bluuebunny/crossref_metadata_2025 huggingface dataset:
The Role of DNA Repair (XPC, XPD, XPF, and XPG) Gene Polymorphisms in the Development of Myeloproliferative Neoplasms
Authors: Crișan Adriana-Stela , Tripon Florin , Bogliș Alina , Crauciuc George-Andrei , Trifa Adrian P. , Lázár Erzsébet , Macarie Ioan , Gabor Manuela Rozalia , Bănescu Claudia
Published: March 2024

Background and Objectives: Several polymorphisms have been described in various DNA repair genes. Nucleotide excision DNA repair (NER) detects defects of DNA molecules and corrects them to restore genome integrity. We hypothesized that the XPC, XPD, XPF, and XPG gene polymorphisms influence the appearance of myeloproliferative neoplasms (MPNs). Materials and Methods: We investigated the XPC 1496C>T (rs2228000, XPC Ala499Val), XPC 2920A>C (rs228001, XPC Lys939Gln), XPD 2251A>C (rs13181, XPD Lys751Gln), XPF-673C>T (rs3136038), XPF 11985A>G (rs254942), and XPG 3507G>C (rs17655, XPG Asp1104His) polymorphisms by polymerase chain reaction–restriction fragment length polymorphism analysis in 393 MPN patients [153 with polycythemia vera (PV), 201 with essential thrombocythemia (ET), and 39 with primary myelofibrosis (PMF)] and 323 healthy controls. Results: Overall, we found that variant genotypes of XPD 2251A>C were associated with an increased risk of MPN (OR = 1.54, 95% CI = 1.15–2.08, p = 0.004), while XPF-673C>T and XPF 11985A>G were associated with a decreased risk of developing MPN (OR = 0.56, 95% CI = 0.42–0.76, p < 0.001; and OR = 0.26, 95% CI = 0.19–0.37, p < 0.001, respectively). Conclusions: In light of our findings, XPD 2251A>C polymorphism was associated with the risk of developing MPN and XPF-673C>T and XPF 11985A>G single nucleotide polymorphisms (SNPs) may have a protective role for MPN, while XPC 1496C>T, XPC 2920A>C, and XPG 3507G>C polymorphisms do not represent risk factors in MPN development.
Cu2−xS and Cu2−xSe Alloys: Investigating the Influence of Ag, Zn, and Ni Doping on Structure and Transport Behavior
Authors: Mikuła Andrzej , Kurek Tomasz , Kożusznik Miłosz , Nieroda Paweł
Published: March 2024

Cu2−xS and Cu2−xSe (0 ≤ x ≤ 0.2) alloys stand out as highly promising materials for thermoelectric applications, owing to the phonon–liquid electron–crystal (PLEC) convention. In this study, we undertake a comprehensive investigation to reassess the synthesis conditions, with a focus on achieving pure-phased systems through a direct reaction between elements at elevated temperatures. Simultaneously, we present experimental evidence showcasing the feasibility of doping these systems with Ag, Ni, and Zn. The study demonstrates that obtaining single-phased systems requires multi-step processes, and the dissolution of chosen impurities appears doubtful, as evidenced by numerous foreign phase segregations. Additionally, it is revealed that the partial dissolution of individual impurities deteriorates the operational parameters of these chalcogenides. For the optimal Cu1.97S composition, it reduces the thermoelectric figure-of-merit ZT from 1.5 to approximately 1.0, 0.65, and 0.85 for Ag-, Ni-, and Zn-doped systems, respectively, while marginally improving their stability. For metal-like Cu1.8Se, the ZT parameter remains at a low level, ranging between 0.09 and 0.15, showing slight destabilization during subsequent operating cycles. The article concludes with an in-depth analysis of the basic thermoelectric performance exhibited by these doped systems, contributing valuable insights into the potential enhancements and applications of Cu2−xS and Cu2−xSe alloys in the field of thermoelectric materials.
Correction: Gargalis et al. A Comparative Investigation of Duplex and Super Duplex Stainless Steels Processed through Laser Powder Bed Fusion. Metals 2023, 13, 1897
Authors: Gargalis Leonidas , Karavias Leonidas , Graff Joachim S. , Diplas Spyros , Koumoulos Elias P. , Karaxi Evangelia K.
Published: March 2024

In the original publication [...]
Dynamic Protein Phosphorylation in Streptococcus pyogenes during Growth, Stationary Phase, and Starvation
Authors: Mikkat Stefan , Kreutzer Michael , Patenge Nadja
Published: March 2024

Phosphorylation of proteins at serine, threonine, and tyrosine residues plays an important role in physiological processes of bacteria, such as cell cycle, metabolism, virulence, dormancy, and stationary phase functions. Little is known about the targets and dynamics of protein phosphorylation in Streptococcus pyogenes, which possesses a single known transmembrane serine/threonine kinase belonging to the class of PASTA kinases. A proteomics and phosphoproteomics workflow was performed with S. pyogenes serotype M49 under different growth conditions, stationary phase, and starvation. The quantitative analysis of dynamic phosphorylation, which included a subset of 463 out of 815 identified phosphorylation sites, revealed two main types of phosphorylation events. A small group of phosphorylation events occurred almost exclusively at threonine residues of proteins related to the cell cycle and was enhanced in growing cells. The majority of phosphorylation events occurred during stationary phase or starvation, preferentially at serine residues. PASTA kinase-dependent cell cycle regulation processes found in related bacteria are conserved in S. pyogenes. Increased protein phosphorylation during the stationary phase has also been described for some other bacteria, and could therefore be a general feature in the physiology of bacteria, whose functions and the kinases involved need to be elucidated in further analyses.
Antimicrobial Use during the SARS-CoV-2 Pandemic in a Greek Tertiary University Hospital
Authors: Biros Dimitrios , Filippas-Ntekouan Sempastian , Limperatou Diamantina , Liontos Angelos , Matzaras Rafail , Tsarapatsani Konstantina-Helen , Kolios Nikolaos-Gavriel , Pappa Christiana , Nasiou Maria , Pargana Eleni , Tsiakas Ilias , Samanidou Valentini , Athanasiou Lazaros , Konstantopoulou Revekka , Milionis Haralampos , Christaki Eirini
Published: March 2024

In cases of SARS-CoV-2 hospitalization, despite low bacterial co-infection rates, antimicrobial use may be disproportionately high. Our aim was to quantify such usage in COVID-19 patients and identify factors linked to increased antibiotic use. We retrospectively studied patients with SARS-CoV-2 infection who were hospitalized at our institution during the pandemic. In the initial two waves of the pandemic, antimicrobial use was notably high (89% in the first wave and 92% in the second), but it decreased in subsequent waves. Elevated procalcitonin (>0.5 μg/mL) and C-reactive protein (>100 mg/L) levels were linked to antibiotic usage, while prior vaccination reduced antibiotic incidence. Antimicrobial use decreased in the pandemic, suggesting enhanced comprehension of SARS-CoV-2′s natural course. Additionally, it was correlated with heightened SARS-CoV-2 severity, elevated procalcitonin, and C-reactive protein levels.
Machine-Learning-Based Prediction of Plant Cuticle–Air Partition Coefficients for Organic Pollutants: Revealing Mechanisms from a Molecular Structure Perspective
Authors: Tao Tianyun , Tao Cuicui , Zhu Tengyi
Published: March 2024

Accurately predicting plant cuticle–air partition coefficients (Kca) is essential for assessing the ecological risk of organic pollutants and elucidating their partitioning mechanisms. The current work collected 255 measured Kca values from 25 plant species and 106 compounds (dataset (I)) and averaged them to establish a dataset (dataset (II)) containing Kca values for 106 compounds. Machine-learning algorithms (multiple linear regression (MLR), multi-layer perceptron (MLP), k-nearest neighbors (KNN), and gradient-boosting decision tree (GBDT)) were applied to develop eight QSPR models for predicting Kca. The results showed that the developed models had a high goodness of fit, as well as good robustness and predictive performance. The GBDT-2 model (Radj2 = 0.925, QLOO2 = 0.756, QBOOT2 = 0.864, Rext2 = 0.837, Qext2 = 0.811, and CCC = 0.891) is recommended as the best model for predicting Kca due to its superior performance. Moreover, interpreting the GBDT-1 and GBDT-2 models based on the Shapley additive explanations (SHAP) method elucidated how molecular properties, such as molecular size, polarizability, and molecular complexity, affected the capacity of plant cuticles to adsorb organic pollutants in the air. The satisfactory performance of the developed models suggests that they have the potential for extensive applications in guiding the environmental fate of organic pollutants and promoting the progress of eco-friendly and sustainable chemical engineering.
Detection of Adulterated Naodesheng Tablet (Naodesheng Pian) via In-Depth Chemical Analysis and Subsequent Reconstruction of Its Pharmacopoeia Q-Markers
Authors: Li Chunhou , Li Xican , Zeng Jingyuan , Cai Rongxin , Chen Shaoman , Chen Ban , Zhao Xiaojun
Published: March 2024

Naodesheng Tablet (Naodesheng Pian), a traditional Chinese medicine formula for stroke treatment, is made up of five herbal medicines, i.e., Sanqi, Gegen, Honghua, Shanzha, and Chuanxiong. However, the current Pharmacopoeia quality-marker (Q-marker) system cannot detect possible adulteration. Our study tried to use a new strategy, i.e., standards-library-dependent ultra-high-performance liquid chromatography-quadrupole-Orbitrap mass spectrometry (UHPLC-Q-Orbitrap MS/MS) putative identification, to reconstruct the Q-marker system. Through the strategy, 30 isomers were successfully differentiated (such as 2′-hydroxygenistein, luteolin, and kaempferol; ginsenoside Rg2 and ginsenoside Rg3; ginsenoside Rf and ginsenoside Rg1). In particular, 11 compounds were unexpectedly found in Naodesheng, including 2′-hydroxygenistein, 7,4′-dihydroxyflavone, pectolinarigenin, 7-methoxy-4′-hydroxyisoflavone, scoparone, matrine, 3,3′,4′,5,6,7,8-heptamethoxyflavone, 5-hydroxyflavone, diosgenin, chloesteryl acetate, and (+)-4-cholesten-3-one. In total, 68 compounds were putatively identified and fully elucidated for their MS spectra. Subsequently, relevant compounds were further investigated using UV-vis scanning experiments, semi-quantitative analysis, and quantum chemical calculation. Finally, five adulterated Naodesheng Tablets were used for validation experiments. The experiment successfully detected five adulterated ones via a lower-version LC-MS analysis. On this basis, three new candidates (hydroxy safflor yellow A (HSYA), citric acid, and levistilide A), along with puerarin and notoginsenoside R1, are re-nominated as the Q-markers for LC-MS analysis. The LC-MS analysis of puerarin, notoginsenoside R1, HSYA, citric acid, and levistilide A can clearly detect adulteration regarding all five herbal medicines mentioned above. Therefore, the reconstructed Q-markers are described as a “perfect” quality control system to detect adulteration in Naodesheng and will offer a valuable recommendation for the Pharmacopoeia Commission.
Short-Chain Sulfur Confined into Nitrogen-Doped Hollow Carbon Nanospheres for High-Capacity Potassium Storage
Authors: Liu Wenhan , Shi Tengfei , Liu Fang , Yang Chen , Qiao Fan , Han Kang , Han Chunhua , Meng Jiashen , Wang Xuanpeng
Published: March 2024

Carbon-based materials are one of the ideal negative electrode materials for potassium ion batteries. However, the limited active sites and sluggish diffusion ion kinetics still hinder its commercialization process. To address these problems, we design a novel carbon composite anode, by confining highly reactive short-chain sulfur molecules into nitrogen-doped hollow carbon nanospheres (termed SHC-450). The formation process involves the controlled synthesis of hollow polyaniline (PANI) nanospheres as precursors via an Ostwald ripening mechanism and subsequent sulfuration treatment. The high content of constrained short-chain sulfur molecules (20.94 wt%) and considerable N (7.15 wt%) ensure sufficient active sites for K+ storage in SHC-450. Accordingly, the SHC-450 electrode exhibits a high reversible capacity of 472.05 mAh g−1 at 0.1 A g−1 and good rate capability (172 mAh g−1 at 2 A g−1). Thermogravimetric analysis shows that SHC-450 has impressive thermal stability to withstand a high temperature of up to 640 °C. Ex situ spectroscopic characterizations reveal that the short-chain sulfur provides high capacity through reversible formation of K2S. Moreover, its special hollow structure not only provides ample space for highly active short-chain sulfur reactants but also effectively mitigates volume expansion during the sulfur conversion process. This work offers new perspectives on enhanced K+ storage performance from an interesting anode design and the space-limited domain principle.
Beau’s Lines and COVID-19; A Systematic Review on Their Association
Authors: Agouridis Aris P. , Mastori-Kourmpani Christina , Antoniou Polyna , Konstantinou Paschalis , Rizos Evangelos C. , Tsioutis Constantinos
Published: March 2024

Background: Beau’s lines are transverse grooves in the nail plate that result from transient interruption of the growth of the proximal nail matrix after severe disease. The aim of this study is to systematically report all evidence on the association of Beau’s lines with COVID-19 infection or vaccination against COVID-19. Methods: PubMed and Scopus databases were searched up to January 2024 for articles reporting Beau’s lines associated with COVID-19 infection or vaccination for COVID-19. PROSPERO ID: CRD42024496830. Results: PubMed search identified 299 records while Scopus search identified 18 records. After screening the bibliography, nine studies including 35 cases were included in our systematic review. The studies were reported from different areas around the world. Included studies documented Beau’s lines following COVID-19 vaccination (two studies) or after COVID-19 infection (seven studies). High variability was recorded in onset and resolution times among included cases, averaging 3 months and 6 months after COVID-19 infection, respectively. In the two studies reporting Beau’s lines after vaccination, onset was at 7 days and 6 weeks and resolution occurred after 8 and 17 weeks, respectively. Conclusions: To the best of our knowledge, this is the first systematic review reporting the association of Beau’s lines with COVID-19 infection and vaccination. Severe immune response can result in the formation of these nail disorders. Of importance, Beau’s lines represent a potential indicator of prior severe COVID-19 infection or vaccination for COVID-19, as well as a sign of long COVID-19 syndrome.
Lactoferrins in Their Interactions with Molecular Targets: A Structure-Based Overview
Authors: Piacentini Roberta , Boffi Alberto , Milanetti Edoardo
Published: March 2024

Lactoferrins and lactoferrin-derived peptides display numerous functions linked to innate immunity in mammalians, spanning from antimicrobial to anti-inflammatory and immunomodulatory actions, and even demonstrate antitumor properties. To date, the proposed mechanisms for their biological actions are varied, although the molecular basis that governs lactoferrin interactions with molecular targets has been clarified only in a limited number of specific cases. However, key in silico methods have recently moved the topic to the fore, thus greatly expanding the possibilities of large-scale investigations on macromolecular interactions involving lactoferrins and their molecular targets. This review aims to summarize the current knowledge on the structural determinants that drive lactoferrin recognition of molecular targets, with primary focus on the mechanisms of activity against bacteria and viruses. The understanding of the structural details of lactoferrins’ interaction with their molecular partners is in fact a crucial goal for the development of novel pharmaceutical products.
Fourth Generation Human Rights in View of the Fourth Industrial Revolution
Authors: Baroni Manuel Jesús López
Published: March 2024

We are at the dawn of the Fourth Industrial Revolution, characterised by the interaction of so-called disruptive technologies (biotechnology, synthetic biology, nanotechnology, neurotechnology and artificial intelligence). We believe that the challenges posed by technoscience cannot be met by the three generations of human rights that already exist. The need to create a fourth generation of human rights is, therefore, explored in this article. For that purpose, the state of the art will be analysed from a scientific and ethical perspective. We will consider the position of academic doctrines on the issues that a fourth generation of human rights should tackle. And, finally, in this fourth generation, we will propose the principles of identity and precaution as reference values, equivalent to the role played by freedom, equality and solidarity in the first three generations of human rights.
Ostracod Assemblages in the East Siberian Sea: A Comparative Study of River-Influenced and River-Isolated Shelf Ecosystems
Authors: Zenina Maria , Ovsepyan Ekaterina , Ovsepyan Yaroslav
Published: March 2024

The East Siberian Sea (ESS) is one of the least studied seas in terms of ostracod fauna. Ostracods are sensitive organisms to environmental changes, and detailed information on their ecology is still required. To fill this knowledge gap, we studied 33 meiobenthic dredge samples collected from the western part of the ESS and the Chaun Bay together with 17 grab samples taken from the eastern part of the sea. Quantitative analyses of the ostracod assemblages demonstrate that the river-influenced western part of the ESS is inhabited by low diverse and impoverished fauna consisting of the taxa which are able to adapt to different environmental conditions. In the isolated Chaun Bay sheltered from significant riverine influence, the ostracod assemblages contain species that prefer more stable conditions. The predominance of living specimens over dead ones and individual valves points to strong carbonate dissolution that is more pronounced in the western ESS than in the Chaun Bay. The formation of such conditions might be related to the high content of dissolved carbon dioxide resulting from bacterial remineralization of in situ produced and land-derived organic matter in the bottom sediments and low pH near the seabed. Numerous ferromanganese crusts were found on the ostracod valve surfaces and inside the shells from the Chaun Bay.
Biomass Densification to Improve Management Efficiency and to Obtain High Value Products in México
Authors: Rosales-Serna Rigoberto , Carrillo-Parra Artemio , Ríos-Saucedo Julio César , Reyes-Jáquez Damián , Sierra-Zurita Donaji , Santana-Espinoza Saúl , Jiménez-Ocampo Rafael , Domínguez-Martínez Pablo Alfredo , Nava-Berumen Cynthia Adriana
Published: March 2024

In México, the utilization of fast-growing plant species for biomass production presents transportation-related issues such as freshness reduction, the transportation of large volumes with minimal weight due to low density, limited storage availability, and logistical challenges. To enhance understanding in this field, the research aimed to evaluate the densification potential of a variety of organic materials, with a specific emphasis on the biomass derived from eight species of rapidly growing plants, three animal species’ manure, and concentrated feed. After conditioning, 100 g samples underwent particle size analysis and were categorized into seven sizes. Pellets and briquettes (40 g, 10% moisture, 15 MPa pressure, 5 min processing, 80 °C temperature) were produced and evaluated for bulk density (BD) and pellet (PD) and briquette durability (BDU). The predominant particle sizes were 0.850 mm and 0.425 mm. Original biomass bulk density (OBBD) varied notably, with ovine manure (0.50 g cm−3) and cattle feed (0.49 g cm−3) exhibiting the highest values. Caprine manure (0.83 g cm−3) and ovine manure (0.78 g cm−3) yielded the densest pellets at 1.76 and 1.84 g cm−3, respectively. Apple tree pellets achieved premium quality with the highest hardness (97.9%). Cattle manure (1.25 g cm−3) and cattle feed (1.25 g cm−3) had the densest briquettes, with notable BBD/OBBD ratios in pine sawdust (4.6) and corn (4.5). Caprine manure and Acacia biomass briquettes showed premium quality with the highest hardness (99.1%), emphasizing densification variations and the need for tailored approaches based on organic material characteristics.
Multistage Interaction Network for Remote Sensing Change Detection
Authors: Zhou Meng , Qian Weixian , Ren Kan
Published: March 2024

Change detection in remote sensing imagery is vital for Earth monitoring but faces challenges such as background complexity and pseudo-changes. Effective interaction between bitemporal images is crucial for accurate change information extraction. This paper presents a multistage interaction network designed for effective change detection, incorporating interaction at the image, feature, and decision levels. At the image level, change information is directly extracted from intensity changes, mitigating potential change information loss during feature extraction. Instead of separately extracting features from bitemporal images, the feature-level interaction jointly extracts features from bitemporal images. By enhancing relevance to spatial variant information and shared semantic channels, the network excels in overcoming background complexity and pseudo-changes. The decision-level interaction combines image-level and feature-level interactions, producing multiscale feature differences for precise change prediction. Extensive experiments demonstrate the superior performance of our method compared to existing approaches, establishing it as a robust solution for remote sensing image change detection.
Joint Classification of Hyperspectral and LiDAR Data Based on Adaptive Gating Mechanism and Learnable Transformer
Authors: Wang Minhui , Sun Yaxiu , Xiang Jianhong , Sun Rui , Zhong Yu
Published: March 2024

Utilizing multi-modal data, as opposed to only hyperspectral image (HSI), enhances target identification accuracy in remote sensing. Transformers are applied to multi-modal data classification for their long-range dependency but often overlook intrinsic image structure by directly flattening image blocks into vectors. Moreover, as the encoder deepens, unprofitable information negatively impacts classification performance. Therefore, this paper proposes a learnable transformer with an adaptive gating mechanism (AGMLT). Firstly, a spectral–spatial adaptive gating mechanism (SSAGM) is designed to comprehensively extract the local information from images. It mainly contains point depthwise attention (PDWA) and asymmetric depthwise attention (ADWA). The former is for extracting spectral information of HSI, and the latter is for extracting spatial information of HSI and elevation information of LiDAR-derived rasterized digital surface models (LiDAR-DSM). By omitting linear layers, local continuity is maintained. Then, the layer Scale and learnable transition matrix are introduced to the original transformer encoder and self-attention to form the learnable transformer (L-Former). It improves data dynamics and prevents performance degradation as the encoder deepens. Subsequently, learnable cross-attention (LC-Attention) with the learnable transfer matrix is designed to augment the fusion of multi-modal data by enriching feature information. Finally, poly loss, known for its adaptability with multi-modal data, is employed in training the model. Experiments in the paper are conducted on four famous multi-modal datasets: Trento (TR), MUUFL (MU), Augsburg (AU), and Houston2013 (HU). The results show that AGMLT achieves optimal performance over some existing models.
Combining Multi-View UAV Photogrammetry, Thermal Imaging, and Computer Vision Can Derive Cost-Effective Ecological Indicators for Habitat Assessment
Authors: Hu Qiao , Zhang Ligang , Drahota Jeff , Woldt Wayne , Varner Dana , Bishop Andy , LaGrange Ted , Neale Christopher M. U. , Tang Zhenghong
Published: March 2024

Recent developments in Unmanned Aircraft Vehicles (UAVs), thermal imaging, and Auto-machine learning (AutoML) have shown high potential for precise wildlife surveys but have rarely been studied for habitat assessment. Here, we propose a framework that leverages these advanced techniques to achieve cost-effective habitat quality assessment from the perspective of actual wildlife community usage. The framework exploits vision intelligence hidden in the UAV thermal images and AutoML methods to achieve cost-effective wildlife distribution mapping, and then derives wildlife use indicators to imply habitat quality variance. We conducted UAV-based thermal wildlife surveys at three wetlands in the Rainwater Basin, Nebraska. Experiments were set to examine the optimal protocols, including various flight designs (61 and 122 m), feature types, and AutoML. The results showed that UAV images collected at 61 m with a spatial resolution of 7.5 cm, combined with Faster R-CNN, returned the optimal wildlife mapping (more than 90% accuracy). Results also indicated that the vision intelligence exploited can effectively transfer the redundant AutoML adaptation cycles into a fully automatic process (with around 33 times efficiency improvement for data labeling), facilitating cost-effective AutoML adaptation. Eventually, the derived ecological indicators can explain the wildlife use status well, reflecting potential within- and between-habitat quality variance.
Extraction of Forest Road Information from CubeSat Imagery Using Convolutional Neural Networks
Authors: Winiwarter Lukas , Coops Nicholas C. , Bastyr Alex , Roussel Jean-Romain , Zhao Daisy Q. R. , Lamb Clayton T. , Ford Adam T.
Published: March 2024

Forest roads provide access to remote wooded areas, serving as key transportation routes and contributing to human impact on the local environment. However, large animals, such as bears (Ursus sp.), moose (Alces alces), and caribou (Rangifer tarandus caribou), are affected by their presence. Many publicly available road layers are outdated or inaccurate, making the assessment of landscape objectives difficult. To address these gaps in road location data, we employ CubeSat Imagery from the Planet constellation to predict the occurrence of road probabilities using a SegNet Convolutional Neural Network. Our research examines the potential of a pre-trained neural network (VGG-16 trained on ImageNet) transferred to the remote sensing domain. The classification is refined through post-processing, which considers spatial misalignment and road width variability. On a withheld test subset, we achieve an overall accuracy of 99.1%, a precision of 76.1%, and a recall of 91.2% (F1-Score: 83.0%) after considering these effects. We investigate the performance with respect to canopy coverage using a spectral greenness index, topography (slope and aspect), and land cover metrics. Results found that predictions are best in flat areas, with low to medium canopy coverage, and in the forest (coniferous and deciduous) land cover classes. The results are vectorized into a drivable road network, allowing for vector-based routing and coverage analyses. Our approach digitized 14,359 km of roads in a 23,500 km2 area in British Columbia, Canada. Compared to a governmental dataset, our method missed 10,869 km but detected an additional 5774 km of roads connected to the network. Finally, we use the detected road locations to investigate road age by accessing an archive of Landsat data, allowing spatiotemporal modelling of road access to remote areas. This provides important information on the development of the road network over time and the calculation of impacts, such as cumulative effects on wildlife.
PolSAR Image Classification with Active Complex-Valued Convolutional-Wavelet Neural Network and Markov Random Fields
Authors: Liu Lu , Li Yongxiang
Published: March 2024

PolSAR image classification has attracted extensive significant research in recent decades. Aiming at improving PolSAR classification performance with speckle noise, this paper proposes an active complex-valued convolutional-wavelet neural network by incorporating dual-tree complex wavelet transform (DT-CWT) and Markov random field (MRF). In this approach, DT-CWT is introduced into the complex-valued convolutional neural network to suppress the speckle noise of PolSAR images and maintain the structures of learned feature maps. In addition, by applying active learning (AL), we iteratively select the most informative unlabeled training samples of PolSAR datasets. Moreover, MRF is utilized to obtain spatial local correlation information, which has been proven to be effective in improving classification performance. The experimental results on three benchmark PolSAR datasets demonstrate that the proposed method can achieve a significant classification performance gain in terms of its effectiveness and robustness beyond some state-of-the-art deep learning methods.
Vertical Profiles of Aerosols Induced by Dust, Smoke, and Fireworks in the Cold Region of Northeast China
Authors: Duanmu Lingjian , Chen Weiwei , Guo Li , Yuan Yuan , Yang Hongwu , Fu Jing , Song Guoqing , Xia Zixuan
Published: March 2024

Despite the long-term implementation of air pollution control policies in northeast China, severe haze pollution continues to occur frequently. With the adoption of a megacity (Changchun) in northeast China, we analysed the vertical characteristics of aerosols and the causes of aerosol pollution throughout the year using multisource data for providing recommendations for controlling pollution events (i.e., straw burning and fireworks). Based on a ground-based LiDAR, it was found that the extinction coefficient (EC) of aerosols at a height of 300 m in Changchun was highest in winter (0.44 km−1), followed by summer (0.28 km−1), with significant differences from those in warmer regions, such as the Yangtze River Delta. Therefore, it is recommended that air pollution control policies be differentiated between winter and summer. On Chinese New Year’s Eve in Changchun, the ignition of firecrackers during the day and night caused increases in the EC at a height of 500 m to 0.37 and 0.88 km−1, respectively. It is suggested that the regulation of firecracker ignition should be reduced during the day and strengthened at night. Based on the CALIPSO and backward trajectory analysis results, two events of dust–biomass-burning composite pollution were observed in March and April. In March, the primary aerosol component was dust from western Changchun, whereas in April, the main aerosol component was biomass-burning aerosols originating from northern and eastern Changchun. Hence, reducing the intensity of spring biomass burning can mitigate the occurrence of dust–biomass-burning composite pollution. These findings can provide emission policy suggestions for areas facing similar issues regarding biomass-burning transmission pollution and firework emissions.
Marine Bioluminescence: Simulation of Dynamics within a Pump-Through Bathyphotometer
Authors: Thombs Austin , Shulman Igor , Matt Silvia
Published: March 2024

Bioluminescence is light produced by organisms through chemical reactions. In most cases, bioluminescent organisms produce light in response to mechanical stimulation, including from shear around objects moving in the water. Many phytoplankton and zooplankton are capable of producing bioluminescence, which is commonly measured as bioluminescence potential, defined as mechanically stimulated light measured inside of a chambered pump-through bathyphotometer. We have developed a numerical model of a pump-through bathyphotometer and simulated flow using Lagrangian particles as an approximation for bioluminescent marine plankton taxa. The results indicate that all particles remain in the detection chamber for a residence time of at least 0.25 s. This suggests that the total first flash of bioluminescent autotrophic and heterotrophic dinoflagellates will be measured based on the existing literature regarding their flash duration. We have found low sensitivity of particle residence time to variations in particle size, density, or measurement depth. In addition, the results show that a high percentage of organisms may experience stimulation well before the detection chamber, or even multiple stimulations within the detection chamber. The results of this work serve to inform the processing of current bioluminescent potential data and assist in the development of future instruments.
Machine Learning and Deep Learning Techniques for Internet of Things Network Anomaly Detection—Current Research Trends
Authors: Rafique Saida Hafsa , Abdallah Amira , Musa Nura Shifa , Murugan Thangavel
Published: March 2024

With its exponential growth, the Internet of Things (IoT) has produced unprecedented levels of connectivity and data. Anomaly detection is a security feature that identifies instances in which system behavior deviates from the expected norm, facilitating the prompt identification and resolution of anomalies. When AI and the IoT are combined, anomaly detection becomes more effective, enhancing the reliability, efficacy, and integrity of IoT systems. AI-based anomaly detection systems are capable of identifying a wide range of threats in IoT environments, including brute force, buffer overflow, injection, replay attacks, DDoS assault, SQL injection, and back-door exploits. Intelligent Intrusion Detection Systems (IDSs) are imperative in IoT devices, which help detect anomalies or intrusions in a network, as the IoT is increasingly employed in several industries but possesses a large attack surface which presents more entry points for attackers. This study reviews the literature on anomaly detection in IoT infrastructure using machine learning and deep learning. This paper discusses the challenges in detecting intrusions and anomalies in IoT systems, highlighting the increasing number of attacks. It reviews recent work on machine learning and deep-learning anomaly detection schemes for IoT networks, summarizing the available literature. From this survey, it is concluded that further development of current systems is needed by using varied datasets, real-time testing, and making the systems scalable.
MeshID: Few-Shot Finger Gesture Based User Identification Using Orthogonal Signal Interference
Authors: Zheng Weiling , Zhang Yu , Jiang Landu , Zhang Dian , Gu Tao
Published: March 2024

Radio frequency (RF) technology has been applied to enable advanced behavioral sensing in human-computer interaction. Due to its device-free sensing capability and wide availability on Internet of Things devices. Enabling finger gesture-based identification with high accuracy can be challenging due to low RF signal resolution and user heterogeneity. In this paper, we propose MeshID, a novel RF-based user identification scheme that enables identification through finger gestures with high accuracy. MeshID significantly improves the sensing sensitivity on RF signal interference, and hence is able to extract subtle individual biometrics through velocity distribution profiling (VDP) features from less-distinct finger motions such as drawing digits in the air. We design an efficient few-shot model retraining framework based on first component reverse module, achieving high model robustness and performance in a complex environment. We conduct comprehensive real-world experiments and the results show that MeshID achieves a user identification accuracy of 95.17% on average in three indoor environments. The results indicate that MeshID outperforms the state-of-the-art in identification performance with less cost.
A Novel Machine Learning-Based ANFIS Calibrated RISS/GNSS Integration for Improved Navigation in Urban Environments
Authors: Mahdi Ahmed E. , Azouz Ahmed , Noureldin Aboelmagd , Abosekeen Ashraf
Published: March 2024

Autonomous vehicles (AVs) require accurate navigation, but the reliability of Global Navigation Satellite Systems (GNSS) can be degraded by signal blockage and multipath interference in urban areas. Therefore, a navigation system that integrates a calibrated Reduced Inertial Sensors System (RISS) with GNSS is proposed. The system employs a machine-learning-based Adaptive Neuro-Fuzzy Inference System (ANFIS) as a novel calibration technique to improve the accuracy and reliability of the RISS. The ANFIS-based RISS/GNSS integration provides a more precise navigation solution in such environments. The effectiveness of the proposed integration scheme was validated by conducting tests using real road trajectory and simulated GNSS outages ranging from 50 to 150 s. The results demonstrate a significant improvement in 2D position Root Mean Square Error (RMSE) of 43.8% and 28% compared to the traditional RISS/GNSS and the frequency modulated continuous wave (FMCW) Radar (Rad)/RISS/GNSS integrated navigation systems, respectively. Moreover, an improvement of 47.5% and 23.4% in 2D position maximum errors is achieved compared to the RISS/GNSS and the Rad/RISS/GNSS integrated navigation systems, respectively. These results reveal significant improvements in positioning accuracy, which is essential for safe and efficient navigation. The long-term stability of the proposed system makes it suitable for various navigation applications, particularly those requiring continuous and precise positioning information. The ANFIS-based approach used in the proposed system is extendable to other low-end IMUs, making it an attractive option for a wide range of applications.
A Coupled Calibration Method for Dual Cameras-Projector System with Sub-Pixel Accuracy Feature Extraction
Authors: Jia Ran , Xue Junpeng , Lu Wenbo , Song Zeyu , Xu Zhichao , Lu Shuxin
Published: March 2024

Binocular structured light systems are widely used in 3D measurements. In the condition of complex and local highly reflective scenes, to obtain more 3D information, binocular systems are usually divided into two pairs of devices, each having a Single Camera and a Projector (SCP). In this case, the binocular system can be seen as Dual Cameras-Projector (DCP) system. In the DCP calibration, the Left-SCP and Right-SCP need to be calibrated separately, which leads to inconsistent parameters for the same projector, thus reducing the measurement accuracy. To solve this problem and improve manoeuvrability, a coupled calibration method using an orthogonal phase target is proposed. The 3D coordinates on a phase target are uniquely determined by the binocular camera in DCP, rather than being calculated separately in each SCP. This ensures the consistency of the projector parameters. The coordinates of the projector image plane are calculated through the unwrapped phase, while the parameters are calibrated by the plane calibration method. In order to extract sub-pixel accuracy feature points, a method based on polynomial fitting using an orthogonal phase target is exploited. The experimental results show that the reprojection error of our method is less than 0.033 pixels, which improves the calibration accuracy.
Comparing the Election Systems for Overseas Constituency Representatives in Multiple Countries
Authors: Yamauchi Shuji , Sekiyama Takashi
Published: March 2024

Although electoral systems are a traditional focus in political science, limited research exists on the characteristics of overseas constituency representation. This study aims to quantitatively elucidate these characteristics through a comparative analysis of the election systems in eight countries. This study analyzes overseas constituency representative systems while focusing on key factors such as the number of eligible voters, seats, voter turnout, and representativeness (value of a single vote). Voter turnout in overseas districts varies significantly among these countries. Notably, Croatia and Romania exhibit exceptionally high voter turnouts in overseas districts. Common characteristics in high-turnout countries include a higher representativeness in overseas districts than the home country and a small proportion of overseas voters in the total electorate. This dynamic incentivizes overseas voters to participate in elections to reflect their minority opinions in national politics. Furthermore, it potentially leads to a higher voter turnout in overseas districts than in the home country.
Enhanced Stature in the Elderly: The Immediate Impact of Acute Postural Exercises
Authors: Ramos-Jiménez Arnulfo , García-Hernández Ismael Antonio , Chávez-Guevara Isaac Armando , Hernández-Torres Rosa Patricia , Murguía-Romero Miguel , Martínez-Sanz José Miguel , Hernández-Lepe Marco Antonio
Published: March 2024

This study investigates the immediate effects of acute postural exercises on the stature of seniors, focusing on changes in both upright and supine stature measurements. A within-subject design with repeated measures was applied, involving seniors participating in continuous exercises aimed at enhancing core musculature strength and promoting muscle relaxation. Stature measurements were recorded pre- and post-exercise in both upright and supine positions, alongside assessments of body mass index (BMI) category classifications. The results revealed a post-exercise increase in stature ranging from 0.9 to 6.0 cm and from 0.2 to 7.2 cm in upright and supine positions, respectively, with an average increase of approximately 3.5 cm in both upright and supine positions. Statistically significant and clinically relevant changes were observed (p < 0.05), including a modification of BMI by approximately two units, reclassifying 55% of participants from overweight or obese to normal weight or overweight. Furthermore, the similarity between post-exercise upright stature and pre-exercise supine stature suggested that the supine position might provide a more accurate measure of stature in seniors. Conclusively, acute postural exercises have an immediate positive impact on the stature of seniors, suggesting their potential utility in clinical settings for accurate stature measurement. However, BMI results should be interpreted with caution because they are only related to the acute change in stature and therefore may lead to the misinterpretation of the study findings, so future studies focused on evaluating the chronic effect of postural exercises integration on the health outcomes of older adults are needed to demonstrate their potential utility in clinical settings to improve postural health and general well-being.
Coverings of Graphoids: Existence Theorem and Decomposition Theorems
Authors: Malnič Aleksander , Zgrablić Boris
Published: March 2024

A graphoid is a mixed multigraph with multiple directed and/or undirected edges, loops, and semiedges. A covering projection of graphoids is an onto mapping between two graphoids such that at each vertex, the mapping restricts to a local bijection on incoming edges and outgoing edges. Naturally, as it appears, this definition displays unusual behaviour since the projection of the corresponding underlying graphs is not necessarily a graph covering. Yet, it is still possible to grasp such coverings algebraically in terms of the action of the fundamental monoid and combinatorially in terms of voltage assignments on arcs. In the present paper, the existence theorem is formulated and proved in terms of the action of the fundamental monoid. A more conventional formulation in terms of the weak fundamental group is possible because the action of the fundamental monoid is permutational. The standard formulation in terms of the fundamental group holds for a restricted class of coverings, called homogeneous. Further, the existence of the universal covering and the problems related to decomposing regular coverings via regular coverings are studied in detail. It is shown that with mild adjustments in the formulation, all the analogous theorems that hold in the context of graphs are still valid in this wider setting.
Susceptibility of Mediterranean Buffalo (Bubalus bubalis) following Experimental Infection with Lumpy Skin Disease Virus
Authors: Di Felice Elisabetta , Pinoni Chiara , Rossi Emanuela , Amatori Giorgia , Mancuso Elisa , Iapaolo Federica , Taraschi Angela , Di Teodoro Giovanni , Di Donato Guido , Ronchi Gaetano Federico , Mercante Maria Teresa , Di Ventura Mauro , Morelli Daniela , Monaco Federica
Published: March 2024

Lumpy skin disease (LSD) is a viral disease of cattle and water buffalo characterized by cutaneous nodules, biphasic fever, and lymphadenitis. LSD is endemic in Africa and the Middle East but has spread to different Asian countries in recent years. The disease is well characterized in cattle while little is known about the disease in buffaloes in which no experimental studies have been conducted. Six buffaloes and two cattle were inoculated with an Albanian LSD virus (LSDV) field strain and clinically monitored for 42 days. Only two buffaloes showed fever, skin nodules, and lymphadenitis. All samples collected (blood, swabs, biopsies, and organs) were tested in real-time PCR and were negative. Between day 39 and day 42 after inoculation, anti-LSDV antibodies were detected in three buffaloes by ELISA, but all sera were negative by virus neutralization test (VNT). Cattle showed severe clinical signs, viremia, virus shedding proven by positive real-time PCR results, and seroconversion confirmed by both ELISA and VNT. Clinical findings suggest that susceptibility in buffaloes is limited compared to in cattle once experimentally infected with LSDV. Virological results support the hypothesis of buffalo resistance to LSD and its role as an accidental non-adapted host. This study highlights that the sensitivity of ELISA and VNT may differ between animal species and further studies are needed to investigate the epidemiological role of water buffalo.
Assessing the Clinical Impact of the SARS-CoV-2 Gamma Variant on Intensive Care Unit Admissions: Insights from a Reference Hospital in Northeastern Brazil
Authors: Nonaka Carolina Kymie Vasques , de Jesus Ribeiro Adlas Michel , Rocha Gisele Vieira , da Hora Helena Souza , Junior Antônio Augusto Fonseca , Lima Fernanda de Macêdo , Bastos Iasmin Nogueira , Teles Samara Alves Sa , Weber Thamires Gomes Lopes , Costa Vanessa Ferreira , Costa-Ferro Zaquer Suzana , Rocha Clarissa Araújo Gurgel , Sardi Silvia Inês , Soares Gúbio , Mendes Ana Verena Almeida , Souza Bruno Solano de Freitas
Published: March 2024

The global challenge posed by the prolonged COVID-19 pandemic underscores the critical need for ongoing genomic surveillance to identify emerging variants and formulate effective public health strategies. This retrospective observational study, conducted in a reference hospital in Northeast Brazil and comprising 2116 cases, employed PCR genotyping together with epidemiological data to elucidate the impact of the Gamma variant during its emergence, revealing distinct patterns in hospitalization rates, severity of illness, and outcomes. The study emphasizes the challenges posed by the variant, particularly an increased tendency for ICU admissions and respiratory support, especially among adults aged 18 to 59 without comorbidities. Laboratory analyses further demonstrate elevated inflammatory, coagulation, and hepatic markers in the Gamma variant cohort, suggesting a more severe systemic response. Despite limitations, including a retrospective approach and single-institution data, the study underscores the importance of ongoing genomic surveillance. Overall, this research contributes valuable insights into the impact of the Gamma variant on COVID-19 dynamics, advocating for continued research and surveillance to inform effective public health strategies regarding evolving viral variants.