Leveraging intelligence from network CDR data for interference aware energy consumption minimization

Cell densification is being perceived as the panacea for the imminent capacity crunch. However, high aggregated energy consumption and increased inter-cell interference (ICI) caused by densification, remain the two long-standing problems. We propose a novel network orchestration solution for simultaneously minimizing energy consumption and ICI in ultra-dense 5G networks. The proposed solution builds on a big data analysis of over 10 million CDRs from a real network that shows there exists strong spatio-temporal predictability in real network traffic patterns. Leveraging this we develop a novel scheme to pro-actively schedule radio resources and small cell sleep cycles yielding substantial energy savings and reduced ICI, without compromising the users QoS. This scheme is derived by formulating a joint Energy Consumption and ICI minimization problem and solving it through a combination of linear binary integer programming, and progressive analysis based heuristic algorithm. Evaluations using: 1) a HetNet deployment designed for Milan city where big data analytics are used on real CDRs data from the Telecom Italia network to model traffic patterns, 2) NS-3 based Monte-Carlo simulations with synthetic Poisson traffic show that, compared to full frequency reuse and always on approach, in best case, proposed scheme can reduce energy consumption in HetNets to 1/8th while providing same or better Qo

How 5G wireless (and concomitant technologies) will revolutionize healthcare?

The need to have equitable access to quality healthcare is enshrined in the United Nations (UN) Sustainable Development Goals (SDGs), which defines the developmental agenda of the UN for the next 15 years. In particular, the third SDG focuses on the need to “ensure healthy lives and promote well-being for all at all ages”. In this paper, we build the case that 5G wireless technology, along with concomitant emerging technologies (such as IoT, big data, artificial intelligence and machine learning), will transform global healthcare systems in the near future. Our optimism around 5G-enabled healthcare stems from a confluence of significant technical pushes that are already at play: apart from the availability of high-throughput low-latency wireless connectivity, other significant factors include the democratization of computing through cloud computing; the democratization of Artificial Intelligence (AI) and cognitive computing (e.g., IBM Watson); and the commoditization of data through crowdsourcing and digital exhaust. These technologies together can finally crack a dysfunctional healthcare system that has largely been impervious to technological innovations. We highlight the persistent deficiencies of the current healthcare system and then demonstrate how the 5G-enabled healthcare revolution can fix these deficiencies. We also highlight open technical research challenges, and potential pitfalls, that may hinder the development of such a 5G-enabled health revolution

User Transmit Power Minimization through Uplink Resource Allocation and User Association in HetNets

The popularity of cellular internet of things (IoT) is increasing day by day and billions of IoT devices will be connected to the internet. Many of these devices have limited battery life with constraints on transmit power. High user power consumption in cellular networks restricts the deployment of many IoT devices in 5G. To enable the inclusion of these devices, 5G should be supplemented with strategies and schemes to reduce user power consumption. Therefore, we present a novel joint uplink user association and resource allocation scheme for minimizing user transmit power while meeting the quality of service. We analyze our scheme for two-tier heterogeneous network (HetNet) and show an average transmit power of -2.8 dBm and 8.2 dBm for our algorithms compared to 20 dBm in state-of-the-art Max reference signal received power (RSRP) and channel individual offset (CIO) based association schemes

Fibroblast growth factor 23 (FGF23) levels, phosphate Intake and its association with Indices of renal handling of phosphate in healthy volunteers

FGF23 is a novel phosphaturic hormone; we aimed to assess the FGF23 levels and its association with dietary phosphate intake and indices of renal handling of phosphate in this study. Prospective study was conducted in which dietary phosphate intake was assessed by food frequency questionnaire (FFQ) along with blood and spot urine samples were collected after overnight fast for determining serum phosphate, FGF23, fractional excretion of phosphate (FePO4 ) and tubular maximum for phosphate (TmP/GFR). FGF23 (C-Term) was measured by a sandwich ELISA. The mean dietary phosphate intake of eighty healthy adults (mean age of 29 ± 5 years) was 1220 ± 426 mg; median FGF23 was 49.9 RU/ml (IQR=33, 76) and mean FePO4 was 7 ± 4.7. Subjects were stratified into two groups according to serum phosphate levels. Significant difference was not found in dietary phosphate intake and FGF23 levels in the two groups. However, TmP/GFR and creatinine were significantly different in the two groups. FePO4 was high in both the groups. Overall a rising pattern of FGF23 levels was seen with increasing serum phosphate levels. Significant positive correlation was found between FGF23 and dietary phosphate (r=0.22, p\u3c0.05) and negative correlation was seen between FGF23 and FePO4 (r=-0.260, p\u3c0.05)

Pattern of drugs of abuse identified in chemical samples

OBJECTIVE: To determine the pattern of drugs of abuse in urine and blood samples processed at referral laboratory in Pakistan so that information on the type of drugs used can be identified and used for ready reference for future strategy. Study Design: Observational study. PLACE AND DURATION OF STUDY: Clinical Laboratory of The Aga Khan University Hospital, Karachi, from July 2006 to March 2008. Methodology: Retrospective review of records were done for the common drugs that are used for screening at the Clinical Laboratory include alcohol, amphetamine, barbiturates, benzodiazepines, cannabinoids, cocaine and opiates. Alcohol was tested in blood and others were identified using urine. Percentages of tests screened positive and negative for individual drugs were computed by using SPSS 16.0. The ratio between male and female users was also established. RESULTS: A total of 17,714 tests were performed for drugs. The mean age of the patients whose samples were processed was 30+/-14.84 years. Majority used benzodiazepines 520/1317 (39.5%) among the samples tested for drug of abuse, followed by cannabinoids 423/5450 (7.8%), alcohol 75/1302 (5.8%), barbiturates 32/1148 (2.8%), opiates 137/5640 (2.4%), cocaine 5/1655 (0.3%) and amphetamine 3/1202 (0.2%). In all, males 15411 (87%) were tested more frequently as compared to females 2303 (13%). CONCLUSION: Males were more frequently tested for drug abuse; however, drug abuse is increasingly seen among females. Benzodiazepines are the most frequently used. The same pattern of drugs abuse existed in different gender and age group. There is a need to explore the pattern and type of drug abuse on national scale

B-type natriuretic peptide versus amino terminal pro-B type natriuretic peptide: selecting the optimal heart failure marker in patients with impaired kidney function

Background: The effect of impaired kidney function on B-type natriuretic peptide (BNP) and N-terminal proBNP (NT-proBNP) is vague. This study was performed to examine the effect of kidney dysfunction on the afore-mentioned markers and determine appropriate cutoffs for systolic heart failure (SHF). Methods: In this cross sectional study adults with estimated glomerular filtration rate (eGFR)/min for ≥3 months were identified in consulting clinics from June 2009 to March 2010. SHF was defined as documented by a cardiologist with ejection fraction of \u3c 40% and assessed by New York Heart Association classification (NYHA). Plasma was assayed for creatinine (Cr), BNP and NT-proBNP. Results: A total of 190 subjects were enrolled in the study, 95 with and 95 without SHF. The mean age of patients was 58 (±15) years, 67.4% being males. Mean BNP levels showed a 2.5 fold and 1.5 fold increase from chronic kidney disease (CKD) stage 3 to stage 5 in patients with and without SHF respectively. NT-proBNP levels in non-heart failure group were 3 fold higher in CKD stage 5 compared to stage 3. Mean NT-proBNP levels were 4 fold higher in CKD stage 5 compared to stage 3 in patients with SHF. Optimal BNP and NT-proBNP cutoffs of SHF diagnosis for the entire CKD group were 300 pg/ml and 4502 pg/ml respectively. Conclusion: BNP and NT-proBNP were elevated in kidney dysfunction even in the absence of SHF; however the magnitude of increase in NT-proBNP was greater than that of BNP. BNP and NT-proBNP can be useful in diagnosing SHF, nonetheless, by using higher cutoffs stratified according to kidney dysfunction. NT-proBNP appears to predict heart failure better than BNP

mHealth based interventions for the assessment and treatment of psychotic disorders: a systematic review

The relative burden of mental health disorders is increasing globally, in terms of prevalence and disability. There is limited data available to guide treatment choices for clinicians in low resourced settings, with mHealth technologies being a potentially beneficial avenue to bridging the large mental health treatment gap globally. The aim of the review was to search the literature systematically for studies of mHealth interventions for psychosis globally, and to examine whether mHealth for psychosis has been investigated. A systematic literature search was completed in Embase, Medline, PsychINFO and Evidence Based Medicine Reviews databases from inception to May 2016. Only studies with a randomised controlled trial design that investigated an mHealth intervention for psychosis were included. A total of 5690 records were identified with 7 studies meeting the inclusion criteria. The majority of included studies, were conducted across Europe and the United Sates with one being conducted in China. The 7 included studies examined different parameters, such as Experiential Sampling Methodology (ESM), medication adherence, cognitive impairment, social functioning and suicidal ideation in veterans with schizophrenia. Considering the increasing access to mobile devices globally, mHealth may potentially increase access to appropriate mental health care. The results of this review show promise in bridging the global mental health treatment gap, by enabling individuals to receive treatment via their mobile phones, particularly for those individuals who live in remote or rural areas, areas of high deprivation and for those from low resourced settings

Application of the Observational Method on Crossrail projects

This is the author accepted manuscript. The final version is available from the Federation of Piling Specialists via http://www.fps.org.uk/fps/news/Crossrail%20Programme%20of%20Proceedings%20FINAL.pdfThis paper describes the use of the Observsational Method (OM) on three Crossrail station excavations. Firstly, at Tottenham Court Road, Western Ticket Hall excavation where a code compliant design was started. By the third excavation stage, it was realised that movements were less than predicted and an OM was introduced. This enabled the lowest level of strutting to be eliminated, leading to savings in both programme and costs. Secondly, at Canary Wharf Crossrail Station, an OM approach was envisaged before the start of construction, but was only designed during the final excavation stage when time was available for back-analysis. A saving in costs and programme was achieved. Thirdly, at Moorgate shaft (part of Liverpool St Station) where construction commenced with a standard codecompliant design. A client-led redesign was carried out after installation of the diaphragm wall with an innovative verification process using a proactive OM approach to enable programme savings. When unusual deflection were observed from the shaft east wall due to structural uncertainties and construction activities, the OM and verification process provided a flexible framework within which to reassess ongoing movements and effects on an adjacent tunnel to ensure construction could proceed safely. The case histories described demonstrate the benefit of adopting the OM for excavations in order to achieve savings in time and cost, and to react to unexpected movements during construction. These case histories fit well within a new framework for OM applications developed as part of the CIRIA C760.ARUP, CSI

Characterization of newly synthesized ZrFe2O5 nanomaterial and investigations of its tremendous photocatalytic properties under visible light irradiation

High functional ZrFe2O5 nanoparticles were synthesized using coprecipitation technique. The chemical composition of nanomaterials was studied by energy-dispersive X-ray (EDX). To observe the morphology, field emission scanning electron microscopy (FE-SEM) was used. X-ray diffraction (XRD) technique was utilized to appraise the structure of the synthesized material. The photocatalytic behavior of ZrFe2O 5 nano-particles was investigated by measuring the degradation rate of toluidine blue O (TBO) dye in aqueous solution in the presence of ZrFe 2O5 nano-particles under visible light irradiation. A steady decrease in absorption peak under visible light irradiation was observed by increasing exposure time. The degradation efficiency was observed as 92% after 140 min of exposure to visible light. Besides, ZrFe2O 5 nanophotocatalyst could be recovered and recycled easily. The rate of TBO and total organic carbon (TOC) removal under visible light irradiation decreased by only 5% and 10%, respectively, after seven cycles of use, demonstrating the high photostability of the synthesized nano-photocatalyst material