A FPGA based Steganographic System Implementing a Modern Steganalysis Resistant LSB Algorithm

Steganography differs from other data hiding techniques because it encodes secret message inside cover object in such a way that transmission of secret message also remains a secret. Widespread usage of digital images, lower computational complexity and better performance makes spatial domain steganographic algorithms well suited for hardware implementation, which are not very frequent. This work tries to implement a modern steganalysis resistant LSB algorithm on FPGA based hardware. The presented work also optimises various operations and elements from original one third probability algorithm with respect to hardware implementation. The target FPGA for the implementation is Xilinx SP605 board (Spartan 6 series XC6SLX45T FPGA). Stego images obtained by the implementation have been thoroughly examined for various qualitative and quantitative aspects, which are found to be at par with original algorithm

Conceptual design to transfer handicapped or old people from one platform to another

The problem to transfer handicapped or old people is as old as the transportation system itself. Earlier and even now they are transferred by many methods like on wheelchairs or with the help of sticks. But all these methods are time consuming and slow and also don’t have any provision for carrying the luggage. These methods are good in general use, but on platforms these cannot be used as these methods will complicate the transportation and will disrupt the free movement of the people on platforms. So here our aim is to design a system or device which will be able to transfer the handicapped people from one platform to another, within the given constraints and should also comply with the societies exiting conditions. The system may be semi-manually driven or semi-automatic or may be fully automatic. Here first of all we are defining the Statement of the problem, followed by the analyzation of the need and then we have given various alternatives we have thought off, following it is the description of different alternatives with the problems we are facing in the practical application of the alternatives. The alternatives thus produced has been evaluated and the best one was chosen. Then, morphological analysis, is done on the chosen alternative, thus giving the final design and specification

Scalable H.264 Wireless Video Transmission over MIMO-OFDM Channels

Abstract. A cross-layer optimization scheme is proposed for scalable video transmission over wireless Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems. The scalable video coding (SVC) extension of H.264/AVC is used for video source coding. The proposed cross-layer optimization scheme jointly optimizes application layer parameters and physical layer parameters. The objective is to minimize the expected video distortion at the receiver. Two methods have been developed for the estimation of video distortion at the receiver, which is essential for the cross-layer optimization. In addition, two different priority mappings of the SVC scalable layers are considered. Experimental results are provided and conclusions are drawn

Regulators of G protein signalling proteins in the human myometrium

The contractile state of the human myometrium is controlled by extracellular signals that promote relaxation or contraction. Many of these signals function through G proteincoupled receptors at the cell surface, stimulating heterotrimeric G proteins and leading to changes in the activity of effector proteins responsible for bringing about the response. G proteins can interact with multiple receptors and many different effectors and are key players in the response. Regulators of G protein signalling (RGS) proteins are GTPase activating proteins for heterotrimeric G proteins and help terminate the signal. Little is known about the function of RGS proteins in human myometrium and we have therefore analysed transcript levels for RGS proteins at various stages of pregnancy (non-pregnant, preterm, term non-labouring, term labouring). RGS2 and RGS5 were the most abundantly expressed isolates in each of the patient groups. The levels of RGS4 and RGS16 (and to a lesser extent RGS2 and RGS14) increased in term labouring samples relative to the other groups. Yeast two-hybrid analysis and co-immunoprecipitation in myometrial cells revealed that both RGS2 and RGS5 interact directly with the cytoplasmic tail of the oxytocin receptor, suggesting they might help regulate signalling through this receptor. Key words: G protein-coupled receptors; labour; myometrium; RGS protein

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Effect of various Crossover operators in Memetic algorithm on Multi-input adders

Abstract: Binary Decision Diagram (BDD) is an important data structure play a major role in reduction of nodes and computation time. In this paper, Memetic algorithm with various crossover operators has been proposed for reduction of BDD node count and the execution time. The results have been compared using various Crossover operators (namely ordered, partially mapped and cyclic) for multi-input Adder Benchmark Circuits