One of the most pressing challenges associated with SARS treatment is the emergence of new variants that may be transmissible, causing more severe disease or being resistant to the current standard of treatment. This study aimed to identify potential drug candidates from novel imidazole derivatives against SARS-CoV-2 main protease (Mpro), a crucial drug target for treating viral infection, using a computational approach that integrated molecular docking and dynamics simulation. In this study, we utilized AutoDock Vina within the PyRx workspace for molecular docking analysis to explore the inhibitory effects of the compounds on the Mpro, a drug target for SARS-CoV-2. The ADMET properties of these compounds, including absorption, distribution, metabolism, excretion, and toxicity, were evaluated using the SwissADME and ADMETLab servers. Each of the 18 compounds that were tested demonstrated strong binding affinities towards Mpro, with imidazolyl–methanone C10 showing the most significant binding affinity. Moreover, pyridyl–imidazole C5, thiophenyl–imidazole C1, and quinoline–imidazole C14 displayed binding affinities of −8.3, −8.2, and −7.7 Kcal/mol, respectively. These compounds interacted with specific amino acid residues (HIS A:41—CYS A:145) within the Mpro protein. To assess the stability of the ligand with the best binding affinity, molecular dynamics (MD) simulations were conducted using Schrodinger software, which revealed its stability over the simulation period. The study provides valuable insights into the potential of imidazole derivatives as SARS-CoV-2 Mpro inhibitors. All compounds including C10 display promising characteristics and hold potential as drug candidates for SARS-CoV-2. However, further optimization and experimental validation of these compounds are necessary to advance their development as effective therapeutics against viral infections. Full article

Encephalitis and acute disseminated encephalomyelitis (ADEM) are often caused or triggered by viruses—but the specific pathogen commonly remains unidentified in routine care. We explored the use of viral metagenomic next-generation sequencing (mNGS) in addition to PCR testing of non-invasive stool samples to see if unbiased testing could potentially increase diagnostic yield. To identify specific clinical cases at the point of care, we took advantage of a previously published digital app allowing instant clinical case classification based on consensus case criteria, the VACC-Tool. This hospital-based prospective digital surveillance program assessed 100 pediatric patients (mean age: 11 years, range: 0.15–17.85; 49% male) with case-confirmed encephalitis and/or ADEM. Analysis of case classification at the point of care revealed that in routine care, 96% of confirmed encephalitis/ADEM cases had been missed. Overall agreement of routine care diagnoses with digital encephalitis/ADEM case classification was <50%. Also in routine care, only 13% of cases held a virus-related diagnosis, i.e., herpesvirus (n = 8) and enterovirus infection (n = 5). Use of mNGS increased the yield of virus detection by 77% (n = 23 virus hits). Specifically, mNGS identified 10 additional virus species beyond herpes- and enteroviruses. Of the additional 23 virus hits detected with mNGS, PCR confirmation was possible post hoc in 14 cases (61%). Linking digital case classification, mNGS, and PCR testing may not be feasible in routine care at this point but may help to provide hints to the pathogenesis of encephalitis/ADEM in childhood, warranting further research and exploration. Full article

(1) The study aims to utilize a reported approach for culturing mesophilic bacteria from a plastic waste environment; (2) The work revived mesophilic microbial population from an aged PET recycling site using a culture-based approach, and determined the purified isolates in genus level in 16S identification; (3) A total of 59 bacterial isolates were obtained, in which microbial species, including Pseudomonas spp, Rhodococcus spp, and Burkholderia spp were identified as abundance. It was observed that the surviving microbes favoured sodium propionate as a short-chain carbon source for growth, rather than the intended plastic substrate, PET. The preference of sodium propionate utilization by several bacterial isolates, including 5601W (detected as Rhodococcus spp.), 5601Y, 7801, and 7802 (detected as Burkholderia spp.), was confirmed through growth curve analysis and cell enumeration conducted in a medium where sodium propionate served as the sole carbon source.; (4) The microbial demonstration revealed the metabolic complex of microbial communities in the environment and indicated the challenges associated with bacterial isolation from environments with accumulated plastic waste. Full article

Babesiosis, caused by Babesia ovis, is a major seasonal issue in sheep, particularly in countries like Türkiye with high Rhipicephalus bursa tick populations. Previous studies employing various methods such as microscopy, serology, or molecular techniques have reported different epidemiological data concerning ovine babesiosis. Addressing this knowledge gap, our study employed a combined nested PCR (nPCR)/indirect ELISA (iELISA) approach, analyzing blood samples collected from 414 sheep between April and July 2023 using both techniques. nPCR amplified the 18S ribosomal RNA gene of B. ovis and determined a molecular prevalence of 1.9%. Conversely, serological testing using iELISA targeted the BoSA1 antigen and revealed a significantly higher positivity rate of 59.9% for anti-B. ovis antibodies. The temporary presence of Babesia after recovery reduces nPCR sensitivity, resulting in lower molecular prevalence. However, even if Babesia is not present in the host, anti-B. ovis antibodies remain in the serum for a long time and can be detected serologically. Our study underscores the necessity of concurrently employing molecular and serological methods for an accurate assessment of B. ovis prevalence. It highlights the importance of comprehensive epidemiological approaches for effective disease management in sheep populations. Full article

The use of validated tools to evaluate the nutritional status of the cancer patient provides guaranteed precision and reliability in their nutritional evaluation, ensuring that the information is accurate and reflects the patient's situation. The aim of this study was to identify the valid and reliable instruments in the evaluation of the nutritional status of cancer patients with a diagnosis of solid tumor undergoing antineoplastic treatment (chemotherapy and/or immunotherapy). A scoping review was conducted to search for original articles published in scientific journals in English, Spanish, or Portuguese in the past five years. In order to identify potentially relevant documents, searches were performed in the following databases: SCOPUS, WOS, CINAHL, MEDLINE, BVS, and PUBMED. DECS-MeSH descriptors and Boolean operators were used. In addition, the Arksey and O’Malley protocol, the Joanne Briggs Institute (JBI) method, and the flow chart of the Preferred Information Elements for Systematic Reviews and Meta-Analyses, known as PRISMA, were followed. The initial search strategy identified a total of 164 references, which were examined successively, leaving a final selection of ten studies. It was found that the most used instrument for nutritional evaluation was the Patient-Generated Subjective Global Assessment (PG-SGA). Other questionnaires also stood out such as the Mini Nutritional Assessment (MNA), the Malnutrition Universal Screening Tool (MUST), the Nutritional Risk Screening (NRS 2002), and the Functional Assessment of Anorexia/Cachexia Therapy (FAACT). The variation in the tools used ranges from subjective assessments to objective measurements, thus underlining the need for a comprehensive and individualized approach. Full article

The objective of this qualitative investigation is to identify the assistive technology recognized by students with disabilities and to determine the assistive technology (software apps and devices) they require both at university and at home. A total of forty-two students, comprising 20 males and 22 females, were recruited from four different countries (Germany, Greece, Italy, and Spain) for participation in this study. The sample encompassed 10 students with visual impairments, 11 with hearing impairments, 11 with mobility impairments, and 10 with specific learning disabilities. Semi-structured interviews were conducted with the students either online or in person. Content analysis was employed to scrutinize the data obtained from these interviews. The outcomes of this analysis shed light on the assistive technology acknowledged, utilized, or desired by students with disabilities in both academic and domestic settings. The findings from this study carry practical implications for fostering inclusive and accessible education within higher education institutions, benefiting accessibility units/offices staff as well as teaching personnel. Full article

The four-wheel steering distributed drive vehicle is a novel type of vehicle with independent control over the four-wheel angle and wheel torque. A method for jointly controlling the distribution of the wheel angle and torque is proposed based on this characteristic. Firstly, the two-degrees-of-freedom model and ideal reference model of four-wheel steering vehicle are established; then, the four-wheel steering controller and torque distribution controller are designed. The rear wheel angle is controlled by the feedforward controller and the feedback controller. The feedforward controller takes the side slip angle of the center of mass as the control target, and the feedback controller takes the yaw angle as the control target. Torque is controlled by two control layers, the additional yaw moment of the upper layer is calculated by the vehicle motion state and fuzzy control theory, and the lower layer distributes wheel torque through the road adhesion coefficient and wheel load. Finally, a simulation platform is established to verify the effectiveness of the proposed control algorithm. Full article

The dual-credit policy promotes green transition in automobile companies. This paper investigates the dual-credit policy framework in the Chinese automotive industry, with a focus on the phenomenon of free riding. This occurs when traditional vehicle manufacturers within an alliance benefit from the excess credits generated by a transitioning vehicle company without fully committing to their own green transitioning. The focus of this study lies on an alliance constituted by a transitioning vehicle company in partnership with two traditional vehicle manufacturers, all interconnected via equity ties. Utilizing an agent-based system dynamics model, this study explores the strategic behaviors emerging from such credit collaborations and their consequent effects on operational efficiency and financial performance. The findings reveal that 1. free riding negatively impacts the transitioning company’s revenue but benefits the alliance by easing transition pressures and boosting collective performance; 2. stricter policies increase intra-alliance credit transfers and performance, while lower credit prices reduce transfer value and harm the transitioning company’s earnings. This study implies that transitioning vehicle companies with equity-linked partners can benefit from a nuanced understanding of how policy mechanisms interact with alliance dynamics under free riding. By adjusting credit transfer strategies in line with market conditions and policy trends, they can better navigate the dual-credit policy landscape, balancing individual profitability with the needs of the broader alliance and long-term sustainability goals. Full article

This study explores the interrelationship between community attachment in AlUla Heritage City (located in Saudi Arabia) and tourists’ green consumption practices, testing support for green tourism development as a mediator. The old historical city of AlUla, a significant city experiencing ongoing preservation and tourism development, represents an adequate context for exploring the link between community attachment and green tourism practices. This study employs a quantitative approach, including surveys with 328 local residents of AlUla. A structural equation modeling partial least square (PLS-SEM) analysis is conducted to explore the indirect influence of community attachment on tourists’ green consumption through the mediating role of support for green tourism development. The findings indicated a positive path from community attachment in AlUla to tourists’ tendencies toward green consumption behavior. Moreover, the mediating effects of support for green tourism development suggested that a deep sense of community attachment improves tourists’ support for green practices in the tourism sector. This study adds to the extended body of the literature on place attachment and green tourism by emphasizing the significance of community place attachment in stimulating tourists’ green consumption practices. Several practical implications for policymakers seeking to promote green tourism practices in heritage cities like AlUla are explored from the study results. Full article

Background and Objectives: Inadequate treatment of asthma and chronic obstructive pulmonary disease (COPD) might have a negative impact on their progression. Inhalation therapy is the cornerstone of pharmacotherapy for these conditions. However, challenges such as low adherence, negative attitudes, and misconceptions about inhaled medications still persist, impeding effective disease management. This study aimed to evaluate adherence, ascertain the level of disease control in asthma and COPD, explore potential misconceptions surrounding inhalation therapy among patients with obstructive lung diseases and the general population in Vojvodina, and evaluate the reliability of newly developed questionnaires employed in the study. Materials and Methods: This cross-sectional study utilized a battery of questionnaires encompassing sociodemographic data, the Asthma Control Test (ACT), the COPD Assessment Test (CAT), along with two novel questionnaires—one for assessing adherence and another for analyzing attitudes toward inhalation therapy. Statistical analyses were conducted using SPSS software, version 25.0. Results: The average ACT score among patients with asthma was 17.31, while it was 19.09 for the CAT questionnaire among COPD patients. The composite score on the newly developed adherence assessment questionnaire was 2.27, exhibiting a reliability coefficient lower than recommended (α = 0.468). Significant statistical differences emerged among sample subgroups regarding attitudes and misconceptions toward inhalation therapy. The reliability coefficient for this questionnaire was deemed satisfactory (α = 0.767). Conclusions: Adherence rates were notably suboptimal in both subgroups of the studied population. The disease control levels were higher among asthma patients, while they exhibited less prevalent misconceptions regarding inhalation therapy compared to COPD patients and the healthy population. Full article

Studies on estimating cumulative fire intensity from spreading wildland fires based on fire radiative energy density (FRED) have primarily been conducted through controlled experiments. The objective of this study was to assess the potential for estimating FRED for freely-burning wildfires at landscape scales. Airborne thermal infrared image sequences collected 8 and 9 December 2017 during the Thomas Fire were used for surface temperature derivation and FRED estimation. Sensitivity of varying ambient temperatures, and a newly developed method that adjusts for ash radiances on fire radiative flux density (FRFD) and FRED estimates were tested. Pixel-level image classification was run to identify FRFD time sequences that were complete or incomplete because of cloud obscuration and provided the basis for an obscuration gap filling technique. Variations in estimated ambient temperature used to estimate FRFD had little impact on FRED estimates, while our ash adjustment led to notable differences. An exponential decay model characterized FRFD time sequences well, providing a basis for gap filling irregular sequences caused by atmospheric obscuration. FRED estimates were regressed on rate of spread (ROS) magnitudes and found to be positively and significantly correlated. FRED magnitudes were higher on 9 December when the Thomas Fire burned under higher wind speeds and lower relative humidity levels (Santa Ana weather conditions) than on 8 December. Full article

This paper addresses the evacuation of people from multipurpose halls and introduces an innovative approach that uses a probabilistic model, specifically the Monte Carlo method, to analyse iterative evacuation processes. The aim is to explore how this modern technology can contribute to the development of effective and safe evacuation plans for mass events. The Monte Carlo method was applied to a specific example of a multipurpose hall that offers different configurations for events such as sports matches, concerts, or performances. The evacuation of people was analysed for two configurations: a hockey match with a capacity of 9500 people and a concert with a capacity of 11,000 people. In both cases, the total evacuation of people from the hall was analysed, and the evacuation time was evaluated when two parameters were changed: speed of movement and preference for door selection. The results of the simulations can provide valuable information for the design of effective safety measures in multipurpose halls and other similar multipurpose venues. This innovative approach to evacuation analysis allows for a comprehensive assessment of the evacuation process, identification of critical areas, and verification of the layout of the space. Full article

In this paper, we study the existence of multiple normalized solutions for a Choquard equation involving fractional p-Laplacian in ${\mathbb{R}}^N$. With the help of variational methods, minimization techniques, and the Lusternik–Schnirelmann category, the existence of multiple normalized solutions is obtained for the above problem. Full article

This work presents a numerical study on atmospheric sound propagation over rough water surfaces with the aim of improving predictions of sound propagation over long distances. A method for generating pseudorandom sea profiles consistent with sea wave spectra is presented. The proposed method is suited for capturing the logarithmic nature of the energy distribution of the waves. Sea profiles representing fully developed seas for sea states 2, 3, 4, and 5 are generated from the Elfouhaily et al. (ECKV) sea wave spectra. Excess attenuation caused by refraction and surface roughness is predicted with a parabolic equation (PE) solver. A novel method for estimating equivalent effective impedance based on PE predictions at different sea states is presented. Parametric expressions using acoustic frequency and significant wave height are developed for effective surface impedances. In this work, sea surface roughness is on a scale comparable with the acoustic wavelength. Under this condition, the acoustic scattering is primarily incoherent. This work shows the limitations of using an equivalent surface impedance in such incoherent scattering cases. Full article

The modified second-grade fluid flow across a plate of semi-infinite extent, which is initiated by the plate’s movement, is considered herein. The relaxation parameters and fractional parameters are introduced to express the generalized constitutive relation. A convolution-based absorbing boundary condition (ABC) is developed based on the artificial boundary method (ABM), addressing issues related to the semi-infinite boundary. We adopt the finite difference method (FDM) for deriving the numerical solution by employing the L1 scheme to approximate the fractional derivative. To confirm the precision of this method, a source term is added to establish an exact solution for verification purposes. A comparative evaluation of the ABC versus the direct truncated boundary condition (DTBC) is conducted, with their effectiveness and soundness being visually scrutinized and assessed. This study investigates the impact of the motion of plates at different fluid flow velocities, focusing on the effects of dynamic elements influencing flow mechanisms and velocity. This research’s primary conclusion is that a higher fractional parameter correlates with the fluid flow. As relaxation parameters decrease, the delay effect intensifies and the fluid velocity decreases. Full article

The burgeoning significance of antiferroelectric (AFE) materials, particularly as viable candidates for electrostatic energy storage capacitors in power electronics, has sparked substantial interest. Among these, lead-free sodium niobate (NaNbO₃) AFE materials are emerging as eco-friendly and promising alternatives to lead-based materials, which pose risks to human health and the environment, attributed to their superior recoverable energy density and dielectric breakdown strength. This review offers an insightful overview of the fundamental principles underlying antiferroelectricity and the applications of AFE materials. It underscores the recent advancements in lead-free NaNbO₃-based materials, focusing on their crystal structures, phase transitions, and innovative strategies devised to tailor their electrostatic energy storage performance. Finally, this review delineates the prevailing challenges and envisages future directions in the realm of NaNbO₃-based electrostatic energy storage capacitors, with the goal of fostering further advancements in this pivotal field. Full article

Sport Vision is a speciality of multidisciplinary interest aimed at improving the performance of the visual system to achieve benefits in practiced sports, as well as in daily life and in preventive care. The type of training practiced by the athlete, his or her physical condition, cognitive level, and level of fatigue condition affects the speed of the reaction time and, consequently, the speed of motor response. Specific orthoptic exercises, the use of technological devices, the recovery of static and dynamic postural stability by using unstable platforms and the dual-task paradigm can help to achieve the expected results. The aim of this systematic review of Sport Vision was to assess the overall existing literature on Sport Vision, paying particular attention to the effects of visual training and its application in different sports and in rehabilitation and preventive settings. We analysed published English language studies about the role of sport vision in athletic performance from 1950 to 2023. We searched through the Medline database. The PRISMA 2020 checklist was used to assess the transparency and reproducibility of this review. The enrolled papers were evaluated with the Jadad Scale, Amstar 2 Scale and Newcastle–Ottawa Scale. 25 (16 studies, 5 reviews, 2 comments, 1 editorial, 1 descriptive paper) out of 476 studies met the inclusion criteria. Due to the variability in the age of the samples, the different techniques, the treatments among the participants in the studies and the finding of non-evaluable articles, a meta-analysis was not conducted. The limitations of this review are the single database research, the studies analyzed contain a non-statistically representative sample size and the lack of a control group. There is no standardized test to measure performance. It was shown that the development of visual skills can benefit athletes in injury prevention, and can lead to improved sports performance and motor function at any age, acquiring adaptive motor behaviour even when the visual system is impaired, due to task repetition and familiarity of the gesture. We intended to identify a multidisciplinary approach and a manual treatment scheme to optimize the circuitry involved in sport vision in order to increase the results that are achieved, but further studies will be needed to this end. Full article

The objective of this research is to achieve biologically autonomous control by utilizing a whole-brain network model, drawing inspiration from biological neural networks to enhance the development of bionic intelligence. Here, we constructed a whole-brain neural network model of Caenorhabditis elegans (C. elegans), which characterizes the electrochemical processes at the level of the cellular synapses. The neural network simulation integrates computational programming and the visualization of the neurons and synapse connections of C. elegans, containing the specific controllable circuits and their dynamic characteristics. To illustrate the biological neural network (BNN)’s particular intelligent control capability, we introduced an innovative methodology for applying the BNN model to a 12-legged robot’s movement control. Two methods were designed, one involving orientation control and the other involving locomotion generation, to demonstrate the intelligent control performance of the BNN. Both the simulation and experimental results indicate that the robot exhibits more autonomy and a more intelligent movement performance under BNN control. The systematic approach of employing the whole-brain BNN for robot control provides biomimetic research with a framework that has been substantiated by innovative methodologies and validated through the observed positive outcomes. This method is established as follows: (1) two integrated dynamic models of the C. elegans’ whole-brain network and the robot moving dynamics are built, and all of the controllable circuits are discovered and verified; (2) real-time communication is achieved between the BNN model and the robot’s dynamical model, both in the simulation and the experiments, including applicable encoding and decoding algorithms, facilitating their collaborative operation; (3) the designed mechanisms using the BNN model to control the robot are shown to be effective through numerical and experimental tests, focusing on ‘foraging’ behavior control and locomotion control. Full article

The traditional Model-Based Reinforcement Learning (MBRL) algorithm has high computational cost, poor convergence, and poor performance in robot spatial cognition and navigation tasks, and it cannot fully explain the ability of animals to quickly adapt to environmental changes and learn a variety of complex tasks. Studies have shown that vicarious trial and error (VTE) and the hippocampus forward prediction mechanism in rats and other mammals can be used as key components of action selection in MBRL to support “goal-oriented” behavior. Therefore, we propose an improved Dyna-Q algorithm inspired by the forward prediction mechanism of the hippocampus to solve the above problems and tackle the exploration–exploitation dilemma of Reinforcement Learning (RL). This algorithm alternately presents the potential path in the future for mobile robots and dynamically adjusts the sweep length according to the decision certainty, so as to determine action selection. We test the performance of the algorithm in a two-dimensional maze environment with static and dynamic obstacles, respectively. Compared with classic RL algorithms like State-Action-Reward-State-Action (SARSA) and Dyna-Q, the algorithm can speed up spatial cognition and improve the global search ability of path planning. In addition, our method reflects key features of how the brain organizes MBRL to effectively solve difficult tasks such as navigation, and it provides a new idea for spatial cognitive tasks from a biological perspective. Full article

The rootstock ‘Rootpac R’ is not used for apricots. The aim of this study was to evaluate the characteristics of ‘Rootpac R’ in comparison to the widely used ‘Myrobalan 29C’ rootstock. The evaluation of the rootstocks was conducted in combination with 16 scion cultivars to assess their effects on vegetative traits and mortality. The total height of the trees on ‘Rootpac R’ initially surpassed the ‘Myrobalan 29C’ trees. By the end of the fourth year, both rootstocks showed comparable heights with ‘Rootpac R’ standing at 317 cm and ‘Myrobalan 29C’ standing at 307 cm. Both rootstocks exhibited comparable TCSA values of 5 cm² initially; ‘Rootpac R’ surpassed 35% compared to ‘Myrobalan 29C’. Canopy space occupancy assessments revealed that ‘Rootpac R’ initially demonstrated superior space utilization, occupying 8% of the designated volume compared to 4% for ‘Myrobalan 29C’. By the fourth year, ‘Rootpac R’ exhibited a higher occupancy rate of 65% compared to 50% for ‘Myrobalan 29C’. For apricot cultivars, such as ‘Bergeron’, ‘C. óriás’, ‘Gönci magyarkajszi’, ‘Lady Cot’, ‘Tardif de Valance’, and ‘Tom Cot’, ‘Rootpac R’ exhibited survival rates beyond the fourth season, highlighting its effectiveness for these varieties. Based on these results, ‘Rootpac R’ rootstock could be useful in apricot growing. Full article

There are many works associating the presence of nitrate in water and the occurrence of cancer in humans. The most common method for quantifying nitrate in water is based on the use of toxic cadmium as a reductant. In this work, a new approach was developed for the quantification of nitrate in bottled water with indirect spectrophotometry using Zn⁰ as a reductant. Nitrate is reduced to nitrite using Zn⁰ in a buffered medium (acetate/acetic acid) and quantified with visible spectrophotometry using the Griess reaction between sulfanilamide and N-(1-naphthyl)-ethylenediamine. The influence of pH, buffer solution (constitution and concentration), Zn⁰ (mass and granulometry), and agitation time on the efficiency of nitrite generation was evaluated. The optimal conditions were an acetate–acetic acid buffer solution with a concentration and pH of 0.75 mol L⁻¹ and 6.00, respectively, and a Zn⁰ particle size of 20 MESH and Zn⁰ mass of 300 mg. The limits of detection and quantification (LoD and LoQ) were 0.024 and 0.08 mg L⁻¹, respectively. The method’s accuracy and precision were evaluated using the analysis of commercial bottled water. In conclusion, the use of Zn⁰ instead of cadmium provided a green method with excellent LoD/LoQ. Further, the method proved to be simple and easy to apply during outdoor analysis. Full article

Current source apportionment models have successfully identified emission sources and quantified their contributions. However, when being utilized for heavy metal source apportion in soil, their accuracy needs to be improved, regarding migration patterns. Therefore, this work intended to improve the pre-existing principal component analysis and multiple linear regression with distance (PCA-MLRD) model to effectively locate pollution pathways (traffic emissions, irrigation water, atmospheric depositions, etc.) and achieve a more precise quantification. The dataset of soil heavy metals was collected from a typical area in the Chang-Zhu-Tan region, Hunan, China in 2021. The identification of the contribution of soil parent material was accomplished through enrichment factors and crustal reference elements. Meanwhile, the anthropogenic emission was identified with principal component analysis and GeoDetector. GeoDetector was used to accurately point to the pollution source from a spatial differentiation perspective. Subsequently, the pollution pathways linked to the identified sources were determined. Non-metal manufacturing factories were found to be significant anthropogenic sources of local soil contamination, mainly through rivers and atmospheric deposition. Furthermore, the influence of irrigation water on heavy metals showed a more pronounced effect within a distance of 1000 m, became weaker after that, and then gradually disappeared. This model may offer improved technical guidance for practical production and the management of soil heavy metal contamination. Full article