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Aims To evaluate the impact of a simplified, rapid cardiovascular magnetic resonance (CMR) protocol embedded in care and supported by a partner education programme on the management of cardiomyopathy (CMP) in low- and middle-income countries (LMICs). Methods and results Rapid CMR focused particularly on CMP was implemented in 11 centres, 7 cities, 5 countries, and 3 continents linked to training courses for local professionals. Patients were followed up for 24 months to assess impact. The rate of subsequent adoption was tracked. Five CMR conferences were delivered (920 attendees—potential referrers, radiographers, reporting cardiologists, or radiologists) and five new centres starting CMR. Six hundred and one patients were scanned. Cardiovascular magnetic resonance indications were 24% non-contrast T2* scans [myocardial iron overload (MIO)] and 72% suspected/known cardiomyopathies (including ischaemic and viability). Ninety-eighty per cent of studies were of diagnostic quality. The average scan time was 22 ± 6 min (contrast) and 12 ± 4 min (non-contrast), a potential cost/throughput reduction of between 30 and 60%. Cardiovascular magnetic resonance findings impacted management in 62%, including a new diagnosis in 22% and MIO detected in 30% of non-contrast scans. Nine centres continued using rapid CMR 2 years later (typically 1–2 days per week, 30 min slots). Conclusions Rapid CMR of diagnostic quality can be delivered using available technology in LMICs. When embedded in care and a training programme, costs are lower, care is improved, and services can be sustained over time.

BACKGROUND:Arrhythmogenic right ventricular cardiomyopathy (ARVC) results in progressive replacement of right ventricular myocardium with fibrofatty tissue. This condition commonly presents with sudden cardiac death, cardiac arrest, or sustained ventricular tachycardia among young adults. Considering the likelihood of sudden incapacitation, a diagnosis of ARVC usually signals the end of a career in aviation. However, the morbidity pattern among those diagnosed later in life may differ as compared to the young.CASE REPORT:A private pilot, in his 60s, applied for renewal of an ICAO Class 2 medical certificate a decade after his previous medical certificate had expired. He declared history of hospitalization due to a heart-related condition. Further information revealed that he had been diagnosed as a case of ARVC and that he had declined to be implanted with an implantable cardioverter-defibrillator. Recent clinical examination and related cardiovascular investigations were normal except echocardiogram findings of left ventricular hypertrophy and left atrial enlargement. The treating cardiologist, in the absence of history of syncope and evidence of right ventricular dysfunction or sustained ventricular tachycardia, considered this condition to be stable with minimal risk of malignant arrhythmia.DISCUSSION:This case report discusses aeromedical decision making in a pilot found to have ARVC late in life. Despite the progressive nature of the condition with its attendant risk of incapacitation, considering the age at diagnosis and absence of any high-risk features of ARVC, the regulator decided to issue the medical certificate with safety pilot restriction to enable this pilot to return to aviation activities.Sharma S.Arrhythmogenic right ventricular cardiomyopathy in an older private pilot. Aerosp Med Hum Perform. 2022; 93(2):111–115.

This work presents a machine learning based method for bi-fidelity modelling. The method, a Knowledge Based Neural Network (KBaNN), performs a local, additive correction to the outputs of a coarse computational model and can be used to emulate either experimental data or the output of a more accurate, but expensive, computational model. An advantage of the method is that it can scale easily with the number of input and output features. This allows bi-fidelity modelling approaches to be applied to a wide variety of problems, for instance in the bi-fidelity modelling of fields. We demonstrate this aspect in this work through an application to Computational Fluid Dynamics, in which local corrections to a velocity field are performed by the KBaNN to account for mesh effects. KBaNNs were trained to make corrections to the free-stream velocity field and the boundary layer. They were trained on a limited data-set consisting of simple two-dimensional flows. The KBaNNs were then tested on a flow over a more complex geometry, a NACA 2412 airfoil. It was demonstrated that the KBaNNs were still able to provide a local correction to the velocity field which improved its accuracy. The ability of the KBaNNs to generalise to flows around new geometries that share similar physics is encouraging. Through knowledge based neural networks it may be possible to develop a system for bi-fidelity, computer based design which uses data from past simulations to inform its predictions.

Purpose: Nonspecific aortoarteritis (NSAA) is a chronic inflammatory vasculitis involving aorta and its branches. We conducted a study prospectively to compare time resolved magnetic resonance angiography (MRA) with diagnostic digital subtraction angiography (DSA) for the vascular assessment in the patients of NSAA. Materials and Methods: Seventeen patients of NSAA were recruited in the study over the period of 3 years. Contrast enhanced MRA using Time-resolved angiography With Interleaved Stochastic Trajectories (TWIST) sequence and diagnostic DSA were performed in these 17 patients. Results: The majority of the patients were young (median age was 25 years, range 8 to 46 years) and 11 patients were females. Erythrocyte sedimentation rate (ESR) was elevated in 9 patients and C-reactive protein (CRP) was elevated in 6 patients. Most commonly involved vessels in our patients were right renal artery (14 patients), abdominal aorta (12 patients) and left renal artery (11 patients). Left and right subclavian arteres were involved in 10 and 6 patients respectively. The sensitivity and specificity of time-resolved MRA using TWIST sequence is 100% as compared to DSA in the assessment of major vessels such as aorta, arch vessels, celiac artery and superior mesenteric artery. However, the sensitivity and specificity of time resolved MRA in the evaluation of renal arteries and vertebral arteries were 100%, 71.4% and 85.7%, 33.3% respectively. No significant association of MRI contrast enhancement with erythrocyte sedimentation rate (p = 1.00) and C-reactive protein (p = 0.600). Conclusion: Time resolved MRA images obtained using TWIST sequence were as qualitative as DSA images and can noninvasively evaluate the vascular involvement in NSAA patients.

Purpose To evaluate safety and efficacy of angiogenesis induced by intraarterial autologous bone marrow–derived stem cell (BMSC) injection in patients with severe peripheral arterial disease (PAD). Materials and Methods Eighty-one patients with severe PAD (77 men), including 56 with critical limb ischemia (CLI) and 25 with severe claudication, were randomized to receive sham injection (group A) or intraarterial BMSC injection at the site of occlusion (group B). Primary endpoints included improvement in ankle–brachial index (ABI) of > 0.1 and transcutaneous pressure of oxygen (TcPO2) of > 15% at mid- and lower foot at 6 mo. Secondary endpoints included relief from rest pain, > 30% reduction in ulcer size, and reduction in major amputation in patients with CLI and > 50% improvement in pain-free walking distance in patients with severe claudication. Results Technical success was achieved in all patients, without complications. At 6 mo, group B showed more improvements in ABI of > 0.1 (35 of 41 [85.37%] vs 13 of 40 [32.50%]; P 15% at the midfoot (35 of 41 [85.37%] vs 17 of 40 [42.50%]; P = .0001] and lower foot (37 of 41 [90.24%] vs 19 of 40 [47.50%]; P 30% reduction in ulcer size among patients with CLI or in > 50% improvement in pain-free walking distance among patients with severe claudication. Conclusions Intraarterial delivery of autologous BMSCs is safe and effective in the management of severe PAD.

An increased incidence of systemic macrothrombotic phenomena such as strokes has been observed in moderate and severe COVID. However, strokes have also been increasingly observed in mild COVID, post COVID, or without obvious COVID illness.To share our experience with a specific stroke type noted during the COVID pandemic period.A single-center observational study was conducted in Western India from January to December 2020, and data regarding stroke patients admitted under Neurology services were noted. Clinical, laboratory, and radiological characteristics of strokes and subtypes were documented.A total of 238 stroke patients were admitted in 2020, 76.5% during the COVID pandemic period. Among 153 ischemic strokes, 16.3% and 56.2% had large vessel occlusion (LVO) in pre-COVID and COVID pandemic period, respectively. Of all ischemic strokes, 20.9% (18 patients) and 12% (3 patients) had free floating thrombus (FFT) in the COVID versus pre-COVID period, respectively. Only 44.4% of all FFT patients could be proven SARS-CoV-2 RT-PCR positive while 50% were COVID suspect with surrogate markers of heightened inflammation at time of stroke. All patients were given anticoagulation and average mRS at discharge was 3.1 (range: 1-6) and 1.84 (range: 0-4) at 3-month follow-up in survivors.This study highlights the presence of FFT causing LVO as a new stroke subtype during the COVID-19 pandemic. With renewed and steeper spike in COVID-19 cases, especially new variants, the resurgence of this stroke subtype needs to be actively explored early in the course of illness to reduce morbidity and mortality.

To highlight the factors leading to the delayed diagnosis of basilar artery occlusion and poor outcome in the postpartum period during the prevailing Corona Virus Disease-2019 (COVID-19) pandemic.We here report a case of a 34-year female who presented with a headache localized to the occipital region after cesarean section under spinal anesthesia. Her headache severity increased over time, and she developed a generalized seizure episode and became unconscious. Subsequently, basilar artery thrombosis was diagnosed. Despite all efforts, she succumbed to death. We believe that we might have saved the patient's life if we could have made the diagnosis beforehand.We recommend that unless shown otherwise, postpartum headache and neck discomfort, even in individuals with no known risk factors, should have a low index of suspicion, early diagnosis using non-invasive radiological study such MRI to rule out this uncommon but deadly illness quickly.

A novel algorithm is presented to aid designers during the conceptual design phase of a new engineering product by rapidly assessing new areas of the design space. The algorithm presented here develops a polynomial chaos-based meta-model that allows the designer to estimate the probability distribution for a candidate design’s performance without requiring additional experiments or simulations. Probabilistic equivalence is used to map either a probability density function or a cumulative distribution function, continuous functions, into a reduced space in which interpolation functions can be developed. Data harvested from experiments or evaluations of an expensive computer code are used to train the meta-model. An advantage of this method over other histogram interpolation methods is that it is non-parametric: the training data are not assumed to belong to a particular family of probability distribution. The algorithm was validated using a standard benchmark test with synthetic data in a continuous-discrete design space. Finally, we exploited the variance of the Gaussian process emulators used as interpolation functions in order to develop a statistic that quantified the level of uncertainty associated with the algorithm’s estimates. This is a key feature if the algorithm is to be of practical use.

Paraneoplastic Pemphigus (PNP), a rare autoimmune blistering disease, can be accompanied by both benign and malignant neoplasms. The most frequently reported associated malignancies include lymphomatoid and hematologic malignancies, Castleman's disease, carcinoma, thymoma. In a patient suspected of PNP, with no known history of malignancy, an extensive workup is suggested to look for underlying malignancy, which has to be treated to induce PNP remission. In this clinical case report, cross sectional imaging of a young female diagnosed with PNP, unveiled a pericardial mass lesion extending into transverse pericardial sinus. Excisional biopsy was performed. Histopathology revealed pericardial ectopic thymoma.

Background Traditionally, quantification of aortic valve calcium (AVC) has been performed with noncontrast computed tomography (NCCT) using the Agatston method. This study sought to derive and validate a systematic method enabling AVC quantification using computed tomographic angiography (CTA) in patients with aortic stenosis (AS). Methods The study included 134 consecutive patients with AS who underwent both NCCT and CTA and were subdivided into derivation (n = 71) and validation cohorts (n = 63). AVC on NCCT (AVCNCCT) was quantified using the Agatston method using the software developed for semiautomatic assessment of coronary calcium. On CTA, the mean contrast attenuation of the aorta in Hounsfield units (AortaHU) and SD was measured in the region of interest at the level of the sinotubular junction. Results Using an adjusted calcium detection threshold of AortaHU + 2 SD, we calculated AVC on CTA (AVCCTA) using the same software without modifying other variables. Correlation between AVCNCCT and AVCCTA in the derivation cohort was excellent (r = 0.9679; P Conclusions AVC quantification on CTA is feasible with high accuracy and reliability and shows excellent agreement with the standard AVCNCCT score. With the systematic approach using "dynamic thresholds" being largely independent of the scan acquisition protocol, AVCDerived can potentially replace AVCNCCT, eliminating the need for separate NCCT acquisition solely for AVC quantification.

Introduction: Prostate cancer ranks second among all cancers affecting men. Common diagnostic tests like Transrectal Ultrasound (TRUS) and Prostate-Specific Antigen (PSA) are suboptimal for diagnostic purpose. Magnetic Resonance Imaging (MRI) has a promising role in detection, guidance for targeted biopsy and staging of prostate cancer. Aim: To evaluate the role of TRUS and MRI in the detection of prostate cancer and to ascertain if any functional parameter or union of parameters is of any utility in detection of prostate cancer. Materials and Methods: A prospective study was conducted which included fifty patients who underwent TRUS and 1.5-T MRI before being subjected toTRUS-guided biopsy. Imaging was compared with histopathological results. The sensitivity, specificity, positive and negative predictive value, positive and negative likelihood ratio for each of the investigation was calculated. Results: The accuracy of the model combining all the imaging variables {T2-weighted imaging (T2WI), MR spectroscopy (MRS), Diffusion-Weighted Imaging (DWI), Apparent Diffusion Coefficient (ADC) and Dynamic Contrast-Enhanced (DCE) MRI} in predicting prostate cancer was 94%, which was higher than the diagnostic accuracy of each variable considered alone (DWI, 92%; ADC, 92%; MRS, 88.0%; DCE-MRI, 92%; and T2WI, 72%). TRUS had a diagnostic accuracy of 80%, sensitivity of 100.0%, specificity of 67.7%, PPV of 65.5% and NPV of 100.0%. Conclusion: TRUS had a high sensitivity and negative predictive value but a low specificity. MRI had both high sensitivity and specificity especially when the combination of functional sequences was used. But, the addition of a third functional technique does not further improve detection. Thus, a limited number of functional sequences are needed in every MRI study for prostatic cancer. However, DWI being the most valuable should be included as one of the sequences.

Aortitis includes conditions with infectious or non-infectious etiology, characterized by inflammatory changes in one or more layers in aortic wall. Age at onset, geographic predilections, distribution and pattern of involvement in aorta, its branches and pulmonary arteries, and systemic associations provide a clue to etiology. Clinical presentations are often non-specific. An integrated approach including clinical, laboratory and imaging assessment is essential to confirm diagnosis and plan treatment. Assessment of disease activity is the key as it influences timing and outcome of treatment. Markers of activity include clinical, laboratory and imaging. Medical management remains the first-line therapy. Revascularization is indicated in the presence of hemodynamically significant stenosis and inactive disease. In the presence of flash pulmonary edema, left ventricular dysfunction or hypertensive encephalopathy, revascularization is performed irrespective of disease activity. Endovascular management is favored over surgery due to its high success and low restenosis rates. Symptomatic aneurysmal disease is usually managed by surgery.

Recently, data mining is gaining more popularity among researcher. Data mining provides various techniques and methods for analysing data produced by various applications of different domain. Similarly, Educational mining is providing a way for analyzing educational data set. Educational mining concerns with developing methods for discovering knowledge from data that come from educational field and it helps to extract the hidden patterns and to discover new knowledge from large educational databases with the use of data mining techniques and tools. Extracted knowledge from educational mining can be used for decision making in higher educational institutions. This paper is based on literature review of different data mining techniques along with certain algorithms like classification, clustering etc. This paper represents the effectiveness of mining techniques with educational data set for higher education institutions.

Humans are utilizing one of the biggest networks of social communication by the web, the development of internet gives a way to the rise of the Online social network that assists users to communicate and accommodate between the users, thus sharing and conveying their emotions and information in an online social network. As users in the online social network are growing and performing several activities, they want trusted users or sources. Trusted users or source of information is one of the primary requirements due to security and privacy of the information. Finding future trusted user is called trust prediction. Several tools are available for predicting trust between users in an online social network. The main aim of trust prediction is to find the trust association between the users in the online social network. In the following study, researchers have at reviewed the diverse trusted-link prediction techniques and evaluated them on the basis of the provided standard dataset provided to us

Objective: We aimed to evaluate the diagnostic accuracy (DA) of dual-source CT coronary angiography (DSCTCA) against invasive coronary angiography (ICA) in assessing stenotic cardiac allograft vasculopathy (CAV) in heart transplant (HTX) recipients. Methods: Consecutive HTX recipients(n = 38) on annual surveillance, underwent DSCTCA prior to ICA on a 192-detector 384-slice DSCT scanner. Cases were classified as no CAV (no stenosis), any CAV (any degree of stenosis) or significant CAV (>50% stenosis). Results: Mean age was 33.66 ± 11.45 years (M:F = 27:11, median time from HTX-23.5 months). Prevalence of any CAV on DSCTCA and ICA was 44.7%(n = 17) and 39.5%(n = 15), respectively and that of significant CAV was 21.1%(n = 8) and 15.8%(n = 6), respectively. 557 (96.7%) segments were interpretable on DSCTCA. Mean radiation dose was 4.24 ± 2.15 mSv. At patient-level, the sensitivity, specificity, positive-predictive value, negative-predictive value (NPV), and DA of DSCTCA for detection of any CAV and significant CAV were 100%, 91.3%, 88.2%, 100%, 94.73% and 100%, 94%, 75%, 100%, 95% respectively. The same on segment-based analysis were 96%, 97.6%, 80%, 99.6%, 97.5% and 100%, 99.6%,86.7%,100%, 99.6%, respectively. There was excellent agreement between the two modalities for detection of any CAV and significant CAV [κ = 0.892 and 0.826 (patient-level), 0.859 and 0.927 (segment-level)]. CAC score correlated significantly with the presence of any CAV on both modalities. A diagnosis of rejection on biopsy did not correlate with any/significant CAV on DSCTCA or ICA. Conclusion: High sensitivity and NPV of DSCTCA in the evaluation of stenotic CAV suggests that it can be an accurate and non-invasive alternative to ICA for routine surveillance of HTX recipients. Advances in knowledge: DSCTCA detects the stenotic CAV non-invasively in transplant recipients with high sensitivity, specificity and NPV when compared with catheter coronary angiography, at lower radiation doses. There is excellent agreement between CT angiography and catheter coronary angiography for detection of any CAV and significant CAV. A diagnosis of rejection on biopsy does not correlate with any/significant CAV on CT angiography or catheter angiography.

We hereby present a case in which we used gadolinium as contrast medium for thoracic endovascular aortic repair in a patient with iodine hypersensitivity.

We introduce a framework for statistical inference of the closure coefficients using machine learning methods. The objective of this framework is to quantify the epistemic uncertainty associated with the closure model by using experimental data via Bayesian statistics. The framework is tailored towards cases for which a limited amount of experimental data is available. It consists of two components. First, by treating all latent variables (non-observed variables) in the model as stochastic variables, all sources of uncertainty of the probabilistic closure model are quantified by a fully Bayesian approach. The probabilistic model is defined to consist of the closure coefficients as parameters and other parameters incorporating noise. Then, the uncertainty associated with the closure coefficients is extracted from the overall uncertainty by considering the noise being zero. The overall uncertainty is rigorously evaluated by using Markov-Chain Monte Carlo sampling assisted by surrogate models. We apply the framework to the Spalart–Allmars one-equation turbulence model. Two test cases are considered, including an industrially relevant full aircraft model at transonic flow conditions, the Airbus XRF1. Eventually, we demonstrate that epistemic uncertainties in the closure coefficients result into uncertainties in flow quantities of interest which are prominent around, and downstream, of the shock occurring over the XRF1 wing. This data-driven approach could help to enhance the predictive capabilities of computational fluid dynamics (CFD) in terms of reliable turbulence modeling at extremes of the flight envelope if measured data is available, which is important in the context of robust design and towards virtual aircraft certification. The plentiful amount of information about the uncertainties could also assist when it comes to estimating the influence of the measured data on the inferred model coefficients. Finally, the developed framework is flexible and can be applied to different test cases and to various turbulence models.

Aims To explore the impact of incorporating a faster cardiac magnetic resonance (CMR) imaging protocol in a low–middle-income country (LMIC) and using the result to guide chelation in transfusion-dependent patients. Methods and results A prospective UK–India collaborative cohort study was conducted in two cities in India. Two visits 13 months apart included clinical assessment and chelation therapy recommendations based on rapid CMR results. Participants were recruited by the local patient advocate charity, who organized the patient medical camps. The average scanning time was 11.3 ± 2.5 min at the baseline and 9.8 ± 2.4 min (P Conclusion For thalassaemia patients in an LMIC, a simplified CMR protocol linked to therapeutic recommendation via the patient camp model led to enhanced chelation therapy and a reduction in cardiac iron in 1 year.

Manufacturing is a technique that produce finished goods after taking supplies, raw materials and ingredients. Manufacturing process is frequently used to produce food, chemicals and other things those have very important place in human’s life. This manufacturing process involve data for analysis and management of the process, but in current scenario the data that are generated by the process is increasing day by day. This huge amount of data in known as big data. Big data is difficult to handle by traditional data management tools. Data that are generated by the manufacturing process collected by the logs records and may be as structured or unstructured. Generally analysis is performed by structured data. Unstructured data also provide good insights in the manufacturing process if analysed in proper manner. This paper involved an efficient approach of big data analysis for manufacturing process.

The manufacturing process is growing due to the development in procedure and computer technology. These modifications have been shown in digital manufacturing of today as compared with flexible manufacturing of three decades ago. The large volumes of data generated by the manufacturing processes. This data can be used in various aspects of manufacturing for improving the consistency of the manufacturing processes, equipment failures prediction, designing of manufacturing equipment, and discover new technologies with the help of this historical data. In manufacturing process unstructure data is generated very fast, due to growth of manufacturing website this data is increasing in the size and variety day by day this will create opportunities and challenges, in the organisation for manufacturing process is related to get efficient information from this huge amount of data by searching and retrieve the data by apply suitable data mining technique this large amount of data will be heterogeneous in nature traditional methods such as keyword search cannot provide efficient Information retrieval. So organisation cannot take appropriate decisions on the basis of the result that is provided by the traditional method. Maximum data is generating in unstructured form. This paper is focus on different unsupervised machine learning techniques used for text mining.

This work presents a framework for predicting unknown input distributions for turbomachinery applications starting from scarce experimental measurements. The problem is relevant to turbomachinery where important parameters are obtained using indirect measurements. In this paper a scroll compressor is used as example but the suggested framework is completely general and can be used to infer missing data on material composition (carbon fiber properties, laser melted specimens for additive manufacturing etc) or input data (such as the turbine inlet temperature). Scroll compressors are small devices with a very complex geometry that is difficult to measure. Moreover these compressors are highly sensitive to manufacturing errors and clearances. For these reasons we have chosen this example as an ideal candidate to prove the effectiveness of the framework. An input probability distribution for the scroll height is recovered based on a scarce, synthetic data set. The scroll height is used as an example of a missing distribution for a geometric parameter as it has the highest variance and is challenging to measure experimentally. The framework consists of two main building blocks: an equivalence in a probabilistic sense and a Non-Intrusive Polynomial Chaos formulation able to deal with scarce data. The probabilistic equivalence is defined by a Probability Density Function (PDF) matching approach in which the statistical distance between probability distributions is quantified by either the Kolmogorov-Smirnov (KS) distance or the Kullback-Leibler (KL) divergence. By representing the missing inputs with a generalised Polynomial Chaos Expansion (gPCE) the back-calculation problem can be recast as an optimisation problem in which an arbitrary Polynomial Chaos (aPC) formulation was used to propagate the uncertain input distributions through a computational model of the system and generate a probability distribution for the Quantity of Interest (QoI). The framework has been tested with multiple non-Askey scheme distributions to prove the generality of the proposed approach.

L-2 Hydroxyglutaric aciduria is a rare metabolic disorder which is autosomal recessive in inheritance. It is characterised by the increased urinary excretion of L-2 hydroxyglutaric acid and the diagnosis is based on the increased levels of the L-2 hydroxy glutaric acid in the urine, serum & CSF. This is a neurometabolic disorder which is associated with slowly progressive psychomotor delay since childhood. We report a case of an 18 –year old female who presented at the emergency department with seizures, fever and on imaging show classic features.

Software testing consumes the major portion of the total efforts required for software development. This activity is very time consuming and labor intensive. It is very hard to do testing in optimal manner. In this paper a new approach is proposed, which uses the nature inspired stochastic algorithm called Cuckoo Search Algorithm (CSA) for the automatic generation of test data for data flow testing. This approach considers all def-use as test adequacy criteria. For assistance to CSA in the state space a new fitness function is also proposed by using the concept of dominator tree and branch distance in a CFG. To validate the proposed approach experiments are carried out on 10 benchmarked programs and findings are contrasted with earlier work done in this domain. Further in order to prove that proposed approach performs better than the above mentioned approaches a statistical difference test (T-test) is also performed.

The intention behind software testing is discovering defects in the developed software, making it error-free, robust and trustworthy. A large quantum of total efforts in the development of software is done on software testing. These efforts may include time, cost and most importantly manpower. The number of efforts required in software testing may be reduced if test data is generated automatically, without trade off the quality of the developed software. In literature, various nature inspired algorithms are used for the optimization of the software testing process. This article is a brief study on the applications of nature inspired algorithms in software testing. To keep the study succinct this study considers only two widely used testing types, structural and functional testing and literature available, since 2010 by considering only SCI or SCOPUS indexed publications.

International audience; This document presents the required layout of articles to Medical data mining has become one of the prominent issues in the field of data mining due to the delicate lifestyle opted by the people which are leading them towards various chronicle health diseases. Heart disease is one of the conspicuous public health concern worldwide issues. Since clinical data is growing rapidly owing to deficient health awareness, various techniques and scientific methods are opted for analyzing this huge data. Several data mining techniques such as Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Decision tree, Naïve Bayes and Artificial Neural Network (ANN) are introduced for the prediction of health disease. These techniques help to mine the relevant and useful amount of data, form the medical dataset which helps to provide beneficial information to the medical institutions. This study presents various issues related to healthcare and various machines learning algorithms which have to withstand to provide the best possible output. A comprehensive review of the literature has been summarized to put lights on the previous work done in this field.

International audience; Theranostics involves finding the biomarkers of a disease, fighting them through site specific drug delivery and following them for prognosis of the disease. Microneedle array technology has been used for drug delivery and extended for continuous monitoring of analytes present in the skin compartment. We envisage the use of microneedle arrays for future theranostic applications. The potential of combining microneedle array-based drug delivery and diagnostics as part of closed-loop control system for the management of diseases and delivery of precision drugs in individual patients is reported in this paper.

Integrating interventional radiology (IR) into clinical practice faces challenges in emerging countries in Asia and Africa. Overcoming them requires innovative solutions customized to local needs. After an in-depth gap analysis of these challenges, we began an organized skill development initiative in late 2015 offering radiologists and their supporting staff fully paid scholarships for IR training. Its concept, structure, and progress are reported here. This initiative covered 8 countries, IR specialists (n = 51), senior residents (n = 24), and 15 educational events (training institute [n = 3]; participating countries [n = 12]). This initiative is intended to develop a global network of trained personnel who can support IR programs in challenging locations of emerging countries.

Aims: The aim of this study is to compare postcontrast three-dimensional (3D) T1-Sampling perfection with application-optimized contrasts by using different flip angle evolutions, 3D fluid-attenuated inversion recovery (FLAIR), and 3D T1-magnetization prepared rapid gradient echo (MPRAGE) sequences in patients of meningitis. Settings and Design: A hospital-based cross-sectional study done in the Department of Radiodiagnosis, IGMC Shimla for a period of 1 year from June 1, 2016, to May 30, 2017. Subjects and Methods: A total of 30 patients suspected of meningitis underwent magnetic resonance imaging evaluation with postcontrast 3D T1-MPRAGE, 3D T1-SPACE, and 3D FLAIR sequences. The abnormal leptomeningeal enhancement was noted by two radiologists together on these sequences and scores were given to the abnormal leptomeningeal enhancement. Statistical Analysis Used: The sensitivity of 3D T1-SPACE, 3D T1-MPRAGE, and 3D FLAIR was calculated and compared. The level of agreement between these sequences was assessed by kappa coefficient. P < 0.05 was taken as statistically significant. Results: 3D T1-SPACE shows superiority in meningeal enhancement along basal cisterns, Sylvian fissure and along cerebral convexities. It is also found to be better in delineating parenchymal lesions. 3D FLAIR failed to demonstrate enhancement along cerebral convexities however found to be better than 3D T1-MPRAGE in delineating enhancement along basal cisterns and Sylvian fissures. 3D T1-MPRAGE has shown subtle enhancement in basal cisterns, Sylvian fissure and along cerebral convexities. 3D T1-SPACE, 3D FLAIR, and 3D T1-MPRAGE has sensitivity of 91.67%, 66.67%, and 54.17%, respectively. Conclusion: Postcontrast 3D T1-SPACE sequence is an excellent tool than postcontrast 3D T1-MPRAGE and 3D FLAIR sequences in the evaluation of meningeal enhancement and depiction of additional lesions in brain parenchyma.

BACKGROUND: Spontaneous aneurysm of the superficial temporal artery in a helicopter pilot while operating in the extreme cold climatic conditions of a very high altitude area led to a thorough search for etiological possibilities related to this case.CASE REPORT: A 38-yr-old military helicopter pilot, while flying at altitudes ranging from 4500 m to 6000 m (15,000 to 20,000 ft) reported with an acute onset of a subcutaneous swelling on his left temple. History and clinical profile did not suggest any traumatic, hematologic, or vasculitic etiology. His inflammatory markers, anti-nuclear antibody, anti-neutrophil cytoplasmic antibodies, complement levels, and whole-body PET scan did not suggest any evidence of vasculitis. Presence of any other intracranial aneurysms was also ruled out. He underwent curative excision biopsy, which showed perivascular inflammation. He was diagnosed as a case of left superficial temporal artery aneurysm. The recovery period was uneventful and the follow-up color Doppler flow imaging of the temporal artery and acute phase reactants was normal.DISCUSSION: Spontaneous aneurysms involving the superficial temporal artery is a very rare diagnosis. Occurrence of such an aneurysm in a young pilot without any identifiable predisposing factors led the authors to hypothesize a possible etiological combination of environmental and mechanical factors along with aviation stresses with the likely compounding role of the helmet. Management and aeromedical aspects of this unique case are discussed in this paper.Sekhar BM, Sheoran S, Routh D, Sharma S. Superficial temporal artery aneurysm in a helicopter pilot operating at high altitude. Aerosp Med Hum Perform. 2019; 90(1):53-57.

ObjectivesWe sought to clarify the variations in the anatomy of the superior cavoatrial junction and anomalously connected pulmonary veins in patients with superior sinus venosus defects using computed tomographic (CT) angiography.MethodsCT angiograms of 96 consecutive patients known to have superior sinus venosus defects were analysed.ResultsThe median age of the patients was 34.5 years. In seven (7%) patients, the defect showed significant caudal extension, having a supero-inferior dimension greater than 25 mm. All patients had anomalous connection of the right superior pulmonary vein. The right middle and right inferior pulmonary vein were also connected anomalously in 88 (92%) and 17 (18%) patients, respectively. Anomalous connection of the right inferior pulmonary vein was more common in those with significant caudal extension of the defect (57% vs 15%, p=0.005). Among anomalously connected pulmonary veins, the right superior, middle, and inferior pulmonary veins were committed to the left atrium in 6, 17, and 11 patients, respectively. The superior caval vein over-rode the interatrial septum in 67 (70%) patients, with greater than 50% over-ride in 3 patients.ConclusionAnomalous connection of the right-sided pulmonary veins is universal, but is not limited to the right upper lobe. Not all individuals have over-riding of superior caval vein. In a minority of patients, the defect has significant caudal extension, and anomalously connected pulmonary veins are committed to the left atrium. These findings have significant clinical and therapeutic implications.

Background: Laparoscopic nephrectomy has been established as the standard of care for the management of benign non-functioning kidneys and has gained worldwide popularity over the past decade. Methods- This study was conducted in the Department of General surgery, Indira Gandhi medical college, Shimla on 20 selected patients of benign non functional kidney admitted for elective Laparoscopic Nephrectomy between July 2018 to June 2019 Results: In this study, the mean operating time in success full laparoscopic nephrectomies was 103.7 + 20.6 min in lap converted to open it was 165 .7 +26.99 min and in hand-assisted tame taken was 150 min which is statically not significant with p value =0.1317. Conclusion: The mean time taken for completion of laparoscopic nephrectomy in first 4 cases was 105 min and in next 4 cases was 108 min and in last 4 cases it was 97 min there was definitive learning curve as in last 4 cases operating time was less as compared to initial cases but operating time also depends on other factors like in hydronephrotic kidney due to well maintained plane dissection take less time ,but in pyonephrotic kidney ,tubercular kidney,previously intervension like PCN, there were dense adhesion resulting in more time for disection. Keywords: Laparoscopy, Nephrectomy, Duration of surgery

Background: Laparoscopic nephrectomy has been established as the standard of care for the management of benign non-functioning kidneys and has gained worldwide popularity over the past decade. Methods: This study was conducted in the Department of General surgery, Indira Gandhi medical college, Shimla on 20 selected patients of benign non functional kidney admitted for elective Laparoscopic Nephrectomy between July 2018 to June 2019 Results: Less than 100 ml of blood was lost in 3(15%) of the patient. 100 to 200 ml was lost in 9(45%) and in 3(15%) patients 200 to 300 ml blood was lost and 5 (25%) had blood loss more than 300 ml. The mean blood loss in successful laparoscopic nephrectomy was 129 +123 ml and in lap converted to open was 435.7 + 174.9 ml. which is significantly less in successful lap nephrectomy which is statistically significant with a p-value of o.oo3 Conclusion: Mean blood loss in laparoscopic nephrectomy was 145 +144 ml and in converted cases, it was 350+200 ml. mean blood loss in hydronephrotic kidney was 145+ 144.2 ml in pyonephrotic kidney 325+ 318 in end stage nephrolithiasis 350+ 200 ml .There was more blood loss in ESRD and pyonephrotic kidney due to dense adhesion whereas blood loss is less in hydronephrotic kidney due to well maintained plane for dissection . Keywords: Laparoscopy, Nephrectomy, Blood loss

A 17-year-old boy presented with precordial chest pain and dyspnoea of three days duration. The patient was in heart failure at presentation and had persistent chest discomfort. There was no histor...

Wireless sensor networks (WSNs) constitute an immense number of mobile or stationary sensor nodes that rely on multi-hop and self-organization. Internet of Things (IoT) is based on interconnected objects which are capable of communicating with each other and also collecting data related to their situation. Hence, for IoT networks, rather than energy-efficient communication, the most crucial challenge for conserving the cost of network management is the reduction of Internet connection numbers. To extend the network lifetime and to avoid interference, an extensively applied method is the efficient usage of energy. The objective of the low energy adaptive clustering hierarchy (LEACH) is the selection of sensor nodes as the cluster-heads (CHs) at several cycles such that there is the acquisition of the extreme power excess’s outcome and, later, its dispersal in the whole WSN. Tabu search (TS) is a metaheuristic which controls the local heuristic search procedure such that there is the exploration of the solution space beyond its local optimality. Multi-verse optimizer (MVO) algorithm is influenced by astrophysics’ multi-verse theory. This work has proposed a multi-hop energy-efficient cluster-based routing with multi-verse optimizer.

Graphene-based point-of-care (PoC) and chemical sensors can be fabricated using photolithographic processes at wafer-scale. However, these approaches are known to leave polymer residues on the graphene surface, which are difficult to remove completely. In addition, graphene growth and transfer processes can introduce defects into the graphene layer. Both defects and resist contamination can affect the homogeneity of graphene-based PoC sensors, leading to inconsistent device performance and unreliable sensing. Sensor reliability is also affected by the harsh chemical environments used for chemical functionalisation of graphene PoC sensors, which can degrade parts of the sensor device. Therefore, a reliable, wafer-scale method of passivation, which isolates the graphene from the rest of the device, protecting the less robust device features from any aggressive chemicals, must be devised. This work covers the application of molecular vapour deposition technology to create a dielectric passivation film that protects graphene-based biosensing devices from harsh chemicals. We utilise a previously reported “healing effect” of Al2O3 on graphene to reduce photoresist residue from the graphene surface and reduce the prevalence of graphene defects to improve graphene device homogeneity. The improvement in device consistency allows for more reliable, homogeneous graphene devices, that can be fabricated at wafer-scale for sensing and biosensing applications.

Perovskite materials have attracted attention due to their excellent optical and electrical properties; however, their unsatisfactory stability limits their application in biochemical detection. In this paper, CsPbBr3 perovskite quantum dots were successfully encapsulated in poly(styrene/acrylamide) microspheres, using a swelling–shrinking method. The manufactured perovskite microspheres (PDPS composites) not only maintained strong photoluminescence (PL) stability but also demonstrated great water solubility. Additionally, a real-time pH monitoring platform was constructed based on the prepared PDPS composites and dopamine, and the system showed a good linear relationship in a pH range of 4–12. Furthermore, urea could be hydrolyzed to produce hydroxyl groups, thereby increasing the pH of the solution. Therefore, this system was then extended for urea and urease detection. As a result, the detection limits of urea and urease were recorded as 1.67 μM and 2.1 mU/mL, respectively. This development provides an interesting demonstration of the expanding list of applications of perovskite materials.

Social Media has a significant effect on both individuals and society. Here, firstly, the present condition of the social media is illustrated, with respect to the facts and statistics before deepening the aspects that are selected from the novel forms of interactions virtually. Specifically focusing on the recent findings in neuroscience research, there are some main questions that have to be answered: How do people deal with these latest types of technologies, and what are the likely consequences of our online behavior socially. A wide range of different interpretations exists in relation to the value of social media as a potent source of learning and communication. In the course of observing the different advantages and drawbacks, the highlight is on the situations for handling social media responsibly. This testing is done on two levels; Global and individual forms of information and the expression of opinions through social media and the impact of social media on real social systems. Further, social media affects the above two levels and this effect is integrated into a broader scenario. As quoted by Ruskin Bond while referring to the current social media structure and usage, “We live in a world where there are more writers than readers”. As a key result, we can conclude that there is an effect of social media on human thinking and as a result on peoples’ quality of life. Besides, emotions are key to communication and the benefits that are known generally may often pose a serious threat to the individuals and society on the whole and hence, there is a need for social media interactions that are sensible.