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20 pages, 17520 KiB

Open AccessArticle

Border Wars and Climate Change: The Impact on the Evolution of the External Defense System of the Hexi Corridor in the Past 2000 Years

by Xinmin Wang and Bo Tan

Atmosphere 2025, 16(3), 335; https://doi.org/10.3390/atmos16030335 (registering DOI) - 16 Mar 2025

Abstract

This study establishes a dataset of ancient military defense system sites in the Hexi Corridor area from the Han Dynasty to the Qing Dynasty to analyze the temporal changes and spatial distribution characteristics of the military defense system in different periods. In addition, [...] Read more.

This study establishes a dataset of ancient military defense system sites in the Hexi Corridor area from the Han Dynasty to the Qing Dynasty to analyze the temporal changes and spatial distribution characteristics of the military defense system in different periods. In addition, it compares the climate characteristics of the Hexi Corridor area though the past 2000 years. It also discusses the possible relationship between the construction of the Hexi military defense system and climate change. We found that the Han and Ming Dynasties were the main periods for constructing the regional military defense system. Furthermore, the Wei, Tsin, and Southern and Northern Dynasties expanded the scale based on the previous period. As a result, the spatial distribution was highly concentrated. During this time, multiple cold–dry and warm–humid periods occurred in the region. Moreover, significant climate change coincided with the heyday of building military facilities and the period of frequent warfare. Environmental factors have an impact on the spatial distribution of military sites. Therefore, the northern border war was the direct cause of the construction of the military defense system. However, the transformation of the environment caused by climate change was the fundamental driving force for this process, evolving across different eras. Full article

(This article belongs to the Special Issue Climate Change Over the Tibetan Plateau and Surroundings on Decadal to Sub-Orbital Timescales and Its Driving Mechanisms)

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34 pages, 1436 KiB

Open AccessReview

Flaxseed in Diet: A Comprehensive Look at Pros and Cons

by Sara Duarte, Muhammad Ajmal Shah and Ana Sanches Silva

Molecules 2025, 30(6), 1335; https://doi.org/10.3390/molecules30061335 (registering DOI) - 16 Mar 2025

Abstract

Flaxseeds, which have been consumed for thousands of years, have recently gained increasing popularity due to their rich composition, including omega-3 fatty acids, lignans, proteins, and fibers. These components are strongly associated with various health benefits, such as improving cardiovascular health, preventing certain [...] Read more.

Flaxseeds, which have been consumed for thousands of years, have recently gained increasing popularity due to their rich composition, including omega-3 fatty acids, lignans, proteins, and fibers. These components are strongly associated with various health benefits, such as improving cardiovascular health, preventing certain types of cancer, controlling diabetes, promoting gastro-intestinal well-being, and aiding in weight management. This monograph explores the role of flaxseeds in nutrition, as well as their potential risks. Despite their numerous health benefits, flaxseeds also represent concerns due to excessive consumption and possible contamination, particularly from cyanogenic glycosides. Therefore, the levels of these compounds must be controlled, and this monograph also analyzes the available methods to detect and reduce these contaminants, ensuring the safety of flaxseed and flaxseed products consumers. Flaxseed is considered a valuable addition when incorporated into the diet, but it is necessary to continue research and promote technological improvements to maximize their benefits and minimize their risks. Full article

(This article belongs to the Special Issue The Role of Dietary Bioactive Compounds in Human Health)

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15 pages, 5992 KiB

Open AccessArticle

Research on the Parametric Design and Application of Ceramic Modeling Based on Python

by Zhenjie Wang, Longyao Xu, Jing Dai, Chengqian Zeng, Yu Zhong, Liyan Liu and Shuanghua Wang

Appl. Sci. 2025, 15(6), 3242; https://doi.org/10.3390/app15063242 (registering DOI) - 16 Mar 2025

Abstract

In response to the growing diverse needs of the ceramic industry, this paper presents a creative approach employing the ErgoLAB human–machine environment synchronization platform to identify key parameters for ceramic shape parametric design. By collecting and analyzing multimodal data, including eye movements, electroencephalographic [...] Read more.

In response to the growing diverse needs of the ceramic industry, this paper presents a creative approach employing the ErgoLAB human–machine environment synchronization platform to identify key parameters for ceramic shape parametric design. By collecting and analyzing multimodal data, including eye movements, electroencephalographic signals, and skin conductance, the study systematically determines the core factors influencing the user experience. Based on this, a Python (IronPython 2.7.9 (2.7.9.0) on NET 4.0.30319.42000 (64-bit))-based parametric design process is developed, covering parameter selection, shape generation, and model visualization. A model library of classic ceramic shapes is rapidly constructed, and ergonomic experiments further investigate the human–computer interaction mechanisms involved. The designs are optimized using fuzzy comprehensive evaluation for aesthetic appeal. Combined with 3D printing technology, a complete closed loop from design to manufacturing is achieved, verifying the manufacturability of the designs. This study not only deepens the understanding of ceramic shape parametric design but also offers strong support for the diverse development of the ceramic industry, providing valuable references for parametric design applications in other industrial fields. Full article

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27 pages, 1629 KiB

Open AccessReview

Botulinum Toxin Therapy: A Comprehensive Review on Clinical and Pharmacological Insights

by Nahla Ayoub

J. Clin. Med. 2025, 14(6), 2021; https://doi.org/10.3390/jcm14062021 (registering DOI) - 16 Mar 2025

Abstract

Background: Botulinum toxin (BoNT), produced by Clostridium botulinum, has transitioned from being a lethal neurotoxin to a versatile therapeutic agent. Its ability to inhibit neurotransmitter release by targeting Soluble N-ethylmaleimide-sensitive factor Attachment Protein Receptor (SNARE) proteins underpins its applications in treating conditions such [...] Read more.

Background: Botulinum toxin (BoNT), produced by Clostridium botulinum, has transitioned from being a lethal neurotoxin to a versatile therapeutic agent. Its ability to inhibit neurotransmitter release by targeting Soluble N-ethylmaleimide-sensitive factor Attachment Protein Receptor (SNARE) proteins underpins its applications in treating conditions such as spasticity, dystonia, chronic pain, and overactive bladder. The clinical and pharmacological properties of BoNT have been extensively studied, with significant advancements in its therapeutic use, safety profile, and understanding of associated adverse effects. Objective: This comprehensive review aims to consolidate historical developments, molecular mechanisms, clinical applications, and challenges associated with BoNT, with a focus on expanding its therapeutic scope while ensuring safety and efficacy. Method: A narrative approach was used to analyze and synthesize insights from 155 references spanning experimental studies, clinical trials, and reviews. Key topics included BoNT’s historical milestones, mechanisms of action, therapeutic applications, and adverse events. Findings: BoNT demonstrates remarkable efficacy in a wide range of medical and cosmetic applications. In movement disorders such as dystonia and spasticity, it reduces muscle overactivity and improves functional outcomes. In chronic pain management, including migraines and neuropathic pain, BoNT significantly alleviates symptoms by modulating neurotransmitter activity. Cosmetic use for conditions like glabellar lines and hyperhidrosis highlights its precision and safety when administered appropriately. For conditions like strabismus and blepharospasm, BoNT effectively restores muscle control, reducing involuntary contractions. In urological applications, BoNT has proven to be an effective therapy for overactive bladder, offering significant symptom relief in refractory cases. However, concerns about long-distance effects, where the toxin may spread beyond the injection site to affect distant muscles or systems, have been reported in certain high-dose or sensitive populations. These findings emphasize the importance of dose optimization and patient-specific approaches. Adverse effects such as localized pain, hematoma, dysphagia, and systemic effects, particularly in high-risk groups, underscore the need for careful monitoring. The development of immunogenicity, leading to neutralizing antibodies, remains a challenge that impacts long-term therapeutic efficacy. Emerging research on novel serotypes, including BoNT/X, and innovations in delivery mechanisms, offer promising avenues to address current limitations. Advances in optimizing dosing regimens and refining injection techniques have also contributed to minimizing complications and improving outcomes across diverse patient populations. Conclusions: BoNT remains a cornerstone in neurology and cosmetic medicine, with its therapeutic potential still expanding. The balance between efficacy and safety, driven by innovations in formulation and application, underscores the importance of continued research. Future directions should focus on minimizing adverse effects, reducing immunogenicity, and exploring novel indications to further enhance its clinical utility. Full article

(This article belongs to the Special Issue Innovations and Challenges in Clinical Toxicology and Therapeutic Drug Monitoring)

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25 pages, 13970 KiB

Open AccessArticle

Identification of Defects in Low-Speed and Heavy-Load Mechanical Systems Using Multi-Fusion Analytic Mode Decomposition Method

by Yanlei Liu, Kun Zhang, Miaorui Yang, Xu Zhang and Yonggang Xu

Sensors 2025, 25(6), 1848; https://doi.org/10.3390/s25061848 (registering DOI) - 16 Mar 2025

Abstract

In view of the higher requirements of modern machinery for multi-sensor information acquisition and fusion technology, this paper proposes a novel multi-fusion analytic mode decomposition (MFAMD) method to separate and demodulate fault features in signals. In low-speed and heavy-load equipment, the signals collected [...] Read more.

In view of the higher requirements of modern machinery for multi-sensor information acquisition and fusion technology, this paper proposes a novel multi-fusion analytic mode decomposition (MFAMD) method to separate and demodulate fault features in signals. In low-speed and heavy-load equipment, the signals collected by multiple sensors contain unknown and unequal fault features and interference. Quaternion-based frequency domain fusion technology and analytically based modal extraction technology can offer novel approaches to processing large data sets in parallel while handling lengthy signals and high sampling rates. The trend spectrum segmentation method based on quaternions optimizes the hysteresis of the binary frequency. The experimental signal verifies that the proposed method is suitable for low-speed and heavy-load bearing faults. Full article

(This article belongs to the Special Issue Intelligent Maintenance and Fault Diagnosis of Mobility Equipment)

26 pages, 6060 KiB

Open AccessArticle

Efficient Removal of Cu(II) from Wastewater Using Chitosan Derived from Shrimp Shells: A Kinetic, Thermodynamic, Optimization, and Modelling Study

by Kheira Benazouz, Nasma Bouchelkia, Hamza Moussa, Razika Boutheldja, Meriem Zamouche, Abdeltif Amrane, Chelliah Parvathiraja, Hamad A. Al-Lohedan, Jean-Claude Bollinger and Lotfi Mouni

Water 2025, 17(6), 851; https://doi.org/10.3390/w17060851 (registering DOI) - 16 Mar 2025

Abstract

Chitosan was hydro-thermally extracted from grey shrimp carapaces and characterized using various techniques (degree of deacetylation (DD), viscosity, thermogravimetric analysis (TGA), scanning electron microscopy (SEM), and surface area analysis (BET)). It was then used for Cu(II) removal in a batch system, achieving a [...] Read more.

Chitosan was hydro-thermally extracted from grey shrimp carapaces and characterized using various techniques (degree of deacetylation (DD), viscosity, thermogravimetric analysis (TGA), scanning electron microscopy (SEM), and surface area analysis (BET)). It was then used for Cu(II) removal in a batch system, achieving a maximum capacity of 89 mg/g under standard conditions. Both pseudo-first-order and pseudo-second-order nonlinear kinetic models described the adsorption of Cu(II) ions on chitosan well, with a better fit of the pseudo-first-order model at low concentrations, while the equilibrium data suggested that the Langmuir model was suitable for describing the adsorption system, with a maximum adsorption capacity of 123 mg/g. A response surface methodology and central composite design were used to optimise and evaluate the effects of six independent parameters: initial Cu(II) concentration, pH, chitosan concentration (S/L), temperature (T), contact time (t), and NaCl concentration on the adsorption efficiency of Cu(II) by the synthesised chitosan. The proposed model was confirmed to accurately describe the phenomenon within the experimental range, achieving an R² value of 1. ANOVA indicated that the initial concentrations of Cu(II) and chitosan concentration (S/L) were the most significant factors, while the other variables had no significant effect on the process. The adsorption capacity of Cu(II) onto the prepared chitosan was also optimised and modelled using artificial neural networks (ANNs). The maximum amount, qmax = 468 mg·g⁻¹, shows that chitosan is a highly effective adsorbent, chelating and complexing for copper ions. Full article

(This article belongs to the Section Wastewater Treatment and Reuse)

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25 pages, 1841 KiB

Open AccessArticle

Cytokine-Based Insights into Bloodstream Infections and Bacterial Gram Typing in ICU COVID-19 Patients

by Rúben Araújo, Luís Ramalhete, Cristiana P. Von Rekowski, Tiago A. H. Fonseca, Cecília R. C. Calado and Luís Bento

Metabolites 2025, 15(3), 204; https://doi.org/10.3390/metabo15030204 (registering DOI) - 16 Mar 2025

Abstract

Background: Timely and accurate identification of bloodstream infections (BSIs) in intensive care unit (ICU) patients remains a key challenge, particularly in COVID-19 settings, where immune dysregulation can obscure early clinical signs. Methods: Cytokine profiling was evaluated to discriminate between ICU patients with and [...] Read more.

Background: Timely and accurate identification of bloodstream infections (BSIs) in intensive care unit (ICU) patients remains a key challenge, particularly in COVID-19 settings, where immune dysregulation can obscure early clinical signs. Methods: Cytokine profiling was evaluated to discriminate between ICU patients with and without BSIs, and, among those with confirmed BSIs, to further stratify bacterial infections by Gram type. Serum samples from 45 ICU COVID-19 patients were analyzed using a 21-cytokine panel, with feature selection applied to identify candidate markers. Results: A machine learning workflow identified key features, achieving robust performance metrics with AUC values up to 0.97 for BSI classification and 0.98 for Gram typing. Conclusions: In contrast to traditional approaches that focus on individual cytokines or simple ratios, the present analysis employed programmatically generated ratios between pro-inflammatory and anti-inflammatory cytokines, refined through feature selection. Although further validation in larger and more diverse cohorts is warranted, these findings underscore the potential of advanced cytokine-based diagnostics to enhance precision medicine in infection management. Full article

(This article belongs to the Special Issue Towards Clinical Interpretation of Metabolomic Data)

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17 pages, 3494 KiB

Open AccessArticle

Membrane-Mediated Conversion of Near-Infrared Amplitude Modulation into the Self-Mixing Signal of a Terahertz Quantum Cascade Laser

by Paolo Vezio, Andrea Ottomaniello, Leonardo Vicarelli, Mohammed Salih, Lianhe Li, Edmund Linfield, Paul Dean, Virgilio Mattoli, Alessandro Pitanti and Alessandro Tredicucci

Photonics 2025, 12(3), 273; https://doi.org/10.3390/photonics12030273 (registering DOI) - 16 Mar 2025

Abstract

A platform for converting near-infrared (NIR) laser power modulation into the self-mixing (SM) signal of a quantum cascade laser (QCL) operating at terahertz (THz) frequencies is introduced. This approach is based on laser feedback interferometry (LFI) with a THz QCL using a metal-coated [...] Read more.

A platform for converting near-infrared (NIR) laser power modulation into the self-mixing (SM) signal of a quantum cascade laser (QCL) operating at terahertz (THz) frequencies is introduced. This approach is based on laser feedback interferometry (LFI) with a THz QCL using a metal-coated silicon nitride trampoline membrane resonator as both the external QCL laser cavity and the mechanical coupling element of the two-laser hybrid system. We show that the membrane response can be controlled with high precision and stability both in its dynamic (i.e., piezo-electrically actuated) and static state via photothermally induced NIR laser excitation. The responsivity to nanometric external cavity variations and robustness to optical feedback of the QCL LFI apparatus allows a highly sensitive and reliable transfer of the NIR power modulation into the QCL SM voltage, with a bandwidth limited by the thermal response time of the membrane resonator. Interestingly, a dual information conversion is possible thanks to the accurate thermal tuning of the membrane resonance frequency shift and displacement. Overall, the proposed apparatus can be exploited for the precise opto-mechanical control of QCL operation with advanced applications in LFI imaging and spectroscopy and in coherent optical communication. Full article

(This article belongs to the Special Issue The Three-Decade Journey of Quantum Cascade Lasers)

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23 pages, 12338 KiB

Open AccessArticle

Learning in Two-Scales Through LSTM-GPT2 Fusion Network: A Hybrid Approach for Time Series Anomaly Detection

by Taoyu Wang, Dan Wu, Jun Wang, Jinwei Zhao, Haoming Wang, Dongnan Xie, Hongtao Zhang and Xinhong Hei

Sensors 2025, 25(6), 1849; https://doi.org/10.3390/s25061849 (registering DOI) - 16 Mar 2025

Abstract

Anomaly detection (AD) in multivariate time series data (MTS) collected by industrial sensors is a crucial undertaking for the damage estimation and damage monitoring of machinery like rocket engines, wind turbine blades, and aircraft turbines. Due to the complex structure of industrial systems [...] Read more.

Anomaly detection (AD) in multivariate time series data (MTS) collected by industrial sensors is a crucial undertaking for the damage estimation and damage monitoring of machinery like rocket engines, wind turbine blades, and aircraft turbines. Due to the complex structure of industrial systems and the varying working environments, the collected MTS often contain a significant amount of noise. Current AD studies mostly depend on extracting features from data to obtain the information associated with various working states, and they attempt to detect the abnormal states in the space of the original data. Nevertheless, the latent space, which includes the most essential knowledge learned by the network, is often overlooked. In this paper, a multi-scale feature extraction and data reconstruction deep learning neural network, designated as LGFN, is proposed. It is specifically designed to detect anomalies in MTS in both the original input space and the latent space. In the experimental section, a comparison is made between the proposed AD process and five well-acknowledged AD methods on five public MTS datasets. The outcomes demonstrate that the proposed method attains state-of-the-art or comparable performance. The memory usage experiment illustrates the space efficiency of LGFN in comparison to another AD method based on GPT-2. The ablation studies emphasise the indispensable role of each module in the proposed AD process. Full article

(This article belongs to the Special Issue Artificial-Intelligence-Driven Intelligent Fault Prediction and Health Management Techniques in Manufacturing Systems: 2nd Edition)

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47 pages, 3071 KiB

Open AccessArticle

The Nexus of Industrial–Urban Sustainability, the Circular Economy, and Climate–Ecosystem Resilience: A Synthesis

by Yee Keong Choy, Ayumi Onuma and Khai Ern Lee

Sustainability 2025, 17(6), 2620; https://doi.org/10.3390/su17062620 (registering DOI) - 16 Mar 2025

Abstract

Circular economic strategies have been widely deployed across the world to decouple industrial–urban growth from resource use and carbon emissions, aiming to mitigate environmental degradation. Despite these efforts, the global circularity gap has widened, and widespread crisis-ridden environmental repercussions continue to drive our [...] Read more.

Circular economic strategies have been widely deployed across the world to decouple industrial–urban growth from resource use and carbon emissions, aiming to mitigate environmental degradation. Despite these efforts, the global circularity gap has widened, and widespread crisis-ridden environmental repercussions continue to drive our planetary system closer to ecosystem collapse and climate breakdown. This article critically analyzes this circularity paradox based on an integrated conceptual framework grounded in environmental economic principles, system theory, the laws of thermodynamics, and empirical case studies. The analysis elucidates the macro-level dynamics and intricate feedback mechanisms between industrial–urban systems and environmental systems, revealing the underlying ecological conflicts and environmental forces that drive deleterious changes in ecosystems and the climate system. These changes causally impede sustainable industrial–urban development. The findings underscore that addressing environmental threats to industrial–urban sustainability requires not only enhancing the efficient use and sustainable management of natural resources but, more importantly, prioritizing the preservation and restoration of ecosystem resilience and climate system stability. Full article

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18 pages, 998 KiB

Open AccessArticle

Assessing the Environmental Impact of Busan New Port Construction in Korea: A Comprehensive Analysis of Water Quality Changes and Suspended Solids in Jinhae Bay

by Jaebum Kim, Arnab Ghosh, Tanushree Paul, Jurng-Jae Yee and Sunghyuk Park

Water 2025, 17(6), 852; https://doi.org/10.3390/w17060852 (registering DOI) - 16 Mar 2025

Abstract

This study investigates the impact of port construction on suspended solid concentrations and key water quality parameters in Jinhae Bay, using seventeen years of water quality data up to 2020. The study highlights the significant impact of suspended solids on marine water quality, [...] Read more.

This study investigates the impact of port construction on suspended solid concentrations and key water quality parameters in Jinhae Bay, using seventeen years of water quality data up to 2020. The study highlights the significant impact of suspended solids on marine water quality, particularly in areas affected by dredging operations at Busan New Port. Suspended solids concentrations peaked at 92 mg/L, exceeding 10 mg/L in both surface and bottom waters, with the highest levels near the port. These solids were identified as key predictors of coastal eutrophication in locations such as Jinhae Bay 01, 17, 19, where positive correlations with Chl-a suggest their role in promoting eutrophication. The highest average Chl-a levels were recorded at Jinhae Bay 01 (9.82 µg/L), while the lowest were at Jinhae Bay 14 (3.2 µg/L). The WQI, ranged from 1 to 3, with Jinhae Bay 19 showing the highest value and Jinhae Bay 14 the lowest due to low dissolved oxygen levels. Using ARIMA modeling, the study effectively analyzed the time-series dynamics of suspended solids, demonstrating their relationships with Chl-a and WQI components. These findings underscore the importance of monitoring and managing suspended solids to mitigate the risk of eutrophication and protect marine ecosystems in the context of port development. Full article

17 pages, 2009 KiB

Open AccessArticle

Transcriptomics Uncovers Pathways Mediating Low-Nitrogen Stress Tolerance in Two Foxtail Millet Varieties

by Jirong Wu, Lu Chen, Zhenrong Yang, Juan Lu, Jinwen Yang, Ning Li and Huawei Shi

Agriculture 2025, 15(6), 628; https://doi.org/10.3390/agriculture15060628 (registering DOI) - 16 Mar 2025

Abstract

Nitrogen crucially impacts foxtail millet (Setaria italica) growth and development. Uncovering low nitrogen (LN) tolerance genes and mechanisms is vital for breeding high nitrogen use efficiency varieties. In this study, the LN tolerance of 50 foxtail millet genotypes was assessed through [...] Read more.

Nitrogen crucially impacts foxtail millet (Setaria italica) growth and development. Uncovering low nitrogen (LN) tolerance genes and mechanisms is vital for breeding high nitrogen use efficiency varieties. In this study, the LN tolerance of 50 foxtail millet genotypes was assessed through field trials and seedling hydroponic experiments. Subsequently, transcriptome analysis was performed on one highly sensitive genotype, named Maotigu, and on one highly tolerant genotype, named Dahuanggu, under LN (0.1 mmol/L) and control (5 mmol/L) conditions in seedling hydroponic experiments. Compared to the control treatment, 823 differentially expressed genes (DEGs) (350 upregulated, 473 downregulated) were identified in the roots of Dahuanggu, while 2427 DEGs (1703 upregulated, 724 downregulated) were detected in Maotigu under LN treatment. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that a total of 3134 DEGs were associated with pathways including plant–pathogen interaction, amino sugar and nucleotide sugar metabolism, nitrogen metabolism, and others. A total of 116 DEGs were commonly identified between Dahuanggu and Maotigu, involving pathways like plant–pathogen interaction, galactose metabolism, and flavone and flavonol biosynthesis. The 28 of 116 DEGs showed opposite expression patterns between Dahuanggu and Maotigu; the expression of 18 genes was further validated using qRT-PCR. These offer valuable insights into the molecular mechanisms underlying LN stress responses in foxtail millet. Full article

(This article belongs to the Section Crop Genetics, Genomics and Breeding)

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22 pages, 4200 KiB

Open AccessArticle

Flow-Induced Shear Stress Combined with Microtopography Inhibits the Differentiation of Neuro-2a Cells

by Eleftheria Babaliari, Paraskevi Kavatzikidou, Dionysios Xydias, Sotiris Psilodimitrakopoulos, Anthi Ranella and Emmanuel Stratakis

Micromachines 2025, 16(3), 341; https://doi.org/10.3390/mi16030341 (registering DOI) - 16 Mar 2025

Abstract

Considering that neurological injuries cannot typically self-recover, there is a need to develop new methods to study neuronal outgrowth in a controllable manner in vitro. In this study, a precise flow-controlled microfluidic system featuring custom-designed chambers that integrate laser-microstructured polyethylene terephthalate (PET) substrates [...] Read more.

Considering that neurological injuries cannot typically self-recover, there is a need to develop new methods to study neuronal outgrowth in a controllable manner in vitro. In this study, a precise flow-controlled microfluidic system featuring custom-designed chambers that integrate laser-microstructured polyethylene terephthalate (PET) substrates comprising microgrooves (MGs) was developed to investigate the combined effect of shear stress and topography on Neuro-2a (N2a) cells’ behavior. The MGs were positioned parallel to the flow direction and the response of N2a cells was evaluated in terms of growth and differentiation. Our results demonstrate that flow-induced shear stress could inhibit the differentiation of N2a cells. This microfluidic system could potentially be used as a new model system to study the impact of shear stress on cell differentiation. Full article

(This article belongs to the Special Issue Microfluidic Chips for Biomedical Applications)

56 pages, 5931 KiB

Open AccessArticle

Multi-Level Determinants of Sustainable Blockchain Technology Adoption in SCM: Individual, Organisational, and Societal Perspectives

by Xiaole Han and Leong-Mow Gooi

Sustainability 2025, 17(6), 2621; https://doi.org/10.3390/su17062621 (registering DOI) - 16 Mar 2025

Abstract

This study examines how individual, organisational, and societal factors influence blockchain technology (BCT) adoption in supply chain management (SCM). Using Partial Least Squares Artificial Neural Networks (PLS-ANNs) and Necessary Condition Analysis (NCA), it identifies key determinants of sustainable BCT adoption among small- and [...] Read more.

This study examines how individual, organisational, and societal factors influence blockchain technology (BCT) adoption in supply chain management (SCM). Using Partial Least Squares Artificial Neural Networks (PLS-ANNs) and Necessary Condition Analysis (NCA), it identifies key determinants of sustainable BCT adoption among small- and medium-sized enterprises (SMEs). The results show that compatibility, top management support, and relative advantage are critical for adoption. This study focuses on SMEs, and further research is needed to assess whether these findings apply to larger organisations. Insights from this research provide a foundation for improving BCT adoption in high-impact sectors and inform strategic adoption practices. By analysing multi-level factors, the study enhances understanding and guides policy development for equitable and sustainable supply chain innovations. Additionally, the findings refine existing BCT adoption models by introducing and validating new determinants, contributing to both theory and practice in SCM. This comprehensive approach bridges research gaps and offers actionable insights for improving BCT adoption, supporting broader economic and social benefits. Full article

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16 pages, 775 KiB

Open AccessArticle

Predictors for Poor Outcomes at Six Months on Pain, Disability, Psychological and Health Status in Greek Patients with Chronic Low Back Pain After Receiving Physiotherapy: A Prospective Cohort Study

by Matthaios Petrelis, Georgios Krekoukias, Ioannis Michopoulos, Vasileios Nikolaou and Konstantinos Soultanis

Clin. Pract. 2025, 15(3), 63; https://doi.org/10.3390/clinpract15030063 (registering DOI) - 16 Mar 2025

Abstract

Background: Although previous studies have suggested a variety of sociodemographic and psychological factors as predictors of poor outcomes in patients with chronic low back pain (CLBP), longitudinal studies remain rare. Objectives: To examine the prognostic indicators for poor outcome at 6 months [...] Read more.

Background: Although previous studies have suggested a variety of sociodemographic and psychological factors as predictors of poor outcomes in patients with chronic low back pain (CLBP), longitudinal studies remain rare. Objectives: To examine the prognostic indicators for poor outcome at 6 months on pain, disability, quality of life, anxiety, depression and somatic symptom disorders (SSDs) in Greek backache patients and to evaluate the medium-term effects of a conservative physiotherapeutic approach (massage, ultrasound, transcutaneous electrical nerve stimulation, low-level laser and exercise program). Methods: A prospective cohort study of 145 volunteers receiving treatment for CLBP in a physiotherapy unit was conducted using random systematic sampling. The intervention was assessed by comparing pre-treatment, post-treatment and six-month measurements with Friedman’s test and the Bonferroni correction, using the pain numerical rating scale (PNRS), Roland–Morris disability questionnaire (RMDQ), EuroQol-5-dimension-5-level (EQ-5D-5L), Hospital Anxiety and Depression Scale (HADS) and Somatic Symptom Scale-8 (SSS-8). Multiple linear regression analysis was carried out to determine the impact of demographics and pre-treatment scores with scores at six months. Results: The mean age was 60.6 years (±14.7). Post-treatment, statistically significant improvements were observed across all outcome measures, including PNRS, RMDQ, EQ-5D-5L and SSS-8 (all p ≤ 0.001), with anxiety showing a notable reduction (p = 0.002). After examining the multiple regression analysis, pre-treatment SSS-8 emerged as a predictor of elevated levels of pain, disability, anxiety and depression at 6 months. Conclusions: The findings yielded not only somatic symptom burden, greater age and pain intensity as prognostic indicators for poor outcomes at six months, but also reported favorable medium-term effects for a conventional physiotherapy regimen in CLBP management, as well. Full article

(This article belongs to the Special Issue Musculoskeletal Pain and Rehabilitation)

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19 pages, 6743 KiB

Open AccessArticle

Automatic Detection of Equatorial Plasma Bubbles in Airglow Images Using Two-Dimensional Principal Component Analysis and Explainable Artificial Intelligence

by Moheb Yacoub, Moataz Abdelwahab, Kazuo Shiokawa and Ayman Mahrous

Mach. Learn. Knowl. Extr. 2025, 7(1), 26; https://doi.org/10.3390/make7010026 (registering DOI) - 16 Mar 2025

Abstract

Equatorial plasma bubbles (EPBs) are regions of depleted electron density that form in the Earth’s ionosphere due to Rayleigh–Taylor instability. These bubbles can cause signal scintillation, leading to signal loss and errors in position calculations. EPBs can be detected in images captured by [...] Read more.

Equatorial plasma bubbles (EPBs) are regions of depleted electron density that form in the Earth’s ionosphere due to Rayleigh–Taylor instability. These bubbles can cause signal scintillation, leading to signal loss and errors in position calculations. EPBs can be detected in images captured by All-Sky Imager (ASI) systems. This study proposes a low-cost automatic detection method for EPBs in ASI data that can be used for both real-time detection and classification purposes. This method utilizes Two-Dimensional Principal Component Analysis (2DPCA) with Recursive Feature Elimination (RFE), in conjunction with a Random Forest machine learning model, to create an Explainable Artificial Intelligence (XAI) model capable of extracting image features to automatically detect EPBs with the lowest possible dimensionality. This led to having a small-sized and extremely fast-trained model that could be used to identify EPBs within the captured ASI images. A set of 2458 images, classified into two categories—Event and Empty—were used to build the database. This database was randomly split into two subsets: a training dataset (80%) and a testing dataset (20%). The produced XAI model demonstrated slightly higher detection accuracy compared to the standard 2DPCA model while being significantly smaller in size. Furthermore, the proposed model’s performance has been evaluated and compared with other deep learning baseline models (ResNet18, Inception-V3, VGG16, and VGG19) in the same environment. Full article

(This article belongs to the Section Learning)

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23 pages, 736 KiB

Open AccessArticle

Innovative Power Generation System for Large Ships Based on Fuel Cells: A Technical–Economic Comparison with a Traditional System

by Alessandro Ruvio, Stefano Elia, Manlio Pasquali, Roberto Pibiri, Stephen McPhail and Matteo Fontanella

Energies 2025, 18(6), 1456; https://doi.org/10.3390/en18061456 (registering DOI) - 16 Mar 2025

Abstract

At present, shipping companies are aiming to meet better energy and environmental requirements when designing large cruise ships, thus decreasing emissions, increasing efficiency and reliability and greatly reducing maintenance time and costs. This paper provides a technical–economic comparison for a real case study, [...] Read more.

At present, shipping companies are aiming to meet better energy and environmental requirements when designing large cruise ships, thus decreasing emissions, increasing efficiency and reliability and greatly reducing maintenance time and costs. This paper provides a technical–economic comparison for a real case study, including a complete feasibility study regarding the sizing of a generation system to supply base hotel loads, between two power plant architectures focused on fuel cells and diesel generators for a cruise ship. The paper describes, in detail, an innovative solid oxide fuel cell(SOFC) generation system, which offers high efficiency and low emissions, assessed for its technical, economic and environmental performance. This study examines generators for hotels, requiring continuous service at constant load and a 1 MW power supply. The work relates to ships with a tonnage of more than 100,000 tons. Subsequently, considering that, in the case study, the diesel generators are powered by LNG (liquefied natural gas), there will also be a comparison with a case where both systems are simply powered by LNG. The main technical specifications required by shipbuilders for choosing the most suitable system for on-board generation (weight, volume, maintenance intervals and operations, as well as investment and operational expenses)are analyzed and described. The economic comparison is based on two extreme assumptions of the purchase and operating costs of the fuel cell system and returns a different result depending on the assumption adopted. The usefulness of the proposed solution based on fuel cells is demonstrated on the basis of an accurate technical, energetic and economic comparison with the conventional technologies based on diesel generators. The work is completed by evaluating the overall power-generating reliability improvement achievable with the new technology, in comparison with the traditional system. The comparison between the fuel cell system and the diesel system shows that the former has a higher weight (+40%), volume (+75%) and initial investment cost (3–6 times higher). However, the lower LNG consumption reduces the annual operating cost and the size and weight of the on-board tanks or, with the same tank capacity, increases the system’s range. The overall reliability of the fuel cell system is significantly higher than that of the traditional system. Full article

(This article belongs to the Special Issue Future of Transport: Hybrid Electrification and Hydrogen Integration in Vehicles and Infrastructure)

12 pages, 2785 KiB

Open AccessArticle

Crystal Chemistry, High-Pressure Behavior, Water Content, and Thermal Stability of Natural Spodumene

by Yuhui Jiang, Jiayi Yu, Yuanze Ouyang, Li Zhang, Xiaoguang Li, Zhuoran Zhang and Yunxuan Li

Minerals 2025, 15(3), 307; https://doi.org/10.3390/min15030307 (registering DOI) - 16 Mar 2025

Abstract

Spodumene (LiAlSi₂O₆) is a member of pyroxene-group minerals. It has the highest theoretical lithium abundance among all of the Li-bearing minerals. In the present work, in situ high-pressure Raman spectroscopic investigation of natural spodumene have been conducted up to [...] Read more.

Spodumene (LiAlSi₂O₆) is a member of pyroxene-group minerals. It has the highest theoretical lithium abundance among all of the Li-bearing minerals. In the present work, in situ high-pressure Raman spectroscopic investigation of natural spodumene have been conducted up to 19.04 GPa. Unheated spodumene and spodumene recovered after heat treatments (up to 1000 °C) have also been analyzed by X-ray diffraction and infrared spectroscopy. The results indicate that spodumene, after the displacive C2/c–P2₁/c transformation triggered at ~3.2 GPa, remains stable at pressures up to 19 GPa at ambient temperature without undergoing decomposition, amorphization, or a second phase transition. The major OH bands of the spodumene samples are observed within the wavenumber range of 2580–3220 cm⁻¹, implying a strong hydrogen bond interaction. The water content of the spodumene is estimated to be 19–97 ppm wt. H₂O based on the integrated absorption area of the OH bands. The FTIR analysis of the spodumene samples recovered after heat treatments implies that spodumene can retain a significant amount of water (up to ~100 ppm H₂O by weight) under high-temperature conditions up to 1000 °C. This suggests that spodumene in subducted slabs is unlikely to undergo dehydration at temperatures below 1000 °C, and is therefore not expected to trigger partial melting. Thus, spodumene may serve as a key carrier for Li, transporting it into the deep mantle without releasing Li into melts during subduction. Full article

(This article belongs to the Special Issue High-Pressure and High-Temperature Mineral Physics)

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17 pages, 2508 KiB

Open AccessReview

Mathematical Modeling of the Rail Track Superstructure–Subgrade System

by Dmytro Kurhan, Szabolcs Fischer and Vladyslav Khmelevskyi

Geotechnics 2025, 5(1), 20; https://doi.org/10.3390/geotechnics5010020 (registering DOI) - 16 Mar 2025

Abstract

The “rail track superstructure–subgrade” system is a sophisticated engineering structure critical in ensuring safe and efficient train operations. Its analysis and design rely on mathematical modeling to capture the interactions between system components and the effects of both static and dynamic loads. This [...] Read more.

The “rail track superstructure–subgrade” system is a sophisticated engineering structure critical in ensuring safe and efficient train operations. Its analysis and design rely on mathematical modeling to capture the interactions between system components and the effects of both static and dynamic loads. This paper offers a detailed review of contemporary modeling approaches, including discrete, continuous, and hybrid models. The research’s key contribution is a thorough comparison of five primary methodologies: (i) quasi-static analytical calculations, (ii) multibody dynamics (MBD) models, (iii and iv) static and dynamic finite element method (FEM) models, and (v) wave propagation-based models. Future research directions could focus on developing hybrid models that integrate MBD and FEM to enhance moving load predictions, leveraging machine learning for parameter calibration using experimental data, investigating the nonlinear and rheological behavior of ballast and subgrade in long-term deformation, and applying wave propagation techniques to model vibration transmission and evaluate its impact on infrastructure. Full article

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21 pages, 2624 KiB

Open AccessArticle

Experimental Study of Rock Failure and Fractal Characteristics Under True Triaxial Unloading

by Chongyan Liu, Guangming Zhao, Cheng Pan, Xiangrui Meng and Wensong Xu

Fractal Fract. 2025, 9(3), 182; https://doi.org/10.3390/fractalfract9030182 (registering DOI) - 16 Mar 2025

Abstract

In order to study the failure and fractal characteristics of unloaded rocks, with the help of the true triaxial unloading rock test system and the acoustic emission (AE) monitoring system, rock failure tests were conducted under varying intermediate principal stress and the mechanical [...] Read more.

In order to study the failure and fractal characteristics of unloaded rocks, with the help of the true triaxial unloading rock test system and the acoustic emission (AE) monitoring system, rock failure tests were conducted under varying intermediate principal stress and the mechanical response features of the rocks were analyzed. An investigation was conducted into the rocks’ AE patterns and multifractal features. The results showed that the rocks’ AE macroscopic and microscopic main failure modes differed slightly under unloading. As the intermediate principal stress σ₂ increased, the fractal dimension of the cracks in the rocks first increased and then decreased. The distribution of rock failure was initially concentrated, then dispersed, and concentrated again at the end. As the σ₂ increased, the number of failure events within a specified area in the rock samples under unloading, as represented by the ring-down count, first increased and then decreased. Meanwhile, the fractal dimension Δα first decreased and then increased. These results characterized the process whereby the failure distribution pattern of the rocks changed from being concentrated to dispersed and back to concentrated again. Full article

(This article belongs to the Special Issue Fractal Analysis and Its Applications in Rock Engineering)

23 pages, 6092 KiB

Open AccessArticle

Exploiting Paradoxical Activation of Oncogenic MAPK Signaling by Targeting Mitochondria to Sensitize NRAS Mutant-Melanoma to Vemurafenib

by Laura Francisca Leite do Prado-Souza, Letícia Silva Ferraz, Tharcísio Citrangulo Tortelli, Jr., César Augusto João Ribeiro, Danilo Trabuco do Amaral, Denise Costa Arruda, Érica Aparecida de Oliveira, Roger Chammas, Silvya Stuchi Maria-Engler and Tiago Rodrigues

Int. J. Mol. Sci. 2025, 26(6), 2675; https://doi.org/10.3390/ijms26062675 (registering DOI) - 16 Mar 2025

Abstract

Vemurafenib is a BRAF (rapidly accelerated fibrosarcoma B-type)-targeted therapy used to treat patients with advanced, unresectable melanoma. It inhibits the MAPK (mitogen-activated protein kinase)/ERK (extracellular signal-regulated kinase) pathway and tumor proliferation in BRAF^V600E-mutated melanoma cells. Resistance to vemurafenib has been reported [...] Read more.

Vemurafenib is a BRAF (rapidly accelerated fibrosarcoma B-type)-targeted therapy used to treat patients with advanced, unresectable melanoma. It inhibits the MAPK (mitogen-activated protein kinase)/ERK (extracellular signal-regulated kinase) pathway and tumor proliferation in BRAF^V600E-mutated melanoma cells. Resistance to vemurafenib has been reported in melanoma patients due to secondary NRAS (neuroblastoma RAS viral oncogene homolog) mutations, which lead to paradoxical MAPK pathway activation and tumor proliferation. However, the impact of this paradoxical activation on mitochondrial dynamics and function in NRAS-mutated melanoma is unclear. Here, we investigated the effects of vemurafenib on NRAS^Q61R-mutated melanoma cells, focusing on mitochondrial dynamics and function. As expected, vemurafenib did not exhibit cytotoxicity in SK-MEL-147 NRAS^Q61R-mutated melanoma cells, even after 72 h of incubation. However, it significantly enhanced the MAPK/ERK signaling through paradoxical activation, accompanied by decreased expression of mitochondrial fusion proteins and activation of the fission protein DRP1 (dynamin-related protein 1), leading to small, rounded mitochondrial morphology. These observations were corroborated by transcriptome data obtained from NRAS-mutated melanoma patients, showing MFN1 (mitofusin 1) and OPA1 (optic atrophy 1) downregulation and DNM1L (DRP1 gene) upregulation. Interestingly, inhibition of mitochondrial fission with mdivi-1 or modulation of oxidative phosphorylation via respiratory chain inhibition or uncoupling significantly sensitized NRAS^Q61R-mutated melanoma cells to vemurafenib. Despite vemurafenib’s low cytotoxicity in NRAS-mutated melanoma, targeting mitochondrial dynamics and/or oxidative phosphorylation may offer a promising strategy for combined therapy. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Oncology in Brazil, 3rd Edition)

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20 pages, 8566 KiB

Open AccessArticle

Simultaneous Removal of Heavy Metals and Dyes on Sodium Alginate/Polyvinyl Alcohol/κ-Carrageenan Aerogel Beads

by Taesoon Jang, Soyeong Yoon, Jin-Hyuk Choi, Narae Kim and Jeong-Ann Park

Gels 2025, 11(3), 211; https://doi.org/10.3390/gels11030211 (registering DOI) - 16 Mar 2025

Abstract

Industrial textile wastewater containing both heavy metals and dyes has been massively produced. In this study, semi-interpenetrating polymer network structures of sodium alginate (SA)/polyvinyl alcohol (PVA)/κ-carrageenan (CG) aerogel beads were synthesized for their simultaneous reduction. The SA/PVA/CG aerogel beads were synthesized through a [...] Read more.

Industrial textile wastewater containing both heavy metals and dyes has been massively produced. In this study, semi-interpenetrating polymer network structures of sodium alginate (SA)/polyvinyl alcohol (PVA)/κ-carrageenan (CG) aerogel beads were synthesized for their simultaneous reduction. The SA/PVA/CG aerogel beads were synthesized through a cost-effective and environmentally friendly method using naturally abundant biopolymers without toxic cross-linkers. The SA/PVA/CG aerogel beads were spheres with a size of 3.8

\pm

0.1 mm, exhibiting total pore areas of 15.2 m²/g and porous structures (pore size distribution: 0.04–242.7 μm; porosity: 93.97%) with abundant hydrogen bonding, high water absorption capacity, and chemical resistance. The adsorption capacity and mechanisms of the SA/PVA/CG aerogel beads were investigated through kinetic and isotherm experiments for heavy metals (Cu(II), Pb(II)), cationic dye (methylene blue, MB), and anionic dye (acid blue 25, AB)) in both single and binary systems. The maximum adsorption capacities of the SA/PVA/CG aerogel beads based on the Langmuir model of Cu(II), Pb(II), and MB were 85.17, 265.98, and 1324.30 mg/g, respectively. Pb(II) showed higher adsorption affinity than Cu(II) based on ionic properties, such as electronegativity and hydration radius. The adsorption of Cu(II), Pb(II), and MB on the SA/PVA/CG aerogel beads was spontaneous, with heavy metals and MB exhibiting endothermic and exothermic natures, respectively. Full article

(This article belongs to the Special Issue Eco-Friendly Gels for Adsorption)

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14 pages, 269 KiB

Open AccessArticle

Indirect Impact of Pandemic on the Diagnosis of New Primary Melanoma: A Retrospective, Multicenter Study

by Luca Nespoli, Lorenzo Borgognoni, Virginia Caliendo, Dario Piazzalunga, Piero Rossi, Marco Clementi, Stefano Guadagni, Corrado Caracò, Serena Sestini, Maria Gabriella Valente, Franco Picciotto, Cosimo Di Raimondo, Davide Ferrari, Irene Tucceri Cimini, Amy Giarrizzo, Salvatore Asero, Matteo Mascherini, Franco De Cian, Francesco Russano, Paolo Del Fiore, Francesco Cavallin, Sara Coppola, Elisabetta Pennacchioli, Pietro Gallina and Marco Rastrelli Show full author list Hide full author list

J. Clin. Med. 2025, 14(6), 2017; https://doi.org/10.3390/jcm14062017 (registering DOI) - 16 Mar 2025

Abstract

Background/Objectives: The indirect impact of the pandemic on the diagnosis and treatment of new primary melanoma has been carefully evaluated in recent years. The aim of the present study was to investigate if the indirect impact of the pandemic in Italy could [...] Read more.

Background/Objectives: The indirect impact of the pandemic on the diagnosis and treatment of new primary melanoma has been carefully evaluated in recent years. The aim of the present study was to investigate if the indirect impact of the pandemic in Italy could be detectable also in the second year of the pandemic, as suggested by the characteristics of melanoma at diagnosis. Methods: Retrospective analysis of 1640 diagnoses of cutaneous melanoma in pre-pandemic period and 1292 diagnoses in the pandemic period from 10 centers (from 1 March 2019 to 28 February 2022). Results: Our findings confirmed an indirect impact of the pandemic on characteristics of incident melanoma, also in the second year of the pandemic in Italy (Breslow thickness p < 0.0001, tumor stage p = 0.002, ulceration p = 0.04, SNLB p = 0.03), without statistically significant differences between centers. A statistically significant reduction in the time interval from diagnosis to surgical treatment was observed, but only in centers that had to modify their case mix to address the needs of treating COVID-19 patients (p = 0.0002). Conclusions: Our study confirmed the indirect impact of the pandemic on melanoma characteristics at the diagnosis in the second year of the pandemic in Italy. We also found no differences in melanoma characteristics between hospitals with different organization. Diagnostic delays may be related to a delayed access of the patient to the entire diagnostic pathway, and therefore, especially in the case of a pandemic, policies to support early diagnosis are crucial. Full article

(This article belongs to the Special Issue Clinical Consequences of COVID-19: 2nd Edition)

19 pages, 7898 KiB

Open AccessArticle

Impact of Standing Water Level and Observation Time on Remote-Sensed Canopy Indices for Rice Nitrogen Status Monitoring

by Gonzalo Carracelas, John Hornbuckle and Carlos Ballester

Remote Sens. 2025, 17(6), 1045; https://doi.org/10.3390/rs17061045 (registering DOI) - 16 Mar 2025

Abstract

The observation time and water background can affect the remote sensing estimates of the nitrogen (N) content in rice crops. This makes the use of vegetation indices (VIs) for N status monitoring and topdressing recommendations challenging, as the timing of panicle initiation and [...] Read more.

The observation time and water background can affect the remote sensing estimates of the nitrogen (N) content in rice crops. This makes the use of vegetation indices (VIs) for N status monitoring and topdressing recommendations challenging, as the timing of panicle initiation and the water level in bays usually differ between farms even when managed using the same irrigation technique. This study aimed to investigate the influence of standing water levels (from 0 to 20 cm) and the time of image acquisition on a set of N-sensitive VIs to identify those less affected by these factors. The experiment was conducted using a split-plot experimental design with two side-by-side bays (main plots) where rice was grown ponded for most of the growing season and aerobically (not permanently ponded), each with four fertilization N rates. The SCCCI and SCCCI² were the only indices that did not vary depending on the time of the day when the multispectral images were collected. These indices showed the lowest variation among water layer treatments (5%), while the Clg index showed the highest (20%). All VIs were significantly correlated with N uptake (average R² = 0.73). However, the SCCCI² was the index that showed the lowest variation in N-uptake estimates resulting in equal N-fertilizer recommendations across water level treatments. The consistent performance of SCCCI² across different water levels makes this index of interest for different irrigation strategies, including aerobic management, which is gaining increasing attention to improve the sustainability of the rice industry. Full article

(This article belongs to the Special Issue Quantitative Remote Sensing and Its Applications in Agriculture and Vegetation)

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22 pages, 11556 KiB

Open AccessArticle

Enhanced Methodology and Experimental Research for Caged Chicken Counting Based on YOLOv8

by Zhenlong Wu, Jikang Yang, Hengyuan Zhang and Cheng Fang

Animals 2025, 15(6), 853; https://doi.org/10.3390/ani15060853 (registering DOI) - 16 Mar 2025

Abstract

Accurately counting chickens in densely packed cages is a major challenge in large-scale poultry farms. Traditional manual counting methods are labor-intensive, costly, and prone to errors due to worker fatigue. Furthermore, current deep learning models often struggle with accuracy in caged environments because [...] Read more.

Accurately counting chickens in densely packed cages is a major challenge in large-scale poultry farms. Traditional manual counting methods are labor-intensive, costly, and prone to errors due to worker fatigue. Furthermore, current deep learning models often struggle with accuracy in caged environments because they are not well-equipped to handle occlusions. In response, we propose the You Only Look Once-Chicken Counting Algorithm (YOLO-CCA). YOLO-CCA improves the YOLOv8-small model by integrating the CoordAttention mechanism and the Reversible Column Networks backbone. This enhancement improved the YOLOv8-small model’s F1 score to 96.7% (+3%) and average precision_50:95 to 80.6% (+2.8%). Additionally, we developed a threshold-based continuous frame inspection method that records the maximum number of chickens per cage with corresponding timestamps. The data are stored in a cloud database for reliable tracking during robotic inspections. The experiments were conducted in an actual poultry farming environment, involving 80 cages with a total of 493 chickens, and showed that YOLO-CCA raised the chicken recognition rate to 90.9% (+13.2%). When deployed on a Jetson AGX Orin industrial computer using TensorRT, the detection speed increased to 90.9 FPS (+57.6 FPS), although the recognition rate slightly decreased to 93.2% (−2.9%). In summary, YOLO-CCA reduces labor costs, improves counting efficiency, and supports intelligent poultry farming transformation. Full article

(This article belongs to the Special Issue Real-Time Sensors and Their Applications in Smart Animal Agriculture)

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31 pages, 4790 KiB

Open AccessArticle

Assessing the Technical–Economic Feasibility of Low-Altitude Unmanned Airships: Methodology and Comparative Case Studies

by Carlo E. D. Riboldi and Luca Fanchini

Aerospace 2025, 12(3), 244; https://doi.org/10.3390/aerospace12030244 (registering DOI) - 16 Mar 2025

Abstract

The current growing interest in lighter-than-air platforms (LTA) has been fueled by the significant development of some enabling technologies, in particular electric motors and on-board electronics. The localization of multiple thrust forces in the layout of the airship, as well as the ability [...] Read more.

The current growing interest in lighter-than-air platforms (LTA) has been fueled by the significant development of some enabling technologies, in particular electric motors and on-board electronics. The localization of multiple thrust forces in the layout of the airship, as well as the ability to manage them through automatic control, promises to mitigate the controllability issues connatural to this type of flying craft. Employed on unmanned missions and close to the ground, LTA vehicles now appear to be a technically viable alternative to other unmanned aerial vehicles (UAVs) or low-flying manned machines and are similarly capable of effectively achieving the corresponding mission goals. A key step in establishing the credibility of LTA vehicles as industrial solutions for an end user is an assessment of the economic effort required for producing and operating them. This study presents an analytic approach for evaluating these costs, based on the data available at a preliminary design level for an airship. Three missions currently flown by other types of flying machines were considered, and for each mission the sizing and preliminary design of a LTA platform capable of providing the same mission performance was carried out. Correspondingly, a newly introduced method for the estimation of the cost of a LTA platform was applied. Also, an estimation of the costs currently sustained by operators for each mission was obtained from the available data and with the support of relevant companies, who currently do not fly LTA platforms but operate with more standard flying machines (in particular, multicopter or fixed-wing UAVs or manned helicopters). Finally, the costs corresponding to both currently flying non-LTA vehicles and suitably designed LTA solutions were compared, yielding indications of the emerging economic trade-offs. Full article

(This article belongs to the Special Issue Design, Characterization and Operations of Lighter-than-Air Flying Vehicles)

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