ALBERT

Description: Neisseria meningitidis is a commensal pathogen that causes infectious cerebrospinal disease in people of all ages. The multivariate role of six disease-causing polysaccharide serotypes is found to play a crucial role in developing vaccines (or general treatment strategies) to treat this emerging pathogen. Iron is a crucial transition metal for N. meningitidis. Proteomic analysis data could be valuable for vaccine design. Here, we conduct a comparative study using computational bioinformatic tools to identify the most effective iron-regulated outer membrane proteins (OMPs) as immunogenic targets for a potential vaccine against N. meningitidis. The basic properties of N. meningitidis OMPs are explored for flexibility, solubility, hydrophilicity, beta-turns, and overall antigenic probability. Results of our study suggest that iron-regulated OMPs are flexible and soluble in water with high densities of conformational B-cell epitopes. As such, they can be recommended as a novel candidate for a vaccine against N. meningitidis both in vitro and in vivo.

Description: Trait tagging through molecular markers is an important molecular breeding tool for crop improvement. SSR markers encoded by functionally relevant parts of a genome are well suited for this task because they may be directly related to traits. However, a limited number of these markers are known for Musa spp. Here, we report 35136 novel functionally relevant SSR markers (FRSMs). Among these, 17,561, 15,373 and 16,286 FRSMs were mapped in-silico to the genomes of Musa acuminata, M. balbisiana and M. schizocarpa, respectively. A set of 273 markers was validated using eight accessions of Musa spp., from which 259 markers (95%) produced a PCR product of the expected size and 203 (74%) were polymorphic. In-silico comparative mapping of FRSMs onto Musa and related species indicated sequence-based orthology and synteny relationships among the chromosomes of Musa and other plant species. Fifteen FRSMs were used to estimate the phylogenetic relationships among 50 banana accessions, and the results revealed that all banana accessions group into two major clusters according to their genomic background. Here, we report the first large-scale development and characterization of functionally relevant Musa SSR markers. We demonstrate their utility for germplasm characterization, genetic diversity studies, and comparative mapping in Musa spp. and other monocot species. The sequences for these novel markers are freely available via a searchable web interface called Musa Marker Database.

Description: Environmental obligation, fuel security, and human health issues have fuelled the search for locally produced sustainable transport fuels as an alternative to liquid petroleum. This study evaluates the sustainability performance of various alternative energy sources, namely, ethanol, electricity, electricity-gasoline hybrid, and hydrogen, for Western Australian road transport using a life cycle sustainability assessment (LCSA) framework. The framework employs 11 triple bottom line (TBL) sustainability indicators and uses threshold values for benchmarking sustainability practices. A number of improvement strategies were devised based on the hotspots once the alternative energy sources failed to meet the sustainability threshold for the determined indicators. The proposed framework effectively addresses the issue of interdependencies between the three pillars of sustainability, which was an inherent weakness of previous frameworks. The results show that the environment-friendly and socially sustainable energy options, namely, ethanol-gasoline blend E55, electricity, electricity-E10 hybrid, and hydrogen, would need around 0.02, 0.14, 0.10, and 0.71 AUD/VKT of financial support, respectively, to be comparable to gasoline. Among the four assessed options, hydrogen shows the best performance for the environmental and social bottom line when renewable electricity is employed for hydrogen production. The economic sustainability of hydrogen fuel is, however, uncertain at this stage due to the high cost of hydrogen fuel cell vehicles (HFCVs). The robustness of the proposed framework warrants its application in a wide range of alternative fuel assessment scenarios locally as well as globally.

Description: Crops can uptake only a fraction of nitrogen from nitrogenous fertilizer, while losing the remainder through volatilization, leaching, immobilization and emissions from soils. The emissions of nitrogen in the form of nitrous oxide (N2O) have a strong potency for global warming and depletion of stratospheric ozone. N2O gets released due to nitrification and denitrification processes, which are aided by different environmental, management and soil variables. In recent years, researchers have focused on understanding and simulating the N2O emission processes from agricultural farms and/or watersheds by using process-based models like Daily CENTURY (DAYCENT), Denitrification-Decomposition (DNDC) and Soil and Water Assessment Tool (SWAT). While the former two have been predominantly used in understanding the science of N2O emission and its execution within the model structure, as visible from a multitude of research articles summarizing their strengths and limitations, the later one is relatively unexplored. The SWAT is a promising candidate for modeling N2O emission, as it includes variables and processes that are widely reported in the literature as controlling N2O fluxes from soil, including nitrification and denitrification. SWAT also includes three-dimensional lateral movement of water within the soil, like in real-world conditions, unlike the two-dimensional biogeochemical models mentioned above. This article aims to summarize the N2O emission processes, variables affecting N2O emission and recent advances in N2O emission modeling techniques in SWAT, while discussing their applications, strengths, limitations and further recommendations.

Description: The present study compared the mechanical, electrical, morphological, and piezoresistive characteristics of epoxy-based sensing nanocomposites fabricated with inclusions of hybridized networks of four different carbon nanomaterials (CNMs), such as carbon nanotube (CNT), graphene, carbon nanofiber (CNF), and graphite nanoplatelet (GNP). Enhancements in elastic modulus and electrical conductivity were achieved by CNT–graphene composites and CNT–CNF composites, and these were explained by the morphological observations carried out in the present study and experimental studies found in the literature. The greatest gauge factor was accomplished by the CNT–GNP composite, followed by the CNT–CNF composite among composites where the CNM networks were sufficiently formed with a content ratio of 3%. The two types of the composites outperformed the composites incorporating solely CNT in terms of gauge factor, and this superiority was explained with the excluded volume theory.

Description: The durability and performance of electrochemical energy converters, such as fuel cells and electrolysers, are not only dependent on the properties and the quality of the used materials. They strongly depend on the operational conditions. Variations in external parameters, such as flow, pressure, temperature and, obviously, load, can lead to significant local changes in current density, even local transients. Segmented cell technology was developed with the purpose to gain insight into the local operational conditions in electrochemical cells during operation. The operando measurement of the local current density and temperature distribution allows effective improvement of operation conditions, mitigation of potentially critical events and assessment of the performance of new materials. The segmented cell, which can replace a regular bipolar plate in the current state of the technology, can be used as a monitoring tool and for targeted developments. This article gives an overview of the development and applications of this technology, such as for water management or fault recognition. Recent advancements towards locally resolved monitoring of humidity and to current distributions in electrolysers are outlined.

Description: Land use and cover change (LUCC) is an important issue affecting the global environment, climate change, and sustainable development. Detecting and predicting LUCC, a dynamic process, and its driving factors will help in formulating effective land use and planning policy suitable for local conditions, thus supporting local socioeconomic development and global environmental protection. In this study, taking Gansu Province as a case study example, we explored the LUCC pattern and its driving mechanism from 1980 to 2018, and predicted land use and cover in 2030 using the integrated LCM (Logistic-Cellular Automata-Markov chain) model and data from satellite remote sensing. The results suggest that the LUCC pattern was more reasonable in the second stage (2005 to 2018) compared with that in the first stage (1980 to 2005). This was because a large area of green lands was protected by ecological engineering in the second stage. From 1980 to 2018, in general, natural factors were the main force influencing changes in land use and cover in Gansu, while the effects of socioeconomic factors were not significant because of the slow development of economy. Landscape indices analysis indicated that predicted land use and cover in 2030 under the ecological protection scenario would be more favorable than under the historical trend scenario. Besides, results from the present study suggested that LUCC in arid and semiarid area could be well detected by the LCM model. This study would hopefully provide theoretical instructions for future land use planning and management, as well as a new methodology reference for LUCC analysis in arid and semiarid regions.

Description: Alfalfa (Medicago sativa L.) is an important legume forage crop. However, its genetic improvement for salt tolerance is challenging, as alfalfa’s response to salt stress is genetically and physiologically complex. A review was made to update the knowledge of morphological, physiological, biochemical, and genetic responses of alfalfa plants to salt stress, and to discuss the potential of applying modern plant technologies to enhance alfalfa salt-resistant breeding, including genomic selection, RNA-Seq analysis, and cutting-edge Synchrotron beamlines. It is clear that alfalfa salt tolerance can be better characterized, genes conditioning salt tolerance be identified, and new marker-based tools be developed to accelerate alfalfa breeding for salt tolerance.

Description: Wearable sensors are a topic of interest in medical healthcare monitoring due to their compact size and portability. However, providing power to the wearable sensors for continuous health monitoring applications is a great challenge. As the batteries are bulky and require frequent charging, the integration of the wireless power transfer (WPT) module into wearable and implantable sensors is a popular alternative. The flexible sensors benefit by being wirelessly powered, as it not only expands an individual’s range of motion, but also reduces the overall size and the energy needs. This paper presents the design, modeling, and experimental characterization of flexible square-shaped spiral coils with different scaling factors for WPT systems. The effects of coil scaling factor on inductance, capacitance, resistance, and the quality factor (Q-factor) are modeled, simulated, and experimentally validated for the case of flexible planar coils. The proposed analytical modeling is helpful to estimate the coil parameters without using the time-consuming Finite Element Method (FEM) simulation. The analytical modeling is presented in terms of the scaling factor to find the best-optimized coil dimensions with the maximum Q-factor. This paper also presents the effect of skin contact with the flexible coil in terms of the power transfer efficiency (PTE) to validate the suitability as a wearable sensor. The measurement results at 405 MHz show that when in contact with the skin, the 20 mm× 20 mm receiver (RX) coil achieves a 42% efficiency through the air media for a 10 mm distance between the transmitter (TX) and RX coils.

Description: Mangrove migration, or transgression in response to global climatic changes or sea-level rise, is a slow process; to capture it, understanding both the present distribution of mangroves at individual patch (single- or clumped trees) scale, and their rates of change are essential. In this study, a new method was developed to delineate individual patches and to estimate mangrove cover from very high-resolution (0.08 m spatial resolution) true color (Red (R), Green (G), and Blue (B) spectral channels) aerial photography. The method utilizes marker-based watershed segmentation, where markers are detected using a vegetation index and Otsu’s automatic thresholding. Fourteen commonly used vegetation indices were tested, and shadows were removed from the segmented images to determine their effect on the accuracy of tree detection, cover estimation, and patch delineation. According to point-based accuracy analysis, we obtained adjusted overall accuracies 〉90% in tree detection using seven vegetation indices. Likewise, using an object-based approach, the highest overlap accuracy between predicted and reference data was 95%. The vegetation index Excess Green (ExG) without shadow removal produced the most accurate mangrove maps by separating tree patches from shadows and background marsh vegetation and detecting more individual trees. The method provides high precision delineation of mangrove trees and patches, and the opportunity to analyze mangrove migration patterns at the scale of isolated individuals and patches.