complexity caused by high dimensional matrix operations. In view of this, two operations are implemented for low complexity. One is reducing the matrix dimension of BSBL by approximation, generating a method named BSBL-APPR, and the other is embedding the generalized approximate message passing (GAMB) technique into BSBL so as to decompose matrix operations into vector or scale operations, named BSBL-GAMP. Moreover, BSBL is able to suppress temporal correlation and handle wideband sources easily. Extensive simulation results are presented to prove the superiority of BSBL over other state-of-the-art algorithms.
Development of a Personal Guide Robot That Leads a Guest Hand-in-Hand While Keeping a Distance
Authors: Wakabayashi Hironobu , Hiroi Yutaka , Miyawaki Kenzaburo , Ito Akinori
Published: April 2024

This paper proposes a novel tour guide robot, “ASAHI ReBorn”, which can lead a guest by hand one-on-one while maintaining a proper distance from the guest. The robot uses a stretchable arm interface to hold the guest’s hand and adjusts its speed according to the guest’s pace. The robot also follows a given guide path accurately using the Robot Side method, a robot navigation method that follows a pre-defined path quickly and accurately. In addition, a control method is introduced that limits the angular velocity of the robot to avoid the robot’s quick turn while guiding the guest. We evaluated the performance and usability of the proposed robot through experiments and user studies. The tour-guiding experiment revealed that the proposed method that keeps distance between the robot and the guest using the stretchable arm enables the guests to look around the exhibits compared with the condition where the robot moved at a constant velocity.
Proposal of a Machine Learning Approach for Traffic Flow Prediction
Authors: Berlotti Mariaelena , Di Grande Sarah , Cavalieri Salvatore
Published: April 2024

Rapid global urbanization has led to a growing urban population, posing challenges in transportation management. Persistent issues such as traffic congestion, environmental pollution, and safety risks persist despite attempts to mitigate them, hindering urban progress. This paper focuses on the critical need for accurate traffic flow forecasting, considered one of the main effective solutions for containing traffic congestion in urban scenarios. The challenge of predicting traffic flow is addressed by proposing a two-level machine learning approach. The first level uses an unsupervised clustering model to extract patterns from sensor-generated data, while the second level employs supervised machine learning models. Although the proposed approach requires the availability of data from traffic sensors to realize the training of the machine learning models, it allows traffic flow prediction in urban areas without sensors. In order to verify the prediction capability of the proposed approach, a real urban scenario is considered.
Response Characteristics of Pressure-Sensitive Conductive Elastomer Sensors Using OFC Electrode with Triangular Wave Concavo-Convex Surfaces
Authors: Katagiri Takeru , Kodama Sogo , Kawahara Kotaro , Umemoto Kazuki , Miyoshi Takanori , Nakayama Tadachika
Published: April 2024

The sensor response of pressure-sensitive conductive elastomers using polymeric materials can be adjusted by altering the type and quantity of fillers used during manufacturing. Another method involves modifying the surface shape of the elastomer. This study investigates the sensor response by altering the surface shape of an electrode using a readily available pressure-sensitive conductive elastomer. By employing an oxygen-free copper electrode with a flat surface (with surface roughness parameters Ra = 0.064 μm and Rz = 0.564 μm) as a baseline, we examined the sensor system’s characteristics. Electrodes were fabricated with triangular wave concavo-convex surfaces, featuring tip angles of 60, 90, and 120°. Improved sensor responses were observed with electrodes having tip angles of 60 and 90°. Additionally, even with varying conductive properties of elastomers, the conductance of the elastomer sensor increased similarly when using an electrode with a 90° tip angle. This study demonstrates the potential for expanding the applications of conductive elastomer sensors, highlighting the noteworthy improvement in sensor response and performance achieved by altering the surface shape of electrodes used with commercially available conductive elastomers.