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.     

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.     

Bailout forward contracts for edge-to-edge internet services

Despite the huge success of the Internet in providing basic communication services, its economic architecture needs to be upgraded so as to provide end-to-end guaranteed or more reliable services to its customers. Currently, a user or an enterprise that needs end-to-end bandwidth guarantees between two arbitrary points in the Internet for a short period of time has no way of expressing its needs. To allow these much needed basic services, we propose a single-domain edge-to-edge (g2g) dynamic capacity contracting mechanism, where a network customer can enter into a bandwidth contract on a g2g path at a future time, at a predetermined price. For practical and economic viability, such forward contracts must involve a bailout option to account for bandwidth becoming unavailable at service delivery time, and must be priced appropriately to enable Internet Service Providers (ISPs) manage risks in their contracting and investments. Our design allows ISPs to advertise point-to-point different prices for each of their g2g paths instead of the current point-to-anywhere prices, allowing discovery of better end-to-end paths, temporal flexibility and efficiency of bandwidth usage. We compute the risk-neutral prices for these g2g bailout forward contracts (BFCs), taking into account correlations between different contracts due to correlated demand patterns and overlapping paths. We apply this multiple g2g BFC framework on network models with Rocketfuel topologies. We evaluate our contracting mechanism in terms of key network performance metrics like fraction of bailouts, revenue earned by the provider, and adaptability to link failures. We also explore the tradeoffs between complexity of pricing and performance benefits of our BFC mechanism.     

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.     

Enhanced Phase Stability and Photoluminescence of Eu3+ Modified t-ZrO2 Nanoparticles

Tetragonal ( t ) ZrO₂ nanoparticles have been obtained by a partial Eu³⁺→Zr⁴⁺ substitution, synthesized using a simple oxalate method at a moderate temperature of 650°C in air. The Eu³⁺ additive, 2 mol% used according to the optimal photoluminescence (PL), gives small crystallites of the sample. On raising the temperature further, the average crystallite size D grows slowly from 16 nm to a value as big as 49 nm at 1200°C. The Eu³⁺: t -ZrO₂ nanoparticles have a wide PL spectrum at room temperature in the visible to near-IR regions (550–730 nm) in the ⁵D₀→⁷F_J (Eu³⁺), J =1–4, electronic transitions. The intensity of the ⁵D₀→⁷F₄ group is as large as that of the characteristic ⁵D₀→⁷F₂ group of the spectrum in the forced electric-dipole allowed transitions. The enhanced t -ZrO₂ phase stability and wide PL can be attributed to the combined effects of an amorphous Eu³⁺-rich surface and part of the Eu³⁺ doping of ZrO₂ of small crystallites.     

Electro-dissolution of 30Nb–Ti alloys in methanolic sulfuric acid—Optimal conditions for electropolishing

The electro-dissolution behaviour of a (30 at.%) Niobium–Titanium (NbTi) alloy in non-aqueous methanolic sulfuric acid solution using the rotating disc electrode (RDE) was ascertained. The optimal condition for electropolishing and the mechanism were proposed. The influence of the rotation rate, process temperature and sulfuric acid concentration on the dissolution kinetics was investigated. The dissolution rate (limiting current) increases linearly with increase in rotation rate and follows a Levich behaviour confirming a mass transport controlled process. The temperature dependence in terms of Arrhenius plot renders an activation energy value of E_a = 16.1 kJ mol⁻¹ for the process. The dissolution rate shows a strong dependence on the sulfuric acid concentration (1 M, 3 M and 5 M). Higher sulfuric acid concentrations lead to decreased dissolution rates (limiting current). The dissolution process is mass transport controlled in all concentrations of sulfuric acid. From an electrochemical perspective, a 3 M sulfuric acid was chosen as optimum owing to better controllability of the material removal rate. The dissolving ions are the probable rate limiting species, indicating a compact salt-film mechanism. The average root mean square (RMS) roughness value for an electropolished surface was approximately 10 nm, which is significantly lower than a mechanically polished surface.     

Review on nano-and microfiller-based polyamide 6 hybrid composite: Effect on mechanical properties and morphology

Polyamide 6 (PA6)-based composites are of evolving interest due to its high strength, wear resistance, and barrier properties. The use of binary composites mostly with nanomaterial and glass fibers has been reviewed and presented in literature. However to obtain a balance of properties like stiffness, toughness, and strength along with cost reduction, ternary composites of PA6 have been designed. To achieve the balance, PA6 blend-based composites, with combination of microfiller/nanofiller or PA6 with combination micro-microfiller, PA6 with microfiller/nanofiller and fiber have been designed. The properties of PA6-based ternary hybrid composites depend on type of dispersed phase used, presence of compatibilizer, type of filler used (nanofiller or microfiller or fiber or hybrid) and combination of fillers used. However, a review in this direction is not available in literature. Here, in this study, an overall understanding of various fillers, dispersed phase, and their combinations can be understood along with the discussion on effect of these on tensile properties and morphology of hybrid composite. In this study, an attempt has been made to review the various fillers and dispersed phase and their combinations which have been used in designing the PA6 hybrid composite with good balance of stiffness, toughness, and strength.     

Occurrence and characterization of carbon nanoparticles below the soot laden zone of a partially premixed flame

An experimental study has been performed to detect the occurrence of nanosized carbon particulates below the soot laden zone of a co-flowing partially premixed flame. Samples have been extracted from different points across the flame and passed through DI water. Absorption and fluorescence spectroscopies have been performed with the collected water suspensions. The occurrence of carbon nanoparticles is evident across the inner flame front. In addition, evidence of naphthalene has also been found inside the inner rich premixed flame. The concentration of naphthalene decreases while that of the carbon nanoparticles increases as the inner flame front is reached. The stability of the nanoparticles in the sample has been ensured by observing that the change in fluorescence quantum yield from the sample over a long duration is small. The band gap energy has been evaluated using the absorption data to characterize the likely structures of the particles in the collected suspension. Two kinds of particles having different zones of band gap energy are found in the flame. Dynamic light scattering measurements show that the particle size grows with the increase in height in the lower part of the flame. While, at 3 and 6 mm elevations the particles are observed to be below 2.5 nm in diameter, the particles at 10 mm elevation are found in the size range of 2.5-5.5 nm.     

Design optimization of deep groove ball bearings using crowding distance particle swarm optimization

This paper presents a crowding distance particle swarm optimization technique to optimize the design parameters of deep groove ball bearings. The design optimization problem is multi-objective in nature. The considered objectives are maximizing dynamic and static load bearing capacities and minimizing elasto-hydrodynamic film thickness. The technique is applied to bearings used in transmission system of a tractor for the purpose of farming. Pareto optimal solutions are obtained using the proposed technique. The results obtained from the technique are found to be superior compared with NSGA-II and catalogue values.     

Numerical and experimental study of a shell and tube heat exchanger for different baffles

In the present work, the shell and tube heat exchanger (STHX) is designed based on The Tubular Exchanger Manufacturers Association standards with hot fluid (water) flowing on the shell side and cold fluid on the tube side. A comparison is made between the Nusselt number and friction factor obtained from numerical and experimental results of segmental baffles (SBs) and helical baffles (HB) with different baffle inclinations. The results show that SB provided a higher Colburn factor (j_s) when compared with HBs STHXs (20°, 30°, 40°, and 50°), but shell side pressure drop is lower for 40° HBs STHXs for the same shell side fluid flow rates.