Background/Objectives: Pain after video-assisted thoracoscopic surgery (VATS) leads to impaired postoperative recovery, possible side effects of opioid usage, and higher rates of chronic post-surgery pain (CPSP). Nevertheless, guidelines on perioperative pain management for VATS patients are lacking. The aim of this study was to analyze the effectiveness of intercostal catheters in combination with a single shot intraoperative intercostal nerve block (SSINB) in comparison to SSINB alone with respect to opioid consumption and CPSP. Methods: Patients receiving an anatomic VATS resection between 2019 and 2022 for primary lung cancer were retrospectively analyzed. A total of 75 consecutive patients receiving an ICC and SSINB and 75 consecutive patients receiving only SSINB were included in our database. After enforcing the exclusion criteria (insufficient documentation, external follow-ups, or patients receiving opioids on a fixed schedule; n = 9) 141 patients remained for further analysis. Results: The ICC and No ICC cohort were comparable in age, gender distribution, tumor location and hospital stay. Patients in the ICC cohort showed significantly less opioid usage regarding the extent (4.48 ± 6.69 SD vs. 7.23 ± 7.55 SD mg, p = 0.023), duration (0.76 ± 0.97 SD vs. 1.26 ± 1.33 SD days, p = 0.012) and frequency (0.90 ± 1.34 SD vs. 1.45 ± 1.51 SD times, p = 0.023) in comparison to the No ICC group. During the first nine months of oncological follow-up assessments, no statistical difference was found in the rate of patients experiencing postoperative pain, although a trend towards less pain in the ICC cohort was found. One year after surgery, the ICC cohort expressed significantly less often pain (1.5 vs. 10.8%, p = 0.035). Conclusions: Placement of an ICC provides VATS patients with improved postoperative pain relief resulting in a reduced frequency of required opioid administration, less days with opioids, and a reduced total amount of opioids consumed. Furthermore, ICC patients have significantly lower rates of CPSP one year after surgery. Full article

22CrMoH was selected for the gear steel material in this work, and the temperature field change in the scanning electron beam was analyzed to determine the optimal scanning parameters and explored the effect of scanning electron beam pretreatment (Abbreviated as: SEBP) on gas-carburizing (GC) efficiency and organizational properties of gear steel. The results showed that the scanning electron beam caused the material to form a thermally deformed layer 110 μm thick, and it promoted the adsorption of carbon atoms on the surface and their inward diffusion. Under the same gas-carburizing conditions, the carburizing efficiency was improved, and the thickness of the carburized layer increased from 0.78 to 1.09 mm. Furthermore, the hardness of the GC specimens with the SEBP increased from 615 to 638 HV_0.05 at 0.1 mm of the sample surface, whereas the hardness of the cross-sectional region decreased gradually, indicating that the scanning electron beam enhanced the adhesion between the carburized layer and matrix zone. A comparative analysis of the microstructures of the GC specimens with and without the SEBP showed that the carbide particles in the surface layer of the samples become smaller and that of volume fraction of residual austenite reduced in size. In terms of the mechanical properties, the surface friction coefficient decreased from 0.87 to 0.46 μ and the GC specimen with the SEBP had a higher cross-sectional hardness gradient. Its friction coefficient was reduced from approximately 0.8 to almost 0.45 μ, and the wear amount of the specimens with SEBP was 47.7% of that of the matrix specimens. Full article

Using recycled concrete aggregates from construction and demolition wastes on structural concrete is a sustainable solution to reduce the consumption of natural resources and the detrimental effects of concrete production on the environment. This paper has collected much data from the literature to study fresh, mechanical properties and durability of concrete made of treated/untreated recycled aggregate (RA). Furthermore, the flexural and shear behavior of recycled aggregate concrete (RAC) beams was studied. This study discussed the distinctions and similarities between reinforced RAC beams and reinforced natural aggregate concrete (NAC) beams. The results of this review’s analysis clearly show that reinforced RAC beams with different RAC ratios perform structurally on par with or slightly worse than reinforced NAC beams, demonstrating the viability of RAC for structural applications. Emphasis is placed on carefully choosing and adjusting material models for recycled aggregate concrete. Ultimately, guidelines for future inquiries in this field are delineated and deliberated upon. The review will be advantageous for academics and professionals who aim to acquire a comprehensive comprehension of the behavior of RAC beams. It addresses several practical concerns connected to the numerical modeling of these components, which have not been adequately covered in existing literature. Full article

Dupin cyclides are classical algebraic surfaces of low degree. Recently, they have gained popularity in computer-aided geometric design (CAGD) and architecture owing to the fact that they contain many circles. We derive algebraic conditions that fully characterize the Dupin cyclides passing through a fixed circle. The results are applied to the basic problem in CAGD of the blending of Dupin cyclides along circles. Full article

(1) Background: Epizootic hemorrhagic disease virus (EHDV) and bluetongue virus (BTV) are orbiviruses that cause hemorrhagic disease (HD) with significant economic and population health impacts on domestic livestock and wildlife. In the United States, white-tailed deer (Odocoileus virginianus) are particularly susceptible to these viruses and are a frequent blood meal host for various species of Culicoides biting midges (Diptera: Ceratopogonidae) that transmit orbiviruses. The species of Culicoides that transmit EHDV and BTV vary between regions, and larval habitats can differ widely between vector species. Understanding how midges are distributed across landscapes can inform HD virus transmission risk on a local scale, allowing for improved animal management plans to avoid suspected high-risk areas or target these areas for insecticide control. (2) Methods: We used occupancy modeling to estimate the abundance of gravid (egg-laden) and parous (most likely to transmit the virus) females of two putative vector species, C. stellifer and C. venustus, and one species, C. haematopotus, that was not considered a putative vector. We developed a universal model to determine habitat preferences, then mapped a predicted weekly midge abundance during the HD transmission seasons in 2015 (July–October) and 2016 (May–October) in Florida. (3) Results: We found differences in habitat preferences and spatial distribution between the parous and gravid states for C. haematopotus and C. stellifer. Gravid midges preferred areas close to water on the border of well and poorly drained soil. They also preferred mixed bottomland hardwood habitats, whereas parous midges appeared less selective of habitat. (4) Conclusions: If C. stellifer is confirmed as an EHDV vector in this region, the distinct spatial and abundance patterns between species and physiological states suggest that the HD risk is non-random across the study area. Full article

Alzheimer’s disease (AD), a multifactorial neurodegenerative disorder, is prevalent among the elderly population. It is a complex trait with mutations in multiple genes. Although the US Food and Drug Administration (FDA) has approved a few drugs for AD treatment, a definitive cure remains elusive. Research efforts persist in seeking improved treatment options for AD. Here, a hybrid pipeline is proposed to apply text mining to identify comorbid diseases for AD and an omics approach to identify the common genes between AD and five comorbid diseases—dementia, type 2 diabetes, hypertension, Parkinson’s disease, and Down syndrome. We further identified the pathways and drugs for common genes. The rationale behind this approach is rooted in the fact that elderly individuals often receive multiple medications for various comorbid diseases, and an insight into the genes that are common to comorbid diseases may enhance treatment strategies. We identified seven common genes—PSEN1, PSEN2, MAPT, APP, APOE, NOTCH, and HFE—for AD and five comorbid diseases. We investigated the drugs interacting with these common genes using LINCS gene–drug perturbation. Our analysis unveiled several promising candidates, including MG-132 and Masitinib, which exhibit potential efficacy for both AD and its comorbid diseases. The pipeline can be extended to other diseases. Full article

Wire arc additive manufacturing (WAAM) has attracted increasing interest in industry and academia due to its capability to produce large and complex metallic components at a high deposition rate. One of the basic tasks in WAAM is to determine appropriate process parameters, which will directly affect the morphology and quality of the weld bead. However, the selection of process parameters relies heavily on empirical data from trial-and-error experiments, which results in significant time and cost expenditures. This paper employed different machine learning models, including SVR, BPNN, and XGBoost, to predict process parameters for WAAM. Furthermore, the SVR model was optimized by the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithms. A 3D laser scanner was employed to obtain the weld bead’s point cloud, and the weld bead size was extracted using the point cloud processing algorithm as the training data. The K-fold cross-validation strategy was applied to train and validate machine learning models. The comparison results showed that PSO–SVR predicted process parameters with the highest precision, with the RMSE, R², and MAE being 1.1670, 0.9879, and 0.8310, respectively. Based on the process parameters produced by PSO–SVR, an optimal process parameter combination was chosen by taking into comprehensive consideration the impacts of power consumption and efficiency. The effectiveness of the process parameter optimization method was proved through three groups of validation experiments, with the energy consumption of the first two groups decreasing by 10.68% and 11.47%, respectively. Full article

Three ionic liquids (ILs) and three deep eutectic solvents (DESs) with identical counterparts, as well as their aqueous solutions, were prepared for the selective extraction of alginate from Sargassum tenerrimum, a brown seaweed. It was found that the ILs and their hydrated systems were only able to extract alginate from the seaweed directly, while the DESs were not, as confirmed by molecular docking studies. When the quality of the polysaccharide was compared to that produced using the hydrated IL system with the widely used conventional method, it was discovered that the physicochemical and rheological characteristics of the alginate produced using the ILs as solvents were on par with those produced using the conventional method. The ILs can be seen as acceptable alternative solvents for the simple extraction of the polysaccharide straight from the seaweed given the consistency of the extraction procedure used in conventional extraction processes. The hydrated ILs were discovered to be more effective than their non-hydrated counterparts. The yield was also maximized up to 54%, which is much more than that obtained using a traditional approach. Moreover, the ionic liquids can also be recovered and reused for the extraction process. Additionally, any residual material remaining after the extraction process was converted into cellulose, making the process environmentally friendly and sustainable. Full article

Background: Understanding self-concept in individuals with intellectual disabilities is crucial for tailored support and interventions. The research question driving this study is: What factors influence the self-concept of individuals with intellectual disabilities, and how is it assessed? Methods: Employing a systematic review following PRISMA guidelines, studies from 1993 to 2024, which used diverse assessment tools such as the Pictorial Scale of Perceived Competence and Acceptance, Myself as a Learner Scale, and other self-report questionnaires, were analysed. Results: Factors influencing self-concept include diagnosis, age, gender, perception of control, school placement, and socioeconomic status. Internal factors like perception of control and external factors like societal attitudes interact to shape self-concept trajectories. Assessments reveal nuanced dimensions of self-perception, facilitating targeted interventions. Conclusions: Assessing self-concept among individuals with intellectual disabilities requires diverse evaluation methods. Insights gained inform tailored interventions to enhance well-being. Further research is needed to validate assessment tools across diverse populations. Recognizing the interplay of internal beliefs, external perceptions, and societal structures is crucial for empowering individuals to embrace their unique identities. Full article

Evolutionary algorithms exhibit flexibility and global search advantages in multi-UAV path planning, effectively addressing complex constraints. However, when there are numerous obstacles in the environment, especially narrow passageways, the algorithm often struggles to quickly find a viable path. Additionally, collaborative constraints among multiple UAVs complicate the search space, making algorithm convergence challenging. To address these issues, we propose a novel hybrid particle swarm optimization algorithm called PPSwarm. This approach initially employs the RRT* algorithm to generate an initial path, rapidly identifying a feasible solution in complex environments. Subsequently, we adopt a priority planning method to assign priorities to UAVs, simplifying collaboration among them. Furthermore, by introducing a path randomization strategy, we enhance the diversity of the particle swarm, thereby avoiding local optimum solutions. The experimental results show that, in comparison to algorithms such as DE, PSO, ABC, GWO, and SPSO, the PPSwarm algorithm demonstrates significant advantages in terms of path quality, convergence speed, and runtime when addressing path planning issues for 40 UAVs across four different scenarios. In larger-scale experiments involving 500 UAVs, the proposed algorithm also exhibits excellent processing capability and scalability. Full article

This study investigates natural-based blends of glutinous rice starch (GRS) and chitosan (CS), varying their molar composition (0:100, 30:70, 50:50, 70:30, and 100:0) to explore their interaction dynamics. Our findings illustrate the versatility of these blends in solution and film forms, offering applications across diverse fields. Our objective is to understand their impact on coatings designed to extend the post-harvest shelf life of mangoes. Results reveal that increasing chitosan content in GRS/CS blends enhances mechanical strength, hydrophobicity, and resistance to Colletotrichum gloeosporioides infection, a common cause of mango anthracnose. These properties overcome limitations of GRS films. Advanced techniques, including FTIR analysis and stereo imaging, confirmed robust interaction between GRS/CS blend films and mango cuticles, improving coverage with higher chitosan content. This comprehensive coverage reduces mango dehydration and respiration, thereby preserving quality and extending shelf life. Coating with a GRS/CS blend containing at least 50% chitosan effectively prevents disease progression and maintains quality over a 10-day storage period, while uncoated mangoes fail to meet quality standards within 2 days. Moreover, increasing the starch proportion in GRS/CS blends enhances film density, optical properties, and reduces reliance on acidic solvents, thereby minimizing undesirable changes in product aroma and taste. Full article

Palliative cancer care patients may live for a long time, but malnutrition worsens the prognosis. Parenteral nutrition (PN) is suitable for replenishing a calorie deficit, but its advantages and tolerance late in the cancer trajectory are debated. We examined symptom development in hospitalized patients with and without PN. A total of 21 palliative cancer care patients receiving PN and 155 palliative cancer care patients not receiving PN during hospitalization in a specialized unit were retrospectively compared. We studied symptom intensity at admission, symptom relief during the hospital stay, and survival. The patients had locally advanced or metastatic cancer, a mean age of 70 years, and their median ECOG performance status was III. Symptom burden at admission was similar in the compared groups. Symptom relief during hospitalization was also similar. However, patients already on PN at admission reported more nausea and patients receiving PN during hospitalization reported better nausea relief compared to patients not receiving this intervention. Overall median survival was less than two months and similar in the compared groups. Based on a limited number of observations and a suboptimal study design, we were not able to demonstrate an increased symptom burden for palliative cancer care patients receiving PN late in the disease trajectory. Full article

Brevibacillus brevis is one of the most common biocontrol strains with broad applications in the prevention and control of plant diseases and insect pests. In order to deepen our understanding of B. brevis genomes, describe their characteristics comprehensively, and mine secondary metabolites, we retrieved the genomic sequences of nine B. brevis strains that had been assembled into complete genomes from the NCBI database. These genomic sequences were analyzed using phylogenetic analysis software, pan-genome analysis software, and secondary metabolite mining software. Results revealed that the genome size of B. brevis strains ranged from 6.16 to 6.73 Mb, with GC content ranging from 47.0% to 54.0%. Phylogenetic analysis classified the nine B. brevis strains into three branches. The analyses of ANI and dDDH showed that B. brevis NEB573 had the potential to become a new species of Brevibacillus and needed further research in the future. The pan-genome analysis identified 10032 gene families, including 3257 core gene families, 3112 accessory gene families, and 3663 unique gene families. In addition, 123 secondary metabolite biosynthetic gene clusters of 20 classes were identified in the genomes of nine B. brevis strains. The major types of biosynthetic gene clusters were non-ribosomal peptide synthase (NRPS) and transAT polyketide synthase (transAT-PKS). Furthermore, a large number of untapped secondary metabolites were identified in B. brevis. In summary, this study elucidated the pan-genome characteristics of the biocontrol bacterium B. brevis and identified its secondary metabolites, providing valuable insights for its further development and utilization. Full article

In recent years, the occurrence of high-voltage cable buffer layer ablation faults has become frequent, posing a serious threat to the safe and stable operation of cables. Failure to promptly detect and address such faults may lead to cable breakdowns, impacting the normal operation of the power system. To overcome the limitations of existing methods for identifying buffer layer ablation faults in high-voltage cables, a method for identifying buffer layer ablation faults based on frequency domain impedance spectroscopy and artificial intelligence is proposed. Firstly, based on the cable distributed parameter model and frequency domain impedance spectroscopy, a mathematical model of the input impedance of a cable containing buffer layer ablation faults is derived. Through a simulation, the input impedance spectroscopy at the first end of the cables under normal conditions, buffer layer ablation, local aging, and inductive faults is performed, enabling the identification of inductive and capacitive faults through a comparative analysis. Secondly, the frequency domain amplitude spectroscopy of the buffer layer ablation and local aging faults are used as datasets and are input into a neural network model for training and validation to identify buffer layer ablation and local aging faults. Finally, using multiple evaluation metrics to assess the neural network model validates the superiority of the MLP neural network in cable fault identification models and experimentally confirms the effectiveness of the proposed method. Full article

The progress in machine learning during the last decade has had a considerable impact on many areas of science and technology, including quantum technology. This work explores the application of reinforcement learning (RL) methods to the quantum control problem of state transfer in a single qubit. The goal is to create an RL agent that learns an optimal policy and thus discovers optimal pulses to control the qubit. The most crucial step is to mathematically formulate the problem of interest as a Markov decision process (MDP). This enables the use of RL algorithms to solve the quantum control problem. Deep learning and the use of deep neural networks provide the freedom to employ continuous action and state spaces, offering the expressivity and generalization of the process. This flexibility helps to formulate the quantum state transfer problem as an MDP in several different ways. All the developed methodologies are applied to the fundamental problem of population inversion in a qubit. In most cases, the derived optimal pulses achieve fidelity equal to or higher than 0.9999, as required by quantum computing applications. The present methods can be easily extended to quantum systems with more energy levels and may be used for the efficient control of collections of qubits and to counteract the effect of noise, which are important topics for quantum sensing applications. Full article

Conducting polymers are used in a wide range of applications, especially in the design and development of electrochemical sensors. Their main advantage, in this context, is their ability to efficiently modify an electrode surface using the direct polymerization of a suitable monomer in an electrochemical cell, or by physical coating. Additionally, the conducting polymers can be mixed with further materials (metal nanoparticles, carbonaceous materials) to enhance conductivity and analytical features (linear range, limit of detection, sensitivity, and selectivity). Due to their characteristics, conducting polymer-based amperometric sensors are applied to the determination of different organic and inorganic analytes. A view of recent advances in this field focusing on pyrrole, thiophene, and 3,4-ethylenedioxythiophene as starting materials is reported. Full article

A facile, one-step nitridation–decomposition method was developed for the synthesis of nanosized tungsten powder with a high surface area. This approach involved the nitridation of WO₃ in NH₃ to form mesoporous tungsten nitride (W₂N), followed by in situ decomposition of W₂N to directly yield single-phase W particles. The phase and morphology evolution during the synthesis were systematically investigated and compared with the carbothermal reduction of WO₃. It was revealed that powdered tungsten product with single-phase particles was obtained after nitridation at 800 °C combined with in situ decomposition at 1000 °C, displaying an average particle size of 15 nm and a large specific surface area of 6.52 m²/g. Furthermore, the proposed method avoided the limitations associated with intermediate phase formation and coarsening observed in carbothermal reduction, which resulted in the growth of W particles up to ~4.4 μm in size. This work demonstrates the potential of the nitridation–decomposition approach for the scalable and efficient synthesis of high-quality, fine-grained tungsten powder. Full article

In all vertebrates, visual signals from each visual field project to the opposite midbrain tectum (called the superior colliculus in mammals). The tectum/colliculus computes visual salience to select targets for context-contingent visually guided behavior: a frog will orient toward a small, moving stimulus (insect prey) but away from a large, looming stimulus (a predator). In mammals, visual signals competing for behavioral salience are also transmitted to the visual cortex, where they are integrated with collicular signals and then projected via the dorsal visual stream to the parietal and frontal cortices. To control visually guided behavior, visual signals must be encoded in body-centered (egocentric) coordinates, and so visual signals must be integrated with information encoding eye position in the orbit—where the individual is looking. Eye position information is derived from copies of eye movement signals transmitted from the colliculus to the frontal and parietal cortices. In the intraparietal cortex of the dorsal stream, eye movement signals from the colliculus are used to predict the sensory consequences of action. These eye position signals are integrated with retinotopic visual signals to generate scaffolding for a visual scene that contains goal-relevant objects that are seen to have spatial relationships with each other and with the observer. Patients with degeneration of the superior colliculus, although they can see, behave as though they are blind. Bilateral damage to the intraparietal cortex of the dorsal stream causes the visual scene to disappear, leaving awareness of only one object that is lost in space. This tutorial considers what we have learned from patients with damage to the colliculus, or to the intraparietal cortex, about how the phylogenetically older midbrain and the newer mammalian dorsal cortical visual stream jointly coordinate the experience of a spatially and temporally coherent visual scene. Full article

Straw incorporation into soil contributes significantly to the sustainable development of agriculture. To investigate the impact of tobacco straw returns on a tobacco–rice replanting system, we designed an experiment with two straw return levels and a control group: T1 (full return), T2 (root return), and CK (no straw return). Over a three-year field experiment in rice fields in South China, we assessed the effects of tobacco straw return on soil quality, microbial diversity, dry matter accumulation, and yield composition of rice. The results demonstrated that returning tobacco straw to the field effectively enhanced rice yield by positively influencing various soil physical, chemical, and biological properties. Compared to those in the CK treatment, as the soil porosity increased from 9.0% to 12.4%, the mean weight diameter of the soil aggregates substantially increased, ranging from 28.7% to 45.2%. There were significant increases in soil organic matter, total nitrogen, and alkaline dissolved nitrogen. Soil sucrase activity increased between 29.8% and 44.9%, and urease activity increased between 4.3% and 62.2% over the three consecutive years of straw return. The diversity index of soil fungi significantly increased. Additionally, rice yield increased markedly, ranging from 1.8% to 5.1%. Overall, the enhancement effect of T1 surpassed that of T2. According to our comprehensive analysis, the incorporation of tobacco straw into the field was found to enhance the physical properties of the soil, elevate soil enzyme activity, and increase the abundance of soil microorganisms. Consequently, this practice led to improved rice yield and a reduction in agricultural waste output. Overall, the return of tobacco straw to the field represents a clean and dependable approach in rice-cultivated tobacco areas to improve soil health and rice productivity. Full article

The presence of pyrite poses a significant impediment to the comprehensive utilization of coal gangue, which is a prevalent solid waste in industrial production. However, the current efficacy of jig separation for pyrite in fine-grade coal gangue remains unsatisfactory. To investigate the influence of particle size distribution on the jig separation of pyrite in fine-grade coal gangue, the raw material was crushed to less than 2 mm using a jaw crusher and subsequently sieved to obtain its particle size distribution curve. Upon fitting the curve, it was observed that it tends towards the Rosin-Rammler (RRSB) and Fuller distributions. Leveraging these two-parameter distribution curves, adjustments were made to determine the mass within each particle size range before conducting thorough mixing followed by jig separation. The results indicate that for fine-grade gangue particles smaller than 2 mm, the RRSB distribution with a uniformity coefficient of n = 0.85 exhibits the most effective separation, although it is comparable to the separation achieved using the size distribution of raw ore. On the other hand, employing the Fuller distribution with modulus of distribution q = 1.5 yields superior separation performance. In comparison to the raw ore, the concentrate shows an increase in sulfur (S) and iron (Fe) content by factors of 3.4 and 2.4, respectively. Furthermore, compared to the RRSB distribution, there is an increase in S and Fe content by 1.91% and 2.30%, respectively; the contents of S and Fe in tailings is 0.71% and 2.72%, which can be directly used as raw materials for coating materials. Therefore, for fine-grade coal gangue particles, jigging under the Fuller distribution demonstrates better effectiveness than under the RRSB distribution. Full article

Governments worldwide have invested considerable money and time into creating pedestrian-oriented urban environments. However, generalizing arbitrary standards for walking environments is challenging. Therefore, this study presents a method for predicting walkability scores of evaluations using five regression models, including Multiple linear, Ridge, LASSO regression, SVR, and XGBoost. The models were trained using semantic segmentation, walkability evaluations based on crowdsourcing, and image scores obtained using the TrueSkill algorithm, and their performances were compared. Feature selection was employed to improve the accuracies of the models, which were retrained using the importance of extracted features. Among the five regression models, XGBoost, a tree-based regression model, exhibited the lowest error rate, high accuracy, and greatest performance improvement after retraining. This study is expected to generalize the walking environments preferred by various people and demonstrate that objective walkability evaluations are possible through a computer system rather than through subjective human judgment. Full article

Corythucha marmorata (Uhler) emerged as an invasive pest in China around 2010, posing a significant threat to plants within the Asteraceae family. Employing the MaxEnt model, this study endeavors to anticipate the potential geographic distribution of Corythucha marmorata amid present and forthcoming climatic conditions, utilizing a dataset of 60 distributional occurrences alongside environmental parameters. The results revealed that presently, suitable regions span from 18–47° N to 103–128° E, with pronounced suitability concentrated notably in Jiangsu, Shanghai, Anhui, Hubei, Jiangxi, Hunan, Guangdong, Guangxi, Chongqing, and Sichuan. Projections suggested a general expansion of suitable habitats, albeit with exceptions noted in SSP1–2.6 and SSP2–4.5 scenarios in the 2050s and SSP5–8.5 in the 2070s. The potential suitability of areas for Corythucha marmorata was influenced by major factors such as precipitation in the warmest quarter (bio18), mean temperature in the warmest quarter (bio10), mean temperature in the wettest quarter (bio8), and annual precipitation (bio12). Notably, temperature and precipitation emerge as primary determinants affecting both current and future ranges. In comparison with the current distributional area, there was a trend towards increasing the potentially suitable areas in the future. Moreover, there was a greater risk of spreading to the north of China in the future. This study serves as a pivotal resource for guiding future endeavors in monitoring, early detection, and preventative management strategies targeting Corythucha marmorata. Full article