bluuebunny/crossref_metadata_2025 huggingface dataset:
Sharks and Rays of Northern Australia’s Roper River, with a Range Extension for the Threatened Speartooth Shark Glyphis glyphis
Authors: Constance Julia M. , Garcia Erica A. ,   Yugul Mangi Rangers, Davies Christy-Louise , Kyne Peter M.
Published: November 2024

Northern Australia is considered a ‘lifeboat’ region for globally threatened shark and ray species (elasmobranchs), although much of the region is understudied. The Roper River in the Northern Territory’s Gulf of Carpentaria has been inadequately surveyed, with most elasmobranch data gained opportunistically through freshwater fish surveys. This study aimed to report the occurrence of elasmobranch species in the Roper River through targeted field surveys conducted between 2016 and 2024 and to review data from other sources. Four euryhaline species were recorded, comprising two sharks, a sawfish, and a stingray. Records of the globally Vulnerable speartooth shark (Glyphis glyphis) represented a significant range extension and the documentation of a new reproductive population. Records of the Critically Endangered largetooth sawfish (Pristis pristis) extended almost 400 km upstream, highlighting extensive use of the river system. A predominantly marine species, the Critically Endangered giant guitarfish (Glaucostegus typus) was observed in brackish estuarine waters, approximately 15 km upstream from the river mouth. Further research is required to develop a more thorough understanding of abundance, life history, and population connectivity for these species in this river system. Given the documentation of threatened species, the potential impacts of fisheries, water allocations, and climate change require assessment.
Expert Consultation: Factors Influencing End-of-Life Decision-Making for Dairy Cattle Across the United States Supply Chain
Authors: Edwards-Callaway Lily , McBride Brianna , Machuca Erica , Dean Lauren , Sayre Kira , Cramer Catie , Román-Muñiz Noa , Keller Kayleigh , Stallones Lorann , Manriquez Diego
Published: November 2024

The end-of-life (i.e., on-farm euthanasia and culling, including fitness for transport to slaughter) of a dairy cow or calf is preceded by a series of decisions often influenced by many complex factors. The aim of this study was to utilize the opinions of experts with roles in the dairy supply chain to identify factors that influence end-of-life decision-making for dairy cattle. Twenty experts serving in supporting roles in the dairy supply chain participated in a survey containing 17 open-ended questions. Of the participants, 55% (n = 11) identified as veterinarians and the remaining 45% (n = 9) participated in other segments of the dairy supply chain. Twelve themes were identified in the qualitative analysis of survey responses. The themes included: Training and Resources, Cattle Health Management, Decision-Making Criteria, Company Culture, Personal Beliefs, Human Well-Being, Animal Welfare, Economics, Guidelines and Inspections, Consumer Perceptions, Supply Chain Considerations, and Communication. Experts indicated that training programs should address euthanasia or fitness-for-transport criteria, the knowledge of common health conditions, and information about what happens to cattle after leaving the dairy. Additional influencing factors included personal beliefs, economics, company culture, and supply chain considerations.
From Gene to Protein: Unraveling the Reproductive Blueprint of Male Grey Squirrels via Nerve Growth Factor (NGF) and Cognate Receptors
Authors: Mercati Francesca , Guelfi Gabriella , Bufalari Antonello , Dall’Aglio Cecilia , Suvieri Chiara , Cocci Paolo , Palermo Francesco Alessandro , Anipchenko Polina , Capaccia Camilla , Cenci-Goga Beniamino , Zerani Massimo , Maranesi Margherita
Published: November 2024

The grey squirrel, an invasive species, threatens the Eurasian red squirrel’s conservation, particularly in Umbria, Italy. Understanding its reproductive biology is essential to limiting its reproductive success. This study investigates the NGF system and its receptors (NTRK1 and p75NTR) in the testes of male grey squirrels, following prior research on female reproductive biology. NGF plays a role in testicular morphogenesis and spermiogenesis in animals and humans. As part of the LIFE Project U-SAVEREDS, eighteen squirrels were captured and classified into three morphotypes (immature, pubertal, and active spermatogenesis). NGF and its receptors were analyzed using real-time PCR, western blotting, immunohistochemistry, and plasma levels measured via ELISA. NGF qPCR expression levels were significantly higher during puberty compared to the immature and spermatogenesis stages (p < 0.01). Immunohistochemistry revealed NGF in Leydig cells, with stronger staining in pubertal and mature squirrels, while NTRK1 was found in Leydig cells in immature squirrels and germ cells in pubertal and mature ones. NGF receptors were observed in Sertoli cells in pubertal and mature squirrels. Plasma NGF levels showed a significant upregulation in pubertal squirrels (135.80 ± 12 pg/mL) compared to those in the immature (25.60 ± 9.32 pg/mL) and spermatogenesis stages (34.20 ± 6.06 pg/mL), with a p value < 0.01. The co-localization of NGF and its receptors suggests that NGF, produced by Leydig cells, regulates testis development and reproductive success through autocrine or paracrine mechanisms, potentially involving an unidentified pathway.
The Use of Antioxidants for Cardiovascular Protection in Fetal Growth Restriction: A Systematic Review
Authors: Rock Charmaine R. , Miller Suzanne L. , Allison Beth J.
Published: November 2024

Fetal growth restriction (FGR) increases the risk of cardiovascular disease. There are currently no treatment options available; however, antioxidants have shown potential to improve cardiovascular deficits associated with FGR. This systematic review aimed to determine whether antenatal antioxidant intervention can effectively protect the developing cardiovascular system in FGR. We searched for interventional studies that used an antenatal antioxidant intervention to improve cardiac and/or vascular outcomes in FGR published between 01/1946 and 09/2024 using MEDLINE and Embase (PROSPERO: CRD42024503756). The risk of bias was assessed with SYRCLE. The studies were assessed for cardiovascular protection based on the percentage of cardiac and/or vascular deficits that were restored with the antioxidant treatment. Studies were characterised as showing strong cardiovascular protection (≥50% restoration), mild cardiovascular protection (>0% but <50% restoration), an antioxidant-only effect (this did not include control group which showed a change with antioxidant intervention compared to FGR) or no cardiovascular protection (0% restoration). Thirty-eight publications met the inclusion criteria, encompassing 43 studies and investigating 15 antioxidant interventions. Moreover, 29/43 studies (71%) reported the restoration of at least one cardiac or vascular deficit with antioxidant intervention, and 21/43 studies (51%) were classified as strong cardiovascular protection. An ex vivo analysis of the arterial function in seven studies revealed endothelial dysfunction in growth-restricted offspring and antioxidant interventions restored the endothelial function in all cases. Additionally, four studies demonstrated that antioxidants reduced peroxynitrite-mediated oxidative stress. Notably, only 13/43 studies (32%) delayed antioxidant administration until after the induction of FGR. Antenatal antioxidant interventions show promise for providing cardiovascular protection in FGR. Melatonin was the most frequently studied intervention followed by nMitoQ, vitamin C and N-acetylcysteine, all of which demonstrated a strong capacity to reduce oxidative stress and improve nitric oxide bioavailability in the cardiovascular system of growth-restricted offspring; however, this systematic review highlights critical knowledge gaps and inconsistencies in preclinical research, which hinder our ability to determine which antioxidant treatments are currently suitable for clinical translation.
Oxidative Stress in an African Ground Squirrel, a Case of Healthy Aging and Reproduction
Authors: Jacobs Paul Juan , Vos Sjoerd , Bishop Chelsea E. , Hart Daniel William , Bennett Nigel Charles , Waterman Jane M.
Published: November 2024

Oxidative stress plays a crucial role in mediating life-history processes, where it can compromise survival and reproduction through harmful alterations to DNA, lipids, and proteins. In this study, we investigated oxidative stress in Cape ground squirrels (Xerus inauris), a longer-lived African ground squirrel species with a high reproductive skew and unique life history strategies. We measured oxidative stress as total antioxidant capacity (TAC), total oxidant status (TOS), and an oxidative stress index (OSI) in blood plasma from individuals of approximately known ages. Our results reveal a distinct pattern of decreasing oxidative stress with age, consistent across both sexes. Females exhibited lower OSI and TOS levels than males. Males employing different life-history strategies, namely natal (staying at home), had significantly lower oxidative stress compared to the band (roaming male groups), likely due to variations in metabolic rate, activity, and feeding rates. However, both strategies exhibited reduced oxidative stress with age, though the underlying mechanisms require further investigation. We propose that selection pressures favoring survival contributed to the observed reduction in oxidative stress with age, potentially maximizing lifetime reproductive success in this species.
Persulfidation of Human Cystathionine γ-Lyase Inhibits Its Activity: A Negative Feedback Regulation Mechanism for H2S Production
Authors: Jia Guanya , Li Heng , Gan Haisheng , Wang Jun , Zhu Zhilong , Wang Yanxiong , Ye Yongyi , Shang Xiaoya , Niu Weining
Published: November 2024

Cystathionine γ-lyase (CSE) is the second enzyme in the trans-sulfuration pathway that converts cystathionine to cysteine. It is also one of three major enzymes responsible for the biosynthesis of hydrogen sulfide (H2S). CSE is believed to be the major source of endogenous H2S in the cardiovascular system, and the CSE/H2S system plays a crucial role in a variety of physiological and pathological processes. However, the regulatory mechanism of the CSE/H2S system is less well understood, especially at the post-translational level. Here, we demonstrated that the persulfidation of CSE inhibits its activity by ~2-fold in vitro. The loss of this post-translational modification in the presence of dithiothreitol (DTT) results in a reversal of basal activity. Cys137 was identified as the site for persulfidation by combining mass spectrometry, mutagenesis, activity analysis and streptavidin–biotin pull-down assays. To test the physiological relevance of the persulfidation regulation of CSE, human aortic vascular smooth muscle cells (HA-VSMCs) were incubated with vascular endothelial growth factor (VEGF), which is known to enhance endogenous H2S levels. Under these conditions, consistent with the change tendency of the cellular H2S level, the CSE persulfidation levels increased transiently and then gradually decreased to the basal level. Collectively, our study revealed a negative feedback regulation mechanism of the CSE/H2S system via the persulfidation of CSE and demonstrated the potential for maintaining cellular H2S homeostasis under oxidative stress conditions, particularly in tissues where CSE is a major source of H2S.
Influence of the Degree of Unsaturation in Fish Oil Supplements on Oxidative Stress and Protein Carbonylation in the Cerebral Cortex and Cerebellum of Healthy Rats
Authors: Moreno Francisco , Méndez Lucía , Fernández Ingrid , Miralles-Pérez Bernat , Giralt Montserrat , Romeu Marta , Ramos-Romero Sara , Torres Josep Lluís , Medina Isabel
Published: November 2024

ω-3 polyunsaturated fatty acids (PUFAs) are crucial for brain structure and function, especially docosahexaenoic acid (DHA). However, an excess of DHA may increase lipid peroxidation due to its high degree of unsaturation, particularly in tissues highly susceptible to oxidative stress, such as the brain. Therefore, this study evaluated the effects of 10 weeks of dietary supplementation with fish oil containing 80% DHA on oxidative stress and the modulation of the carbonylated proteome in both the cerebral cortex and cerebellum of male Sprague Dawley rats. The results were compared with those induced by oils with a lower degree of fat unsaturation (fish oil containing 25% DHA and 25% eicosapentaenoic acid, soybean oil containing 50% linoleic acid and coconut oil containing 90% saturated fat). The results demonstrated that fish oil containing 80% DHA significantly increased the ω3/ω6 ratio in both the cortex and cerebellum while stimulating antioxidant defense by enhancing the reduced glutathione amount and decreasing the carbonylation of specific proteins, mainly those involved in glycolysis and neurotransmission. The majority of sensitive proteins in both brain regions followed this carbonylation trend (in decreasing order): soybean > EPA/DHA 1:1 > coconut > 80% DHA. The results also indicated that the cerebellum is more responsive than the cortex to changes in the cellular redox environment induced by varying degrees of fat unsaturation. In conclusion, under healthy conditions, dietary supplementation with fish oils containing high DHA levels makes the brain more resilient to potential oxidative insults compared to oils with lower DHA content and a lower degree of fatty acid unsaturation.
Polyphenolic Antioxidants in Bilberry Stems and Leaves: A Non-Targeted Analysis by Two-Dimensional NMR Spectroscopy and Liquid Chromatography–High-Resolution Mass Spectrometry
Authors: Faleva Anna V. , Ulyanovskii Nikolay V. , Onuchina Alexandra A. , Kosyakov Dmitry S.
Published: November 2024

Compared with those of berries, the stems and leaves of the genus Vaccinium are important and underestimated sources of polyphenols with high antioxidant activity. In the course of this work, aqueous methanol extracts of the aerial parts of common bilberry (Vaccinium myrtillus L.) and bog bilberry (Vaccinium uliginosum L.) were studied to analyze the component compositions of their biologically active polyphenolic compounds. The aqueous methanol fractions of the stems and leaves of the studied samples contained 8.7 and 4.6% extractives, respectively, and were comparable in total polyphenol content, but presented significant differences in antioxidant activity. The identification of polyphenolic compounds was carried out via the following two-stage analytical procedure: (1) non-targeted screening of dominant structures via the 2D NMR method and (2) analysis of HPLC-HRMS data via the scanning of precursor ions for a specific ion. A total of 56 phenolic compounds were identified, including the glycosides quercetin, proanthocyanidins, and catechins, as well as various conjugates of caffeic and p-coumaric acids, including iridoids. Some of the latter, such as caffeoyl and p-coumaroyl hydroxydihydromonotropein, as well as a number of lignan glycosides, were described for the first time in V. uliginósum and V. myrtillus.
Correction: Mahmoud et al. Coriander Oil Reverses Dexamethasone-Induced Insulin Resistance in Rats. Antioxidants 2022, 11, 441
Authors: Mahmoud Mona F. , Ali Noura , Mostafa Islam , Hasan Rehab A. , Sobeh Mansour
Published: November 2024

In the original publication [...]
Nitroxyl Hybrids with Curcumin and Stilbene Scaffolds Display Potent Antioxidant Activity, Remodel the Amyloid Beta Oligomer, and Reverse Amyloid Beta-Induced Cytotoxicity
Authors: Budamagunta Madhu S. , Mori Hidetoshi , Silk Joshua , Slez Ryan R. , Bognár Balázs , Mendiola Ulises Ruiz , Kálai Tamás , Maezawa Izumi , Voss John C.
Published: November 2024

The disorder and heterogeneity of low-molecular-weight amyloid-beta oligomers (AβOs) underlie their participation in multiple modes of cellular dysfunction associated with the etiology of Alzheimer’s disease (AD). The lack of specified conformational states in these species complicates efforts to select or design small molecules to targeting discrete pathogenic states. Furthermore, targeting AβOs alone may be therapeutically insufficient, as AD progresses as a multifactorial, self-amplifying cascade. To address these challenges, we have screened the activity of seven new candidates that serve as Paramagnetic Amyloid Ligand (PAL) candidates. PALs are bifunctional small molecules that both remodel the AβO structure and localize a potent antioxidant that mimics the activity of SOD within live cells. The candidates are built from either a stilbene or curcumin scaffold with nitroxyl moiety to serve as catalytic antioxidants. Measurements of PAL AβO binding and remolding along with assessments of bioactivity allow for the extraction of useful SAR information from screening data. One candidate (HO-4450; PMT-307), with a six-membered nitroxyl ring attached to a stilbene ring, displays the highest potency in protecting against cell-derived Aβ. A preliminary low-dose evaluation in AD model mice provides evidence of modest treatment effects by HO-4450. The results for the curcumin PALs demonstrate that the retention of the native curcumin phenolic groups is advantageous to the design of the hybrid PAL candidates. Finally, the PAL remodeling of AβO secondary structures shows a reasonable correlation between a candidate’s bioactivity and its ability to reduce the fraction of antiparallel β-strand.
Imeglimin Halts Liver Damage by Improving Mitochondrial Dysfunction in a Nondiabetic Male Mouse Model of Metabolic Dysfunction-Associated Steatohepatitis
Authors: Kaji Kosuke , Takeda Soichi , Iwai Satoshi , Nishimura Norihisa , Sato Shinya , Namisaki Tadashi , Akahane Takemi , Yoshiji Hitoshi
Published: November 2024

Imeglimin promotes glucose-stimulated insulin secretion in the pancreas in a glucose-dependent manner and inhibits gluconeogenesis in the liver. Meanwhile, imeglimin can improve mitochondrial function in hepatocytes. We used a nondiabetic metabolic dysfunction-associated steatohepatitis (MASH) model to examine the effects of imeglimin on MASH independent of its glucose-lowering action. Mice fed a choline-deficient high-fat diet (CDA-HFD) were orally administered imeglimin (100 and 200 mg/kg twice daily), and MASH pathophysiology was evaluated after 8 weeks. Moreover, an in vitro study investigated the effects of imeglimin on palmitic acid (PA)-stimulated lipid accumulation, apoptosis, and mitochondrial dysfunction in human hepatocytes. CDA-HFD-fed mice showed hepatic steatosis, inflammation, and fibrosis without hyperglycemia. Imeglimin reduced hepatic steatosis in response to increased expression of β-oxidation-related markers. Imeglimin reduced reactive oxygen species accumulation and increased mitochondrial biogenesis in CDA-HFD-fed mice. Consequently, imeglimin suppressed hepatocyte apoptosis and decreased macrophage infiltration with reduced proinflammatory cytokine expression, suppressing hepatic fibrosis development. PA-stimulated hepatocytes induced lipogenesis, inflammatory cytokine production, and apoptosis, which were significantly suppressed by imeglimin. In mitochondrial function, imeglimin improved PA-stimulated decrease in mitochondrial membrane potential, mitochondrial complexes activity, oxygen consumption rate, and mitochondrial biogenesis marker expression. In conclusion, imeglimin could contribute to prevention of MASH progression through suppressing de novo lipogenesis and enhancing fatty acid oxidation.
Development of Mixing Temperature Prediction Model for Single-Duct Variable Air Volume System Using CFD
Authors: Kim Minjun , Kim Hyojun , Lee Jinhyun , Cho Younghum
Published: November 2024

The purpose of this study was to determine the annual energy consumption that can be attributed to heating, ventilation, and air conditioning (HVAC) systems’ mixing temperature error. To develop a mixing temperature prediction model for a single-duct variable air volume (VAV) system, the mixing temperature was measured using 15 temperature sensors installed in an HVAC mixing chamber as well as the existing air handling unit’s (AHU) mixing temperature sensor. The mixing chamber was modeled using computational fluid dynamics (CFD), and a coefficient of variation of the root-mean-square error of 7.927% indicated that the model was reliable. Next, CFD simulation cases were formulated, and the temperature distribution of the mixing chamber was analyzed. This revealed that the amount of outdoor airflow input and the change in the temperature distribution of the mixing chamber were directly proportional to each other and that the mixing temperature measurements for the mixing chamber were not accurate. The mixing temperature prediction model was developed through multiple regression analysis and was successfully applied and verified. Compared with the measurements provided by existing mixing temperature sensors, the mixing temperature prediction model indicated an absolute error of 0.008–0.42 °C, confirming the model’s prediction performance.
Chondrogenic Cancer Grading by Combining Machine and Deep Learning with Raman Spectra of Histopathological Tissues
Authors: Lazzini Gianmarco , D’Acunto Mario
Published: November 2024

Raman spectroscopy (RS) is a promising tool for cancer diagnosis. In particular, in the last years several studies have demonstrated how the diagnostic performances of RS can be significantly improved by employing machine learning (ML) algorithms for the interpretation of Raman-based data. Recently, it has been demonstrated that RS can perform an accurate classification of chondrosarcoma tissues. Chondrosarcoma is a cancer of bones, that can occur in the soft tissues near the bones. It is normally characterized by three different malignant degrees and a benign counterpart, knows as enchondroma. In line with these findings, in this paper, we exploited ML algorithms to distinguish, as well as possible, between the three grades of chondrosarcoma and to distinguish between chondrosarcoma and enchondroma. We obtained a high level of accuracy of classification by analyzing a dataset composed of a relatively small number of Raman spectra, collected in a previous study by one of the authors of this paper. Such spectra were acquired from micrometric tissue sections with a confocal Raman microscope. We tested the classification performances of a support vector machine (SVM) and a random forest classifier (RFC), as representatives of ML algorithms, and two versions of the multi-layer perceptron (MLPC) as representatives of deep learning (DL). These models, especially RFC and MLPC, showed excellent classification performances, with accuracy reaching 99.7%. This outcome makes the aforementioned models a promising route for future improvements of diagnostic devices focused on detecting cancerous bone tissues. Alongside the diagnostic purpose, the aforementioned approach allowed us to identify characteristic molecules, i.e., amino acids, nucleic acids, and bioapatites, relevant for obtaining the final diagnostic response, through the use of a tool named by us Raman Band Identification (RBI). The method to evaluate RBI is the most important contribution of this paper, because RBI could represent a relevant parameter for the identification of biochemical processes on the basis of the tumor progression and associated malignant degree. In turn, the spectral bands highlighted by RBI could provide precious indicators in an attempt to restrict the spectral acquisition to specific Raman bands. This last objective could help to reduce the amount of experimental data needed to obtain an accurate final grading outcome, with a consequent reduction in the computational cost.
Usability and Affects Study of a Virtual Reality System Toward Scorpion Phobia Exposure Therapy
Authors: Gutierrez-Sanchez Ma. de Jesus , Gonzalez-Islas Juan-Carlos , Huerta-Ortiz Luis-Manuel , Franco-Arcega Anilu , Vazquez-Vazquez Vanessa-Monserrat , Suarez-Navarrete Alberto
Published: November 2024

In this study, we present a framework to develop and evaluate a virtual reality exposure therapy system with biofeedback toward scorpion phobia treatment. The system is developed based on the methodology for the development of virtual reality educational environments; usability is evaluated with the System Usability Scale (SUS), the affects are measured with the Positive and Negative Affect Schedule (PANAS), and the biofeedback heart rate is measured in real time using a wearable device and the HypeRate app. A descriptive study was conducted with a non-probabilistic convenience sample of undergraduate students. The non-clinical sample consisted of 51 participants (11 women and 40 men) (mean = 20.75, SD = 2.42 years). The system usability score was 75.49, higher than the average of 68. For positive affects, the average value of the overall sample was 28.18, while for negative affects it was 13.67. The results of this preliminary study, while not determining that the system could currently be applied in clinical settings, demonstrate however that the system can initially be considered as a pre-feasibility study, and if the limitations of the unbalanced non-clinical sample are addressed, it could be used in the future for this purpose. The main contribution is the proposed framework to integrate usability and affects evaluation, as well as biofeedback in a VRET system toward scorpion phobia treatment.
Versatility Evaluation of Landslide Risk with Window Sizes and Sampling Techniques Based on Deep Learning
Authors: Ren Fudong , Isobe Koichi
Published: November 2024

Across the globe, landslides cause significant loss of life, injuries, and widespread damage to homes and infrastructure. Therefore, assessing and analyzing landslide hazards is crucial to human, environmental, cultural, economic, and social sustainability. This study utilizes ArcGIS 10.8 and Python 3.9 to create landslide databases for Niigata Prefecture (NIG), Iwate and Miyagi Prefectures (IWT-MYG), and Hokkaido (HKD), drawing on data obtained from the National Research Institute for Earth Science and Disaster Resilience, Japan. A distinguishing feature of this study is the application of a Convolutional Neural Network (CNN), which significantly outperforms traditional machine learning models in image-based pattern recognition by extracting contextual information from surrounding areas, a distinct advantage in image and pattern recognition tasks. Unlike conventional methods that often require manual feature selection and engineering, CNNs automate feature extraction, enabling a more nuanced understanding of complex patterns. By experimenting with CNN input window sizes ranging from 3 × 3 to 27 × 27 pixels and employing diverse sampling techniques, we demonstrate that larger windows enhance the model’s predictive accuracy by capturing a wider range of environmental interactions critical for effective landslide modeling. CNN models with 19 × 19 pixel windows typically yield the best overall performance, with CNN-19 achieving an AUC of 0.950, 0.982 and 0.969 for NIG, HKD, and IWT-MYG, respectively. Furthermore, we improve prediction reliability using oversampling and a random window-moving method. For instance, in the NIG region, the AUC of the oversampling CNN-19 is 0.983, while the downsampling AUC is 0.950). These techniques, less commonly applied in traditional machine learning approaches to landslide detection, help address the issue of data imbalance often seen in landslide datasets, where instances of landslides are far outnumbered by non-landslide occurrences. While challenges remain in enhancing the model’s generalization, this research makes significant progress in developing more robust and adaptable tools for landslide prediction, which are vital for ensuring environmental and societal resilience.
Development of a VR360 Ecological System for Learning Indigenous Cultures and Environmental Conservation
Authors: Tarng Wernhuar , Hsu Jen-Chu
Published: November 2024

The cultures and religious beliefs of Taiwanese indigenous peoples are deeply rooted in ecological protection and environmental ethics. Indigenous peoples emphasize reverence for nature, ecological diversity, sustainable living, resource sharing, and sanctity of nature. Integrating environmental education with indigenous culture can promote biodiversity and ecological conservation while preserving indigenous traditions and fostering sustainable development. This study combined Virtual Reality 360-degree (VR360) technology with indigenous culture to develop a virtual ecological system as a learning tool for environmental education in indigenous elementary schools. The VR360 system simulates the ecological environments of Chichiawan Creek and the Atayal Nanshan Tribe in the mountainous regions of northern Taiwan to provide students with immersive experiences that enhance their learning interest and motivation. Through interactive operations, they can observe the appearance, characteristics, and habitual behaviors of Formosan Landlocked Salmon and other conservation animals to understand the relationship between maintaining biodiversity and ecological balance. The VR360 ecological system enhances learning effectiveness and motivation using low-cost cardboard glasses, making it suitable for promoting indigenous culture and environmental education while reducing the digital divide in remote tribal areas.
Application of Machine Learning in Construction Productivity at Activity Level: A Critical Review
Authors: Lim Ying Terk , Yi Wen , Wang Huiwen
Published: November 2024

There are two crucial resources (i.e., labor and equipment) of productivity in the construction industry. Productivity modeling of these resources would aid stakeholders in project management and improve construction scheduling and monitoring. Hence, this research aims to review machine learning (ML) applications in the process of construction productivity modeling (CPM) for construction labor productivity (CLP) and construction equipment productivity (CEP) from dataset acquisition to data analysis and evaluation, which includes their trends and applicability. An extensive analysis of 131 journals focused on the application of machine learning in construction productivity (ML-CP) from 1990 to 2024 via a mixed review methodology (bibliometric analysis and systematic review) was conducted. It can be concluded that despite the rise in automated dataset collection, the traditional method has its advantages. The review further found that the selection of ML models relies on each particular application, available data, and computational resources. Noticeably, artificial neural networks, convolutional neural networks, support vector machines, and even deep learning demonstrating have been adopted due to their effectiveness in different functionalities and processes in CPM. This study will supplement the insights gained in the review with a comprehensive understanding of how ML applications operate at each stage of CPM, enabling researchers to make future improvements.
Determination of Geochemical Background and Baseline and Research on Geochemical Zoning in the Desert and Sandy Areas of China
Authors: Wen Weiji , Yang Fan , Xie Shuyun , Wang Chengwen , Song Yuntao , Zhang Yuepeng , Zhou Weihang
Published: November 2024

Resources in deserts and sandy landscapes have potential for development, but existing surveys and sampling have not collected desert soil samples. As such, the geochemical background of these spaces remains unexplored due to the vastness and desolation of deserts. Therefore, researching the geochemical background values and geochemical baseline values of deserts is of long-term significance. Our research indicates that in addition to macrostructural environmental divisions, microelement geochemistry can also be used for geological unit zoning. In this paper, geochemical background and geochemical baseline values of 61 desert elements were calculated using the iterative method, frequency histograms method, and multifractal concentration-area method. It also analyzes the distribution characteristics of major, trace, and rare earth elements, and divides the 12 desert sand regions into different geochemical zones. This paper determines, for the first time, the geochemical background values of elements in Chinese deserts, filling the gap in the study of desert background values. By combining machine learning methods, different deserts have been divided into three geochemical zones. This research will greatly enhance our ability to interpret the geochemical distribution and evolutionary patterns of desert elements in China, and it has important scientific significance and practical value for desert research.
Evaluating the Usefulness of a PNT Solution Using DGNSS-SBAS for Canoe Slalom: Simulated and Real-World Analysis
Authors: Macdermid Paul William , Irwin Mathew E. , Cochrane Darryl
Published: November 2024

This study investigated the accuracy and precision of a commercially available PNT solution that uses DGNSS-SBAS technology. Time and position data were sampled at a frequency of 20Hz during both a short and long trajectory of a simulated controlled dry-land slalom, as well as during a real-world on-water slalom exercise. The primary objective was to assess the positional accuracy, availability, integrity, and service continuity of the PNT solution while evaluating its ability to differentiate between trajectories. Additionally, the simulated results were compared with an on-water real-world slalom test to validate the findings. The results of the controlled dry-land slalom test indicate that the PNT solution provided accurate measurements with an overall mean ± SD Hrms of 0.20 ± 0.02 m. The integrity measures, HDOD and PDOP, were found to be ideal to excellent, with values of 0.68 ± 0.03 and 1.36 ± 0.07, respectively. The PNT solution utilised an average of 20 ± 1 satellites from the constellation, resulting in an accuracy of <1.5% when measuring the known trajectory of 50 simulated slalom runs. The data from the real-world on-water slalom test supported these findings, providing similar or improved results. Based on these findings, a PNT solution using DGNSS-SBAS can be considered an effective means of tracking athlete trajectory in the sport of canoe slalom. Future research should be conducted to quantify its efficacy more precisely.
Multi-Platform Point Cloud Registration Method Based on the Coarse-To-Fine Strategy for an Underground Mine
Authors: Sun Wenxiao , Qu Xinlu , Wang Jian , Jin Fengxiang , Li Zhiyuan
Published: November 2024

Spatially referenced and geometrically accurate laser scanning is essential for the safety monitoring of an underground mine. However, the spatial inconsistency of point clouds collected by heterogeneous platforms presents challenges in achieving seamless fusion. In our study, the terrestrial and handheld laser scanning (TLS and HLS) point cloud registration method based on the coarse-to-fine strategy is proposed. Firstly, the point features (e.g., target spheres) are extracted from TLS and HLS point clouds to provide the coarse transform parameters. Then, the fine registration algorithm based on identical area extraction and improved 3D normal distribution transform (3D-NDT) is adopted, which achieves the datum unification of the TLS and HLS point cloud. Finally, the roughness is calculated to downsample the fusion point cloud. The proposed method has been successfully tested on two cases (simulated and real coal mine point cloud). Experimental results showed that the registration accuracy of the TLS and HLS point cloud is 4.3 cm for the simulated mine, which demonstrates the method can capture accurate and complete spatial information about underground mines.
Usefulness of the Magnetodynamic Mallet in Tooth Extraction: A Case Series
Authors: Baldi Domenico , Baldi Francesca , Giordano Federica , De Giorgis Luisa , Bagnasco Francesco , Lugas Andrea Tancredi , Menini Maria , Colombo Jacopo
Published: November 2024

Background: Tooth extraction techniques have been refined over the years in order to be less traumatic and to better preserve alveolar bone. A recently introduced extraction method involves the use of the Magnetic Mallet®, which allows clinicians to be more precise and perform extractions faster. Moreover, the instrument enables the procedure to be less traumatic for patients. The aim of the present study was to clinically evaluate whether extractions performed using the Magnetic Mallet® can lead to less buccolingual bone resorption. Methods: Between February 2023 and June 2023, nine patients with an average age of 62 years underwent 29 extractions using the Magnetic Mallet®. Sectorial CBCTs were performed in order to measure buccolingual bone thickness at time 0 (T0, before extraction) and 3 months after extraction (T3M). All the extractions were performed by two different expert operators exclusively using the Magnetic Mallet®. For statistical analysis, a two-sample t-test was performed to determine the difference between the measurements taken at T0 and those taken at T3M in the 29 dental elements and the difference in bone loss between the surgeries conducted by the two clinicians. Results: A total of 22 teeth were extracted in the upper jaw and 7 in the lower jaw. The average degree of mobility was 1. The average degree of force impressed by the instrument to extract the teeth was 2, while the average frequency of blows administered was 7. The average time taken for the extractions was 3½ min. After 3 months, the mean buccolingual bone resorption was 1.54 mm (SD: ±). The difference in buccolingual bone thickness between T0 and T3 was significant at an alpha significance level of 0.01. No difference in bone resorption was found between the surgeries conducted by the two clinicians. Conclusions: The use of the Magnetic Mallet® results in bone loss in the buccolingual direction comparable with existing data in the literature on healing the post-extraction socket. This tool seems to be predictable in producing the same results between different operators.
Location-Based Relay Selection in Full-Duplex Random Relay Networks
Authors: Bang Jonghyun , Kim Taehyoung
Published: November 2024

Full-duplex relay (FDR) has attracted considerable interest in enhancing the performance of relay networks by utilizing resources more efficiently. In this paper, we propose a framework for full-duplex random relay networks (FDRRNs), where relay nodes equipped with full-duplex (FD) capability are randomly distributed within a finite two-dimensional region. We first derive the outage probability of an FDRRN and then identify the potential relay location that minimizes the outage probability. Furthermore, we introduce a low-complexity relay selection algorithm that selects the relay node nearest to the potential relay location. Finally, simulation results show that the proposed relay selection algorithm achieves performance comparable to that of the max-min relay selection algorithm.
Limitations and Performance Analysis of Spherical Sector Harmonics for Sound Field Processing
Authors: Bi Hanwen , Xu Shaoheng , Ma Fei , Abhayapala Thushara D. , Samarasinghe Prasanga N.
Published: November 2024

Developing spherical sector harmonics (SSHs) benefits sound field decomposition and analysis over spherical sector regions. Although SSHs demonstrate potential in the field of spatial audio, a comprehensive investigation into their properties and performance is absent. This paper seeks to close this gap by revealing three key limitations of SSHs and exploring their performance in two aspects: sector sound field radial extrapolation and sector sound field decomposition and reconstruction. First, SSHs are not solutions to the Helmholtz equation, which is their main limitation. Then, due to the violation of the Helmholtz equation, SSHs lack the ability to conduct sound field radial extrapolation, especially for interior cases. Third, when using SSHs to decompose and reconstruct a sound field, the shifted associated Legendre polynomials and scaled exponential function in SSHs result in severe distortion around the edge of the sector region. In light of these three limitations, the future implementation of SSHs should focus on processing and analyzing the measurement sector region without any extrapolation process, and the measurement region should be larger than the target sector region.
Green Manufacturing for a Green Environment from Manufacturing Sector in Guangdong Province: Mediating Role of Sustainable Operations and Operational Transparency
Authors: Saqib Zulkaif Ahmed , Xu Gang , Luo Qin
Published: November 2024

This work investigates the manufacturing operations of focal firms to manage the enhancement of environmental sustainability (EnS). To achieve this, indirect and direct effects of operational transparency (OPT) and sustainable operations (SUP) between environmental business practices (EBPr) and EnS are proposed. By leveraging the resource-based view theory, this study seeks to clarify how integrating transparency and sustainable operations can enhance a firm’s ability to manage environmental challenges effectively. Aligning environmental business practices with sustainable operations and transparency concepts appears to be an appropriate choice for environmental sustainability. A well-designed questionnaire was formed and used to collect the observations from 1214 focal firms. FsQCA and SEM approaches are employed to analyze one of the research questions of operations management: How do OPT and SUP mediate the effects of EBPr on the environmental sustainability of a firm? The final results clarify that the indirect effects of OPT and SUP significantly completely exist and are positive. The findings describe that firms with operational transparency and sustainability perform well in resolving operational and sustainable issues.
Exogenous Versus Endogenous Nandrolone in Doping Investigations: A Systematic Literature Review
Authors: Scendoni Roberto , Ricchezze Giulia , Mietti Gianmario , Cerioni Alice , Froldi Rino , Cingolani Mariano , Buratti Erika , Cippitelli Marta
Published: November 2024

Nandrolone, or 19-nortestosterone, is an anabolic steroid derived from testosterone, known for its androgenic and anabolic effects. Often used illicitly by athletes to boost performance, its use is banned by the World Anti-Doping Agency (WADA) in and out of competition. Nandrolone’s main metabolites, 19-norandrosterone (19-NA) and 19-noretiocholanolone (19-NE), are typically detected in urine. This systematic review, registered with PROSPERO and following PRISMA guidelines, examines nandrolone’s metabolism, factors affecting its natural production, and the analytical methods used in doping tests. Searches on PubMed, Scopus, and Web of Science yielded 517 studies, of which 57 were selected for analysis after excluding duplicates and unrelated articles. Descriptive statistics were applied to assess data on metabolic pathways, endogenous production influences, and detection techniques. Based on this review, it clearly emerges that the only technique that can distinguish endogenous production from an exogenous intake is gas chromatography/combustion/isotope ratio mass spectrometry (GC-C-IRMS). In addition, factors influencing endogenous production are considered and explored. Overall, this review provides useful information regarding nandrolone and its main metabolites.
Use of a Semi-Explicit Probabilistic Numerical Model for Concrete Cracking: From Static to Dynamic Loadings
Authors: Costa Gustavo , Rossi Pierre , Rita Mariane , Fairbairn Eduardo , Ribeiro Fernando
Published: November 2024

In this paper, concrete cracking is investigated in dynamics through finite element modeling. A probabilistic semi-explicit model, previously developed and validated for static loading, is extended for dynamic loading. The model in statics is based on two material mechanical parameters: the tensile strength and the critical strain-energy release rate in mode I, GIC, of the Linear Elastic Fracture Mechanics (LEFM) theory. Concerning the dynamic aspects of the model, the tensile strength rate effect is modeled by an empirical dynamic-to-static strength ratio (Dynamic Increase Factor—DIF) and a similar formulation is proposed for GIC. The structural rate effect is naturally captured when mass and damping are included in the equation of motion. For static and dynamic loading, only macroscopic crack propagation is considered. Some numerical simulations in statics and dynamics are presented in the present paper. The main results related to this work can be summarized as follows: the dispersion of the numerical results related to the load–displacement curves decreases with the loading rate. The crack pattern considerably changes with loading rate (numerically and experimentally); the agreement between the experimental and numerical results (load–displacement curves and crack pattern) indicates the model is promising for engineering applications.
A Study on the Attenuation Patterns of Underground Blasting Vibration and Their Impact on Nearby Tunnels
Authors: Li Zhengrong , Cheng Zhiming , Shi Yulian , Li Yongjie , Huang Yonghui , Zhang Zhiyu
Published: November 2024

The natural caving method, as a new technique in underground mining, has been promoted and applied in several countries worldwide. The destruction of the bottom rock mass structure directly impacts the structural stability of underground engineering, resulting in damage and collapse of underground tunnels. Therefore, based on the principles of explosion theory and field monitoring data, a scaled three-dimensional numerical simulation model of underground blasting was constructed using LS-DYNA19.0 software to investigate the attenuation patterns of underground blasting vibrations and their impact on nearby tunnels. The results show that the relative error range between the simulated blasting vibration velocities based on the FEM-SPH (Finite Element Method–Smoothed Particle Hydrodynamics) algorithm and the measured values is between 7.75% and 9.85%, validating the feasibility of this method. Significant fluctuations in blasting vibration velocities occur when the blast center increases to within a range of 10–20 m. As the blast center distance exceeds 25 m, the vibration velocities are increasingly influenced by the surrounding stress. Additionally, greater stress results in higher blasting vibration velocities and stress wave intensities. Fitting the blasting vibration velocities of various measurement points using the Sadovsky formula yields fitting correlation coefficients ranging between 0.92 and 0.97, enabling the prediction of on-site blasting vibration velocities based on research findings. Changes in propagation paths lead to localized fluctuations in the numerical values of stress waves. These research findings are crucial for a deeper understanding of underground blasting vibration patterns and for enhancing blasting safety.
Recent Advances for the Development of Sustainable Transport and Their Importance in Case of Global Crises: A Literature Review
Authors: Sobczuk Sebastian , Borucka Anna
Published: November 2024

The 21st century is a time of rapid development, marked by technological advances, globalization, and international cooperation. It is also a period that has witnessed numerous global crises. In light of recent events, such as the migration crisis, the COVID-19 pandemic, and the escalation of the conflict between Ukraine and Russia, it is crucial to consider how to ensure economic stability and enhance the security of the transportation sector in the face of emerging threats. The goal of this publication is to identify the latest solutions in sustainable transportation development and to highlight their relevance in the context of potential global crises. To achieve this, a systematic review of the current research on transportation industry innovations was conducted using 4 different databases, yielding 492 results. From these, 223 publications were selected for analysis based on established criteria. The selected transport solutions were grouped into specific categories, and then their relevance in the context of global crises was discussed. The findings highlighted key solutions essential for economic stability and transport sector safety in potential crisis situations, while also pointing to further research directions. Additionally, they offer actionable concepts for transport organizers to promote a more resilient and sustainable flow of passengers and goods in anticipation of future crises.