Non-local Attention Optimized Deep Image Compression

This paper proposes a novel Non-Local Attention Optimized Deep Image Compression (NLAIC) framework, which is built on top of the popular variational auto-encoder (VAE) structure. Our NLAIC framework embeds non-local operations in the encoders and decoders for both image and latent feature probability information (known as hyperprior) to capture both local and global correlations, and apply attention mechanism to generate masks that are used to weigh the features for the image and hyperprior, which implicitly adapt bit allocation for different features based on their importance. Furthermore, both hyperpriors and spatial-channel neighbors of the latent features are used to improve entropy coding. The proposed model outperforms the existing methods on Kodak dataset, including learned (e.g., Balle2019, Balle2018) and conventional (e.g., BPG, JPEG2000, JPEG) image compression methods, for both PSNR and MS-SSIM distortion metrics

The price effects of prohibiting price parity clauses: evidence from international hotel groups

Dominant platforms such as Booking.com and Amazon often impose Price Parity Clauses to prevent sellers from charging lower prices on alternative sales channels. We provide quasi-experimental evidence on the removal of these price restrictions in France in 2015 for three major international hotel groups. First, our analyses reveal limited and non-significant price effects for rooms sold through channels visible to consumers, such as the hotels' websites or Online Travel Agencies. Second, we document a significant price reduction on sales channels not visible to consumers, such as the hotels' direct offline channel. Third, we identify a significant shift in sales share from online travel agencies to the hotels' direct offline channel

Highly sensitive electrochemical sensing platform for the detection of L-dopa based on electropolymerizing glutathione disulfide and multi-walled carbon nanotube-modified electrodes

Afacile sensing platformfor the detection of L-dopa has been developed by electropolymerizing glutathione disulfide (PGSSG) on the surface of glass carbon electrodes (GCE) which were modified by multi-walled carbon nanotubes (MWCNTs). The electrochemical behaviour of the proposed electrodes were investigated via cyclic voltammetry (CV) and differential pulse voltammetry DPV). The morphology of the PGSSG and PGSSG/MWCNTs were characterized by scanning electron microscopy (SEM). Under the optimized experimental conditions, the sensing platform showed the linear response to L-Dopa in a range from 1.0 × 10–6 to 1.2 × 10–3 M with a detection limit of 3.3 × 10–7M (S/N = 3). Moreover, with the merits of high sensitivity and selectivity, good stability and reproducibility, the sensor was successfully applied for the determination of L-dopa in a real sample.Keywords: L-dopa, glutathione disulfide, multi-walled carbon nanotubes, electropolymerization, electrochemical determinatio

The Price Effects of Banning Price Parity Clauses in the EU: Evidence from International Hotel Groups

Dominant platforms such as Booking.com and Amazon often impose Price Parity Clauses to prevent sellers from charging lower prices on alternative sales channels. We provide quasi-experimental evidence on the full removal of these price restrictions in France in 2015 for three major international hotel groups. Our analysis reveals a limited and non-significant effect on room prices. The external validity of this finding is established by focusing on similar policy interventions in Germany in 2016 and Austria in 2017. Our results imply that the prohibitions of Price Parity Clauses turned out to be ineffective in sizeably reducing final prices for consumers

Weight changes from early to middle adulthood and cardiometabolic multimorbidity later in life among middle-aged and older adults: a retrospective cohort study from the NHANES 1999-2018

BackgroundWeight gain in adulthood can influence the development of diabetes and cardiovascular diseases. It is speculated that weight gain is related to cardiometabolic multimorbility (CMM). This study was designed to examine the relationships between weight changes from early to middle adulthood and the risk of CMM.MethodsData of the National Health and Nutrition Examination Survey (NHANES) 1999-2018 cycles were analyzed in the present study. Weights at age 25 years and 10 years before recruitment were self-reported and were used to define five weight change patterns including stable normal, maximum overweight, obesity to non-obesity, non-obesity to obesity, and stable obesity patterns. Meanwhile, absolute weight changes were classified into five groups: weight loss≥ 2.5 kg, weight change within 2.5 kg, 2.5 kg≤ weight gain < 10.0 kg, 10.0 kg≤ weight gain < 20.0 kg, and weight gain≥ 20.0 kg. CMM was defined as the coexistence of two or three of diabetes, coronary heart disease (CHD), and stroke.ResultsA total of 25,994 participants were included. Across adulthood, compared to stable normal weight, maximal overweight, obesity to non-obesity, non-obesity to obesity, and stable obesity were consistently associated with increased risks of diabetes, CHD, and CMM. For instance, stable obesity was respectively related to 358.0% (HR: 4.58, 95% CI: 4.57, 4.58), 88.0% (HR: 1.88, 95% CI: 1.88, 1.88), and 292.0% (HR: 3.92, 95% CI: 3.91, 3.92) higher risks of diabetes, CHD, and CMM. Meanwhile, any account of weight loss and gain was linked to higher risks of diabetes, CHD, and CMM than weight change within 2.5 kg. However, participants with maximum overweight had a decreased incidence of stroke (HR: 0.85, 95% CI: 0.85, 0.86), and weight loss ≥ 2.5 kg and weight gain ≥ 2.5 and <20 kg were also related to a lower risk of stroke. J-shaped or U-shaped associations of absolute weight changes with the risks of diabetes, CHD, and CMM were observed.ConclusionsMaintaining a stable normal weight can benefit more from the prevention of diabetes, CHD, and CMM. Both weight gain and loss across adulthood were accompanied by increased risks of diabetes, CHD, and CMM