Search

A 2 mm thin layer of wet Spirulina platensis biomass was dried using two methods: refractance window drying (RW) and combined RW and FIR drying (RWF). The effect of drying temperature (40–60 °C) and proximity to FIR heaters (5 and 10 cm) was evaluated on falling rate drying characteristics. The moisture (Deff) and thermal (α) diffusivity coefficients were obtained in the range 1.728 × 10−8 to 5.289 × 10−9 and 1.322 × 10−8 to 4.169 × 10−9 m2 s−1, respectively (R2, 0.921–0.984). RW drying at ≥50 °C caused loss of color, phytopigments, and lipid peroxidation. At 40 °C, RW drying led to a long drying period (300.50 ± 3.53 min), poor drying rate (0.039 ± 0.002 g-H2O/min), lowest Deff and α (5.289 × 10−9 and 4.169 × 10−9 m2 s−1), and chlorophyll loss (32.2%). Combined RW and FIR drying at 40 °C and 5 cm proximity (RWF40-5cm) reduced drying time (15.1%), increased drying rate (27.8%), improved α (15%), and Deff (14.9%). RWF40-5cm dried biomass showed excellent retention of color (ΔE = 4.64 ± 1.32), protein (93.8%), γ-linolenic acid (90.1%), chlorophyll (87.9%), and phycocyanin (86.7%) from freeze-dried biomass (FD). Low-temperature RWF40-5cm drying could be a potential alternative to freeze-drying for effective and safe drying of heat-sensitive Spirulina platensis biomass. [ABSTRACT FROM AUTHOR]

This paper presents a comparative analysis of bioinspired algorithms employed on a PV system subject to standard conditions, under step-change of irradiance conditions, and a partial shading condition for tracking the global maximum power point (GMPP). Four performance analysis and comparison techniques are artificial bee colony, particle swarm optimization, genetic algorithm, and a new metaheuristic technique called jellyfish optimization, respectively. These existing algorithms are well-known for tracking the GMPP with high efficiency. This paper compares these algorithms based on extracting GMPP in terms of maximum power from a PV module running at a uniform (STC), nonuniform solar irradiation (under step-change of irradiance), and partial shading conditions (PSCs). For analysis and comparison, two modules are taken: 1Soltech-1STH-215P and SolarWorld Industries GmbH Sunmodule plus SW 245 poly module, which are considered to form a panel by connecting four series modules. Comparison is based on maximum power tracking, total execution time, and minimum number of iterations to achieve the GMPP with high tracking efficiency and minimum error. Minitab software finds the regression equation (objective function) for STC, step-changing irradiation, and PSC. The reliability of the data (P-V curves) was measured in terms of p value, R, R 2 , and VIF. The R 2 value comes out to be near 1, which shows the accuracy of the data. The simulation results prove that the new evolutionary jellyfish optimization technique gives better results in terms of higher tracking efficiency with very less time to obtain GMPP in all environmental conditions, with a higher efficiency of 98 to 99.9% with less time of 0.0386 to 0.1219 sec in comparison to ABC, GA, and PSO. The RMSE value for the proposed method JFO (0.59) is much lower than that of ABC, GA, and PSO. [ABSTRACT FROM AUTHOR]

The increasing demand for electrical energy is a result of advancing technologies and changing lifestyles worldwide. Meeting this escalating energy need poses a substantial challenge, especially the difficulty in constructing new conventional power plants due to limited fossil fuel resources. To address this, demand-side management (DSM) in smart grid (SG), integrated with solar photovoltaic energy (SPE) have emerged as a crucial tool for effectively managing electricity demand, ensuring flexibility and reliability. DSM achieves optimal electricity utilization by rescheduling the operation schedules of consumer appliances and carefully adjusting their demand profiles. Integrating DSM into a smart grid framework is highly advantageous for the power industry's pursuit of sustainable energy goals. While various heuristic-based optimization techniques have been employed for DSM, the focus on SPE has been limited to small-scale residential loads. This study utilizes the Ant Colony Optimization (ACO) algorithm to tackle a day ahead DSM minimization problem, considering SPE in areas with large number of appliances. The DSM minimization problem falls into the category of discrete combinatorial problems, making it well-suited for ACO optimization. The self-healing, self-protection, and self-organizing attributes of ACO make it particularly effective for DSM solutions. Residential, commercial, and industrial loads, with and without SPE integration, are considered to demonstrate the efficacy of the proposed ACO algorithm. Simulation results are compared with other studies in the literature, including Evolutionary Algorithm (EA), Moth Flame Optimization (MFO), and Bacterial Foraging Optimization (BFO), in terms of reducing consumer's cost of energy (CCE) and utility peak load (UPL). The findings indicate that the proposed ACO algorithm outperforms the other algorithms considered in the current context. [ABSTRACT FROM AUTHOR]

Accurate parameter identification plays an integral role in the modeling of an optimized solar module which in turn helps in the error-free prediction of its output. Five important parameters: the photoelectric current (Iph), ideality factor(α), saturation current (Io), series resistance (Rs), and shunt resistance (Rsh) are required for the accurate modeling of the PV cells/modules and need to be extracted as these parameters are not provided by the manufacturer in the datasheet. This paper proposes a new metaheuristic jellyfish optimization (JFO) algorithm for the parameter extraction of a solar module. The JFO algorithm achieves the optimal solution without being trapped in local solutions in less time. The parameter extraction using the JFO algorithm is done on two different solar modules i.e., Soltech-1STH-215P and PWP-201. The results are compared in terms of extracted parameters (Iph, α, Io, Rs, and Rsh) with the well-known optimization techniques like PSO, GA, and others available in the literature and with the manufacturer I–V and P–V characteristics. The proposed technique I–V and P–V characteristics are validated at different environmental conditions and are found to be similar to that of PSO and GA. It is also observed that the extracted parameters obtained using JFO are comparable with the other twenty-two techniques, and the proposed technique is one of the highly efficient techniques that can be utilized for parameter extraction of PV modules and to predict solar cell characteristics for all commercial modules without setting up any experimental measurements. MATLAB/simulation software is used for implementation and performance validation. [ABSTRACT FROM AUTHOR]

When tracking the peak power point in PV systems, incremental conductance is the most common technique used. This approach preserves the first trap in the local peak power point, but it is unable to quickly keep up with the ever-changing peak power point under varying irradiance and temperature conditions. In this paper, the authors propose a hybrid algorithm, combining an artificial ecosystem optimizer and an incremental-conductance-based MPPT to solve these issues of traditional MPPT under varying irradiance and temperature conditions. The proposed hybrid algorithm has been applied to three scenarios, namely the constant irradiance condition, the varying irradiance condition, and the varying temperature condition. Under the constant irradiance condition, the PV array is maintained at a temperature of 25 °C and an irradiance of 1000 W / m 2 . The voltage of the DC link of the neutral-pointed-clamped inverter is maintained at 1000 V. Under the varying irradiance condition, the irradiance of the PV array is increased from 400   W / m 2   to 1000 W / m 2 with a step size of 0.2 s. The same step size is maintained while decreasing the irradiance level from 1000 W / m 2 to 400 W / m 2 ,   with a step change of 0.2 s. However, the temperature is maintained at 25 °C. Under the varying temperature condition, the temperature of the PV array varies from 35 °C, 25 °C, 15 °C, 10 °C, 15 °C, 25 °C, and 35 °C with a step size of 0.2 s, and the irradiance is maintained at 1000   W / m 2 . The DC link voltage in all three conditions is maintained at 1000 V, which confirms that the hybrid algorithm has been able to vary the duty cycle of the pulse wave modulation generator in such a manner that the variable DC voltage produced by the PV array has been changed by the flyback converter into a stable DC voltage. The simulation results show that the total harmonic distortion (THD) under all the simulated scenarios is within 5%, which agrees with IEEE standards. In the future, this algorithm may be compared with other types of available MPPTs under partial shading. [ABSTRACT FROM AUTHOR]

Inspection data can be used to comprehend and plan effective maintenance of bridges. In particular, the year of initial construction is one of the most important criteria for formulating maintenance plans, making budget allocations, and estimating soundness. In an initial survey of bridges in Cambodia, it was concluded that the year of construction of only 54% of 2439 bridges surveyed is known, with the remaining 46% remaining unknown. In this research, Landsat satellite data is used to estimate the year of construction of these bridges. Landsat provides spatial spectral reflectance information covering more than 30 years, and for longer bridges this can be used to estimate the year of construction by visual judgement. However, limited image resolution means this is not possible for shorter bridges. Instead, a method using the Landsat Normalized Difference Water Index (NDWI) is used to estimate the year of construction. Three pixels are selected from Landsat image data in such a way that one lies on the current location of a bridge and two other reference pixels are placed on similar terrain at a certain distance perpendicular to the bridge axis. NDWI values are plotted over time for the three pixels and the difference in value between the bridge pixel and the two reference pixels is then compared. Before the bridge is constructed, all three pixels should have similar NDWI values, but after construction the value of the target bridge pixel should differ from the other two because the NDWI value of a bridge surface is different from that of the surrounding vegetation. By looking for this change, the year of construction of a bridge can be estimated. All the bridges in the Cambodian database are classified into three categories based on length (which affects their visibility in Landsat images) and year of construction is estimated. The results show that estimated year of construction has the same accuracy in all three categories. [ABSTRACT FROM AUTHOR]

Folate (vitamin B9) and its biologically active derivatives are well-known antioxidant molecules protecting cells from oxidative degradation. The presence of high glucose, often found in diabetic patients, causes oxidative stress resulting in cellular stress and inflammatory injury. Cells in organs such as the lung are highly prone to inflammation, and various protective mechanisms exist to prevent the progressive disorders arising from inflammation. In the present study, the synthetic form of folate, i.e. folic acid, and active forms of folate, i.e. 5-methyltetrahydrofolate and 10-formyltetrahydrofolate, were evaluated for their antioxidant and antiinflammatory potential against high glucose (50 mM)–mediated oxidative stress and inflammation in BEAS-2B cells, an immortalised bronchial epithelial cell line. High glucose treatment showed a 67% reduction in the viability of BEAS-2B cells, which was restored to the viability levels seen in control cultures by the addition of active folate derivatives to the culture media. The DCFH-DA fluorometric assay was performed for oxidative stress detection. The high glucose–treated cells showed a significantly higher fluorescence intensity (1.81- and 3.8-fold for microplate assay and microscopic observation, respectively), which was normalised to control levels on supplementation with active folate derivatives. The proinflammatory NF-κB p50 protein expression in the active folate derivative–supplemented high glucose–treated cells was significantly lower compared to the folic acid treatment. In support of these findings, in silico microarray GENVESTIGATOR database analysis showed that in bronchiolar small airway epithelial cells exposed to inflammatory condition, folate utilization pathway genes are largely downregulated. However, the folate-binding protein gene, which encodes to the folate receptor 1 (FOLR1), is significantly upregulated, suggesting a high demand for folate by these cells in inflammatory situations. Supplementation of the active folate derivatives 5-methyltetrahydrofolate and 10-formyltetrahydrofolate resulted in significantly higher protection over the folic acid from high glucose–induced oxidative stress and inflammation. Therefore, the biologically active folate derivatives could be a suitable alternative over the folic acid for alleviating inflammatory injury-causing oxidative stress. [ABSTRACT FROM AUTHOR]

Micronutrient rich microalgae, Chlorella and Spirulina, could be natural food supplements to overcome the micronutrient deficiency, increasingly recognised as a global health issue. In two independent experiments, the Spirulina and Chlorella were evaluated as prophylactic and ameliorative dietary supplements of vitamin B12. Erythrocyte stability (relative osmotic fragility and haemolysis percentage), haematological parameters, micronutrient deficiency (serum levels of iron, zinc), plasma vitamin B12 and vitamin B12 biomarker (methylmalonic acid) were analysed. The deficient groups receiving Spirulina and Chlorella as prophylactic dietary supplements showed a 1.34 to 1.41 folds increase in serum iron and a 2.13 to 2.19 folds increase in plasma vitamin B12, compared to B12 deficient group. Supplementation of Spirulina to ameliorate vitamin B12 deficiency combined with micronutrient limitation showed an increase of 1.14 folds and 1.2 folds in serum iron and zinc respectively and 1.51 folds in plasma vitamin B12 compared to the deficient group. The relative osmotic fragility of erythrocytes in deficient experimental animals was 17 to 45% higher compared to the control. The osmotic fragility and deformation in the morphology of erythrocytes observed under vitamin B12 deficiency, alone or in combination with micronutrient limitation, were prevented and ameliorated on dietary supplementation with the microalgal biomass. [ABSTRACT FROM AUTHOR]

The sources of bioavailable vitamin B12 are limited, and most of them are animal-derived. Chlorella vulgaris, a freshwater microalga, is known for immune system boosting, nutraceutical properties and presence of a natural form of vitamin B12. The present study focused on the in vivo evaluation of the Chlorella biomass as a source of bioavailable vitamin B12 to alleviate the vitamin B12 deficiency status of Wistar rats. Experimental animals were evaluated for the vitamin B12 deficiency-related circulatory marker (serum vitamin B12) and functional markers (plasma homocysteine and urinary methylmalonic acid), haematological and histological changes. The results showed that an increase of 2.4-fold in urinary methylmalonic acid (13.01 ± 0.89 µmoles moles of creatinine−1), 2.6-fold in plasma homocysteine (17.18 ± 3.57 µmole L−1), and 48% decrease in serum vitamin B12 levels (252.69 ± 1.46 pg mL−1) in vitamin B12 deficient group compared to control animals. The Chlorella biomass supplementation in the diet led to the restoration of the functional and circulatory markers, hematological parameters, and vitamin B12 content of kidney and liver to control levels. The Chlorella biomass supplementation increased the erythrocyte precursors and MAST cells in the bone marrow and also normalized the histological features of kidney, liver, and lung tissues. The results suggest that the vitamin B12 from the Chlorella biomass was bioavailable and facilitated the improvement of vitamin B12 status in deficient rats. [ABSTRACT FROM AUTHOR]

Summary: With the advent of rapid advancements in the energy storage technologies and in harnessing the renewable resources, a variety of mix of "Problem formulation techniques" and "Solution methodologies" have emerged for scheduling the power generation in Grid integrated environment. Multiple constituent attributes and their combinations thereof define the nature of Unit Commitment problem formulation in a complex way. An attempt has been made in this paper to consolidate the available research efforts, spanning over about past two decades, so as to unravel the rising complexities in developing the unit commitment formulation in this rapidly evolving green energy era. The prevailing unit commitment models have been thoroughly reviewed on the bases of deployment of different combinations of features like objective functions, constraints, optimization techniques, types of renewable generation, and types of storage. This review work presents, in a categorized manner, the viewpoints on problem formulation as well as on the solution methodologies. Further, a novel Unit Commitment model has been proposed by the authors wherein modeling details of each of them have been presented in a conscientious manner. The proposed model is unique as the battery charge/ discharge decision making has been included as a co‐optimization problem with the existing Unit Commitment problem. The superiority of the proposed model has also been reported. [ABSTRACT FROM AUTHOR]

Dominating set, minimum dominating set and minimum connected dominating set is correct sequence need to study in any wireless network system. One must need to have MCDS for efficient and cost effective wireless network system. A graph G = (V; E), a dominating set D is a subset of V such that any vertex not in D is adjacent to at least one vertex in D. In a graph G = (V; E) a connected dominating set is a subset of vertices such that every vertex is either in the subset or adjacent to a vertex in the subset and the subgraph induced by the subset is connected. A minimum connected dominating set is such a vertex subset with minimum cardinality. In this paper, we present a new method i.e. AJK algorithm we can easily find a minimum connected dominating set. We can easily see that this algorithm gives a constant performance guarantee. The results show that, despite its simplicity, the proposed algorithm gives very good solutions. [ABSTRACT FROM AUTHOR]

Chlorella vulgaris is known for its protein, growth factor, and nutritional constituents. Chlorella vulgaris was cultivated in a 1000-L outdoor open raceway pond with a maximum volumetric productivity of 130 mg L-1 day-1. The harvested biomass was dried through different methods, viz., sun drying (30 °C), oven drying (60 °C), lyophilization (−110 °C), drum drying (120 °C), and spray drying (100–150 °C). The effect of the drying method on proximate composition, pigments (chlorophyll, carotenoids), bioactive compounds (total phenolic content, flavonoid content), vitamin B12, antioxidant properties (ferric reducing antioxidant power, DPPH, and total antioxidant activity), and the color quality of C. vulgaris biomass was evaluated. Surface characterization by scanning electron microscopy (SEM) and functional group characterization through Fourier transform infrared spectroscopy were also performed. The biomass dried through lyophilization and sun drying retained maximum bioactive compounds and antioxidant activities. In contrast, drum drying resulted in a loss of nutrients, viz., protein (up to 44%), lipid (up to 41%), vitamin B12 (up to 40%), total phenolic content (> 50%), total flavonoid content (> 50%), and antioxidant activity (> 50%). Oven drying led to a loss of 30% in total flavonoid content and 17% in ferric reducing antioxidant power. SEM showed the destruction of cell wall integrity in the drum-dried sample and porous structure in the spray-dried sample. This study suggests that drying methods affect the nutrients and bioactive compounds of C. vulgaris biomass, and therefore a drying method should be selected carefully depending on the end use of the biomass. [ABSTRACT FROM AUTHOR]

Corrosion of the steel reinforcing bars in concrete structures is one of the major maintenance problems. Corrosion results in expansive pressure on the surrounding concrete, which causes internal damage that may become visible as surface cracking. Such damage may degrade structural safety and serviceability. Effective maintenance requires the evaluation of residual performance based on estimates of spatially nonuniform levels of corrosion, which are typically obtained through surface measurements only. In this study, the authors have developed a simulation system for estimating the levels of internal corrosion along the reinforcing bar length from surface crack information. This innovative system is produced by integrating the technique of Model Predictive Control (MPC) with Rigid‐Body‐Spring Models (RBSM) of corrosion‐induced cracking at the concrete mesoscale. In this study, MPC controls the simulated surface cracks such that they match the observed cracks by optimizing the internal expansions of springs representing the steel‐concrete interface within the RBSM. The applicability of the system is verified using both synthetic crack width data and crack data collected from in‐house laboratory testing. In the laboratory testing, corrosion levels were quantified by 3D scanning of the extracted reinforcing bars. The simulation results agree with the corrosion measurements, demonstrating the potential of the MPC‐RBSM system for predicting the corrosion distribution along reinforcing bars using surface crack data. [ABSTRACT FROM AUTHOR]

In this paper, we present a theoretical proposal to realize Quantum Memory (QM) for storage of blue light pulses (420 nm) using Electromagnetically Induced Transparency (EIT). Three-level lambda-type EIT configuration system is solved in a fully quantum mechanical approach. Storing blue light has the potential application in the field of underwater quantum communication as it experiences less attenuation inside the sea water. Our model works by exciting the relevant transitions of 8 7 Rb atoms using a three-level lambda-type configuration in a Two-Dimensional Magneto-Optical Trap (2D MOT) with an optical cavity inside it. We have estimated Optical Depth inside the cavity (ODc) of 1. 4 3 × 1 0 5 , group velocity ( v g ) = 2. 6 × 1 0 3 ms − 1 , Delay Bandwidth Product(DBP) of 23 and maximum storage efficiency as 9 9 % in our system. [ABSTRACT FROM AUTHOR]

This paper describes the navigation of an automated Pioneer P3-DX wheeled robot between obstacles using particle swarm optimization (PSO) algorithm tuned feedforward neural network (FNN). This PSO algorithm minimizes the mean square error between the actual and predicted values of the FNN. In this work, 2 separate DC motors and 16 ultrasonic sensors have been used for making differential drive steering angle and for collecting the distance from obstacles, respectively. The proposed without tuned FNN and PSO-tuned FNN receives obstacle's distance as inputs form ultrasonic sensors and control the steering angle of a differential drive of automated Pioneer P3-DX wheeled robot as output. We have compared the results between without tuned FNN and PSO-tuned FNN, and it has been found that PSO-tuned FNN gives a better trajectory and takes less distance to reach the target. Virtual Robot Experimentation Platform software has been used to design the real-time simulation results. A comparative study between without tuned FNN and PSO-tuned FNN verifies the effectiveness of PSO-tuned FNN for automated Pioneer P3-DX wheeled robot navigation. Also, we have compared this winner PSO-tuned FNN to the previously developed PSO-optimized Fuzzy Logic Controller navigational technique to show the authenticity and real-time implementation of PSO-tuned FNN. [ABSTRACT FROM AUTHOR]

Life cycle assessment (LCA) of indigenous freshwater microalgae, Scenedesmus dimorphus, cultivation in open raceway pond and its conversion to biodiesel and biogas were carried out. The LCA inventory inputs for the biogas scenario was entirely based on primary data obtained from algal cultivation (in pilot scale raceway pond), harvesting, and biogas production; while only the downstream processing involved in biodiesel production namely drying, reaction and purification were based on secondary data. Overall, eight scenarios were modeled for the integrated process involving: algae-based CO2 capture and downstream processing scenarios for biodiesel and biogas along with impact assessment of nutrient addition and extent of recycling in a life cycle perspective. The LCA results indicated a huge energy deficit and net CO2 negative in terms of CO2 capture for both the biodiesel and biogas scenarios, majorly due to lower algal biomass productivity and higher energy requirements for culture mixing. The sensitivity analysis indicated that variability in the biomass productivity has predominant effect on the primary energy demand and global warming potential (GWP, kg CO2 eq.) followed by specific energy consumption for mixing algal culture. Furthermore, the LCA results indicated that biogas conversion route from microalgae was more energy efficient and sustainable than the biodiesel route. The overall findings of the study suggested that microalgae-mediated CO2 capture and conversion to biodiesel and biogas production can be energy efficient at higher biomass productivity (> 10 g m−2 day−1) and via employing energy-efficient systems for culture mixing (< 2 W m−3). [ABSTRACT FROM AUTHOR]

An increase in the share of distributed generation (DG) in the global generation system is a direct indication of the development of available technologies. The extraction of natural energy resources and their use as DG has several advantages, such as the reduction in line losses, improved voltage profile and reliability, etc., but the incorrect installation of these power plants can also have some negative effects. The innovation in technology has motivated to extract the maximum benefit of natural energy resources. Due to this, the capacity and location of these energy resources should be carefully identified. The optimal placement of a distributed generation power plant, in the existing network, is analyzed in this article. The proposed methodology is inspired by the human immune system. In this methodology clonal selection principle of immune system is combined with particle swarm optimization. For checking the validity of the proposed method two test systems, IEEE 33-node radial distribution system and IEEE 14-node loop distribution system, are considered. Results show the validity of the proposed algorithm in radial as well as in loop distribution system. [ABSTRACT FROM AUTHOR]

Recent studies have publicized that renewable energy resources are the only answer to trim down energy crisis and also able to diminish green house gases. Thats why disperse generation is very significant for sustainable development in power sector. This paper presents an analytical algorithm to find optimal location and a best suitable size of distributed generator (DG) to minimize system losses. Authors also prove that scatter generation is used not only to reduce the gap between demand and supply of power with minimum amount losses, but it can also improve the reliability of distribution system. The results obtained from a case study of 34 bus radial distribution system have proved the efficiency of algorithms for loss minimization and competency of DG to enhance the reliability indices of the conventional distribution system. [ABSTRACT FROM AUTHOR]

The effects of various production parameters such as pH, temperature, incubation time and sources of carbon were tested in submerged fermentation process by shake flask culture method in production of amylase by bacteria isolated from groundnut field soil. The production medium with provision of glucose as carbon source, yeast extract as nitrogen source incubated for 48 h, maintained with pH of 6.5 at 39°C, was found optimal for production of amylase. [ABSTRACT FROM AUTHOR]

Medicines and vaccines are designed to prevent and treatment of diseases and with their benefits they have side effects some are unexpected. Pharmacovigilance ensures the rigorous testing of clinical drugs to improve patient and reduce the risk of negative side effects, PV certifies whether a drug works and it is safe to use. In 1994 more than 100,000 deaths occurred because of ADR, after the introduction of PV the rate of morbidity drastically decreased. Thousands of drugs are life threatening at their clinical trials, but after the introduction of PV mortality rate decreased. And some future impact of PV Making medicine safer to the world, command on technology Main tool of PV is data analytics. PV focuses on data processing instead of data analysis and treating science as a heart of PV, self acting to inventive. [ABSTRACT FROM AUTHOR]

An oxidative copper-catalyzed cross-coupling of arylboronic acids with various ring-size lactams has been developed. The N-arylated lactams were obtained in moderate to excellent yields without any additional bases, ligands, or additives. This reaction shows complete selectivity for N-arylation of lactams in the presence of a hydroxyl group. [ABSTRACT FROM AUTHOR]

The acetylcholine receptor is an essential link between the brain and the muscles, so it is a sensitive location for attack. In this study, some reversible [diethylenetriaminepentaacetic acid--(amino acid)2] have been docked computationally to the active site of the acetylcholine receptor. The induced fit method was employed to perform the automolecular docking for these systems. The result of docking studies generated thermodynamic properties, such as free energy of bindings (Glide score) and their weak electrostatic interactions. On the basis of these results, scintigraphic imaging studies were performed in mice. Among the radiotracers evaluated in this study, compound derived from 5-hydroxytryptophan/tryptophan exhibited remarkable localization in the brain, whereas radiotracer derived from L-histidine shows moderate accumulation in the brain. Preliminary studies with these amino acid--based ligands are encouraging to carrying out further in vivo experiments for targeted imaging. [ABSTRACT FROM AUTHOR]

Three sample preparation procedures, soak, stomach, and blend, were evaluated using the Bacteriological Analytical Manual Salmonella culture method with eight types of leafy green produce. In the soak method, test portions were added to lactose broth without homogenization; in the stomach method, test portions were stomached with lactose broth; and in the blend method, test portions were blended with lactose broth. Twenty artificially contaminated test portions were analyzed with each procedure in individual experimental trials. The number of test portions identified as positive were compared among the procedures. Statistically significant differences were identified with Fisher's exact two-tailed F test (P < 0.05). Where differences did occur (P < 0.05), the soak procedure was the most effective or was at least as effective as homogenization by either blending or stomaching. Statistically significant differences most frequently occurred with romaine lettuce and cabbage; for these items, blending was significantly less effective than the soak procedure. Overall, for all of the produce types examined, results showed that the soak procedure was more effective than either of the homogenization procedures in recovering Salmonella from leafy green produce. Of the 540 test portions examined by each sample preparation method, 344 were positive for the presence of Salmonella by soaking, 293 by stomaching, and 232 by blending. We recommend that the soak procedure replace homogenization for the analysis of leafy green produce because the soak procedure is more productive than homogenization by either blending or stomaching of the leafy green produce types as reported herein. [ABSTRACT FROM AUTHOR]

Abstract  We study the so-called Generalized Median graph problem where the task is to construct a prototype (i.e., a ‘model’) from an input set of graphs. While our primary motivation comes from an important biological imaging application, the problem effectively captures many vision (e.g., object recognition) and learning problems, where graphs are increasingly being adopted as a powerful representation tool. Existing techniques for his problem are evolutionary search based; in this paper, we propose a polynomial time algorithm based on a linear programming formulation. We propose an additional algorithm based on a bi-level method to obtain solutions arbitrarily close to the optimal in (worst case) non-polynomial time. Within this new framework, one can optimize edit distance functions that capture similarity by considering vertex labels as well as he graph structure simultaneously. We first discuss experimental evaluations in context of molecular image analysis problems—he methods will provide the basis for building a topological map of all 23 pairs of the human chromosome. Later, we include (a) applications to other biomedical problems and (b) evaluations on a public pattern recognition graph database. [ABSTRACT FROM AUTHOR]

Abstract Biplane projection imaging is one of the primary methods for imaging and visualizing the cardiovascular system in medicine. A key problem in such a technique is to determine the imaging geometry (i.e., the relative rotation and translation) of two projections so that the 3-D structure can be accurately reconstructed. Based on interesting observations and efficient geometric techniques, we present in this paper new algorithmic solutions for this problem. Comparing with existing optimization-based approaches, our techniques yield better accuracy and have bounded execution time, thus is more suitable for on-line applications. Our techniques can easily detect outliers to further improve the accuracy. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we consider an interesting generalization of the classic job scheduling problem in which each job needs to compete not only for machines but also for other types of resources. The contentions among jobs for machines and for resources could interfere with each other, which complicates the problem dramatically. We present a family of approximation algorithms for solving several variants of the problem by using a generic algorithmic framework. Our algorithms achieve a constant approximation ratio (i.e., 3) when there is only one type of resources or certain dependency relation exists among multiple types of resources. When the r resources are unrelated, the approximation ratio of our algorithm becomes k+2, where k≤ r is a constant depending on the problem instance. As an application, we also show that our techniques can be easily applied to optical burst switching (OBS) networks to design more efficient wavelength scheduling algorithms. [ABSTRACT FROM AUTHOR]

Use of organic resins such as epoxy and vinyl esters as bonding materials in fibre reinforced polymer (FRP) strengthening of concrete members is widely accepted. However, the performance of organic resins is compromised when exposed to high temperature and extreme weather conditions leading to reduced durability of the strengthened systems. The present study attempts to evaluate the effectiveness of inorganic (cement mortar and geopolymer mortar) bonding materials for shear strengthening of prestressed concrete (PSC) beams using the near-surface mounting (NSM) technique. Different types of bonding materials are used in this study for NSM shear strengthening including: (i) epoxy resin, (ii) high strength cement grout (HSCG) and (iii) geopolymer mortar. Bond tests were first conducted to evaluate the pull-out/bond strength of different bonding materials. Bond tests revealed that epoxy resin had the highest bond strength followed by geopolymer mortar and HSCG. Sixteen full-scale PSC beams were cast with and without stirrups. The beams were strengthened using NSM CFRP laminates oriented at 45-degree configuration and then tested under a three-point bending configuration. Experimental results revealed that the performance of high strength cement grout and geopolymer mortar was similar but with a lesser efficiency compared to the epoxy resin. [ABSTRACT FROM AUTHOR]

Spirulina evaluated as a source of vitamin B12 through the modulation of vitamin B12 deficiency mediated physiological and biochemical changes in experimental animals. The B12 deficient male weanling Wistar rats were fed with Spirulina‐supplemented diet for 10 weeks. An increase in urinary methylmalonic acid (22.70 ± 4.08 µmol/moles of creatinine) and plasma homocysteine (16.55 ± 0.48 µmol/L) levels in the B12 deficient group was observed, while these were equal to control in the Spirulina fed group (8.71 ± 0.48 µmol/mol of creatinine and 6.88 ± 1.18 µmol/L, respectively). The vitamin B12 levels in serum (874.27 ± 89.69), plasma (615.53 ± 26.5 pg/ml), kidney (10.19 ± 1.066 ng/g), and liver tissues (6.37 ± 0.62 ng/g) in the Spirulina fed group were similar to control. Severe atrophic changes in the testes and altered tissue architecture in lung and spleen as seen in the B12 deficient group were normalized in the Spirulina fed group. The study validates that Spirulina can improve the vitamin B12 status. Practical applications: The present study showed that the supplementation of Spirulina in the diet of vitamin B12 deficient rats leads to the normalization of vitamin B12 deficiency‐induced circulatory and functional biomarkers along with biochemical and histological changes. Vegetarian sources for vitamin B12 are limited and the results presented here provide scientific validation for the use of Spirulina as a potential vegetarian source of bioavailable vitamin B12. [ABSTRACT FROM AUTHOR]