Search Results (3,477)

Nephrite is a significant jade resource, and systematic investigation of its deposits contributes to regional metallogenic synthesis and exploration targeting. The recently discovered white nephrite deposit in the Dikou area, Fujian Province, remains inadequately characterized. This study presents a comprehensive mineralogical investigation employing polarizing microscopy, scanning electron microscopy, electron probe microanalysis, X-ray powder diffraction and laser Raman spectroscopy to elucidate the mineralogical and petrochemical characteristics of Dikou nephrite and constrain its genesis. The results demonstrate that tremolite constitutes the predominant mineral phase, accompanied by abundant diopside and quartz, with minor dolomite, prehnite, and apatite. Based on subtle compositional variations, tremolite can be categorized into two generations: early metasomatic Tr-I and late-stage Tr-II. All tremolite samples exhibit Fe-depleted, Mg-enriched composition with Mg# > 0.99. The mineral assemblage and textural relationships record multiple episodes of hydrothermal metasomatism. Integrated with the regional geological constraints, the deposit formation is genetically linked to the Neoproterozoic–Early Paleozoic ocean–continent transition of the South China Plate and is classified as D-type nephrite. The Dikou nephrite exhibits the mineral assemblage typical of dolomite-related deposits, displaying a distinctive felt-like fibrous texture that yields a homogeneous structure and superior aesthetic quality. Its Fe-depleted composition imparts a notably lighter coloration relative to D-type nephrite from other deposits. This study advances understanding of Dikou nephrite genesis, highlights the diversity of metallogenic environments in Fujian Province, and provides a theoretical framework for exploration of analogous deposits. Full article

Drawing an analogy to the 5th century heresy of Nestorianism, this paper argues that the separation of life from faith in the modern era constitutes a kind of functional Nestorianism, that negates the universality of the Christian claim and renders such a claim. The paper argues that, in their form and function, many Catholic educational institutions unwittingly adopt this functional Nestorianism by means of a structural compartmentalisation of the faith into confined spaces within the curriculum and within the institutional imagination and that in doing so, such institutions risk mirroring—at the level of educational practice—and thus perpetuating, what Pope Paul VI referred to as ‘the drama of our time’, that being, ‘the split between the Gospel and culture’. The paper concludes by offering six Christocentric principles to guide curriculum development and implementation in Catholic educational institutions. Full article

Non-negative matrix factorization directly decomposes data features into a base matrix and community matrix, which are easily affected by noise. Multi-view datasets have multiple feature matrices, each with a different angle. The data features need to be re-synthesized rather than simply concatenated or added. Based on the advantages and disadvantages of multi-view clustering and non-negative matrix factorization, we attempt to transplant the method of analyzing abstract connected graphs, analogize the similarity between edges and samples in the graph, and propose a deep non-negative matrix factorization model for clustering by constructing a similarity matrix and decomposing it. At the same time, in order to reduce the interference of noise, we introduce a denoising auto-encoder and non-negative matrix factorization in series, and research the reconstruction features, ultimately forming a model structure framework of “denoising auto-encoder, non-negative matrix factorization, clustering”. Through experiments, the denoising auto-encoder-enhanced non-negative matrix factorization achieved good results on five datasets. It achieved an accuracy of 87 percenton the BBC Sport dataset and 61 percent on Wiki-fea, which increased by two percentage points. The clustering results demonstrate that the model can effectively alleviate the impact of noise and provide new ideas for how to integrate multi-view features. Full article

Doxorubicin is an effective chemotherapeutic agent, but it causes gastrointestinal toxicity that impairs treatment efficacy and quality of life. This study investigated the effects of liraglutide, a GLP-1 analog, on acute doxorubicin-induced gut toxicity in rats. Sixty male Wistar rats were assigned to four groups: Control (C), Doxorubicin (D), Liraglutide (L), and Doxorubicin + Liraglutide (DL). Groups L and DL received liraglutide (0.6 mg/kg, s.c.) for two weeks. D and DL were given a single dose of doxorubicin (20 mg/kg, i.p). After 48 h, the distal colon, feces, and blood were collected. Results: Doxorubicin caused crypt disruption, goblet cell loss, apoptosis, and reduced fecal short-chain fatty acids. Levels of TNF-α, NF-κB, Bcl-2, TLR4, and antioxidant enzymes were unchanged among groups. Microbiota analysis showed similar α-diversity but altered β-diversity. Doxorubicin reduced Bacteroidetes and increased Proteobacteria, with higher Arcanobacterium and Clavibacter genera abundance. Liraglutide alone decreased Bacteroidetes and increased Corynebacterium and Actinobaculum genera. Combined treatment showed no significant effects. We conclude that acute doxorubicin administration induces intestinal structural damage, reduces short-chain fatty acids, and changes microbiota composition. Although liraglutide alters microbial profiles, it does not attenuate doxorubicin-induced gut toxicity. Full article

Alternative proteins and novel processing technologies are crucial to transforming contemporary food systems into ones with lower environmental impact while meeting the rising global demand for protein. Alternative protein sources from plants, microbes, insects, and cultivated cells offer diverse nutritional and techno-functional attributes that can partially or fully replace conventional animal proteins in meat analogs and related products. This review synthesizes the current knowledge on major categories of alternative protein sources, including plant-based ingredients, microbial- and fermentation-derived proteins, insect and other emerging sources, and cultivated (cell-based) meat, with a specific focus on their suitability for structured meat analog applications. Modern structuring and processing technologies are discussed, including the traditional wet and dry extrusion to modern technologies like high-moisture extrusion, high-pressure processing, shear-cell technology, 3D printing, fermentation-based structuring, and enzymatic protein modification. Furthermore, this review critically evaluates product design and quality attributes of meat analogs, including physicochemical properties, sensory performance, nutritional aspects, and safety considerations. This review highlights technological and scale-up challenges, as well as the necessity of multi-criteria optimization in sensory quality, nutrition, sustainability, and affordability, and presents research priorities focused on combining multiple protein sources and advanced processing pathways for next-generation meat analog. This review provides an integrated framework linking protein sources, processing technologies, antioxidant functionality, and sustainability considerations to support the development of next-generation meat analogs. In addition, this review highlights the intrinsic antioxidant potential of alternative proteins, emphasizing the role of bioactive peptides, polyphenols, and structure–function relationships in enhancing oxidative stability and product quality. Full article

Fabry–Perot resonator (FPR) sensors are widely implemented in optical and microwave waveguides because their interference fringe spectra enable highly sensitive, stable, and calibration-free measurements. In contrast, despite the extensive use of beams and plates as waveguides in vibration- and ultrasound-based structural health monitoring (SHM), an explicit FPR framework for these mechanical waveguides has not been established. This paper demonstrates that flexural beams can be rigorously treated as FPRs despite their inherently dispersive nature. Through analytical derivation, wave-propagation analysis, and fringe-based group-velocity extraction, we show that flexural-beam resonances arise from multi-reflection interference analogous to Fabry–Perot interference. A closed-form relationship between the frequency-dependent group velocity and the FPR free spectral range (FSR) is established, enabling inverse determination of mechanical or environmental perturbance from the FPR fringe spectrum. By extending FPR-based fringe analysis to dispersive mechanical waveguides, this work introduces a theoretical framework for implementing dispersive mechanical waveguide-based FPR sensors. Full article

The paper deals with the concept of how to regulate structure formation in the interfacial transition zone (ITZ) between the Ordinary Portland Cement (OPC) matrix and basalt to ensure the durability of basalt fiber-reinforced concretes. It has been demonstrated that the alkali–silica reaction (ASR) can be transformed from a destructive (negative) process into a constructive one in OPC concrete through activation by sodium water glass combined with the incorporation of an Al₂O₃-containing additive, namely metakaolin. Alkaline activation increased the compressive strength of OPC basalt fiber-reinforced concrete by 1.6–1.9 times. The formation of stable zeolite-like hydration products within the Na₂O-CaO-Al₂O₃-SiO₂-H₂O system promoted self-healing of the ITZ. This resulted in a 5.6-fold increase in ITZ microhardness compared to the cement matrix, as well as transforming expansion into shrinkage of concrete with a final value of 0.01 mm/m after 360 days. The structure-forming processes in the ITZ ensured a 1.14-fold increase in the compressive strength of 180-day alkali-activated OPC basalt fiber-reinforced concrete compared to its 30-day strength, in contrast to a 0.92-fold decrease in the strength of the non-modified OPC analog under conditions accelerating the development of ASR. Full article

A large number of low-resistivity and low-permeability reservoirs have been discovered in the deep Paleogene strata of the Wenchang Sag. These reservoirs are characterized by complex porosity–permeability relationships and difficulties in fluid property identification, which restrict the progress of exploration and development operations. However, existing reservoir studies mostly focus on either low-permeability or low-resistivity reservoirs, with relatively few investigations targeting this specific type. Using petrological analysis and physical property testing as the main methods, combined with sedimentary and diagenetic studies, this paper examines the characteristics and genesis of low-resistivity and low-permeability reservoirs in the Paleogene of the Wenchang Sag. The results show that the Paleogene reservoirs are dominated by lithic quartz sandstones, with secondary pores as the main reservoir space, consisting of medium–small pores and fine throats. Samples of the same grain size exhibit a favorable porosity–permeability correlation. Based on capillary pressure curve morphology, the reservoirs can be classified into three types: high mercury intrusion saturation with low displacement pressure, medium mercury intrusion saturation with medium displacement pressure, and medium mercury intrusion saturation with medium–high displacement pressure. The low porosity and permeability are mainly attributed to the fact that the reservoir rocks are primarily deposited in near-source braided fluvial delta underwater distributary channels, resulting in low compositional and textural maturity of sandstones. Strong compaction resistance leads to a significant reduction in primary pores during burial, and intergranular cement filling further deteriorates physical properties. On the other hand, rapid lithological changes and complex pore structures give rise to abundant isolated pores and poor connectivity, leading to high irreducible water saturation. Coupled with high formation water salinity, these factors collectively give rise to low-resistivity reservoirs in the study area. This study clarifies the formation mechanism of low-permeability and low-resistivity reservoirs in the Paleogene of the Wenchang Sag, providing guidance for reservoir evaluation in subsequent oil and gas exploration and serving as a reference for analogous areas. Full article

Major depressive disorder is a highly prevalent psychiatric disease, and many patients remain symptomatic despite treatment. Rodent models are central to preclinical depression research, but their translational impact is often constrained by the lack of direct human analogs. We conducted a review to identify behavioral tasks with direct cross-species analogs between rodents and humans. We focused on tests with comparable assay structures that measure depressive symptoms and related constructs. We followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and included all relevant studies. After screening 9680 studies and applying inclusion and exclusion criteria, 62 studies were included. We identified 10 behavioral tests with comparable human and rodent versions. These tests include assays of positive and negative valence systems, affective bias, and cognitive systems. These cross-species behavioral tests help close the gap between animal and human paradigms and advance the understanding of the neurobiology underlying depression. Each test has distinct strengths and limitations in its implementation across species. These assays offer a promising bridge between human and rodent research, and continued efforts to standardize and develop these tests will help maximize their utility in enhancing the understanding of depression and developing more effective treatments for mood disorders. Full article

Autophagy dysfunction is implicated in the pathogenesis of Alzheimer’s disease (AD), and enhancing autophagic flux has been proposed as a potential strategy for addressing neurodegenerative diseases. To expand the structural diversity of ingenol esters and systematically evaluate their autophagic flux activation activity, a systematic phytochemical investigation of ingenane diterpenoids from Euphorbia peplus was conducted. A total of 13 ingenane-type compounds were isolated and identified, including two previously undescribed compounds, euphingenol A and B (1–2), together with 11 known analogs (3–13). Their structures were elucidated by extensive spectroscopic analyses (HRESIMS and NMR) and comparison with literature data. The compounds were evaluated for their bioactivity with flow cytometry in assays of autophagic flux in HM Cherry-GFP-LC3 (human microglia cells stably expressing the tandem monomeric mCherry-GFP-tagged LC3) cells. 17-O-benzoyl-20-deoxyingenol (3) significantly activated autophagic flux at concentrations of 10 μM and 40 μM, while euphingenol A (1) induced a dose-dependent increase, with structure-activity relationship analysis indicating that C-17 acylation enhances this bioactivity. These findings suggest that compound 3 warrants further investigation as a potential modulator of autophagic flux, possibly through binding to PKCδ (protein kinase C), with relevance to autophagy-related neurodegenerative conditions. Full article

The rapid development of smart energy infrastructures and renewable energy systems requires advanced sensing solutions that provide high accuracy, expandability, and stability under real operating conditions. However, conventional gas monitoring systems are predominantly based on resistive or voltage-output sensors, which require complex analog front-end circuits and analog-to-digital conversion, leading to increased system complexity, cost, and susceptibility to electromagnetic interference. This paper tackles this limitation by proposing a frequency-domain sensing approach for multichannel monitoring of biogas plant parameters. The objective of this study is to develop and experimentally validate an extendable sensing architecture based on autogenerator microelectronic gas transducers with direct gas concentration–frequency conversion and FPGA-based digital acquisition. The proposed method is grounded in a physical–mathematical model of the space-charge capacitance of gas-sensitive semiconductor structures derived from Poisson’s equation, facilitating analytical formulation of conversion and sensitivity functions. A multichannel FPGA-based measurement system is implemented to process frequency signals without analog conditioning or ADC stages. Experimental validation was performed for CH₄ (0–85%), CO₂ (0–60%), H₂, NH₃, and H₂S (1–20,000 ppm). The results demonstrate measurement uncertainty within 0.25–0.5%, with sensitivity reaching 350–748 Hz/ppm for H₂, 455–750 Hz/ppm for NH₃, and 253–375 Hz/ppm for H₂S, while methane and carbon dioxide sensitivities reach up to 112 kHz/% and 98.7 kHz/%, respectively. Spectral analysis in the LTE-1800 band confirms improved noise immunity (up to 4.5×) and extended transmission capabilities. A 12-channel FPGA-based monitoring system (RDM-BP-1) with a 1 s sampling interval, IP67 protection, and wireless connectivity is developed and validated. The proposed architecture eliminates analog signal conditioning, reduces hardware complexity, and provides an easily expandable and reliable sensing solution for smart buildings, renewable energy systems, and cloud-integrated energy infrastructures. Full article

Background/Objective: Postoperative recovery after spine surgery varies substantially and cannot be fully explained by structural pathology alone. This study evaluates postoperative outcomes using a structured 2 × 2 Surgical Trauma Gradient integrating exposure-related invasiveness (minimally invasive vs. open) and biomechanical strategy (decompression vs. fusion), and examines the modifying role of Type-D personality. Methods: This observational cohort study included 200 patients undergoing elective spine surgery. Patients were stratified into four surgical subgroups: minimally invasive decompression, open decompression, minimally invasive fusion, and open fusion. Primary outcomes included pain intensity (Visual Analog Scale), functional disability (Oswestry Disability Index), patient satisfaction (Patient Satisfaction Index), and postoperative complications at 12-month follow-up. Surgical invasiveness was modeled both categorically and as an ordinal gradient. Multivariable regression, logistic regression, interaction analysis, and longitudinal mixed-effects models were applied. Results: Postoperative outcomes demonstrated a consistent gradient across increasing surgical burden. In multivariable models, higher surgical invasiveness independently predicted greater residual pain (β = 0.69; 95% CI 0.55–0.82; p < 0.001) and higher functional disability (β = 6.20; 95% CI 5.10–7.30; p < 0.001). Increasing invasiveness was also associated with lower patient satisfaction (β = −0.38; 95% CI −0.47 to −0.29; p < 0.001) and higher complication risk (OR = 1.64; 95% CI 1.12–2.41; p = 0.01). Type-D personality independently predicted worse postoperative pain (β = 0.41; p = 0.008) and significantly modified the association between surgical burden and pain (interaction β = 0.22; p = 0.012). Conclusions: Postoperative outcomes follow a structured Surgical Trauma Gradient influenced by both surgical burden and psychosocial vulnerability, particularly Type-D personality. Integrating these dimensions may improve perioperative risk stratification and support individualized treatment strategies. Full article

This study examines the applicability of coding-theoretic tools to the digital monitoring of information space. The proposed approach treats response patterns to socially significant stimuli as binary sequences and interprets their analysis as a classification problem analogous to error correction in coding theory. To verify the feasibility of this framework, a model psychological test consisting of seven binary questions was analyzed using a procedure derived from the Hamming code (7,4). The method makes it possible to map the full space of observed answer combinations onto a smaller set of reference codewords and thereby identify stable response configurations. The obtained results show that the distributions produced after coding-based transformation are markedly non-uniform and contain recurrent maxima, indicating the presence of structured patterns in collective responses. It is also shown that permutations of question order substantially affect the resulting distributions and correlation indicators, which highlights both the sensitivity and the analytical potential of the proposed encoding scheme. The main contribution of the study is methodological: it demonstrates that error-correcting coding can be operationalized as a formal tool for detecting latent regularities in simplified monitoring data. At the same time, the present results should be regarded as proof of concept, since further work is required to validate the approach on larger datasets, compare it with baseline classification methods, and extend it to longer and multivalued response sequences. Full article

Palm kernel oil is commonly incorporated into plant-based cheeses to mimic the textural and structural properties of animal fats owing to its high saturated fat content. Nevertheless, growing concerns regarding saturated fat consumption have stimulated research into alternative lipid sources for plant-based products. Therefore, this study aimed to evaluate the effects of substituting palm kernel oil with rice bran oil shortening (SRBO) on some selected physical, textural, functional, chemical, fatty acid and microstructural properties of plant-based mozzarella cheese analogs. Five formulations with SRBO levels of 0, 25, 50, 75, and 100% were prepared and their physicochemical properties were analyzed. Increasing SRBO significantly affected color due to natural pigments in rice bran oil. The pH value declined with higher SRBO, likely due to oxidation of unsaturated fatty acids. Texture profile analysis showed increases in hardness, springiness, cohesiveness, gumminess, and chewiness when SRBO was increased from 0% to 100%. Meltability slightly decreased at 25–75% but remained unchanged at 100% SRBO, while stretchability decreased significantly, attributed to β-type fat crystals disrupting protein networks. The work of shear decreased significantly (p ≤ 0.05), indicating improved spreadability attributed to the softer, less-crystalline nature of unsaturated fats compared to saturated fats. Proximate analysis revealed reduced fat content and a shift from saturated to unsaturated fats, notably oleic and linoleic acids, offering potential cardiovascular benefits. Confocal laser scanning microscopy showed denser fat crystal networks and smaller fat droplets at higher SRBO levels, enhancing oil retention and stability. Protein, fiber, moisture, and ash content remained stable across samples. These findings suggested that SRBO could be a functional and health-conscious alternative to palm kernel oil in plant-based mozzarella cheese, improving nutritional quality without compromising texture or functionality. Full article

The rapid expansion of the Internet of Vehicles (IoV) necessitates high-capacity backhaul connectivity, yet the deployment of such networks under strict hardware and power constraints poses significant computational challenges for network optimization. To address this challenge, this paper investigates a joint transmit–receive beamforming optimization problem for narrowband wireless backhaul in IoV networks under constant-modulus constraints. Unlike ideal digital architectures, we focus on cost-effective analog phase shifters, which introduce strictly non-convex constant-modulus constraints, rendering the optimization problem mathematically intractable for standard solvers. Since the resulting problem is highly non-convex, we develop two structured numerical methods: an iterative alternating optimization (AO) method and a joint optimization (JO) method, where AO employs auxiliary WMMSE-guided alternating updates together with constant-modulus projection, while JO jointly updates both beamformers over the constant-modulus feasible set. We compare their achievable sum-rate performance with that of a CDO-based benchmark and analyze their dominant computational costs through representative Big-O complexity expressions. Furthermore, we examine the effect of SVD-based and random feasible initializations on empirical convergence behavior, runtime, and final achievable performance. Simulation results demonstrate that the proposed computational methods significantly improve achievable sum-rate performance compared with the CDO benchmark. Moreover, SVD-based initialization provides a more structured starting point and generally leads to better convergence behavior and lower runtime than random feasible initialization. The empirical timing results further show that AO exhibits faster empirical convergence and requires lower runtime, whereas JO achieves better final sum-rate performance after more iterations. Full article