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In this study, a 10% KOH solution was used to decompose the meat, skin, and digestive system of mullets. The factors in each experiment are as follows: 1) VKOH:mmeat is 10/1 (mL·g–1), incubated at 25 °C for 72 h; VKOH:mskin is 15/1 (mL·g–1), incubated at 40 °C for 72 h; VKOH:mdigestive system is 20/1 (mL·g–1), incubated at 40 °C for 72 h. The actual sample images display microplastics in the surveyed parts of the mullets with different shapes and colours.

A conjugated molecular triad based on pyrene and 9,9-dioctyl-9H-fluorene has been successfully synthesised via the Suzuki cross-coupling reaction with yield of 48%. In this polymerization, the Pd(PPh3)4 has been used as the catalytic in the presence of K2CO3 as base in a mixture of toluene/ethanol/H2O at 80oC under N2 . The chemical structures of the conjugated molecules were determined via Fourier-transform infrared spectroscopy (FTIR) and nuclear magnetic resonance (1H-NMR) that proved the chemical structure of 1,1’-(9,9-dioctyl-9H-fluorene-2,7-diyl)dipyrene. The optical properties of the molecules were investigated via UV-Vis in different concentration that exhibited the maximum absorption of 340 nm. The conjugated molecular triad also have been investigated by fluorescence spectroscopy that showed a mission peak at 475 nm under the excitation of 350 nm of wavelength. In addition, the 1,1’-(9,9-dioctyl-9H-fluorene-2,7-diyl)dipyrene exhibited a fluorescence quenching as a chemosensor in the presence of mesotrione, a nitroaromatic herbicide. This phenomenon proved the efficient energy and electron transfer from a photo-excited pyrene moiety to the ground state electron-deficient mesotrione as a result of Forster resonance energy transfer (FRET) mechanism.

This paper is devoted to analyzing the regularity in time and polynomial decay of solutions for a class of fractional reaction–diffusion equations (FrRDEs) involving delays and nonlinear perturbations in a bounded domain of Rd$\operatorname{\mathbf {R}}^{d}$. By establishing some regularity estimates in both time and space variables of the resolvent operator, we present results on the Hölder and C1$C^{1}$‐regularity in time of solutions for both time‐delayed linear and semilinear FrRDEs. Based on the aforementioned results, we study the existence, uniqueness, and regularity of solutions to an identification problem subjected to the delay FrRDE and the additional observations given at final time. Furthermore, under quite reasonable assumptions on nonlinear perturbations and the technique of measure of noncompactness, the existence of decay solutions with polynomial rates for the problem under consideration is shown. [ABSTRACT FROM AUTHOR]

Previous studies on horseshoe bats (Rhinolophus spp.) have described many coronaviruses related to SARS‐CoV (SARSCoVr) in China and only a few coronaviruses related to SARS‐CoV‐2 (SARSCoV2r) in Yunnan (southern China), Cambodia, Laos and Thailand. Here, we report the results of several field missions carried out in 2017, 2021 and 2022 across Vietnam during which 1218 horseshoe bats were sampled from 19 locations. Sarbecoviruses were detected in 11% of faecal RNA extracts, with much more positives among Rhinolophus thomasi (46%). We assembled 38 Sarbecovirus genomes, including 32 SARSCoVr, four SARSCoV2r, and two recombinants of SARSCoVr and SARSCoV2r (RecSar), one showing a Spike protein very similar to SARS‐CoV‐2. We detected a bat co‐infected with four coronaviruses, including two sarbecoviruses. Our analyses revealed that Sarbecovirus genomes evolve in Vietnam under strong geographical and host constraints. First, we found evidence for a deep separation between viruses from northern Vietnam and those from central and southern Vietnam. Second, we detected only SARSCoVr in Rhinolophus thomasi, both SARSCoVr and SARSCoV2r in Rhinolophus affinis, and only RecSar in Rhinolophus pusillus captured close to the border with China. Third, the bias in favour of Uracil in synonymous third codon positions of SARSCoVr extracted from R. thomasi showed a negative correlation with latitudes. Our results also provided support for an emergence of SARS‐CoV in horseshoe bats from northern Yunnan and emergence of SARS‐CoV‐2 in horseshoe bats from northern Indochina subtropical forests (southern Yunnan, northern Laos and north‐western Vietnam). [ABSTRACT FROM AUTHOR]

This study aimed for a better understanding of the niche specification of bacteria carrying the tfd-genes for aerobic 2,4-dichlorphenoxyacetic acid (2,4-D) degradation in the rice paddy ecosystem. To achieve this, a dedicated microcosm experiment was set up to mimic the rice paddy system, with and without 2,4-D addition, allowing spatial sampling of the different rice paddy compartments and niches, i.e., the main anaerobic bulk soil and the aerobic surface water, surface soil, root surface and rhizosphere compartments. No effect of 2,4-D on the growth and morphology of the rice plant was noted. 2,4-D removal was faster in the upper soil layers compared to the deeper layers and was more rapid after the second 2,4-D addition compared to the first. Moreover, higher relative abundances of the 2,4-D catabolic gene tfdA and of the mobile genetic elements IncP-1 and IS1071 reported to carry the tfd-genes, were observed in surface water and surface soil when 2,4-D was added. tfdA was also detected in the root surface and rhizosphere compartment but without response to 2,4-D addition. While analysis of the bacterial community composition using high-throughput 16S rRNA gene amplicon sequencing did not reveal expected tfd-carrying taxa, subtle community changes linked with 2,4-D treatment and the presence of the plant were observed. These findings suggest (i) that the surface soil and surface water are the primary and most favorable compartements/niches for tfdmediated aerobic 2,4-D biodegradation and (ii) that the community structure in the 2,4-D treated rice paddy ecosystem is determined by a niche-dependent complex interplay between the effects of the plant and of 2,4-D. [ABSTRACT FROM AUTHOR]

The medicinal mushroom Cordyceps militaris is widely exploited in traditional medicine and nutraceuticals in Asian countries. However, fruiting body production in C. militaris is facing degeneration through cultivation batches, and the molecular mechanism of this phenomenon remains unclear. This study showed that fruiting body formation in three different C. militaris strains, namely G12, B12, and HQ1, severely declined after three successive culturing generations using the spore isolation method. PCR analyses revealed that these strains exist as heterokaryons and possess both the mating-type loci, MAT1-1 and MAT1-2. Further, monokaryotic isolates carrying MAT1-1 or MAT1-2 were successfully separated from the fruiting bodies of all three heterokaryotic strains. A spore combination of the MAT1-1 monokaryotic isolate and the MAT1-2 monokaryotic isolate promoted fruiting body formation, while the single monokaryotic isolates could not do that themselves. Notably, we found that changes in ratios of the MAT1-2 spores strongly influenced fruiting body formation in these strains. When the ratios of the MAT1-2 spores increased to more than 15 times compared to the MAT1-1 spores, the fruiting body formation decreased sharply. In contrast, when MAT1-1 spores were increased proportionally, fruiting body formation was only slightly reduced. Our study also proposes a new solution to mitigate the degeneration in the heterokaryotic C. militaris strains caused by successive culturing generations.

The Chinese mitten crab (Eriocheir sinensis) has significant economic potential in both the Chinese domestic and global markets. The hemolymph microbiota is known to play a critical role in regulating physiological and biochemical functions in crustaceans. However, the study of the hemolymph microbiota of E. sinensis in response to infections has not been undertaken. In this study, changes in the composition and function of the hemolymph microbiota in E. sinensis infected with either Staphylococcus aureus (Sa) or Aeromonas hydrophila (Ah) were investigated using 16S rRNA sequencing, with a phosphate buffer saline (PBS) injection serving as the control. Results showed that the dominant hemolymph microbiota of E. sinensis were Proteobacteria, Bacteroidota, and Firmicutes. The relative abundance of the phyla Firmicutes, Bdellovibrionota, and Myxococcota was significantly reduced in both Sa and Ah groups compared to the PBS group. At the genus level, compared to the PBS group, a significant increase in the abundance of Flavobacterium and Aeromonas was found in both Ah and Sa groups. The analysis of the functional profile showed that pathways related to ‘cell growth and death’, ‘metabolism of terpenoids and polyketides’, ‘cancers’, ‘lipid metabolism’, ‘neurodegenerative diseases’, ‘metabolism of other amino acids’, ‘xenobiotics biodegradation and metabolism’, and ‘circulatory system and endocrine system’ were predominant in the Ah group. Meanwhile, pathways related to ‘metabolism or genetic information progressing’, such as ‘translation’, ‘metabolic diseases’, and ‘cellular processes and signaling’, were enriched in the Sa group. This study revealed the effects of pathogens (S. aureus or A. hydrophila) on the maintenance of the hemolymph microbiota in E. sinensis. It shed light on the mechanisms employed by the hemolymph microbiota of E. sinensis under pathogen stimulation.

Hemorrhagic stroke due to ruptured brain arteriovenous malformations (AVMs) is a common cause in young stroke patients. When the ruptured AVMs are in deep location, the choice of endovascular intervention with the arterial approach to AVM embolization is routine but in many cases, it is not feasible due to the inability to access because of the small and tortuous arterial branch, however, the intravenous approach also results in high complete obliteration rates but also carries a higher risk of stroke than the intra-arterial route. We describe a 36-year-old female patient diagnosed with intracranial and intraventricular hemorrhage who underwent complete transvenous embolization of the ruptured AVMs, and achieved near-complete clinical recovery after 1 month with the modified Rankin scale 1.

Traditional models for various machine learning problems such as image classification perform well only under the assumption of a closed set. This implies that inputs must belong to the classes for which the models were trained. Data collected in the real world may not belong to any finite set of classes, and training a model with an infinite number of classes would obviously be impossible. Rather than incorrectly classifying outlier inputs that belong to unknown classes as members of one of the classes on which the model was trained, learning models must recognize and reject such data samples, or request human assistance in labeling them. For example, when a self-driving vehicle detects unfamiliar scenes or objects, it must notify the driver and hand over control. Various models have been proposed to address the open-set problem. However, the existing models are generally complex or use complicated techniques such as generative adversarial networks and auto-encoders, and their efficiency is not proportional to their complexity. In this study, we propose Triple-Sigmoid as a simple activation function comprised of three Sigmoid functions. Using Triple-Sigmoid in the last activation layer of any deep neural network model enables the model to recognize outliers. Although Triple-Sigmoid can be applied to a variety of machine learning problems, including semi-supervised learning, active learning, and incremental learning, we only investigated the open-set recognition problem in this work. The results of numerous experiments are presented to validate that substituting Triple-Sigmoid for conventional activations such as Softmax and Sigmoid not only retained performance in closed-set settings, but also significantly improved performance in open-set configurations. Furthermore, these results demonstrate that Triple-Sigmoid significantly outperformed existing state-of-the-art methods. Source code for the proposed model is available at https://github.com/dinhtuantran/triple-sigmoid.

Destruction of citrus fruits by fungal pathogens during preharvest and postharvest stages can result in severe losses for the citrus industry. Antagonistic microorganisms used as biological agents to control citrus pathogens are considered alternatives to synthetic fungicides. In this study, we aimed to identify fungal pathogens causing dominant diseases on citrus fruits in a specialized citrus cultivation region of Vietnam and inspect soilborne Bacillus isolates with antifungal activity against these pathogens. Two fungal pathogens were characterized as Colletotrichum gloeosporioides and Penicillium digitatum based on morphological characteristics and ribosomal DNA internal transcribed spacer sequence analyses. Reinfection assays of orange fruits confirmed that C. gloeosporioides causes stem-end rot, and P. digitatum triggers green mold disease. By the heterologous expression of the green fluorescent protein (GFP) in C. gloeosporioides using Agrobacterium tumefaciens-mediated transformation, we could observe the fungal infection process of the citrus fruit stem-end rot caused by C. gloeosporioides for the first time. Furthermore, we isolated and selected two soilborne Bacillus strains with strong antagonistic activity for preventing the decay of citrus fruits by these pathogens. Molecular analyses of 16 S rRNA and gyrB genes showed that both isolates belong to B. velezensis. Antifungal activity assays indicated that bacterial culture suspensions could strongly inhibit C. gloeosporioides and P. digitatum, and shield orange fruits from the invasion of the pathogens. Our work provides a highly effective Bacillus-based preservative solution for combating the fungal pathogens C. gloeosporioides and P. digitatum to protect citrus fruits at the postharvest stages.

Laser powder bed fusion (L-PBF) is one of the most widely used metal additive manufacturing technology for fabrication of functional and structural components. However, inconsistency in quality and reliability of L-PBF products is still a significant barrier preventing it from wider adoption. Machine learning (ML) of monitoring data offers a unique solution to effectively identify possible defects and predict the quality of L-PBF products. In this work, we introduce a semi-supervised ML approach to detect anomalies that occurred in L-PBF products. We train the ML model to classify surface appearances in the reference monitoring data. We then correlate the classified appearances to post-process characteristics, e.g. surface roughness, morphology, or tensile strength. We demonstrate that the established correlation enables the determination of key appearances indicative of the quality of the printed samples including anomaly-free, lack-of-fusion and overheated. We further validate our ML approach by performing prediction on test samples having various geometries.

Understanding the negative effects of climate change and changes to land use/land cover on natural hazards is an important feature of sustainable development worldwide, as these phenomena are inextricably linked with natural hazards such as landslides. The contribution of this study is an attempt to develop a state-of-the-art method to assess the effects of climate change and changes in land use/land cover on landslide susceptibility in the Tra Khuc river basin in Vietnam. The method is based on machine learning and remote sensing algorithms, namely radial basis function neural networks–search and rescue optimization (RBFNN–SARO), radial basis function neural network–queuing search algorithm (RBFNN–QSA), radial basis function neural network–life choice-based optimizer (RBFNN–LCBO), radial basis function neural network–dragonfly optimization (RBFNN–DO). All proposed models performed well, with AUC value of >0.9. The RBFNN–QSA model performed best, with an AUC value of 0.98, followed by RBFNN–SARO (AUC = 0.97), RBFNN–LCBO (AUC = 0.95), RBFNN–DO (AUC = 0.93), and support vector machine (SVM; AUC = 0.92). The results show that both climate and land use/land cover change greatly in the future: Precipitation increases 18% by 2030 and 25.1% by 2050; the total production forest, protected forest and built-up area change considerably between 2010 and 2050. These changes influence landslide susceptibility: The area of high and very high landslide susceptibility decrease by approximately 100 and 300 km2 respectively in the study area from 2010 to 2050. The findings of this study can support decision-makers in formulating appropriate strategies to reduce damage from landslides, such as limiting construction in areas where future landslides are predicted. Although this study applies to a particular region of Vietnam, the findings can be applied in other mountainous regions around the world.

Unfolded protein response (UPR) is a stress response that is specific to the endoplasmic reticulum (ER). UPR is activated upon accumulation of unfolded (or misfolded) proteins in the ER's lumen to restore protein folding capacity by increasing the synthesis of chaperones. In addition, UPR also enhances degradation of unfolded proteins and reduces global protein synthesis to alleviate additional accumulation of unfolded proteins in the ER. Herein, we describe a cell-based ultra-high throughput screening (uHTS) campaign that identifies a small molecule that can modulate UPR and ER stress in cellular and in vivo disease models. Using asialoglycoprotein receptor 1 (ASGR) fused with Cypridina luciferase (CLuc) as reporter assay for folding capacity, we have screened a million small molecule library and identified APC655 as a potent activator of protein folding, that appears to act by promoting chaperone expression. Furthermore, APC655 improved pancreatic β cell viability and insulin secretion under ER stress conditions induced by thapsigargin or cytokines. APC655 was also effective in preserving β cell function and decreasing lipid accumulation in the liver of the leptin-deficient (ob/ob) mouse model. These results demonstrate a successful uHTS campaign that identified a modulator of UPR, which can provide a novel candidate for potential therapeutic development for a host of metabolic diseases.

Abstract This paper presents a novel DSO support tool with visualisation capability for forecasting network congestion in distribution systems with a high level of renewables. To incorporate the uncertainties in the distribution systems, the probabilistic power flow framework has been utilised. An advanced photovoltaic production forecast based on sky images and a load forecast using an artificial neural network is used as the input to the tool. In addition, advanced load models and operating modes of photovoltaic inverters have been incorporated into the tool. The tool has been applied in case studies to perform congestion forecasts for two real distribution systems to validate its usability and scalability. The results from case studies demonstrated that the tool performs satisfactorily for both small and large networks and is able to visualise the cumulative probabilities of nodes voltage deviation and network components (branches and transformers) congestion for a variety of forecast horizons as desired by the DSO. The results have also shown that explicit inclusion of load‐voltage dependency models would improve the accuracy of the congestion forecast. For demonstrating the applicability of the tool, it has been integrated into an existing distribution management system via the IoT platform of a DMS vendor, Atos Worldgrid.

Indirect carotid cavernous fistulas (ICCFs) are rare disease entities triggered by indirect low flow between the cavernous sinus and the meningeal branches of the internal or external carotid artery or from both. To evaluate clinical characteristics, angiography, and relationship to the result of endovascular treatment of indirect carotid cavernous fistulas. A prospective study of 32 patients diagnosed to identify ICCFs through digital subtraction angiography (DSA) and intravascular intervention. Results showed that indirect carotid cavernous fistulas were more common in females of advanced age (68.8%) and occurred spontaneously (87.5%); the most common symptoms included chemosis (93.75%), headache (87.5%), proptosis (53.1%), and tinnitus (37.5%) with type D being the most common (81.2%). Thirty out of thirty-two patients with intervention had complete flow block (83.3%), near complete (13.3%), and failure in one case. Incomplete occlusion interventions and failures were of the type D complication. The complication and number of drainage veins are related (p

Crab species are economically important crustaceans with high demand in markets. Development of the culture system resulted in an increase in disease outbreaks. Disquisition and application of methods that can prevent and control diseases during the crab culture period are crucially essential. The application of prebiotics and probiotics to replace the overuse of antibiotics has practical significance in sustainability of the crab farming. Previously, both prebiotics and probiotics have shown to confer benefits in growth promotion, immunostimulation, and disease control in crab culture. These components can directly stimulate humoral immunity by increasing activities of lysozyme, phagocytosis, respiratory burst, and phenoloxidase. They also activate the cell-mediated immunity by binding to pattern recognition receptors expressed on immune cells and modulating cell signal transduction pathways. Furthermore, the mechanism of action and effectiveness in use of prebiotics and probiotics are summarized in this study, indicating the potential application of prebiotics and probiotics as feed additives in crab farming.