Time-Efficient resource allocation algorithm over HSDPA in femtocell networks

This paper presents a time-efficient optimal resource allocation algorithm aiming to maximize the system throughput of the single-user High Speed Downlink Packet Access (HSDPA) deployed in femtocell base station. The system throughput maximization with constrained total power is rst formulated as a constrained integer programming problem. We rst prove that a two-group bit and energy allocation provides the global optimum solution in the system without multipath. We then focus on the use of the two-group allocation method over frequency selective channels. A pre-processing method was used to systematically cluster and remove channels to stop using energies over severely degraded channels with the two-group allocation approach. This improves the system throughput whilst greatly reducing the computation complexity. The proposed twogroup approach with channel removal is suitable for femtocell base station with limited signal processing capability.Accepted versio

Rate Multiplication and Two-group Resource Allocation in Multi-code CDMA Networks

Accepted versio

Evaluation of two interaction techniques for visualization of dynamic graphs

Several techniques for visualization of dynamic graphs are based on different spatial arrangements of a temporal sequence of node-link diagrams. Many studies in the literature have investigated the importance of maintaining the user's mental map across this temporal sequence, but usually each layout is considered as a static graph drawing and the effect of user interaction is disregarded. We conducted a task-based controlled experiment to assess the effectiveness of two basic interaction techniques: the adjustment of the layout stability and the highlighting of adjacent nodes and edges. We found that generally both interaction techniques increase accuracy, sometimes at the cost of longer completion times, and that the highlighting outclasses the stability adjustment for many tasks except the most complex ones.Comment: Appears in the Proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016

Declining Burden of Malaria Over two Decades in a Rural Community of Muheza District, North-Eastern Tanzania.

The recently reported declining burden of malaria in some African countries has been attributed to scaling-up of different interventions although in some areas, these changes started before implementation of major interventions. This study assessed the long-term trends of malaria burden for 20 years (1992--2012) in Magoda and for 15 years in Mpapayu village of Muheza district, north-eastern Tanzania, in relation to different interventions as well as changing national malaria control policies.\ud Repeated cross-sectional surveys recruited individuals aged 0 -- 19 years from the two villages whereby blood smears were collected for detection of malaria parasites by microscopy. Prevalence of Plasmodium falciparum infections and other indices of malaria burden (prevalence of anaemia, splenomegaly and gametocytes) were compared across the years and between the study villages. Major interventions deployed including mobile clinic, bed nets and other research activities, and changes in national malaria control policies were also marked. In Magoda, the prevalence of P. falciparum infections initially decreased between 1992 and 1996 (from 83.5 to 62.0%), stabilized between 1996 and 1997, and further declined to 34.4% in 2004. A temporary increase between 2004 and 2008 was followed by a progressive decline to 7.2% in 2012, which is more than 10-fold decrease since 1992. In Mpapayu (from 1998), the highest prevalence was 81.5% in 1999 and it decreased to 25% in 2004. After a slight increase in 2008, a steady decline followed, reaching <5% from 2011 onwards. Bed net usage was high in both villages from 1999 to 2004 (>=88%) but it decreased between 2008 and 2012 (range, 28% - 68%). After adjusting for the effects of bed nets, age, fever and year of study, the risk of P. falciparum infections decreased significantly by >=97% in both villages between 1999 and 2012 (p < 0.001). The prevalence of splenomegaly (>40% to <1%) and gametocytes (23% to <1%) also decreased in both villages.Discussion and conclusionsA remarkable decline in the burden of malaria occurred between 1992 and 2012 and the initial decline (1992 -- 2004) was most likely due to deployment of interventions, such as bed nets, and better services through research activities. Apart from changes of drug policies, the steady decline observed from 2008 occurred when bed net coverage was low suggesting that other factors contributed to the most recent pattern. These results suggest that continued monitoring is required to determine causes of the changing malaria epidemiology and also to monitor the progress towards maintaining low malaria transmission and reaching related millennium development goals

Comparability of Results from Pair and Classical Model Formulations for Different Sexually Transmitted Infections

The “classical model” for sexually transmitted infections treats partnerships as instantaneous events summarized by partner change rates, while individual-based and pair models explicitly account for time within partnerships and gaps between partnerships. We compared predictions from the classical and pair models over a range of partnership and gap combinations. While the former predicted similar or marginally higher prevalence at the shortest partnership lengths, the latter predicted self-sustaining transmission for gonorrhoea (GC) and Chlamydia (CT) over much broader partnership and gap combinations. Predictions on the critical level of condom use (Cc) required to prevent transmission also differed substantially when using the same parameters. When calibrated to give the same disease prevalence as the pair model by adjusting the infectious duration for GC and CT, and by adjusting transmission probabilities for HIV, the classical model then predicted much higher Cc values for GC and CT, while Cc predictions for HIV were fairly close. In conclusion, the two approaches give different predictions over potentially important combinations of partnership and gap lengths. Assuming that it is more correct to explicitly model partnerships and gaps, then pair or individual-based models may be needed for GC and CT since model calibration does not resolve the differences

Vitamin B₁₂ and folate decrease inflammation and fibrosis in NASH by preventing syntaxin 17 homocysteinylation

Background & Aims Several recent clinical studies have shown that serum homocysteine (Hcy) levels are positively correlated, while vitamin B12 (B12) and folate levels are negative correlated, with non-alcoholic steatohepatitis (NASH) severity. However, it is not known whether hyperhomocysteinemia (HHcy) plays a pathogenic role in NASH. Methods We examined the effects of HHcy on NASH progression, metabolism, and autophagy in dietary and genetic mouse models, patients, and primates. We employed vitamin B12 (B12) and folate (Fol) to reverse NASH features in mice and cell culture. Results Serum Hcy correlated with hepatic inflammation and fibrosis in NASH. Elevated hepatic Hcy induced and exacerbated NASH. Gene expression of hepatic Hcy-metabolizing enzymes was downregulated in NASH. Surprisingly, we found increased homocysteinylation (Hcy-lation) and ubiquitination of multiple hepatic proteins in NASH including the key autophagosome/lysosome fusion protein, Syntaxin 17 (Stx17). This protein was Hcy-lated and ubiquitinated, and its degradation led to a block in autophagy. Genetic manipulation of Stx17 revealed its critical role in regulating autophagy, inflammation and fibrosis during HHcy. Remarkably, dietary B12/Fol, which promotes enzymatic conversion of Hcy to methionine, decreased HHcy and hepatic Hcy-lated protein levels, restored Stx17 expression and autophagy, stimulated β -oxidation of fatty acids, and improved hepatic histology in mice with pre-established NASH. Conclusions HHcy plays a key role in the pathogenesis of NASH via Stx17 homocysteinylation. B12/folate also may represent a novel first-line therapy for NASH. Lay summary The incidence of non-alcoholic steatohepatitis, for which there are no approved pharmacological therapies, is increasing, posing a significant healthcare challenge. Herein, based on studies in mice, primates and humans, we found that dietary supplementation with vitamin B12 and folate could have therapeutic potential for the prevention or treatment of non-alcoholic steatohepatitis

Evaluation of metabolic syndrome in adults of Talca city, Chile

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Drug Off-Target Effects Predicted Using Structural Analysis in the Context of a Metabolic Network Model

Recent advances in structural bioinformatics have enabled the prediction of protein-drug off-targets based on their ligand binding sites. Concurrent developments in systems biology allow for prediction of the functional effects of system perturbations using large-scale network models. Integration of these two capabilities provides a framework for evaluating metabolic drug response phenotypes in silico. This combined approach was applied to investigate the hypertensive side effect of the cholesteryl ester transfer protein inhibitor torcetrapib in the context of human renal function. A metabolic kidney model was generated in which to simulate drug treatment. Causal drug off-targets were predicted that have previously been observed to impact renal function in gene-deficient patients and may play a role in the adverse side effects observed in clinical trials. Genetic risk factors for drug treatment were also predicted that correspond to both characterized and unknown renal metabolic disorders as well as cryptic genetic deficiencies that are not expected to exhibit a renal disorder phenotype except under drug treatment. This study represents a novel integration of structural and systems biology and a first step towards computational systems medicine. The methodology introduced herein has important implications for drug development and personalized medicine

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases