Search Results (150,111)

Soil desiccation cracks are common in farmland under dry conditions, which can alter soil water movement by providing preferential flow paths and thus affect water and fertilizer use efficiency. Understanding the mechanism of soil shrinkage and cracking is of great significance for optimizing field management by crack utilization or prevention. The behavior of soil shrinkage and cracking was monitored during drying experiments and analyzed with the help of a digital image processing method. The results showed that during shrinkage, the changes in soil height and equivalent diameter with water content differed significantly. The height change consisted of a rapid decline stage and a residual stage, while the equivalent diameter had a stable stage before the rapid decline stage. The VG-Peng model was suitable to fit the soil shrinkage characteristic curves, and the curves revealed that the soil shrinkage contained structural shrinkage, proportional shrinkage, residual shrinkage, and zero shrinkage stages. According to the changes in evaporation intensity, soil water evaporation could be divided into three stages: stable stage, declining stage, and residual stage. Cracks first formed in the defect areas and edge areas of the soil, and they mainly propagated in the stable evaporation stage. Crack development was dominated by an increase in crack length during the early cracking stage, while the propagation of crack width played a major role during the later stage. At the end of drying, the contribution ratio of crack length and width to the crack area was approximately 30% and 70%, respectively. The box-counting fractal dimension of the stabilized cracks was approximately 1.65, indicating that the crack network had significant self-similarity. The experimental results were used to implement the discrete element method to model the process of soil shrinkage and cracking. The models could effectively simulate the variation characteristics of soil height and equivalent diameter during shrinkage, as well as the variation characteristics of crack ratio and length density during cracking, with acceptable relative errors. In particular, the modeled morphology of the crack network was highly similar to the experimental observation. Our results provide new insights into the characterization and simulation of soil desiccation cracks, which will be conducive to understanding crack evolution and soil water movement in farmland. Full article

The genus Quercus is an ecological keystone and economically vital component of Northern Hemisphere forests. While genomic studies have advanced our understanding of its nuclear and chloroplast genomes, the mitochondrial genomes of oaks remain less explored due to their complex evolutionary dynamics, which include extreme size variation, frequent rearrangements, and recurrent horizontal gene transfer. This study presents the assembly, annotation, and comparative analysis of mitogenomes from three closely related Asian oaks—Q. engleriana, Q. kongshanensis, and Q. tungmaiensis—using PacBio HiFi sequencing. The assemblies revealed distinct structural organizations: the Q. engleriana and Q. kongshanensis mitogenomes each comprised one circular contig and one linear contig, whereas the Q. tungmaiensis mitogenome comprised one circular contig and two linear contigs. Comparative analyses revealed variations in codon usage bias, simple sequence repeats, and predicted RNA editing sites. Notably, RNA editing in rps12 was uniquely observed in Q. kongshanensis. Mitochondrial targeting of plastid transcripts constituted 1.39%, 1.79%, and 2.24% of the mitogenomes, respectively. Phylogenetic reconstruction based on mitochondrial PCGs robustly resolved Q. kongshanensis and Q. tungmaiensis as sister species, with all three forming a distinct clade separate from other Quercus species. This study provides comprehensive mitogenomic resources essential for elucidating Quercus evolutionary biology and supporting germplasm development. Full article

Salmonella is a major zoonotic pathogen and phage cocktails offer a novel strategy against its infections. This study aimed to characterize Salmonella phages and assess the efficacy of various phage combinations, both in vitro and in vivo. Three phages (PJN012, PJN042, PJN065) were isolated, showing stability across a broad range of temperatures and pH values, and lacking genes associated with lysogenicity, virulence, and antibiotic resistance. Combined with two known phages (PJN025, vB_SalS_JNS02), they formed cocktails tested for lytic activity against S. Enteritidis and S. Typhimurium. Phage cocktails (comprising 2–5 phages) that demonstrated efficacy in vitro were validated using Galleria mellonella models. For S. Enteritidis strain 015, prophylactic cocktail C18 increased larval survival to 90% at 48 h (vs. 3% control). For S. Typhimurium strain 024, phage cocktail 26 showed the best therapeutic effect when co-injected with the bacterium, with a survival rate of up to 85% at 96 h, compared to 30% in the positive control group. Biofilm assays showed cocktails inhibited formation more effectively (e.g., at 24 h, C14 and C17 reduced biofilm formation by 93.74% and 94.21%, respectively) than removed established ones. The cocktails depended on bacterial type, phage genera, combinations, and incubation time. Robust in vitro screening remains crucial for optimizing phage formulations despite potential in vivo discrepancies. Full article

In this paper, a new 3D printing system based on temperature–pressure double closed-loop collaborative control is proposed to solve the problem of 3D printing accuracy of starch food. The rapid and accurate adjustment of the nozzle temperature is realized by the hybrid control of Bang-Bang and PID, and the extrusion pressure is optimized in real time by combining the adaptive fuzzy PID algorithm, which effectively reduces the influence from the change of material rheological properties and external interference. The experimental results show that the printing accuracy of the system is up to 98% at 40 °C, the pressure fluctuation is reduced by 80%, and the molding accuracy of complex structures is improved to 97%, which significantly improves the over-extrusion and under-extrusion, and provides an effective solution for stable and high-precision printing of high-viscosity food materials. Full article

Cardiac inflammation and hypertrophy develop as a pathologic response to an array of insults, such as myocardial infarctions, chronic systemic hypertension, and valvular defects. Due to the high prevalence of such conditions, there is an increasing need to prevent and halt cardiac hypertrophy. Because cardiac damage and subsequent remodeling can lead to arrhythmias, heart failure, and even sudden cardiac death, inhibition of cardiac hypertrophy is key to reducing cardiovascular-related mortality. The immune system is the driving force behind inflammatory reactions. All three pathways of complement system activation—classical, lectin, and alternative—are implicated in developing cardiac damage, inflammation, and hypertrophy due to infectious and non-infectious causes, autoimmune diseases, genetic polymorphisms, and forms of complement dysregulation. Of interest in this review is the role of the complement system, a collection of soluble and membrane-bound proteins that mediate inflammatory processes through interactions with signaling molecules and immune cells. This review comprehensively discusses the roles of these complement pathways in contagious, chronic inflammatory, genetic, and metabolic diseases. An overview of the completed and terminated clinical trials aimed at preventing cardiovascular mortality by targeting various aspects of the complement system and inflammatory reaction is included. Most current treatments for cardiac inflammation and remodeling primarily target the renin–angiotensin–aldosterone system (RAAS), which prevents further remodeling by reducing myocardial workload. However, moving forward, there may be a place for emerging anti-complement therapeutics, which impair the inflammatory response that generates hypertrophy itself. Full article

This paper studies discontinuous quasilinear sub-elliptic systems associated with Hörmander’s vector fields under controllable and natural growth conditions. By a new $\mathcal{A}$-harmonic approximation reformulation for bilinear forms $\mathcal{A}\in \mathrm{Bil}({\mathbb{R}}^{kN},{\mathbb{R}}^{kN})$, we obtain optimal partial Hölder continuity with exact exponents for weak solutions with vanishing mean oscillation coefficients. Full article

The shadow economy weakens fiscal sustainability, hampers the financing of public goods, and impedes the achievement of sustainable development goals. The informal sector remains a persistent challenge for policymakers, as it distorts competition, reduces transparency, and undermines the effectiveness of economic and fiscal policies. The aim of this article is to identify the key factors determining the size of the shadow economy in European Union countries and to provide policy-relevant insights. The analysis covers data on the share of the informal economy in GDP and macroeconomic variables such as GDP per capita, consumer price index, average wages, household consumption, government expenditure, and unemployment, as well as indicators of digital development in society and the economy (DESI, IDT), the share of cashless transactions in GDP, and information on the implementation of digital tax administration tools and restrictions on cash payments. Five hypotheses (H1–H5) are formulated concerning the effects of income growth, labour market conditions, digitalisation, cashless payments, and tax administration tools on the shadow economy. The research question addresses which factors—macroeconomic conditions, economic and social digitalisation, payment structures, and fiscal innovations in tax administration—play the most significant role in determining the size of the shadow economy in EU countries and whether these mechanisms have broader implications for fiscal sustainability and sustainable development. The empirical strategy is based on multilevel models with countries as clusters, complemented by correlation and comparative analyses. The results indicate that the most significant factor in limiting the size of the shadow economy is the level of GDP per capita and its growth, whereas the impact of card payments appears to be superficial, reflecting overall increases in wealth. Higher wages, household consumption, and digital development as measured by the DESI also play an important role. The implementation of digital solutions in tax administration, such as SAF-T or e-PIT/pre-filled forms, along with restrictions on cash transactions, can serve as complementary measures. The findings suggest that sustainable strategies to reduce the shadow economy should combine long-term economic growth with digitalisation and improved tax administration, which may additionally foster the harmonisation of economic systems and support sustainable development. Full article

Increasing the amount of data with complex dynamics requires the constant updating of statistical distributions. This study aimed to introduce a new three-parameter distribution, named the new exponentiated Weibull (NEW) distribution, by applying the logarithmic transformation to the exponentiated Weibull distribution. The exponentiated Weibull distribution is a powerful generalization of the Weibull distribution that includes several classical distributions as special cases—Weibull, exponential, Rayleigh, and exponentiated exponential—which make it capable of capturing diverse forms of hazard functions. By combining the advantages of the logarithmic transformation and exponentiated Weibull, the new distribution offers great flexibility in modeling different forms of hazard functions, including increasing, J-shaped, reverse-J-shaped, and bathtub-shaped functions. Some mathematical properties of the NEW distribution were studied. Moreover, four different methods of estimation—the maximum likelihood (ML), least squares (LS), Cramer–Von Mises (CVM), and percentile (PE) methods—were employed to estimate the distribution parameters. To assess the performance of the estimates, three simulation studies were conducted, showing the benefit of the ML method, followed by the PE method, in estimating the model parameters. Additionally, five datasets were used to evaluate the effectiveness of the new distribution in fitting real data. Compared with some Weibull-type extensions, the results demonstrate the superiority of the new distribution in modeling various forms of real data and provide evidence for the applicability of the new distribution. Full article

N-Acetylneuraminic acid (Neu5Ac), the predominant form of sialic acids (Sias), is extensively utilized in the food, pharmaceutical, and cosmetic industries. Microbial fermentation serves as a critical production method for its economical, eco-friendly, and scalable production. Escherichia coli and Bacillus subtilis, as primary industrial workhorses for Neu5Ac production, have been extensively investigated owing to their well-characterized genetic frameworks and mature molecular toolkits. Nevertheless, the intricate regulatory networks inherent to microbial systems present formidable obstacles to the high-efficiency biosynthesis of Neu5Ac. This review delineates the genetic and molecular mechanisms underlying Neu5Ac biosynthesis in both E. coli and B. subtilis. Furthermore, the rational and irrational strategies for constructing Neu5Ac microbial cell factories are systematically summarized, including the application of rational metabolic engineering to relieve feedback regulation, reconfigure metabolic networks, implement dynamic regulation, and optimize carbon sources; as well as the use of irrational strategies including directed evolution of key enzymes and high-throughput screening based on biosensors. Finally, this review addresses current challenges in Neu5Ac bioproduction and proposes integrative solutions combining machine learning with systems metabolic engineering to advance the construction of high-titer Neu5Ac microbial cell factory and the refinement of advanced fermentation technologies. Full article

Texture testing is applied in various industries. Recently, a simple, accelerometer-equipped texture testing device (Surface Tester of Food Resilience; STFR) has been developed, and we elaborated formulae describing the movement of the probe. In this paper, we describe the validation of said formulae, relying on video image analysis of the travel of the spherical probe. This allowed us to select the best-fit mathematical models. We elaborated formulae for accurate calculation of specimen surface characteristics and present an application integrating these formulae in the test procedure. The impact of correct height adjustment and specimen height was found to be critical for reproducibility of measurements and thus needs attendance. These findings form the basis for future comparative studies with established texture analyzers. Full article

Micro-arc oxidation (MAO) technology demonstrates remarkable advantages in fabricating ceramic coatings on lightweight alloys. For aluminum alloys, MAO rapidly forms dense, pore-free ceramic layers within minutes, significantly enhancing corrosion and wear resistance at low processing costs. In magnesium alloys, optimized electrolyte compositions and process parameters enable composite coatings with a combination of high hardness and self-lubrication properties, while post-treatments like laser melting or corrosion inhibitors extend salt spray corrosion resistance. Titanium alloys benefit from MAO coatings with exceptional interfacial bonding strength and mechanical performance, making them ideal for biomedical implants and aerospace components. Notably, dense ceramic oxide films grown in situ via MAO on high-entropy alloys (HEAs) triple surface hardness and enhance wear/corrosion resistance. However, MAO applications on steel require pretreatments like aluminizing, thermal spraying, or ion plating. Current challenges include coating uniformity control, efficiency for complex geometries, and long-term stability. Future research focuses on multifunctional coatings (self-healing, antibacterial) and eco-friendly electrolyte systems to expand engineering applications. Full article

Contamination with heavy metals, including chromium that exists in two oxidation states—Cr(III) and Cr(VI)—poses a significant challenge for the soil environment. Both chemical forms of chromium can exert toxic effects on microorganisms that play a key role in maintaining soil fertility and plant health. The aim of the study was to compare the selective toxic effects of Cr(III) and Cr(VI) ions on soil bacterial and fungal taxonomic diversity using NGS technology. The data obtained enabled a comprehensive characterisation of the taxonomic profile of the soil microbiome exposed to both forms of chromium, providing a basis for further research into the adaptation and resistance mechanisms of microorganisms. The calculated diversity indices, in particular the Shannon-Wiener index, suggest that Cr(VI) is more toxic to bacteria than Cr(III). In soil contaminated with chromium, the relative abundance of chromium-resistant bacteria of the phylum Actinobacteriota increased to the detriment of chromium-sensitive Acidobacteriota and Proteobacteriota. The abundance of Ascomycota, the dominant fungal phylum, increased in soil with Cr(III) and decreased in soil with Cr(VI). Cr(III) promoted the growth of bacteria of the genera Phycicoccus and Arthrobacter and Penicillium fungi. In turn, Cr(VI) stimulated the growth of bacteria of the genera Mycoplana and Cellulosimicrobium, and Trichoderma fungi. The study demonstrated that microbial resistance mechanisms are influenced by the chemical form of chromium. In addition, the increased abundance of chromium-resistant taxa highlights their potential for the bioremediation of soils contaminated with this element. Full article

Minerals bearing rare earth elements (REEs) are formed through long geological processes, among which monazite, bastnasite, xenotime, and ionic adsorption clays are the most economically exploited. Although Brazil has one of the largest reserves of REEs on the planet, its production is still not significant on the world stage. China remains dominant, with the largest reserves of REEs and controlling more than half of world production. Due to their important application in advanced clean and low-carbon energy technologies, REEs have become fundamental to the energy transition process. Technological applications related to catalyst synthesis, ceramics production, and metallurgy have been explored. Furthermore, the use of REEs in devices of great demand today, such as computer memory, rechargeable batteries, and mobile phones, has been cited. With the growing demand for these critical minerals, large mining companies are seeking to implement cleaner production policies in their processes and save natural resources to minimize the environmental impacts of the exploration. Robust analytical techniques have made it possible to characterize these elements in multi-element geological matrices, with the increasing exploration and identification of new REE mineral reserves. Full article

Urbanization generates large quantities of arsenic-contaminated excavated soils that pose environmental risks due to arsenic volatilization during high-temperature sintering processes. While these soils have potential for recycling into construction materials, their reuse is hindered by arsenic release. This study demonstrated calcium hydroxide (Ca(OH)₂) as a highly effective additive for suppressing arsenic volatilization during soil sintering, while simultaneously improving material properties. Through comprehensive characterization using inductively coupled plasma-mass spectrometry (ICP-MS), scanning electron microscopy (SEM) and X-ray microtomography (μCT), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS), results demonstrated that Ca(OH)₂ addition (0.5–2 wt.%) reduces arsenic volatilization by 57% through formation of thermally stable calcium arsenate (Ca₃(AsO₄)₂). Ca(OH)₂ acted via two mechanisms: (a) chemical immobilization through Ca-As-O compound formation, (b) physical encapsulation in a calcium-aluminosilicate matrix during liquid-phase sintering, and (c) pH buffering that maintains arsenic in less volatile forms. Optimal performance was achieved at 0.5% Ca(OH)₂, yielding 9.14 MPa compressive strength (29% increase) with minimal arsenic leaching (<110 ppb). Microstructural analysis showed Ca(OH)₂ promoted densification while higher doses increased porosity. This work provides a practical solution for safe reuse of arsenic-contaminated soils, addressing both environmental concerns and material performance requirements for construction applications. Full article

Background: Cardiovascular diseases (CVDs) remain the primary cause of global mortality, with arterial hypertension, ischemic heart disease (IHD), and cerebrovascular accident (CVA) forming a progressive continuum from early risk factors to severe outcomes. While numerous studies focus on isolated biomarkers, few integrate multidimensional visualization with artificial intelligence to reveal hidden, clinically relevant patterns. Methods: We conducted a comprehensive analysis of 106 patients using an integrated framework that combined clinical, biochemical, and lifestyle data. Parameters included renal function (glomerular filtration rate, cystatin C), inflammatory markers, lipid profile, enzymatic activity, and behavioral factors. After normalization and imputation, we applied correlation analysis, parallel coordinates visualization, t-distributed stochastic neighbor embedding (t-SNE) with k-means clustering, principal component analysis (PCA), and Random Forest modeling with SHAP (SHapley Additive exPlanations) interpretation. Bootstrap resampling was used to estimate 95% confidence intervals for mean absolute SHAP values, assessing feature stability. Results: Consistent patterns across outcomes revealed impaired renal function, reduced physical activity, and high hypertension prevalence in IHD and CVA. t-SNE clustering achieved complete separation of a high-risk group (100% CVD-positive) from a predominantly low-risk group (7.8% CVD rate), demonstrating unsupervised validation of biomarker discriminative power. PCA confirmed multidimensional structure, while Random Forest identified renal function, hypertension status, and physical activity as dominant predictors, achieving robust performance (Accuracy 0.818; AUC-ROC 0.854). SHAP analysis identified arterial hypertension, BMI, and physical inactivity as dominant predictors, complemented by renal biomarkers (GFR, cystatin) and NT-proBNP. Conclusions: This study pioneers the integration of multidimensional visualization and AI-driven analysis for CVD risk profiling, enabling interpretable, data-driven identification of high- and low-risk clusters. Despite the limited single-center cohort (n = 106) and cross-sectional design, the findings highlight the potential of interpretable models for precision prevention and transparent decision support in cardiovascular aging research. Full article