State of air quality in and outside of hospital wards in urban centres – A case study in Lahore, Pakistan

Particulate pollution in healthcare facilities is a potential threat to healthcare workers, patients and visitors. A study was carried out to monitor particulate levels in and outside of five wards of Sheikh Zayed Hospital, a tertiary healthcare facility of Lahore. Measurements indicated that the hourly mean concentrations of PM2.5 in a medical, pulmonology (chest), surgical, pediatric and nephrology ward were 78 ± 37, 86 ± 46, 94 ± 48, 169 ± 122 and 488 ± 314 µg m-3 respectively. The outside levels of PM2.5 of the same wards were 69 ± 27, 81 ± 49, 178 ± 85, 282 ± 164 and 421 ± 240 µg m-3. Indoor levels were higher than outdoors in all the wards except surgical and pediatric ward. Such elevated levels of PM can result in aggravation of the poor health status of the patients as well as affecting the hospital staff and visitors

Changes in particulate matter concentrations at different altitudinal levels with environmental dynamics

Ambient air quality is defined not only by the source strength but a variety of meteorological parameters as well. In the current study, ambient concentrations of PM along with temperature and relative humidity levels were monitored at seven different locations of Pakistan. A DustTrak DRX (Model 8533, TSI Inc.) was employed for twenty four hours real time monitoring of particulate matter at the selected sites. A considerable variation was observed in the 24 hour trend of particulate matter (PM) at different locations owing to variation in meteorological conditions due to different altitudes and seasons, and natural and anthropogenic sources in the vicinity. The highest average concentrations of PM2.5 (407 mu g/m(3)) were observed at highest elevation (Makra Peak, Shogran, 3089 m) while lowest averages (102 mu g/m(3)) were obtained at the seaside (Hawks Bay, Karachi, 0 m). On the other hand PMTotal fraction exhibited highest levels at site B (506 mu g/m(3)) and lowest at Site A (121 mu g/m(3)). Correlation factors were determined for PM and meteorological parameters at each location. More research needs to be conducted to have a comprehensive knowledge about the physical parameters controlling particulate dispersal at different altitudes within the country

Machine Learning based Energy Management Model for Smart Grid and Renewable Energy Districts

The combination of renewable energy sources and prosumer-based smart grid is a sustainable solution to cater to the problem of energy demand management. A pressing need is to develop an efficient Energy Management Model (EMM) that integrates renewable energy sources with smart grids. However, the variable scenarios and constraints make this a complex problem. Machine Learning (ML) methods can often model complex and non-linear data better than the statistical models. Therefore, developing an ML algorithm for the EMM is a suitable option as it reduces the complexity of the EMM by developing a single trained model to predict the performance parameters of EMM for multiple scenarios. However, understanding latent correlations and developing trust in highly complex ML models for designing EMM within the stochastic prosumer-based smart grid is still a challenging task. Therefore, this paper integrates ML and Gaussian Process Regression (GPR) in the EMM. At the first stage, an optimization model for Prosumer Energy Surplus (PES), Prosumer Energy Cost (PEC), and Grid Revenue (GR) is formulated to calculate base performance parameters (PES, PEC, and GR) for the training of the ML-based GPR model. In the second stage, stochasticity of renewable energy sources, load, and energy price, same as provided by the Genetic Algorithm (GA) based optimization model for PES, PEC, and GR, and base performance parameters act as input covariates to produce a GPR model that predicts PES, PEC, and GR. Seasonal variations of PES, PEC, and GR are incorporated to remove hitches from seasonal dynamics of prosumers energy generation and prosumers energy consumption. The proposed adaptive Service Level Agreement (SLA) between energy prosumers and the grid benefits both these entities. The results of the proposed model are rigorously compared with conventional optimization (GA and PSO) based EMM to prove the validity of the proposed model

Effects of temperature on thick branes and the fermion (quasi-)localization

Following Campos's work [Phys. Rev. Lett. 88, 141602 (2002)], we investigate the effects of temperature on flat, de Sitter (dS), and anti-de Following Campos's work [Phys. Rev. Lett. \textbf{88}, 141602 (2002)], we investigate the effects of temperature on flat, de Sitter (dS), and anti-de Sitter (AdS) thick branes in five-dimensional (5D) warped spacetime, and on the fermion (quasi-)localization. First, in the case of flat brane, when the critical temperature reaches, the solution of the background scalar field and the warp factor is not unique. So the thickness of the flat thick brane is uncertain at the critical value of the temperature parameter, which is found to be lower than the one in flat 5D spacetime. The mass spectra of the fermion Kaluza-Klein (KK) modes are continuous, and there is a series of fermion resonances. The number and lifetime of the resonances are finite and increase with the temperature parameter, but the mass of the resonances decreases with the temperature parameter. Second, in the case of dS brane, we do not find such a critical value of the temperature parameter. The mass spectra of the fermion KK modes are also continuous, and there is a series of fermion resonances. The effects of temperature on resonance number, lifetime, and mass are the same with the case of flat brane. Last, in the case of AdS brane, {the critical value of the temperature parameter can less or greater than the one in the flat 5D spacetime.} The spectra of fermion KK modes are discrete, and the mass of fermion KK modes does not decrease monotonically with increasing temperature parameter.Comment: 24 pages, 15 figures, published versio

The breadth of primary care: a systematic literature review of its core dimensions

Background: Even though there is general agreement that primary care is the linchpin of effective health care delivery, to date no efforts have been made to systematically review the scientific evidence supporting this supposition. The aim of this study was to examine the breadth of primary care by identifying its core dimensions and to assess the evidence for their interrelations and their relevance to outcomes at (primary) health system level. Methods: A systematic review of the primary care literature was carried out, restricted to English language journals reporting original research or systematic reviews. Studies published between 2003 and July 2008 were searched in MEDLINE, Embase, Cochrane Library, CINAHL, King's Fund Database, IDEAS Database, and EconLit. Results: Eighty-five studies were identified. This review was able to provide insight in the complexity of primary care as a multidimensional system, by identifying ten core dimensions that constitute a primary care system. The structure of a primary care system consists of three dimensions: 1. governance; 2. economic conditions; and 3. workforce development. The primary care process is determined by four dimensions: 4. access; 5. continuity of care; 6. coordination of care; and 7. comprehensiveness of care. The outcome of a primary care system includes three dimensions: 8. quality of care; 9. efficiency care; and 10. equity in health. There is a considerable evidence base showing that primary care contributes through its dimensions to overall health system performance and health. Conclusions: A primary care system can be defined and approached as a multidimensional system contributing to overall health system performance and health

Nonclassical Fields and the Nonlinear Interferometer

We demonstrate several new results for the nonlinear interferometer, which emerge from a formalism which describes in an elegant way the output field of the nonlinear interferometer as two-mode entangled coherent states. We clarify the relationship between squeezing and entangled coherent states, since a weak nonlinear evolution produces a squeezed output, while a strong nonlinear evolution produces a two-mode, two-state entangled coherent state. In between these two extremes exist superpositions of two-mode coherent states manifesting varying degrees of entanglement for arbitrary values of the nonlinearity. The cardinality of the basis set of the entangled coherent states is finite when the ratio $\chi / \pi$ is rational, where $\chi$ is the nonlinear strength. We also show that entangled coherent states can be produced from product coherent states via a nonlinear medium without the need for the interferometric configuration. This provides an important experimental simplification in the process of creating entangled coherent states.Comment: 21 pages, 2 figure

Don't Stop Thinking About Leptoquarks: Constructing New Models

We discuss the general framework for the construction of new models containing a single, fermion number zero scalar leptoquark of mass $\simeq 200-220$ GeV which can both satisfy the D0/CDF search constraints as well as low energy data, and can lead to both neutral and charged current-like final states at HERA. The class of models of this kind necessarily contain new vector-like fermions with masses at the TeV scale which mix with those of the Standard Model after symmetry breaking. In this paper we classify all models of this type and examine their phenomenological implications as well as their potential embedding into SUSY and non-SUSY GUT scenarios. The general coupling parameter space allowed by low energy as well as collider data for these models is described and requires no fine-tuning of the parameters.Comment: Modified text, added table, and updated reference

Transcription profiling reveals potential mechanisms of dysbiosis in the oral microbiome of rhesus macaques with chronic untreated SIV infection.

A majority of individuals infected with human immunodeficiency virus (HIV) have inadequate access to antiretroviral therapy and ultimately develop debilitating oral infections that often correlate with disease progression. Due to the impracticalities of conducting host-microbe systems-based studies in HIV infected patients, we have evaluated the potential of simian immunodeficiency virus (SIV) infected rhesus macaques to serve as a non-human primate model for oral manifestations of HIV disease. We present the first description of the rhesus macaque oral microbiota and show that a mixture of human commensal bacteria and "macaque versions" of human commensals colonize the tongue dorsum and dental plaque. Our findings indicate that SIV infection results in chronic activation of antiviral and inflammatory responses in the tongue mucosa that may collectively lead to repression of epithelial development and impact the microbiome. In addition, we show that dysbiosis of the lingual microbiome in SIV infection is characterized by outgrowth of Gemella morbillorum that may result from impaired macrophage function. Finally, we provide evidence that the increased capacity of opportunistic pathogens (e.g. E. coli) to colonize the microbiome is associated with reduced production of antimicrobial peptides

Clinical-pathological study on β-APP, IL-1β, GFAP, NFL, Spectrin II, 8OHdG, TUNEL, miR-21, miR-16, miR-92 expressions to verify DAI-diagnosis, grade and prognosis

Traumatic brain injury (TBI) is one of the most important death and disability cause, involving substantial costs, also in economic terms, when considering the young age of the involved subject. Aim of this paper is to report a series of patients treated at our institutions, to verify neurological results at six months or survival; in fatal cases we searched for βAPP, GFAP, IL-1β, NFL, Spectrin II, TUNEL and miR-21, miR-16, and miR-92 expressions in brain samples, to verify DAI diagnosis and grade as strong predictor of survival and inflammatory response. Concentrations of 8OHdG as measurement of oxidative stress was performed. Immunoreaction of β-APP, IL-1β, GFAP, NFL, Spectrin II and 8OHdG were significantly increased in the TBI group with respect to control group subjects. Cell apoptosis, measured by TUNEL assay, were significantly higher in the study group than control cases. Results indicated that miR-21, miR-92 and miR-16 have a high predictive power in discriminating trauma brain cases from controls and could represent promising biomarkers as strong predictor of survival, and for the diagnosis of postmortem traumatic brain injury