Search Results (106)

Pine wilt disease (PWD), caused by the pine wood nematode (PWN, Bursaphelenchus xylophilus), poses a significant threat to global pine forests and calls for the development of innovative management strategies. Microbial control emerges as an effective, cost-efficient, and environmentally sustainable approach to eliminate the damage from PWD. This review consolidates molecular mechanisms in the microbiological control of PWD, which focus on three core strategies: microbial control activity against PWN, biological control of vector insects, and the enhancement of host tree resistance to nematode infections. The review thoroughly evaluates integrated control strategies in which microbial control is used in traditional management practices. Recent studies have pinpointed promising microbial agents for PWN control, such as nematophagous microorganisms, nematicidal metabolites, parasitic fungi that target vector insects, and microbes that boost plant resistance. In particular, the control potential of volatile organic compounds (VOCs) produced by microorganisms against PWN and the enhancement of pine resistance to PWN by microorganisms were emphasized. Moreover, we assessed the challenges and opportunities associated with the field application of microbiological control agents. We emphasized the feasibility of multi-strategy microbial integrated control, which provides a framework for future studies on microbial-based PWD control strategies. Full article

Volatile organic compounds (VOCs) in biological samples originate both from exogenous and endogenous sources. Recent studies have highlighted their potential as cancer biomarkers, emphasizing the need for accurate detection methods in clinical settings. However, analysis of VOCs in whole blood (WB) samples remains challenging due to the complex matrix effects caused by the protein−VOC binding phenomenon and lack of standardized sample preparation protocols. Therefore, this study suggests a standardized method for advanced VOC analysis in WB samples specifically for veterinary applications. We compared 12 combinations of reagents composed of protein denaturing reagents and salts, particularly urea mixtures, to enhance VOC decoupling from proteins and improve matrix effect uniformity in gas chromatography−mass spectrometry (GC-MS) analysis. Among all combinations, urea with NaCl showed an optimal performance, demonstrating an advancement in the detection sensitivity of up to 151.3% and a significantly reduced matrix effect variation (−35.5% to 25%) compared with the water-only control. This novel approach eliminates complex procedures while maintaining accuracy, making it particularly suitable for veterinary uses. The method’s standardization and improved performance characteristics offer a practical solution for efficient VOC detection in veterinary diagnostics, potentially advancing tumor biomarker research. Full article

Volatile organic compounds (VOCs) significantly contribute to atmospheric pollution and present considerable health hazards. This study involves the fabrication of a novel ionic liquid/polymer nanofiber membrane, [P_(14)666]TMPP/PAN, using electrospinning, and its subsequent evaluation for adsorption performance concerning typical aromatic volatile organic compounds—benzene, toluene, and xylene. The membranes were methodically analysed utilising SEM, TGA, FTIR, and XRD techniques. Adsorption tests indicated that augmenting the [P_(14)666]TMPP loading improved VOC uptake, with the 80 wt% ionic liquid membrane attaining maximum adsorption capacities of 1466.81, 569.14, and 456.29 mg/g for benzene, toluene, and xylene, respectively—signifying enhancements of 23.6-, 4.8-, and 8.4-fold compared to pristine PAN. Furthermore, regeneration studies validated consistent performance across four adsorption–desorption cycles. The results underscore the efficacy of electrospun [P_(14)666]TMPP/PAN membranes as reusable adsorbents for the elimination of volatile organic compounds in air purification applications. Full article

Eucalyptus wood particleboard (EPB), commonly used in indoor decoration, releases volatile organic compounds (VOCs) that can adversely affect indoor air quality and human health. This study systematically examined the VOC emission characteristics of EPB using headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography mass spectrometry (GC-MS). A total of 65 VOCs were identified, with medium-volatility organic compounds (MVOCs) accounting for 28 compounds, low-volatility organic compounds (LVOCs) for 26, and high-volatility organic compounds (HVOCs) for 11. Terpenoids dominated the VOCs, comprising 78.46%, followed by aldehydes (10.77%) and alkanes (7.69%). Key odorant compounds (KOCs) were identified using the relative odor activity value (ROAV), with hexanal (ROAV = 100) and o-cymene (ROAV = 76.90) emerging as the most significant contributors to the overall odor profile. Thermal post-treatment at temperatures of 50–60 °C for durations of 6–12 h was found to be an effective method for reducing the residual VOCs and KOCs in the EPB, leading to a marked decrease in the peak areas of key odorants. The findings suggest several strategies for minimizing VOC emissions and eliminating residual odor, including reducing the use of miscellaneous wood materials, controlling the production of o-cymene, and employing thermal post-treatment at moderate temperatures. These measures provide a promising approach to reducing VOC and odor emissions from EPB and similar composite wood products, thereby enhancing their suitability for indoor applications. This study innovatively establishes an evaluation system for VOC emission characteristics in wood-based panels based on the ROAV. It elucidates the contribution mechanisms of key odor-active substances (e.g., hexanal and pentanal) and presents a thermal post-treatment process for source control, achieving simultaneous VOCs and odor elimination. A ROAV-guided hierarchical management strategy is proposed, providing scientific guidelines for the industrial production of high-quality particleboards with ultralow emissions (TVOC < 50 μg/m³) and minimal odor intensity (OI < Grade 3). Full article

With the increasing demand for air pollution control, the development of efficient and stable catalysts to degrade hazardous VOCs such as toluene has become particularly important. Herein, various copper-doped attapulgite-supported cobalt oxide spinel composites (Cu_xCo_3−xO₄/ATP) were synthesized using an ultrasonic-assisted precipitation method. The results showed that the abundant Si-OH groups on the surface of ATP played a crucial role in anchoring Co, and the instantaneous high-energy input of ultrasonication facilitated the formation of Si-O-Co bonds in Co₃O₄/ATP. The doping of Cu ions induced the expansion of the Co₃O₄ lattice, resulting in a significant number of oxygen vacancies. The ultrasound-induced synthesized Cu_0.1Co_2.9O₄/ATP catalyst exhibited the best catalytic oxidation performance, achieving a 99% toluene degradation rate at 300 °C under a weight hourly space velocity (WHSV) of 10,000 mL·g⁻¹ h⁻¹ and initial toluene concentration of 1000 ppm, along with high stability during 12 h of continuous running. This work presents a new strategy for the cost-effective catalytic elimination of VOCs. Full article

Catalytic combustion is an efficient and economic technology for eliminating volatile organic compounds (VOCs) in industrial environments. This study evaluated the synergistic catalytic properties of bimetallic oxides, viz., CoM/γ-Al₂O₃ (M = Cu, Fe, or Ni), for improving the combustion efficiency of toluene. The CoM/γ-Al₂O₃ catalysts were prepared by an impregnation method and characterized by using advanced techniques. Among the bimetallic catalysts, CoCu/γ-Al₂O₃ exhibited the best performance. The findings revealed that owing to the strong synergistic interaction between Cu, Co, and the γ-Al₂O₃ support, the active species in the CoCu/γ-Al₂O₃ catalyst were effectively stabilized, and they significantly enhanced the redox performance and acidity of the catalyst, demonstrating superior catalytic activity and sulfur resistance. Conversely, the CoFe/γ-Al₂O₃ catalyst performed poorly, exhibiting a significant decline in its activity owing to sulfur poisoning. The insights from this study provide theoretical support for designing efficient, sulfur-resistant catalysts that are crucial to reducing industrial VOC emissions. Full article

Volatile organic compounds (VOCs) from petrochemical, pharmaceutical, and other industries have serious damage to human health and the environment. Catalytic oxidation is a promising method to eliminate air pollution due to its high efficiency, wide application range, and environmental friendliness. However, in the actual industrial environment, the composition of industrial exhaust gases is complex, including VOCs, water vapour, chloride, sulfide and so on. The impurities would have competitive adsorption with reactants or react with the active sites, leading to the decline of catalytic activity, even the deactivation of catalysts. Therefore, this review summarises the recent research on the anti-poisoning ability of catalysts in the catalytic oxidation of VOCs, primarily focusing on the effect of water vapour, chloride, and sulfide. The catalytic oxidation mechanism manifested that the adsorption and activation of reactants are significant in VOCs degradation. On this basis, the mechanism of catalyst poisoning was analysed, and the inhibitory effect of impurities on the oxidation reaction was elucidated. According to the research status, three anti-poisoning strategies are proposed, including building a bimetallic system, modifying supports, and establishing the protected coating. This work provides a theoretical foundation and reference point for the rational construction of anti-poisoning catalysts in VOCs elimination. Full article

Developing efficient strategies for VOC emission abatement is an urgent task for protection of the environment and human health. Complete catalytic oxidation exhibits advantages, making it an effective, environmentally friendly, and economically profitable approach for VOC elimination. Pd-based catalysts are known as highly active for hydrocarbon catalytic oxidation. The nature of carrier materials is of particular importance because it may affect activity by changing physicochemical properties of the palladium species. In this work, Al₂O₃, CeO₂, CeO₂-Al₂O₃, and Y-doped CeO₂-Al₂O₃ were used as carriers of palladium catalysts. Methane and benzene were selected as representatives of two types of hydrocarbons. A decisive step in complete methane oxidation is the first C–H bond breaking, while the extraordinary stability of the six-membered ring structure is a challenge in benzene oxidation. The support effect was explored by textural measurements using XRF, XRD, XPS, EPR, and TPR techniques. Three ceria-containing samples showed superior CH₄ oxidation performance, achieving 90% methane conversion at about 300 °C and complete oxidation at 320 °C. Evidence for presence of Pd²⁺ species in all samples regarded as most active was provided by XP-derived analysis. Pd/Y-Ce/Al catalysts exhibited very high activity in benzene oxidation by reaching 100% conversion at 180 °C. The contributions of higher Pd and Ce³⁺ surface concentrations, the presence of O₂⁻-adsorbed superoxo species, and Pd⁰ ↔ PdO redox transfer were considered. The potential of a simple, environmentally friendly, and less energy demanding mechanochemical preparation procedure of mixed oxides was demonstrated. Full article

As an important means to ensure the safety of power transmission, the inspection of overhead transmission lines requires high accuracy for detecting small objects on the transmission lines and relies heavily on the construction of large-scale datasets by using deep learning instead of manual inspection. However, transmission inspection data often involve some sensitive information and need to be labeled by professionals, so it is difficult to construct a large transmission inspection dataset. In order to solve the problem of how to effectively train only on a small amount of transmission line data and achieve high object detection accuracy considering the large-scale variation in transmission objects, we propose an enhanced self-supervised pre-training model for DETR-like models, which are innovative object detectors eliminating hand-crafted non-maximum suppression and manual anchor design compared to previous CNN-based detectors. This paper mainly covers the following two points: (i) We compare UP-DETR and DETReg, noting that UP-DETR’s random cropping method performs poorly on small datasets and affects DETR’s localization ability. To address this, we adopt DETReg’s approach, replacing Selective Search with Edge Boxes for better results. (ii) To tackle large-scale variations in transmission inspection datasets, we propose a multi-scale feature reconstruction task, aligning feature embeddings with multi-scale encoder embeddings, and enhancing multi-scale object detection. Our method surpasses UP-DETR DETReg with DETR variants when fine-tuning PASCAL VOC and PTL-AI Furnas for object detection. Full article

Currently, detectors have made significant progress in inference speed and accuracy. However, these detectors require Non-Maximum Suppression (NMS) during the post-processing stage to eliminate redundant boxes, which limits the optimization of model inference speed. We first analyzed the reason for the dependence on NMS in the post-processing stage. The result showed that a score loss in a one-to-many label assignment leads to the presence of high-quality redundant boxes, making them difficult to remove. To realize end-to-end object detection and simplify the detection pipeline, we propose herein a mixed label assignment (MLA) training method, which uses one-to-many label assignment to provide rich supervision signals, alleviating the performance degradation, and we eliminate the need for NMS in the post-processing stage by using one-to-one label assignment. Additionally, a window feature propagation block (WFPB) is introduced, utilizing the inductive bias of images to enable feature sharing in local regions. Through these methods, we conducted experiments on the VOC and DUO datasets; our end-to-end detector MA-YOLOX achieved 66.0 mAP and 52.6 mAP, respectively, outperforming the YOLOX by 1.7 and 1.6. Additionally, our model performed faster than other real-time detectors without NMS. Full article

Increased levels and detrimental effects of volatile organic compounds (VOCs) on air quality and human health have become an important issue in the environmental field. Benzene is classified as one of the most hazardous air pollutants among non-halogenated aromatic hydrocarbons with toxic, carcinogenic, and mutagenic effects. Various technologies have been applied to decrease harmful emissions from various sources such as petrochemistry, steel manufacturing, organic chemical, paint, adhesive, and pharmaceutical production, vehicle exhausts, etc. Catalytic oxidation to CO₂ and water is an attractive approach to VOC removal due to high efficiency, low energy consumption, and the absence of secondary pollution. However, catalytic oxidation of the benzene molecule is a great challenge because of the extraordinary stability of its six-membered ring structure. Developing highly efficient catalysts is of primary importance for effective elimination of benzene at low temperatures. This review aims to summarize and discuss some recent advances in catalyst composition and preparation strategies. Advantages and disadvantages of using noble metal-based catalysts and transition metal oxide-based catalysts are addressed. Effects of some crucial factors such as catalyst support nature, metal particle size, electronic state of active metal, redox properties, reactivity of lattice oxygen and surface adsorbed oxygen on benzene removal are explored. Thorough elucidation of reaction mechanisms in benzene oxidation is a prerequisite to develop efficient catalysts. Benzene oxidation mechanisms are analyzed based on in situ catalyst characterization, reaction kinetics, and theoretical simulation calculations. Considering the role of oxygen vacancies in improving catalytic performance, attention is given to oxygen defect engineering. Catalyst deactivation due to coexistence of water vapor and other pollutants, e.g., sulfur compounds, is discussed. Future research directions for rational design of catalysts for complete benzene oxidation are provided. Full article

Since actual industrial emissions contain a wide range of volatile organic compounds, studies into the simultaneous catalytic degradation of multi-component VOCs are essential. This work developed Pd-CeZrO_x samples for the simultaneous elimination of benzene and toluene. Firstly, CeZrO_x supports were synthesized using several methods (co-precipitation, CTAB template co-precipitation, and sol–gel method). Pd active species were then added into the 1.0Pd-CeZrO_x samples using the impregnation procedure. XRD, BET, NH₃-TPD, Raman, EPR, XPS, and H₂-TPR were utilized to analyze the as-prepared Pd-CeZrO_x samples. The catalytic performance tests reveal that the performance of 1.0Pd-CeZrO_x-CTAB outperforms that of 1.0Pd-CeZrO_x-PM and 1.0Pd-CeZrO_x-CASG, and 1.0Pd-CeZrO_x-CTAB displays superior catalytic activity for both benzene and toluene oxidation. The improved redox properties, the abundant surface oxygen vacancies, and the surface Pd²⁺ species of the 1.0Pd-CeZrO_x-CTAB sample may be responsible for the simultaneous degradation activity of benzene and toluene. Full article

The removal of benzene, toluene, ethylbenzene, and xylene (BTEX) from air was investigated in two similar biotrickling filters (BTFs) packed with polyurethane (PU) foam, differing in terms of inoculation procedure (BTF A was packed with pre-incubated PU discs, and BTF B was inoculated via the continuous recirculation of a liquid inoculum). The effects of white rot fungi enzyme extract addition and system responses to variable VOC loading, liquid trickling patterns, and pH were studied. Positive effects of both packing incubation and enzyme addition on biotrickling filtration performance were identified. BFF A exhibited a shorter start-up period (approximately 20 days) and lower pressure drop (75 ± 6 mm H₂O) than BTF B (30 days; 86 ± 5 mm H₂O), indicating the superior effects of packing incubation over inoculum circulation during the biotrickling filter start-up. The novel approach of using white rot fungi extracts resulted in fast system recovery and enhanced process performance after the BTF acidification episode. Average BTEX elimination capacities of 28.8 ± 0.4 g/(m³ h) and 23.1 ± 0.4 g/(m³ h) were reached for BTF A and BTF B, respectively. This study presents new strategies for controlling and improving the abatement of BTEX in biotrickling filters. Full article

The primary cause of bottled wine sediment is tartrate crystal precipitation. To prevent this, wines undergo a stabilization process before bottling. The most commonly used method is cold stabilization, which induces the precipitation of tartrate crystals that are then removed, thereby eliminating the excess ions that cause instability in wine. Another approach to tartaric stabilization is using enological stabilizers with a colloid protective effect, which prevents the formation of tartrate crystals. The most commonly used tartaric stabilizers are sodium carboxymethylcellulose (CMC) and metatartaric acid. However, both have drawbacks: they are semi-synthetic products, and metatartaric acid degrades over time, losing its stabilizing effect. This study aims to compare the effects of cold stabilization, stabilization with CMC, and metatartaric acid on the chemical composition, particularly the volatilome, of white, rosé, and red wines. Cold stabilization significantly impacted the wine volatilome, especially in white and rosé wines, by decreasing total alcohols and increasing total esters. It also reduced the color intensity of rosé and red wines by lowering monomeric anthocyanins. In contrast, enological stabilizers had minimal impact on the wines’ phenolic composition, chromatic characteristics, and volatilome. The sensory impact of cold stabilization is complex; it can potentially enhance the aroma of white and rosé wines by increasing ester VOCs and decreasing higher alcohols, but it negatively affects the color of rosé and red wines. Full article

Weakly supervised semantic segmentation (WSSS) aims to segment objects without a heavy burden of dense annotations. Pseudo-masks serve as supervisory information for training segmentation models, which is crucial to the performance of segmentation models. However, the generated pseudo-masks contain significant noisy labels, which leads to poor performance of the segmentation models trained on these pseudo-masks. Few studies address this issue, as these noisy labels remain inevitable even after the pseudo-masks are improved. In this paper, we propose an uncertainty-weight transform module to mitigate the impact of noisy labels on model performance. It is noteworthy that our approach is not aimed at eliminating noisy labels but rather enhancing the robustness of the model to noisy labels. The proposed method adopts a frequency-based approach to estimate pixel uncertainty. Moreover, the uncertainty of pixels is transformed into loss weights through a set of well-designed functions. After dynamically assigning weights, the model allocates attention to each pixel in a significantly differentiated manner. Meanwhile, the impact of noisy labels on model performance is weakened. Experiments validate the effectiveness of the proposed method, achieving state-of-the-art results of 69.3% on PASCAL VOC 2012 and 39.3% on MS COCO 2014, respectively. Full article