Search Results (4,153)

In 3D integrated circuits, a placement decision that looks acceptable from a 2D wirelength view can still create a local thermal or stress problem after stacking. This issue becomes more visible as the number of tiers and the density of vertical interconnects increase. We propose ThermIC, a placement framework that brings thermal and mechanical risk estimates into the placement loop rather than treating them only as post-layout checks. The novelty of ThermIC does not lie in treating graph neural networks, reinforcement learning, uncertainty-aware learning, or physics-informed regularization as individually new techniques. Instead, ThermIC contributes a placement-time coupling mechanism in which physically typed graph propagation, dense multi-constraint risk prediction, and action-level reinforcement learning feedback are jointly organized for stacked 3D-IC placement. ThermIC uses a heterogeneous graph encoder to carry thermal, stress, timing, and congestion information through the netlist; a constraint head to estimate local hotspot, stress-risk, timing-violation, and congestion probabilities; and a sequential placement policy trained with physics-informed penalties. We evaluate the method on ThermIC-Bench, a simulated corpus with more than 30,000 finite-element samples from 18 heterogeneous 3D-IC designs with 4–8 tiers. Because the present study does not include proprietary industrial circuits, silicon measurements, or a tape-out case, the experimental results are interpreted as simulation-based benchmark evidence rather than final industrial qualification. ThermIC connects the heat-kernel branch to the discretized heat-conduction equation and the stress-filter branch to linear thermo-elastic equilibrium, providing a mechanism-level basis for physical interpretability. The analysis distinguishes offline simulation/training cost from online deployment cost and reports complexity, runtime, and memory scaling for practical large-scale use. Under joint DRC, thermo-mechanical stress, and thermally coupled timing checks, ThermIC obtains an $82.1\%$ physical verification pass rate. The peak-temperature error is $3.1$ °C, the hotspot localization IoU is 0.89, and the number of placement-closure iterations is reduced by $3.7\times$ relative to the heuristic baseline. Together, these benchmark results indicate that early, differentiable multi-physics feedback can make 3D placement less dependent on late correction cycles. Full article

Snow removal vehicles operate under severe working conditions, and the snowplow mounting frame is a critical structural component responsible for transmitting loads generated during snow-removal operations. To improve material utilization and reduce structural weight without compromising mechanical performance, a lightweight design methodology based on topology optimization was developed. The primary design objective was to achieve at least a 16% reduction in structural mass while maintaining acceptable stress, strain, deformation, and durability performance. First, a three-dimensional model of the mounting frame assembly was established, and finite element analysis was conducted using ANSYS under representative loading conditions. Topology optimization based on compliance minimization with a mass constraint was then performed to identify structurally inefficient regions and generate an optimized material distribution. Based on the optimization results, the mounting frame was reconstructed into a practical and manufacturable CAD model and subsequently re-evaluated through finite element analysis and fatigue assessment. The mass of the mounting frame was successfully reduced from 177.52 kg to 137.77 kg, corresponding to a weight reduction of 22.39%, significantly exceeding the initial design target. Despite this substantial reduction in weight, the maximum stress, strain, and deformation remained within allowable design limits. Furthermore, fatigue analysis predicted no fatigue failure within 1 × 10⁶ loading cycles, while the minimum fatigue safety factor remained greater than unity, confirming the durability and reliability of the redesigned structure. The results demonstrate that topology optimization provides an effective approach for improving material utilization, reducing structural weight, and enhancing the overall structural efficiency of snow-removal equipment. The successful reconstruction of the optimized topology into a manufacturable design further highlights the practical industrial applicability of the proposed methodology. Full article

Ageing vessels are critical to the sensory maturation of Baijiu, yet the interfacial material processes by which traditional ceramics modulate liquor chemistry remain insufficiently defined. Here, Zisha and ceramic-clay particles with distinct aluminosilicate frameworks, mineral compositions, and pore structures were investigated to elucidate their roles in sauce-flavor Baijiu ageing. Ceramic characterization was combined with elemental and volatile analyses using ICP-MS, GC-MS, and GC-IMS. The results showed that pore development in Zisha was primarily governed by fluxing metal oxides and the Si/Al framework, whereas metal-ion migration into Baijiu was regulated by the SiO₂-rich matrix, pore accessibility, and trace elemental composition. Metal elements exhibited reversible interfacial exchange rather than simple leaching, revealing a dynamic metal-ion cycling process during ageing. This process was associated with selective remodeling of the volatile profile. Compared with ceramic-clay particles, Zisha promoted the accumulation of acetophenone, 3-pentanone, and pyrazine derivatives while reducing dimethyl disulfide and heptanal. Sensory evaluation of Baijiu aged in ceramic jars further validated these findings. These findings identify Zisha ceramics as active material–flavour interfaces and provide a mechanistic basis for the rational design of ceramic ageing vessels to direct Baijiu flavour maturation. Full article

Phytoextraction is a sustainable strategy for removing potentially valuable elements from contaminated substrates while contributing to site remediation. However, the effectiveness of repeated phytoextractive cycles remains poorly investigated. This study evaluated the phytoextraction performance of Helianthus annuus (HA) cultivated on mining soil from Complejo Minero Fabril Sierra Pintada (Argentina) containing elevated concentrations of Ni, Zn, Sr, P, and Cu over three successive three-month cultivation cycles in TRL-4 bioreactors (BRs). The scalability of the process was subsequently assessed through projection to TRL 6 using a Vegetable Depuration Module (VDM). Elemental concentrations in soil and biomass were determined by X-ray fluorescence, while bioaccumulation coefficients, translocation factors, arbuscular mycorrhizal colonization and glomalin-related soil proteins (GRSP) were assessed to identify biological factors associated with phytoextraction performance. Projected bioextractive potential at TRL 6 (VDM) during the first cycle reached 16.15 ± 2.40 g Cu, 20.81 ± 2.19 g Zn, 7.43 ± 1.15 g Ni, 11.39 ± 1.19 g Sr, and 126.87 ± 15.42 g P. Phytoextractive efficiency declined substantially after the first cultivation cycle, indicating that a single crop harvested at the flowering stage maximized element removal under the tested conditions. The accumulation of economically relevant elements in sunflower biomass could be integrated with downstream metal recovery processes, highlighting the potential of HA for phytomining applications. Full article

Background/Objectives: Rice (Oryza sativa) is the staple food for over half the global population, and nitrogen availability is the primary limiting factor determining rice yield. As the rate-limiting enzyme in nitrogen assimilation and allocation, glutamate synthase (GOGAT) plays an irreplaceable role throughout the plant life cycle. The evolutionary history, natural genetic variation, and regulatory networks of the GOGAT family in rice source–sink tissues during grain filling remain largely elusive. Methods: Here, we combined comparative genomics, population genetics, transcriptomic and biochemical approaches to systematically characterize the GOGAT gene family. Genome-wide identification was performed across 12 angiosperm species, followed by haplotype analysis using resequencing data from ~2000 rice accessions. Transcriptomic, enzymatic activity and metabolite content determination were integrated to investigate their responses to three nitrogen gradient treatments in source (roots, flag leaves) and sink (developing embryos) tissues. Results: A total of 48 GOGAT genes were identified, clustered into two ancient subfamilies (GLU/GLT), with a Poaceae-specific duplication event generating GLT1 and GLT2 subgroups. Specifically, three rice GOGAT genes exhibited distinct domestication signatures: Fd-GOGAT showed strong indica-japonica subspecific differentiation, while NADH-GOGAT2 harbored tropical japonica-specific haplotypes. Furthermore, tissue-specific and developmental stage-dependent nitrogen response patterns were revealed, identifying 5 days after pollination as the critical metabolic switch point. OsGOGAT promoters are enriched with light-, ABA- and stress-responsive cis-elements, suggesting coordinated hormonal and environmental regulation. Conclusions: This study provides comprehensive insights into the functional divergence of the plant GOGAT gene family and coordinated strategies that rice employs under exogenous nitrogen stress, and identifies elite haplotypes for nitrogen-efficient rice breeding. Full article

Hypertension is a major risk factor for primary stroke; however, reliable noninvasive physiological biomarkers for early stroke warning in hypertensive patients remain elusive. To characterize the dynamic evolution of cerebral arterial blood conductivity—from the earliest hypertensive stages through to imminent stroke onset—we developed four physiologically grounded numerical models: normotension, borderline hypertension, established hypertension, and pre-stroke hypertension. These models were constructed based on empirically validated correlations between in vivo cerebral arterial blood conductivity and key hemodynamic parameters. All input physiological data were rigorously sourced from peer-reviewed clinical studies. Each model was coupled with standardized geometries constructed using population-averaged templates. Using the finite element method, we simulated blood conductivity across a full cardiac cycle under realistic in vivo physiological conditions. Crucially, we performed quantitative decomposition analysis to isolate and assess the individual contributions of specific physiological parameter changes—such as systolic pressure, dynamic viscosity of blood, hematocrit, and blood flow velocity—to the observed shifts in conductivity during hypertensive progression. Results revealed a biphasic, stage-dependent evolutionary pattern: conductivity initially rises slightly in borderline hypertension, then declines markedly as hypertension advances toward the pre-stroke stage. Relative to the normotensive baseline, conductivity in the pre-stroke model decreased by 17.61%—a reduction strongly associated with hypertension-induced reductions in cerebral blood flow velocity and concurrent increases in hematocrit. Comprehensive mesh independence and time-step sensitivity analyses confirmed the numerical robustness and computational reliability of all simulations. Collectively, these findings demonstrate that cerebral arterial blood conductivity undergoes quantifiable, pre-symptomatic deviation prior to stroke onset, establishing it as mechanistically grounded. The research findings demonstrate substantial theoretical significance and translational potential, grounded in a rigorously validated modeling framework and serving as a robust basis for generating and refining novel scientific hypotheses. Full article

Background/Objectives: Commercial meal delivery diets are increasingly used as a convenient alternative to home-prepared meals. However, limited data are available regarding their mineral composition and potential exposure to toxic elements. This study aimed to evaluate the content of selected essential minerals (Ca, Cu, Fe, Mg, Se and Zn) and toxic elements (Cd and Pb) in daily food rations (DFRs) offered by selected commercial catering services in Poland. Methods: DFRs representing three dietary models (Hashimoto, DASH, and low-carb diets) were collected from commercial catering providers. Concentrations of essential minerals were determined using atomic absorption spectrometry (AAS), whereas toxic elements were determined using inductively coupled plasma mass spectrometry (ICP-MS). Mineral adequacy was assessed using Estimated Average Requirement (EAR) and Tolerable Upper Intake Level (UL) reference values. Exposure to toxic elements was evaluated using Estimated Daily Intake (EDI), estimated weekly Intake (EWI), Target Hazard Quotient (THQ), and Carcinogenic Risk (CR) indices. Results: Ca was the nutrient most frequently supplied in insufficient amounts, with 80–98% of analyzed meal plans failing to meet the EAR. In contrast, the remaining minerals were generally supplied in adequate amounts. Nevertheless, excessive intake of selected minerals was observed in some dietary models, with up to 37% of DASH diets exceeding the UL for Zn and approximately 32% of Hashimoto diets exceeding the UL for Cu. Although Cd and Pb were detected in all analyzed DFRs, THQ and CR values indicated negligible health risk. Conclusions: The analyzed meal delivery diets generally provided adequate amounts of most investigated minerals and did not pose a significant health risk related to Cd or Pb exposure. However, these findings apply only to the analyzed meal plans and should not be generalized to all commercial catering services or seasonal menu cycles in Poland. The widespread inadequacy of Ca intake and the occurrence of excessive Zn and Cu intake in selected dietary models highlight the need for improved nutritional quality control of commercially prepared diets. Full article

The insulated gate bipolar transistor (IGBT) is widely applied in industrial fields such as rail transit, wind power generation, smart grids, and renewable energy. The temperature distribution, stress variation patterns, thermal performance, and modeling damage in the solder layer of IGBT modules under thermal and stress loadings have rarely been studied. This study first established a three-dimensional geometric model based on the actual dimensions of the IGBT module. A finite element model was successfully constructed for thermal/mechanical multi-physics coupled simulation based on the ANSYS Workbench platform to simulate the temperature, deformation trends, and stress distribution patterns of the solder layer in the IGBT module. Secondly, the solder layer defects of the IGBT module were categorized into five major types, and 37 sets of 3D models of IGBT with damaged solder layers were designed, followed by thermal/mechanical coupled simulation analysis for each. Finally, the influence of the void positions, sizes, and distribution types in the solder layer on the module temperature, heat dissipation path, and thermal stress was simulated during thermal cycling. The results showed that the highest stress at the edge of the solder layer is 6.2504 × 10⁷ Pa, the lowest junction temperature is 70.79 °C, and the average thermal stress is 1.2388 (m/m). The highest junction temperature reached 72.562 °C under central solder layer damage states as determined by a thermal/mechanical coupled simulation analysis of four different types of solder layer defects. This research provides a theoretical basis and reliable technical support for the anti-damage and failure of IGBT modules and high-power devices. Full article

Immune checkpoint inhibitors (ICIs) have improved clinical outcomes in recurrent or metastatic head and neck squamous cell carcinoma (HNSCC), including oral squamous cell carcinoma (OSCC). However, many patients eventually develop resistance to systemic therapy, highlighting the need for novel strategies that can restore or sustain antitumor immunity. Near-infrared photoimmunotherapy (PIT) has emerged as a tumor-selective locoregional treatment that not only induces targeted tumor cell death but also promotes antitumor immune activation through immunogenic cell death. This narrative review summarizes current evidence regarding PIT for recurrent oral cancer and explores the immunological rationale for sequential ICI–PIT–ICI therapy (ICI–PIT–ICI sequence). Within this framework, PIT-induced tumor antigen release and inflammatory activation may reinitiate elements of the cancer-immunity cycle, whereas continued PD-1 blockade may help sustain newly activated tumor-reactive T-cell responses. To illustrate this concept, we present two cases of recurrent oral cancer treated with the ICI–PIT–ICI sequence. Both patients achieved durable clinical and radiological complete responses following PIT and subsequent nivolumab continuation. Longitudinal analyses of peripheral immune surrogate markers demonstrated a biphasic temporal pattern characterized by transient increases in inflammatory markers, including neutrophil-to-lymphocyte ratio, C-reactive protein, platelet-to-lymphocyte ratio, and systemic immune-inflammation index, followed by recovery trends in absolute lymphocyte count and lymphocyte-to-monocyte ratio during continued PD-1 blockade. These observations support the biological plausibility of PIT as an immune-modulating intervention with potential immune-reprogramming effects. Although hypothesis-generating, the ICI–PIT–ICI sequence may represent a promising strategy integrating locoregional tumor destruction with systemic immune modulation in recurrent oral cancer. Further prospective studies incorporating peripheral and tissue-based immune profiling are warranted. Full article

This study presents a cradle-to-grave Life-Cycle Assessment of a multifunctional building-integrated photovoltaic (BIPV) skylight system combining a recycled aluminum frame, double-glazing unit, semi-transparent cadmium telluride (CdTe) photovoltaic glass, and an organic phase change material (PCM) for passive thermal regulation. Assessed over a 30-year service life in accordance with EN 15804+A2 using One Click LCA, the system is evaluated across 13 environmental impact categories for a declared unit of 0.72 m². Results show that materials production is the dominant environmental driver across all categories, contributing 72.0% of total GWP (78.00 kg CO₂-eq). Component replacement is the second contributor with 9.8% of GWP. End-of-life burdens account for 7.7% of cradle-to-grave GWP. When Module D credits are included, the system achieves an indicative net GWP balance of −808.34 kg CO₂-eq, that is conditional on a static Romanian grid-mix assumption; under progressive grid decarbonization this benefit is reduced, so the figure should be read as scenario-dependent potential rather than an immutable property of the product. Abiotic depletion of mineral elements is the only category where Module D does not fully offset system burdens, highlighting the relevance of critical raw material considerations for CdTe technologies. These findings demonstrate that BIPV depend on low-impact manufacturing and underscore the importance of multi-indicator LCA as the appropriate evaluation framework for integrated energy-generating building products. Full article

Graphene-based nanosheets (GNS), including graphene, graphene oxide (GO), reduced graphene oxide (rGO), and graphene nanoplatelets (GNPs), have attracted increasing attention for developing high-performance and sustainable cementitious composites. Compared with conventional dispersion strategies, graphene-based coating strategies enable the targeted localization of GNS at critical interfacial transition zones (ITZs), thereby maximizing their reinforcing efficiency while mitigating agglomeration issues. This review systematically summarizes recent advances in GNS coating technologies for cementitious composites, including physical adsorption, chemical assembly, electrophoretic deposition, and in situ growth. The effects of GNS coatings on interfacial engineering, mechanical performance, durability enhancement, and smart functionalities are critically discussed. Existing studies indicate that GNS coatings can improve strength, crack resistance, impermeability, and resistance to chloride ingress, freeze–thaw cycles, and other degradation processes mainly through ITZ densification and microstructure refinement. However, these benefits are strongly dependent on the coating method, substrate type, and stability of the graphene–substrate interface in calcium-rich alkaline pore solutions. In particular, physically adsorbed GO coatings may suffer from desorption or Ca²⁺-induced aggregation, chemically assembled coatings require further validation beyond laboratory-scale systems, and electrophoretic deposition is mainly applicable to electrically conductive substrates. In addition, localized conductive networks created by GNS coatings facilitate multifunctional properties such as self-sensing, electromagnetic shielding, and electrothermal performance. From a carbon-neutrality perspective, the improvements in mechanical properties and durability provide opportunities to reduce material consumption, extend service life, and lower life-cycle carbon emissions. Nevertheless, their carbon-neutral contribution should be verified through quantitative life-cycle assessment rather than inferred directly from strength or durability enhancement alone. Finally, the remaining challenges associated with large-scale implementation, long-term stability, cost-effectiveness, and field-scale validation are discussed. Particular attention is given to the fact that most existing evidence is derived from laboratory-scale specimens rather than real structural elements exposed to service environments. Full article

Accurate junction temperature (T_j) sensing is essential for the reliability of silicon carbide (SiC) power modules in electric vehicles. Nonetheless, the physical separation and consequent thermal signal delay between sensing elements and chips pose significant challenges to precise junction temperature monitoring. To solve this issue, an embedded temperature sensing structure integrated into the designed double-sided cooling (DSC) SiC power module is proposed, which leverages 3D vertical interconnects to enhance temperature observability. The customized design of a copper spacer serves as the primary heat dissipation path and electrical connection between the upper and lower chips in the same location. A compact thermal resistance network and 3D finite-element simulations are developed to reveal the vertical thermal coupling between the spacers and the chips, enabling accurate junction temperature estimation from spacer temperature. The proposed concept is experimentally validated on a fabricated prototype using embedded K-type thermocouples and an IR camera under power cycling conditions. The measured temperature differences between the copper spacers and the junction temperature are maintained within approximately 0.5 –2 °C under the tested operating range. This approach provides a potential application in real-time condition monitoring and thermal management in high-power-density electric drives. Full article

Background/Objectives: eccDNA is a promising cancer biomarker in liquid biopsy. However, the reliability and reproducibility of eccDNA studies rely on the standardization of pre-analytical handling and processing of eccDNA, as well as transparent methodological reporting. Although evidence-based guidelines for cell-free DNA handling provide clear recommendations for plasma/serum processing, the extent to which eccDNA studies report and adhere to these key procedures remains uncertain. Methods: We systematically reviewed 14 studies (2017–2025) assessing eccDNA in plasma or serum from cancer patients. Each study was evaluated against 22 checklist items summarized from the NCI Biospecimen Collection and Processing Guideline, categorized into biospecimen collection, blood processing, and eccDNA processing. Items were classified as “reported,” “not reported,” or “deviated from NCI guideline,” and missing/deviation rates were calculated. Results: Publication was largely post-guideline (13/14 after 2020). Reporting gaps were widespread. Items with 100% missing were venipuncture site (14/14), freeze–thaw cycles (14/14), and fitness for downstream analysis/pre-assay QC (14/14). Other frequently missing elements included blood volume (10/14; 71%), collection tube type (7/14; 50%), date/time from draw to processing (11/14; 79%), second centrifugation parameters (8/14; 57%), storage temperature before freezing (6/14; 43%), frozen storage duration (13/14; 93%), and post-thaw handling (13/14; 93%). By contrast, the extraction method was consistently reported (0% missing), and most reported quantification (21% missing). Deviations from the NCI guideline were uncommon when items were reported, such as a blood processing delay (2/14; 14%) and the use of circulating nucleic acid kits for eccDNA extraction (1/14; 7%). Conclusions: Inconsistent reporting of pre-analytical procedures limits the reproducibility, transparency, and clinical translation of eccDNA research. We propose a concise reporting checklist informed by the NCI guideline. By focusing on the most frequently underreported aspects of key pre-analytical eccDNA procedures, the checklist provides researchers with an efficient and succinct methodological reporting framework that will enhance transparency and promote standardization in future eccDNA studies. Full article

High-efficiency industrial motors are increasingly important for reducing energy consumption, operating costs, and indirect carbon emissions. This study presents a comparative evaluation of IE2 and IE4 efficiency class induction motors with the same rated power and frame size through finite element analysis and prototype testing. Two-dimensional transient electromagnetic models were developed in ANSYS Maxwell to investigate magnetic flux distribution, torque behavior, losses, and steady-state performance, and the numerical results were experimentally validated according to IEC 60034-2-1 procedures. The results show that the IE4 motor provides a more balanced magnetic flux distribution, lower local saturation tendency, reduced torque ripple, and lower total losses than the IE2 motor. Experimental measurements confirmed the numerical predictions with good agreement, particularly at the rated operating point. In addition to higher efficiency, the IE4 motor exhibited stronger starting and breakdown torque characteristics, indicating superior load-handling capability. An economic assessment based on a representative duty cycle showed that the relative additional cost of the IE4 motor can be recovered within approximately 0.81 years, while lower annual electricity consumption also reduces indirect CO₂ emissions. Furthermore, the IE4 prototype operated at a lower thermal steady-state temperature, supporting longer insulation life and improved long-term reliability. Overall, the findings demonstrate that replacing conventional IE2 motors with IE4 alternatives is not merely an efficiency upgrade, but also a technically robust, economically justified, and environmentally effective strategy for sustainable industrial systems. Full article

Building Information Modeling (BIM) usually represents a building as a static snapshot of the model’s state. Dynamic extensions, such as Internet of Things(IoT)-enabled sensing or immersive visualization, already exist, but the underlying data model remains state-based. The Industry Foundation Classes (IFC) standard does not define a formal mechanism that would link the same physical element across successive phases of a building’s life cycle. Design, construction, and operation are recorded in separate IFC files, and the same element is assigned different Globally Unique Identifiers (GUIDs) in each. The result is fragmentation of the element’s identity, loss of the history of property changes, and the inability to formulate cross-phase queries. This paper proposes the BIM-Phase ontology based on the fundamental Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) ontology, which solves this problem by introducing a distinction between a building element as an endurant and its life cycle phases as perdurants. The ontology comprises nine classes, six object relations, and six axioms expressed in Web Ontology Language 2 Description Logic (OWL 2 DL). Phase properties and relations are represented using a reification pattern, which maintains full compatibility with the expressiveness of OWL 2 DL. The ontology was validated using an example of a single-family residential building developed in Autodesk Revit. Three structural elements (external wall, floor slab, and column) were tracked across three phases of the life cycle. Eight competency questions covering scalar, constitutional, and mereological changes were defined and mapped to ontology constructs, confirming that the BIM-Phase enables the recording of changes and the formulation of cross-phase queries that are impossible in classic IFC. All eight questions were answered correctly on the published knowledge graph, and the HermiT reasoner confirmed the logical consistency of the model. The findings show that preserving element identity across phases requires only a minimal ontological layer on top of existing standards. We recommend introducing persistent, phase-independent identifiers of building elements alongside IFC GUIDs, as this single change enables full lifecycle change tracking. Full article