Recently, marine-extracted sulfated polysaccharides (SPs) have been the subject of myriad research since they are considered an eco-friendly source of biologically active compounds. Meanwhile, food and pharmaceutical industries are in urgent need to produce natural sugar substitutes and antioxidants as alternatives to synthetic ones which are associated with cytotoxicity and safety issues. This study assesses the potential of using marine SPs obtained via the ultrasonic-assisted extraction of different marine species, to utilize them as antioxidant sugar substitutes. The carbohydrate, total phenolic contents and antioxidant activities, were measured for the SPs extracts of the algal species of Ulva lactuca, Jania rubens and the marine plant mangrove Avicennia marina. These SPs were structurally elucidated by Fourier Transform Infrared (FTIR) spectroscopic and high-performance liquid chromatography (HPLC) analyses. The results revealed that a highest yield percent of SPs was obtained from Ulva lactuca, 5.50 ± 0.25 %. The SPs of Avicennia marina had the highest carbohydrate content, 44 ± 1 % and antioxidant activity, 78.85 ± 0.06 at the 100 μg/mL concentration and 89.50 ± 0.21 at the 250 μg/mL concentration. Meanwhile, the highest phenolic content was exhibited by algal SPs obtained from Jania rubens, 132.60 ± 2.50 mgGa/g. Results also showed that the antioxidant potential of Jania rubens and Avicennia marina can be owed to their high glucose content. This work emphasizes the need to consider sulfated polysaccharides from marine sources for their antioxidant activity and to correlate it with their monosaccharide content to determine the effect of reducing sugar concentration on the antioxidant activity.

Current nanotechnology provides the possibility of creating hybrid nanostructures composed of semiconductor quantum dots and metal nanoparticles. Due to the interaction of excitons with surface plasmons, several optical properties are strongly modified, attracting the scientific attention in quantum dot – metal nanoparticle hybrids, both theoretically and experimentally. A system that has attracted important attention in the literature is the asymmetric, tunneling-controlled, double semiconductor quantum dot, demonstrating interesting optical properties, such as tunneling-induced transparency, slow light, and Autler-Townes splitting, while the pump-probe optical response and the four-wave mixing in this nanostructure gives interesting results. In this study, we theoretically examine the pump-probe optical response in a complex structure composed of an asymmetric double semiconductor quantum dot molecule, which is coupled to a metal nanoparticle via a long-range Coulomb interaction. We aim at the investigation of the modified nonlinear pump-probe optical properties of a double semiconductor quantum dot molecule, due to the excitonic-plasmonic interaction. Starting with the Hamiltonian, in the dipole and the rotating wave approximations, we first derive the density-matrix equations treating the problem in the quasi-static limit, which are solved numerically and obtain the steady state response of the system. Next, we use the results from the density matrix elements to calculate the first-order susceptibility and present the absorption/dispersion spectra for the semiconductor quantum dot and the metal nanoparticle separately, as well as, for the whole hybrid system, as a function of the pump-probe field detuning. The dependence of the spectral response is investigated, while the interparticle distance varies, for different values of the physical quantities introduced in the problem, including the electron-tunnelling coupling rate, the energy difference between the upper states of the semiconductor quantum dot molecule and the pump-field detuning.

We establish a statistical-measures approach to describe the spectral-spatial analysis of the dynamical atom-field couplings associated with two-pair of pulses propagation in multilevel atomic media. The statistical measures are functional measures that depend on the collective coupling as well as on the eigenvalues of the Nonlinear-Liouville equation. The Nonlinear-Liouville equation is a nonlinear evolution equation which is a second-order differential equation in time. It describes the multi-wave mixing process within the atomic system, as well as coherent oscillations. The proposed spectral estimators prevail spatial multi-peak structure, which depends on the reduction or the enhancement of an effective Rabi-frequency. Decomposition of collective oscillations provides an intuitive guess to special-weight of the field's area. We introduce two functional wavelets to simulate the atomic polarization response. One of these functionals exposes the dependence on the multicomponent sine-Gordon equation for the atomic polarization, which is adequate at relatively small propagation distances. The second one is composed of combined sine and cosine functionals on the area of the fields. The cosine functional reflects the significance of the atomic inversion on the polarization response to electromagnetic field excitations. The proposed functional-wavelets inducts new sources for soliton features to the transition-radiation propagation associated with Maxwell-Bloch equations.

In the present study, a combination of experimental techniques is studied to monitor the state of fresh concrete inside composite formworks. The aim is to acquire information about the stiffness of the concrete for which safe removal of the formworks can be done. Determining early age properties of concrete is important not only for ensuring safety on construction sites but also for presenting economic advantages. Removal of formworks in the appropriate time avoids delays in the construction works and allows the reuse of formworks in an efficient manner and thus reduce the associated cost. Experimental monitoring was complemented by numerical simulations to clearly investigate the ultrasonic propagation in fresh concrete and how the hydration process affects this propagation. The experiments showed promising results in monitoring the increase of stiffness in the concrete inside the formwork through an one-sided measurement. Strain measurements carried out at different heights of a cylindrical formwork gave information about the pressure distribution on the formwork to ensure limit stress values are not reached. In addition, monitoring the strain variation confirmed the trends of increase in the stiffness by giving indications about the shrinkage and thermal expansion of concrete.

Metallic nanoparticles, due to their reduced size and high surface area, have unique properties that facilitate their application, with excellent results, in various scientific fields and allows an easy functionalization of their surface with a variety of ligands. Noble metallic nanoparticles play a special role in nanomedicine due to their proved antibacterial, antifungal and strong antioxidant activity. These metallic nanoparticles can be prepared using both conventional and unconventional routes and, in the last decades, the methods involving plants and their aqueous extracts are constantly and successfully replacing expensive and time - consuming conventional chemical methods. This paper describes the one - pot green synthesis of silver nanoparticles (AgNPs) and gold nanoparticles (AuNPs) from aqueous plant extracts and corresponding metallic salts under different time and temperature conditions. Both silver and gold nanoparticles are green synthesized from plants with important pharmacological benefits to human health: Hyssopus (Hyssopus officinalis), European goldenrod (Solidago virgaurea) and Knotgrass (Polygonum aviculare) and their synthesis is monitored by recording the UV - Vis spectra at specific time intervals: 0s, 5 min, 15 min, 30 min, 1 hour and 24 hours in order to evaluate their stability in time. FTIR spectra were used for the specific determination of functional groups and DLS was used to determine the nanometer scale of the particles. Also, antioxidant activity was evaluated using the DPPH method for both silver and gold nanoparticles and compared to that of the crude aqueous extracts.

Currently, there is an increased interest among scientists in laser-induced methods (LIPAA, LIBDE, LIMP) for optical materials processing. The plume is formed due to the interaction of laser radiation transmitted through the glass sample with an absorbing target. In particular, our team is working on laser-induced microplasma (LIMP) glass processing method development, which is realized by a plasma plume action arising at the interface of a carbon-based target and an optically transparent sample. Basically, the plasma plume can be considered as a spot tool that forms micro and nano-dimensional relief on the surface of a transparent sample. This tool possesses some characteristics to be investigated: geometry, divergence, and temperature. Detailed knowledge of these characteristics will improve the processing results.

Here, we report on a detailed experimental study of glass processing by LIMP. The results are supported with calculation of a laser beam distortion by the microlens formed on the glass backside. This distortion affects on the plasma plume inducing radiation spot, and as a result, reduce the efficiency and accuracy of glass processing. The study contributes to understanding the importance of experimental conditions - air gap, focus plane position, to improve the quality of the indirect laser-plasma method.

A spell checker is a tool used for analyzing and validating spelling mistakes in the text. Recently, the role of a spell checker has diversified, and it is also used to suggest possible corrections to the detected spelling mistakes. Tamil is one of the oldest surviving and international spoken languages of the world, and it is grammatically very rich. Grammar is vital for effective communication and information transmission. However, learning the language rules and the old teaching methodology becomes a challenge for the researchers. The amalgamation of computer and language using natural language processing (NLP) provides a solution to this problem. In this paper, an advanced NLP technique is used to detect wrongly spelled words in the Tamil language text, and to provide possible correct word suggestions and the probability of occurrence of each word in the corpus. The proposed model recommends correct suggestions for the misspelled words using the minimum edit distance (MED) algorithm, which is customized for the Tamil vocabulary. A distance matrix is created between the misspelled word and all possible permutations of the word. Dynamic programming is used for calculating the least possible changes needed to correct the misspelled words, and suggesting the most appropriate words as the corrections.

In recent times, soil erosion has become one of the major environmental issues considering large scale anthropogenic activities and frequent extreme weather events globally. These activities and events cause the wearing away of top soil, initiating loss in agricultural land, and triggering disasters like landslides in the hilly regions. So, such regions demand soil conservation measures such as plantation, and construction of check dams. Due to limited resources in developing countries like India, prioritization of land-based on susceptibility to soil erosion makes the implementation of these measures efficient. In the present study, the openly accessible TanDEM-X 90m DEM and TOPSIS-AHP ensemble model are used for prioritization of Upper Kosi Watershed based on soil erodibility. This watershed having fifth (5^th) order perennial Kosi river is a showcase for different landscapes, biodiversity, micro-climate, and hydrogeology. TanDEM-X DEM is preprocessed for stream network generation and catchment delineation which is further used for extraction of 10 morphometric attributes (MAs) of each sub-watershed. AHP model is used for calculating the weights of MAs. AHP model concludes that Watershed slope, Stream frequency, and Drainage density play a greater role in soil erosion as compared to other MAs. Morphometric parameters and its weightage is utilized in the execution of the TOPSIS model to calculate the closest coefficient for each sub-watershed. Further, these closest coefficient is classified into low (0.147-0.167), medium (0.167-0.326), and high (0.326-0.794) susceptible zones for prioritization of sub-watershed based on the geometric mean method. This study highlights that Upper Kosi watershed contains 4.73%, 38.79%, 56.48% of its area in high, medium, and low susceptible zone respectively. The result can assist the decision-makers and planners in choosing suitable regions depending on the available resources for conservation measures in Upper Kosi watershed.

Principal component analysis (PCA) is a widespread technique for the analysis of multivariate data, which finds applications in the fields of machine learning and artificial intelligence, to name a few, and is commonly used for data compression and denoising [1]. Standard PCA seeks to calculate the subspace that minimizes the Euclidean distance (L2-norm) of the data points to it. Unfortunately, PCA is extremely sensitive to the presence of large outliers in the data. Recently, the L1-norm has been proposed as an alternative criterion to classical L2-norm in PCA, drawing considerable research interest on account of its increased robustness to outliers [2], [3].

The proposed contribution shows that, when combined with a whitening preprocessing step, L1-norm based PCA is endowed with discriminative power and can perform data classification in an unsupervised manner, i.e., sparing the need for labelled data. By minimizing the L1-norm in the feature space, the technique mimics the action of common spatial patterns (CSP), a supervised feature extraction method used in brain computer interfaces. This result is of theoretical interest and opens new interesting research perspectives for L1-PCA. Furthermore, it enables us to perform classification using algorithms for optimizing the L1-norm, which inherit the improved robustness to outliers of the L1-norm criterion. Several numerical experiments will confirm the theoretical findings.

REFERENCES

[1] I. T. Jolliffe. Principal component analysis. Springer, New York, NY, 2002.
[2] N. Kwak. Principal component analysis based on L1-norm maximization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(9):1672–1680, Sep 2008.
[3] Panos P. Markopoulos, George N. Karystinos, and Dimitris A. Pados. Optimal algorithms for L1-subspace signal processing. IEEE Transactions on Signal Processing, 62(19):5046–5058, Oct 2014.

Abstract:

The antibiotic Ciprofloxacin HCl (CPH) is a representative example of pharmaceutical contaminants of emerging concern which are frequently released in wastewater effluents and can cause hazardous health effects. In this work, we investigate the potential of utilizing porous polymeric membranes incorporating metal nanoparticles for removing CPH from water. In this regard, polylactic acid membranes were impregnated in situ with single, binary and tertiary systems of nanoparticles of cobalt, copper and nickel, among others. Membranes loaded with cobalt exhibited the best performance among all the examined membranes. They yielded removal efficiencies above 80% at an initial CPH concentration range of 10-50 ppm and pH 6.5, thus exceeding those of the bare membranes by about 1.3 times under the same conditions. As confirmed by Brunauer, Emmet and Teller (BET) analysis, the incorporation of cobalt nanoparticles into the mesoporous membranes increased their surface area and pore volume by 5 and 10 times, respectively. Thermogravimetric analysis (TGA) showed that cobalt nanoparticles had no catalytic influence on the dissociation of the membrane polymeric chains. Fourier Transform Infra-red (FTIR) and zeta potential measurements suggested that binding could possibly occur via physical along with catalytic degradation.