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Spectral resolution is an important parameter of a wavemeter. Here, we propose a compact wavemeter based on two gratings and signal processing. By applying the Multiple Signal Classification (MUSIC) algorithm to process the sampled Talbot patterns and reconstruct the spectrum, we have demonstrated through simulations the capability to enhance spectral resolution. Overall, we present a compact wavemeter capable of improving resolution. Using this method, while maintaining the contrast of the Talbot patterns, the spectral resolution can reach 5 pm, which is higher than that of any currently reported Talbot wavemeters.

Radiotherapy plays a critical role in the clinical treatment of breast cancer. However, the efficacy of traditional X-ray radiotherapy is greatly limited by its low tumor specificity and treatment tolerance mediated by the tumor microenvironment. Herein, we proposed a novel nano-radiotherapy sensitization strategy to design and construct a cancer cell membrane-coated siRNA-decorated Au/MnO2 nanosensitizer (R&F@Au/MnO2-CM) to synergistically enhance radio-immunotherapy for breast cancer. In the integrated nanosensitizer, the cancer cell membrane (CM) derived from 4T1 breast cancer cells is utilized for targeted functionality, while Au/MnO2 is designed to improve X-ray absorption and alleviate tumor hypoxia. Additionally, PD-L1 siRNA (R) is used to downregulate PD-L1 expression in tumor cells. In an in situ mouse model of 4T1 breast cancer, R&F@Au/MnO2-CM demonstrated accurate tumor identification via CM-mediated homologous targeting after intravenous injection, which was monitored in real-time through NIR-II fluorescence imaging of NIR-935 (F). Subsequently, the radiotherapy sensitivity was achieved due to the strong radiation absorption properties and oxygen generation through catalysis of Au/MnO2 upon X-ray irradiation. Furthermore, the immunosuppressive microenvironment of the tumor is improved by downregulating PD-L1, enhancing synergistic anti-tumor effect. Our findings demonstrate a promising approach for tumor treatment by combining targeted enhanced radiotherapy with immune activation.

The prediction of electricity consumption plays a vital role in promoting sustainable development, ensuring energy security and resilience, facilitating regional planning, and integrating renewable energy sources. A novel electricity consumption characterization and prediction model based on land use was proposed. This model achieves land-use subdivision to provide highly correlated variables; exhibits strong interpretability, thereby revealing even marginal effects of land use on electricity consumption; and demonstrates high performance, thereby enabling large-scale simulations and predictions. Using 297 cities and 2,505 counties as case studies, the key findings are as follows: (1) The model demonstrates strong generalization ability (R2 = 0.91), high precision (Kappa = 0.77), and robustness, with an overall prediction accuracy exceeding 80 %; (2) The marginal impact of industrial land on electricity consumption is more complex, with more efficiency achieved by limiting its area to either 104.3 km2 or between 288.2 and 657.3 km2; (3) The marginal impact of commercial and residential land on electricity consumption exhibits a strong linear relationship (R2 > 0.80). Restricting the scale to 11.3 km2 could effectively mitigate this impact. Mixed commercial and residential land is advantageous for overall electricity consumption control, but after exceeding 43.5 km2, separate layout considerations for urban residential land are necessary; (4) In 2030, Shanghai's electricity consumption is projected to reach 155,143 million kW·h, making it the highest among the 297 cities. Meanwhile, Suzhou Industrial Park leads among the 2,505 districts with a consumption of 30,996 million kW·h; (5) Identify future electricity consumption hotspots and clustering characteristics, evaluate the renewable energy potential in these hotspot areas, and propose targeted strategies accordingly.

Plaque rupture with consequent thrombosis is the leading cause of acute cardiovascular events, during which macrophage death is a hallmark. Ferroptosis is a pivotal intermediate link between early and advanced atherosclerosis. Existing evidence indicates the involvement of macrophage ferroptosis in plaque vulnerability; however, the exact mechanism remains elusive. The aim of this study was to explore key ferroptosis-related genes (FRGs) involved in plaque progression and the underlying molecular mechanisms involved. The expression landscape of FRGs was obtained from atherosclerosis-related GEO datasets. Molecular mechanism studies of ferroptosis were performed using bone marrow-derived macrophages (BMDMs) and macrophage-derived foam cells (MDFCs). Bioinformatics analysis and immunohistochemistry revealed that macrophage haem oxygenase-1 (HMOX1) is the key FRG involved in plaque destabilization. Hypoxic conditions induced a significant increase in Hmox1 expression in MDFCs but not in macrophages. In addition, the beneficial or deleterious effects of Hmox1 were dependent on the degree of Hmox1 induction. Hmox1 overexpression drove inflammatory responses and ferroptotic oxidative stress in MDFCs and aggravated the plaque burden in atherosclerotic model mice. Further mechanistic investigations demonstrated that hypoxia-mediated degradation of egl-9 family hypoxia-inducible factor 3 (Egln3) stabilized Hif1a, which subsequently promoted Hmox1 transcription. Our findings suggest that high Hmox1 expression under hypoxia is deleterious to MDFC viability and plaque stability, providing a reference for the management of acute cardiovascular events.

Abstract Background Class III peroxidases (PODs) perform crucial functions in various developmental processes and responses to biotic and abiotic stresses. However, their roles in wheat seed dormancy (SD) and germination remain elusive. Results Here, we identified a wheat class III POD gene, named TaPer12-3A, based on transcriptome data and expression analysis. TaPer12-3A showed decreasing and increasing expression trends with SD acquisition and release, respectively. It was highly expressed in wheat seeds and localized in the endoplasmic reticulum and cytoplasm. Germination tests were performed using the transgenic Arabidopsis and rice lines as well as wheat mutant mutagenized with ethyl methane sulfonate (EMS) in Jing 411 (J411) background. These results indicated that TaPer12-3A negatively regulated SD and positively mediated germination. Further studies showed that TaPer12-3A maintained H2O2 homeostasis by scavenging excess H2O2 and participated in the biosynthesis and catabolism pathways of gibberellic acid and abscisic acid to regulate SD and germination. Conclusion These findings not only provide new insights for future functional analysis of TaPer12-3A in regulating wheat SD and germination but also provide a target gene for breeding wheat varieties with high pre-harvest sprouting resistance by gene editing technology.

The spectral energy distribution (SED) of galaxies is essential for deriving fundamental properties like stellar mass and star formation history (SFH). However, conventional methods, including both parametric and nonparametric approaches, often fail to accurately recover the observed cosmic star formation rate (SFR) density due to oversimplified or unrealistic assumptions about SFH and their inability to account for the complex SFH variations across different galaxy populations. To address this issue, we introduce a novel approach that improves galaxy broadband SED analysis by incorporating physical priors derived from hydrodynamical simulations. Tests using IllustrisTNG simulations demonstrate that our method can reliably determine galaxy physical properties from broadband photometry, including stellar mass within 0.05 dex, current SFR within 0.3 dex, and fractional stellar formation time within 0.2 dex, with a negligible fraction of catastrophic failures. When applied to the Sloan Digital Sky Survey (SDSS) main photometric galaxy sample with spectroscopic redshift, our estimates of stellar mass and SFR are consistent with the widely used MPA-JHU and GSWLC catalogs. Notably, using the derived SFHs of individual SDSS galaxies, we estimate the cosmic SFR density and stellar mass density with remarkable consistency to direct observations up to z ~ 6. This demonstrates a significant advancement in deriving SFHs from SEDs that closely align with observational data. Consequently, our method can reliably recover observed spectral indices such as D _n (4000) and H δ _A by synthesizing the full spectra of galaxies using the estimated SFHs and metal enrichment histories, relying solely on broadband photometry as input. Furthermore, this method is extremely computationally efficient compared to conventional approaches.

In ΛCDM cosmology, galaxies form and evolve in their host dark matter (DM) halos. Halo mass is crucial for understanding the halo–galaxy connection. The abundance-matching (AM) technique has been widely used to derive the halo masses of galaxy groups. However, the quenching of the central galaxy can decouple the coevolution of its stellar mass and DM halo mass. Different halo assembly histories can also result in significantly different final stellar masses of the central galaxies. These processes can introduce substantial uncertainties into the halo masses derived from the AM method, particularly leading to a systematic bias between groups with star-forming centrals (blue groups) and passive centrals (red groups). To improve this, we have developed a new machine learning (ML) algorithm that accounts for these effects and is trained on simulations. Our results show that the ML method eliminates the systematic bias in the derived halo masses for blue and red groups and is, on average, ~one-third more accurate than the AM method. With careful calibrations of observable quantities from simulations and observations from the Sloan Digital Sky Survey (SDSS), we apply our ML model to the SDSS groups to derive their halo masses down to 10 ^11.5 M _⊙ or even lower. The derived SDSS group halo mass function agrees well with the theoretical predictions, and the derived stellar-to-halo mass relations for both the red and blue groups match well with those obtained from direct weak-lensing measurements. These new halo mass estimates enable more accurate investigation of the galaxy–halo connection and the role of halos in galaxy evolution.

Energy transition has brought widespread attentions to the concept of coupled utilization of the geothermal and solar energy. This paper provides an integrated assessment on developing a nanofluid geothermal-photovoltaic hybrid system that addresses the multi-objective optimization and multi-criteria evaluation difficulties. The coupling system design and dispatch are optimized by considering the multiple objectives from the microscopic particles to the system. The life cycle cost, levelized cost of energy, levelized cost of heat, and the irreversibility are introduced in the optimization stage. The optimization parameters include the pipe arrangement, type of nanoparticles, and the concentration of the nanoparticles in nanofluids. A combined analysis including the energy, exergy, economy, and the environment is proposed to evaluate the various objectives and cases. The results show that the combination of 2% Al2O3 nanofluid and spiral pipe has the optimum performance. The monocrystalline solar panels with the nanofluids-aided heat pump create the least CO2 emissions (550 kg/year), the least LCOE (198.18 $), and the highest exergy efficiency. However, the LCOH (211.78 $/MWh) is still much high. Only when the electricity cost is higher than 0.11$/kWh, the proposed coupling system would show competitiveness. In summary, these results effectively prove the robustness and superiority of the hybrid system.

In order to improve the characteristics of uneven melting in the melting process of the horizontal latent heat energy storage system, the triplex-tube latent heat energy storage unit is taken as the research object, and the flip mechanism is applied to its melting process. Numerical simulation is used for the research, and the numerical model is verified by experimental data. The results show that under different dimensionless times, the melting performance of the unit can be significantly improved by a single flip. When the dimensionless time is 0.4576, it is found that the total melting time of the unit is reduced by 16.17 %, the average heat absorption rate is increased by 14.7 %, but the total heat energy absorption is reduced by 3.85 %. The results show that the addition of a flip can effectively shorten the melting time and increase the heat absorption rate, but it has a negative effect on the total heat absorption in one melting cycle. Moreover, through the comparison of dynamic flow rate, dynamic temperature response, and temperature interval, it is shown that the addition of flip effectively reduces the negative influence of the hard-to-melt zone on the melting performance of the unit during the melting process. The flip mechanism reduces the proportion of high-temperature phase change material in the melting process and makes the melting process more uniform.

Ground source heat pump (GSHP) technology has gained significant attention as a viable solution for the heating, ventilation, and air conditioning (HVAC) of buildings. One of the factors that can impact the performance of GSHP systems is the soil moisture content. In this study, an innovative approach, referred to as soil impedance topology, is introduced as an alternative to traditional methods for measuring soil moisture content in geothermal heat pump systems. This method is inspired by pipeline grid utilizes impedance measurement, which provides a direct measurement of soil moisture content without the need for sensors. The study also proposes a changing rule of impedance with varying moisture content, where capacitance increases and resistance decreases when the soil moisture content is less than 20% but stabilizes beyond a water content of 20%. The accuracy of the topological mechanism prediction method is high, as demonstrated through the verification of the Smith circle and measured data. However, it is noted that the performance may be insufficient in the high frequency band and high soil moisture content. The use of impedance topology provides a more accurate and reliable method for measuring soil moisture content as well as for modeling and predicting heat transfer rates and system performance. This technology has strong potential to improve efficiency, reduce energy costs, and enhance the environmental sustainability of geothermal heat pump systems.

Thermal energy storage (TES) has emerged as a promising solution to enhance nuclear safety by passively removing decay heat during reactor shutdown and accidents, thus preventing overheating of the reactor core and protecting the integrity of containment barriers. The research of TES with different structures has broad application prospects and practical significance. In this study, the melting process of phase change material (PCM) in various TES structures was simulated by the numerical simulation method in two and three dimensions. The mechanism of gravity-driven natural convection enhancing heat transfer was revealed. The effects of different TES structures, fin pitch, fin height, and fin thickness on heat transfer performance were studied. The results showed that many vortices formed by liquid PCM are the main reason for enhancing the natural convection. Adding fins could greatly accelerate the heat storage process. The melting time of PCM in annular and spiral finned tube TES was 47.3% and 61.3% less than that in smooth tube TES, respectively. In the present study, the heat transfer effect was enhanced as the spiral fin pitch became small, the fin height increased and the fin thickness increased. Two opposite effects of fin structure on the natural convection were revealed: (1) positive effect provided by heat transfer enhancement and (2) negative effect produced by blockage.

Drought stress is a critical environmental factor that significantly impacts plant growth and productivity. However, the transcriptome analysis of differentially expressed genes in response to drought stress in Camellia oleifera Abel. is still unclear. This study analyzed the transcriptome sequencing data of C. oleifera under drought treatments. A total of 20,674 differentially expressed genes (DEGs) were identified under drought stress, with the number of DEGs increasing with the duration of drought. Specifically, 11,793 and 18,046 DEGs were detected after 8 and 15 days of drought treatment, respectively, including numerous upregulated and downregulated genes. Gene Ontology (GO) enrichment analysis showed that the DEGs were primarily involved in various biological processes. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that carbon metabolism, glyoxylate and dicarboxylate metabolism, proteasome, glycine, serine, and threonine metabolism were the main affected pathways. Among the DEGs, 376 protein kinases, 42 proteases, 168 transcription factor (TF) genes, and 152 other potential functional genes were identified, which may play significant roles in the drought response of C. oleifera. The expression of relevant functional genes was further validated using quantitative real-time PCR (qRT-PCR). These findings contribute to the comprehension of drought tolerance mechanisms in C. oleifera and bolster the identification of drought-resistant genes for molecular breeding purposes.

Phase-change thermal storage is essential for renewable energy utilization, addressing spatiotemporal energy transfer imbalances. However, enhancing heat transfer in pure phase-change materials (PCMs) has been challenging due to their low thermal conductivity. Rotational actuation, as an active method, improves heat transfer and storage efficiency. This study numerically examined the melting behavior of finned thermal storage units at various rotational speeds. The influence of speed was analyzed via melting time, rate, phase interface, temperature, and flow distribution. Results showed that rotational speed effects were non-monotonic: excessive speeds may hinder complete melting or reduce efficiency. There existed an optimal speed for the fastest melting rate and a limited speed range for complete melting. At the preferred rotation speed of 2.296 rad·s−1, the utilization of PCMs in a finned tube could mitigate the risk of local overheating by 97.2% compared to a static tube, while improving heat storage efficiency by 204.9%.

Over the last several decades, extensive research has been conducted on the baryon cycles within cosmic structures, encompassing a broad mass range from dwarf galaxies to galaxy clusters. However, a notable gap in understanding the cosmic baryon cycle is the poor galaxy groups with halo masses around 10 ^13 M _⊙ . Poor galaxy groups, like our own Local Group, are prevalent throughout the Universe, yet robust detection of their hot, X-ray-emitting intragroup medium (IGrM) has remained elusive. The presence of this hot IGrM is crucial for addressing the long-standing “missing baryons” problem. Previous ROSAT-based studies were limited by a small number of X-ray bright samples, thus restricting the scope of their findings. Here, we show a robust detection of this hot IGrM in a large, optically selected poor groups sample, based on the stacked X-ray images from the eROSITA Final Equatorial Depth Survey. These groups are identified in DESI Legacy Survey with a mass range of log( M _halo / h ^−1 M _⊙ ) = 11.5–13.5 and a redshift range of z = 0.1–0.5. Additionally, our results indicate that despite its presence in virtually groups at all sizes, this gas component is still not sufficient to recover the universal baryon fraction, and hence the “missing baryons” problem still persists in poor galaxy groups.

Double-cone ignition [Zhang et al., Phil. Trans. R. Soc. A 378, 20200015 (2020)] was proposed recently as a novel path for direct-drive inertial confinement fusion using high-power lasers. In this scheme, plasma jets with both high density and high velocity are required for collisions. Here we report preliminary experimental results obtained at the Shenguang-II upgrade laser facility, employing a CHCl shell in a gold cone irradiated with a two-ramp laser pulse. The CHCl shell was pre-compressed by the first laser ramp to a density of 3.75 g/cm3 along the isentropic path. Subsequently, the target was further compressed and accelerated by the second laser ramp in the cone. According to the simulations, the plasma jet reached a density of up to 15 g/cm3, while measurements indicated a velocity of 126.8 ± 17.1 km/s. The good agreements between experimental data and simulations are documented.

In recent years, data has become one of the most important resources in the digital economy. Unlike traditional resources, the digital nature of data makes it difficult to value and contract. Therefore, establishing an efficient and standard data-transaction market system would be beneficial for lowering cost and improving productivity among the parties in this industry. Although numerous studies have been dedicated to the issue of complying with data regulations and other data-transaction issues such as privacy and pricing, little work has been done to provide a comprehensive review of these studies in the fields of machine learning and data science. To provide a complete and up-to-date understanding of this topic, this review covers the three key issues of data transaction: data rights, data pricing, and privacy computing. By connecting these topics, this paper provides a big picture of a data ecosystem in which data is generated by data subjects such as individuals, research agencies, and governments, while data processors acquire data for innovational or operational purposes, and benefits are allocated according to the data’s respective ownership via an appropriate price. With the long-term goal of making artificial intelligence (AI) beneficial to human society, AI algorithms will then be assessed by data protection regulations (i.e., privacy protection regulations) to help build trustworthy AI systems for daily life.

Diesel engines are playing an important role in the transportation system and regardless to their acceptable efficiency (near 40 %), the main problems are the amounts of CO2 and soot production of these engines. In this research, Oxymethylene ether is used as a blend with diesel by a numerical study, and engine performance, fuel economy, and emission analyses have been investigated. The OM355 engine with Euro II emission standard is selected as the base engine and the percentages of Soot, NOx, CO2, flame speed, flame surface density, brake specific fuel consumption, specific power, and specific torque has been studied from 0 to 60% of diesel-OME1 compounds. Overall results of this numerical investigation indicate that OME1 can be a suitable component due to positive effects on the exhaust emissions. Initial estimates show that engine soot and NOx emissions can be reduced more than 80% and CO2 also near to 66% reduced compared to pure paraffinic diesel. In fact, due to a lower combustion temperature of OME1, soot and NOx emissions would barely produce due to their formation limit temperature, hence the engine operates much cleaner. The main disadvantage of this synthetic fuel is the low amount of heating value and lower cetane number in comparison to diesel, which in turn leads to a performance loss and a higher amount of fuel consumption for producing a specific amount of power and torque output.

Latent heat thermal storage (LHTS) system is vital to reduce environment pollution. In the shell-and-tube heat accumulator, the position of the inner heating tube plays a vital role in the thermal storage. To analyze the effect of the inner tube position on the phase transition, a two-dimensional numerical model is developed. The structure has the minimum full melting time of 3480 s when the inner tube is 12 mm (L = 12 mm) from the center. Compared with L = 0 mm, the full melting time at L = 12 mm can be reduced by 13.4%.

Abstract The present investigation is carried out to predict the flow characteristics of a micropolar liquid that is infused with ternary nanoparticles across a stretching/shrinking surface under the impact of chemical reactions and radiation. Here, three dissimilarly shaped nanoparticles (copper oxide, graphene and copper nanotubes) are suspended in H2O to analyse the characteristics of flow, heat and mass transfer. The flow is analysed using the inverse Darcy model, while the thermal analysis is based on the thermal radiation. Furthermore, the mass transfer is examined in light of the impact of first order chemically reactive species. The considered flow problem is modelled resulting with the governing equations. These governing equations are highly non linear partial differential equations. Adopting suitable similarity transformations partial differential equations are reduced to ordinary differential equations. The thermal and mass transfer analysis comprises two cases: PST/PSC and PHF/PMF. The analytical solution for energy and mass characteristics is extracted in terms of an incomplete gamma function. The characteristics of a micropolar liquid are analysed for various parameters and presented through graphs. The impact of skin friction is also considered in this analysis. The stretching and rate of mass transfer have a large influence on the microstructure of a product manufactured in the industries. The analytical results produced in the current study seem to be helpful in the polymer industry for manufacturing stretched plastic sheets.

The impact of the enhanced heat transfer performance of longitudinal fins on the entire process of melting and solidification in a phase change heat storage unit is investigated through experiments and numerical simulations in this paper. The position and structure of the longitudinal fins are optimized by using the response surface method while ensuring that the total volume of the heat storage medium remains unchanged. Studies have identified that some challenging zones in melting and solidification significantly impact the heat transfer of the entire heat storage cycle. Specifically, the challenging zone in melting primarily exists in the lower part of the unit during the charing process, while the challenging zone in solidification is mainly distributed around the unit during the discharging process. Through optimization, the optimized structure (fin spacing is 22.5 mm, fin width is 6.05 mm) can reduce the charging and discharging time by 16.94 % and 45.90 %, respectively. Additionally, the round trip time is significantly reduced by 39.19 %, and the mean heat absorption rate during the melting process is enhanced by 20.28 %. Moreover, the mean heat release rate during solidification is enhanced by 80.23 %.

The operation of a diesel engine leads to the emission of a substantial amount of waste heat flue gas, resulting in a continuous increase in the wall temperature of the exhaust system. To mitigate this continuous rise in temperature, a pre-swirling device has been developed to enhance the heat exchange between cold air and the wall, thus averting heating wall by the hot air. In this study, an experimental system was devised and implemented to analyze the dynamic behavior of the wall temperature in an air duct. The system considered both with and without the pre-swirling device, incorporating different cold air temperatures and flow rates to examine its impact on the increase in wall temperature. The results revealed a gradual rise in wall temperature after reaching a steady state, particularly demonstrating lower wall temperatures at 19 measurement points in the presence of pre-swirl compared to without swirl. Notably, the maximum temperature rise in the air duct wall was reduced by 55.7 %, from 7.9 °C without pre-swirl to 3.5 °C with the inclusion of the pre-swirling device, highlighting the significant thermal protection it provides and suggesting potential applications in exhaust thermal protection engineering. Moreover, the experimental findings consistently indicate that the incorporation of a pre-swirling device effectively diminishes the increase in wall temperature across different cold air flow rates and temperatures.

Thermochemical heat transformers (THT) can offer the potential for efficient energy storage and upgrade based on a reversible solid-gas reaction. A mechanical booster pump (MBP)-assisted water-based sorption thermochemical heat transformer driven by low-grade solar thermal energy is proposed to handle variations in the heat demand of buildings. The MBP operates during the discharging process to adjust the magnitudes of temperature lift by compression ratio depending on the user’s demands. The performances of the proposed cycle employing three different reactive salts are investigated and compared with the conventional THT cycle under various operating conditions. Results indicate that compared to the conventional THT cycle, the proposed cycle achieves a maximum temperature lift of 15–17°C, 17–19°C, and 23–26°C for SrBr2, LiOH, and CaCl2 in the evaporating temperature range of 20–40°C, respectively. In the same operating conditions, SrBr2 demonstrates the highest energy and exergy efficiencies, while CaCl2 is inferior to the others due to its greater sensible heat consumption and lower reaction heat under the studied conditions. A suggestion is put forth for enhancing the temperature lift by employing a two-stage MBP-assisted cycle that utilizes the reactive salt SrBr2. Compared to the single-stage MBP-assisted cycle, the heat output temperature can be further increased by up to 3–16°C at the expense of a maximum decrease of 6.6%, 84.4%, and 9.0% in coefficient of performance (COP) based on total energy input, COP based on electricity input, and exergy efficiency, respectively, at 30°C evaporating temperature. The economic and environmental analysis indicates that the proposed system is economically and environmentally feasible and could be a promising alternative to residential water heaters.

The energy usage of parallel chillers systems accounts for 25–40 % of the total energy cost of a building. In light of global warming concerns and the need for energy conservation, it is essential to distribute the load of the parallel chillers systems effectively to achieve energy savings in buildings. Accordingly, this study presents a multi-strategy improved sparrow search algorithm (MSSA) to address optimization of the optimal chillers loading (OCL) problem. The proposed algorithm augments the basic sparrow search algorithm (SSA) by introducing the Sine chaotic map, Levy flight method, and Cauchy variation to enhance diversity, avoid local optima, and increase global and local search capacities. We use 9 benchmark functions to check the performance of the proposed MSSA algorithm, and the results are better than the selected algorithms such as particle swarm algorithm (PSO), harris hawks optimization (HHO), artificial rabbit optimization (ARO) and sparrow search algorithm (SSA). In addition, MSSA is applied to two typical cases to demonstrate its performance to optimal chillers loading and the results indicate that the MSSA outperforms similar algorithms. This study validates that MSSA can provide a promising solution to resolve the OCL problem.

Due to the intermittency and discontinuity of solar energy, thermal energy storage (TES) using phase change materials (PCMs) is generally required to ensure stable operation in solar heating systems (SHS) during winter. This paper presents the design of a TES unit with different horizontal metal foam filling ratios (60%–100%), and simulations of thermal characteristics, such as complete melting time and heat storage capacity by numerical method. Based on the heating demands of an office building in Xi'an, TES units are combined in parallel and economic indexes are calculated based on static evaluation method, including initial investment and investment payback period. Novelty, the contribution of gradient microstructure to the phase transition process is evaluated from thermophysical properties and economy. Results show that the TES unit with a filling ratio of 90% possesses the shortest complete melting time of 5310 s, which is 87.56% shorter than that of a TES unit with pure PCM. Finally, economic assessments of the engineering application of the partially filled metal foam structure are carried out, and it is determined that the SHS with the TES system of 90% filling ratio requires the least number of 548 TES units, with a payback period of three heating seasons.

Buildings play a crucial role in global electricity consumption, but their function is evolving. Rather than merely consuming energy, buildings have the potential to become energy producers through participating in flexibility services, which involve demand response and distributed energy supplies. However, the new technological and societal challenges that arise from temporal and spatial changes on both supply and demand sides make building services increasingly complex. This paper presents an opportunity for flexibility services offered by building energy systems via power-to-heat technology and discusses four key aspects: quantitative indicators based on thermal inertia, model predictive control for building flexibility, flexible system optimization for smart buildings, and applications of flexible services. Thermal inertia is a crucial factor that transcends technical constraints and serves as a bridge between the demand and supply sides. Demand-side response and data-driven cogeneration under model predictive control are essential for managing building flexibility. In addition, flexible system optimization is achieved through the combination of demand-side trading and disturbed system optimization. Applications of flexible services represent a combination of demand-side trading and disturbed system optimization in the fields of engineering and sociology. Finally, the paper explores the challenges, as well as the potential and models of building flexibility services technologies, including features that can facilitate automated operational decision-making on both the demand and supply sides.

Chinese Space Station Telescope (CSST) has the capability to conduct a slitless spectroscopic survey simultaneously with a photometric survey. The spectroscopic survey will measure slitless spectra, potentially providing more accurate estimations of galaxy properties, particularly redshifts, compared to using broadband photometry. CSST relies on these accurate redshifts to use baryon acoustic oscillations (BAOs) and other probes to constrain the cosmological parameters. However, due to the low resolution and signal-to-noise ratio of slitless spectra, measurement of redshifts is significantly challenging. In this study, we employ a Bayesian neural network (BNN) to assess the accuracy of redshift estimations from slitless spectra anticipated to be observed by CSST. The simulation of slitless spectra is based on real observational data from the early data release of the Dark Energy Spectroscopic Instrument (DESI-EDR) and the 16th data release of the Baryon Oscillation Spectroscopic Survey (BOSS-DR16), combined with the 9th data release of the DESI Legacy Survey (DESI LS DR9). The BNN is constructed employing a transfer learning technique, by appending two Bayesian layers after a convolutional neural network, leveraging the features learned from the slitless spectra and corresponding redshifts. Our network can provide redshift estimates along with corresponding uncertainties, achieving an accuracy of σ _NMAD = 0.00063, outlier percentage η = 0.92%, and weighted mean uncertainty $\overline{E}=0.00228$ . These results successfully fulfill the requirement of σ _NMAD < 0.005 for BAO and other studies employing CSST slitless spectroscopic surveys.

The effect of an external magnetic field on the evolution of the self-generated electromagnetic field during laser ablation is investigated by using the Vlasov–Fokker–Planck simulations. It is found that the self-generated field is rotated and distorted under an external magnetic field, and for highly magnetized plasma, the rotation of the electric field becomes stable after the laser ablation. The theoretical analysis indicates that the rotation and tortuosity are primarily attributed to the advection of the Nernst effect and the Righi–Leduc (RL) flux. The curl of the self-generated field increases with the Hall parameter $\chi_\mathrm{e}$ and reaches a peak at $\chi_\mathrm{e} = 0.075$ , then it decreases with the $\chi_\mathrm{e}$ continuous increase. As the Hall parameter increases, the RL flux contributes more than 60% to the rotation of the electric field. Furthermore, the distortion of the electric field continues to rotate after the laser ablation due to the cross-gradient Nernst transport. These findings provide theoretical references for the evolution of the self-generated electromagnetic field in laser-driven magnetized plasmas.

Observations of gravitational waves (GW) provide us with a new probe to study the Universe. GW events can be used as standard sirens if their redshifts are measured. Normally, standard sirens can be divided into bright/dark sirens according to whether the redshifts are measured by electromagnetic (EM) counterpart observations. First, we investigate the capability of the 2.5 m Wide-Field Survey Telescope (WFST) to take follow-up observations of kilonova counterparts. For binary neutron star (BNS) bright sirens, WFST is expected to observe 10–20 kilonovae per year in the second-generation GW detection era. As for neutron star–black hole (NSBH) mergers, when a BH spin is extremely high and the neutron star (NS) is stiff, the observation rate is ∼10 per year. Combining optical and GW observations, the bright sirens are expected to constrain the Hubble constant H _0 to ∼2.8% in five years of observations. As for dark sirens, the tidal effects of NSs during merging provide us with a cosmological model-independent approach to measure the redshifts of GW sources. Then we investigate the applications of tidal effects in redshift measurements. We find in the third generation era, the host galaxy groups of around 45% BNS mergers at z < 0.1 can be identified through this method, if the equation of state is ms1, which is roughly equivalent to the results from luminosity distant constraints. Therefore, tidal effect observations provide a reliable and cosmological model-independent method of identifying BNS mergers’ host galaxy groups. Using this method, the BNS/NSBH dark sirens can constrain H _0 to 0.2%/0.3% over a five-year observation period.

The two-point correlation function (2PCF) is a powerful statistical tool to measure galaxy clustering. Although 2PCF has also been used to study the clustering of stars on subparsec to kiloparsec scales, its physical implication is not clear. In this study, we use the Illustris-TNG50 simulation to study the connection between the 2PCF of accreted halo stars and the assembly histories of Milky Way-mass galaxies. We find, in general, that the 2PCF signal increases with the increase in galactocentric radii, r , and with the decrease in the pair separations. Galaxies that assemble late on average have stronger 2PCF signals. With z _1/4 , z _1/2 , and z _3/4 defined as the redshifts when galaxies accreted one-fourth, half, and three-fourths of their ex situ stellar mass today, we find they all show the strongest correlations with the 2PCF signals at r < ∼ 0.2 R _200 . z _3/4 shows the strongest correlations than those of z _1/4 or z _1/2 . However, the correlations have large scatters. The 2PCFs in the velocity space show weaker correlations with the galaxy formation times within ∼0.35 R _200 than real-space 2PCFs, and the scatter is considerably large. Both the real- and velocity-space 2PCFs correlate with the assembly histories of the host dark matter halos as well. Within 0.3 R _200 , the real-space 2PCF shows stronger correlations with the galaxy formation histories than with the halo formation histories. We conclude that it is difficult to use 2PCF alone to precisely predict the formation times or assembly histories of galaxies.

We report a ∼5.2 σ detection of the kinetic Sunyaev–Zel’dovich (kSZ) effect in Fourier space, by combining the DESI galaxy groups and the Planck data. We use the density-weighted pairwise kSZ power spectrum as the summary statistic, and the detailed procedure of its measurement is presented in this paper. Meanwhile, we analyze the redshift space group density power spectrum to constrain its bias parameters and photo- z uncertainties. These best-fitted parameters are substituted to a nonlinear kSZ model, and we fit the measured kSZ power spectrum with this model to constrain the group optical depth $\bar{\tau }$ . Selected by a varying lower mass threshold M _th , the galaxy group catalogs with different median masses ( $\tilde{M}$ ) are constructed from the Data Release 9 data of the DESI Legacy Imaging Surveys. $\tilde{M}$ spans a wide range of ∼10 ^13 –10 ^14 M _⊙ / h and the heaviest $\tilde{M}\sim {10}^{14}\ {M}_{\odot }/h$ is larger than those of most other kSZ detections. When the aperture photometric filter radius θ _AP is set to be 4.′2, the $\tilde{M}=1.75\times {10}^{13}\ {M}_{\odot }/h$ group sample at the median redshift $\tilde{z}=0.64$ has the highest kSZ detection signal-to-noise ratio = 5.2. By fitting $\bar{\tau }{\rm{s}}$ from various samples against their $\tilde{M}$ s, we obtain a linear $\mathrm{log}\bar{\tau }-\mathrm{log}\tilde{M}$ relation: $\mathrm{log}\bar{\tau }=\gamma (\mathrm{log}\tilde{M}-14)+\mathrm{log}\beta $ , in which γ = 0.55 ± 0.1. We also vary the aperture photometric filter radius and measure the $\bar{\tau }$ profiles of group samples, whose constraints on the baryon distribution within and around dark matter halos will be discussed in a companion paper.

We conducted an investigation of the Coma cluster of galaxies by running a series of constrained hydrodynamic simulations with GIZMO-SIMBA and GADGET-3 based on initial conditions reconstructed from the SDSS survey volume in the ELUCID project. We compared simulation predictions and observations for galaxies, intracluster medium (ICM) and intergalactic medium (IGM) in and around the Coma cluster to constrain galaxy formation physics. Our results demonstrate that this type of constrained investigation allows us to probe in more detail the implemented physical processes, because the comparison between simulations and observations is free of cosmic variance and hence can be conducted in a “one-to-one” manner. We found that an increase in the earlier star formation rate and the supernova feedback of the original GIZMO-SIMBA model is needed to match observational data on stellar, interstellar medium, and ICM metallicity. The simulations without active galactic nucleus (AGN) feedback can well reproduce the observational ICM electron density, temperature, and entropy profiles, ICM substructures, and the IGM temperature–density relation, while the ones with AGN feedback usually fail. However, one requires something like AGN feedback to reproduce a sufficiently large population of quiescent galaxies, particularly in low-density regions. The constrained simulations of the Coma cluster thus provide a test bed to understand processes that drive galaxy formation and evolution.

In this paper, we introduce a U-Net model of deep learning algorithms for reconstructions of the 3D peculiar velocity field, which simplifies the reconstruction process with enhanced precision. We test the adaptability of the U-Net model with simulation data under more realistic conditions, including the redshift space distortion effect and halo mass threshold. Our results show that the U-Net model outperforms the analytical method that runs under ideal conditions, with a 16% improvement in precision, 13% in residuals, 18% in correlation coefficient, and 27% in average coherence. The deep learning algorithm exhibits exceptional capacities to capture velocity features in nonlinear regions and substantially improve reconstruction precision in boundary regions. We then apply the U-Net model trained under Sloan Digital Sky Survey (SDSS) observational conditions to the SDSS Data Release 7 data for observational 3D peculiar velocity reconstructions.

In this investigation, we leverage the combination of the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 9, Survey Validation 3, and Year 1 data sets to estimate the conditional luminosity functions and conditional stellar mass functions (CLFs and CSMFs) of galaxies across various halo mass bins and redshift ranges. To support our analysis, we utilize a realistic DESI mock galaxy redshift survey (MGRS) generated from a high-resolution Jiutian simulation. An extended halo-based group finder is applied to both MGRS catalogs and DESI observation. By comparing the r - and z -band luminosity functions (LFs) and stellar mass functions (SMFs) derived using both photometric and spectroscopic data, we quantified the impact of photometric redshift (photo- z ) errors on the galaxy LFs and SMFs, especially in the low-redshift bin at the low-luminosity/mass end. By conducting prior evaluations of the group finder using MGRS, we successfully obtain a set of CLF and CSMF measurements from observational data. We find that at low redshift, the faint-end slopes of CLFs and CSMFs below ∼10 ^9 h ^−2 L _⊙ (or h ^−2 M _⊙ ) evince a compelling concordance with the subhalo mass functions. After correcting the cosmic variance effect of our local Universe following Chen et al., the faint-end slopes of the LFs/SMFs turn out to also be in good agreement with the slope of the halo mass function.

The properties of the galaxies are tightly connected to their host halo mass and halo assembly history. Accurate measurement of the halo assembly history in observation is challenging but crucial to the understanding of galaxy formation and evolution. The stellar-to-halo mass ratio ( M _* / M _h ) for the centrals has often been used to indicate the halo assembly time t _h,50 of the group, where t _h,50 is the lookback time at which a halo has assembled half of its present-day virial mass. Using mock data from the semi-analytic models, we find that M _* / M _h shows a significant scatter with t _h,50 , with a strong systematic difference between the group with a star-forming central (blue group) and passive central (red group). To improve the accuracy, we develop machine learning models to estimate t _h,50 for galaxy groups using only observable quantities in the mocks. Since star formation quenching will decouple the co-growth of the dark matter and baryon, we train our models separately for blue and red groups. Our models have successfully recovered t _h,50 , within an accuracy of ∼1.09 Gyr. With careful calibrations of individual observable quantities in the mocks with Sloan Digital Sky Survey (SDSS) observations, we apply the trained models to the SDSS Yang et al. groups and derive the t _h,50 for each group for the first time. The derived SDSS t _h,50 distributions are in good agreement with that in the mocks, in particular for blue groups. The derived halo assembly history, together with the halo mass, make an important step forward in studying the halo–galaxy connections in observation.

We adopt the two-point correlation function (2PCF) as a statistical tool to quantify the spatial clustering of halo stars for galaxy systems spanning a wide range in host halo virial mass ( $11.25\lt {\mathrm{log}}_{10}{M}_{200c}/{M}_{\odot }\lt 15$ ) and redshifts (0 < z < 1.5) from the IllustrisTNG simulations. Consistent with a previous study, we identify clear correlations between the strength of the 2PCF signals and galaxy formation redshifts, but over a much wider mass range. We find that such correlations are slightly stronger at higher redshifts and get weakened with the increase of host halo mass. We demonstrate that the spatial clustering of halo stars is affected by two factors: (1) the clustering gets gradually weakened as time passes (phase mixing); (2) newly accreted stars at more recent times would increase the clustering. For more massive galaxy systems, they assemble late, and the newly accreted stars would increase the clustering. The late assembly of massive systems may also help to explain the weaker correlations between the 2PCF signals and the galaxy formation redshifts in massive halos, as their 2PCFs are affected more by recently accreted stars, while formation redshift characterizes mass accretion on a much longer timescale. We find that the orbits of satellite galaxies in more massive halos maintain larger radial anisotropy, reflecting the more active accretion state of their hosts while also contributing to their stronger mass loss rates.

This study is based on heat transfer and a two-dimensional MHD Walters’ liquid B flow containing copper nanoparticles driven by a stretching sheet in a porous medium. Mass transpiration and thermal radiation effects are considered. The set of partial differential equations affected by the Marangoni boundary condition is used. A nonlinear system of equations is solved to obtain the coupled ordinary differential equations using the similarity transformations and Laplace transform technique. An exact solution is obtained for the transformed system. In the analysis, it is noted that the inclusion of smaller copper nanoparticles provides superior thermal conductivity with temperature. The velocity and temperature distributions are analysed for radiation number, Prandtl number, magnetic parameter, viscoelastic parameter and permeability parameter. Results revealed that heat transfer rate was improved by the coupled effect of enhanced conductivity and thermal radiation. Thermal performance judgements by radiation provide design guidance in thermal engineering applications.

IntroductionGlobal climate change can affect the sensitivity of tree radial growth to climate factors, but the specific responses of tree radial growth to microclimate along the altitudinal gradient in the long term are still unclear.MethodsIn this study, the tree-ring width chronologies of Pinus tabuliformis Carr. in Shanxi Province of China were studied at three altitude gradients (1200-1300 m (low altitude), 1300-1400 m (medium altitude) and 1400-1500 m (high altitude)) during 1958-2017.ResultsThe results showed that (1) the climate background could be divided into two periods based on the Mann-Kendall test analysis: 1958–1996 was a stable period (mean annual temperature (MAT)=10.25°C, mean annual precipitation (MAP)=614.39 mm), and 1997–2017 was a rapid change period (MAT=10.91°C, MAP=564.70 mm), indicating a warming and drying trend in the study region. (2) The radial growth of P. tabuliformis at different altitudes showed inconsistent variation patterns. The tree radial growth at low and medium altitudes (CV=27.01% for low altitude and CV=24.69% for medium altitude) showed larger variation amplitudes during the rapid change period than that in the stable period (CV=12.40% for low altitude and CV=18.42% for medium altitude). In contrast to the increasing trend, the tree radial growth rates at the high altitude showed a decreasing trend across years. (3) In the stable period, the radial growth of P. tabuliformis at the low altitude showed a significantly negative response to temperature and a positive response to precipitation in May and June. The tree radial growth at the medium altitude was positively related to precipitation in June and minimum temperature in February. The tree growth at the high altitude was mainly positively correlated with the temperature in May and August. In the rapid change period, the radial growth of P. tabuliformis at the low altitude was affected by more meteorological factors than that in the stable period. Medium-altitude trees were positively influenced by precipitation in June and minimum temperature in January, whereas high-altitude trees responded positively to wind speed in February. (4) Along altitudinal gradients, tree radial growth was more related to temperature than precipitation in the stable period. The tree radial growth at the high altitude during the rapid change period was only affected by wind speed in February, whereas the tree radial growth at low and medium altitudes was mainly affected by temperature to a similar extent during the two periods.DiscussionThe study indicated that tree growth-climate response models could help deeply understand the impact of climate change on tree growth adaptation and would be beneficial for developing sustainable management policies for forest ecosystems in the transition zone from warm-temperate to subtropical climates.

Since the energy sector is the dominant contributor to global greenhouse gas emissions, the decarbonization of energy systems is crucial for climate change mitigation. Two major challenges of energy systems decarbonization are renewable transition planning and sustainable systems operations. To address the challenges, incorporating emerging information and communication technologies can facilitate both the design and operations of future smart energy systems with high penetrations of renewable energy and decentralized structures. The present work provides a comprehensive overview of the applicability of emerging information and communication technologies in renewable transition and smart energy systems, including artificial intelligence, quantum computing, blockchain, next-generation communication technologies, and the metaverse. Relevant research directions are introduced through reviewing existing literature. This review concludes with a discussion of the industrial use cases and demonstrations of smart energy technologies.

Global climate change imposes significant challenges on the ecological environment and human sustainability. Industrial parks, in line with the national climate change mitigation strategy, are key targets for low-carbon revolution within the industrial sector. To predict the carbon emission of industrial parks and formulate the strategic path of emission reduction, this paper amalgamates the benefits of the “top-down” and “bottom-up” prediction methodologies, incorporating the logarithmic mean divisia index (LMDI) decomposition method and long-range energy alternatives planning (LEAP) model, and integrates the Tapio decoupling theory to predict the carbon emissions of an industrial park cluster of an economic development zone in Yancheng from 2020 to 2035 under baseline (BAS) and low-carbon scenarios (LC1, LC2, and LC3). The findings suggest that, in comparison to the BAS scenario, the carbon emissions in the LC1, LC2, and LC3 scenarios decreased by 30.4%, 38.4%, and 46.2%, respectively, with LC3 being the most suitable pathway for the park’s development. Finally, the paper explores carbon emission sources, and analyzes emission reduction potential and optimization measures of the energy structure, thus providing a reference for the formulation of emission reduction strategies for industrial parks.

Biogas heating plays a crucial role in the transition to clean energy and the mitigation of agricultural pollution. To address the issue of low biogas production during winter, the implementation of a multi-energy complementary system has become essential for ensuring heating stability. To guarantee the economy, stability, and energy-saving operation of the heating system, this study proposes coupling biogas and solar energy with a phase-change energy-storage heating system. The mathematical model of the heating system was developed, taking an office building in Xilin Hot, Inner Mongolia (43.96000° N, 116.03000° E) as a case study. Additionally, the Sparrow Search Algorithm (SSA) was employed to determine equipment selection and optimize the dynamic operation strategy, considering the minimum cost and the balance between the supply and demand of the building load. The operating economy was evaluated using metrics such as payback period, load ratio, and daily rate of return. The results demonstrate that the multi-energy complementary heating system, with a balanced supply and demand, yields significant economic benefits compared to the central heating system, with a payback period of 4.15 years and a daily return rate of 32.97% under the most unfavorable working conditions. Moreover, the development of a daily optimization strategy holds practical engineering significance, and the optimal scheduling of the multi-energy complementary system, with a balance of supply and demand, is realized.

Despite the important role of the genre awareness in facilitating the effective communication in the global business context and the need to teach and practice writing for various social purposes, there was scant classroom-based research on effects of providing peer feedback on EFL learners’ genre awareness in business writing for fulfilling the particular communicative purpose. This study examined whether student reviewers could improve their genre awareness in business letter writing by providing peer feedback to other students’ writings at varying levels. Sixty business English majors, taking the business writing course for 1 year under the tutelage of the same instructor, participated in the current study. They were randomly assigned to the experimental group who reviewed the students’ drafts at different levels (high, medium and low) and gave written comments and the control group who received no treatment but did self-revision. Both groups followed the genre-specific evaluation criteria during peer feedback and self-revision. Repeated-measures ANOVA on the two groups’ writing performances at different timepoints (pretest, immediate posttest, transfer posttest and delayed transfer posttest) demonstrated that the participants in the experimental group had better performance than those in the control group at the transfer posttest as well as the delayed transfer posttest. Moreover, providing weakness comments on both the low-quality and the medium-quality drafts had significant effects on their own writing quality at the subsequent tests, whereas providing strength feedback on the high-quality drafts had statistically significant impacts on their own writing quality at the immediate posttest and the delayed transfer posttest. However, multiple linear regression analyses demonstrated that only offering weakness comments to the medium-quality drafts could effectively predict the reviewers’ overall writing quality in the immediate posttest, the transfer posttest, and the delayed transfer posttest. Tentative research and pedagogical implications of the findings were discussed.

Solar energy is a sustainable source that can be effectively utilized to address winter heating challenges in buildings. To ensure the efficient application of solar energy for heating purposes and to maintain reliable performance of the heating system, the integration of phase-change materials (PCMs) in thermal energy storage (TES) systems has emerged as a crucial auxiliary approach. This study focuses on the design and simulation of four TES structures: smooth, finned, metallic foam, and metallic foam-finned tubes. It explores their thermal characteristics, such as complete melting time and heat flux, under various flow conditions. Additionally, a residential building in Xi’an is selected as the object, where the proposed solar energy phase-change TES system is employed to meet the heating demand. Economic indicators, including initial investment and investment payback period, are estimated using a static evaluation method. The results highlight that the complete melting time of the TES unit with a metallic foam-finned tube is 4800 s, which is 88.3% less than the smooth tube. Finally, based on the actual project, it is determined that the metallic foam-finned heating system, with an HTF flow rate of 0.25 m/s, requires the fewest TES devices (914) and has a payback period of 13 months.

Stomach adenocarcinoma (STAD) is one of the most common malignant tumors of the digestive tract, and its survival predictors are critical for precision medicine but have not been fully investigated. The complement system is a complex multistep cascade at the interface of innate and adaptive immunity, which augments the function of antibodies and phagocytes. This study aimed to construct and validate a CSRG signature based on TCGA (The Cancer Genome Atlas) STAD dataset and revalidated it in an external GEO (Gene Expression Omnibus) STAD cohort. Subsequently, we assessed the association of risk levels with the stromal and immune cell infiltration level in STAD using the ESTIMATE, single-sample Gene Set Enrichment Analysis (ssGSEA), and Microenvironment Cell Populations-counter (MCP-counter) algorithm. It was found that the CSRG signature, based on three genes (SERPINE1, PROC, and CFHR3), was significantly and independently associated with the OS in TCGA STAD patients (p < 0.001). Subsequently, we found that the high-risk STAD harbors more immune cell infiltration than the low-risk group, and the ESTIMATE results indicated that there exists a more stromal component in the tumor microenvironment of the high-risk groups. Compared to the low-risk group, the high-risk STAD patients had higher expressions of marker genes for immune checkpoint inhibitors (ICIs) and showed higher sensitivity to the chemotherapy agents (rapamycin, nilotinib, 5-fluorouracil, axitinib, DMOG, and JNK inhibitor VIII). The prognostic value of the CSRGs was further validated by nomogram plots, which revealed that it was superior to tumor TNM and pathologic stage. Finally, the three expression levels were evaluated in GES-1, HGC27, and AGS cells by qRT-PCR.

Abstract Imbalance of macrophage polarization plays an indispensable role in acute lung injury (ALI), which is considered as a promising target. Matrix metalloproteinase-9 (MMP-9) is expressed in the macrophage, and has a pivotal role in secreting inflammatory cytokines. We reported that saquinavir (SQV), a first-generation human immunodeficiency virus-protease inhibitor, restricted exaggerated inflammatory response. However, whether MMP-9 could regulate macrophage polarization and inhibit by SQV is still unknown. We focused on the important role of macrophage polarization in CLP (cecal ligation puncture)-mediated ALI and determined the ability of SQV to maintain M2 over M1 phenotype partially through the inhibition of MMP-9. We also performed a limited clinical study to determine if MMP-9 is a biomarker of sepsis. Lipopolysaccharide (LPS) increased MMP-9 expression and recombinant MMP-9 (rMMP-9) exacerbated LPS-mediated M1 switching. Small interfering RNA to MMP-9 inhibited LPS-mediated M1 phenotype and SQV inhibition of this switching was reversed with rMMP-9, suggesting an important role for MMP-9 in mediating LPS-induced M1 phenotype. MMP-9 messenger RNA levels in peripheral blood mononuclear cells of these 14 patients correlated with their clinical assessment. There was a significant dose-dependent decrease in mortality and ALI after CLP with SQV. SQV significantly inhibited LPS-mediated M1 phenotype and increased M2 phenotype in cultured RAW 264.7 and primary murine bone marrow-derived macrophages as well as lung macrophages from CLP-treated mice. This study supports an important role for MMP-9 in macrophage phenotypic switching and suggests that SQV-mediated inhibition of MMP-9 may be involved in suppressing ALI during systemic sepsis.

The energy management strategy of hybrid electric vehicles is of significant importance to improve the fuel economy. In this regard, two energy management strategies are designed for power-split hybrid electric city bus (HECB), which are based on the linear time-varying stochastic model predictive control (LTV-SMPC) and stochastic model predictive control based on Pontriagin’s minimum principle (PMP-SMPC). In the present study, the Markov chain and long short-term memory (LSTM) forecast demand torque and velocity respectively are applied to establish a combination forecast model. Then several processes, including linear approximation, processing simplified control model, the proposed nonlinear vehicle model is converted into a linear time-varying model. Meanwhile, the energy management problem in a linear quadratic programming problem is solved. Considering linearization error and limitations of the quadratic optimization, Pontriagin’s minimum principle (PMP) is applied to optimize the nonlinear model predictive control. Based on the reference theory, the range of coordinated variables is derived, and the optimal coordination variable is searched by dichotomy to realize the rolling optimization of the model predictive control (MPC). Finally, the effectiveness of the proposed energy management strategy is verified by simulating several case studies. Obtained results show that compared with the rule-based (RB) control strategy, the fuel economy of LTV-SMPC and PMP-SMPC increases by 8.79% and 14.42%, respectively. Meanwhile, it is concluded that the two strategies have real-time computing potential.

At present, solar remote sensing instruments face problems regarding the short detection time for solar activity and the need to preheat the electronics before detection. The accurate orbit prediction function ensures that the maximum error of the payload electronics system preheating time is less than 8 s, enabling the electronics to obtain stable and reliable solar remote sensing data, and allowing the prediction function to adapt to the changes in preheating time and the limit position of turntable rotation. To achieve the complete detection of solar activity by a payload in orbit, a turntable with two directions of rotation was accurately controlled to achieve rapid capture and track the Sun’s activity, and the delay time for tracking the Sun successfully was less than 8 s to ensure that the payload made full use of the solar detection time for full detection. The turntable’s tracking error was less than 0.002°, allowing the payload to obtain high-precision solar remote sensing data in orbit. The above methods enable the payload to realize the complete, stable, and high-precision detection of solar activity in orbit for wavelengths ranging approximately from 165 nm to 2400 nm.

Reliability is the most critical characteristic of space missions, for example in capturing and tracking moving targets. To this end, two methods are designed to track sunlight using solar remote-sensing instruments (SRSIs). The primary method is to use the offset angles of the guide mirror for closed-loop tracking, while the alternative method is to use the sunlight angles, calculated from the satellite attitude, solar vector, and mechanical installation correction parameters, for open-loop tracking. By comprehensively analyzing the error and rectifying the calibration of the solar tracking system, we demonstrate that the absolute value of the azimuth tracking precision is less than 0.0121° and the pitch is less than 0.0037° with the primary method. Correspondingly, they are 0.0992° and 0.0960° with the alternative method. These precisions meet the requirements of SRSIs. In addition, recalibration due to mechanical vibration during the satellite’s launch may invalidate the above methods, leading to the failure of SRSIs. Hence, we propose a dedicated injection parameter strategy to rectify the sunlight angles to capture and track the sunlight successfully. The stable and effective results in the ultraviolet to near-infrared spectrum validate the SRSI’s high-precision sunlight tracking performance. Furthermore, the above methods can also be applied to all orbital inclinations and may provide a solution for capturing and tracking moving targets.

We carry out a thermal energy census of hot baryons at z < 1, by cross correlating the Planck Modified Internal Linear Combination Algorithm (MILCA) y map with 0.8 million clusters/groups selected from the Yang et al. catalog. The thermal Sunyaev–Zel’dovich effect around these clusters/groups is reliably obtained, which enables us to make our model constraints based on one-halo (1h) and two-halo (2h) contributions, respectively. (1) The total measurement signal-to-noise (S/N) of the one-halo term is 63. We constrain the Y – M relation over the halo mass range of 10 ^13 –10 ^15 M _⊙ h ^−1 , and find Y ∝ M ^α with α = 1.8 at z = 0.14 ( α = 2.1 at z = 0.75). The total thermal energy of gas bound to clusters/groups increases from 0.1 meV cm ^−3 at z = 0.14 to 0.22 meV cm ^−3 at z = 0.75. (2) The 2h term is used to constrain the bias-weighted electron pressure 〈 b _y P _e 〉. We find that 〈 b _y P _e 〉 (in units of meV cm ^−3 ) increases from 0.24 ± 0.02 at z = 0.14 to 0.45 ± 0.02 at z = 0.75. These results lead to several implications. (i) The hot gas fraction f _gas in clusters/groups monotonically increase with the halo mass, where f _gas of a 10 ^14 M _⊙ h ^−1 halo is ∼50% (25%) of the cosmic mean at z = 0.14 (0.75). (ii) By comparing the 1h and 2h terms, we obtain a tentative constraint on the thermal energy of unbound gas. (iii) The above results lead to significant suppression of the matter and weak-lensing power spectrum at small scales. These implications are important for astrophysics and cosmology, and we will further investigate them with improved data and gas modeling.

The assembly of galaxies over cosmic time is tightly connected to the assembly of their host dark matter halos. We investigate the stellar mass growth history and the chemical enrichment history of central galaxies in the Sloan Digital Sky Survey Mapping Nearby Galaxies at Apache Point Observatory. We find that the derived stellar metallicity of passive central galaxies is always higher than that of the star-forming ones. This stellar metallicity enhancement becomes progressively larger toward low-mass galaxies (at a given epoch) and earlier epochs (at a given stellar mass), which suggests strangulation as the primary mechanism for star formation quenching in central galaxies not only in the local Universe but also very likely at higher redshifts up to z ∼ 3. We show that at the same present-day stellar mass, passive central galaxies assembled half of their final stellar mass ∼2 Gyr earlier than star-forming central galaxies, which agrees well with the semi-analytic model. Exploring the semi-analytic model, we find that this is because passive central galaxies reside in, on average, more massive halos with a higher halo mass increase rate across cosmic time. As a consequence, passive central galaxies are assembled faster and also quenched earlier than their star-forming counterparts. While at the same present-day halo mass, different halo assembly history also produces a very different final stellar mass of the central galaxy within, and halos assembled earlier host more massive centrals with a higher quenched fraction, in particular around the “golden halo mass” at 10 ^12 M _⊙ . Our results call attention back to the dark matter halo as a key driver of galaxy evolution.

Based on the DECaLS shear catalog, we study the scaling relations between halo mass ( M _h ) and various proxies for Sloan Digital Sky Survey central galaxies, including stellar mass ( M _* ), stellar velocity dispersion ( σ _* ), abundance-matching halo mass ( M _AM ), and satellite velocity dispersion ( σ _s ), and their dependencies on galaxy and group properties. In general, these proxies all have strong positive correlations with M _h , consistent with previous studies. We find that the M _h – M _* and M _h – σ _* relations depend strongly on group richness ( N _sat ), while the M _h – M _AM and M _h – σ _s relations are independent of it. Moreover, the dependence on the star formation rate (SFR) is rather weak in the M _h – σ _* and M _h – σ _s relations, but very prominent in the other two. σ _s is thus the best proxy among them, and its scaling relation is in good agreement with hydrodynamical simulations. However, estimating σ _s accurately for individual groups/clusters is challenging because of interlopers and the requirement for sufficient satellites. We construct new proxies by combining M _* , σ _* , and M _AM , and find that the proxy with 30% contribution from M _AM and 70% from σ _* can minimize the dependence on N _sat and the SFR. We obtain the M _h –supermassive black hole (SMBH) mass relation via the SMBH scaling relation and find indications for rapid and linear growth phases for the SMBH. We also find that correlations among M _h , M _* , and σ _* change with M _* , indicating that different processes drive the growth of galaxies and SMBHs at different stages.