Investigating IoT Middleware Platforms for Smart Application Development

With the growing number of Internet of Things (IoT) devices, the data generated through these devices is also increasing. By 2030, it is been predicted that the number of IoT devices will exceed the number of human beings on earth. This gives rise to the requirement of middleware platform that can manage IoT devices, intelligently store and process gigantic data generated for building smart applications such as Smart Cities, Smart Healthcare, Smart Industry, and others. At present, market is overwhelming with the number of IoT middleware platforms with specific features. This raises one of the most serious and least discussed challenge for application developer to choose suitable platform for their application development. Across the literature, very little attempt is done in classifying or comparing IoT middleware platforms for the applications. This paper categorizes IoT platforms into four categories namely-publicly traded, open source, developer friendly and end-to-end connectivity. Some of the popular middleware platforms in each category are investigated based on general IoT architecture. Comparison of IoT middleware platforms in each category, based on basic, sensing, communication and application development features is presented. This study can be useful for IoT application developers to select the most appropriate platform according to their application requirement

Are Leaf Traits Suitable for Assessing the Feeding Value of Native Grass Species?

Research on forage feeding value other than in vivo assessment can be roughly divided into three kinds of approach. The first aims to predict feeding value using a set of enzymatic or physical methods. A second approach is based on phenological stages of species. These approaches are mainly used for pure stands of improved grasses or legumes. However, for native grassland, a complex type of vegetation, a third approach, based on botanical records, has been proposed to rank grassland communities for their feeding value. The aim of this work concerns the third approach. We tested whether leaf traits (e.g. specific leaf area (SLA), leaf dry matter content (LDMC) and leaf life span (LLS)), assessed under non-limiting plant growth conditions, ranked the species in the same order as did chemical components and digestibility

Photonics based perfect secrecy cryptography : toward fully classical implementations

Funding: A.D.F. acknowledges support from UK EPSRC (EP/L017008/1).Developing an unbreakable cryptography is a longstanding question and a global challenge in the internet era. Photonics technologies are at the frontline of research, aiming at providing the ultimate system capable of ending the cybercrime industry by changing the way information is treated and protected now and in the long run. Such perspective discusses some of the current challenges as well as opportunities that classical and quantum systems open in the field of cryptography as both a science and an engineering.PostprintPeer reviewe

The Nature and Origin of Mass Spectral Peaks

In Chapter one, a general review of mass spectrometry was made in which the history of mass spectrometry was traced from the discoveries of Goldstein and Wien to J. J. Thomson's first mass spectrograph and Aston's first mass spectrometer. The evolution and improvement in these early instruments was followed by reference to the work of Barber and Stephens, Nier, Herzog and Mattauch for the development of double-focusing instruments. Other types of instruments such as the dynamic instruments, have also been mentioned. Methods of ionisation and systems of sample introduction were described, as were the uses of mass spectrometry in analytical chemistry, both qualitatively and quantitatively, and in other branches of science. Automatic data acquisition, reduction and processing techniques, including precise mass measurement, were mentioned. Several theories useful in the interpretation of mass spectra were considered. The types of ions formed in the mass spectrometer were indicated and particular emphasis was placed on the use of metastable ions as a source of information to the organic mass spectroscopist. In addition, the relevance of thermochemical measurements, isotopic labelling, substituent effects, ion-molecule reactions and chemical ionisation to ion structure determination was discussed. In Chapter two, a new method of precise mass measurement of ions by mass spectrometry was described, and compared with methods used in the past by other workers. These ranged from the classical peak matching technique to the first semiautomatic process developed by Biemann and finally to ether more advanced automatic processes for both electrical and photographic recording, using on or off-line systems. The new mathematical method used, spline-fit interpolation was shown to yield results which were as accurate as the results obtained by the basic automatic method of Biemann; moreover, it had several advantages in its simplicity and applicability to both electrical and photographic recording systems. In Chapter three, the shape of the peaks in a double-focusing mass spectrometer in slow scans was studied. The mathematical treatment and the results showed that the peaks can be considered triangular. The calculation of the areas of the peaks accordingly became an easier task than if they were calculated using the planimeter, even in a digitisation treatment. In Chapter four, a review of ionisation phenomena was made. The definitions of ionisation and appearance potentials were given and methods for their calculation critically reviewed. Ways in which thermochemical data and structural details may be elucidated from these data were described. The ionisation and appearance potentials for the positive ions of methanol, deuterated methanol and ethylene glycol and their fragments were calculated from experimental data acquired by electron-impact on the neutral molecule. Thermochemical data and structural details derived from these observed values were discussed, and a compelling argument leading to the conclusion that the structure of the ion CH3O+ is in fact CH2OH+ was presented

A generator of cauchy-distributed time series with specific Hurst index

A generator of artificial Cauchy-distributed time series is presented. This generator transforms any random time series, e.g., standardized fractional Gaussian noise (FGN), into a Cauchy-distributed series with specific location and scale parameters and correlation structure, determined by the Hurst index. The proposed algorithm consists of an inverse cumulative distribution function (ICDF) transformation, a wavelet-analysis synthesis and, finally, a linear transformation. The resulting Cauchy-distributed series has approximately the desired location and scale parameters and exactly the desired Hurst index. The performance of the proposed generator is evaluated by estimating the location, scale and Hurst parameters from artificial time series and by calculating the mean squared error (MSE) of their cumulative distribution function (CDF). The input location, scale and Hurst index used in the simulations are taken from jitter samples of monitored Voice over Internet Protocol (VoIP) calls, which have been proved to be adequately modeled with these processes under some circumstances

Spatial patterns and urban governance in Kuwait: exploring the links between the physical, the socio-economic and the political

As a city-state, Kuwait represents an instructive case-study to investigate barriers to sustainable urban development. Among the many challenges faced by the country, the spatial configuration of the metropolis – and the various adverse effects that stem from it – is a key area of concern. In this study, we focus on spatial segregation and measure it at the metropolitan and governorate levels to determine just how serious the problem really is. The results confirm the existence of a highly divided society. Without being able to make causality claims (given the limitations in the data), our evidence points to potential drivers of different nature. A key working hypothesis of our investigation was that urban governance arrangements in Kuwait may be an important part of the story behind these spatial patterns. The empirical findings of our analysis of the governance network of spatial planning in Kuwait strongly support this notion and allow us to draw some policy recommendations to break urban Kuwait’s ‘vicious cycle’, where popular aspirations around unsustainable practices send strong signals to the institutions tasked with formulating policy which, once implemented, recreate societal expectations

Prognostic Impact of Admission Blood Glucose for All-Cause Mortality in Patients with Acute Coronary Syndromes: Added Value on Top of GRACE Risk Score

BACKGROUND: Abnormal glucose metabolism is a predictor of worse outcome after acute coronary syndrome (ACS). However, this parameter is not included in risk prediction scores, including GRACE risk score. We sought to evaluate whether the inclusion of blood glucose at admission in a model with GRACE risk score improves risk stratification. METHODS: Study of consecutive patients included in a single centre registry of ACS. Our primary endpoint was the occurrence of all-cause mortality at one-year follow-up. The ability of the two logistic regression models (GRACE risk score alone and in combination with blood glucose) to predict death was analysed. Continuous net reclassification improvement (NRI) and integrated discrimination improvement (IDI), with corresponding 95% confidence intervals (CIs), were also calculated. RESULTS: We included 2099 patients, with a mean age of 64 (SD=13) years, 69% males. In our sample, 55.1% presented with ST-segment elevation ACS and 13.1% in Killip class ≥ 2. Only 25% were known diabetic at admission. In-hospital mortality was 5.8% and 9.7% at one-year follow-up. The best cut-point for blood glucose was 160 mg/dl (sensitivity 62% and specificity 68%), and 35.2% of the patients had increased levels. This group was elderly, had more prevalence of cardiovascular risk factors, worse renal function and GRACE score as well as more frequently Killip class ≥2. Treatment was similar in both groups besides less frequent use of clopidogrel in high glycaemic patients. The hyperglycaemia group had higher one-year mortality (17.2% vs. 5.6%, p<0.001). Moreover, binary blood glucose remained a predictor of death independently of the GRACE risk score and the presence of diabetes (odds ratio (OR) 1.99, 95% CI 1.40-2.84, p<0.001). The inclusion of blood glucose, as a continuous variable, in a logistic regression model with GRACE score, increased the area under the ROC curve from 0.80 to 0.82 (p=0.018) as well as the goodness-of-fit and was associated with an improvement in both the NRI (37%) and the IDI (0.021), suggesting effective reclassification. CONCLUSIONS: A blood glucose level on admission ≥ 160 mg/dl is an independent predictor of mortality in medium-term follow-up. It offers an incremental predictive value when added to the GRACE risk score, although with a modest magnitude of improvement, probably due to the high predictive performance of the GRACE risk score alone.info:eu-repo/semantics/publishedVersio

Is It Possible to Simplify Risk Stratification Scores for Patients with ST-Segment Elevation Myocardial Infarction Undergoing Primary Angioplasty?

INTRODUCTION: There are several risk scores for stratification of patients with ST-segment elevation myocardial infarction (STEMI), the most widely used of which are the TIMI and GRACE scores. However, these are complex and require several variables. The aim of this study was to obtain a reduced model with fewer variables and similar predictive and discriminative ability. METHODS: We studied 607 patients (age 62 years, SD=13; 76% male) who were admitted with STEMI and underwent successful primary angioplasty. Our endpoints were all-cause in-hospital and 30-day mortality. Considering all variables from the TIMI and GRACE risk scores, multivariate logistic regression models were fitted to the data to identify the variables that best predicted death. RESULTS: Compared to the TIMI score, the GRACE score had better predictive and discriminative performance for in-hospital mortality, with similar results for 30-day mortality. After data modeling, the variables with highest predictive ability were age, serum creatinine, heart failure and the occurrence of cardiac arrest. The new predictive model was compared with the GRACE risk score, after internal validation using 10-fold cross validation. A similar discriminative performance was obtained and some improvement was achieved in estimates of probabilities of death (increased for patients who died and decreased for those who did not). CONCLUSION: It is possible to simplify risk stratification scores for STEMI and primary angioplasty using only four variables (age, serum creatinine, heart failure and cardiac arrest). This simplified model maintained a good predictive and discriminative performance for short-term mortality

COVID-19 in relation to hyperglycemia and diabetes mellitus

Coronavirus disease 2019 (COVID-19), triggered by the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), may lead to extrapulmonary manifestations like diabetes mellitus (DM) and hyperglycemia, both predicting a poor prognosis and an increased risk of death. SARS-CoV-2 infects the pancreas through angiotensin-converting enzyme 2 (ACE2), where it is highly expressed compared to other organs, leading to pancreatic damage with subsequent impairment of insulin secretion and development of hyperglycemia even in non-DM patients. Thus, this review aims to provide an overview of the potential link between COVID-19 and hyperglycemia as a risk factor for DM development in relation to DM pharmacotherapy. For that, a systematic search was done in the database of MEDLINE through Scopus, Web of Science, PubMed, Embase, China National Knowledge Infrastructure (CNKI), China Biology Medicine (CBM), and Wanfang Data. Data obtained underline that SARS-CoV-2 infection in DM patients is more severe and associated with poor clinical outcomes due to preexistence of comorbidities and inflammation disorders. SARS-CoV-2 infection impairs glucose homeostasis and metabolism in DM and non-DM patients due to cytokine storm (CS) development, downregulation of ACE2, and direct injury of pancreatic beta-cells. Therefore, the potent anti-inflammatory effect of diabetic pharmacotherapies such as metformin, pioglitazone, sodium-glucose co-transporter-2 inhibitors (SGLT2Is), and dipeptidyl peptidase-4 (DPP4) inhibitors may mitigate COVID-19 severity. In addition, some antidiabetic agents and also insulin may reduce SARS-CoV-2 infectivity and severity through the modulation of the ACE2 receptor expression. The findings presented here illustrate that insulin therapy might seem as more appropriate than other anti-DM pharmacotherapies in the management of COVID-19 patients with DM due to low risk of uncontrolled hyperglycemia and diabetic ketoacidosis (DKA). From these findings, we could not give the final conclusion about the efficacy of diabetic pharmacotherapy in COVID-19; thus, clinical trial and prospective studies are warranted to confirm this finding and concern