A low phytic acid (lpa) rice mutant line, denoted as Os-lpa-XS110-2, was developed through gamma irradiation (Liu et al., 2007). Subsequently, this mutant line was cultivated alongside its parental wild-type counterpart, Xiushui 110, in four distinct field trials conducted in China. The primary objective of this research was to conduct a comparative proteomic analysis between the parental and mutant lines, aiming to detect and compare protein species with varying levels of relative abundance and their potential involvement in phytic acid biosynthesis. To elucidate the molecular underpinnings of this alteration, proteome analyses were conducted on both the parental and mutant lines, employing LC-MS/MS in conjunction with 2-dimensional gel electrophoresis. Only, 7 proteins consistently exhibited significant differential abundance across all trial locations, suggesting that the regulation of these proteins is less susceptible to environmental influences. In a broader context, among the 700 detected proteins, 56 displayed noteworthy up- or down-regulation across diverse geographical regions. Notably, storage and housekeeping proteins emerged as the most frequently identified protein categories, with globulin and glutelin demonstrating prominent differences in abundance. However, based on our current understanding, none of the identified proteins appear to have direct roles in phytic acid biosynthesis.

Alcohol use is one of the main risk factors related to many diseases. However, alcohol use information is buried in the patient's clinical records, and extracting this information from narrative text requires substantial manual labor. This work aims to develop an automated system for detecting alcohol use status from patients' discharge summaries. A combination of machine learning and rule-based techniques has been employed in order to identify alcohol status in three stages. In the first stage, the proposed system detects alcohol-related sentences by utilizing a keyword search technique. The second stage distinguishes between the negative and positive alcohol sentences and identifies the temporal status. In this stage different machine learning classifiers have been employed in order to achieve the best performance. Finally, the document level alcohol use status is aggregated from the sentence-level for each patient's record. The proposed system exhibits high performance in identifying alcohol use status, achieving an Fl-score up to 0.99 in identifying alcohol use related records, 0.96 in detecting negative records and 0.89 identifying temporal status.

This paper presents an integrated artificial neural network (ANN) approach for the design and prediction of energy generated from a thermoelectric generator (TEG) under the influence of the operating environmental parameters. The unique ANN model can predict the output voltage generated as well as ensuring the reliability of the output. Deriving of individual input parameter can also be obtained from the learned network when given a required output voltage together with sensitivity analysis for the identification of key input parameters that have strong influence in the output value generated by the TEG were also incorporated in the model, making it an efficient tool for the design and conceptualisation of a TEG. This proposed approach is particularly useful when TEG users are faced with limited resources for achieving their required output power. The developed ANN model shows the mean square error (MSE) of 0.0008 in modelling an experimental dataset consisting of 4096 data. The predicted results obtained from the optimized ANN model are also verified with the testing of experimental data and a good agreement is obtained with errors of +/− 0.15.

Understanding the information and clusters hidden inside multidimensional data can be challenging and complicated. Dimension reduction is usually considered as the first step for data analysis and interpretation. The focus of this paper is on the improvement of data clustering performance of Self Organising Maps (SOM) by embedding Auto-Associative Neural Networks (AANN). SOM is known as a computational tool that carries out topology preservation from high-dimensional input space onto a low-dimensional grid such as two-dimensional (2D) map. It has been used to visualize and explore inherent clusters and properties of the data. In this paper, a structurally flexible combination of AANN and SOM is developed, applied and investigated on Iris Flowers and Italian Olive oils datasets. The results have shown that the combined technique of AANNSOM has led to improvement of data clustering performance. It has reduced quantization error by 93.1 %, and topographic error by 35.2%, when compared to SOM alone.

Thermoelectric generators (TEG) convert the thermal energy flowing through them into electrical energy in a quantity dependent on the temperature gradient across the thermocouple between the TEG ceramic substrates. Electrical outputs generated by the TEG shown on technical sheets provided by the manufacturer are usually a mismatch to the actual energy generated. This is due to the measurement methods, which are usually conducted under laboratory conditions, often omitting the environmental parameters that the TEG is or will be operating in. Hence the mismatch is of relevant importance to simulating the evolution of thermoelectric systems during thermal transients. In this paper, a finite volume method for three dimensional diffusions to derive the surface temperature on the TEG ceramic substrate is used in conjunction with the environmental parameters and construction material to predict the temperature gradient with high accuracy which will therefore reflect a more precise output voltage generated by the TEG.

The genus Pseudoalteromonas constitutes an ecologically significant group of marine Gammaproteobacteria with potential biotechnological value as producers of bioactive compounds and of enzymes. Understanding their roles in the environment and bioprospecting for novel products depend on efficient ways of identifying environmental isolates. Matrix Assisted Laser Desorption/Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) biotyping has promise as a rapid and reliable method of identifying and distinguishing between different types of bacteria, but has had relatively limited application to marine bacteria and has not been applied systematically to Pseudoalteromonas. Therefore, we constructed a MALDI-TOF MS database of 31 known Pseudoalteromonas species, to which new isolates can be compared by MALDI-TOF biotyping. The ability of MALDI-TOF MS to distinguish between species was scrutinized by comparison with 16S rRNA gene sequencing. The patterns of similarity given by the two approaches were broadly but not completely consistent. In general, the resolution of MALDI-TOF MS was greater than that of 16S rRNA gene sequencing. The database was tested with 13 environmental Pseudoalteromonas isolates from UK waters. All of the test strains could be identified to genus level by MALDI-TOF MS biotyping, but most could not be definitely identified to species level. We conclude that several of these isolates, and possibly most, represent new species. Thus, further taxonomic investigation of Pseudoalteromonas is needed before MALDI-TOF MS biotyping can be used reliably for species identification. It is, however, a powerful tool for characterizing and distinguishing among environmental isolates and can make an important contribution to taxonomic studies.

The prasinophytes (early diverging Chlorophyta), consisting of simple unicellular green algae, occupy a critical position at the base of the green algal tree of life, with some of its representatives viewed as the cell form most similar to the first green alga, the 'ancestral green flagellate'. Relatively large-celled unicellular eukaryotic phytoflagellates (such as Tetraselmis and Scherffelia), traditionally placed in Prasinophyceae but now considered as members of Chlorodendrophyceae (core Chlorophyta), have retained some primitive characteristics of prasinophytes. These organisms share several ultrastructural features with the other core chlorophytes (Trebouxiophyceae, Ulvophyceae and Chlorophyceae). However, the role of Chlorodendrophycean algae as the evolutionary link between cellular individuality and cellular cooperation has been largely unstudied. Here, we show that clonal populations of a unicellular chlorophyte, Tetraselmis indica, consist of morphologically and ultrastructurally variant cells which arise through asymmetric cell division. These cells also differ in their physiological properties. The structural and physiological differences in the clonal cell population correlate to a certain extent with the longevity and function of cells.

Structure-borne noise is an important aspect of offshore platform sound field. It can be generated either directly by vibrating machineries induced mechanical force, indirectly by the excitation of structure or excitation by incident airborne noise. Therefore, limiting of the transmission of vibration energy throughout the offshore platform is the key to control the structureborne noise. This is usually done by introducing damping treatment to the steel structures. Two types of damping treatment using onboard are presented. By conducting a Statistical Energy Analysis (SEA) simulation on a jack-up rig, the noise level in the source room, the neighboring rooms, and remote living quarter cabins are compared before and after the damping treatments been applied. The results demonstrated that, in the source neighboring room and living quarter area, there is a significant noise reduction with the damping treatment applied, whereas in the source room where air-borne sound predominates that of structure-borne sound, the impact is not obvious. The conclusion on effective damping treatment in the offshore platform is made which enable acoustic professionals to implement noise control during the design stage for offshore crews’ hearing protection and habitant comfortability. Keywords—Statistical energy analysis, damping treatment, noise control, offshore platform.

This paper aims to develop a prototype for a web-based wireless remote temperature monitoring device for patients. This device uses a patient and coordinator set design approach involving the measurement, transmission, receipt and recording of patients’ temperatures via the MiWi wireless network. The results of experimental tests on the proposed system indicated a wider distance coverage and reasonable temperature resolution and standard deviation. The system could display the temperature and patient information remotely via a graphical-user interface as shown in the tests on three healthy participants. By continuously monitoring participants’ temperatures, this device will likely improve the quality of the health care of the patients in normal ward as less human workload is involved.

Accurate and defendable taxonomic identification of microalgae strains is vital for culture collections, industry and academia; particularly when addressing issues of intellectual property. We demonstrate the remarkable effectiveness of Matrix Assisted Laser Desorption Ionisation Time of Flight Mass Spectrometry (MALDI-TOF-MS) biotyping to deliver rapid and accurate strain separation, even in situations where standard molecular tools prove ineffective. Highly distinctive MALDI spectra were obtained for thirty two biotechnologically interesting Dunaliella strains plus strains of Arthrospira , Chlorella , Isochrysis, Tetraselmis and a range of culturable co-occurring bacteria. Spectra were directly compared with genomic DNA sequences (internal transcribed spacer, ITS). Within individual Dunaliella isolates MALDI discriminated between strains with identical ITS sequences, thereby emphasising and enhancing knowledge of the diversity within microalgae culture collections. Further, MALDI spectra did not vary with culture age or growth stage during the course of the experiment; therefore MALDI presents stable and accurate strain-specific signature spectra. Bacterial contamination did not affect MALDI’s discriminating power. Biotyping by MALDI-TOF-MS will prove effective in situations wherein precise strain identification is vital, for example in cases involving intellectual property disputes and in monitoring and safeguarding biosecurity. MALDI should be accepted as a biotyping tool to complement and enhance standard molecular taxonomy for microalgae.

The unsupervised learning of Self Organizing Map (SOM) is an effective computational tool in data mining exploration processes. It provides topology preserved data mapping from high-dimensional input space into low-dimensional representation such as two-dimensional map. The visualization and classification of clustered data even with good topological preservation between input and output spaces however are not always easy to be interpreted especially when the data are unknown. The boundaries between the clusters and sub-clusters mapped on SOM map are occasionally not clear. In this paper, we develop an improved SOM (iSOM) method to produce an alternative SOM clustering, classification and visualization. The proposed method firstly groups data into their own classes and then arrange them on the third axis according to their computational distances to winning neurons. The method is demonstrated by computing iSOM clustering and classification on Iris Flowers dataset. The computational results have shown that iSOM was able to provide additional inherent information compared to SOM method. The separation of classes, the positions of a data with respect to other data, the existence of sub-clusters have been clearly presented while classification accuracy has increased.

Lithium Iron phosphate (LiFePO4) battery has obtained extensive attention of researchers for its high energy density, little contamination and ready availability. In this paper, different numbers of RC branches in the equivalent Thevenin circuit model are explored by comparing accuracy of curve fitting with in-house experimental data. Besides, battery system with 6 cells of second order equivalent circuit is modeled using Matlab/Simscape. A multirate strong tracking extended filter (MRSTEKF) is proposed by introducing the multirate control strategy and lifting technology into strong tracking extended Kalman filter (STEKF) to improve tracking stability and estimation precision of state of charge (SOC). Root mean square error (RMSE) is exploited to evaluate the performance of the algorithms of extended Kalman filter (EKF), STEKF and MRSTEKF. Simulation results demonstrate that the proposed MRSTEKF is faster than EKF and STEKF by 55.34% and 49.51%, and is more precise by 52.66% and 33.88%.

Dynamic modeling and simulation of remotely-operated vehicle (ROV) are essential for search and rescue mission using AUV in remote distance. For initial model, hydrodynamic coefficients used in the ROV dynamic model are estimated using computation and analytical methods. The control strategy from launch to recovery is simulated using MATLABTM and SimulinkTM software. A three-dimension animation for ROV underwater operation is used to visualize the launch and recovery process of the AUV. The control simulation using a sliding mode controller (SMC) is designed to control the surge, sway, heave and yaw positions and velocities of the ROV under the sea wave and current disturbances. Simulated results show that the ROV is able to capture the AUV under the effect of current and wave disturbances.

Natural gas, one of the fossil fuels, has shown promising growth due to its price and lower pollutant emissions compared to other fossil fuels. One option for transporting natural gas is the use of Liquefied Natural Gas (LNG) carriers. An LNG carrier is one of the most expensive, complex and potentially hazardous cargo carriers that is operating across the world's oceans due to its cargo. The aim of this paper is to identify the relationship of seven main components involved in constructing an LNG carrier. It can be done through an understanding of the principals involved in the LNG carrier design process. Understanding each component and the inter-component relationships requires detailed investigation into the behaviour of components relative to any changes in the multitude of variables. The main challenge is to consider and adapt all of the possible constraints within each component. Here, each component is required to communicate with each other in one language. As a result a comprehensive ‘system of systems’ of an LNG carrier relationship will be developed to be used as a tool to construct a new LNG carrier efficiently.

Uptake and discharge of ballast water by ocean-going ships contribute to the worldwide spread of aquatic invasive species, with negative impacts on the environment, economies, and public health. The International Ballast Water Management Convention aims at a global answer. The agreed standards for ballast water discharge will require ballast water treatment. Systems based on various physical and/or chemical methods were developed for on-board installation and approved by the International Maritime Organization. Most common are combinations of high-performance filters with oxidizing chemicals or UV radiation. A well-known problem of oxidative water treatment is the formation of disinfection by-products, many of which show genotoxicity, carcinogenicity, or other long-term toxicity. In natural biota, genetic damages can affect reproductive success and ultimately impact biodiversity. The future exposure towards chemicals from ballast water treatment can only be estimated, based on land-based testing of treatment systems, mathematical models, and exposure scenarios. Systematic studies on the chemistry of oxidants in seawater are lacking, as are data about the background levels of disinfection by-products in the oceans and strategies for monitoring future developments. The international approval procedure of ballast water treatment systems compares the estimated exposure levels of individual substances with their experimental toxicity. While well established in many substance regulations, this approach is also criticised for its simplification, which may disregard critical aspects such as multiple exposures and long-term sub-lethal effects. Moreover, a truly holistic sustainability assessment would need to take into account factors beyond chemical hazards, e.g. energy consumption, air pollution or waste generation.

As implementation of the Ballast Water Convention draws nearer a major challenge is the development of protocols which accurately assess compliance with the D-2 Standard. Many factors affect the accuracy of assessment: e.g. large volume of ballast water, the shape, size and number of ballast tanks and the heterogeneous distribution of organisms within tanks. These factors hinder efforts to obtain samples that truly represent the total ballast water onboard a vessel. A known cell density of Tetraselmis suecica was added to a storage tank and sampled at discharge. The factors holding period, initial cell density and sampling interval affected representativeness. Most samples underestimated cell density, and some tanks with an initial cell density of 100 cells ml−1 showed <10 cells ml−1 at discharge, i.e. met the D-2 standard. This highlights difficulties in achieving sample representativeness and when applied to a real ballast tank this will be much harder to achieve.

The aim of this paper is to illustrate the main relationship between the independent variables that heavily contribute to fleet resizing. Commonly a shipping company has a fleet for transporting the goods from one port to another around the world. This fleet consists of a group of carriers that transports a fixed amount of cargo between two ports over a period of time and for a fixed cost. The number of carriers in the fleet is heavily dependent on the amount of goods to be delivered annually as stated in the contract. The number of carriers can vary according to the size and speed of the vessels. In addition, fleet operations, scheduling, routing and fleet design can contribute to the development of the overall configuration of the shipping fleet. Specialised long haul carriers with known operating routes such as liquefied natural gas (LNG) carrier transportation depends on the following factors: the ship's daily running costs, voyage costs, costs at sea, costs at port and daily lay-up costs, as well as the number of round voyages per year, lay-up costs of the carrier and number of lay-up days per year. It is clear that there are many different input parameters that are required for fleet optimisation. The objective of fleet optimisation is generally to find the ideal number of ships to deliver the goods according to the contract and to reduce overall fleet costs. The costs are referred to as capital and operational costs. The capital costs or initial expenses are all of the costs that are incurred prior to the commissioning and entry into service of the LNG carrier. Meanwhile, other fixed and variable costs, or future expenses, are all costs that are incurred after delivery of the vessel. However before carried out any fleet optimisation, comprehensive study regarding relationship between all the parameters that affect the fleet size should be established.