Search Results (7,780)

The NA64 experiment at the CERN H4 beamline recently started a high-energy positron-beam program to search for light dark matter particles through a thick-target, missing-energy measurement. To fulfill the energy resolution requirement of the physics measurement ${\sigma }_E/E\simeq 2.5\%/\sqrt{E\left[\mathrm{GeV}\right]}\oplus 0.5\%$ and cope with the constraints and performance requests of the NA64 setup, a new high-resolution homogeneous electromagnetic calorimeter PKR-CAL has been designed. The detector is based on PbWO₄ crystals, each read by multiple SiPM sensors to maximize the light collection. The PKR-CAL design has been optimized to mitigate and control unavoidable SiPM saturation effects at high light levels, as well as to minimize the gain fluctuations induced by instantaneous variations of the H4 beam intensity. The R&D program culminated in the construction of a small-scale prototype, POKERINO. In this work, we present the results from the experimental characterization campaign of the POKERINO, aiming at demonstrating that the obtained performances are compatible with the application requirements. Full article

Greenhouse cultivation enables year-round vegetable production and high yields through precise environmental regulation. Yet, the same stable microclimate that promotes crop growth also favors the proliferation of pests and diseases. This review synthesizes current knowledge on how greenhouse climate variables govern pest and disease epidemiology in tomato, cucumber, and sweet pepper. Only greenhouse-based studies were included to ensure direct relevance to protected horticulture. Microclimatic stability determines infection probability, vector behavior, and host susceptibility. Warm, humid conditions promote fungal and bacterial pathogens, whereas dry, high vapor pressure deficit (VPD) environments favor mites and thrips and enhance virus transmission. Species-specific traits further modulate vulnerability. Tomato is dominated by virus–bacterium complexes and foliar/stem fungal diseases, cucumber by phytopathogenic fungi favored by high relative humidity (RH) and soilborne pathogens, and sweet pepper by virus–vector systems and long-cycle fungal infections. Temperature exerts the strongest influence, while RH and VPD jointly regulate surface moisture and vector activity. Light intensity and spectral composition also affect pest orientation and fungal sporulation. Integrating environmental sensing, biological control, and adaptive climate regulation offers a pathway toward preventive, climate-smart Integrated Pest Management (IPM). The review highlights the emerging role of climate-informed decision-support systems (DSSs) and the need for greenhouse-specific datasets to improve pest and disease forecasting. Full article

Artificial light at night (ALAN) data is widely used in urban function analysis and socio-economic activity monitoring, but its application at the micro-scale of cities still faces challenges. This study utilizes high spatial resolution SDGSAT-1 nighttime light data to explore the spatial heterogeneity of ALAN at the street scale in two representative Chinese cities—Beijing and Guangzhou. By integrating multi-source data (such as building vector data, road networks, and point of interest data), a multi-dimensional indicator system covering urban morphology, functional structure, and transportation accessibility is constructed. Based on this, the study employs a Geographically Weighted Random Forest (GWRF) model combined with the Shapley Additive Explanations (SHAP) method to deeply analyze the non-linear relationships between ALAN intensity and multiple driving factors, as well as their spatial variability. Results demonstrate the superiority of the GWRF model over global models in capturing spatial non-stationarity, with R² values of 0.67 for Beijing and 0.74 for Guangzhou, compared to 0.62 and 0.71 for the random forest models, respectively. Road density is the dominant factor influencing nighttime light intensity in both Beijing and Guangzhou. However, the relationship between ALAN and its driving factors varies across these cities. In Beijing, a balanced multi-factor model is observed, whereas in Guangzhou, ALAN intensity is primarily driven by road density, with secondary influences from other factors like sky view factor. This study validates SDGSAT-1 for micro-scale analysis, offering a scientific basis for differentiated urban lighting planning. Full article

Early and recent studies have demonstrated that exposure to moonlight influences the entire life cycle of plants from seed germination to vegetative growth and reproduction. Exposure to moonlight was found to induce genome reorganization in plants and significant changes in gene expression, protein, and metabolite profiles. However, the specific factors that facilitate moonlight perception are unknown. To uncover the photoreceptors responsible for moonlight perception, we analyzed Arabidopsis phototropin mutants (phot1, phot2, and phot1phot2) as well as the phytochrome mutants phyA and phyB for their response to full moonlight (FML). De-etiolation assays revealed that plants do perceive and respond to FML within 5 h of exposure. Thus, among the photoreceptor mutants analyzed, only phot1 and phot1phot2 were impaired in apical hook opening and cotyledon unfolding under FML. Interestingly, under high light intensity, all examined mutants underwent proper de-etiolation. Further analysis showed that phot1 as well as phyB mutants were impaired in response to moonlight, displaying no changes in nuclear size and in protein profiles following exposure to FML and were comparable to plants exposed to dark. The FML (5 h exposure) did not induce the formation of fewer, large nuclear photobodies, as occurred following 5 h exposure to growth-room light. Our findings highlighted phot1 and phyB as photoreceptors necessary for plants to perceive and respond to FML. It is proposed that the initial perception of moonlight is facilitated by the blue-light receptor phot1 and is subsequently interpreted into a functional state by the R/FR receptor phyB. Full article

Accurate assessment of light properties is essential and is measured with photometric and colorimetric standardized methods. However, the spatial characteristic of light—harshness—remains difficult to quantify. Building on the authors’ previous work, this study presented a fully automated method for determining light source harshness based on image analysis of cast shadows in a standardized environment. The improved method eliminated the need for manual shadow segmentation by introducing algorithmic noise removal and adaptive smoothing of shadow data. The method was applied to 180 test images comprising 30 combinations of photographic light-shaping attachments (e.g., softboxes, beauty dishes, and snoots) across two light sources (halogen and xenon) and three intensity levels. The results showed that the method was capable of detecting subtle differences in shadow properties and confirmed the influence of geometry, material, and orientation of the light modifiers on harshness. In addition, the results provided quantitative insight into the influence of photographic light modifiers on the original light. Full article

Polydimethylsiloxane (PDMS) films doped with graphene nanoplatelets (GNP) with an embossed surface-relief grating were investigated as photothermal actuated sensors. The films were initially characterized using controlled environmental heating where the wavelength of a diffracted white-light probe beam measured at a fixed angle increased monotonically with temperature due to thermal expansion of the grating. An asymmetric double sigmoidal function tracked the shift in peak diffraction wavelength. The observed thermal response is consistent with the thermal expansion of a freestanding PDMS composite film. When a continuous-wave (CW) laser was incident on the film, intensity-dependent photothermal expansion caused a transient deformation in the grating. The photomechanical behavior of the grating, tracked by the diffracted probe beam with a miniature spectrometer, was then shown to act as a laser power meter. These results demonstrate that photomechanical materials can be used as add-ons to existing optical spectroscopy devices for power-sensing applications. Full article

To explore whether the causal chain of “Industry–University–Government Integrated Innovation Ecosystem → Novel Energy Storage Technology Innovation → Dual-Control Energy Targets” can be achieved, this study analyzes panel data from 30 provinces, municipalities, and autonomous regions in China (excluding Tibet, Hong Kong, Macao, and Taiwan) from 2010 to 2022. By employing a complex mediation effect model combining dynamic Qualitative Comparative Analysis (QCA) and the dynamic panel system Generalized Method of Moments (GMM) model, this study identifies five configuration pathways for driving innovation in novel energy storage technologies within an integrated innovation ecosystem. These include two industry digitalization–university innovation resource-dominant pathways: a government-light and digitally driven “university–industry” resource-sharing and knowledge-conversion synergy, and an industry leadership pathway embedded with university collaborative innovation under a digitalization framework. Two policy-driven hybrid and industry–leadership synergistic pathways are also extracted: a growth pathway for policy-supported hybrid organizations under insufficient industry digitalization and a policy-driven innovation substitution pathway compensating for the absence of university niche roles. Additionally, a multidimensional collaborative development pathway is identified, reflecting comprehensive collaboration. In the dynamic panel system GMM model, all five pathways collectively suppress total energy consumption and energy intensity, while also indirectly driving the achievement of dual-control energy targets through innovation in novel energy storage technologies. Pathways driven by government-light and digitally facilitated collaboration, industry leadership, and comprehensive collaboration show significant direct negative effects on energy consumption and intensity. However, the policy-driven innovation substitution pathway exhibits limited contribution due to the absence of university innovation components, thereby failing to significantly advance regional dual-control energy goals. Full article

Visual cues are critical for orientation and migration in riverine fishes, providing potential mechanisms for behavioral guidance. This study investigated how light spectrum and intensity interact to modulate phototactic responses in two schizothoracine fishes from the upper Yalong River. Results showed Schizopygopsis malacanthus preferred blue light and avoided red light, with preferences shifting with flow intensity; Schizothorax kozlovi favored green light and avoided light-red light, with minimal flow impact. We propose that engineers build fishway entrances or ideal habitat attractors that prioritize low-intensity blue light (10 lx) and medium-intensity green light (50 lx), supplemented by medium-intensity blue light (50 lx). This study provides scientific evidence and application value for restoring fish habitats, fish passages, and fisheries. Full article

Nighttime light (NTL), a crucial indicator of human activity intensity, has not been systematically analyzed for its interactive mechanisms with air pollution and climate change. This study first investigates the spatiotemporal evolution of China’s total nighttime light (TNTL) and average nighttime light (ANTL), alongside key indicators of meteorological parameters and air pollution, at the grid scale from 2000 to 2023. We then employ prefecture-level city data and a geographically and temporally weighted regression (GTWR) model to quantify the spatiotemporally heterogeneous associations of temperature (TMP), precipitation (PRE), fine particulate matter (PM_2.5), ozone (O₃), land use (LUL), topography, and socioeconomic factors with NTL. The results indicate that (1) China’s NTL exhibits a significant overall upward trend, with areas of increase or significant increase comprising 92.04% of the total study area. TNTL growth demonstrates regional heterogeneity, expanding by a factor of 4.91 in East China and 2.65 in Northeast China; (2) meteorological and air pollution indicators display spatiotemporal non-stationarity, with the synergistic effect between O₃ and PRE being the strongest; (3) among NTL drivers, LUL contributes most significantly (0.44), followed by TMP (0.14) > PM_2.5 (−0.33 × 10⁻¹) > O₃ (0.17 × 10⁻¹) > PRE (−0.33 × 10⁻⁶); (4) TMP and PRE may primarily influence NTL by altering ecological conditions and nighttime activity patterns. TMP shows a strong positive correlation with NTL in the junction zone of South, East, and Central China, whereas PRE predominantly exerts a negative influence; (5) air pollution exhibits distinct spatiotemporal effects: high PM_2.5 and O₃ generally correspond to lower NTL, though positive correlations persist in some areas due to industrial structures, highlighting the need for integrated policies that balance air quality management with sustainable urban planning; (6) the 2013 “Air Pollution Prevention and Control Action Plan” significantly strengthened the negative correlation between PM_2.5 and NTL in North China. However, O₃ concentrations increased by 28.9% after 2017, underscoring the challenge of coordinating VOC and NOx controls for long-term atmospheric sustainability. Full article

Land use practices are a key driver of soil nitrogen (N) dynamics, yet their influence on N accumulation within distinct soil organic matter (SOM) fractions remains insufficiently understood. This study aimed to elucidate the responses of N accrual in different SOM fractions to contrasting land uses. To achieve this purpose, soil samples were collected from seven representative land uses: forest, pasture, corn plantation, sugarcane plantation, cassava plantation, orchard, and abandoned land. Subsequently, soil samples were fractionated into free particulate SOM (fSOM), occluded light SOM (oSOM), weakly bound form SOM (wSOM), and strongly bound form SOM (sSOM) fractions, and N contents were quantified for each fraction. The results showed pronounced land use effects on both the magnitude and distribution of N among SOM fractions. The forest land use consistently promoted greater N accumulation in fSOM (0.15 g N kg⁻¹ soil), oSOM (0.14 g N kg⁻¹ soil), and wSOM fractions (0.29 g N kg⁻¹ soil), reflecting high organic inputs and low disturbance intensity. The pasture land use exhibited the highest N accumulation in the sSOM fraction (1.01 g N kg⁻¹ soil), indicating enhanced stabilization of N through strong organo-mineral associations. Intensively managed croplands and abandoned land generally displayed lower N storage across SOM fractions. Overall, these findings highlight the critical role of land use in regulating N partitioning and stabilization within SOM fractions and underscore the importance of low-disturbance, perennial vegetation systems for improving long-term soil N retention. Full article

Atmospheric laser beam propagation is typically perturbed by the dual influences of aerosol particle systems and atmospheric turbulence. This joint perturbation induces intensity fluctuations in the transmitted optical field, which significantly degrades the performance of laser-based systems. This study integrates and improves upon existing simulation algorithms, establishing a coupled model that combines the Monte Carlo method and multi-phase screens. The model accurately characterizes optical field evolution and reveals that the impacts of scattering and turbulence on the scintillation index (SI) are not simply additive: turbulence perturbation enhances intensity fluctuations, leading to an increase in SI; however, as the energy proportion of scattered light rises, its statistical stationarity begins to dominate the optical field characteristics, stabilizing SI. Based on radiative transfer and Mie scattering theories, an analytical formula for single-scattering SI is derived, enabling direct calculation from fundamental parameters. Furthermore, a composite SI expression is established using the scattered-to-transmitted light intensity ratio. To address model deviations along the dimensions of visibility and turbulence strength, a sinusoidal compensation model and a logarithmic compensation model are proposed, respectively. Validation results verify the complementary and competitive mechanisms of scattering and turbulence in modulating intensity fluctuations. This research provides efficient theoretical tools and practical references for simulating and optimizing laser transmission in complex atmospheric environments. Full article

Geiger-mode avalanche photodiode (GM-APD) array light detection and ranging (LiDAR) has significant advantages in low-light scenes due to its single-photon-level detection sensitivity. However, it is susceptible to noise, which leads to a decrease in target localization accuracy. Traditional methods rely on long-term accumulation to distinguish signal photons from noise photons, making it difficult to achieve efficient processing, especially in scenarios with sparse echo photons and low signal-to-noise ratio (SNR), where performance is limited. To quickly and accurately obtain three-dimensional (3D) information of the target under such extreme conditions, this paper proposes a method for target detection and temporal window depth estimation based on intensity information guidance. First, noise suppression is performed on the intensity image according to its statistical characteristics, and an outlier detection mechanism based on neighborhood sparsity is introduced to remove outliers, thereby completing the target detection. Next, by exploiting the spatial continuity and reflectivity similarity of the target, local fusion of photon data within the target neighborhood is performed to construct highly consistent “superpixels”. Finally, according to the distribution difference between signal photons and noise photons on the time axis, temporal window screening is applied to the superpixels to extract depth information, and empty pixels are filled using a convex segmentation method to achieve depth estimation of the target. The experimental results demonstrate that under conditions of low photon counts and strong noise, the proposed method significantly outperforms traditional and existing methods in target recovery and depth estimation by effectively integrating target intensity information. Furthermore, this method achieves faster reconstruction speed, enabling high-precision and high-efficiency 3D target reconstruction. Full article

Background: Wild jujube (Ziziphus jujuba var. spinosa) exhibits remarkable tolerance to saline-alkali stress, yet its molecular mechanisms remain poorly understood. 3-ketoacyl-CoA synthase (KCS) is a key enzyme involved in the biosynthesis of very-long-chain fatty acids (VLCFAs), which constitute pivotal precursors for membrane lipids involved in stress adaptation. Methods: Through genome-wide analysis and molecular biology techniques, 20 ZjKCS genes were identified. Results: The ZjKCS genes were grouped into nine subfamilies, exhibiting highly conserved gene structures, motifs, and functional domains within each subfamily. Two pairs of collinear gene pairs were identified, with the ZjKCS12-ZjKCS18 pair retaining core conserved functions despite intense purifying selection. ZjKCS genes are rich in cis-acting elements associated with light transduction, phytohormone responses, and abiotic stress adaptation. Tissue-specific expression patterns of ZjKCS under light, ABA (abscisic acid), and MeJA (methyl jasmonate) treatments were analyzed by quantitative real-time PCR (qRT-PCR). Under saline-alkali stress, ZjKCS genes were significantly upregulated, with most showing strong sustained induction during later treatment stages. Conclusions: These findings indicate that the ZjKCS family participates in saline-alkali stress and abiotic stress adaptation, potentially by enhancing VLCFA synthesis to reinforce and remodel membrane lipid structure. This study provides a foundation for elucidating lipid-mediated stress resistance mechanisms in stress-tolerant fruit trees. Full article

Light availability is a key environmental factor influencing plant functional traits and ecological strategies. To investigate how natural populations of Iris pumila respond to contrasting irradiance, we conducted an in situ reciprocal transplant experiment using clonal genotypes from two natural populations, each originating from an open dune and a shaded forest habitat. Leaves collected from each of the replanted and transplanted genotypes were analyzed for structural (specific leaf area—SLA, leaf dry matter content—LDMC), physiological (specific leaf water content—SLWC, photosynthetic pigments) and biochemical (peroxidase—POD, glutathione reductase—GR, phenolics and anthocyanins) traits. Shade-grown individuals developed thinner leaves with higher SLA and chlorophyll content, enhancing light-harvesting efficiency, whereas sun-exposed plants exhibited greater LDMC, increased POD and GR activities and higher anthocyanin levels—traits consistent with enhanced photoprotection under high irradiance. All genotypes exhibited pronounced plasticity to light intensity, with habitat exerting a stronger influence on trait expression than population origin. To evaluate oxidative balance, we proposed the ODAC index (Oxidative Damage to Antioxidant Capacity), which integrates lipid peroxidation with antioxidant capacity. ODAC values revealed consistent population-level differences, with higher values in Dune genotypes across habitats, indicating a constitutively elevated oxidative load relative to antioxidant protection and suggesting differentiation in redox regulation between populations. Overall, leaf trait variation in I. pumila appears to be primarily driven by plastic responses to light conditions, while differentiation in oxidative physiology contributes to functional divergence between populations. Full article

In urban driving cycles, battery electric vehicles are subject to frequent start–stop operations, which lead to substantial braking energy losses. Although fuzzy control (FC) strategies are commonly employed for regenerative braking, their performance is often constrained by subjectively defined membership functions and rules. To address this limitation, this paper proposes an improved FC strategy that is optimized using the particle swarm optimization (PSO) algorithm. Focusing on a front-wheel-drive BEV, a three-input single-output fuzzy controller is developed in accordance with ECE regulations, where braking intensity, battery state of charge (SOC), and vehicle speed serve as inputs, and the motor braking force ratio serves as the output. A co-simulation platform based on AVL-Cruise 2019 and Matlab/Simulink 2017a is established to evaluate the strategy under the New European Driving Cycle (NEDC) and the Worldwide Light Vehicles Test Cycle (WLTC). Additionally, hardware-in-the-loop (HIL) tests are conducted to validate the practical feasibility and accuracy of the optimized strategy. The results demonstrate that the PSO-optimized FC strategy achieves a performance in real-world controllers that is comparable to that observed in a simulation, confirming its real-time applicability. Specifically, under the NEDC, the optimized strategy reduces battery SOC from 0.90 to 0.8795, representing improvements of 0.2515% and 0.4670% over the unoptimized FC strategy and the ideal distribution strategy, respectively. The regenerative braking efficiency is enhanced by 2.45% and 10.48%. Under the WLTC, the final SOC with the optimized strategy is 0.8488, reflecting gains of 0.5202% and 0.8380% over the two reference strategies, while regenerative braking efficiency improves by 2.32% and 8.95%. These findings indicate that the proposed strategy offers a safe and effective solution for improving the regenerative braking performance in electric vehicles. Full article