Search results for: nonideal complex plasma

Authors: Randa Alharbi, Vladislav Vyshemirsky

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Systems biology is an important field in science which focuses on studying behaviour of biological systems. Modelling is required to produce detailed description of the elements of a biological system, their function, and their interactions. A well-designed model requires selecting a suitable mechanism which can capture the main features of the system, define the essential components of the system and represent an appropriate law that can define the interactions between its components. Complex biological systems exhibit stochastic behaviour. Thus, using probabilistic models are suitable to describe and analyse biological systems. Continuous-Time Markov Chain (CTMC) is one of the probabilistic models that describe the system as a set of discrete states with continuous time transitions between them. The system is then characterised by a set of probability distributions that describe the transition from one state to another at a given time. The evolution of these probabilities through time can be obtained by chemical master equation which is analytically intractable but it can be simulated. Uncertain parameters of such a model can be inferred using methods of Bayesian inference. Yet, inference in such a complex system is challenging as it requires the evaluation of the likelihood which is intractable in most cases. There are different statistical methods that allow simulating from the model despite intractability of the likelihood. Approximate Bayesian computation is a common approach for tackling inference which relies on simulation of the model to approximate the intractable likelihood. Particle Markov chain Monte Carlo (PMCMC) is another approach which is based on using sequential Monte Carlo to estimate intractable likelihood. However, both methods are computationally expensive. In this paper we discuss the efficiency and possible practical issues for each method, taking into account the computational time for these methods. We demonstrate likelihood-free inference by performing analysing a model of the Repressilator using both methods. Detailed investigation is performed to quantify the difference between these methods in terms of efficiency and computational cost.

Keywords: Approximate Bayesian computation(ABC), Continuous-Time Markov Chains, Sequential Monte Carlo, Particle Markov chain Monte Carlo (PMCMC)

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Authors: Su-Lin Yu

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Coalition politics has been one of feminists’ persistent concerns. Following recent feminist discussion on new modes of affiliation across difference, she will explore how the process of female subject formation depends on alliances across different cultural locations. First, she will examine how coalition politics is reformulated across difference in contemporary feminist literature. In particular, the paper will identify the particular contexts and locations in which coalition building both enables and constrains the female subject. She will attempt to explore how contemporary feminist literature highlights the possibilities and limitations for solidarity and affiliations. To understand coalition politics in contemporary feminist works, she will engage in close readings of two texts: Rebecca Walker’s Black, White and Jewish: Memoir of a Shifting Self and Danzy Senna’s Caucasia. Both Walker and Senna have articulated the complex nodes of identity that are staged by a politics of location as they refuse to be boxed into simplistic essentialist positions. Their texts are characterized by the characters’ racial ambiguity and their social and geographical mobility of life in the contemporary United States. Their experiences of living through conflictual and contradictory relationships never fully fit the boundaries of racial categorization. Each of these texts demonstrates the limits as well as the possibilities of working with diversity among and within persons and groups, thus, laying the ground for complex alliance formation. Because each of the protagonists must negotiate a set of contradictions, they will have to constantly shift their affiliations. Rather than construct a static alliance, they describe a process of moving ‘beyond boundaries,’ an embracing of multiple locations. As self-identified third wavers, Rebecca Walker and Danzy Senna have been identified and marked with the status of ‘leader’ by the feminist establishment and by mainstream U.S. media. Their texts have captured both mass popularity and critical attention in the feminist and, often, the non-feminist literary community. By analyzing these texts, she will show how contemporary American feminist literature reveals coalition politics which is fraught with complications and unintended consequences. Taken as a whole, then, these works provide an important examination not only of coalition politics of American feminism, but also a snapshot of a central debate among feminist critique of coalition politics as a whole.

Keywords: coalition politics, contemporary women’s literature, identity, female subject

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Authors: A. H. Nanher, N. P. Singh, Shashidhar Yadav, Sachin Tyagi

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Agricultural production system is an outcome of a complex interaction of seed, soil, water and agro-chemicals (including fertilizers). Therefore, judicious management of all the inputs is essential for the sustainability of such a complex system. Precision agriculture gives farmers the ability to use crop inputs more effectively including fertilizers, pesticides, tillage and irrigation water. More effective use of inputs means greater crop yield and/or quality, without polluting the environment the focus on enhancing the productivity during the Green Revolution coupled with total disregard of proper management of inputs and without considering the ecological impacts, has resulted into environmental degradation. To evaluate a new approach for site-specific nutrient management (SSNM). Large variation in initial soil fertility characteristics and indigenous supply of N, P, and K was observed among Field- and season-specific NPK applications were calculated by accounting for the indigenous nutrient supply, yield targets, and nutrient demand as a function of the interactions between N, P, and K. Nitrogen applications were fine-tuned based on season-specific rules and field-specific monitoring of crop N status. The performance of SSNM did not differ significantly between high-yielding and low-yielding climatic seasons, but improved over time with larger benefits observed in the second year Future, strategies for nutrient management in intensive rice systems must become more site-specific and dynamic to manage spatially and temporally variable resources based on a quantitative understanding of the congruence between nutrient supply and crop demand. The SSNM concept has demonstrated promising agronomic and economic potential. It can be used for managing plant nutrients at any scale, i.e., ranging from a general recommendation for homogenous management of a larger domain to true management of between-field variability. Assessment of pest profiles in FFP and SSNM plots suggests that SSNM may also reduce pest incidence, particularly diseases that are often associated with excessive N use or unbalanced plant nutrition.

Keywords: nutrient, pesticide, crop, yield

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Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Neumoin Anton Ivanovich, Opra Denis Pavlovich

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Materials based on titanium oxide compounds are widely used in such areas as solar energy, photocatalysis, food industry and hygiene products, biomedical technologies, etc. Demand for them has also formed in the battery industry (an example of this is the commercialization of Li4Ti5O12), where much attention has recently been paid to the development of next-generation systems and technologies, such as sodium-ion batteries. This dictates the need to search for new materials with improved characteristics, as well as ways to obtain them that meet the requirements of scalability. One of the ways to solve these problems can be the creation of nanomaterials that often have a complex of physicochemical properties that radically differ from the characteristics of their counterparts in the micro- or macroscopic state. At the same time, it is important to control the texture (specific surface area, porosity) of such materials. In view of the above, among other methods, the hydrothermal technique seems to be suitable, allowing a wide range of control over the conditions of synthesis. In the present study, a method was developed for the preparation of mesoporous nanostructured sodium trititanate (Na2Ti3O7) with a hierarchical architecture. The materials were synthesized by hydrothermal processing and exhibit a complex hierarchically organized two-layer architecture. At the first level of the hierarchy, materials are represented by particles having a roughness surface, and at the second level, by one-dimensional nanotubes. The products were found to have high specific surface area and porosity with a narrow pore size distribution (about 6 nm). As it is known, the specific surface area and porosity are important characteristics of functional materials, which largely determine the possibilities and directions of their practical application. Electrochemical impedance spectroscopy data show that the resulting sodium trititanate has a sufficiently high electrical conductivity. As expected, the synthesized complexly organized nanoarchitecture based on sodium trititanate with a porous structure can be practically in demand, for example, in the field of new generation electrochemical storage and energy conversion devices.

Keywords: sodium trititanate, hierarchical materials, mesoporosity, nanotubes, hydrothermal synthesis

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Authors: A. Abbasi Moshaii, M. Soltan Rezaee, M. Mohammadi Moghaddam

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Control of some mechanisms is hard because of their complex dynamic equations. If part of the complexity is resulting from uncertainties, an efficient way for solving that is robust control. By this way, the control procedure could be simple and fast and finally, a simple controller can be designed. One kind of these mechanisms is 3-RRR which is a parallel mechanism and has three revolute joints. This paper aims to robust control a 3-RRR planner mechanism and it presents that this could be used for other mechanisms. So, a significant problem in mechanisms control could be solved. The relevant diagrams are drawn and they show the correctness of control process.

Keywords: 3-RRR, dynamic equations, mechanisms control, structural uncertainty

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Authors: Poonam Sharma, Ankur Srivastav

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Cities are complex and dynamic systems that constitute a significant challenge to urban planning. The increasing size of the built-up area owing to growing population pressure and economic growth have lead to massive Landuse/Landcover change resulted in the loss of natural habitat and thus reducing the green covers in urban areas. Urban environmental quality is influenced by several aspects, including its geographical configuration, the scale, and nature of human activities occurring and environmental impacts generated. Cities have transformed into complex and dynamic systems that constitute a significant challenge to urban planning. Cities and their sustainability are often discussed together as the cities stand confronted with numerous environmental concerns as the world becoming increasingly urbanized, and the cities are situated in the mesh of global networks in multiple senses. A rapid transformed urban setting plays a crucial role to change the green area of natural habitats. To examine the pattern of urban growth and to measure the Landuse/Landcover change in Gurgoan in Haryana, India through the integration of Geospatial technique is attempted in the research paper. Satellite images are used to measure the spatiotemporal changes that have occurred in the land use and land cover resulting into a new cityscape. It has been observed from the analysis that drastically evident changes in land use has occurred with the massive rise in built up areas and the decrease in green cover and therefore causing the sustainability of the city an important area of concern. The massive increase in built-up area has influenced the localised temperatures and heat concentration. To enhance the decision-making process in urban planning, a detailed and real world depiction of these urban spaces is the need of the hour. Monitoring indicators of key processes in land use and economic development are essential for evaluating policy measures.

Keywords: cityscape, geospatial techniques, green cover index, urban environmental quality, urban planning

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Authors: Harikrishna Yadav Nanganuru, Narasimhulu Korrapati

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The demand for the lead (Pb) in the battery industry has been growing for last twenty years. On an average about 2.35 million tons of lead is used in the battery industry. According to the survey of supply and demand battery industry is using 75% of lead produced every year. Due to the increase in battery scrap, secondary lead production has been increasing in this decade. Europe and USA together account for 75% of the world’s secondary lead production. The effluent from used battery scrap consists of high concentrations of lead. Unauthorized disposal of spent batteries, which contain intolerable concentration of lead, into landfills or municipal water canals causes release of Pb into the environment. Lead is one of the toxic heavy metals that have large damaging effects on the human health. Due to its persistence and toxicity, the presence of Pb in drinking water is considered as a special concern. Accumulation of Pb in the human body for long period of time can result in the malfunctioning of some organs. Many technologies have been developed for the removal of lead using microorganisms. In this paper, effluent was taken from the spent battery scrap and was characterized by inductively coupled plasma atomic emission spectrometer. Microorganisms play an important role in removal of lead from the contaminated sites. So, the bacteria were isolated from the effluent. Optimum conditions for the microbial growth and applied for the lead removal. These bacterial cells were immobilized and used for the removal of Pb from the known concentration of metal solution. Scanning electron microscopic (SEM) studies were shown that the Pb was efficiently adsorbed by the immobilized bacteria. From the results of Atomic Absorption Spectroscopy (AAS), 83.40 percentage of Pb was removed in a batch culture.

Keywords: adsorption, effluent, immobilization, lead (Pb)

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Authors: B. Godefroy, D. Beladjine, K. Beddiar

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In France, construction BIM actors commonly evoke the BIM gains for exploitation by integrating of the life cycle of a building. The standardization of level 7 of development would achieve this stage of the digital model. The householders include local public authorities, social landlords, public institutions (health and education), enterprises, facilities management companies. They have a dual role: owner and manager of their housing complex. In a context of financial constraint, the BIM of exploitation aims to control costs, make long-term investment choices, renew the portfolio and enable environmental standards to be met. It assumes a knowledge of the existing buildings, marked by its size and complexity. The information sought must be synthetic and structured, it concerns, in general, a real estate complex. We conducted a study with professionals about their concerns and ways to use it to see how householders could benefit from this development. To obtain results, we had in mind the recurring interrogation of the project management, on the needs of the operators, we tested the following stages: 1) Inculcate a minimal culture of BIM with multidisciplinary teams of the operator then by business, 2) Learn by BIM tools, the adaptation of their trade in operations, 3) Understand the place and creation of a graphic and technical database management system, determine the components of its library so their needs, 4) Identify the cross-functional interventions of its managers by business (operations, technical, information system, purchasing and legal aspects), 5) Set an internal protocol and define the BIM impact in their digital strategy. In addition, continuity of management by the integration of construction models in the operation phase raises the question of interoperability in the control of the production of IFC files in the operator’s proprietary format and the export and import processes, a solution rivaled by the traditional method of vectorization of paper plans. Companies that digitize housing complex and those in FM produce a file IFC, directly, according to their needs without recourse to the model of construction, they produce models business for the exploitation. They standardize components, equipment that are useful for coding. We observed the consequences resulting from the use of the BIM in the property industry and, made the following observations: a) The value of data prevail over the graphics, 3D is little used b) The owner must, through his organization, promote the feedback of technical management information during the design phase c) The operator's reflection on outsourcing concerns the acquisition of its information system and these services, observing the risks and costs related to their internal or external developments. This study allows us to highlight: i) The need for an internal organization of operators prior to a response to the construction management ii) The evolution towards automated methods for creating models dedicated to the exploitation, a specialization would be required iii) A review of the communication of the project management, management continuity not articulating around his building model, it must take into account the environment of the operator and reflect on its scope of action.

Keywords: information system, interoperability, models for exploitation, property industry

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Authors: M. Mathuthu, N. N. Gaxela, R. Y. Olobatoke

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A study was carried out to assess the heavy metal and radionuclide concentrations of water from the waste water treatment plant in Mafikeng Local Municipality to evaluate treatment efficiency. Ten water samples were collected from various stages of water treatment which included sewage delivered to the plant, the two treatment stages and the effluent and also the community. The samples were analyzed for heavy metal content using Inductive Coupled Plasma Mass Spectrometer. Gross α/β activity concentration in water samples was evaluated by Liquid Scintillation Counting whereas the concentration of individual radionuclides was measured by gamma spectroscopy. The results showed marked reduction in the levels of heavy metal concentration from 3 µg/L (As)–670 µg/L (Na) in sewage into the plant to 2 µg/L (As)–170 µg/L (Fe) in the effluent. Beta activity was not detected in water samples except in the in-coming sewage, the concentration of which was within reference limits. However, the gross α activity in all the water samples (7.7-8.02 Bq/L) exceeded the 0.1 Bq/L limit set by World Health Organization (WHO). Gamma spectroscopy analysis revealed very high concentrations of 235U and 226Ra in water samples, with the lowest concentrations (9.35 and 5.44 Bq/L respectively) in the in-coming sewage and highest concentrations (73.8 and 47 Bq/L respectively) in the community water suggesting contamination along water processing line. All the values were considerably higher than the limits of South Africa Target Water Quality Range and WHO. However, the estimated total doses of the two radionuclides for the analyzed water samples (10.62 - 45.40 µSv yr-1) were all well below the reference level of the committed effective dose of 100 µSv yr-1 recommended by WHO.

Keywords: gross α/β activity, heavy metals, radionuclides, 235U, 226Ra, water sample

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Authors: Clifford Lewis

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This paper aims to advance the conversation of an alternative view of leadership, namely ‘leadership as the management of meaning’. Here, leadership is considered as a social process of the management of meaning within an employment context, as opposed to a psychological trait, set of behaviours or relational consequence as seen in mainstream leadership research. Specifically, this study explores the relationship between intersectional identities and the management of meaning. Design: Semi-structured, one-on-one interviews were conducted with women and men of colour working in the South African private sector organisations in various leadership positions. Employing an intersectional approach using gender and race, participants were selected by using purposive and snowball sampling concurrently. Thematic and Axial coding was used to identify dominant themes. Findings: Findings suggest that, both gender and race shape how leaders manage meaning. Findings also confirm that intersectionality is an appropriate approach when studying the leadership experiences of those groups who are underrepresented in organisational leadership structures. The findings points to the need for further research into the differential effects of intersecting identities on organisational leadership experiences and that ‘leadership as the management of meaning’ is an appropriate approach for addressing this knowledge gap. Theoretical Contribution: There is a large body of literature on the complex challenges faced by women and people of colour in leadership but there is relatively little empirical work on how identity influences the management of meaning. This study contributes to the leadership literature by providing insight into how intersectional identities influence the management of meaning at work and how this impacts the leadership experiences of largely marginalised groups. Practical Implications: Understanding the leadership experiences of underrepresented groups is important because of both legal mandates and for building diverse talent for organisations and societies. Such an understanding assists practitioners in being sensitive to simplistic notions of challenges individuals might face in accessing and practicing leadership in organisations. Advancing the conversation on leadership as the management of meaning allows for a better understanding of complex challenges faced by women and people of colour and an opportunity for organisations to systematically remove unfair structural obstacles and develop their diverse leadership capacity.

Keywords: intersectionality, diversity, leadership, sensemaking

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Authors: Rahul Madathiparambil Visalakshan, Alex Cavallaro, John Hayball, Krasimir Vasilev

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The role of biomaterial surface nanotopograhy on fibrinogen adsorption and unfolding, and the subsequent immune response were studied. Inconsistent topography and varying chemical functionalities along with a lack of reproducibility pose a challenge in determining the specific effects of nanotopography or chemistry on proteins and cells. It is important to have a well-defined nanotopography with a homogeneous chemistry to study the real effect of nanotopography on biological systems. Therefore, we developed a technique that can produce well-defined and highly reproducible topography to identify the role of specific roughness, size, height and density with the presence of homogeneous chemical functionality. Using plasma polymerisation of oxazoline monomers and immobilized gold nanoparticles we created surfaces with an equal number density of nanoparticles of different sizes. This surface was used to study the role of surface nanotopography and the interplay of surface chemistry on proteins and immune cells. The effect of nanotopography on fibrinogen adsorption was investigated using Quartz Cristal Microbalance with Dissipation and micro BCA. The mass of fibrinogen adsorbed on the surface increased with increasing size of nano-topography. Protein structural changes up on adsorption to the nano rough surface was studied using circular dichroism spectroscopy. Fibrinogen unfolding varied depending on the specific nanotopography of the surfaces. It was revealed that the in vitro immune response to the nanotopography surfaces changed due to this protein unfolding.

Keywords: biomaterial inflammation, protein and cell responses, protein unfolding, surface nanotopography

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Authors: Abbas Ebrahimi, Zohreh Pourhossein, Nariman Miraalami

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The experiment was conducted to evaluate the effects of different levels of dried citrus sinensis peel (DCSP) on the blood parameters of broilers. Four hundred Ross 308 strain day old broiler in a completely randomized design with five treatments (four replicates per treatment and each replicate had 20 chicks) were categorized. Each treatment used either regulatory diet including 1.5% and 3% DCSP in the base diet and in two periods of 1st to 21st day and 1st to 42nd day and base diet without any additive for six weeks. Data analysis was performed using SAS software and mean comparison was conducted by Duncan method. The results determined that using different level of DCSP has significant effects on blood plasma parameters (P<0.05). Cholesterol, glucose, triglyceride, low density lipoprotein (LDL) at the rearing period was significantly influenced by experimental treatments (P<0.05). However, uric acid, alkaline phosphatase and high density lipoprotein (HDL) was not affected by experimental treatments (P>0.05). The lowest rate of blood cholesterol was concerned to the treatment which was used 3% DCSP 1st to 42nd day and the highest mean of blood cholesterol were concerned to the control treatment. The lowest rate of blood triglyceride was concerned to the treatment which was used 3% DCSP 1st to 42nd day and the highest mean of blood triglyceride were concerned to the control treatment. The lowest rate of blood alkaline phosphatase was concerned to the treatment which was used 3% DCSP 1st to 42nd day and the highest mean of blood alkaline phosphatase were concerned to the treatment which was used 3% DCSP 1st to 21st day.

Keywords: blood parameters, broilers, dried citrus sinensis peel, regulatory diet

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Authors: Javad Jozaei, Rob G. Bell, Paula Blackett, Scott A. Stephens

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In the last few decades, Social Vulnerability Assessment (SVA) has been a favoured means in evaluating the susceptibility of social systems to drivers of change, including climate change and natural disasters. However, the application of SVA to inform responsive and practical strategies to deal with uncertain climate change impacts has always been challenging, and typically agencies resort back to conventional risk/vulnerability assessment. These challenges include complex nature of social vulnerability concepts which influence its applicability, complications in identifying and measuring social vulnerability determinants, the transitory social dynamics in a changing environment, and unpredictability of the scenarios of change that impacts the regime of vulnerability (including contention of when these impacts might emerge). Research suggests that the conventional quantitative approaches in SVA could not appropriately address these problems; hence, the outcomes could potentially be misleading and not fit for addressing the ongoing uncertain rise in risk. The second phase of New Zealand’s Resilience to Nature’s Challenges (RNC2) is developing a forward-looking vulnerability assessment framework and methodology that informs the decision-making and policy development in dealing with the changing coastal systems and accounts for complex dynamics of New Zealand’s coastal systems (including socio-economic, environmental and cultural). Also, RNC2 requires the new methodology to consider plausible drivers of incremental and unknowable changes, create mechanisms to enhance social and community resilience; and fits the New Zealand’s multi-layer governance system. This paper aims to analyse the conventional approaches and methodologies in SVA and offer recommendations for more responsive approaches that inform adaptive decision-making and policy development in practice. The research adopts a qualitative research design to examine different aspects of the conventional SVA processes, and the methods to achieve the research objectives include a systematic review of the literature and case study methods. We found that the conventional quantitative, reductionist and deterministic mindset in the SVA processes -with a focus the impacts of rapid stressors (i.e. tsunamis, floods)- show some deficiencies to account for complex dynamics of social-ecological systems (SES), and the uncertain, long-term impacts of incremental drivers. The paper will focus on addressing the links between resilience and vulnerability; and suggests how resilience theory and its underpinning notions such as the adaptive cycle, panarchy, and system transformability could address these issues, therefore, influence the perception of vulnerability regime and its assessment processes. In this regard, it will be argued that how a shift of paradigm from ‘specific resilience’, which focuses on adaptive capacity associated with the notion of ‘bouncing back’, to ‘general resilience’, which accounts for system transformability, regime shift, ‘bouncing forward’, can deliver more effective strategies in an era characterised by ongoing change and deep uncertainty.

Keywords: complexity, social vulnerability, resilience, transformation, uncertain risks

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Authors: Migena Mana, Ahmed Khalid Syed, Abdul Malik, Nikhil Cherian

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In recent years, advancements in deep learning enabled researchers to tackle the problem of self-driving cars. Car companies use huge datasets to train their deep learning models to make autonomous cars a reality. However, this approach has certain drawbacks in that the state space of possible actions for a car is so huge that there cannot be a dataset for every possible road scenario. To overcome this problem, the concept of reinforcement learning (RL) is being investigated in this research. Since the problem of autonomous driving can be modeled in a simulation, it lends itself naturally to the domain of reinforcement learning. The advantage of this approach is that we can model different and complex road scenarios in a simulation without having to deploy in the real world. The autonomous agent can learn to drive by finding the optimal policy. This learned model can then be easily deployed in a real-world setting. In this project, we focus on three RL algorithms: Q-learning, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO). To model the environment, we have used TORCS (The Open Racing Car Simulator), which provides us with a strong foundation to test our model. The inputs to the algorithms are the sensor data provided by the simulator such as velocity, distance from side pavement, etc. The outcome of this research project is a comparative analysis of these algorithms. Based on the comparison, the PPO algorithm gives the best results. When using PPO algorithm, the reward is greater, and the acceleration, steering angle and braking are more stable compared to the other algorithms, which means that the agent learns to drive in a better and more efficient way in this case. Additionally, we have come up with a dataset taken from the training of the agent with DDPG and PPO algorithms. It contains all the steps of the agent during one full training in the form: (all input values, acceleration, steering angle, break, loss, reward). This study can serve as a base for further complex road scenarios. Furthermore, it can be enlarged in the field of computer vision, using the images to find the best policy.

Keywords: autonomous driving, DDPG (deep deterministic policy gradient), PPO (proximal policy optimization), reinforcement learning

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Authors: Sudhakara Naidu Neppalli, Tejas S. Bhosale

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It is well known that the block copolymer (BCP) can form a complex molecule, through non-covalent bonds such as hydrogen bond, ionic bond and co-ordination bond, with low molecular weight compound as well as with macromolecules, which provide vast applications, includes the alteration of morphology and properties of polymers. Hence we covered the research that, the importance of non-covalent bonds in increasing the non-favourable segmental interactions of the blocks was well examined by attaching and detaching the bonds between the BCP and additive. We also monitored the phase transition of block copolymer and effective interaction parameter (χeff) for Li-doped polymers using small angle x-ray scattering and transmission electron microscopy. The effective interaction parameter (χeff) between two block components was evaluated using Leibler theory based on the incompressible random phase approximation (RPA) for ionized BCP in a disordered state. Furthermore, conductivity experiments demonstrate that the ionic conductivity in the samples quenched from the different structures is morphology-independent, while it increases with increasing ion salt concentration. Morphological transitions, interaction parameter, and thermal stability also examined in quarternized block copolymer. D-spacing was used to estimate effective interaction parameter (χeff) of block components in weak and strong segregation regimes of ordered phase. Metal-containing polymer has been the topic of great attention in recent years due to their wide range of potential application. Similarly, metal- ligand complex is used as a supramolecular linker between the polymers giving rise to a ‘Metallo-Supramolecule assembly. More precisely, functionalized polymer end capped with 2, 2’:6’, 2”- terpyridine ligand can be selectively complexed with wide range of transition metal ions and then subsequently attached to other terpyridine terminated polymer block. In compare to other supramolecular assembly, BCP involved metallo-supramolecule assembly offers vast applications such as optical activity, electrical conductivity, luminescence and photo refractivity.

Keywords: band gap, block copolymer, conductivity, interaction parameter, phase transition

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Authors: Murali Munisamy, Gauthaman Karunakaran, Mubarak Al-Gahtany, Vivekanandhan Subbiah, M. Manjari Tripati

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Background: Sodium valproate is a widely prescribed broad-spectrum anti-epileptic drug. It shows high inter-individual variability in pharmacokinetics and pharmacodynamics and has a narrow therapeutic range. We evaluated the effects of polymorphic uridine diphosphate glucuronosyltransferase (UGT1A9) metabolizing enzyme on the pharmacokinetics of sodium valproate in the patients with epilepsy who showed toxicity to therapy. Methods: Genotype analysis of the patients was made with polymerase chain–restriction fragment length polymorphism (RFLP) with sequencing. Plasma drug concentrations were measured with reversed phase high-performance liquid chromatography (HPLC) and concentration–time data were analyzed by using a non-compartmental approach. Results: The results of this study suggested a significant genotypic as well as allelic association with valproic acid toxicity for UGT1A9 polymorphic enzymes. The elimination half-life (t 1/2=40.2 h) of valproic acid was longer and the clearance rate (CL=937 ml/h) was lower in the poor metabolizers group of UGT1A9 polymorphism who showed toxicity than in the intermediate metabolizers group (t1/2=35.5 h, CL=1042 ml/h) or the extensive metabolizers group (t1/2=26. h, CL=1,302 ml/h). Conclusion: Our findings suggest that the UGT1A9 genetic polymorphism plays a significant role in the steady state concentration of sodium valproate, and it thereby has an impact on the toxicity of the sodium valproate used in the patients with epilepsy.

Keywords: UGT1A9, sodium valporate, pharmacogenetics, polymorphism

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Authors: R. M. López-Gutiérrez, L. Cardoza-Avendaño, H. Cervantes-de Ávila, J. A. Michel-Macarty, C. Cruz-Hernández, A. Arellano-Delgado, R. Carmona-Rodríguez

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In this paper, synchronization of multiple chaotic semiconductor lasers is achieved by appealing to complex system theory. In particular, we consider dynamical networks composed by semiconductor laser, as interconnected nodes, where the interaction in the networks are defined by coupling the first state of each node. An interesting case is synchronized with master-slave configuration in star topology. Nodes of these networks are modeled for the laser and simulated by Matlab. These results are applicable to private communication.

Keywords: chaotic laser, network, star topology, synchronization

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Authors: Massimiliano Nastri

Abstract:

The study examines the façade systems according to the constitutive and typological characters, as well as the functional and applicative requirements such as the expressive, constructive, and interactive criteria towards the environmental, perceptive, and energy conditions. The envelope systems are understood as instruments of mediation, interchange, and dynamic interaction between environmental conditions. The façades are observed for the sustainable concept of eco-efficient envelopes, selective and multi-purpose filters, adaptable and adjustable according to the environmental performance.

Keywords: typologies of façades, environmental and energy sustainability, interaction and perceptive mediation, technical skins

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Authors: Husham Bayazed

Abstract:

Immune responses following surgical trauma play a pivotal role in predicting postoperative outcomes from healing and recovery to postoperative complications. Postoperative complications, including infections and protracted recovery, occur in a significant number of about 300 million surgeries performed annually worldwide. Complications cause personal suffering along with a significant economic burden on the healthcare system in any community. The accurate prediction of postoperative complications and patient-targeted interventions for their prevention remain major clinical provocations. Recent Findings: Recent studies are focusing on immune dysregulation mechanisms that occur in response to surgical trauma as a key determinant of postoperative complications. Antecedent studies mainly were plunging into the detection of inflammatory plasma markers, which facilitate in providing important clues regarding their pathogenesis. However, recent Single-cell technologies, such as mass cytometry or single-cell RNA sequencing, have markedly enhanced our ability to understand the immunological basis of postoperative immunological trauma complications and to identify their prognostic biological signatures. Summary: The advent of proteomic technologies has significantly advanced our ability to predict the risk of postoperative complications. Multiomic modeling of patients' immune states holds promise for the discovery of preoperative predictive biomarkers and providing patients and surgeons with information to improve surgical outcomes. However, more studies are required to accurately predict the risk of postoperative complications in individual patients.

Keywords: immune dysregulation, postoperative complications, surgical trauma, flow cytometry

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Authors: Hasanpasha N. Sholapur, Basanagouda M.Patil

Abstract:

Alcoholic extract of the bark of Moringa oleifera Lam. (MO), (Moringaceae), has been evaluated experimentally in the past for its insulin sensitizing potentials. In order to explore the possibility of the class of phytochemical(s) responsible for this experimental claim, the alcoholic extract was fractionated into non-polar [petroleum ether (PEF)], moderately non-polar [ethyl acetate (EAF)] and polar [aqueous (AQF)] fractions. All the fractions and pioglitazone (PIO) as standard (10mg/kg were p.o., once daily for 11 d) were investigated for their chronic effect on fasting plasma glucose, triglycerides, total cholesterol, insulin, oral glucose tolerance and acute effect on oral glucose tolerance in dexamethasone-induced (1 mg/kg s.c., once daily for 11 d) chronic model and acute model (1 mg/kg i.p., for 4 h) respectively for insulin resistance (IR) in rats. Among all the fractions tested, chronic treatment with EAF (140 mg/kg) and PIO (10 mg/kg) prevented dexamethasone-induced IR, indicated by prevention of hypertriglyceridemia, hyperinsulinemia and oral glucose intolerance, whereas treatment with AQF (95 mg/kg) prevented hepatic IR but not peripheral IR. In acute study single dose treatment with EAF (140 mg/kg) and PIO (10 mg/kg) prevented dexamethasone-induced oral glucose intolerance, fraction PEF did not show any effect on these parameters in both the models. The present study indicates that the triterpenoidal and the phenolic class of phytochemicals detected in EAF of alcoholic extract of MO bark may be responsible for the prevention of dexamethasone-induced insulin resistance in rats.

Keywords: Moringa oleifera, insulin resistance, dexamethasone, serum triglyceride, insulin, oral glucose tolerance test

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Authors: Nelson F. F. Ebecken, Gilberto C. Pereira, Lucio P. de Andrade

Abstract:

Bays, estuaries and coastal ecosystems are some of the most used and threatened natural systems globally. Its deterioration is due to intense and increasing human activities. This paper aims to monitor the socio-ecological in Brazil, model and simulate it through a multilayer network representing a DPSIR structure (Drivers, Pressures, States-Impacts-Responses) considering the concept of Management based on Ecosystems to support decision-making under the National/State/Municipal Coastal Management policy. This approach considers several interferences and can represent a significant advance in several scientific aspects. The main objective of this paper is the coupling of three different types of complex networks, the first being an ecological network, the second a social network, and the third a network of economic activities, in order to model the marine ecosystem. Multilayer networks comprise two or more "layers", which may represent different types of interactions, different communities, different points in time, and so on. The dependency between layers results from processes that affect the various layers. For example, the dispersion of individuals between two patches affects the network structure of both samples. A multilayer network consists of (i) a set of physical nodes representing entities (e.g., species, people, companies); (ii) a set of layers, which may include multiple layering aspects (e.g., time dependency and multiple types of relationships); (iii) a set of state nodes, each of which corresponds to the manifestation of a given physical node in a layer-specific; and (iv) a set of edges (weighted or not) to connect the state nodes among themselves. The edge set includes the intralayer edges familiar and interlayer ones, which connect state nodes between layers. The applied methodology in an existent case uses the Flow cytometry process and the modeling of ecological relationships (trophic and non-trophic) following fuzzy theory concepts and graph visualization. The identification of subnetworks in the fuzzy graphs is carried out using a specific computational method. This methodology allows considering the influence of different factors and helps their contributions to the decision-making process.

Keywords: marine ecosystems, complex systems, multilayer network, ecosystems management

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Authors: S. R. Nayaka, Putta Swamy

Abstract:

Graph polynomial is one of the algebraic representations of the Graph. The degree polynomial is one of the simple algebraic representations of graphs. The degree polynomial of a graph G of order n is the polynomial Deg(G, x) with the coefficients deg(G,i) where deg(G,i) denotes the number of vertices of degree i in G. In this article, we investigate the behavior of the roots of some families of Graphs in the complex field. We investigate for the graphs having only integral roots. Further, we characterize the graphs having single roots or having real roots and behavior of the polynomial at the particular value is also obtained.

Keywords: degree polynomial, regular graph, minimum and maximum degree, graph operations

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Authors: Muhammad Mohsin, Mir Md Abdus Salam, Pertti Pulkkinen, Ari Pappinen

Abstract:

Soil and water contamination by heavy metals is a major challenging issue for the environment. Phytoextraction is an emerging, environmentally friendly and cost-efficient technology in which plants are used to eliminate pollutants from the soil and water. We aimed to assess the copper (Cu) and zinc (Zn) removal efficiency by two willow varieties such as Klara (S. viminalis x S. schwerinii x S. dasyclados) and Karin ((S.schwerinii x S. viminalis) x (S. viminalis x S.burjatica)) under different soil treatments (control/unpolluted, polluted, lime with polluted, wood ash with polluted). In 180 days of pot experiment, these willow varieties were grown in a highly polluted soil collected from Pyhasalmi mining area in Finland. The lime and wood ash were added to the polluted soil to improve the soil pH and observe their effects on metals accumulation in plant biomass. The Inductively Coupled Plasma Optical Emission Spectrometer (ELAN 6000 ICP-EOS, Perkin-Elmer Corporation) was used in this study to assess the heavy metals concentration in the plant biomass. The result shows that both varieties of willow have the capability to accumulate the considerable amount of Cu and Zn varying from 36.95 to 314.80 mg kg⁻¹ and 260.66 to 858.70 mg kg⁻¹, respectively. The application of lime and wood ash substantially affected the stimulation of the plant height, dry biomass and deposition of Cu and Zn into total plant biomass. Besides, the lime application appeared to upsurge Cu and Zn concentrations in the shoots and leaves in both willow varieties when planted in polluted soil. However, wood ash application was found more efficient to mobilize the metals in the roots of both varieties. The study recommends willow plantations to rehabilitate the Cu and Zn polluted soils.

Keywords: heavy metals, lime, phytoextraction, wood ash, willow

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Authors: Zahid Ullah, Atlas Khan

Abstract:

This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

Procedia PDF Downloads 107

Authors: Madalina Postaru, Alexandra Tucaliuc, Dan Cascaval, Anca Irina Galaction

Abstract:

Ergosterol (ergosta-5,7,22-trien-3β-ol) is the precursor of vitamin D2 (ergocalciferol), known as provitamin D2 as it is converted under UV radiation to this vitamin. The natural sources of ergosterol are mainly the yeasts (Saccharomyces sp., Candida sp.), but it can be also found in fungus (Claviceps sp.) or plants (orchids). As ergosterol is mainly accumulated in yeast cell membranes, especially in free form in the plasma-membrane, and the chemical synthesis of ergosterol does not represent an efficient method for its production, this study aimed to analyze the influence of aeration efficiency on ergosterol production by S. cerevisiae in batch and fed-batch fermentations, by considering different levels of mixing intensity, aeration rate, and n-dodecane concentration. Our previous studies on ergosterol production by S. cerevisiae in batch and fed-batch fermentation systems indicated that the addition of n-dodecane led to the increase of almost 50% of this sterol concentration, the highest productivity being reached for the fed-batch process. The experiments were carried out in a laboratory stirred bioreactor, provided with computer-controlled and recorded parameters. In batch fermentation system, the study indicated that the oxygen mass transfer coefficient, kLa, is amplified for about 3 times by increasing the volumetric concentration of n-dodecane from 0 to 15%. Moreover, the increase of dissolved oxygen concentration by adding n-dodecane leads to the diminution for 3.5 times of the produced alcohol amount. In fed-batch fermentation process, the positive influence of hydrocarbon on oxygen transfer rate is amplified mainly at its higher concentration level, as the result of the increased yeasts cells amount. Thus, by varying n-dodecane concentration from 0 to 15% vol., the kLa value increase becomes more important than for the batch fermentation, being of 4 times

Keywords: ergosterol, yeast fermentation, n-dodecane, oxygen-vector

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Authors: Yousuf Alkhezi

Abstract:

Since most of the literature on algebra does not make much deal with the special case of mapping cone. This paper is an alternative way to examine the special tensor product and mapping cone. Also, we show that the isomorphism that implies the mapping cone commutes with the tensor product for the ordinary tensor product no longer holds for the pinched tensor product. However, we show there is a morphism. We will introduce an alternative way of mapping cone. We are looking for more properties which is our future project. Also, we want to apply these new properties in some application. Many results and examples with classical algorithms will be provided.

Keywords: complex, tensor product, pinched tensore product, mapping cone

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Authors: Eugene Y. C. Wong, Daniel Y. W. Mo, Cosmo T. Y. Ng, Jessica K. Y. Chan, Leith K. Y. Chan, Henry Y. K. Lau

Abstract:

The real-time planning visualisation, precise allocation and loading optimisation in air cargo load planning operations are increasingly important as more considerations are needed on dangerous cargo loading, locations of lithium batteries, weight declaration and limited aircraft capacity. The planning of the unit load devices (ULD) can often be carried out only in a limited number of hours before flight departure. A dynamic air cargo load planning system is proposed with the optimisation of cargo load plan and visualisation of planning results in virtual reality systems. The system aims to optimise the cargo load planning and visualise the simulated loading planning decision on air cargo terminal operations. Adopting simulation tools, Cave Automatic Virtual Environment (CAVE) and virtual reality technologies, the results of planning with reference to weight and balance, Unit Load Device (ULD) dimensions, gateway, cargo nature and aircraft capacity are optimised and presented. The virtual reality system facilities planning, operations, education and training. Staff in terminals are usually trained in a traditional push-approach demonstration with enormous manual paperwork. With the support of newly customized immersive visualization environment, users can master the complex air cargo load planning techniques in a problem based training with the instant result being immersively visualised. The virtual reality system is developed with three-dimensional (3D) projectors, screens, workstations, truss system, 3D glasses, and demonstration platform and software. The content will be focused on the cargo planning and loading operations in an air cargo terminal. The system can assist decision-making process during cargo load planning in the complex operations of air cargo terminal operations. The processes of cargo loading, cargo build-up, security screening, and system monitoring can be further visualised. Scenarios are designed to support and demonstrate the daily operations of the air cargo terminal, including dangerous goods, pets and animals, and some special cargos.

Keywords: air cargo load planning, optimisation, virtual reality, weight and balance, unit load device

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Authors: Siobhan Hegarty, Michael Bloomfield, Kim Entholt, Dorothy Williams, Helen Kennerley

Abstract:

Complex Post-Traumatic Stress Disorder (CPTSD) confers greater risk of poor outcomes than does Post-Traumatic Stress Disorder (PTSD). Despite this, the current treatment guidelines for CPTSD aim to reduce only the ‘core’ symptoms of re-experiencing, hyper-vigilance and avoidance, while not addressing the Disturbances of Self Organisation (DSO) symptoms that distinguish this novel diagnosis from PTSD. The Recovering from Child Abuse Programme (RCAP) is a group protocol, based on the principles of cognitive behavioural therapy (CBT). Preliminary evidence suggests the program is effective at reducing DSO symptoms. This pilot study is the first to investigate the potential effectiveness of the RCAP for the specific treatment of CPTSD. This study was conducted as a service evaluation in a secondary care, traumatic stress service. Treatment was delivered once a week, in two-hour sessions, to ten existing female CPTSD patients of the service, who had experienced sexual abuse in childhood. The programme was administered by two therapists and two additional facilitators, following the RCAP protocol manual. Symptom severity was measured before the administration of therapy and was tracked across a range of measures (International Trauma Questionnaire; Patient Health Questionnaire; Community Assessment of Psychic Experience; Work and Social Adjustment Scale) at five time points, over the course of treatment. Qualitative appraisal of the programme was gathered via weekly feedback forms and from audio-taped recordings of verbal feedback given during group sessions. Preliminary results suggest the programme causes a slight reduction in CPTSD and depressive symptom severity and preliminary qualitative analysis suggests that the RCAP is both helpful and acceptable to group members. Final results and conclusions will follow completed thematic analysis of results.

Keywords: Child sexual abuse, Cognitive behavioural therapy, Complex post-traumatic stress disorder, Recovering from child abuse programme

Procedia PDF Downloads 133