Search Results (899)

Cow efficiency is vitally important to beef sustainability, and computer simulation models may be useful tools to identify characteristics of the most efficient cow genotypes for a given production environment. The objective of this analysis was to determine whether the Beef Cattle Systems Model could replicate empirical research demonstrating a genotype–nutritional environment interaction for efficiency of feed conversion to calves weaned. Combinations of cow genotypes for lactation potential (8, 10, and 12 kg/d at peak milk) and growth potential (450, 505, and 650 kg mature weight) were simulated across four dry matter intake levels (58, 76, 93, and 111 g/kg BW^0.75). At lower dry matter intakes, cows had lesser body condition scores and weight and longer postpartum intervals, but dry matter intake had minimal influence on pregnancy percentage or calf-weaning weight. These trends match empirical research except for pregnancy percentage, where decreasing dry matter intake had a dramatic effect on pregnancy percentage in high-milking, high-growth-potential genotypes. Efficiency of feed conversion was greatest at low dry matter intake for the model simulation with no evidence of a genotype–dry matter intake interaction, which is in contrast to empirical research demonstrating a genotype–dry matter intake interaction. In conclusion, standard nutrition equations do not replicate the genotype–nutritional environment interaction observed in empirical research studies. Full article

The global food industry is undergoing a major shift driven by increasing consumer demand for clean-label and naturally preserved foods. Fresh pasta is highly vulnerable to fungal damage because of its high water activity (a_w > 0.85), typically ranging between 0.92 and 0.97, moderate to near-neutral pH (around 5.0–7.0), and nutrient-rich composition, all of which create favorable conditions for fungal growth during refrigeration, mainly by genera such as Penicillium and Aspergillus. Fungal contamination results in significant economic losses due to reduced product quality and poses potential health risks associated with mycotoxin production. Although conventional chemical preservatives are relatively effective in preventing spoilage, their use conflicts with clean-label trends and faces growing regulatory and consumer scrutiny. In this context, antifungal lactic acid bacteria (LAB) have emerged as a promising natural alternative for biopreservation. Several LAB strains, particularly those isolated from cereal-based environments (e.g., Lactobacillus plantarum and L. amylovorus), produce a broad spectrum of antifungal metabolites, including organic acids, phenylalanine-derived acids, cyclic dipeptides, and volatile compounds. These metabolites act synergistically to inhibit fungal growth through multiple mechanisms, such as cytoplasmic acidification, energy depletion, and membrane disruption. However, the application of LAB in fresh pasta production requires overcoming several challenges, including the scale-up from laboratory to industrial processes, the maintenance of metabolic activity within the complex pasta matrix, and the preservation of desirable sensory attributes. Furthermore, regulatory approval (GRAS/QPS status), economic feasibility, and effective consumer communication are crucial for successful commercial implementation. This review analyzes studies published over the past decade on fresh pasta spoilage and the antifungal activity of lactic acid bacteria (LAB), highlighting the progressive refinement of LAB-based biopreservation strategies. The literature demonstrates a transition from early descriptive studies to recent research focused on strain-specific mechanisms and technological integration. Overall, LAB-mediated biopreservation emerges as a sustainable, clean-label approach for extending the shelf life and safety of fresh pasta, with future developments relying on targeted strain selection and synergistic preservation strategies. Full article

Solar energy is a widely available renewable source suitable for diverse applications, including residential, industrial and aerospace sectors. To maximize energy capture, solar tracking systems adjust panels to maintain perpendicular alignment with sunlight. Various tracking techniques are employed to adjust these trackers, such as sensors, predefined algorithms, deep learning, and image-processing techniques. Image processing-based trackers have gained prominence for their precision and accuracy. This approach uses cameras as sensors to capture real-time sky images and analyze them to detect the sun and its coordinates, orienting solar panels toward its center. This technology can be integrated with other techniques to enhance energy output with high accuracy, minimal tracking error, and low maintenance requirements. This review examines computer vision methods used in solar tracking systems, synthesizing findings from 26 studies published between 2009 and 2024. The paper discusses main system components, methods utilized, and results obtained. Findings demonstrate that the robustness and accuracy of these tracking systems have increased compared to other tracking systems, while tracking error has decreased. Full article

Unmanned Aerial Vehicle (UAV)-based inspection is crucial for the maintenance and monitoring of high-voltage transmission lines, but detecting small objects in inspection images presents significant challenges, especially under complex backgrounds and varying lighting. These challenges are particularly evident when detecting the wire features of optical fiber composite overhead ground wire and conventional ground wires. Optical fiber composite overhead ground wire (OPGW) is a specialized cable designed to replace conventional shield wires on power utility towers. It contains one or more optical fibers housed in a protective tube, surrounded by layers of aluminum-clad steel and/or aluminum alloy wires, ensuring robust mechanical strength for grounding and high-bandwidth capabilities for remote sensing and control. Existing detection methods often struggle with low accuracy, insufficient performance, and high computational demands when dealing with small objects. To address these issues, this paper proposes an energy-efficient OPGW feature detection model for UAV-based inspection. The model incorporates a Feature Enhancement Module (FEM) to replace the C3K2 module in the sixth layer of the YOLO11 backbone, improving multi-scale feature extraction. A P2 shallow detection head is added to enhance the perception of small and edge features. Additionally, the traditional Intersection over Union (IoU) loss is replaced with Normalized Wasserstein Distance (NWD) loss function, which improves boundary regression accuracy for small objects. Experimental results show that the proposed method achieves a ${\mathrm{mAP}}_{50}$ of 78.3% and ${\mathrm{mAP}}_{50–95}$ of 52.0%, surpassing the baseline by 2.3% and 1.1%, respectively. The proposed model offers the advantages of high detection accuracy and low computational resource requirements, providing a practical solution for sustainable UAV-based inspections. Full article

High-resolution TIR missions require sustained and well-characterized radiometric accuracy to support applications such as land surface temperature retrieval, drought monitoring, and surface energy budget analysis. To address this need, we develop an operational and automated ground-based vicarious radiometric calibration framework for TIR sensors and demonstrate its performance using the Wide-swath Thermal Infrared Imager (WTI) onboard Gaofen-5 01A (GF-5A). Three arid Gobi calibration sites were selected by integrating Moderate Resolution Imaging Spectroradiometer (MODIS) cloud products, Shuttle Radar Topography Mission (SRTM)-derived topography, and WTI-based radiometric uniformity metrics to ensure low cloud cover, flat terrain, and high spatial homogeneity. Automated ground stations deployed at Golmud, Dachaidan, and Dunhuang have continuously recorded 1 min contact surface temperature since October 2023. Field-measured emissivity spectra, Integrated Global Radiosonde Archive (IGRA) radiosonde profiles, and MODTRAN (MODerate resolution atmospheric TRANsmission) v5.2 simulations were combined to compute top-of-atmosphere (TOA) radiances, which were subsequently collocated with WTI imagery. After data screening and gain-stratified regression, linear calibration coefficients were derived for each TIR band. Based on 189 scenes from February–July 2024, all four bands exhibit strong linearity (R-squared greater than 0.979). Validation using 45 independent scenes yields a mean brightness–temperature root-mean-square error (RMSE) of 0.67 K. A full radiometric-chain uncertainty budget—including contact temperature, emissivity, atmospheric profiles, and radiative transfer modeling—results in a combined standard uncertainty of 1.41 K. The proposed framework provides a low-maintenance, traceable, and high-frequency solution for the long-term on-orbit radiometric calibration of GF-5A WTI and establishes a reproducible pathway for future TIR missions requiring sustained calibration stability. Full article

This study explored the effects of Bifidobacterium animalis subspecies lactis CECT 8145 (B. animalis CECT 8145)—in both live probiotic and heat-treated postbiotic form—on metabolic health and digestion in male and female Labrador Retrievers during weight gain and loss. The study consisted of two, seven-week phases: weight gain (200% maintenance energy intake; Phase (1) and weight loss (100% maintenance energy requirement for ideal weight; Phase (2), separated by a 2-week washout period. In each phase, forty-five adult Labrador Retrievers (1.6–12.5 years) were randomly assigned to daily supplementation with live B. animalis CECT 8145 probiotic (PRO, n = 15), heat-treated B. animalis CECT 8145 postbiotic (POST, n = 15), or placebo control (CON, n = 15). Body weight, body condition score, fecal quality and food consumption were monitored throughout the study, and body composition, fecal, and blood samples were analyzed at the beginning and end of each phase. Digestibility was evaluated at the end of each phase. Post-prandial glucose responses were affected by intervention during weight loss, with a 6% reduction in the area under the curve (AUC) in POST compared to CON dogs (p = 0.035). Glucagon was decreased in females supplemented with POST (p = 0.0014), while POST males showed increased glucagon-like peptide-1 (GLP-1) compared to CON (p = 0.016) during weight gain. Serum GGT levels decreased, within the normal reference range, in POST compared to CON dogs during weight gain (post hoc p = 0.041). Fecal isovalerate was also reduced and fat digestibility increased (p = 0.026) in POST compared to CON (p = 0.018) during weight gain. There was a significant association between the group and gastric inhibitory polypeptide (GIP), with a decrease in GIP in POST over time (p = 0.030), and glucagon tended to be decreased in POST compared to CON (p = 0.073). Overall, these findings suggest supplementation with postbiotic B. animalis CECT 8145 may improve certain markers of Labrador retrievers’ metabolic health. Full article

Narrowband Internet of Things (NB-IoT) is widely used for connecting low-power devices that must operate for years without maintenance. To design reliable systems, it is essential to understand how much energy these devices consume under different conditions and which power sources can support long lifetimes. This study presents a detailed experimental evaluation of NB-IoT power consumption using a commercial System-on-Module (LMT-SoM). We measured various transmissions across different payload sizes, signal strengths, and temperatures. The results show that sending larger packets is far more efficient: a 1280-byte message requires about 7 times less energy per bit than an 80-byte message. However, standby currents varied widely between devices, from 6.7 µA to 23 µA, which has a major impact on battery life. Alongside these experiments, we compared different power sources for a 5-year deployment. Alkaline and lithium-thionyl chloride batteries were the most cost-effective solutions for indoor use, while solar panels combined with supercapacitors provided a sustainable option for outdoor applications. These findings offer practical guidance for engineers and researchers to design NB-IoT devices that balance energy efficiency, cost, and sustainability. Full article

Glycolysis-derived pyruvate is the almost exclusive source of acetyl-CoA for energy production in mitochondrial compartments of all types of neuronal and glial cells. Neurons utilize several times more glucose than glial cells due to their neurotransmitter functions. Cholinergic neurons that are responsible for cognitive functions require additional amounts of acetyl-CoA for acetylcholine-transmitter synthesis in their cytoplasmic compartment. It may be assured by preferential localization of ATP-citrate lyase (ACLY) in the cytoplasm of cholinergic neurons’ perikaryons and axonal terminals. This thesis is supported by the existence of strong regional and developmental correlations of ATP-citrate lyase and choline acetyltransferase (ChAT) activities and ACh levels in the brain. Electrolytic or chemical lesions of cholinergic nuclei cause proportional loss of the above parameters in the respective cortical target areas. On the other hand, the regional activity of mitochondrial pyruvate dehydrogenase complex (PDHC), which synthesizes nearly the whole pool of neuronal acetyl-CoA, displays no correlation with cholinergic innervation. It makes cholinergic neurons highly susceptible to brain pathologies impairing energy metabolism. Therefore, the ACLY pathway, which provides acetyl units directly to the site of acetylcholine synthesis in cholinergic nerve terminals, plays a key role in the maintenance of cholinergic neurotransmission. On the other hand, in cholinergic motor neurons, various ACLY–protein complexes are involved not only in neurotransmission but also in axonal transport of cholinergic elements from the perikaryon to cholinergic neuro-muscular junctions. This review presents findings supporting this thesis. Full article

Reliable data availability and transparent governance are fundamental requirements for distributed edge-to-cloud systems that must operate across multiple administrative domains. Conventional cloud-centric architectures centralize control and storage, creating bottlenecks and limiting autonomous collaboration at the network edge. This paper introduces a decentralized governance and service-management framework that leverages Decentralized Autonomous Organizations (DAOs) and Decentralized Applications (DApps) to to govern and orchestrate verifiable, tamper-resistant, and continuously accessible data exchange between heterogeneous edge and cloud components. By embedding blockchain-based smart contracts within swarm-enabled edge infrastructures, the approach enables automated decision-making, auditable coordination, and fault-tolerant data sharing without relying on trusted intermediaries. The proposed OASEES framework demonstrates how DAO-driven orchestration can enhance data availability and accountability in real-world scenarios, including energy grid balancing, structural safety monitoring, and predictive maintenance of wind turbines. Results highlight that decentralized governance mechanisms enhance transparency, resilience, and trust, offering a scalable foundation for next-generation edge-to-cloud data ecosystems. Full article

Digital Twin technology is transforming how buildings are designed, operated, and optimized, serving as a key enabler of smarter, more energy-efficient, and sustainable built environments. By creating dynamic, data-driven virtual replicas of physical assets, Digital Twins support continuous monitoring, predictive maintenance, and performance optimization across a building’s lifecycle. This paper provides a structured review of current developments and future trends in Digital Twin applications within the building sector, particularly highlighting their contribution to decarbonization, operational efficiency, and performance enhancement. The analysis identifies major challenges, including data accessibility, interoperability among heterogeneous systems, scalability limitations, and cybersecurity concerns. It emphasizes the need for standardized protocols and open data frameworks to ensure seamless integration across Building Management Systems (BMSs), Building Information Models (BIMs), and sensor networks. The paper also discusses policy and regulatory aspects, noting how harmonized standards and targeted incentives can accelerate adoption, particularly in retrofit and renovation projects. Emerging directions include Artificial Intelligence integration for autonomous optimization, alignment with circular economy principles, and coupling with smart grid infrastructures. Overall, realizing the full potential of Digital Twins requires coordinated collaboration among researchers, industry, and policymakers to enhance building performance and advance global decarbonization and urban resilience goals. Full article

Road transport systems are central to sustainable mobility and the energy transition because they account for a large share of final energy use and remain heavily dependent on fossil fuels. With more than 90% of transport energy still supplied by petroleum-based fuels, improving energy efficiency and reducing emissions in road networks has become a strategic priority. This review compares Australia, Hong Kong, and the United Kingdom to examine how road-design standards and emerging digital technologies can improve energy performance across planning, design, operations, and maintenance. Using Australia’s Austroads Guide to Road Design, Hong Kong’s Transport Planning and Design Manual (TPDM), and the UK’s Design Manual for Roads and Bridges (DMRB) as core reference frameworks, we apply a rubric-based document analysis that codes provisions by mechanism type (direct, indirect, or emergent), life-cycle stage, and energy relevance. The findings show that energy-relevant outcomes are embedded through different pathways: TPDM most strongly supports urban operational efficiency via coordinated/adaptive signal control and public-transport prioritization; DMRB emphasizes strategic-network flow stability and whole-life carbon governance through managed motorway operations and life-cycle assessment requirements; and Austroads provides context-sensitive, performance-based guidance that supports smoother operations and active travel, with implementation varying by jurisdiction. Building on these results, the paper proposes an AI-enabled benchmarking overlay that links manual provisions to comparable energy and carbon indicators to support cross-jurisdictional learning, investment prioritization, and future manual revisions toward safer, more efficient, and low-carbon road transport systems. Full article

Indonesia faces growing pressure to strengthen waste management while expanding renewable energy generation, particularly from high-moisture biomass such as palm oil mill effluent (POME) and the organic fraction of municipal solid waste (OFMSW). Anaerobic digestion technology (ADT) is technically suitable for both feedstocks; however, its deployment depends on broader operational, financial, social, and institutional conditions. This study evaluates ADT readiness for biomass waste-to-energy (BWTE) development in Indonesia using a multistakeholder Japanese Technology Readiness Assessment (J-TRA) framework. The results and discussion are supported by a literature review, secondary data analysis, and interviews with government agencies, industry actors, financiers, non-governmental organizations, and researchers. The results reveal a clear divergence in readiness outcomes. POME-based ADT reaches Technology Readiness Levels (TRLs) of 6–8, supported by a stable and homogeneous feedstock supply, established industrial operations, and corporate incentives to mitigate methane emissions. Key remaining constraints relate to high capital costs for smaller mills, low electricity purchase tariffs, and competing export incentives for untreated POME. In contrast, OFMSW-based ADT remains at TRL 2–4, constrained by inconsistent waste segregation, insufficient operation and maintenance capacity, limited municipal budgets, residential safety concerns, and fragmented governance across waste and energy institutions. Across both cases, readiness is shaped by five interacting forces. The first three are technical: feedstock characteristics, operations and maintenance (O&M) capability, and financial certainty. The remaining two are enabling conditions: social acceptance and institutional coordination. This study concludes that Indonesia’s BWTE transition requires integrated technological, behavioral, and policy interventions, supported by further research on hybrid valorization pathways and context-specific life-cycle and cost analyses. Full article

Isolated microgrids with green hydrogen storage offer a promising solution for supplying electricity to remote communities where conventional grid expansion is infeasible. Designing such systems requires balancing two conflicting objectives: minimizing installation and operation costs while maximizing supply reliability. This paper proposes a multi-objective optimization methodology, based on the Non-dominated Sorting Genetic Algorithm II, to determine the optimal sizing of multiple microgrid components. This sizing explicitly addresses both the power capacities (kW) (for photovoltaic panels, wind turbines, electrolyzers, and fuel cells) and the energy storage capacities (kWh and kg) (for batteries and hydrogen tanks, respectively), aiming to generate Pareto-optimal solutions that explore this trade-off. The proposed method evaluates the trade-off by minimizing two objectives: the Net Present Value, which includes investment, replacement, and maintenance costs, and the total expected interruption hours, derived from an hourly energy balance analysis. The methodology’s effectiveness is validated using four distinct case studies. Three of these are based on real locations with specific load profiles and climate data. To test the method’s robustness, a fourth case study uses a fictitious load profile, designed with pronounced seasonal variations and a clear distinction between weekday and weekend consumption. Our results demonstrate the method’s ability to identify efficient hybrid renewable topologies combining photovoltaic and/or wind generation, batteries, and hydrogen systems (electrolyzer, storage tank, and fuel cell). The obtained cost–reliability curves provide practical decision-support tools for system planners. Full article

Vitamin B1 (thiamine) is a water-soluble B vitamin. As a cofactor of many enzymes, it is essential for the proper functioning of many body systems and organs, including metabolic and energy metabolism. In extreme cases, vitamin B1 deficiency causes neurodegenerative disorders, including beri-beri, or cognitive impairment resulting from encephalopathy. B1 avitaminosis may result from increased demand, dietary errors, malabsorption, or excessive loss. Thiamine supplementation is used in cases of vitamin B1 deficiency or for preventative measures in situations of increased demand. Vitamin B1 can be administered enterally or parenterally (intravenously, intramuscularly, subcutaneously). The route and dose depend on the individual patient’s clinical situation. Hypersensitivity to vitamin B1 is rare and appears to be primarily associated with rapid intravenous infusion of large doses of thiamine hydrochloride over a short period (intravenous bolus). Hypersensitivity to thiamine administered by routes other than intravenous or intramuscular injection appears to be an incidental phenomenon. Thiamine should also be considered as an occupational allergen. The mechanism of thiamine hypersensitivity has not been clearly elucidated. However, considering the clinical nature and dynamics of the reaction, the most likely reaction seems to be an immediate type of hypersensitivity reaction (immunoglobulin E (IgE)-dependent), in which thiamine (but not its metabolites) acts as a hapten. Diagnosing hypersensitivity to vitamin B1 is difficult due to the lack of validated tests for additional testing. In individuals requiring thiamine supplementation who have experienced hypersensitivity to intramuscular or intravenous administration of this vitamin, switching to oral administration may be considered (provided this does not reduce treatment efficacy). This form of supplementation is usually well tolerated by individuals allergic to parenteral thiamine. However, if enteral supplementation does not guarantee the maintenance of therapeutic potential, thiamine desensitization may be considered, which seems to be an effective therapeutic method in such a clinical situation. Full article

The growing demand for energy-efficient and sustainable manufacturing requires maintenance strategies that extend beyond reliability optimization toward active energy management. This study proposes a Smart Hybrid Maintenance System (SHMS) that integrates Reliability-Centered Maintenance (RCM) and Condition-Based Maintenance (CBM) principles with energy performance assessment. The framework combines classical reliability indicators (MTBF, MTTR, and Availability) with energy-oriented Key Performance Indicators (EEI, EENS, and OEE) to quantify the relationship between machine degradation, operational availability, and energy efficiency. The methodology was validated using two datasets: NASA N-CMAPSS for simulation-based benchmarking and the Smart RDM industrial environment for real process data. Results demonstrate that predictive maintenance supported by the Hybrid Risk Index ($HRI$) reduces unplanned downtime by up to 12%, corresponding to a 7–9% decrease in specific energy consumption and a measurable improvement in the Energy Efficiency Index. By embedding energy metrics into predictive maintenance decision-making, the SHMS enables dual optimization of reliability and energy performance. The proposed approach not only enhances equipment availability and cost efficiency but also supports industrial decarbonization targets, positioning predictive maintenance as a key enabler of energy-aware and sustainable manufacturing aligned with Industry 5.0 objectives. Full article