Characterisation of anthocyanins from Garcinia indica Choisy

The present study deals with isolation and characterisation of anthocyanins present in Garcinia indica Choisy (popularly known as kokum), which is a potential source of a natural food colourant. The kokum was found to contain a very high concentration of anthocyanins (2.4 g/100 g of kokum fruit), compared to other natural sources. Acid hydrolysis ascertained that this anthocyanin consisted of a single aglycone, i.e., cyanidin. A comparison of saponified and unsaponified fraction indicated that the pigment was not acylated. HPLC, mass and NMR spectroscopy analyses confirmed that the pigment essentially contains two anthocyanins, which were identified as cyanidin 3-glucoside and cyanidin 3-sambubioside.     

Optimization of solid–liquid extraction of phytochemicals from Garcinia indica Choisy by response surface methodology

A central composite rotatable design was employed to study the effect of ultrasound assisted extraction conditions namely sonication amplitude (10–90%), sonication cycle (0.1–1.0 s^?1), solid–liquid ratio (2–10) and extraction time (5–35 min) on the total anthocyanin extraction from Garcinia indica Choisy. Overall extractions of total anthocyanin, acidity and antioxidant activity were considered as response variables. The significant (p < 0.05) response surface models with high coefficients of determination values (R²) ranging from 0.91 to 0.93 were fitted for the experimental data, which indicated that the polynomial response models fitted well for describing the extraction efficiencies of anthocyanin, acidity and antioxidant activity. Based on the design, the optimal conditions for obtaining higher extraction were extraction time 35 min, cycle ranging from 0.44 to 0.48 s^?1, percentage amplitude ranging from 10 to 14%, and solid–liquid ratio 10. The graphical optimization of superimposed contour plots fulfilled the conditions to obtain total anthocyanin (Y₁) ≥ 135 mg/100 g DW, total titratable acidity (Y₂) ≤ 25 g/100 g DW and antioxidant activity (Y₃) ≥ 14.5 M Trolox/100 g DW. The study demonstrated that response surface methodology can be utilized for deriving the optimum conditions for extraction of anthocyanin from G. indica Choisy.     

Hybrid Lead Halide Perovskites for Ultrasensitive Photoactive Switching in Terahertz Metamaterial Devices

The recent meteoric rise in the field of photovoltaics with the discovery of highly efficient solar‐cell devices is inspired by solution‐processed organic–inorganic lead halide perovskites that exhibit unprecedented light‐to‐electricity conversion efficiencies. The stunning performance of perovskites is attributed to their strong photoresponsive properties that are thoroughly utilized in designing excellent perovskite solar cells, light‐emitting diodes, infrared lasers, and ultrafast photodetectors. However, optoelectronic application of halide perovskites in realizing highly efficient subwavelength photonic devices has remained a challenge. Here, the remarkable photoconductivity of organic–inorganic lead halide perovskites is exploited to demonstrate a hybrid perovskite–metamaterial device that shows extremely low power photoswitching of the metamaterial resonances in the terahertz part of the electromagnetic spectrum. Furthermore, a signature of a coupled phonon–metamaterial resonance is observed at higher pump powers, where the Fano resonance amplitude is extremely weak. In addition, a low threshold, dynamic control of the highly confined electric field intensity is also observed in the system, which could tremendously benefit the new generation of subwavelength photonic devices as active sensors, low threshold optically controlled lasers, and active nonlinear devices with enhanced functionalities in the infrared, optical, and the terahertz parts of the electromagnetic spectrum.     

The Extracellular Zn2+ Concentration Surrounding Excited Neurons Is High Enough to Bind Amyloid‐β Revealed by a Nanowire Transistor

The Zn²⁺ stored in the secretory vesicles of glutamatergic neurons is coreleased with glutamate upon stimulation, resulting in the elevation of extracellular Zn²⁺ concentration (). This elevation of regulates the neurotransmission and facilitates the fibrilization of amyloid‐β (Aβ). However, the exact surrounding neurons under (patho)physiological conditions is not clear and the connection between and the Aβ fibrilization remains obscure. Here, a silicon nanowire field‐effect transistor (SiNW‐FET) with the Zn²⁺‐sensitive fluorophore, FluoZin‐3 (FZ‐3), to quantify the in real time is modified. This FZ‐3/SiNW‐FET device has a dissociation constant of ≈12 × 10^?9m against Zn²⁺. By placing a coverslip seeded with cultured embryonic cortical neurons atop an FZ‐3/SiNW‐FET, the elevated to ≈110 × 10^?9m upon stimulation with α‐amino‐3‐hydroxy‐5‐methyl‐4‐isoxazolepropionic acid (AMPA). Blockers against the AMPA receptor or exocytosis greatly suppress this elevation, indicating that the Zn²⁺ stored in the synaptic vesicles is the major source responsible for this elevation of . In addition, a SiNW‐FET modified with Aβ could bind Zn²⁺ with a dissociation constant of ≈633 × 10^?9m and respond to the Zn²⁺ released from AMPA‐stimulated neurons. Therefore, the can reach a level high enough to bind Aβ and the Zn²⁺ homeostasis can be a therapeutic strategy to prevent neurodegeneration.     

Finite dimensional approximation and Newton-based algorithm for stochastic approximation in Hilbert space

This paper presents a finite dimensional approach to stochastic approximation in infinite dimensional Hilbert space. The problem was motivated by applications in the field of stochastic programming wherein we minimize a convex function defined on a Hilbert space. We define a finite dimensional approximation to the Hilbert space minimizer. A justification is provided for this finite dimensional approximation. Estimates of the dimensionality needed are also provided. The algorithm presented is a two time-scale Newton-based stochastic approximation scheme that lives in this finite dimensional space. Since the finite dimensional problem can be prohibitively large dimensional, we operate our Newton scheme in a projected, randomly chosen smaller dimensional subspace.     

Fast adaptive algorithms for abrupt change detection

We propose two fast algorithms for abrupt change detection in streaming data that can operate on arbitrary unknown data distributions before and after the change. The first algorithm, MB-GT\textsf{MB-GT} , computes efficiently the average Euclidean distance between all pairs of data points before and after the hypothesized change. The second algorithm, MB-CUSUM\textsf{MB-CUSUM} , computes the log-likelihood ratio statistic for the data distributions before and after the change, similarly to the classical CUSUM algorithm, but unlike that algorithm, MB-CUSUM\textsf{MB-CUSUM} does not need to know the exact distributions, and uses kernel density estimates instead. Although a straightforward computation of the two change statistics would have computational complexity of O(N ⁴) with respect to the size N of the streaming data buffer, the proposed algorithms are able to use the computational structure of these statistics to achieve a computational complexity of only O(N ²) and memory requirement of O(N). Furthermore, the algorithms perform surprisingly well on dependent observations generated by underlying dynamical systems, unlike traditional change detection algorithms.     

Optimal Reservoir Release Policy Considering Heterogeneity of Command Area by Elitist Genetic Algorithm

A number of models with conventional optimization techniques have been developed for optimization of reservoir water release policies. However these models are not able to consider the heterogeneity in the command area of the reservoir appropriately, due to non linear nature of the processes involved. The optimization model based on genetic algorithm (GA) can deal with the non linearity due to its inherent ability to consider complex simulation model as evaluation function for optimization. GA based models available in literature generally minimize the water deficits and do not optimize the total net benefits through optimal reservoir release policies. The present study focuses on optimum releases from the reservoir considering heterogeneity of the command area and responses of the command area to the releases instead of minimizing only the reservoir storage volumes. An optimization model has been developed for the reservoir releases based on elitist GA approach considering the heterogeneity of the command area. The developed model was applied to Waghad irrigation project in upper Godavari basin of Maharashtra, India. The results showed that 19% increase in the total net benefits could be possible by adopting the proposed water release policy over the present practice keeping same distribution of area under different crops. The model presented in this study can also optimize the crop area under irrigation. It is found that irrigated area can be increased to 50% of ICA (Irrigable Command Area) from the existing 23% with resulting addition to total net benefits by 31%. The effect of adopting the proposed irrigation schedule and increased irrigation areas would be to increase the net benefits to existing farmers.     

The Effect of Faults on Network Expansion

We study the problem of how resilient networks are to node faults. Specifically, we investigate the question of how many faults a network can sustain and still contain a large (i.e., linear-sized) connected component with approximately the same expansion as the original fault-free network. We use a pruning technique that culls away those parts of the faulty network that have poor expansion. The faults may occur at random or be caused by an adversary. Our techniques apply in either case. In the adversarial setting we prove that for every network with expansion a large connected component with basically the same expansion as the original network exists for up to a constant times faults. We show this result is tight in the sense that every graph G of size n and uniform expansion can be broken into components of size o(n) with faults. Unlike the adversarial case, the expansion of a graph gives a very weak bound on its resilience to random faults. While it is the case, as before, that there are networks of uniform expansion that are not resilient against a fault probability of a constant times it is also observed that there are networks of uniform expansion that are resilient against a constant fault probability. Thus, we introduce a different parameter, called the span of a graph, which gives us a more precise handle on the maximum fault probability. We use the span to show the first known results for the effect of random faults on the expansion of d-dimensional meshes.     

On the variational equilibrium as a refinement of the generalized Nash equilibrium

We are concerned with a class of games in which the players’ strategy sets are coupled by a shared constraint. A widely employed solution concept for such generalized Nash games is the generalized Nash equilibrium (GNE). The variational equilibrium (VE) (Facchinei & Kanzow, 2007) is a specific kind of GNE characterized by the solution of the variational inequality formed from the common constraint and the mapping of the gradients of player objectives. Our contribution is a theory that provides sufficient conditions for ensuring that the existence of a GNE implies the existence of a VE; in such an instance, the VE is said to be a refinement of the GNE. For certain games, these conditions are shown to be necessary. This theory rests on a result showing the equality of the Brouwer degree of two suitably defined functions, whose zeros are the GNE and VE, respectively. This theory has a natural extension to the primal–dual space of strategies and Lagrange multipliers corresponding to the shared constraint. Our results unify some known results pertaining to such equilibria and provide mathematical substantiation for ideas that were known to be appealing to economic intuition.     

It won’t happen to me: An assessment of optimism bias in music piracy

Piracy continues to be a threat to the global economy. Previous literature on factors influencing individual’s attitude towards piracy indicates that as perceived risk increases, individuals attitude of acceptance of piracy should decrease. In spite of the increased risks, some people pirate, there has been no explanation for this apparent paradox. We attempt to explain this paradox by using the concept of optimism bias. Results of structural equation modeling using a sample of 219 college students provide evidence that individuals having an optimism bias engage in piracy because they consider themselves to be at lower risk than average compared to a group. Implications for practice and future research avenues are discussed.