GAECH: Genetic Algorithm Based Energy Efficient Clustering Hierarchy in Wireless Sensor Networks

Clustering the Wireless Sensor Networks (WSNs) is the major issue which determines the lifetime of the network. The parameters chosen for clustering should be appropriate to form the clusters according to the need of the applications. Some of the well-known clustering techniques in WSN are designed only to reduce overall energy consumption in the network and increase the network lifetime. These algorithms achieve increased lifetime, but at the cost of overloading individual sensor nodes. Load balancing among the nodes in the network is also equally important in achieving increased lifetime. First Node Die (FND), Half Node Die (HND), and Last Node Die (LND) are the different metrics for analysing lifetime of the network. In this paper, a new clustering algorithm, Genetic Algorithm based Energy efficient Clustering Hierarchy (GAECH) algorithm, is proposed to increase FND, HND, and LND with a novel fitness function. The fitness function in GAECH forms well-balanced clusters considering the core parameters of a cluster, which again increases both the stability period and lifetime of the network. The experimental results also clearly indicate better performance of GAECH over other algorithms in all the necessary aspects

Screening trials of spinal cord stimulation for neuropathic pain in England—a budget impact analysis

Screening trials of spinal cord stimulation (SCS) prior to full implantation of a device are recommended by expert guidelines and international regulators. The current study sought to estimate the budget impact of a screening trial of SCS and the costs or savings of discontinuing the use of a screening trial. A budget impact analysis was performed considering a study population that reflects the size and characteristics of a patient population with neuropathic pain in England eligible for SCS. The perspective adopted was that of the NHS with a 5-year time horizon. The base case analysis indicate that a no screening trial strategy would result in cost-savings to the NHS England of £400,000–£500,000 per year. Sensitivity analyses were conducted to evaluate different scenarios. If ≥5% of the eligible neuropathic pain population received a SCS device, cost-savings would be >£2.5 million/year. In contrast, at the lowest assumed cost of a screening trial (£1,950/patient), a screening trial prior to SCS implantation would be cost-saving. The proportion of patients having an unsuccessful screening trial would have to be ≥14.4% for current practice of a screening trial to be cost-saving. The findings from this budget impact analysis support the results of a recent UK multicenter randomized controlled trial (TRIAL-STIM) of a policy for the discontinuation of compulsory SCS screening trials, namely that such a policy would result in considerable cost-savings to healthcare systems

Appropriate referral and selection of patients with chronic pain for spinal cord stimulation: European consensus recommendations and e-health tool

Background: Spinal cord stimulation (SCS) is an established treatment for chronic neuropathic, neuropathic-like and ischaemic pain. However, the heterogeneity of patients in daily clinical practice makes it often challenging to determine which patients are eligible for this treatment, resulting in undesirable practice variations. This study aimed to establish patient-specific recommendations for referral and selection of SCS in chronic pain. Methods: A multidisciplinary European panel used the RAND/UCLA Appropriateness Method (RUAM) to assess the appropriateness of (referral for) SCS for 386 clinical scenarios in four pain areas: chronic low back pain and/or leg pain, complex regional pain syndrome, neuropathic pain syndromes and ischaemic pain syndromes. In addition, the panel identified a set of psychosocial factors that are relevant to the decision for SCS treatment. Results: Appropriateness of SCS was strongly determined by the neuropathic or neuropathic-like pain component, location and spread of pain, anatomic abnormalities and previous response to therapies targeting pain processing (e.g. nerve block). Psychosocial factors considered relevant for SCS selection were as follows: lack of engagement, dysfunctional coping, unrealistic expectations, inadequate daily activity level, problematic social support, secondary gain, psychological distress and unwillingness to reduce high-dose opioids. An educational e-health tool was developed that combines clinical and psychosocial factors into an advice on referral/selection for SCS. Conclusions: The RUAM was useful to establish a consensus on patient-specific criteria for referral/selection for SCS in chronic pain. The e-health tool may help physicians learn to apply an integrated approach of clinical and psychosocial factors. Significance: Determining the eligibility of SCS in patients with chronic pain requires careful consideration of a variety of clinical and psychosocial factors. Using a systematic approach to combine evidence from clinical studies and expert opinion, a multidisciplinary European expert panel developed detailed recommendations to support appropriate referral and selection for SCS in chronic pain. These recommendations are available as an educational e-health tool (https://www.scstool.org/)

GAECH: Genetic Algorithm Based Energy Efficient Clustering Hierarchy in Wireless Sensor Networks

Clustering the Wireless Sensor Networks (WSNs) is the major issue which determines the lifetime of the network. The parameters chosen for clustering should be appropriate to form the clusters according to the need of the applications. Some of the well-known clustering techniques in WSN are designed only to reduce overall energy consumption in the network and increase the network lifetime. These algorithms achieve increased lifetime, but at the cost of overloading individual sensor nodes. Load balancing among the nodes in the network is also equally important in achieving increased lifetime. First Node Die (FND), Half Node Die (HND), and Last Node Die (LND) are the different metrics for analysing lifetime of the network. In this paper, a new clustering algorithm, Genetic Algorithm based Energy efficient Clustering Hierarchy (GAECH) algorithm, is proposed to increase FND, HND, and LND with a novel fitness function. The fitness function in GAECH forms well-balanced clusters considering the core parameters of a cluster, which again increases both the stability period and lifetime of the network. The experimental results also clearly indicate better performance of GAECH over other algorithms in all the necessary aspects

Neuropathic pain questionnaires for back pain, what do we know?

Introduction Low back pain is a global public health concern, with an estimated lifetime prevalence of 84%. Axial low back pain refers to pain confined to an area in the low back and is different to radicular pain which radiates to extremities. Axial low back pain has traditionally been considered as nociceptive. However, research suggests it may have neuropathic components. Neuropathic axial low back pain is an unresolved, hotly contested topic due to controversies surrounding its aetiology, diagnosis, clinical course, prognosis and treatment options. Purpose The reference standard for diagnosing neuropathic pain is by medical history and clinical assessment (i.e., sensory testing), with optional neuropathic screening tools and selective, further diagnostic tests when clinically needed. Neuropathic screening tools are not always specific for neuropathic radiating low back pain, let alone neuropathic axial low back pain. Additionally, not all have been validated for the English language (e.g., PainDETECT). Research also suggests the percentage of patients identified as having neuropathic radiating low back pain may be dependent on the combination of reference standards used. Implications There is a need for research that works towards improving understanding of neuropathic axial low back pain and developing a standardised, validated and reliable system for assessing and identifying this condition. This body of research will promote earlier stratification and more rapid referral for appropriate treatment, and improve awareness, assessment and visibility of this condition amongst healthcare practitioners and in healthcare settings. This will lead to transformations in Pathways and health guidelines, ultimately improving patient outcomes

A Feasibility Study Exploring Measures of Autonomic Function in Patients With Failed Back Surgery Syndrome Undergoing Spinal Cord Stimulation

Objectives Failed back surgery syndrome (FBSS) is associated with impaired autonomic tone, characterized by sympathetic prevalence and vagal withdrawal. Although spinal cord stimulation (SCS) alleviates pain in FBSS, there is limited research investigating how SCS affects measures of autonomic function. This was a prospective, open-label, feasibility study exploring measures of autonomic function in patients with FBSS receiving SCS therapy. Materials and Methods A total of 14 patients with FBSS were recruited for baseline measurements and underwent a trial of 10-kHz SCS. There were three failed trials, resulting in the remaining 11 participants receiving a fully implanted 10-kHz SCS system. One participant requested an explant, resulting in ten participants completing both baseline and follow-up (three to six months after SCS implant) measurements. Autonomic function was assessed using time- and frequency-domain heart rate variability (HRV), baroreceptor reflex sensitivity (BRS), and muscle sympathetic nerve activity (MSNA) using microneurography. Because this was a feasibility study, most of the analysis was descriptive. However, paired t-tests and Wilcoxon signed-rank tests tested for differences between baseline and follow-up. Results In the whole (N = 14) and final (N = 10) samples, there was between-participant variation in baseline and follow-up measures. This, combined with a small sample, likely contributed to finding no statistically significant differences in any of the measures between baseline and follow-up. However, plotting baseline and follow-up scores for individual participants revealed that those who showed increases in MSNA frequency, square root of the mean of the squared differences between adjacent RR intervals (RMSSD), percentage of the number of RR intervals >50 ms (pRR50), total power, and up BRS between baseline and follow-up had distinct clustering of baseline values compared with those who showed decreases in these measures. Conclusions Findings from this feasibility study will aid with informing hypotheses for future research. A key aspect that should be considered in future research concerns exploring the role of baseline measures of autonomic function in influencing change in autonomic function with SCS therapy

Indexing Scheme and Similarity Measures for Macromolecular Sequences

Nucleotide composition and distribution along a DNA sequence is known to play a vital role in the determination of gene functions. Protein coding regions, regulatory sequences, and other functional regions are determined generally by homology studies with comparable genes from other species or specific experimental verification. With the rapid and explosive increase in sequence information, new computational techniques for rapid determination of such information and comparative studies of different genes are becoming necessary which ideally should encompass not only DNA sequences but other macromolecular sequences as wel