Search Results (964)

While the Ankom RF system facilitates efficient high-throughput in vitro fermentation studies, its high cost and limited flexibility constrain its broader applicability. To address these limitations, we developed and validated a low-cost, modular gas monitoring system (FerME), assembled from commercially available components. To evaluate its performance and reproducibility relative to the Ankom RF system (Ankom Technology, Macedon, NY, USA), in vitro rumen fermentation experiments were conducted under strictly controlled and identical conditions. Whole rumen contents were collected approximately 2 h post-feeding from individual mid- or late-lactation dairy cows and immediately transported to the laboratory. Each fermenter received 50 mL of processed rumen fluid, 100 mL of anaerobically prepared artificial saliva buffer, and 1.2 g of the donor cow’s diet. Bottles were sealed with the respective system’s pressure sensors, flushed with CO₂, and incubated in a 50 L water bath maintained at 39 °C. FerME (New Taipei City, Taiwan) and Ankom RF fermenters were placed side-by-side to ensure uniform thermal conditions. To assess the effect of filter bag use, an additional trial employed Ankom F57 filter bags (Ankom Technology, Macedon, NY, USA; 25 μm pore size). Trial 1 revealed no significant differences in cumulative gas production, volatile fatty acids (VFAs), NH₃-N, or pH between systems (p > 0.05). However, the use of filter bags reduced gas output and increased propionate concentrations (p < 0.05). Trial 2, which employed filter bags in both systems, confirmed comparable results, with the FerME system demonstrating improved precision (CV: 4.8% vs. 13.2%). Gas composition (CH₄ + CO₂: 76–82%) and fermentation parameters remained consistent across systems (p > 0.05). Importantly, with 12 pressure sensors, the total cost of FerME was about half that of the Ankom RF system. Collectively, these findings demonstrate that FerME is a reliable, low-cost alternative for real-time rumen fermentation monitoring and could be suitable for studies in animal nutrition, methane mitigation, and related applications. Full article

During large-scale pavement construction, the preparation of SBS-modified asphalt typically produces large amounts of harmful fumes. The emergence of deodorants can effectively alleviate the problem of smoke emissions during the asphalt manufacturing process. On the basis of ensuring the original road performance, exploring more suitable dosages and types of deodorant is urgently needed. Five commercial deodorants were evaluated using an asphalt smoke collection system, and UV-visible spectrophotometry (UV) was employed to screen the deodorants based on smoke concentration. Gas chromatography–mass spectrometry (GC-MS) was used to quantitatively analyze changes in harmful smoke components before and after adding two deodorants. Subsequently, the mechanisms of action of the two different types of deodorants were analyzed microscopically using fluorescence microscopy. Finally, the performance of bitumen and asphalt mixtures after adding deodorants was evaluated. The results showed that deodorant A (reactive type) and D (adsorption type) exhibited the best smoke suppression effects, with optimal addition rates of 0.6% and 0.5%, respectively. Deodorant A reduced benzene homologues by nearly 50% and esters by approximately 40%, while deodorant D reduced benzene homologues by approximately 70% and esters by approximately 60%, without producing new toxic gases. Both deodorants had a minimal impact on the basic properties of bitumen and the road performance of asphalt mixtures, with all indicators meeting technical specifications. This research provides a theoretical basis for the effective application of deodorants in the future, truly enabling a transition from laboratory research to large-scale engineering applications in the construction of environmentally friendly roads. Full article

Intensive vegetable farming emits high nitrous oxide (N₂O) due to traffic-induced compaction, highlighting the need for preventing nitrogen (N) losses through better traffic management. This study examined the effects of Controlled Traffic Farming (CTF) and Random Traffic Farming (RTF) on N₂O emissions using intact soil cores (diameter: 18.7 cm; depth: 25 cm) collected from a vegetable production system in Pukekohe, New Zealand. Soil cores from CTF beds, CTF tramlines, and RTF plots were analysed under fertilised (140 kg N/ha) and unfertilised conditions. N₂O fluxes were monitored over 58 days using gas chambers. The fertilised RTF system significantly (p < 0.05) increased N₂O emissions (5.4 kg N₂O–N/ha) compared to the unfertilised RTF system (1.53 kg N₂O–N/ha). The emission from fertilised RTF was 46% higher than the maximum N₂O emissions (3.7 kg N₂O–N/ha) reported under New Zealand pasture conditions. The fertilised CTF system showed a 31.6% reduction in N₂O emissions compared to fertilised RTF and did not differ significantly from unfertilised CTF. In general, CTF has demonstrated some resilience against fertiliser-induced N₂O emissions, indicating the need for further investigation into its role as a greenhouse gas mitigation strategy. Full article

This article describes a new software architecture for the non-invasive detection of canine leishmaniasis disease. The proposed platform combines gas-sensing technologies, artificial intelligence (AI), and modular cloud-based software components to identify disease-specific volatile organic compounds (VOCs) found in dog breath and hair samples. The system, which has a multi-tier architecture that includes data collection, pre-processing, machine learning-based analysis, diagnosis-request processing, and user interfaces for veterinarians, faculty researchers, and dog owners, has been integrated into a Li-ion Power website plug-in. The primary goal of implementing the proposed platform is to detect parasites at any point they are infectious to a host. This includes detecting parasites at all stages of their life cycle, where they can infect a new host. In addition, this is crucial for accurate diagnosis, effective treatment, and preventing further transmission. Full article

To improve the accuracy of Japanese finger-spelled character recognition using an RGB camera, we focused on feature design and refinement of the recognition method. By leveraging angular features extracted via MediaPipe, we proposed a method that effectively captures subtle motion differences while minimizing the influence of background and surrounding individuals. We constructed a large-scale dataset that includes not only the basic 50 Japanese syllables but also those with diacritical marks, such as voiced sounds (e.g., “ga”, “za”, “da”) and semi-voiced sounds (e.g., “pa”, “pi”, “pu”), to enhance the model’s ability to recognize a wide variety of characters. In addition, the application of a change-point detection algorithm enabled accurate segmentation of sign language motion boundaries, improving word-level recognition performance. These efforts laid the foundation for a highly practical recognition system. However, several challenges remain, including the limited size and diversity of the dataset and the need for further improvements in segmentation accuracy. Future work will focus on enhancing the model’s generalizability by collecting more diverse data from a broader range of participants and incorporating segmentation methods that consider contextual information. Ultimately, the outcomes of this research should contribute to the development of educational support tools and sign language interpretation systems aimed at real-world applications. Full article

Flowering is a key agronomic trait that directly influences the yield of the tea-oil tree (Camellia oleifera). Floral initiation, which precedes flower bud differentiation, represents a critical developmental stage affecting the flowering outcomes. However, the molecular mechanisms underlying floral initiation in C. oleifera remain poorly understood. In this study, buds from five key developmental stages of a 12-year-old C. oleifera cultivar ‘changlin53’ were collected as experimental samples. Scanning electron microscopy was employed to identify the stage of floral initiation. UPLC-MS/MS was used to analyze endogenous gibberellin (GA) concentrations, while transcriptomic analysis was performed to reveal the underlying transcriptional regulatory network. Six GA types were detected during floral initiation and petal development. GA₄ was exclusively detected at the sprouting stage (BII), while GA₃ was present in all samples but was significantly lower in BII and the flower bud primordium formation stage (BIII) than in the other samples. A total of 64 differentially expressed genes were concurrently enriched in flower development, reproductive shoot system development, and shoot system development. Weighted gene co-expression network analysis (WGCNA) identified eight specific modules significantly associated with different developmental stages. The magenta module, containing Unigene0084708 (CoFT) and Unigene0037067 (CoLEAFY), emerged as a key regulatory module driving floral initiation. Additionally, GA20OX1 and GA2OX8 were identified as candidate genes involved in GA-mediated regulation of floral initiation. Based on morphological and transcriptomic analyses, we conclude that floral initiation of C. oleifera is a continuous regulatory process governed by multiple genes, with the FT-LFY module playing a central role in the transition from apical meristem to floral meristem. Full article

The International Maritime Organization (IMO) has set a goal to reach net-zero greenhouse gas emissions from international shipping by or around 2050. The ship energy efficiency framework has played a positive role over the past decade in improving carbon intensity and reducing greenhouse gas emissions by employing the technical and operational energy efficiency metrics as effective appraisal tools. To quantify the ship energy efficiency performance and review the existing energy efficiency framework, this paper analyzed the data for the reporting year of 2023 extracted from the European Union (EU) monitoring, reporting, and verification (MRV) system, and investigated the operational profiles and energy efficiency for the ships calling at EU ports. The results show that the data accumulated in the EU MRV system could provide powerful support for conducting ship energy efficiency appraisals, which could facilitate the formulation of decarbonization policies for global shipping and management decisions for stakeholders. However, data quality, ship operational energy efficiency metrics, and co-existence with the IMO data collection system (DCS) remain issues to be addressed. With the improvement of IMO DCS system and the implementation of IMO Net-Zero Framework, harmonizing the two systems and avoiding duplicated regulation of shipping emissions at the EU and global levels are urgent. Full article

Background: Renal trauma accounts for approximately 3–5% of all trauma cases, predominantly affecting young males. The most common etiology is blunt trauma, particularly due to road traffic accidents, and it frequently occurs as part of polytrauma involving multiple organ systems. Management strategies are primarily dictated by hemodynamic stability, overall clinical condition, comorbidities, and injury severity graded according to the AAST classification. This study aimed to evaluate the effectiveness of non-operative management (NOM) in high-grade renal trauma (AAST grades III–V), beyond its established role in low-grade injuries (grades I–II). Secondary endpoints included the identification of independent prognostic factors for NOM failure and in-hospital mortality. Methods: We conducted a retrospective observational study including patients diagnosed with blunt renal trauma who presented to the Emergency Department of Policlinico Umberto I in Rome between 1 January 2013 and 30 April 2024. Collected data comprised demographics, trauma mechanism, vital signs, hemodynamic status (shock index), laboratory tests, blood gas analysis, hematuria, number of transfused RBC units in the first 24 h, AAST renal injury grade, ISS, associated injuries, treatment approach, hospital length of stay, and mortality. Statistical analyses, including multivariable logistic regression, were performed using SPSS v28.0. Results: A total of 244 patients were included. Low-grade injuries (AAST I–II) accounted for 43% (n = 105), while high-grade injuries (AAST III–V) represented 57% (n = 139). All patients with low-grade injuries were managed non-operatively. Among high-grade injuries, 124 patients (89%) were treated with NOM, including observation, angiography ± angioembolization, stenting, or nephrostomy. Only 15 patients (11%) required nephrectomy, primarily due to persistent hemodynamic instability. The overall mortality rate was 13.5% (33 patients) and was more closely associated with the overall injury burden than with renal injury severity. Multivariable analysis identified shock index and active bleeding on CT as independent predictors of NOM failure, whereas ISS and age were significant predictors of in-hospital mortality. Notably, AAST grade did not independently predict either outcome. Conclusions: In line with the current international literature, our study confirms that NOM is the treatment of choice not only for low-grade renal injuries but also for carefully selected hemodynamically stable patients with high-grade trauma. Our findings highlight the critical role of physiological parameters and overall ISS in guiding management decisions and underscore the need for individualized assessment to minimize unnecessary nephrectomies and optimize patient outcomes. Full article

Melastoma dodecandrum is primarily propagated through stem cuttings, which limits genetic variation and constrains breeding efforts. To overcome this limitation and facilitate molecular breeding, the establishment of a reliable and efficient regeneration system is essential. This study investigated the effects of plant growth regulators (PGRs) and culture media on the in vitro regeneration system of M. dodecandrum. The highest rate of callus induction (96.67%) was achieved when sterile leaf explants were cultured on Murashige and Skoog (MS) basal medium supplemented with 2.00 mg·L⁻¹ 2,4-dichlorophenoxyacetic acid (2,4-D) and 0.50 mg·L⁻¹ 6-benzylaminopurine (6-BA). For callus differentiation, the optimal formulation of MS + 2.0 mg·L⁻¹ 6-BA + 0.5 mg·L⁻¹ naphthylacetic acid (NAA) resulted in a differentiation frequency of 83.33%. The optimal PGR combinations for shoot proliferation were 1.5 mg·L⁻¹ 6-BA + 0.1 mg·L⁻¹ NAA and 0.5 mg·L⁻¹ 6-BA + 0.2 mg·L⁻¹ NAA. The optimal rooting media were MS medium supplemented with 0.1, 0.2, or 0.5 mg·L⁻¹ indole-3-butyric acid (IBA) or 1/2MS medium supplemented with 0.1 mg·L⁻¹ IBA. Additionally, this study investigated the dynamic changes in endogenous hormones during the regeneration process. The levels and ratios of hormones, including gibberellin (GA₃), abscisic acid (ABA), indole-3-acetic acid (IAA), and zeatin (ZT), collectively regulated the regeneration process. Elevated levels of ABA and GA₃ may promote callus initiation as well as the growth and development of adventitious roots during the early induction stage. Reduced levels of ABA and IAA favored callus differentiation into shoots, whereas elevated GA₃ levels facilitated proliferation of adventitious shoots. Throughout the regeneration process, fluctuations in ZT levels remained relatively stable. This study successfully established an in vitro regeneration system for M. dodecandrum using leaf explants, providing theoretical guidance and technical support for further molecular breeding efforts, genetic transformation, and industrial development. Full article

A chili pepper variety and origin detection system that integrates a field-programmable gate array (FPGA) with an electronic nose (e-nose) is proposed in this paper to address the issues of variety confusion and origin ambiguity in the chili pepper market. The system uses the AIRSENSE PEN3 e-nose from Germany to collect gas data from thirteen different varieties of chili peppers and two specific varieties of chili peppers originating from seven different regions. Model training is conducted via the proposed lightweight convolutional neural network ChiliPCNN. By combining the strengths of a convolutional neural network (CNN) and a multilayer perceptron (MLP), the ChiliPCNN model achieves an efficient and accurate classification process, requiring only 268 parameters for chili pepper variety identification and 244 parameters for origin tracing, with 364 floating-point operations (FLOPs) and 340 FLOPs, respectively. The experimental results demonstrate that, compared with other advanced deep learning methods, the ChiliPCNN has superior classification performance and good stability. Specifically, ChiliPCNN achieves accuracy rates of 94.62% in chili pepper variety identification and 93.41% in origin tracing tasks involving Jiaoyang No. 6, with accuracy rates reaching as high as 99.07% for Xianjiao No. 301. These results fully validate the effectiveness of the model. To further increase the detection speed of the ChiliPCNN, its acceleration circuit is designed on the Xilinx Zynq7020 FPGA from the United States and optimized via fixed-point arithmetic and loop unrolling strategies. The optimized circuit reduces the latency to 5600 ns and consumes only 1.755 W of power, significantly improving the resource utilization rate and processing speed of the model. This system not only achieves rapid and accurate chili pepper variety and origin detection but also provides an efficient and reliable intelligent agricultural management solution, which is highly important for promoting the development of agricultural automation and intelligence. Full article

In the context of the dual-carbon goals, this study proposes a cooperative game-theoretic optimization strategy to enhance the energy utilization efficiency, operational efficiency, and cost-effectiveness of integrated energy systems (IESs) while simultaneously reducing carbon emissions, improving operational flexibility, and mitigating renewable energy variability. To achieve these goals, an IES framework integrating power-to-gas (P2G) technology and carbon capture and storage (CCS) facilities is established to regulate carbon emissions. The system incorporates P2G conversion units and thermal components—specifically, hydrogen fuel cells, electrolyzers, reactors, and electric boilers—aiming to maximize energy conversion efficiency and asset utilization. A cooperative game-theoretic optimization model is developed to facilitate collaboration among multiple stakeholders within the coalition, which employs the Shapley value method to ensure equitable distribution of the cooperative surplus, thereby maximizing collective benefits. The model is solved using an improved gray wolf optimizer (IGWO). The simulation results demonstrate that the proposed strategy effectively coordinates multi-IES scheduling, significantly reduces carbon emissions, facilitates the efficient allocation of cooperation gains, and maximizes overall system utility. Full article

Ships play a crucial role in modern society, serving purposes such as marine transportation, tourism, and exploration. Malfunctions or defects in the main engine, which is a core component of ship operations, can disrupt normal functionality and result in substantial financial losses. Consequently, early fault diagnosis of abnormal engine conditions is critical for effective maintenance. In this paper, we propose a deep hybrid model for fault diagnosis of ship main engines, utilizing exhaust gas temperature data. The proposed model utilizes both time-domain features (TDFs) and time-series raw data. In order to effectively extract features from each type of data, two distinct feature extraction networks and an attention module-based classifier are designed. The model performance is evaluated using real-world cylinder exhaust gas temperature data collected from the large ship low-speed two-stroke main engine. The experimental results demonstrate that the proposed method outperforms conventional methods in fault diagnosis accuracy. The experimental results demonstrate that the proposed method improves fault diagnosis accuracy by 6.146% compared to the best conventional method. Furthermore, the proposed method maintains superior performanceeven in noisy environments under realistic industrial conditions. This study demonstrates the potential of using exhaust gas temperature using a single sensor signal for data-driven fault detection and provides a scalable foundation for future multi-sensor diagnostic systems. Full article

This dataset presents environmental observations collected in August 2021 from 18 port and harbor sites located around Jeju Island, Korea. It includes physical, biogeochemical, and greenhouse gas (GHG) variables measured in surface seawater, such as temperature, salinity, dissolved oxygen, nutrients, chlorophyll-a, pH, total alkalinity, and dissolved inorganic carbon. Concentrations and air–sea fluxes of nitrous oxide (N₂O), methane (CH₄), and carbon dioxide (CO₂) were also quantified. All measurements were conducted following standardized analytical protocols, and certified reference materials and duplicate analyses were used to ensure data accuracy. Consequently, the dataset revealed that elevated nutrient accumulation in port and harbor waters and GHG concentrations tended to be higher at sites with stronger land-based influence. During August 2021, most sites functioned as sources of N₂O, CH₄, and CO₂ to the atmosphere. This integrated dataset offers valuable insights into the influence of anthropogenic and hydrological factors on coastal GHG dynamics and provides a foundation for future studies across diverse semi-enclosed marine systems. Full article

This paper presents methods for modelling and optimising the industrial limestone grinding process carried out using a real limestone plant. Two key process evaluation indicators were developed: specific electric energy consumption and an extended indicator that also includes gas usage. Using process data collected from the SCADA system and results from industrial factorial experiments, regression artificial neural network models were developed, with controllable process parameters used as inputs. In the next phase, black-box optimisation was performed using Bayesian and genetic algorithms to identify optimal mill operating settings. The results demonstrate significant improvements in energy efficiency, with energy savings reaching up to 48% in selected cases. The proposed methodology can be effectively applied to enhance energy performance in similar industrial grinding processes. Full article

EU accession countries, including the Republic of Serbia, are under growing pressure to align their plastic waste management systems with EU environmental directives. Despite this, significant challenges remain, including inadequate infrastructure, a limited recycling capacity, and weak enforcement mechanisms. This study employs life cycle assessment (LCA) to evaluate the environmental impacts of polyethylene terephthalate (PET) packaging waste in Serbia, focusing on three end-of-life scenarios (EoL): landfilling, recycling, and incineration. Using GaBi Professional v6.0 software and the ReCiPe 2016 methodology, the results indicate that mismanaged PET waste contributes notably to terrestrial ecotoxicity (3.69 kg 1.4-DB eq.) and human toxicity (non-cancer) (2.36 kg 1.4-DB eq.). In 2023, 14,967.8 tons of PET were collected by authorized operators; however, unreported quantities likely end up in landfills or the natural environment. Beyond the quantified LCA results, this study highlights microplastic pollution as an emerging environmental concern. It advocates for the development of Serbia-specific characterization factors (CFs) for PET microplastics, incorporating localized fate, exposure, and effect data. Tailored CFs would enhance the precision of impact assessments for Serbian terrestrial ecosystems, contributing to more effective, evidence-based environmental policies. These insights are crucial for supporting Serbia’s transition to sustainable waste management and for meeting EU environmental standards. Full article