Reversible data hiding in JPEG images based on adjustable padding

In this paper, we propose a reversible data hiding scheme that enables an adjustable amount of information to be embedded in JPEG images based on padding strategy. The proposed embedding algorithm only modifies, in a subtle manner, an adjustable number of zero-valued quantised DCT coefficients to embed the message. Hence, compared with a state-of-the-art based on histogram shifting, the proposed scheme has a relatively low distortion to the host images. In addition to this, we found that by representing the message in ternary instead of in binary, we can embed a greater amount of information while the level of distortion remains unchanged. Experimental results support that the proposed scheme can achieve better visual quality of the marked JPEG image than the histogram shifting based scheme. The proposed scheme also outperforms this state-of-the-art in terms of the ease of implementation

Secure secret sharing in the cloud

In this paper, we show how a dealer with limited resources is possible to share the secrets to players via an untrusted cloud server without compromising the privacy of the secrets. This scheme permits a batch of two secret messages to be shared to two players in such a way that the secrets are reconstructable if and only if two of them collaborate. An individual share reveals absolutely no information about the secrets to the player. The secret messages are obfuscated by encryption and thus give no information to the cloud server. Furthermore, the scheme is compatible with the Paillier cryptosystem and other cryptosystems of the same type. In light of the recent developments in privacy-preserving watermarking technology, we further model the proposed scheme as a variant of reversible watermarking in the encrypted domain

Attenuation of Brain Nitrostative and Oxidative Damage by Brain Cooling during Experimental Traumatic Brain Injury

The aim of the present study was to ascertain whether brain cooling causes attenuation of traumatic brain injury by reducing brain nitrostative and oxidative damage. Brain cooling was accomplished by infusion of 5 mL of 4°C saline over 5 minutes via the external jugular vein. Immediately after the onset of traumatic brain injury, rats were randomized into two groups and given 37°C or 4°C normal saline. Another group of rats were used as sham operated controls. Behavioral and biochemical assessments were conducted on 72 hours after brain injury or sham operation. As compared to those of the sham-operated controls, the 37°C saline-treated brain injured animals displayed motor deficits, higher cerebral contusion volume and incidence, higher oxidative damage (e.g., lower values of cerebral superoxide dismutase, catalase, glutathione peroxidase and glutathione reductase, but higher values of cerebral malondialdehyde), and higher nitrostative damage (e.g., higher values of neuronal nitric oxide synthase and 3-nitrotyrosine). All the motor deficits and brain nitrostative and oxidative damage were significantly reduced by retrograde perfusion of 4°C saline via the jugular vein. Our data suggest that brain cooling may improve the outcomes of traumatic brain injury in rats by reducing brain nitrostative and oxidative damage

Deep Learning for Reversible Steganography: Principles and Insights

Deep-learning\textendash{centric} reversible steganography has emerged as a promising research paradigm. A direct way of applying deep learning to reversible steganography is to construct a pair of encoder and decoder, whose parameters are trained jointly, thereby learning the steganographic system as a whole. This end-to-end framework, however, falls short of the reversibility requirement because it is difficult for this kind of monolithic system, as a black box, to create or duplicate intricate reversible mechanisms. In response to this issue, a recent approach is to carve up the steganographic system and work on modules independently. In particular, neural networks are deployed in an analytics module to learn the data distribution, while an established mechanism is called upon to handle the remaining tasks. In this paper, we investigate the modular framework and deploy deep neural networks in a reversible steganographic scheme referred to as prediction-error modulation, in which an analytics module serves the purpose of pixel intensity prediction. The primary focus of this study is on deep-learning\textendash{based} context-aware pixel intensity prediction. We address the unsolved issues reported in related literature, including the impact of pixel initialisation on prediction accuracy and the influence of uncertainty propagation in dual-layer embedding. Furthermore, we establish a connection between context-aware pixel intensity prediction and low-level computer vision and analyse the performance of several advanced neural networks

Privacy-aware reversible watermarking in cloud computing environments

As an interdisciplinary research between watermarking and cryptography, privacy-aware reversible watermarking permits a party to entrust the task of embedding watermarks to a cloud service provider without compromising information privacy. The early development of schemes were primarily based upon traditional symmetric-key cryptosystems, which involve an extra implementation cost of key exchange. Although recent research attentions were drawn to schemes compatible with asymmetric-key cryptosystems, there were notable limitations in the practical aspects. In particular, the host signal must either be enciphered in a redundant way or be pre-processed prior to encryption, which would largely limit the storage efficiency and scheme universality. To relax the restrictions, we propose a novel research paradigm and devise different schemes compatible with different homomorphic cryptosystems. In the proposed schemes, the encoding function is recognised as an operation of adding noise, whereas the decoding function is perceived as a corresponding denoising process. Both online and offline contentadaptive predictors are developed to assist watermark decoding for various operational requirements. A three-way trade-off between the capacity, fidelity and reversibility is analysed mathematically and empirically. It is shown that the proposed schemes achieve the state-the-art performance

Attenuation of Acute Lung Inflammation and Injury by Whole Body Cooling in a Rat Heatstroke Model

Whole body cooling is the current therapy of choice for heatstroke because the therapeutic agents are not available. In this study, we assessed the effects of whole body cooling on several indices of acute lung inflammation and injury which might occur during heatstroke. Anesthetized rats were randomized into the following groups and given (a) no treatment or (b) whole body cooling immediately after onset of heatstroke. As compared with the normothermic controls, the untreated heatstroke rats had higher levels of pleural exudates volume and polymorphonuclear cell numbers, lung myloperoxidase activity and inducible nitric oxide synthase expression, histologic lung injury score, and bronchoalveolar proinflammatory cytokines and glutamate, and PaCO2. In contrast, the values of mean arterial pressure, heart rate, PaO2, pH, and blood HCO3− were all significantly lower during heatstroke. The acute lung inflammation and injury and electrolyte imbalance that occurred during heatstroke were significantly reduced by whole body cooling. In conclusion, we identified heat-induced acute lung inflammation and injury and electrolyte imbalance could be ameliorated by whole body cooling

The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals

To dissect the genetic architecture of blood pressure and assess effects on target-organ damage, we analyzed 128,272 SNPs from targeted and genome-wide arrays in 201,529 individuals of European ancestry and genotypes from an additional 140,886 individuals were used for validation. We identified 66 blood pressure loci, of which 17 were novel and 15 harbored multiple distinct association signals. The 66 index SNPs were enriched for cis-regulatory elements, particularly in vascular endothelial cells, consistent with a primary role in blood pressure control through modulation of vascular tone across multiple tissues. The 66 index SNPs combined in a risk score showed comparable effects in 64,421 individuals of non-European descent. The 66-SNP blood pressure risk score was significantly associated with target-organ damage in multiple tissues, with minor effects in the kidney. Our findings expand current knowledge of blood pressure pathways and highlight tissues beyond the classic renal system in blood pressure regulation

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms