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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

In the current design work, turbine performance requirements are getting higher and higher, and turbine blade design needs multiple rounds of iterative optimization. Three-dimensional turbine optimization involves multiple parameters, and 3D simulation takes a long time. Machine learning methods can make full use of historically accumulated data to train high-precision data models, which can greatly reduce turbine blade performance evaluation time and improve optimization efficiency. Based on the data model, the advanced intelligent combinatorial optimization technology can effectively reduce the number of iterations, find the better model faster, and improve the optimization calculation efficiency. Based on the different cooling parts of turbine blades and machine learning, this research explores the potential of implementing different machine learning algorithms in the field of turbine cooling design. Full article

We present theoretical investigations examining the electronic and magnetic properties of the SmFe_12-xMo_x (x = 1,2) and SmFe₁₀Mo₂H compounds, including magneto-crystalline anisotropy, magnetic moments, exchange-coupling parameters, and Curie temperatures. The spin-polarized fully relativistic Korringa–Kohn–Rostoker (SPR-KKR) band structure method has been employed, using the coherent potential approximation (CPA) to deal with substitutional disorder. Hubbard-U correction was applied to the local spin density approximation (LSDA+U) in order to account for the significant correlation effects arising from the 4f electronic states of Sm. According to our calculations, the total magnetic moments increases with H addition, in agreement with experimental data. Adding one H atom in the near-neighbor environment of the Fe 8j site reduces the magnetic moments of Fe 8j and enhances the magnetic moment of Fe 8f. For every investigated alloy, the site-resolved spin magnetic moments of Fe on the 8i, 8j, and 8f sites exhibit the same magnitude sequence, with $m_s^{Fe}$ (8i) > $m_s^{Fe}$ (8j) > $m_s^{Fe}$ (8f). While the addition of H has a positive impact on magneto-crystalline anisotropy energy (MAE), the increase in Mo concentration is detrimental to MAE. The computed exchange-coupling parameters reveal the highest values between the closest Fe 8i spins, followed by Fe 8i and Fe 8j spins, for all investigated alloys. The Curie temperature of the alloys under investigation is increased by decreasing the Mo concentration or by H addition, which is qualitatively consistent with experimental findings. Full article

The use of mining pumps to transport solid-liquid two-phase flows results in solid particles causing varying degrees of wear in the flow-passing components of the pump. In this study, a computational fluid dynamics analysis was performed employing SST k-ω turbulence and discrete phase models to predict the wear characteristics of small two-stage mining pumps. The wear rates of the flow-passing components (first- and second-stage impellers and guide vanes) of the pump were simulated considering three solid-particle sizes under three flow conditions (low flow, rated flow, and high flow), with the highest wear rate occurring on the surfaces of the first-stage guide vane in the low-flow condition. Subsequently, a pump wear experiment was performed using an experimental pump with parameters and structure similar to the numerical model at the pump’s rated flow. The experimental results were compared to numerical results obtained using the same numerical method and wear model. The wear characteristics shown in the numerical and experimental results were consistent with each other. Thus, the numerical method used in this study can accurately predict the wear of flow-passing components in a mining pump, and the method was found to be suitable for the prediction of wear characteristics in mining pumps. Full article

Transformer-based models are driving a significant revolution in the field of machine learning at the moment. Among these innovations, vision transformers (ViTs) stand out for their application of transformer architectures to vision-related tasks. By demonstrating performance as good, if not better, than traditional convolutional neural networks (CNNs), ViTs have managed to capture considerable interest in the field. This study focuses on the resilience of ViTs and CNNs in the face of adversarial attacks. Such attacks, which introduce noise into the input of machine learning models to produce incorrect outputs, pose significant challenges to the reliability of machine learning models. Our analysis evaluated the adversarial robustness of CNNs and ViTs by using regularization techniques and adversarial training methods. Adversarial training, in particular, represents a traditional approach to boosting defenses against these attacks. Despite its prominent use, our findings reveal that regularization techniques enable vision transformers and, in most cases, CNNs to enhance adversarial defenses more effectively. Through testing datasets like CIFAR-10 and CIFAR-100, we demonstrate that vision transformers, especially when combined with effective regularization strategies, demonstrate adversarial robustness, even without adversarial training. Two main inferences can be drawn from our findings. Firstly, it emphasizes how effectively vision transformers could strengthen artificial intelligence defenses against adversarial attacks. Secondly, it shows how regularization, which requires much fewer computational resources and covers a wide range of adversarial attacks, can be effective for adversarial defenses. Understanding and improving a model’s resilience to adversarial attacks is crucial for developing secure, dependable systems that can handle the complexity of real-world applications as artificial intelligence and machine learning technologies advance. Full article

We previously reported that a combined myo-inositol, probiotics, and enriched micronutrient supplement (intervention) taken preconception and in pregnancy reduced postpartum blood loss (PBL) and major postpartum hemorrhage compared with a standard micronutrient supplement (control), as secondary outcomes of the NiPPeR trial. This study aimed to identify the intervention components that may contribute to this effect. Associations of plasma concentrations of myo-inositol and vitamins B2, B6, B12, and D at preconception (before and after supplementation), early (~7-weeks), and late pregnancy (~28-weeks) with PBL were assessed by multiple linear regression, adjusting for site, ethnicity, preconception BMI, parity, and previous cesarean section. Amongst 583 women, a higher concentration of myo-inositol in early pregnancy was associated with a PBL reduction [β_adj −1.26 (95%CI −2.23, −0.29) mL per µmol/L myo-inositol increase, p = 0.011]. Applying this co-efficient to the increase in mean 7-week-myo-inositol concentration of 23.4 µmol/L with the intervention equated to a PBL reduction of 29.5 mL (~8.4% of mean PBL of 350 mL among controls), accounting for 84.3% of the previously reported intervention effect of 35 mL. None of the examined vitamins were associated with PBL. Therefore, myo-inositol may be a key intervention component mediating the PBL reduction. Further work is required to determine the mechanisms involved. Full article

(1) Background: Intravesical chemotherapy is the standard of care in intermediate-risk non-muscleinvasive bladder cancer (NMIBC). Different agents are used across the world based on availability, cost, and practice patterns. Epirubicin (EPI), one of these agents, has been used by many centers over many decades. However, its true differential efficacy compared to other agents and its tolerability are still poorly reported. We aimed to assess the differential efficacy and safety of intravesical EPI in NMIBC patients. (2) Methods: This study aimed to systematically review the efficacy and safety profile of Epirubicin (EPI) in the management of non-muscle invasive bladder cancer (NMIBC) compared to other adjuvant therapies. A systematic search of the PUBMED, Web of Science, clinicaltrials.gov, and Google Scholar databases was conducted on 31 December 2023, using relevant terms related to EPI, bladder cancer, and NMIBC. The inclusion criteria targeted studies that evaluated patients treated with EPI following the transurethral resection of bladder tumors (TURBT) for NMIBC and compared oncological outcomes such as recurrence and progression with other adjuvant therapies, including Mitomycin C (MMC), Gemcitabine (GEM), and Bacillus Calmette-Guérin (BCG). Additionally, studies investigating the safety profile of EPI administered intravesically at room temperature and under hyperthermia, as well as oncological outcomes associated with hyperthermic intravesical EPI administration, were included. (3) Results: Eleven studies reported adverse events after adjuvant intravesical instillations with EPI; the most frequently reported adverse events included cystitis (34%), dysuria, pollakiuria, hematuria, bladder irritation/spasms, fever, nausea and vomiting, and generalized skin rash (2.3%). Nine studies compared EPI to BCG in terms of recurrence and progression rates; BCG instillations showed a lower recurrence rate compared to EPI, with limited or non-significant differences in progression rates. Two studies found no significant differences between EPI and MMC regarding progression and recurrence rates. One study showed statistically significant lower recurrence and progression rates with GEM in high-risk NMIBC patients. Another study found no significant differences between EPI and GEM regarding recurrence and progression. (4) Conclusions: EPI exhibits similar oncological performances to Gemcitabine and Mitomycin C currently used for adjuvant therapy in NMIBC. Novel delivery mechanisms such as hyperthermia are interesting newcomers. Full article

In this study, we used full-sib families to investigate the association between growth and gonad development during first sexual maturation of M. nipponense. We found that male GSI was significantly negatively correlated with growth traits (p < 0.01) and there were no significant correlations between female GSI (Gonadosomatic index) and growth traits (p > 0.05). HSI (Hepatopancreas index) in both males and females showed no significant correlations with growth traits (p > 0.05). We furthermore investigated the association between the specific allele of Mn-CTS L1 polymorphism and gonad development and growth traits. In total, 35 mutation loci were screened and 16 high-quality single-nucleotide polymorphisms (SNPs) loci were obtained after validation. Four and two SNPs proved to be strongly associated with all growth traits in female and male M. nipponense separately, among which A+118T might be a candidate SNP positively associated with large growth traits. Two and one SNPs were screened, respectively, in males and females to associate with GSI, while three SNPs were detected to associate with female HSI, among which A+1379C may be applied as a potential molecular marker for gene-assisted selection to improve both reproduction speed and growth traits in M. nipponense. Full article