Search Results (20,565)

The Super-long Gravity Heat Pipe (SLGHP) is an efficient geothermal energy utilization technology that can transmit thermal energy by fully utilizing natural temperature differences without external energy input. This study focuses on the high-altitude geothermal environment of Mount Meager, Canada, and employs numerical simulations and dynamic thermal analysis to systematically investigate the thermal transport performance of the SLGHP system under both steady-state and dynamic operating conditions. The study also examines the impact of various structural parameters on the system’s performance. Three-dimensional CFD simulations were conducted to analyze the effects of pipe diameter, length, filling ratio, working fluid selection, and pipe material on the heat transfer efficiency and heat flux distribution of the SLGHP. The results indicate that working fluids such as CO₂ and NH₃ significantly enhance the heat flux density, while increasing pipe diameter may reduce the amount of liquid retained in the condenser section, thereby affecting condensate return and thermal stability. Furthermore, dynamic thermal analysis using a three-node RC network model simulated the effects of diurnal temperature fluctuations and variations in the convective heat transfer coefficient in the condenser section on system thermal stability. The results show that the condenser heat flux can reach a peak of 5246 W/m² during the day, while maintaining a range of 2200–2600 W/m² at night, with the system exhibiting good thermal responsiveness and no significant lag or flow interruption. In addition, based on the thermal output of the SLGHP system and the integration with the Organic Rankine Cycle (ORC) system, the power generation potential analysis indicates that the system, with 100 heat pipes, can provide stable power generation of 50–60 kW. In contrast to previous SLGHP studies focused on generalized modeling, this work introduces a site-specific CFD–RC framework, quantifies structural sensitivity via heat flux indices, and bridges numerical performance with economic feasibility, offering actionable insights for high-altitude deployment. This system has promising practical applications, particularly for providing stable renewable power in remote and cold regions. Future research will focus on field experiments and system optimization to further improve system efficiency and economic viability. Full article

This study proposes a hybrid deep learning framework for predicting vehicle crash frequency (F_i) using nationwide traffic accident and traffic volume data from the United States (2019–2022). Crash frequency is defined as the product of exposure frequency ($N_a$) and crash risk rate ($\lambda$), a structure widely adopted for its ability to separate physical exposure from the crash likelihood. $N_a$ was computed using an extended Safety Performance Function (SPF) that incorporates roadway traffic volume, segment length, number of lanes, and traffic density, while $\lambda$ was estimated using a multilayer perceptron-based deep neural network (DNN) with inputs such as impact speed, road surface condition, and vehicle characteristics. The DNN integrates rectified linear unit (ReLU) activation, batch normalization, dropout layers, and the Huber loss function to capture nonlinearity and over-dispersion beyond the capability of traditional statistical models. Model performance, evaluated through five-fold cross-validation, achieved R² = 0.7482, MAE = 0.1242, and MSE = 0.0485, demonstrating a strong capability to identify high-risk areas. Compared to traditional regression approaches such as Poisson and negative binomial models, which are often constrained by equidispersion assumptions and limited flexibility in capturing nonlinear effects, the proposed framework demonstrated substantially improved predictive accuracy and robustness. Unlike prior studies that loosely combined SPF terms with machine learning, this study explicitly decomposes F_i into $N_a$ and $\lambda$, ensuring interpretability while leveraging DNN flexibility for crash risk estimation. This dual-layer integration provides a unique methodological contribution by jointly achieving interpretability and predictive robustness, validated with a nationwide dataset, and highlights its potential for evidence-based traffic safety assessments and policy development. Full article

The mechanism of the electrophilic addition between phenylacetylene and N-heterocyclic carbene borane (NHC–borane), initiated by di-tert-butyl peroxide (DTBP), was elucidated at the M06-2X-D3/ma-def2-TZVP level to yield the Z-configured product. The computational results show that DTBP undergoes homolysis to generate two t-BuO· radicals; subsequently, it undergoes an H-shift reaction with N-heterocyclic carbene borane to form the N-heterocyclic carbene boron radical. Then, it is added to phenylacetylene to obtain the product radical intermediate. Finally, the product is yielded via an H-shift reaction. Meanwhile, this paper also explores the formation pathways of relevant byproducts. Structural analysis of the reaction reveals that weak interactions have a significant impact on the selectivity of the Z-configuration of the product. In addition, electron spin density contour maps are used to explain the electron distribution and reaction sites during the reaction process. This paper will provide relevant theoretical support for this type of addition reaction. Full article

A complex network topology marked by co-competitive relationships between manufacturing enterprises can meaningfully influence low-carbon technology selection, thereby affecting the low-carbon technology diffusion process. This study develops a small-world network game model based on an optimal update strategy involving the government and manufacturers with co-competitive relationships, and then uses it to assess the evolutionary dynamics of low-carbon technology selection and diffusion among manufacturers. The results indicate that the government should identify the critical threshold for subsidies based on the carbon tax to optimize the regulatory and incentivizing effects of government subsidies. The topological structure of manufacturers’ small-world networks is the key to low-carbon technology selection and diffusion. In favorable conditions, when a small-world network approaches a regular network in terms of structure, the extent of low-carbon technology diffusion is maximized; in unfavorable conditions, diffusion is minimal. Thus, the government can tighten or relax market access restrictions on the manufacturing industry and encourage the development of manufacturing clusters to change the structure of market competition. Compared with the random selection, the optimal update strategy can increase the probability density of low-carbon technology diffusion among manufacturers and rapidly achieve a balanced, stable state. Full article

Lipids are structurally diverse biomolecules that play essential roles in cellular function, energy storage, and signaling. The human lipidome, a dynamic and complex subset of the metabolome, is shaped by both endogenous factors, such as genetics, sex, age, and metabolic health, and exogenous influences like lifestyle, diet, and microbiota. Among these, diet stands out as one of the most modifiable and impactful determinants, influencing lipid composition across plasma, serum, and lipoprotein fractions. While traditional lipid profiling provides limited insight, lipidomics enables comprehensive characterization of lipid species, revealing mechanistic links between lipid metabolism and diseases such as cardiovascular disease (CVD), metabolic syndrome (MetS), and inflammatory disorders. This review explores: (1) the relationship between lipid profiles and CVD risk, (2) the internal and external modulators of the lipidome, and (3) current evidence on how specific dietary patterns, including Mediterranean, Nordic, low glycemic, and vegetarian diets, and individual nutrients such as omega-3 fatty acids (FAs), plant sterols, and mycoprotein, influence lipidomic profiles. Advances in lipidomics highlight that dietary fat quality, food matrix, and eating patterns can significantly modulate lipid species such as triacylglycerols (TAGs), ceramides (Cers), and phospholipids, with implications for cardiometabolic health. Notably, distinct responses are observed across plasma High-Density Lipoprotein (HDL) and Low-Density Lipoprotein (LDL) lipidomes, emphasizing the need for compartment-specific analyses. Understanding these diet-lipidome interactions offers promising avenues for precision nutrition and the development of lipid-based biomarkers for disease prevention and management. Full article

This work aimed to synthesize rigid polyurethane foams with improved functional properties through modification with the addition of cellulose in the form of straw: unmodified, silanized, and silanized with the addition of fumed silica. The prepared rigid polyurethane foams contained 0.5; 1; and 3 parts by weight of the modifier about the weight of the polyol used. As part of the work, a number of tests were carried out to determine the impact of the modifiers used on the reaction kinetics and on the functional properties of rigid polyurethane foams. Silanization improved thermal stability and interfacial compatibility, while silica further enhanced porosity and surface activity. The optimal properties were obtained at low loadings: 0.5 wt.% provided the best mechanical strength, and 1 wt.% yielded the most uniform cell morphology and density. Higher contents increased porosity, reduced strength, and lowered water resistance. Dynamic mechanical analysis confirmed predominantly elastic behavior, with silica-modified fillers offering the most stable thermomechanical response. Overall, even small amounts of modified straw enhanced mechanical, structural, and water-resistant properties, demonstrating its potential as a sustainable and cost-effective biofiller for eco-friendly polyurethane foams. Full article

Machilus thunbergii Siebold & Zucc. is recognized as an excellent tree species for landscaping and shelter forest. Excessive drought can affect the changes of physiological and biochemical substances in plants. However, little is known at present regarding the drought stress of M. thunbergii seedlings. In this paper, matrix water content, the anatomical structure of leaves, relative water content of leaves, and physiological characteristics index of leaves under droughting stress were dynamically observed. Droughting stress led to the wilting of M. thunbergii leaves, gradual closure of stomata on leaf epidermis, increases in stomatal density, gradual loosening of leaf cell structure arrangement, a thickening in leaf palisade tissue, and reductions in spongy tissue. Droughting stress caused the relative water content of the cultivation substrate to decline, the cultivation substrate reached the moderate drought level, and the seedlings began to die. Droughting stress led to the destruction of activity and balance of the leaf protective enzyme system, excessive accumulation of free radicals, the destruction of enzyme structure and function, and the production of lipid peroxidation product MDA. Droughting stress reduced the relative water content of leaves as a whole, the content of osmotic adjustment substances proline and soluble protein continued to decline, and a large number of electrolyte leakage in cells, causing serious damage to seedlings. Full article

The thioether-functionalized 2-azabutadiene (ⁱPrS)₂C=C(H)-N=CPh₂ L1 ligates to Mn(CO)₅Br to form the five-membered chelate compound fac-MnBr(CO)₃[(ⁱPrS)₂C=C(H)-N=CPh₂] MnPropBr, whose crystal structure has been determined from X-ray diffraction data. In the crystal, different secondary intermolecular interactions, such as Br^…HC and π^…π, give rise to a supramolecular network. The electronic properties of the metal–ligand bonds in MnPropBr are similar to those of complex MnPhBr (with R = SPh instead of ⁱPrS); this also applies to a series of structurally analogous fac-ReX(CO)₃[(RS)₂C=C(H)-N=CPh₂] (X = Cl, Br and I; R = SⁱPr, SPh and S^tBu) rhenium complexes and are discussed on the basis of QT-AIM (Quantum Theory of Atoms in Molecules) calculations. New bond length/electron density relationships are proposed for the metal–halide bonds, including, for the first time, complexes of one given metal and all three corresponding halides. In order to obtain a set of coherent data, three manganese complexes that belong to the family fac-MnX(CO)₃[N∩N] (X = Cl, Br and I; N∩N is a chelating ligand with two coordinating N atoms) were included in this study. Full article

Heme enzymes that bind and reduce O₂ are susceptible to poisoning by NO. The high reactivity and affinity of NO for ferrous heme produces stable ferrous-NO complexes, which in theory should preclude O₂ binding and turnover. However, NO inhibition is often competitive with respect to O₂ and rapidly reversible, thus providing cellular and organismal survival advantages. This kinetic paradox has prompted a search for mechanisms for reversal and hence resistance. Here, I critically review proposed resistance mechanisms for NO dioxygenase (NOD) and cytochrome c oxidase (CcO), which substantiate reduction or oxidation of the tightly bound NO but nevertheless fail to provide kinetically viable solutions. A ferrous heme intermediate is clearly not available during rapid steady-state turnover. Reversible inhibition can be attributed to NO competing with O₂ in transient low-affinity interactions with either the ferric heme in NOD or the ferric heme-cupric center in CcO. Toward resolution, I review the underlying principles and evidence for kinetic control of ferric heme reduction via an O₂-triggered ferric heme spin crossover and an electronically-forced motion of the heme and structurally-linked protein side chains that elicit electron transfer and activate O₂ in the flavohemoglobin-type NOD. For CcO, kinetics, structures, and density functional theory point to the existence of an analogous O₂ and reduced oxygen intermediate-controlled electron-transfer gate with a linked proton pump function. A catalytic cycle and mechanism for CcO is finally at hand that links each of the four O₂-reducing electrons to each of the four pumped protons in time and space. A novel proton-conducting tunnel and channel, electron path, and pump mechanism, most notably first hypothesized by Mårten Wikström in 1977 and pursued since, are laid out for further scrutiny. In both models, low-energy spin-orbit couplings or ‘spintronic’ interactions with O₂ and NO or copper trigger the electronic motions within heme that activate electron transfer to O₂, and the exergonic reactions of transient reactive oxygen intermediates ultimately drive all enzyme, electron, and proton motions. Full article

In low-voltage (LV) distribution networks, system operating conditions are always unbalanced due to the unpredictability of the load demand in each phase, coupled with a potentially asymmetrical network structure due to different phase conductors’ sizes and lengths. The widespread diffusion of distributed generators (DGs) among network users has significantly contributed to reducing the overall load of the electrical system, but at the cost of making voltages slightly more unbalanced. In this article, an LV distribution test network equipped with several single-phase DGs has been considered, and all During-Fault Voltages (DFVs) have been studied, according to each possible type of short circuit. To provide a measure of the asymmetry of unsymmetrical voltage dips, three different indices based on the symmetrical components of the voltages have been considered; moreover, the Monte Carlo simulation (MCS) method has allowed for studying faults and asymmetries in a probabilistic manner. Through the probability density functions (pdfs) of the DFVs, it has been possible to assess the impact of single-phase DGs on the asymmetry of bus voltages due to short-circuits. Full article

The aim of this study was to investigate the effect of a static, homogeneous magnetic field on the physicochemical properties of magnetic hydrogels based on collagen and superparamagnetic iron oxide nanoparticles (SPIONs), chemically crosslinked with genipin. The crosslinking process was initiated in the presence of a magnetic field with three different induction values (100, 250 and 500 mT), generated in specially designed experimental systems. It was demonstrated that the applied field did not noticeably affect the crosslinking efficiency, and stable hydrogels with a high gel fraction in the range of 87–94% were obtained. STEM image analysis revealed that in the highest magnetic field, the nanoparticles tended to form larger clusters, while at lower fields and in the material crosslinked at zero field, smaller clusters and chains of nanoparticles were observed mainly. This observation was reflected in the magnetic susceptibility, which showed a weaker response to the magnetic field of the material obtained by crosslinking in the presence of the 500 mT field compared to the material crosslinked without the field—larger clusters of nanoparticles may hinder the alignment of the magnetic moments of their constituent nanoparticles. Studies of the physicochemical properties of the hydrogels obtained indicate that the presence of larger clusters can cause a local decrease in the crosslinking density, resulting in a slight decrease in the storage modulus and increased initial swelling and degradation rates. The results obtained show that the application of a homogeneous magnetic field with moderate induction values during the crosslinking process can be used as a tool for modification of the microstructure of magnetic collagen-based hydrogels. The possibility of such structural modifications may be useful in designing biomaterials with properties tailored to their target application. Full article

This study proposes a multi-stage collaborative design framework integrating sensitivity analysis, response surface methodology (RSM), and topology optimization for synergistic lightweighting and performance enhancement of micromanufacturing systems using ultra-precision computer numerical control (CNC) machine tools. Overall sensitivity analysis identified the base and column as stiffness-critical components, while the spindle box exhibited significant weight-reduction potential. Using spindle box wall and bottom thickness as variables, RSM models for mass and stress were constructed. Multi-objective optimization via a genetic clustering algorithm achieved a 57.2% (590 kg) weight reduction under stress constraints (<45 MPa). Subsequent variable-density topology optimization (SIMP model) reconfigured the rib layouts of the base and column under volume constraints, reducing their weights by 38.5% (2844 kg) and 41.5% (1292 kg), respectively. Whole-machine validation showed that maximum static deformation decreased from 0.17 mm to 0.09 mm, maximum stress reduced from 58 MPa to 35 MPa, and first-order natural frequency increased from 50.68 Hz to 84.08 Hz, significantly enhancing dynamic stiffness. Cumulative weight reduction exceeded 3000 kg, achieving a balance between lightweighting and static/dynamic performance improvement. This work provides an effective engineering pathway for a structural design of high-end micromanufacturing systems. Full article

High-density communities, characterized by concentrated populations and compact built environments, often exacerbate issues such as green space fragmentation, uneven distribution, and intensified urban heat island effects. Investigating the spatiotemporal heterogeneity and evolutionary characteristics of landscape patterns driven by population density (POP), road density (RD), street-level GDP (GDP_S), and nighttime light intensity (NTL) in Wuhan’s high-density communities using a geographically weighted regression (GWR) model is essential for informing sustainable urban planning strategies. The results showed that ED, PD, and SHDI exhibit consistent annual declines averaging 1.53%, 0.97% and 0.59%, respectively, while AI increased steadily at 0.11% per year. This indicates that human intervention has surpassed natural succession and become the dominant force in shaping landscape patterns. Among them, POP and RD are the direct driving factors for landscape pattern changes, while GDP_S and NTL indirectly affect landscape patterns through economic structural adjustments and land use changes, forming differentiated spatial patterns in high-density communities. In terms of relationships, the GWR model performs better than ordinary least squares regression (OLS) by adjusting R² and residual Moran’s I, significantly improving its explanatory power. This study demonstrates the effectiveness of the GWR model in revealing the spatiotemporal heterogeneity between socioeconomic factors and landscape patterns, providing a transferable analytical framework for high-density cities. It thereby offers empirical and methodological support for addressing regional ecological constraints and advancing sustainable urban renewal. Full article

Titanium matrix composites (TMCs) possess excellent properties, which are widely applied in various high-end fields. An ultrafine multi-scale network structure may further enhance the TMCs. Then, the application potential is widened. Here, the in situ synthesized TC4-B-Si composites were prepared by selective laser melting technology, to achieve ultrafine microstructure by inducing ultra-rapid heating/cooling process. The preparation process–structure–performance relationships were investigated. It was found that an appropriate laser energy density leads to high-density TMCs with stable molten pools and good interlayer bonding. With the decreasing energy density, the in situ generated TiB network structure is refined from the sub-micron scale to the nano-scale. The most Si atoms are supersaturated solid-dissolved in the titanium matrix. In addition, the TiB distribution becomes heterogeneous. Due to the co-effect of grain refinement and reinforcement distribution, the microhardness shows a rising and then falling trend, with decreasing energy density. With a good balance of these two factors, the maximum value of microhardness reaches 454 HV. Therefore, controlling process parameters is a feasible way to achieve multi-structures, and thus enhanced properties. This method is expected to be used on various lightweight and wear-resistant structural components. Full article

Plastic pollution is an increasingly pressing environmental concern due to its persistence in ecosystems. To address this issue, this study evaluates polyethylene biodegradation and bioelectricity generation using Aspergillus ochraceopetaliformis in microbial fuel cells (MFCs). Single-chamber MFCs were designed (three) with carbon and zinc electrodes, where the fungus was cultivated in a nutrient-rich medium to enhance its metabolic activity. Parameters such as pH, power density, and FTIR spectra were monitored to assess plastic biodegradation. The results demonstrated a significant reduction in polyethylene mass and structure, along with a maximum generation of 0.921 V and 4.441 mA on day 26, with a power density of 0.148 mW/cm² and a current of 5.847 mA/cm². The optimal pH for fungal activity in the MFC was recorded at 7.059. Furthermore, FTIR analysis revealed a decrease in peak intensity at 1470 cm⁻¹ and 723 cm⁻¹, indicating structural modifications in the treated plastics. Furthermore, microbial fuel cells connected in series successfully powered an LED bulb, generating a maximum voltage of 2.78 V. These findings confirm the feasibility of using Aspergillus ochraceopetaliformis for biodegradation and bioelectricity generation, although practical applications require further optimization of system conditions and improvements in long-term stability. This research contributes to the development of biotechnological strategies for plastic waste management, sustainable integrating approaches with energy potential. Full article