Leakage Reduction Research Articles

The Current State of Robot-Assisted Minimally Invasive Esophagectomy (RAMIE): Outcomes from the Upper GI International Robotic Association (UGIRA) Esophageal Registry.

Robot-assisted minimally invasive esophagectomy (RAMIE) is increasingly adopted in centers worldwide, with ongoing refinements to enhance results. This study aims to assess the current state of RAMIE worldwide and to identify potential areas for improvement. This descriptive study analyzed prospective data from esophageal cancer patients who underwent transthoracic RAMIE in Upper GI International Robotic Association (UGIRA) centers. Main endpoints included textbook outcome rate, surgical techniques, and perioperative outcomes. Analyses were performed separately for intrathoracic (Ivor-Lewis) and cervical anastomosis (McKeown), divided into three time cohorts (2016-2018, 2019-2020, 2021-2023). A sensitivity analysis was conducted with cases after the learning curve (> 70 cases). Across 28 UGIRA centers, 2012 Ivor-Lewis and 1180 McKeown procedures were performed. Over the time cohorts, textbook outcome rates were 39%, 48%, and 49% for Ivor-Lewis, and 49%, 63%, and 61% for McKeown procedures, respectively. Fully robotic procedures accounted for 66%, 51%, and 60% of Ivor-Lewis procedures, and 53%, 81%, and 66% of McKeown procedures. Lymph node yield showed 27, 30, and 30 nodes in Ivor-Lewis procedures, and 26, 26, and 34 nodes in McKeown procedures. Furthermore, high mediastinal lymphadenectomy was performed in 65%, 43%, and 37%, and 70%, 48%, and 64% of Ivor-Lewis and McKeown procedures, respectively. Anastomotic leakage rates were 22%, 22%, and 16% in Ivor-Lewis cases, and 14%, 12%, and 11% in McKeown cases. Hospital stay was 13, 14, and 13 days for Ivor-Lewis procedures, and 12, 9, and 11days for McKeown procedures. In Ivor-Lewis and McKeown, respectively, the sensitivity analysis revealed textbook outcome rates of 43%, 54%, and 51%, and 47%, 64%, and 64%; anastomotic leakage rates of 28%, 18%, and 15%, and 13%, 11%, and 10%; and hospital stay of 11, 12, and 12days, and 10, 9, and 9days. This study demonstrates favorable outcomes over time in achieving textbook outcome after RAMIE. Areas for improvement include a reduction of anastomotic leakage and shortening of hospital stay.

An efficient leakage power optimization framework based on reinforcement learning with graph neural network

Threshold voltage (Vth\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$V_{th}$$\\end{document}) assignment is convenient for leakage optimization due to the exponential relation between leakage power and Vth\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$V_{th}$$\\end{document} by swapping logic cells without routing effort. However, it poses great challenge in large scale circuit design as an NP-hard problem. Machine learning-based approaches have been proposed to solve this problem, aiming to achieve well tradeoff between leakage power reduction and runtime speed up without new induced timing violation. In this paper, a leakage power optimization framework based on reinforcement learning (RL) with graph neural network (GNN) is first-ever proposed to formulate Vth\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$V_{th}$$\\end{document} assignment as a RL process by learning timing and physical characteristics of each circuit instance with GNN. Multiple instances are selected in a non-overlapped manner for each RL action iteration to speed up convergence and decouple timing interdependence along circuit path, where the corresponding reward is carefully defined to tradeoff between leakage reduction and potential timing violation. The proposed framework was validated by the Opencores and IWLS 2005 benchmark circuits with TSMC 28 nm technology. Experimental results demonstrate that our work outperforms prior non-analytical and GNN-based methods with better leakage power optimization by additional 5% to 17% reduction, which is highly consistent with the commercial tool. When transferring the trained RL-based framework to unseen circuits, it achieves the roughly identical leakage optimization results as seen circuit and speed up the runtime by 5.7×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes$$\\end{document} to 8.5×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes$$\\end{document} compared with commercial tool.

Cellfare: Delivering Self-Targeted Social Protection Using Mobile Phones

This article proposes a new form of self-targeted social protection scheme: beneficiaries carry out a series of small tasks on their mobile phones, each linked to a small payment. Key advantages over traditional public works include potentially large reductions in leakage, costs, and delays. The proposed scheme may also be suitable to wider demographics as it does not require physical labour and can be availed from home. A prototype implementation of a ‘cellfare’ scheme was tested in rural India, and 42 participants with experience of the Mahatma Gandhi National Rural Employment Guarantee Act, a large Indian public works programme, favourably compared the proposed scheme to the existing one.

Coupler-Assisted Leakage Reduction for Scalable Quantum Error Correction with Superconducting Qubits

Coupler-Assisted Leakage Reduction for Scalable Quantum Error Correction with Superconducting Qubits

The effect of water loss on demand–supply departure of Addis Ababa, Ethiopia

Water scarcity is a critical issue affecting numerous regions, including Addis Ababa, Ethiopia. The city’s growing population and rising water consumption place significant pressure on its existing water infrastructure. This study evaluates the impact of water loss due to leakages in the distribution system on the demand–supply gap in Addis Ababa, utilizing the WB EasyCalc software for analysis. Data analysis from 2023 indicate that monthly water loss contributes to an additional unmet demand of 5 million cubic meters (MCM), emphasizing the urgent need for effective water loss reduction strategies to enhance supply reliability. Currently, the city achieves only 42% water supply coverage, with an average loss of 300 L per connection per day and approximately 25,000 L lost per kilometer of pipeline daily. Furthermore, non-revenue water (NRW) accounts for 41.8% of total production, with real losses constituting 64%. The Infrastructure Leakage Index (ILI) score of 27 underscores the critical need for targeted leakage management interventions. The significance of this research lies in its quantification of water loss and its direct correlation with unmet demand in Addis Ababa. The findings provide essential insights for policymakers and stakeholders, highlighting the necessity for improved infrastructure management and strategic interventions to bolster water supply reliability. Implementing effective leakage reduction measures could substantially mitigate water scarcity challenges, thereby supporting sustainable urban development and enhancing public health outcomes in a city where access to clean water is vital for economic and social stability.

Risk Reduction of Severe Anastomotic Leakage by Evaluation of Blood Perfusion Using Indocyanine Green After Minimally Invasive Esophagectomy Followed by Narrow Gastric Tube Reconstruction

Risk Reduction of Severe Anastomotic Leakage by Evaluation of Blood Perfusion Using Indocyanine Green After Minimally Invasive Esophagectomy Followed by Narrow Gastric Tube Reconstruction

Analysis of leakage artifacts and their impact on convergence of algebraic reconstruction in multi-contrast magnetic particle imaging

Objective.Magnetic particle imaging (MPI) is a tracer-based medical imaging modality with great potential due to its high sensitivity, high spatiotemporal resolution, and ability to quantify the tracer concentration. Image reconstruction in MPI is an ill-posed problem, which the use of regularization methods can address. Multi-contrast MPI reconstructs the signal from different tracer materials or environments separately, resulting in multi-channel images that enable quantification of, for example, temperature or viscosity. Single- and multi-contrast MPI reconstructions produce different kinds of artifacts. The objective of this work is threefold: first, to present the concept of multi-contrast specific MPI channel leakage artifacts; second, to ascertain the source of these leakage artifacts; and third, to introduce a method for their reduction.Approach.A definition for leakage artifacts is established, and a quantification method is proposed. A comprehensive analysis is conducted to establish a connection between the properties of the multi-contrast MPI system matrix and the leakage artifacts. Moreover, a two-step measurement and reconstruction method is introduced to reduce channel leakage artifacts between multi-contrast MPI channels.Main results.The severity of these artifacts correlates with the system matrix shape and condition number and depends on the similarity of the corresponding frequency components. Using the proposed two-step method on both semi-simulated and measured data a significant leakage reduction and speed up the convergence of the multi-contrast MPI reconstruction was observed.Significance.The multi-contrast system matrix analysis we conducted is essential for understanding the source of the channel leakage artifacts and finding methods to reduce them. Our proposed two-step method is expected to improve the potential for real-time multi-contrast MPI applications.

Mitigating calibration errors from mutual coupling with time-domain filtering of 21 cm cosmological radio observations

Abstract The 21 cm transition from neutral Hydrogen promises to be the best observational probe of the Epoch of Reionisation (EoR). This has led to the construction of low-frequency radio interferometric arrays, such as the Hydrogen Epoch of Reionization Array (HERA), aimed at systematically mapping this emission for the first time. Precision calibration, however, is a requirement in 21 cm radio observations. Due to the spatial compactness of HERA, the array is prone to the effects of mutual coupling, which inevitably lead to non-smooth calibration errors that contaminate the data. When unsmooth gains are used in calibration, intrinsically spectrally-smooth foreground emission begins to contaminate the data in a way that can prohibit a clean detection of the cosmological EoR signal. In this paper, we show that the effects of mutual coupling on calibration quality can be reduced by applying custom time-domain filters to the data prior to calibration. We find that more robust calibration solutions are derived when filtering in this way, which reduces the observed foreground power leakage. Specifically, we find a reduction of foreground power leakage by 2 orders of magnitude at k∥ ≈ 0.5 h Mpc−1.

Thermal–Elastohydrodynamic Lubrication Characteristics of the Flow Distribution Pair of Balanced Double-Row Axial Piston Pumps

A theoretical model for the calculation of thermal elastohydrodynamic lubrication performance of the flow distribution pair of piston pumps is established, which is composed of the oil film pressure governing equation and energy equation, and solved by means of numerical solution and simulation. We carry out quantitative analysis of the influence of various parameters on the thermal elastohydrodynamic lubrication characteristics of the flow distribution pair. The results indicate that both the oil film thickness and the cylinder tilt angle of the flow distribution pair vary in a periodic manner. The increase in the rotational speed of the cylinder block will increase the film thickness of the oil film and reduce the fluctuation, and the inclination angle of the cylinder block and its fluctuation amplitude will decrease. An increase in working pressure will lead to a decrease in the average oil film thickness, an increase in fluctuations, and an elevation in both the tilt angle of the cylinder block and its fluctuation amplitude. The increase in the rotational speed of the cylinder block and the increase in the working pressure will lead to the increase in the viscous friction dissipation of the flow distribution pair, the increase in the oil film temperature and the increase in the leakage. The reduction in the sealing belt will lead to the reduction in oil film friction torque and leakage.

Optimal monitoring design for uncertainty quantification during geologic CO[formula omitted] sequestration: A machine learning approach

An effective monitoring design is crucial to ensure the safe and permanent geologic storage of CO2. Optimal monitoring design involve an optimal placement of monitoring wells, and optimal monitoring measurement data (pressure, CO2 saturation, temperature, etc.). We developed a filtering-based data assimilation approach to design an optimal monitoring strategy for well placement and monitoring data design. To efficiently solve the optimization problem and reduce computational costs, Artificial Neural Networks are used to develop computationally efficient reduced-order models based on full-physics numerical simulations of CO2 injection in saline aquifers. We demonstrate our approach in two scenarios of CO2 leakage through legacy or abandoned wellbores where an optimal monitoring strategy are devised to reduce the uncertainty in cumulative CO2 leakage in the geologic CO2 sequestration (GCS) site. The optimal monitoring design resulted in an uncertainty reduction in the cumulative leakage of CO2 of approximately 73% and 62% in each case, respectively. The proposed approach is efficient in developing monitoring designs under geologic uncertainty and enables safe geologic carbon sequestration operations.

Exogenous Methyl Jasmonate Alleviates Mechanical Damage in Banana Fruit by Regulating Membrane Lipid Metabolism

Bananas are economically important fruits, but they are vulnerable to mechanical damage during harvesting and transport. This study examined the effects of methyl jasmonate (MeJA) on the cell membrane integrity and membrane lipid metabolism of wounded banana fruits after harvest. The results showed that 10 and 50 μM MeJA treatments on mechanically wounded bananas significantly delayed ripening and senescence in comparison with the control. At the end of storage, MeJA-treated groups showed a significant reduction in electrolyte leakage and malondialdehyde content, indicating that MeJA protected cell membrane integrity. MeJA also led to a significant decrease in the activity of antioxidant enzymes, including lipoxygenase, diacylglycerol kinase, and lipid phosphate phosphatase. Furthermore, MeJA reduced phospholipase (C and D), phosphatidic acid, and diacylglycerol levels, as well as slowed down the decrease in phosphatidylcholine and phosphatidylinositol contents. Compared to the control, MeJA significantly downregulated the expression of MaPLDγ, MaPLDα, and MaPLDζ. Therefore, MeJA treatment could be a reliable method to delay the senescence of harvested banana fruits subjected to mechanical wounding.

Reducing Leakage of Single-Qubit Gates for Superconducting Quantum Processors Using Analytical Control Pulse Envelopes

Improving the speed and fidelity of quantum logic gates is essential to reach quantum advantage with future quantum computers. However, fast logic gates lead to increased leakage errors in superconducting quantum processors based on qubits with low anharmonicity, such as transmons. To reduce leakage errors, we propose and experimentally demonstrate two new analytical methods, Fourier ansatz spectrum tuning derivative removal by adiabatic gate (FAST DRAG) and higher-derivative (HD) DRAG, both of which enable shaping single-qubit control pulses in the frequency domain to achieve stronger suppression of leakage transitions compared to previously demonstrated pulse shapes. Using the new methods to suppress the ef transition of a transmon qubit with an anharmonicity of −212 MHz, we implement RX(π/2) gates achieving a leakage error below 3.0×10−5 down to a gate duration of 6.25 ns without the need for iterative closed-loop optimization. The obtained leakage error represents a 20-fold reduction in leakage compared to a conventional cosine DRAG pulse. Employing the FAST DRAG method, we further achieve an error per gate of (1.56±0.07)×10−4 at a 7.9-ns gate duration, outperforming conventional pulse shapes both in terms of error and gate speed. Furthermore, we study error-amplifying measurements for the characterization of temporal microwave control-pulse distortions, and demonstrate that non-Markovian coherent errors caused by such distortions may be a significant source of error for sub-10-ns single-qubit gates unless corrected using predistortion. Published by the American Physical Society 2024

Detection of Short-Chain Chlorinated Aliphatic Hydrocarbons through an Engineered Biosensor with Tailored Ligand Specificity.

Short-chain chlorinated aliphatic hydrocarbons (SCAHs), commonly used as industrial reagents and solvents, pose a significant threat to ecosystems and human health as they infiltrate aquatic environments due to extensive usage and accidental spills. Whole-cell biosensors have emerged as cost-effective, rapid, and real-time analytical tools for environmental monitoring and remediation. While the broad ligand specificity of transcriptional factors (TFs) often prohibits the application of such biosensors. Herein, we exploited a semirational transition ligand approach in conjunction with a positive/negative fluorescence-activated cell sorting (FACS) strategy to develop a biosensor based on the TF AlkS, which is highly specific for SCAHs. Furthermore, through promoter-directed evolution, the performance of the biosensor was further enhanced. Mutation in the -10 region of constitutive promoter PalkS resulted in reduced AlkS leakage expression, while mutation in the -10 region of inducible promoter PalkB increased its accessibility to the AlkS-SCAHs complex. This led to an 89% reduction in background fluorescence leakage of the optimized biosensor, M2-463, further enhancing its response to SCAHs. The optimized biosensor was highly sensitive and exhibited a broader dynamic response range with a 150-fold increase in fluorescence output after 1 h of induction. The detection limit (LOD) reached 0.03 ppm, and the average recovery rate of SCAHs in actual water samples ranged from 95.87 to 101.20%. The accuracy and precision of the proposed biosensor were validated using gas chromatography-mass spectrometry (GC-MS), demonstrating the promising application for SCAH detection in an actual environment sample.

A Novel Method for Optimising Energy Efficiency in High-Performance Computing Systems

This paper introduces a new method to promote energy efficiency in computing systems. The rapidly growing demand for computational power in high-performance computing (HPC) systems is accompanied by a significant increase in energy consumption. This research investigates the many ways to minimise energy consumption in HPC systems without sacrificing computational performance. Building upon previous research we combined and refined ideas to develop an optimised approach. Our method utilises a tri-modular framework incorporating an Energy-Efficient Hardware Design, Resource Management, and Optimisation, and Server Virtualisation. The first module employs a method of designing smart energy-efficient hardware. This method incorporates leakage reduction techniques such as clock gating and sleep states. The second module uses a technique focused on optimising server software. This method is based on Dynamic Voltage and frequency scaling (DVFS) for power management in data centres. The third module is based on server virtualisation and employs software to create multiple virtual machines on a single physical server allowing for a significant reduction in energy and hardware costs. The methods used in these three modules are systematically integrated to produce a more efficient consumption of electricity. This will allow for the computing system to minimise energy consumption without compromising computational power.

Interpretive modeling of tungsten divertor leakage during experiments with neon gas seeding

Many existing and future tokamaks with tungsten divertors operate, or will operate, with low-Z impurity seeding, but the direct effect of these seeded impurities on tungsten Scrape-off-Layer (SOL) transport has not been explored in detail. This paper reports on a DIII-D experiment designed to test how tungsten divertor leakage from the Small-Angle Slot V-Shaped, tungsten-coated divertor is impacted by neon seeding at a variety of injection rates and poloidal injection locations. Measurements from the experiment show an inverse relationship between the neon injection rate and the tungsten core penetration factor. Interpretive modeling is performed with a combination of the SOLPS-ITER and DIVIMP codes to assess the underlying tungsten behavior. The modeling results show that the reduction in tungsten divertor leakage is driven by both an increase in the divertor collisionality as well as a reduction in the ion temperature gradient near the divertor target. Collisions between low-Z impurities and tungsten impurities are found to have a significant impact on the tungsten SOL transport, such that ignoring the low-Z impurity collisional effects on the tungsten transport can result in an overestimate of the divertor leakage by an order-of-magnitude. Given the importance of these localized interactions, neon seeding from the closed, slot-like divertor has a clear advantage in being able to reduce tungsten divertor leakage without the high levels of neon core contamination that occur when seeding from other poloidal locations.

A comparative study on rotordynamics characteristics of hole-pattern damping seals with different cavity shapes

PurposeThe purpose of this paper is to improve the seal performance by proper design of the cavity shape of the damping holes, especially the rotordynamics characteristics of the hole-pattern damped seal (HPDS).Design/methodology/approachA new damping seal structure that comprises a circle-shaped cavity and two directional leaf-shaped cavities with a dovetail-shaped diversion groove is proposed. The comparative study on the sealing characteristics of dovetail-shape, leaf-shape and classical circular HPDSs was carried out using ANSYS CFX.FindingsThe dovetail-shaped HPDS significantly outperformed two other damping seal designs in leakage and rotordynamic performance. At a rotating speed of 7,500 rpm, it showed a 25% reduction in leakage, a 23% increase in average effective damping and a 119% increase in average effective stiffness. The cross-coupled stiffness Kxy shifted from positive to negative, reducing circumferential flow. The dovetail's inclined leaf-shaped grooves create a double vortex that slows jet velocity in the seal clearance and alters spiral flow direction, resulting in a uniform pressure distribution and enhanced rotor stability at low frequencies.Originality/valueThis study proposes a novel HPDS with dovetail-shaped diversion grooves. The seal can realize the simultaneous improvement of rotordynamics and leakage characteristics compared to the current seal structure.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0127/

3D criteria to improve real-time pressure control in water distribution network system architecture

ABSTRACT Real-time control (RTC) methods have been developed for over one decade to regulate service pressure and reduce leakage using pressure control valves in water distribution networks (WDN). The present study investigates control node selection frameworks and RTC system architecture for the field-oriented control of a rural WDN. The unique topology of the case-study area, the small size of the area, and high-pressure variety increased the considerations of the RTC system. A computer code was developed based on the method of characteristics for the hydraulic simulation of the network. The code could analyze unsteady flows through sloped pipes, implement pressure-based analysis, and regulate control valves based on the target node. Leakage reduction, pressure fluctuation reduction, and cavitation prevention were used as three criteria and constraints in the selection of control nodes. It was found that the optimal strategy would reduce the real water loss from 25 to 10%. Furthermore, key parameters in remote sensing were evaluated to minimize the number of sensors in order to further simplify the control algorithm and RTC system architecture through an artificial neural network (ANN) approach. The control function with a convergence rate of 99% was introduced.

Source/drain extension asymmetric counter-doping for suppressing channel leakage in stacked nanosheet transistors

In the relentless pursuit of semiconductor device scaling, stacked silicon nanosheet gate-all-around field-effect transistors (NSFETs) are emerging as key candidates for sub-3nm technology nodes. However, the challenge of channel leakage in these devices is critical and necessitates innovative solutions. A novel SDE asymmetric counter-doping technique is proposed in this study. It investigates the impact of source/drain extension on device performance using different process schemes through three-dimensional technical computer-aided design (3D TCAD) simulations. The simulations demonstrate a comprehensive technically advantages for 25.2 %/16.65 % reduction in the off-state leakage, 27.36 %/15.03 % improvement in the on-off current ratio of N/P NSFETs, respectively. Furthermore, it shows more performance gain as the gate length scaling beyond 3 nm technology nodes. The compatibility of the asymmetric counter-doping method with mainstream NSFET integration flows and its scalability to 10 nm gate lengths indicate that it is a promising approach to optimize NSFETs performance with little extra process cost.

Circuits implementations using carbon nanotube field-effect transistor nanotechnology

Device scaling is a pivotal aspect in the field of electronics, aimed at enhancing the performance of integrated circuits (ICs) by reducing the dimensions of transistors. The device scaling presents the short channel effects (SCEs) in the nanoscale regime. To address the SCEs, nanometer IC designers have turned to the carbon nanotube field-effect transistor (CNTFET) technology, which offers unique properties and mitigates the challenges associated with transistor scaling. In this research work, a leakage reduction technique known as the input-dependent (INDEP) method is suggested to tackle the leakage current issue at the nanoscale regime using CNTFET technology. The INDEP method involves the incorporation of two additional transistors within the logic circuit. To evaluate the efficacy of the INDEP method, a CNTFET-based 7-stage inverter chain is meticulously designed at 32 nm CNTFET technology node. Subsequent comparative analysis against alternative designs is conducted, assessing performance metrics such as power dissipation, delay, and power delay product (PDP). The suggested INDEP method reduces power dissipation by 83.75% and improves PDP by 78.44%. Furthermore, the study delves into the impact of process, voltage, and temperature (PVT) variations. Additionally, the investigation explores the influence of parameters such as the number of carbon nanotubes, temperature, supply voltage, and chiral indices on the performance of the 7-stage inverter chain. The simulation results demonstrate that the CNTFET-based INDEP technique yields promising outcomes, characterized by low power dissipation, precise output, and minimal uncertainty across all evaluated metrics.

Selenium Nanoparticles Boost the Drought Stress Response of Soybean by Enhancing Pigment Accumulation, Oxidative Stress Management and Ultrastructural Integrity

Drought is a persistent and devastating obstacle to crop production, affecting both humanity and livestock. The application of selenium (Se) effectively mitigates various types of abiotic stresses and enhances crop yield under unfavorable conditions. However, our understanding of how nano-Se (nSe) alleviates drought stress (DS) in soybeans is still limited. To address this gap, our study focused on assessing the effectiveness of foliar nSe application during the reproductive stage of soybeans. Three concentrations of nSe were applied to plants grown in pots filled with clay loam soil, simulating DS conditions. Our findings reveal that nSe spraying significantly promoted the accumulation of above-ground dry biomass and enhanced relative water content (RWC) and photosynthetic pigment over alone-DS treatment. Furthermore, nSe application boosted the activity and contents of protective enzymes and osmolytes, resulting in a dose-dependent reduction in electrolyte leakage (EL), reactive oxygen species (ROS) accumulation, and malondialdehyde (MDA) content. Additionally, nSe improved stomatal characteristics and mesophyll cell ultrastructure, further mitigating the adverse effects of drought stress. These findings suggest the potential of nSe as an effective strategy to enhance soybean tolerance and potentially improve crop yields under drought conditions.