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Keywords = efficiency assessment

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27 pages, 3470 KiB  
Article
Spatiotemporal Evolution and Influencing Factors of Carbon Emission Efficiency of Apple Production in China from 2003 to 2022
by Dejun Tan, Juanjuan Cheng, Jin Yu, Qian Wang and Xiaonan Chen
Agriculture 2025, 15(15), 1680; https://doi.org/10.3390/agriculture15151680 (registering DOI) - 2 Aug 2025
Abstract
Understanding the carbon emission efficiency of apple production (APCEE) is critical for promoting green and low-carbon agricultural development. However, the spatiotemporal dynamics and driving factors of APCEE in China remain inadequately explored. This study employs life cycle assessment, super-efficiency slacks-based measures, [...] Read more.
Understanding the carbon emission efficiency of apple production (APCEE) is critical for promoting green and low-carbon agricultural development. However, the spatiotemporal dynamics and driving factors of APCEE in China remain inadequately explored. This study employs life cycle assessment, super-efficiency slacks-based measures, and a panel Tobit model to evaluate the carbon footprint, APCEE, and its determinants in China’s two major production regions from 2003 to 2022. The results reveal that: (1) Producing one ton of apples in China results in 0.842 t CO2e emissions. Land carbon intensity and total carbon emissions peaked in 2010 (28.69 t CO2e/ha) and 2014 (6.52 × 107 t CO2e), respectively, exhibiting inverted U-shaped trends. Carbon emissions from various production areas show significant differences, with higher pressure on carbon emission reduction in the Loess Plateau region, especially in Gansu Province. (2) The APCEE in China exhibits a W-shaped trend (mean: 0.645), with overall low efficiency loss. The Bohai Bay region outperforms the Loess Plateau and national averages. (3) The structure of the apple industry, degree of agricultural mechanization, and green innovation positively influence APCEE, while the structure of apple cultivation, education level, and agricultural subsidies negatively impact it. Notably, green innovation and agricultural subsidies display lagged effects. Moreover, the drivers of APCEE differ significantly between the two major production regions. These findings provide actionable pathways for the green and low-carbon transformation of China’s apple industry, emphasizing the importance of spatially tailored green policies and technology-driven decarbonization strategies. Full article
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
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27 pages, 3806 KiB  
Article
Dynamic Evolution and Resilience Enhancement of the Urban Tourism Ecological Health Network: A Case Study in Shanghai, China
by Man Wei and Tai Huang
Systems 2025, 13(8), 654; https://doi.org/10.3390/systems13080654 (registering DOI) - 2 Aug 2025
Abstract
Urban tourism has evolved into a complex adaptive system, where unregulated expansion disrupts the ecological balance and intensifies resource stress. Understanding the dynamic evolution and resilience mechanisms of the tourism ecological health network (TEHN) is essential for supporting sustainable urban tourism as a [...] Read more.
Urban tourism has evolved into a complex adaptive system, where unregulated expansion disrupts the ecological balance and intensifies resource stress. Understanding the dynamic evolution and resilience mechanisms of the tourism ecological health network (TEHN) is essential for supporting sustainable urban tourism as a coupled human–natural system. Using Shanghai as a case study, we applied the "vigor–organization–resilience–services" (VORS) framework to evaluate ecosystem health, which served as a constraint for constructing the TEHN, using the minimum cumulative resistance (MCR) model for the period from 2001 to 2023. A resilience framework integrating structural and functional dimensions was further developed to assess spatiotemporal evolution and guide targeted enhancement strategies. The results indicated that as ecosystem health degraded, particularly in peripheral areas, the urban TEHN in Shanghai shifted from a dispersed to a centralized structure, with limited connectivity in the periphery. The resilience of the TEHN continued to grow, with structural resilience remaining at a high level, while functional resilience still required enhancement. Specifically, the low integration and limited choice between the tourism network and the transportation system hindered tourists from selecting routes with higher ecosystem health indices. Enhancing functional resilience, while sustaining structural resilience, is essential for transforming the TEHN into a multi-centered, multi-level system that promotes efficient connectivity, ecological sustainability, and long-term adaptability. The results contribute to a systems-level understanding of tourism–ecology interactions and support the development of adaptive strategies for balancing network efficiency and environmental integrity. Full article
(This article belongs to the Section Complex Systems and Cybernetics)
23 pages, 2663 KiB  
Article
How Nanofluids May Enhance Energy Efficiency and Carbon Footprint in Buildings?
by Sylwia Wciślik
Sustainability 2025, 17(15), 7035; https://doi.org/10.3390/su17157035 (registering DOI) - 2 Aug 2025
Abstract
Nanofluids are an innovative working medium in solar hot water installations (DHWs), thanks to their increased thermal conductivity and heat transfer coefficient. The aim of this work was to assess the effect of Al2O3 nanofluids in a water–ethylene glycol base [...] Read more.
Nanofluids are an innovative working medium in solar hot water installations (DHWs), thanks to their increased thermal conductivity and heat transfer coefficient. The aim of this work was to assess the effect of Al2O3 nanofluids in a water–ethylene glycol base (40:60%) and with the addition of Tween 80 surfactant (0.2 wt%) on thermal efficiency (ε) and exergy (ηex) in a plate heat exchanger at DHW flows of 3 and 12 L/min. The numerical NTU–ε model was used with dynamic updating of thermophysical properties of nanofluids and the solution of the ODE system using the ode45 method, and the validation was carried out against the literature data. The results showed that the nanofluids achieved ε ≈ 0.85 (vs. ε ≈ 0.87 for the base fluid) and ηex ≈ 0.72 (vs. ηex ≈ 0.74), with higher entropy generation. The addition of Tween 80 reduced the viscosity by about 10–15%, resulting in a slight increase of Re and h-factor; however, the impact on ε and ηex was marginal. The environmental analysis with an annual demand of Q = 3000 kWh/year and an emission factor of 0.2 kg CO2/kWh showed that for ε < 0.87 the nanofluids increased the emissions by ≈16 kg CO2/year, while at ε ≈ 0.92, a reduction of ≈5% was possible. This paper highlights the need to optimize nanofluid viscosity and exchanger geometry to maximize energy and environmental benefits. Nowadays, due to the growing problems of global warming, the analysis of energy efficiency and carbon footprint related to the functioning of a building seems to be crucial. Full article
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22 pages, 728 KiB  
Article
Design and Performance Evaluation of LLM-Based RAG Pipelines for Chatbot Services in International Student Admissions
by Maksuda Khasanova Zafar kizi and Youngjung Suh
Electronics 2025, 14(15), 3095; https://doi.org/10.3390/electronics14153095 (registering DOI) - 2 Aug 2025
Abstract
Recent advancements in large language models (LLMs) have significantly enhanced the effectiveness of Retrieval-Augmented Generation (RAG) systems. This study focuses on the development and evaluation of a domain-specific AI chatbot designed to support international student admissions by leveraging LLM-based RAG pipelines. We implement [...] Read more.
Recent advancements in large language models (LLMs) have significantly enhanced the effectiveness of Retrieval-Augmented Generation (RAG) systems. This study focuses on the development and evaluation of a domain-specific AI chatbot designed to support international student admissions by leveraging LLM-based RAG pipelines. We implement and compare multiple pipeline configurations, combining retrieval methods (e.g., Dense, MMR, Hybrid), chunking strategies (e.g., Semantic, Recursive), and both open-source and commercial LLMs. Dual evaluation datasets of LLM-generated and human-tagged QA sets are used to measure answer relevancy, faithfulness, context precision, and recall, alongside heuristic NLP metrics. Furthermore, latency analysis across different RAG stages is conducted to assess deployment feasibility in real-world educational environments. Results show that well-optimized open-source RAG pipelines can offer comparable performance to GPT-4o while maintaining scalability and cost-efficiency. These findings suggest that the proposed chatbot system can provide a practical and technically sound solution for international student services in resource-constrained academic institutions. Full article
(This article belongs to the Special Issue AI-Driven Data Analytics and Mining)
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15 pages, 3579 KiB  
Article
Dual-Control-Gate Reconfigurable Ion-Sensitive Field-Effect Transistor with Nickel-Silicide Contacts for Adaptive and High-Sensitivity Chemical Sensing Beyond the Nernst Limit
by Seung-Jin Lee, Seung-Hyun Lee, Seung-Hwa Choi and Won-Ju Cho
Chemosensors 2025, 13(8), 281; https://doi.org/10.3390/chemosensors13080281 (registering DOI) - 2 Aug 2025
Abstract
In this study, we propose a bidirectional chemical sensor platform based on a reconfigurable ion-sensitive field-effect transistor (R-ISFET) architecture. The device incorporates Ni-silicide Schottky barrier source/drain (S/D) contacts, enabling ambipolar conduction and bidirectional turn-on behavior for both p-type and n-type configurations. Channel polarity [...] Read more.
In this study, we propose a bidirectional chemical sensor platform based on a reconfigurable ion-sensitive field-effect transistor (R-ISFET) architecture. The device incorporates Ni-silicide Schottky barrier source/drain (S/D) contacts, enabling ambipolar conduction and bidirectional turn-on behavior for both p-type and n-type configurations. Channel polarity is dynamically controlled via the program gate (PG), while the control gate (CG) suppresses leakage current, enhancing operational stability and energy efficiency. A dual-control-gate (DCG) structure enhances capacitive coupling, enabling sensitivity beyond the Nernst limit without external amplification. The extended-gate (EG) architecture physically separates the transistor and sensing regions, improving durability and long-term reliability. Electrical characteristics were evaluated through transfer and output curves, and carrier transport mechanisms were analyzed using band diagrams. Sensor performance—including sensitivity, hysteresis, and drift—was assessed under various pH conditions and external noise up to 5 Vpp (i.e., peak-to-peak voltage). The n-type configuration exhibited high mobility and fast response, while the p-type configuration demonstrated excellent noise immunity and low drift. Both modes showed consistent sensitivity trends, confirming the feasibility of complementary sensing. These results indicate that the proposed R-ISFET sensor enables selective mode switching for high sensitivity and robust operation, offering strong potential for next-generation biosensing and chemical detection. Full article
(This article belongs to the Section Electrochemical Devices and Sensors)
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25 pages, 19905 KiB  
Article
Assessing Urban Park Accessibility via Population Projections: Planning for Green Equity in Shanghai
by Leiting Cen and Yang Xiao
Land 2025, 14(8), 1580; https://doi.org/10.3390/land14081580 (registering DOI) - 2 Aug 2025
Abstract
Rapid urbanization and demographic shifts present significant challenges to spatial justice in green space provision. Traditional static assessments have become increasingly inadequate for guiding park planning, which now requires a dynamic, future-oriented analytical approach. To address this gap, this study incorporates population dynamics [...] Read more.
Rapid urbanization and demographic shifts present significant challenges to spatial justice in green space provision. Traditional static assessments have become increasingly inadequate for guiding park planning, which now requires a dynamic, future-oriented analytical approach. To address this gap, this study incorporates population dynamics into urban park planning by developing a dynamic evaluation framework for park accessibility. Building on the Gaussian-based two-step floating catchment area (Ga2SFCA) method, we propose the human-population-projection-Ga2SFCA (HPP-Ga2SFCA) model, which integrates population forecasts to assess park service efficiency under future demographic pressures. Using neighborhood-committee-level census data from 2000 to 2020 and detailed park spatial data, we identified five types of population change and forecast demographic distributions for both short- and long-term scenarios. Our findings indicate population decline in the urban core and outer suburbs, with growth concentrated in the transitional inner-suburban zones. Long-term projections suggest that 66% of communities will experience population growth, whereas short-term forecasts indicate a decline in 52%. Static models overestimate park accessibility by approximately 40%. In contrast, our dynamic model reveals that accessibility is overestimated in 71% and underestimated in 7% of the city, highlighting a potential mismatch between future population demand and current park supply. This study offers a forward-looking planning framework that enhances the responsiveness of park systems to demographic change and supports the development of more equitable, adaptive green space strategies. Full article
(This article belongs to the Special Issue Spatial Justice in Urban Planning (Second Edition))
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18 pages, 2432 KiB  
Article
Alkali Lignin-Based Biopolymer Formulations for Electro-Assisted Drug Delivery of Natural Antioxidants in Breast Cancer Cells—A Preliminary Study
by Severina Semkova, Radina Deneva, Georgi Antov, Donika Ivanova and Biliana Nikolova
Int. J. Mol. Sci. 2025, 26(15), 7481; https://doi.org/10.3390/ijms26157481 (registering DOI) - 2 Aug 2025
Abstract
Recently, a number of natural biologically active substances have been proven to be attractive alternatives to conventional anticancer medicine or as adjuvants in contemporary combination therapies. Although lignin-based materials were previously accepted as waste materials with limited usefulness, recent studies increasingly report the [...] Read more.
Recently, a number of natural biologically active substances have been proven to be attractive alternatives to conventional anticancer medicine or as adjuvants in contemporary combination therapies. Although lignin-based materials were previously accepted as waste materials with limited usefulness, recent studies increasingly report the possibility of their use for novel applications in various industrial branches, including biomedicine. In this regard, the safety, efficiency, advantages and limitations of lignin compounds for in vitro/in vivo applications remain poorly studied and described. This study was carried out to investigate the possibility of using newly synthesized, alkali lignin-based micro-/nano-biopolymer formulations (Lignin@Formulations/L@F) as carriers for substances with antioxidant and/or anticancer effectiveness. Moreover, we tried to assess the opportunity for using an electro-assisted approach for achieving improved intracellular internalization. An investigation was conducted on an in vitro panel of breast cell lines, namely two breast cancer lines with different metastatic potentials and one non-tumorigenic line as a control. The characterization of all tested formulations was performed via DLS (dynamic light scattering) analysis. We developed an improved separation procedure via size/charge unification for all types of Lignin@Formulations. Moreover, in vitro applications were investigated. The results demonstrate that compared to healthy breast cells, both tested cancer lines exhibited slight sensitivity after treatment with different formulations (empty or loaded with antioxidant substances). This effect was also enhanced after applying electric pulses. L@F loaded with Quercetin was also explored only on the highly metastatic cancer cell line as a model for the breast cancer type most aggressive and non-responsive to traditional treatments. All obtained data suggest that the tested formulations have potential as carriers for the electro-assisted delivery of natural antioxidants such as Quercetin. Full article
(This article belongs to the Special Issue Natural Products in Cancer Prevention and Treatment)
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24 pages, 6999 KiB  
Article
Plasmid DNA Delivery to Cancer Cells with Poly(L-lysine)-Based Copolymers Bearing Thermally Sensitive Segments: Balancing Polyplex Tightness, Transfection Efficiency, and Biocompatibility
by Mustafa Kotmakci, Natalia Toncheva-Moncheva, Sahar Tarkavannezhad, Bilge Debelec Butuner, Ivaylo Dimitrov and Stanislav Rangelov
Pharmaceutics 2025, 17(8), 1012; https://doi.org/10.3390/pharmaceutics17081012 (registering DOI) - 2 Aug 2025
Abstract
Background/Objectives. Efficient nucleic acid delivery into target cells remains a critical challenge in gene therapy. Due to its advantages in biocompatibility and safety, recent research has increasingly focused on non-viral gene delivery. Methods. A series of copolymers—synthesized by integrating thermally sensitive poly(N-isopropylacrylamide) [...] Read more.
Background/Objectives. Efficient nucleic acid delivery into target cells remains a critical challenge in gene therapy. Due to its advantages in biocompatibility and safety, recent research has increasingly focused on non-viral gene delivery. Methods. A series of copolymers—synthesized by integrating thermally sensitive poly(N-isopropylacrylamide) (PNIPAm), hydrophilic poly(ethylene glycol) (PEG) grafts, and a polycationic poly(L-lysine) (PLL) block of varying lengths ((PNIPAm)77-graft-(PEG)9-block-(PLL)z, z = 10–65)—were investigated. Plasmid DNA complexation with the copolymers was achieved through temperature-modulated methods. The resulting polyplexes were characterized by evaluating complex strength, particle size, zeta potential, plasmid DNA loading capacity, resistance to anionic stress, stability in serum, and lysosomal membrane destabilization assay. The copolymers’ potential for plasmid DNA delivery was assessed through cytotoxicity and transfection studies in cancer cell lines. Results. Across all complexation methods, the copolymers effectively condensed plasmid DNA into stable polyplexes. Particle sizes (60–90 nm) ranged with no apparent correlation to copolymer type, complexation method, or N/P ratio, whereas zeta potentials (+10–+20 mV) and resistance to polyanionic stress were dependent on the PLL length and N/P ratio. Cytotoxicity analysis revealed a direct correlation between PLL chain length and cell viability, with all copolymers demonstrating minimal cytotoxicity at concentrations required for efficient transfection. PNL-20 ((PNIPAm)77-graft-(PEG)9-block-(PLL)20) exhibited the highest transfection efficiency among the tested formulations while maintaining low cytotoxicity. Conclusions. The study highlights the promising potential of (PNIPAm)77-graft-(PEG)9-block-(PLL)z copolymers for effective plasmid DNA delivery to cancer cells. It reveals the importance of attaining the right balance between polyplex tightness and plasmid release to achieve improved biocompatibility and transfection efficiency. Full article
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25 pages, 2100 KiB  
Article
Flexible Demand Side Management in Smart Cities: Integrating Diverse User Profiles and Multiple Objectives
by Nuno Souza e Silva and Paulo Ferrão
Energies 2025, 18(15), 4107; https://doi.org/10.3390/en18154107 (registering DOI) - 2 Aug 2025
Abstract
Demand Side Management (DSM) plays a crucial role in modern energy systems, enabling more efficient use of energy resources and contributing to the sustainability of the power grid. This study examines DSM strategies within a multi-environment context encompassing residential, commercial, and industrial sectors, [...] Read more.
Demand Side Management (DSM) plays a crucial role in modern energy systems, enabling more efficient use of energy resources and contributing to the sustainability of the power grid. This study examines DSM strategies within a multi-environment context encompassing residential, commercial, and industrial sectors, with a focus on diverse appliance types that exhibit distinct operational characteristics and user preferences. Initially, a single-objective optimization approach using Genetic Algorithms (GAs) is employed to minimize the total energy cost under a real Time-of-Use (ToU) pricing scheme. This heuristic method allows for the effective scheduling of appliance operations while factoring in their unique characteristics such as power consumption, usage duration, and user-defined operational flexibility. This study extends the optimization problem to a multi-objective framework that incorporates the minimization of CO2 emissions under a real annual energy mix while also accounting for user discomfort. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is utilized for this purpose, providing a Pareto-optimal set of solutions that balances these competing objectives. The inclusion of multiple objectives ensures a comprehensive assessment of DSM strategies, aiming to reduce environmental impact and enhance user satisfaction. Additionally, this study monitors the Peak-to-Average Ratio (PAR) to evaluate the impact of DSM strategies on load balancing and grid stability. It also analyzes the impact of considering different periods of the year with the associated ToU hourly schedule and CO2 emissions hourly profile. A key innovation of this research is the integration of detailed, category-specific metrics that enable the disaggregation of costs, emissions, and user discomfort across residential, commercial, and industrial appliances. This granularity enables stakeholders to implement tailored strategies that align with specific operational goals and regulatory compliance. Also, the emphasis on a user discomfort indicator allows us to explore the flexibility available in such DSM mechanisms. The results demonstrate the effectiveness of the proposed multi-objective optimization approach in achieving significant cost savings that may reach 20% for industrial applications, while the order of magnitude of the trade-offs involved in terms of emissions reduction, improvement in discomfort, and PAR reduction is quantified for different frameworks. The outcomes not only underscore the efficacy of applying advanced optimization frameworks to real-world problems but also point to pathways for future research in smart energy management. This comprehensive analysis highlights the potential of advanced DSM techniques to enhance the sustainability and resilience of energy systems while also offering valuable policy implications. Full article
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14 pages, 841 KiB  
Article
Enhanced Deep Learning for Robust Stress Classification in Sows from Facial Images
by Syed U. Yunas, Ajmal Shahbaz, Emma M. Baxter, Mark F. Hansen, Melvyn L. Smith and Lyndon N. Smith
Agriculture 2025, 15(15), 1675; https://doi.org/10.3390/agriculture15151675 (registering DOI) - 2 Aug 2025
Abstract
Stress in pigs poses significant challenges to animal welfare and productivity in modern pig farming, contributing to increased antimicrobial use and the rise of antimicrobial resistance (AMR). This study involves stress classification in pregnant sows by exploring five deep learning models: ConvNeXt, EfficientNet_V2, [...] Read more.
Stress in pigs poses significant challenges to animal welfare and productivity in modern pig farming, contributing to increased antimicrobial use and the rise of antimicrobial resistance (AMR). This study involves stress classification in pregnant sows by exploring five deep learning models: ConvNeXt, EfficientNet_V2, MobileNet_V3, RegNet, and Vision Transformer (ViT). These models are used for stress detection from facial images, leveraging an expanded dataset. A facial image dataset of sows was collected at Scotland’s Rural College (SRUC) and the images were categorized into primiparous Low-Stressed (LS) and High-Stress (HS) groups based on expert behavioural assessments and cortisol level analysis. The selected deep learning models were then trained on this enriched dataset and their performance was evaluated using cross-validation on unseen data. The Vision Transformer (ViT) model outperformed the others across the dataset of annotated facial images, achieving an average accuracy of 0.75, an F1 score of 0.78 for high-stress detection, and consistent batch-level performance (up to 0.88 F1 score). These findings highlight the efficacy of transformer-based models for automated stress detection in sows, supporting early intervention strategies to enhance welfare, optimize productivity, and mitigate AMR risks in livestock production. Full article
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23 pages, 2029 KiB  
Systematic Review
Exploring the Role of Industry 4.0 Technologies in Smart City Evolution: A Literature-Based Study
by Nataliia Boichuk, Iwona Pisz, Anna Bruska, Sabina Kauf and Sabina Wyrwich-Płotka
Sustainability 2025, 17(15), 7024; https://doi.org/10.3390/su17157024 (registering DOI) - 2 Aug 2025
Abstract
Smart cities are technologically advanced urban environments where interconnected systems and data-driven technologies enhance public service delivery and quality of life. These cities rely on information and communication technologies, the Internet of Things, big data, cloud computing, and other Industry 4.0 tools to [...] Read more.
Smart cities are technologically advanced urban environments where interconnected systems and data-driven technologies enhance public service delivery and quality of life. These cities rely on information and communication technologies, the Internet of Things, big data, cloud computing, and other Industry 4.0 tools to support efficient city management and foster citizen engagement. Often referred to as digital cities, they integrate intelligent infrastructures and real-time data analytics to improve mobility, security, and sustainability. Ubiquitous sensors, paired with Artificial Intelligence, enable cities to monitor infrastructure, respond to residents’ needs, and optimize urban conditions dynamically. Given the increasing significance of Industry 4.0 in urban development, this study adopts a bibliometric approach to systematically review the application of these technologies within smart cities. Utilizing major academic databases such as Scopus and Web of Science the research aims to identify the primary Industry 4.0 technologies implemented in smart cities, assess their impact on infrastructure, economic systems, and urban communities, and explore the challenges and benefits associated with their integration. The bibliometric analysis included publications from 2016 to 2023, since the emergence of urban researchers’ interest in the technologies of the new industrial revolution. The task is to contribute to a deeper understanding of how smart cities evolve through the adoption of advanced technological frameworks. Research indicates that IoT and AI are the most commonly used tools in urban spaces, particularly in smart mobility and smart environments. Full article
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36 pages, 645 KiB  
Article
A KPI-Based Framework for Evaluating Sustainable Agricultural Practices in Southern Angola
by Eduardo E. Eliseu, Tânia M. Lima and Pedro D. Gaspar
Sustainability 2025, 17(15), 7019; https://doi.org/10.3390/su17157019 (registering DOI) - 1 Aug 2025
Abstract
Agricultural production in southern Angola faces challenges due to unsustainable practices, including inefficient use of water, fertilizers, and machinery, resulting in low yields and environmental degradation. Therefore, clear and measurable indicators are needed to guide farmers toward more sustainable practices. The scientific literature [...] Read more.
Agricultural production in southern Angola faces challenges due to unsustainable practices, including inefficient use of water, fertilizers, and machinery, resulting in low yields and environmental degradation. Therefore, clear and measurable indicators are needed to guide farmers toward more sustainable practices. The scientific literature insufficiently addresses this issue, leaving a significant gap in the evaluation of key performance indicators (KPIs) that can guide good agricultural practices (GAPs) adapted to the context of southern Angola, with the goal of promoting a more resilient and sustainable agricultural sector. So, the objective of this study is to identify and assess KPIs capable of supporting the selection of GAPs suitable for maize, potato, and tomato cultivation in the context of southern Angolan agriculture. A systematic literature review (SLR) was conducted, screening 2720 articles and selecting 14 studies that met defined inclusion criteria. Five KPIs were identified as the most relevant: gross margin, net profit, water use efficiency, nitrogen use efficiency, and machine energy. These indicators were analyzed and standardized to evaluate their contribution to sustainability across different GAPs. Results show that organic fertilizers are the most sustainable option for maize, drip irrigation for potatoes, and crop rotation for tomatoes in southern Angola because of their efficiency in low-resource environments. A clear, simple, and effective representation of the KPIs was developed to be useful in communicating to farmers and policy makers on the selection of the best GAPs in the cultivation of different crops. The study proposes a validated KPI-based methodology for assessing sustainable agricultural practices in developing regions such as southern Angola, aiming to lead to greater self-sufficiency and economic stability in this sector. Full article
19 pages, 2359 KiB  
Article
Research on Concrete Crack Damage Assessment Method Based on Pseudo-Label Semi-Supervised Learning
by Ming Xie, Zhangdong Wang and Li’e Yin
Buildings 2025, 15(15), 2726; https://doi.org/10.3390/buildings15152726 (registering DOI) - 1 Aug 2025
Abstract
To address the inefficiency of traditional concrete crack detection methods and the heavy reliance of supervised learning on extensive labeled data, in this study, an intelligent assessment method of concrete damage based on pseudo-label semi-supervised learning and fractal geometry theory is proposed to [...] Read more.
To address the inefficiency of traditional concrete crack detection methods and the heavy reliance of supervised learning on extensive labeled data, in this study, an intelligent assessment method of concrete damage based on pseudo-label semi-supervised learning and fractal geometry theory is proposed to solve two core tasks: one is binary classification of pixel-level cracks, and the other is multi-category assessment of damage state based on crack morphology. Using three-channel RGB images as input, a dual-path collaborative training framework based on U-Net encoder–decoder architecture is constructed, and a binary segmentation mask of the same size is output to achieve the accurate segmentation of cracks at the pixel level. By constructing a dual-path collaborative training framework and employing a dynamic pseudo-label refinement mechanism, the model achieves an F1-score of 0.883 using only 50% labeled data—a mere 1.3% decrease compared to the fully supervised benchmark DeepCrack (F1 = 0.896)—while reducing manual annotation costs by over 60%. Furthermore, a quantitative correlation model between crack fractal characteristics and structural damage severity is established by combining a U-Net segmentation network with the differential box-counting algorithm. The experimental results demonstrate that under a cyclic loading of 147.6–221.4 kN, the fractal dimension monotonically increases from 1.073 (moderate damage) to 1.189 (failure), with 100% accuracy in damage state identification, closely aligning with the degradation trend of macroscopic mechanical properties. In complex crack scenarios, the model attains a recall rate (Re = 0.882), surpassing U-Net by 13.9%, with significantly enhanced edge reconstruction precision. Compared with the mainstream models, this method effectively alleviates the problem of data annotation dependence through a semi-supervised strategy while maintaining high accuracy. It provides an efficient structural health monitoring solution for engineering practice, which is of great value to promote the application of intelligent detection technology in infrastructure operation and maintenance. Full article
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18 pages, 309 KiB  
Article
Effects of Adding Hydroxytyrosol to the Diet of Pigs in the Nursery Phase on Growth Performance, Biochemical Markers, and Fatty Acid Profile
by Rafael Domingos Augusto Rofino, Cassio Antonio Ficagna, Taeline Zamboni, Bruna Klein, Enrico A. Altieri, Kevin E. O’Connor, Reeta Davis, Margaret Walsh, Fernando de Castro Tavernari, Marcel Manente Boiago, Aleksandro Schafer da Silva and Diovani Paiano
Animals 2025, 15(15), 2268; https://doi.org/10.3390/ani15152268 (registering DOI) - 1 Aug 2025
Abstract
This study evaluated the effects of dietary hydroxytyrosol (HT) addition on piglets during the nursery phase across two experiments. In the first, 72 weaned male piglets (~26 days old, 7.3 ± 0.5 kg) were assigned to one of four diets containing 0, 5, [...] Read more.
This study evaluated the effects of dietary hydroxytyrosol (HT) addition on piglets during the nursery phase across two experiments. In the first, 72 weaned male piglets (~26 days old, 7.3 ± 0.5 kg) were assigned to one of four diets containing 0, 5, 10, or 50 mg HT/kg feed. Growth performance, serum biochemistry, histological and behavioral parameters, and meat lipid profiles were assessed. In the second study, the apparent digestibility of diets containing 0, 25, or 50 mg HT/kg feed was evaluated using 15 male piglets (21.5 ± 1.5 kg) through total excreta collection. Results revealed that HT influenced serum glucose and gamma-glutamyl transferase, histological inflammation, and active behaviors. HT modified lipid profiles, reduced capric, lauric, linolenic, arachidonic, cis-5,8,11,14,17-eicosapentaenoic fatty acid concentrations, and increased the nervonic acid profile. The digestibility of dry matter, organic matter, energy, and protein increased with HT use up to 50 mg/kg of feed. These findings demonstrate that HT positively impacts piglet efficiency, changing the fatty acid profile with increased nervonic acid, highlighting its potential as a dietary additive for improving nursery pig production. Full article
(This article belongs to the Section Animal Nutrition)
25 pages, 1105 KiB  
Review
Review and Decision-Making Tree for Methods to Balance Indoor Environmental Comfort and Energy Conservation During Building Operation
by Shan Lin, Yu Zhang, Xuanjiang Chen, Chengzhi Pan, Xianjun Dong, Xiang Xie and Long Chen
Sustainability 2025, 17(15), 7016; https://doi.org/10.3390/su17157016 (registering DOI) - 1 Aug 2025
Abstract
Effective building operation requires a careful balance between energy conservation and indoor environmental comfort. Although numerous methods have been developed to reduce energy consumption during the operational phase, their objectives and applications vary widely. However, the complexity of building energy management makes it [...] Read more.
Effective building operation requires a careful balance between energy conservation and indoor environmental comfort. Although numerous methods have been developed to reduce energy consumption during the operational phase, their objectives and applications vary widely. However, the complexity of building energy management makes it challenging to identify the most suitable methods that simultaneously achieve both comfort and efficiency goals. Existing studies often lack a systematic framework that supports integrated decision-making under comfort constraints. This research aims to address this gap by proposing a decision-making tree for selecting energy conservation methods during building operation with an explicit consideration of indoor environmental comfort. A comprehensive literature review is conducted to identify four main energy-consuming components during building operation: the building envelope, HVAC systems, lighting systems, and plug loads and appliances. Three key comfort indicators—thermal comfort, lighting comfort, and air quality comfort—are defined, and energy conservation methods are categorized into three strategic groups: passive strategies, control optimization strategies, and behavioural intervention strategies. Each method is assessed using a defined set of evaluation criteria. Subsequently, a questionnaire survey is administered for the calibration of the decision tree, incorporating stakeholder preferences and expert judgement. The findings contribute to the advancement of understanding regarding the co-optimization of energy conservation and occupant comfort in building operations. Full article
(This article belongs to the Special Issue Novel Technologies and Digital Design in Smart Construction)
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