Performance Evaluation of Multicore Cache Locking using Multimedia Applications

Supporting real-time multimedia applications on multicore systems is a great challenge due to cache’s dynamic behavior. Studies show that cache locking may improve execution time predictability and power/performance ratio. However, entire locking at level-1 cache (CL1) may not be efficient if smaller amount of instructions/data compared to the cache size is locked. An alternative choice may be way (i.e., partial) locking. For some processors, way locking is possible only at level-2 cache (CL2). Even though both CL1 cache locking and CL2 cache locking improve predictability, it is difficult to justify the performance and power trade-off between these two cache locking mechanisms. In this work, we assess the impact of CL1 and CL2 cache locking on the performance, power consumption, and predictability of a multicore system using ISO standard H.264/AVC, MPEG4, and MPEG3 multimedia applications and FFT and DFT codes. Simulation results show that both the performance and predictability can be increased and the total power consumption can be decreased by using a cache locking mechanism added to a cache memory hierarchy. Results also show that for the applications used, CL1 cache locking outperforms CL2 cache locking

Structural and electronic properties of Si/Ge nanoparticles

Results of a theoretical study of the electronic properties of (Si)Ge and (Ge)Si core/shell nanoparticles, homogeneous SiGe clusters, and Ge$|$Si clusters with an interphase separating the Si and Ge atoms are presented. In general, (Si)Ge particles are more stable than (Ge)Si ones, and SiGe systems are more stable than Ge$|$Si ones. It is found that the frontier orbitals, that dictate the optical properties, are localized to the surface, meaning that saturating dangling bonds on the surface with ligands may influence the optical properties significantly. In the central parts we identify a weak tendency for the Si atoms to accept electrons, whereas Ge atoms donate electrons.Comment: To appear in Phys. Rev.

GPU Computing to Improve Game Engine Performance

Although the graphics processing unit (GPU) was originally designed to accelerate the image creation for output to display, today's general purpose GPU (GPGPU) computing offers unprecedented performance by offloading computing-intensive portions of the application to the GPGPU, while running the remainder of the code on the central processing unit (CPU). The highly parallel structure of a many core GPGPU can process large blocks of data faster using multithreaded concurrent processing. A game engine has many "components" and multithreading can be used to implement their parallelism. However, effective implementation of multithreading in a multicore processor has challenges, such as data and task parallelism. In this paper, we investigate the impact of using a GPGPU with a CPU to design high-performance game engines. First, we implement a separable convolution filter (heavily used in image processing) with the GPGPU. Then, we implement a multiobject interactive game console in an eight-core workstation using a multithreaded asynchronous model (MAM), a multithreaded synchronous model (MSM), and an MSM with data parallelism (MSMDP). According to the experimental results, speedup of about 61x and 5x is achieved due to GPGPU and MSMDP implementation, respectively. Therefore, GPGPU-assisted parallel computing has the potential to improve multithreaded game engine performance

Prospects and Challenges of Journalism in Northern Divisions of Bangladesh: An Exploratory Study

Journalists are highly respected members of our society usually known as mass media personalities who make important contributions to the promotion of economy education safety security peace loveand overall prosperity of the country They also up hold public opinions sufferings as well as all the happenings of every nook and corner of our society through electronic and print media so that the people all over the country as well as the government can know the overall aspects and situation of the country which could help all the organs of government to take propersteps in case of necessary and emergenc

Deep CNN-LSTM With Self-Attention Model for Human Activity Recognition Using Wearable Sensor

Human Activity Recognition (HAR) systems are devised for continuously observing human behavior - primarily in the fields of environmental compatibility, sports injury detection, senior care, rehabilitation, entertainment, and the surveillance in intelligent home settings. Inertial sensors, e.g., accelerometers, linear acceleration, and gyroscopes are frequently employed for this purpose, which are now compacted into smart devices, e.g., smartphones. Since the use of smartphones is so widespread now-a-days, activity data acquisition for the HAR systems is a pressing need. In this article, we have conducted the smartphone sensor-based raw data collection, namely H-Activity , using an Android-OS-based application for accelerometer, gyroscope, and linear acceleration. Furthermore, a hybrid deep learning model is proposed, coupling convolutional neural network and long-short term memory network (CNN-LSTM), empowered by the self-attention algorithm to enhance the predictive capabilities of the system. In addition to our collected dataset ( H-Activity ), the model has been evaluated with some benchmark datasets, e.g., MHEALTH, and UCI-HAR to demonstrate the comparative performance of our model. When compared to other models, the proposed model has an accuracy of 99.93% using our collected H-Activity data, and 98.76% and 93.11% using data from MHEALTH and UCI-HAR databases respectively, indicating its efficacy in recognizing human activity recognition. We hope that our developed model could be applicable in the clinical settings and collected data could be useful for further research.publishedVersio

In Vitro Screening for Antioxidant and Anticholinesterase Effects of Uvaria littoralis Blume.: A Nootropic Phytotherapeutic Remedy

Background: Oxidative stress is strongly linked in the development of numerous chronic and degenerative disorders. Medicinal plants with antioxidant and anticholinesterase activities exert a key role for the management of oxidative stress related disorders mainly Alzheimer's disease (AD). Therefore the purpose of this study was to assess antioxidant potentiality and anticholinesterase inhibitory activity of crude methanolic extract (CME), petroleum ether fraction (PEF), chloroform fraction (CLF), ethyl acetate fraction (EAF) and aqueous fraction (AQF) of Uvaria littoralis (U. littoralis) leaves. Methods: The antioxidant compounds namely total flavonoids contents (TFCs) and total proanthocyanidins contents (TPACCs) were determined for quantities constituent’s characterization. Antioxidant capacity of U. littoralis leaves were estimated by the iron reducing power (IRPA), 1, 1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging and nitric oxide (NO) radical scavenging capacity. Anticholinesterase effects were estimated for acetylcholinesterase (AChE) and butyrylcholinestrase (BChE) activity. Results: The EAF of U. littoralis leaves showed the highest TFCs as compared to CLF, CME, PEF and AQF. TPACCs were also found highest in EAF. The highest absorbance for IRPA was found in EAF (2.220 nm) with respect to CME and other fractions at the highest concentration. The EAF showed best DPPH and NO radical scavenging activity with IC50 values of 31.63 and 55.47 μg/mL, respectively with regard to CME and remaining fractions. The PEF represents highest AChE inhibitory activity with IC50 values of 35.19 μg/mL and CLF showed highest BChE inhibitory activity with IC50 values of 32.49 μg/mL. Conclusions: The findings of the current study demonstrate the presence of antioxidant phytochemicals, likewise, turns out antioxidant and anticholinesterase potentiality of U. littoralis leaves which could be a prestigious candidate for the treatment of neurodegenerative diseases especially AD

Evaluation of Gentamicin's Antimicrobial Resistance Pattern Against Uropathogens in a Tertiary Health Care Center in Dhaka City, Bangladesh

Treatment of UTI patients with aminoglycosides is a familiar incidence. Resistance of antibiotics is also a familiar incidence but it is alarming when it goes to a high ratio. The vital public health problem in developing country like Bangladesh is resistance of antibiotics to different types of bacteria causing UTI and the rates of these bacterial resistances are changing for various antibiotic therapy. Our aim was to assess the susceptible pattern of Gentamicin a drug of Aminoglycosides group against uropathogens. A total of 12943 urine samples were collected in 2016 (Jan-Dec) and out of which 1236 (9.55%) were bacteriologically positive out of these isolated  95.1% were gram negative and 4.9% gram positive organism. Male were found more prone to get UTI under 10 years and between 51-90 years of age and female were more affected in 10 to 50 years and over 90 years of age group. E. coli was the most prevalent (83.9%) isolate followed by Klebsiella spp. (6.7%), Staphylococcus aureus (2.6%), Pseudomonas spp. (2.2%), Enterococcus spp. (2.0%) and Proteus spp. (1.1%). The most predominant organism Acinetobacter spp. (100%) were found sensitive to Gentamicin in both male and female patients and Enterococcus spp. in male (62.5%) and female (58.8%) were found resistant.  Around 37.4% male and 32.5% female were found resistant to E.coli. Keywords: Gentamicin, Aminoglycosides, UTI, Resistance, Uropathogen. DOI: 10.7176/JHMN/67-08 Publication date:October 31st 201

Susceptibility to Vibrio cholerae Infection in a Cohort of Household Contacts of Patients with Cholera in Bangladesh

Vibrio cholerae is the bacterium that causes cholera, a severe form of diarrhea that leads to rapid and potentially fatal dehydration when the infection is not treated promptly. Cholera remains an important cause of diarrhea globally, and V. cholerae continues to cause major epidemics in the most vulnerable populations. Although there have been recent discoveries about how the bacterium adapts to the human intestine and causes diarrhea, there is little understanding of why some people are protected from infection with V. cholerae. This article describes several factors that are associated with the risk of developing V. cholerae infection among people living in the same household with a patient with severe cholera who are at high risk of contracting the infection. One of the findings is that IgA antibodies, a type of antibody associated with immunity at mucosal surfaces such as the intestine, that target several components of the bacteria are associated with immunity to V. cholerae infection. This article also describes genetic and nutritional factors that additionally influence susceptibility to V. cholerae infection

Global, regional, and national burden of meningitis and its aetiologies, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: Although meningitis is largely preventable, it still causes hundreds of thousands of deaths globally each year. WHO set ambitious goals to reduce meningitis cases by 2030, and assessing trends in the global meningitis burden can help track progress and identify gaps in achieving these goals. Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we aimed to assess incident cases and deaths due to acute infectious meningitis by aetiology and age from 1990 to 2019, for 204 countries and territories. Methods: We modelled meningitis mortality using vital registration, verbal autopsy, sample-based vital registration, and mortality surveillance data. Meningitis morbidity was modelled with a Bayesian compartmental model, using data from the published literature identified by a systematic review, as well as surveillance data, inpatient hospital admissions, health insurance claims, and cause-specific meningitis mortality estimates. For aetiology estimation, data from multiple causes of death, vital registration, hospital discharge, microbial laboratory, and literature studies were analysed by use of a network analysis model to estimate the proportion of meningitis deaths and cases attributable to the following aetiologies: Neisseria meningitidis, Streptococcus pneumoniae, Haemophilus influenzae, group B Streptococcus, Escherichia coli, Klebsiella pneumoniae, Listeria monocytogenes, Staphylococcus aureus, viruses, and a residual other pathogen category. Findings: In 2019, there were an estimated 236 000 deaths (95% uncertainty interval [UI] 204 000–277 000) and 2·51 million (2·11–2·99) incident cases due to meningitis globally. The burden was greatest in children younger than 5 years, with 112 000 deaths (87 400–145 000) and 1·28 million incident cases (0·947–1·71) in 2019. Age-standardised mortality rates decreased from 7·5 (6·6–8·4) per 100 000 population in 1990 to 3·3 (2·8–3·9) per 100 000 population in 2019. The highest proportion of total all-age meningitis deaths in 2019 was attributable to S pneumoniae (18·1% [17·1–19·2]), followed by N meningitidis (13·6% [12·7–14·4]) and K pneumoniae (12·2% [10·2–14·3]). Between 1990 and 2019, H influenzae showed the largest reduction in the number of deaths among children younger than 5 years (76·5% [69·5–81·8]), followed by N meningitidis (72·3% [64·4–78·5]) and viruses (58·2% [47·1–67·3]). Interpretation: Substantial progress has been made in reducing meningitis mortality over the past three decades. However, more meningitis-related deaths might be prevented by quickly scaling up immunisation and expanding access to health services. Further reduction in the global meningitis burden should be possible through low-cost multivalent vaccines, increased access to accurate and rapid diagnostic assays, enhanced surveillance, and early treatment. Funding: Bill & Melinda Gates Foundation

Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality. Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children <18 years who were newly diagnosed with or undergoing active treatment for acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, retinoblastoma, Wilms tumour, glioma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, medulloblastoma and neuroblastoma. Of 2327 cases, 2118 patients were included in the study. The primary outcome measure was all-cause mortality at 30 days, 90 days and 12 months. Results All-cause mortality was 3.4% (n=71/2084) at 30-day follow-up, 5.7% (n=113/1969) at 90-day follow-up and 13.0% (n=206/1581) at 12-month follow-up. The median time from diagnosis to multidisciplinary team (MDT) plan was longest in low-income countries (7 days, IQR 3-11). Multivariable analysis revealed several factors associated with 12-month mortality, including low-income (OR 6.99 (95% CI 2.49 to 19.68); p<0.001), lower middle income (OR 3.32 (95% CI 1.96 to 5.61); p<0.001) and upper middle income (OR 3.49 (95% CI 2.02 to 6.03); p<0.001) country status and chemotherapy (OR 0.55 (95% CI 0.36 to 0.86); p=0.008) and immunotherapy (OR 0.27 (95% CI 0.08 to 0.91); p=0.035) within 30 days from MDT plan. Multivariable analysis revealed laboratory-confirmed SARS-CoV-2 infection (OR 5.33 (95% CI 1.19 to 23.84); p=0.029) was associated with 30-day mortality. Conclusions Children with cancer are more likely to die within 30 days if infected with SARS-CoV-2. However, timely treatment reduced odds of death. This report provides crucial information to balance the benefits of providing anticancer therapy against the risks of SARS-CoV-2 infection in children with cancer