Applications of Carbon Nanotubes to Flexible Transparent Conductive Electrodes

Transparent conductive electrodes (TCEs) have attracted great interest because of their wide range of applications in solar cells, liquid crystal displays (LCDs), organic light-emitting diodes (OLEDs), and touch screen panels (TSPs). Indium-tin-oxide (ITO) thin films as TCEs possess exceptional optoelectronic properties, but they have several disadvantages such as a brittle nature due to their low fracture strain and lack of flexibility, a high processing temperature that damages the flexible substrates, low adhesion to polymeric materials, and relative rarity on Earth, which makes their price unstable. This has motivated several research studies of late for developing alternative materials to replace ITO such as metal meshes, metal nanowires, conductive polymers, graphene, and carbon nanotubes (CNTs). Out of the abovementioned candidates, CNTs have advantages in chemical stability, thermal conductivity, mechanical strength, and flexibility. However, there are still several problems yet to be solved for achieving CNT-based flexible TCEs with excellent characteristics and high stability. In this chapter, the properties of CNTs and their applications especially for flexible TCEs are presented, including the preparation details of CNTs based on solution processes, the surface modification of flexible substrates, and the various types of hybrid TCEs based on CNTs

Understanding the internet topology evolution dynamics

The internet structure is extremely complex. The Positive-Feedback Preference (PFP) model is a recently introduced internet topology generator. The model uses two generic algorithms to replicate the evolution dynamics observed on the internet historic data. The phenomenological model was originally designed to match only two topology properties of the internet, i.e. the rich-club connectivity and the exact form of degree distribution. Whereas numerical evaluation has shown that the PFP model accurately reproduces a large set of other nontrivial characteristics as well. This paper aims to investigate why and how this generative model captures so many diverse properties of the internet. Based on comprehensive simulation results, the paper presents a detailed analysis on the exact origin of each of the topology properties produced by the model. This work reveals how network evolution mechanisms control the obtained topology properties and it also provides insights on correlations between various structural characteristics of complex networks.Comment: 15 figure

SRFormer: Empowering Regression-Based Text Detection Transformer with Segmentation

Existing techniques for text detection can be broadly classified into two primary groups: segmentation-based methods and regression-based methods. Segmentation models offer enhanced robustness to font variations but require intricate post-processing, leading to high computational overhead. Regression-based methods undertake instance-aware prediction but face limitations in robustness and data efficiency due to their reliance on high-level representations. In our academic pursuit, we propose SRFormer, a unified DETR-based model with amalgamated Segmentation and Regression, aiming at the synergistic harnessing of the inherent robustness in segmentation representations, along with the straightforward post-processing of instance-level regression. Our empirical analysis indicates that favorable segmentation predictions can be obtained at the initial decoder layers. In light of this, we constrain the incorporation of segmentation branches to the first few decoder layers and employ progressive regression refinement in subsequent layers, achieving performance gains while minimizing additional computational load from the mask. Furthermore, we propose a Mask-informed Query Enhancement module. We take the segmentation result as a natural soft-ROI to pool and extract robust pixel representations, which are then employed to enhance and diversify instance queries. Extensive experimentation across multiple benchmarks has yielded compelling findings, highlighting our method's exceptional robustness, superior training and data efficiency, as well as its state-of-the-art performance

Estimation of Significant Wave Height using the features of cygnss Delay Doppler Map

Significant Wave Height (SWH) is a key parameter to characterize waves, which is typically used in sea state monitoring such as wave forecast to ensure ocean navigation safety. Satellite radar altimeter is probably the primary tool to obtain SWH information. However, it cannot be used for large-scale sea state monitoring unless many of theses satellites are deployed. In this article, we aim to study the potential of Global Navigation Satellite System (GNSS)-Reflectometry (GNSS-R) in SWH measurement based on spaceborne Delay-Doppler Maps (DDMs) data. First, 3 observables (i.e., Delay-Doppler Map Average (DDMA), leading edge slope (LES) of normalized integrated delay waveform (NIDW) (LES-NIDW), and trailing edge slope (TES) of NIDW (TES-NIDW) derived from the DDMs are introduced for SWH estimation. Then, an empirical SWH retrieval model is proposed based on three observables. Subsequently, ERA5 SWH is used as reference data to verify the performance of the proposed model. The experimental results show that the Root Mean Square Error (RMSE) and Correlation Coefficient (CC) estimated by SWH of the three observables are better than 0.54 m and 0.88 m, respectively. Among them, the estimation performance based on DDMA observable is the best, with RMSE and CC of 0.49 m and 0.89 m. This study shows the potential of spaceborne GNSS-R in SWH retrieval. © 2022 IEEE.This work was supported by the Grant RYC-2016-20918 financed by MCIN/AEI /10.13039 /501100011033 and by ESF Investing in your future.Peer ReviewedPostprint (published version

Treatment with K6PC-5, a selective stimulator of SPHK1, ameliorates intestinal homeostasis in an animal model of Huntington's disease

Abstract Emerging evidence indicates that Huntington's disease (HD) may be described as multi-organ pathology. In this context, we and others have contributed to demonstrate that the disease is characterized by an impairment of the homeostasis of gastro-intestinal (GI) tract. Sphingolipids represent a class of molecules involved in the regulation and maintenance of different tissues and organs including GI system. In this study, we investigated whether the alteration of Sphingosine-1-phosphate (S1P) metabolism, previously described in human HD brains and animal models, is also detectable peripherally in R6/2 HD mice. Our findings indicate, for the first time, that sphingolipid metabolism is perturbed early in the disease in the intestinal tract of HD mice and, its modulation by K6PC-5, a selective activator of S1P synthesis, preserved intestinal integrity and homeostasis. These results further support the evidence that modulation of sphingolipid pathways may represent a potential therapeutic option in HD and suggest that it has also the potential to counteract the peripheral disturbances which may usually complicate the management of the disease and affect patient's quality of life

Elevated intracellular cAMP exacerbates vulnerability to oxidative stress in optic nerve head astrocytes.

Glaucoma is characterized by a progressive loss of retinal ganglion cells and their axons, but the underlying biological basis for the accompanying neurodegeneration is not known. Accumulating evidence indicates that structural and functional abnormalities of astrocytes within the optic nerve head (ONH) have a role. However, whether the activation of cyclic adenosine 3',5'-monophosphate (cAMP) signaling pathway is associated with astrocyte dysfunction in the ONH remains unknown. We report here that the cAMP/protein kinase A (PKA) pathway is critical to ONH astrocyte dysfunction, leading to caspase-3 activation and cell death via the AKT/Bim/Bax signaling pathway. Furthermore, elevated intracellular cAMP exacerbates vulnerability to oxidative stress in ONH astrocytes, and this may contribute to axonal damage in glaucomatous neurodegeneration. Inhibition of intracellular cAMP/PKA signaling activation protects ONH astrocytes by increasing AKT phosphorylation against oxidative stress. These results strongly indicate that activation of cAMP/PKA pathway has an important role in astrocyte dysfunction, and suggest that modulating cAMP/PKA pathway has therapeutic potential for glaucomatous ONH degeneration

Determination of Thyroid Volume by Ultrasonography among Schoolchildren in Philippines

Objective. Iodine deficiency is defined by the goiter and the urinary iodine concentration. However, a lack of local thyroid volume reference data resulted in the vague definition of goiter, especially in school-aged children. The aim of this paper was to determine the thyroid volumes by ultrasonography in schoolchildren aged 6 to 12 years living in Cagayan areas in Philippine. Methods. Cross-sectional thyroid ultrasonographic data of 158 schoolchildren aged 6–12 years from Tuguegarao and Lagum in Cagayan valley, Philippine were used. Thyroid volumes were compared based on logistic issue and urban and rural area and compared with other previously reported data. Results. The mean values of thyroid volume in Tuguerago and Lagum were 2.99 ± 1.34 mL and 2.42 ± 0.92 mL. The thyroid size was significantly in association with age (P < 0.00), weight (P < 0.00), height (P < 0.00), and BSA (P < 0.00) by Pearson's correlation. The median thyroid volumes of schoolchildren investigated in this study were generally low compared to international reference data by age group but not by BSA. Conclusions. We propose for the first time local reference ultrasound values for thyroid volumes in 6–12 aged schoolchildren that should be used for monitoring iodine deficiency disorders

Soybeans Ameliolate Diabetic Nephropathy in Rats

Diabetic nephropathy is one of the most frequent and serious complications of diabetes mellitus. Soybeans have been shown to reduce urinary albumin excretion and total cholesterol in non-diabetic patients with nephrotic syndrome. However, reports focusing specifically on diabetic nephropathy are scarce and the available results are inconsistent. It was reported that soybean consumption reduced urinary protein excretion in type 1 diabetic patients with diabetic nephropathy, whereas it was found to elicit an increase in urinary protein excretion when soybeans were consumed by type 2 diabetic patients. This study aims to investigate the effects of soybean in diabetic nephropathy, particularly the effects of consuming soybeans on the histopathology of diabetic nephropathy, using aquaporin (AQP) and osteopontin (OPN) expression as diagnostic markers. Male Sprague-Dawley rats were assigned to one of three groups: control, diabetic with red chow diet and diabetic with soybean diet. For histological examination, the expression of OPN and AQP, renal function and hemoglobin A1c were evaluated at the end of the study. Improvements in glomerular and tubulointerstitial lesions were demonstrated in the diabetic rat group given a soybean diet. OPN and AQP expression were suppressed in the kidney specimens of diabetic rats with the soybean diet. In conclusion, soybeans may prevent the weight loss and morphological disruption of the kidney associated with diabetes mellitus. Soybeans also may improve glycemic control. It seems likely that long-term control of blood glucose levels using a soybean diet could prevent the progression of diabetes mellitus, and therefore, nephropathy could be prevented

Estimation of swell height using spaceborne GNSS-R data from eight CYGNSS satellites

Global Navigation Satellite System (GNSS)-Reflectometry (GNSS-R) technology has opened a new window for ocean remote sensing because of its unique advantages, including short revisit period, low observation cost, and high spatial-temporal resolution. In this article, we investigated the potential of estimating swell height from delay-Doppler maps (DDMs) data generated by spaceborne GNSS-R. Three observables extracted from the DDM are introduced for swell height estimation, including delay-Doppler map average (DDMA), the leading edge slope (LES) of the integrated delay waveform (IDW), and trailing edge slope (TES) of the IDW. We propose one modeling scheme for each observable. To improve the swell height estimation performance of a single observable-based method, we present a data fusion approach based on particle swarm optimization (PSO). Furthermore, a simulated annealing aided PSO (SA-PSO) algorithm is proposed to handle the problem of local optimal solution for the PSO algorithm. Extensive testing has been performed and the results show that the swell height estimated by the proposed methods is highly consistent with reference data, i.e., the ERA5 swell height. The correlation coefficient (CC) is 0.86 and the root mean square error (RMSE) is 0.56 m. Particularly, the SA-PSO method achieved the best performance, with RMSE, CC, and mean absolute percentage error (MAPE) being 0.39 m, 0.92, and 18.98%, respectively. Compared with the DDMA, LES, TES, and PSO methods, the RMSE of the SA-PSO method is improved by 23.53%, 26.42%, 30.36%, and 7.14%, respectively.This work was supported in part by the National Natural Science Foundation of China under Grant 42174022, in part by the Future Scientists Program of China University of Mining and Technology under Grant 2020WLKXJ049, in part by the Postgraduate Research & Practice Innovation Program of Jiangsu Province under Grant KYCX20_2003, in part by the Programme of Introducing Talents of Discipline to Universities, Plan 111, Grant No. B20046, and in part by the China Scholarship Council (CSC) through a State Scholarship Fund (No. 202106420009).Peer ReviewedPostprint (published version