Search Results (826)

This data descriptor presents CINES-REC-CITY, an open synthetic dataset providing high-resolution load profiles for energy community research. The dataset represents a typical German urban district with 70 apartments across eight multi-family buildings, including diverse socioeconomic characteristics. Three main components are provided at 15 min resolution for a full year: non-controllable residential electricity consumption for all apartments, charging profiles for 17 battery electric vehicles with trip information, and heat pump operation data for both variable-speed and hysteresis-controlled ground-source systems. All profiles were generated using validated bottom-up stochastic simulation models accounting for realistic user behavior, mobility patterns, and thermal building physics. The modular structure allows for selective combination of components, enabling investigation of different technology penetration scenarios. The dataset serves as a reference benchmark for reproducible research, allowing for direct comparison of optimization approaches, business models, and control strategies using identical underlying consumption patterns. It is suitable for techno-economic analysis, algorithm development for flexible load control, and grid impact assessment. All data is provided in CSV format with weather data for consistent extensions. Full article

The efficacy of polymer-based nanopesticides (NPs) is strongly governed by carrier concentration and surface charge, which affect shell thickness, drug release kinetics, and photostability. However, the influence of these two factors in pesticide release and delivery performance remains unclear. This study introduces a NIR-II fluorescence dye-tracing strategy to enable high-resolution monitoring of NP behavior in model plants. By systematically varying polymer concentration and copolymer blocks, we investigate their impact on release behavior, photostability, and stem uptake. As the polymer concentration increased, NPs demonstrated a controlled slow release and better photostability, yet a lower pesticide loading capability. In model plants, PISNPs transport quickly and can accumulate at wound sites, effectively offering antifungal properties. This work provides experimental evidence for optimizing polymer carrier design to achieve efficient, controlled release while minimizing photodegradation risks, offering practical guidelines for developing high-performance, low-risk nanopesticide formulations. Full article

Smart warehouses require autonomous mobile robots to complete lifelong tasks while avoiding conflicts, respecting battery constraints, and sharing charging stations. Existing MAPF methods provide strong conflict resolution, but energy, charging, and online action repair are commonly evaluated separately. We present ECR-HR, an energy-constrained hybrid repair framework that combines a normalized energy model, charging-aware goals, risk-informed priorities, and bounded local conflict repair. The scientific contribution is a coupled execution and evaluation interface rather than a new complete MAPF solver or a claim of dominance over MAPF-LNS2. In reproducible simulation, we compare ECR-HR with classical, repair-based, lazy-search, conflict-based, and learning-based baselines. In 40-seed nominal evaluation, ECR-HR reduces candidate conflict rate relative to WHCA* from 0.0479 to 0.0255 ($p=3.89\times {10}^{-6}$) while MAPF-LNS2 achieves the strongest raw success. A 30-seed study using MovingAI map geometry, priority and repair comparisons, module-level runtime profiling, simulated disturbance tests, 25-seed energy coefficient sensitivity, and preference weight sensitivity further define the framework’s operating boundary. Enhanced GNN-PPO-HR increases held-out success from the original 0.188 to $0.753\pm 0.174$ but remains below mature search baselines. All evidence is simulation-based, the energy coefficients are normalized rather than hardware-calibrated, and real-robot validation remains necessary. Full article

Gas Electron Multiplier (GEM) detectors have become an indispensable component of modern tracking systems. The heart of a GEM detector is a thin polyimide foil (∼50 µm) clad with copper (∼5 µm) on both sides and containing an array of regularly spaced holes (typically diameter of ∼70 µm and pitch of ∼140 µm) fabricated using photolithographic techniques. The presence of the dielectric substrate (polyimide) within the amplification region introduces a time dependent response when the detector is exposed to external irradiation, a phenomenon commonly referred to as the charging-up effect. This effect arises from the accumulation of charge on the insulating polyimide surfaces, leading to a gradual modification of the local electric field configuration inside the GEM holes and, consequently, a variation in the detector gain over time. The charging-up behaviour has been systematically investigated for triple GEM chamber prototypes using an Fe-55 radioactive source (5.9 keV X-rays) with an activity of ∼20 mCi. The characteristic charging-up time constant has been extracted, and its dependence on detector gain and irradiation rate has been examined. In addition, the uniformity of detector performance in terms of count rate, gain, and energy resolution has been studied both before and after the charging-up process. In this review article, the experimental setup, data acquisition methodology, and analysis procedures developed and carried out by our group are summarised. The key findings reported by other groups, relevant Monte Carlo simulation efforts, and future outlook for the charging-up investigation on GEM based detectors are also discussed in this article. The investigations and their outcomes reviewed here provide valuable insight into the charging-up dynamics of GEM detectors and their dependence on operational parameters. Full article

N-glycosylation, particularly terminal mannose exposure, is a critical quality attribute affecting macrophage targeting and the clinical efficacy of enzyme replacement therapy for Gaucher disease. This study developed a universal, sensitive, and quantitative method to compare the N-glycan profiles of three recombinant human glucocerebrosidase products from different expression systems: imiglucerase, velaglucerase alfa, and velaglucerase beta. Using 2-aminobenzamide labeling combined with HILIC-UPLC-FLD and high-resolution mass spectrometry, an N-glycan profiling platform was established. A multidimensional calibration system integrating retention time, glucose unit values, and mass-to-charge ratios was constructed, and collision-induced dissociation tandem MS was used to identify isomers and phosphorylated glycans. The method showed good specificity, linearity, precision, and accuracy. Glycan profiling revealed clear product-dependent differences: imiglucerase was enriched in core-fucosylated Man3 structures, velaglucerase alfa was dominated by Man9 and contained more phosphorylated and sialylated glycans, whereas velaglucerase beta showed a highly homogeneous Man5 profile. These findings demonstrate how distinct manufacturing strategies shape glycosylation patterns and provide a basis for biosimilar development and comparability assessment. Full article

Elucidating structure–activity relationships in semiconductor photocatalysis has been significantly impeded by the inherent limitations of ensemble-averaged characterization techniques, which obscure the spatiotemporal heterogeneity intrinsic to catalytic surfaces. Single-molecule fluorescence microscopy (SMFM) surmounts this bottleneck by offering nanometer-scale spatial resolution coupled with the capacity to resolve single-turnover events. Herein, we provide a comprehensive overview of the State-of-the-Art applications of fluorogenic probe-coupled SMFM in deciphering the microscopic mechanisms governing photocatalysis. We begin by delineating the operational principles of total internal reflection fluorescence (TIRF) microscopy and categorizing the response mechanisms of three distinct classes of fluorogenic probes: oxidative (e.g., Amplex Red, APF), reductive (e.g., Resazurin, DN-BODIPY), and acidic (e.g., furfuryl alcohol, thiophene) reporters. Subsequently, we highlight seminal studies wherein SMFM has been leveraged to visualize facet-dependent charge separation on model photocatalysts—including TiO₂, BiOBr, and InSe—to map the dynamic activity associated with surface defects and to precisely locate active sites during photoelectrochemical water splitting. Finally, we critically assess the prevailing technical challenges, such as limitations in probe specificity and background interference, while offering a perspective on prospective avenues for methodological refinement. This review is intended to serve as a methodological cornerstone for advancing mechanistic understanding in photocatalysis and for guiding the rational design of high-performance catalysts. Full article

Accurate battery state-of-charge (SOC) estimation under dynamic operating conditions remains challenging because battery responses are nonlinear, history-dependent, temperature-sensitive, and prone to transient disturbances. To address this problem, this paper proposes a representation-level temporal–frequency symmetry framework, termed the Joint Temporal–Frequency Cross-Domain Attention Network (JTFCD-Net), for joint SOC estimation and voltage reconstruction. Here, symmetry denotes aligned latent representations rather than physical invariance: temporal and frequency-aware views are derived from the same battery process, mapped into the same latent space, and kept at identical temporal resolution and hidden dimensionality. A temporal aggregation block extracts local dynamics at multiple receptive fields, and a Temporal Attention Aggregation Module (TAAM) captures long-range dependence. A Frequency-Aware Attention Module (FAM) then uses global spectral statistics to perform lightweight channel recalibration, thereby injecting coarse frequency-domain information into the temporal representation while preserving the hidden feature shape. A Cross-Domain Attention Module (CDAM) performs bidirectional cross-attention, allowing the two views to query and exchange information. The fused representation is decoded by a main SOC head and an auxiliary voltage reconstruction head, which preserves voltage-response dynamics in the shared representation. Experiments on the CALCE A123 benchmark under multiple fixed ambient temperatures and operating conditions show that JTFCD-Net yields consistently lower errors than the selected baseline methods, while ablation studies confirm the contribution of cross-domain fusion and auxiliary voltage supervision. External validation on the NASA Ames battery aging dataset is also conducted as an independent laboratory-scale cell benchmark. These results indicate that combining temporal modeling with frequency-aware representation learning is a promising direction, although deployment value still requires validation in real BMS settings. Full article

Despite the rapid expansion of photovoltaic (PV) installations over the past decade, challenges such as curtailments of renewable energy sources (RESs) and grid constraints continue to limit the capacity of Cyprus’ power system to accommodate higher solar penetration. In this context, grid reliability, defined as the ability to maintain stable operation by balancing supply and demand, minimizing curtailment, and reducing stress on the island network, has emerged as a critical concern. The deployment of PV-plus-storage systems offers a viable solution to enhance grid reliability while alleviating operational constraints. This paper presents a real-world case study of the first commercially deployed grid-connected PV-powered, battery-integrated electric vehicle (EV) charging station in Cyprus. Commissioned in May 2025, the system integrates a 60.32 kW_p rooftop PV array, a 100 kW/97 kWh battery energy storage system (BESS), and a 160 kW DC fast charger. A custom cloud-based energy management platform enables real-time monitoring, forecasting, and optimization under a zero-export scheme. High-resolution operational and weather data were collected between 15 May and 30 November 2025. Over this period, the integrated PV-battery system supplied 29% of the site’s total energy demand (self-sufficiency rate of 28.97%) and achieved a self-consumption rate of 98.69%. Such rates would not have been attainable with a pure PV system, given the depot’s evening-concentrated EV charging demand profile, which requires the BESS to time-shift daytime solar generation. The system reduced depot electricity costs by approximately 29%, generating €16,010 in savings and avoiding 26.47 tonnes of carbon dioxide (CO₂) emissions compared to a grid-only baseline. Beyond site-level performance, the system contributed to grid stress reduction by absorbing excess PV generation that would otherwise have been curtailed/wasted. Operational insights indicate minimal temperature-related issues, highlight the importance of automated fault detection and alerting to minimize downtime, and demonstrate how periodic operation strategies can optimize system performance and mitigate curtailment in Cyprus’s isolated grid. Full article

The aim of this work is to develop high-precision time-of-flight (TOF) devices based on high-refractive-index solid Cherenkov radiators read out by silicon photomultipliers (SiPMs). Cherenkov light is prompt and, therefore, ideal for reaching the intrinsic timing limits of TOF systems. By utilizing a thin, high-refractive-index radiator, a nearly instantaneous signal is generated by particles exceeding the Cherenkov threshold. In order to achieve the ultimate time resolution, we carried out a rigorous optimization of the radiator material and geometry, alongside the efficiency of the optical coupling to the SiPM sensors. The key factors limiting the time resolution were characterized by comprehensive Monte Carlo simulations, subsequently validated against experimental beam test data. We assembled small-scale prototypes instrumented with various Hamamatsu SiPM array sensors with active areas ranging from 1.3 to 3 mm, coupled with various window materials, such as fused silica and MgF₂, featuring various thickness values. The prototypes were successfully tested in beam test campaigns at the CERN-PS T10 beamline. The data were collected with a complete chain of front-end and readout electronics based on either the Petiroc 2A or the Radioroc 2 interfaced to a picoTDC to measure charges and times. By comparing the time measurements from two SiPM arrays, we were able to measure a time resolution better than 33.2 ps at the full system level, with a charged-particle detection efficiency of 100%. Our results demonstrate the expected performance benchmarks for the charged-particle detection efficiency and time resolution, and they highlight the potential of the developed Cherenkov-based TOF detectors for next-generation particle identification systems. Full article

Thin-film interference in photoresist stacks can become a significant source of uncertainty in lithographic focus metrology, particularly when high measurement stability is required. To evaluate this effect, a Fresnel-based multilayer reflection model is used to analyze the optical response of the resist stack and to guide the selection of dual-wavelength illumination. On this basis, a dual-wavelength optical triangulation system is developed for focus metrology in 350 nm lithography, with signal acquisition performed by a linear charge-coupled device (LCCD). Rather than improving precision by reducing detector pitch, the system employs a two-stage sub-pixel localization strategy in which template matching provides coarse spot localization and weighted centroid interpolation refines the final position within localized calculation windows, keeping the computational cost manageable. A covariance-based uncertainty analysis predicts a total root-mean-square uncertainty of 27.23 nm. Prototype experiments were performed on a bare silicon wafer to establish the intrinsic performance of the instrument before introducing process-dependent optical effects. Under these conditions, the system achieved a vertical resolution of 10 nm, a repeatability of 35 nm, and a stability of 13.16 nm. The additional uncertainty expected under resist-coated-wafer conditions was assessed separately through the thin-film model. These results verify the baseline capability of the proposed system and support the feasibility of the dual-wavelength strategy for focus metrology in 350 nm lithography. Full article

High penetration of distributed photovoltaic (PV) systems has significantly increased microgrid net load volatility and uncertainty, posing challenges for conventional point forecasting methods that fail to provide sufficient operational risk information. To address this, this study proposes a multi-step net load forecasting framework that explicitly accounts for renewable energy fluctuations and system dynamics. A multi-quantile model generates 90% confidence prediction intervals for 1 and 4 h horizons at 15 min resolution. To mitigate under-coverage caused by cumulative errors, a stepwise conformal calibration strategy is applied to adjust each forecasting step independently, enhancing interval reliability and consistency. Net load volatility scenarios derived from PV ramping intensity are used to analyze uncertainty evolution under low, medium, and high fluctuation conditions. Case studies based on a high-PV microgrid dataset from eastern China demonstrate that calibrated intervals improve coverage, particularly in high-volatility scenarios, and, when integrated into rolling energy management, enhance battery state-of-charge safety margins and reduce peak grid import with minimal additional cost. The approach maintains point forecast accuracy while providing interpretable net load risk bounds, supporting informed scheduling and demand management in high-renewable microgrids. Full article

The identification of dyes in ancient textiles is crucial for provenance research and scientific conservation. However, the extremely significant value of these cultural relics necessitates the use of non-destructive analytical techniques. To establish a non-destructive, in-situ, accurate, and rapid method for identifying natural dyes in ancient silk fabric samples, we employed desorption electrospray ionization high-resolution mass-spectrometry imaging (DESI-MSI). By optimizing key instrumental parameters—including sample pretreatment method, DESI spray solvent composition, and DESI heated transfer line (HTL) temperature—we determined the optimal mass-spectrometry imaging conditions. The optimal conditions for achieving the highest mass-spectrometry ion peak signal intensity and the best imaging quality were as follows: employing sample pretreatment using double-sided adhesive tape; a spray solvent composed of methanol (100%, v/v) with 0.1% formic acid and 0.1 μg/mL of leucine enkephalin; and an HTL temperature of 400 °C. The characteristic compound in the G42 silk fabric sample was successfully separated. Based on the characteristic mass-to-charge ratio of the major component, the compound was preliminarily identified as berberine. This result was further verified by tandem mass-spectrometry imaging and tandem mass spectra and finally confirmed by comparison with the mass spectrum of a reference standard. Consequently, the source of the dye in the sample was determined to be amur cork tree. The experiments confirmed the applicability and accuracy of the DESI-MSI method for the non-destructive analysis of precious textiles. This work underscores the urgent need to use such non-destructive techniques to provide technical support for the identification of high-value, inaccessible, or fragile silk artifacts and guide the historical tracing and preservation of these cultural relics. Full article

As synchrotron radiation sources (SRSs) expand to cover a broader energy range, the demand for hybrid detectors with improved spatial and energy resolution is increasing. This paper presents the design and characterization of a prototype pixel readout ASIC featuring a small pixel size and low noise, developed for low energy soft X-ray applications. This chip adopts the single photon-counting (SPC) approach and each pixel consists of a front-end amplifier, a discriminator, a charge injection circuitry and a pair of 15-bit counters with associated logic. Fabricated in a 130 nm CMOS process, the chip integrates a 2 × 16 pixel matrix with a 50 µm ×50 µm pixel size. Measurement results indicate the maximum pixel equivalent noise charge (ENC) across the matrix is 20 e⁻rms without sensor attached. The results validate that the chip design has the potential to deliver a low-energy resolution for soft X-ray applications. Full article

This study successfully developed an efficient one-dimensional confinement strategy to encapsulate polyoxometalate NiMo₆ clusters densely and uniformly within the cavities of a single-walled carbon nanotube (SWCNT), constructing a unique core–shell NiMo₆@SWCNT composite electrocatalyst. Comprehensive characterization including high-resolution transmission electron microscopy (HRTEM), energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR), and ultraviolet-visible absorption spectroscopy (UV-Vis) systematically confirmed the uniform dispersion and structural integrity of NiMo₆ within the SWCNT channels. Key evidence encompasses: (1) EDS elemental mapping revealing high co-localization of Ni/Mo signals inside the lumens; (2) transmission electron microscopy (TEM) images confirming the effectiveness of the filling process. The composite achieved an exceptionally low overpotential of 308 mV to drive a current density of 10 mA cm⁻² (significantly outperforming pure NiMo₆ at 365 mV and pristine SWCNT at 519 mV), exhibited a remarkably low Tafel slope of 96.64 mV dec⁻¹, possessed a high electrochemical active surface area (10.75 mF cm⁻²), and very low charge transfer resistance. Critically, it showed negligible current density decay during prolonged chronoamperometric operation over 35,000 s (>9.7 h). This work not only validates the confined encapsulation as a viable strategy for fabricating highly active polyoxometalate/carbon composites, but also elucidates that the performance enhancement stems from a “triple synergy”: the intrinsic catalytic activity of NiMo₆, the highly conductive/mass-transport network provided by SWCNT, and the synergistic effects arising from the confined interface—namely stress regulation and electronic coupling. This insight provides a novel perspective for designing high-performance non-precious metal electrocatalysts. Full article

High-resolution vertical profile observations of ocean environmental parameters are essential for investigating mesoscale ocean dynamic phenomena, such as internal waves, mesoscale eddies, and oceanic fronts. At present, vertical profile measurement in marine surveys mainly relies on shipborne winches to deploy and recover marine sensors, which entails high labor costs and considerable energy consumption. Unmanned observation platforms integrated with winch systems enable automatic sensor deployment and recovery, offering a viable approach to cutting observation costs. Nevertheless, inadequate energy supply remains a critical bottleneck restricting the large-scale popularization and application of such equipment. Accordingly, the development of high-efficiency winch systems tailored for unmanned autonomous observation platforms is of great engineering significance for facilitating long-term, continuous, and low-energy marine profile observation. This paper proposes a novel energy-saving winch with an embedded three-stage parallel nested energy storage structure for unmanned marine observation platforms. During operation, the coil spring energy storage system is charged during cable payout, and the stored elastic potential energy is released to assist motor driving in the cable retraction process. This auxiliary driving mode reduces motor power demand and improves the overall energy utilization efficiency of the platform. Experimental results demonstrate that, neglecting ocean current resistance, the proposed winch reduces energy consumption by 5% during cable payout and 21% during cable retraction. The overall energy consumption is decreased by 13% throughout a complete vertical profile measurement cycle. Under constrained and fixed energy supply conditions, this technology substantially enhances the sampling capability of unmanned marine platforms for ocean environmental monitoring. It further improves operational efficiency and extends continuous service time, providing key technical support for revealing ocean dynamic evolution and clarifying the formation and driving mechanisms of marine environmental phenomena. Full article