Fusarium spp. are commonly associated with the root rot complex of soybean (Glycine max). Previous surveys identified six common Fusarium species from Manitoba, including F. oxysporum, F. redolens, F. graminearum, F. solani, F. avenaceum, and F. acuminatum. This study aimed to determine their pathogenicity, assess host resistance, and evaluate the genetic diversity of Fusarium spp. isolated from Canada. The pathogenicity of these species was tested on two soybean cultivars, ‘Akras’ (moderately resistant) and ‘B150Y1′ (susceptible), under greenhouse conditions. The aggressiveness of the fungal isolates varied, with root rot severities ranging from 1.5 to 3.3 on a 0–4 scale. Subsequently, the six species were used to screen a panel of 20 Canadian soybean cultivars for resistance in a greenhouse. Cluster and principal component analyses were conducted based on the same traits used in the pathogenicity study. Two cultivars, ‘P15T46R2′ and ‘B150Y1′, were consistently found to be tolerant to F. oxysporum, F. redolens, F. graminearum, and F. solani. To investigate the incidence and prevalence of Fusarium spp. in Canada, fungi were isolated from 106 soybean fields surveyed across Manitoba, Saskatchewan, Ontario, and Quebec. Eighty-three Fusarium isolates were evaluated based on morphology and with multiple PCR primers, and phylogenetic analyses indicated their diversity across the major soybean production regions of Canada. Overall, this study contributes valuable insights into host resistance and the pathogenicity and genetic diversity of Fusarium spp. in Canadian soybean fields. Full article

Angiotensin-converting enzyme (ACE) metabolizes a number of important peptides participating in blood pressure regulation and vascular remodeling. Elevated ACE expression in tissues (which is generally reflected by blood ACE levels) is associated with an increased risk of cardiovascular diseases. Elevated blood ACE is also a marker for granulomatous diseases. Decreased blood ACE activity is becoming a new risk factor for Alzheimer’s disease. We applied our novel approach—ACE phenotyping—to characterize pairs of tissues (lung, heart, lymph nodes) and serum ACE in 50 patients. ACE phenotyping includes (1) measurement of ACE activity with two substrates (ZPHL and HHL); (2) calculation of the ratio of hydrolysis of these substrates (ZPHL/HHL ratio); (3) determination of ACE immunoreactive protein levels using mAbs to ACE; and (4) ACE conformation with a set of mAbs to ACE. The ACE phenotyping approach in screening format with special attention to outliers, combined with analysis of sequencing data, allowed us to identify patient with a unique ACE phenotype related to decreased ability of inhibition of ACE activity by albumin, likely due to competition with high CCL18 in this patient for binding to ACE. We also confirmed recently discovered gender differences in sialylation of some glycosylation sites of ACE. ACE phenotyping is a promising new approach for the identification of ACE phenotype outliers with potential clinical significance, making it useful for screening in a personalized medicine approach. Full article

This paper addresses the problem of fault detection in DC microgrids in the presence of denial-of-service (DoS) attacks. To deal with the nonlinear term in DC microgrids, a Takagi-Sugeno (T-S) model is employed. In contrast to the conventional approach of utilizing current sampling data in the traditional event-triggered mechanism (ETM), a novel integrated ETM employs historical information from measured data. This innovative strategy mitigates the generation of additional triggering packets resulting from random perturbations, thus reducing redundant transmission data. Under the assumption of faults occurring within a finite-frequency domain, a resilient event-based ${\mathcal{H}}_{-}/{\mathcal{H}}_{\infty }$ fault detection filter (FDF) is designed to withstand DoS attacks. The exponential stability conditions are derived in the form of linear matrix inequalities to ensure the performance of fault detected systems. Finally, the simulation results are presented, demonstrating that the designed FDF effectively detects finite-frequency faults in time even under DoS attacks. Furthermore, the FDF exhibits superior fault detection sensitivity compared to the conventional ${\mathcal{H}}_{\infty }$ method, thus confirming the efficacy of the proposed approach. Additionally, it is observed that a trade-off exists between fault detection performance and the data releasing rate (DRR). Full article

Building-integrated flexible resources can offer economical availability to accommodate high-penetrated renewable energy sources (RESs), which can be potentially coordinated to achieve cost-effective supply. This paper proposes a resilience-oriented planning model of urban distribution system source–network–load–storage in the context of high-penetrated building-integrated resources. In this model, source–network–load–storage resources are cost-optimally planned, including the lines, soft open point (SOP), building-integrated photovoltaics (BIPVs), building-integrated wind turbine (BIWT), building-integrated energy storage system (ESS), etc. To enhance fault recovery capability during extreme faults, fault scenarios are incorporated into the distribution system operation via coupled multiple recovery stages. The resilience-oriented planning is a thorny problem due to its source–network–load–storage couplings, normal-fault couplings, etc. The original resilience-oriented planning is reformulated as a mixed-integer linear programming (MILP) problem, which can then be solved with a two-stage method and evaluated via a multi-dimensional evaluation metrics. The proposed planning methodology is benchmarked over a Portugal 54-node urban distribution system to verify the superiority and effectiveness on the system economy and resilience levels. Case studies show that the proposed methodology can exploit the optimal synergies of different source–network–load–storage components and enhance system dispatchability. Full article

Treatment strategies for steatohepatitis are of special interest given the high prevalence of obesity and fatty liver disease worldwide. This study aimed to investigate the potential therapeutic mechanism of L-carnitine (LC) and Ginkgo biloba leaf extract (GB) supplementation in ameliorating the adverse effects of hyperlipidemia and hepatosteatosis induced by a high-cholesterol diet (HCD) in an animal model. The study involved 50 rats divided into five groups, including a control group, a group receiving only an HCD, and three groups receiving an HCD along with either LC (300 mg LC/kg bw), GB (100 mg GB/kg bw), or both. After eight weeks, various parameters related to lipid and glucose metabolism, antioxidant capacity, histopathology, immune reactivity, and liver ultrastructure were measured. LC + GB supplementation reduced serum total cholesterol, triglyceride, low-density lipoprotein cholesterol, glucose, insulin, HOMA-IR, alanine transaminase, and aspartate transaminase levels and increased high-density lipoprotein cholesterol levels compared with those in the HCD group. Additionally, treatment with both supplements improved antioxidant ability and reduced lipid peroxidation. The histological examination confirmed that the combination therapy reduced liver steatosis and fibrosis while also improving the appearance of cell organelles in the ultrastructural hepatocytes. Finally, the immunohistochemical analysis indicated that cotreatment with LC + GB upregulated the immune expression of GLP-1 and β-Cat in liver sections that were similar to those of the control animals. Mono-treatment with LC or GB alone substantially but not completely protected the liver tissue, while the combined use of LC and GB may be more effective in treating liver damage caused by high cholesterol than either supplement alone by regulating hepatic oxidative stress and the protein expression of GLP-1 and β-Cat. Full article

Investigations have shown that storage bugs seriously harm grains during storage. In the interim, essential oils (EOs) have been proven to be a good botanical pesticide. The anti-Lasioderma serricorne properties of Elsholtzia ciliata essential oil, which was obtained by steam distillation, were evaluated using DL-limonene, carvone, and their two optical isomer components using contact, repelling, and fumigation techniques. Simultaneously, the fumigation, contact, and repellent activities of carvone and its two optical isomers mixed with DL-limonene against L. serruricorne were evaluated. The results showed that E. ciliata, its main components (R-carvone, DL-limonene), and S-carvone exhibited both fumigations (LC₅₀ = 14.47, 4.42, 20.9 and 3.78 mg/L) and contact (LD₅₀ = 7.31, 4.03, 28.62 and 5.63 µg/adult) activity against L.serricorne. A binary mixture (1:1) of R-carvone and DL-limonene displayed an obvious synergistic effect. A binary mixture (1:1) of carvone and its two optical isomers exhibited an obvious synergistic effect, too. Furthermore, the repellent activity of the EO, carvone, and its two optical isomers, DL-limonene, and a combination of them varied. To stop insect damage during storage, E. ciliata and its components can be utilized as bio-insecticides. Full article

Establishing a suitable and useful soil quality index (SQI) is the key to accurately evaluating changes in soil quality (SQ) under different land use types. In the present study, a suitable and useful SQI using a minimum data set (MDS) with two scoring methods (linear scoring method and nonlinear scoring method) and two additive models (simple additive model with same weighting value and weighted additive model with significant different weighting value) was established to compare SQ under different land uses in Longtan valley. Soil samples were collected under one dryland (DRYL), one paddy (PADD), one orchard (GRA), and one natural forest (FORE), and 13 soil properties were measured. The four land use types had the same soil type and similar environmental conditions. Land use types had significant effects on the measured 12 soil properties. The top two principal components in Principal Component Analysis were chosen, and their cumulative variance was more than 90%. Soil indicators of soil labile carbon, C/N ratio, and microaggregates were chosen as members of MDS in this study. Significant (p < 0.001) positive correlations among the four establishing SQIs were found. The values of the sensitive index ranged from 47.17% to 82.12% for the four SQIs, and the SQI established using the nonlinear scoring method and weighted additive model (SQI-NLW) had the highest values. Among the four land use types, the four SQIs had similar change trends, and the average values of SQ under FORE (0.73) and PADD (0.68) were significantly higher than those under GRA (0.54) and DRYL (0.43). These results indicated that the SQI-NLW was an effective and precise tool to assess SQ under different land uses in similar regions, and the FORE and PADD were the suitable land use types for the sustainable use of soils in karst regions. Full article

Supervised learning methods excel in traditional relation extraction tasks. However, the quality and scale of the training data heavily influence their performance. Few-shot relation extraction is gradually becoming a research hotspot whose objective is to learn and extract semantic relationships between entities with only a limited number of annotated samples. In recent years, numerous studies have employed prototypical networks for few-shot relation extraction. However, these methods often suffer from overfitting of the relation classes, making it challenging to generalize effectively to new relationships. Therefore, this paper seeks to utilize a diffusion model for data augmentation to address the overfitting issue of prototypical networks. We propose a diffusion model-enhanced prototypical network framework. Specifically, we design and train a controllable conditional relation generation diffusion model on the relation extraction dataset, which can generate the corresponding instance representation according to the relation description. Building upon the trained diffusion model, we further present a pseudo-sample-enhanced prototypical network, which is able to provide more accurate representations for prototype classes, thereby alleviating overfitting and better generalizing to unseen relation classes. Additionally, we introduce a pseudo-sample-aware attention mechanism to enhance the model’s adaptability to pseudo-sample data through a cross-entropy loss, further improving the model’s performance. A series of experiments are conducted to prove our method’s effectiveness. The results indicate that our proposed approach significantly outperforms existing methods, particularly in low-resource one-shot environments. Further ablation analyses underscore the necessity of each module in the model. As far as we know, this is the first research to employ a diffusion model for enhancing the prototypical network through data augmentation in few-shot relation extraction. Full article

Brevibacillus sp. JNUCC 41, characterized as a plant-growth-promoting rhizobacterium (PGPR), actively participates in lipid metabolism and biocontrol based on gene analysis. This study aimed to investigate the crucial secondary metabolites in biological metabolism; fermentation, extraction, and isolation were performed, revealing that methyl indole-3-acetate showed the best hyaluronidase (HAase) inhibitory activity (IC₅₀: 343.9 μM). Molecular docking results further revealed that the compound forms hydrogen bonds with the residues Tyr-75 and Tyr-247 of HAase (binding energy: −6.4 kcal/mol). Molecular dynamics (MD) simulations demonstrated that the compound predominantly binds to HAase via hydrogen bonding (MM-PBSA binding energy: −24.9 kcal/mol) and exhibits good stability. The residues Tyr-247 and Tyr-202, pivotal for binding in docking, were also confirmed via MD simulations. This study suggests that methyl indole-3-acetate holds potential applications in anti-inflammatory and anti-aging treatments. Full article

Small secreted peptides (SSPs) play important roles in regulating plants’ growth and development in response to external stimulus, but the genes and functions of SSPs in many species are still unknown. Therefore, it is particularly significant to characterize and annotate SSP genes in plant genomes. As a widely used stock of pears, Pyrus betulifolia has strong resistance to biotic and abiotic stresses. In this study, we analyzed the SSPs genes in the genome of P. betulifolia according to their characteristics and homology. A total of 1195 SSP genes were identified, and most of them are signaling molecules. Among these, we identified a new SSP, subtilase peptide 3 (SUBPEP3), which derived from the PA region of preSUBPEP3, increasing the expression level under salt stress. Both adding synthetic peptide SUBPEP3 to the culture medium of pears and the overexpression of SUBPEP3 in tobacco can improve the salt tolerance of plants. In summary, we annotated the SSP genes in the P. betulifolia genome and identified a small secreted peptide SUBPEP3 that regulates the salt tolerance of P. betulifolia, which provides an important theoretical basis for further revealing the function of SSPs. Full article

The exponential growth of urban centers has exacerbated the prevalence of traffic-related issues. This surge has amplified the conflict between the escalating need for travel among individuals and the constricted availability of road infrastructure. Consequently, the escalation of traffic accidents and the exacerbation of environmental pollution have emerged as increasingly pressing concerns. Urban road intersections, serving as pivotal junctures for vehicle convergence and dispersal, have remained a focal point for scholarly inquiry regarding enhanced operational efficacy and safety. Concurrently, vehicles navigating intersections are subject to external influences, such as pedestrian crossings and signal controls, causing frequent fluctuations in their operational dynamics. These fluctuations contribute to heightened exhaust emissions, exacerbating air pollution and posing health risks to pedestrians frequenting these intersections. A reasonable signal timing scheme can enable more vehicles to pass through the intersection safely and smoothly and reduce the pollutants generated by transportation. Therefore, optimizing signal timing schemes at intersections to alleviate traffic problems is a topic that needs to be studied urgently. In this paper, the emission model based on specific power is analyzed. Through an analysis of the correlation between specific power distribution intervals and the emission rates of individual pollutants, it has been observed that vehicle emission rates are at their lowest during idle speed, progressively increasing with rising vehicle speeds. Investigation into specific power distribution based on variables, such as vehicle type, frequency of stops, and varying delays, has led to the deduction that the peak specific power of vehicles at intersections consistently occurs within the (0, 1) interval. Furthermore, it has been established that high-saturation intersections exhibit higher peak specific power compared to low-saturation intersections. Full article

Anaerobic digestion is an important means to turn agricultural waste into resources and an important way to address the challenges in treating vegetable residues in China. In this study, the co-digestion of dairy manure with tomato residue was investigated to clarify the effect of the total solids (TS) of the digestion substrate on methane’s production and mechanism using the self-made anaerobic digestion device. The results showed that all treatments could rapidly ferment methane and that the daily methane production showed a trend of increasing first and then decreasing. The optimal concentrations of the digestion substrate for liquid anaerobic digestion (L-AD), hemi-solid-state anaerobic digestion (HSS-AD), and solid-state anaerobic digestion (SS-AD) were 10%, 18%, and 25%, respectively. Compared with SS-AD and HSS-AD, L-AD gas production peaked 3–6 days earlier. Treatment TS25 had the best cumulative methane production, reaching 117.4 mL/g VS. However, treatment TS6 had acid accumulation and a very unstable system. The cumulative methane production of SS-AD was higher than that of HSS-AD and L-AD. Firmicutes and Bacteroidetes were the dominant flora, and Methanoculleus, Methanosarcina, and Methanobrevibacter were the main archaeal groups. The TS significantly changed the microbial community composition of the digestion system, especially the low TS treatment. The results presented herein indicated that TS significantly changed the bacterial and archaeal community composition of the digestion system, and thus with the increase in TS from 6% to 25%, the methane yield increased. Full article

The maintenance of an uninterrupted electricity supply to meet demand is of paramount importance for maintaining the stable operation of an electrical power system. Machine learning and deep learning play a crucial role in maintaining that stable operation. These algorithms have the ability to acquire knowledge from past data, enabling them to efficiently identify and forecast potential scenarios of instability in the future. This work presents a hybrid convolutional long short-term memory (ConvLSTM) technique for training and predicting nodal voltage stability in an IEEE 14-bus microgrid. Analysis of the findings shows that the suggested ConvLSTM model exhibits the highest level of precision, reaching a value of 97.65%. Furthermore, the ConvLSTM model has been shown to perform better compared to alternative machine learning and deep learning models such as convolutional neural networks, k-nearest neighbors, and support vector machine models, specifically in terms of accurately forecasting voltage stability. The IEEE 14-bus system tests indicate that the suggested method can quickly and accurately determine the stability status of the system. The comparative analysis obtained the results and further justified the efficiency and voltage stability of the proposed model. Full article

BRAF mutation identification is important for the diagnosis and treatment of several tumor types, both solid and hematologic. Rapid identification of BRAF mutations is required to determine eligibility for targeted BRAF inhibitor therapy. The Idylla BRAF mutation assay is a rapid, multiplex allele-specific PCR test designed to detect the most common oncogenic BRAF V600 mutations in formalin-fixed paraffin-embedded (FFPE) tissue samples. Here, we describe the validation of the Idylla BRAF mutation assay in our laboratory. During routine clinical practice, we noticed cases in which BRAF V600 mutations were identified with unusual amplification curves, with three cases displaying a delayed amplification within a double amplification pattern and two false-positive calls. We therefore initiated a quality improvement effort to systematically and retrospectively evaluate next-generation sequencing (NGS)-tested cases with BRAF mutations identified within five amino acids of BRAF codon V600 and did not identify additional false-positive cases. We hypothesize that late amplification in a double amplification pattern may represent non-specific amplification, whereas cases displaying single delayed amplification curves may stem from the presence of either non-V600 variants, very low-level V600 variants, cytosine deamination artifacts, and/or non-specific amplification by an allele-specific PCR primer. Regardless, we recommend that Idylla BRAF cases with non-classical amplification curves undergo reflex NGS testing. These findings are likely relevant for other Idylla assays interrogating hotspot mutations in genes such as EGFR, IDH1/2, KRAS, and NRAS. Full article

A thorough understanding of the impact of climatic factors on agricultural production is crucial for improving crop models and enhancing predictability of crop prices and yields. Fluctuations in crop yield and price can have significant implications for the market sector and farming community. Given the projected increase in frequency and intensity of extreme events, reliable modelling of cropping patterns becomes essential. Temperature anomalies are expected to play a prominent role in future extreme events, emphasizing the need to comprehend their influence on crop yield. Forecasting extreme yield, which encompasses both the highest and lowest levels of agricultural production within a given time period, along with peak crop prices representing the highest market values, poses greater challenges in forecasting compared to other values. Probability-based predictions, accounting for uncertainty and variability, offer a more accurate approach for extreme value estimation and risk assessment. In this study, we employ a multivariate analysis based on vine copula to explore the interdependencies between temperature anomalies and daily strawberry yield in Santa Maria, California. By considering the maximum and minimum daily yields each month, we observe an increased probability of yield loss with rising temperature anomalies. While we do not explicitly consider the specific impacts of temperature anomalies under individual Representative Concentration Pathway (RCP) scenarios, our analysis is conducted within the broader context of the current global warming scenario. This allows us to capture the overall anticipated effects of regional temperature anomalies on agriculture. The findings of this study have potential impacts and consequences for understanding the vulnerability of agricultural systems and improving crop model predictions. By enhancing our understanding of the relationships between temperature anomalies and crop yield, we can inform decision-making processes related to the impact of climate change on agriculture. This research contributes to the ongoing efforts in improving agricultural sustainability and resilience in the face of changing climatic conditions. Full article

Methylglyoxal (MGO) is a highly reactive α-dicarbonyl compound formed endogenously from 3-carbon glycolytic intermediates. Methylglyoxal accumulated in plasma and urine of hyperglycemic and diabetic individuals acts as a potent peptide glycation molecule, giving rise to advanced glycation end products (AGEs) like arginine-derived hydroimidazolone (MG-H1) and carboxyethyl-lysine (CEL). Methylglyoxal-derived AGEs exert their effects mostly via activation of RAGE, a cell surface receptor that initiates multiple intracellular signaling pathways, favoring a pro-oxidant environment through NADPH oxidase activation and generation of high levels of reactive oxygen species (ROS). Diabetic bladder dysfunction is a bothersome urological complication in patients with poorly controlled diabetes mellitus and may comprise overactive bladder, urge incontinence, poor emptying, dribbling, incomplete emptying of the bladder, and urinary retention. Preclinical models of type 1 and type 2 diabetes have further confirmed the relationship between diabetes and voiding dysfunction. Interestingly, healthy mice supplemented with MGO for prolonged periods exhibit in vivo and in vitro bladder dysfunction, which is accompanied by increased AGE formation and RAGE expression, as well as by ROS overproduction in bladder tissues. Drugs reported to scavenge MGO and to inactivate AGEs like metformin, polyphenols, and alagebrium (ALT-711) have shown favorable outcomes on bladder dysfunction in diabetic obese leptin-deficient and MGO-exposed mice. Therefore, MGO, AGEs, and RAGE levels may be critically involved in the pathogenesis of bladder dysfunction in diabetic individuals. However, there are no clinical trials designed to test drugs that selectively inhibit the MGO–AGEs–RAGE signaling, aiming to reduce the manifestations of diabetes-associated bladder dysfunction. This review summarizes the current literature on the role of MGO–AGEs–RAGE–ROS axis in diabetes-associated bladder dysfunction. Drugs that directly inactivate MGO and ameliorate bladder dysfunction are also reviewed here. Full article

Background: Heart failure (HF) affects around 60 million individuals worldwide. The primary aim of this study was to evaluate the efficacy of lung ultrasound (LUS) in managing HF with the goal of reducing hospital readmission rates. Methods: A systematic search was conducted on PubMed, Embase, Google Scholar, Web of Science, and Scopus, covering clinical trials, meta-analyses, systematic reviews, and original articles published between 1 January 2019 and 31 December 2023, focusing on LUS for HF assessment in out-patient settings. There is a potential for bias as the effectiveness of interventions may vary depending on the individuals administering them. Results: The PRISMA method synthesized the findings. Out of 873 articles identified, 33 were selected: 19 articles focused on prognostic assessment of HF, 11 centred on multimodal diagnostic assessments, and two addressed therapeutic guidance for HF diagnosis. LUS demonstrates advantages in detecting subclinical congestion, which holds prognostic significance for readmission and mortality during out-patient follow-up post-hospital-discharge, especially in complex scenarios, but there is a lack of standardization. Conclusions: there are considerable uncertainties in their interpretation and monitoring changes. The need for an updated international consensus on the use of LUS seems obvious. Full article

Selective laser melting (SLM) technology used for the design and production of porous implants can successfully address the issues of stress shielding and aseptic loosening associated with the use of solid implants in the human body. In this paper, orthogonal experiments were used to optimize the process parameters for SLM molding of Ti-6Al-4V (TC4) material to investigate the effects of the process parameters on the densities, microscopic morphology, and roughness, and to determine the optimal process parameters using the roughness as a judging criterion. Based on the optimized process parameters, the mechanical properties of SLM-formed TC4 alloy specimens are investigated experimentally in this paper. The main conclusions are as follows: the optimal combination of roughness is obtained by polar analysis, the microhardness of SLM-molded TC4 alloy molded specimens is more uniform, the microhardness of specimens on the side and the front as well as the abrasion resistance is higher than that of casting specimens, the yield strength and tensile strength of specimens is higher than that of ASTM F136 standard and casting standard but the elongation is not as good as that of the standard, and the elasticity and compressive strength of porous specimens are higher than that of casting specimens at different volume fractions. The modulus of elasticity and compressive strength are within the range of human skeletal requirements. This work makes it possible to fabricate high-performance porous femoral joint implants from TC4 alloy SLM-molded materials. Full article

Coastal zones, despite their contribution to global economies, continue to suffer the negative impacts of climate variability, which limit the livelihoods of people, particularly small-scale fishermen. This study examined climate variability, coastal livelihoods, and the influence of ocean change on the total annual fish catch in Ghana’s Coastal Savannah zone. The mixed-methods approach was used to analyze primary data (semi-structured questionnaires and interviews), secondary data (sea surface temperature (SST) and salinity (SSS), and fish catch), and statistical tests (chi-square, binary logistic regression, and multiple regression). Findings revealed a significant increase in climate variability awareness among fishermen, attributed to the influence of broadcast media. However, they lack sufficient information regarding the transformation of cities, the urbanization process, and its impact on the global climate. Increasing temperatures and sea level rise emerged as the most prevalent impacts of climate variability over the past two decades in the zone. Although the fishermen lack awareness regarding the changes in SSS and their effects on fish, the findings of the multiple regression analysis established that changes in SSS exert a more pronounced effect on the decreasing fishing catch in the zone compared to those in SST. Empirical fish catch records supported the fishermen’s claim of a substantial decrease in total fish catch in the zone over the past 20 years. Aside from climate variability impacts, the involvement of many people and light fishing emerged as additional factors contributing to the decreasing fish catch in the zone. High premix fuel prices or shortages and “saiko” activities were the main obstacles that hindered the fishermen’s activities. “Saiko” is an unlawful activity in which foreign industrial trawlers sell fish directly to Ghanaian canoes or small-scale fishermen at sea. The fishermen lack sufficient means of supporting their livelihoods, as there is a lack of viable alternative livelihood options. Additionally, the majority of the fishermen experience symptoms of fever and headaches. The binary logistic regression analysis showed that the fishermen’s income insufficiency could be substantially reduced if they were to have their own houses, canoes, or fish all year. This situation highlights the need for heightened support from policymakers for improved sustainable livelihood prospects as well as health and well-being. Full article

Tomato leaf disease control in the field of smart agriculture urgently requires attention and reinforcement. This paper proposes a method called LAFANet for image-text retrieval, which integrates image and text information for joint analysis of multimodal data, helping agricultural practitioners to provide more comprehensive and in-depth diagnostic evidence to ensure the quality and yield of tomatoes. First, we focus on six common tomato leaf disease images and text descriptions, creating a Tomato Leaf Disease Image-Text Retrieval Dataset (TLDITRD), introducing image-text retrieval into the field of tomato leaf disease retrieval. Then, utilizing ViT and BERT models, we extract detailed image features and sequences of textual features, incorporating contextual information from image-text pairs. To address errors in image-text retrieval caused by complex backgrounds, we propose Learnable Fusion Attention (LFA) to amplify the fusion of textual and image features, thereby extracting substantial semantic insights from both modalities. To delve further into the semantic connections across various modalities, we propose a False Negative Elimination-Adversarial Negative Selection (FNE-ANS) approach. This method aims to identify adversarial negative instances that specifically target false negatives within the triplet function, thereby imposing constraints on the model. To bolster the model’s capacity for generalization and precision, we propose Adversarial Regularization (AR). This approach involves incorporating adversarial perturbations during model training, thereby fortifying its resilience and adaptability to slight variations in input data. Experimental results show that, compared with existing ultramodern models, LAFANet outperformed existing models on TLDITRD dataset, with top1, top5, and top10 reaching 83.3% and 90.0%, and top1, top5, and top10 reaching 80.3%, 93.7%, and 96.3%. LAFANet offers fresh technical backing and algorithmic insights for the retrieval of tomato leaf disease through image-text correlation. Full article

Cellulose nitrates (CNs)-blended composites based on celluloses of bacterial origin (bacterial cellulose (BC)) and plant origin (oat-hull cellulose (OHC)) were synthesized in this study for the first time. Novel CNs-blended composites made of bacterial and plant-based celluloses with different BC-to-OHC mass ratios of 70/30, 50/50, and 30/70 were developed and fully characterized, and two methods were employed to nitrate the initial BC and OHC, and the three cellulose blends: the first method involved the use of sulfuric–nitric mixed acids (MAs), while the second method utilized concentrated nitric acid in the presence of methylene chloride (NA + MC). The CNs obtained using these two nitration methods were found to differ between each other, most notably, in viscosity: the samples nitrated with NA + MC had an extremely high viscosity of 927 mPa·s through to the formation of an immobile transparent acetonogel. Irrespective of the nitration method, the CN from BC (CN BC) was found to exhibit a higher nitrogen content than the CN from OHC (CN OHC), 12.20–12.32% vs. 11.58–11.60%, respectively. For the starting BC itself, all the cellulose blends of the starting celluloses and their CNs were detected using the SEM technique to have a reticulate fiber nanostructure. The cellulose samples and their CNs were detected using the IR spectroscopy to have basic functional groups. TGA/DTA analyses of the starting cellulose samples and the CNs therefrom demonstrated that the synthesized CN samples were of high purity and had high specific heats of decomposition at 6.14–7.13 kJ/g, corroborating their energy density. The CN BC is an excellent component with in-demand energetic performance; in particular, it has a higher nitrogen content while having a stable nanostructure. The CN BC was discovered to have a positive impact on the stability, structure, and energetic characteristics of the composites. The presence of CN OHC can make CNs-blended composites cheaper. These new CNs-blended composites made of bacterial and plant celluloses are much-needed in advanced, high-performance energetic materials. Full article