Search Results (2,562)

All novel materials should be analyzed for their potential environmental hazard. In this study, the toxicity of different silver–chitosan nanocomposites—potential candidates for wound dressings or antimicrobial surface coatings—was evaluated using environmentally relevant aquatic microcrustaceans Daphnia magna and Thamnocephalus platyurus and naturally luminescent bacteria Vibrio fischeri. Three silver-chitosan nanocomposites (nAgCSs) with different weight ratios of Ag to CS were studied. Citrate-coated silver nanoparticles (nAg-Cit), AgNO₃ (ionic control) and low molecular weight chitosan (LMW CS) were evaluated in parallel. The primary size of nAgCSs was ~50 nm. The average hydrodynamic sizes in deionized water were ≤100 nm, and the zeta potential values were positive (16–26 mV). The nAgCSs proved very toxic to aquatic crustaceans: the 48-h EC₅₀ value for D. magna was 0.065–0.232 mg/L, and the 24-h LC₅₀ value for T. platyurus was 0.25–1.04 mg/L. The toxic effect correlated with the shedding of Ag ions (about 1%) from nAgCSs. Upon exposure of V. fischeri to nAgCSs for 30 min, bacterial luminescence was inhibited by 50% at 13–33 mg/L. However, the inhibitory effect (minimum bactericidal concentration, MBC) on bacterial growth upon 1 h exposure was observed at higher concentrations of nAgCSs, 40–65 mg/L. LMW CS inhibited bacterial luminescence upon 30-min exposure at 5.6 mg/L, but bacterial growth was inhibited at a much higher concentration (1 h MBC > 100 mg/L). The multi-trophic test battery, where D. magna was the most sensitive test organism, ranked the silver-chitosan nanocomposites from ‘extremely toxic’ [L(E)C₅₀ ≤ 0.1 mg/L] to ‘very toxic’ [L(E)C₅₀ > 0.1–1 mg/L]. Chitosan was toxic (EC(L)₅₀) to crustaceans at ~12 mg/L, and ranked accordingly as ‘harmful’ [L(E)C₅₀ > 10–100 mg/L]. Thus, silver-chitosan nanocomposites may pose a hazard to aquatic organisms and must be handled accordingly. Full article

As a member of the pattern recognition receptor (PRR) class, scavenger receptor class B type 1 (SRB1) plays a key role in innate immunity. Grass carp (Ctenopharyngodon idellus) ranks among the most extensively cultivated freshwater aquaculture species in China. However, little is known about the function of SRB1 in C. idellus. In this research study, a SRB1 gene was identified in C. idellus, named CiSRB1. The full-length cDNA of CiSRB1 is 2486 bp long, with an open reading frame (ORF) of 2486 bp encoding a 497 amino acid (aa) protein containing a conserved CD36 domain. The identified genomic DNA length of CiSRB1 is 20,042 bp, including 12 exons and 11 introns. The predictive analysis of protein interactions revealed that CiSRB1 could interact with the outer capsid proteins of typical GCRV strains. The tissue distribution of CiSRB1 exhibited age-dependent characteristics. CiSRB1 displayed the highest expression in the intestines and moderate levels in muscle, spleen, liver, and brain of one-year-old grass carp while maintaining relatively low levels in three-year-old grass carp. Following grass carp reovirus (GCRV) infection, notable upregulation of CiSRB1 transcripts was observed in major immune tissues (gills, intestines, spleen, and liver). Furthermore, significant differences were found between one-year-old and three-year-old grass carp, with lower CiSRB1 expression levels being detected in the older group. Additionally, a distinct response to GCRV infection was observed in one-year-old and three-year-old grass carp. It was found that one-year-old individuals had a mortality rate of up to 84% 6 days post-infection (dpi), whereas all three-year-old counterparts survived after GCRV infection. The analysis of GCRV copy numbers across tissues revealed substantially higher levels in one-year-old grass carp compared with their older counterparts, confirming the existence of age-dependent susceptibility to GCRV infection in grass carp. Combined with these results, it was speculated that the decline in cell-surface CiSRB1 expression with age may impede reovirus binding to host cells, potentially explaining why older grass carp demonstrated enhanced resistance to GCRV infection. This observation accentuates the importance of CiSRB1 in the context of GCRV infection and provides insights into age-dependent susceptibility to reovirus. Full article

In the sphere of urban renewal of historic districts, preserving and innovatively reinterpreting traditional architectural styles remains a primary research focus. However, the modernization and adaptive reuse of traditional buildings often necessitate changes in their functionality. To cater to the demands of tourism in historic districts, many traditional residential buildings require conversion to commercial use, resulting in a mismatch between their external form and their internal function. This study explored an automated approach to transform traditional residences into commercially viable designs, offering an efficient and scalable solution for the modernization of historic architecture. We developed a methodology based on diffusion models, focusing on a dataset of nighttime shopfront facades. By training a low-rank adaptation (LoRA) model and integrating the ControlNet model, we enhanced the accuracy and stability of the generated images. The methodology’s performance was validated through qualitative and quantitative assessments, optimizing the batch size, repetition, and learning rate configurations. These evaluations confirmed the method’s effectiveness. Our findings significantly advance the modern commercial style transformation of historical architectural facades, providing a novel solution that maintains the aesthetic and functional integrity, thereby fostering breakthroughs in traditional design thinking and exploring new possibilities for the preservation and commercial adaptation of historical buildings. Full article

The escalating global rates of precancerous lesions associated with human papillomavirus (HPV) types not targeted by current vaccines underscore the need to explore the prevalence of HPV types within the Greek female population and their involvement in precancerous lesion development. In the current study, we enrolled a cohort of 253 women aged 18 to 65 years, residing in Greece, who underwent routine screening in three tertiary care referral hospitals. Each participant completed a demographic questionnaire. An HPV DNA test was administered using the VisionArray^® HPV kit (ZytoVision GmbH) to qualitatively detect and genotype 41 clinically relevant HPV genotypes. Of all 253 women examined, 114 (45.1%) tested positive for HPV DNA. The primary type detected was HPV51 (high-risk), present in 21 women (8.3% of the total), followed by HPV54 (low-risk) in 17 women (6.7%); HPV16 (high-risk) ranked third, identified in 14 women (5.5%). Among the HPV-positive women, 65 were positive for high-risk HPV types (57% of HPV-positive women) and were referred for colposcopy and cervical biopsy. These procedures identified 24 women with cervical intraepithelial neoplasia 1 (CIN1) lesions and 2 with cervical intraepithelial neoplasia 2 (CIN2) lesions. The most prevalent HPV type among women with CIN1 lesions was HPV16, found in nine (37.5%) women, while HPV51 ranked second, identified in six (25%) women. Both women with CIN2 lesions tested positive for HPV16, whereas one of them was also tested positive for HPV45. Our study is the first to report the prevalence of HPV51 among HPV-positive women in the Greek female population. This highlights the need for further research to fully understand the potential of HPV types not covered by current vaccines, such as HPV51, to cause high-grade lesions or cervical cancer. Full article

Synovial sarcoma (SS) is a rare soft-tissue tumor characterized by a monomorphic blue spindle cell histology and variable epithelial differentiation. Morphologically, SSs may be confused with other sarcomas. Systemic treatment is more effective for patients with high-risk SSs, patients with advanced disease, and younger patients. However, further studies are required to find new prognostic biomarkers. Herein, we describe the morphological, molecular, and clinical findings, using a wide immunohistochemical panel, of a series of SS cases. We studied 52 cases confirmed as SSs by morphological diagnosis and/or molecular studies. Clinical data (gender, age, tumor size, tumor location, resection margins, adjuvant treatment, recurrences, metastasis, and survival) were also retrieved for each patient. All the available H&E slides were examined by four pathologists. Three tissue microarrays (TMAs) were constructed for each of the tumors, and a wide immunohistochemical panel was performed. For time-to-event variables, survival analysis was performed using Kaplan–Meier curves and log-rank testing, or Cox regression. Statistical significance was considered at p < 0.05. The mean age of our patients was 40.33, and the median was 40.5 years. We found a predominance of males versus females (1.7:1). The most frequent morphological subtype was monophasic. TRPS1, SS18-SSX, and SSX-C-terminus were positive in 96% of cases. GLI1 expression was strong in six and focal (cytoplasmic) in twenty patients. Moreover, BCOR was expressed in more than half of SSs. Positive expression of both proteins, BCOR and GLI1, was correlated with a worse prognosis. Multivariate analysis was also performed, but only BCOR expression appeared to be significant. The combination of GLI1 and BCOR antibodies can be used to group SSs into three risk groups (low, intermediate, and high risk). We hypothesize that these findings could identify which patients would benefit from receiving adjuvant treatment and which would not. Moreover, these markers could represent therapeutic targets in advanced stages. However, further, larger series of SSs and molecular studies are necessary to corroborate our present findings. Full article

Email is an excellent technique for connecting users at low cost. Spam emails pose the risk of collecting a user’s personal information by fooling them into clicking on a link or engaging in other fraudulent activities. Furthermore, when a spam message is delivered, the user may read the entire message before deciding it is spam and deleting it. Most approaches to email classification proposed by other authors use natural language processing (NLP) methods to analyze the content of email messages. One of the biggest shortcomings of NLP-based methods is their dependence on the language in which a message is written. To construct an effective email cyber threat intelligence (CTI) sharing framework, the privacy of a message’s content must be preserved. This article proposes a novel domain-specific ontology and method for emails that require only the metadata of email messages to be shared to preserve their privacy, making them applicable to solutions for sharing email CTI. To preserve privacy, a new semantic parser was developed for the proposed email domain-specific ontology to populate email metadata and create a dataset. Machine learning algorithms were examined, and experiments were conducted to identify and classify spam messages using the newly created dataset. Feature-ranking algorithms, chi-squared, ANOVA (analysis of variance), and Kruskal–Wallis tests were used. In all experiments, the kernel naïve Bayes model demonstrated acceptable results. The highest accuracy of 92.28% and an F1 score of 95.92% for recognizing spam email messages were obtained using the proposed domain-specific ontology, the newly developed semantic parser, and the created metadata dataset. Full article

In existing image retrieval algorithms, negative samples often appear at the forefront of retrieval results. To this end, in this paper, we propose a feature fusion-based re-ranking method for home textile image retrieval, which utilizes high-level semantic similarity and low-level texture similarity information of an image and strengthens the feature expression via late fusion. Compared with single-feature re-ranking, the proposed method combines the ranking diversity of multiple features to improve the retrieval accuracy. In our re-ranking process, Markov random walk is used to update the similarity metrics, and we propose local constraint diffusion based on contextual similarity. Finally, the fusion–diffusion algorithm is used to optimize the sorted list via combining multiple similarity metrics. We set up a large-scale home textile image dataset, which contains $89k$ home textile product images from $12k$ categories, and evaluate the image retrieval performance of the proposed model with the Recall@k and mAP@K metrics. The experimental results show that the proposed re-ranking method can effectively improve the retrieval results and enhance the performance of home textile image retrieval. Full article

Graph representation learning aims to map nodes or edges within a graph using low-dimensional vectors, while preserving as much topological information as possible. During past decades, numerous algorithms for graph representation learning have emerged. Among them, proximity matrix representation methods have been shown to exhibit excellent performance in experiments and scale to large graphs with millions of nodes. However, with the rapid development of the Internet, information interactions are happening at the scale of billions every moment. Most methods for similarity matrix factorization still focus on static graphs, leading to incomplete similarity descriptions and low embedding quality. To enhance the embedding quality of temporal graph learning, we propose a temporal graph representation learning model based on the matrix factorization of Time-constrained Personalize PageRank (TPPR) matrices. TPPR, an extension of personalized PageRank (PPR) that incorporates temporal information, better captures node similarities in temporal graphs. Based on this, we use Single Value Decomposition or Nonnegative Matrix Factorization to decompose TPPR matrices to obtain embedding vectors for each node. Through experiments on tasks such as link prediction, node classification, and node clustering across multiple temporal graphs, as well as a comparison with various experimental methods, we find that graph representation learning algorithms based on TPPR matrix factorization achieve overall outstanding scores on multiple temporal datasets, highlighting their effectiveness. Full article

Large-scale group decision-making (LSGDM) involves aggregating the opinions of participating decision-makers into collective opinions and selecting optimal solutions, addressing challenges such as a large number of participants, significant scale, and a low consensus. In real-world scenarios of LSGDM, various challenges are often encountered due to factors such as fuzzy uncertainties in decision information, the large size of decision groups, and the diverse backgrounds of participants. This paper introduces a dual fine-tuning-based LSGDM method using an online review. Initially, the sentiment analysis is conducted on online review data, and the identified sentiment words are graded and quantified into a fuzzy data set to understand the emotional tendencies of the text. Then, the Louvain algorithm is used to cluster the decision-makers. Meanwhile, a method combining Euclidean distances with Wasserstein distances is introduced to accurately measure data similarities and improve clustering performances. During the consensus-reaching process (CRP), a two-stage approach is employed to adjust the scores: to begin with, by refining the scores of the decision representatives via minor-scale group adjustments to generate a score matrix. Then, by identifying the scores corresponding to the minimum consensus level in the matrix for adjustment. Subsequently, the final adjusted score matrix is integrated with the prospect–regret theory to derive the comprehensive brand scores and rankings. Ultimately, the practicality and efficiency of the proposed model are demonstrated using a case study focused on the purchase of solar lamps. In summary, not only does the model effectively extract the online review data and enhance decision efficiency via clustering, but the dual fine-tuning mechanism in the model to improve consensus attainment also reduces the number of adjustment rounds and avoids multiple cycles without achieving the consensus. Full article

We advanced the practical development of compressive hyperspectral cameras for remote sensing scenarios with a design that simultaneously compresses and captures high-quality spectral information of a scene via configurable measurements. We built a prototype imaging system that is compatible with light-modulation devices that encode the incoming spectrum. The sensing approach enables a substantial reduction in the volume of data collected and transmitted, facilitating large-scale remote hyperspectral imaging. A main advantage of our sensing design is that it allows for adaptive sampling. When prior information of a survey region is available or gained, the modulation patterns can be re-programmed to efficiently sample and detect desired endmembers. Given target spectral signatures, we propose an optimization scheme that guides the encoding process. The approach severely reduces the number of required sampling patterns, with the ability to achieve image segmentation and correct distortions. Additionally, to decode the modulated data, we considered a novel reconstruction algorithm suited for large-scale images. The computational methodology leverages the multidimensional structure and redundant representation of hyperspectral images via the canonical polyadic decomposition of multiway arrays. Under realistic remote sensing scenarios, we demonstrated the efficiency of our approach with several data sets collected by our prototype camera and reconstructed by our low-rank tensor decoder. Full article

A series of ester-linked tetracarboxylic dianhydrides containing multiple para-phenylene units (TA-pPhs) was synthesized to obtain novel modified polyimides, namely poly(ester imide)s (PEsIs). The flame retardancy and film toughness of PEsIs tended to deteriorate with the structural extension of the repeating units (or monomers) via ester groups. To identify the structural factors necessary for achieving the highest flame retardancy rank (UL-94, V-0), we systematically investigated the structure–property relationships of a series of TA-pPh-based PEsIs. Among them, a PEsI derived from para-quaterphenylene-containing TA-pPh (TA-DPQP) and p-phenylenediamine (p-PDA) exhibited the best property combination, featuring an extremely high glass transition temperature (T_g), very low linear coefficient of thermal expansion (CTE), low water uptake (W_A), ultralow linear coefficient of humidity (hygroscopic) expansion (CHE), unexpectedly high film toughness, and excellent flame retardancy (V-0 rank). Moreover, we examined the effects of substituents of TA-pPh and discussed the mode of action for the increased film toughness. This study also investigated the structure–property relationship for a series of PEsIs derived from isomeric naphthalene-containing tetracarboxylic dianhydrides. Some of the PEsIs obtained in this study, such as the TA-DPQP/p-PDA system, hold promise as novel high-temperature dielectric substrates for use in flexible printed circuits. Full article

An assessment of soil characteristics pertaining to their suitability for agricultural use in general is necessary to reverse the declining trend of soil quality and to ensure sustainable agriculture. The aim of this study was to determine the soil resistance (SRI) and degradation indices (SDI) under different agrotechniques and to find out whether management-induced changes are large enough to reduce soil degradation. The study was based on the comparison of physicochemical data of 3 long-term experiments conducted in the western part of Lithuania. Changes in soil properties over the past 20 years (1999–2019) have been determined. The most commonly used measures in Lithuania, such as soil liming, manuring, residue maintenance, and tillage, were selected for the analysis. The analysis carried out showed that the soil, which was fertilized with manure, had a higher value of soil quality parameters compared to natural Retisol: organic matter (by 0.53 percentage points), total nitrogen (by 0.04 percentage points), and the available amounts of phosphorus (by 69 mg/kg) and potassium (by 6.6 mg/kg). The assessment of the relative annual change in SOC content revealed that long-term soil manuring has significant SOC sequestration capability. Among the soil management techniques examined, it appeared that the greatest relative annual change (0.47 g kg⁻¹yr⁻¹) in SOC content was noted in manured soil. The results indicate that the higher degradation, and resistance values were observed in acid soil (pH 4.2), where liming was applied, indicating greater sensitivity to degradation. Based on analyzed indices, the agricultural practices ranked as: manuring > residue management > reduced tillage > liming. The lowest SRI values were obtained for low level of nutrients (from −0.11 to 0.89), organic carbon (from −0.72 to −0.49), and pH (from −0.25 to –0.1), indicating that these properties are more sensitive to applied agricultural practices compared to others. All these findings provide information for promoting better soil management, soil protection, land use planning, and the planning of remedial measures, especially in the most afflicted areas. Full article

This study examines the correspondence between the borrowability indices from the Loanwoard Typology (LWT) project and Castilianization indices from the Atlas Lingüístico Galego (ALGa) across seven semantic fields. To this end, we identified all Castilianisms in the ALGa and conducted a quantitative analysis to compare these indices. Results obtained indicate a mismatch between the rankings of the LWT project and the ALGa. For example, the field ‘The body’ has the highest level of Castilianization according to the ALGa but the lowest borrowed score in the LWT project. Moreover, Castilianization levels in the ALGa show greater dispersion than borrowability levels from the LWT project. In fact, in each semantic field, many concepts (52.2%) have low levels of Castilianization, between 0% and 10%, and only a few concepts have high levels. A more detailed analysis of three semantic fields (‘The body’, ‘Agriculture and vegetation’, and ‘The physical world’) suggests that explanations based solely on semantic criteria (such as the existence of an unalterable central lexicon) are insufficient; other factors such as prestige, urbanization, cultural modernity, frequency of word usage, and perhaps other intralinguistic factors should be taken into account. Full article

Osteoarthritis is associated with high risks of sarcopenia in older populations. Exercise interventions are promising treatments for musculoskeletal impairments in knee osteoarthritis (KOA). The purpose of this study was to identify the comparative effects of exercise monotherapy and its adjunct treatments on muscle volume and serum inflammation for older individuals with KOA. A literature search in the electronic databases was comprehensively performed from this study’s inception until April 2024 to identify relevant randomized controlled trials (RCTs) that reported muscle morphology and inflammation outcomes after exercise. The included RCTs were analyzed through a frequentist network meta-analysis (NMA). The standard mean difference (SMD) with a 95% confidence interval was estimated for treatment effects on muscle morphology and inflammation biomarkers. The relative effects on each main outcome among all treatment arms were compared using surface under the cumulative ranking (SUCRA) scores. The certainty of evidence (CoE) was assessed by the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) ranking system. Probable moderators of the treatment efficacy were investigated by network meta-regression analysis. This study included 52 RCTs (4255 patients) for NMA. Among the 27 identified treatment arms, isokinetic training plus physical modality as well as low-load resistance training plus blood-flow restriction yielded the most optimal treatment for inflammation reduction (−1.89; SUCRA = 0.97; CoE = high) and muscle hypertrophy (SMD = 1.28; SUCRA = 0.94; CoE = high). The patient’s age (β = −0.73), the intervention time (β = −0.45), and the follow-up duration (β = −0.47) were identified as significant determinants of treatment efficacy on muscle hypertrophy. Exercise therapy in combination with noninvasive agents exert additional effects on inflammation reduction and muscle hypertrophy compared to its corresponding monotherapies for the KOA population. However, such treatment efficacy is likely moderated by the patient’s age, the intervention time, and the follow-up duration. Full article

Tillage practices are of critical importance in maintaining soil quality on cropland and for food production, with rice cultivation representing a significant portion of the world’s food production and greenhouse gas (GHG) emissions. While numerous studies have examined the effects of reduced and no-tillage on soil GHG emissions and rice yields, the impact of adopting a rotational approach to tillage practices on the rice cultivation cycle remains uncertain. In this study, we conducted a four-year (2017–2020) field experiment in a single rice-growing area in Northeast China with the aim of investigating the effects of different tillage practices on GHG emissions from paddy fields and rice yields under full straw return conditions. We set up three experimental treatments: rotary tillage, plowing, and rotational tillage (i.e., a combination of one year of plowing and one year of rotary tillage). The results showed that averaged across all treatments, average methane (CH₄, 302.6 ± 51.1 kg ha⁻¹) and nitrous oxide (N₂O, 0.86 ± 0.361 kg ha⁻¹) emissions and rice yield (9.0 ± 0.9 t ha⁻¹) did not exhibit significant inter-annual variability during the entire experimental period and were comparable to the average for the region. The ranking of GHG emissions during the rice-growing season was as follows: rotary tillage > plowing > rotational tillage. Across the experimental period, CH₄ and N₂O emissions were 9.1% and 8.5% lower in the plowing treatment and 21.2% and 13.1% lower in the rotational tillage treatment compared to the rotary tillage treatment. During the experimental period, there was no significant effect of tillage treatments on rice yield. This reduction in emissions may be attributed to changes in soil penetration resistance. In the rotational and plowing treatments, soil penetration resistance was in a range more adapted to rice growth and GHG emissions reduction compared to the rotary tillage treatment. The yield-scale GHG emission intensity was reduced by 12.7% and 26.1% in the plowing and rotational tillage treatments, respectively, in comparison to the rotary tillage treatment. This suggests that rotational tillage is a management practice that can achieve greenhouse gas emission reductions in paddy fields and stabilize or possibly increase rice yields. Consequently, the results demonstrated that a rotational alternation of multiple tillage practices is a synergistic strategy for achieving low carbon and high yield in rice in the cold rice-growing region of Northeast China. Full article