bluuebunny/crossref_metadata_2025 huggingface dataset:
Type 1 Diabetes and Cataracts: Investigating Mediating Effects of Serum Metabolites Using Bidirectional Mendelian Randomization
Authors: Shi Yumeng , Qin Jingxi , Li Yankai , Yang Jin , Lu Yi
Published: November 2024

Purpose: To investigate the causal relationship between type 1 diabetes (T1D) and cataracts and to explore the mediating role of serum metabolites. Methods: This study employed bidirectional Mendelian randomization (MR) using genetic variants as instrumental variables to infer causality in both directions: from T1D to cataracts and cataracts to T1D. Genetic data for T1D, its complications, and cataracts were sourced from independent genome-wide association study (GWAS) datasets. A two-step multivariable MR combined with mediation analysis was conducted to evaluate the indirect effects of serum metabolites in the causal pathway from T1D to cataracts. Results: The MR analysis demonstrated a significant causal association between T1D and an increased risk of cataracts (OR = 1.01–1.05; p < 0.05). Further analysis showed that patients with T1D complications such as coma, ketoacidosis, nephropathy, and retinopathy exhibited a significantly higher risk of developing cataracts compared to those without complications. Sensitivity analyses upheld the robustness of these findings, with no evidence of heterogeneity or pleiotropy. Additionally, 102 serum metabolites were found to exhibit statistically significant mediation effects on cataract risk, with four (13-HODE + 9-HODE, 2-naphthol sulfate, docosadienoate (22:2n6), and X-12906) showing significant mediation effects. Specifically, 13-HODE + 9-HODE had a protective effect, while the other three metabolites were linked to an increased cataract risk. Conclusions: This study provides strong evidence of a causal link between T1D and cataracts, highlighting the mediating role of specific serum metabolites. These findings underscore the importance of early detection and management of cataracts in patients with T1D and suggest potential therapeutic targets for mitigating cataract risk. Further research should focus on replicating these findings in diverse populations and exploring the underlying metabolic pathways in greater detail.
Green Synthesis and Characterization of Silver Nanoparticles from Minthostachys acris Schmidt Lebuhn (Muña) and Its Evaluation as a Bactericidal Agent Against Escherichia coli and Staphylococus aureus
Authors: Ayma Fabián Ccahuana , Osorio Anaya Ana María , Peiter Gabrielle Caroline , Jaerger Silvia , Schneider Ricardo
Published: November 2024

The search for new synthesis methodologies based on the principles of green chemistry has led to various studies for the production of silver nanoparticles (AgNPs) using extracts from different parts of plants. Based on this, the present study aims to carry out green synthesis (biosynthesis), characterization, and antibacterial evaluation of reduced and stabilized silver nanoparticles (AgNPs) with aqueous extracts of Minthostachys acris in a simple, ecological, and environmentally safe manner. The extraction process of the organic components is performed using two methods: immersion and the agitation of the leaves of Minthostachys acris Schmidt Lebuhn (Muña) at 0.1% for different times (0.5, 1, 3, 6, and 10 min). Compounds such as hydroxycinnamic acid derivatives, quinic, caffeic, rosmarinic acids, and flavonols present in the Muña extract facilitate the formation of AgNPs; this compounds act as a coating and stabilizing agent. The bioactive components from natural resources facilitate the formation of AgNPs, partially or completely replacing the contaminating and toxic elements present in chemical reagents. The biosynthesis is carried out at room temperature for pH 7 and 8. The synthesized AgNPs are characterized by UV-visible spectroscopy to identify the surface plasmon resonance (SPR) band, which shows an absorption peak around 419 nm and 423 nm for pH 7 and p.H 8, respectively, and Fourier-transform infrared spectroscopy (FTIR) to identify the possible biomolecules responsible for bioreduction and stabilization, with a peak at 1634 cm−1. Dynamic light scattering (DLS) shows the hydrodynamic size of the colloidal nanoparticles between 11 and 200 nm, and scanning electron microscopy (SEM) reveals monodisperse AgNPs of different morphologies, mostly nanospheres, while Laser-Induced Breakdown Spectroscopy (LIBS) demonstrates the presence of Ag in the colloidal solution. The evaluation of the bactericidal activity of the AgNPs using the disk diffusion method against Escherichia coli (E. coli) and Staphylococus aureus (S.aureus) shows that the synthesized AgNPs have effective antibacterial activity against E. coli for the extracts obtained at 6 min for both the immersion and agitation methods, respectively. The significance of this work lies in the use of bioactive components from plants to obtain AgNPs in a simple, rapid, and economical way, with potential applications in biomedical fields.
Aerial Remote Sensing of Aquatic Microplastic Pollution: The State of the Science and How to Move It Forward
Authors: Chabot Dominique , Marteinson Sarah C.
Published: November 2024

Microplastics (MPs) are pervasive environmental contaminants in aquatic systems. Due to their small size, they can be ingested by aquatic biota, and numerous negative effects have been documented. Determining the risks to aquatic organisms is reliant on characterizing the environmental presence and concentrations of MPs, and developing efficient ways to do so over wide scales by means of aerial remote sensing would be beneficial. We conducted a systematic literature review to assess the state of the science of aerial remote sensing of aquatic MPs and propose further research steps to advance the field. Based on 28 key references, we outline three main approaches that currently remain largely experimental rather than operational: remote sensing of aquatic MPs based on (1) their spectral characteristics, (2) their reduction of water surface roughness, and (3) indirect proxies, notably other suspended water constituents. The first two approaches have the most potential for wide-scale monitoring, and the spectral detection of aquatic MPs is seemingly the most direct approach, with the fewest potential confounding factors. Whereas efforts to date have focused on inherently challenging detection in coarse-resolution satellite imagery, we suggest that better progress could be made by experimenting with image acquisition at much lower altitudes and finer spatial and spectral resolutions, which can be conveniently achieved using drones equipped with high-precision hyperspectral sensors. Beyond developing drone-based aquatic MP monitoring capabilities, such experiments could help with upscaling to satellite-based monitoring for global coverage.
Microplastic Aerosol Contamination in Porto (Portugal)
Authors: Logvina Yuliya , Moreira Diogo Silva , Santos Rui Pedro Moreira , Neves Inês Filipa , Ribeiro Helena , Pinto da Silva Luís , Esteves da Silva Joaquim
Published: November 2024

Microplastic pollution, particularly particles smaller than 5 mm, poses significant environmental and health risks due to their potential for inhalation and long-range transport. This study provides the first long-term assessment of airborne microplastics and fibers in Porto, Portugal, over 18 months (September 2022 to March 2024). Bi-weekly samples were collected using a Microplastic Collector NILU, which were size-fractionated into five categories (>125 μm, 125–63 μm, 63–25 μm, 25–12 μm, and 12–1.2 μm) and quantified via optical microscopy. Microplastic concentrations ranged from 26 to 1484 MPs/day/m2, while fiber concentrations varied from 14 to 646 fibers/day/m2. With a focus on the 12–1.2 μm size range due to their classifications as PM10 and PM2.5, the highest microplastic concentrations were 164 MPs/day/m2 (12–1.2 μm) and 534 MPs/day/m2 (25–12 μm). Recovery rates varied among polymers, with PP, PE-HD, and ABS showing high accuracy (75.9%) and PES significantly lower (26.5%). This study highlights the significant temporal variability in airborne microplastic and fiber pollution, correlations with meteorological parameters, and the need for ongoing monitoring and targeted mitigation strategies to address associated health risks.
Efficient Reuse of Rare Earth Carbonate Precipitation Mother Liquor for Rare Earth Leaching in Strong Acid-Restricted Area
Authors: Feng Jian , Wu Xiaoyan , Zhou Fang , Chi Ruan
Published: November 2024

Due to the restrictions of strong acids in some regions, the reuse process of rare earth (RE) precipitation mother liquor is difficult to carry out. To achieve the straightforward and efficient reuse of precipitation mother liquor in such areas, the potential for directly reusing this liquor for rare earth (RE) leaching was explored. The results showed that when the RE concentration in the leachate ranged from 0.1 to 1.5 g/dm3 and the RE precipitation rate exceeded 96%, the residual total carbonate content in precipitation mother liquor was less than 0.01 mol/L, and the solution pH was 7–8. Furthermore, when the total carbonate content in leaching liquor was lower than 0.01 mol/L, the presence of carbonate had a minimal impact on the RE leaching efficiency, which was observed to exceed 93%. Additionally, the process of mother liquor leaching was analyzed using dynamic models and chromatography tray theory. It was found that the leaching results were well fitted with the shrinking core model, and the apparent activation energy of RE was 5.77 kJ/mol, indicating that the reaction was controlled by diffusion, and the reaction order was 0.672 for RE. This confirms that a total carbonate content below 0.01 mol/L in the precipitation mother liquor can be directly used for the RE leaching process.
Wavelet-Detected Changes in Nocturnal Brain Electrical Activity in Patients with Non-Motor Disorders Indicative of Parkinson’s Disease
Authors: Runnova Anastasiya E. , Zhuravlev Maksim O. , Kiselev Anton R. , Parsamyan Ruzanna R. , Simonyan Margarita A. , Drapkina Oxana M.
Published: November 2024

Background/Objectives—Parkinson’s disease (PD) is the second most common neurodegenerative disorder caused by the destruction of neurons in the substantia nigra of the brain. Clinical diagnosis of this disease, based on monitoring motor symptoms, often leads to a delayed start of PD therapy and control, where over 60% of dopaminergic nerve cells are damaged in the brain substantia nigra. The search for simple and stable characteristics of EEG recordings is a promising direction in the development of methods for diagnosing PD and methods for diagnosing the preclinical stage of PD development. Methods—42 subjects participated in work, of which 4 female/10 male patients were included in the group of patients with non-motor disorders, belonging to the risk group for developing PD (median age: 62 years, height: 164 cm, weight: 70 kg, pulse: 70, BPsys and BPdia: 143 and 80)/(median age: 68 years, height: 170 cm, weight: 73.9 kg, pulse: 75, BPsys and BPdia: 143 and 82). The first control group of healthy participants included 6 women (median age: 33 years, height: 161 cm, weight: 66 kg, pulse: 80, BPsys and BPdia: 110 and 80)/8 men (median age: 36.3 years, height: 175 cm, weight: 69 kg, pulse: 78, BPsys and BPdia: 120 and 85). The second control group of healthy participants included 8 women (median age: 74 years, height: 164 cm, weight: 70 kg, pulse: 70, BPsys and BPdia: 145 and 82)/6 men (median age: 51 years, height: 172 cm, weight: 72.5 kg, pulse: 74, BPsys and BPdia: 142 and 80). Wavelet oscillatory pattern estimation is performed on patients’ nocturnal sleep recordings without separating them into sleep stages. Results—Amplitude characteristics of oscillatory activity in patients without motor disorders and the prodromal PD stage are significantly reduced both in terms of changes in the number of patterns and in terms of their duration. This pattern is especially pronounced for high-frequency activity, in frequency ranges close to 40 Hz. Conclusions—The success of the analysis of the electrical activity of the brain, performed over the entire duration of the night recording, makes it promising to further use during daytime monitoring the concept of oscillatory wavelet patterns in patients with non-motor disorders, belonging to the risk group for developing PD. The daytime monitoring system can become the basis for developing screening tests to detect neurodegenerative diseases as part of routine medical examinations.
Risk of Stroke or Heart Attack in Mild Cognitive Impairment and Subjective Cognitive Impairment
Authors: Lauriola Michele , Esposito Luigi , D’Onofrio Grazia , Ciccone Filomena , la Torre Annamaria , Addante Filomena , Cocomazzi Annagrazia , Cascavilla Leandro , Ariano Olga , Serviddio Gaetano , Greco Antonio
Published: November 2024

Background: The study aimed to identify Mild Cognitive Impairment (MCI) as an alert clinical manifestation of increased probability of major acute vascular events (MVEs), such as Ischemic Stroke and heart attack. Methods: In a longitudinal study, 181 (M = 81, F = 100; mean age of 75.8 ± 8.69 years) patients were enrolled and divided into three groups based on diagnosis: Subjective Cognitive Impairment (SCI), amnestic MCI Single Domain (aMCI-SD), and amnestic MCI More Domain (aMCI-MD). Clinical assessment and the presence of vascular risk factors were collected. Results: The distribution of MVEs showed a higher incidence in the first two years of follow-up of 7.4% in SCI, 12.17% in aMCI-SD, and 8.57% in aMCI-MD. Acute Myocardial Infarction showed a major incidence in one year of follow-up (41%) and in two years of follow-up (29%). Also, Ischemic Stroke showed a major incidence in one year of follow-up (30%) and in two years of follow-up (40%). A statistically significant difference in the progression to dementia was shown (SCI 3.75%; aMCI-SD 10.43%; aMCI-MD 37%; p-value < 0.001). Conclusions: MCI is considered an expression of the systemic activation of mechanisms of endothelial damage, representing a diagnosis predictive of increased risk of MVEs.
Effect of Phytochemical-Rich Food Intake on Respiratory and Muscle Function in Middle-Aged Patients with COPD: A Cross-Sectional Study
Authors: Ranogajec Alda , Ilić Ana , Benko Meštrović Snježana , Rumbak Ivana
Published: November 2024

Background: It is known that the consumption of single phytochemicals improves respiratory function in chronic obstructive pulmonary disease (COPD) patients. Since phytochemicals have a synergistic effect on health, a more comprehensive analysis is needed. The aim of this study was to estimate the intake of phytochemicals using the dietary phytochemical index (DPI) and assess their association with respiratory function, inspiratory muscle strength and function, and peripheral muscle strength. Methods: This study was conducted at the Special Hospital for Pulmonary Diseases in Zagreb (September 2023 to May 2024). The DPI was assessed using three 24 h recalls from 71 COPD patients (66.5 ± 8.4 years; 53.5% men). Anthropometric measurements, respiratory function, inspiratory muscle function and strength, and peripheral muscle strength were assessed during pulmonary rehabilitation following standard protocols. Results: Patients were divided into DPI tertiles with mean values of 7.3 ± 3.0, 16.0 ± 3.0, and 32.2 ± 8.8, respectively. After controlling for confounding factors, a significant association was found between DPI tertiles and FEV1 (p-trend < 0.001), FVC (p-trend = 0.002), FEV1/FVC (p-trend < 0.001), MIP (p-trend = 0.012), and MSUE (p-trend = 0.002). In addition, an inverse association was found between DPI tertiles and diaphragm thickness during inhalation (p-trend = 0.012) and exhalation (p-trend = 0.013). Conclusions: This study suggests that a higher intake of phytochemicals could be beneficial in dietary interventions for COPD therapy. Future prospective studies are needed to confirm these findings.
Effects of the Use of Probiotics in Post-Bariatric Surgery Obesity: Meta-Umbrella of Systematic Reviews
Authors: de Sousa Danilo Ferreira , Salaroli Luciane Bresciani
Published: November 2024

Obesity is a multifaceted health issue linked to conditions like type 2 diabetes, hypertension, and cardiovascular disease. Bariatric surgery is a well-established method for significant weight loss and health improvement, but maintaining weight loss and recovering post-surgery can be challenging. Probiotics, beneficial live microorganisms, are suggested as potential aids in managing obesity and its complications, but research on their effectiveness in this context is limited and diverse. This study aimed to evaluate the impact of probiotics on obesity in individuals post-bariatric surgery. A meta-umbrella review was conducted, analyzing systematic reviews and meta-analyses of probiotics’ effects. The review included studies from PubMed, Scopus, EMBASE, and Cochrane Library, focusing on weight loss, body composition, and metabolic parameters. Four systematic reviews met the criteria. The findings indicate that probiotics may significantly reduce waist circumference and body weight, and improve lipid and liver markers. However, their effects on glycemic parameters, quality of life, and adverse events were less clear. Overall, probiotics might offer modest benefits in managing weight and improving certain metabolic parameters after bariatric surgery. However, their overall efficacy, especially regarding glycemic control and quality of life, remains uncertain. Further high-quality research is needed to confirm these findings and elucidate the mechanisms involved.
Cilomilast Modulates Rhinovirus-Induced Airway Epithelial ICAM-1 Expression and IL-6, CXCL8 and CCL5 Production
Authors: Zhu Jie , Edwards Michael R. , Message Simon D. , Stanciu Luminita A. , Johnston Sebastian L. , Jeffery Peter K.
Published: November 2024

Background: Cilomilast, a phosphodiesterase-4 (PDE4) selective inhibitor, has anti-inflammatory effects in vitro and in vivo and reduces COPD exacerbations. We tested the hypothesis that cilomilast inhibits virus-induced airway epithelial intercellular adhesion molecule-1 (ICAM-1) expression and inflammatory cytokine/chemoattractants, IL-6, CXCL8, and CCL5 production in vitro. Methods: BEAS-2B bronchial epithelial cells were incubated with 0.5–2 MOI (multiplicity of infection–infectious units/cell) of rhinovirus 16 (RV16). Then, 0.1–10 μM cilomilast or 10 nM dexamethasone, as inhibition control, were added pre- or post-1 h RV16 infection. Supernatant and cells were sampled at 8, 24, 48, and 72 h after infection. Cell surface ICAM-1 expression was detected by immunogold labelling and visualised by high-resolution scanning electron microscopy (HR-SEM), while IL-6, CXCL8, and CCL5 protein release and mRNA expression were measured using an ELISA and RT-PCR. Results: Cilomilast significantly decreased RV16-induced ICAM-1 expression to approximately 45% (p < 0.01). CXCL8 protein/mRNA production was reduced by about 41% (p < 0.05), whereas IL-6 protein/mRNA production was increased to between 41–81% (p < 0.001). There was a trend to reduction by cilomilast of RV16-induced CCL5. Conclusions: Cilomilast has differential effects on RV16-induced ICAM-1 and interleukins, inhibiting virus-induced ICAM-1 expression and CXCL8 while increasing IL-6 production. These in vitro effects may help to explain the beneficial actions of this PDE4 inhibitor in vivo.
Correction: Jeong, J.-Y.; Hwang, Y.-J. Natural Phytochemical and Visible Light at Different Wavelengths Show Synergistic Antibacterial Activity against Staphylococcus aureus. Pharmaceutics 2024, 16, 612
Authors: Jeong Jae-Young , Hwang You-Jin
Published: November 2024

In the original publication [...]
Mechanical Characterization of Individual Needles in Microneedle Arrays: Factors Affecting Compression Test Results
Authors: Tsuboko Yusuke , Sakoda Hideyuki , Okamoto Yoshihiro , Nomura Yusuke , Yamamoto Eiichi
Published: November 2024

Background: This study aims to investigate the impact of test conditions on the results of the compression testing of microneedle arrays (MNAs). Methods: Uniaxial compression tests were conducted on polyglycolic acid-fabricated biodegradable MNAs. Load–displacement curves were obtained for varying conditions, including the number of microneedles (MNs) compressed simultaneously, compression speeds, and compression angles. Subsequently, the buckling load and stiffness were calculated, and the MN deformation during compression was observed. Results: The buckling load and stiffness per MN decreased significantly with a simultaneous increase in compressed MNs. The mean buckling load and stiffness of 52 MNs in single-needle compression tests were 0.211 ± 0.008 N and 13.9 ± 1.3 N/mm, respectively, with no variation among the three MNAs. However, a significant difference in buckling load and stiffness was observed among the MNs within the MNAs. Additionally, buckling loads and stiffnesses were significantly lower in certain MNs at the same location in different MNAs. Buckling load and stiffness decreased significantly during inclined compression compared to during vertical compression. While the tests evaluate the mechanical properties of MNAs, test results may vary depending on test conditions. Conclusions: Compression testing of the individual MNs comprising an MNA helps evaluate the mechanical properties of MNs and ensure the quality of MNAs.
Enteric Delayed-Release Granules Loading Dendrobine Ameliorates Hyperlipidemia in Mice by Regulating Intestinal Flora Composition
Authors: Song Shunqiang , Yang Liangyu , Chen Tingting , Xiong Yongai
Published: November 2024

Background/Objectives: In this paper, we created enteric delayed-release granules that load Dendrobine (DNL) directly into the intestinal flora of hyperlipidemic mice, based on the relationship between intestinal flora and hyperlipidemia. Methods: We then used pharmacodynamics and 16 Sr RNA high-throughput sequencing to examine the hypolipidemic effects and mechanism of these granules. Solvent evaporation was used to create the DNL, which was then characterized using FT–IR, XRD, SEM, and DSC. A high-fat diet was used to create the mouse model of hyperlipidemia in C57BL/6J mice. Dendrobine, various dosages of DNL, TMAO, and the combination of TMAO and DNL were subsequently gavaged on the mice. The makeup of the intestinal flora in the mouse colon was analyzed using 16S rRNA sequencing, and the effectiveness and mechanism of DNL in controlling the intestinal flora for the treatment of hyperlipidemia in mice were investigated. Results/Conclusions: The findings showed that DNL could effectively improve the dysbiosis brought on by hyperlipidemia by significantly lowering the mice’s body weight and blood lipid level (p < 0.05), while also regulating the function of their intestinal flora, increasing the abundance of Actinobacteria (p < 0.05) and Thick-walled bacterium (p < 0.05), and decreasing the abundance of Desulfovibrio (p < 0.05) and Mycobacterium anisopliae (p < 0.05) in the intestinal flora of mice, inhibiting the growth of intestinal harmful microorganisms, providing space for the reproduction of beneficial bacteria, and thus maintaining the stability of the intestinal flora’s structure.
The Impact of Seasonal Variation on Salivary Hormone Responses During Simulated Mountain Warfare
Authors: Stein Jesse A. , Palombo Laura J. , Givens Andrea C. , Bernards Jake R. , Kloss Emily B. , Bennett Daniel W. , Niederberger Brenda A. , Kelly Karen R.
Published: November 2024

Military personnel routinely complete stressful training exercises in harsh environmental conditions to prepare for intense operational demands. Purpose: This study determined the effect of environmental conditions on salivary hormone profiles in Marines during a mountain warfare training exercise (MTX). Methods: Two cohorts of Marines (age 22 ± 4, height 174 ± 7 cm, body mass 79.2 ± 11.5 kg) completed an MTX (elevation 2100 to 3500 m) in the Fall (n = 63, temperature 11 ± 2 °C) and Winter (n = 64, temperature −5 ± 4 °C). Saliva samples were provided before (PRE), during (MID), and after (POST) the MTX, and were assayed for α-amylase, cortisol, DHEA, testosterone, and osteocalcin. Results: Linear mixed models were used to determine significant interactions (time × season) and found differences in DHEA, testosterone, and osteocalcin. Testosterone and DHEA were lower at MID compared to PRE and POST during the Fall MTX. Testosterone was higher at MID compared to PRE and POST during the Winter MTX, while DHEA remained stable. Osteocalcin was higher in Fall participants compared to Winter but demonstrated a similar trend to increase at MID and decrease at POST in both groups. Cortisol was higher during the Winter MTX compared to the Fall. Conclusions: These findings highlight the differential physiological stress responses in varying seasonal conditions, suggesting the need for tailored training strategies to enhance military readiness and prevent hormonal dysregulation. Further research is needed to elucidate the mechanisms underlying these seasonal effects.
A Physics-Guided Machine Learning Model for Predicting Viscoelasticity of Solids at Large Deformation
Authors: Qin Bao , Zhong Zheng
Published: November 2024

Physics-guided machine learning (PGML) methods are emerging as valuable tools for modelling the constitutive relations of solids due to their ability to integrate both data and physical knowledge. While various PGML approaches have successfully modeled time-independent elasticity and plasticity, viscoelasticity remains less addressed due to its dependence on both time and loading paths. Moreover, many existing methods require large datasets from experiments or physics-based simulations to effectively predict constitutive relations, and they may struggle to model viscoelasticity accurately when experimental data are scarce. This paper aims to develop a physics-guided recurrent neural network (RNN) model to predict the viscoelastic behavior of solids at large deformations with limited experimental data. The proposed model, based on a combination of gated recurrent units (GRU) and feedforward neural networks (FNN), utilizes both time and stretch (or strain) sequences as inputs, allowing it to predict stress dependent on time and loading paths. Additionally, the paper introduces a physics-guided initialization approach for GRU–FNN parameters, using numerical stress–stretch data from the generalized Maxwell model for viscoelastic VHB polymers. This initialization is performed prior to training with experimental data, helping to overcome challenges associated with data scarcity.
Optimal Feature-Guided Position-Shape Dual Optimization for Building Point Cloud Facade Detail Enhancement
Authors: Li Shiming , Yan Fengtao , Ma Kaifeng , Hu Qingfeng , Wang Feng , Liu Wenkai
Published: November 2024

Dense three-dimensional point clouds are the cornerstone of modern architectural 3D reconstruction, containing a wealth of semantic structural information about building facades. However, current methods struggle to automatically and accurately extract the complex detailed structures of building facades from unstructured point clouds, with detailed facade modeling often relying heavily on manual interaction. This study introduces an efficient method for semantic structural detail enhancement of building facade point clouds, achieved through feature-guided dual-layer optimization of position and shape. The proposed framework addresses three key challenges: (1) robust extraction of facade semantic feature point clouds to effectively perceive the underlying geometric features of facade structures; (2) improved grouping of similarly structured objects using Hausdorff distance discrimination, overcoming the impact of point cloud omissions and granularity differences; (3) position-shape double optimization for facade enhancement, achieving detailed structural optimization. Validated on three typical datasets, the proposed method not only achieved 98.5% accuracy but also effectively supplemented incomplete scan results. It effectively optimizes semantic structures that widely exist and have the characteristic of repeated appearance on building facades, providing robust support for smart city construction and analytical applications.
Radar Moving Target Detection Based on Small-Sample Transfer Learning and Attention Mechanism
Authors: Zhu Jiang , Wen Cai , Duan Chongdi , Wang Weiwei , Yang Xiaochao
Published: November 2024

Moving target detection is one of the most important tasks of radar systems. The clutter echo received by radar is usually strong and heterogeneous when the radar works in a complex terrain environment, resulting in performance degradation in moving target detection. Utilizing prior knowledge of the clutter distribution in the space–time domain, this paper proposes a novel moving target detection network based on small-sample transfer learning and attention mechanism. The proposed network first utilizes offline data to train the feature extraction network and reduce the online training time. Meanwhile, the attention mechanism used for feature extraction is applied in the beam-Doppler domain to improve classification accuracy of targets. Then, a small amount of real-time data are applied to a small-sample transfer network to fine-tune the feature extraction network. Finally, the target detection can be realized by the fine-tuned network. Simulation experiments show that the proposed network can eliminate the influence of heterogeneous clutter on moving target detection, and the attention mechanism can improve clutter suppression under a low signal-to-noise ratio regime. The proposed network has a lower computational load compared to conventional neural networks, enabling its use in real-time applications on space-borne/airborne radars.
Flooded Infrastructure Change Detection in Deeply Supervised Networks Based on Multi-Attention-Constrained Multi-Scale Feature Fusion
Authors: Qin Gang , Wang Shixin , Wang Futao , Li Suju , Wang Zhenqing , Zhu Jinfeng , Liu Ming , Gu Changjun , Zhao Qing
Published: November 2024

Flood disasters are frequent, sudden, and have significant chain effects, seriously damaging infrastructure. Remote sensing images provide a means for timely flood emergency monitoring. When floods occur, emergency management agencies need to respond quickly and assess the damage. However, manual evaluation takes a significant amount of time; in current, commercial applications, the post-disaster flood vector range is used to directly overlay land cover data. On the one hand, land cover data are not updated in time, resulting in the misjudgment of disaster losses; on the other hand, since buildings block floods, the above methods cannot detect flooded buildings. Automated change-detection methods can effectively alleviate the above problems. However, the ability of change-detection structures and deep learning models for flooding to characterize flooded buildings and roads is unclear. This study specifically evaluated the performance of different change-detection structures and different deep learning models for the change detection of flooded buildings and roads in very-high-resolution remote sensing images. At the same time, a plug-and-play, multi-attention-constrained, deeply supervised high-dimensional and low-dimensional multi-scale feature fusion (MSFF) module is proposed. The MSFF module was extended to different deep learning models. Experimental results showed that the embedded MSFF performs better than the baseline model, demonstrating that MSFF can be used as a general multi-scale feature fusion component. After FloodedCDNet introduced MSFF, the detection accuracy of flooded buildings and roads changed after the data augmentation reached a maximum of 69.1% MIoU. This demonstrates its effectiveness and robustness in identifying change regions and categories from very-high-resolution remote sensing images.
Predicting Chemical Body Composition Using Body Part Composition in Boer × Saanen Goats
Authors: Teixeira Izabelle A. M. A. , Ferreira Adrian F. M. , Pereira Filho José M. , Tedeschi Luis O. , Resende Kleber T.
Published: November 2024

Two experiments were conducted to determine which part of the empty body of Boer × Saanen intact male kids can be used to predict the chemical composition of the whole body. In the first experiment, kids were fed ad libitum and slaughtered at 5, 10, and 15 kg body weight (BW). Eighteen animals were group-fed at three intake levels (ad libitum or restricted to 30% and 60% of the ad libitum level). When the ad libitum animal in the group reached 15 kg BW, all animals in the group were slaughtered. In the second experiment, kids were fed ad libitum and slaughtered at 15, 20, and 25 kg BW. Twenty-one animals were group-fed at three intake levels and slaughtered when the ad libitum animal within the group reached 25 kg BW. Analyzed body parts included head + feet, hide, organs, neck, shoulder, ribs, loin, leg, 9–11th ribs, and half carcass. Principal component and cluster analyses showed that the neck, 9–11th ribs, and loin had the highest frequency of grouping with the empty body. These body parts were used to develop prediction models for estimating body composition. The neck, loin, and 9–11th ribs accurately and precisely predicted the dry matter, ash, fat, protein, and energy body composition of goats, with most models also incorporating BW as a predictor variable. The equations showed root mean squared error (RMSE) lower than 13.5% and a concordance correlation coefficient (CCC) greater than 0.84. Fat and protein concentrations in the loin and neck were also reliable predictors of empty body energy composition (RMSE = 2.9% of mean and concordance correlation coefficient = 0.93). Removing the loin and 9–11th ribs could reduce the carcass retail price. Using the neck to estimate body composition in growing Boer × Saanen goats provides a valuable alternative for nutrition studies, given its low commercial value.
A 2.4 GHz IEEE 802.15.4 Multi-Hop Network for Mountainous Forest and Watercourse Environments: Sensor Node Deployment and Performance Evaluation
Authors: Booranawong Apidet , Hirunkitrangsri Puwasit , Buranapanichkit Dujdow , Pochaiya Charernkiat , Jindapetch Nattha , Saito Hiroshi
Published: November 2024

In this paper, we demonstrate the realistic test of a 2.4 GHz multi-hop wireless network for mountainous forest and watercourse environments. A multi-hop network using IEEE 802.15.4 XBee3 micro-modules and a communication protocol among nodes were developed. A wireless node deployment solution was introduced for practical testing. The proposed system’s communication reliability was tested in two different scenarios: a mountainous forest with sloping areas and trees and a watercourse, which referred to environmental and flooding monitoring applications. Wireless network performances were evaluated through the received signal strength indicator (RSSI) level of each wireless link, a packet delivery ratio (PDR), as the successful rate of packet transmission, and the end-to-end delay (ETED) of all data packets from the transmitter to the receiver. The experimental results demonstrate the success of the multi-hop WSN deployment and communication in both scenarios, where the RSSI of each link was kept at the accepted level and the PDR achieved the highest result. Furthermore, as a real-time response, the data from the source could be sent to the sink with a small ETED.
Solar Power Supply for Sensor Applications in the Field: A Guide for Environmental Scientists
Authors: Boitier Vincent , Cao Kha Bao Khanh , Estibals Bruno , Raimbault Vincent , Cauchoix Maxime , Druilhe Jean-Louis , Elger Arnaud
Published: November 2024

The move toward sophisticated sensor networks in ecological applications requires a substantial amount of energy. Energy storage solutions based simply on batteries are often not sufficient to cover the energy needs, so a standalone power supply using solar energy harvesting is generally required. However, designing an appropriate solar power supply without oversizing and avoiding output power disruption all year long is not a trivial task. This paper provides a set of guidelines as well as useful information and advice for environmental researchers and other non-experts to select the right components when designing their own autonomous solar power supply for a range between 10 mW and 10 W. The design steps are compiled into a comprehensive document, free of irrelevant information yet still presenting a general overview of the solar power supply design process, in order to make this task more accessible and understandable for non-experts. The methodology for simple initial dimensioning was carried out and applied to a real-life use case by using the estimated or measured daily consumption combined with free meteorological data of the deployment site provided by various websites. Next, an hourly simulation completed the first sizing. A year of experimental results validated the methodology.
Assessing the Environmental Sustainability Corridor: Carbon Emissions in Relation to Gold Price, Economic Growth, Foreign Direct Investment, and Renewable Energy Consumption
Authors: Seraj Mehdi , Olaide Ayantayo Rukayat
Published: November 2024

The growing concerns about global warming and its perceived influence on economic sustainability require a reassessment of the environmental consequences of gold mining, with a special focus on BRICS countries: Brazil, Russia, India, China, and South Africa. This paper examines the environmental sustainability corridor, carbon emission, gold price, economic growth, foreign direct investment (FDI), and renewable energy use between 1989 and 2020. The long-run association among the variables is checked by us through the PMG technique. Our findings indicate that while the gold price, FDI, and renewable energy use decrease carbon emission, economic growth adds to the increase in carbon emissions in the long run. These findings bring out the dual challenge of promoting economic growth while managing environmental impact. The study underlines how policymakers need to provide regulatory frameworks which will encourage renewable energy and responsible foreign investment, as a means of trying to mitigate the environmental impacts of gold mining and achieve sustainable development. Our research adds to the continuing debate about how economic expansion can be balanced with environmental preservation for resource-rich countries.
Quantifying Peak Load-Carrying Capability: A Comprehensive Reliability Analysis of Grid-Connected Hybrid Systems
Authors: Almgbel Osamah H. , Seedahmed Mustafa M. A. , Alhussainy Abdullah Ali , Alghamdi Sultan , Rawa Muhyaddin , Alturki Yusuf A.
Published: November 2024

Energy leaders around the world are constantly looking into feasibility and opportunities in renewable energy to diversify their energy sources. This study examines the reliability of a grid-connected microgrid consisting of solar energy, wind energy, and storage batteries to supply the required load and share the surplus with the grid. As the reliability of each component separately has an impact on system reliability, in this study, the loss of load expectation (LOLE) technique was used to estimate the peak load-carrying capability (PLCC) of the systems and the duration of outages as a means of analyzing the reliability of these systems and selecting the optimal combination among the cases. Moreover, this study used the load data of the area under study as the primary load and considered the grid as a secondary load to share the surplus after fulfilling the demand requirements. Furthermore, ten cases of grid-connected system configurations were considered to conduct this research, incorporating various combinations of solar panels, wind turbines (WTs), and batteries. The results revealed that, while maintaining an acceptable risk level represented by an LOLE of 0.1 days per year, the WT (850 MW) case emerged as the leading power producer compared to the other cases. It was able to produce 840.245 MW and 818.345 MW as the total power produced and the amount of surplus power that will be delivered to the grid after meeting the primary load needs in the area under study, respectively. This analysis can be informative for administrators in charge of planning and policy-making, helping them to take appropriate action.
Land Use Change and Its Impact on the Quality of the Ecological Environment in Xinjiang
Authors: Han Zhijuan , Wu Shu , Liu Jie
Published: November 2024

Xinjiang is a key area for implementing the Belt and Road Initiative, as well as an ecological security barrier in Northwest China. In this study, the remote sensing ecological index (RSEI) was constructed on the basis of the Google Earth Engine (GEE) platform combined with multiperiod (MODIS) remote sensing imagery to analyze the land use changes in Xinjiang and their impacts on the ecological and environmental quality from 2000 to 2023. The results are as follows. (1) The areas of land use changes in Xinjiang are concentrated mainly in the oasis areas around the mountain ranges and the Tarim Basin. (2) The quality of the overall ecological environment of Xinjiang showed an insignificant linear decreasing trend, with an annual rate of change of −0.0009 a−1 (p > 0.05). (3) The spatial distribution of the RSEI in Xinjiang revealed a significant positive spatial correlation and clustering pattern, which was high in the west and low in the east. (4) The increase in the cultivated land area had a positive effect on improving the quality of the ecological environment in Xinjiang. When the cultivated land area increased by 10%, the area of improvement in the quality of the ecological environment increased by 8.8%.
Port Service Coordination Sustainability in the Yangtze River Delta in China Based on Spatial Effects
Authors: Leng Zhaohua , Yuan Kebiao , Chen Xiaohong
Published: November 2024

With the prevalence of international trade protectionism and transformation and the upgrading of the domestic market structure, the contradiction between the demand for and the competitive development of the port market in the Yangtze River Delta in China has become increasingly prominent. The 19 major ports of the Yangtze River Delta in China were selected for this study, and using the methods of index evaluation, gravitational model, and spatial interpolation, the spatial effects in the hinterland were calculated from three dimensions, central potential, spatial gravity and distribution convenience, and the regional coordination of port services. The results show that the potential of the Shanghai Port and Ningbo Zhoushan Port in China is stronger, and the difference in the distribution of the ports is quite clear. The spatial gravity of each port city can be superimposed over one another to form a clear dense semi-circular zone, and the ability of the marginal ports to participate in this zone is weak. The convenience of their distribution in the hinterland changes from being location-dependent to traffic-dependent. The service gap in the hinterland of the port system is more significant, but the expansion of spatial effects makes the sustainability of regional coordination gradually improve. Finally, several policy suggestions are proposed to ensure ecological responsibility among resource-oriented enterprises.
CFD Simulation of Moving-Bed Pyrolizer for Sewage Sludge Considering Gas and Tar Behavior
Authors: Hamazaki Mayu , Miao Shan , Kameyama Mitsuo , Kamiuchi Hisashi , Dowaki Kiyoshi
Published: November 2024

This study focused on the small-scale dual fluidized-bed gasifier for hydrogen (H2) production from sewage sludge. One of the current problems with the pyrolizer is tar condensation. Tar could reduce the efficiency of the H2 yield by adhering and condensing on walls and pipes. It was revealed that more tar can be decomposed with higher reaction temperatures. Therefore, this study aimed to increase the tar decomposition efficiency with raising the heat carriers’ (HCs) temperature and analyzing the temperature distribution in the furnaces using a CFD simulation. The tar decomposition rate in the pyrolizer was +34.4%pt. by 100 °C of the HCs’ temperature rising. It is implied that less tar trouble and a longer lifetime of the H2 production plant could be expected by raising the HCs’ temperature. However, comparing the heat transfer efficiency of the whole system, the lower HC inlet temperature of +7.4%pt., because of the hot gas, which supplies heat to the HCs, required more heat, making the thermal efficiency poorer. In addition, the environmental impact of the AGM was increased by 27.2% with the HCs’ temperature rising to 100 °C. Thus, the heat exchange efficiency of the preheater needs to be improved to raise the HCs’ inlet temperature and reduce the amount of hot gas required.
Evaluation and External Driving Factors Analysis of Water–Energy–Food Resilience Security—Based on Spatial Durbin Model and Four Provinces Along the Yellow River
Authors: Huang Ruopeng , Liu Haibin
Published: November 2024

Research on water–energy–food security is crucial for ensuring the sustainable development of human society. Building on the water–energy–food theory and resilience concepts, a novel perspective termed “resilience security” was proposed. This differs from traditional approaches focused on coordination security and efficiency security. An indicator evaluation system consisting of 29 indicators was developed. Panel data from 2009 to 2022 in 40 cities across Shandong, Shanxi, Henan, and Shaanxi Provinces along the Yellow River were used to assess local water–energy–food resilience security. The nine external driving factors were empirically analyzed in different provinces using a spatial Durbin model. The findings indicate that: (1) over the 14-year period, the water––energy–food resilience security of the sample transitioned from a near-exposure state to an initial resistance state; and (2) over the 14-year period, administrative power, market power, resource flow capacity, population density, industrial structure, urbanization level, scientific and technological inputs, environmental governance inputs, and spatial geographic factors significantly influenced regional water–energy–food resilience security, with notable variations across provinces.
Carbon Footprint of Yerba Mate (Ilex paraguariensis) Value Chain in Misiones Province (Argentina)
Authors: Chifarelli Diego Hernán , Gruber Lorena , Azzini Lapo , Nicese Francesco Paolo , Giordani Edgardo
Published: November 2024

Yerba mate (YM) is an important crop derived from the cultivation of the native tree Ilex paraguariensis in northeastern Argentina, used for the preparation of mate infusion, which is widely consumed in South America. This study aimed at assessing the environmental impact, namely of CO2 equivalent (CO2eq.) emissions, of the YM value chain while identifying environmental hotspots along the production chain, from nursery up to transport. A cradle-to-wholesale approach was carried out, considering as the main functional unit 1 kg of commercial YM produced in Misiones Province and transported to Buenos Aires, the largest YM market in the world. Primary data were gathered from representative nurseries and plantations of the region; processing and packaging data were collected from a local cooperative, while the assessment of the impact due to truck transport was performed considering a distance of 1200 km from Buenos Aires. All the processes were analyzed using LCA methodology following the guidelines outlined in the ISO 14044 regulation (EN ISO 14044); the GaBi software (Sphera Solution, Inc., Chicago, IL, USA), updated to version 10.7.21.8, was used for process modeling, while the CML 2001 calculation method, updated as of the latest release in August 2016, was used to calculate the impacts. The results (1.24 kg CO2eq./kg. YM produced in Misiones and transported to Buenos Aires) show that the cultivation phase of YM has very little impact, while most of the emissions are related to the drying phase and the subsequent transportation from the production area to Buenos Aires.