Propagation of solitons of the magnetization in magnetic nano-particle arrays

It is clarified for the first time that solitons originating from the dipolar interaction in ferromagnetic nano-particle arrays are stably created. The characteristics can be well controlled by the strength of the dipolar interaction between particles and the shape anisotropy of the particle. The soliton can propagate from a particle to a neighbor particle at a clock frequency even faster than 100 GHz using materials with a large magnetization. Such arrays of nano-particles might be feasible in an application as a signal transmission line.Comment: RevTeX, 3 pages, 3 PostScript figures, To appear in Journal of Magnetism and Magnetic Material

Case of acute rheumatic fever (ARF) that occurred after presumed macrolide failure

Group A Streptococcal pharyngitis is a common illness in the pediatric population. Penicillin or amoxicillin remain the standard therapy. In nonanaphylactic cases of penicillin allergy, a first-generation cephalosporin may be used

Sustainable innitiatives taken by p&g to protect environment

In the era of rapid industrialization and fast-track development the environmental issues suffer a lot. Be it any industry, organization or society the development must be carried out keeping the sustainability in mind. The opportunity of these overnight development approaches has ramified the environmental issues. The present communication enumerates the measures of environmental impact by taking a case of Procter and Gamble. Authors have studied the strategies of Procter and Gamble and their sustainable behavior in Indian as well as global context. Various data of last decade has been analyzed. It is found that the company P&G is moving in a right direction by providing new paradigms of realistic development. All the data for this study has been taken from secondary sources

Regional optimum frequency analysis of resting-state fMRI data for early detection of Alzheimer’s disease biomarkers

The blood-oxygen label dependent (BOLD) signal obtained from functional magnetic resonance images (fMRI) varies significantly among populations. Yet, there is some agreement among researchers over the pace of the blood flow within several brain regions relative to the subject’s age and cognitive ability. Our analysis further suggested that regional coherence among the BOLD fMRI voxels belonging to the individual region of the brain has some correlation with underlying pathology as well as cognitive performance, which can suggest potential biomarkers to the early onset of the disease. To capitalise on this we propose a method, called Regional Optimum Frequency Analysis (ROFA), which is based on finding the optimum synchrony frequency observed at each brain region for each of the resting-state BOLD frequency bands (Slow 5 (0.01–0.027 Hz), Slow 4 (0.027–0.073 Hz) and slow 3 (0.073 to 0.198 Hz)), and the whole frequency band (0.01–0.167 Hz) respectively. The ROFA is carried out on fMRI data of total 310 scans, i.e., 26, 175 and 109 scans from 21 young-healthy (YH), 69 elderly-healthy (EH) and 33 Alzheimer’s disease (AD) patients respectively, where these scans include repeated scans from some subjects acquired at 3 to 6 months intervals. A 10-fold cross-validation procedure evaluated the performance of ROFA for classification between the YH vs EH, YH vs AD and EH vs AD subjects. Based on the confusion-matrix parameters; accuracy, precision, sensitivity and Matthew’s correlation coefficient (MCC), the proposed ROFA classification outperformed the state-of-the-art Group-independent component analysis (Group-ICA), Functional-connectivity, Graph metrics, Eigen-vector centrality, Amplitude of low-frequency fluctuation (ALFF) and fractional amplitude of low-frequency fluctuations (fALFF) based methods with more than 94.99% precision and 95.67% sensitivity for different subject groups. The results demonstrate the effectiveness of the proposed ROFA parameters (frequencies) as adequate biomarkers of Alzheimer’s disease

Regional optimum frequency analysis of resting-state fMRI data for early detection of Alzheimer’s disease biomarkers

The blood-oxygen label dependent (BOLD) signal obtained from functional magnetic resonance images (fMRI) varies significantly among populations. Yet, there is some agreement among researchers over the pace of the blood flow within several brain regions relative to the subject’s age and cognitive ability. Our analysis further suggested that regional coherence among the BOLD fMRI voxels belonging to the individual region of the brain has some correlation with underlying pathology as well as cognitive performance, which can suggest potential biomarkers to the early onset of the disease. To capitalise on this we propose a method, called Regional Optimum Frequency Analysis (ROFA), which is based on finding the optimum synchrony frequency observed at each brain region for each of the resting-state BOLD frequency bands (Slow 5 (0.01–0.027 Hz), Slow 4 (0.027–0.073 Hz) and slow 3 (0.073 to 0.198 Hz)), and the whole frequency band (0.01–0.167 Hz) respectively. The ROFA is carried out on fMRI data of total 310 scans, i.e., 26, 175 and 109 scans from 21 young-healthy (YH), 69 elderly-healthy (EH) and 33 Alzheimer’s disease (AD) patients respectively, where these scans include repeated scans from some subjects acquired at 3 to 6 months intervals. A 10-fold cross-validation procedure evaluated the performance of ROFA for classification between the YH vs EH, YH vs AD and EH vs AD subjects. Based on the confusion-matrix parameters; accuracy, precision, sensitivity and Matthew’s correlation coefficient (MCC), the proposed ROFA classification outperformed the state-of-the-art Group-independent component analysis (Group-ICA), Functional-connectivity, Graph metrics, Eigen-vector centrality, Amplitude of low-frequency fluctuation (ALFF) and fractional amplitude of low-frequency fluctuations (fALFF) based methods with more than 94.99% precision and 95.67% sensitivity for different subject groups. The results demonstrate the effectiveness of the proposed ROFA parameters (frequencies) as adequate biomarkers of Alzheimer’s disease

Case of acute rheumatic fever (ARF) that occurred after presumed macrolide failure

Group A Streptococcal pharyngitis is a common illness in the pediatric population. Penicillin or amoxicillin remain the standard therapy. In nonanaphylactic cases of penicillin allergy, a first-generation cephalosporin may be used

Phase-Type Survival Trees to Model a Delayed Discharge and Its Effect in a Stroke Care Unit

The problem of hospital patients’ delayed discharge or ‘bed blocking’ has long been a challenge for healthcare managers and policymakers. It negatively affects the hospital performance metrics and has other severe consequences for the healthcare system, such as affecting patients’ health. In our previous work, we proposed the phase-type survival tree (PHTST)-based analysis to cluster patients into clinically meaningful patient groups and an extension of this approach to examine the relationship between the length of stay in hospitals and the destination on discharge. This paper describes how PHTST-based clustering can be used for modelling delayed discharge and its effects in a stroke care unit, especially the extra beds required, additional cost, and bed blocking. The PHTST length of stay distribution of each group of patients (each PHTST node) is modelled separately as a finite state continuous-time Markov chain using Coxian-phase-type distributions. Delayed discharge patients waiting for discharge are modelled as the Markov chain, called the ‘blocking state’ in a special state. We can use the model to recognise the association between demographic factors and discharge delays and their effects and identify groups of patients who require attention to resolve the most common delays and prevent them from happening again. The approach is illustrated using five years of retrospective data of patients admitted to the Belfast City Hospital with a stroke diagnosis

Human Arm simulation for interactive constrained environment design

During the conceptual and prototype design stage of an industrial product, it is crucial to take assembly/disassembly and maintenance operations in advance. A well-designed system should enable relatively easy access of operating manipulators in the constrained environment and reduce musculoskeletal disorder risks for those manual handling operations. Trajectory planning comes up as an important issue for those assembly and maintenance operations under a constrained environment, since it determines the accessibility and the other ergonomics issues, such as muscle effort and its related fatigue. In this paper, a customer-oriented interactive approach is proposed to partially solve ergonomic related issues encountered during the design stage under a constrained system for the operator's convenience. Based on a single objective optimization method, trajectory planning for different operators could be generated automatically. Meanwhile, a motion capture based method assists the operator to guide the trajectory planning interactively when either a local minimum is encountered within the single objective optimization or the operator prefers guiding the virtual human manually. Besides that, a physical engine is integrated into this approach to provide physically realistic simulation in real time manner, so that collision free path and related dynamic information could be computed to determine further muscle fatigue and accessibility of a product designComment: International Journal on Interactive Design and Manufacturing (IJIDeM) (2012) 1-12. arXiv admin note: substantial text overlap with arXiv:1012.432