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In the formerly glaciated terrains in the northern hemisphere and countries such as Finland, till is the most common sediment covering the bedrock. Specifically, indicator or heavy mineral studies utilising till as a vector for mineral deposits undercover have been successful. The pyrite trace-element composition from in situ mineral analyses has been shown to be an effective discriminator between different mineral deposit types, and this has led to research using heavy mineral pyrite in till to identify potential mineral deposits in a given area. However, pyrite is easily oxidised in till beds, and thus, alternative methods should be considered. Goethite pseudomorphs are more commonly found in the till sediments as remnants after pyrite oxidation. This study evaluates trace element compositions of goethitised pyrite recovered in the till beds from central Lapland in northern Finland. Intra-grain trace-elemental variations gathered using laser-ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) between the intact pyrite core and oxidised rim demonstrated complex dynamics and variations between different trace-element values. For example, Cu, V and Mn exhibited elevated trace-element values in the goethite rim compared to the pyrite core. However, elemental ratios such as Ni/As and Co/Ni remain stable between the pyrite core and oxidised rim. Therefore, these ratios have the potential to be used as a discriminating tool between the pyrite core and oxidised rim. In addition, nanoscale variabilities using focused ion beam (FIB) and transmission electron microscopy (TEM) were utilised to inspect possible nano inclusions within the studied heavy mineral grain. The FIB and TEM studies revealed a nanocrystalline pyrite nodule observation within the goethite rim. Full article

Plants are being researched as potential sources of novel drugs, which has led to a recent acceleration in the discovery of new bioactive compounds. Research on tissue culture technology for the synthesis and processing of plant compounds has skyrocketed, surpassing all expectations. These plants can be bought either raw or as extracts, where some of the chemicals are extracted by mashing the plant in water, alcohol, or another solvent. The use of herbal medicine may open new chances for reducing the onset of infections and treating different diseases including cancer. A perennial plant that blooms in the winter, Cyclamen, is one of the most widely used potted flowers in many nations. Alkaloids, flavonoids, phenols, tannins, saponins, sterols, and glycosides are the main active components of Cyclamen. Analgesic, cytotoxic, antioxidant, antimicrobial, and anti-inflammatory properties have all been demonstrated as potential effects of various extracts of Cyclamen tubers. However, the use of this medicinal plant in official medicine will require further research in the areas of pharmacology. Furthermore, it is necessary to create standard operating procedures for a crude herbal medication. In this regard, this review aims to highlight the key characteristics of the Cyclamen plant, such as its various parts, species, stages of development, and geographic range; pinpoint its intriguing bioactivities, its antioxidant, anti-inflammatory, and its anti-cancerous effects; and ascertain its potential medicinal uses and the main future perspectives. Full article

Changes in weather conditions directly impact the output of wind power, photovoltaic systems, and other forms of uncontrollable power generation. During extreme weather events, the output from wind and photovoltaic sources is typically reduced. In light of this, this paper proposes a two-stage operational strategy for energy storage, under scenarios of extreme-heat-with-low-wind-speed, in power systems. Firstly, historical data on wind and solar power, along with weather characteristics, are collected to analyze the power output during multi-day periods of extreme heat and low wind speed. Then, Monte Carlo simulations are employed to generate multi-day load curves with inherent uncertainties, based on regional load characteristics of the power system. Finally, a two-stage operation strategy for energy storage charging and discharging is established. In the first stage, normal operations are conducted to identify periods of power shortage across various types of loads. In the second stage, based on the identified moments of power shortage from the first stage, charging and discharging constraints are applied to the energy storage systems. The feasibility and effectiveness of this two-stage operational strategy are then validated through simulations, using historical data to generate scenarios of multi-day extreme-heat-and-low-wind-speed conditions. Full article

Distracted driving significantly affects the efficiency and safety of traffic flow. Modeling distracted driving behavior in microscopic traffic flow simulation is essential for understanding its critical impacts on traffic flow. However, due to the influence of various external factors and the considerable uncertainties in behavior characteristics, modeling distracted driving behavior remains a challenge. This study proposed a model which incorporates distraction features into the microscopic traffic flow model to simulate distracted driving behavior. Specifically, the study first examines the characteristics of distracted driving, including the intervals and durations of distraction events, as well as the patterns and environments of distraction. It then introduces distraction parameters into the Intelligent Driver Model (IDM), including reaction time delays and perception deviations in both speed difference and following distance. These parameters are quantified by probabilistic distributions to reflect the uncertainty and individual differences in driving behavior. The model is calibrated and validated using 772 distracted following events from the Shanghai Naturalistic Driving Study (SH-NDS) data. Three patterns of distraction (excessive, moderate, mild) are distinguished and modeled separately. The results show that the model's accuracy surpasses that of the IDM under various road types and traffic volumes, with an average improvement in model accuracy of about 11.30% on expressways with high traffic volume, 4.54% on expressways with low traffic volume, and 4.46% on surface roads. Meanwhile, the model can effectively simulate the variations in reaction times and perceptual deviations in both speed and following distance for different distraction modes at the individual level, maintaining consistency with reality. Finally, the study simulates distracted driving behavior under different road environments and traffic volumes to explore the impact of distracted driving on traffic flow. The simulation results indicate that an increase in the proportion of distraction reduces the efficiency and safety of traffic flow, which is consistent with real-world observations. Since the model considers human distraction factors, it can generate more dangerous driving scenarios in simulations, which holds significant importance for safety-related research. The findings from this study are expected to be helpful for understanding distracted driving behavior and mitigate its negative influence on the efficiency and safety of traffic flow. Full article

Background/Objectives: The aim of this study was to analyze a group of patients with a bicuspid aortic valve (BAV) examined with ECG-gated cardiac CT (ECG-CT), focusing on the assessment of the clinical reasons for cardiac CT, cardiovascular abnormalities coexisting with their BAV, and coronary artery stenosis. Methods: A detailed statistical analysis was conducted on 700 patients with a BAV from a group of 15,670 patients examined with ECG-CT. Results: The incidence of a BAV in ECG-CT was 4.6%. The most common reason for examination was suspicion of coronary heart disease—31.1%. Cardiovascular defects most frequently associated with a BAV were a VSD (4.3%) and coarctation of the aorta (3.6%), while among coronary anomalies, they were high-take-off coronary arteries (6.4%) and paracommissural orifice of coronary arteries (4.4%). The analysis of the coronary artery calcium index showed significantly lower values for type 2 BAV compared to other valve types (p < 0.001), with the lowest average age in this group of patients. Moreover, the presence of a raphe between the coronary and non-coronary cusps was associated with a higher rate of significant coronary stenosis compared to other types of BAVs (p < 0.001). Conclusions: The most common reason for referral for cardiac ECG-CT in the group ≤ 40-year-olds with a BAV was the suspicion of congenital cardiovascular defects, while in the group of over 40-year-olds, it was the suspicion of coronary artery disease. The incidence of cardiovascular abnormalities co-occurring with BAV and diagnosed with ECG-CT differs among specific patient subgroups. The presence of a raphe between the coronary and non-coronary cusps appears to be a potential risk factor for significant coronary stenosis in patients with BAVs. Full article

Leishmania (Viannia) spp. can harbor a double-stranded RNA virus known as Leishmania RNA virus 1 (LRV-1), whose presence has been reported in nine countries across the Americas and seven Leishmania species. Here, we studied 100 Leishmania (Viannia) isolates from patients with cutaneous leishmaniasis collected from different endemic areas in Panama from 2016 to 2022. We identified L. (V.) panamensis, L. (V.) guyanensis, L. (V.) braziliensis/guyanensis hybrid, and L. (V.) panamensis sp.1. (genetic variant). LRV-1 was detected by RT-PCR in 9% of L. (Viannia) isolates (eight cases in L. (V.) panamensis, and one in L. (V.) guyanensis). Phylogenetic analysis based on sequencing data classified all LRV-1 isolates within genotype A, suggesting that LRV phylogenetic proximity is closely aligned with geographical distribution or to the phylogenetic proximity of the Leishmania host in the case of the L. (V.) panamensis and L. (V.) guyanensis in Panama. Full article

Following the Belt and Road, the Air Silk Road has also been proposed. The coordinated development of multiple transportation modes, including air, land, and water, will create a strong transportation force in node cities. However, the current insufficient supply of cargo in various regions and the lack of integration among different transportation modes result in low transportation efficiency, which in turn affects the further advancement of the Belt and Road. To investigate these issues and attempt to find a solution, we selected 44 candidate cities from the prefecture-level cities in China as nodes based on relevant government policies, and constructed an integrated transportation network. For each node city, we first calculated the values of six classical indicators and then used the CRITIC to assign weights to each indicator. Subsequently, we employed the TOPSIS method combined with Grey Relational Analysis (GRA) to compute the comprehensive score for each node city. Based on the spatial layout and government policies under the BRI, eight cities, including Wuhan, Chongqing, Tianjin, Shanghai, Guangzhou, Lianyungang, Hefei, and Dalian, were finally recommended as the consolidation centers of the integrated transportation network. It is hoped that the results of this analysis can provide some insights for the government to outline and build the consolidation centers of the integrated transportation network composed of railway, air, highway, and water routes, which in turn can offer insights for elevating the Belt and Road Initiative (BRI) to a new level. Full article

Centrifugal pump pressure pulsation contains various signals in different frequency domains, which interact and superimpose on each other, resulting in characteristics such as intermittency, non-stationarity, and complexity. Computational Fluid Dynamics (CFD) and traditional time series models are unable to handle nonlinear and non-smooth problems, resulting in low accuracy in the prediction of pressure fluctuations. Therefore, this study proposes a new method for predicting pressure fluctuations. The pressure pulsation signals at the inlet of the centrifugal pump are processed using Variational Mode Decomposition–Particle Swarm Optimization (VMD-PSO), and the signal is predicted by Convolutional Neural Networks–Long Short-Term Memory (CNN-LSTM) model. The results indicate that the proposed prediction model combining VMD-PSO with four neural networks outperforms the single neural network prediction model in terms of prediction accuracy. Relatively high accuracy is achieved by the VMD-PSO-CNN-LSTM model for multiple forward prediction steps, particularly for a forward prediction step of 1 (Pre = 1), with a root mean square error of 0.03145 and an average absolute percentage error of 1.007%. This study provides a scientific basis for the intelligent operation of centrifugal pumps. Full article

The planning for the scale of the urban rail transit network (URTN) is one of the key tasks of URTN planning. The scale should match the urban development (UD). A reasonable scale can improve travel efficiency, increase economic activities, and promote UD, while an unreasonable scale may consume more urban resources, fail to meet urban transportation demands, and even inhibit UD. Currently, the URTN scale is primarily determined by qualitative analyses and static indicators, which leads to the scale does not match UD perfectly. To determine a reasonable scale, a System Dynamics–Lotka–Volterra (SD-LV) model is constructed. The SD model is adopted to simulate the dynamic interaction between the URT and UD. The LV (Lotka–Volterra) model is employed to calculate the scale, in which the mutualism coefficients are proposed to characterize the mutualistic relationships between the URT and UD. The model is validated by using a dataset of the Beijing URTN from 2017 to 2021. The simulation errors of the URTN scale range from −4.3% to 1.32%, which demonstrates the robustness and effectiveness of the proposed model. The study offers quantitative theoretical insights for determining the reasonable scale of the URTN. Full article

The scarcity of potable water emphasizes the urgent need to develop and implement more sustainable treatment technologies, considering both energy consumption and environmental impact. These technologies require effective disinfection systems that avoid the use of chemicals. Innovations in this area, utilizing UV-LED technology, can significantly improve efficiency, reduce costs, and mitigate environmental impacts. This study aimed to evaluate the antimicrobial properties of various encapsulated UV light-emitting diodes (LEDs) to identify the most suitable candidate for constructing an LED array capable of disinfecting large volumes of water. Different devices from various manufacturers, with differing costs and wavelengths, were examined, leading to the selection of the optimal candidate (LED 2) based on its antimicrobial effectiveness and cost-effectiveness. The impact of parameters such as bacterial concentration, sample volume, exposure time, and conditions on disinfection capacity was thoroughly investigated. Exposure to LED 2 resulted in substantial reductions in the viability of bacteria and yeast, demonstrating efficacy even against Clostridium perfringens endospores. Subsequently, an LED array was developed based on these findings and rigorously evaluated for efficacy, confirming its effectiveness as an efficient and environmentally friendly water treatment device. Full article

Water pollution is a major environmental challenge. Due to the inefficiency of conventional wastewater treatment plants in degrading many organic complex compounds, these recalcitrant pollutants end up in rivers, lakes, oceans and other bodies of water, affecting the environment and human health. Semiconductor photocatalysis is considered an efficient complement to conventional methods, and the use of various nanomaterials for this purpose has been widely explored, with a particular focus on improving their activity under visible light. This work focuses on developing magnetic and photoactive zinc/magnesium mixed ferrites (Zn_0.5Mg_0.5Fe₂O₄) by sol-gel and solvothermal synthesis methods, which are two of the most important and efficient methods used for the synthesis of ferrite nanoparticles. The nanoparticles (NPs) synthesized by the sol-gel method exhibited an average size of 14.7 nm, while those synthesized by the solvothermal method had an average size of 17.4 nm. Both types possessed a predominantly cubic structure and demonstrated superparamagnetic behavior, reaching a magnetization saturation value of 60.2 emu g⁻¹. Due to the high recombination rate of electrons/holes, which is an intrinsic feature of ferrites, surface functionalization with silver was carried out to enhance charge separation. The results demonstrated a strong influence of adsorption and of the deposition of silver. Several optimization steps were performed during synthesis, allowing us to create efficient catalysts, as proved by the almost full removal of the dye malachite green attaining 95.0% (at a rate constant of 0.091 min⁻¹) and 87.6% (at a rate constant of 0.017 min⁻¹) using NPs obtained by the sol-gel and solvothermal methods, respectively. Adsorption in the dark accounted for 89.2% of the dye removal for nanoparticles prepared by sol-gel and 82.8% for the ones obtained by the solvothermal method. These results make mixed zinc/magnesium ferrites highly promising for potential industrial application in effluent photoremediation using visible light. Full article

Infectious bronchitis virus (IBV) causes infectious bronchitis in chicken, an acute, highly contagious respiratory infection. Because of genetic mutations and recombination, IBV forms many subtypes, which makes it difficult to treat the disease and apply commercial vaccines. Therefore, to detect IBV in time and stop the virus from spreading, a novel and convenient IBV detection technology based on reverse transcription recombinase-aided amplification (RT-RAA) was established in this study. According to the S1 gene of IBV CH Ⅰ–Ⅴ and Mass genotypes and S1 gene of IBV CH Ⅵ genotype, a set of optimal primers were designed and selected to establish a real-time dual fluorescence RT-RAA method. The lowest detection line was 10 copies/μL of RNA molecules and the method exhibited no cross-reactivity with avian reticuloendotheliosis virus (REV), infectious bursal disease virus (IBDV), avian leukosis virus (ALV), Newcastle disease virus (NDV), chicken infectious anemia virus (CIAV), infectious laryngotracheitis virus (ILTV), Marek’s disease virus (MDV), and H9N2 avian influenza virus (H9N2), demonstrating high specificity. When compared to qPCR detection results, our method achieved a sensitivity of 96.67%, a specificity of 90%, and a Kappa value of 0.87 for the IBV CH Ⅰ–Ⅴ and Mass genotypes, and achieved a sensitivity of 100%, a specificity of 97.73%, and a Kappa value of 0.91 for the IBV CH Ⅵ genotype. Full article

In order to effectively adjust reservoir heterogeneity and further exploit the remaining oil, a new type of low-viscosity gel was prepared by adding a regulating agent, retarder, and reinforcing agent on the basis of a polymer + Cr³⁺ crosslinking system. The new gel has the advantages of low initial viscosity, a slow gel formation rate, and high strength after gel formation. The effectiveness of the gel was verified through three-layer core displacement experiments, and the injection scheme was optimized by changing the slug combination of the polymer and the gel. The results showed that the gel can effectively block the high-permeability layer and adjust reservoir heterogeneity. An injection of 0.1 pore volume (PV) low-initial-viscosity gel can improve oil recovery by 5.10%. By changing the slug combination of the gel and polymer, oil recovery was further increased by 3.12% when using an injection of 0.07 PV low-initial-viscosity gel +0.2 PV high-concentration polymer +0.05 PV low-initial-viscosity gel +0.5 PV high-concentration polymer. Full article

Evaluating the conservation effectiveness of multiple types of protected areas (PAs) on carbon sequestration services can enhance the role of PAs in mitigating global warming. Here, we evaluated the conservation status and effectiveness of national parks, nature reserves, forest parks, geo-parks, and scenic spots on carbon sequestration within the Loess Plateau throughout 2000–2020. The results show that all existing PA types have good representation and conservation effectiveness on carbon sequestration. Nature reserves are the most representative of carbon sequestration but are the least effective in protecting carbon sequestration and are the only ones that are weekly effective in protecting critical carbon sequestration. The main factors influencing these results are PA size, 2000 precipitation, slope, change rate of evapotranspiration, PA rank, and 2000 evapotranspiration. We suggest upgrading the critical carbon sequestration distribution areas in scenic spots, forest parks and geo-parks to national parks or nature reserves in the future and implementing appropriate protection and restoration measures in low carbon sequestration areas within grassland and wild plant nature reserves to help achieve the goal of carbon neutrality early. Full article