Search Results (1,729)

Background: Accurate estimation of the postmortem interval (PMI) is critical in forensic death investigations. Traditional signs of death—algor mortis, livor mortis, and rigor mortis—are generally reliable only within the first two to three days after death, with their accuracy decreasing as decomposition progresses. This paper presents a systematic review conducted in accordance with PRISMA guidelines, aiming to evaluate and compare current methods for estimating the PMI. Specifically, the study identifies both traditional and modern techniques, analyzes their advantages, limitations, and applicable timeframes, critically synthesizes the literature, and highlights the importance of combining multiple approaches to improve accuracy. Methods: A systematic search was conducted in the PubMed, Scopus, and Web of Science databases, following the PRISMA guidelines. The review included original articles and reviews that evaluated PMI estimation methods (through thanatological signs, entomology, microbial succession, molecular, imaging, and omics approaches). Extracted data included study design, methodology, PMI range, and accuracy information. Out of the 1245 identified records, 50 studies met the inclusion criteria for qualitative synthesis. Results: Emerging methods, such as molecular markers, microbial succession, omics technologies, and advanced imaging show improved accuracy across extended postmortem intervals. RNA degradation methods demonstrated higher accuracy within the first 72 h, while entomology and microbial analysis are more applicable during intermediate and late decomposition stages. Although no single method is universally reliable, combining traditional and modern approaches tailored to case-specific factors improves overall PMI estimation accuracy. Conclusions: This study supports the use of an integrative, multidisciplinary, and evidence-based approach to improve time-since-death estimation. Such a strategy enhances forensic outcomes by enabling more precise PMI estimates in complex or delayed cases, increasing legal reliability, and supporting court-admissible expert testimony based on validated, multi-method protocols. Full article

The synthesis of “green ammonia” from “green hydrogen” represents a critical pathway for renewable energy integration and industrial decarbonization. This study investigates the green ammonia synthesis process using an axial–radial fixed-bed reactor equipped with three catalyst layers. A simplified two-dimensional physical model was developed, and a multiscale simulation approach combining computational fluid dynamics (CFD) with physics-informed neural networks (PINNs) employed. The simulation results demonstrate that the majority of fluid flows axially through the catalyst beds, leading to significantly higher temperatures in the upper bed regions. The reactor exhibits excellent heat exchange performance, ensuring effective preheating of the feed gas. High-pressure zones are concentrated near the top and bottom gas outlets, while the ammonia mole fraction approaches 100% near the bottom outlet, confirming superior conversion efficiency. By integrating PINNs, the prediction accuracy was substantially improved, with flow field errors in the catalyst beds below 4.5% and ammonia concentration prediction accuracy above 97.2%. Key reaction kinetic parameters (pre-exponential factor k₀ and activation energy Ea) were successfully inverted with errors within 7%, while computational efficiency increased by 200 times compared to traditional CFD. The proposed CFD–PINN integrated framework provides a high-fidelity and computationally efficient simulation tool for green ammonia reactor design, particularly suitable for scenarios with fluctuating hydrogen supply. The reactor design reduces energy per unit ammonia and improves conversion efficiency. Its radial flow configuration enhances operational stability by damping feed fluctuations, thereby accelerating green hydrogen adoption. By reducing fossil fuel dependence, it promotes industrial decarbonization. Full article

Background: Against the backdrop of the large-scale and intensive development of the livestock industry, enhancing the reproductive efficiency of cattle has become a crucial factor in industrial development. Holstein cows, as the most predominant dairy cattle breed globally, are characterized by high milk yield and excellent milk quality. However, their reproductive efficiency is comprehensively influenced by a variety of complex factors, and improving their reproductive performance faces numerous challenges. The ovary, as the core organ of the female reproductive system, plays a decisive role in embryonic development and pregnancy maintenance. It is not only the site where eggs are produced and developed but it also regulates the cow’s estrous cycle, ovulation process, and the establishment and maintenance of pregnancy by secreting various hormones. The normal functioning of the ovary is crucial for the smooth development of the embryo and the successful maintenance of pregnancy. Methods: Currently, traditional sequencing technologies have obvious limitations in deciphering ovarian function and reproductive regulatory mechanisms. To overcome the bottlenecks of traditional sequencing technologies, this study selected Holstein cows as the research subjects. Ovarian samples were collected from one pregnant and one non-pregnant Holstein cow, and single-nucleus transcriptome sequencing technology was used to conduct an in-depth study on the ovarian cells of Holstein cows. Results: By constructing a cell type-specific molecular atlas of the ovaries, nine different cell types were successfully identified. This study compared the proportions of ovarian cell types under different physiological states and found that the proportion of endothelial cells decreased during pregnancy, while the proportions of granulosa cells and luteal cells increased significantly. In terms of functional enrichment analysis, oocytes during both pregnancy and non-pregnancy play roles in the “cell cycle” and “homologous recombination” pathways. However, non-pregnant oocytes are also involved in the “progesterone-mediated oocyte maturation” pathway. Luteal cells during pregnancy mainly function in the “cortisol synthesis and secretion” and “ovarian steroidogenesis” pathways; non-pregnant luteal cells are mainly enriched in pathway processes such as the “AMPK signaling pathway”, “pyrimidine metabolism”, and “nucleotide metabolism”. Cell communication analysis reveals that there are 51 signaling pathways involved in the pregnant ovary, with endothelial cells, granulosa cells, and luteal cells serving as the core communication hubs. In the non-pregnant ovary, there are 48 pathways, and the interaction between endothelial cells and stromal cells is the dominant mode. Conclusions: This study provides new insights into the regulatory mechanisms of reproductive efficiency in Holstein cows. The differences in the proportions of ovarian cell types, functional pathways, and cell communication patterns under different physiological states, especially the increase in the proportions of granulosa cells and luteal cells during pregnancy and the specificity of related functional pathways, indicate that these cells play a crucial role in the reproductive process of cows. These findings also highlight the importance of ovarian cells in pathways such as “cell cycle”, “homologous recombination”, and “progesterone-mediated oocyte maturation”, as well as the cell communication mechanisms in regulating ovarian function and reproductive performance. Full article

Ensuring software quality during development requires effective regression testing. However, test suites in open-source libraries often grow large, redundant, and difficult to maintain. Most traditional test suite optimization methods treat test cases as atomic units, without analyzing the utility of individual instructions. This paper presents an intelligent method for test case synthesis using a Q-learning agent. The agent learns to construct compact test cases by interacting with an execution environment and receives rewards based on branch coverage improvements and simultaneous reductions in test case length. The training process includes a pretraining phase that transfers knowledge from the original test suite, followed by adaptive learning episodes on individual test cases. As a result, the method requires no formal documentation or API specifications and uses only execution traces of the original test cases. An explicit synthesis algorithm constructs new test cases by selecting API calls from a learned policy encoded in a Q-table. Experiments were conducted on two open-source C++ libraries of differing API complexity and original test suite size. The results show that the proposed method can reach up to 67% test suite reduction while preserving branch coverage, confirming its effectiveness for regression test suite minimization in resource-constrained or specification-limited environments. Full article

The genus Sonchus (Asteraceae) comprises 98 species, including 17 predominantly herbaceous taxa native to the Mediterranean region. These plants have long been utilized as traditional wild food sources due to their high nutritional value, as they are rich in vitamins A, C, and K, essential minerals, and bioactive compounds with antioxidant and anti-inflammatory properties. This review aims to provide a comprehensive synthesis of the taxonomy, geographic distribution, phytochemical composition, traditional uses, historical significance, and pharmacological properties of Sonchus species. A systematic literature search was conducted using PubMed, Scopus, Web of Science, and Google Scholar, focusing on studies from 1980 to 2024. Inclusion and exclusion criteria were applied, and methodological quality was assessed using standardized tools. A bibliometric analysis of 440 publications (from 1856 to 2025) reveals evolving research trends, with S. oleraceus, S. arvensis, and S. asper being the most extensively studied species. The review provides detailed taxonomic insights into 17 species and 14 subspecies, emphasizing their ecological adaptations and biogeographical patterns. Additionally, it highlights the cultural and medicinal relevance of Sonchus since antiquity while underscoring the threats posed by environmental degradation and changing dietary habits. Sonchus oleraceus and S. tenerrimus dominate the culinary applications of the genus, likely due to favorable taste, wide accessibility, and longstanding cultural importance. The comprehensive nutritional profile of Sonchus species positions these plants as valuable contributors to dietary diversity and food security. Finally, the study identifies current knowledge gaps and proposes future research directions to support the conservation and sustainable utilization of Sonchus species. Full article

Tetrasubstituted dihydrothiophenes represent a class of heterocyclic compounds with significant potential in various fields, particularly in medicinal chemistry and materials science. In this work, we have developed an eco-friendly and efficient method for synthesizing such compounds, using porcine pancreatic lipase (PPL) as a biocatalyst to promote the cyclization reaction between β-ketothioamides and β-nitrostyrenes. Through this approach, sixteen tetrasubstituted dihydrothiophenes were successfully synthesized, and all of them achieved high yields, ranging from 80% to 96%. This research not only expands the application scope of lipase in organic synthesis, demonstrating its versatility beyond traditional hydrolytic reactions, but also provides a new environmentally friendly pathway for the production of tetrasubstituted dihydrothiophenes, which is of great significance for advancing related fields of chemical synthesis. Full article

Background: Anoectochilus roxburghii (Wall.) Lindl. (A. roxburghii) was widely used in traditional Chinese medicine and also as a health food in China. Gibberellins (GAs) are plant hormones that regulate various aspects of growth and development in A. roxburghii. Ent-kaurene synthase (KS) plays a crucial role in the biosynthesis of GAs in plants. However, there is limited functional analysis of KS in GA biosynthesis and its effect on salt tolerance, especially in A. roxburghii. Methods: The ArKS genes were cloned from A. roxburghii, and its salt tolerance characteristics were verified by prokaryotic expression. Under salt stress, analyze the regulation of KS gene on GA and active ingredient content by qRT-PCR and HPLC-MS/MS, and explore the mechanism of exogenous GAs promoting active ingredient enrichment by regulating the expression level of the KS under salt stress. Results: The ArKS protein was highly homologous to KSs with other plant species; subcellular localization of KS protein was lacking kytic vacuole. The transformants displayed a significant increase in salt tolerance under the stress conditions of 300 mM NaCl. And the expression of ArKS genes and the GAs accumulation was downregulated under the salt stress; among them, the contents of GA3, GA7, GA8, GA24, and GA34 showed a significant decrease. It was further found that there was an increase (1.36 times) in MDA content and a decrease (0.84 times) in relative chlorophyll content under the salt conditions from A. roxburghii. However, the content of active constituents was elevated from A. roxburghii under the NaCl stress, including polysaccharides, total flavonoids, and free amino acids, which increased by 1.14, 1.23, and 1.44 times, respectively. Interestingly, the ArKS gene expression and the chlorophyll content was increased, MDA content showed a decrease from 2.02 μmoL·g⁻¹ to 1.74 μmoL·g⁻¹ after exogenous addition of GAs, and the elevation of active constituents of polysaccharides, total flavonoids, and free amino acids were increased by 1.02, 1.09, and 1.05 times, implying that GAs depletion mitigated the damage caused by adversity to A. roxburghii. Conclusions: The ArKS gene cloned from A. roxburghii improved the salt tolerance of plants under salt stress by regulating GA content. Also, GAs not only alleviate salt tolerance but also play a key role in the synthesis of active components in A. roxburghii. The functions of KS genes and GAs were identified to provide ideas for improving the salt tolerance and quality of ingredients in artificial cultivation from A. roxburghii. Full article

Sacred choral music continues to hold a significant place in contemporary concert settings, with historical and newly composed works featuring in today’s choral programmes. Contemporary choral composers have continued to engage with the longstanding tradition of setting sacred texts to music, bringing fresh interpretations through their innovative compositional techniques and fusion of styles. Irish composer Rhona Clarke’s (b. 1958) expansive choral oeuvre includes a wealth of both sacred and secular compositions but reveals a notable propensity for the setting of sacred texts in Latin. Her synthesis of archaic and contemporary techniques within her work demonstrates both the solemn and visceral aspects of these texts, as well as a clear nod to tradition. This article focuses on Clarke’s choral work O Vis Aeternitatis (2020), a setting of a text by the medieval musician and saint Hildegard of Bingen (c. 1150). Through critical score analysis, we investigate the piece’s melodic, harmonic, and textural frameworks; the influence of Hildegard’s original chant; and the use of extended vocal techniques and contrasting vocal timbres as we articulate core characteristics of Clarke’s compositional style and underline her foregrounding of the more visceral aspects of Hildegard’s words. Clarke’s fusion of creative practices from past and present spotlights moments of dramatic escalation and spiritual importance, and exhibits the composer’s distinctive compositional voice as she reimagines Hildegard’s text for the twenty-first century. Full article

Biobutanol is becoming more relevant as a promising alternative biofuel, primarily due to its advantageous characteristics. These include a higher energy content and density compared to traditional biofuels, as well as its ability to mix effectively with gasoline, further enhancing its viability as a potential replacement. A viable strategy for attaining carbon neutrality, reducing reliance on fossil fuels, and utilizing sustainable and renewable resources is the use of biomass to produce biobutanol. Lignocellulosic materials have gained widespread recognition as highly suitable feedstocks for the synthesis of butanol, together with various value-added byproducts. The successful generation of biobutanol hinges on three crucial factors: effective feedstock pretreatment, the choice of fermentation techniques, and the subsequent enhancement of the produced butanol. While biobutanol holds promise as an alternative biofuel, it is important to acknowledge certain drawbacks associated with its production and utilization. One significant limitation is the relatively high cost of production compared to other biofuels; additionally, the current reliance on lignocellulosic feedstocks necessitates significant advancements in pretreatment and bioconversion technologies to enhance overall process efficiency. Furthermore, the limited availability of biobutanol-compatible infrastructure, such as distribution and storage systems, poses a barrier to its widespread adoption. Addressing these drawbacks is crucial for maximizing the potential benefits of biobutanol as a sustainable fuel source. This document presents an extensive review encompassing the historical development of biobutanol production and explores emerging trends in the field. Full article

A scalable synthesis of two-dimensional titanium nitride chloride (TiNCl) via flash Joule heating (FJH) using titanium tetrachloride (TiCl₄) precursor has been developed. This single-step method overcomes traditional synthesis challenges, including high energy consumption, multi-step procedures, and hazardous reagent requirements. The structural and chemical properties of the synthesized TiNCl were characterized through multiple analytical techniques. X-ray diffraction (XRD) patterns confirmed the presence of TiNCl phase, while Raman spectroscopy data showed no detectable oxide impurities. Fourier transform infrared spectroscopy (FTIR) analysis revealed characteristic Ti–N stretching vibrations, further confirming successful titanium nitride synthesis. Transmission electron microscopy (TEM) imaging revealed thin, plate-like nanostructures with high electron transparency. These analyses confirmed the formation of highly crystalline TiNCl flakes with nanoscale dimensions and minimal structural defects. The material exhibits excellent structural integrity and phase purity, demonstrating potential for applications in photocatalysis, electronics, and energy storage. This work establishes FJH as a sustainable and scalable approach for producing MXenes with controlled properties, facilitating their integration into emerging technologies. Unlike conventional methods, FJH enables rapid, energy-efficient synthesis while maintaining material quality, providing a viable route for industrial-scale production of two-dimensional materials. Full article

Background: The rising demand for aesthetic dental treatments has spurred interest in peroxide-free color correctors as alternatives to traditional hydrogen peroxide formulations, which are associated with tooth sensitivity and potential enamel demineralization. This systematic review evaluates the whitening efficacy and safety profile of hydrogen peroxide-free color corrector (HPFCC) products, focusing on color change metrics, enamel and dentin integrity, and adverse effects. Methods: Following PRISMA guidelines, we searched PubMed, Scopus, and Web of Science throughout January 2025 for randomized controlled trials, observational studies, and in vitro experiments comparing HPFCC to placebo or peroxide-based agents. The data extraction covered study design, sample characteristics, intervention details, shade improvement (ΔE00 or CIE Lab), enamel/dentin mechanical properties (microhardness, roughness, elastic modulus), and incidence of sensitivity or tissue irritation. Risk of bias was assessed using the Cochrane tool for clinical studies and the QUIN tool for in vitro research. Results: Six studies (n = 20–80 samples or subjects) met the inclusion criteria. In vitro, HPFCC achieved mean ΔE00 values of 3.5 (bovine incisors; n = 80) and 2.8 (human molars; n = 20), versus up to 8.9 for carbamide peroxide (p < 0.01). Across studies, HPFCC achieved a mean ΔE00 of 2.8–3.5 surpassing the perceptibility threshold of 2.7 and approaching the clinical acceptability benchmark of 3.3. Surface microhardness increased by 12.9 ± 11.7 VHN with HPFCC (p < 0.001), and ultramicrohardness rose by 110 VHN over 56 days in prolonged use studies. No significant enamel erosion or dentin roughness changes were observed, and the sensitivity incidence remained below 3%. Conclusions: These findings derive from one clinical trial (n = 60) and five in vitro studies (n = 20–80), encompassing violet-pigment serums and gels with differing concentrations. Due to heterogeneity in designs, formulations, and outcome measures, we conducted a narrative synthesis rather than a meta-analysis. Although HPFCC ΔE00 values were lower than those of carbamide peroxide, they consistently exceeded perceptibility thresholds while maintaining enamel integrity and causing sensitivity in fewer than 3% of subjects, supporting HPFCCs as moderate but safe alternatives for young patients. Full article

The Online Droplet Inspection system plays a vital role in closed-loop control for OLED inkjet printing. However, generating realistic synthetic droplet images for reliable restoration and precise measurement of droplet parameters remains challenging due to the complex, multi-factor degradation inherent to microscale droplet imaging. To address this, we propose a physics-informed degradation model, Diffraction–Gaussian–Motion–Noise (DGMN), that integrates Fraunhofer diffraction, defocus blur, motion blur, and adaptive noise to replicate real-world degradation in droplet images. To optimize the multi-parameter configuration of DGMN, we introduce the MISABO (Multi-strategy Improved Subtraction-Average-Based Optimizer), which incorporates Sobol sequence initialization for search diversity, lens opposition-based learning (LensOBL) for enhanced accuracy, and dimension learning-based hunting (DLH) for balanced global–local optimization. Benchmark function evaluations demonstrate that MISABO achieves superior convergence speed and accuracy. When applied to generate synthetic droplet images based on real droplet images captured from a self-developed OLED inkjet printer, the proposed MISABO-optimized DGMN framework significantly improves realism, enhancing synthesis quality by 37.7% over traditional manually configured models. This work lays a solid foundation for generating high-quality synthetic data to support droplet image restoration and downstream inkjet printing processes. Full article

This study introduces a paradigm shift in permanent magnet synchronous motor (PMSM) control through the development of hybrid dual fractional-order sliding mode control (HDFOSMC) architecture integrated with evolutionary parameter learning (EPL). Conventional PMSM control frameworks face critical limitations in ultra-precision applications due to their inability to reconcile dynamic agility with steady-state precision under time-varying parameters and compound disturbances. The proposed HDFOSMC framework addresses these challenges via two synergistic innovations: (1) a dual fractional-order sliding manifold that fuses the rapid transient response of non-integer-order differentiation with the small steady-state error capability of dual-integral compensation, and (2) an EPL mechanism enabling real-time adaptation to thermal drift, load mutations, and unmodeled nonlinearities. Validation can be obtained through the comparison of the results on PMSM testbenches, which demonstrate superior performance over traditional fractional-order sliding mode control (FOSMC). By integrating fractional-order theory, sliding mode control theory, and parameter self-tuning theory, this study proposes a novel control framework for PMSM. The developed system achieves high-precision performance under extreme operational uncertainties through this innovative theoretical synthesis and comparative results. Full article

Radon anomalies have long been explored as potential geochemical precursors to seismic activity due to their responsiveness to subsurface stress variations. However, before this study, the scientific progression of this research domain had not been systematically examined through a quantitative lens. This study presents a comprehensive bibliometric analysis of 379 articles published between 1977 and 2025 and indexed in Scopus and Web of Science. Utilizing the Bibliometrix R-package and its Biblioshiny interface, the analysis investigates temporal publication trends, leading countries, institutions, international collaboration networks, and thematic evolution. The results reveal a marked increase in research output since 2010, with China, India, and Italy emerging as the most prolific contributors. Thematic mapping indicates a shift from conventional geochemical monitoring toward the integration of artificial intelligence techniques, such as decision trees and neural networks, for anomaly detection and predictive modeling. Notwithstanding this methodological evolution, core research themes remain centered on radon concentration monitoring and the analysis of environmental parameters. Overall, the findings highlight the coexistence of traditional and emerging approaches, emphasizing the importance of standardized methodologies and interdisciplinary collaboration. This bibliometric synthesis provides strategic insights to inform future research and strengthen the role of radon monitoring in seismic early warning systems. Full article

Hypercholesterolemia is a major modifiable risk factor for atherosclerotic cardiovascular disease (ASCVD), affecting a significant proportion of the adult population worldwide. This narrative review provides a comprehensive and up-to-date overview of hyperlipidemia management, spanning from epidemiological trends and underlying pathophysiological mechanisms to the limitations of conventional therapies such as statins and ezetimibe. Particular emphasis is placed on cardiovascular risk assessment, current stratification tools, and international guideline-based interventions. The present paper, focusing primarily on the biological mechanisms of dyslipidemia and the clinical use of traditional lipid-lowering agents, serves as the first part of a two-part series, preceding a forthcoming review of novel pharmacological approaches. Our data synthesis is based on a structured literature search conducted across Google Scholar, PubMed, and Scopus, including studies published up to June 2025. The review also includes aspects related to non-pharmacological strategies, pharmacoeconomic considerations, and pharmacogenetic influences on treatment response. Ultimately, this work aims to equip clinicians with evidence-based, nuanced insights essential for optimizing lipid management and reducing cardiovascular risk, while setting the foundation for understanding how emerging therapies may overcome current therapeutic limitations. Full article