Search results for: nonideal complex plasma

Authors: Meimei Shi

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Objectives: The identification of endangered species, especially simultaneous detection of multiple species in complex samples, plays a critical role in alleged wildlife crime incidents and prevents illegal trade. This study was to develop a multi-locus DNA metabarcoding method for endangered animal species identification. Methods: Several pairs of universal primers were designed according to the mitochondria conserved gene regions. Experimental mixtures were artificially prepared by mixing well-defined species, including endangered species, e.g., forest musk, bear, tiger, pangolin, and sika deer. The artificial samples were prepared with 1-16 well-characterized species at 1% to 100% DNA concentrations. After multiplex-PCR amplification and parameter modification, the amplified products were analyzed by capillary electrophoresis and used for NGS library preparation. The DNA metabarcoding was carried out based on Illumina MiSeq amplicon sequencing. The data was processed with quality trimming, reads filtering, and OTU clustering; representative sequences were blasted using BLASTn. Results: According to the parameter modification and multiplex-PCR amplification results, five primer sets targeting COI, Cytb, 12S, and 16S, respectively, were selected as the NGS library amplification primer panel. High-throughput sequencing data analysis showed that the established multi-locus DNA metabarcoding method was sensitive and could accurately identify all species in artificial mixtures, including endangered animal species Moschus berezovskii, Ursus thibetanus, Panthera tigris, Manis pentadactyla, Cervus nippon at 1% (DNA concentration). In conclusion, the established species identification method provides technical support for customs and forensic scientists to prevent the illegal trade of endangered animals and their products.

Keywords: DNA metabarcoding, endangered animal species, mitochondria nucleic acid, multi-locus

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Authors: J. Novak, A. Kohoutkova, V. Kristek, J. Vodicka, M. Sramek

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While the use of cast-in-place concrete for an airfield and highway pavement overlay is very common, the application of precast concrete elements is very limited today. The main reasons consist of high production costs and complex structural behavior. Despite that, several precast concrete systems have been developed and tested with the aim to provide a system with rapid construction. The contribution deals with the reinforcement design of a hexagonal element developed for a proposed airfield pavement system. The sub-base course of the system is composed of compacted recycled concrete aggregates and fiber reinforced concrete with recycled aggregates place on top of it. The selected element belongs to a group of precast concrete elements which are being considered for the construction of a surface course. Both high costs of full-scale experiments and the need to investigate various elements force to simulate their behavior in a numerical analysis software by using finite element method instead of performing expensive experiments. The simulation of the selected element was conducted on a nonlinear model in order to obtain such results which could fully compensate results from experiments. The main objective was to design reinforcement of the precast concrete element subject to quasi-static loading from airplanes with respect to geometrical imperfections, manufacturing imperfections, tensile stress in reinforcement, compressive stress in concrete and crack width. The obtained findings demonstrate that the position and the presence of imperfection in a pavement highly affect the stress distribution in the precast concrete element. The precast concrete element should be heavily reinforced to fulfill all the demands. Using under-reinforced concrete elements would lead to the formation of wide cracks and cracks permanently open.

Keywords: imperfection, numerical simulation, pavement, precast concrete element, reinforcement design, stress analysis

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Authors: John Justo Ambuchi, Zhaohan Zhang, Yujie Feng

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Quick development and usage of nanotechnology have resulted to massive use of various nanoparticles, such as iron oxide nanoparticles (IONPs) and multi-wall carbon nanotubes (MWCNTs). Thus, this study investigated the role of IONPs and MWCNTs in enhancing bioenergy recovery. Results show that IONPs at a concentration of 750 mg/L and MWCNTs at a concentration of 1500 mg/L induced faster substrate utilization and biogas production rates than the control. IONPs exhibited higher carbon oxygen demand (COD) removal efficiency than MWCNTs while on the contrary, MWCNT performance on biogas generation was remarkable than IONPs. Furthermore, scanning electron microscopy (SEM) investigation revealed extracellular polymeric substances (EPS) excretion from AGS had an interaction with nanoparticles. This interaction created a protective barrier to microbial consortia hence reducing their cytotoxicity. Microbial community analyses revealed genus predominance of bacteria of Anaerolineaceae and Longilinea. Their role in biodegradation of the substrate could have highly been boosted by nanoparticles. The archaea predominance of the genus level of Methanosaeta and Methanobacterium enhanced methanation process. The presence of bacteria of genus Geobacter was also reported. Their presence might have significantly contributed to direct interspecies electron transfer in the system. Exposure of AGS to nanoparticles promoted direct interspecies electron transfer among the anaerobic fermenting bacteria and their counterpart methanogens during the anaerobic digestion process. This results provide useful insightful information in understanding the response of microorganisms to IONPs and MWCNTs in the complex natural environment.

Keywords: anaerobic granular sludge, extracellular polymeric substances, iron oxide nanoparticles, multi-wall carbon nanotubes

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Authors: A. G. Barua, Uttam Rajkhowa, Pranjal Moni Nath, Nur Abdul Kadir

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Mycobacterium tuberculosis (MTB) is one of the most closely-related intracellular bacterial pathogens, grouped as the M. tuberculosis complex (MTC). MTB, the primary agent of human tuberculosis (TB), can develop clinical TB in animals as 75 percent of canine mycobacterial infection is caused by close contact with an infected human being. In the present study, molecular detection of TB in dogs in three North-eastern states of India, Assam Mizoram, and Nagaland was carried out. So far, there has been a lack of systematic study in these regions, hampered by slow diagnostic methods and poor infrastructure. In an attempt to rectify this situation, molecular epidemiology was carried out for nine months to detect canine TB in a sample of 340 dogs. Isolation of DNA was done with swabs (throat/nasal), nodules of lungs and fluids from 100 suspected dogs and the molecular study were carried out with the help of conventional and real-time PCR. Post-mortem study was also carried out. Our results showed that the prevalence of clinical TB in dogs from a high-risk setting was 1 percent. However, the prevalence of immunological sensitization to M. tuberculosis antigen in dogs living in contact with sputum smeared positive TB cases was almost 50 percent. The latter setting had the maximum impact in terms of TB transmission. During the study period, a survey with a standard questionnaire was carried out in the TB hospitals to study reverse zoonosis. It was observed that an infected human being was one of the major risk factors for dogs to contract the infection. This observation was drawn by examining the probable airborne transmission from humans to their pets or strays. The present study helped to discover the nuances of TB transmission more clearly and systematically as compared to other sporadic tests to detect MTB in canine.

Keywords: Assam and Nagaland, canine TB, India, molecular detection, tuberculosis

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Authors: Susmita Roy, Madhavan Nallani

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In recent years' polymersomes, self-assembled polymeric vesicles emerge from block copolymers, have been widely investigated due to their enhance stability and unique advantageous properties compared to their phospholipid counterpart, liposomes, dendrimers, and micelles. It provides a distinctive platform for advanced therapeutics and the creation of complex (bio) catalytically active systems for research in Nanomedicine and synthetic biology. Inspired by nature, where compartmentalization of biological components is all ubiquitous, we are interested in developing a platform technology of self-assembled multifunctional compartments with applications in areas from targeted drug/gene delivery, biosensing, pharmaceutical to cosmetics. Polymersome surfaces can be a proper choice of derivatization with a controlled amount of functional groups. To achieve site-specific targeting of polymersomes, biological recognition motives can be attached to the polymersomes surface by standard bioconjugation techniques, (like esterification, amidation, thiol-maleimide coupling, click-chemistry routes or other coupling methods). Herein, we are developing easy going, one-step bioconjugation strategies for site-specific surface functionalized biodegradable polymeric and/or polymer-lipid hybrid vesicles for targeted drug delivery. Biodegradable polymer, polycaprolactone-b-polyethylene glycol (PCL-PEG), polylactic acid-b-polyethylene glycol (PLA-PEG) and phospholipid, 1-palmitoyl-2- oleoyl-sn-glycero-3-phosphocholine (POPC) has been widely used for numerous vesicle formulations. Some of these drug-loaded formulations are being tested on mice for controlled release. These surface functionalized polymersomes are also appropriate for membrane protein reconstitution/insertion, antibodies conjugation and various bioconjugation with diverse targeted molecules for controlled drug delivery.

Keywords: drug delivery, membrane protein, polymersome, surface modification

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Authors: Ana Maria Reis d'Azevedo Breda, Catarina Maria Neto da Cruz

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The role of images/illustrations in communicating meanings and triggering emotions assumes an increasingly relevant role in contemporary texts, regardless of the age group for which they are intended or the nature of the texts that host them. It is no coincidence that children's books are full of illustrations and that the image/text ratio decreases as the age group grows. The vast majority of children's books can be considered multimodal texts containing text and images/illustrations interacting with each other to provide the young reader with a broader and more creative understanding of the book's narrative. This interaction is very diverse, ranging from images/illustrations that are not essential for understanding the storytelling to those that contribute significantly to the meaning of the story. Usually, these books are also read by adults, namely by parents, educators, and teachers who act as mediators between the book and the children, explaining aspects that are or seem to be too complex for the child's context. It should be noted that there are books labeled as children's books that are clearly intended for both children and adults. In this work, following a qualitative and interpretative methodology based on written productions, participant observation, and field notes, we will describe the perceptions of future teachers of the 1st cycle of basic education, attending a master's degree at a Portuguese university, about the role of the image in literary and non-literary texts, namely in mathematical texts, and how these can constitute precious resources for emotional regulation and for the design of creative didactic situations. The analysis of the collected data allowed us to obtain evidence regarding the evolution of the participants' perception regarding the crucial role of images in children's literature, not only as an emotional regulator for young readers but also as a creative source for the design of meaningful didactical situations, crossing other scientific areas, other than the mother tongue, namely mathematics.

Keywords: children’s literature, emotions, multimodal texts, soft skills

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Authors: André C. Silva, Izabela L. A. Moraes, Elenice M. S. Silva, Carlos M. Silva Filho

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In Brazil, most soils are acidic and low in essential nutrients required for the growth and development of plants, making fertilizers essential for agriculture. As the biggest producer of soy in the world and a major producer of coffee, sugar cane and citrus fruits, Brazil is a large consumer of phosphate. Brazilian’s phosphate ores are predominantly from igneous rocks showing a complex mineralogy, associated with carbonites and oxides, typically iron, silicon and barium. The adopted industrial concentration circuit for this type of ore is a mix between magnetic separation (both low and high field) to remove the magnetic fraction and a froth flotation circuit composed by a reverse flotation of apatite (barite’s flotation) followed by direct flotation circuit (rougher, cleaner and scavenger circuit). Since the 70’s fatty acids obtained from vegetable oils are widely used as lower-cost collectors in apatite froth flotation. This is a very effective approach to the apatite family of minerals, being that this type of collector is both selective and efficient (high recovery). This paper presents Jatropha curcas L. oil (JCO) as a renewable and sustainable source of fatty acids with high selectivity in froth flotation of apatite. JCO is considerably rich in fatty acids such as linoleic, oleic and palmitic acid. The experimental campaign involved 216 tests using a modified Hallimond tube and two different minerals (apatite and quartz). In order to be used as a collector, the oil was saponified. The results found were compared with the synthetic collector, Fotigam 5806 produced by Clariant, which is composed mainly by soy oil. JCO showed the highest selectivity for apatite flotation with cold saponification at pH 8 and concentration of 2.5 mg/L. In this case, the mineral recovery was around 95%.

Keywords: froth flotation, jatropha curcas, microflotation, selectivity

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Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

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Authors: Arzu K. Kamberli, Tolga Ulusoy

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Technological developments and the resulting global communication have made the 21st century when large capitals are moved from one end to the other via a button. As a result, the flow of capital inflows has accelerated, and capital inflow has brought with it crisis-related infectiousness. Considering the irrational human behavior, the financial crisis in the world under the influence of the whole world has turned into the basic problem of the countries and increased the interest of the researchers in the reasons of the crisis and the period in which they lived. Therefore, the complex nature of the financial crises and its linearly unexplained structure have also been included in the new discipline, econophysics. As it is known, although financial crises have prediction mechanisms, there is no definite information. In this context, in this study, using the concept of electric field from the electrostatic part of physics, an early econophysical approach for global financial crises was studied. The aim is to define a model that can take place before the financial crises, identify financial fragility at an earlier stage and help public and private sector members, policy makers and economists with an econophysical approach. 2001 Turkey crisis has been assessed with data from Turkish Central Bank which is covered between 1992 to 2007, and for 2001 Argentina crisis, data was taken from IMF and the Central Bank of Argentina from 1997 to 2007. As an econophysical method, an analogy is used between the Gauss's law used in the calculation of the electric field and the forecasting of the financial crisis. The concept of Φ (Financial Flux) has been adopted for the pre-warning of the crisis by taking advantage of this analogy, which is based on currency movements and money mobility. For the first time used in this study Φ (Financial Flux) calculations obtained by the formula were analyzed by Matlab software, and in this context, in 2001 Turkey and Argentina Crisis for Φ (Financial Flux) crisis of values has been confirmed to give pre-warning.

Keywords: econophysics, financial crisis, Gauss's Law, physics

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Authors: Donatella Giuliani

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In this research, we propose an unsupervised grayscale image segmentation method based on a combination of the Firefly Algorithm and the Gaussian Mixture Model. Firstly, the Firefly Algorithm has been applied in a histogram-based research of cluster means. The Firefly Algorithm is a stochastic global optimization technique, centered on the flashing characteristics of fireflies. In this context it has been performed to determine the number of clusters and the related cluster means in a histogram-based segmentation approach. Successively these means are used in the initialization step for the parameter estimation of a Gaussian Mixture Model. The parametric probability density function of a Gaussian Mixture Model is represented as a weighted sum of Gaussian component densities, whose parameters are evaluated applying the iterative Expectation-Maximization technique. The coefficients of the linear super-position of Gaussians can be thought as prior probabilities of each component. Applying the Bayes rule, the posterior probabilities of the grayscale intensities have been evaluated, therefore their maxima are used to assign each pixel to the clusters, according to their gray-level values. The proposed approach appears fairly solid and reliable when applied even to complex grayscale images. The validation has been performed by using different standard measures, more precisely: the Root Mean Square Error (RMSE), the Structural Content (SC), the Normalized Correlation Coefficient (NK) and the Davies-Bouldin (DB) index. The achieved results have strongly confirmed the robustness of this gray scale segmentation method based on a metaheuristic algorithm. Another noteworthy advantage of this methodology is due to the use of maxima of responsibilities for the pixel assignment that implies a consistent reduction of the computational costs.

Keywords: clustering images, firefly algorithm, Gaussian mixture model, meta heuristic algorithm, image segmentation

Procedia PDF Downloads 217

Authors: Qinghua Xing, Xinyi Tao, Haisheng Wang, Baisuo Zhao

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The first true anaerobic, halophilic alkali thermophile, Natranaerobius thermophilus DSM 18059T, serves as a valuable model for studying cellular adaptations to saline, alkaline and thermal extremes. To uncover the adaptive strategies employed by N. thermophilus in coping with these challenges, we conducted a comprehensive iTRAQ-based quantitative proteomic analysis under different conditions of salinity (3.5 M vs. 2.5 M Na+), pH (pH 9.6 vs. pH 8.6), and temperature (52°C vs. 42°C). The increased intracellular accumulation of glycine betaine, through both synthesis and transport, plays a critical role in N. thermophilus' adaptation to these combined stresses. Under all three stress conditions, the up-regulation of Trk family proteins responsible for K+ transport is observed. Intracellular K+ concentration rises in response to salt and pH levels. Multiple types of Na+/H+ antiporter (NhaC family, Mrp family and CPA family) and a diverse range of FOF1-ATP synthase are identified as vital components for maintaining ionic balance under different stress conditions. Importantly, proteins involved in amino acid metabolism, carbohydrate metabolism, ABC transporters, signaling and chemotaxis, as well as biological macromolecule repair and protection, exhibited significant up-regulation in response to these extreme conditions. These metabolic pathways emerge as critical factors in N. thermophilus' adaptation mechanisms under extreme environmental stress. To validate the proteomic data, ddPCR analysis confirmed changes in mRNA expression, thereby corroborating the up-regulation and down-regulation patterns of 19 co-up-regulated and 36 key proteins under saline, alkaline and thermal stresses. This research enriches our understanding of the complex regulatory systems that enable polyextremophiles to survive in combined extreme conditions.

Keywords: polyextremophiles, natranaerobius thermophilus, saline- alkaline- thermal stresses, combined extremes

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Authors: David de Oliveira Costa, Miguel Ângelo Lellis Moreira, Carlos Francisco Simões Gomes, Daniel Augusto de Moura Pereira, Marcos dos Santos

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Strategic management is a fundamental process for global companies that intend to remain competitive in an increasingly dynamic and complex market. To do so, it is necessary to maintain alignment with their principles and values. The Balanced Scorecard (BSC) proposes to ensure that the overall business performance is based on different perspectives (financial, customer, internal processes, and learning and growth). However, relying solely on the BSC may not be enough to ensure the success of strategic management. It is essential that companies also evaluate and prioritize strategic projects that need to be implemented to ensure they are aligned with the business vision and contribute to achieving established goals and objectives. In this context, the proposition involves the incorporation of the SAPEVO-M multicriteria method to indicate the degree of relevance between different perspectives. Thus, the strategic objectives linked to these perspectives have greater weight in the classification of structural projects. Additionally, it is proposed to apply the concept of the Impact & Probability Matrix (I&PM) to structure and ensure that strategic projects are evaluated according to their relevance and impact on the business. By structuring the business's strategic management in this way, alignment and prioritization of projects and actions related to strategic planning are ensured. This ensures that resources are directed towards the most relevant and impactful initiatives. Therefore, the objective of this article is to present the proposal for integrating the BSC methodology, the SAPEVO-M multicriteria method, and the prioritization matrix to establish a concrete weighting of strategic planning and obtain coherence in defining strategic projects aligned with the business vision. This ensures a robust decision-making support process.

Keywords: MCDA process, prioritization problematic, corporate strategy, multicriteria method

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Authors: M. Dezyani, R. Ezzati bbelvirdi, M. Shakerian, H. Mirzaei

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Sodium Hexametaphosphate (SHMP) is commonly used as an Emulsifying Salt (ES) in process cheese, although rarely as the sole ES. It appears that no published studies exist on the effect of SHMP concentration on the properties of process cheese when pH is kept constant; pH is well known to affect process cheese functionality. The detailed interactions between the added phosphate, Casein (CN), and indigenous Ca phosphate are poorly understood. We studied the effect of the concentration of SHMP (0.25-2.75%) and holding time (0-20 min) on the textural and Rheological properties of pasteurized process Cheddar cheese using a central composite rotatable design. All cheeses were adjusted to pH 5.6. The meltability of process cheese (as indicated by the decrease in loss tangent parameter from small amplitude oscillatory rheology, degree of flow, and melt area from the Schreiber test) decreased with an increase in the concentration of SHMP. Holding time also led to a slight reduction in meltability. Hardness of process cheese increased as the concentration of SHMP increased. Acid-base titration curves indicated that the buffering peak at pH 4.8, which is attributable to residual colloidal Ca phosphate, was shifted to lower pH values with increasing concentration of SHMP. The insoluble Ca and total and insoluble P contents increased as concentration of SHMP increased. The proportion of insoluble P as a percentage of total (indigenous and added) P decreased with an increase in ES concentration because of some of the (added) SHMP formed soluble salts. The results of this study suggest that SHMP chelated the residual colloidal Ca phosphate content and dispersed CN; the newly formed Ca-phosphate complex remained trapped within the process cheese matrix, probably by cross-linking CN. Increasing the concentration of SHMP helped to improve fat emulsification and CN dispersion during cooking, both of which probably helped to reinforce the structure of process cheese.

Keywords: Iranian processed cheese, emulsifying salt, rheology, texture

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Authors: David A. Harness

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Natural evolution of ATP cognitive systems is to meet AI peer review standards. ATP process of axiom selection from Mizar to prove a conjecture would be further refined, as in all human and machine learning, by solving the real world problem of the proposed AI peer review challenge: Determine which conjecture forms the higher confidence level constructive proof between Standard Model of Physics SU(n) lattice gauge group operation vs. present non-standard 4D GEM EOS SU(n) lattice gauge group spatially extended operation in which the photon and electron are the first two trace angular momentum invariants of a gravitoelectromagnetic (GEM) energy momentum density tensor wavetrain integration spin-stress pressure-volume equation of state (EOS), initiated via 32 lines of Mathematica code. Resulting gravitoelectromagnetic spectrum ranges from compressive through rarefactive of the central cosmological constant vacuum energy density in units of pascals. Said self-adjoint group operation exclusively operates on the stress energy momentum tensor of the Einstein field equations, introducing quantization directly on the 4D spacetime level, essentially reformulating the Yang-Mills virtual superpositioned particle compounded lattice gauge groups quantization of the vacuum—into a single hyper-complex multi-valued GEM U(1) × SU(1,3) lattice gauge group Planck spacetime mesh quantization of the vacuum. Thus the Mizar corpus already contains all of the axioms required for relevant DeepMath premise selection and unambiguous formal natural language parsing in context deep learning.

Keywords: automated theorem proving, constructive quantum field theory, information theory, neural networks

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Authors: Wilfred Jeyatheese Jeyaraj

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Education is a key determinant of future success, and every person deserves non-discriminant access to information for educational inevitabilities in any case. Analysing and understanding complex information is a crucial learning tool, especially for students. In order to compete equally with sighted students, visually impaired students require the unhinged access to access to all the available information resources. When the education of visually impaired students comes to a focal point, it can be stated that visually impaired students encounter several obstacles and barriers before they enter the university and during their time there as students. These obstacles and barriers are spread across technical, organizational and social arenas. This study reveals the possible approaches to absorb and benefit from the information provided by the Sri Lankan University Libraries for visually impaired students. Purposive sampling technique was used to select sample visually impaired students attached to the Sri Lankan National universities. There are 07 National universities which accommodate the visually impaired students and with the identified data, they were selected for this study and 80 visually impaired students were selected as the sample group. Descriptive type survey method was used to collect data. Structured questionnaires, interviews and direct observation were used as research instruments. As far as the Sri Lankan context spread is concerned, visually impaired students are able to finish their courses through their own determination to overcome the barriers they encounter on their way to graduation, through moral and practical support from their own friends and very often through a high level of creativity. According to the findings there are no specially trained university librarians to serve visually impaired users and less number of assistive technology equipment are available at present. This paper enables all university libraries in Sri Lanka to be informed about the social isolation of visually compromised students at the Sri Lankan universities and focuses on the rectification issues by considering their distinct case for interaction.

Keywords: information access, Sri Lanka, university libraries, visual impairment

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Authors: Mohamed Boullouz, Mohamed Louay Metougui

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Accurate modeling of greenhouse gas (GHG) emissions, crop growth, soil productivity, and biochemical processes is crucial considering escalating global concerns about climate change and the urgent need to improve agricultural sustainability. The application of the denitrification-disintegration (DNDC) model in the context of Morocco's unique agro-climate is thoroughly investigated in this study. Our main research hypothesis is that the DNDC model offers an effective and powerful tool for precisely simulating a wide range of significant parameters, including greenhouse gas emissions, crop growth, yield potential, and complex soil biogeochemical processes, all consistent with the intricate features of environmental Moroccan agriculture. In order to verify these hypotheses, a vast amount of field data covering Morocco's various agricultural regions and encompassing a range of soil types, climatic factors, and crop varieties had to be gathered. These experimental data sets will serve as the foundation for careful model calibration and subsequent validation, ensuring the accuracy of simulation results. In conclusion, the prospective research findings add to the global conversation on climate-resilient agricultural practices while encouraging the promotion of sustainable agricultural models in Morocco. A policy architect's and an agricultural actor's ability to make informed decisions that not only advance food security but also environmental stability may be strengthened by the impending recognition of the DNDC model as a potent simulation tool tailored to Moroccan conditions.

Keywords: greenhouse gas emissions, DNDC model, sustainable agriculture, Moroccan cropping systems

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Authors: Sina Mahdavi

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Background and Objective: Multiple sclerosis (MS) is an inflammatory autoimmune disease of the CNS that affects the myelination process in the central nervous system (CNS). Complex interactions of various "environmental or infectious" factors may act as triggers in autoimmunity and disease progression. The association between viral infections, especially human endogenous retrovirus (HERV) and MS is one potential cause that is not well understood. This study aims to summarize the available data on HERV infection in MS disease progression. Materials and Methods: For this study, the keywords "Multiple sclerosis", "Human endogenous retrovirus", and "central nervous system" in the databases PubMed, Google Scholar, Sid, and MagIran between 2016 and 2022 were searched and 14 articles chosen, studied, and analyzed. Results: In the leptomeningeal cells of MS patients, a retrovirus-like element associated with reverse transcriptase (RT) activity called multiple sclerosis-associated retroviruses (MSRV) has been identified. HERVs are expressed in the human CNS despite mechanisms to suppress their expression. External factors, especially viral infections such as influenza virus, Epstein-Barr virus, and herpes simplex virus type 1, can activate HERV gene expression. The MSRV coat protein is activated by activating TLR4 at the brain surface, particularly in oligodendroglial progenitor cells and macrophages, leading to immune cascades followed by the downregulation of myelin protein expression. The HERV-K18 envelope gene (env) acts as a superantigen and induces inflammatory responses in patients with MS. Conclusion: There is a high expression of endogenous retroviruses during the course of MS, which indicates the relationship between HERV and MS, that this virus can play a role in the development of MS by creating an inflammatory state. Therefore, measures to modulate the expression of endogenous retroviruses may be effective in reducing inflammatory processes in demyelinated areas of MS patients.

Keywords: multiple sclerosis, human endogenous retrovirus, central nervous system, MSRV

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Authors: A. Rostampouryasouri, A. Maghoul, S. Tahersima

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The rapid growth of urbanization and the subsequent increase in population in cities have resulted in the destruction of the environment to cater to the needs of citizens. The industrialization of urban life has led to the production of pollutants, which has significantly contributed to the rise of air pollution. Infrastructure can have both positive and negative effects on air pollution. The effects of infrastructure on air pollution are complex and depend on various factors such as the type of infrastructure, location, and context. This study examines the effects of infrastructure on air pollution, drawing on a range of empirical evidence from Iran and China. Our paper focus for analyzing the data is on the following concepts: 1. Urban design and planning principles and practices 2. Infrastructure efficiency and optimization strategies 3. Public transportation systems and their environmental impact 4. GHG emissions reduction strategies in urban areas 5. Case studies and best practices in sustainable urban development This paper employs a mixed methodology approach with a focus on developmental and applicative purposes. The mixed methods approach combines both quantitative and qualitative research methods to provide a more comprehensive understanding of the research topic. A group of 20 architectural specialists and experts who are proficient in the field of research, design, and implementation of green architecture projects were interviewed in a systematic and purposeful manner. The research method was based on content analysis using MAXQDA2020 software. The findings suggest that policymakers and urban planners should consider the potential impacts of infrastructure on air pollution and take measures to mitigate negative effects while maximizing positive ones. This includes adopting a nature-based approach to urban planning and infrastructure development, investing in information infrastructure, and promoting modern logistic transport infrastructure.

Keywords: GHG emissions, infrastructure efficiency, urban development, urban design

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Authors: Rojan Afrouz

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The main aim of this study is understanding Afghan women’s perception of domestic violence and their experience of abuse by their family members. The voice of Afghan women has not been heard much particularly in Australia. Their families and communities have silenced some of them in the name of family honour and reputation, and others have not had the opportunity to talk about the issue. Although domestic violence is an issue in every country, research suggests that this is more likely to be considered acceptable behaviour in Afghanistan than elsewhere. Given the high public visibility of initiatives which aim to tackle domestic violence in Australia, it is entirely possible that Afghan women’s perceptions and beliefs about domestic violence will have changed since their arrival in this country. Thus, their understandings, perceptions and their experience of domestic violence have been investigated to improve the Afghan women’s situation in Australia. Methods: This qualitative study has been conducted among Afghan women who have lived in Australia less than ten years. Semi-structured interviews either face to face or by phone have been used to collect data for this study. The interviews have been audio-recorded and transcribed verbatim. Nvivo software has been used for data analysis. Findings: Participants’ definitions of domestic violence vary. They defined domestic violence in relation to their educational levels, their personal life and experience of domestic violence. Some women tended to change the definitions to be more relevant to their own life and experience. Many women had the knowledge of different domestic violence acts that have been distinguished as violent acts in Australia or other western countries. Some of the participants stated that they had the experience of domestic violence from their partner or one of the family members. Those who have been abused, their experiences were diverse and had been perpetrated by different family members. Majority of participants revealed the story of other women in their family and community that have been abused. Conclusion: Moving to Australia helped women to be aware of the issues and recognising that they are in the abusive relationships. However, intersecting multiple identities in a complex system of oppression, domination or discrimination makes the experience of domestic violence more complicated among Afghan community in Australia that cannot be addressed easily.

Keywords: domestic violence, intersectionality, immigration, afghan women

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Authors: Xiaoqing Wang, Jianjian Zong, Li Li, Yanxing Zheng, Jinrong Tong, Mao Zhan

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With the rapid development of network and communication technology, a great deal of data has been generated in different domains of a network. These data show a trend of increasing scale and more complex structure. Therefore, an effective and flexible cross-domain data-sharing system is needed. The Cross-domain Data Sharing System(CDSS) in a net-centric environment is composed of three sub-systems. The data distribution sub-system provides data exchange service through publish-subscribe technology that supports asynchronism and multi-to-multi communication, which adapts to the needs of the dynamic and large-scale distributed computing environment. The access control sub-system adopts Attribute-Based Access Control(ABAC) technology to uniformly model various data attributes such as subject, object, permission and environment, which effectively monitors the activities of users accessing resources and ensures that legitimate users get effective access control rights within a legal time. The cross-domain access security negotiation subsystem automatically determines the access rights between different security domains in the process of interactive disclosure of digital certificates and access control policies through trust policy management and negotiation algorithms, which provides an effective means for cross-domain trust relationship establishment and access control in a distributed environment. The CDSS’s asynchronous,multi-to-multi and loosely-coupled communication features can adapt well to data exchange and sharing in dynamic, distributed and large-scale network environments. Next, we will give CDSS new features to support the mobile computing environment.

Keywords: data sharing, cross-domain, data exchange, publish-subscribe

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Authors: Iara Rezende, Djalma Silva, Alcino Costa Neto

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Considering the transformations of the contemporary world linked to globalization and climate changes caused by global warming, the environmental and energy issues have been increasingly present in the decisions of the world scenario. Thus, the aim of reducing the impacts caused by human activities there are the energy efficiency measures, which are also applicable in the scope of Civil Engineering. Considering that a large part of the energy demand from buildings is related to the need to adapt the internal environment to the users comfort and productivity, measures capable of reducing this need can minimize the climate changes impacts and also the energy consumption of the building. However, these important measures are currently little used by civil engineers, either because of the interdisciplinarity of the subject, the time required to apply certain methods or the difficult interpretation of the results obtained by computational programs that often have a complex and little applied approach. Thus, it was proposed the development of a Java application with a simpler and applied approach to evaluate the thermal performance of a building in order to obtain results capable of assisting the civil engineers in the decision making related to the users thermal comfort. The program was built in Java programming language and the method used for the evaluation was the Center Scientifique et Technique du Batiment (CSTB) method. The program was used to evaluate the thermal performance of a university classroom. The analysis was carried out from simulations considering the worst climatic situation of the building occupation. Thus, at the end of the process, the favorable result was obtained regarding the classroom comfort zone and the feasibility of using the program, thus achieving the proposed objectives.

Keywords: building occupation, CSTB method, energy efficiency measures, Java application, thermal comfort

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Authors: Zahra F. Al-Khateeb, Shenel Shekerzade, Hasna Boumenar, Siân M. Henson, Jordi L. Tremoleda, A. T. Michael-Titus

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Traumatic brain injury (TBI) is the leading cause of disability and death in young adults and also increases the risk ofneurodegeneration. The mechanisms linking moderate to severe TBI to neurodegeneration are not known. It has been proposed that cellular senescence inductionpost-injury could amplify neuroinflammation and induce long-term changes. The impact of these processes after injury to an immature brain has not been characterised yet. We carried out a controlled cortical impact injury (CCI) in juvenile 1 month-old male CD1 mice. Animals were anesthetised and received a unilateral CCI injury. The sham group received anaesthesia and had a craniotomy. A naïve group had no intervention. The brain tissue was analysed at 5 days and 35 days post-injury using immunohistochemistry and markers for microglia, astrocytes, and senescence. Compared tonaïve animals, injured mice showed an increased microglial and astrocytic reaction early post-injury, as reflected in Iba1 and GFAP markers, respectively; the GFAP increase persisted in the later phase. The senescence analysis showed a significant increase inγH2AX-53BP1 nuclear foci, 8-oxoguanine, p19ARF, p16INK4a, and p53 expression in naïve vs. sham groups and naïve vs. CCI groups, at 5 dpi. At 35 days, the difference was no longer statistically significant in all markers. The injury induced a decrease p21 expression vs. the naïve group, at 35 dpi. These results indicate the induction of a complex senescence response after immature brain injury. Some changes occur early and may reflect the activation/proliferation of non-neuronal cells post-injury that had been hindered, whereas changes such as p21 downregulation may reflect a delayed response and pro-repair processes.

Keywords: cellular senescence, traumatic brain injury, brain injury, controlled cortical impact

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Authors: Zahid Ullah, Atlas Khan

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The rapid growth of data in various domains has created a pressing need for effective methods to transform this data into meaningful knowledge. In this era of big data, mathematical and statistical innovations play a crucial role in unlocking insights and facilitating informed decision-making in data analytics. This abstract aims to explore the transformative potential of these innovations and their impact on converting raw data into actionable knowledge. Drawing upon a comprehensive review of existing literature, this research investigates the cutting-edge mathematical and statistical techniques that enable the conversion of data into knowledge. By evaluating their underlying principles, strengths, and limitations, we aim to identify the most promising innovations in data analytics. To demonstrate the practical applications of these innovations, real-world datasets will be utilized through case studies or simulations. This empirical approach will showcase how mathematical and statistical innovations can extract patterns, trends, and insights from complex data, enabling evidence-based decision-making across diverse domains. Furthermore, a comparative analysis will be conducted to assess the performance, scalability, interpretability, and adaptability of different innovations. By benchmarking against established techniques, we aim to validate the effectiveness and superiority of the proposed mathematical and statistical innovations in data analytics. Ethical considerations surrounding data analytics, such as privacy, security, bias, and fairness, will be addressed throughout the research. Guidelines and best practices will be developed to ensure the responsible and ethical use of mathematical and statistical innovations in data analytics. The expected contributions of this research include advancements in mathematical and statistical sciences, improved data analysis techniques, enhanced decision-making processes, and practical implications for industries and policymakers. The outcomes will guide the adoption and implementation of mathematical and statistical innovations, empowering stakeholders to transform data into actionable knowledge and drive meaningful outcomes.

Keywords: data analytics, mathematical innovations, knowledge extraction, decision-making

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Authors: Paula Paulino, Alzira Matias, Ana Margarida Veiga Simão

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Self-regulated learning (SRL) directs students in analyzing proposed tasks, setting goals and designing plans to achieve those goals. The literature has suggested a metacognitive strategy for goal attainment known as Mental Contrasting with Implementation Intentions (MCII). This strategy involves Mental Contrasting (MC), in which a significant goal and an obstacle are identified, and Implementation Intentions (II), in which an "if... then…" plan is conceived and operationalized to overcome that obstacle. The present study proposes to assess the MCII process and whether it promotes students’ commitment towards learning goals during school tasks in sciences subjects. In this investigation, we intended to study the MCII strategy in a systemic context of the classroom. Fifty-six students from middle school and secondary education attending a public school in Lisbon (Portugal) participated in the study. The MCII strategy was explicitly taught in a procedure that included metacognitive modeling, guided practice and autonomous practice of strategy. A mental contrast between a goal they wanted to achieve and a possible obstacle to achieving that desire was instructed, and then the formulation of plans in order to overcome the obstacle identified previously. The preliminary results suggest that the MCII metacognitive strategy, applied to the school context, leads to more sophisticated reflections, the promotion of learning goals and the elaboration of more complex and specific self-regulated plans. Further, students achieve better results on school tests and worksheets after strategy practice. This study presents important implications since the MCII has been related to improved outcomes and increased attendance. Additionally, MCII seems to be an innovative process that captures students’ efforts to learn and enhances self-efficacy beliefs during learning tasks.

Keywords: implementation intentions, learning goals, mental contrasting, metacognitive strategy, self-regulated learning

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Authors: Minoo Ghasemzadeh, Rouzbeh Riazi, Shidvash Vakilipour, Alireza Ramezani

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In this study, thermo acoustic oscillations of a lean premixed combustor has been investigated, and a mono-dimensional code was developed in this regard. The linearized equations of motion are solved for perturbations with time dependence〖 e〗^iwt. Two flame models were considered in this paper and the effect of mean flow and boundary conditions were also investigated. After manipulation of flame heat release equation together with the equations of flow perturbation within the main components of the combustor model (i.e., plenum/ premixed duct/ and combustion chamber) and by considering proper boundary conditions between the components of model, a system of eight homogeneous equations can be obtained. This simplification, for the main components of the combustor model, is convenient since low frequency acoustic waves are not affected by bends. Moreover, some elements in the combustor are smaller than the wavelength of propagated acoustic perturbations. A convection time is also assumed to characterize the required time for the acoustic velocity fluctuations to travel from the point of injection to the location of flame front in the combustion chamber. The influence of an extended flame model on the acoustic frequencies of combustor was also investigated, assuming the effect of flame speed as a function of equivalence ratio perturbation, on the rate of flame heat release. The abovementioned system of equations has a related eigenvalue equation which has complex roots. The sign of imaginary part of these roots determines whether the disturbances grow or decay and the real part of these roots would give the frequency of the modes. The results show a reasonable agreement between the predicted values of dominant frequencies in the present model and those calculated in previous related studies.

Keywords: combustion instability, dominant frequencies, flame speed, premixed combustor

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Authors: Maria Bercea, Monica Diana Olteanu

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Investigation of polymer systems able to change inside of the body into networks represent an attractive approach, especially when there is a minimally invasive and patient friendly administration. Pharmaceutical formulations based on Pluronic F127 [poly (oxyethylene) (PEO) blocks (70%) and poly(oxypropylene) (PPO) blocks (30%)] present an excellent potential as drug delivery systems. The use of Pluronic F127 alone as gel-forming solution is limited by some characteristics, such as poor mechanical properties, short residence time, high permeability, etc. Investigation of the interactions between the natural and synthetic polymers and surfactants in solution is a subject of great interest from both scientific and practical point of view. As for example, formulations based on Pluronics and chitosan could be used to obtain dual phase transition hydrogels responsive to temperature and pH changes. In this study, different materials were prepared by using poly(vinyl alcohol), chitosan solutions mixed with aqueous solutions of Pluronic F127. The rheological properties of different formulations were investigated in temperature sweep experiments as well as at a constant temperature of 37oC for exploring in-situ gel formation in the human body conditions. In addition, some viscometric investigations were carried out in order to understand the interactions which determine the complex behaviour of these systems. Correlation between the thermodynamic and rheological parameters and phase separation phenomena observed for the investigated systems allowed the dissemination the constitutive response of polymeric materials at different external stimuli, such as temperature and pH. The rheological investigation demonstrated that the viscoelastic moduli of the hydrogels can be tuned depending on concentration of different components as well as pH and temperature conditions and cumulative contributions can be obtained.

Keywords: hydrogel, polymer mixture, stimuli responsive, biomedical applications

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Authors: I. Gupta, B. Karmakar

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Bengal has a long history (8^th century A.D. onwards) of decorating the wall of brick-built temples with curved terracotta plaques on a diverse range of subjects. These could be considered as one of the most significant visual archives to understand the various facets of the then contemporary societies. The temples under focus include Char-bangla temple complex (circa 1755 A.D.), Bhavanishvara temple (circa 1755 A.D.) and the Gangeshvara Shiva Jor-bangla temple (circa 1753 A.D.), located within a part of the river Bhagirathi basin in Baranagar, Murshidabad, West Bengal, India. Though, a diverse range of subjects have been intricately carved mainly on the front façades of the Baranagar temple cluster, the study specifically concentrates on depictions related to religious and non-religious acts performed by practitioners of various religious sects of late medieval Bengal with the intention to acquire knowledge about the various facets of their life. Apart from this, the paper also mapped the spatial location of these religious performers on the temples’ façades to examine if any systematic plan or arrangement had been employed for connoting a particular idea. Further, an attempt is made to provide a commentary on the attire worn by followers of various religious sects of late medieval Bengal. The primary materials for the study comprise the depictions which denote religious activities carved on the terracotta plaques. The secondary material has been collected from published and unpublished theses, journals and books. These data have been further supplemented with photographic documentation, some useful line-drawings and descriptions in table format to get a clear understanding of the concerned issues.

Keywords: attire, scheme of allocation, terracotta temple, various religious sect

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Authors: Yuchen LI, Martyn Kurr, Peter Golyshin

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Biological invasion is a global problem. Invasive species can threaten local ecosystems by competing for resources, consuming local species, and reproducing faster than natives. Sargassum muticum is an invasive algae in the UK. It negatively impacts local algae through overshading and can cause reductions in local biodiversity. One possibility for its success is herbivore release. According to the Enemy Release Hypothesis, invasives are less impacted by local herbivores than natives. In many species, gastrointestinal (GI) tract microbes have been found as a key factor in food preference and similar mechanisms may exist in the relationship between local consumers and S. muticum. Some populations of native Littorina snails accept S. muticum as a food source, while others avoid it. This project aims to establish the relationship between GI tract microbes and the feeding preferences of L. littorea, when offered both native algae and S. muticum. Individuals of L. littorea from a site invaded by S. muticum around 18 years ago were compared to those from an un-invaded site nearby. Sargassum-experienced snails are more likely to consume it than those naïve, and pronounced differences were found in the GI-tract microbial communities through 16S (prokaryote) and 18S (eukaryote) sequencing. Sargassum-naïve snails were then exposed to a faecal pellets from experienced snails to ‘inoculate’ them with microbes from the exposed snails. Preliminary results suggest these faecal-pellet-exposed but otherwise Sargassum-naïve snails subsequently begun consuming S. muticum. It is unclear if these results are due to genuine changes in GI-tract microbes or through some other mechanism, such as behavioural responses to chemical cues in the faecal pellets, but these results are nevertheless of significance for invasive ecology, suggesting that foraging preferences for an invasive prey type are malleable and possibly programmable in laboratory settings.

Keywords: invasive algae, sea snails, gut microbiome, biocontrol

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Authors: Sarah Barnard, John Arnold, Fehmidah Munir, Sara Bosley

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Gender issues in higher education continue to represent a complex issue as institutions grapple with the role that organisations can play in combatting inequality. Schemes like Athena SWAN and the Aurora leadership programme in the UK context are attempting to tackle some of the issues around representation and the recognition of women in the sector. This paper is the first of its kind in reporting findings from a mixed-methods longitudinal study on both professional services and academic women in higher education in the UK. Online surveys have been completed by over 2,000 women in the sector. The qualitative elements include interviews with women and their mentors, and diaries with a select group of women. So far results have shown that contrary to the stereotype of women lacking leadership skills or having no desire to go into higher roles, women in the sector consistently assessed their leadership abilities positively, especially but not only regarding interpersonal interaction and facilitation. Over 80% of women agreed that they felt confident about putting themselves forward for positions of responsibility at work. However, qualitative data shows that confidence remains a salient term for how women talk about the challenges they have faced at work. This suggests that the work needed to challenge systemic gender issues requires action to be driven above the individual level. Overall, academics reported more negative experiences than professional services staff. Similarly BAME women’s responses are more negative. Therefore, the study offers some information on the differential experiences of women. In conclusion, women in higher education are undertaking considerable ‘below the radar’ leadership activities in what they perceive to be a somewhat inhospitable hostile workplace culture. The significant amount of effort expended in the sector is affecting slow, partial impacts on gender inequalities.

Keywords: gender, higher education, leadership, longitudinal research

Procedia PDF Downloads 244

Authors: Addisu H. Addis, Hugh T. Blair, Paul R. Kenyon, Stephen T. Morris, Nicola M. Schreurs, Dorian J. Garrick

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Agent-based modeling (ABM) enables an in silico representation of complex systems and cap-tures agent behavior resulting from interaction with other agents and their environment. This study developed an ABM to represent a pasture-based beef cattle finishing systems in New Zea-land (NZ) using attributes of the rearer, finisher, and processor, as well as specific attributes of dairy-origin beef cattle. The model was parameterized using values representing 1% of NZ dairy-origin cattle, and 10% of rearers and finishers in NZ. The cattle agent consisted of 32% Holstein-Friesian, 50% Holstein-Friesian–Jersey crossbred, and 8% Jersey, with the remainder being other breeds. Rearers and finishers repetitively and simultaneously interacted to determine the type and number of cattle populating the finishing system. Rearers brought in four-day-old spring-born calves and reared them until 60 calves (representing a full truck load) on average had a live weight of 100 kg before selling them on to finishers. Finishers mainly attained weaners from rearers, or directly from dairy farmers when weaner demand was higher than the supply from rearers. Fast-growing cattle were sent for slaughter before the second winter, and the re-mainder were sent before their third winter. The model finished a higher number of bulls than heifers and steers, although it was 4% lower than the industry reported value. Holstein-Friesian and Holstein-Friesian–Jersey-crossbred cattle dominated the dairy-origin beef finishing system. Jersey cattle account for less than 5% of total processed beef cattle. Further studies to include re-tailer and consumer perspectives and other decision alternatives for finishing farms would im-prove the applicability of the model for decision-making processes.

Keywords: agent-based modelling, dairy cattle, beef finishing, rearers, finishers

Procedia PDF Downloads 99