Efficient H.264 intra Frame CODEC with Best prediction matrix mode algorithm

The continuous growth of smart communities and everincreasingdemand of sending or storing videos, have led toconsumption of huge amount of data. The video compressiontechniques are solving this emerging challenge. However, H.264standard can be considered most notable, and it has proven to meetproblematic requirements. The authors present (BPMM) as a novelefficient Intra prediction scheme. We can say that the creation of ourproposed technique was in a phased manner; it's emerged as aproposal and achieved impressive results in the performanceparameters as compression ratios, bit rates, and PSNR. Then in thesecond stage, we solved the challenges of overcoming the obstacle ofencoding bits overhead. In this research, we try to address the finalphase of the (BPMM) codec and to introduce our approach in a globalmanner through realization of decoding mechanism. For evaluation ofour scheme, we utilized VHDL as a platform. Final results haveproven our success to pass bottleneck of this phase, since the decodedvideos have the same PSNR that our encoder tells us, whilepreserving steady compression ratio treating the overhead. We aspireour BPMM algorithm will be adopted as reference design of H.264 inthe ITU

Deep learning can improve early skin cancer detection

Skin cancer is the most common form of cancer affecting humans. Melanoma is the most dangerous type of skin cancer; and early diagnosis is extremely vital in curing the disease. So far, the human knowledge in this field is very limited, thus, developing a mechanism capable of identifying the disease early on can save lives, reduce intervention and cut unnecessary costs. In this paper, the researchers developed a new learning technique to classify skin lesions, with the purpose of observing and identifying the presence of melanoma.  This new technique is based on a convolutional neural network solution with multiple configurations; where the researchers employed an International Skin Imaging Collaboration (ISIC) dataset. Optimal results are achieved through a convolutional neural network composed of 14 layers. This proposed system can successfully and reliably predict the correct classification of dermoscopic lesions with 97.78% accuracy

Pattern and severity of childhood unintentional injuries in Ismailia city, Egypt

In 2009, more than 746 000 injury cases were registered in the Ministry of Health hospitals in Egypt, with an injury rate of 1 004/100 000 population. Around 38% of all injuries occur among children and young adults less than 20 years of age. Furthermore, more than 20 000 people lose their lives to injuries every year (27/100 000). However, these data lack information on injury pattern, severity, provided care and outcome of injuries, which are essential data for planning injury control programmes.The aim of this study was to determine the frequency, nature and risk factors of childhood injuries in the Suez Canal University Hospital Emergency Department.The study included a total of 551 children of 12 years of age. The most common causes of injuries among those children were falls (60%), road traffic injuries (15%) and burns (7%). The most commonly sustained injuries were fractures (23%), cuts or open wounds (21%), sprains (20%) and burns (13%). Overall injury severity scores (ISSs) were low across all injury types, except road traffic injuries (RTIs). The majority of patients were treated and discharged without disability (50.5%), while 7.4% had long-term temporary disability that lasted for more than 6 weeks, and 1.9% sustained permanent disability. There were two deaths (0.4% proportionate mortality); both of them were due to falls from a height.In conclusion, the study confirms the feasibility of documenting the burden of childhood injuries on health systems in Egypt. It also confirmed the need for tailored injury-prevention research in Egypt. The resulting data should encourage interventional trials to be conducted, appropriate injury-prevention strategies to be implemented and timely interventions to be planned.Keywords: Childhood unintentional injuries, Egypt, risk factors

Telomere length, comorbidity, functional, nutritional and cognitive status as predictors of 5 years post hospital discharge survival in the oldest old

Background: Telomere length has been considered in many cross-sectional studies as a biomarker of aging. However the association between shorter telomeres with lower survival at advanced ages remains a controversial issue. This association could reflect the impact of other health conditions than a direct biological effect. Objective: To test whether leukocyte telomere length is associated with 5-year survival beyond the impact of other risk factors of mortality like comorbidity, functional, nutritional and cognitive status. Design: Prospective study. Setting and participants: A population representative sample of 444 patients (mean age 85 years; 74% female) discharged from the acute geriatric hospital of Geneva University Hospitals (January-December 2004), since then 263 (59.2%) had died (December 2009). Measurements: Telomere length in leukocytes by flow cytometry. Results: In univariate model, telomere length at baseline and cognitive status were not significantly associated with mortality even when adjusting for age (R2=9.5%) and gender (R2=1.9%). The best prognostic predictor was the geriatric index of comorbidity (GIC) (R2=8.8%; HR=3.85) followed by more dependence in instrumental (R2=5.9%; HR=3.85) and based (R2=2.3%; HR=0.84) activities of daily living and lower albumin levels (R2=1.5%; HR=0.97). Obesity (BMI>30: R2=1.6%; HR=0.55) was significantly associated with a two-fold decrease in the risk of mortality compared to BMI between 20-25. When all independent variables were entered in a full multiple Cox regression model (R2=21.4%), the GIC was the strongest risk predictor followed by the nutritional and functional variables. Conclusion: Neither telomeres length nor the presence of dementia are predictors of survival whereas the weight of multiple comorbidity conditions, nutritional and functional impairment are significantly associated with 5-year mortality in the oldest ol

LIDAR-INERTIAL LOCALIZATION WITH GROUND CONSTRAINT IN A POINT CLOUD MAP

Real-time localization is a crucial task in various applications, such as automatic vehicles (AV), robotics, and smart city. This study proposes a framework for map-aided LiDAR-inertial localization, with the objective of accurately estimating the trajectory in a point clouds map. The proposed framework addresses the localization problem through a factor graph optimization (FGO), enabling the fusion of homogenous measurements for sensor fusion and designed absolute and relative constraints. Specifically, the framework estimates the light detection and ranging (LiDAR) odometry by leveraging inertial measurement unit (IMU) and registering corresponding featured points. To eliminate the accumulative error, this paper employs a ground plane distance and a map matching error to constraint the positioning error along the trajectory. Finally, local odometry and constraints are integrated using a FGO, including LiDAR odometry, IMU pre-integration, and ground constraints, map matching constraints, and loop closure. Experimental results were evaluated on an open-source dataset, UrbanNav, with an overall localization accuracy of 2.29 m (root mean square error, RMSE)

Use it or lose it! Cognitive activity as a protec-tive factor for cognitive decline associated with Alzheimer's disease.

Because of the worldwide aging of populations, Alzheimer's disease and other dementias constitute a devastating experience for patients and families as well as a major social and economic burden for both healthcare systems and society. Multiple potentially modifiable cardiovascular and lifestyle risk factors have been associated with this disease. Thus, modifying these risk factors and identifying protective factors represent important strategies to prevent and delay disease onset and to decrease the social burden. Based on the cognitive reserve hypothesis, evidence from epidemiological studies shows that low education and cognitive inactivity constitute major risk factors for dementia. This indicates that a cognitively active lifestyle may protect against cognitive decline or delay the onset of dementia. We describe a newly developed preventive programme, based on this evidence, to stimulate and increase cognitive activity in older adults at risk for cognitive decline. This programme, called "BrainCoach", includes the technique of "motivational interviewing" to foster behaviour change. If the planned feasibility study is successful, we propose to add BrainCoach as a module to the already existing "Health Coaching" programme, a Swiss preventive programme to address multiple risk factors in primary care

Defining the temporal evolution of gut dysbiosis and inflammatory responses leading to hepatocellular carcinoma in Mdr2 -/- mouse model.

BACKGROUND: Emerging evidence implicates the gut microbiome in liver inflammation and hepatocellular carcinoma (HCC) development. We aimed to characterize the temporal evolution of gut dysbiosis, in relation to the phenotype of systemic and hepatic inflammatory responses leading to HCC development. In the present study, Mdr2 -/- mice were used as a model of inflammation-based HCC. Gut microbiome composition and function, in addition to serum LPS, serum cytokines/chemokines and intrahepatic inflammatory genes were measured throughout the course of liver injury until HCC development. RESULTS: Early stages of liver injury, inflammation and cirrhosis, were characterized by dysbiosis. Microbiome functional pathways pertaining to gut barrier dysfunction were enriched during the initial phase of liver inflammation and cirrhosis, whilst those supporting lipopolysaccharide (LPS) biosynthesis increased as cirrhosis and HCC ensued. In parallel, serum LPS progressively increased during the course of liver injury, corresponding to a shift towards a systemic Th1/Th17 proinflammatory phenotype. Alongside, the intrahepatic inflammatory gene profile transitioned from a proinflammatory phenotype in the initial phases of liver injury to an immunosuppressed one in HCC. In established HCC, a switch in microbiome function from carbohydrate to amino acid metabolism occurred. CONCLUSION: In Mdr2 -/- mice, dysbiosis precedes HCC development, with temporal evolution of microbiome function to support gut barrier dysfunction, LPS biosynthesis, and redirection of energy source utilization. A corresponding shift in systemic and intrahepatic inflammatory responses occurred supporting HCC development. These findings support the notion that gut based therapeutic interventions could be beneficial early in the course of liver disease to halt HCC development

Malignant perivascular epithelioid cell tumor of the uterus

Perivascular epithelioid cell tumors (PEComas) are a rare collection of tumors arising in a wide array of anatomic locations and characterized by a myomelanocytic phenotype. PEComas which occur in non-classic anatomic distributions are known as perivascular epithelioid cell tumor-not otherwise specified (PEComa-NOS), and one of the most common primary sites for PEComa-NOS is the uterus. The risk of aggressive behavior of these tumors has been linked to a number of factors evaluable on pathologic review following initial surgical resection. We report a case of PEComa-NOS of the uterus with multiple high-risk features, including frank vascular invasion, with no evidence of recurrent disease 18 months following initial surgical resection

Outcomes in hepatitis C virus–infected recipients of living donor vs. deceased donor liver transplantation

In this retrospective study of hepatitis C virus (HCV)–infected transplant recipients in the 9-center Adult to Adult Living Donor Liver Transplantation Cohort Study, graft and patient survival and the development of advanced fibrosis were compared among 181 living donor liver transplant (LDLT) recipients and 94 deceased donor liver transplant (DDLT) recipients. Overall 3-year graft and patient survival were 68% and 74% in LDLT, and 80% and 82% in DDLT, respectively. Graft survival, but not patient survival, was significantly lower for LDLT compared to DDLT ( P = 0.04 and P = 0.20, respectively). Further analyses demonstrated lower graft and patient survival among the first 20 LDLT cases at each center (LDLT 20; P = 0.002 and P = 0.002, respectively) and DDLT recipients ( P 20 and DDLT were not significantly different ( P = 0.66 and P = 0.74, respectively). Overall, 3-year graft survival for DDLT, LDLT >20, and LDLT 20 were not significantly different. Important predictors of graft loss in HCV-infected patients were limited LDLT experience, pretransplant HCC, and higher MELD at transplantation. Liver Transpl 13:122–129, 2007. © 2006 AASLD.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/55915/1/20995_ftp.pd