Sequential Sparsening by Successive Adaptation in Neural Populations

In the principal cells of the insect mushroom body, the Kenyon cells (KC), olfactory information is represented by a spatially and temporally sparse code. Each odor stimulus will activate only a small portion of neurons and each stimulus leads to only a short phasic response following stimulus onset irrespective of the actual duration of a constant stimulus. The mechanisms responsible for the sparse code in the KCs are yet unresolved. Here, we explore the role of the neuron-intrinsic mechanism of spike-frequency adaptation (SFA) in producing temporally sparse responses to sensory stimulation in higher processing stages. Our single neuron model is defined through a conductance-based integrate-and-fire neuron with spike-frequency adaptation [1]. We study a fully connected feed-forward network architecture in coarse analogy to the insect olfactory pathway. A first layer of ten neurons represents the projection neurons (PNs) of the antenna lobe. All PNs receive a step-like input from the olfactory receptor neurons, which was realized by independent Poisson processes. The second layer represents 100 KCs which converge onto ten neurons in the output layer which represents the population of mushroom body extrinsic neurons (ENs). Our simulation result matches with the experimental observations. In particular, intracellular recordings of PNs show a clear phasic-tonic response that outlasts the stimulus [2] while extracellular recordings from KCs in the locust express sharp transient responses [3]. We conclude that the neuron-intrinsic mechanism is can explain a progressive temporal response sparsening in the insect olfactory system. Further experimental work is needed to test this hypothesis empirically. [1] Muller et. al., Neural Comput, 19(11):2958-3010, 2007. [2] Assisi et. al., Nat Neurosci, 10(9):1176-1184, 2007. [3] Krofczik et. al. Front. Comput. Neurosci., 2(9), 2009.Comment: 5 pages, 2 figures, This manuscript was submitted for review to the Eighteenth Annual Computational Neuroscience Meeting CNS*2009 in Berlin and accepted for oral presentation at the meetin

Appliance for Water consumption management in showering by using Arduino kit, Energy NExus and SensorS : AWARENESS kit

Peer reviewe

Ferroelectric-driven tunable magnetism in ultrathin platinum films

Electric control of magnetism in magnetoelectric (ME) multiferroics is expected to have a significant impact on a wide range of technological applications. Here, we predict the modulation of magnetism in ultrathin platinum films due to the ferroelectric polarization of the BaTiO3 substrate, which along with biaxial strain changes the density of states at the Fermi energy. We demonstrate that both the magnitude and direction of the magnetization depend strongly on the polarization direction and/or strain. This leads to an unprecedented ME effect involving a giant change of magnetocrystalline anisotropy under polarization switching due to the large spin-orbit coupling of Pt. These findings pave the way of an alternative strategy for the design of nonvolatile and ultralow power spintronics and magnetic memory storage devices

Identifying Patients With Coronary Artery Disease Using Rest and Exercise Seismocardiography

Coronary artery disease (CAD) is the most common cause of death globally. Patients with suspected CAD are usually assessed by exercise electrocardiography (ECG). Subsequent tests, such as coronary angiography and coronary computed tomography angiography (CCTA) are performed to localize the stenosis and to estimate the degree of blockage. The present study describes a non-invasive methodology to identify patients with CAD based on the analysis of both rest and exercise seismocardiography (SCG). SCG is a non-invasive technology for capturing the acceleration of the chest induced by myocardial motion and vibrations. SCG signals were recorded from 185 individuals at rest and immediately after exercise. Two models were developed using the characterization of the rest and exercise SCG signals to identify individuals with CAD. The models were validated against related results from angiography. For the rest model, accuracy was 74%, and sensitivity and specificity were estimated as 75 and 72%, respectively. For the exercise model accuracy, sensitivity, and specificity were 81, 82, and 84%, respectively. The rest and exercise models presented a bootstrap-corrected area under the curve of 0.77 and 0.91, respectively. The discrimination slope was estimated 0.32 for rest model and 0.47 for the exercise model. The difference between the discrimination slopes of these two models was 0.15 (95% CI: 0.10 to 0.23, p \u3c 0.0001). Both rest and exercise models are able to detect CAD with comparable accuracy, sensitivity, and specificity. Performance of SCG is better compared to stress-ECG and it is identical to stress-echocardiography and CCTA. SCG examination is fast, inexpensive, and may even be carried out by laypersons

Accumulative fold-forging (AFF) as a novel severe plastic deformation process to fabricate a high strength ultra-fine grained layered aluminum alloy structure

The final publication is available at Elsevier via http:/dx.doi.org/10.1016/j.matchar.2017.12.023 © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/A novel severe plastic deformation (SPD) process termed accumulative fold forging (AFF) is introduced to fabricate a homogenous ultra-fine grained (UFG) layered metal structure by repetitive folding and forging aluminum alloy foil. The present work studies AFF applied to thin foils of AA8006 Al-Fe-Mn aluminum alloy after 26 folding steps to produce a UFG structure containing 67,108,864 layers across a 2mm thickness. The structure of the layers and grain refinement are studied using X-ray diffraction (XRD), field-emission scanning electron microscopy (FE-SEM) and scanning-transmission electron microscopy (STEM) analysis. The results indicate a well-bonded inter-layer structure with an average grain size of about 200nm parallel and 250nm perpendicular to the forging direction, while dislocation density increased to ~7.2×1015m−2 following AFF. The mechanical strength of the aluminum foil is evaluated in the terms of indentation hardness testing before and after AFF process. The processed UFGed layered material exhibited an average hardness value of ~61.5 Vickers as compared to the initial value of ~30.4 Vickers for the annealed foil alloy, which indicates an improvement of ~100% due to the contributions of grain refinement, work hardening and interfacial strengthening of the bonded layers.Natural Sciences and Engineering Research Council of Canada (NSERC

Real-time flood overflow forecasting in Urban Drainage Systems by using time-series multi-stacking of data mining techniques

© 2023 The Author(s).Overflow forecasting in early warning systems is acknowledged as an essential task for devastating urban flood risk management. Although many machine learning models have been developed recently to forecast water levels in urban drainage systems (UDS), they usually require big and accurate data resources [1]. Alternatively, ensemble data mining models are becoming more popular, in which time-series numerical data are turned into the categorised features that classify wet weather conditions as two classes of overflow and non-overflow conditions [2]. However, the concept of time-series ensemble modelling i.e., blending different data mining techniques for predictions with different timesteps is still new [3]. Furthermore, the application of more advanced models, particularly multi-blending in these types of ensemble modelling requires more investigation. This study aims to introduce a novel multi-stacking model that integrates different decision tree frameworks by developing various base weak learner data mining techniques and associated base model performance indicators in the process of time-series blending of pre-trained stacked ensemble models. The performance of this new approach is compared by several previously developed ensemble models [2] through confusion matrix performance criteria, including hit rate, overestimation, and underestimation. This method is demonstrated by its application to a real case study of UDS located in the northwest of London for performance assessment up to 5hr ahead (i.e., 20 timesteps with 15-min intervals). In total, 140 base-models and 20 stacked models were developed that are stored in the data warehouse to use as real-time early-warning flood overflow forecasting for this case study. These developed models were used through introduced decision three framework that specified stacking blending methodology. Results show that while base models and stacked models suffer from high miss rate, especially for forecasting more than 3hrs ahead (more than 50%), the proposed multi-stacking model could perfectly maintain the miss rate (i.e., sum of over- and under-estimations) of up to 4hr-ahead predictions less than 10%, but this rate dropped to nearly 30% for 5hr-ahead predictions. However, the rate of overflow forecasting remained acceptably near 80% whereas it is recorded to less than 58% for other benchmark models. Using different decision frameworks for determining importance of each stacked model in blending mode of multi-stacking method shows could reduce errors in forecasting rate and take advantage of each model in real-time early warning urban flood forecasting.Peer reviewe

Natural history of colonization with methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus (VRE): a systematic review

Background: No published systematic reviews have assessed the natural history of colonization with methicillin-resistant Staphylococcus aureus (MRSA) or vancomycin-resistant Enterococcus (VRE). Time to clearance of colonization has important implications for patient care and infection control policy. Methods: We performed parallel searches in OVID Medline for studies that reported the time to documented clearance of MRSA and VRE colonization in the absence of treatment, published between January 1990 and July 2012. Results: For MRSA, we screened 982 articles, identified 16 eligible studies (13 observational studies and 3 randomized controlled trials), for a total of 1,804 non-duplicated subjects. For VRE, we screened 284 articles, identified 13 eligible studies (12 observational studies and 1 randomized controlled trial), for a total of 1,936 non-duplicated subjects. Studies reported varying definitions of clearance of colonization; no study reported time of initial colonization. Studies varied in the frequency of sampling, assays used for sampling, and follow-up period. The median duration of total follow-up was 38 weeks for MRSA and 25 weeks for VRE. Based on pooled analyses, the model-estimated median time to clearance was 88 weeks after documented colonization for MRSA-colonized patients and 26 weeks for VRE-colonized patients. In a secondary analysis, clearance rates for MRSA and VRE were compared by restricting the duration of follow-up for the MRSA studies to the maximum observed time point for VRE studies (43 weeks). With this restriction, the model-fitted median time to documented clearance for MRSA would occur at 41 weeks after documented colonization, demonstrating the sensitivity of the pooled estimate to length of study follow-up. Conclusions: Few available studies report the natural history of MRSA and VRE colonization. Lack of a consistent definition of clearance, uncertainty regarding the time of initial colonization, variation in frequency of sampling for persistent colonization, assays employed and variation in duration of follow-up are limitations of the existing published literature. The heterogeneity of study characteristics limits interpretation of pooled estimates of time to clearance, however, studies included in this review suggest an increase in documented clearance over time, a result which is sensitive to duration of follow-up