Stratum-Confined Solid-State Reaction (SC-SSR) toward Colloidal Silicon-Based Hollow Nanostructures for Bioapplications

Silicon nanostructures (SiNSs) can provide multifaceted bioapplications; but preserving their subhundred nm size during high-temperature silica-to-silicon conversion is the major bottleneck. The SC-SSR utilizes an interior metal-silicide stratum space at a predetermined radial distance inside silica nanosphere to guide the magnesiothermic reduction reaction (MTR)-mediated synthesis of hollow and porous SiNSs. In depth mechanistic study explores solid-to-hollow transformation encompassing predefined radial boundary through the participation of metal-silicide species directing the in-situ formed Si-phase accumulation within the narrow stratum. Evolving thin-porous Si-shell remains well protected by the in-situ segregated MgO emerging as a protective cast against the heat-induced deformation and interparticle sintering. Retrieved hydrophilic SiNSs (<100 nm) can be conveniently processed in different biomedia as colloidal solutions and endocytosized inside cells as photoluminescence (PL)-based bioimaging probes. Inside the cell, rattle-like SiNSs encapsulated with Pd nanocrystals can function as biorthogonal nanoreactors to catalyze intracellular synthesis of probe molecules through C-C cross coupling reaction.     

Residual UNet with Dual Attention—An ensemble residual UNet with dual attention for multi-modal and multi-class brain MRI segmentation

In this paper, we have proposed a variant of UNet for brain magnetic resonance imaging (MRI) segmentation. The proposed model, termed as Residual UNet with Dual Attention (RUDA), addresses the two significant challenges of UNet: extraction of the complex features with unclear boundaries and the problem of over-segmentation due to the redundancy caused by the skip connection usage. RUDA is constituted upon the residual blocks for extracting the complex structures. It Introduces attention into the skip connections to avoid redundancy and thereby the chance of over-segmentation. Our model segments brain MRI into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) regions, which are considered crucial informative substructures for diagnosing neurological disorders such as Alzheimer's. It has been implemented in an ensemble manner to accommodate the multi-sequence (T1-weighted, IR, and T2-FLAIR) scans. The empirical analysis shows that with an accuracy of 93.80%, RUDA outperforms the two baseline models: UNet (91.37%), ResUNet (91.44%).     

Dual Metal Double Gate Ge-Pocket TFET (DMG-DG-Ge-Pocket TFET) with Hetero Dielectric: DC & Analog Performance Projections

Silicon - This work exclusively illustrates dual-metal double gate Ge pocket tunnel field effect transistor (DMG-DG-Ge pocket TFET) with hetero gate dielectric. This structure includes dual-metal...     

Beta Vulgaris root as a natural food colouring in doughnut: Dough rheological properties and bioactive composition

In the present study, the influence of Beta vulgaris root powder (BVP) incorporated at 0%, 5%, 7.5%, 10% and 12.5% levels on the empirical and fundamental rheological characteristics; dough texture properties; nutritional and bioactive components in the doughnut were carried out. The addition of BVP, decreased the WAC (58.4%–51.2%), DDT (6.19–1.31 min), extensibility (148–95 mm), and springiness (4.56–3.24 N) and viscosity parameters to varying extent. The frequency sweep test indicated that both the dynamic moduli increased and G' was higher than G" at all levels indicating the solid elastic structure of the dough. The dimensional characteristics of the doughnuts indicated a decrease in volume (103.3–85 mL) and an increase in weight (35.8–46.7 g) and compression force (11.6–14.5 N). The sensory studies indicated that 10% BVP incorporated doughnut was highly acceptable with higher dietary fibre content. The higher retention of betacyanin (17.88 mg 100 g⁻¹), betaxanthin (12.9 mg 100 g⁻¹), betanin (6.61 mg 100 g⁻¹), TPC (25.74 mg GAE 100 g⁻¹), TFC (77.08 mg QE 100 g⁻¹) and TAC (28.76 mMTE 100 g⁻¹) was observed.     

Dielectric spectroscopy-based characterisation of different types of Paneer (Indian cottage cheese) in terms of texture,microstructure and functional groups

Different variants of Paneer were prepared with cow milk (CM), buffalo milk (BM), skimmed milk powder (SMP) and blends (40:60, 50:50, 60:40) of SMP with CM/BM. The Paneer composition, texture, microstructure and spread of functional groups were correlated with the dielectric capacitance values. Results depicted a strong correlation (R² > 0.95) between milk used for Paneer making and its proximate composition in terms of the capacitance value, and it was highest for CM followed by BM; 100% SMP Paneer recorded lowest values. Paneer made from blends of SMP and liquid milk had the lowest transmittance value, indicating higher total protein content.     

Mutagens in commercial food processing and its microbial transformation

Food Science and Biotechnology - Mutagens are chemical molecules that have the ability to damage DNA. Mutagens can enter into our body upon consumption of improperly cooked or processed food...     

Position-track-time three-dimensional network model-based improvement for high-speed rail scheduling and operation

The train timetable and station operation plan play a critical role in the high-speed railway (HSR) planning and management. The existing hierarchical optimization methods for the planning process of the HSR would affect the efficiency of train schedules and are often difficult to achieve an optimized scheme. This paper proposes a position-track-time three-dimensional network, which describes the process of train operations in sections and stations at a macroscopic scale, while the track infrastructure including the position of insulation joints in stations are modeled microscopically. The modeled train running times and dwell times are based on standard timetable design values given in full minutes by the China Railway Corporation, while the interlocking times and minimum headway times are not specified explicitly. The problem is formulated as a large-scale 0–1 linear integer programming model, which is solved using an extended branch-and-price algorithm. The effectiveness and precision of the model are verified through a real-world case study on the Beijing–Shanghai HSR line. The results indicate that the proposed model can effectively improve the line capacity by 17.2% while ensuring that there is no conflict between train operations in sections and stations.     

An efficient certificateless key exchange protocol for heterogeneous networks in human-centered IoT systems

Human-centered Internet of things (IoT) systems enable human beings to enjoy the ubiquitous services and play more and more important roles in our life. A common application scenario in human-centered IoT systems is that two distributed wireless devices from heterogeneous networks want to communicate with each other. However, key generation centers (KGCs) from different networks usually use independent security parameters. It is difficult for two users with different security parameters to establish a common session key. We propose a certificateless key exchange protocol for two different devices managed by different KGCs to address the issue. The security of the proposed protocol is conducted in the random oracle model with the hardness assumption of elliptic curve computational Diffie-Hellman (ECDH) problem. The main merits of our protocol include the following: (a) it enables users from heterogeneous networks to establish upon a shared session key, (b) it can solve the key escrow problem, (c) it does not use bilinear pairings and obtains computational efficiency, and (d) it achieves stronger security compared with other related protocols.