In this paper, a novel laser-induced TIG arc narrow-gap welding technology is proposed for thick plates of TC4 titanium alloy. The feasibility of achieving high-performance welding joints is investigated by adjusting the spatial deviation position of the laser, arc, and filler wire. The results exhibited remarkable capabilities. By augmenting the laser-arc malposition, a stable deflection of the arc can be achieved, resulting in enhanced heat input to the sidewall adjacent to the laser side and improved fusion capability. Moreover, an inclined weld can be obtained through increased malposition between the filler wire and arc, which helps to improve interlayer fusion and suppress porosity defects. This method, involving alternating bilateral offsets between passes, successfully achieved narrow-gap welding of 24 mm-thick TC4 titanium alloy with an average tensile strength of 880.68 MPa (equivalent to 95.05% of base material strength). Therefore, this technology exhibits promising potential as an automated welding technique for achieving high-quality narrow-gap welding in titanium alloys. Full article

The general population’s assessment and perception of a city can be influenced by its skyline, which is one of its representatives. This paper uses semantic segmentation and exploratory factor analysis to conduct a study from two different perspectives, aiming to analyse the development and current situation of the skyline of Hefei’s political and cultural new district. By collecting pictures of the skyline of the New Administrative and Cultural District, the New Administrative and Cultural District of Hefei’s skyline is being studied for overall changes using the semantic segmentation method, and to evaluate the quality of the skyline in various years, the entropy weight–TOPSIS is employed. Through the literature investigation and creation status of the new political and cultural district, the index system is scientifically formulated to conduct a questionnaire survey, and its reliability and validity are tested. This study is conducted with exploratory factor analysis of factors that are vital in the city skyline. The results of this study show that (1) after the semantic segmentation of the pictures, it is found that the proportion of buildings and the proportion of vegetation are both rising; the proportion of buildings tends to level off after 2018, and the proportion of vegetation shows a uniform increase. In the relative proximity ranking, the overall trend is increasing, and the skyline is ranked first in 2024. (2) Two variables were identified based on the findings of the exploratory factor analysis: ‘skyline value’ and ‘neighbourhood ecological quality’. The results of this study show that the skyline of Hefei’s New Administrative and Cultural District in 2024 is the best overall, and that the skyline of the New Administrative and Cultural District has developed into one of the city images of Hefei, and that its optimisation can be considered in terms of the “quality of the surrounding ecological environment”. Full article

Due to the rapid development of high-speed trains, the service safety of vehicle body materials and structures has become a focal point in transport and impact engineering. Numerical simulations on the collision resistance of vehicle materials and structures are crucial for the safety assessment and optimal structural design of high-speed trains but have not been fully investigated due to the lack of damage model parameters. This study focuses on the Johnson-Cook (J-C) constitutive and damage-fracture models of a typical vehicle material, Q345C steel. A series of mechanical tests are conducted on the Q345C steel, including the quasi-static and dynamic compression/tension tests, quasi-static tension tests at different temperatures, and fracture tests along different stress paths, using the material test system and the split Hopkinson pressure/tension bar. Then, the parameters of the Johnson-Cook constitutive and damage-fracture models are calibrated based on the experimental results. In terms of the damage parameters related to stress paths, a new method of combining experiments and simulations is proposed to obtain the real, local fracture strains of the Q345C steel samples. This method allows the measurements of equivalent plastic strain and stress triaxiality histories under nonlinear stress paths, which are hardly accessible from individual experiments, and facilitates the accurate calibration of stress-path-related damage parameters. In addition, a high-speed plate penetration test is used to validate the J-C parameters, which can be directly implemented in the commercial finite element software Abaqus. The projectile trajectories from the simulation and experiment agree well with each other, demonstrating the reliability of the model parameters for impact scenarios and the efficiency of the experimental procedures utilized for calibration. Full article

Genetic mutations leading to premature termination codons are known to have detrimental effects. Using the Lepidoptera model insect, the silkworm (Bombyx mori), we explored the genetic compensatory response triggered by mutations with premature termination codons. Additionally, we delved into the molecular mechanisms associated with the nonsense-mediated mRNA degradation pathway. CRISPR/Cas9 technology was utilized to generate a homozygous bivoltine silkworm line BmTrpA1^−/− with a premature termination. Transcript levels were assessed for the BmTrpA paralogs, BmPyrexia and BmPainless as well as for the essential factors Upf1, Upf2, and Upf3a involved in the nonsense-mediated mRNA degradation (NMD) pathway. Upf2 was specifically knocked down via RNA interference at the embryonic stage. The results comfirmed that the BmTrpA1 transcripts with a 2-base deletion generating a premature termination codon in the BmTrpA1^−/− line. From day 6 of embryonic development, the mRNA levels of BmPyrexia, BmPainless, Upf1, and Upf2 were significantly elevated in the gene-edited line. Embryonic knockdown of Upf2 resulted in the suppression of the genetic compensation response in the mutant. As a result, the offspring silkworm eggs were able to hatch normally after 10 days of incubation, displaying a non-diapause phenotype. It was observed that a genetic compensation response does exist in BmTrpA1^−/− B. mori. This study presents a novel discovery of the NMD-mediated genetic compensation response in B. mori. The findings offer new insights into understanding the genetic compensation response and exploring the gene functions in lepidopteran insects, such as silkworms. Full article

In addressing the challenge of assessing healthy brain aging across diverse interventions, this study introduces the use of MRI-derived Brain Healthcare Quotients (BHQ) for comprehensive evaluation. We analyzed BHQ changes in 319 participants aged 24–69, who were allocated into dietary (collagen peptide, euglena, matcha, isohumulone, xanthophyll) and physical activity (hand massage with lavender oil, handwriting, office stretching, pink lens, clinical art) groups, alongside a control group, over a month. These interventions were specifically chosen to test the efficacy of varying health strategies on brain health, measured through BHQ indices: GM-BHQ for gray matter volume, and FA-BHQ for white matter integrity. Notably, significant improvements in FA-BHQ were observed in the collagen peptide group, with marginal increases in the hand massage and office stretching groups. These findings highlight BHQ’s potential as a sensitive tool for detecting brain health changes, offering evidence that low-intensity, easily implemented interventions can have beneficial effects on brain health. Moreover, BHQ allows for the systematic evaluation of such interventions using standard statistical approaches, suggesting its value in future brain healthcare research. Full article

Common-mode voltage (CMV) brings shaft voltage and shaft current, and corrodes the bearings of the permanent-magnet synchronous machine (PMSM), which affects the reliability of the whole PMSM drive system. Since the CMV applied by the zero voltage vectors (ZVVs) is three times that applied by the active voltage vectors (AVVs), a modulation scheme achieving minimum CMV without ZVV is proposed and introduced into the model predictive control structure for the PMSM drive system. Firstly, the whole modulation range is divided into three regions, including the low voltage modulation region (LVMR), high voltage modulation region (HVMR), and over-voltage modulation region (OVMR). Meanwhile, the regional boundary expression is derived. Then, the active zero-state pulse width modulation (AZSPWM) is adopted in LVMR. To improve the steady-state performance, near-state pulse width modulation (NSPWM) without opposite ZVVs is applied to the HVMR. Furthermore, when the reference voltage vector (VV) is located in OVMR, an optimal scheme is proposed to improve the dynamic response. Under the premise of no ZVV existing in the whole modulation region, simulation and experimental results show that the proposed hybrid modulation method can improve the steady-state and dynamic performance of the PMSM drive system. Full article

The eastern Junggar Basin in Xinjiang harbors abundant coal resources within the Middle Jurassic Xishanyao Formation. However, the formation environment associated with these coal-bearing strata remains unclear. Geochemical characteristics serve as crucial geological indicators of the sedimentary period. Therefore, it is imperative to explore the geochemical attributes and sedimentary context of the coal-rich layers within the Middle Jurassic Xishanyao Formation in the Zhundong region to enhance the prospects of coal extraction and utilization. The elemental compositions, both major and trace, of the Xishanyao Formation were analyzed through X-ray fluorescence spectrometry (XRF) and inductively coupled plasma mass spectrometry (ICP-MS). A comprehensive analysis was conducted on the sediment provenance, tectonic background, and depositional environment of the coal-bearing strata in the Xishanyao Formation. Moreover, through the utilization of a range of discrimination indices, including Sr/Cu, B/Ga, Sr/Ba, V/Cr, Ni/Co, and δCe, the paleo-depositional setting of the coal-containing layers was reconstructed. The findings suggest that the primary source rocks of the coal-bearing beds in the Xishanyao Formation consist of continental tholeiites, with the predominant material composition in the source region being felsic volcanic rocks originating from the upper crust. The tectonic backdrop of the source region is marked by a continental island arc environment. During the sedimentation period of the Xishanyao Formation, the depositional environment was characterized by a freshwater oxidizing setting. Additionally, it experienced a transition from arid-hot to humid-hot before returning to arid-hot conditions. Full article

The investigation of magnesium (Mg) isotopes in dolomite has mainly focused on marine dolomite environments, leaving a significant gap in the understanding of their dynamics within lacustrine settings, especially in saline lake basins. In this study, a total of 16 sediment core samples from Well BX-7 in the Qianjiang Depression were sequentially selected for scanning electron microscope observation, whole-rock analysis for major and minor elements, and isotopic measurements including δ¹⁸O_carb, δ¹³C_carb, δ²⁶Mg_dol, and δ²⁶Mg_Si. In addition, two intact cores were subjected to detailed analysis on the centimeter scale. Sedimentation models were established to elucidate dolomite formation under contrasting climatic conditions, specifically humid climates with a significant riverine Mg input versus relatively dry conditions with a lower Mg input. Furthermore, a quantitative model was developed to assess the magnesium flux and isotopic mass balance within lacustrine systems, simulating the magnesium isotope variations in lake water under different climatic scenarios. The dolomite sample data at a smaller scale (sampling interval ≈ 3~5 mm) demonstrate a consistent trend with the established model, providing additional confirmation of its reliability. Dolomite precipitated under humid climatic conditions exhibits a lower and relatively stable δ²⁶Mg_dol, lower δ¹⁸O, and higher CIA, indicating higher river inputs and relatively stable Mg isotope values of lake water controlled by river input. Nevertheless, dolomite formed under relatively dry climatic conditions shows a relatively high δ²⁶Mg_dol, higher δ¹⁸O, and lower CIA, suggesting reduced river inputs and weathering intensity, as well as relatively high magnesium isotope values of the lake water controlled by dolomite precipitation. This study contributes to the understanding of magnesium isotopes in lacustrine dolomite systems. Full article

In this study, the idea of using a fully symmetric U-Net deep learning model for forecasting a segmented image of high global aerosol concentrations is implemented. As the forecast relies on historical data, the model used a sequence of the last eight segmented images to make the prediction. For this, the classic U-Net model was modified to use ConvLSTM2D layers with MaxPooling3D and UpSampling3D layers. In order to achieve complete symmetry, the output data are given in the form of a series of eight segmented images shifted by one image in the time sequence so that the last image actually represents the forecast of the next image of high aerosol concentrations. The proposed model structure was tuned by the new FOX metaheuristic algorithm. Based on our analysis, we found that this algorithm is suitable for tuning deep learning models considering their stochastic nature. It was also found that this algorithm spends the most time in areas close to the optimal value where there is a weaker linear correlation with the required metric and vice versa. Taking into account the characteristics of the used database, we concluded that the model is capable of generating adequate data and finding patterns in the time domain based on the ddc and dtc criteria. By comparing the achieved results of this model using the AUC-PR metric with the previous results of the ResNet3D-101 model with transfer learning, we concluded that the proposed symmetric U-Net model generates data better and is more capable of finding patterns in the time domain. Full article

Coconut palms (Cocos nucifera L.) are globally significant palms with both economic and cultural value. Despite the increasing demand for coconut products, production is decreasing globally due to palm senility, pests, and diseases. It has been estimated that over half of the world’s coconut palms need to be replaced immediately. The coconut industry has acknowledged that conventional propagation methods are unlikely to yield sufficient high-quality planting material. Therefore, coconut tissue culture is considered a potential solution to this problem. By using coconut tissue culture, a large number of plantlets can be obtained in a short period of time. In this study, the quality of explants and the development stage (visible shoot/non-visible shoot) of coconut used for micropropagation were examined. To our knowledge, little research has been undertaken on this aspect of coconut micropropagation. Our results indicated that tender coconut fruit exhibited an advantage over mature fruits. In addition, coconut plumule explants subjected to an extended storage of 15 days demonstrated enhanced development compared to those without storage. Notably, smaller embryos utilized as explants displayed superior callus formation compared to their larger counterparts. Finally, embryos possessing shoots exhibited improved callus initiation, albeit accompanied by a more pronounced browning effect. Further investigations are required to obtain more knowledge about the most suitable conditions for plumule explants that lead to optimal callus initiation. Full article

Bamboo is a naturally occurring composite material, which exhibits a decomposable structure with varying composition. The distinct structural features of bamboo contribute to its exceptional strength and flexibility, making it an excellent choice for construction purposes. However, only a limited portion of bamboo species has been studied for its mechanical properties, and research on Bambusa arundinaceae has primarily focused on its pharmaceutical values. Therefore, we investigated the relationship between the structural characteristics of B. arundinaceae and its mechanical properties using axial compression experiments and tangential bending experiments. The results showed that the distribution density of vascular bundles (VBs) of B. arundinaceae ranged from 1.98 to 4.34 pcs/mm²,while the volume fraction of fiber sheaths (FSs) ranged from 35.82 to 42.58%. The average compressive strength, flexural strength, and flexural elasticity modulus were 113.99 MPa, 239.07 MPa, and 17.39 GPa, which were 97.56%, 64.07%, and 66.09% higher than those of moso bamboo (Phyllostachys edulis), respectively. The compressive strength, flexural strengths, and elasticity modulus of B. arundinaceae were positively correlated with both the distribution density of VBs and the volume fraction of FSs. These insights are crucial for the advancement of durable and efficient materials in diverse sectors including construction and manufacturing. Full article

Ilex chinensis Sims. is an evergreen tree species native to China and mainly distributed in the region south of the Qinling Mountains and the Huai River. This species has important ornamental, medicinal, ecological, and economic values, and plays a positive role in improving the environment and people’s lives. To reveal the genetic diversity and genetic structure of 401 individuals from 14 populations in the major distribution area of I. chinensis, 11 pairs of SSR primers were selected for PCR amplification. The products were then subjected to capillary electrophoresis, and the genetic diversity of Ilex individuals was analyzed using relevant software. The results showed that the genetic diversity of I. chinensis was at a moderate-to-high level. A total of 54 alleles were detected at 11 SSR loci in the 14 Ilex populations, with an average of 4.831 alleles per locus. AMOVA analysis indicated that the genetic variation of I. chinensis populations mainly originated within populations. A STRUCTURE analysis divided the 401 I. chinensis individuals into four different genetic clusters. The unweighted pair group methods using arithmetic averages (UPGMA) clustering based on Nei’s genetic distance revealed that the population from Xinping of Yuxi, Yunnan Province (XP), and the population from Longan of Qianxinan, Guizhou Province (LoA) were located in the outermost layer of the phylogenetic tree, indicating the furthest genetic relationship between these two population and other populations. The remaining populations could be roughly divided into two groups. Principal coordinate analysis (PCoA) demonstrated that the 401 individuals were clearly divided into three groups, which was consistent with the results of the STRUCTURE analysis and UPGMA clustering. This study identified the hotspots of genetic diversity of I. chinensis, as well as units for the conservation of individuals. It also revealed the patterns of genetic variation and population distribution of I. chinensis in different regions, providing a molecular basis for the geographical zoning and formulation of breeding programs for I. chinensis, as well as germplasm resource management. Full article

Ginkgo biloba L. is a valuable medicinal plant known for its high content of flavonoids and terpenoids in the leaves of young trees. Pruning can increase leaf yield in ginkgo plantations; however, it is unclear how the intensity of pruning affects leaf yield and quality. In addition, G. biloba exhibits low cutting rooting rates, which limits its efficiency in asexual propagation. In our study, we compared consecutive pruning with varying levels of intensity, including top pruning, light pruning, and heavy pruning, to evaluate the effects of pruning on leaf yield and cutting rooting. The results showed that these three pruning methods all contributed to an increase in the number of new branches, the leaf weight, and the flavonoid content in five-year-old trees. Among them, the effect of light pruning was the best, with a 150% increase in branch number, a 130% increase in leaf weight, and a 40.6% increase in flavonoid content. The secondary pruning further increased leaf area by 22.3%, indicating that secondary pruning further enhanced the rejuvenation of plants and increased leaf yield. At the transcriptional level, pruning can significantly change the expression of genes related to bud sprouting, resulting in a particularly significant increase in SHR expression in the buds. Pruning also promoted the expression of important genes related to flavonoid synthesis, including chalcone synthase (CHS), flavonoid 3′-hydroxylase (F3′H), flavonol synthase (FLS), and dihydroflavonol reductase (DFR). Furthermore, we demonstrated a significant increase in the rooting rate of these second-pruned branch cuttings and screened the optimal hormone ratio for rooting, which is 1.5 μM MeJA + 400 mg/L NAA + 100 mg/L Uniconazole-P. These results suggest that secondary pruning can effectively rejuvenate plants to promote cutting rooting in G. biloba. This method can not only be used to improve the yield and quality of ginkgo leaves, but also for cutting propagation. Full article

Ginkgo biloba L. leaves are rich in secondary metabolites with important medicinal values; to increase their contents, foliar spraying of micronutrients is a potential strategy. Zinc, a multifunctional element, has a significant impact on the content of secondary metabolites in other plants, but relevant research into ginkgo is still lacking. In our study, different spraying time and concentration strategies were used to investigate the effects of zinc sulfate (ZnSO₄) on physiological indicators and secondary metabolites of 2-year-old ginkgo. The results demonstrated that ZnSO₄ could increase the contents of hydrogen peroxide, abscisic acid, and free amino acids in ginkgo leaves. It also enhances the antioxidant enzyme activity of ginkgo leaves, decreases the content of plant auxin, and ultimately facilitates the accumulation of ginkgo terpene lactones (TTL). Spraying ZnSO₄ in June resulted in a more significant increase in the contents of TTL and flavonoids compared to spraying in August. After spraying 12 mmol/L ZnSO₄ in June, the contents of TTL and flavonoids in ginkgo leaves were significantly elevated by 35.95% and 24.30%, respectively, compared to those in the CK (p < 0.05). The contents of ginkgolide A, B, and C were notably increased by 45.93%, 46.56%, and 74.29%, respectively, compared to those in the CK (p < 0.05). Therefore, our study suggests that the optimal timing for spraying ZnSO₄ on ginkgo is in June, with a recommended concentration of 12 mmol/L. Our study provides a theoretical basis for the accumulation of secondary metabolites in ginkgo and guides the production of its leaf-utilization plantations. Full article

The Mediterranean Basin is severely impacted by anthropogenic changes affecting both natural ecosystems and human livelihoods. The region is highly vulnerable to natural hazards, with floods being considered the most important, due both to their frequency and impacts. Koiliaris watershed (northwest of Crete Island, Greece) represents a relevant case study as past land-use changes via deforestation and intense cultivation practices induce soil organic matter losses, making soils susceptible to water erosion and desertification. The restoration of native riparian forests has been identified as the most effective nature-based solution (NBS) for the area. Through modeling, our study assessed the effectiveness of this NBS in addressing flood risk and erosion while providing additional ecosystem services (carbon sequestration and biodiversity conservation). A cost–benefit analysis has been then implemented to also investigate the sustainability of the investment from an economic point of view. Our results show the NBS would be successful in ensuring a better flow of targeted ecosystem services compared to the business-as-usual conditions. The associated investment would result in economic sustainability and associated costs would be paid back in five years. Though site-specific, our study provides lessons learned for dealing with future land-restoration challenges in the Mediterranean to cope with climate change-related challenges. Full article

Tree height is one of the key dendrometric parameters for indirectly estimating the timber volume or aboveground biomass of a forest. Field measurement is time-consuming and labor-intensive, while unmanned aerial vehicle (UAV)-borne LiDAR is a more efficient tool for acquiring tree heights of large-area forests. Although individual tree heights extracted from point cloud data are of high accuracy, they are still affected by some weather and environment factors. In this study, taking a planted M. glyptostroboides (Metasequoia glyptostroboides Hu & W.C. Cheng) stand as the study object, we preliminarily assessed the effects of various illumination conditions (solar altitude angle and cloud cover) on tree height extraction using UAV LiDAR. The eight point clouds of the target stand were scanned at four time points (sunrise, noon, sunset, and night) in two consecutive days (sunny and overcast), respectively. The point clouds were first classified into ground points and aboveground vegetation points, which accordingly produced digital elevation model (DEM) and digital surface model (DSM). Then, the canopy height model (CHM) was obtained by subtracting DEM from DSM. Subsequently, individual trees were segmented based on the seed points identified by local maxima filtering. Finally, the individual tree heights of sample trees were separately extracted and assessed against the in situ measured values. As results, the R² and RMSEs of tree heights obtained in the overcast daytime were commonly better than those in the sunny daytime; the R² and RMSEs at night were superior among all time points, while those at noon were poorest. These indicated that the accuracy of individual tree height extraction had an inverse correlation with the intensity of illumination. To obtain more accurate tree heights for forestry applications, it is best to acquire point cloud data using UAV LiDAR at night, or at least not at noon when the illumination is generally strongest. Full article

Promoting the development of eco-industries plays a significant role in achieving the harmonious symbiosis between economic growth and environmental protection as well as enhancing the comprehensive effectiveness of ecological and economic benefits. Due to their unique nature, cooperatives may play a crucial role in facilitating the integration between farmers and the development of eco-industries. To investigate whether cooperatives possess the capacity to enhance the income-generating effects for farmers involved in eco-industries, this study selected the Crested Ibis National Nature Reserve (CINNR), a representative area for eco-industry development, as the research site. Data were gathered through face-to-face interviews, and this research empirically analyzed the impact of cooperatives on the income-generating effect of farmers using endogenous switching regression (ESR). The findings are threefold. First, cooperatives indeed enhance the income-generating effects for farmers engaged in eco-industries. Second, variables such as the distribution of agroforestry materials, premium capacity, soil quality, and status of village cadres have a positive impact on farmers joining cooperatives, whereas punishment initiatives discourage their participation. Third, for farmers who have joined cooperatives, factors such as the distribution of agroforestry materials, premium capacity, low-cost conservation initiatives, land area, status of village cadres, the proportion of labor force, technical training, soil quality, and land area positively affect their income from eco-industries. Conversely, punishment initiatives, age, and land location negatively impact their income. The results of this study provide new ideas for farmers to participate in the development of eco-industries, new evidence showing co-operatives can improve farmers’ income, and new directions for coordinating conflicts between conservation and development in protected areas. Full article

Urban green spaces play a vital role in improving the quality of life and well-being of urban residents. However, their economic benefits in different spatial contexts within highly urbanized areas remain a critical yet understudied topic. This study delves into the economic value of urban green spaces in Cheongju City, Republic of Korea, and investigates the distance-decay features associated with the proximity of green spaces to residential properties. Two spatial econometric models were employed to address these questions: the spatially autoregressive (SAR) model and the generalized additive model (GAM). The SAR model was used to assess the economic benefits of urban green spaces, whereas the distance decay of these benefits was examined with the GAM. Empirical analyses revealed that small-sized parks or forests under 20 ha hold greater economic value when in proximity to residential areas compared to medium-sized parks or forests between 20 and 200 ha. Conversely, large parks or forests over 200 ha appeared to have a disamenity effect, negatively impacting property prices when in close proximity. The GAM’s smooth functions illustrated that the distance-decay effect was shorter for small-sized green spaces and exhibited an inverted U-shape for large-sized ones, resulting in a negative benefit of proximity. Our findings suggest that urban green spaces have a positive impact on property prices, but this effect may not apply uniformly to large-sized parks or forests. Therefore, to enhance the residents’ welfare, green infrastructure policies should prioritize the provision of accessible small- and/or medium-sized parks or forests near residential areas. Full article

Of the numerous methods applied in rainfall-runoff models, the most common is the NRCS-CN method that is applied to calculate raised-water runoffs and compare them with the runoff values measured for 12 selected rainfall-runoff events. This study was conducted on three experimental forest catchments with an area ranging from 67.6 to 747 ha. Total rainfall values ranging from 22.2 to 84.1 mm were analysed. Relatively low effective rainfall values were obtained for the lowest average for catchment 1 (Pe = 0.23 mm) and the runoff coefficient (α = 0.40%) and for the highest average for catchment 3 (Pe = 1.35 mm) and an average runoff coefficient (α = 3.12%). The maximum potential retention Si value, corresponding to each pair of P-Pe events, was the effect of the catchment’s moisture and absorptive capacity conditions. The lowest retention S value was calculated for catchment 3. The highest average retention value was calculated for catchment 1, in which the lightest soils were found. The best fit of the initial loss coefficient for the majority of rainfall-runoff events occurred for the λ coefficient values of 0.05 and 0.075. At higher λ, the effective rainfall Pe was not generated. LAG times calculated using 10 methods yielded diverse values. The fit of a specific formula was largely influenced by the size of the catchment, as well as the number and type of parameters considered during model calibration. The method based on catchment width demonstrated the best fit for all catchments, with R² ranging from 0.77 to 0.78 and RMSE from 0.52 for catchment 2 to 1.11 for catchment 1. Full article

The amount of rainfall in different regions is influenced by various factors, including time, place, climate, and geography. In the Lake Urmia basin, Mediterranean air masses significantly impact precipitation. This study aimed to model precipitation in the Lake Urmia basin using monthly rainfall data from 16 meteorological stations and five machine learning methods (RF, M5, SVR, GPR, and KNN). Eight input scenarios were considered, including the monthly index, longitude, latitude, altitude, distance from stations to Lake Urmia, and distance from the Mediterranean Sea. The results revealed that the random forest model consistently outperformed the other models, with a correlation rate of 0.968 and the lowest errors (RMSE = 5.66 mm and MAE = 4.03 mm). This indicates its high accuracy in modeling precipitation in this basin. This study’s significant contribution is its ability to accurately model monthly precipitation using spatial variables and monthly indexes without measuring precipitation. Based on the findings, the random forest model can model monthly rainfall and create rainfall maps by interpolating the GIS environment for areas without rainfall measurements. Full article

In this work, the spatial distribution, potential sources, and risk assessment of perfluoroalkyl substances (PFASs) were investigated at 22 surface water sampling sites in Hefei City. The study encompassed 11 distinct types of PFASs, which included 7 perfluoroalkyl carboxylic acids (PFCAs) and 4 perfluoroalkyl sulfonic acids (PFSAs). The findings indicated that the overall concentration of PFASs varied between 12.96 to 545.50 ng/L, with perfluorooctanoic acid (PFOA), perfluorobutanesulfonic acid (PFBS), perfluorobutyric acid (PFBA), and perfluorohexanoic acid (PFHxA) being the most prevalent, contributing to an average of 71% of the total PFASs concentration. Principal component analysis (PCA) elucidated the primary sources of PFASs, which included industrial emissions, fluoropolymer production and treatment, textile processing, and the impact of the electroplating industry. Employing the risk quotient (RQ) method facilitated the assessment of ecological risks associated with PFASs in surface water within the study area, suggesting that the current concentrations of PFASs in Hefei’s surface water pose a relatively low ecological risk. However, the long-term ecological effects of PFASs cannot be overlooked due to their potential for long-range transport and the cumulative nature of biological food chains. Full article

This study assesses the performance of the Weather Research and Forecasting (WRF) model using a high-resolution spatial grid (1 km) with various combinations of physical parameterization packages to simulate a severe event in August 2021 in the southeastern Brazilian coast. After determining the optimal set of physical parameterizations for representing wind patterns during this event, a year-long evaluation was conducted, covering forecast horizons of 24, 48, and 72 h. The simulation results were compared with observational wind data from four weather stations. The findings highlight variations in the efficacy of different physical parameterization sets, with certain sets encountering challenges in accurately depicting the peak of the severe event. The most favorable results were achieved using a combination of Tiedtke (cumulus), Thompson (microphysics), TKE (boundary layer), Monin-Obukhov (surface layer), Unified-NOAH (land surface), and RRTMG (shortwave and longwave radiation). Over the one-year forecasting period, the WRF model effectively represented the overall wind pattern, including forecasts up to three days in advance (72-h forecast horizon). Generally, the statistical metrics indicate robust model performance, even for the 72-h forecast horizon, with correlation coefficients consistently exceeding 0.60 at all analyzed points. While the model proficiently captured wind distribution, it tended to overestimate northeast wind speed and gust intensities. Notably, forecast accuracy decreased as stations approached the ocean, exemplified by the ATPM station. Full article