bluuebunny/crossref_metadata_2025 huggingface dataset:
Interaction of Norsecurinine-Type Oligomeric Alkaloids with α-Tubulin: A Molecular Docking Study
Authors: Vergoten Gérard , Bailly Christian
Published: May 2024

The medicinal plant Securinega virosa (Roxb ex. Willd) Baill., also known as Flueggea virosa (Roxb. ex Willd.) Royle, is commonly used in traditional medicine in Africa and Asia for the management of diverse pathologies, such as parasite infections, diabetes, and gastrointestinal diseases. Numerous alkaloids have been isolated from the twigs and leaves of the plant, notably a variety of oligomeric indolizidine alkaloids derived from the monomers securinine and norsecurinine which both display anticancer properties. The recent discovery that securinine can bind to tubulin and inhibit microtubule assembly prompted us to investigate the potential binding of two series of alkaloids, fluevirosines A–H and fluevirosinine A–J, with the tubulin dimer by means of molecular modeling. These natural products are rare high-order alkaloids with tri-, tetra-, and pentameric norsecurinine motifs. Despite their large size (up to 2500 Å3), these alkaloids can bind easily to the large drug-binding cavity (about 4800 Å3) on α-tubulin facing the β-tubulin unit. The molecular docking analysis suggests that these hydrophobic macro-alkaloids can form stable complexes with α/β-tubulin. The tubulin-binding capacity varies depending on the alkaloid size and structure. Structure-binding relationships are discussed. The docking analysis identifies the trimer fluevirosine D, tetramer fluevirosinine D, and pentamer fluevirosinine H as the most interesting tubulin ligands in the series. This study is the first to propose a molecular target for these atypical oligomeric Securinega alkaloids.
Application of Developmental Regulators for Enhancing Plant Regeneration and Genetic Transformation
Authors: Xu Pingjun , Zhong Yinxiao , Xu Ang , Liu Bingshuang , Zhang Yue , Zhao Anqi , Yang Xiaoming , Ming Meiling , Cao Fuliang , Fu Fangfang
Published: May 2024

Establishing plant regeneration systems and efficient genetic transformation techniques plays a crucial role in plant functional genomics research and the development of new crop varieties. The inefficient methods of transformation and regeneration of recalcitrant species and the genetic dependence of the transformation process remain major obstacles. With the advancement of plant meristematic tissues and somatic embryogenesis research, several key regulatory genes, collectively known as developmental regulators, have been identified. In the field of plant genetic transformation, the application of developmental regulators has recently garnered significant interest. These regulators play important roles in plant growth and development, and when applied in plant genetic transformation, they can effectively enhance the induction and regeneration capabilities of plant meristematic tissues, thus providing important opportunities for improving genetic transformation efficiency. This review focuses on the introduction of several commonly used developmental regulators. By gaining an in-depth understanding of and applying these developmental regulators, it is possible to further enhance the efficiency and success rate of plant genetic transformation, providing strong support for plant breeding and genetic engineering research.
The Effect of Temperature on the Inflorescence Formation Model for Phalaenopsis
Authors: Chen Jiunyuan , Chen Chiachung
Published: May 2024

Phalaenopsis orchids are a popular ornamental plant in the flower market. During some festivals, demand increases significantly. These mature orchids must be placed in cooling rooms for inflorescence formation at specific times to increase the financial return from their sale. The purpose of this study is to evaluate the effect of day and night temperatures on the inflorescence formation percentage using the proposed sigmoid model. Four varieties that are cultured in different vegetative temperature regimes are placed in a cooling room. An empirical inflorescence formation model is proposed as a management tool to predict the inflorescence formation percentage for Phalaenopsis. Some data sets from previous studies are used for comparison. The accumulation temperature is calculated using the day and night temperatures and is an index to predict the inflorescence formation percentage. The results show that there is a similar distribution of the inflorescence formation percentage and accumulation temperature for the four varieties. The proposed sigmoid model has a good fitting ability for the inflorescence formation percentage. This inflorescence formation model from the pooled data sets allows quantitative microclimate management of the vegetative and cooling room.
Effective Removal of Microplastic Particles from Wastewater Using Hydrophobic Bio-Substrates
Authors: Bhagwat Kalyani Prasad , Rodrigue Denis , Romero-Zerón Laura
Published: May 2024

The rapid increase in soil and water pollution is primarily attributed to anthropogenic factors, notably the mismanagement of post-consumer plastics on a global scale. This exploratory research design evaluated the effectiveness of natural hydrophobic cattail (Typha Latifolia) fibres (CFs) as bio-adsorbents of microplastic particles (MPPs) from wastewater. The study investigates how the composition of the adsorption environment affects the adsorption rate. Straightforward batch adsorption tests were conducted to evaluate the “spontaneous” sorption of MPPs onto CFs. Five MPP materials (PVC, PP, LDPE, HDPE, and Nylon 6) were evaluated. Industrial wastewater (PW) and Type II Distilled Water (DW) were employed as adsorption environments. The batch test results show that CFs are effective in removing five MPP materials from DW and PW. However, a higher removal percentage of MPPs was observed in PW, ranging from 89% to 100% for PVC, PP, LDPE, and HDPE, while the adsorption of Nylon 6 increased to 29.9%, a removal increase of 50%. These findings indicate that hydrophobic interactions drive the “spontaneous and instantaneous” adsorption process and that adjusting the adsorption environment can effectively enhance the MPP removal rate. This research highlights the significant role that bio-substrates can play in mitigating environmental pollution, serving as efficient, sustainable, non-toxic, biodegradable, low-cost, and reliable adsorbents for the removal of MPPs from wastewaters.
Nanofibrous ε-Polycaprolactone Matrices Containing Nano-Hydroxyapatite and Humulus lupulus L. Extract: Physicochemical and Biological Characterization for Oral Applications
Authors: Villanueva-Lumbreras Jaime , Rodriguez Ciro , Aguilar María Rosa , Avilés-Arnaut Hamlet , Cordell Geoffrey A. , Rodriguez-Garcia Aida
Published: May 2024

Oral bone defects occur as a result of trauma, cancer, infections, periodontal diseases, and caries. Autogenic and allogenic grafts are the gold standard used to treat and regenerate damaged or defective bone segments. However, these materials do not possess the antimicrobial properties necessary to inhibit the invasion of the numerous deleterious pathogens present in the oral microbiota. In the present study, poly(ε-caprolactone) (PCL), nano-hydroxyapatite (nHAp), and a commercial extract of Humulus lupulus L. (hops) were electrospun into polymeric matrices to assess their potential for drug delivery and bone regeneration. The fabricated matrices were analyzed using scanning electron microscopy (SEM), tensile analysis, thermogravimetric analysis (TGA), FTIR assay, and in vitro hydrolytic degradation. The antimicrobial properties were evaluated against the oral pathogens Streptococcus mutans, Porphyromonas gingivalis, and Aggregatibacter actinomycetemcomitans. The cytocompatibility was proved using the MTT assay. SEM analysis established the nanostructured matrices present in the three-dimensional interconnected network. The present research provides new information about the interaction of natural compounds with ceramic and polymeric biomaterials. The hop extract and other natural or synthetic medicinal agents can be effectively loaded into PCL fibers and have the potential to be used in oral applications.
Microstructural and Hydrophilic Properties of Polylactide Polymer Samples with Various 3D Printing Patterns
Authors: Lenshin Alexandr S. , Frolova Vera E. , Kannykin Sergey V. , Domashevskaya Evelina P.
Published: May 2024

The aim of the work is to study the effect of the 3D printing process on the microstructural and hydrophilic properties of polylactic acid (PLA) samples with various model printing patterns obtained from the black filament PLA by sequentially applying polymer layers using the FDM (fused deposition modeling) method. X-ray phase analysis revealed the partial crystallization of PLA polymer chains in the printed samples, which occurs under thermal and mechanical action on the original amorphous PLA filament during 3D printing to varying degrees, depending on the geometry of the pattern and the morphology of its surface. At the same time, IR spectroscopy data indicate the preservation of all intrastructural chemical bonds of polylactide. Measured at the original installation, the values of the wetting edge angles on the surface of the printed samples are in the range φ = 50–60°, which is significantly less than the right angle. This indicates the hydrophilic properties of the whole sample’s surface. At the same time, the influence of different geometries of model drawings in printed samples was found not only on the morphology of the sample’s surface according to SEM data but also on its wettability.
Antimicrobial Properties of Carboxymethyl Cellulose/Starch/N’N Methylenebisacrylamide Membranes Endowed by Ultrasound and Their Potential Application in Antimicrobial Packaging
Authors: Cheng Youliang , Cheng Xinyi , Fang Changqing , Chen Jing , Zhang Xin , Cao Changxue , Wang Jinpeng
Published: May 2024

Cellulose is used widely in antimicrobial packaging due to its abundance in nature, biodegradability, renewability, non-toxicity, and low cost. However, how efficiently and rapidly it imparts high antimicrobial activity to cellulose-based packaging materials remains a challenge. In this work, Ag NPs were deposited on the surface of carboxymethyl cellulose/starch/N’N Methylenebisacrylamide film using ultrasonic radiation. Morphology and structure analysis of as-prepared films were conducted, and the antibacterial effects under different ultrasonic times and reductant contents were investigated. These results showed that Ag NPs were distributed uniformly on the film surface under an ultrasonic time of 45 min. The size of Ag NPs changes as the reducing agent content decreases. The composite film demonstrated a slightly better antibacterial effect against E. coli than against S. aureus. Therefore, this work can provide valuable insights for the research on antimicrobial packaging.
Eco-Friendly Poly (Butylene Adipate-co-Terephthalate) Coated Bi-Layered Films: An Approach to Enhance Mechanical and Barrier Properties
Authors: Venkatesan Raja , Alagumalai Krishnapandi , Vetcher Alexandre A. , Al-Asbahi Bandar Ali , Kim Seong-Cheol
Published: May 2024

In this research work, a coated paper was prepared with poly (butylene adipate-co-terephthalate) (PBAT) film to explore its use in eco-friendly food packaging. The paper was coated with PBAT film for packaging using hot pressing, a production method currently employed in the packaging industry. The coated papers were evaluated for their structural, mechanical, thermal, and barrier properties. The structural morphology and chemical analysis of the coated paper confirmed the consistent formation of PBAT bi-layered on paper surfaces. Surface coating with PBAT film increased the water resistance of the paper samples, as demonstrated by tests of barrier characteristics, including the water vapor transmission rate (WVTR), oxygen transmission rate (OTR), and water contact angle (WCA) of water drops. The transmission rate of the clean paper was 2010.40 cc m−2 per 24 h for OTR and 110.24 g m−2 per 24 h for WVTR. If the PBAT-film was coated, the value decreased to 91.79 g m−2 per 24 h and 992.86 cc m−2 per 24 h. The hydrophobic nature of PBAT, confirmed by WCA measurements, contributed to the enhanced water resistance of PBAT-coated paper. This result presents an improved PBAT-coated paper material, eliminating the need for adhesives and allowing for the fabrication of bi-layered packaging.
Mechanical and Physical Changes in Bio-Polybutylene-Succinate Induced by UVC Ray Photodegradation
Authors: Scolaro Cristina , Brahimi Salim , Falcone Aurora , Beghetto Valentina , Visco Annamaria
Published: May 2024

Bio-polybutylene succinate (PBS) is a biodegradable polymer obtained from renewable feedstock having physical–mechanical properties like traditional low-density polyethylene (LDPE). PBS is employed by many manufacturing sectors, from biomedical to agri-food and cosmetics. Although some studies have already evaluated the resistance of PBS to photodegradation caused by natural outdoor solar exposure (UVA-UVB), a systematic study on the resistance to degradation caused by exposure to UVC rays, which is the subject of this study, has not yet been carried out. PBS was exposed to UVC either neat or filled with 2% carbon black (CB). Mechanical and physical characterization (tensile, hardness, calorimetry, contact angle, morphology, and surface roughness analyses) indicates that the bulk and surface properties of the polymer matrix changes after exposure to UVC radiations, due to a severe degradation. However, the presence of carbon black compensates for the degradation phenomenon. Because UVC rays are used for the sterilization process, necessary in applications such as biomedical, cosmetic, pharmaceutical, food, and other products, a comparison of the protocol used in this paper with the literature’s data has been reported and discussed.
Investigating Salt Precipitation in Continuous Supercritical Water Gasification of Biomass
Authors: Dutzi Julian , Boukis Nikolaos , Sauer Jörg
Published: May 2024

The formation of solid deposits in the process of supercritical water gasification (SCWG) is one of the main problems hindering the commercial application of the process. Seven experiments were conducted with the grass Reed Canary Grass with different preheating temperatures, but all ended early due to the formation of solid deposits (maximum operation of 3.8 h). The position of solid deposits in the lab plant changed with the variation in the temperature profile. Since the formation of solid deposits consisting of salts, coke, and corrosion products is a severe issue that needs to be resolved in order to enable long-time operation, inner temperature measurements were conducted to determine the temperature range that corresponds with the zone of solid formation. The temperature range was found to be 400 to 440 °C. Wherever this temperature was first reached solid deposits occurred in the system that led to blockage of the flow. Additional to the influence of the temperature, the influence of the flow direction (up-flow or down-flow) on the operation of the continuous SCWG plant was examined. If salts are not separated from the system sufficiently, up-flow reactors should be avoided because they amplify the accumulation of solid deposits leading to a shortened operation time. The heating concept coupled with the salt separation needs to be redesigned in order to separate the salts before entering the gasification reactors. Outside of the determined temperature zone no deposition was visible. Thus, even though the gasification efficiency was low it could be shown that the operation was limited to the deposits forming in the heating section and not by incomplete gasification in the reactor where T > 600 °C.
MFACNet: A Multi-Frame Feature Aggregating and Inter-Feature Correlation Framework for Multi-Object Tracking in Satellite Videos
Authors: Zhao Hu , Shen Yanyun , Wang Zhipan , Zhang Qingling
Published: May 2024

Efficient multi-object tracking (MOT) in satellite videos is crucial for numerous applications, ranging from surveillance to environmental monitoring. Existing methods often struggle with effectively exploring the correlation and contextual cues inherent in the consecutive features of video sequences, resulting in redundant feature inference and unreliable motion estimation for tracking. To address these challenges, we propose the MFACNet, a novel multi-frame features aggregating and inter-feature correlation framework for enhancing MOT in satellite videos with the idea of utilizing the features of consecutive frames. The MFACNet integrates multi-frame feature aggregation techniques with inter-feature correlation mechanisms to improve tracking accuracy and robustness. Specifically, our framework leverages temporal information across the features of consecutive frames to capture contextual cues and refine object representations over time. Moreover, we introduce a mechanism to explicitly model the correlations between adjacent features in video sequences, facilitating a more accurate motion estimation and trajectory associations. We evaluated the MFACNet using benchmark datasets for satellite-based video MOT tasks and demonstrated its superiority in terms of tracking accuracy and robustness over state-of-the-art performance by 2.0% in MOTA and 1.6% in IDF1. Our experimental results highlight the potential of precisely utilizing deep features from video sequences.
Upgraded Low-Frequency 3D Lightning Mapping System in North China and Observations on Lightning Initiation Processes
Authors: Liu Mingyuan , Qie Xiushu , Sun Zhuling , Jiang Rubin , Zhang Hongbo , Chen Ruiling , Yuan Shanfeng , Wang Yu , Liu Xiangke
Published: May 2024

The three-dimensional (3D) low-frequency lightning mapping system (LF-LMS) in north China has been updated. The lightning electric field derivative (dE/dt) sensor and continuous acquisition mode has been newly designed to ensure a capability of entire lightning processes detection, especially weak discharges during lightning the initiation process. The twice cross-correlation delay estimation and the grid iteration nested optimization location algorithm are used to realize the 3D location of the discharge channel, and the location resolution and calculation speed are balanced consequently. The location results of the rocket-triggered lightning demonstrated that the system achieved a high-resolution mapping of lightning discharge channels, which coincided well with the optical images. The horizontal and vertical location error for rocket triggered lightning was less than 40 m in both horizontal and vertical. Intracloud (IC) lightning flashes were observed to be initiated by three different discharge processes, initial breakdown pulse (IBP), narrow bipolar event (NBE), and initial E-change (IEC). The corresponding initial height was 10.5 km, 6.9 km, and 9.2 km, respectively. The upward negative leader was initially located, followed by scatter radiation sources and negative recoil leaders in the lower negative charge region for all cases. The electric field characteristics of the IEC and subsequent IBPs indicated that they are different discharge processes with the same current direction. The IEC process might correspond to the discharge process with continuous current and less noticeable current changes.
Characterization of Aerosol and CO2 Co-Emissions around Power Plants through Satellite-Based Synergistic Observations
Authors: Sun Lu , Yu Siqi , Liu Dong
Published: May 2024

The tracking of carbon and aerosol co-emissions is essential for environmental management. Satellite-based atmospheric synoptic observation networks provide large-scale and multifaceted data to help resolve emission behaviors. This study employs a comprehensive analysis of atmospheric dynamics, combustion byproducts, and aerosol characteristics around power plants. Strong correlations between Aerosol Optical Depth (AOD) at 500 nm and the column-averaged dry-air mole fraction of carbon dioxide (XCO2) were observed, revealing synchronous peaks in their emission patterns. The investigation into combustion completeness utilized metrics such as the ratio of carbon monoxide (CO)/XCO2 and Black Carbon Extinction (BCEXT)/Total Aerosol Extinction (TOTEXT). Discrepancies in these ratios across cases suggest variations in combustion efficiency and aerosol characteristics. Nitrogen dioxide (NO2) distributions closely mirrored XCO2, indicating consistent emission patterns, while variations in sulfur dioxide (SO2) distributions implied differences in sulfide content in the coal used. The influence of coal composition on AOD/XCO2 ratios was evident, with sulfide content contributing to variations besides combustion efficiency. This multifactorial analysis underscores the complex interplay of combustion completeness, aerosol composition, and coal components in shaping the air quality around power stations. The findings highlight the need for a nuanced understanding of these factors for effective air quality management.
Wide-Area Subsidence Monitoring and Analysis Using Time-Series InSAR Technology: A Case Study of the Turpan Basin
Authors: Li Ruren , Gong Xuhui , Zhang Guo , Chen Zhenwei
Published: May 2024

Ground subsidence often occurs over a large area. Although traditional monitoring methods have high accuracy, they cannot perform wide-area ground deformation monitoring. Synthetic Aperture Radar (SAR) interferometry (InSAR) technology utilizes phase information in SAR images to extract surface deformation information in a low-cost, large-scale, high-precision, and high-efficiency manner. With the increasing availability of SAR satellite data and the rapid development of InSAR technology, it provides the possibility for wide-area ground deformation monitoring using InSAR technology. Traditional time-series InSAR methods have cumbersome processing procedures, have large computational requirements, and rely heavily on manual intervention, resulting in relatively low efficiency. This study proposes a strategy for wide-area InSAR multi-scale deformation monitoring to address this issue. The strategy first rapidly acquires ground deformation information using Stacking technology, then identifies the main subsidence areas by setting deformation rate thresholds and visual interpretation, and finally employs advanced TS-InSAR technology to obtain detailed deformation time series for the main subsidence areas. The Turpan Basin in Xinjiang, China, was selected as the study area (7474.50 km2) to validate the proposed method. The results are as follows: (1) The basin is generally stable, but there is ground subsidence in the southern plain area, mainly affecting farmland. (2) From 2016 to 2019, the maximum subsidence rate in the farmland area was approximately 0.13 m/yr, with a maximum cumulative subsidence of about 0.25 m, affecting a total area of approximately 952.49 km2. The subsidence mainly occurred from late spring to mid-autumn, while lifting or subsidence mitigation occurred from late autumn to early spring. The study also analyzed the impacts of rainfall, geographical environment, and human activities on subsidence and found that multiple factors, including water resource reduction, overexploitation, geological characteristics, and the expansion of human activities, contributed to the subsidence problem in the Turpan Basin. This method contributes to wide-area InSAR deformation monitoring and the application of InSAR technology in engineering.
Seasonal Monitoring Method for TN and TP Based on Airborne Hyperspectral Remote Sensing Images
Authors: Dong Lei , Gong Cailan , Wang Xinhui , Wang Yang , He Daogang , Hu Yong , Li Lan , Yang Zhe
Published: May 2024

Airborne sensing images harness the combined advantages of hyperspectral and high spatial resolution, offering precise monitoring methods for local-scale water quality parameters in small water bodies. This study employs airborne hyperspectral remote sensing image data to explore remote sensing estimation methods for total nitrogen (TN) and total phosphorus (TP) concentrations in Lake Dianshan, Yuandang, as well as its main inflow and outflow rivers. Our findings reveal the following: (1) Spectral bands between 700 and 750 nm show the highest correlation with TN and TP concentrations during the summer and autumn seasons. Spectral reflectance bands exhibit greater sensitivity to TN and TP concentrations compared to the winter and spring seasons. (2) Seasonal models developed using the Catboost method demonstrate significantly higher accuracy than other machine learning (ML) models. On the test set, the root mean square errors (RMSEs) are 0.6 mg/L for TN and 0.05 mg/L for TP concentrations, with average absolute percentage errors (MAPEs) of 23.77% and 25.14%, respectively. (3) Spatial distribution maps of the retrieved TN and TP concentrations indicate their dependence on exogenous inputs and close association with algal blooms. Higher TN and TP concentrations are observed near the inlet (Jishui Port), with reductions near the outlet (Lanlu Port), particularly for the TP concentration. Areas with intense algal blooms near shorelines generally exhibit higher TN and TP concentrations. This study offers valuable insights for processing small water bodies using airborne hyperspectral remote sensing images and provides reliable remote sensing techniques for lake water quality monitoring and management.
Space–Air–Ground–Sea Integrated Network with Federated Learning
Authors: Zhao Hao , Ji Fei , Wang Yan , Yao Kexing , Chen Fangjiong
Published: May 2024

A space–air–ground–sea integrated network (SAGSIN) is a promising heterogeneous network framework for the next generation mobile communications. Moreover, federated learning (FL), as a widely used distributed intelligence approach, can improve advanced network performance. In view of the combination and cooperation of SAGSINs and FL, an FL-based SAGSIN framework faces a number of unprecedented challenges, not only from the communication aspect but also on the security and privacy side. Motivated by these observations, in this article, we first give a detailed state-of-the-art review of recent progress and ongoing research works on FL-based SAGSINs. Then, the challenges of FL-based SAGSINs are discussed. After that, for different service demands, basic applications are introduced with their benefits and functions. In addition, two case studies are proposed, in order to improve SAGSINs’ communication efficiency under a significant communication latency difference and to protect user-level privacy for SAGSIN participants, respectively. Simulation results show the effectiveness of the proposed algorithms. Moreover, future trends of FL-based SAGSINs are discussed.
Analysis of Atmospheric Boundary Layer Characteristics on Different Underlying Surfaces of the Eastern Tibetan Plateau in Summer
Authors: Wen Xiaohang , Ma Jie , Chen Mei
Published: May 2024

The atmospheric boundary layer is a key region for human activities and the interaction of various layers and is an important channel for the transportation of momentum, heat, and various substances between the free atmosphere and the surface, which has a significant impact on the development of weather and climate change. During the Second Tibetan Plateau Scientific Expedition and Research Program (STEP) in June 2022, utilizing the comprehensive stereoscopic observation experiment of the “Plateau Low Vortex Network”, this study analyzed the variation characteristics and influencing factors of the atmospheric boundary layer height (ABLH) at three stations with different underlying surface types on the Qinghai–Tibet Plateau (QTP): Qumalai Station (grassland), Southeast Tibet Observation and Research Station for the Alpine Environment (SETORS, forest), and Sieshan Station (cropland). The analysis utilized sounding observation data, microwave radiometer data, and ERA5 reanalysis data. The results revealed that the temperature differences between the sounding observation data and microwave radiometer data were minor at the three stations, with a notable temperature inversion phenomenon observed at Sieshan Station. Regarding water vapor density, the differences between the sounding observation data and microwave radiometer data were relatively small at Sieshan Station. The relative humidity increased with height at Sieshan Station, whereas it increased and then decreased with height at SETORS and Qumalai Station. The ABLH at all sites reached its maximum value around noon, approximately 1500 m, and exhibited mostly convective boundary layer (CBL) characteristics. During the night, the ABLH mostly showed a stable boundary layer (SBL) pattern, with heights around 250 m. In summer, latent heat flux (LE) and sensible heat flux (H) in the eastern plateau were generally lower than those in the western plateau except at 20:00, where they were higher. Vertical velocity (w) in the eastern plateau was greater than in the western plateau. Among Sieshan Station and SETORS, LE, and H had the most significant impact on ABLH, while at Qumalai Station, ABLH was more influenced by surface long-wave radiation (Rlu). These four influencing factors showed a positive correlation with ABLH. The impact of different underlying surface types on ABLH primarily manifests in surface temperature variations, solar radiation intensity, vegetation cover, and terrain. Grasslands typically exhibit a larger range of ABLH variations, while the ABLH in forests and mountainous cropland areas is relatively stable.
Distinguishing the Uterine Artery, the Ureter, and Nerves in Laparoscopic Surgical Images Using Ensembles of Binary Semantic Segmentation Networks
Authors: Serban Norbert , Kupas David , Hajdu Andras , Török Peter , Harangi Balazs
Published: May 2024

Performing a minimally invasive surgery comes with a significant advantage regarding rehabilitating the patient after the operation. But it also causes difficulties, mainly for the surgeon or expert who performs the surgical intervention, since only visual information is available and they cannot use their tactile senses during keyhole surgeries. This is the case with laparoscopic hysterectomy since some organs are also difficult to distinguish based on visual information, making laparoscope-based hysterectomy challenging. In this paper, we propose a solution based on semantic segmentation, which can create pixel-accurate predictions of surgical images and differentiate the uterine arteries, ureters, and nerves. We trained three binary semantic segmentation models based on the U-Net architecture with the EfficientNet-b3 encoder; then, we developed two ensemble techniques that enhanced the segmentation performance. Our pixel-wise ensemble examines the segmentation map of the binary networks on the lowest level of pixels. The other algorithm developed is a region-based ensemble technique that takes this examination to a higher level and makes the ensemble based on every connected component detected by the binary segmentation networks. We also introduced and trained a classic multi-class semantic segmentation model as a reference and compared it to the ensemble-based approaches. We used 586 manually annotated images from 38 surgical videos for this research and published this dataset.
Analyzing the Thermal Characteristics of Three Lining Materials for Plantar Orthotics
Authors: Querol-Martínez Esther , Crespo-Martínez Artur , Gómez-Carrión Álvaro , Morán-Cortés Juan Francisco , Martínez-Nova Alfonso , Sánchez-Rodríguez Raquel
Published: May 2024

Introduction: The choice of materials for covering plantar orthoses or wearable insoles is often based on their hardness, breathability, and moisture absorption capacity, although more due to professional preference than clear scientific criteria. An analysis of the thermal response to the use of these materials would provide information about their behavior; hence, the objective of this study was to assess the temperature of three lining materials with different characteristics. Materials and Methods: The temperature of three materials for covering plantar orthoses was analyzed in a sample of 36 subjects (15 men and 21 women, aged 24.6 ± 8.2 years, mass 67.1 ± 13.6 kg, and height 1.7 ± 0.09 m). Temperature was measured before and after 3 h of use in clinical activities, using a polyethylene foam copolymer (PE), ethylene vinyl acetate (EVA), and PE-EVA copolymer foam insole with the use of a FLIR E60BX thermal camera. Results: In the PE copolymer (material 1), temperature increases between 1.07 and 1.85 °C were found after activity, with these differences being statistically significant in all regions of interest (p < 0.001), except for the first toe (0.36 °C, p = 0.170). In the EVA foam (material 2) and the expansive foam of the PE-EVA copolymer (material 3), the temperatures were also significantly higher in all analyzed areas (p < 0.001), ranging between 1.49 and 2.73 °C for EVA and 0.58 and 2.16 °C for PE-EVA. The PE copolymer experienced lower overall overheating, and the area of the fifth metatarsal head underwent the greatest temperature increase, regardless of the material analyzed. Conclusions: PE foam lining materials, with lower density or an open-cell structure, would be preferred for controlling temperature rise in the lining/footbed interface and providing better thermal comfort for users. The area of the first toe was found to be the least overheated, while the fifth metatarsal head increased the most in temperature. This should be considered in the design of new wearables to avoid excessive temperatures due to the lining materials.
Automated Porosity Characterization for Aluminum Die Casting Materials Using X-ray Radiography, Synthetic X-ray Data Augmentation by Simulation, and Machine Learning
Authors: Bosse Stefan , Lehmhus Dirk , Kumar Sanjeev
Published: May 2024

Detection and characterization of hidden defects, impurities, and damages in homogeneous materials like aluminum die casting materials, as well as composite materials like Fiber–Metal Laminates (FML), is still a challenge. This work discusses methods and challenges in data-driven modeling of automated damage and defect detectors using measured X-ray single- and multi-projection images. Three main issues are identified: Data and feature variance, data feature labeling (for supervised machine learning), and the missing ground truth. It will be shown that simulation of synthetic measuring data can deliver a ground truth dataset and accurate labeling for data-driven modeling, but it cannot be used directly to predict defects in manufacturing processes. Noise has a significant impact on the feature detection and will be discussed. Data-driven feature detectors are implemented with semantic pixel Convolutional Neural Networks. Experimental data are measured with different devices: A low-quality and low-cost (Low-Q) X-ray radiography, a typical industrial mid-quality X-ray radiography and Computed Tomography (CT) system, and a state-of-the-art high-quality μ-CT device. The goals of this work are the training of robust and generalized data-driven ML feature detectors with synthetic data only and the transition from CT to single-projection radiography imaging and analysis. Although, as the title implies, the primary task is pore characterization in aluminum high-pressure die-cast materials, but the methods and results are not limited to this use case.
LiDAR-Based Intensity-Aware Outdoor 3D Object Detection
Authors: Naich Ammar Yasir , Carrión Jesús Requena
Published: May 2024

LiDAR-based 3D object detection and localization are crucial components of autonomous navigation systems, including autonomous vehicles and mobile robots. Most existing LiDAR-based 3D object detection and localization approaches primarily use geometric or structural feature abstractions from LiDAR point clouds. However, these approaches can be susceptible to environmental noise due to adverse weather conditions or the presence of highly scattering media. In this work, we propose an intensity-aware voxel encoder for robust 3D object detection. The proposed voxel encoder generates an intensity histogram that describes the distribution of point intensities within a voxel and is used to enhance the voxel feature set. We integrate this intensity-aware encoder into an efficient single-stage voxel-based detector for 3D object detection. Experimental results obtained using the KITTI dataset show that our method achieves comparable results with respect to the state-of-the-art method for car objects in 3D detection and from a bird’s-eye view and superior results for pedestrian and cyclic objects. Furthermore, our model can achieve a detection rate of 40.7 FPS during inference time, which is higher than that of the state-of-the-art methods and incurs a lower computational cost.
An Improved Initial Alignment Method Based on SE2(3)/EKF for SINS/GNSS Integrated Navigation System with Large Misalignment Angles
Authors: Sun Jin , Chen Yuxin , Cui Bingbo
Published: May 2024

This paper proposes an improved initial alignment method for a strap-down inertial navigation system/global navigation satellite system (SINS/GNSS) integrated navigation system with large misalignment angles. Its methodology is based on the three-dimensional special Euclidean group and extended Kalman filter (SE2(3)/EKF) and aims to overcome the challenges of achieving fast alignment under large misalignment angles using traditional methods. To accurately characterize the state errors of attitude, velocity, and position, these elements are constructed as elements of a Lie group. The nonlinear error on the Lie group can then be well quantified. Additionally, a group vector mixed error model is developed, taking into account the zero bias errors of gyroscopes and accelerometers. Using this new error definition, a GNSS-assisted SINS dynamic initial alignment algorithm is derived, which is based on the invariance of velocity and position measurements. Simulation experiments demonstrate that the alignment method based on SE2(3)/EKF can achieve a higher accuracy in various scenarios with large misalignment angles, while the attitude error can be rapidly reduced to a lower level.
Stretchable and Flexible Painted Thermoelectric Generators on Japanese Paper Using Inks Dispersed with P- and N-Type Single-Walled Carbon Nanotubes
Authors: Nakajima Takumi , Hoshino Koki , Yamamoto Hisatoshi , Kaneko Keisuke , Okano Yutaro , Takashiri Masayuki
Published: May 2024

As power sources for Internet-of-Things sensors, thermoelectric generators must exhibit compactness, flexibility, and low manufacturing costs. Stretchable and flexible painted thermoelectric generators were fabricated on Japanese paper using inks with dispersed p- and n-type single-walled carbon nanotubes (SWCNTs). The p- and n-type SWCNT inks were dispersed using the anionic surfactant of sodium dodecylbenzene sulfonate and the cationic surfactant of dimethyldioctadecylammonium chloride, respectively. The bundle diameters of the p- and n-type SWCNT layers painted on Japanese paper differed significantly; however, the crystallinities of both types of layers were almost the same. The thermoelectric properties of both types of layers exhibited mostly the same values at 30 °C; however, the properties, particularly the electrical conductivity, of the n-type layer increased linearly, and of the p-type layer decreased as the temperature increased. The p- and n-type SWCNT inks were used to paint striped patterns on Japanese paper. By folding at the boundaries of the patterns, painted generators can shrink and expand, even on curved surfaces. The painted generator (length: 145 mm, height: 13 mm) exhibited an output voltage of 10.4 mV and a maximum power of 0.21 μW with a temperature difference of 64 K at 120 °C on the hot side.
Power and Efficiency in Living Systems
Authors: Glazier Douglas S.
Published: May 2024

Energy transformation powers change in the universe. In physical systems, maximal power (rate of energy input or output) may occur only at submaximal efficiency (output/input), or conversely, maximal efficiency may occur only at submaximal power. My review of power and efficiency in living systems at various levels of biological organization reveals that (1) trade-offs (negative correlations) between power and efficiency, as expected in physical systems, chiefly occur for resource-supply systems; (2) synergy (positive correlations) between power and efficiency chiefly occurs for resource use systems, which may result from (a) increasing energy allocation to production versus maintenance as production rate increases and (b) natural selection eliminating organisms that exceed a maximal power limit because of deleterious speed-related effects; (3) productive power indicates species-wide ‘fitness’, whereas efficiency of resource acquisition for production indicates local ‘adaptiveness’, as viewed along a body size spectrum and within clades of related species; (4) covariation of the power and efficiency of living systems occurs across space and time at many scales; (5) the energetic power/efficiency of living systems relates to the rates and efficiencies/effectiveness of nutrient/water uptake/use, the functional performance of various activities, and information acquisition/processing; and (6) a power/efficiency approach has many useful theoretical and practical applications deserving more study.
Decoding the Volatile Profile of White Romanian Fetească Wines
Authors: Manolache Fulvia-Ancuța , Duță Denisa-Eglantina , Criveanu-Stamatie Gabriela Daniela , Iordache Teodora-Alexandra , Todașcă Maria-Cristina
Published: May 2024

The wine’s volatilome, most of the time, defines not only its aroma, but also, its major attributes. In the case of wines, the authentication process has become imperative, in light of increased production of alcoholic beverages; consequently, reliable analytical methods have served for it. Therefore, the goal of this research was to establish the global volatile profile of traditional Romanian white wines from Fetească varieties (Fetească albă, Fetească regală) in order to identify its unique characteristics by means of a headspace solid-phase microextraction coupled with gas chromatography analysis (HS-SPME/GC-MS) and e-Nose devoted techniques. Statistics was also employed aimed at differentiating the analyzed wine by varietal groups. Consequently, 23 volatile compounds were detected and quantified in 39 Fetească white wine samples originating from various production areas (Muntenia, Oltenia, Transylvania, Banat and Dobrogea), then further classified according to their odor thresholds in five aromatic classes (floral, fruity, sweet, lactic (cheesy) and other). In addition, statistics (Principal Component Analysis (PCA), Hieratical Clustering Analysis (HCA)) were used aiming to differentiate the analyzed varietal groups. The outcomes have pointed out the existence of distinct clusters connected with ethyl esters or alcohol composition and production year, depending on each examined variety.
Beyond the Walls: Patterns of Child Labour, Forced Labour, and Exploitation in a New Domestic Workers Dataset
Authors: Trodd Zoe , Waite Catherine , Goulding James , Boyd Doreen S.
Published: May 2024

The new Domestic Workers Dataset is the largest single set of surveys (n = 11,759) of domestic workers to date. Our analysis of this dataset reveals features about the lives and work of this “hard-to-find” population in India—a country estimated to have the largest number of people living in forms of contemporary slavery (11 million). The data allow us to identify child labour, indicators of forced labour, and patterns of exploitation—including labour paid below the minimum wage—using bivariate analysis, factor analysis, and spatial analysis. The dataset also helps to advance our understanding of how to measure labour exploitation and modern slavery by showing the value of “found data” and participatory and citizen science approaches.
Energy Poverty and Health Expenditure: Empirical Evidence from Vietnam
Authors: Nguyen-Phung Hang Thu , Le Hai
Published: May 2024

Utilizing data from the 2016 Vietnam Household Living Standard Survey, we undertake an empirical investigation into the influence of energy poverty on the health expenditure of Vietnamese households. Employing a double-hurdle model, our empirical findings reveal a negative relationship between energy poverty and health expenditure. Specifically, our results indicate that for each incremental unit increase in energy poverty, there is a substantial reduction of 42.5 percentage points in the overall health expenditure of the households. Furthermore, as energy poverty deepens, we observe declines of 24.6 percentage points and 45.5 percentage points in the expenses incurred for inpatient/outpatient care and self-treatment, respectively. To validate the robustness of our results, we conduct several sensitivity analyses, including propensity score matching, double/debiased machine learning. Across all these methods, our findings consistently underscore the significant and persistent adverse impact of energy poverty on the examined outcome variables. Additionally, to examine the underlying pathways, we conduct a structural equation modeling analysis and find that the relationship between energy poverty and health expenses is mediated by household hospitalization and expenditures on essential items, such as food and daily necessities.
Estimating Soil Erodible Fraction Using Multivariate Regression and Proximal Sensing Data in Arid Lands, South Egypt
Authors: Abd-Elazem Alaa H. , El-Sayed Moatez A. , Fadl Mohamed E. , Zekari Mohammedi , Selmy Salman A. H. , Drosos Marios , Scopa Antonio , Moursy Ali R. A.
Published: May 2024

Estimating soil erodible fraction based on basic soil properties in arid lands is a valuable research topic in the field of soil science and land management. The Proximal Sensing (PS) technique offers a non-destructive and efficient method to assess wind erosion potential in arid regions. By using Partial Least Squares Regression (PLSR) and Support Vector Machine (SVM) models and combining soil texture and chemical properties, determined through Visible-Near Infrared (vis-NIR) spectroscopy in 96 soil samples, this study aims to predict soil erodibility, soil organic matter (SOM), and calcium carbonate equivalent (CaCO3) in arid lands located in Elkobaneyya Valley, Aswan Governorate, Egypt. Results showed that the soil erodibility fraction (EF-Factor) had the highest values and possessed a strong relationship between slope and SOM of 0.01% in determining soil erodibility. The PLSR model performed better than SVM for estimating SOM, CaCO3, and EF-Factor. Furthermore, the results showed that the spectral responses of CaCO3 were observed in separate places in the wavelengths of 570, 649, 802, 1161, 1421, 1854, and 2362 nm, and the wavelengths with SOM parameter were 496, 658, 779, 1089, 1417, 1871, and 2423 nm. The EF-factor shows the highest significant correlation with spectral reflectance values at 526, 688, 744, 1418, 1442, 2292, and 2374 nm. The accuracy and performance of the PLSR model in estimating the EF-Factor using spectral reflectance data and the distribution of data points for both the calibration and validation data-sets indicate a good accuracy of the PLSR model, with RMSE values of 0.0921 and 0.0836 Mg h MJ−1 mm−1, coefficient of determination (R2) values of 0.931 and 0.76, and RPD values of 2.168 and 2.147, respectively.