Hybrid Strategy Research Articles

Breast tumor segmentation using neural cellular automata and shape guided segmentation in mammography images.

Using computer-aided design (CAD) systems, this research endeavors to enhance breast cancer segmentation by addressing data insufficiency and data complexity during model training. As perceived by computer vision models, the inherent symmetry and complexity of mammography images make segmentation difficult. The objective is to optimize the precision and effectiveness of medical imaging. The study introduces a hybrid strategy combining shape-guided segmentation (SGS) and M3D-neural cellular automata (M3D-NCA), resulting in improved computational efficiency and performance. The implementation of Shape-guided segmentation (SGS) during the initialization phase, coupled with the elimination of convolutional layers, enables the model to effectively reduce computation time. The research proposes a novel loss function that combines segmentation losses from both components for effective training. The robust technique provided aims to improve the accuracy and consistency of breast tumor segmentation, leading to significant improvements in medical imaging and breast cancer detection and treatment. This study enhances breast cancer segmentation in medical imaging using CAD systems. Combining shape-guided segmentation (SGS) and M3D-neural cellular automata (M3D-NCA) is a hybrid approach that improves performance and computational efficiency by dealing with complex data and not having enough training data. The approach also reduces computing time and improves training efficiency. The study aims to improve breast cancer detection and treatment methods in medical imaging technology.

A Novel Hybrid Deep-Learning Approach for Flood-Susceptibility Mapping

Flood-susceptibility mapping (FSM) is crucial for effective flood prediction and disaster prevention. Traditional methods of modeling flood vulnerability, such as the Analytical Hierarchy Process (AHP), require weights defined by experts, while machine-learning and deep-learning approaches require extensive datasets. Remote sensing is also limited by the availability of images and weather conditions. We propose a new hybrid strategy integrating deep learning with the HEC–HMS and HEC–RAS physical models to overcome these challenges. In this study, we introduce a Weighted Residual U-Net (W-Res-U-Net) model based on the target of the HEC–HMS and RAS physical simulation without disregarding ground truth points by using two loss functions simultaneously. The W-Res-U-Net was trained on eight sub-basins and tested on five others, demonstrating superior performance with a sensitivity of 71.16%, specificity of 91.14%, and area under the curve (AUC) of 92.95% when validated against physical simulations, as well as a sensitivity of 88.89%, specificity of 93.07%, and AUC of 95.87% when validated against ground truth points. Incorporating a “Sigmoid Focal Loss” function and a dual-loss function improved the realism and performance of the model, achieving higher sensitivity, specificity, and AUC than HEC–RAS alone. This hybrid approach significantly enhances the FSM model, especially with limited real-world data.

Physics-informed and data-driven hybrid method for transmission accuracy design optimization of planetary roller screw mechanism

The planetary roller screw mechanism (PRSM) faces an ever-increasing precision transmission demand in current advanced equipment. The relationship between machining errors and transmission accuracy remains elusive due to the over-simplified physical models and small-sample experimental datasets. This work proposes a physics-informed and data-driven hybrid strategy for PRSM transmission accuracy evaluation and tolerance optimization. In the physical model, a PRSM transmission accuracy model is developed to calculate transmission error that considers 16 machining errors in eccentric, nominal diameter, pitch, flank angle, and roller consistency. In the dataset establishment, thread profile measurements and dynamic leadscrew inspections are conducted for the machining error and transmission accuracy data acquisition. A data augmentation approach combining the physical model with the generative adversarial network is utilized to predict travel deviation, variations, and axial backlash and estimate machining error contribution with the small-sample experimental dataset. It is firstly found that the roller consistency of nominal diameter significantly affects PRSM travel variation V2π with a 17.3 % importance value. With the developed framework, the key tolerances for screw, roller, nut, and roller consistency are optimized toward a typical precision transmission requirement using the non-dominated sorting genetic algorithm. It also provides a tolerance grade recommendation table with PRSM transmission accuracy level in engineering practice.

2‐Chloroquinolinyl‐thiazolidine‐2,4‐dione Hybrids as Potential α‐Amylase Inhibitors: Synthesis, Biological Evaluations, and In Silico Studies

AbstractRecently, molecular hybridization strategy has paved a way to develop novel lead compounds for the α‐amylase targeted antidiabetic therapy. In this study, we disclosed a series of new hybrids of thiazolidine‐2,4‐diones with 2‐chloroquinoline‐3‐yl moiety as potential antidiabetic agents. The molecular structures of all the synthesized hybrids (15a–n) were confirmed by spectroscopic studies (FT‐IR, ESI‐MS, 1H, 13C NMR, and elemental analysis). When in vitro antidiabetic evaluation of these agents was carried out in a dose‐dependent manner, it was revealed that several compounds (15f–h, 15j, and 15n) were endowed with significant antidiabetic activities and exhibited more than 50% α‐amylase inhibition at a dose of 50 µg/mL. Particularly, hybrid 15n was found to be more potent than acarbose with 95% inhibition of α‐amylase and IC50 of 5.00 ± 0.18 µM under given conditions. Further, it was demonstrated that 15n bearing 2‐chloroquinolinyl and thiazolidin‐2,4‐dione scaffolds functionalized with 3‐OMe and 4‐OH groups was not only able to effectively bind with α‐amylase receptor site with best docking score (−9.644 kcal/mol) but also possessed drug‐likenesses properties with no violations of Lipinski rule. Overall, this study discovered new 2‐chloroquinolinyl‐thiazolidine‐2,4‐diones hybrids as novel α‐amylase inhibitors and compound 15n as promising lead for its further development as antidiabetic agent.

Future armed conflicts - A new point of view

This article focusses on future wars and the resulting consequences for the development of the armed forces. The purpose of this study is to indicate the course of future armed conflicts on the base of the forecasts presented by the largest research centres as well as to signal the need to look at them from a new point of view, disregarding the current tense situation in the world. The subjects of the research are armed conflicts, and above all, the possible ways of conducting them in the future, as well as the domains in which they will be fought. The authors assume that the causes and forms of future armed conflicts will evolve. Changes will depend on the time and place of the outbreak of conflicts, the technology used, as well as the scale of their play. It is also assumed that future armed conflicts will take place in all domains, between equal opponents or between great powers and smaller states or organizations, which are weaker to them in every respect. In the paper, the authors took an attempt to answer the following questions: How will the geopolitical and economic situation in the world change, also in the context of progressing climate change? How will armed conflicts evolve in a changing world? How will future wars play out and what capabilities should military forces have to fight them? According to the analysis, the authors claim that future armed conflicts will: take place in all domains; require a rapid situation assessment and decisions; conducted in a complex environment; include hybrid strategies; increasingly difficult to resolve; non-linear; took the form of asymmetric activities; periodically conducted without electronic devices (an opponent can disable devices or track them); implemented by modular units capable of conducting independent activities at the lowest levels; saturated with robots and drones.

Construction of heterogeneous MOF-on-MOF for highly efficient gaseous iodine sequestration under static conditions

Considering the unexpected nuclear power waste emission and potential nuclear leakage, the exploration of robust materials for the effective capture and storage of radioactive iodine is of great importance but still remains a challenge. In this work, we report the rational synthesis of functionalized NH2-UiO-66-on-ZIF-67 architecture to enhance the static adsorption and retention of volatile iodine. Such MOF-on-MOF heterostructures was fabricated through seeding ZIF-67 core on the surface of NH2-UiO-66 satellite via a facile polyvinylpyrrolidone (PVP) regulated internal extended growth strategies. NH2-UiO-66-on-ZIF-67 exhibited unique core-satellite structure, which significantly promotes the binding interactions with iodine through synergizing of the N-rich imidazole moieties and surface functionalized amino groups within the porosity channels. As a result, the as fabricated NH2-UiO-66-on-ZIF-67 achieves enhanced mass diffusion and high capture capacity of 3600 mg/g for iodine vapor under static sorption conditions. Moreover, water vapor in humid conditions (relative humidity of 18 %) has almost no effect on the static iodine adsorption performance of the material. This study sheds light on a reliable MOF-on-MOF hybrid strategy for effective radioiodine treatment to ensure the safety nuclear waste management.

Manganese Complex-Gold Nanoparticle Hybrid for Biofilm Inhibition and Eradication.

Biofilms, which are resistant to conventional antimicrobial treatments, pose significant challenges in medical and industrial environments. This study introduces manganese complex-gold nanoparticles (Mn-DPA-AuNPs) as a hybrid strategy for biofilm inhibition and eradication. Upon exposure to green light, these nanoparticles significantly enhance the generation of reactive oxygen species (ROS), including hydrogen peroxide and superoxide. This activity substantially reduces the regrowth potential of the surviving bacteria within the biofilm, with marked efficacy noted in Pseudomonas aeruginosa PAO1. This study highlights the potential of integrating manganese complexes with gold nanoparticles to develop advanced antimicrobial agents against resistant biofilms, offering a promising approach to enhance microbial control in diverse settings.

Design, synthesis and biological evaluation of dual inhibitors targeting AR/AR-Vs and PARP1 in castration resistant prostate cancer therapy

The combination of androgen signaling inhibitors and PARP inhibitors has shown promising results in clinical trials for the treatment of castration-resistant prostate cancer (CRPC). Multi-target inhibitors can inhibit tumors through different pathways, addressing the limitations of traditional single target inhibitors. We designed and synthesized dual inhibitors targeting AR/AR-Vs and PARP1 using a pharmacophore hybridization strategy. The most potent compound, II-3, inhibits AR/AR-Vs signaling and induces DNA damage by inhibiting PARP1. The IC50 values of II-3 in the castration-resistant prostate cancer cell lines 22RV1 and C4–2 are 4.38 ± 0.56 µM, and 3.44 ± 0.63 µM, respectively. II-3 not only suppresses the proliferation and migration of 22RV1 and C4–2 cells, but also promotes their apoptosis. Intraperitoneal injection of II-3 effectively inhibits tumor growth in 22RV1 xenograft nude mice without evident drug-induced toxicity. Overall, a series of novel dual inhibitors targeting AR/AR-Vs and PARP1 were designed and synthesized, and meanwhile the in vivo and in vitro effects were comprehensively explored, which provided a potential new therapeutic strategy for CRPC.

An active disturbance rejection stair-like generalized predictive control with time delay weakening for denitrification process in thermal power unit

The optimization control of the selective catalytic reduction (SCR) denitrification system holds significant importance in the production of the power generation industry. This paper presents an active disturbance rejection stair-like generalized predictive control with time delay weakening (WADRC-SGPC) to enhance the control performance in SCR denitrification system. Compared with classical generalized predictive control (GPC), active disturbance rejection generalized predictive control (ADRC-GPC) combines the advantages of ADRC, uses Extended State Observer (ESO) to compensate the uncertainty of the system, and regards the compensated system as a series integrator. Therefore, it has the advantages of no system identification and online calculation of Diophantine equation. In addition, a time delay weakening link is incorporated for the known part of the system model, which effectively improves the performance of the controller. The parameter selection issue of the weight function in time delay weakening is addressed using a hybrid strategy whale optimization algorithm. Finally, the superior performance of the proposed control strategy in terms of set-point tracking and disturbance rejection is verified through simulation experiments.

The Challenges of “Renewed” Enlargement to the Western Balkan Countries

In the last two decades, acting as an anchor for a transition to democracy and a market economy, the EU has given membership perspectives to the Western Balkan countries of Albania, Serbia, Bosnia and Herzegovina, North Macedonia, Montenegro, and Croatia. At the outset, the EU triggered democratic reforms, empowered civil society organisations, and established democratic rules in those countries. However, on Croatia’s joining the EU in 2013, the Union demonstrated what can be best described as apparent enlargement fatigue and took a break from the widening of Western Balkan countries for the five subsequent years. However, the Russian invasion of Ukraine in February 2022 revitalised the EU enlargement policy towards Western Balkan countries for security and geostrategic considerations. In that purview, this paper seeks to explore contextual constraints associated with the EU’s renewed enlargement policy towards Western Balkan countries. Using the conceptual framework of Alcaro and his co-authors (2022), it is argued that the EU renewed enlargement operates in a context driven by the following three key processes: (1) multi-actor geostrategic competition; (2) regional fragmentation; and (3) intra-EU contestation. In this context, considering international, regional, and institutional contextual constraints, the EU’s leverage on the Western Balkan countries would not be taken for granted, suggesting that the EU needs to develop hybrid strategies transcending classic tools of enlargement.

Энергоэффективность многоядерных процессоров: сравнительное исследование аппаратных технологий

Background: The constant increase in processing demand has prompted the development of multi-core processors, which are critical to obtaining high performance in a variety of computing devices. However, this growth in processing capacity comes at the expense of increased energy consumption, posing substantial problems for energy efficiency. Objective: The article will examine and compare several hardware solutions for improving energy efficiency in multi-core processors, offering a full overview of their effectiveness and application. Methods: We used a quantitative research methodology, simulating multi-core processing environments with various hardware optimization techniques such as Dynamic Voltage and Frequency Scaling (DVFS), Clock Gating, and Power Gating. Each technique was evaluated in a variety of operational circumstances to establish its effect on energy consumption and processing efficiency. Results: The findings show that DVFS provides significant energy savings with negligible performance trade-offs in cases with moderate workloads. In contrast, Clock Gating performed best in low workload settings, whereas Power Gating performed best in high-load conditions, dramatically reducing idle power consumption. Conclusion: The comparison research demonstrates that no single technique beats all others; rather, the choice of an effective energy efficiency strategy is significantly influenced by unique workload factors. A hybrid strategy, which combines both techniques depending on real-time workload demands, can greatly improve the energy efficiency of multi-core processors. This study advances our understanding of energy management in advanced computing systems, providing insights for future research and practical applications in the field of energy-efficient computing.

Waste polyethylene terephthalate-derived organic-inorganic hybrid materials as sustainable dual electrodes for Li-ion batteries

The hybrid Fe-Li2TP structure is constructed from waste polyethylene terephthalate (w-PET) derived dilithium terephthalate (Li2TP) and conventional Fe2O3 by hydrothermal reaction. It is being studied for both anode and cathode for LIBs. As an anode, it exhibits a reversible capacity of 505 mAh/g after 100th cycle at 1 C-rate with ∼100 % coulombic efficiency (CE). In addition, as a cathode, it shows highly reversible charge/discharge capacities of 107.50/107.52 mAh/g after the 100th cycle at 0.1 C-rate with 100 % CE. Further, in the cathodic studies via galvanostatic intermittent titration technique (GITT), the average lithium diffusion (DLi+) coefficients are calculated to be 2.96 × 10-10, 3.89 × 10−10 cm2 s−1 and the electrical (µ) mobilities to be 5.86 × 1011 m2 V−1 s−1, 1.12 × 1011 m2 V−1 s−1 for charge and discharge pulses, respectively. The combined nano-rod and nano-spherical morphologies reduce the diffusion length, and adding 10 % SWCNTs during electrode fabrication enhances the electronic conductivity. This organic–inorganic hybrid strategy of Fe-Li2TP strongly mitigates the electrode dissolution, reducing the structural strain and preventing electrolyte decomposition at higher voltage. Computational studies show an optimized Fe-Li2TP structure with a 2.7-fold lower band gap value (1.9040 eV) than the pristine Li2TP.

Hybrid group opportunistic maintenance strategy for offshore wind turbines considering maintenance resource allocation in harsh working environments

The intelligent maintenance of offshore wind turbines (OWTs) is vital for sustainable energy generation and utilization, as harsh working environments generally limit their application. As offshore wind farms expand into deeper waters, operational and maintenance costs continue to increase. Therefore, devising targeted maintenance strategies for offshore wind farms is crucial. Existing strategies often overlook the role of maintenance resources in controlling the operational and maintenance costs. To address this problem, this study proposes a hybrid group opportunistic maintenance strategy to implement resource allocation-based maintenance for OWTs under dynamic conditions. First, a failure rate model based on the life decline and system coupling is proposed to capture the evolution of failures in OWTs in harsh working environments, thereby enhancing the accuracy of fault maintenance. Subsequently, a hybrid linear and nonlinear deterioration model is proposed to identify the different deterioration trends owing to the various sensitivities of diverse components to harsh working environments, which enhances the precision of degradation maintenance. In addition, a maintenance resource allocation model is proposed to allocate resources in advance, thereby increasing resource utilization and reducing maintenance costs. A multi-objective optimization approach is proposed to maximize the mean maintenance level (MML) and minimize the per unit cycle expected maintenance cost rate (PECR) by considering harsh working environments. Finally, the nutcracker optimization algorithm is introduced into the maintenance model to generate the optimal solution in a multi-objective manner. The results show that the maintenance model is feasible and effective for practical adaptive maintenance applications of OWTs in harsh working environments in practical applications.

Fluorinated ionic liquid mediated nanostructure with enhanced conductivity and fluorine retention in Na3V2(PO4)2F3 cathode toward high-performance sodium-ion batteries

Na3V2(PO4)2F3 (NVPF) is considering as a promising cathode material for sodium-ion batteries (SIBs), due to its framework robustness and high working voltage. For NVPF cathodes, the main obstacle of poor conductivity could be well-addressed by carbon hybridization or nano-crystallization strategies. However, carbon compositing process would bring up fluorine-loss issue and the designation of tailor-made nanocomposite remains challenging. Here, we realize the optimal regulation on crystal growth by virtue of a fluorinated ionic liquid usage, which could compensate the fluorine-loss during high-temperature annealing process. As a structural-directing agent, ionic liquid with low surface tension also helps to reduce surficial Gibbs free energy of NVPF crystal, facilitating to reduce the particle size. Meanwhile, the π-cation interaction between reduced graphene oxide (rGO) and cations of ionic liquid is beneficial to fabricate ultrathin rGO-wrapped NVPF nanoplates (I-NVPF@rGO). The tailored I-NVPF@rGO exhibits enhanced conductivity and optimized crystal planes, resulting in excellent rate capability and improved energy density. When coupling with MoS2/SnS/rGO anode, the MoS2/SnS/rGO||I-NVPF@rGO full battery delivers a capacity of 116 mA h g−1 at 0.2 C. This strategy offers valuable insights into the development of sodium-ion batteries.

Programmable soft DNA hydrogels stimulate cellular endocytic pathways and proliferation

Hydrogels are pivotal in tissue engineering, regenerative medicine, and drug delivery applications. Existing hydrogel platforms are not easily customizable and often lack precise programmability, making them less suited for 3D tissue culture and programming of cells. DNA molecules stand out among other promising biomaterials due to their unparalleled precision, programmability, and customization. In this study, we introduced a palette of novel cellular scaffolding platforms made of pure DNA-based hydrogel systems while improving the shortcomings of the existing platforms. We showed a quick and easy one step synthesis of DNA hydrogels using thermal annealing based on sequence specific hybridization strategy. We also demonstrated the formation of multi-armed branched supramolecular scaffolds with custom mechanical stiffness, porosity, and network density by increasing or decreasing the number of branching arms. These mechanically tuneable DNA hydrogels proved to be a suitable suitable platform for modulating the physiological processes of retinal pigment epithelial cells (RPE1). In-vitro studies showed dynamic changes at multiple levels, ranging from a change in morphology to protein expression patterns, enhanced membrane traffic, and proliferation. The soft DNA hydrogels explored here are mechanically compliant and pliable, thus excellently suited for applications in cellular programming and reprogramming. This research lays the groundwork for developing a DNA hydrogel system with a higher dynamic range of stiffness, which will open exciting avenues for tissue engineering and beyond.

4d-2p-4f Gradient Orbital Coupling Enables Tandem Catalysis for Simultaneous Abatement of N2O and CO on Atomically Dispersed Rh/CeO2 Catalyst.

N2O and CO coexist in various industrial and mobile sources. The synergistic reaction of N2O and CO to generate N2 and CO2 has garnered significant research interest, but it remains extremely challenging. Herein, we constructed an atomically dispersed Rh-supported CeO2 catalyst with asymmetric Rh-O-Ce sites through gradient Rh 4d-O 2p-Ce 4f orbital coupling. This design effectively regulates the 4f electron states of Ce and promotes the electron filling of the O 3π* antibonding orbital to facilitate N-O bond cleavage. Near-ambient-pressure X-ray photoelectron spectroscopy (NAP-XPS) reveals that CO reacts with the surface-adsorbed O* generated by N2O decomposition through self-tandem catalysis, accelerating the rate-limiting step in N2O decomposition and activating the synergistic reaction of N2O and CO at temperatures as low as 115 °C. This work can guide the development of high-performance catalysts using the strategy of high-order orbital hybridization combined with the tandem concept to achieve versatile catalytic applications.

Experimental investigation of hybrid energy sharing strategy for multi-source electric vehicle

This paper deals with a current topic addressing the issue of energy management. Adequate energy management consists of finding the best harmony between different sources intended to supply the vehicle to satisfy the power required by the traction motor while ensuring good performances. Energy management strategy makes it possible to find the adequate distribution of the energy flow between power source elements by generating power references to be given by each source to satisfy the required power while respecting the constraints on these sources. In this context, a new energy management strategy based on the combination of flatness theory and the frequency separation principle is developed. This strategy determines the powers that the energy sources must supply and provides power source references based on their dynamics, imposing constraints to be taken into account. This novel hybrid strategy is applied to a hybrid vehicle configuration that uses a fuel cell as the primary source with a hybrid storage device (supercapacitor and battery). The implementation using dSPACE DS1005 will be presented to demonstrate the effectiveness of the proposed strategy.

Curved-crease origami hybrid structures with tailorable buckling and energy absorption

Origami-inspired structures (OIS), renowned for their lightweight design, encounter energy absorption challenges attributed to global buckling. This paper presents a design and hybridization strategy that integrates origami-inspired structures with existing state-of-the-art cellular lattices to create origami-inspired hybrid structures (OIHS), aimed at addressing buckling concerns and customizing the crushing behavior of thin-walled structures. The investigation explores the compressive response of additively-manufactured curved crease OIS and prismatic structures (PS) with diverse cross-sections, including circular origami structure (COS), triangular origami structure (TOS), square origami structure (SOS), and hexagon origami structure (HOS). The experimental results indicate that the COS design offered the highest specific energy absorption (SEA) of 11 kJ/kg, due to controlled deformation associated with the crease lines. The COS hybridized structure, with cellular lattices, exhibited a yielding-dominated behavior, resulting in a lower peak force, a sustained plateau force and a well-controlled deformation response. Furthermore, the COS hybridized with a plate lattice, exceeded the SEA of the auxetic and BCC OIHS structures by 62 % and 71 %, respectively. The circular origami plate hybrid (COPH) design was selected to investigate the effect of varying the top edge angle (α) and the relative density on the mechanical properties and the SEA. It was found that increasing the value of alpha resulted in a higher peak stress and an increased buckling load. Moreover, with its higher relative density, the vertical plate within the OIS contributed to a greater level of structural stability in the plateau region, resulting in an increase in mechanical properties and SEA. These findings advance the understanding of OIS by presenting effective hybridization strategies to mitigate buckling and achieve stable plateau stresses and higher crushing force efficiencies, particularly at lower relative densities, surpassing those reported in the literature. This contributes significantly to the broader field of lightweight structural design.

Characterization of genetic diversity in Eragrostis tef (zucc.) Trotter through microsatellite and morphological markers

Eragrostis tef (Zucc.) Trotter is Ethiopia's most significantly important grain crop; however, its productivity is quite low (1.7 tons per hectare) due to a variety of issues, including the poor yield potential of varieties produced thus far. To achieve future production improvements in tef, comprehensive study of the crop's genetic variability and variety, utilizing both genetic and morphological markers, necessary. The study was designed to assess the genetic diversity of 64 tef genotypes utilizing 10 Simple Sequence Repeats (SSRs) markers. This investigation took place at the Agricultural Biotechnology Research Center in Holeta, Ethiopia. Field phenotypic diversity evaluation was conducted at two distinct locations: Debre Zeit and Worabe, applied a simple lattice design during 2020/21 season. Molecular analysis of variance demonstrated a substantial proportion of variation among individuals (46 %), followed closely variation among individuals (43 %), with the least variation observed within population (11 %). Concurrently, analysis of morphological data, encompassing twenty phenotypic characteristics, revealed significant variation (P ≤ 0.01) among almost all the tested genotypes for recorded parameters, as indicated by combined analysis of variance across sites. These findings underscore the high diversity among the studied genotypes, suggesting a considerable potential for crop improvement through direct selection and intra-specific hybridization strategies. From the perspectives of both conservation and utilization of tef genetic materials, there is a pressing need for more extensive and systematic molecular level research. Promoting field trials and genotype-by-environment interaction research is crucial. These efforts will enhance our understanding of tef genetic and contribute to its effective conservation and utilization.

Discovery of Novel Nonpeptidic Proteasome Inhibitors Using Covalent Virtual Screening and Biological Evaluation.

Many reported proteasome inhibitors, including the three clinically approved inhibitors, bortezomib, carfilzomib, and ixazomib, have peptidic structures. In this study, using a hybrid and versatile strategy for covalent virtual screening by combining warhead screening and preprocessing with GOLD and CovDock software that were applied to the ZINC virtual library, we identified multiple proteasome inhibitors with new nonpeptidic structural scaffolds. Proteasome inhibition assays confirmed the inhibitory activities of these new compounds. These results demonstrate the effectiveness of our computational strategy for large-scale covalent virtual screening. Furthermore, these identified proteasome inhibitors may serve as starting points for the development of a new class of nonpeptidic therapeutic agents.