bluuebunny/crossref_metadata_2025 huggingface dataset:
Curcuminoid Chalcones: Synthesis, Stability, and New Neuroprotective and Sonosensitising Activities
Authors: Olender Dorota , Józkowiak Małgorzata , Piotrowska-Kempisty Hanna , Sowa-Kasprzak Katarzyna , Zaprutko Lucjusz , Muszalska-Kolos Izabela , Baranowska-Wójcik Ewa , Szwajgier Dominik
Published: September 2023

The primary purpose of this work was to design and obtain a series of curcuminoid chalcone–NSAID hybrid derivatives. The ester-type hybrid compounds with ibuprofen (i), ketoprofen (ii), and naproxen (iii) were obtained in two ways, using the Claisen–Schmidt reaction and the Steglich esterification reaction. The designed molecules were successfully synthesised, and FT-IR, MS, and NMR spectroscopy confirmed their structures. Moreover, the cytotoxic effect of the sonodynamic therapy and the anti-inflammatory, antioxidant, and anticholinergic properties of some curcuminoid chalcones and curcuminoid chalcones hybrids were evaluated. The curcuminoid chalcone derivatives showed promising neuroprotective activity as sonosensitisers for sonodynamic therapy in the studied cell lines. Additionally, the stability of the ester-type hybrid compounds with promising activity was determined. The RP-HPLC method was used to observe the degradation of the tested compounds. Studies have shown that structural isomers of ester-type hybrid compounds (3ai, 3bi) are characterised by a similar susceptibility to degradation factors, i.e., they are extremely unstable in alkaline environments, very unstable in acidic environments, unstable in neutral environments, practically stable in oxidising environments, and photolabile in solutions and in the solid phase. These compounds maintain adequate stability in environment at pH 1.2 and 6.8, which may make them good candidates for developing formulations for oral administration.
Advantages and Prospective Implications of Smart Materials in Tissue Engineering: Piezoelectric, Shape Memory, and Hydrogels
Authors: Ganeson Keisheni , Tan Xue May Cindy , Abdullah Amirul Al Ashraf , Ramakrishna Seeram , Vigneswari Sevakumaran
Published: September 2023

Conventional biomaterial is frequently used in the biomedical sector for various therapies, imaging, treatment, and theranostic functions. However, their properties are fixed to meet certain applications. Smart materials respond in a controllable and reversible way, modifying some of their properties because of external stimuli. However, protein-based smart materials allow modular protein domains with different functionalities and responsive behaviours to be easily combined. Wherein, these “smart” behaviours can be tuned by amino acid identity and sequence. This review aims to give an insight into the design of smart materials, mainly protein-based piezoelectric materials, shape-memory materials, and hydrogels, as well as highlight the current progress and challenges of protein-based smart materials in tissue engineering. These materials have demonstrated outstanding regeneration of neural, skin, cartilage, bone, and cardiac tissues with great stimuli-responsive properties, biocompatibility, biodegradability, and biofunctionality.
Safety Evaluation and Population Pharmacokinetics of Camostat Mesylate and Its Major Metabolites Using a Phase I Study
Authors: Kim Gwanyoung , Moon Hyun-ki , Kim Taeheon , Yun So-hye , Yun Hwi-yeol , Hong Jang Hee , Kim Dae-Duk
Published: September 2023

Camostat mesylate is expected to be promising as a treatment option for COVID-19, in addition to other indications for which it is currently used. Furthermore, in vitro experiments have confirmed the potential of camostat and its metabolites to be effective against COVID-19. Therefore, clinical trials were conducted to evaluate the safety and pharmacokinetic characteristics of camostat after single-dose administration. Additionally, we aim to predict the pharmacokinetics of repeated dosing through modeling and simulation based on clinical trials. Clinical trials were conducted on healthy Korean adults, and an analysis was carried out of the metabolites of camostat, GBPA, and GBA. Pharmacokinetic modeling and simulation were performed using Monolix. There were no safety issues (AEs, physical examinations, clinical laboratory tests, vital sign measurements, and ECG) during the clinical trial. The pharmacokinetic characteristics at various doses were identified. It was confirmed that AUC last and Cmax increased in proportion to dose in both GBPA and GBA, and linearity was also confirmed in log-transformed power model regression. Additionally, the accumulation index was predicted (1.12 and 1.08 for GBPA and GBA). The pharmacokinetics of camostat for various dose administrations and indications can be predicted prior to clinical trials using the developed camostat model. Furthermore, it can be used for various indications by connecting it with pharmacodynamic information.
Thermo-Responsive Hydrogels Encapsulating Targeted Core–Shell Nanoparticles as Injectable Drug Delivery Systems
Authors: Ertugral-Samgar Elif Gulin , Ozmen Ali Murad , Gok Ozgul
Published: September 2023

As therapeutic agents that allow for minimally invasive administration, injectable biomaterials stand out as effective tools with tunable properties. Furthermore, hydrogels with responsive features present potential platforms for delivering therapeutics to desired sites in the body. Herein, temperature-responsive hydrogel scaffolds with embedded targeted nanoparticles were utilized to achieve controlled drug delivery via local drug administration. Poly(N-isopropylacrylamide) (pNIPAM) hydrogels, prepared with an ethylene-glycol-based cross-linker, demonstrated thermo-sensitive gelation ability upon injection into environments at body temperature. This hydrogel network was engineered to provide a slow and controlled drug release profile by being incorporated with curcumin-loaded nanoparticles bearing high encapsulation efficiency. A core (alginate)–shell (chitosan) nanoparticle design was preferred to ensure the stability of the drug molecules encapsulated in the core and to provide slower drug release. Nanoparticle-embedded hydrogels were shown to release curcumin at least four times slower compared to the free nanoparticle itself and to possess high water uptake capacity and more mechanically stable viscoelastic behavior. Moreover, this therapy has the potential to specifically address tumor tissues over-expressing folate receptors like ovaries, as the nanoparticles target the receptors by folic acid conjugation to the periphery. Together with its temperature-driven injectability, it can be concluded that this hydrogel scaffold with drug-loaded and embedded folate-targeting nanoparticles would provide effective therapy for tumor tissues accessible via minimally invasive routes and be beneficial for post-operative drug administration after tumor resection.
Agro-Morphological and Molecular Characterization Reveal Deep Insights in Promising Genetic Diversity and Marker-Trait Associations in Fagopyrum esculentum and Fagopyrum tataricum
Authors: Pipan Barbara , Sinkovič Lovro , Neji Mohamed , Janovská Dagmar , Zhou Meiliang , Meglič Vladimir
Published: September 2023

Characterisation of genetic diversity is critical to adequately exploit the potential of germplasm collections and identify important traits for breeding programs and sustainable crop improvement. Here, we characterised the phenotypic and genetic diversity of a global collection of the two cultivated buckwheat species Fagopyrum esculentum and Fagopyrum tataricum (190 and 51 accessions, respectively) using 37 agro-morphological traits and 24 SSR markers. A wide range of variation was observed in both species for most of the traits analysed. The two species differed significantly in most traits, with traits related to seeds and flowering contributing most to differentiation. The accessions of each species were divided into three major phenoclusters with no clear geographic clustering. At the molecular level, the polymorphic SSR markers were highly informative, with an average polymorphic information content (PIC) of over 0.65 in both species. Genetic diversity, as determined by Nei’s expected heterozygosity (He), was high (He = 0.77 and He = 0.66, respectively) and differed significantly between species (p = 0.03) but was homogeneously distributed between regions, confirming the lack of genetic structure as determined by clustering approaches. The weak genetic structure revealed by the phenotypic and SSR data and the low fixation indices in both species suggested frequent seed exchange and extensive cultivation and selection. In addition, 93 and 140 significant (p < 0.05) marker-trait associations (MTAs) were identified in both species using a general linear model and a mixed linear model, most of which explained >20% of the phenotypic variation in associated traits. Core collections of 23 and 13 phenotypically and genetically diverse accessions, respectively, were developed for F. esculentum and F. tataricum. Overall, the data analysed provided deep insights into the agro-morphological and genetic diversity and genetic relationships among F. esculentum and F. tataricum accessions and pointed to future directions for genomics-based breeding programs and germplasm management.
Statistics and Analysis of Digital Information on Vascular Plant Specimens and the History of Plant Collecting in Guangzhou, China
Authors: Liang Miaoting , Qin Xinsheng
Published: September 2023

This paper presents a comprehensive analysis of digitized specimen data and relevant literature to investigate the vascular plant diversity in Guangzhou City, China. Specimen data were collected from various sources, including the China Digital Herbarium (CVH), the National Specimen Resource Sharing Platform (NSII), Global Plants on JSTOR, and the Global Biodiversity Information Facility (GBIF). Following data standardization, the study identified 41,890 vascular plant specimens, encompassing 248 families, 1563 genera, and 4536 species, including subspecies and cultivated plants. Among them, the native plants of Guangzhou city accounted for 60.6% of the species. The temporal analysis identified three distinct peaks in specimen collection: 1916–1920, 1928–1936, and 1950–1964. Collection activities were primarily concentrated between the months of April and November. The distribution of collected specimens exhibited significant variation among different species, with families such as Fabaceae, Poaceae, and Myrtaceae having the highest number of specimens. Similarly, genera such as Eucalyptus, Ficus, and Citrus were well-represented. The most frequently collected species included Litchi chinensis, Eucalyptus robusta, and Cycas taiwaniana. Remarkably, 21 species had specimen counts exceeding 100. Unfortunately, approximately three-quarters of the species had fewer than 10 recorded specimens. Alarmingly, 1220 species were represented by only one specimen. Geographically, the majority of specimens originated from the former suburbs of Guangzhou, Conghua Delta Mountain, and Liuxi River areas, while other regions had limited representation. In terms of specimen collections, the Herbarium of South China Botanical Garden of the Chinese Academy of Sciences (IBSC) recorded the highest number of specimens (13,828 specimens), followed by the Tree Herbarium of South China Agricultural University (CANT; 3869 specimens) and the Herbarium of Sun Yat-sen University (SYS; 3654 specimens). The collection history in Guangzhou spans nearly 300 years and can be broadly divided into two distinct periods. The first period extends from the late 13th century to 1949, primarily encompassing the collection efforts of foreign visitors in Guangzhou, and represents the pioneering phase of plant taxonomy research in China. The second period, from 1949 to the present, is characterized by extensive investigations and collection activities conducted by local scholars, with a specific emphasis on native plant resources. By meticulously organizing and verifying information derived from historical documents and specimens, the paper effectively summarizes the plant collection and research history of Guangzhou, providing detailed profiles of the key collectors. These findings furnish reliable historical reference materials for the study of plant taxonomy and diversity in Guangzhou.
Segmentation and Phenotype Calculation of Rapeseed Pods Based on YOLO v8 and Mask R-Convolution Neural Networks
Authors: Wang Nan , Liu Hongbo , Li Yicheng , Zhou Weijun , Ding Mingquan
Published: September 2023

Rapeseed is a significant oil crop, and the size and length of its pods affect its productivity. However, manually counting the number of rapeseed pods and measuring the length, width, and area of the pod takes time and effort, especially when there are hundreds of rapeseed resources to be assessed. This work created two state-of-the-art deep learning-based methods to identify rapeseed pods and related pod attributes, which are then implemented in rapeseed pots to improve the accuracy of the rapeseed yield estimate. One of these methods is YOLO v8, and the other is the two-stage model Mask R-CNN based on the framework Detectron2. The YOLO v8n model and the Mask R-CNN model with a Resnet101 backbone in Detectron2 both achieve precision rates exceeding 90%. The recognition results demonstrated that both models perform well when graphic images of rapeseed pods are segmented. In light of this, we developed a coin-based approach for estimating the size of rapeseed pods and tested it on a test dataset made up of nine different species of Brassica napus and one of Brassica campestris L. The correlation coefficients between manual measurement and machine vision measurement of length and width were calculated using statistical methods. The length regression coefficient of both methods was 0.991, and the width regression coefficient was 0.989. In conclusion, for the first time, we utilized deep learning techniques to identify the characteristics of rapeseed pods while concurrently establishing a dataset for rapeseed pods. Our suggested approaches were successful in segmenting and counting rapeseed pods precisely. Our approach offers breeders an effective strategy for digitally analyzing phenotypes and automating the identification and screening process, not only in rapeseed germplasm resources but also in leguminous plants, like soybeans that possess pods.
Identification and Expression of the MADS-box Gene Family in Different Versions of the Ginkgo biloba Genome
Authors: Zhou Pengyan , Wang Zesen , Li Yingang , Zhou Qi
Published: September 2023

MADS-box transcription factors play important roles in many organisms. These transcription factors are involved in processes such as the formation of the flower organ structure and the seed development of plants. Ginkgo biloba has two genome versions (version 2019 and version 2021), and there is no analysis or comparison of the MADS-box gene family in these two genomes. In this study, 26 and 20 MADS-box genes were identified from the two genomes of Ginkgo, of which 12 pairs of genes reached more than 80% similarity. According to our phylogenetic analysis results, we divided these genes into type I (Mα and Mγ subfamilies) and type II (MIKC and Mδ subfamilies) members. We found that both sets of genomes lacked the Mβ gene, while the MIKC gene was the most numerous. Further analysis of the gene structure showed that the MIKC genes in the two genomes had extralong introns (≥20 kb); these introns had different splicing patterns, and their expression might be more abundant. The gene expression analysis proved that GbMADS genes were expressed to varying degrees in eight Ginkgo biological tissues. Type II GbMADS genes not only were found to be related to female flower bud differentiation and development but also are important in seed development. Therefore, MADS-box genes may play important roles in the development of Ginkgo reproductive organs, which may suggest a genetic role in sexual differentiation. This study further contributes to the research on MADS-box genes and provides new insights into sex determination in Ginkgo.
The Durable Chitosan Functionalization of Cellulosic Fabrics
Authors: Flinčec Grgac Sandra , Biruš Tea-Dora , Tarbuk Anita , Dekanić Tihana , Palčić Ana
Published: September 2023

In this work, the durability of chitosan functionalization of cellulosic textile substrates, cotton and cotton/polyester blended fabrics, was studied. Chitosan is a naturally occurring biopolymer that can be produced inexpensively. It should be dissolved in an acidic solution to activate its antimicrobial and other properties, i.e., good biocompatibility, bioabsorbability, wound healing, hemostatic, anti-infective, antibacterial, non-toxic, and adsorptive properties. The application of chitosan to textile products has been researched to achieve antimicrobial properties, but the durability, after several maintenance cycles, has not. Chitosan functionalization was carried out using maleic acid (MA) and 1,2,3,4-butanetetracarboxylic acid (BTCA) as crosslinking and chitosan-activating agents and sodium hypophosphite monohydrate as a catalyst. To determine durability, the fabrics were subjected to 10 maintenance cycles according to ISO 6330:2012 using Reference detergent 3 and drying according to Procedure F. The properties were monitored after the 3rd and 10th cycles. The crosslinking ability of chitosan with cellulosic fabrics was monitored by Fourier infrared spectrometry using the ATR technique (FTIR-ATR). Changes in mechanical properties, whiteness and yellowing, and antimicrobial properties were determined using standard methods. Compared to maleic acid, BTCA proved to be a better crosslinking agent for chitosan.
Colorless Polyimides Derived from 5,5′-bis(2,3-norbornanedicarboxylic anhydride): Strategies to Reduce the Linear Coefficients of Thermal Expansion and Improve the Film Toughness
Authors: Hasegawa Masatoshi , Miyama Takuya , Ishii Junichi , Watanabe Daisuke , Uchida Akira
Published: September 2023

In this paper, novel colorless polyimides (PIs) derived from 5,5′-bis(2,3-norbornanedicarboxylic anhydride) (BNBDA) were presented. The results of single-crystal X-ray structural analysis using a BNBDA-based model compound suggested that it had a unique steric structure with high structural linearity. Therefore, BNBDA is expected to afford new colorless PI films with an extremely high glass transition temperature (Tg) and a low linear coefficient of thermal expansion (CTE) when combined with aromatic diamines with rigid and linear structures (typically, 2,2′-bis(trifluoromethyl)benzidine (TFMB)). However, the polyaddition of BNBDA and TFMB did not form a PI precursor with a sufficiently high molecular weight; consequently, the formation of a flexible, free-standing PI film via the two-step process was inhibited because of its brittleness. One-pot polycondensation was also unsuccessful in this system because of precipitation during the reaction, probably owing to the poor solubility of the initially yielded BNBDA/TFMB imide oligomers. The combinations of (1) the structural modification of the BNBDA/TFMB system, (2) the application of a modified one-pot process, in which the conditions of the temperature-rising profile, solvents, azeotropic agent, catalysts, and reactor were refined, and (3) the optimization of the film preparation conditions overcame the trade-off between low CTE and high film toughness and afforded unprecedented PI films with well-balanced properties, simultaneously achieving excellent optical transparency, extremely high Tg, sufficiently high thermal stability, low CTE, high toughness, relatively low water uptake, and excellent solution processability.
Hybrid Polyelectrolyte Capsules Loaded with Gadolinium-Doped Cerium Oxide Nanoparticles as a Biocompatible MRI Agent for Theranostic Applications
Authors: Kolmanovich Danil D. , Chukavin Nikita N. , Savintseva Irina V. , Mysina Elena A. , Popova Nelli R. , Baranchikov Alexander E. , Sozarukova Madina M. , Ivanov Vladimir K. , Popov Anton L.
Published: September 2023

Layer-by-layer (LbL) self-assembled polyelectrolyte capsules have demonstrated their unique advantages and capability in drug delivery applications. These ordered micro/nanostructures are also promising candidates as imaging contrast agents for diagnostic and theranostic applications. Magnetic resonance imaging (MRI), one of the most powerful clinical imaging modalities, is moving forward to the molecular imaging field and requires advanced imaging probes. This paper reports on a new design of MRI-visible LbL capsules, loaded with redox-active gadolinium-doped cerium oxide nanoparticles (CeGdO2−x NPs). CeGdO2−x NPs possess an ultrasmall size, high colloidal stability, and pronounced antioxidant properties. A comprehensive analysis of LbL capsules by TEM, SEM, LCSM, and EDX techniques was carried out. The research demonstrated a high level of biocompatibility and cellular uptake efficiency of CeGdO2−x-loaded capsules by cancer (human osteosarcoma and adenocarcinoma) cells and normal (human mesenchymal stem) cells. The LbL-based delivery platform can also be used for other imaging modalities and theranostic applications.
Zein as a Basis of Recyclable Injection Moulded Materials: Effect of Formulation and Processing Conditions
Authors: Alsadat-Seyedbokaei Fahimeh , Felix Manuel , Bengoechea Carlos
Published: September 2023

The growing concern about reducing carbon footprint has led to the progressive replacement of traditional polymeric materials by natural-based biodegradable materials. However, materials from natural sources (i.e., plants) typically possess poorer mechanical properties when compared to conventional plastics. To counterbalance this, they need to be adequately formulated and processed to eventually meet the standards for certain applications. Zein is the major storage protein from corn and can be obtained as a by-product from the corn-oil industry. It is an excellent candidate for producing green materials due to its stability, biodegradability, renewability, and suitable mechanical and technical-functional properties. In the present work, zein was blended with a plasticizer (i.e., glycerol) at three different zein/glycerol ratios (75/25, 70/30, and 65/25) and then injection moulded at three different processing temperatures (120, 150, and 190 °C). The properties of both blends and bioplastics were evaluated using dynamic mechanical analysis (DMA), tensile tests, and water absorption capacity (WUC). The properties–structure interrelation was assessed through a scanning electron microscope. Generally, a higher zein content and processing temperature led to a certain reinforcement of the samples. Moreover, all bioplastics displayed a thermoplastic behaviour finally melting at temperatures around 80 °C. The lack of massive crosslinking enabled this melting, which finally could be used to confirm the ability of zein based materials to be recycled, while maintaining their properties. The recyclability of thermoplastic zein materials widens the scope of their application, especially considering its biodegradability.
Rheological and Mechanical Properties of an Acrylic PSA
Authors: Simões Beatriz D. , Marques Eduardo A. S. , Carbas Ricardo J. C. , Maul Steven , Stihler P. , Weißgraeber Philipp , da Silva Lucas F. M.
Published: September 2023

The adhesion of pressure-sensitive adhesives (PSAs) is a complex phenomenon that can be understood through the characterization of different properties, including viscoelastic, mechanical, and fracture properties. The aim of the present paper is to determine the viscoelastic behaviour of an acrylic PSA and place it in the viscoelastic window, as well as to determine the tensile strength of the material. Additionally, different numbers of stacked adhesive layers and two crosshead speeds were applied to characterize the tensile strength of the adhesive in the different conditions. Adding a new interface between layers showed a negative influence in the tensile strength, while a higher crosshead speed implied a considerable increase in the same value. Finally, double cantilever beam (DCB) fracture tests were performed, and the J-integral approach was used to evaluate the fracture energy throughout the tests. The substrate roughness, the number of stacked layers, and the thickness of the PSA proved to decrease the performance of the PSA in fracture tests. While tensile bulk tests in viscoelastic materials are not easily found in the literature, as well as DCB tests, for fracture characterization, the obtained results allowed for the characterization of those properties in an acrylic PSA.
Patriotism and Love of the Neighbor: A Kierkegaardian View of a Contested Virtue
Authors: Evans C. Stephen
Published: September 2023

Though patriotism has traditionally been considered a virtue, in many countries of the world today, the status of patriotism as a virtue has been challenged. Philosopher John Hare has recently defended patriotism as a virtue. Kierkegaard, with his suspicion of “the crowd” and attack on “Christendom” has sometimes been thought to be one of the critics of patriotism. This paper argues that Kierkegaard’s view is actually close to Hare’s. Kierkegaard does believe that patriotism can be a virtue, though it is perhaps especially susceptible to distortion and corruption. Patriotism, like other natural forms of “preferential love”, must be infused with the love of the neighbor to be a genuine virtue.
Multi-Task Learning for UAV Aerial Object Detection in Foggy Weather Condition
Authors: Fang Wenxuan , Zhang Guoqing , Zheng Yuhui , Chen Yuwen
Published: September 2023

Adverse weather conditions such as haze and snowfall can degrade the quality of captured images and affect performance of drone detection. Therefore, it is challenging to locate and identify targets in adverse weather scenarios. In this paper, a novel model called Object Detection in a Foggy Condition with YOLO (ODFC-YOLO) is proposed, which performs image dehazing and object detection jointly by multi-task learning approach. Our model consists of a detection subnet and a dehazing subnet, which can be trained end-to-end to optimize both tasks. Specifically, we propose a Cross-Stage Partial Fusion Decoder (CSP-Decoder) in the dehazing subnet to recover clean features of encoder from complex weather conditions, thereby reducing the feature discrepancy between hazy and clean images, thus enhancing the feature consistency between different tasks. Additionally, to increase the feature modeling and representation capabilities of our network, we also propose an efficient Global Context Enhanced Extraction (GCEE) module to extract beneficial information from blurred images by constructing global feature context long-range dependencies. Furthermore, we propose a Correlation-Aware Aggregated Loss (CAALoss) to average noise patterns and tune gradient magnitudes across different tasks, accordingly implicitly enhancing data diversity and alleviating representation bias. Finally, we verify the advantages of our proposed model on both synthetic and real-world foggy datasets, and our ODFC-YOLO achieves the highest mAP on all datasets while achieving 36 FPS real-time detection speed.
The Effects of Precipitation Event Characteristics and Afforestation on the Greening in Arid Grasslands, China
Authors: Guo Xuan , Guo Qun , Hu Zhongmin , Li Shenggong , Min Qingwen , Mu Songlin , Xu Chengdong , Sun Linli
Published: September 2023

Global greening and its relationship with climate change remain the hot topics in recent years, and are of critical importance for understanding the interactions between the terrestrial ecosystem carbon cycle and the climate system. China, especially north China, has contributed a lot to global greening during the past few decades. As a water-limited ecosystem, human activities, not precipitation amount, were thought as the main contributor to the greening of north China. Considering the importance of precipitation event characteristics (PEC) in the altered precipitation regimes, we integrated long-term normalized difference vegetation index (NDVI) and meteorological datasets to reveal the role of precipitation regimes, especially PECs, on vegetation growth across temperate grasslands in north China. Accompanied with a significantly decreased growing season precipitation (GSP), NDVI increased significantly in the largest area of the temperate grasslands during 1982–2015, i.e., greening. We found that 28.44% of the area was explained by PECs, including more heavy or extreme precipitation events, alleviated extreme drought, and fewer light events, while only 0.92% of the area was associated with GSP. NDVI did not always increase over the 30 years and there was a decrease during 1996–2005. Taking afforestation projects in desertified lands into account, we found that precipitation, mainly PECs, explained more the increase and decline of NDVI during 1982–1995 and 1996–2005, respectively, while an equivalent explanatory power of precipitation and afforestation projects to the increase in NDVI after 2005. Our study indicates a possible higher productivity under future precipitation regime scenario (e.g., fewer but larger precipitation events) or intensive afforestation activity, implying more carbon sequestration or livestock production of temperate steppe in the future.
Impact of Spectral Resolution and Signal-to-Noise Ratio in Vis–NIR Spectrometry on Soil Organic Matter Estimation
Authors: Yu Bo , Yuan Jing , Yan Changxiang , Xu Jiawei , Ma Chaoran , Dai Hu
Published: September 2023

Recently, considerable efforts have been devoted to the estimation of soil properties using optical payloads mounted on drones or satellites. Nevertheless, many studies focus on diverse pretreatments and modeling techniques, while there continues to be a conspicuous absence of research examining the impact of parameters related to optical remote sensing payloads on predictive performance. The main aim of this study is to evaluate how the spectral resolution and signal-to-noise ratio (SNR) of spectrometers affect the precision of predictions for soil organic matter (SOM) content. For this purpose, the initial soil spectral library was partitioned into to two simulated soil spectral libraries, each of which were individually adjusted with respect to the spectral resolutions and SNR levels. To verify the consistency and generality of our results, we employed four multiple regression models to develop multivariate calibration models. Subsequently, in order to determine the minimum spectral resolution and SNR level without significantly affecting the prediction accuracy, we conducted ANOVA tests on the RMSE and R2 obtained from the independent validation dataset. Our results revealed that (i) the factors significantly affecting SOM prediction performance, in descending order of magnitude, were the SNR levels > spectral resolutions > estimation models, (ii) no substantial difference existed in predictive performance when the spectral resolution fell within 100 nm, and (iii) when the SNR levels exceeded 15%, altering them did not notably affect the SOM predictive performance. This study is expected to provide valuable insights for the design of future optical remote sensing payloads aimed at monitoring large-scale SOM dynamics.
Automated Georectification, Mosaicking and 3D Point Cloud Generation Using UAV-Based Hyperspectral Imagery Observed by Line Scanner Imaging Sensors
Authors: Finn Anthony , Peters Stefan , Kumar Pankaj , O’Hehir Jim
Published: September 2023

Hyperspectral sensors mounted on unmanned aerial vehicles (UAV) offer the prospect of high-resolution multi-temporal spectral analysis for a range of remote-sensing applications. However, although accurate onboard navigation sensors track the moment-to-moment pose of the UAV in flight, geometric distortions are introduced into the scanned data sets. Consequently, considerable time-consuming (user/manual) post-processing rectification effort is generally required to retrieve geometrically accurate mosaics of the hyperspectral data cubes. Moreover, due to the line-scan nature of many hyperspectral sensors and their intrinsic inability to exploit structure from motion (SfM), only 2D mosaics are generally created. To address this, we propose a fast, automated and computationally robust georectification and mosaicking technique that generates 3D hyperspectral point clouds. The technique first morphologically and geometrically examines (and, if possible, repairs) poorly constructed individual hyperspectral cubes before aligning these cubes into swaths. The luminance of each individual cube is estimated and normalised, prior to being integrated into a swath of images. The hyperspectral swaths are co-registered to a targeted element of a luminance-normalised orthomosaic obtained using a standard red–green–blue (RGB) camera and SfM. To avoid computationally intensive image processing operations such as 2D convolutions, key elements of the orthomosaic are identified using pixel masks, pixel index manipulation and nearest neighbour searches. Maximally stable extremal regions (MSER) and speeded-up robust feature (SURF) extraction are then combined with maximum likelihood sample consensus (MLESAC) feature matching to generate the best geometric transformation model for each swath. This geometrically transforms and merges individual pushbroom scanlines into a single spatially continuous hyperspectral mosaic; and this georectified 2D hyperspectral mosaic is then converted into a 3D hyperspectral point cloud by aligning the hyperspectral mosaic with the RGB point cloud used to create the orthomosaic obtained using SfM. A high spatial accuracy is demonstrated. Hyperspectral mosaics with a 5 cm spatial resolution were mosaicked with root mean square positional accuracies of 0.42 m. The technique was tested on five scenes comprising two types of landscape. The entire process, which is coded in MATLAB, takes around twenty minutes to process data sets covering around 30 Ha at a 5 cm resolution on a laptop with 32 GB RAM and an Intel® Core i7-8850H CPU running at 2.60 GHz.
InfoLa-SLAM: Efficient Lidar-Based Lightweight Simultaneous Localization and Mapping with Information-Based Keyframe Selection and Landmarks Assisted Relocalization
Authors: Lin Yuan , Dong Haiqing , Ye Wentao , Dong Xue , Xu Shuogui
Published: September 2023

This work reports an information-based landmarks assisted simultaneous localization and mapping (InfoLa-SLAM) in large-scale scenes using single-line lidar. The solution employed two novel designs. The first design was a keyframe selection method based on Fisher information, which reduced the computational cost of the nonlinear optimization for the back-end of SLAM by selecting a relatively small number of keyframes while ensuring the accuracy of mapping. The Fisher information was acquired from the point cloud registration between the current frame and the previous keyframe. The second design was an efficient global descriptor for place recognition, which was achieved by designing a unique graphical feature ID to effectively match the local map with the global one. The results showed that compared with traditional keyframe selection strategies (e.g., based on time, angle, or distance), the proposed method allowed for a 35.16% reduction in the number of keyframes in a warehouse with an area of about 10,000 m2. The relocalization module demonstrated a high probability (96%) of correction even under high levels of measurement noise (0.05 m), while the time consumption for relocalization was below 28 ms. The proposed InfoLa-SLAM was also compared with Cartographer under the same dataset. The results showed that InfoLa-SLAM achieved very similar mapping accuracy to Cartographer but excelled in lightweight performance, achieving a 9.11% reduction in the CPU load and a significant 56.67% decrease in the memory consumption.
Camera and LiDAR Fusion for Urban Scene Reconstruction and Novel View Synthesis via Voxel-Based Neural Radiance Fields
Authors: Chen Xuanzhu , Song Zhenbo , Zhou Jun , Xie Dong , Lu Jianfeng
Published: September 2023

3D reconstruction of urban scenes is an important research topic in remote sensing. Neural Radiance Fields (NeRFs) offer an efficient solution for both structure recovery and novel view synthesis. The realistic 3D urban models generated by NeRFs have potential future applications in simulation for autonomous driving, as well as in Augmented and Virtual Reality (AR/VR) experiences. Previous NeRF methods struggle with large-scale, urban environments. Due to the limited model capability of NeRF, directly applying them to urban environments may result in noticeable artifacts in synthesized images and inferior visual fidelity. To address this challenge, we propose a sparse voxel-based NeRF. First, our approach leverages LiDAR odometry to refine frame-by-frame LiDAR point cloud alignment and derive accurate initial camera pose through joint LiDAR-camera calibration. Second, we partition the space into sparse voxels and perform voxel interpolation based on 3D LiDAR point clouds, and then construct a voxel octree structure to disregard empty voxels during subsequent ray sampling in the NeRF, which can increase the rendering speed. Finally, the depth information provided by the 3D point cloud on each viewpoint image supervises our NeRF model, which is further optimized using a depth consistency loss function and a plane constraint loss function. In the real-world urban scenes, our method significantly reduces the training time to around an hour and enhances reconstruction quality with a PSNR improvement of 1–2 dB, outperforming other state-of-the-art NeRF models.
Understanding the Emotional Impact and Coping Strategies of Professionals Working with Domestic Violence Victims
Authors: Ferreira Elisabete , Figueiredo Ana Sofia , Santos Anita
Published: September 2023

Domestic violence (DV) remains a significant public health concern and a violation of human rights. The complex challenges faced by professionals who directly engage DV victims, combined with their consistent exposure to distressing narratives, have the potential to significantly impact the well-being of these practitioners. This, in turn, can directly influence the quality of the support they provide to victims. The present study aims to explore the psychological impact of working with DV victims on these professionals while simultaneously investigating the coping mechanisms they employ. Twenty-four professionals from DV victim support in Portugal participated in this qualitative research. Through semi-structured interviews and thematic analysis, the study unveils that this line of work can indeed be profoundly impactful, potentially resulting in adverse outcomes such as fatigue, emotional exhaustion, frustration, and difficulties in emotional regulation. Nonetheless, the research also reveals that professionals are capable of developing coping strategies to mitigate the negative impact of their work. This study proposes a set of suggested measures that should not only be adopted by professionals but should also be smoothly incorporated into the strategies of organizations committed to supporting DV victims. Ultimately, by bolstering the welfare of DV professionals, this research strives to enhance the quality of support extended to victims and provide meaningful input for informed policymaking, improved practices, and effective training approaches.
A Multidimensional Understanding of the Relationship between Sexual Identity, Heteronormativity, and Sexual Satisfaction among a Cisgender Sample
Authors: van Eeden-Moorefield Brad , Cooke Steph , Bible Jacqueline , Gyan Elvis
Published: September 2023

Contemporary scholarship has begun to focus more on understanding the myriad health disparities (e.g., sexual anxiety, depression) related to sexual identity and its correlates. Sexual satisfaction is linked to many of these disparities, thereby serving as a potentially impactful correlate to understand more deeply in ways that might suggest potential intervention sites to mitigate various disparities. Further, there have also been calls to consider sexual identity multidimensionally beyond only self-identified sexual orientation (LGBQ+ vs. heterosexual) as well as to better understand the role of cultural factors, such as heteronormativity, as correlates of health disparities. Accordingly, this cross-sectional study used internet survey data from 455 cisgender adults of varying sexual identities to test a moderated mediating model linking two dimensions of sexual identity (self-identified sexual orientation and attraction) to sexual satisfaction as mediated by heteronormativity. Results from the multi-group path model analysis were significant for moderation and suggest that heteronormativity mediated the relationship between the attraction dimension of sexual identity and sexual satisfaction only for those who identified as queer (i.e., LGBQ+), whereas attraction was directly related to sexual satisfaction for those that self-identified as heterosexual. Thus, different dimensions of sexual identity have differential impacts on sexual satisfaction and negative impacts of heteronormativity appear significant only for those that identify as queer.
Streamflow Response to Climate and Land-Use Changes in a Tropical Island Basin
Authors: Cao Can , Sun Rui , Wu Zhixiang , Chen Bangqian , Yang Chuan , Li Qian , Fraedrich Klaus
Published: September 2023

The effects of climate change and of land use/cover change (LUCC) on streamflow as demonstrated by hydrological models are pressing issues on the frontiers of global environmental change research. The Nandu River Basin (NRB) as the largest of three river basins on the tropical Hainan Island, China, is subjected to an analysis of streamflow response to climate and to land-use change. It is based on the Soil and Water Assessment Tool (SWAT) coupled with climate change signals extracted from the global climate model data in the Coupled Model Intercomparison Project Phase 6 (CMIP6) and with land-use change scenarios modeled by Cellular Automata (CA)—Markov. The results are summarized as follows: (1) Climate change contributed more to streamflow change than land-use change in the NRB, with contributions of 97.57% and 2.43%, respectively. Precipitation and temperature were the most important climate variables, contributing 92.66% and 4.91% to streamflow change. (2) In the tropical island basin from 1990 to 2015, LUCC regulated the hydrological processes in the NRB and affected hydrological processes by increasing evapotranspiration and decreasing surface runoff and subsurface flow, which resulted in decreasing streamflow. (3) Under the climate change and land-use change scenarios of the near-term period (2021–2040), the annual streamflow decreased as during the reference period (1995–2014); particularly, it decreased most (−6.16%) on the SSP126 path. These results present a case study for understanding the hydrological cycle of tropical island basins and to provide a theoretical basis for water resources management and regional sustainable development of tropical islands.
Application of a Hyperspectral Remote Sensing Model for the Inversion of Nickel Content in Urban Soil
Authors: Zhong Qing , Eziz Mamattursun , Sawut Rukeya , Ainiwaer Mireguli , Li Haoran , Wang Liling
Published: September 2023

Hyperspectral remote sensing technology can provide a rapid and nondestructive method for soil nickel (Ni) content detection. In order to select a high-effective method for estimating the soil Ni content using a hyperspectral remote sensing technique, 88 soil samples were collected in Urumqi, northwest China, to obtain Ni contents and related hyperspectral data. At first, 12 spectral transformations were used for the original spectral data. Then, Pearson’s correlation coefficient analysis (PCC) and the CARS method were used for selecting important wavelengths. Finally, partial least squares regression (PLSR), random forest regression (RFR) and support vector machine regression (SVMR) models were used to establish the hyperspectral inversion models of the Ni content in the soil using the important wavelengths. The coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), and residual prediction deviation (RPD) were selected to evaluate the inversion effects of the models. The results indicated that using the PCC and CARS method for the original and transformed wavebands can effectively improve the correlations between the spectral data and Ni content of the soil in the study area. The random forest regression model, based on the first-order differentiation of the reciprocal (RTFD–RFR), was more stable and had the best inversion effects, with the highest predictive ability (R2 = 0.866, RMSE = 1.321, MAE = 0.986, RPD = 2.210) for determining the Ni content in the soil. The RTFD–RFR methods can be used as a means of the inversion of the Ni content in urban soil. The results of the study can provide a technical support for the hyperspectral estimation of the Ni content of urban soil.
Do Sustainability Perceptions Affect Lake Destination Loyalty?
Authors: Ramazanova Makhabbat , Tortella Bartolomé Deyà , Kakabayev Anuarbek , Caldeira Ana Maria , Carneiro Maria João
Published: September 2023

Despite a growing concern over sustainability in tourism, research on this domain, regarding, specifically, lake destinations, is still scarce. Although perceptions on lake destinations have been studied, no study is known that has analyzed the impact of visitors’ perceptions on satisfaction and behavioral intentions. Thus, this paper aims to develop and test a model to analyze the effect of lake visitors’ perceptions of destination’s sustainability on both satisfaction and loyalty towards lake destinations. A questionnaire survey was conducted in the Shchuchinsk-Burabay resort area, an important lake destination in Northern Kazakhstan. The results support the proposed lake destination loyalty model, tested using partial least squares structural equation modelling (PLS-SEM). Sustainability proved to be decisively influential, with water quality being the dimension with the highest impact on satisfaction with the lakes, along with a positive key impact of other dimensions of perceptions of the lakes being the absence of congestion. In addition, both water quality and lack of congestion had, conjointly with other features, a significant indirect impact on satisfaction with lake destinations and on loyalty. Based on the research findings, theoretical conclusions and practical implications are drawn.
The Diversity of Environmental, Social, and Governance Aspects in Sustainability: A Systematic Literature Review
Authors: Jámbor Attila , Zanócz Anett
Published: September 2023

Significant emphasis has recently been placed on measuring companies from a sustainability perspective by environmental, social, and governance (ESG) scores, resulting in a considerable amount of financial, accounting, business, and management research on the subject. We provide a concise and harmonized systematic literature review of the current trends within this area for a broader range of academic researchers and practitioners. This work comprehensively explains ESG ratings, scores, and reports and aims to summarize how CSR activities are accounted for as non-financial information. The review aims to provide information and a better understanding of the complexity of corporate ESG aspects for those interested in this area. The results suggest that diverse methodologies, subjective elements, and some complexity of ESG measurement exist, leading to companies unconsciously using ESG ratings based on incorrect measures. Scoring methodologies are controversial, highlighting the need for more certainty about the validity of the ratings. ESG ratings need more reliability, and ESG reports do not help increase credibility, transparency, or accountability. Greenwashing emerges from loose regulation, measurement complexity, and the absence of transparency, emphasizing the need for more auditing and regulations in sustainability reporting and rating. Our results also demonstrate that ESG reporting is an ever-growing issue in sustainability and finances, and regulators must focus on it. Inconsistencies and uncertainties exist in ESG ratings and reporting; therefore, education is needed for decision-makers to understand better how this emerging topic works in practice.