Offshore LNG Production

A natural gas liquefaction plant was designed for offshore production of LNG, using only N2 and CO2 as refrigerants in the cooling cycles to avoid potential hazards of mixed hydrocarbon refrigerants. The process was designed to accommodate 13,500 lb-mole/hr (roughly 1MMmtpa) of raw natural gas feed, and fits within all parameters required in the process specifications. Safety concerns, the start-up process, and other potential considerations are also included. The Net Present Value of the project was found to be $37M at an internal rate of return (IRR) of 18.4%. Further analysis of the assumptions made in these calculations may be required before final project approval is made; however, estimates tend towards conservatism

Stability Analysis of an Autonomous Microgrid Operation Based on Particle Swarm Optimization

This paper presents the stability analysis for an inverter based Distributed Generation (DG) unit in an autonomous microgrid operation. The small-signal model of the controlled Voltage Source Inverter (VSI) system is developed in order to investigate the dynamic stability for the given operating point and under the proposed power controller. This model includes all the details of the proposed controller, while no switching actions are considered. System oscillatory modes and the sensitivity to the control parameters are the main performance indices which are considered, particularly when the microgrid is islanded or under the load change condition. In this work, the proposed power controller is composed of an inner current control loop and an outer power control loop, both based on a synchronous reference frame and conventional PI regulators. These controllers also utilize the Particle Swarm Optimization (PSO) for real-time self-tuning in order to improve the quality of the power supply. The complete small-signal model is linearized and used to define the system state matrix which is employed for eigenvalue analysis. The results prove that the stability analysis is fairly accurate and the controller offers reliable system\u27s operation

PSO algorithm for an optimal power controller in a microgrid

This paper presents the Particle Swarm Optimization (PSO) algorithm to improve the quality of the power supply in a microgrid. This algorithm is proposed for a real-time selftuning method that used in a power controller for an inverter based Distributed Generation (DG) unit. In such system, the voltage and frequency are the main control objectives, particularly when the microgrid is islanded or during load change. In this work, the PSO algorithm is implemented to find the optimal controller parameters to satisfy the control objectives. The results show high performance of the applied PSO algorithm of regulating the microgrid voltage and frequency

Binding of Extracellular Maspin to 1 Integrins Inhibits Vascular Smooth Muscle Cell Migration

Maspin is a serpin that has multiple effects on cell behavior, including inhibition of migration. How maspin mediates these diverse effects remains unclear, as it is devoid of protease inhibitory activity. We have previously shown that maspin rapidly inhibits the migration of vascular smooth muscle cells (VSMC), suggesting the involvement of direct interactions with cell surface proteins. Here, using immunofluorescence microscopy, we demonstrate that maspin binds specifically to the surface of VSMC in the dedifferentiated, but not the differentiated, phenotype. Ligand blotting of VSMC lysates revealed the presence of several maspin-binding proteins, with a protein of 150 kDa differentially expressed between the two VSMC phenotypes. Western blotting suggested that this protein was the ß1 integrin subunit, and subsequently both a3ß1 and a5ß1, but not avß3, were shown to associate with maspin by coimmunoprecipitation. Specific binding of these integrins was also observed using maspin-affinity chromatography, using HT1080 cell lysates. Direct binding of maspin to a5ß1 was confirmed using a recombinant a5ß1-Fc fusion protein. Using conformation-dependent anti-ß1 antibodies, maspin binding to VSMC was found to lead to a decrease in the activation status of the integrin. The functional involvement of a5ß1 in mediating the effect of maspin was established by the inhibition of migration of CHO cells overexpressing human a5 integrin, but not those lacking a5 expression. Our observations suggest that maspin engages in specific interactions with a limited number of integrins on VSMC, leading to their inactivation, and that these interactions are responsible for the effects of maspin in the pericellular environment

An in silico model to demonstrate the effects of Maspin on cancer cell dynamics

Most cancer treatments efficacy depends on tumor metastasis suppression, where tumor suppressor genes play an important role. Maspin (Mammary Serine Protease Inhibitor), an non-inhibitory serpin has been reported as a potential tumor suppressor to influence cell migration, adhesion, proliferation and apoptosis in in vitro and in vivo experiments in last two decades. Lack of computational investigations hinders its ability to go through clinical trials. Previously, we reported first computational model for maspin effects on tumor growth using artificial neural network and cellular automata paradigm with in vitro data support. This paper extends the previous in silico model by encompassing how maspin influences cell migration and the cell–extracellular matrix interaction in subcellular level. A feedforward neural network was used to define each cell behavior (proliferation, quiescence, apoptosis) which followed a cell-cycle algorithm to show the microenvironment impacts over tumor growth. Furthermore, the model concentrates how the in silico experiments results can further confirm the fact that maspin reduces cell migration using specific in vitro data verification method. The data collected from in vitro and in silico experiments formulates an unsupervised learning problem which can be solved by using different clustering algorithms. A density based clustering technique was developed to measure the similarity between two datasets based on the number of links between instances. Our proposed clustering algorithm first finds the nearest neighbors of each instance, and then redefines the similarity between pairs of instances in terms of how many nearest neighbors share the two instances. The number of links between two instances is defined as the number of common neighbors they have. The results showed significant resemblances with in vitro experimental data. The results also offer a new insight into the dynamics of maspin and establish as a metastasis suppressor gene for further molecular research

Local diversity of heathland Cercozoa explored by in-depth sequencing

Cercozoa are abundant free-living soil protozoa and quantitatively important in soil food webs; yet, targeted high-throughput sequencing (HTS) has not yet been applied to this group. Here we describe the development of a targeted assay to explore Cercozoa using HTS, and we apply this assay to measure Cercozoan community response to drought in a Danish climate manipulation experiment (two sites exposed to artificial drought, two unexposed). Based on a comparison of the hypervariable regions of the 18S ribosomal DNA of 193 named Cercozoa, we concluded that the V4 region is the most suitable for group-specific diversity analysis. We then designed a set of highly specific primers (encompassing ~270 bp) for 454 sequencing. The primers captured all major cercozoan groups; and >95% of the obtained sequences were from Cercozoa. From 443 350 high-quality short reads (>300 bp), we recovered 1585 operational taxonomic units defined by >95% V4 sequence similarity. Taxonomic annotation by phylogeny enabled us to assign >95% of our reads to order level and ~85% to genus level despite the presence of a large, hitherto unknown diversity. Over 40% of the annotated sequences were assigned to Glissomonad genera, whereas the most common individually named genus was the euglyphid Trinema. Cercozoan diversity was largely resilient to drought, although we observed a community composition shift towards fewer testate amoebae

A quantitative image analysis for the cellular cytoskeleton during in vitro tumor growth

The cellular cytoskeleton is a dynamic subcellular structure that can be a marker of key biological phenomena including cell division, organelle movement, shape changes and locomotion during the avascular tumor phase. Little attention is paid to quantify changes in the cytoskeleton while nuclei and cytoplasmic both are present in subcellular microscopic images. In this paper, we proposed a quantitative image analysis method to analyze subcellular cytoskeletal changes using a texture analysis method preceded by segmentation of nuclei, cytoplasm and ruffling regions (area except nuclei and cytoplasm). To test and validate this model we hypothesized that Mammary Serine Protease Inhibitor (maspin) acts as cytoskeleton regulator that mediates cell-extracellular matrix (ECM) adhesion in tumor. Maspin-a tumor suppressor gene shows multiple tumor suppressive properties such as increasing tumor cell apoptosis and reducing migration, proliferation, invasion, and overall tumor metastasis. The proposed method obtained separated ruffling regions from segmentation steps and then adopted gray–level histograms (GLH) and grey-level co-occurrence matrix (GLCM) texture analysis techniques. In order to verify the reliability, the proposed texture analysis method was used to compare the control and maspin expressing cells grown on different ECM components: plastic, collagen I, fibronectin and laminin. The results show that the texture parameters extracted reflect the different cytoskeletal changes. These changes indicate that maspin acts as a regulator of the cell-ECM enhancement process, while it reduces the cell migration. Overall, this paper not only presents a quantitative image analysis approach to analyze subcellular cytoskeletal architectures but also provides a comprehensive tool for the biologist, pathologist, cancer specialist, and computer scientist to understand cellular and subcellular organization of cells. In long term, this method can be extended to be used in live cell tracking in vivo, image informatics based point-of-care expert system and quantification of various complex architectures in organisms

Leadership Style and Organizational Commitment among Nursing Staff in Saudi Arabia

© 2018 The Authors. Aims: To examine how nurse managers' leadership styles, and nurses' organisational commitment in Saudi Arabia relate. Background: Effective leadership is influential in staff retention; however, recruiting and maintaining nurses is an increasing problem in Saudi Arabia. Methods: Using a survey design, the Multifactor Leadership Questionnaire and the Organisational Commitment Questionnaire were distributed to a sample of 219 nurses and nurse managers from two hospitals in Saudi Arabia. Results: Transformational leadership was the most dominant leadership style. After controlling for the influence of manager/staff status, nationality and hospitals, transformational leadership was the strongest contributor to organisational commitment. Perceptions of both transformational and transactional leadership styles, increased with age for nurse managers and nursing staff. Conclusion: Introducing the Full Range of Leadership model to the Saudi nursing workforce could help to prepare Saudi nurses for positions as nurse managers and leaders. Implications for Nursing Management: The study provides insight into the type of leadership that is best suited to the dynamic and changing health care system in Saudi Arabia. It is possible that transformational leaders could influence and induce positive changes in nursing

Effects of Noninhibitory Serpin Maspin on the Actin Cytoskeleton: A Quantitative Image Modeling Approach

Recent developments in quantitative image analysis allow us to interrogate confocal microscopy images to answer biological questions. Clumped and layered cell nuclei and cytoplasm in confocal images challenges the ability to identify subcellular compartments. To date, there is no perfect image analysis method to identify cytoskeletal changes in confocal images. Here, we present a multidisciplinary study where an image analysis model was developed to allow quantitative measurements of changes in the cytoskeleton of cells with different maspin exposure. Maspin, a noninhibitory serpin influences cell migration, adhesion, invasion, proliferation, and apoptosis in ways that are consistent with its identification as a tumor metastasis suppressor. Using different cell types, we tested the hypothesis that reduction in cell migration by maspin would be reflected in the architecture of the actin cytoskeleton. A hybrid marker-controlled watershed segmentation technique was used to segment the nuclei, cytoplasm, and ruffling regions before measuring cytoskeletal changes. This was informed by immunohistochemical staining of cells transfected stably or transiently with maspin proteins, or with added bioactive peptides or protein. Image analysis results showed that the effects of maspin were mirrored by effects on cell architecture, in a way that could be described quantitatively

Identification of novel peptide motifs in the serpin maspin that affect vascular smooth muscle cell function

Maspin is a non-inhibitory member of the serpin family that affects cell behaviours related to migration and survival. We have previously shown that peptides of the isolated G α-helix (G-helix) domain of maspin show bioactivity. Migration, invasion, adhesion and proliferation of vascular smooth muscle cells (VSMC) are important processes that contribute to the build-up of atherosclerotic plaques. Here we report the use of functional assays of these behaviours to investigate whether other maspin-derived peptides impact directly on VSMC; focusing on potential anti-atherogenic properties. We designed 18 new peptides from the structural moieties of maspin above ten amino acid residues in length and considered them beside the existing G-helix peptides. Of the novel peptides screened those with the sequences of maspin strand 4 and 5 of beta sheet B (S4B and S5B) reduced VSMC migration, invasion and proliferation, as well as increasing cell adhesion. A longer peptide combining these consecutive sequences showed a potentiation of responses, and a 7-mer contained all essential elements for functionality. This is the first time that these parts of maspin have been highlighted as having key roles affecting cell function. We present evidence for a mechanism whereby S4B and S5B act through ERK1/2 and AMP-activated protein kinase (AMPK) to influence VSMC responses