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

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\u27s 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

Evaluation of the mixing performance in a planar passive micromixer with T micromixer with square chamber mixing units (SAR)

Microscale mixing methods are crucial in various disciplines, encompassing chemical reactions and biological investigations. The present study used simulation methodologies to investigate the operational efficiency of splitting recombination (SAR) micromixers. The study demonstrates that SAR micromixers offer a notable advantage in enhancing mixing efficiency. The advantage above is a consequence of the effective combination of splitting-recombination and chaotic advection processes within the micromixer architecture. An in-depth analysis of the micromixer's behavior demonstrates that its performance is supported by intricate fluid dynamics, which provide remarkably high mixing efficiency. It is worth noting that the micromixer exhibits its maximum mixing efficiency, which is roughly 99% when the Reynolds number (Re) is at or below 0.5. Nevertheless, it is seen that as the Reynolds number grows, there is a steady decrease in mixing efficiency. At a Reynolds number of 70, the measurement of mixing efficiency yields a value of 75%. However, when the Reynolds number is further increased to a range of 90-100, the efficiency decreases to its lowest value of approximately 60%. The results above highlight the exceptional mixing ability of the SAR micromixer, hence stressing its potential for various applications that demand improved mixing capabilities. The results emphasize the promise of SAR micromixers as a reliable solution for complex mixing processes in many applications, providing valuable insights that may contribute to future developments in microscale mixing technologies.</p

Evaluating the mixing performance in a planar passive micromixer with t-shape and SAR mixing chambers: comparative study

In Microfluidic devices have gained significant interest in various fields, including biomedical diagnostics, environmental preservation, animal epidemic avoidance, and food safety regulation. Micromixing phenomena are crucial for these devices' functionality, as they accurately and efficiently manipulate fluids within microchannels. The process aims to blend samples accurately and swiftly within these scaled-down devices, governed by the promotion of dispersion among distinct fluid species or particles. Advancements in passive and active micromixers have led to innovative designs incorporating diverse processes to enhance mixing efficiency. Examples include two-dimensional impediments, controlled imbalanced collisions, and complex configurations like spiral and convergence-divergence structures. Active micromixers use external cues to initiate and regulate mixing processes, including thermal, magnetic, sound, pressure, and electrical fields. The trajectory of micromixing technologies is significantly influenced by current developments in microfluidics. One notable advancement is the incorporation of micromixers into 3D printing methodologies, facilitating the development of adaptable microfluidic systems. Additionally, the incorporation of microfluidic principles into paper-based channels creates opportunities for the development of cost-effective and portable diagnostic devices. The process of micro-mixing is critical in boosting the functionalities of these devices.</p

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