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The mitigation of water flooding in the gas diffusion layer (GDL) at relatively high current densities is indispensable for enhancing the performance of proton exchange membrane fuel cells (PEMFCs). In this paper, a 2D multicomponent LBM model is developed to investigate the effects of porosity distribution and compression on the liquid water dynamic behaviors and distribution. The results suggest that adopting the gradient GDL structure with increasing porosity along the thickness direction significantly reduces the breakthrough time and steady–state total water saturation inside the GDL. Moreover, the positive gradient structure reaches the highest breakthrough time and water saturation at 10% compression ratio (CR) when the GDL is compressed, and the corresponding values decrease with further increase of the CR. Considering the breakthrough time, total water saturation and water distribution at the entrance of the GDL at the same time, the gradient structure with continuously increasing porosity can perform better water management capacity at 30% CR. This paper is useful for understanding the two–phase process in a gradient GDL structure and provides guidance for future design and manufacturing.

Carbonate reservoirs worldwide are complex in structure, diverse in form, and highly heterogeneous. Based on these characteristics, the reservoir stimulation technologies and fluid flow characteristics of carbonate reservoirs are briefly described in this study. The development methods and EOR technologies of carbonate reservoirs are systematically summarized, the relevant mechanisms are analyzed, and the application status of oil fields is catalogued. The challenges in the development of carbonate reservoirs are discussed, and future research directions are explored. In the current development processes of carbonate reservoirs, water flooding and gas flooding remain the primary means but are often prone to channeling problems. Chemical flooding is an effective method of tertiary oil recovery, but the harsh formation conditions require high-performance chemical agents. The application of emerging technologies can enhance the oil recovery efficiency and environmental friendliness to a certain extent, which is welcome in hard-to-recover areas such as heavy oil reservoirs, but the economic cost is often high. In future research on EOR technologies, flow field control and flow channel plugging will be the potential directions of traditional development methods, and the application of nanoparticles will revolutionize the chemical EOR methods. On the basis of diversified reservoir stimulation, combined with a variety of modern data processing schemes, multichannel EOR technologies are being developed to realize the systematic, intelligent, and cost-effective development of carbonate reservoirs.

Infectious diseases caused by bacteria are a global threat to the human health. Here, we propose a solvent “irrigation” technique to endow TiO 2 nanotubes (NTs) to precisely modify with functional nanomaterials, and apply them in constructing a near-infrared (NIR) light controlled drug-delivery system for rapid necrosis of bacteria. In this design, the NIR stimuli-responsive functional shell is located on the external tube wall of TiO 2 NT; the internal tube wall offers sufficient binding sites for drug loading. Using kanamycin as a model drug, we demonstrate that the reactive oxygen species generated in photocatalysis not only controllably release the loaded drug by scissoring the linked chains, but also effectively compromise bacteria membrane integrity by damaging the cell wall. Benefiting from the damages, antibiotics rapidly enter the bacteria and reach ≥99.9% reduction in Escherichia coli colony within only 2 h. Importantly, such a covalently conjugation-based delivery system can efficiently relieve radical-induced inflammation and cytotoxicity. This study provides an innovative design strategy for engineering delivery systems with tailorable components, enduring stimuli-response by multiple triggers.

Accurate glioma grading before surgery is of the utmost importance in treatment planning and prognosis prediction. But previous studies on magnetic resonance imaging (MRI) images were not effective enough. According to the remarkable performance of convolutional neural network (CNN) in medical domain, we hypothesized that a deep learning algorithm can achieve high accuracy in distinguishing the World Health Organization (WHO) low grade and high grade gliomas. One hundred and thirteen glioma patients were retrospectively included. Tumor images were segmented with a rectangular region of interest (ROI), which contained about 80% of the tumor. Then, 20% data were randomly selected and leaved out at patient-level as test dataset. AlexNet and GoogLeNet were both trained from scratch and fine-tuned from models that pre-trained on the large scale natural image database, ImageNet, to magnetic resonance images. The classification task was evaluated with five-fold cross-validation (CV) on patient-level split. The performance measures, including validation accuracy, test accuracy and test area under curve (AUC), averaged from five-fold CV of GoogLeNet which trained from scratch were 0.867, 0.909, and 0.939, respectively. With transfer learning and fine-tuning, better performances were obtained for both AlexNet and GoogLeNet, especially for AlexNet. Meanwhile, GoogLeNet performed better than AlexNet no matter trained from scratch or learned from pre-trained model. In conclusion, we demonstrated that the application of CNN, especially trained with transfer learning and fine-tuning, to preoperative glioma grading improves the performance, compared with either the performance of traditional machine learning method based on hand-crafted features, or even the CNNs trained from scratch.

Chiral recognition, such as enantioselective interactions of enzyme with chiral agents, is one of the most important issues in the natural world. But artificial chiral receptors are much less efficient than natural ones. For tackling the chiral recognition and enantiomer excess (ee) analysis, up until now all the fluorescent receptors have been developed based on fluorescence intensity changes. Here we report that the chiral recognition of a large number of chiral carboxylic acids, including chiral agrochemicals 2,4-D, is carried out based on fluorescent colour changes rather than intensity changes of AIEgen rotors. Moreover, the fluorescence wavelength of the AIEgen rotor linearly changes with ee of the carboxylic acid, enabling the ee to be accurately measured with average absolute errors (AAE) of less than 2.8%. Theoretical calculation demonstrates that the wavelength change is ascribed to the rotation of the AIEgen rotor upon interaction with different enantiomers. Artificial receptors for chiral recognition are important in enantiomer excess analysis but current artificial detectors are based on fluorescence intensity changes only. Here the authors propose a different detection mechanism based on change of the fluorescence emission wavelength of an AIEgen rotor.

For the intersection family X of general Fermat-type hypersurfaces in PKN defined over an algebraically closed field K, we extend Brotbek’s symmetric differential forms by a geometric approach, and we further exhibit unveiled families of lower degree symmetric differential forms on all possible intersections of X with coordinate hyperplanes. Thereafter, we develop what we call the ‘moving coefficients method’ to prove a conjecture made by Olivier Debarre: for a generic choice ofc⩾N/2hypersurfacesH1,…,Hc⊂PCNof degreesd1,…,dcsufficiently large, the intersectionX:=H1∩⋯∩Hchas ample cotangent bundleΩX, and concerning effectiveness, the lower bound d1,…,dc⩾∏l=N/2Nl4(l+1)2l works. Lastly, thanks to known results about the Fujita Conjecture, we establish the very-ampleness of SymκΩX for all κ⩾κ0, with a uniform lower bound κ0=64(∑i=1cdi)2.

Food contamination has emerged as a significant global health concern, posing substantial challenges to the food industry. Bacteria are the primary cause of foodborne diseases. Consequently, it is crucial to develop accurate and efficient sensing platforms to detect foodborne bacteria in food products. Among various detection methods, biosensors have emerged as a promising solution due to their portability, affordability, simplicity, selectivity, sensitivity, and rapidity. Electrospun nanofibers have gained increasing popularity in enhancing biosensor performance. These nanofibers possess a distinctive three-dimensional structure, providing a large surface area and ease of preparation. This review provides an overview of the electrospinning technique, nanofibers and nanofiber-based biosensors. It also explores their mechanisms and applications in the detection of foodborne bacteria such as Salmonella, Listeria monocytogenes (L. monocytogenes), Escherichia coli (E. coli), Staphylococcus aureus (S. aureus) and Pseudomonas putida (P. putida).

Aiming at the problems of high cleaning intensity, low efficiency, and hidden safety hazards of high-altitude curtain walls, this study proposes that the image processing method is a kind of image processing technology in human-computer collaborative visual design. The algorithm uses generalized mapping to scramble the picture and then expands and replaces the scrambled pictures one by one through the image processing technical support system. Studies have shown that this calculation method has mixed pixel values, good diffusion performance, and strong resistance performance. The pixel distribution of the processed image is relatively random, and the features of similar loudness are not relevant. It is proved through experiments that the above calculation methods have strong safety performance.

A  Janus cargo has been developed via the combination of magnetic mesoporous silica (MMS) with asymmetric decoration of Pt nanoparticles (PtNPs). Mesoporous morphology of MMS provides plenty of space for loading photosensitizers and targeting agents; the magnetic feature endows the as-formed nanospheres with satisfactory isolation function in removal of low abundant target cells. The excellent catalytic ability of PtNPs can effectively alleviate the hypoxia condition of tumor microenvironment via the decomposition of hydrogen peroxide (H 2 O 2 ), as well as an O 2 -drived nanomotor for highly efficient drug release. Using CCRF-CEM as the model target cell, the Janus cargo is demonstrated to possess significantly improved performance in cell capture and photodynamic therapy. Specially, owing to the patchy Pt decoration, the loaded photosensitizers exhibit a more efficient release behavior. More importantly, asymmetric O 2 -emission from one side of the nanocargo acts as a driving force, which could effectively accelerate the motion ability of cargo in cell media, thus leading to an enhanced therapeutic effect compared with the traditionally symmetric nanocargo. This Janus cargo would offer a new paradigm to design highly efficient drug carrier for gaining an improved photodynamic therapy in hypoxic cancer cells. Graphic abstract

Andreev reflection is an important quantum tunneling phenomenon in the conductor-superconductor junction. The Andreev reflection coefficients T AR of a hybrid system with s -wave superconductor connected by topological nodal-line semimetals (TNLSMs-SC junction system) is calculated theoretically by using the Landauer–Büttiker formula combined with the nonequilibrium Green’s function method. The results show that when the direction of the boundary state electron and the incident electron are the same, only the bulk states of the TNLSMs involve the Andreev reflection of the hybrid system, and the Andreev reflection coefficients T AR enhance with the increase of the Fermi energy E F . We also study the effect of on-site energy ε z and mass term m on the Andreev reflection and find that the Andreev reflection in the system decreases rapidly with the increase of on-site energy ε z and mass term m . Moreover, we find that only in the presence of a mass term m , the Andreev reflection coefficients T AR of the system changes with the rise of the Fermi energy E F . When a perpendicular magnetic field is applied in the system, the Andreev reflection coefficients T AR in the superconducting gap will appear a series of oscillating peaks. For a hybrid system with the large perpendicular magnetic field applied, we find that the maximum Andreev reflection coefficients T AR = 7.2 at the Fermi energy E F = 0.0 and the incident electron energy E = ± 0.1 . The Andreev reflection coefficients T AR is gradually enhanced in the superconducting gap (incident energy | E | ⩽ 0.2 ) when a disorder is applied to the superconductor region of the system. However, the symmetry of the Andreev reflection coefficients T AR is broken when the perpendicular magnetic field is applied to the system. These peculiar transport properties of the TNLSMs-SC junction system are expected to provide theoretical guidance for future applications.