ALBERT

Description: Background: Single-stranded DNA binding proteins (SSB) are essential for DNA replication, repair, and recombination in all organisms. SSB works in concert with a variety of DNA metabolizing enzymes such as DNA polymerase. Results: We have cloned and purified SSB from Bacillus anthracis (SSBBA). In the absence of DNA, at concentrations [less than or equal to]100 mug/ml, SSBBA did not form a stable tetramer and appeared to resemble bacteriophage T4 gene 32 protein. Fluorescence anisotropy studies demonstrated that SSBBA bound ssDNA with high affinity comparable to other prokaryotic SSBs. Thermodynamic analysis indicated both hydrophobic and ionic contributions to ssDNA binding. FRET analysis of oligo(dT)70 binding suggested that SSBBA forms a tetrameric assembly upon ssDNA binding. This report provides evidence of a bacterial SSB that utilizes a novel mechanism for DNA binding through the formation of a transient tetrameric structure. Conclusions: Unlike other prokaryotic SSB proteins, SSBBA from Bacillus anthracis appeared to be monomeric at concentrations [less than or equal to]100 mug/ml as determined by SE-HPLC. SSBBA retained its ability to bind ssDNA with very high affinity, comparable to SSB proteins which are tetrameric. In the presence of a long ssDNA template, SSBBA appears to form a transient tetrameric structure. Its unique structure appears to be due to the cumulative effect of multiple key amino acid changes in its sequence during evolution, leading to perturbation of stable dimer and tetramer formation. The structural features of SSBBA could promote facile assembly and disassembly of the protein-DNA complex required in processes such as DNA replication.

Description: This article describes an aging study of a foam-vacuum insulation panel (VIP) composite insulation board installed on a test wall in a natural exposure test facility through a 30-month period. Silica-based VIPs with a polymeric barrier film were used in this study. The study results showed the effectiveness of a VIP-based insulation to reduce the heat gains and losses through a wall compared to regular rigid foam insulation of the same thickness. However, the long-term performance monitoring indicated a gradual decline in the thermal performance of the foam-VIP composite. In addition, one-dimensional numerical models were created to simulate the in situ behavior of the foam-VIP composite. One model utilized constant thermal conductivities of the test wall components and another utilized temperature-dependent thermal conductivities; the latter used measurements of conductivity over temperatures ranging from −15 to 55 °C. The results of the simulations emphasized the need to use both temperature and time-dependent material properties for accurately predicting the long-term performance of VIP-based insulation systems.

Description: Long-term precipitation estimates with both finer spatial resolution and better quality are vital and highly needed in various related fields. Numerous downscaling algorithms have been investigated based on the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA), to obtain precipitation data with finer resolution (~1 km). However, this research was restricted by the time span of the TMPA dataset, as the starting time of TMPA was 1998. In this study, a new methodological framework incorporating wavelet coherence and Cubist was proposed to retrospectively obtain downscaled precipitation estimates (DS) over the Tibetan Plateau (TP), based on TMPA and ground observations, in 1990s. The correlations and similarities of precipitation patterns between the target years, from 1990 to 1999, and reference years, from 2000 to 2013, were firstly determined using wavelet coherence based on ground observations. Following this, the TMPA data in the reference years were regarded as the reference in the corresponding target years, which were adopted to be downscaled using Cubist models and land surface variables, to obtain the DS in the target years. We found that the DS showed continuous trends, which corresponded well with the ground observations. Additionally, the performances of the DS were better than those of the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) data over the TP. Therefore, this methodological framework has great potential for obtaining precipitation estimates for the period of the 1990s for which TMPA data is inaccessible.

Description: Background: In humans, many diseases are associated with the accumulation of free radicals. Antioxidants can scavenge free radicals and minimize their impact. Therefore, the search for naturally occurring antioxidants of plant origin is imperative. Here, we aimed to investigate the antioxidant and free radical scavenging properties of methanolic extracts from Tabebuia pallida (T. pallida) stem bark (TPSB), root bark (TPRB), leaves (TPL), and flowers (TPF). Methods: The antioxidant and free radical scavenging activity were determined by several standard methods using spectrophotomer. Total phenolic and flavonoid contents were estimated using Folin-Ciocalteu reagent and aluminum chloride colorimetric assay methods, respectively. Results: Among the extracts, TPL showed the highest total antioxidant capacity followed by TPRB, TPF, and TPSB. Based on DPPH and hydroxyl radical scavenging activity, TPL showed strong scavenging activity (91.05 ± 1.10 and 62.00 ± 0.57) with IC 50 of 9.20 ± 0.28 and 46.00 ± 2.84 μg/mL, respectively when compared with standard BHT (IC 50 of 7.00 ± 0.25 μg/mL) and CA (75.00 ± 0.14 μg/mL). These results suggest that TPL had the highest radical scavenging activity among the extractives that closely resembled the standard’s. In lipid peroxidation inhibition assay, TPL exhibited the most potent inhibitory activity (83.18 ± 2.12 %) with IC 50 of 12.00 ± 2.12 μg/mL, which closely resembled standard CA (IC 50 of 10.50 ± 0.28 μg/mL). Also, the reducing capacity on ferrous ion was in the following order: TPL 〉 TPRB 〉 TF 〉 TPSB. The phenolic and flavonoid contents of TPL were higher than other extractives. A positive correlation (p value

Description: The Internet-of-Things (IoT) framework has been considered as an enabler of the smart world where all devices will be deployed with extra-sensory power in order to sense the world as well as communicate with other sensor nodes. As a result, smart devices require more energy. Therefore, energy harvesting (EH) and wireless power transfer (WPT) emerge as a remedy for relieving the battery limitations of wireless devices. In this work, we consider a multi-user amplify-and-forward (AF)-assisted network, wherein multiple source nodes communicate with destination nodes with the help of a relay node. All the source nodes and the relay node have the capability of EH. In addition, to cope with a single point of failure i.e., failure of the relay node due to the lack of transmit power, we consider the WPT from the source nodes to the relay node. For WPT, a dedicated energy control channel is utilized by the source nodes. To maximize the sum rate using a deadline, we adopt a joint approach of power allocation and WPT and formulate an optimization problem under the constraints of the battery as well as energy causality. The formulated problem is non-convex and intractable. In order to make the problem solvable, we utilize a successive convex approximation method. Furthermore, an iterative algorithm based on the dual decomposition technique is investigated to get the optimal power allocation and transfer. Numerical examples are used to illustrate the performance of the proposed iterative algorithm.

Description: With increasing computing capabilities of modern supercomputers, the size of the data generated from the scientific simulations is growing rapidly. As a result, application scientists need effective data summarization techniques that can reduce large-scale multivariate spatiotemporal data sets while preserving the important data properties so that the reduced data can answer domain-specific queries involving multiple variables with sufficient accuracy. While analyzing complex scientific events, domain experts often analyze and visualize two or more variables together to obtain a better understanding of the characteristics of the data features. Therefore, data summarization techniques are required to analyze multi-variable relationships in detail and then perform data reduction such that the important features involving multiple variables are preserved in the reduced data. To achieve this, in this work, we propose a data sub-sampling algorithm for performing statistical data summarization that leverages pointwise information theoretic measures to quantify the statistical association of data points considering multiple variables and generates a sub-sampled data that preserves the statistical association among multi-variables. Using such reduced sampled data, we show that multivariate feature query and analysis can be done effectively. The efficacy of the proposed multivariate association driven sampling algorithm is presented by applying it on several scientific data sets.

Description: Alternative fuels for the transport sector are being emphasized due to energy security and environmental issues. Possible alternative fuel options need to be assessed to realize their potential to alleviate environmental burdens before policy formulations. Western Australia (WA) is dominated by private cars, accounting for around 72% vehicles with 87% of those using imported gasoline, and resulting in approximately 14% of greenhouse gas (GHG) emissions from the transport sector. There is an urgent need for WA to consider alternative transport fuels not only to reduce the environmental burden but also to avoid future energy security consequences. This study assesses the environmental life cycle assessment (ELCA) of transport fuel options suitable for WA. The study revealed that ethanol (E65), electric (EV) and plug-in electric vehicle (PHEV) options can decrease global warming potential (GWP) by 40%, 29% and 14%, respectively, when compared to gasoline. The EV and PHEV also performed better than gasoline in the fossil fuel depletion (FFD) and water consumption (WC) impact categories. Gasoline, however, demonstrated better environmental performance in all the impact categories compared to hydrogen and that was mainly due to the high electricity requirement during the production of hydrogen. The use of platinum in hydrogen fuel cells and carbon fibre in the hydrogen tank for hydrogen fuel cell vehicles (HFCV) and Li-ion battery for EVs are the most important sources of environmental impacts. The findings of the study would aid the energy planners and decision makers in carrying out a comparative environmental assessment of the locally-sourced alternative fuels for WA.

Description: Given the growing intent to prevent decay in environmental management, the present study seeks to unearth the impact of corporate environmental strategy on employees’ voluntary environmental behavior by regulating or facilitating their perceived psychological green climate. Research problems and research questions are built on the essence of multiple theories—goal-setting theory, social identity theory, and social learning theory for grounding the research model. A total of 294 replies were collected through a self-administered survey from diverse industrial panoramas. We used structural equation modeling (SEM) analytics via AMOS-version 20.0 for measuring the hypothesized results. The study revealed that the corporate environmental strategy is displaying an insignificant direct influence on voluntary environmental behavior. However, the corporate environmental strategy indirectly influences, via the mediation effect, voluntary environmental behavior of employees through their psychological green climate perception. Directions for future research are recommended based on insights from the implications and limitations of the study.