Search Results (1,284)

We present a novel derivation of the spacetime metric generated by matter, without invoking Einstein’s field equations. For static sources, the metric arises from a relativistic formulation of D’Alembert’s principle, where the inertial force is treated as a real dynamical entity that exactly compensates gravity. This leads to a conformastatic metric whose geodesic equation—parametrized by proper time—reproduces the relativistic version of Newton’s second law for free fall. To extend the description to moving matter—uniformly or otherwise—we apply a Lorentz transformation to the static metric. The resulting non-static metric accounts for the motion of the sources and, remarkably, matches the weak-field limit of general relativity as obtained from the linearized Einstein equations in the de Donder (or Lorenz) gauge. This approach—at least at Solar System scales, where gravitational fields are weak—is grounded in a new dynamical interpretation of the Equivalence Principle. It demonstrates how gravity can emerge from the relativistic structure of inertia, without postulating or solving Einstein’s equations. Full article

Low fertility limits reproductive efficiency in cattle. This study was conducted with multiparous Brangus cows receiving dietary supplementation with or without L-citrulline [Cit; an immediate precursor of L-arginine (Arg)]. During the entire experimental period, cows grazed green pasture and had free access to drinking water and mineral blocks. One hundred and seven (107) cows were assigned randomly to one of three treatment groups: dried distillers grains with solubles (DDGS) without Cit supplement (n = 36); DDGS top-dressed with rumen-protected Cit product (RPAA; n = 36); or unprotected Cit product (RUAA; n = 35). After 2 months of lactation, all cows were synchronized to estrus and were bred once via artificial insemination. From Day 1 to Day 60 of gestation, cows were individually fed once daily 0.84 kg of a supplement (DDGS; control), 0.56 kg of DDGS plus 0.28 kg of RUAA (containing 0.07 kg of unencapsulated Cit), or 0.56 kg of DDGS plus 0.28 kg of RPAA (containing 0.07 kg of rumen-protected Cit). The supplemental dose of Cit was equivalent to 0.5% of the estimated daily intake of 14 kg dry matter from pasture. On Days 40 and 60 of gestation, ultrasound was used to determine pregnancy rates. Each pregnant cow had a single conceptus. On Day 60 of gestation, blood samples were obtained from the jugular vein. All cows grazed normally and appeared healthy. Birth rates for live-born calves were 22% and 35% in cows receiving DDGS alone and Cit supplementation, respectively (p < 0.05). The beneficial effect of Cit was associated with increases in concentrations of Cit (+19%), Arg (+20%), ornithine (+19%), proline (+17%), and insulin (+82%) but decreases in concentrations of ammonia (–14%) in maternal plasma (p < 0.05). Thus, dietary supplementation with Cit is a simple, novel, and cost-effective nutritional method to increase the reproductive efficiency of lactating beef cows. Full article

Particulate matter (PM), a complex mixture of solid particles and liquid droplets, originates from both natural sources, such as sand, pollen, and marine salts, and anthropogenic activities, including vehicle emissions and industrial processes. While PM itself is not inherently toxic in all its forms, it often acts as a carrier of xenobiotic toxicants, such as heavy metals and organic pollutants, which adhere to its surface. This combination can result in synergistic toxic effects, significantly enhancing the potential harm to biological systems. Due to its small size and composition, PM can penetrate deep into the respiratory tract, acting as a physical “shuttle” that facilitates the distribution and bioavailability of toxic substances to distant organs. The omnipresence of PM in the environment leads to unavoidable and constant exposure, contributing to increased morbidity and mortality rates, particularly among vulnerable populations like the elderly, children, and individuals with pre-existing health conditions. This exposure also imposes a substantial financial burden on healthcare systems, as treating PM-related illnesses requires significant medical resources and leads to higher healthcare costs. Addressing these challenges necessitates effective mitigation strategies, including reducing PM exposure, improving air quality, and exploring novel approaches such as AI-based exposure prediction and nutritional interventions to protect public health and minimize the adverse effects of PM pollution. Full article

Students and educators spend considerable time in indoor learning spaces on university campuses, where indoor air quality (IAQ), of which particulate matter (PM) is an important component, is a critical concern that architecture students must address. However, IAQ is seldom monitored and very rarely, if at all, reported in these spaces. We used a novel living lab approach to provide third-year students of building services with a hands-on learning activity. During a two-week monitoring period, students designed, assembled, and operated low-cost PM sensors using Arduino platforms. The data analysis showed hotspots where the IAQ was consistently compromised and showed repetitive patterns in time. Workshop and laboratory areas repeatedly recorded the highest PM levels in 15 min sampling events distributed over daily two-hour segments, averaging 43.3 and 47.9 μg/m³ PM₁₀, respectively, with maxima of 118.6 and 119.9 μg/m³ PM₁₀. These measurements would have qualified as ‘moderate’ IAQ if sustained over a full day. A distinct weekly pattern was discovered, with Mondays being worse. The results demonstrated a new practical approach to monitoring the building’s IAQ at minimal cost while obtaining reproducible data. This tool provided educators with a valuable teaching tool that provided students with a deeper understanding of indoor air pollution. Full article

Nanophotonics, the study of light–matter interactions at the nanometer scale, has emerged as a transformative field that bridges photonics and nanotechnology. Using engineered nanomaterials—including plasmonic metals, high-index dielectrics, two-dimensional (2D) materials, and hybrid systems—nanophotonics enables light manipulation beyond the diffraction limit, unlocking novel applications in sensing, imaging, and quantum technologies. This review provides a comprehensive overview of recent advances (post-2020) in nanophotonic materials, fabrication methods, and their cutting-edge applications. We first discuss the fundamental principles governing nanophotonic phenomena, such as localized surface plasmon resonances (LSPRs), Mie resonances, and exciton–polariton coupling, highlighting their roles in enhancing light–matter interactions. Next, we examine state-of-the-art fabrication techniques, including top-down (e.g., electron beam lithography and nanoimprinting) and bottom-up (e.g., chemical vapor deposition and colloidal synthesis) approaches, as well as hybrid strategies that combine scalability with nanoscale precision. We then explore emerging applications across diverse domains: quantum photonics (single-photon sources, entangled light generation), biosensing (ultrasensitive detection of viruses and biomarkers), nonlinear optics (high-harmonic generation and wave mixing), and integrated photonic circuits. Special attention is given to active and tunable nanophotonic systems, such as reconfigurable metasurfaces and hybrid graphene–dielectric devices. Despite rapid progress, challenges remain, including optical losses, thermal management, and scalable integration. We conclude by outlining future directions, such as machine learning-assisted design, programmable photonics, and quantum-enhanced sensing, and offering insights into the next generation of nanophotonic technologies. This review serves as a timely resource for researchers in photonics, materials science, and nanotechnology. Full article

Soil organic matter (SOM) is a fundamental indicator of soil health and a major component of the global carbon cycle; its accurate quantification is essential for sustainable agriculture. Conventional chemical assays yield only point-based soil measurements and miss the spatial distribution of soil elements; airborne hyperspectral remote sensing has emerged as a promising approach for the quantitative measurement and characterization of SOM. Inversion models translate hyperspectral data into quantitative SOM estimates. However, existing models rely solely on a single preprocessing pathway, limiting their ability to fully exploit available spectral information. We address these limitations by developing a marginal contribution-driven spectral fusion network (MC-SFNet) that conducts feature-level fusion of heterogeneous preprocessing outputs within a physics-guided deep architecture. Moreover, the combination of data-driven fusion and the Kubelka–Munk (KM) model yields more physically interpretable spectral features, advancing beyond prior purely data-driven methods. We validated MC-SFNet on a self-constructed remote sensing, high-throughput hyperspectral dataset comprising 200 black soil samples from Northeastern China (400–1000 nm, 256 bands). Experimental results show that our network reduces the RMSE by 10.7% relative to the prevailing generalized hyperspectral soil-inversion model. The proposed method provides a novel preprocessing pathway for forthcoming airborne high-throughput hyperspectral missions to extract soil-specific spectral information more effectively and further enhance large-scale SOM retrieval accuracy. Full article

Using data on the children of the respondents who participated in Wave IV (2008) and Wave V (2016–2018) of the National Longitudinal Study of Adolescent to Adult Health, we estimate the effect of long-term exposure to ozone (O₃) and particulate matter 2.5 (PM_2.5) on diagnoses of allergies and asthma in adolescence and young adulthood. Estimates from individual-level fixed-effect models with time-varying controls show that exposure to PM_2.5 and O₃ is associated with higher likelihood of asthma and allergies in females at younger ages (10–12 years old) and allergies in males at older ages (13 years old and above). These findings are novel and contribute to the growing body of literature exploring gender and age differences in susceptibility to asthma and allergies. Full article

Neglected Tropical Diseases (NTDs) encompass a range of disorders, including infectious diseases caused by viruses, bacteria, parasites, fungi, and toxins, mainly affecting underprivileged individuals in developing countries. Among the NTDs, those caused by parasites belonging to the Trypanosomatidae family are particularly impacting and require attention, since the lack of financial incentives has led to constraints on the development of novel drugs to tackle them effectively. To circumvent the minor advances in drug discovery in this area, academic research emerges as a crucial player, namely through the identification and validation of new drug targets, thereby contributing to the development of more efficient, safe, and less expensive therapies against Trypanosomatidae infections. Noteworthy, this is a matter of utmost urgency since these diseases are endemic in countries with low socioeconomic standards. This review provides a comprehensive understanding of the current paradigm of NTDs caused by parasites belonging to the Trypanosomatidae family, addressing the ongoing limitations and challenges associated to the current chemotherapy solutions for these diseases and discussing the opportunities unravelled by recent research that led to the identification of new biomolecular targets that are common to Trypanosomatidae parasites. Among these, the unique properties of Trypanothione Synthetase (TryS) and Trypanothione Reductase (TryR), two key protozoan enzymes that are essential for the survival of Trypanosoma and Leishmania parasites, will be emphasised. In addition to a critical analysis of the latest advances in the discovery of novel molecules capable of inhibiting TryS and TryR, the possibility of dual targeting through a combination of TryS and TryR inhibitors will be addressed Full article

In the evolving digital landscape, the pervasive influence of artificial intelligence (AI) on social media platforms reveals a compelling paradox: the capability to provide personalized experiences juxtaposed with inherent biases reminiscent of human imperfections. Such biases prompt rigorous contemplation on matters of fairness, equity, and societal ramifications, and penetrate the foundational essence of AI. Within this intricate context, the present work ventures into novel domains by examining the potential of quantum computing as a viable remedy for bias in artificial intelligence. The conceptual framework of the quantum sentinel is presented—an innovative approach that employs quantum principles for the detection and scrutiny of biases in AI algorithms. Furthermore, the study poses and investigates the question of whether the integration of advanced quantum computing to address AI bias is seen as an excessive measure or a requisite advancement commensurate with the intricacy of the issue. By intertwining quantum mechanics, AI bias, and the philosophical considerations they induce, this research fosters a discourse on the journey toward ethical AI, thus establishing a foundation for an ethically conscious and balanced digital environment. We also show that the quantum Zeno effect can protect SVM hyperplanes from bias through targeted simulations. Full article

A quantitative study of the complicated three-dimensional structures of artificial atoms in the field of intense matter physics requires a collaborative method that combines a statistical analysis of unusual graph features related to atom topology. Simplified circuits can also be produced by using similar transformations to streamline complex circuits that need laborious mathematical calculations during analysis. These modifications can also be used to determine the number of spanning trees required for specific graph families. The explicit derivation of formulas to determine the number of spanning trees for novel pyramid graph types based on the Fritsch graph, which is one of only six graphs in which every neighborhood is a 4- or 5-vertex cycle, is the focus of our study. We conduct this by utilizing our understanding of difference equations, weighted generating function rules, and the strength of analogous transformations found in electrical circuits. Full article

Background: Vascular dysfunction is increasingly recognized as a shared contributor to both cognitive impairment and late-life depression (LLD). However, the combined diagnostic value of cerebral hemodynamics, neuroimaging markers, and neuropsychological outcomes remains underexplored. This study aimed to investigate the associations be-tween transcranial Doppler (TCD) ultrasound parameters, cognitive performance, and depressive symptoms in older adults with mild cognitive impairment (MCI) and LLD. Importantly, we evaluated the integrative value of TCD-derived indices alongside MRI-confirmed white matter lesions (WMLs) and standardized neurocognitive and affective assessments. Methods: In this cross-sectional study, 96 older adults were enrolled including 78 cognitively unimpaired individuals and 18 with MCI. All participants underwent structured clinical, neuropsychological, and imaging evaluations including the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Geriatric Depression Scale (GDS-15), MRI-based Fazekas scoring of WMLs, and TCD ultrasonography of the middle cerebral artery. Hemodynamic variables included mean blood flow velocity (MBFV), end-diastolic velocity (EDV), pulsatility index (PI), and resistive index (RI). Logistic regression and receiver operating characteristic (ROC) analyses were used to identify independent predictors of MCI. Results: Participants with MCI showed significantly lower MBFV and EDV, and higher PI and RI (p < 0.05 for all) compared with cognitively unimpaired participants. In multivariate analysis, lower MBFV (OR = 0.64, p = 0.02) and EDV (OR = 0.70, p = 0.03), and higher PI (OR = 3.2, p < 0.01) and RI (OR = 1.9, p < 0.01) remained independently associated with MCI. ROC analysis revealed excellent discriminative performance for RI (AUC = 0.919) and MBFV (AUC = 0.879). Furthermore, PI correlated positively with depressive symptom severity, while RI was inversely related to the GDS-15 scores. Conclusions: Our findings underscore the diagnostic utility of TCD-derived hemodynamic parameters—particularly RI and MBFV—in identifying early vascular contributions to cognitive and affective dysfunction in older adults. The integration of TCD with MRI-confirmed WML assessment and standardized cognitive/mood measures represents a novel and clinically practical multi-modal approach for neurovascular profiling in aging populations. Full article

The detection of trace chemicals at low and ultra-low concentrations is critical for applications in environmental monitoring, medical diagnostics, food safety and other fields. Conventional detection techniques often lack the required sensitivity, specificity, or cost-effectiveness, making real-time, in situ analysis challenging. Surface-enhanced Raman spectroscopy (SERS) is a powerful analytical tool, offering improved sensitivity through the enhancement of Raman scattering by plasmonic nanostructures. While noble metals such as Ag and Au are currently the reference choices for SERS substrates, fabrication methods should balance enhancement efficiency, reproducibility and scalability. In this study, we propose a novel approach for SERS substrate fabrication using reactive Aerosol Jet Printing (r-AJP) as an innovative additive manufacturing technique. The r-AJP process enables in-flight Ag seed reduction and nucleation of Ag nanoparticles (NPs) by mixing silver nitrate and ascorbic acid aerosols before deposition, as suggested by computational fluid dynamics (CFD) simulations. The resulting coatings were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM) analyses, revealing the formation of nanoporous crystalline Ag agglomerates partially covered by residual matter. The as-prepared SERS substrates exhibited remarkable SERS activity, demonstrating a high enhancement factor (10⁶) for rhodamine (R6G) detection. Our findings highlight the potential of r-AJP as a scalable and cost-effective fabrication strategy for next-generation SERS sensors, paving the way for the development of a new additive manufacturing tool for noble metal material deposition. Full article

In recent years, Ga-based liquid metals have emerged as a prominent research focus in catalysis, owing to their unique properties, including fluidity, low melting point, high thermal and electrical conductivity, and tunable surface characteristics. This review summarizes the synthesis strategies for Ga-based liquid metal catalysts, with a focus on recent advances in their applications across electrocatalysis, thermal catalysis, photocatalysis, and related fields. In electrocatalysis, these catalysts exhibit potential for reactions such as electrocatalytic CO₂ reduction, electrocatalytic ammonia synthesis, electrocatalytic hydrogen production, and the electrocatalytic oxidation of alcohols. As to thermal catalysis, these catalysts are employed in processes such as alkane dehydrogenation, selective hydrogenation, thermocatalytic CO₂ reduction, thermocatalytic ammonia synthesis, and thermocatalytic plastic degradation. In photocatalysis, they can be used in other photocatalytic reactions such as organic matter degradation and overall water splitting. Furthermore, Ga-based liquid metal catalysts also exhibit distinct advantages in catalytic reactions within battery systems and mechano-driven catalysis, offering innovative concepts and technical pathways for developing novel catalytic systems. Finally, this review discusses the current challenges and future prospects in Ga-based liquid metal catalysis. Full article

Snails at hydrothermal vents rely on symbiotic bacteria for nutrition; however, the specifics of these associations in adapting to such extreme environments remain underexplored. This study investigated the community structure and metabolic potential of bacteria associated with two Indian Ocean vent snails, Chrysomallon squamiferum and Gigantopelta aegis. Using microscopic, phylogenetic, and metagenomic analyses, this study examines bacterial communities inhabiting the foot and gland tissues of these snails. G. aegis exhibited exceptionally low bacterial diversity (Shannon index 0.14–0.18), primarily Gammaproteobacteria (99.9%), including chemosynthetic sulfur-oxidizing Chromatiales using Calvin–Benson–Bassham cycle and methane-oxidizing Methylococcales in the glands. C. squamiferum hosted significantly more diverse symbionts (Shannon indices 1.32–4.60). Its black variety scales were dominated by Campylobacterota (67.01–80.98%), such as Sulfurovum, which perform sulfur/hydrogen oxidation via the reductive tricarboxylic acid cycle, with both Campylobacterota and Gammaproteobacteria prevalent in the glands. The white-scaled variety of C. squamiferum had less Campylobacterota but a higher diversity of heterotrophic bacteria, including Delta-/Alpha-Proteobacteria, Bacteroidetes, and Firmicutes (classified as Desulfobacterota, Pseudomomonadota, Bacteroidota, and Bacillota in GTDB taxonomy). In C. squamiferum, Gammaproteobacteria, including Chromatiales, Thiotrichales, and a novel order “Endothiobacterales,” were chemosynthetic, capable of oxidizing sulfur, hydrogen, or iron, and utilizing the Calvin–Benson–Bassham cycle for carbon fixation. Heterotrophic Delta- and Alpha-Proteobacteria, Bacteroidetes, and Firmicutes potentially utilize organic matter from protein, starch, collagen, amino acids, thereby contributing to the holobiont community and host nutrition accessibility. The results indicate that host species and intra-species variation, rather than the immediate habitat, might shape the symbiotic microbial communities, crucial for the snails’ adaptation to vent ecosystems. Full article

This study presents a novel approach to address these challenges by introducing automobile platinum honeycomb catalysts into biomass combustion systems. The study employed a dual methodology, combining experimental investigations and a Life Cycle Assessment (LCA) case study, to comprehensively evaluate the catalyst’s performance and environmental impacts. The catalyst’s ability to facilitate combustion without open flame formation and its operational efficiency throughout combustion phases position it as a promising avenue for reducing gaseous and particulate matter emissions. The LCA considers multiple impact categories, employing the ReCiPe 2008 Hierarchist midpoint and endpoint perspective to assess environmental effects. The experimental results show that the catalyst effectively reduced CO, SO₂, and particulate emissions. Temperatures below 400 °C diminished the catalyst’s performance. The catalyst achieved a 100% CO conversion rate at specific temperatures of 427.4–490.3 °C. The findings highlight the potential for a 34% reduction in environmental impacts when replacing conventional rice husk combustion with the catalyst-integrated system. Notably, the study emphasizes the significance of sustainable catalyst manufacturing processes and cleaner electricity sources in maximizing environmental benefits. In conclusion, the integration of platinum honeycomb catalysts into biomass combustion systems, exemplified by rice husk combustion, emerges as a promising strategy for achieving more sustainable and environmentally friendly bioenergy production. Full article