Endosulfan induced biochemical changes in nitrogen-fixing cyanobacteria

Pesticide contamination in aquatic ecosystem including paddy fields is a serious global environmental concern. Cyanobacteria are also affected by pesticides as non- target organism. For better exploitation of cyanobacteria as biofertiliser, it is indispensable to select tolerant strains along with understanding of their tolerance. Three cyanobacterial strains viz. Aulosira fertilissima, Anabaena variabilis and Nostoc muscorum were studied for their stress responses to an organochlorine pesticide 'endosulfan' with special reference to oxidative stress, role of proline and antioxidant enzymes in endosulfan induced free radical detoxification. Reduction in growth, photosynthetic pigments and carbohydrate of the test microorganisms were accompanied with increase in their total protein, proline, malondialdehye (MDA), superoxide dismutase (SOD), ascorbate peroxidase (APX) and catalase (CAT) in higher endosulfan doses. Increased amount of MDA is indicative of formation of free radicals, while increased level of CAT, APX, SOD and proline indicated their involvement in free radical scavenging mechanism. In lower concentrations, test pesticide showed increase in photosynthetic pigments. Order of tolerance was Nostoc muscorum>Anabaena variabilis>Aulosira fertilissima.     

Influence of electrical discharge machining parameters on cutting parameters of carbon fiber-reinforced plastic

Today the use of high-strength carbon fiber-reinforced plastics (CFRP) composite as a material for many engineering applications is showing an increasing demand in the industry. These composites are replacing the traditional use of steel because they offer many advantages such as very light weight, high strength, and high stiffness associated with good corrosion-resistant properties. Unfortunately, there is little technological knowledge on the electrical discharge machining (EDM) process of high-strength composite materials, especially about the CFRP. In this work, a study has made into the possibility of using EDM process as a means of machining CFRP composite. Various cutting conditions such as peak current, pulse-on time, pulse-off time and open-circuit voltage were selected to perform electrical discharge machining. The effect of electrode rotation was also studied. Optimum cutting conditions and machine settings for EDM were chosen for machining CFRP composites.     

A new design approach for dual‐band patch antenna serving Ku/K band satellite communications

A printed planar antenna with simple and intelligent geometrical structure has been proposed for Ku/K band satellite communication systems. The radiating patch of the antenna is formed by cutting rectangular slots and extending the radiating element to some extent. The final design of the antenna with optimized parameters is fabricated on ceramic–polytetrafluoroethylene substrate materials of dielectric constant ε_r = 10.2. The antenna is excited through a microstrip feed line and has reduced ground plane that covers only the non‐radiating portion of the antenna. The reduced complexity of the antenna is easy to fabricate and has overall dimension of 40 × 35 × 1.905 mm³. The results from experimental analysis show that the proposed antenna can guarantee a wide bandwidth of 12.0 to 16.4 GHz at lower band, and the upper band covers the frequency in the range of 17.53 to 19.5 GHz. The antenna has achieved appreciable gain in the range of 3.14 to 4.68 dBi for lower band and 2.03 to 3.65 dBi for upper band. The proposed antenna has offered almost symmetrical and directional radiation pattern that is essentially suitable for serving Ku/K band satellite applications. Copyright © 2015 John Wiley & Sons, Ltd.     

OpenSim: open-source software to create and analyze dynamic simulations of movement

Dynamic simulations of movement allow one to study neuromuscular coordination, analyze athletic performance, and estimate internal loading of the musculoskeletal system. Simulations can also be used to identify the sources of pathological movement and establish a scientific basis for treatment planning. We have developed a freely available, open-source software system (OpenSim) that lets users develop models of musculoskeletal structures and create dynamic simulations of a wide variety of movements. We are using this system to simulate the dynamics of individuals with pathological gait and to explore the biomechanical effects of treatments. OpenSim provides a platform on which the biomechanics community can build a library of simulations that can be exchanged, tested, analyzed, and improved through a multi-institutional collaboration. Developing software that enables a concerted effort from many investigators poses technical and sociological challenges. Meeting those challenges will accelerate the discovery of principles that govern movement control and improve treatments for individuals with movement pathologies.     

Highly ordered nanowire arrays on plastic substrates for ultrasensitive flexible chemical sensors

The development of a robust method for integrating high-performance semiconductors on flexible plastics could enable exciting avenues in fundamental research and novel applications. One area of vital relevance is chemical and biological sensing, which if implemented on biocompatible substrates, could yield breakthroughs in implantable or wearable monitoring systems. Semiconducting nanowires (and nanotubes) are particularly sensitive chemical sensors because of their high surface-to-volume ratios. Here, we present a scalable and parallel process for transferring hundreds of pre-aligned silicon nanowires onto plastic to yield highly ordered films for low-power sensor chips. The nanowires are excellent field-effect transistors, and, as sensors, exhibit parts-per-billion sensitivity to NO2, a hazardous pollutant. We also use SiO2 surface chemistries to construct a 'nano-electronic nose' library, which can distinguish acetone and hexane vapours via distributed responses. The excellent sensing performance coupled with bendable plastic could open up opportunities in portable, wearable or even implantable sensors.     

Study of three‐dimensional natural convection and entropy generation in an inclined solar collector equipped with partitions

Three‐dimensional natural convection in an inclined solar collector equipped with partitions has been investigated numerically. The presence of partitions improves the performances of the collector by increasing the heat transfer near the absorber. A parametric study was done for various partitions length and Rayleigh numbers, while Prandtl number and inclination angle were fixed at 0.71 and 45°, respectively. Results are reported in terms of isosurfaces of temperature, isotherms, particles trajectories, velocity vector projection, average Nusselt number along the absorber plate and entropies generation contours.     

A qualitative investigation on the importance of boundary layer in pervaporation separation of an aqueous organic reaction

The importance of boundary layer was investigated for the hydrolysis of ethyl acetate using a dense standard poly(vinyl alcohol) (PVA) membrane. A resistance in a series model approach was used to study the effect of a boundary layer for the permeation of aqueous organic mixtures involved in the study. The initial feed mixture consisted of 10% water (H₂O), 40% ethyl acetate (EA), 50% acetic acid (AA), and 0% ethanol (E) (all weight percentage basis). The experiments were conducted at 65°C. The amount of all species in the feed reservoir was found to decrease with time. Selectivity calculations based on a resistance in the series model approach indicates that the boundary layer contributes to selective permeation of aqueous organic compounds. © 1998 John Wiley & Sons, Inc. J Appl Polym Sci 70: 2361–2369, 1998     

Time-based DDoS attack detection through hybrid LSTM-CNN model architectures: An investigation of many-to-one and many-to-many approaches

Internet data thefts, intrusions and DDoS attacks are some of the big concerns for the network security today. Detection of these anomalies, is gaining tremendous impetus with the development of machine learning and artificial intelligence. Even now researchers are shifting the base from machine learning to the deep neural architectures with auto-feature selection capabilities. We in this paper propose multiple deep neural network architectures which can select, co-learn and teach the gradients of the neural network by itself with no human intervention. This is what we call as meta-learning. The models are configured in both many to one and many to many design architectures. We combine long short-term memory (LSTM), bi-directional long short-term memory (BiLSTM), convolutional neural network (CNN) layers along with attention mechanism to achieve the higher accuracy values among all the available deep learning model architectures. LSTMs overcomes the vanishing and exploding gradient problem of RNN and attention mechanism mimics the human cognitive attention that screens the network flow to obtain the key features for network traffic classification. In addition, we also add multiple convolutional layers to get the key features for network traffic classification. We get the time series analysis of the traffic done for the possibility of a DDoS attack without using any feature selection techniques and without balancing the dataset. The performance analysis is done based on confusion matrix scores, that is, accuracy, false alarm rate (FAR), sensitivity, specificity, false-positive rate (FPR), F1 score, area under curve (AUC) analysis and loss functions on well-known public benchmark KDD Cup'99 data set. The results of our experiments reveal that our models outperform existing techniques, showing their superiority in performance.     

Hydrological Delineation of Homogeneous Regions in Tunisia

An innovative method for hydrological delineation of homogeneous regions in Tunisia is presented. The approach considered is based on the shape of the empirical Cumulative Distribution Function (CDF) and similarities of physiographic and climatic characteristics. Based on annual flood data of 49 hydrometric stations, with record lengths ranging from 10 to 100 years, spatial trends of the shape of the CDF were employed to identify mixed processes in the flood series. This resulted in dividing the study area into mixture and non-mixture zones. Hydrologic homogeneity of the delineated regions was tested by L (Linear) moment-based statistical tests. The exercise resulted in dividing Tunisia into 10 homogeneous regions, where mixed flood processes haven't been recognized.