A comparitive study on handover probability analysis for future HetNets

The need of wireless services increasing day by day due to the advancements in the field of wireless technology towards 5G for instant transferring the mails, messages and video calling without any interruption. In LTE and 5G wireless networks, major task is to provide seamless connection anywhere, anytime when the user may roam among Heterogeneous Wireless Networks (HetNets). To achieve proper mobility management among HetNets, handoff or hadover is required. Handover Probability is one of the metric to estimate the handover performance, which is a probability of Mobile Node to handover the present connection from the current base station to another base station or enode B. In this paper, handoff probability analysis is done for   multiple HetNets based on Handover Algorithm. To estimate this algorithm, bandwidth is considered as one of the key parameter. A comparative analysis of handover probability for two, three, four and five HetNets has been performed. The results can demonstrate that the variation of handover probability with respect to traffic load, threshold and bandwidth. It is observed that, as the number of wireless networks increases handover probability slightly increases with traffic load. These results are more significant to estimate further wrong decision handovers based on that Quality of Service (QoS) is evaluated in practical HetNets such as integration of LTE, Wi-Fi and WiMAX etc.

Proton magnetic resonance spectroscopy in multiple sclerosis.

Proton magnetic resonance spectroscopy ((1)H-MRS) provides tissue metabolic information in vivo. This article reviews the role of MRS-determined metabolic alterations in lesions, normal-appearing white matter, gray matter, and spinal cord in advancing our knowledge of pathologic changes in multiple sclerosis (MS). In addition, the role of MRS in objectively evaluating therapeutic efficacy is reviewed. This potential metabolic information makes MRS a unique tool to follow MS disease evolution, understand its pathogenesis, evaluate the disease severity, establish a prognosis, and objectively evaluate the efficacy of therapeutic interventions

Generalized fuzzy clustering for segmentation of multi-spectral magnetic resonance images.

An integrated approach for multi-spectral segmentation of MR images is presented. This method is based on the fuzzy c-means (FCM) and includes bias field correction and contextual constraints over spatial intensity distribution and accounts for the non-spherical cluster\u27s shape in the feature space. The bias field is modeled as a linear combination of smooth polynomial basis functions for fast computation in the clustering iterations. Regularization terms for the neighborhood continuity of intensity are added into the FCM cost functions. To reduce the computational complexity, the contextual regularizations are separated from the clustering iterations. Since the feature space is not isotropic, distance measure adopted in Gustafson-Kessel (G-K) algorithm is used instead of the Euclidean distance, to account for the non-spherical shape of the clusters in the feature space. These algorithms are quantitatively evaluated on MR brain images using the similarity measures

Knowledge Acquisition by Networks of Interacting Agents in the Presence of Observation Errors

In this work we investigate knowledge acquisition as performed by multiple agents interacting as they infer, under the presence of observation errors, respective models of a complex system. We focus the specific case in which, at each time step, each agent takes into account its current observation as well as the average of the models of its neighbors. The agents are connected by a network of interaction of Erd\H{o}s-Renyi or Barabasi-Albert type. First we investigate situations in which one of the agents has a different probability of observation error (higher or lower). It is shown that the influence of this special agent over the quality of the models inferred by the rest of the network can be substantial, varying linearly with the respective degree of the agent with different estimation error. In case the degree of this agent is taken as a respective fitness parameter, the effect of the different estimation error is even more pronounced, becoming superlinear. To complement our analysis, we provide the analytical solution of the overall behavior of the system. We also investigate the knowledge acquisition dynamic when the agents are grouped into communities. We verify that the inclusion of edges between agents (within a community) having higher probability of observation error promotes the loss of quality in the estimation of the agents in the other communities.Comment: 10 pages, 7 figures. A working manuscrip

Volume and shape in feature space on adaptive FCM in MRI segmentation.

Intensity non-uniformity (bias field) correction, contextual constraints over spatial intensity distribution and non-spherical cluster\u27s shape in the feature space are incorporated into the fuzzy c-means (FCM) for segmentation of three-dimensional multi-spectral MR images. The bias field is modeled by a linear combination of smooth polynomial basis functions for fast computation in the clustering iterations. Regularization terms for the neighborhood continuity of either intensity or membership are added into the FCM cost functions. Since the feature space is not isotropic, distance measures, other than the Euclidean distance, are used to account for the shape and volumetric effects of clusters in the feature space. The performance of segmentation is improved by combining the adaptive FCM scheme with the criteria used in Gustafson-Kessel (G-K) and Gath-Geva (G-G) algorithms through the inclusion of the cluster scatter measure. The performance of this integrated approach is quantitatively evaluated on normal MR brain images using the similarity measures. The improvement in the quality of segmentation obtained with our method is also demonstrated by comparing our results with those produced by FSL (FMRIB Software Library), a software package that is commonly used for tissue classification

Abstract 219: Use of Machine Learning Models to Identify Atherosclerotic Cardiovascular Disease Patients at Very High Risk for Future Events in a Multi-state Health Care System

Background: In the 2018 AHA/ACC Blood Cholesterol Guideline, it is recommended that ASCVD patients be classified as very high-risk (VHR) vs not-VHR (NVHR) to guide treatment decisions. This has important implications for ezetimibe and PCSK9 inhibitor eligibility. We aimed to develop a tool that could assist in more easily identifying VHR patients based on machine learning (ML) techniques. This approach offers a powerful, assumption-free alternative to conventional methods, such as logistic regression, to identify potential interactions among risk factors while incorporating the hierarchy of interaction among variables. Method: We used EHR-derived ICD-10 codes to identify patients within our health system with ASCVD. VHR was defined by ≥2 major ASCVD events (ACS ≤12 months, history of MI \u3e12 months, ischemic stroke, or symptomatic PAD) or 1 major ASCVD event and ≥2 high-risk conditions (age ≥65, diabetes, hypertension, smoking, heterozygous familial hypercholesterolemia, CKD, CHF, persistently elevated LDL-C ≥100 mg/dl, or prior CABG/PCI). Patients not meeting these criteria were classified as NVHR. We randomly assigned patients into a training set and a testing set. Classification and regression tree (CART) modeling was performed on the training set and validated on the testing set. The results were compared with a random forest model. Variables in both models included age, sex, race, ethnicity, and each of the VHR criteria above. The primary outcome for both models was VHR classification. Performance of the two models were compared using area under the curve (AUC). Result: A total of 180,669 ASCVD patients were identified in 2018: 104,123 (58%) were VHR and 76,546 (42%) were NVHR. Mean age and sex were 73.1±11.9 years, 55% male and 70.1±13.4 years, 54% male for the VHR and NVHR groups, respectively. Half the population was randomly selected as the training dataset (n=90,334) and the other half was used as the testing dataset (n=90,335). Both CART and random forest models identified recent ACS, ischemic stroke, hypertension, PAD, and history of MI as the top five predictors of VHR status. Ninety-six percent of patients with recent ACS were classified as VHR. Among patients with no recent ACS, 95% were classified as VHR if they had a stroke and hypertension. Among patients with no ACS or stroke, 89% were classified as VHR if they had PAD. Finally, among patients with no ACS, stroke or PAD, 90% were classified as VHR if they had a history of MI. The misclassification rate of the CART model on the testing set was 4.3%. The AUC for the CART and random forest models was 0.949 and 0.968, respectively. Conclusion: Both ML methods were highly predictive of VHR status among those with ASCVD. Use of this approach affords a simplified means to drive clinical decision making at the point of care

Oxidative and pro-inflammatory impact of regular and denicotinized cigarettes on blood brain barrier endothelial cells: is smoking reduced or nicotine-free products really safe?

Background: Both active and passive tobacco smoke (TS) potentially impair the vascular endothelial function in a causative and dose-dependent manner, largely related to the content of reactive oxygen species (ROS), nicotine, and pro-inflammatory activity. Together these factors can compromise the restrictive properties of the blood–brain barrier (BBB) and trigger the pathogenesis/progression of several neurological disorders including silent cerebral infarction, stroke, multiple sclerosis and Alzheimer’s disease. Based on these premises, we analyzed and assessed the toxic impact of smoke extract from a range of tobacco products (with varying levels of nicotine) on brain microvascular endothelial cell line (hCMEC/D3), a well characterized human BBB model. Results: Initial profiling of TS showed a significant release of reactive oxygen (ROS) and reactive nitrogen species (RNS) in full flavor, nicotine-free (NF, “reduced-exposure” brand) and ultralow nicotine products. This release correlated with increased oxidative cell damage. In parallel, membrane expression of endothelial tight junction proteins ZO-1 and occludin were significantly down-regulated suggesting the impairment of barrier function. Expression of VE-cadherin and claudin-5 were also increased by the ultralow or nicotine free tobacco smoke extract. TS extract from these cigarettes also induced an inflammatory response in BBB ECs as demonstrated by increased IL-6 and MMP-2 levels and up-regulation of vascular adhesion molecules, such as VCAM-1 and PECAM-1. Conclusions: In summary, our results indicate that NF and ultralow nicotine cigarettes are potentially more harmful to the BBB endothelium than regular tobacco products. In addition, this study demonstrates that the TS-induced toxicity at BBB ECs is strongly correlated to the TAR and NO levels in the cigarettes rather than the nicotine conten

Benign cervical multi-nodular goiter presenting with acute airway obstruction: a case report

<p>Abstract</p> <p>Introduction</p> <p>Benign cervical goiters rarely cause acute airway obstruction.</p> <p>Case presentation</p> <p>We report the case of a 64-year-old woman of African descent who presented with acute shortness of breath. She required immediate intubation and later a total thyroidectomy for a benign cervical multi-nodular goiter with no retrosternal tracheal compression.</p> <p>Conclusion</p> <p>Benign multi-nodular goiters are commonly left untreated once euthyroid. Peak inspiratory flow rates should be measured via spirometry in all goiters to assess the degree of tracheal compression. Once tracheal compression is identified, an elective total thyroidectomy should be performed to prevent morbidity and mortality from acute airway obstruction.</p

Ten-year outcomes after off-pump versus on-pump coronary artery bypass grafting:Insights from the Arterial Revascularization Trial

Objective We performed a post hoc analysis of the Arterial Revascularization Trial to compare 10-year outcomes after off-pump versus on-pump surgery. Methods Among 3102 patients enrolled, 1252 (40% of total) and 1699 patients received off-pump and on-pump surgery (151 patients were excluded because of other reasons); 2792 patients (95%) completed 10-year follow-up. Propensity matching and mixed-effect Cox model were used to compare long-term outcomes. Interaction term analysis was used to determine whether bilateral internal thoracic artery grafting was a significant effect modifier. Results One thousand seventy-eight matched pairs were selected for comparison. A total of 27 patients (2.5%) in the off-pump group required conversion to on-pump surgery. The off-pump and on-pump groups received a similar number of grafts (3.2 ± 0.89 vs 3.1 ± 0.8; P = .88). At 10 years, when compared with on-pump, there was no significant difference in death (adjusted hazard ratio for off-pump, 1.1; 95% confidence interval, 0.84-1.4; P = .54) or the composite of death, myocardial infarction, stroke, and repeat revascularization (adjusted hazard ratio, 0.92; 95% confidence interval, 0.72-1.2; P = .47). However, off-pump surgery performed by low volume off-pump surgeons was associated with a significantly lower number of grafts, increased conversion rates, and increased cardiovascular death (hazard ratio, 2.39; 95% confidence interval, 1.28-4.47; P = .006) when compared with on-pump surgery performed by on–pump-only surgeons. Conclusions The findings showed that in the Arterial Revascularization Trial, off-pump and on-pump techniques achieved comparable long-term outcomes. However, when off-pump surgery was performed by low-volume surgeons, it was associated with a lower number of grafts, increased conversion, and a higher risk of cardiovascular death.</p

Age‐related changes in cerebellar and hypothalamic function accompany non‐microglial immune gene expression, altered synapse organization, and excitatory amino acid neurotransmission deficits

We describe age-related molecular and neuronal changes that disrupt mobility or energy balance based on brain region and genetic background. Compared to young mice, aged C57BL/6 mice exhibit marked locomotor (but not energy balance) impairments. In contrast, aged BALB mice exhibit marked energy balance (but not locomotor) impairments. Age-related changes in cerebellar or hypothalamic gene expression accompany these phenotypes. Aging evokes upregulation of immune pattern recognition receptors and cell adhesion molecules. However, these changes do not localize to microglia, the major CNS immunocyte. Consistent with a neuronal role, there is a marked age-related increase in excitatory synapses over the cerebellum and hypothalamus. Functional imaging of these regions is consistent with age-related synaptic impairments. These studies suggest that aging reactivates a developmental program employed during embryogenesis where immune molecules guide synapse formation and pruning. Renewed activity in this program may disrupt excitatory neurotransmission, causing significant behavioral deficits