Spatio‐temporal trends of nutrients and physico‐chemical parameters on lake ecosystem and fisheries prior to onset of cage farming and re‐opening of the Mbita passage in the Nyanza Gulf of Lake Victoria

Many large lake ecosystems are experiencing increasing eutrophication and persistent cyanobacteria‐dominated algal blooms affecting their water quality and ecosystem productivity because of widespread non‐point and point nutrient sources. Accordingly, the present study utilized data of July 2003 and January–February 2004, as well as previous measurements of nutrients and physico‐chemical variables (electrical conductivity, dissolved oxygen, temperature, pH, turbidity and chlorophyll‐a), to characterize the spatial and temporal trends, as a means of better understanding the factors influencing lake environmental conditions, as support tools for long‐term ecosystem management and for better understanding the long‐term trends and effects. Inshore gulf areas were found to represent zones of maximum nutrient concentrations, compared to the deep main lake zones, with significant inter‐parameter correlations. Phosphorus, silicon and chlorophyll‐a concentrations were significantly correlated. Water electrical conductivity was also significantly and positively correlated with soluble reactive silicon (SRSi), alkalinity hardness DO, while exhibiting a negative association with water transparency. Water turbidity and transparency, electrical conductivity, and SRSi concentrations clearly describe a gradient from the gulf into the main lake. For such a shallow gulf, these findings suggest primary productivity is influenced mainly by the availability of nutrients, light transparency and the extent of availability of resuspended nutrients. The increasing eutrophic state of Lake Victoria is a serious concern since it contributes to an increased potential of more frequent occurrences of cyanobacterial blooms, a potential public health risk to both humans and wildlife. Improved understanding of influences from previous fish species introductions and concomitant changes in indigenous fish species, increased lake basin population and anthropogenic activities, water hyacinth resurgences, sustainability of biodiversity, and current interests in cage farming, are among the major concerns and challenges facing the contemporary Lake Victoria. The trends regarding nutrients and physico‐chemical characteristics are intended to support better monitoring efforts and data to promote the lake's ecosystem services and the sustainable management of the lake ecosystem.     

Chemical control of superconducting properties of (Y, Ca)(Sr, Ba)2Cu2.7Ga0.3O7?δ

The partial substitution of Ga at the Cu(1) (chain) sites of the YBa₂Cu₃O₇ structure allows synthesis at ambient pressure of Ba-free analogs, e.g., YSr₂Cu_2.7Ga_0.3O_7– . Materials with this composition have been found to be nonsuperconducting, but superconductivity has been induced by one or more of the following methods: Ca substitutions at the Y site; Ba substitutions at the Sr site; annealing in high-pressure oxygen. The influence of these chemical manipulations onT _c has been monitored and all methods have been found to enhanceT _c . The electronic effects of Ba substitutions have been deduced indirectly using powder neutron diffraction, and such substitutions appear to result in a redistribution of hole density into the Cu(1) sites from the superconducting CuO₂ planes.     

Synthesis, composition, and structure of superconducting (Y, Ca)Sr, Ba)2Cu2GaO7?δ

The superconducting properties of Y_1–y Ca _y Sr₂Cu₂GaO_7– have been examined and related to the Ca content,y, and the use of annealing treatments at 350 bar oxygen. Superconductivity withT _c up to 41 K was found only for high-pressure-annealed samples, and the structural effects of Ca substitution and high-pressure treatment were examined using powder neutron diffraction. Small but significant changes in Cu-Cu and Cu-O distances were found and suggest that the Cu ions are more highly charged in superconducting samples. Partial substitution of Ba for Sr was found to be possible (up to 20%) to give samples which, after annealing in high-pressure oxygen, were superconducting at temperatures up to 68 K.     

A Dynamic Hybrid Decoder Apprroach Using EG-LDPC Codes for Signal Processing Applications

The Low-Density Parity Check (LDPC) codes of Euclidean Geometry (EG) are encrypted and decrypted in numerous ways, namely Soft Bit Flipping (SBF), Sequential Peeling Decoder (SPD), Belief Propagation Decoder (BPD), Majority Logic Decoder/Detector (MLDD), and Parallel Peeling Decoder (PPD) decoding algorithms. These algorithms provide aextensive range of trade-offs between latency decoding, power consumption, hardware complexity-required resources, and error rate performance. Therefore, the problem is to communicate a sophisticated technique specifying the both soft and burst errors for effective information transmission. In this research, projected a technique named as Hybrid SBF (HSBF) decoder for EG-LDPC codes, which reduces the decoding complexity and maximizes the signal transmission and reception. In this paper, HSBF is also known as Self Reliability based Weighted Soft Bit Flipping (SRWSBF) Decoder. It is obvious from the outcomes that the proposed technique is better than the decoding algorithms SBF, MLDD, BPD, SPD and PPD. Using Xilinx synthesis and SPARTAN 3e, a simulation model is designed to investigate latency, hardware utilization and power consumption. Average latency of 16.65 percent is found to be reduced. It is observed that in considered synthesis parameters such as number of 4-input LUTs, number of slices, and number of bonded IOBs, excluding number of slice Flip-Flops, hardware utilization is minimized to an average of 4.25 percent. The number of slices Flip-Flops resource use in the proposed HSBF decoding algorithm is slightly higher than other decoding algorithms, i.e. 1.85%. It is noted that, over the decoding algorithms considered in this study, the proposed research study minimizes power consumption by an average of 41.68%. These algorithms are used in multimedia applications, processing systems for security and information.

     

MESSB–LWE: multi-extractable somewhere statistically binding and learning with error-based integrity and authentication for cloud storage

The concept of cloud envisioned cyber-physical systems is a practical technology that allows users to interact with each other while transferring data in the cloud. In cyber-physical systems, cloud storage utilizes data deduplication techniques to improve the performance of its applications. However, this method exposes sensitive data and causes security risks. Various research related to cloud storage has been conducted. Despite the advantages of this technology, it lacks the necessary security features and high performance. In the proposed method, a victim's virtual computer is moved to the cloud without interfering with the other processes running on the network. It protects against the attacks caused by encrypting the data with a cryptographically binding hash. Post-Quantum Cryptographic techniques, such as lightweight Multi-Extractable Somewhere Statistically Binding and Learning With Error authenticate data sharing protocols (MESSB–LWE), have been used. These allow for safe data sharing across geographically scattered physical devices and clients with lightweight concepts. The numerical analysis of MESSB–LWE is carried out in different stages, and the results show that it has incredible performance and practicality when compared to the literature. Finally, the authors have explored a couple of factors that should be considered for future research work in authentication for securing remote systems in the cloud environment.

     

Characterization and evaluating the mechanical performance of halloysite nanotubes reinforced acrylonitrile butadiene styrene/polycarbonate composites exposed to aggressive environmental conditions

Developing light weight polymer based composites dispersed with novel reinforcements which can function well in the presence of aggressive environments is an active research field in the materials engineering. Hence, in the current work, halloysite nanotubes (1 %, 2 %, 4 %, 6 %, 8 % and 10 % by weight) were reinforced into acrylonitrile butadiene styrene/polycarbonate blend and the role of reinforcing phases on the mechanical performance under aggressive environmental conditions has been evaluated. Hardness was measured as gradually increased in the composites with the increased content of the reinforcements. Impact strength of the composites was observed as increased in the composites up to 4 % reinforcement and further decreased. Increased strength was measured for the composite up to 2 % reinforcement. Ductility of the composites was decreased as reflected form the decreased % of elongation with the higher fraction of reinforcements due to induced brittleness. The composites were exposed to diluted sulfuric acid for 3 h and 6 h at 60 °C and then subjected to tensile loading. With the increased time of exposure, composites with 1 % and 2 % reinforcement exhibited relatively better performance.     

Robust object tracking with background-weighted local kernels

Object tracking is critical to visual surveillance, activity analysis and event/gesture recognition. The major issues to be addressed in visual tracking are illumination changes, occlusion, appearance and scale variations. In this paper, we propose a weighted fragment based approach that tackles partial occlusion. The weights are derived from the difference between the fragment and background colors. Further, a fast and yet stable model updation method is described. We also demonstrate how edge information can be merged into the mean shift framework without having to use a joint histogram. This is used for tracking objects of varying sizes. Ideas presented here are computationally simple enough to be executed in real-time and can be directly extended to a multiple object tracking system.     

Multidroplet Impact Model for Prediction of Residual Stresses in Water Jet Peening of Materials

In this article, a multidroplet impact model, proposed for predicting residual stresses induced on materials subjected to water jet peening, is presented. This approach considers the impact pressure distribution due to high-velocity droplets impinging on the material surface instead of stationary pressure distribution for prediction of residual stresses on water jet-peened surfaces. It makes use of Reichardt's theory for predicting the velocity distribution of droplets and liquid impact theory for predicting the impact pressure and duration of impact of high-velocity droplets. For predicting residual stresses on the surface and subsurface of material subjected to water jet peening, finite element modeling approach was adopted by using transient elastoplastic finite element analysis by considering an impingement of a set of droplets in succession to one another over a certain time period after which this pressure is released. The effectiveness of the proposed approach was demonstrated bv comparing the predicted residual stresses with those predicted by using the single set of droplets approach proposed by Rajesh et al. [6]. Finally, the practical relevance of the proposed approach was shown by comparing the predicted results with the experimental results obtained by water peening of 6063-T6 aluminium alloy.     

Evaluation of a multimode fiber optic low coherence interferometer for path length resolved Doppler measurements of diffuse light

The performance of a graded index multimode fiber optic low coherence Mach-Zehnder interferometer with phase modulation is analyzed. Investigated aspects were its ability to measure path length distributions and to perform path length resolved Doppler measurements of multiple scattered photons in a turbid suspension of particles undergoing Brownian and translational motion. The path length resolution of this instrument is compared with a system using single mode fibers for illumination and detection. The optical path lengths are determined from the zero order moment of the phase modulation peak in the power spectrum. The weighted first moment, which is equal to the average Doppler shift, shows a linear response for different mean flow velocities within the physiological range.