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Non-aqueous media dyeing is an important water-saving and salt-free dyeing technology in the textile dyeing industry. In this investigation, a salt-free and alkaline-free dyeing technology was developed for wool fabrics. After padding with reactive dye solution, wool fabric was fixed in a non-aqueous medium at 90 °C for 90 s. After washing, the fixation of reactive dye can achieve more than 98% in a salt-free and alkali-free dyeing environment. The effect of fixing method on the physical properties of wool fabrics was analyzed by TGA, DSC, and XRD. Compared with steam and cold batch fixing method, the fixing process in non-aqueous medium has little effect on the mechanical properties of wool fabrics. The final decomposition temperature of wool fabric dyed with non-aqueous medium was about 46 °C, which was higher than that of the fabric samples dyed by other methods. Moreover, the crystallinity of wool fiber was increased after non-aqueous fixation process. And non-aqueous medium had no influence on the surface morphology of wool fabrics. For non-aqueous medium and steaming fixing methods, there were only hydrolyzed dyes, but some hetero-bifunctional dyes were detected in the cold batching system, indicating that reactive dyes could effectively react with wool fibers in non-aqueous medium and steaming fixing system.

The Aeromonas salmonicida is responsible for causing furunculosis in various fish species. Furunculosis is a ubiquitous disease that affects the aquaculture industry and causes the mass mortality of turbot. Vibrio vulnificus is a pathogen that causes skin ulcers and hemorrhagic septicemia in fish, resulting in significant mortality in aquaculture. In this study, we have established a bivalent inactivated vaccine against A. salmonicida and V. vulnificus with Montanide™ ISA 763 AVG as an adjuvant. This bivalent inactivated vaccine was used to immunize turbot by intraperitoneal injection, and the relevant immune indexes were detected. The results demonstrate that the bivalent inactivated vaccine exhibited a relative percent survival (RPS) of 77% following A. salmonicida and V. vulnificus intraperitoneal challenge. The vaccinated group exhibited higher levels of acid phosphatase activity and lysozyme activity compared to the control group. ELISA results showed a significant increase in serum antibody levels in immunized turbot, which was positively correlated with immunity. In the kidney tissue, related immune genes (TLR5, CD4, MHCI and MHCII) were up-regulated significantly, showing that the vaccine can induce cellular and humoral immune responses in turbot. In conclusion, the bivalent inactivated vaccine against A. salmonicida and V. vulnificus was immunogenic, efficiently preventing turbot from infection, which has the potential to be applied in aquaculture.

A recent development in non-aqueous two-step (disperse and reactive) dyeing technology, minimizes water usage, eliminates the need for salt, and avoids the production of wastewater during the dyeing of polyester/cotton blend fabrics. However, an issue of color staining on cotton fibers during the disperse dyeing process has been observed. To address this issue, the mechanisms of dyeing polyester fibers and staining cotton components by disperse dyes in this process were investigated, using C.I. Disperse Red 177 as an example. It was observed that the adsorption isotherm of the disperse dye on cotton fibers resembled the Freundlich type. Moreover, as the temperature increased, the affinity between the dye and the cotton component decreased, thereby reducing the staining rate of disperse dyes on cotton fibers. High performance liquid chromatography (HPLC) analysis revealed that 22% of disperse dyes absorbed by cotton components were hydrolyzed dyes, while 78% were original dyes. This was attributed to the greater interaction energy between the original dye and the cotton fiber compared to the hydrolyzed dye. The primary interaction between disperse dyes and cotton fibers was identified as dispersion forces. From investigating the uptake, staining and hydrolysis performance of disperse dyes, the study sheds light on the mechanism of color staining behavior of disperse dye on cotton fibers, demonstrating the potential of a one-bath two-step dyeing process in non-aqueous medium dyeing system.

Aeromonas salmonicida is the pathogen underlying furunculosis, causing a septicemic infection that influences both salmonid and non-salmonid fish. Early diagnosis of these contagions is essential for disease surveillance and prevention, so a rapid and sensitive approach is needed. Herein, a recombinase polymerase amplification EXO (RPA-EXO) assay and RPA with a lateral flow dipstick (RPA-LFD) were produced for testing A. salmonicida. The RPA-EXO and RPA-LFD primer sets were devised based on the conserved fragment sequence of the vapA gene. Then, RPA-EXO and RPA-LFD reaction systems were established, and the reaction temperature and time were optimized. After optimization, the RPA-EXO method was capable of testing A. salmonicida within 10 min, and the RPA-LFD method could detect A. salmonicida in only 5 min. The RPA-EXO and RPA-LFD methods exhibited high specificity with no cross-reaction with other strains. To assess sensitivity, a partial vapA gene was cloned, and serial plasmid dilutions were created ranging from 1 × 106 to 1 × 10−1 copies/μL. The detection limit of RPA-EXO was 1 × 102 copies/μL, and the detection limit of RPA-LFD was 1 copy/μL. For spiked turbot tissue samples, the sensitivity detection of A. salmonicida was 1.2 × 101 CFU/mL and 1.2 CFU/mL by RPA-EXO and RPA-LFD, respectively. In comparative analyses of clinical samples, the diagnostic results of RPA-EXO and RPA-LFD were compared with those of the standard conventional PCR test and showed nearly 100% consistency. Therefore, our RPA-EXO and RPA-LFD assays exhibited excellent specificity and sensitivity, which provided two simple, fast and dependable methods to conduct large-scale field investigations of A. salmonicida in resource-limited settings.

In recent years, a new type of Spiroplasma has been found that can cause “tremor disease” of the Chinese mitten crab Eriocheir sinensis. The outbreak of epidemic tremor disease has caused a serious setback in the Chinese mitten crab farming industry, with an incidence rate of more than 30% and mortality rates of 80–100%. Therefore, finding a sensitive method to detect tremor disease in E. sinensis has become a current research focus. In this research, a loop-mediated isothermal amplification detection method coupled with hydroxynaphthol blue dye (LAMP-HNB) was developed and used to rapidly detect Spiroplasma eriocheiris. First, we designed and synthesized specific outer primers, inner primers and loop primers based on the 16S ribosomal RNA gene of S. eriocheiris. Second, the LAMP-HNB detection method for S. eriocheiris was successfully established by screening the primers, adjusting the temperature and time of the reaction, and optimizing the concentrations of Mg2+ and dNTPs. In the specific tests, only samples infected with S. eriocheiris showed positive results, and other infections caused by bacteria and parasites tested negative, proving that the test has high specificity. Moreover, the detection limit was 2.5 × 10–6 ng/µL, indicating high sensitivity. This method for detecting S. eriocheiris provides rapid visual output based on LAMP-HNB detection and is a simple, fast, sensitive, and inexpensive method that can be applied to a wide range of field investigations.

Traditional water-based dyeing of polyester textiles usually generates burdensome processes and a great deal of wastewater, which can no longer meet the green and sustainable developments in the textile dyeing industry. In the silicone waterless dyeing system, polyester textiles can be dyed with disperse dye without water. However, the dyeing performance of polyester textiles is influenced by the dispersant. In this study, the relationship between the properties of dispersants and disperse dyeing performance was studied. When the amount of dispersant NNO (2-Naphthalenesulfonic acid) was 1.2%, the exhaustion of disperse red 177 and the final K/S value of the dyed fabric improved to 94.18% and 14.73, respectively. However, the exhaustion of disperse red 177 was reduced from 90.73% to 82.61%, and the final K/S value of the dyed fabric was decreased from 14.77 to 14.01 when the dosage of MF (Naphthalenesulfonic acid) was 1.2%. Compared with different dyeing systems, the final uptake of disperse red 177 was 93.81% and 94.18% in traditional water-based and silicone waterless dyeing systems and the K/S value of the dyed fabric was almost the same. The washing and rubbing fastness (wet and dry) of the dyed fabric were found to be at a level of 4 or 4–5, and the light fastness of the dyed fabric was 3–4. If only the dispersant was added in the silicone waterless dyeing system, there was no leveling problems on dyed samples. Moreover, the maximum absorption wavelength of disperse red 177 was not changed after adding the dispersant. With an increasing amount of dispersant NNO, the solubility of the dye in the silicone solvent decreased, but it increased with an increasing amount of dispersant MF. In the relationship between dye exhaustion and dye solubility in a silicone waterless dyeing system, the exhaustion of dye was linearly and inversely proportional to the dye solubility. A dispersant with better hydrophilicity can decrease the solubility of the dye in dyeing media, and the dyeing performance of dye is better. Compared with previous studies, the exhaustion of dye was consistent with the ClogP value (hydrophobic constant) of the dyeing accelerant. Therefore, a dispersant with high hydrophilicity can reduce the solubility of dye and improve the exhaustion of disperse dye in a silicone waterless dyeing system. Moreover, the color fastness of the dyed fabric did not change before and after adding the dispersant.

The Aeromonas salmonicida is responsible for causing furunculosis in various fish species. Furunculosis is a ubiquitous disease that affects the aquaculture industry and causes the mass mortality of turbot. Vibrio vulnificus is a pathogen that causes skin ulcers and hemorrhagic septicemia in fish, resulting in significant mortality in aquaculture. In this study, we have established a bivalent inactivated vaccine against A. salmonicida and V. vulnificus with Montanide™ ISA 763 AVG as an adjuvant. This bivalent inactivated vaccine was used to immunize turbot by intraperitoneal injection, and the relevant immune indexes were detected. The results demonstrate that the bivalent inactivated vaccine exhibited a relative percent survival (RPS) of 77% following A. salmonicida and V. vulnificus intraperitoneal challenge. The vaccinated group exhibited higher levels of acid phosphatase activity and lysozyme activity compared to the control group. ELISA results showed a significant increase in serum antibody levels in immunized turbot, which was positively correlated with immunity. In the kidney tissue, related immune genes (TLR5, CD4, MHCI and MHCII) were up-regulated significantly, showing that the vaccine can induce cellular and humoral immune responses in turbot. In conclusion, the bivalent inactivated vaccine against A. salmonicida and V. vulnificus was immunogenic, efficiently preventing turbot from infection, which has the potential to be applied in aquaculture.

This work proposes an LSTM-based sentiment classification model with multi-head attention mechanism and TF-IDF optimization. Through the integration of TF-IDF feature extraction and multi-head attention, the model significantly improves text sentiment analysis performance. Experimental results on public data sets demonstrate that the new method achieves substantial improvements in the most critical metrics like accuracy, recall, and F1-score compared to baseline models. Specifically, the model achieves an accuracy of 80.28% on the test set, which is improved by about 12% in comparison with standard LSTM models. Ablation experiments also support the necessity and necessity of all modules, in which the impact of multi-head attention is greatest to performance improvement. This research provides a proper approach to sentiment analysis, which can be utilized in public opinion monitoring, product recommendation, etc.

In this paper, we propose an optimized Transformer model that integrates Bayesian algorithms with a Bidirectional Gated Recurrent Unit (BiGRU), and apply it to fake news classification for the first time. First, we employ the TF-IDF method to extract features from news texts and transform them into numeric representations to facilitate subsequent machine learning tasks. Two sets of experiments are then conducted for fake news detection and classification: one using a Transformer model optimized only with BiGRU, and the other incorporating Bayesian algorithms into the BiGRU-based Transformer. Experimental results show that the BiGRU-optimized Transformer achieves 100% accuracy on the training set and 99.67% on the test set, while the addition of the Bayesian algorithm maintains 100% accuracy on the training set and slightly improves test-set accuracy to 99.73%. This indicates that the Bayesian algorithm boosts model accuracy by 0.06%, further enhancing the detection capability for fake news. Moreover, the proposed algorithm converges rapidly at around the 10th training epoch with accuracy nearing 100%, demonstrating both its effectiveness and its fast classification ability. Overall, the optimized Transformer model, enhanced by the Bayesian algorithm and BiGRU, exhibits excellent continuous learning and detection performance, offering a robust technical means to combat the spread of fake news in the current era of information overload.

The proliferation of misinformation on social media has raised significant societal concerns, necessitating robust detection mechanisms. Large Language Models such as GPT-4 and LLaMA2 have been envisioned as possible tools for detecting misinformation based on their advanced natural language understanding and reasoning capabilities. This paper conducts a comparison of LLM-based approaches to detecting misinformation between text-based, multimodal, and agentic approaches. We evaluate the effectiveness of fine-tuned models, zero-shot learning, and systematic fact-checking mechanisms in detecting misinformation across different topic domains like public health, politics, and finance. We also discuss scalability, generalizability, and explainability of the models and recognize key challenges such as hallucination, adversarial attacks on misinformation, and computational resources. Our findings point towards the importance of hybrid approaches that pair structured verification protocols with adaptive learning techniques to enhance detection accuracy and explainability. The paper closes by suggesting potential avenues of future work, including real-time tracking of misinformation, federated learning, and cross-platform detection models.