bluuebunny/crossref_metadata_2025 huggingface dataset:
Achieving Highly Efficient Photocatalytic Hydrogen Evolution through the Construction of g-C3N4@PdS@Pt Nanocomposites
Authors: Ma Ligang , Lin Chao , Jiang Wenjun , Yan Shun , Jiang Huilin , Song Xiang , Ai Xiaoqian , Cao Xiaoxiao , Ding Yihuan
Published: January 2024

Selective supported catalysts have emerged as a promising approach to enhance carrier separation, particularly in the realm of photocatalytic hydrogen production. Herein, a pioneering exploration involves the loading of PdS and Pt catalyst onto g-C3N4 nanosheets to construct g-C3N4@PdS@Pt nanocomposites. The photocatalytic activity of nanocomposites was evaluated under visible light and full spectrum irradiation. The results show that g-C3N4@PdS@Pt nanocomposites exhibit excellent properties. Under visible light irradiation, these nanocomposites exhibit a remarkable production rate of 1289 μmol·g−1·h−1, marking a staggering 60-fold increase compared to g-C3N4@Pt (20.9 μmol·g−1·h−1). Furthermore, when subjected to full spectrum irradiation, the hydrogen production efficiency of g-C3N4@PdS@Pt-3 nanocomposites reaches an impressive 11,438 μmol·g−1·h−1, representing an eightfold enhancement compared to g-C3N4@Pt (1452 μmol·g−1·h−1) under identical conditions. Detailed investigations into the microstructure and optical properties of g-C3N4@PdS catalysts were conducted, shedding light on the mechanisms governing photocatalytic hydrogen production. This study offers valuable insights into the potential of these nanocomposites and their pivotal role in advancing photocatalysis.
CONSMI: Contrastive Learning in the Simplified Molecular Input Line Entry System Helps Generate Better Molecules
Authors: Qian Ying , Shi Minghua , Zhang Qian
Published: January 2024

In recent years, the application of deep learning in molecular de novo design has gained significant attention. One successful approach involves using SMILES representations of molecules and treating the generation task as a text generation problem, yielding promising results. However, the generation of more effective and novel molecules remains a key research area. Due to the fact that a molecule can have multiple SMILES representations, it is not sufficient to consider only one of them for molecular generation. To make up for this deficiency, and also motivated by the advancements in contrastive learning in natural language processing, we propose a contrastive learning framework called CONSMI to learn more comprehensive SMILES representations. This framework leverages different SMILES representations of the same molecule as positive examples and other SMILES representations as negative examples for contrastive learning. The experimental results of generation tasks demonstrate that CONSMI significantly enhances the novelty of generated molecules while maintaining a high validity. Moreover, the generated molecules have similar chemical properties compared to the original dataset. Additionally, we find that CONSMI can achieve favorable results in classifier tasks, such as the compound–protein interaction task.
The High-Precision Liquid Chromatography with Electrochemical Detection (HPLC-ECD) for Monoamines Neurotransmitters and Their Metabolites: A Review
Authors: Guiard Bruno P. , Gotti Guillaume
Published: January 2024

This review highlights the advantages of high-precision liquid chromatography with an electrochemical detector (HPLC-ECD) in detecting and quantifying biological samples obtained through intracerebral microdialysis, specifically the serotonergic and dopaminergic systems: Serotonin (5-HT), 5-hydroxyindolacetic acid (5-HIAA), 3,4-dihydroxyphenylacetic acid (DOPAC), dopamine (DA), 3-metoxytryptamin (3-MT) and homovanillic acid (HVA). Recognized for its speed and selectivity, HPLC enables direct analysis of intracerebral microdialysis samples without complex derivatization. Various chromatographic methods, including reverse phase (RP), are explored for neurotransmitters (NTs) and metabolites separation. Electrochemical detector (ECD), particularly with glassy carbon (GC) electrodes, is emphasized for its simplicity and sensitivity, aimed at enhancing reproducibility through optimization strategies such as modified electrode materials. This paper underscores the determination of limits of detection (LOD) and quantification (LOQ) and the linear range (L.R.) showcasing the potential for real-time monitoring of compounds concentrations. A non-exhaustive compilation of literature values for LOD, LOQ, and L.R. from recent publications is included.
New Stable Gallium(III) and Indium(III) Complexes with Thiosemicarbazone Ligands: A Biological Evaluation
Authors: Verderi Lorenzo , Scaccaglia Mirco , Rega Martina , Bacci Cristina , Pinelli Silvana , Pelosi Giorgio , Bisceglie Franco
Published: January 2024

The aim of this work is to explore a new library of coordination compounds for medicinal applications. Gallium is known for its various applications in this field. Presently, indium is not particularly important in medicine, but it shares a lot of chemical traits with its above-mentioned lighter companion, gallium, and is also used in radio imaging. These metals are combined with thiosemicarbazones, ligating compounds increasingly known for their biological and pharmaceutical applications. In particular, the few ligands chosen to interact with these hard metal ions share the ideal affinity for a high charge density. Therefore, in this work we describe the synthesis and the characterization of the resulting coordination compounds. The yields of the reactions vary from a minimum of 21% to a maximum of 82%, using a fast and easy procedure. Nuclear Magnetic Resonance (NMR) and Infra Red (IR) spectroscopy, mass spectrometry, elemental analysis, and X-ray Diffraction (XRD) confirm the formation of stable compounds in all cases and a ligand-to-metal 2:1 stoichiometry with both cations. In addition, we further investigated their chemical and biological characteristics, via UV-visible titrations, stability tests, and cytotoxicity and antibiotic assays. The results confirm a strong stability in all explored conditions, which suggests that these compounds are more suitable for radio imaging applications rather than for antitumoral or antimicrobic ones.
Silver and Copper Complexes with Ibuprofen and Caffeine—Preparation and Evaluation of Their Selected Biological Effects
Authors: Borówka Anna , Sierosławska Anna , Baier Andrea , Rymuszka Anna , Olszewska Elżbieta
Published: January 2024

Several organometallic complexes based on more than twenty different metals have already been approved for medical applications. The aim of the presented research was to obtain complexes of silver and copper with the non-steroidal anti-inflammatory drugs ibuprofen and xanthine alkaloid caffeine and evaluate selected aspects of their bioactivity and biosafety in terms of their future possible applications. The obtained complexes were characterized by Fourier-transform infrared spectroscopy, thermogravimetry, UV-VIS spectroscopy, conductometry, elemental analysis, and bioassays. Cytotoxicity for normal human cells of the CCD-Co18 cell line was evaluated by determining the IC50 value, with metabolic and morphology assessments. It was observed that complexes containing ibuprofen and caffeine exhibited lower toxicity than those with ibuprofen only. Complexes with copper showed lower toxicity towards healthy human fibroblasts compared to silver-based compounds, with an IC50 above 140 μg mL−1. However, in the silver complexes, the presence of caffeine increased the potency of COX-2 inhibition. Antimicrobial effects against different Gram-positive and Gram-negative bacterial strains were evaluated by MIC determination with values less than 20 μg mL−1.
Eclipsed and Twisted Excimers of Pyrene and 2-Azapyrene: How Nitrogen Substitution Impacts Excimer Emission
Authors: Dai Yasi , Rambaldi Filippo , Negri Fabrizia
Published: January 2024

Due to their unique photophysical and electronic properties, pyrene and its analogues have been the subject of extensive research in recent decades. The propensity of pyrene and its derivatives to form excimers has found wide application in various fields. Nitrogen-substituted pyrene derivatives display similar photophysical properties, but for them, excimer emission has not been reported to date. Here, we use time-dependent density functional theory (TD-DFT) calculations to investigate the low-lying exciton states of dimers of pyrene and 2-azapyrene. The excimer equilibrium structures are determined and the contribution of charge transfer (CT) excitations and intermolecular interactions to the exciton states is disclosed using a diabatization procedure. The study reveals that the dimers formed by the two molecules have quite similar exciton-state patterns, in which the relevant CT contributions govern the formation of excimer states, along with the La/Lb state inversion. In contrast with pyrene, the dipole–dipole interactions in 2-azapyrene stabilize the dark eclipsed excimer structure and increase the barrier for conversion into a bright twisted excimer. It is suggested that these differences in the nitrogen-substituted derivative might influence the excimer emission properties.
Ruthenium–Cyclopentadienyl–Cycloparaphenylene Complexes: Sizable Multicharged Cations Exhibiting High DNA-Binding Affinity and Remarkable Cytotoxicity
Authors: Ypsilantis Konstantinos , Sifnaiou Evangelia , Garypidou Antonia , Kordias Dimitrios , Magklara Angeliki , Garoufis Achilleas
Published: January 2024

Two novel sizable multicharged cationic complexes, of the formulae [(η6–-[12]CPP)[Ru(η5–-Cp)]12]Χ12 and [(η6–-[11]CPP)[Ru(η5–-Cp)]11]Χ11, CPP = cycloparaphenylene, Cp = cyclopentadienyl, X = [PF6]−, (1), (3) and [Cl]−, (2), (4), were synthesized and characterized using NMR techniques, high-resolution mass spectrometry, and elemental analyses. Complexes (1) and (3) were stable in acetone and acetonitrile solutions over 48 h. In contrast, the water-soluble (2) and (4) begin to decompose in aqueous media after 1 h, due to the [Cl]− tendency for nucleophilic attack on ruthenium of the {Ru(η5–-Cp)} units. Fluorescence quenching experiments conducted during the stability window of (2) with the d(5′-CGCGAATTCGCG-3′)2-EtBr adducts revealed remarkably high values for Ksv = 1.185 × 104 ± 0.025 M−1 and Kb = 3.162 × 105 ± 0.001 M−1. Furthermore, the cytotoxic activity of (2) against A2780, A2780res, and MCF-7 cancer cell lines shows that it is highly cytotoxic with IC50 values in the range of 4.76 ± 1.85 to 16 ± 0.81 μΜ.
Nutritional Status of Breastfeeding Mothers and Impact of Diet and Dietary Supplementation: A Narrative Review
Authors: Carretero-Krug Alejandra , Montero-Bravo Ana , Morais-Moreno Carmen , Puga Ana M. , Samaniego-Vaesken Mª de Lourdes , Partearroyo Teresa , Varela-Moreiras Gregorio
Published: January 2024

Adequate nutrition during breastfeeding is crucial for ensuring the good health of mothers and babies. Despite the high energy and nutrient demands of breastfeeding, lactating women are often vulnerable from a nutritional perspective. The nutritional focus during breastfeeding tends to be on the newborn, often neglecting the mother’s diet. Therefore, in the present narrative review, nutrient intakes were compared with the dietary reference values (DRVs) proposed by the European Food Safety Authority (EFSA) as well as by the World Health Organization/Food and Agriculture Organization (WHO/FAO). In the diets of lactating mothers, dietary inadequacies were observed in the intake of some vitamins, such as folic acid, vitamin B12, vitamin A, and vitamin D, and in the intake of certain minerals like calcium, iron, and iodine; polyunsaturated omega-3 fatty acid deficiencies, primarily in eicosapentaenoic acid and docosahexaenoic acid, were also observed. On the other hand, the debate on the necessity of supplementation during lactation continues; the need for nutritional supplementation during lactation depends on many factors, such us mothers’ eating habits. There seems to be a positive association between nutritional supplementation of the lactating mother and the concentration of certain nutrients in human milk. The present narrative review provides an update on the nutritional status (fatty acids and micronutrients) of breastfeeding mothers and the impact of diet and dietary supplementation on human milk composition.
Do Primary Health Professionals in Brazil Have a Misperception about Food? The Role of Food Literacy as a Positive Predictor
Authors: Zeminian Larissa Baungartner , Corona Ligiana Pires , da Silva Marcela Chagas , Batista Isabelle do Nascimento , da Cunha Diogo Thimoteo
Published: January 2024

Risk perception is socially constructed; psychological elements control people’s reactions to a hazard, and even health professionals may have difficulty determining what healthy food is. This work aimed to measure food literacy and food risk perceptions among primary healthcare professionals in a Brazilian city. In the first phase, 280 health professionals working in primary care in Rio Claro, Brazil, were studied. The Short Food Literacy Questionnaire (SFLQ-Br) and scales of risk and benefit perception of 50 foods were used. In the second phase, 20 professionals were interviewed to investigate the responses to different foods observed in the first phase. In this second phase, 16 users of the health system were also enrolled to understand their perceptions and how the nutrition messages conveyed by the health team reached them. Professionals scored an average of 34.5 on food literacy (for which there is a maximum score of 52). They showed difficulty with dietary guidelines and their interpretation. Food’s risk and benefit perception were generally consistent with the recommendations of the Food Guide for the Brazilian Population. However, some processed foods or those with no proven health benefits were considered healthy by the study participants, indicating a biased perception (e.g., gelatin, processed turkey breast, cream crackers, and cereal bars). Less misperception was observed when food literacy was higher, which positively predicted risk perception. The reasons for identifying benefits of these foods ranged from the false impression that they are natural and nutritious foods to the comparative claim that they are better for health than similar foods. The results indicate the need to educate health professionals based on current references to avoid bias in population counseling.
Efficacy and Safety of Calcifediol in Young Adults with Vitamin D Deficiency: A Phase I, Multicentre, Clinical Trial—POSCAL Study
Authors: Guerra López Pedro , Urroz Elizalde Mikel , Vega-Gil Noelia , Sánchez Santiago Blanca , Zorrilla Martínez Iñaki , Jiménez-Mercado Mario , Jódar Esteban , Landeta Manzano Araitz , Campo Hoyos Cristina , Frías Iniesta Jesús
Published: January 2024

Vitamin D deficiency is highly prevalent, and recent evidence suggests a possible association between vitamin D deficiency and various health conditions. The aim of this study was to assess monthly calcifediol treatments for vitamin D deficiency (or biweekly, if the deficiency was severe) in a young adult population with no associated comorbidities. This multicentre phase I trial started with a four month open-label treatment phase (TP) that included 101 participants (65% women with mean age 29.8 years). Eighty-two percent of the subjects (79/96) achieved 25(OH)D levels within the target range (20–60 ng/mL) by the end of the TP, and they were subsequently randomised and subjected to a double-blind, placebo-controlled, five month follow-up phase (FP). At the end of the FP, 89% of participants maintained vitamin D levels of >20 ng/mL with calcifediol, versus 49% with placebo (p < 0.001). Subjects receiving monthly calcifediol during both phases (n = 32) maintained 25(OH)D levels >20 ng/mL, whereas those on the placebo during the FP (n = 38) exhibited deficiency levels of 25(OH)D by the end of the study. No clinically relevant changes in bone metabolism parameters or toxic 25(OH)D levels were observed, and no serious adverse events were reported throughout the study. Calcifediol is a safe and effective treatment for vitamin D deficiency in the young adult population, but long-term use may be required to sustain optimal 25(OH)D levels.
Intentional Dental Modifications in the African Population
Authors: Kgabi Candy , Manica Scheila , Pandey Hemlata
Published: January 2024

(1) This research paper aims to conduct a comprehensive review of the existing scientific literature on intentional dental modifications within the African population. By synthesizing and analysing studies, this paper aims to shed light on the prevalence, cultural significance, and forensic implications of intentional dental modifications. (2) A scoping review was conducted according to PRISMA for Scoping Reviews and a search performed in June 2023 on the three electronic databases Scopus, PubMed, and Web of Science. (3) The search resulted in 30 studies and showed that intentional dental modifications, also referred to as nontherapeutic dental modifications, are prevalent across the African population for reasons linked to traditional medicine, ethnic affiliation, and individualism, with the highest-reported modification being infant oral mutilation at 53%, followed by tooth filing at 10%, and others such as lip plates, diastema piercings, dental avulsion, dental tattooing, crowns, and oral piercings. (4) The quality and quantity of the available literature on intentional dental modifications in the African population is limited due to bias in reporting, as most studies are those of individuals with severe health complications. The data gathered from this study could further aid in the analysis and identification of nontherapeutic dental modifications, be used in profiling, and assist in the estimation of population affiliation.
HTLV-1 Tax Tug-of-War: Cellular Senescence and Death or Cellular Transformation
Authors: Bellon Marcia , Nicot Christophe
Published: January 2024

Human T cell leukemia virus type 1 (HTLV-1) is a retrovirus associated with a lymphoproliferative disease known as adult T cell leukemia/lymphoma (ATLL). HTLV-1 infection efficiently transforms human T cells in vivo and in vitro. The virus does not transduce a proto-oncogene, nor does it integrate into tumor-promoting genomic sites. Instead, HTLV-1 uses a random mutagenesis model, resulting in cellular transformation. Expression of the viral protein Tax is critical for the immortalization of infected cells by targeting specific cellular signaling pathways. However, Tax is highly immunogenic and represents the main target for the elimination of virally infected cells by host cytotoxic T cells (CTLs). In addition, Tax expression in naïve cells induces pro-apoptotic signals and has been associated with the induction of non-replicative cellular senescence. This review will explore these conundrums and discuss the mechanisms used by the Tax viral oncoprotein to influence life-and-death cellular decisions and affect HTLV-1 pathogenesis.
DNA Barcode-Assisted Inventory of the Marine Macroalgae from the Azores, Including New Records
Authors: Gabriel Daniela , Schmidt William E. , Micael Joana , Moura Mónica , Fredericq Suzanne
Published: January 2024

Up to the present study, only 8.5% of the 522 macroalgal species reported at the Azores have sequences deposited in GenBank and BOLD public repositories. The sequences of four genetic markers (cox1, rbcL, UPA, tufA) were obtained for recently collected samples from two Azorean islands. DNA barcode-assisted identification was conducted on newly generated and unpublished sequences from public repositories. A literature review of recently published studies, including the molecular identifications of Azorean macroalgae, was also performed. The results confirm the occurrence of 51 species (including subspecific ranks) and provide four new records, namely, three cryptogenic species (Olokunia boudouresquei, Padina gymnospora, and Ulva lacinulata) and one introduced species (Ulva australis). This study contributes 23 DNA barcodes generated for the first time to the Azores, which now has 10.5% of its marine flora represented in public repositories. Additionally, UPA sequences were generated for the first time for the five taxa.
Phase Transition in Ant Colony Optimization
Authors: Mori Shintaro , Nakamura Shogo , Nakayama Kazuaki , Hisakado Masato
Published: January 2024

Ant colony optimization (ACO) is a stochastic optimization algorithm inspired by the foraging behavior of ants. We investigate a simplified computational model of ACO, wherein ants sequentially engage in binary decision-making tasks, leaving pheromone trails contingent upon their choices. The quantity of pheromone left is the number of correct answers. We scrutinize the impact of a salient parameter in the ACO algorithm, specifically, the exponent α, which governs the pheromone levels in the stochastic choice function. In the absence of pheromone evaporation, the system is accurately modeled as a multivariate nonlinear Pólya urn, undergoing phase transition as α varies. The probability of selecting the correct answer for each question asymptotically approaches the stable fixed point of the nonlinear Pólya urn. The system exhibits dual stable fixed points for α≥αc and a singular stable fixed point for α<αc where αc is the critical value. When pheromone evaporates over a time scale τ, the phase transition does not occur and leads to a bimodal stationary distribution of probabilities for α≥αc and a monomodal distribution for α<αc.
Triterpenoidal Saponins from the Leaves of Aster koraiensis Offer Inhibitory Activities against SARS-CoV-2
Authors: Kim Ji-Young , Kim Tai Young , Son So-Ri , Kim Suyeon Yellena , Kwon Jaeyoung , Kwon Hak Cheol , Lee C. Justin , Jang Dae Sik
Published: January 2024

Triterpenoidal saponins have been reported to be able to restrain SARS-CoV-2 infection. To isolate antiviral compounds against SARS-CoV-2 from the leaves of Aster koraiensis, we conducted multiple steps of column chromatography. We isolated six triperpenoidal saponins from A. koraiensis leaves, including three unreported saponins. Their chemical structures were determined using HR-MS and NMR data analyses. Subsequently, we tested the isolates to assess their ability to impede the entry of the SARS-CoV-2 pseudovirus (pSARS-CoV-2) into ACE2+ H1299 cells and found that five of the six isolates displayed antiviral activity with an IC50 value below 10 μM. Notably, one unreported saponin, astersaponin J (1), blocks pSARS-CoV-2 in ACE2+ and ACE2/TMPRSS2+ cells with similar IC50 values (2.92 and 2.96 μM, respectively), without any significant toxic effect. Furthermore, our cell-to-cell fusion and SARS-CoV-2 Spike-ACE2 binding assays revealed that astersaponin J inhibits membrane fusion, thereby blocking both entry pathways of SARS-CoV-2 while leaving the interaction between the SARS-CoV-2 Spike and ACE2 unaffected. Overall, this study expands the list of antiviral saponins by introducing previously undescribed triterpenoidal saponins isolated from the leaves of A. koraiensis, thereby corroborating the potency of triterpenoid saponins in impeding SARS-CoV-2 infection.
Mining and Mineral Processing Journals in the WoS and Their Rankings When Merging SCIEx and ESCI Databases—Case Study Based on the JCR 2022 Data
Authors: Korman Tomislav , Malvić Tomislav , Lozynskyi Vasyl , Briševac Zlatko , Kovač Zoran , Hrnčević Lidia , Pavlić Krešimir
Published: January 2024

The 2022 JCR included ESCI journals for the first time, increasing the number of publication titles by approximately 60%. In this paper, the subcategory Mining and Mineral Processing (part of the Engineering and Geosciences category, where 12 of the ESCI journals were merged with the 20 SCIEx ones) is presented and analyzed. Only three of the ESCI journals included in the database were ranked Q1/Q2. The inclusion of the entire ESCI added new content for readers and authors relying on JCR sources. This paper offers authors, researchers, and publishers in the Mining and Mineral Processing field practical insights into the potential benefits and challenges associated with the changing landscape of indexed journals, as well as in-depth, systematic analyses that provide potential authors with the opportunity to select the most suitable journal for submitting their papers.
A Deep-Learning-Based Method for Extracting an Arbitrary Number of Individual Power Lines from UAV-Mounted Laser Scanning Point Clouds
Authors: Zhu Sha , Li Qiang , Zhao Jianwei , Zhang Chunguang , Zhao Guang , Li Lu , Chen Zhenghua , Chen Yiping
Published: January 2024

In recent years, laser scanners integrated with Unmanned Aerial Vehicles (UAVs) have exhibited great potential in conducting power line inspections in harsh environments. The point clouds collected for power line inspections have numerous advantages over remote image data. However, point cloud-based individual power line extraction, which is a crucial technology required for power line inspections, still poses several challenges such as massive 3D points, imbalanced category points, etc. Moreover, in various power line scenarios, previous studies often require manual setup and careful adjustment of different thresholds to separate different power lines, which is inefficient for practical applications. To handle these challenges, in this paper, we propose a multi-branch network to automatically extract an arbitrary number of individual power lines from point clouds collected by UAV-based laser scanners. Specifically, to handle the massive 3D point clouds in complex outdoor scenarios, we propose to leverage deep neural network for efficient and rapid feature extraction in large-scale point clouds. To mitigate imbalanced data quantities across different categories, we propose to design a weighted cross-entropy loss function to measure the varying importance of each category. To achieve the effective extraction of an arbitrary number of power lines, we propose leveraging a loss function to learn the discriminative features that can differentiate the points belonging to different power lines. Once the discriminative features are learned, the Mean Shift method can distinguish the individual power lines by clustering without supervision. The evaluations are executed on two datasets, which are acquired at different locations with UAV-mounted laser scanners. The proposed method has been thoroughly tested and evaluated, and the results and discussions confirm its outstanding ability to extract an arbitrary number of individual power lines in point clouds.
Individual Tree-Scale Aboveground Biomass Estimation of Woody Vegetation in a Semi-Arid Savanna Using 3D Data
Authors: Muumbe Tasiyiwa Priscilla , Singh Jenia , Baade Jussi , Raumonen Pasi , Coetsee Corli , Thau Christian , Schmullius Christiane
Published: January 2024

Allometric equations are the most common way of assessing Aboveground biomass (AGB) but few exist for savanna ecosystems. The need for the accurate estimation of AGB has triggered an increase in the amount of research towards the 3D quantification of tree architecture through Terrestrial Laser Scanning (TLS). Quantitative Structure Models (QSMs) of trees have been described as the most accurate way. However, the accuracy of using QSMs has yet to be established for the savanna. We implemented a non-destructive method based on TLS and QSMs. Leaf-off multi scan TLS point clouds were acquired in 2015 in Kruger National Park, South Africa using a Riegl VZ1000. The 3D data covered 80.8 ha with an average point density of 315.3 points/m2. Individual tree segmentation was applied using the comparative shortest-path algorithm, resulting in 1000 trees. As 31 trees failed to be reconstructed, we reconstructed optimized QSMs for 969 trees and the computed tree volume was converted to AGB using a wood density of 0.9. The TLS-derived AGB was compared with AGB from three allometric equations. The best modelling results had an RMSE of 348.75 kg (mean = 416.4 kg) and a Concordance Correlation Coefficient (CCC) of 0.91. Optimized QSMs and model repetition gave robust estimates as given by the low coefficient of variation (CoV = 19.9% to 27.5%). The limitations of allometric equations can be addressed by the application of QSMs on high-density TLS data. Our study shows that the AGB of savanna vegetation can be modelled using QSMs and TLS point clouds. The results of this study are key in understanding savanna ecology, given its complex and dynamic nature.
Correction: López-Vilos et al. Clustering-Based Energy-Efficient Self-Healing Strategy for WSNs under Jamming Attacks. Sensors 2023, 23, 6894
Authors: López-Vilos Nicolás , Valencia-Cordero Claudio , Souza Richard Demo , Montejo-Sánchez Samuel
Published: January 2024

In the published publication [...]
Deployment of Constellation with Different Inclinations Using the Nodal Precession and Thrust
Authors: Zhao Shuailong , Zhu Qinyu , Tao Xuefeng , Zhang Yasheng
Published: January 2024

Strategy selection is critical for constellation deployment missions, both in terms of energy consumption and time cost. The different effects of impulse thrust and continuous thrust on orbit elements lead to a different choice of strategy. With impulse thrust, constellation types are differentiated according to high and medium-low inclinations. Constellations with high inclination are deployed using a strategy that controls the inclination. Constellations with medium-low inclination are deployed using a strategy that controls the semi-long axis. With continuous thrust, constellations are classified according to high, medium, and low inclination. High inclination constellations are deployed with a strategy of controlling inclination. Medium inclination constellations are deployed with a strategy that controls the semi-long axis. Low inclination constellations are deployed with a strategy of directly applying continuous thrust.
Evaluating Accuracy in Five Commercial Sleep-Tracking Devices Compared to Research-Grade Actigraphy and Polysomnography
Authors: Kainec Kyle A. , Caccavaro Jamie , Barnes Morgan , Hoff Chloe , Berlin Annika , Spencer Rebecca M. C.
Published: January 2024

The development of consumer sleep-tracking technologies has outpaced the scientific evaluation of their accuracy. In this study, five consumer sleep-tracking devices, research-grade actigraphy, and polysomnography were used simultaneously to monitor the overnight sleep of fifty-three young adults in the lab for one night. Biases and limits of agreement were assessed to determine how sleep stage estimates for each device and research-grade actigraphy differed from polysomnography-derived measures. Every device, except the Garmin Vivosmart, was able to estimate total sleep time comparably to research-grade actigraphy. All devices overestimated nights with shorter wake times and underestimated nights with longer wake times. For light sleep, absolute bias was low for the Fitbit Inspire and Fitbit Versa. The Withings Mat and Garmin Vivosmart overestimated shorter light sleep and underestimated longer light sleep. The Oura Ring underestimated light sleep of any duration. For deep sleep, bias was low for the Withings Mat and Garmin Vivosmart while other devices overestimated shorter and underestimated longer times. For REM sleep, bias was low for all devices. Taken together, these results suggest that proportional bias patterns in consumer sleep-tracking technologies are prevalent and could have important implications for their overall accuracy.
FPIRST: Fatigue Driving Recognition Method Based on Feature Parameter Images and a Residual Swin Transformer
Authors: Xiao Weichu , Liu Hongli , Ma Ziji , Chen Weihong , Hou Jie
Published: January 2024

Fatigue driving is a serious threat to road safety, which is why accurately identifying fatigue driving behavior and warning drivers in time are of great significance in improving traffic safety. However, accurately recognizing fatigue driving is still challenging due to large intra-class variations in facial expression, continuity of behaviors, and illumination conditions. A fatigue driving recognition method based on feature parameter images and a residual Swin Transformer is proposed in this paper. First, the face region is detected through spatial pyramid pooling and a multi-scale feature output module. Then, a multi-scale facial landmark detector is used to locate 23 key points on the face. The aspect ratios of the eyes and mouth are calculated based on the coordinates of these key points, and a feature parameter matrix for fatigue driving recognition is obtained. Finally, the feature parameter matrix is converted into an image, and the residual Swin Transformer network is presented to recognize fatigue driving. Experimental results on the HNUFD dataset show that the proposed method achieves an accuracy of 96.512%, thus outperforming state-of-the-art methods.
The Influence of Micro-Hexapod Walking-Induced Pose Changes on LiDAR-SLAM Mapping Performance
Authors: Seki Hiroshi , Yamamoto Yuhi , Nagasawa Sumito
Published: January 2024

Micro-hexapods, well-suited for navigating tight or uneven spaces and suitable for mass production, hold promise for exploration by robot groups, particularly in disaster scenarios. However, research on simultaneous localization and mapping (SLAM) for micro-hexapods has been lacking. Previous studies have not adequately addressed the development of SLAM systems considering changes in the body axis, and there is a lack of comparative evaluation with other movement mechanisms. This study aims to assess the influence of walking on SLAM capabilities in hexapod robots. Experiments were conducted using the same SLAM system and LiDAR on both a hexapod robot and crawler robot. The study compares map accuracy and LiDAR point cloud data through pattern matching. The experimental results reveal significant fluctuations in LiDAR point cloud data in hexapod robots due to changes in the body axis, leading to a decrease in map accuracy. In the future, the development of SLAM systems considering body axis changes is expected to be crucial for multi-legged robots like micro-hexapods. Therefore, we propose the implementation of a system that incorporates body axis changes during locomotion using inertial measurement units and similar sensors.
HRYNet: A Highly Robust YOLO Network for Complex Road Traffic Object Detection
Authors: Tang Lindong , Yun Lijun , Chen Zaiqing , Cheng Feiyan
Published: January 2024

Object detection is a crucial component of the perception system in autonomous driving. However, the road scene presents a highly intricate environment where the visibility and characteristics of traffic targets are susceptible to attenuation and loss due to various complex road scenarios such as lighting conditions, weather conditions, time of day, background elements, and traffic density. Nevertheless, the current object detection network must exhibit more learning capabilities when detecting such targets. This also exacerbates the loss of features during the feature extraction and fusion process, significantly compromising the network’s detection performance on traffic targets. This paper presents a novel methodology by which to overcome the concerns above, namely HRYNet. Firstly, a dual fusion gradual pyramid structure (DFGPN) is introduced, which employs a two-stage gradient fusion strategy to enhance the generation of more comprehensive multi-scale high-level semantic information, strengthen the interconnection between non-adjacent feature layers, and reduce the information gap that exists between them. HRYNet introduces an anti-interference feature extraction module, the residual multi-head self-attention mechanism (RMA). RMA enhances the target information by implementing a characteristic channel weighting policy, thereby reducing background interference and improving the attention capability of the network. Finally, the detection performance of HRYNet was evaluated by utilizing three datasets: the horizontally collected dataset BDD1000K, the UAV high-altitude dataset Visdrone, and a custom dataset. Experimental results demonstrate that HRYNet achieves a higher mAP_0.5 compared with YOLOv8s on the three datasets, with increases of 10.8%, 16.7%, and 5.5%, respectively. To optimize HRYNet for mobile devices, this study presents Lightweight HRYNet (LHRYNet), which effectively reduces the number of model parameters by 2 million. The results demonstrate that LHRYNet outperforms YOLOv8s in terms of mAP_0.5, with improvements of 6.7%, 10.9%, and 2.5% observed on the three datasets, respectively.
A Review of Dynamic Object Filtering in SLAM Based on 3D LiDAR
Authors: Peng Hongrui , Zhao Ziyu , Wang Liguan
Published: January 2024

SLAM (Simultaneous Localization and Mapping) based on 3D LiDAR (Laser Detection and Ranging) is an expanding field of research with numerous applications in the areas of autonomous driving, mobile robotics, and UAVs (Unmanned Aerial Vehicles). However, in most real-world scenarios, dynamic objects can negatively impact the accuracy and robustness of SLAM. In recent years, the challenge of achieving optimal SLAM performance in dynamic environments has led to the emergence of various research efforts, but there has been relatively little relevant review. This work delves into the development process and current state of SLAM based on 3D LiDAR in dynamic environments. After analyzing the necessity and importance of filtering dynamic objects in SLAM, this paper is developed from two dimensions. At the solution-oriented level, mainstream methods of filtering dynamic targets in 3D point cloud are introduced in detail, such as the ray-tracing-based approach, the visibility-based approach, the segmentation-based approach, and others. Then, at the problem-oriented level, this paper classifies dynamic objects and summarizes the corresponding processing strategies for different categories in the SLAM framework, such as online real-time filtering, post-processing after the mapping, and Long-term SLAM. Finally, the development trends and research directions of dynamic object filtering in SLAM based on 3D LiDAR are discussed and predicted.
Human Digital Twin in Industry 5.0: A Holistic Approach to Worker Safety and Well-Being through Advanced AI and Emotional Analytics
Authors: Davila-Gonzalez Saul , Martin Sergio
Published: January 2024

This research introduces a conceptual framework designed to enhance worker safety and well-being in industrial environments, such as oil and gas construction plants, by leveraging Human Digital Twin (HDT) cutting-edge technologies and advanced artificial intelligence (AI) techniques. At its core, this study is in the developmental phase, aiming to create an integrated system that could enable real-time monitoring and analysis of the physical, mental, and emotional states of workers. It provides valuable insights into the impact of Digital Twins (DT) technology and its role in Industry 5.0. With the development of a chatbot trained as an empathic evaluator that analyses emotions expressed in written conversations using natural language processing (NLP); video logs capable of extracting emotions through facial expressions and speech analysis; and personality tests, this research intends to obtain a deeper understanding of workers’ psychological characteristics and stress levels. This innovative approach might enable the identification of stress, anxiety, or other emotional factors that may affect worker safety. Whilst this study does not encompass a case study or an application in a real-world setting, it lays the groundwork for the future implementation of these technologies. The insights derived from this research are intended to inform the development of practical applications aimed at creating safer work environments.
A 0.05 m Change in Inertial Measurement Unit Placement Alters Time and Frequency Domain Metrics during Running
Authors: Kiernan Dovin , Katzman Zachary David , Hawkins David A. , Christiansen Blaine Andrew
Published: January 2024

Inertial measurement units (IMUs) provide exciting opportunities to collect large volumes of running biomechanics data in the real world. IMU signals may, however, be affected by variation in the initial IMU placement or movement of the IMU during use. To quantify the effect that changing an IMU’s location has on running data, a reference IMU was ‘correctly’ placed on the shank, pelvis, or sacrum of 74 participants. A second IMU was ‘misplaced’ 0.05 m away, simulating a ‘worst-case’ misplacement or movement. Participants ran over-ground while data were simultaneously recorded from the reference and misplaced IMUs. Differences were captured as root mean square errors (RMSEs) and differences in the absolute peak magnitudes and timings. RMSEs were ≤1 g and ~1 rad/s for all axes and misplacement conditions while mean differences in the peak magnitude and timing reached up to 2.45 g, 2.48 rad/s, and 9.68 ms (depending on the axis and direction of misplacement). To quantify the downstream effects of these differences, initial and terminal contact times and vertical ground reaction forces were derived from both the reference and misplaced IMU. Mean differences reached up to −10.08 ms for contact times and 95.06 N for forces. Finally, the behavior in the frequency domain revealed high coherence between the reference and misplaced IMUs (particularly at frequencies ≤~10 Hz). All differences tended to be exaggerated when data were analyzed using a wearable coordinate system instead of a segment coordinate system. Overall, these results highlight the potential errors that IMU placement and movement can introduce to running biomechanics data.
Potential of Deep Eutectic Solvents in the Extraction of Organic Compounds from Food Industry By-Products and Agro-Industrial Waste
Authors: Molnar Maja , Gašo-Sokač Dajana , Komar Mario , Jakovljević Kovač Martina , Bušić Valentina
Published: January 2024

Global food waste has a huge impact on the environment, as it is a source of greenhouse gas emissions and wasted natural resources. Across the world, over 30% of food is lost or wasted each year. Aside from this, the food industry, as well, is one of the biggest sources of agro-industrial waste and by-products, which can be valorized and used for different purposes. Such waste is a good source of bioactive organic compounds that can be extracted without altering their properties, where deep eutectic solvents can serve as green solvents and as an excellent replacement for volatile organic solvents. Isolated compounds can be used in innovative food production, chemical production, cosmetics and other industries. Deep eutectic solvents have attracted extraordinary attention due to their advantages such as environmental friendliness, availability and easy preparation, easy handling and utilization of non-toxic components for their formation. Due to these properties, they are a greener alternative to classic organic solvents for many processes, including extractions. In this paper, we review the utilization of deep eutectic solvents as potential green media for the extraction of organic compounds such as polyphenols, carbohydrates, proteins and alkaloids from by-products of the food industry and from agro-industrial waste.
Carceralities and Approved Gender Violence: The Case of Direct Provision in Ireland
Authors: Chakraborty Arpita , Repo Virve
Published: January 2024

In this article, we argue that Direct Provision in Ireland is a state approved form of gendered carcerality which creates and exacerbates conditions of gendered violence. Direct Provision is a system of processing asylum seekers in Ireland where they are temporarily provided accommodation while they wait for a decision on their refugee status claim. This article shows how carceral practices are layered and gendered, making some spaces and bodies more carceral than others. These carceralities increase the institutional burden which agglomerates in human bodies and makes the lives of an already precarious population unliveable. Through a review of the strategies adopted by the government in relation to migrants, undocumented workers and asylum seekers, this article shows how the gendered experiences of certain asylum seekers like mothers and sexual violence survivors become the political site where state approved carceral practices and gendered violence merge.
Microwave-Assisted Production of 5-Hydroxymethylfurfural from Fructose Using Sulfamic Acid as a Green Catalyst
Authors: Bertoncello Molon Vinícius , Ferreira Bruno Luís , Colombo Tedesco Carolina , Delagustin Maria Gabriele , Barcellos Thiago
Published: January 2024

The development of safe-by-design synthesis of valuable chemicals from biomass derivatives is a key step towards sustainable chemical transformations in both academia and industry. 5-Hydroxymethylfurfural (5-HMF) is a biomass derivative chemical of high commercial interest due to its wide range of chemical and biofuel applications. In this scenario, the present work contributes to a methodology for producing 5-hydroxymethylfurfural (5-HMF) through fructose dehydration reaction under microwave irradiation. The proposed protocol uses a simple sodium chloride–saturated aqueous-i-PrOH biphasic system and catalysis of sulfamic acid, a low-cost solid Brønsted–Lowry inorganic acid, which presents pivotal features of a sustainable catalyst. A 23 full factorial design was applied to achieve the highest conversion and 5-HMF yield, allowing the identification of the main factors involved in the process. Under the optimized conditions, fructose at the concentration of 120 g L−1 was converted with 91.15 ± 6.98% after 20 min at 180 °C, using 10 mol% of catalyst. 5-HMF was produced in 80.34 ± 8.41% yield and 73.20 ± 8.23% selectivity. Thus, the present contribution discloses a new optimized methodology for converting the biomass derivative fructose to 5-hydroxymethylfurfural (5-HMF).
The Impact of Capital Structure on the Performance of Serbian Manufacturing Companies: Application of Agency Cost Theory
Authors: Stoiljković Aleksandra , Tomić Slavica , Leković Bojan , Uzelac Ozren , Ćurčić Nikola V.
Published: January 2024

This paper examines the impact of debt in the capital structure on agency costs and therefore on the performance of a company. The efficiency of companies was estimated using two parametric techniques: Ordinary Least Squares (OLS) methods and a Stochastic Frontier Analysis (SFA). The estimated efficiency represents a measure of (inverse) agency costs. Agency costs cause a lower level of efficiency compared to companies that have minimized these costs, and companies that reach the efficiency frontier, in the observed context of this research, are viewed as those that have minimized agency costs. A panel regression model was applied in order to determine the direction and intensity of the influence of leverage and control variables on the initially estimated efficiency of the company. The results of this research on Serbian manufacturing companies show the expected positive effect of capital structure (leverage) on the efficiency of the company, which is in accordance with the predictions of the agency cost theory. The contribution of this research is reflected in the application of efficiency as a performance indicator in the observed context of examining the theory of agency costs, bearing in mind that the measure of efficiency is closer to the theoretical view of these costs.