Since SARS-CoV-2 is a highly transmissible virus, alternative reliable, fast, and cost-effective methods are still needed to prevent virus spread that can be applied in the laboratory and for point-of-care testing. Reverse transcription real-time fluorescence quantitative PCR (RT-qPCR) is currently the gold criteria for detecting RNA viruses, which requires reverse transcriptase to reverse transcribe viral RNA into cDNA, and fluorescence quantitative PCR detection was subsequently performed. The frequently used reverse transcriptase is thermolabile; the detection process is composed of two steps: the reverse transcription reaction at a relatively low temperature, and the qPCR performed at a relatively high temperature, moreover, the RNA to be detected needs to pretreated if they had advanced structure. Here, we develop a fast and sensitive one-tube SARS-CoV-2 detection platform based on Ultra-fast RTX-PCR and Pyrococcus furiosus Argonaute-mediated Nucleic acid Detection (PAND) technology (URPAND). URPAND was achieved ultra-fast RTX-PCR process based on a thermostable RTX (exo-) with both reverse transcriptase and DNA polymerase activity. The URPAND can be completed RT-PCR and PAND to detect nucleic acid in one tube within 30 min. This method can specifically detect SARS-CoV-2 with a low detection limit of 100 copies/mL. The diagnostic results of clinical samples with one-tube URPAND displayed 100% consistence with RT-qPCR test. Moreover, URPAND was also applied to identify SARS-CoV-2 D614G mutant due to its single-nucleotide specificity. The URPAND platform is rapid, accurate, tube closed, one-tube, easy-to-operate and free of large instruments, which provides a new strategy to the detection of SARS-CoV-2 and other RNA viruses. Full article

During robot-assisted rehabilitation, failure to recognize lower limb movement may efficiently limit the development of exoskeleton robots, especially for individuals with knee pathology. A major challenge encountered with surface electromyography (sEMG) signals generated by lower limb movements is variability between subjects, such as motion patterns and muscle structure. To this end, this paper proposes an sEMG-based lower limb motion recognition using an improved support vector machine (SVM). Firstly, non-negative matrix factorization (NMF) is leveraged to analyze muscle synergy for multi-channel sEMG signals. Secondly, the multi-nonlinear sEMG features are extracted, which reflect the complexity of muscle status change during various lower limb movements. The Fisher discriminant function method is utilized to perform feature selection and reduce feature dimension. Then, a hybrid genetic algorithm-particle swarm optimization (GA-PSO) method is leveraged to determine the best parameters for SVM. Finally, the experiments are carried out to distinguish 11 healthy and 11 knee pathological subjects by performing three different lower limb movements. Results demonstrate the effectiveness and feasibility of the proposed approach in three different lower limb movements with an average accuracy of 96.03% in healthy subjects and 93.65% in knee pathological subjects, respectively. Full article

The present study aimed to investigate the chemical content of Romanian juneberries (Amelanchier lamarckii), their effect on antioxidant and enzyme inhibition activities, and their bioaccessibility after simulated in-vitro digestion. In Amelanchier lamarckii extract (AME), 16 polyphenolic compounds were identified by LC-ESI+-MS analysis. The most representative compounds found in the extract were cyanidin-galactoside, 3,4-dihydroxy-5-methoxybenzoic acid, feruloylquinic acid, and kaempferol, all belonging to the anthocyanins, phenolic acids, and flavonols subclasses. The polyphenols of AME exert quenching abilities of harmful reactive oxygen species, as the CUPRAC antioxidant assay value was 323.99 µmol Trolox/g fruit (FW), whereas the FRAP antioxidant value was 4.10 μmol Fe²⁺/g fruit (FW). Enzyme inhibition assays targeting tyrosinase (IC50 = 8.843 mg/mL), α-glucosidase (IC50 = 14.03 mg/mL), and acetylcholinesterase (IC50 = 49.55 mg/mL) were used for a screening of AME’s inhibitory potential against these key enzymes as a common approach for the discovery of potential antidiabetic, skin pigmentation, and neurodegenerative effects. The screening for the potential antidiabetic effects due to the α-glucosidase inhibition was performed in glucose-induced disease conditions in a human retinal pigmented epithelial cell experimental model, proving that AME could have protective potential. In conclusion, AME is a valuable source of phenolic compounds with promising antioxidant potential and metabolic disease-protective effects, warranting further investigation for its use in the nutraceutical and health industries. Full article

In order to increase the utilization rate of stainless steel slag, reduce storage needs, and mitigate environmental impacts, this study replaces a portion of limestone with varying amounts of stainless steel slag in the calcination of Portland cement clinker. The study primarily examines the influence of stainless steel slag on the phase composition, microstructure, compressive strength, and free calcium oxide (ƒ-CaO) content of Portland cement clinker. The results show the following: (1) Using stainless steel slag to calcine Portland cement clinker can lower the calcination temperature, reducing industrial production costs and energy consumption. (2) With an increase in the amount of stainless steel slag, the dicalcium silicate (C₂S) and tricalcium silicate (C₃S) phases in Portland cement clinker initially increase and then decrease; the C₃S crystals gradually transform into continuous hexagonal plate-shaped distributions, while the tricalcium aluminate (C₃A) and tetracalcium aluminoferrite (C₄AF) crystal structures become denser. When the stainless steel slag content is 15%, the dicalcium silicate and tricalcium silicate phases are at their peak; the C₃S crystals are continuously distributed with a relatively dense structure, and C₃A and C₄AF crystals melt and sinter together, becoming distributed around C₃S. (3) As stainless steel slag content increases, the compressive strength of Portland cement clinker at 3 days, 7 days, and 28 days increases and then decreases, while ƒ-CaO content decreases and then increases. When the stainless steel slag content is 15%, the compressive strength at 28 days is at its highest, 64.4 MPa, with the lowest ƒ-CaO content, 0.78%. The test results provide a basis for the utilization of stainless steel slag in the calcination of Portland cement clinker. Full article

Particle Swarm Optimization (PSO) algorithms within control structures are a realistic approach; their task is often to predict the optimal control values working with a process model (PM). Owing to numerous numerical integrations of the PM, there is a big computational effort that leads to a large controller execution time. The main motivation of this work is to decrease the computational effort and, consequently, the controller execution time. This paper proposes to replace the PSO predictor with a machine learning model that has “learned” the quasi-optimal behavior of the couple (PSO and PM); the training data are obtained through closed-loop simulations over the control horizon. The new controller should preserve the process’s quasi-optimal control. In identical conditions, the process evolutions must also be quasi-optimal. The multiple linear regression and the regression neural networks were considered the predicting models. This paper first proposes algorithms for collecting and aggregating data sets for the learning process. Algorithms for constructing the machine learning models and implementing the controllers and closed-loop simulations are also proposed. The simulations prove that the two machine learning predictors have learned the PSO predictor’s behavior, such that the process evolves almost identically. The resulting controllers’ execution time have decreased hundreds of times while keeping their optimality; the performance index has even slightly increased. Full article

Alcohol consumption, associated with various cancers, mental disorders, and aggressive behavior, leads to three million deaths globally each year. In Brazil, the alcohol per capita consumption among drinkers aged 15 and over is 41.7 g of pure alcohol/day (~1 L beer/day), which falls into the risky consumption category and exceeds the global average by almost 30%. An effective way to mitigate alcohol-related harm is to increase its retail price. This study assesses the costs of consuming leading brands of beer and sugarcane spirit cachaça (Brazil’s most popular alcoholic beverages) against the expenditure on staple foods. Data on food and alcoholic beverage prices were collected in João Pessoa, Brazil, for 2020 and 2021. The cost per gram of pure alcohol and food were considered to establish consumption patterns of 16.8 g/day (moderate), 41.7 g/day, and 83.4 g/day (heavy), distributed in three scenarios involving the beverages alone or combined (64% beer and 36% cachaça), and a balanced 2000 kcal/day staple diet. The study finds that all heavy consumption scenarios cost less or significantly less (cachaça alone) than a 2000 kcal/day staple diet, highlighting an urgent need for fiscal policies, such as a minimum unit pricing for alcohol, to address public health concerns. Full article

 In the realm of accelerated testing within controlled laboratory settings, the fidelity of the service environment assumes paramount importance. It is imperative to replicate real-world conditions while compressing the testing duration to facilitate early evaluations, thereby optimizing time and cost efficiencies. Traditional immersion protocols, reflective solely of full ballast tank conditions, inadequately expedite the corrosion process representative of an average ballast tank environment. Through the integration of immersion with fog/dry conditions, aligning the test protocol more closely with the internal conditions of an average ballast tank, heightened rates of general corrosion are achieved. This augmentation yields an acceleration factor of 7.82 times the standard test duration, under the assumption of a general corrosion rate of 0.4 mm/year for uncoated ballast tank steel, with both sides exposed. Subsequently, the fog/dry test protocol, albeit only resembling the environment of an empty ballast tank, closely trails in terms of acceleration efficacy. The fog/dry test protocol offers cost-effectiveness and replicability compared to the AMACORT CIFD-01 protocol, making it a strong competitor despite the relatively close acceleration factor. Full article

Knee osteoarthritis is the most prevalent type of osteoarthritis. Patients frequently encounter pain triggered by movement that evolves into impaired joint function. Needing persistent rest or having night-time pain signifies advanced disease. Qualitative research is considered the most effective method for comprehending patients’ needs and contexts. Methods: This study employed a qualitative research design, allowing the researchers to acquire insights into the patients’ beliefs and values, and the contextual factors influencing the formation and expression of these beliefs and values. Results: A cohort of nine patients awaiting total knee replacement (TKR) surgery was included and they were interviewed until data saturation was achieved. The results of the phenomenological analysis resulted in the identification of three themes: “The existence of pain impedes the capacity to participate in daily life activities”; “TKR induced fears and uncertainties regarding the progression of the disease”; “Severe nighttime pain compromising sleep quality”. Conclusions: This study analyzes the experiences of people awaiting TKR surgery, emphasizing the importance of addressing their unique needs to improve preoperative education and rehabilitation. In this way, patients’ recovery during the postoperative phase can be improved. Full article

In synthetic aperture radar (SAR) signal processing, compared with the raw data of level-0, level-1 SAR images are more readily accessible and available in larger quantities. However, an amount of level-1 images are affected by radio frequency interference (RFI), which typically originates from Linear Frequency Modulation (LFM) signals emitted by ground-based radars. Existing research on interference suppression in level-1 data has primarily focused on two methods: transforming SAR images into simulated echo data for interference suppression, or focusing interference in the frequency domain and applying notching filters to reduce interference energy. However, these methods overlook the effective utilization of the interference parameters or are confined to suppressing only one type of LFM interference at a time. In certain SAR images, multiple types of LFM interference manifest bright radiation artifacts that exhibit varying lengths along the range direction while remaining constant in the azimuth direction. It is necessary to suppress multiple LFM interference on SAR images when original echo data are unavailable. This article proposes a joint sparse recovery algorithm for interference suppression in the SAR image domain. In the SAR image domain, two-dimensional LFM interference typically exhibits differences in parameters such as frequency modulation rate and pulse width in the range direction, while maintaining consistency in the azimuth direction. Based on this observation, this article constructs a series of focusing operators for LFM interference in SAR images. These operators enable the sparse representation of dispersed LFM interference. Subsequently, an optimization model is developed that can effectively suppress multi-LFM interference and reduce image loss with the assistance of a regularization term in the image domain. Simulation experiments conducted in various scenarios validate the superior performance of the proposed method. Full article

Previous studies have shown that boletes are abundant and diverse in China, especially in tropical and subtropical regions. In the present study, morphological, ecological, host relationship, and a four-locus (28S, tef1, rpb1, and rpb2) molecular phylogenetic analyses were used to study the family Boletaceae in subtropical and tropical China. Four new bluing species are described from three genera, viz. Boletellus verruculosus (Chinese name疣柄条孢牛肝菌), Xerocomellus tenuis (Chinese name细柄红绒盖牛肝菌), Xer. brunneus (Chinese name褐盖红绒盖牛肝菌), and Xerocomus zhangii (Chinese name张氏绒盖牛肝菌). Moreover, the genus Nigroboletus is treated as a synonym of Xerocomellus, and a new combination, namely Xer. roseonigrescens (Chinese name玫瑰红绒盖牛肝菌), is proposed. Full article

The backfill area of tunnel projects may deform or collapse due to the cyclic disturbance of groundwater and train loads. Hence, the anti-deformation and crack resistance performance of backfill materials under cyclic disturbance is critical to engineering safety. In this paper, concrete was produced by mixing 0.85 mm, 1–3 mm and 3–6 mm rubber particles instead of 10% sand, and tested to discuss the effect of rubber particle size on the deterioration of concrete material properties (compressive characteristics and energy dissipation) after bearing cyclic loading. The stress–strain curve and various parameters obtained through the uniaxial compression test and cyclic load test were used to explore the optimal grain size that can be applied to the tunnel engineering backfill area, and numerical simulation was adopted to calculate the deformation of the surrounding rock and the structural stress of different backfill materials. Research shows that the increase in particle size lessens the compressive strength, deformation resistance and cracking resistance of specimens, but after the cyclic loading test, the concrete material deterioration analysis indicates that rubber concrete has lesser and more stable losses compared to ordinary concrete, so the optimum rubber particle size is 0.85 mm. Numerical calculations show that RC-1 reduces the arch top displacement by 0.4 mm, increases the arch bottom displacement by 0.6 mm and increases the maximum principal stress by 11.5% compared to OC. Therefore, rubber concrete can ensure the strength and stability requirements of tunnel structures, which can provide a reference for similar projects. Full article

Blue space interventions evidently have a positive impact on well-being and mental health, yet longitudinal studies on the lasting impact of such interventions are scarce. In this qualitative follow-up study with semi-structured interviews, we explored the long-term experiences over 18–42 months among six out of the initial eight women from the primary study, also including two instructors from the initial study. The participants, dealing with mental disorders, participated in the group-based intervention Freedom on Water, participating in stand-up paddling. Five main themes emerged from the empirical analysis: SUP as a catalyst for broadening horizons; learning: stepping out of the comfort zone; a break from diagnosis and rumination; connectedness to nature, specifically blue nature, and to the group; a life-changing journey; and a shift in mindset. The study revealed a long-term, life-changing impact of the program on participants’ well-being and mental health. Nature and blue space activities had become a greater part of their lives, improving their mental health with feelings of calmness, positivity, healing, and freedom. Stepping out of their comfort zone facilitated experiences of success and transformed their mindsets. Moreover, they experienced a break from rumination, and they became more outwardly focused, with confidence in themselves and their abilities, while making new friendships and engaging in new and different contexts. Full article

An essential component of autonomous transportation system management and decision-making is precise and real-time traffic flow forecast. Predicting future traffic conditionsis a difficult undertaking because of the intricate spatio-temporal relationships involved. Existing techniques often employ separate modules to model spatio-temporal features independently, thereby neglecting the temporally and spatially heterogeneous features among nodes. Simultaneously, many existing methods overlook the long-term relationships included in traffic data, subsequently impacting prediction accuracy. We introduce a novel method to traffic flow forecasting based on the combination of the feature-augmented down-sampling dynamic graph convolutional network and multi-head attention mechanism. Our method presents a feature augmentation mechanism to integrate traffic data features at different scales. The subsampled convolutional network enhances information interaction in spatio-temporal data, and the dynamic graph convolutional network utilizes the generated graph structure to better simulate the dynamic relationships between nodes, enhancing the model’s capacity for capturing spatial heterogeneity. Through the feature-enhanced subsampled dynamic graph convolutional network, the model can simultaneously capture spatio-temporal dependencies, and coupled with the process of multi-head temporal attention, it achieves long-term traffic flow forecasting. The findings demonstrate that the ADDGCN model demonstrates superior prediction capabilities on two real datasets (PEMS04 and PEMS08). Notably, for the PEMS04 dataset, compared to the best baseline, the performance of ADDGCN is improved by 2.46% in MAE and 2.90% in RMSE; for the PEMS08 dataset, compared to the best baseline, the ADDGCN performance is improved by 1.50% in RMSE, 3.46% in MAE, and 0.21% in MAPE, indicating our method’s superior performance. Full article

Huntington’s disease (HD) arises from expanded CAG repeats in exon 1 of the Huntingtin (HTT) gene. The resultant misfolded HTT protein accumulates within neuronal cells, negatively impacting their function and survival. Ultimately, HTT accumulation results in cell death, causing the development of HD. A nonhuman primate (NHP) HD model would provide important insight into disease development and the generation of novel therapies due to their genetic and physiological similarity to humans. For this purpose, we tested CRISPR/Cas9 and a single-stranded DNA (ssDNA) containing expanded CAG repeats in introducing an expanded CAG repeat into the HTT gene in rhesus macaque embryos. Analyses were conducted on arrested embryos and trophectoderm (TE) cells biopsied from blastocysts to assess the insertion of the ssDNA into the HTT gene. Genotyping results demonstrated that 15% of the embryos carried an expanded CAG repeat. The integration of an expanded CAG repeat region was successfully identified in five blastocysts, which were cryopreserved for NHP HD animal production. Some off-target events were observed in biopsies from the cryopreserved blastocysts. NHP embryos were successfully produced, which will help to establish an NHP HD model and, ultimately, may serve as a vital tool for better understanding HD’s pathology and developing novel treatments. Full article

The built environment’s impact on human activities has been a hot issue in urban research. Compared to motorized spaces, the built environment of pedestrian and cycling street spaces dramatically influences people’s travel experience and travel mode choice. The streets’ built environment data play a vital role in urban design and management. However, the multi-source, heterogeneous, and massive data acquisition methods and tools for the built environment have become obstacles for urban design and management. To better realize the data acquisition and for deeper understanding of the urban built environment, this study develops a new portable, low-cost Arduino-based multi-sensor array integrated into a single portable unit for built environment measurements of street cycling spaces. The system consists of five sensors and an Arduino Mega board, aimed at measuring the characteristics of the street cycling space. It takes air quality, human sensation, road quality, and greenery as the detection objects. An integrated particulate matter laser sensor, a light intensity sensor, a temperature and humidity sensor, noise sensors, and an 8K panoramic camera are used for multi-source data acquisition in the street. The device has a mobile power supply display and a secure digital card to improve its portability. The study took Beijing as a sample case. A total of 127.97 G of video data and 4794 Kb of txt records were acquired in 36 working hours using the street built environment data acquisition device. The efficiency rose to 8474.21% compared to last year. As an alternative to conventional hardware used for this similar purpose, the device avoids the need to carry multiple types and models of sensing devices, making it possible to target multi-sensor data-based street built environment research. Second, the device’s power and storage capabilities make it portable, independent, and scalable, accelerating self-motivated development. Third, it dramatically reduces the cost. The device provides a methodological and technological basis for conceptualizing new research scenarios and potential applications. Full article

Mass-impregnated (MI) cables have been used for many years as cables in high-voltage direct current (HVDC) systems. In line commutated converter (LCC) HVDC systems, polarity reversal for power flow control can induce significant electrical stress on MI cables. Furthermore, the mass oil and kraft paper comprising the impregnated insulation have significantly different coefficients of thermal expansion. Load fluctuations in the cable lead to expansion and contraction of the mass, creating pressure within the insulation and causing redistribution of the impregnant. During this process, shrinkage cavities can form within the butt gaps. Since the dielectric strength of the cavities is lower than that of the surrounding impregnation, cavitation phenomena in impregnated paper insulation are considered a factor in degrading insulation performance. Consequently, this study analyzes the electrical conductivity of thermally aged materials and investigates the transient electric field characteristics within the cable. Additionally, it closely analyzes the formation and dissolution of cavities in MI cables during polarity reversal based on a numerical model of pressure behavior in porous media. The conductivity of the impregnated paper indicates that it has excellent resistance to thermal degradation. Simulation results for various load conditions highlight that the interval of load-off time and the magnitude of internal pressure significantly influence the cavitation phenomenon. Lastly, the study proposes stable system operation methods to prevent cavitation in MI cables. Full article

Particular matter (PM) constitutes one of the major air pollutants. Human exposure to fine PM (PM with a median diameter less than or equal to 2.5 μm, PM_2.5) has many negative and diverse outcomes for human health, such as respiratory mortality, lung cancer, etc. Accurate air-quality forecasting on a regional scale enables local agencies to design and apply appropriate policies (e.g., meet specific emissions limitations) to tackle the problem of air pollution. Under this framework, low-cost sensors have recently emerged as a valuable tool, facilitating the spatiotemporal monitoring of air pollution on a local scale. In this study, we present a deep learning approach (long short-term memory, LSTM) to forecast the intra-day air pollution exceedances across urban and suburban areas. The PM_2.5 data used in this study were collected from 12 well-calibrated low-cost sensors (Purple Air) located in the greater area of the Municipality of Thermi in Thessaloniki, Greece. The LSTM-based methodology implements PM_2.5 data as well as auxiliary data, meteorological variables from the Copernicus Atmosphere Monitoring Service (CAMS), which is operated by ECMWF, and time variables related to local emissions to enhance the air pollution forecasting performance. The accuracy of the model forecasts reported adequate results, revealing a correlation coefficient between the measured PM_2.5 and the LSTM forecast data ranging between 0.67 and 0.94 for all time horizons, with a decreasing trend as the time horizon increases. Regarding air pollution exceedances, the LSTM forecasting system can correctly capture more than 70.0% of the air pollution exceedance events in the study region. The latter findings highlight the model’s capabilities to correctly detect possible WHO threshold exceedances and provide valuable information regarding local air quality. Full article

The utilization of phase change materials (PCMs) in solar water heating systems (SWHS) has undergone notable advancements, driven by a rising demand for systems delivering superior performance and efficiency. Extensive research suggests that enhancing heat transfer (HTE) in storage systems is crucial for achieving these improvements. This review employs a bibliometric analysis to track the evolution of HTE methods within this field. While current literature underscores the necessity for further exploration into hot water generation applications, several methodologies exhibit significant promise. Particularly, strategies such as fins, encapsulation, and porous media emerge as prominent HTE techniques, alongside nanofluids, which hold the potential for augmenting solar water heating systems. This review also identifies numerous unexplored techniques awaiting investigation, aiming to pave new paths in research and application within the field of hot water generation. It highlights methods that could be used independently or alongside predominantly used techniques. Full article

This study empirically analyzes how the Hallyu (Korean Wave) phenomenon affects Korea’s consumer goods exports to China using Chinese provincial-level panel data covering the period from 2011 to 2020. This paper adopts Baidu Index big data with the keywords “Korean drama”, “Korean movie”, “Korean music”, and “Korean entertainment” as proxy variables for Hallyu. The paper investigates the impact of Hallyu on Korean consumer goods exports by subdividing consumer goods into seven processing steps. In addition to the effect of the composite Hallyu index, the effect of each Hallyu content is also examined. Moreover, this study also investigates the impact of the political issue of the deployment of the THAAD American anti-ballistic missile defense system by dividing the period from 2011 to 2020 into before and after 2016. An export equation that includes income level, the Hallyu index, as well as other variables recognized as factors affecting Korea’s exports in existing studies, is used. Several interesting conclusions have been reached. First, Hallyu in China has a significant impact on Korea’s exports of non-durable consumer goods and processed household food and beverages to China. Second, the political issue of the deployment of THAAD has a negative impact on Korea’s exports of consumer goods to China. Third, among the four types of Hallyu content, dramas, as the most popular content in China, have the greatest influence on Korea’s exports of consumer goods to China. Full article

Evaluating and selecting appropriate contractors is critical to the success of specific construction projects in the building industry. Existing approaches for addressing this problem are unsatisfactory due to the ignorance of the multi-dimensional nature of the evaluation process and inappropriate consideration of existent risks. This study presents a DEA game cross-efficiency model with loss aversion for evaluating and selecting specific contractors. The competitiveness of the evaluation process is modeled using game theory with respect to the adoption of the cross-efficiency model. The attitude of the decision maker toward risks is tackled with the use of loss aversion, which is a phenomenon formalized in prospect theory. As a result, the proposed approach can adequately screen available contractors through prequalification and adequately consider the attitude of the decision maker toward risks, leading to effective decisions being made. An example is presented to demonstrate the applicability of the proposed model in evaluating and selecting appropriate contractors for specific construction projects. The results show that the proposed model is effective and efficient in producing a unique solution for contractor selection through appropriate modeling of the multi-dimensional contractor selection process and adequate consideration of the competition between the contractors and the attitude of the decision maker toward risks in practical situations. Full article

Phytophthora infestans (Mont.) de Bary, the oomycotic pathogen responsible for potato late blight, is the most devastating disease of potato production. The primary pesticides used to control oomycosis are phenyl amide fungicides, which cause environmental pollution and toxic residues harmful to both human and animal health. To address this, an antimicrobial peptide, NoPv1, has been screened to target Plasmopara viticola cellulose synthase 2 (PvCesA2) to inhibit the growth of Phytophthora infestans (P. infestans). In this study, we employed AlphaFold2 to predict the three-dimensional structure of PvCesA2 along with NoPv peptides. Subsequently, utilizing computational methods, we dissected the interaction mechanism between PvCesA2 and these peptides. Based on this analysis, we performed a saturation mutation of NoPv1 and successfully obtained the double mutants DP1 and DP2 with a higher affinity for PvCesA2. Meanwhile, dynamics simulations revealed that both DP1 and DP2 utilize a mechanism akin to the barrel-stave model for penetrating the cell membrane. Furthermore, the predicted results showed that the antimicrobial activity of DP1 was superior to that of NoPv1 without being toxic to human cells. These findings may offer insights for advancing the development of eco-friendly pesticides targeting various oomycete diseases, including late blight. Full article