ZnS/CuS nanoparticles encapsulated in multichannel carbon fibers as high-performance anode materials for flexible Li-ion capacitors

Transition metal sulfides (TMSs) are widely recognized for their potential as anode materials in the development of flexible lithium-ion capacitors (FLICs) owing to their high theoretical capacity. However, their practical application has been significantly limited by rapid capacity decay and sluggish kinetics associated with TMS volume variation. In response to these challenges, we have prepared ZnS/CuS nanoparticles embedded in continuous and multichannel carbon fibers (CFs). This was achieved through a process involving blow-spinning and subsequent sulfidation. Notably, the electrochemical performance of these materials was largely improved, owing to the synergistic effect of bimetallic sulfides. The ZnS/CuS-CF anode material demonstrated a high specific capacity of over 900 mAh g−1 at a current density of 0.2 A g−1. Furthermore, it exhibited superior rate capacity (300 mAh g−1 at 20 A g−1) and excellent cyclic stability, maintaining its performance over 1000 cycles at 10 A g−1. We also prepared lithium-ion capacitors (LICs) using the same method. These LICs exhibited a maximum energy density of 136 Wh kg−1, a high power density of 43.5 kW kg−1, and an impressive cyclic stability over 4000 cycles. In addition, the FLICs, when configured in the form of a pouch cell, demonstrated significant potential for the development of smart, flexible electronic devices

TNF-α-1031T/C gene polymorphism as a predictor of malnutrition in patients with gastric cancer

IntroductionMalnutrition is a complex clinical syndrome, the exact mechanism of which is yet not fully understood. Studies have found that malnutrition is associated with anorexia and inadequate intake, tumor depletion, leptin, tumor-induced metabolic abnormalities in the body, and catabolic factors produced by the tumor in the circulation and cytokines produced by the host immune system. Among these, single nucleotide polymorphisms (SNPs) are present in the gene encoding the pro-inflammatory cytokine TNF-α.AimThe objective of this study was to investigate TNF-α -1,031 T/C gene polymorphism as an unfavorable predictor of malnutrition in patients with gastric cancer.MethodsThe study group consisted of 220 gastric cancer patients treated at Affiliated Jinhua Hospital, Zhejiang University School of Medicine. Malnutrition was mainly assessed by the Global Consensus on Malnutrition Diagnostic Criteria (GLIM). DNA was extracted from peripheral leukocytes of whole blood samples using an animal DNA extraction kit. DNA was amplified using a 1.1× T3 Super PCR mixture and genotyped using SNP1 software.ResultsThere are three major genetic polymorphisms in TNF-α. Among the 220 patients with gastric cancer, there were 7 patients with the CC genotype, 61 with the CT genotype and 152 with the TT genotype. Compared to patients with the TT genotype, patients with the C allele had an approximately 2.5-fold higher risk of developing malnutrition (p = 0.003; OR = 0.406). On the basis of multivariate analysis, patients with the CC genotype had an approximately 20.1-fold higher risk of developing malnutrition (p = 0.013; OR = 20.114), while those with the CT genotype had an almost 3.7-fold higher risk of malnutrition (p = 0.002; OR = 3.218).ConclusionSNP (−1,031 T/C) of the TNF-α may be a useful marker in the assessment of the risk of nutritional deficiencies in gastric cancer patients. Patients with gastric cancer carrying the C allele should be supported by early nutritional intervention, but more research is still needed to explore confirmation

A Fast Adaptive Multi-Scale Kernel Correlation Filter Tracker for Rigid Object

The efficient and accurate tracking of a target in complex scenes has always been one of the challenges to tackle. At present, the most effective tracking algorithms are basically neural network models based on deep learning. Although such algorithms have high tracking accuracy, the huge number of parameters and computations in the network models makes it difficult for such algorithms to meet the real-time requirements under limited hardware conditions, such as embedded platforms with small size, low power consumption and limited computing power. Tracking algorithms based on a kernel correlation filter are well-known and widely applied because of their high performance and speed, but when the target is in a complex background, it still can not adapt to the target scale change and occlusion, which will lead to template drift. In this paper, a fast multi-scale kernel correlation filter tracker based on adaptive template updating is proposed for common rigid targets. We introduce a simple scale pyramid on the basis of Kernel Correlation Filtering (KCF), which can adapt to the change in target size while ensuring the speed of operation. We propose an adaptive template updater based on the Mean of Cumulative Maximum Response Values (MCMRV) to alleviate the problem of template drift effectively when occlusion occurs. Extensive experiments have demonstrated the effectiveness of our method on various datasets and significantly outperformed other state-of-the-art methods based on a kernel correlation filter

How Non-Uniform Stiffness Affects the Propulsion Performance of a Biomimetic Robotic Fish

Live fish in nature exhibit various stiffness characteristics. The anguilliform swimmer, like eels, has a relatively flexible body, while the thunniform swimmer, like the swordfishes, has a much stiffer body. Correspondingly, in the design of biomimetic robotic fish, how to balance the non-uniform stiffness to achieve better propulsion performance is an essential question needed to be answered. In this paper, we conduct an experimental study on this question. First, a customized experimental platform is built, which eases the adjustment of the non-uniform stiffness ratio, the stiffness of the flexible part, the flapping frequency, and the flapping amplitude. Second, extensive experiments are carried out, finding that to maximize the propulsion performance of the biomimetic robotic fish, the non-uniform stiffness ratio is required to adapt to different locomotor parameters. Specifically, the non-uniform stiffness ratio needs to be reduced when the robotic fish works at low frequency, and it needs to be increased when the robotic fish works at high frequency. Finally, detailed discussions are given to further analyze the experimental results. Overall, this study can shed light on the design of a non-uniform biomimetic robotic fish, which helps to increase its propulsion performance

Thrust Improvement of a Biomimetic Robotic Fish by Using a Deformable Caudal Fin

In nature, live fish has various deformable fins which are capable to promote the swimming speed, efficiency, stability, and thrust generation. However, this feature is rarely possessed by current man-made biomimetic robotic fishes. In this paper, a novel deformable caudal fin platform is proposed to improve thrust generation of biomimetic robotic fish. First, the design of the deformable caudal fin is given, which includes a servo motor, a gear-based transmission mechanism, fin bones, and silica membrane. Second, an improved Central Pattern Generator (CPG) model was developed to coordinately control the flapping of the tail and the deformation of the caudal fin. More specifically, three deformation patterns, i.e., conventional nondeformable mode, sinusoidal-based mode, instant mode, of the caudal fin are investigated. Third, extensive experiments are conducted to explore the effects of deformation of the caudal fin on the thrust generation of the biomimetic robotic fish. It was found that the instant mode of the caudal fin has the largest thrust, which sees a 27.5% improvement compared to the conventional nondeformable mode, followed by the sinusoidal-based mode, which also sees an 18.2% improvement. This work provides a novel way to design and control the deformation of the caudal fin, which sheds light on the development of high-performance biomimetic robotic fish

Na0.76V6O15/Activated Carbon Hybrid Cathode for High-Performance Lithium-Ion Capacitors

Lithium-ion hybrid capacitors (LICs) are regarded as one of the most promising next generation energy storage devices. Commercial activated carbon materials with low cost and excellent cycling stability are widely used as cathode materials for LICs, however, their low energy density remains a significant challenge for the practical applications of LICs. Herein, Na0.76V6O15 nanobelts (NaVO) were prepared and combined with commercial activated carbon YP50D to form hybrid cathode materials. Credit to the synergism of its capacitive effect and diffusion-controlled faradaic effect, NaVO/C hybrid cathode displays both superior cyclability and enhanced capacity. LICs were assembled with the as-prepared NaVO/C hybrid cathode and artificial graphite anode which was pre-lithiated. Furthermore, 10-NaVO/C//AG LIC delivers a high energy density of 118.9 Wh kg−1 at a power density of 220.6 W kg−1 and retains 43.7 Wh kg−1 even at a high power density of 21,793.0 W kg−1. The LIC can also maintain long-term cycling stability with capacitance retention of approximately 70% after 5000 cycles at 1 A g−1. Accordingly, hybrid cathodes composed of commercial activated carbon and a small amount of high energy battery-type materials are expected to be a candidate for low-cost advanced LICs with both high energy density and power density

Direct C–H Functionalization of Pyridine via a Transient Activator Strategy: Synthesis of 2,6-Diarylpyridines

A Pd-catalyzed highly selective direct diarylation of pyridines has been developed using a transient activator strategy. Both (MeO)₂SO₂ and Cu₂O are required for this transformation. The in situ generated <i>N</i>-methylpyridinium salt can be arylated at both 2- and 6-positions under the cooperative Pd/Cu catalysis. A subsequent <i>N</i>-demethylation then gives the 2,6-diarylpyridines. This protocol provides a novel synthetic route for the symmetric 2,6-diarylpyridines