•External short circuit of lithium battery is experimented at three ambient temperatures.•The impacts of SOC and ambient temperature on maximum temperature rise are analysed.•The heat generation ...caused by external short circuit is proved having two modes.•An online prediction approach of ESC-caused maximum temperature rise is proposed.•The presented algorithm can achieve the precise prediction 22.3 s ahead of time.
External short circuit (ESC) is a severe fault that can cause the large current and high temperature of lithium-ion batteries (LiBs) immediately. Temperature rise prediction is crucial for LiB safety management in an all-climate electric vehicles application because many disastrous consequences are caused by high temperature. This study mainly investigates the ESC-caused temperature rise characteristics of LiB, and proposes an online prediction approach of the maximum temperature rise. Three original contributions are made: (1) Abusing tests of LiBs under ESC are conducted at varying ambient temperatures, and the influences of battery state of charge (SOC) and ambient temperature on the maximum temperature rise are revealed. (2) Characteristics of temperature rises are analysed, therein finding that the heat generation of LiBs caused by ESC presents two modes: Joule heat-dominant mode and reaction heat/Joule heat blended mode; leakage is an external manifestation of the latter. (3) Two heat generation modes are proved to be linearly separable at temperature rise discharge capacity plane, and then a two-step prediction approach of maximum temperature rise is proposed based on support vector machine. Finally, the presented approach is validated by the experimental data. The maximum temperature rise can be predicted up to 22.3 s ahead of time and very precise prediction results are obtained, where the mean prediction error for the eight test cells is 3.05%.
Design and preparation of high N-doped content biomass-derived hierarchical porous carbon with appropriate pores size distribution and high electrical conductivity draw extensive research attention ...for supercapacitors. Herein, N-doped mesopore-dominated hierarchical porous graphitic carbons PG/PEI-CNi and PG/urea-CNi are successfully synthesized based on a facile “in-situ template catalyst formed-removed” method, in which the corresponding mixture of peach gum/polyethylenimine/NiCl2 and peach gum/urea/NiCl2 are treated with hydrothermal and carbonization process, respectively. As-prepared PG/PEI-CNi and PG/urea-CNi possess high N-doped content (8.7 and 8.4 at. %), high specific surface area (875.9 and 1161.4 m2 g−1) and excellent electronic conductivity (10.08 and 11.43 S cm−1). The PG/PEI-CNi and PG/urea-CNi exhibit high capacitance of 369 and 426 F g−1 at 0.5 A g−1 and excellent capacitance retention of 95.13% and 97.09% at 20 A g−1 after 10000 cycles, respectively. Moreover, PG/PEI-CNi and PG/urea-CNi assembled symmetric supercapacitors display excellent energy density of 25.76 and 30.28 W h kg−1 at power density of 180 W kg−1 in 1 M Na2SO4 electrolyte, respectively. The proposed “in-situ template catalyst formed-removed” method is prominent in the preparation of high-performance electrode materials for energy conversion/storage devices.
•Umbrella review of various cancer risks related to red and processed meat intake.•100 g/d increment of red meat could increase by 11–51% risk of multiple cancer.•50 g/d increment of processed meat ...could increase by 8–72% risk of multiple cancer.•Red and processed meat consumption seems to be not related to any benefit of cancer.
The purpose of this umbrella review was to evaluate the quality of evidence, validity and biases of the associations between red and processed meat consumption and multiple cancer outcomes according to existing systematic reviews and meta-analyses. The umbrella review identified 72 meta-analyses with 20 unique outcomes for red meat and 19 unique outcomes for processed meat. Red meat consumption was associated with increased risk of overall cancer mortality, non-Hodgkin lymphoma (NHL), bladder, breast, colorectal, endometrial, esophageal, gastric, lung and nasopharyngeal cancer. Processed meat consumption might increase the risk of overall cancer mortality, NHL, bladder, breast, colorectal, esophageal, gastric, nasopharyngeal, oral cavity and oropharynx and prostate cancer. Dose-response analyses revealed that 100 g/d increment of red meat and 50 g/d increment of processed meat consumption were associated with 11%-51% and 8%-72% higher risk of multiple cancer outcomes, respectively, and seemed to be not correlated with any benefit.
Photothermal therapy refers to the addition of targeted drugs with photothermal effects into the patient's body. Through targeting, the drug specifically recognizes tumor cells and accumulates around ...tumor cells. Afterwards, it is irradiated with a laser of a specific wavelength to achieve a local temperature increase, thereby achieving the effect of killing or locating tumor cells. Therefore, the most important part of this treatment method is the photothermal probe with a targeting effect and good photothermal effect. The existing photothermal probes are mainly composed of inorganic substances, organic small molecules and organic biomolecules. This paper will mainly introduce the development status and prospects of performance of these three types of photothermal probes to introduce photothermal agent development.
Thermoelectric generators (TEGs) provide a unique solution for energy harvesting from waste heat, presenting a potential solution for green energy. However, traditional rigid and flexible TEGs cannot ...work on complex and dynamic surfaces. Here, we report a stretchable TEG (S-TEG) (over 50% stretchability of the entire device) that is geometrically suitable for various complex and dynamic surfaces of heat sources. The S-TEG consists of hot-pressed nanolayered p-(Sb
Te
) and n-(Bi
Te
)-type thermoelectric couple arrays and exploits the wavy serpentine interconnects to integrate all units. The internal resistance of a 10 × 10 array is 22 ohm, and the output power is ∼0.15 mW/cm
at Δ
= 19 K on both developable and nondevelopable surfaces, which are much improved compared with those of existing S-TEGs. The energy harvesting of S-TEG from the dynamic surfaces of the human skin offers a potential energy solution for the wearable devices for health monitoring.
Image style transfer aims to assign a specified artist's style to a real image. However, most existing methods cannot generate textures of various thicknesses due to the rich semantic information of ...the input image. The image loses some semantic information through style transfer with a uniform stroke size. To address the above problems, we propose an improved multi-stroke defocus adaptive style transfer framework based on a stroke pyramid, which mainly fuses various stroke sizes in the image spatial dimension to enhance the image content interpretability. We expand the receptive field of each branch and then fuse the features generated by the multiple branches based on defocus degree. Finally, we add an additional loss term to enhance the structural features of the generated image. The proposed model is trained using the Common Objects in Context (COCO) and Synthetic Depth of Field (SYNDOF) datasets, and the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) are used to evaluate the overall quality of the output image and its structural similarity with the content image, respectively. To validate the feasibility of the proposed algorithm, we compare the average PSNR and SSIM values of the output of the modified model and those of the original model. The experimental results show that the modified model improves the PSNR and SSIM values of the outputs by 1.43 and 0.12 on average, respectively. Compared with the single-stroke style transfer method, the framework proposed in this study improves the readability of the output images with more abundant visual expression.
Using deep learning technology to segment oral CBCT images for clinical diagnosis and treatment is one of the important research directions in the field of clinical dentistry. However, the blurred ...contour and the scale difference limit the segmentation accuracy of the crown edge and the root part of the current methods, making these regions become difficult-to-segment samples in the oral CBCT segmentation task. Aiming at the above problems, this work proposed a Difficult-to-Segment Focus Network (DSFNet) for segmenting oral CBCT images. The network utilizes a Feature Capturing Module (FCM) to efficiently capture local and long-range features, enhancing the feature extraction performance. Additionally, a Multi-Scale Feature Fusion Module (MFFM) is employed to merge multiscale feature information. To further improve the loss ratio for difficult-to-segment samples, a hybrid loss function is proposed, combining Focal Loss and Dice Loss. By utilizing the hybrid loss function, DSFNet achieves 91.85% Dice Similarity Coefficient (DSC) and 0.216 mm Average Symmetric Surface Distance (ASSD) performance in oral CBCT segmentation tasks. Experimental results show that the proposed method is superior to current dental CBCT image segmentation techniques and has real-world applicability.
Tooth loss has endangered human health for thousands of years, and people can apply dentures or dental implants to restore tooth loss today. Tissue engineering provides a novel way to regenerate a ...new functional tooth in vivo or vitro to help patients regain masticatory function and appearance. In this summarize review, we will discuss some promising seed cells in dental tissue engineering, the scaffolds that can be used to regenerate teeth, and some growth factors which can promote the development of tooth. Although significant progresses have been made nowadays, some challenges still remain. Hence, tissue engineering could be a choice to replace missing tooth in the future when the obstacles are solved.
Plug-in hybrid electric vehicles (PHEVs) have been recognized as one of the most promising vehicle categories nowadays due to their low fuel consumption and reduced emissions. Energy management is ...critical for improving the performance of PHEVs. This paper proposes an energy management approach based on a particle swarm optimization (PSO) algorithm. The optimization objective is to minimize total energy cost (summation of oil and electricity) from vehicle utilization. A main drawback of optimal strategies is that they can hardly be used in real-time control. In order to solve this problem, a rule-based strategy containing three operation modes is proposed first, and then the PSO algorithm is implemented on four threshold values in the presented rule-based strategy. The proposed strategy has been verified by the US06 driving cycle under the MATLAB/Simulink software environment. Two different driving cycles are adopted to evaluate the generalization ability of the proposed strategy. Simulation results indicate that the proposed PSO-based energy management method can achieve better energy efficiency compared with traditional blended strategies. Online control performance of the proposed approach has been demonstrated through a driver-in-the-loop real-time experiment.