Watermarks Technique in MPEG-1Video by B-spline

As the computers are more and more integrated via the network, thedistribution of digital media is becoming faster, easier, and requiring less effort tomake exact copies. One of the major impediments is the lack of effectiveintellectual property protection of digital media to discourage unauthorizedcopying and distribution.This paper aims to produce random and dynamic watermarking technique toprovide copyright protection for digital media (video) by embedding a digitalimage for video sequences compressed according to the MPEG-1 video codingstandard.Digital image is used to be embedded in one of the most widespread video codingstandard (MPEG-1), by implementing third degree B-spline curve equation on Iframesmacroblocks data to interpolate data and provide according to thecomparing condition effective points that represent the selected location wherewatermark image will be embedded.Using B-spline curve fitting equation will show distribution of watermark locationthrough secondary intra-frame of MPEG-1 standard by drawing curves dependingon watermarked points as control points.Test measurements will be used to prove robustness of the proposed techniqueagainst watermark attacks and control point for curve drawing illustrating howwatermark image is distributed among a number of video samples

Extreme learning machine based sub-key generation for cryptography system

The key generation process is the substantial step in any cryptosystem. Incorporating Artificial Neural Network (ANN) in the algorithmic work of cryptography achieves good performance in realizing high accuracy and security. In this paper, ANN based sub-key generation algorithm is presented. Extreme learning Machine (ELM) type is adopted for one hidden layer neural network. Initial key includes all needed information about ANN topology, activation function, and seeds for Pseudo-Random Number Generation (PRNG) in each round to initialize input-hidden layer weights and data. Sub-key in each round is generated from output layer weights. Evaluation measures have proved complete sensitivity and inevitability of this approach. In addition, it contributes in reducing the risks of breaking the symmetric key algorithms due to the generated independent sub-key in each round. Thus, it can be integrated in any cryptosystem for subkey generation

Emésztőrendszeri diszfunkció és humorális immunválasz kapcsolata IV-es típusú kollagén mutációkkal Drosophilában

The structure and function of the mucosal epithelia is determined and supported by the underlying basement membrane (BM). The BM functions in separation, epithelial cell polarization, absorption, sensation and secretion in various tissues and body compartments. The BM is a specialized form of the extracellular matrix, composed of numerous components with a predominance of type IV collagens COL4A1 and COL4A2. Mammals, including humans, harbor three pairs of type IV collagen genes (COL4A1-6). The inherited disorder of renal, ocular and cochlear basement membranes associates with mutations of the X-linked COL4A5 gene in the majority of patients with Alport syndrome, whereas lesions in the autosomal COL4A3 and COL4A4 genes are responsible for the symptoms of Alport syndrome in about 20% of patients. The majority of the mammalian BM is composed of building units of type IV collagen trimers with (COL4A1)2COL4A2 composition. Clinical manifestations associated with COL4A1 mutations include perinatal cerebral hemorrhage and porencephaly, hereditary angiopathy, nephropathy, aneurysms, and muscle cramps (HANAC), ocular dysgenesis, myopathy and Walker-Warburg syndrome. The latest reports demonstrate systemic tissue degeneration and pleiotropy associated with COL4A1 mutations and confirm the experimental observations that the phenotypes of COL4A2 mutations are phenocopies of COL4A1 gene mutations. The mucosal epithelia of the gastrointestinal tract are constantly challenged by the microbiome resulting in various types of interactions including commensalism, symbiosis and pathogenicity. Host-microbe interactions in the gut are studied only in a few animal models including Drosophila melanogaster. Antimicrobial defense in Drosophila is facilitated by phagocytosis of pathogenic microorganisms, by the synthesis of antimicrobial peptides (AMPs) and by the generation of reactive oxygen species. Gut-associated bacterial community in Drosophila is scarce, harboring 1-20 bacterial phylotypes. Recent studies identified five dominating commensal species in the gut of wild-type flies: Lactobacillus plantarum, Lactobacillus brevis, Acetobacter pomorum, Gluconobacter morbifer and Commensalibacter intestini. Overexpression of AMPs, demonstrated in caudal hypomorphic RNAi mutants, resulted in restructuring of the commensal bacterial population with the dominance of the pathogenic Gluconobacter morbifer accompanied by degradation of gut epithelial cells and high mortality of the host. These observations suggested a potential role for high levels of AMPs in epithelial cell degeneration, gut pathogenesis, and increased mortality. In aging flies, dysfunction of the intestinal barrier that normally permits the absorption of nutrients and solutes and hampers host contact with harmful entities including microorganisms has been, accordingly, tightly linked to overexpression of AMPs. Compromised intestinal barrier function was also noted in big bang (bbg) null Drosophila mutants. The BBG protein is localized in the gut epithelial septate junctions that, in the absence of BBG, are compromised and result in reduced lifespan and chronic inflammation of the anterior midgut epithelium in mutant animals. We have recently reported an allelic series of conditional, dominant, temperature-sensitive (DTS) mutations in the type IV collagen gene col4a1 in Drosophila. The col4a1mutant heterozygotes are viable and fertile at permissive temperature (20oC), but perish at restrictive temperature (29oC). The phenotype associated with mutations of col4a1 include severe myopathy resulting from massive degradation of striated muscle fibers and degeneration of both the circular smooth muscle cells and epithelial cells of the gut that occurs following detachment from the BM. While there are signs of some repair, the capacity of the scavenger system, and/or the kinetics of cell renewal and regeneration fail to keep up with the ongoing cell degeneration in these mutants. Based on these observations, we hypothesized that col4a1 mutants may suffer from extensive cell damage-induced chronic inflammation and demonstrate a robust immune response. In Drosophila, during inflammation the immune response involves the immediate synthesis of AMPs. Therefore, we have carried out a series of tests in order to determine whether AMP induction is associated with mutation-induced aberrant col4a1 functions in DTS-L3 mutants selected for analysis based on the presence of confirmed cell degeneration and its lowest survival rate among the col4a1 mutant lines at 29oC..

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Extreme learning machine based optimal embedding location finder for image steganography.

In image steganography, determining the optimum location for embedding the secret message precisely with minimum distortion of the host medium remains a challenging issue. Yet, an effective approach for the selection of the best embedding location with least deformation is far from being achieved. To attain this goal, we propose a novel approach for image steganography with high-performance, where extreme learning machine (ELM) algorithm is modified to create a supervised mathematical model. This ELM is first trained on a part of an image or any host medium before being tested in the regression mode. This allowed us to choose the optimal location for embedding the message with best values of the predicted evaluation metrics. Contrast, homogeneity, and other texture features are used for training on a new metric. Furthermore, the developed ELM is exploited for counter over-fitting while training. The performance of the proposed steganography approach is evaluated by computing the correlation, structural similarity (SSIM) index, fusion matrices, and mean square error (MSE). The modified ELM is found to outperform the existing approaches in terms of imperceptibility. Excellent features of the experimental results demonstrate that the proposed steganographic approach is greatly proficient for preserving the visual information of an image. An improvement in the imperceptibility as much as 28% is achieved compared to the existing state of the art methods

Extreme learning machine based optimal embedding location finder for image steganography

<div><p>In image steganography, determining the optimum location for embedding the secret message precisely with minimum distortion of the host medium remains a challenging issue. Yet, an effective approach for the selection of the best embedding location with least deformation is far from being achieved. To attain this goal, we propose a novel approach for image steganography with high-performance, where extreme learning machine (ELM) algorithm is modified to create a supervised mathematical model. This ELM is first trained on a part of an image or any host medium before being tested in the regression mode. This allowed us to choose the optimal location for embedding the message with best values of the predicted evaluation metrics. Contrast, homogeneity, and other texture features are used for training on a new metric. Furthermore, the developed ELM is exploited for counter over-fitting while training. The performance of the proposed steganography approach is evaluated by computing the correlation, structural similarity (SSIM) index, fusion matrices, and mean square error (MSE). The modified ELM is found to outperform the existing approaches in terms of imperceptibility. Excellent features of the experimental results demonstrate that the proposed steganographic approach is greatly proficient for preserving the visual information of an image. An improvement in the imperceptibility as much as 28% is achieved compared to the existing state of the art methods.</p></div

General framework of the proposed OELF model.

<p>General framework of the proposed OELF model.</p

Achieved host (left) and stego (right) images.

<p>Achieved host (left) and stego (right) images.</p

Training data set percentage dependent variation of Corr for the Lena, Sails, and Baboon images.

<p>Training data set percentage dependent variation of Corr for the Lena, Sails, and Baboon images.</p