Recent Advances in Boron Nitride Based Hybrid Polymer Nanocomposites

Boron nitride (BN) is an eminent inorganic compound having many interesting characteristics such as improved oxidation resistance, mechanical strength, good thermal conductivity (TC), higher bandgap, high chemical stability, thermal stability, high hydrophobicity, and electrical insulation. The use of BN as a filler in polymers is a well-established strategy to tailor the properties of polymer composites. Recent studies depict an interesting urge to reap the synergistic effect of various nanofillers with BN in the form of hybrids. Hence the consolidation of the works on BN based hybrid fillers would definitely attract researchers so that these new filler systems could be transformed into useful polymer nanocomposites in future. This review article focuses on the synthesis and characterization of various boron nitride based hybrids in detail. Moreover, the review also throws light on different BN hybrid reinforced polymer nanocomposites (PNCs) and their thermal, electrical, electronic as well as biomedical applications in a detailed manner. Thus the review anticipates serving as a tool toward understanding the recent trends in the field of boron nitride hybrid based ternary polymer composites.     

Differential response of glaciers with varying debris cover extent: evidence from changing glacier parameters

Supraglacial debris (SGD) cover on mountain glaciers is known to greatly influence various glacier processes and alter their response to climate change. In this study, vital glacier parameters of five glaciers with varying debris coverage (about 7–26%), located in Zanskar basin, Ladakh Himalaya, were monitored using Landsat imagery (from 1977 to 2013) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) global digital elevation model (GDEM). Results reveal how varying amounts of SGD induce categorically distinct responses on glaciers, sharing same geographical settings. The clean glaciers (CG) in the area were found to have higher retreat rates (about 8–19 m year^?1), comparable areal shrinkage (about 13–15%), higher accumulation area ratios (AARs) (>0.5), rapid increase in SGD (about 1.6–3.0-fold), and association with increasing numbers of peri- and proglacial lakes (2–8 per glacier). The debris-covered glaciers (DCG) showed minimal frontal changes (about 2–5 m year^?1), higher areal shrinkage (about 14–21%), low AARs (<0.5), slow SGD changes (about ≤1.2-fold), and association with increasing numbers of peri- and supraglacial lakes (SGLs) (2–39 per glacier). Moreover, while changes in SGD had a strong negative correlation with changes in glacier area, retreat rates, and AAR, they were positively related with increase in area of SGLs.     

Selection of a network of large lakes and reservoirs suitable for global environmental change analysis using Earth Observation

The GloboLakes project, a global observatory of lake responses to environmental change, aims to exploit current satellite missions and long remote-sensing archives to synoptically study multiple lake ecosystems, assess their current condition, reconstruct past trends to system trajectories, and assess lake sensitivity to multiple drivers of change. Here we describe the selection protocol for including lakes in the global observatory based upon remote-sensing techniques and an initial pool of the largest 3721 lakes and reservoirs in the world, as listed in the Global Lakes and Wetlands Database. An 18-year-long archive of satellite data was used to create spatial and temporal filters for the identification of waterbodies that are appropriate for remote-sensing methods. Further criteria were applied and tested to ensure the candidate sites span a wide range of ecological settings and characteristics; a total 960 lakes, lagoons, and reservoirs were selected. The methodology proposed here is applicable to new generation satellites, such as the European Space Agency Sentinel-series.     

Ferrimagnetic resonance and low temperature transition in Ni- and Co-substituted powder magnetite

The effects of nickel and cobalt substitution on ferrimagnetic resonance in high-purity magnetite powder have been investigated. The low-temperature transition temperature and damping parameter, , are found to decrease with increasing solute additions. The linewidth, H, varies in proportion to the anisotropy field of the ferrites, narrowing with increasing nickel content but broadening with increasing cobalt content. Theg factor increases with the dopant concentration, passing through a maximum around room temperature. Decreasing the deviation from stoichiometry by appropriate annealing decreases the transition temperature shift but slightly increases H, g and .     

The control function of management

The control function of management can be a critical determinant of organizational success. Most authors discuss control only through feedback and adjustment processes. This article takes a broader perspective on control and discusses the following questions: What is good control? Why are controls needed? How can good control be achieved? If multiple control strategies are feasible, how should the choice among them be made?     

Fabrication of nanoscale tungsten tip arrays for scanning probemicroscopy-based devices

A new fabrication process for nanoscale tungsten tip arrays was developed for scanning probe microscopy-based devices. It is suitable to make a huge array on a device chip and is potentially compatible with CMOS technology. In this study, tungsten was selected as a tip material because of its hardness and conductivity. The newly developed fabrication process mainly consists of several important techniques: a combination of optical lithography and electron beam (EB) lithography to reduce the total exposure time with high resolution and chromium/tungsten/chromium (Cr/W/Cr) sandwich deposition and etching in which the first chromium layer is used as a mask and a second one is used as an etch stop. A periodic array of dots in an EB resist with a spot diameter of less than 50 nm was obtained by a combination of optical lithography and EB lithography with a positive resist (polymethylmethacrylate) in which all processing conditions were optimized carefully. A thin and uniform chromium film, deposited by ion-beam sputtering, allowed the use of thin polymethylmethacrylate (PMMA) film which led to the high resolution. The conditions of dc magnetron sputtering were also optimized in order to deposit a densely packed and low-resistivity film. The resulting tungsten tip arrays had a cylindrical shape with diameters of less than 60 nm and heights of 300 nm     

Artificial neural network-driven federated learning for heart stroke prediction in healthcare 4.0 underlying 5G

In recent years, smart healthcare, artificial intelligence (AI)-aided diagnostics, and automated surgical robots are just a few of the innovations that have emerged and gained popularity with the advent of Healthcare 4.0. Such technologies are powered by machine learning (ML) and deep learning (DL), which are preferable for disease diagnosis, identifying patterns, prescribing treatments, and forecasting diseases like stroke prediction, cancer prediction and so forth. Nevertheless, much data is needed for AI, ML, and DL-based systems to train effectively and provide the desired outcomes. Further, it raises concerns about data privacy, security, communication overhead, regulatory compliance and so forth. Federated learning (FL) is a technology that protects data security and privacy by limiting data sharing and utilizing model information of distributed systems to enhance performance. However, existing approaches are traditionally verified on pre-established datasets that fail to capture real-life applicability. Therefore, this study proposes an AI-enabled stroke prediction architecture consisting of FL based on the artificial neural network (ANN) model using data from actual stroke cases. This architecture can be implemented on healthcare-based wearable devices (WD) for real-time use as it is effective, precise, and computationally affordable. In order to continuously enhance the performance of the global model, the proposed FL-based architecture aggregates the optimizer weights of many clients using a fifth-generation (5G) communication channel. Then, the performance of the proposed FL-based architecture is studied based on multiple parameters such as accuracy, precision, recall, bit error rate, and spectral noise. It outperforms the traditional approaches regarding accuracy, which is 5% to 10% higher.     

Remote Measurement of Eye Direction Allowing Subject Motion Over One Cubic Foot of Space

The remote oculometer is a new instrument for the remote measurement of eye direction and pupil diameter. The electrooptical sensor unit is located several feet from the subject, who is free to move the eye being sensed throughout 1 ft3 of space. The video processing is performed in real time by a standard minicomputer. The oculometer processor (minicomputer) provides automatic calibration and linearization to each subject and can, supply the output eye-direction information in the form of either fixation-point coordinates on any specified fixation plane, azimuth and elevation, or direction cosines.The oculometer measures line-of-sight to an accuracy of 1° for eye rotation angles, relative to the sensor unit, of from 0° to + 30° elevation and from -30 ° to + 30 ° azimuth.