Research on emergency logistics information traceability model and resource optimization allocation strategies based on consortium blockchain.

In response to increasingly complex social emergencies, this study realizes the optimization of logistics information flow and resource allocation by constructing the Emergency logistics information Traceability model (ELITM-CBT) based on alliance blockchain technology. Using the decentralized, data immutable and transparent characteristics of alliance blockchain technology, this research breaks through the limitations of traditional emergency logistics models and improves the accuracy and efficiency of information management. Combined with the hybrid genetic simulated Annealing algorithm (HGASA), the improved model shows significant advantages in emergency logistics scenarios, especially in terms of total transportation time, total cost, and fairness of resource allocation. The simulation results verify the high efficiency of the model in terms of timeliness of emergency response and accuracy of resource allocation, and provide innovative theoretical support and practical scheme for the field of emergency logistics. Future research will explore more efficient consensus mechanisms, and combine big data and artificial intelligence technology to further improve the performance and adaptability of emergency logistics systems.

Alcohol-induced gut microbiome dysbiosis enhances the colonization of Klebsiella pneumoniae on the mouse intestinal tract.

Chronic alcohol consumption, an important risk factor for diseases and deaths, can cause intestinal microbiota dysbiosis and increase the infection of some opportunistic pathogens. However, the current studies on the effects of alcohol-induced intestinal microbiota dysbiosis on gut colonization of Klebsiella pneumoniae are still scarce. In the present study, we established a binge-on-chronic alcohol model in mice to identify the characteristics of alcohol-induced intestinal microbiome and metabolite dysbiosis using multi-omics and explored the effects and potential mechanisms of these dysbioses on the intestinal colonization of K. pneumoniae. The results show that chronic alcohol consumption alters the diversity and composition of gut microbiota (including bacteria and fungi), decreases the complexity of the interaction between intestinal bacteria and fungi, disturbs the gut metabolites, and promotes the colonization of K. pneumoniae on the gut of mice. The relevance analyses find that alcohol-induced gut microbiome dysbiosis has a strong correlation with the alteration of secondary bile acids. In vitro results suggest that the high concentration of lithocholic acid, a secondary bile acid, could significantly inhibit the proliferation of K. pneumoniae, and the adhesion of K. pneumoniae to Caco-2 cells. Our results indicate that alcohol-induced microbiome dysbiosis contributes to decreased levels of secondary bile acids, which was one of the main reasons affecting the colonization of K. pneumoniae in mice's intestines. Some secondary bile acids (e.g., lithocholic acid) might be a potential drug to prevent the colonization and spread of K. pneumoniae.IMPORTANCEAlcohol is one of the most commonly misused substances in our lives. However, long-term heavy drinking will increase the colonization of some opportunistic pathogens (e.g., Klebsiella pneumoniae) in the body. Here, we revealed that binge-on-chronic alcohol consumption disrupted the balance between gut bacteria and fungi, induced the gut microbiome and metabolites dysbiosis, and promoted the colonization of K. pneumoniae in the intestine of mice. In particular, alcohol-taking disrupted intestinal bile acid metabolism and reduced the lithocholic acid concentration. However, a high concentration of lithocholic acid can protect against intestinal colonization of K. pneumoniae by inhabiting the bacterial growth and adhesion to the host cell. Hence, regulating the balance of gut microbiota and intestinal bile acid metabolism may be a potential strategy for reducing the risk of K. pneumoniae infection and spread.

Relationship between sphingolipids-mediated neuroinflammation and alcohol use disorder.

BACKGROUND: Alcohol use disorder is a chronic recurrent encephalopathy, and its pathogenesis has not been fully understood. Among possible explanations, neuroinflammation caused by the disorders of brain central immune signaling has been identified as one possible mechanism of alcohol use disorder. As the basic components of cells and important bioactive molecules, sphingolipids are essential in regulating many cellular activities. Recent studies have shown that sphingolipids-mediated neuroinflammation may be involved in the development of alcohol use disorder. METHODS: PubMed databases were searched for literature on sphingolipids and alcohol use disorder (alcohol abuse, alcohol addiction, alcohol dependence, and alcohol misuse) including evidence of the relationship between sphingolipids-mediated neuroinflammation and alcohol use disorder (formation, withdrawal, treatment). RESULTS: Disorders of sphingolipid metabolism, including the different types of sphingolipids and regulatory enzyme activity, have been found in patients with alcohol use disorder as well as animal models, which in turn cause neuro-inflammation in the central nervous system. Thus, these disorders may also be an important mechanism in the development of alcohol use disorder in patients. In addition, different sphingolipids may have different or even reverse effects on alcohol use disorder. CONCLUSIONS: The sphingolipids-mediated neuroinflammation plays an important role in the development of alcohol use disorder. This review proposes a potential approach to prevent and treat alcohol use disorders by manipulating sphingolipid metabolism.

Safety and effectiveness of lurasidone in the treatment of Chinese schizophrenia patients: An interim analysis of post-marketing surveillance.

BACKGROUND: Schizophrenia is a psychiatric disorder characterized by chronic or recurrent symptoms. Lurasidone was licensed in China in 2019 for the treatment of adult schizophrenia in adults with a maximum dose of 80 mg/d. However, post-market surveillance (PMS) with an adequate sample size is required for further validation of the drug's safety profile and effectiveness. AIM: To conduct PMS in real-world clinical settings and evaluate the safety and effectiveness of lurasidone in the Chinese population. METHODS: A prospective, multicenter, open-label, 12-wk surveillance was conducted in mainland China. All patients with schizophrenia from 10 sites who had begun medication with lurasidone between September 2019 and August 2022 were eligible for enrollment. Safety assessments included adverse events (AEs), adverse drug reactions (ADRs), extrapyramidal symptoms (EPS), akathisia, use of EPS drugs, weight gain, and laboratory values as metabolic parameters and the QTc interval. The effectiveness was assessed using the brief psychiatric rating scale (BPRS) from baseline to the end of treatment. RESULTS: A total of 965 patients were enrolled in the full analysis set and 894 in the safety set in this interim analysis. The average daily dose was 61.7 ± 19.08 mg (mean ± SD) during the treatment. AEs and ADRs were experienced by 101 patients (11.3%) and 78 patients (8.7%), respectively, which were mostly mild. EPS occurred in 25 individuals with a 2.8% incidence, including akathisia in 20 individuals (2.2%). Moreover, 59 patients received drugs for treating EPS during the treatment, with an incidence of 6.6% which dropped to 5.4% at the end of the treatment. The average weight change was 0.20 ± 2.36 kg (P = 0.01687) with 0.8% of patients showing a weight gain of ≥ 7% at week 12 compared with that at the baseline. The mean values of metabolic parameters and the QTc interval at baseline and week 12 were within normal ranges. The mean changes in total BPRS scores were -8.9 ± 9.76 (n = 959), -13.5 ± 12.29 (n = 959), and -16.8 ± 13.97 (n = 959) after 2/4, 6/8, and 12 wk, respectively (P < 0.001 for each visit compared with the baseline) using the last-observation-carried-forward method. CONCLUSION: The interim analysis of the PMS of adult patients with schizophrenia demonstrate the safety and effectiveness of lurasidone in the Chinese population. No new safety or efficacy concerns were identified.

Effects of Different Die Metals on the Performance and Friction and Wear of Composite Materials during the Extrusion Process.

Extrusion technology is widely utilized in the rubber processing industry, with the extruder serving as the core equipment. As mixed rubber enters the extruder, it undergoes conveyance and plasticization, ultimately forming specific shapes and dimensions upon extrusion. The extruder head is a crucial component, playing a key role in achieving the final product's required size and shape. Factors such as its structure, materials, and manufacturing processes significantly impact the efficiency, product quality, and sustainability of the extrusion process. However, prolonged operation leads to severe wear of the extruder head, adversely affecting rubber product quality. Additionally, extruder head processing poses challenges, with maintenance and repair being complex procedures. Therefore, exploring a wear-resistant, long-lasting metal material for the extruder head without compromising mixed rubber performance is essential. This study focuses on severely worn extruder head metal materials, comparing wear levels after friction with STELLITE 6 alloy, Hastelloy C-276 alloy, 38CrMoAlA, and tungsten carbide with composite rubber. Results show that compared to the NR/BR composite material after Hastelloy C-276 alloy friction, rubber Payne effect increased by 4.4% (38CrMoAl), 3.2% (STELLITE 6), and 4.6% (tungsten carbide). Similarly, rubber dispersion decreased by 9.4% (38CrMoAl), 4.7% (STELLITE 6), and 9.8% (tungsten carbide). Rolling resistance increased by 18.1% (38CrMoAl), 16% (STELLITE 6), and 23.4% (tungsten carbide). Friction coefficient increased by 3.5% (38CrMoAl), 2.8% (STELLITE 6), and 4.3% (tungsten carbide). Wear volume increased by 39.3% (38CrMoAl), 45.3% (STELLITE 6), and 48.9% (tungsten carbide). Specifically, using Hastelloy C-276 alloy as the extruder head metal material yields the best NR/BR composite material dispersion, highest ten times tear strength, excellent anti-wet skid resistance, and minimum rolling resistance. Conversely, using the other alloys results in varying reductions in the physical and mechanical properties of NR/BR composite materials. This research is crucial for improving rubber product quality and extending extruder head lifespan.

Effects of virtual reality-based cue exposure therapy on craving and physiological responses in alcohol-dependent patients-a randomised controlled trial.

BACKGROUND: Cue exposure therapy is used to treat alcohol dependence. However, its effectiveness is controversial due to the limitations of the clinical treatment setting. Virtual reality technology may improve the therapeutic effect. The aim of this study is to explore whether virtual reality-based cue exposure therapy can reduce the psychological craving and physiological responses of patients with alcohol dependence. METHODS: Forty-four male alcohol-dependent patients were recruited and divided into the study group (n = 23) and the control group (n = 21) according to a random number table. The control group received only conventional clinical treatment for alcohol dependence. The study group received conventional clinical treatment with the addition of VR cue exposure (treatment). The primary outcome was to assess psychological craving and physiological responses to cues of patients before and after treatment. RESULTS: After virtual reality-based cue exposure therapy, the changes in VAS and heart rate before and after cue exposure in the study group were significantly lower than those in the control group (P < 0.05), while the changes in skin conductance and respiration between the study group and the control group were not significantly different (P > 0.05). The changes in VAS and heart rate before and after cue exposure in the study group were significantly lower than those before treatment (P < 0.05), while the changes in skin conductance and respiration were not significantly different from those before treatment (P > 0.05). The changes in VAS, heart rate, skin conductance and respiration before and after cue exposure in the control group were not significantly different from those before treatment (P > 0.05). CONCLUSION: Virtual reality-based cue exposure therapy can reduce the psychological craving and part of the physiological responses of alcohol-dependent patients during cue exposure in the short term and may be helpful in the treatment of alcohol dependence. TRIAL REGISTRATION: The study protocol was registered at the China Clinical Trial Registry on 26/02/2021 ( www.chictr.org.cn ; ChiCTR ID: ChiCTR2100043680).

Intestinal microbiome dysbiosis in alcohol-dependent patients and its effect on rat behaviors.

IMPORTANCE: Intestinal microbiome dysbiosis is associated with psychiatric disease through the "microbiota-gut-brain" axis. Here, we revealed that there was obvious intestinal microbiome (including bacterial and fungal) dysbiosis in alcohol-dependent patients. Alcohol consumption seriously disturbs the gut equilibrium between bacteria and fungi, reduces the interactions among bacterial-fungal trans-kingdom, and increases intestinal permeability. Gut microbiota should be considered as a whole to study the development of alcohol dependence. The gut microbiome of alcohol-dependent patients increased the anxiety- and depression-like behavior in rats. The gut microbiota dysbiosis may promote the development of alcohol dependence by regulating the endogenous cholecystokinin (CCK) and related receptors. Hence, regulating the balance of gut microbiota and the endogenous CCK may be a potential strategy for reducing the risk of relapse in alcohol addiction patients.

The α1 adrenoceptor antagonist prazosin potentiates morphine induced conditioned place preference in rats.

The norepinephrine (NE) system is involved in pathways that regulate morphine addiction. Here, we investigated the role of α1 adrenoceptor in the ventrolateral orbital cortex (VLO) of rats with repeated morphine treatment and underlying molecular mechanisms. The rewarding properties of morphine were assessed by the conditioned place preference (CPP) paradigm. Prazosin, an α1 adrenoceptor antagonist, was microinjected into the VLO. The expression of α1 adrenoceptor, p-CaMKII/CaMKII, CRTC1, BDNF and PSD95 in the VLO were determined by immunohistochemistry or western blotting. Neurotransmitter NE in the VLO and inflammatory factors in serum were detected separately through high-performance liquid chromatography and enzyme-linked immunosorbent assay. Our experimental results showed that repeated morphine administration induced stable CPP and prazosin promoted the morphine-induced CPP. Microinjection of prazosin in the VLO not only blocked the activity of α1 adrenoceptor, decreased CaMKII phosphorylation and CRTC1, which eventually resulted in a regression of synaptic plasticity-related proteins, but also was accompanied by significantly decreasing of NE in the VLO and increasing of inflammatory cytokines in peripheral blood. These findings suggested that prazosin potentiates the addictive effects of morphine. The effect of increased CPP through reducing α1 adrenoceptor and NE was associated with the CaMKII-CRTC1 pathway and synaptic plasticity-related proteins in the VLO and inflammatory cytokines in the peripheral blood. The NE system may therefore be an underlying therapeutic target in morphine addiction. Additionally, we believe that the clinical use of prazosin in hypertensive patients with morphine abuse may be a potential risk because of its reinforcing effect on addiction.

The efficacy of virtual reality exposure therapy for the treatment of alcohol use disorder among adult males: a randomized controlled trial comparing with acceptance and commitment therapy and treatment as usual.

Background: This multicenter, three-armed, parallel, single-blind randomized controlled trial (RCT) primarily aims to compare the efficacy of virtual reality exposure therapy (VRET) with that of acceptance and commitment therapy (ACT) and treatment as usual (TAU) to depreciate the degree of alcohol craving among alcohol use disorder patients who have undergone in-patient detoxification across four timelines (t0 = baseline prior to intervention, t1 = 4 weeks after baseline, t2 = 12 weeks after baseline, and t3 = 24 weeks after baseline). The secondary aims of this RCT are to compare the efficacy of VRET with that of ACT and TAU to alleviate the severity of alcohol use disorder, dissipate comorbid depressive and anxiety symptoms, and normalize event-related potential (ERP) in electroencephalogram (EEG) monitoring across the four timelines. Methods: Initially, after 2 weeks of in-patient detoxification, 120 patients with alcohol use disorder will be randomized into three groups (VRET, ACT, and TAU control groups) via stratified permuted block randomization in a 1:1:1 ratio. Baseline assessment (t0) commences, whereby all the participants will be administered with sociodemographic, clinical, and alcohol use characteristics questionnaire, such as Alcohol Use Disorder Identification Test (AUDIT), Penn Alcohol Craving Scale (PACS), Hamilton Anxiety Rating Scale (HAM-A), and Hamilton Depression Rating Scale (HAM-D), while event-related potential (ERP) detection in electroencephalogram (EEG) will also be carried out. Then, 4 weeks of VRET, ACT, and non-therapeutic supportive activities will be conducted in the three respective groups. For the subsequent three assessment timelines (t1, t2, and t3), the alcohol use characteristic questionnaire, such as AUDIT, PACS, HAM-D, HAM-A, and ERP monitoring, will be re-administered to all participants. Discussion: As data on the effects of non-pharmacological interventions, such as VRET and ACT, on the treatment of alcohol craving and preventing relapse in alcohol use disorder are lacking, this RCT fills the research gap by providing these important data to treating clinicians. If proven efficacious, the efficacy of VRET and ACT for the treatment of other substance use disorders should also be investigated in future. Clinical trial registration: NCT05841823 (ClinicalTrials.gov).

Recognition of opinion leaders in blockchain-based social networks by structural information and content contribution.

Exploring the influence of social network users in the blockchain environment and identifying opinion leaders can help understand the information dissemination characteristics of blockchain social networks, direct the discovery of quality content, and avoid the spread of rumors. Members of blockchain-based social networks are given new responsibilities by token awards and consensus voting, which alters how users connect to the network and engage with one another. Based on blockchain theory and the relevant theories of opinion leaders in social networks, this article combines structural information and content contributions to identify opinion leaders. Firstly, user influence indicators are defined from the perspective of network structure and behavioral characteristics of user contributions. Then, ECWM is constructed, which combines the entropy weight method and the criteria importance through intercriteria correlation (CRITIC) weighting method to address the correlation and diversity among indicators. Furthermore, an improved Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), called ECWM-TOPSIS, is proposed to identify opinion leaders in blockchain social networks. Moreover, to verify the effectiveness of the method, we conducted a comparative analysis of the proposed algorithm on the blockchain social platform Steemit by using two different methods (voting score and forwarding rate). The results show that ECWM-TOPSIS produces significantly higher performance than other methods for all selected top N opinion leaders.

Acclimatizing waste activated sludge in a thermophilic anaerobic fixed-bed biofilm reactor to maximize biogas production for food waste treatment at high organic loading rates.

Thermophilic anaerobic digestion (TAD) provides a promising solution for sustainable high-strength waste treatment due to its enhanced methane-rich biogas recovery. However, high organic loading rates (OLR) exceeding 3.0 kgCOD/m3/day and short hydraulic retention times (HRT) below 10 days pose challenges in waste-to-energy conversion during TAD, stemming from volatile fatty acids (VFAs) accumulation and methanogenesis failure. In this study, we implemented a stepwise strategy for acclimatizing waste activated sludge (WAS) in a thermophilic anaerobic fixed-bed biofilm reactor (TA-FBBR) to optimize methanogen populations, thereby enhancing waste-to-energy efficiencies under elevated OLRs in food waste treatment. Results showed that following stepwise acclimatization, the TA-FBBR achieved stable methane production of approximately 5.8 L/L-reactor/day at an ultrahigh OLR of ∼20 kgCOD/m3/day and ∼15 kgVS/m3/day at 6-day HRT in food waste treatment. The average methane yield reached 0.45 m3/kgCODremoval, attaining the theoretical production in TAD. Moreover, VFA concentrations were stabilized below 1000 mg/L at the ultrahigh OLR under 6-day HRT, while maintaining an acetate/propionate ratio of > 1.8 and a VFA/TAK ratio of < 0.3 serving as effective indicators of system stability and methane yield potential. The microbial community analysis revealed that the WAS acclimatization strategy fostered the microbial diversity and abundance of Methanothermobacter and Methanosarcina. Methanosarcina in the biofilm were observed to be twice as abundant as Methanothermobacter, indicating a potential preference for biofilm existence among methanogens. The findings demonstrated an effective strategy, specifically the stepwise acclimatization of WAS in a thermophilic fixed-bed biofilm reactor, to enhance the food waste treatment performance at high OLRs, contributing valuable mechanistic and technical insights for future sustainable high-strength waste management.

Serum metabolomics analysis in patients with alcohol dependence.

Objective: Alcohol dependence (AD) is a chronic recurrent mental disease caused by long-term drinking. It is one of the most prevalent public health problems. However, AD diagnosis lacks objective biomarkers. This study was aimed to shed some light on potential biomarkers of AD patients by investigating the serum metabolomics profiles of AD patients and the controls. Methods: Liquid chromatography-mass spectrometry (LC-MS) was used to detect the serum metabolites of 29 AD patients (AD) and 28 controls. Six samples were set aside as the validation set (Control: n = 3; AD group: n = 3), and the remaining were used as the training set (Control: n = 26; AD group: n = 25). Principal component analysis (PCA) and partial least squares discriminant analysis (PCA-DA) were performed to analyze the training set samples. The metabolic pathways were analyzed using the MetPA database. The signal pathways with pathway impact >0.2, value of p <0.05, and FDR < 0.05 were selected. From the screened pathways, the metabolites whose levels changed by at least 3-fold were screened. The metabolites with no numerical overlap in their concentrations in the AD and the control groups were screened out and verified with the validation set. Results: The serum metabolomic profiles of the control and the AD groups were significantly different. We identified six significantly altered metabolic signal pathways, including protein digestion and absorption; alanine, aspartate, and glutamate metabolism; arginine biosynthesis; linoleic acid metabolism; butanoate metabolism; and GABAergic synapse. In these six signal pathways, the levels of 28 metabolites were found to be significantly altered. Of these, the alterations of 11 metabolites changed by at least 3-fold compared to the control group. Of these 11 metabolites, those with no numerical overlap in their concentrations between the AD and the control groups were GABA, 4-hydroxybutanoic acid, L-glutamic acid, citric acid and L-glutamine. Conclusion: The metabolite profile of the AD group was significantly different from that of the control group. GABA, 4-hydroxybutanoic acid, L-glutamic acid, citric acid, and L-glutamine could be used as potential diagnostic markers for AD.

All-in-one aerial image enhancement network for forest scenes.

Drone monitoring plays an irreplaceable and significant role in forest firefighting due to its characteristics of wide-range observation and real-time messaging. However, aerial images are often susceptible to different degradation problems before performing high-level visual tasks including but not limited to smoke detection, fire classification, and regional localization. Recently, the majority of image enhancement methods are centered around particular types of degradation, necessitating the memory unit to accommodate different models for distinct scenarios in practical applications. Furthermore, such a paradigm requires wasted computational and storage resources to determine the type of degradation, making it difficult to meet the real-time and lightweight requirements of real-world scenarios. In this paper, we propose an All-in-one Image Enhancement Network (AIENet) that can restore various degraded images in one network. Specifically, we design a new multi-scale receptive field image enhancement block, which can better reconstruct high-resolution details of target regions of different sizes. In particular, this plug-and-play module enables it to be embedded in any learning-based model. And it has better flexibility and generalization in practical applications. This paper takes three challenging image enhancement tasks encountered in drone monitoring as examples, whereby we conduct task-specific and all-in-one image enhancement experiments on a synthetic forest dataset. The results show that the proposed AIENet outperforms the state-of-the-art image enhancement algorithms quantitatively and qualitatively. Furthermore, extra experiments on high-level vision detection also show the promising performance of our method compared with some recent baselines.

Study on synergistic pyrolysis and kinetics of mixed plastics based on spent fluid-catalytic-cracking catalyst.

At present, disposable plastic products such as plastic packaging are very common in our daily life. These products are extremely easy to cause serious damage to the soil and marine environment due to their short design and service life, difficulties in degradation, or long degradation cycles. Thermochemical method (pyrolysis or catalytic pyrolysis) is an efficient and environmentally friendly way to treat plastic waste. In order to further reduce the energy consumption of plastic pyrolysis and improve the recycling rate of spent fluid catalytic cracking (FCC) catalysts, we adopt the "waste-to-waste" approach to apply the spent FCC catalysts as catalysts in the catalytic pyrolysis of plastics, exploring the pyrolysis characteristics, kinetic parameters, and synergistic effects between different typical plastics (polypropylene, low-density polyethylene, polystyrene). The experimental results show that the spent FCC catalysts used in the catalytic pyrolysis of plastics are beneficial to reduce the overall pyrolysis temperature and activation energy, in which the maximum weight loss temperature decreases by about 12 â„ƒ and the activation energy decreases by about 13%. The activity of spent FCC catalysts is improved after modification by microwave and ultrasonic, which further improve the catalytic efficiency and reduce the energy consumption of pyrolysis. The co-pyrolysis of mixed plastics is dominated by positive synergistic effect, which is conducive to improving the thermal degradation rate and shortening the pyrolysis time. This study provides relevant theoretical support for the resource application of spent FCC catalysts and "waste-to-waste" treatment of plastic waste.

Study on the Mechanism and Experiment of Styrene Butadiene Rubber Reinforcement by Spent Fluid Catalytic Cracking Catalyst.

Spent Fluid Catalytic Cracking (FCC) Catalyst is a major waste in the field of the petroleum processing field, with a large output and serious pollution. The treatment cost of these waste catalysts is high, and how to achieve their efficient reuse has become a key topic of research at home and abroad. To this end, this paper conducted a mechanistic and experimental study on the replacement of some carbon blacks by spent FCC catalysts for the preparation of rubber products and explored the synergistic reinforcing effect of spent catalysts and carbon blacks, in order to extend the reuse methods of spent catalysts and reduce the pollution caused by them to the environment. The experimental results demonstrated that the filler dispersion and distribution in the compound are more uniform after replacing the carbon black with modified spent FCC catalysts. The crosslinking density of rubber increases, the Payne effect is decreased, and the dynamic mechanical properties and aging resistance are improved. When the number of replacement parts reached 15, the comprehensive performance of the rubber composites remained the same as that of the control group. In this paper, the spent FCC catalysts modified by the physical method instead of the carbon-black-filled SBR can not only improve the performance of rubber products, but also can provide basic technical and theoretical support to realize the recycling of spent FCC catalysts and reduce the environmental pressure. The feasibility of preparing rubber composites by spent catalysts is also verified.

Semi-supervised wildfire smoke detection based on smoke-aware consistency.

The semi-transparency property of smoke integrates it highly with the background contextual information in the image, which results in great visual differences in different areas. In addition, the limited annotation of smoke images from real forest scenarios brings more challenges for model training. In this paper, we design a semi-supervised learning strategy, named smoke-aware consistency (SAC), to maintain pixel and context perceptual consistency in different backgrounds. Furthermore, we propose a smoke detection strategy with triple classification assistance for smoke and smoke-like object discrimination. Finally, we simplified the LFNet fire-smoke detection network to LFNet-v2, due to the proposed SAC and triple classification assistance that can perform the functions of some specific module. The extensive experiments validate that the proposed method significantly outperforms state-of-the-art object detection algorithms on wildfire smoke datasets and achieves satisfactory performance under challenging weather conditions.

Enhanced nutrient removal and bioenergy production in microalgal photobioreactor following anaerobic membrane bioreactor for decarbonized wastewater treatment.

This study investigated the nutrient removal, decarbonization potentials, and bioenergy production (i.e., algal biomass and biogas) between a membrane photobioreactor (MPBR) and a sequencing photobioreactor (SPBR) as the post-treatment process of an anaerobic membrane bioreactor (AnMBR) for municipal wastewater treatment. All photobioreactors without aeration showed favourable performance on AnMBR effluent polishing and bioenergy production. In comparison, MPBRs achieved higher removal efficiencies with 98.4 %-99.1 % NH4-N and 74.8 %-88.4 % PO4-P removal compared to the SPBRs with 41.1 %-82.0 % NH4-N and 39.6 %-72.9 % PO4-P removal. MPBRs enhanced more nutrient utilization (24.9-49.3 g(N)/(m3·d) and 3.4-8.1 g(P)/(m3·d)) and CO2 assimilation (22.9-43.4 g(C)/(m3·d)), and concentrated more microalgae with 1.58-1.98 g/L higher than the SPBRs. Moreover, the MPBR effectively upgraded the biogas from AnMBR with superior methane percentage of 89.4 %-93.4 % due to its better CO2 biofixation. The MPBR, with better carbon, nitrogen and phosphorous removal and bioenergy production, following AnMBR is an attractive decarbonized technology for future sustainable wastewater treatment.

Effect of Wet Mixing on Properties of Radial-Orientation Basalt Fiber-Reinforced Rubber Compounds.

The effects of wet mixing and traditional mixing on the properties of radial-orientation basalt fiber-reinforced rubber products were studied through experiments. The results show that compared with traditional mixing, the basalt fibers under the wet mixing conditions can more effectively enhance the physical and mechanical properties of composites. The properties of the composites, such as carbon black dispersion, filler dispersion, rolling resistance and wet-sliding resistance, were the best after the latex and carbon black were premixed and then mixed by a mixer. Through extrusion experiments with the developed short-fiber radial-orientation die, it can be found that the fluidity of composites after extrusion is enhanced. Through analysis utilizing an electron microscope, it is shown that when the BFs added with KH550 (3-Aminopropyltriethoxysilane) were modified by KH560 ((3-Glycidyloxypropyl)trimethoxysilane), the interface layers of BF (basalt fiber)-KH560-NR and BF-KH550-NR were formed, which improves the adhesion between BFs and the rubber matrix. Qualitative characterization experiments on the orientation direction of the vulcanized composites were carried out through the experiments; that is, the qualitative characterization experiments on the segmented cutting and vulcanization of the composites in the radial direction showed that the short-fiber radial-orientation die could greatly improve the radial orientation degree of the short fibers in the radial direction. After adding KH560, the performance of the composites reinforced by the short fibers was improved to a certain extent compared with those without KH560. By adding DZ (N,N-Dicyclohexyl-2-benzothiazolsulfene amide) and CTP(cytidine triphosphate disodium) into the vulcanization system, the curing process of compounds in mixing and extrusion was delayed and the scorching resistance of short-fiber-reinforced composites was enhanced. Under the same conditions, the properties of the compounds after extrusion were greatly improved compared with those without extrusion.

Effect of Interfacial Lubrication between Rubber and Metal on Reducing Mixer Chamber Wall Wear in Mixing Process.

This paper focused on adding a suitable lubrication effect at the interface between the rubber and mixer chamber wall on reducing the surface wear rate of the mixer chamber wall. In the research process, the contact model between the compound and internal mixer chamber wall was simplified to the pin-on-disc experimental model. The experimental results showed that the friction coefficient and the metal surface wear rate of the mixer chamber were reduced (by approximately 24%) by adding an appropriate amount of antifriction agent in the mixing process, while the comprehensive properties of the compound showed an improvement trend. By analyzing the surface elements of the rubber compound, the MoS2 with an anti-wear effect on the surface of the rubber compound can form a lubrication mechanism between the rubber, filler, and mixer chamber wall metal. Combined with the result of the comprehensive properties of rubber, which showed that although the appropriate amount of antifriction agent formed a lubrication protection mechanism between the rubber and the inner mixing chamber wall, the mechanism did not affect the friction behavior required for mixing. The study can effectively enhance the effective friction mixing and reduce the wear and power consumption of the mixing chamber caused by excess friction during the mixing process.

Influence of the Synergistic Effect of Multi-Walled Carbon Nanotubes and Carbon Fibers in the Rubber Matrix on the Friction and Wear of Metals during the Mixing Process.

As a piece of high-intensity running equipment, the wear of an internal mixer determines the quality of rubber and its life. In general, the wear of an internal mixer is caused by the friction between the rubber and metal during the mixing process, and the most severe wear position is the end face of the equipment. In this paper, a mixture of multi-walled carbon nanotubes (MWCNTs) and carbon fibers (CFs) are added to rubber by mechanical compounding to obtain MWCNT/CF/carbon black (CB) composites. By investigating the synergistic mechanism of MWCNTs and CFs, we analyze the effect of the MWCNT/CF ratio on the frictional wear of metal on the end face of the internal mixer. At the microscopic level, MWCNTs and CFs form a spatial meshwork with CB particles through synergistic interactions. The CB particles can be adsorbed on the spatial meshwork to promote the dispersion of CB particles. In addition, the formation of oil film can be slowed down due to the spatial meshwork, which could hinder the spillage of aromatic oil. Meanwhile, the spatial meshwork serves as a physical isolation layer between the rubber and metal to reduce friction. Therefore, it dramatically impacts the dispersion degree of CB particles, the friction coefficient, the roughness of the surface, and the wear of metal. It shows that the synergistic effect of MWCNT/CF and CB particles is best when the CF content of the rubber matrix is 5 phr, showing the most stable spatial network structure, the best dispersion of CB particles, and minor wear on the end face of the internal mixer.