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Seismic stability analyses of soil slopes in the presence of weak interlayers are rather challenging within the framework of plasticity theory, due to the construction of kinematically admissible velocity fields and statically allowable stress fields at limit state. Finite-element limit-analysis procedures including finite-element upper-bound (FEUB) and finite-element lower-bound (FELB) approach are introduced in this study, retaining the merits of FEM and limit analysis theory to tackle above issues. Incorporating modified pseudo-dynamic approach, seismic slope stability analyses are transformed to linear programming models, in terms of lower- and upper-bound formulations. Pseudo-static and modified pseudo-dynamic solutions of the factor of safety (FoS) are sought through optimization with an interior-point algorithm. An appealing merit of the proposed procedure is that both lower and upper bounds are searched, aiding to better estimate the true solution of FoS. Limit equilibrium and Abaqus are applied to validate FEUB and FELB results. Effects of dual weak interlayers’ position and dimension on seismic slope stability are investigated. Critical failure surface and velocity field are plotted by post-processing, demonstrating a rotational-translational failure mechanism. Based on less than 5% difference between lower- and upper-bound solutions, the proposed procedure is capable of providing a reliable guidance for slope design and assessment.

The aim of this study was to develop a novel ultrathin fibrous membrane with a core–sheath structure as an antioxidant food packaging membrane. The core–sheath structure was prepared by coaxial electrospinning, and the release of active substances was regulated by its special structure. Ferulic acid (FA) was incorporated into the electrospun zein/polyethylene oxide ultrathin fibers to ensure their synergistic antioxidant properties. We found that the prepared ultrathin fibers had a good morphology and smooth surface. The internal structure of the fibers was stable, and the three materials that we used were compatible. For the different loading positions, it was observed that the core layer ferulic-acid-loaded fibers had a sustained action, while the sheath layer ferulic-acid-loaded fibers had a pre-burst action. Finally, apples were selected for packaging using fibrous membranes to simulate practical applications. The fibrous membrane was effective in reducing water loss and apple quality loss, as well as extending the shelf life. According to these experiments, the FA-loaded zein/PEO coaxial electrospinning fiber can be used as antioxidant food packaging and will also undergo more improvements in the future.

Developing efficient strategies for the deoxygenative functionalization of carbonyl compounds is crucial for enhancing the effective utilization of biomass and the upgrading of chemical feedstocks. In this study, we present an elegant cathodic reduction strategy that enables a tandem alkylation/dearomatization reaction between quinoline derivatives and aryl aldehydes/ketones in a one-pot process. Our approach can be executed via two distinct paths: the aluminum (Al)-facilitated spin-center shift (SCS) path and the Al-facilitated direct deoxygenation path. Both paths are theoretically substantiated by DFT calculations. The crux of this protocol is the in-situ activation of the alcohol intermediates by Al salts, which substantially lowers the activation energy necessary for the formation of key transition states, thereby effectively facilitating the deoxygenation process. Control experiments have not only successfully identified the intermediates but also established that the hydrogen source for the reaction is derived from water and tetrabutylammonium salt. Notably, this method is transition metal-free and compatible with water and oxygen. Developing efficient strategies for the deoxygenative functionalization of carbonyl compounds is crucial for enhancing the effective utilization of biomass and the upgrading of chemical feedstocks. In this study, the authors present an elegant cathodic reduction strategy that enables a tandem alkylation/dearomatization reaction between quinoline derivatives and aryl aldehydes/ketones in a one-pot process.

In this study, three kinds of electrohydrodynamic atomization (EHDA) processes (electrospraying, electrospinning, and coaxial electrospinning) are implemented to create hydroxypropyl methylcellulose (HPMC) based ultra‐thin products for providing the fast dissolution of a poorly water‐soluble drug ketoprofen (KET). An EHDA apparatus, characterized by a novel spinneret, is homemade for conducting the three processes. The three types of products are electrospun nanofibers E1, electrosprayed microparticles E2, and core‐shell nanofibers E3. SEM and TEM results indicate that they have the anticipated morphologies and inner structures. X‐ray diffraction and Fourier Transform Infrared results verify that KET is mainly amorphous in all the composites due to its fine compatibility with HPMC. In vitro dissolution tests demonstrate that the drug rapid release performances has an order of E3>E1>E2≫KET powders. The fast dissolution mechanisms are suggested and the advantages of the three products are compared. The super performance of E3 in furnishing the rapid release is attributed to a synergistic action of small size (of the shell thickness), high porosity, amorphous state of drug, and the solubility of HPMC. EHDA nanostructures can support the development of nano drug delivery systems (DDSs) through tailoring the spatial distribution of drug molecules within the nano products.

Background The rapid spread of coronavirus disease 2019 (COVID-19) was declared as an emerging public health threat by the World Health Organization. As various measures have been taken successfully to combat the epidemic caused by SARS-CoV-2, a growing number of fully recovered patients have been discharged from hospitals. However, some of them have relapsed. Little is known about the causes that triggered the relapse. Case presentation We report a case of a 40 years old man who suffered from recurrent pulmonary infection with progression of lesions on chest computed tomography (CT), elevated levels of ferritin and IL2R, reduced lymphocyte count and positive oropharyngeal swab test for SARS-CoV-2 again after 5 days discharge from hospital. The anti-SARS-CoV-2 antibody level of this patient was very low at the time of relapse, suggesting a weak humoral immune response to the virus. Total exon sequencing revealed mutations in TRNT1 gene, which may be responsible for B cell immunodeficiency. Therefore, uncleared SARS-CoV-2 at his first discharge was likely to lead to his recurrence. However, viral superinfection and non-infectious organizing pneumonia could not be completely excluded. Conclusion COVID-19 relapse may occur in a part of discharged patients with low titers of anti-SARS-CoV-2 antibodies. These patients should be maintained in isolation for longer time even after discharge. A more sensitive method to detect SARS-CoV-2 needs to be established and serological testing for specific antibodies may be used as a reference to determine the duration of isolation.

The integration of text-to-image generation capabilities within GPT-4 allows for the convenient creation of various graphics. However, the proficiency of GPT-4 in crafting challenging scientific visuals remains largely unexplored. In this study, we conduct systematic experiments by employing multiple prompt engineering techniques with various supplementary materials to generate complex scientific illustrations for environmental studies. The locally enhanced electric field treatment for water disinfection is used as an example to illustrate the universal reflection of GPT-4 in graphic creation. From the experiments, we summarize that the existing prompt methods struggle in accuracy, modifiability, and reproducibility for scientific image generation. Based on the findings and insights drawn from the extensive experimental results, we develop GPT4Designer, a framework intended to generate scientific images without tedious prompt modifications. Specifically, a simple but surprisingly effective “envision-first” strategy by combining detailed prompting and guided envisioning is developed in the GPT4Designer framework. This strategy yields images with consistent styles aligned with the initial envisioning, significantly improving modifiability. Besides, by refining the conceptualization phase, we achieve much better control over the output, resulting in both high accuracy and reproducibility. This advancement is not only crucial for environmental scientists seeking to quickly produce engaging and accurate visuals (e.g., with only one step), but also demonstrates the existence “chain-of-thought” in image generation, which can inspire more works on the creative application of text-to-image generation models or tools.

Physiological maturity date is a critical parameter for the selection of breeding lines in soybean breeding programs. The conventional method to estimate the maturity dates of breeding lines uses visual ratings based on pod senescence by experts, which is subjective by human estimation, labor-intensive and time-consuming. Unmanned aerial vehicle (UAV)-based phenotyping systems provide a high-throughput and powerful tool of capturing crop traits using remote sensing, image processing and machine learning technologies. The goal of this study was to investigate the potential of predicting maturity dates of soybean breeding lines using UAV-based multispectral imagery. Maturity dates of 326 soybean breeding lines were taken using visual ratings from the beginning maturity stage (R7) to full maturity stage (R8), and the aerial multispectral images were taken during this period on 27 August, 14 September and 27 September, 2018. One hundred and thirty features were extracted from the five-band multispectral images. The maturity dates of the soybean lines were predicted and evaluated using partial least square regression (PLSR) models with 10-fold cross-validation. Twenty image features with importance to the estimation were selected and their changing rates between each two of the data collection days were calculated. The best prediction (R2 = 0.81, RMSE = 1.4 days) was made by the PLSR model using image features taken on 14 September and their changing rates between 14 September and 27 September with five components, leading to the conclusion that the UAV-based multispectral imagery is promising and practical in estimating maturity dates of soybean breeding lines.

* Nanowire-assisted LEEFT is applied for water disinfection with low voltages. * LEEFT inactivates bacteria by disrupting cell membrane through electroporation. * Multiple electrodes and device configurations have been developed for LEEFT. * The LEEFT is low-cost, highly efficient, and produces no DBPs. * The LEEFT can potentially be applicable for water disinfection at all scales. Water disinfection is a critical step in water and wastewater treatment. The most widely used chlorination suffers from the formation of carcinogenic disinfection by-products (DBPs) while alternative methods (e.g., UV, O 3, and membrane filtration) are limited by microbial regrowth, no residual disinfectant, and high operation cost. Here, a nanowire-enabled disinfection method, locally enhanced electric field treatment (LEEFT), is introduced with advantages of no chemical addition, no DBP formation, low energy consumption, and efficient microbial inactivation. Attributed to the lightning rod effect, the electric field near the tip area of the nanowires on the electrode is significantly enhanced to inactivate microbes, even though a small external voltage (usually<5 V) is applied. In this review, after emphasizing the significance of water disinfection, the theory of the LEEFT is explained. Subsequently, the recent development of the LEEFT technology on electrode materials and device configurations are summarized. The disinfection performance is analyzed, with respect to the operating parameters, universality against different microorganisms, electrode durability, and energy consumption. The studies on the inactivation mechanisms during the LEEFT are also reviewed. Lastly, the challenges and future research of LEEFT disinfection are discussed.

Treatment failure or relapse due to tumor escape caused by reduction in target antigen expression has become a challenge in the field of CART therapy. Target antigen density is closely related to the effectiveness of CART therapy, and reduced or lost target antigen expression limits the efficacy of CART therapy and hinders the durability of CAR T cells. Epigenetic drugs can regulate histones for molecular modifications to regulate the transcriptional, translational and post-translational modification processes of target agents, and we demonstrated for the first time the role in regulating CD22 expression and its effect on the efficacy of CD22 CART. In this paper, we found that Chidamide promoted the expression of CD22 on the surface of B-cell tumor cells in vitro and in vivo, and enhanced the function of CD22 CART. As for mechanisms, we demonstrated that Chidamide did not affect CD22 mRNA transcription, but significantly increased the expression of total CD22 protein, indicating that Chidamide may upregulate cell surface CD22 expression by affecting the distribution of CD22 protein. In summary, our results suggest that Chidamide may enhance the efficacy of CD22 CART by inhibiting histone deacetylases to regulate post-transcriptional modifications that affect protein distribution to increase the expression of CD22 on the cell surface.

(1) Background: Yield-monitoring systems are widely used in grain crops but are less advanced for hay and forage. Current commercial systems are generally limited to weighing individual bales, limiting the spatial resolution of maps of hay yield. This study evaluated an Uncrewed Aerial Vehicle (UAV)-based imaging system to estimate hay yield. (2) Methods: Data were collected from three 0.4 ha plots and a 35 ha hay field of red clover and timothy grass in September 2020. A multispectral camera on the UAV captured images at 30 m (20 mm pixel−1) and 50 m (35 mm pixel−1) heights. Eleven Vegetation Indices (VIs) and five texture features were calculated from the images to estimate biomass yield. Multivariate regression models (VIs and texture features vs. biomass) were evaluated. (3) Results: Model R2 values ranged from 0.31 to 0.68. (4) Conclusions: Despite strong correlations between standard VIs and biomass, challenges such as variable image resolution and clarity affected accuracy. Further research is needed before UAV-based yield estimation can provide accurate, high-resolution hay yield maps.