Optical design of a compact aberration-corrected time-delay compensated monochromator for high-order harmonic source

High cholesterol absorption efficiency is determined by genetic variation in small intestinal sterol transporters and affects one-third of individuals. Their risk for atherosclerotic cardiovascular disease (ASCVD) is increased compared with low cholesterol absorbers, despite similar serum lipid concentrations. We investigated the association of cholesterol absorption efficiency with proatherogenic properties of low-density lipoproteins (LDLs). The study cohort consisted of 90 middle-aged participants, 56 females and 34 males, without lipid-lowering therapy or ASCVD. They were divided into low (n=45) and high (n=45) cholesterol absorbers by the median value of serum cholestanol to cholesterol ratio. LDL aggregation susceptibility and binding of lipoproteins to proteoglycans were determined as biomarkers of lipoprotein atherogenicity. Nuclear magnetic resonance spectroscopy, mass spectrometry, and gas-liquid chromatography were used to determine lipoprotein subclass profile, LDL lipidome, and serum concentrations of cholesterol and noncholesterol sterols, respectively. Age, dietary cholesterol, and serum total cholesterol or lipoprotein cholesterol levels did not differ between the groups. In the high absorbers, LDL particles were larger, and LDL aggregation susceptibility and the binding of lipoproteins to proteoglycans were increased in the low absorbers. Of LDL surface lipids, sphingomyelin 42:3;O2, and phosphatidylcholine (PC) 32:0 correlated positively, whereas PC 32:1 correlated negatively with serum cholestanol levels. These LDL surface lipids were also associated with increased LDL aggregation susceptibility and proteoglycan-binding. The present findings suggest that increased proatherogenic properties in high cholesterol absorbers may contribute to increased ASCVD risk. https://clinicaltrials.gov/study/NCT01315964.

Design and implementation of high gain dual-polarized antenna for sub-6GHz applications

An original bio-inspired approach, modeled after the magnificent frigatebird, is proposed in this study to optimize Maximum Power Point Tracking (MPPT) for photovoltaic arrays operating in grid-tied configurations, in response to the growing demand for higher efficiency during the ongoing transition toward sustainable energy. By modeling the frigatebird’s strategic shifts between wide-range scouting and target-focused behavior, the algorithm maintains a dynamic equilibrium between exploration and exploitation, ensuring robust MPPT performance even under rapidly changing irradiance and temperature conditions. The photovoltaic setup under study consists of a 50 kW SunPower panel array, paired with a boost-type DC–DC converter and a three-phase inverter. System behavior was examined in MATLAB/Simulink across three operating scenarios: standard test benchmarks, fast-changing irradiance conditions, and real-world solar measurements collected in Tetouan, Morocco. Simulation outcomes reveal that the MFB-based control achieves a high energy conversion efficiency of 99.5% with a rapid response time of 0.27 s, providing improved performance compared with widely used MPPT methods such as P&O and ABC in terms of dynamic response, tracking precision, and total harmonic distortion (THD). The proposed algorithm relies on a simple computational structure with a limited number of control parameters, contributing to reduced computational burden and supporting its suitability for real-time embedded MPPT applications. A performance comparison against fourteen other MPPT approaches reported in recent studies further supports the effectiveness and adaptability of the proposed method. The findings indicate that MFB represents a promising and scalable solution for advanced smart PV systems, with potential applications in real-time embedded platforms and hybrid renewable energy networks. While the present validation is based on detailed simulation results, experimental implementation and hardware-based assessment are considered as natural extensions of this work. • Novel bio-inspired MPPT based on magnificent frigatebird foraging behavior. • Fast and accurate MPPT under rapid irradiance and temperature variations. • High tracking efficiency of 99.49% with 0.27 s dynamic response. • Superior performance compared with P&O, ABC and recent MPPT methods. • Low computational complexity suitable for real-time embedded systems.

Co-optimization of area ratio and material fraction in segmented N-type thermoelectric legs using XGBoost–ANN surrogates

Thermal-stable rotor with enhanced cooling design for efficient electric motor applications.

CRISPR-on-beads: A simple and sensitive assay for detection of methicillin-resistant staphylococcus aureus

Enhanced environmental tolerance of sulfonated graphene-Bi2MoO6 for hydrogen evolution under harsh conditions with high efficiency

Robots performing collaborative long-horizon dexterity cell micromanipulation tasks are challenging and practically significant, such as peeling cell membranes, which is considered one of the most technically demanding procedures. The imitation learning (IL) approach is expected to address the challenges of multitask coupling and object modeling difficulties in long-horizon tasks. Existing IL algorithms suffer from compounding error as they perform only a simple mapping of the task environment space to the action space. In this article, we propose a skill information representation IL (SIRIL) algorithm for long-horizon dexterous robot micromanipulation tasks. First, SIRIL extracts the discrete latent codes of the expert video frames by the VQ-GAN encoder, and the distribution of the latent codes is modeled by an autoregressive transformer. SIRIL quantifies the representation of the expert's skill information by computing the log-likelihood of the latent discrete codes, which allows for the extraction of safe action constraints. Finally, SIRIL predicts actions by integrating actions from previous time steps, and actions that satisfy the safety constraints are executed, which effectively suppresses compounding error. Real experiments show that the SIRIL algorithm can complete the deformable zebrafish embryonic cells dexterous membrane stripping surgery. Ablation studies further confirmed SIRIL's high efficiency in various subtasks, including PushCell, GraspCell, and PeelCell, which achieves an average accuracy of 86.7% and a high final success rate of 64.7%, significantly outperforming existing algorithms. Code is available at https://github.com/zycrobot/SIRIL.

Biomass-derived catalyst for CO2 cycloaddition: High efficiency and low environmental impact

Construction of dual-enzyme hybrid nanoflowers by protein self-assembly and biomineralization for efficient biosynthesis of d-tagatose.

Rapid in-situ enrichment of anammox bacteria in a thiosulfate-driven partial denitrification and anammox biofilter packed with iron sponge.

The rising penetration of renewable energy sources promotes the development of the high-voltage direct current (HVDC) systems for large-scale power integration and transmission. To meet the future demands of meshed HVDC grids, high-voltage high-power dc-dc converters are required to serve as essential interfaces to bridge the HVDC links with different voltage levels. This paper proposes a T-type modular multilevel converter (T-MMDC) composed of two energy buffering arms to transfer partial power and an active filtering arm for removing bulky passive filters. By utilizing the coordination of arms, the proposed T-MMDC not only enables flexible power regulation and bidirectional fault ride-through, but also has the advantages of cost-efficiency, small footprint, and high efficiency. The topology configuration, quantitative characterization of operating principle, analytical parameter design, and fault ride-through control scheme are presented sequentially, providing a straightforward and detailed guideline for engineers. Full-scale simulations from a 320kV@0.5GW case and down-scale experiments from a 750V@5kW prototype confirm the effectiveness of the proposed operating principle and fault ride-through capability of T-MMDC and its good potential for HVDC grids.

CbAgo-enriched Cas12a biosensor for cancer mutations screening.

It is a desirable solution to integrate photovoltaic (PV) and energy storage (ES) into ac grid using a multi-port converter due to its high efficiency and reliability. In this paper, an improved three-phase three-level multi-port converter (TPTL-MPC) is presented for the PV, ES, and grid-connected hybrid systems, which can effectively reduce power conversion stage, thereby further enhancing overall system efficiency. Moreover, an optimal zero-sequence component (ZSC) injection method is proposed to reduce inductor current ripple under active power, reactive power, and different operational modes and dc port voltage. Meanwhile, the proposed optimal ZSC injection method can also reduce low-frequency voltage and current ripples of the PV port and ES port, which is beneficial for reducing the filter capacitors at the ports. To accommodate the voltage variation of PV and ES, dc voltage ratio-based sinusoidal pulse width modulation (DVR-SPWM) and its digital implementation for improved TPTL-MPC are proposed. The smooth switching between the various operational modes is also realized by control strategy. Finally, the experimental results have been provided to confirm effectiveness and feasibility of the improved TPTL-MPC based on the proposed optimal ZSC injection method.

Partial power processing is an attractive solution that processes only a portion of the total power, which has the advantage of increasing efficiency. It can maintain high efficiency over a wide input range when combined with two stages. Since the conventional two-stage partial power processing structure adopts a full-bridge topology or multiple transformers to achieve smooth integration with a DC regulator, it results in a relatively high partial power processing ratio or a large number of circuit components, which limits the achievable efficiency. To deal with this issue, this article proposes a half-bridge-based partial power processing two-stage resonant converter combined with a buck-boost regulator. The integration of a parallel resonant converter and a buck-boost regulator within a half-bridge topology enables high conversion efficiency and a wide input voltage range while minimizing component complexity. This structure also enables a low partial power processing ratio while achieving a high step-up suitable for the target application. The theoretical analysis presented in this article highlights that the choice of DC regulator and the partial power processing ratio are critical factors in the design of a two-stage partial power processing converter. To experimentally validate the proposed converter, a 200W prototype was developed, operating at a switching frequency of 100kHz. The prototype was tested to confirm the functional feasibility and evaluate the performance of the proposed design.

A simplistic preparation of gold-decorated magnetic hybrid nanoparticles as recyclable Nanocatalysts for the hydrogenation of Nitroarenes as well as surface-enhanced Raman scattering substrates

Copper-doped COF triggered bioorthogonal synergistic cancer therapy through apoptosis and cuproptosis.

Preparation and study of sulfide-based electrocatalysts synthesized from NiFeCr layered triple hydroxide precursor for utilization in water splitting applications.

A high-performance permanent magnet linear generator should have low mover mass, sufficient output power, high efficiency, and high power density. Simultaneously improving the multiple parameters of a linear generator is quite challenging due to conflicting parametric requirements. This paper proposes an advanced design optimization procedure combining particle swarm optimization and genetic algorithm to address conflicting requirements. A problem statement is presented regarding such requirements through mathematical model analysis. Simulation work is executed using a finite element-based platform, ANSYS/Maxwell. Particle swarm optimization is first applied to identify an effective stator configuration, where the generator with E 1 stator supplies 3.45 kW more power than the E 2 counterpart. On the contrary, despite a 36.46 % reduction in the mover mass of C-stator, its efficiency is 8.96 % higher than that of the linear generator with the E 1 stator. A genetic algorithm is then applied to optimize the initial C-cored design, yielding simultaneous enhancements of 7.12 % in power, 13.97 % in power density, and 3.03 % in efficiency, along with a 32.5 % reduction in mover mass. The workflow and outcomes are summarized through a structured optimization flowchart. • Identification of conflicting parameters through mathematical model analysis. • Proposal of an advanced methodology to improve multiple parameters simultaneously. • Improvement of multiple parameters concurrently despite reducing the mover mass.