Search results for: variability

Authors: Mohamed Fawzy Elzarei, Yousef Mohammed Al-Dakheel, Ali Mohamed Alseaf

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Modern molecular techniques, like single marker analysis for linked traits to these markers, can provide us with rapid and accurate genetic results. In the last two decades of the last century, the applications of molecular techniques were reached a faraway point in cattle, sheep, and pig. In goats, especially in our region, the application of molecular techniques is still far from other species. As reported by many researchers, microsatellites marker is one of the suitable markers for lie studies. The single marker linked to traits of interest is one technique allowed us to early select animals without the necessity for mapping the entire genome. Simplicity, applicability, and low cost of this technique gave this technique a wide range of applications in many areas of genetics and molecular biology. Also, this technique provides a useful approach for evaluating genetic differentiation, particularly in populations that are poorly known genetically. The expected breeding value (EBV) and yield deviation (YD) are considered as the most parameters used for studying the linkage between quantitative characteristics and molecular markers, since these values are raw data corrected for the non-genetic factors. A total of 17 microsatellites markers (from chromosomes 6, 14, 18, 20 and 23) were used in this study to search for areas that could be responsible for genetic variability for some milk traits and search of chromosomal regions that explain part of the phenotypic variance. Results of single-marker analyses were used to identify the linkage between microsatellite markers and variation in EBVs of these traits, Milk yield, Protein percentage, Fat percentage, Litter size and weight at birth, and litter size and weight at weaning. The estimates of the parameters from forward and backward solutions using stepwise regression procedure on milk yield trait, only two markers, OARCP9 and AGLA29, showed a highly significant effect (p≤0.01) in backward and forward solutions. The forward solution for different equations conducted that R2 of these equations were highly depending on only two partials regressions coefficient (βi,) for these markers. For the milk protein trait, four marker showed significant effect BMS2361, CSSM66 (p≤0.01), BMS2626, and OARCP9 (p≤0.05). By the other way, four markers (MCM147, BM1225, INRA006, andINRA133) showed highly significant effect (p≤0.01) in both backward and forward solutions in association with milk fat trait. For both litter size at birth and at weaning traits, only one marker (BM143(p≤0.01) and RJH1 (p≤0.05), respectively) showed a significant effect in backward and forward solutions. The estimates of the parameters from forward and backward solution using stepwise regression procedure on litter weight at birth (LWB) trait only one marker (MCM147) showed highly significant effect (p≤0.01) and two marker (ILSTS011, CSSM66) showed a significant effect (p≤0.05) in backward and forward solutions.

Keywords: microsatellites marker, estimated breeding value, stepwise regression, milk traits

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Authors: Mohit Kumar

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Natural fractures are classified in two broad categories of joints and faults on the basis of shear movement in the deposited strata. Natural fracture always has high structural relationship with extensional or non-extensional tectonics and sometimes the result is seen in the form of micro cracks. Geological evidences suggest that both large and small-scale fractures help in to analyze the seismic anisotropy which essentially contribute into characterization of petro physical properties behavior associated with directional migration of fluid. We generally question why basement study is much needed as historically it is being treated as non-productive and geoscientist had no interest in exploration of these basement rocks. Basement rock goes under high pressure and temperature, and seems to be highly fractured because of the tectonic stresses that are applied to the formation along with the other geological factors such as depositional trend, internal stress of the rock body, rock rheology, pore fluid and capillary pressure. Sometimes carbonate rocks also plays the role of basement and igneous body e.g basalt deposited over the carbonate rocks and fluid migrate from carbonate to igneous rock due to buoyancy force and adequate permeability generated by fracturing. So in order to analyze the complete petroleum system, FMC (Fluid Migration Characterization) is necessary through fractured media including fracture intensity, orientation and distribution both in basement rock and county rock. Thus good understanding of fractures can lead to project the correct wellbore trajectory or path which passes through potential permeable zone generated through intensified P-T and tectonic stress condition. This paper deals with the analysis of these fracture property such as intensity, orientation and distribution in basement rock as large scale fracture can be interpreted on seismic section, however, small scale fractures show ambiguity in interpretation because fracture in basement rock lies below the seismic wavelength and hence shows erroneous result in identification. Seismic attribute technique also helps us to delineate the seismic fracture and subtle changes in fracture zone and these can be inferred from azimuthal anisotropy in velocity and amplitude and spectral decomposition. Seismic azimuthal anisotropy derives fracture intensity and orientation from compressional wave and converted wave data and based on variation of amplitude or velocity with azimuth. Still detailed analysis of fractured basement required full isotropic and anisotropic analysis of fracture matrix and surrounding rock matrix in order to characterize the spatial variability of basement fracture which support the migration of fluid from basement to overlying rock.

Keywords: basement rock, natural fracture, reservoir characterization, seismic attribute

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Authors: Neha Gupta, Sonika Verma, Seema Puri, Nikhil Tandon, Narendra K. Arora

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The concurrent increasing prevalence of underweight and overweight/obesity among children with changing lifestyle and the rapid transitioning society has necessitated the need for a unifying/multi-level approach to understand the determinants of the problem. The present community-based cross-sectional research study was conducted to assess the associations between lifestyle behavior and food environment of the child at household, neighborhood, and school with the BMI of children (6-12 year old) (n=612) residing in three rural clusters of Palwal district, Haryana. The study used innovative and robust methods for assessing the lifestyle and various components of food environment in the study. The three rural clusters selected for the study were located at three different locations according to their access to highways in the SOMAARTH surveillance site. These clusters were significantly different from each other in terms of their socio-demographic and socio-economic profile, living conditions, environmental hygiene, health seeking behavior and retail density. Despite of being different, the quality of living conditions and environmental hygiene was poor across three clusters. The children had higher intakes of dietary energy and sugars; one-fifth share of the energy being derived from unhealthy foods, engagement in high levels of physical activity and significantly different food environment at home, neighborhood and school level. However, despite having a high energy intake, 22.5% of the recruited children were thin/severe thin, and 3% were overweight/obese as per their BMI-for-age categories. The analysis was done using multi-variate logistic regression at three-tier hierarchy including individual, household and community level. The factors significantly explained the variability in governing the risk of getting thin/severe thin among children in rural area (p-value: 0.0001; Adjusted R2: 0.156) included age (>10years) (OR: 2.1; 95% CI: 1.0-4.4), the interaction between minority category and poor SES of the household (OR: 4.4; 95% CI: 1.6-12.1), availability of sweets (OR: 0.9; 95% CI: 0.8-0.99) and cereals (OR: 0.9; 95% CI: 0.8-1.0) in the household and poor street condition (proxy indicator of the hygiene and cleanliness in the neighborhood) (OR: 0.3; 95% CI: 0.1-1.1). The homogeneity of other factors at neighborhood and school level food environment diluted the heterogeneity in the lifestyles and home environment of the recruited children and their households. However, it is evident that when various individual factors interplay at multiple levels amplifies the risk of undernutrition in a rural community. Conclusion: These rural areas in Haryana are undergoing developmental, economic and societal transition. In correspondence, no improvements in the nutritional status of children have happened. Easy access to the unhealthy foods has become a paradox.

Keywords: transition, food environment, lifestyle, undernutrition, overnutrition

Procedia PDF Downloads 157

Authors: Fruzsina Luca Kézér, Viktor Jurkovich, Ottó Szenci, János Tőzsér, Levente Kovács

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Positive interaction between people and animals could have a favorable effect on the welfare and production by reducing stress levels. However, to the repeated contact with humans (e.g. farm staff, veterinarians or herdsmen), animals may respond with escape behavior or avoidance, which both have negative effects on the ease of handling, welfare and may lead to the expression of aggressive behaviors. Rough or aversive handling can impair health and the function of the cardiac autonomic activity due to fear and stress, which also can be determined by certain parameters of heart rate variability (HRV). Although the essential relationships between fear from humans and basal tone of the autonomic nervous system were described by the authors previously, several questions remained unclear in terms of the associations between different coping strategies (behavioral syndromes) of the animals and physiological responsiveness to humans. The main goal of this study was to find out whether human behavior and emotions to the animals have an impact on cardiac function and behavior of animals with different coping styles in response situations. Therefore, in the present study, special (fear, approaching, restraint, novel arena, novel object) tests were performed on healthy, 2-year old heifers (n = 104) differing in coping styles [reactive (passive) vs. proactive (active) coping]. Animals were categorized as reactive or proactive based on the following tests: 1) aggressive behavior at the feeding bunk, 2) avoidance from an approaching person, 3) immobility, and 4) daily activity (number of posture changes). Heart rate, the high frequency (HF) component of HRV as a measure of vagal activity and the ratio between the low frequency (LF) and HF components (LF/HF ratio) as a parameter of sympathetic nervous system activity were calculated for all individual during lying posture (baseline) and for response situations in novel object, novel arena, and unfamiliar person tests (both for 5 min), respectively. The differences between baseline and response were compared between groups. Higher sympathetic (higher heart rates and LF/HF ratios) and lower parasympathetic activity (lower HF) was found for proactive animals in response situations than for reactive (passive) animals either during the novel object, the novel arena and the unfamiliar person test. It suggests that animals with different behavioral traits differ in their immediate autonomic adaptation to novelty and people. Based on our preliminary results, it seems, that the analysis of HRV can help to understand the physiological manifestation of responsiveness to novelty and human presence in dairy cattle with different behavioral syndromes.

Keywords: behavioral syndromes, human-cattle interaction, novel arena test, physiological responsiveness, proactive coping, reactive coping

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Authors: Soma Kanta Baral

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Background: Since 1981, when the first AIDS case was reported, worldwide, more than 34 million people have been infected with HIV. Almost 95 percent of the people infected with HIV live in developing countries. As HBV & HIV share similar routes of transmission by sexual intercourse or drug use by parenteral injection, co-infection is common. Because of the limited access to healthcare & HIV treatment in developing countries, HIV-infected individuals are present late for care. Enumeration of CD4+ T cell count at the time of diagnosis has been useful to initiate the therapy in HIV infected individuals. The baseline CD4+ T cell count shows high immunological variability among patients. Methods: This prospective study was done in the serology section of the Department of Microbiology over a period of one year from august 2012 to July 2013. A total of 13037 individuals subjected for HIV test were included in the study comprising of 4982 males & 8055 females. Blood sample was collected by vein puncture aseptically with standard operational procedure in clean & dry test-tube. All blood samples were screened for HIV as described by WHO algorithm by Immuno-chromatography rapid kits. Further confirmation was done by biokit ELISA method as per the manufacturer’s guidelines. After informed consent, HIV positive individuals were screened for HBsAg by Immuno-chromatography rapid kits (Hepacard). Further confirmation was done by biokit ELISA method as per the manufacturer’s guidelines. EDTA blood samples were collected from the HIV sero-positive individuals for baseline CD4+ T count. Then, CD4+ T cells count was determined by using FACS Calibur Flow Cytometer (BD). Results: Among 13037 individuals screened for HIV, 104 (0.8%) were found to be infected comprising of 69(66.34%) males & 35 (33.65%) females. The study showed that the high infection was noted in housewives (28.7%), active age group (30.76%), rural area (56.7%) & in heterosexual route (80.9%) of transmission. Out of total HIV infected individuals, distribution of HBV co-infection was found to be 6(5.7%). All co- infected individuals were married, male, above the age of 25 years & heterosexual route of transmission. Baseline CD4+ T cell count of HIV infected patient was found higher (mean CD4+ T cell count; 283cells/cu.mm) than HBV co-infected patients (mean CD4+ T cell count; 91 cells/cu.mm). Majority (77.2%) of HIV infected & all co-infected individuals were presented in our center late (CD4+ T cell count;< 350/cu. mm) for diagnosis and care. Majority of co- infected 4 (80%) were late presented with advanced AIDS stage (CD4+ count; <200/cu.mm). Conclusions: The study showed a high percentage of HIV sero-positive & co- infected individuals. Baseline CD4+ T cell count of majority of HIV infected individuals was found to be low. Hence, more sustained and vigorous awareness campaigns & counseling still need to be done in order to promote early diagnosis and management.

Keywords: HIV/AIDS, HBsAg, co-infection, CD4+

Procedia PDF Downloads 191

Authors: Dian Mayasari, Yosi Bayu Murti, Sylvia Utami Tunjung Pratiwi, Sudarsono

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Melastoma malabathricum L. is an Indo-Pacific herb that has been traditionally used to treat several ailments such as wounds, dysentery, diarrhea, toothache, and diabetes. This plant is common across tropical Indo-Pacific archipelagos and is tolerant of a range of soils, from low-lying areas subject to saltwater inundation to the salt-free conditions of mountain slopes. How the soil and environmental variation influences secondary metabolite production in the herb, and an understanding of the plant’s utility as traditional medicine, remain largely unknown and unexplored. The objective of this study is to evaluate the variability of the metabolic profiles of M. malabathricum L. across its geographic distribution. By employing high-performance liquid chromatography-diode array detector (HPLC-DAD), a highly established, simple, sensitive, and reliable method was employed for establishing the chemical fingerprints of 72 samples of M. malabathricum L. leaves from various geographical locations in Indonesia. Specimens collected from six terrestrial and archipelago regions of Indonesia were analyzed by HPLC to generate chromatogram peak profiles that could be compared across each region. Data corresponding to the common peak areas of HPLC chromatographic fingerprint were analyzed by hierarchical component analysis (HCA) and principal component analysis (PCA) to extract information on the most significant variables contributing to characterization and classification of analyzed samples data. Principal component values were identified as PC1 and PC2 with 41.14% and 19.32%, respectively. Based on variety and origin, the high-performance liquid chromatography method validated the chemical fingerprint results used to screen the in vitro antioxidant activity of M. malabathricum L. The result shows that the developed method has potential values for the quality of similar M. malabathrium L. samples. These findings provide a pathway for the development and utilization of references for the identification of M. malabathricum L. Our results indicate the importance of considering geographic distribution during field-collection efforts as they demonstrate regional metabolic variation in secondary metabolites of M. malabathricum L., as illustrated by HPLC chromatogram peaks and their antioxidant activities. The results also confirm the utility of this simple approach to a rapid evaluation of metabolic variation between plants and their potential ethnobotanical properties, potentially due to the environments from whence they were collected. This information will facilitate the optimization of growth conditions to suit particular medicinal qualities.

Keywords: fingerprint, high performance liquid chromatography, Melastoma malabathricum l., metabolic profiles, principal component analysis

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Authors: A. D. Rao, Sachiko Mohanty, R. Gayathri, V. Ranga Rao

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Modeling on coupled physical and biogeochemical processes of coastal waters is vital to identify the primary production status under different natural and anthropogenic conditions. About 7, 500 km length of Indian coastline is occupied with number of semi enclosed coastal bodies such as estuaries, inlets, bays, lagoons, and other near shore, offshore shelf waters, etc. This coastline is also rich in wide varieties of ecosystem flora and fauna. Directly/indirectly extensive domestic and industrial sewage enter into these coastal water bodies affecting the ecosystem character and create environment problems such as water quality degradation, hypoxia, anoxia, harmful algal blooms, etc. lead to decline in fishery and other related biological production. The present study is focused on the southeast coast of India, starting from Pulicat to Gulf of Mannar, which is rich in marine diversity such as lagoon, mangrove and coral ecosystem. Three dimensional Massachusetts Institute of Technology general circulation model (MITgcm) along with Darwin biogeochemical module is configured for the western Bay of Bengal (BoB) to study the biogeochemistry over this region. The biogeochemical module resolves the cycling of carbon, phosphorous, nitrogen, silica, iron and oxygen through inorganic, living, dissolved and particulate organic phases. The model domain extends from 4°N-16.5°N and 77°E-86°E with a horizontal resolution of 1 km. The bathymetry is derived from General Bathymetric Chart of the Oceans (GEBCO), which has a resolution of 30 sec. The model is initialized by using the temperature, salinity filed from the World Ocean Atlas (WOA2013) of National Oceanographic Data Centre with a resolution of 0.25°. The model is forced by the surface wind stress from ASCAT and the photosynthetically active radiation from the MODIS-Aqua satellite. Seasonal climatology of nutrients (phosphate, nitrate and silicate) for the southwest BoB region are prepared using available National Institute of Oceanography (NIO) in-situ data sets and compared with the WOA2013 seasonal climatology data. The model simulations with the two different initial conditions viz., WOA2013 and the generated NIO climatology, showed evident changes in the concentration and the evolution of the nutrients in the study region. It is observed that the availability of nutrients is more in NIO data compared to WOA in the model domain. The model simulated primary productivity is compared with the spatially distributed satellite derived chlorophyll data and at various locations with the in-situ data. The seasonal variability of the model simulated primary productivity is also studied.

Keywords: Bay of Bengal, Massachusetts Institute of Technology general circulation model, MITgcm, biogeochemistry, primary productivity

Procedia PDF Downloads 101

Authors: Aarthi Mariappan, Janani Selvaraj, P. B. Harathi, M. Prashanthi Devi

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Anthropogenic modification of the urban environment has largely increased in the recent years in order to sustain the growing human population. Intense industrial activity, permanent and high traffic on the roads, a developed subterranean infrastructure network, land use patterns are just some specific characteristics. Every day, the urban environment is polluted by more or less toxic emissions, organic or metals wastes discharged from specific activities such as industrial, commercial, municipal. When these eventually deposit into the soil, the physical and chemical properties of the surrounding soil is changed, transforming it into a human exposure indicator. Metals are non-degradable and occur cumulative in soil due to regular deposits are a result of permanent human activity. Due to this, metals are a contaminant factor for soil when persistent over a long period of time and a possible danger for inhabitant’s health on prolonged exposure. Metals accumulated in contaminated soil may be transferred to humans directly, by inhaling the dust raised from top soil, or by ingesting, or by dermal contact and indirectly, through plants and animals grown on contaminated soil and used for food. Some metals, like Cu, Mn, Zn, are beneficial for human’s health and represent a danger only if their concentration is above permissible levels, but other metals, like Pb, As, Cd, Hg, are toxic even at trace level causing gastrointestinal and lung cancers. In urban areas, metals can be emitted from a wide variety of sources like industrial, residential, commercial activities. Our study interrogates the spatial distribution of heavy metals in soil in relation to their permissible levels and their association with the health risk to the urban population in Coimbatore, India. Coimbatore region is a high cancer risk zone and case records of gastro intestinal and respiratory cancer patients were collected from hospitals and geocoded in ArcGIS10.1. The data of patients pertaining to the urban limits were retained and checked for their diseases history based on their diagnosis and treatment. A disease map of cancer was prepared to show the disease distribution. It has been observed that in our study area Cr, Pb, As, Fe and Mg exceeded their permissible levels in the soil. Using spatial overlay analysis a relationship between environmental exposure to these potentially toxic elements in soil and cancer distribution in Coimbatore district was established to show areas of cancer risk. Through this, our study throws light on the impact of prolonged exposure to soil contamination in soil in the urban zones, thereby exploring the possibility to detect cancer risk zones and to create awareness among the exposed groups on cancer risk.

Keywords: soil contamination, cancer risk, spatial analysis, India

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Authors: Chandanee Wasana Kalansooriya

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Dietary behaviour is a crucial factor affecting diabetes control. With increasing rates of diabetes prevalence in Asian countries, examining their dietary patterns, which are largely based on rice, is timely required. It has been identified that higher consumption of some rice varieties is associated with increased risk of type 2 diabetes. Although diabetes patients are advised to consume healthier rice varieties, which contains low glycemic, several conditions, one of which food insecurity, make them difficult to preserve those healthy dietary guidelines. Hence this study tries to investigate how food security affects on making right decisions of rice consumption within diabetes affected households using a sample from Sri Lanka, a country which rice considered as the staple food and records the highest diabetes prevalence rate in South Asia. The study uses data from the Household Income and Expenditure Survey 2016, a nationally representative sample conducted by the Department of Census and Statistics, Sri Lanka. The survey used a two-stage stratified sampling method to cover different sectors and districts of the country and collected micro-data on demographics, health, income and expenditures of different categories. The study uses data from 2547 households which consist of one or more diabetes patients, based on the self-recorded health status. The Household Dietary Diversity Score (HDDS), which constructed based on twelve food groups, is used to measure the level of food security. Rice is categorized into three groups according to their Glycemic Index (GI), high GI, medium GI and low GI, and the likelihood and impact made by food security on each rice consumption categories are estimated using a Two-part Model. The shares of each rice categories out of total rice consumption is considered as the dependent variable to exclude the endogeneity issue between rice consumption and the HDDS. The results indicate that the consumption of medium GI rice is likely to increase with the increasing household food security, but low GI varieties are not. Households in rural and estate sectors are less likely and Tamil ethnic group is more likely to consume low GI rice varieties. Further, an increase in food security significantly decreases the consumption share of low GI rice, while it increases the share of medium GI varieties. The consumption share of low GI rice is largely affected by the ethnic variability. The effects of food security on the likelihood of consuming high GI rice varieties and changing its shares are statistically insignificant. Accordingly, the study concludes that a higher level of food security does not ensure diabetes patients are consuming healthy rice varieties or reducing consumption of unhealthy varieties. Hence policy attention must be directed towards educating people for making healthy dietary choices. Further, the study provides a room for further studies as it reveals considerable ethnic and sectorial differences in making healthy dietary decisions.

Keywords: diabetes, food security, glycemic index, rice consumption

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Authors: Ibtissem Hosni, Lilia Bennaceur Farah, Saber Mohamed Naceur

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In order to assess the water availability in the soil, it is crucial to have information about soil distributed moisture content; this parameter helps to understand the effect of humidity on the exchange between soil, plant cover and atmosphere in addition to fully understanding the surface processes and the hydrological cycle. On the other hand, aerodynamic roughness length is a surface parameter that scales the vertical profile of the horizontal component of the wind speed and characterizes the surface ability to absorb the momentum of the airflow. In numerous applications of the surface hydrology and meteorology, aerodynamic roughness length is an important parameter for estimating momentum, heat and mass exchange between the soil surface and atmosphere. It is important on this side, to consider the atmosphere factors impact in general, and the natural erosion in particular, in the process of soil evolution and its characterization and prediction of its physical parameters. The study of the induced movements by the wind over soil vegetated surface, either spaced plants or plant cover, is motivated by significant research efforts in agronomy and biology. The known major problem in this side concerns crop damage by wind, which presents a booming field of research. Obviously, most models of soil surface require information about the aerodynamic roughness length and its temporal and spatial variability. We have used a bi-dimensional multi-scale (2D MLS) roughness description where the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each one having a spatial scale using the wavelet transform and the Mallat algorithm to describe natural surface roughness. We have introduced multi-layer aspect of the humidity of the soil surface, to take into account a volume component in the problem of backscattering radar signal. As humidity increases, the dielectric constant of the soil-water mixture increases and this change is detected by microwave sensors. Nevertheless, many existing models in the field of radar imagery, cannot be applied directly on areas covered with vegetation due to the vegetation backscattering. Thus, the radar response corresponds to the combined signature of the vegetation layer and the layer of soil surface. Therefore, the key issue of the numerical estimation of soil moisture is to separate the two contributions and calculate both scattering behaviors of the two layers by defining the scattering of the vegetation and the soil blow. This paper presents a synergistic methodology, and it is for estimating roughness and soil moisture from C-band radar measurements. The methodology adequately represents a microwave/optical model which has been used to calculate the scattering behavior of the aerodynamic vegetation-covered area by defining the scattering of the vegetation and the soil below.

Keywords: aerodynamic, bi-dimensional, vegetation, synergistic

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Authors: Douglas E. Mainhart, Alejandro Fierro-Cabo, Bradley Christoffersen, Charlotte Reemts

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Semi-arid ecosystems across the globe have faced land conversion for agriculture and resource extraction activities, posing a threat to the important ecosystem services they provide. Revegetation-centered restoration efforts in these regions face low success rates due to limited soil water availability and high temperatures leading to elevated seedling mortality after planting. Typical methods to alleviate these stresses require costly post-planting interventions aimed at improving soil moisture status. We set out to evaluate the efficacy of applying in-nursery treatments to address transplant shock. Four native Tamaulipan thornscrub species were compared. Three treatments were applied: elevated CO2, drought hardening (four-week exposure each), and antitranspirant foliar spray (the day prior to planting). Our goal was to answer two primary questions: (1) Do treatments improve survival and growth of seedlings in the early period post-planting? (2) If so, what underlying physiological changes are associated with this improved performance? To this end, we measured leaf gas exchange (stomatal conductance, light saturated photosynthetic rate, water use efficiency), leaf morphology (specific leaf area), and osmolality before and upon the conclusion of treatments. A subset of seedlings from all treatments have been planted, which will be monitored in coming months for in-field survival and growth.First month field survival for all treatment groups were high due to ample rainfall following planting (>85%). Growth data was unreliable due to high herbivory (68% of all sampled plants). While elevated CO2 had infrequent or no detectable influence on all aspects of leaf gas exchange, drought hardening reduced stomatal conductance in three of the four species measured without negatively impacting photosynthesis. Both CO2 and drought hardening elevated leaf osmolality in two species. Antitranspirant application significantly reduced conductance in all species for up to four days and reduced photosynthesis in two species. Antitranspirants also increased the variability of water use efficiency compared to controls. Collectively, these results suggest that antitranspirants and drought hardening are viable treatments for reducing short-term water loss during the transplant shock period. Elevated CO2, while not effective at reducing water loss, may be useful for promoting more favorable water status via osmotic adjustment. These practices could improve restoration outcomes in Tamaulipan thornscrub and other semi-arid systems. Further research should focus on evaluating combinations of these treatments and their species-specific viability.

Keywords: conservation, drought conditioning, semi-arid restoration, plant physiology

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Authors: Mehrnaz Mostafavi

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The assessment and categorization of incidental lung nodules present a considerable challenge in healthcare, often necessitating resource-intensive multiple computed tomography (CT) scans for growth confirmation. This research addresses this issue by introducing a distinct computational approach leveraging radiomics and deep-learning methods. However, understanding local services is essential before implementing these advancements. With diverse tracking methods in place, there is a need for efficient and accurate identification approaches, especially in the context of managing lung nodules alongside pre-existing cancer scenarios. This study explores the integration of text-based algorithms in medical data curation, indicating their efficacy in conjunction with machine learning and deep-learning models for identifying lung nodules. Combining medical images with text data has demonstrated superior data retrieval compared to using each modality independently. While deep learning and text analysis show potential in detecting previously missed nodules, challenges persist, such as increased false positives. The presented research introduces a Structured-Query-Language (SQL) algorithm designed for identifying pulmonary nodules in a tertiary cancer center, externally validated at another hospital. Leveraging natural language processing (NLP) and machine learning, the algorithm categorizes lung nodule reports based on sentence features, aiming to facilitate research and assess clinical pathways. The hypothesis posits that the algorithm can accurately identify lung nodule CT scans and predict concerning nodule features using machine-learning classifiers. Through a retrospective observational study spanning a decade, CT scan reports were collected, and an algorithm was developed to extract and classify data. Results underscore the complexity of lung nodule cohorts in cancer centers, emphasizing the importance of careful evaluation before assuming a metastatic origin. The SQL and NLP algorithms demonstrated high accuracy in identifying lung nodule sentences, indicating potential for local service evaluation and research dataset creation. Machine-learning models exhibited strong accuracy in predicting concerning changes in lung nodule scan reports. While limitations include variability in disease group attribution, the potential for correlation rather than causality in clinical findings, and the need for further external validation, the algorithm's accuracy and potential to support clinical decision-making and healthcare automation represent a significant stride in lung nodule management and research.

Keywords: lung cancer diagnosis, structured-query-language (SQL), natural language processing (NLP), machine learning, CT scans

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Authors: Debashis Nath

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Drawn from multiple reanalysis datasets, an increasing trend and westward shift in the number of Potential Vorticity (PV) intrusion events over the Pacific are evident. The increased frequency can be linked to a long-term trend in upper tropospheric (UT, 200 hPa) equatorial westerly wind and subtropical jets (STJ) during boreal winter to spring. These may be resulting from anomalous warming and cooling over the western Pacific warm pool and the tropical eastern Pacific, respectively. The intrusions brought dry and ozone rich air of stratospheric origin deep into the tropics. In the tropical UT, interannual ozone variability is mainly related to convection associated with El Niño/Southern Oscillation. Zonal mean stratospheric overturning circulation organizes the transport of ozone rich air poleward and downward to the high and midlatitudes leading there to higher ozone concentration. In addition to these well described mechanisms, we observe a long-term increasing trend in ozone flux over the northern hemispheric outer tropical (10–25°N) central Pacific that results from equatorward transport and downward mixing from the midlatitude UT and lower stratosphere (LS) during PV intrusions. This increase in tropospheric ozone flux over the Pacific Ocean may affect the radiative processes and changes the budget of atmospheric hydroxyl radicals. The results demonstrate a long-term increase in outer tropical Pacific PV intrusions linked with the strengthening of the upper tropospheric equatorial westerlies and weakening of the STJ. Zonal variation in SST, characterized by gradual warming in the western Pacific–warm pool and cooling in the central–eastern Pacific, is associated with the strengthening of the Pacific Walker circulation. In the Western Pacific enhanced convective activity leads to precipitation, and the latent heat released in the process strengthens the Pacific Walker circulation. However, it is linked with the trend in global mean temperature, which is related to the emerging anthropogenic greenhouse signal and negative phase of PDO. On the other hand, the central-eastern Pacific cooling trend is linked to the weakening of the central–eastern Pacific Hadley circulation. It suppresses the convective activity due to sinking air motion and imports less angular momentum to the STJ leading to a weakened STJ. While, more PV intrusions result from this weaker STJ on its equatorward side; significantly increase the stratosphere-troposphere exchange processes on the longer timescale. This plays an important role in determining the atmospheric composition, particularly of tropospheric ozone, in the northern outer tropical central Pacific. It may lead to more ozone of stratospheric origin in the LT and even in the marine boundary, which may act as harmful pollutants and affect the radiative processes by changing the global budgets of atmospheric hydroxyl radicals.

Keywords: PV intrusion, westerly duct, ozone, Central Pacific

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Authors: Kim Anema, Matthias Max, Chris Zevenbergen

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For any flood risk manager the 'safety paradox' has to be a familiar concept: low probability leads to a sense of safety, which leads to more investments in the area, which leads to higher potential consequences: keeping the aggregated risk (probability*consequences) at the same level. Therefore, it is important to mitigate potential consequences apart from probability. However, when the (perceived) probability is so low that there is no recognizable trend for society to adapt to, addressing the potential consequences will always be the lagging point on the agenda. Preparedness programs fail because of lack of interest and urgency, policy makers are distracted by their day to day business and there's always a more urgent issue to spend the taxpayer's money on. The leading question in this study was how to address the social consequences of flooding in a context of (perceived) low probability. Disruptions of everyday urban life, large or small, can be caused by a variety of (un)expected things - of which flooding is only one possibility. Variability like this is typically addressed with resilience - and we used the concept of Community Resilience as the framework for this study. Drawing on face to face interviews, an extensive questionnaire and publicly available statistical data we explored the 'whole society response' to two recent urban flood events; the Brisbane Floods (AUS) in 2011 and the Dresden Floods (GE) in 2013. In Brisbane, we studied how the societal impacts of the floods were counteracted by both authorities and the public, and in Dresden we were able to validate our findings. A large part of the reactions, both public as institutional, to these two urban flood events were not fuelled by preparedness or proper planning. Instead, more important success factors in counteracting social impacts like demographic changes in neighborhoods and (non-)economic losses were dynamics like community action, flexibility and creativity from authorities, leadership, informal connections and a shared narrative. These proved to be the determining factors for the quality and speed of recovery in both cities. The resilience of the community in Brisbane was good, due to (i) the approachability of (local) authorities, (ii) a big group of ‘secondary victims’ and (iii) clear leadership. All three of these elements were amplified by the use of social media and/ or web 2.0 by both the communities and the authorities involved. The numerous contacts and social connections made through the web were fast, need driven and, in their own way, orderly. Similarly in Dresden large groups of 'unprepared', ad hoc organized citizens managed to work together with authorities in a way that was effective and speeded up recovery. The concept of community resilience is better fitted than 'social adaptation' to deal with the potential consequences of an (im)probable flood. Community resilience is built on capacities and dynamics that are part of everyday life and which can be invested in pre-event to minimize the social impact of urban flooding. Investing in these might even have beneficial trade-offs in other policy fields.

Keywords: community resilience, disaster response, social consequences, preparedness

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Authors: Sibgha Noreen, Muhammad Salim Akhter, Seema Mahmood

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Salt stress is an abiotic stress that causes a heavy toll on growth and development and also reduces the productivity of arable and horticultural crops. Globally, a quarter of total arable land has fallen prey to this menace, and more is being encroached because of the usage of brackish water for irrigation purposes. Though barley is categorized as salt-tolerant crop, but cultivars show a wide genetic variability in response to it. In addressing salt stress, silicon nutrition would be a facile tool for enhancing salt tolerant to sustain crop production. A greenhouse study was conducted to evaluate the response of barley (Hordeum vulgare L.) cultivars to silicon nutrition under salt stress. The treatments included [(a) four barley cultivars (Jou-87, B-14002, B-14011, B-10008); (b) two salt levels (0, 200 mM, NaCl); and (c) two silicon levels (0, 200ppm, K2SiO3. nH2O), arranged in a factorial experiment in a completely randomized design with 16 treatments and repeated 4 times. Plants were harvested at 15 days after exposure to different experimental salinity and silicon foliar conditions. Results revealed that various physiological and biochemical attributes differed significantly (p<0.05) in response to different treatments and their interactive effects. Cultivar “B-10008” excelled in biological yield, chlorophyll constituents, antioxidant enzymes, and grain yield compared to other cultivars. The biological yield of shoot and root organs was reduced by 27.3 and 26.5 percent under salt stress, while it was increased by 14.5 and 18.5 percent by exogenous application of silicon over untreated check, respectively. The imposition of salt stress at 200 mM caused a reduction in total chlorophyll content, chl ‘a’ , ‘b’ and ratio a/b by 10.6,16.8,17.1 and 7.1, while spray of 200 ppm silicon improved the quantum of the constituents by 10.4,12.1,10.2,10.3 over untreated check, respectively. The quantum of free amino acids and protein content was enhanced in response to salt stress and the spray of silicon nutrients. The amounts of superoxide dismutase, catalases, peroxidases, hydrogen peroxide, and malondialdehyde contents rose to 18.1, 25.7, 28.1, 29.5, and 17.6 percent over non-saline conditions under salt stress. However, the values of these antioxidants were reduced in proportion to salt stress by 200 ppm silicon applied as rooting medium on barley crops. The salt stress caused a reduction in the number of tillers, number of grains per spike, and 100-grain weight to the amount of 29.4, 8.6, and 15.8 percent; however, these parameters were improved by 7.1, 10.3, and 9.6 percent by foliar spray of silicon over untreated crop, respectively. It is concluded that the barley cultivar “B-10008” showed greater tolerance and adaptability to saline conditions. The yield of barley crops could be potentiated by a foliar spray of 200 ppm silicon at the vegetative growth stage under salt stress.

Keywords: salt stress, silicon nutrition, chlorophyll constituents, antioxidant enzymes, barley crop

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Authors: Pavlina Capkova, Josef Srovnal, Vera Becvarova, Marie Trkova, Zuzana Capkova, Andrea Stefekova, Vaclava Curtisova, Alena Santava, Sarka Vejvalkova, Katerina Adamova, Radek Vodicka

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ASDs are heterogeneous and complex developmental diseases with a significant genetic background. Recurrent CNVs are known to be a frequent cause of ASD. These CNVs can have, however, a variable expressivity which results in a spectrum of phenotypes from asymptomatic to ID/DD/ASD. ASD is associated with ID in ~75% individuals. Various platforms are used to detect pathogenic mutations in the genome of these patients. The performed study is focused on a determination of the frequency of pathogenic mutations in a group of ASD patients and a group of ID/DD patients using various strategies along with a comparison of their detection rate. The possible role of the origin of these mutations in aetiology of ASD was assessed. The study included 35 individuals with ASD and 68 individuals with ID/DD (64 males and 39 females in total), who underwent rigorous genetic, neurological and psychological examinations. Screening for pathogenic mutations involved karyotyping, screening for FMR1 mutations and for metabolic disorders, a targeted MLPA test with probe mixes Telomeres 3 and 5, Microdeletion 1 and 2, Autism 1, MRX and a chromosomal microarray analysis (CMA) (Illumina or Affymetrix). Chromosomal aberrations were revealed in 7 (1 in the ASD group) individuals by karyotyping. FMR1 mutations were discovered in 3 (1 in the ASD group) individuals. The detection rate of pathogenic mutations in ASD patients with a normal karyotype was 15.15% by MLPA and CMA. The frequencies of the pathogenic mutations were 25.0% by MLPA and 35.0% by CMA in ID/DD patients with a normal karyotype. CNVs inherited from asymptomatic parents were more abundant than de novo changes in ASD patients (11.43% vs. 5.71%) in contrast to the ID/DD group where de novo mutations prevailed over inherited ones (26.47% vs. 16.18%). ASD patients shared more frequently their mutations with their fathers than patients from ID/DD group (8.57% vs. 1.47%). Maternally inherited mutations predominated in the ID/DD group in comparison with the ASD group (14.7% vs. 2.86 %). CNVs of an unknown significance were found in 10 patients by CMA and in 3 patients by MLPA. Although the detection rate is the highest when using CMA, recurrent CNVs can be easily detected by MLPA. CMA proved to be more efficient in the ID/DD group where a larger spectrum of rare pathogenic CNVs was revealed. This study determined that maternally inherited highly penetrant mutations and de novo mutations more often resulted in ID/DD without ASD in patients. The paternally inherited mutations could be, however, a source of the greater variability in the genome of the ASD patients and contribute to the polygenic character of the inheritance of ASD. As the number of the subjects in the group is limited, a larger cohort is needed to confirm this conclusion. Inherited CNVs have a role in aetiology of ASD possibly in combination with additional genetic factors - the mutations elsewhere in the genome. The identification of these interactions constitutes a challenge for the future. Supported by MH CZ – DRO (FNOl, 00098892), IGA UP LF_2016_010, TACR TE02000058 and NPU LO1304.

Keywords: autistic spectrum disorders, copy number variant, chromosomal microarray, intellectual disability, karyotyping, MLPA, multiplex ligation-dependent probe amplification

Procedia PDF Downloads 328

Authors: Shashikant Iyengar, Jasmeet Kaur, Anup Singh, Arun Kumar, Ira Sahay

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Insulin resistance (IR) is a condition that occurs when cells in the body become less responsive to insulin, leading to higher levels of both insulin and glucose in the blood. This condition is linked to metabolic syndromes, including diabetes. It is crucial to address IR promptly after diagnosis to prevent long-term complications associated with high insulin and high blood glucose. This four-month case study highlights the importance of treating the underlying condition to manage diabetes effectively. Insulin is essential for regulating blood sugar levels by facilitating the uptake of glucose into cells for energy or storage. In IR individuals, cells are less efficient at taking up glucose from the blood resulting in elevated blood glucose levels. As a result of IR, beta cells produce more insulin to make up for the body's inability to use insulin effectively. This leads to high insulin levels, a condition known as hyperinsulinemia, which further impairs glucose metabolism and can contribute to various chronic diseases. In addition to regulating blood glucose, insulin has anti-catabolic effects, preventing the breakdown of molecules in the body, such as inhibiting glycogen breakdown in the liver, inhibiting gluconeogenesis, and inhibiting lipolysis. If a person is insulin-sensitive or metabolically healthy, an optimal level of insulin prevents fat cells from releasing fat and promotes the storage of glucose and fat in the body. Thus optimal insulin levels are crucial for maintaining energy balance and plays a key role in metabolic processes. During the four-month study, researchers looked at the impact of a low-carb dietary (LCD) intervention on two male individuals (A & B) who had Type-2 diabetes. Althoughvneither of these individuals were obese, they were both slightly overweight and had abdominal fat deposits. Before the trial began, important markers such as fasting blood glucose (FBG), triglycerides (TG), high-density lipoprotein (HDL) cholesterol, and Hba1c were measured. These markers are essential in defining metabolic health, their individual values and variability are integral in deciphering metabolic health. The ratio of TG to HDL is used as a surrogate marker for IR. This ratio has a high correlation with the prevalence of metabolic syndrome and with IR itself. It is a convenient measure because it can be calculated from a standard lipid profile and does not require more complex tests. In this four-month trial, an improvement in insulin sensitivity was observed through the ratio of TG/HDL, which, in turn, improves fasting blood glucose levels and HbA1c. For subject A, HbA1c dropped from 13 to 6.28, and for subject B, it dropped from 9.4 to 5.7. During the trial, neither of the subjects were taking any diabetic medications. The significant improvements in their health markers, such as better glucose control, along with an increase in energy levels, demonstrate that incorporating LCD interventions can effectively manage diabetes.

Keywords: metabolic disorder, insulin resistance, type-2 diabetes, low-carb nutrition

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Authors: Moustafa Osman Mohammed

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This paper introduces Luhmann’s autopoietic social systems starting with the original concept of autopoiesis by biologists and scientists, including the modification of general systems based on socialized medicine. A specific type of autopoietic system is explained in the three existing groups of the ecological phenomena: interaction, social and medical sciences. This hypothesis model, nevertheless, has a nonlinear interaction with its natural environment ‘interactional cycle’ for the exchange of photon energy with molecular without any changes in topology. The external forces in the systems environment might be concomitant with the natural fluctuations’ influence (e.g. radioactive radiation, electromagnetic waves). The cantilever sensor deploys insights to the future chip processor for prevention of social metabolic systems. Thus, the circuits with resonant electric and optical properties are prototyped on board as an intra–chip inter–chip transmission for producing electromagnetic energy approximately ranges from 1.7 mA at 3.3 V to service the detection in locomotion with the least significant power losses. Nowadays, therapeutic systems are assimilated materials from embryonic stem cells to aggregate multiple functions of the vessels nature de-cellular structure for replenishment. While, the interior actuators deploy base-pair complementarity of nucleotides for the symmetric arrangement in particular bacterial nanonetworks of the sequence cycle creating double-stranded DNA strings. The DNA strands must be sequenced, assembled, and decoded in order to reconstruct the original source reliably. The design of exterior actuators have the ability in sensing different variations in the corresponding patterns regarding beat-to-beat heart rate variability (HRV) for spatial autocorrelation of molecular communication, which consists of human electromagnetic, piezoelectric, electrostatic and electrothermal energy to monitor and transfer the dynamic changes of all the cantilevers simultaneously in real-time workspace with high precision. A prototype-enabled dynamic energy sensor has been investigated in the laboratory for inclusion of nanoscale devices in the architecture with a fuzzy logic control for detection of thermal and electrostatic changes with optoelectronic devices to interpret uncertainty associated with signal interference. Ultimately, the controversial aspect of molecular frictional properties is adjusted to each other and forms its unique spatial structure modules for providing the environment mutual contribution in the investigation of mass temperature changes due to pathogenic archival architecture of clusters.

Keywords: autopoiesis, nanoparticles, quantum photonics, portable energy, photonic structure, photodynamic therapeutic system

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Authors: Asmit Neupane, Narayan Prasad Gautam, Prabin Bhusal

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Indian pangolin, locally called as ‘Salak’, ‘Sal machha’, ‘Pakho machha’, is a globally endangered species, nationally categorized as a critically endangered species, protected under the National Parks and Wildlife Conservation (NPWC) Act 1973 and appended in Appendix I of CITES. Indian pangolins occur in the tropical areas of Terai region and Chure foothills of eastern Nepal, and India, Bangladesh, Pakistan, and Sri Lanka. They utilize a wide range of habitats, including primary and secondary tropical forest, limestone forest, bamboo forest, grassland, and agricultural lands. So, in regard to this fact, this research is aimed to provide detailed information regarding the current distribution pattern, status, habitat preference, prevailing threats and attitude of local people towards species conservation in Madhesh Province, Nepal. The study was conducted in four CFs, two from Bara district and two from Dhanusha district. The study area comprised of Churia range and foothills with tropical and sub-tropical vegetation. A total of 24 transects were established, each of 500*50 m2, where indirect signs of Indian pangolin, including active/old burrows, pugmarks and scratches, were found. Altogether 93 burrows were found, where only 20 were active burrows. Similarly, a vegetation survey and social survey was also conducted. The data was analyzed using Stata 16 and SPSS software. Distance from settlement, ground cover, aspect, presence/absence of ants/termites and human disturbance were the important habitat parameters having statistically significant relationship with the distribution of Indian pangolin in the area. The species was found to prefer an elevation of 360 to 540m, 0-15º slope, red soil, North-east aspect, moderate crown and ground cover, without fire and rocks, vicinity of water, roads, settlement, Sal dominated forest and minimum disturbed by human activities. Similarly, the attitude of local people towards Indian pangolin conservation was found to be significantly different with respect to age, sex and education level. The study concludes that majority of active burrows were found in Churia hills, which indicates that Indian pangolin population is gradually moving uphill towards higher elevation as hilly area supports better prey availability and also less human disturbance. Further studies are required to investigate microhabitat preferences, seasonal variability and impacts of climate change on the distribution, habitat and prey availability of Indian pangolin for the sustainable conservation of this species.

Keywords: conservation, IUCN red list, local participation, small mammal, status, threats

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Authors: Corentin Jankowiak, Aggelos Zacharopoulos, Caterina Brandoni

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In a context of increasing stress put on the electricity network by the decarbonization of many sectors, energy storage is likely to be the key mitigating element, by acting as a buffer between production and demand. In particular, the highest potential for storage is when connected closer to the loads. Yet, low voltage storage struggles to penetrate the market at a large scale due to the novelty and complexity of the solution, and the competitive advantage of fossil fuel-based technologies regarding regulations. Strong and reliable numerical simulations are required to show the benefits of storage located near loads and promote its development. The present study was restrained from excluding aggregated control of storage: it is assumed that the storage units operate independently to one another without exchanging information – as is currently mostly the case. A computationally light battery model is presented in detail and validated by direct comparison with a domestic battery operating in real conditions. This model is then used to develop Peak-Shaving (PS) control strategies as it is the decentralized service from which beneficial impacts are most likely to emerge. The aggregation of flatter, peak- shaved consumption profiles is likely to lead to flatter and arbitraged profile at higher voltage layers. Furthermore, voltage fluctuations can be expected to decrease if spikes of individual consumption are reduced. The crucial part to achieve PS lies in the charging pattern: peaks depend on the switching on and off of appliances in the dwelling by the occupants and are therefore impossible to predict accurately. A performant PS strategy must, therefore, include a smart charge recovery algorithm that can ensure enough energy is present in the battery in case it is needed without generating new peaks by charging the unit. Three categories of PS algorithms are introduced in detail. First, using a constant threshold or power rate for charge recovery, followed by algorithms using the State Of Charge (SOC) as a decision variable. Finally, using a load forecast – of which the impact of the accuracy is discussed – to generate PS. A performance metrics was defined in order to quantitatively evaluate their operating regarding peak reduction, total energy consumption, and self-consumption of domestic photovoltaic generation. The algorithms were tested on load profiles with a 1-minute granularity over a 1-year period, and their performance was assessed regarding these metrics. The results show that constant charging threshold or power are far from optimal: a certain value is not likely to fit the variability of a residential profile. As could be expected, forecast-based algorithms show the highest performance. However, these depend on the accuracy of the forecast. On the other hand, SOC based algorithms also present satisfying performance, making them a strong alternative when the reliable forecast is not available.

Keywords: decentralised control, domestic integrated batteries, electricity network performance, peak-shaving algorithm

Procedia PDF Downloads 95

Authors: Benjamin Glasner, Carlos Henriquez, Fernando Alfaro, Nicole Trefault, Santiago Andrade, Rodrigo De La Iglesia

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A central question in ecology refers to the relative importance that local-scale variables have over community composition, when compared with regional-scale variables. In coastal environments, strong seasonal abiotic influence dominates these systems, weakening the impact of other parameters like micronutrients. After the industrial revolution, micronutrients like trace metals have increased in ocean as pollutants, with strong effects upon biotic entities and biological processes in coastal regions. Coastal picoplankton communities had been characterized as a cyanobacterial dominated fraction, but in recent years the eukaryotic component of this size fraction has gained relevance due to their high influence in carbon cycle, although, diversity patterns and responses to disturbances are poorly understood. South Pacific upwelling coastal environments represent an excellent model to study seasonal changes due to a strong influence in the availability of macro- and micronutrients between seasons. In addition, some well constrained coastal bays of this region have been subjected to strong disturbances due to trace metal inputs. In this study, we aim to compare the influence of seasonality and trace metals concentrations, on the community structure of planktonic picoeukaryotes. To describe seasonal patterns in the study area, satellite data in a 6 years time series and in-situ measurements with a traditional oceanographic approach such as CTDO equipment were performed. In addition, trace metal concentrations were analyzed trough ICP-MS analysis, for the same region. For biological data collection, field campaigns were performed in 2011-2012 and the picoplankton community was described by flow cytometry and taxonomical characterization with next-generation sequencing of ribosomal genes. The relation between the abiotic and biotic components was finally determined by multivariate statistical analysis. Our data show strong seasonal fluctuations in abiotic parameters such as photosynthetic active radiation and superficial sea temperature, with a clear differentiation of seasons. However, trace metal analysis allows identifying strong differentiation within the study area, dividing it into two zones based on trace metals concentration. Biological data indicate that there are no major changes in diversity but a significant fluctuation in evenness and community structure. These changes are related mainly with regional parameters, like temperature, but by analyzing the metal influence in picoplankton community structure, we identify a differential response of some plankton taxa to metal pollution. We propose that some picoeukaryotic plankton groups respond differentially to metal inputs, by changing their nutritional status and/or requirements under disturbances as a derived outcome of toxic effects and tolerance.

Keywords: Picoeukaryotes, plankton communities, trace metals, seasonal patterns

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Authors: Ionut Vintu, Stefan Laible, Ruth Schulz

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Agricultural robotics has been developing steadily over recent years, with the goal of reducing and even eliminating pesticides used in crops and to increase productivity by taking over human labor. The majority of crops are arranged in rows. The first step towards autonomous robots, capable of driving in fields and performing crop-handling tasks, is for robots to robustly detect the rows of plants. Recent work done towards autonomous driving between plant rows offers big robotic platforms equipped with various expensive sensors as a solution to this problem. These platforms need to be driven over the rows of plants. This approach lacks flexibility and scalability when it comes to the height of plants or distance between rows. This paper proposes instead an algorithm that makes use of cheaper sensors and has a higher variability. The main application is in tree nurseries. Here, plant height can range from a few centimeters to a few meters. Moreover, trees are often removed, leading to gaps within the plant rows. The core idea is to combine row detection algorithms with graph-based localization methods as they are used in SLAM. Nodes in the graph represent the estimated pose of the robot, and the edges embed constraints between these poses or between the robot and certain landmarks. This setup aims to improve individual plant detection and deal with exception handling, like row gaps, which are falsely detected as an end of rows. Four methods were developed for detecting row structures in the fields, all using a point cloud acquired with a 3D LiDAR as an input. Comparing the field coverage and number of damaged plants, the method that uses a local map around the robot proved to perform the best, with 68% covered rows and 25% damaged plants. This method is further used and combined with a graph-based localization algorithm, which uses the local map features to estimate the robot’s position inside the greater field. Testing the upgraded algorithm in a variety of simulated fields shows that the additional information obtained from localization provides a boost in performance over methods that rely purely on perception to navigate. The final algorithm achieved a row coverage of 80% and an accuracy of 27% damaged plants. Future work would focus on achieving a perfect score of 100% covered rows and 0% damaged plants. The main challenges that the algorithm needs to overcome are fields where the height of the plants is too small for the plants to be detected and fields where it is hard to distinguish between individual plants when they are overlapping. The method was also tested on a real robot in a small field with artificial plants. The tests were performed using a small robot platform equipped with wheel encoders, an IMU and an FX10 3D LiDAR. Over ten runs, the system achieved 100% coverage and 0% damaged plants. The framework built within the scope of this work can be further used to integrate data from additional sensors, with the goal of achieving even better results.

Keywords: 3D LiDAR, agricultural robots, graph-based localization, row detection

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Authors: Devansh Desai, Rahul Nigam

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Crop water stress (W) at a given growth stage starts to set in as moisture availability (M) to roots falls below 75% of maximum. It has been found that ratio of crop evapotranspiration (ET) and reference evapotranspiration (ET0) is an indicator of moisture adequacy and is strongly correlated with ‘M’ and ‘W’. The spatial variability of ET0 is generally less over an agricultural farm of 1-5 ha than ET, which depends on both surface and atmospheric conditions, while the former depends only on atmospheric conditions. Solutions from surface energy balance (SEB) and thermal infrared (TIR) remote sensing are now known to estimate latent heat flux of ET. In the present study, ET and moisture adequacy index (MAI) (=ET/ET0) have been estimated over two contrasting western India agricultural farms having rice-wheat system in semi-arid climate and arid grassland system, limited by moisture availability. High-resolution multi-band TIR sensing observations at 65m from ECOSTRESS (ECOsystemSpaceborne Thermal Radiometer Experiment on Space Station) instrument on-board International Space Station (ISS) were used in an analytical SEB model, STIC (Surface Temperature Initiated Closure) to estimate ET and MAI. The ancillary variables used in the ET modeling and MAI estimation were land surface albedo, NDVI from close-by LANDSAT data at 30m spatial resolution, ET0 product at 4km spatial resolution from INSAT 3D, meteorological forcing variables from short-range weather forecast on air temperature and relative humidity from NWP model. Farm-scale ET estimates at 65m spatial resolution were found to show low RMSE of 16.6% to 17.5% with R2 >0.8 from 18 datasets as compared to reported errors (25 – 30%) from coarser-scale ET at 1 to 8 km spatial resolution when compared to in situ measurements from eddy covariance systems. The MAI was found to show lower (<0.25) and higher (>0.5) magnitudes in the contrasting agricultural farms. The study showed the potential need of high-resolution high-repeat spaceborne multi-band TIR payloads alongwith optical payload in estimating farm-scale ET and MAI for estimating consumptive water use and water stress. A set of future high-resolution multi-band TIR sensors are planned on-board Indo-French TRISHNA, ESA’s LSTM, NASA’s SBG space-borne missions to address sustainable irrigation water management at farm-scale to improve crop water productivity. These will provide precise and fundamental variables of surface energy balance such as LST (Land Surface Temperature), surface emissivity, albedo and NDVI. A synchronization among these missions is needed in terms of observations, algorithms, product definitions, calibration-validation experiments and downstream applications to maximize the potential benefits.

Keywords: thermal remote sensing, land surface temperature, crop water stress, evapotranspiration

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Authors: I. Hosni, L. Bennaceur Farah, N. Saber, R Bennaceur

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Soil moisture content is a key variable in many environmental sciences. Even though it represents a small proportion of the liquid freshwater on Earth, it modulates interactions between the land surface and the atmosphere, thereby influencing climate and weather. Accurate modeling of the above processes depends on the ability to provide a proper spatial characterization of soil moisture. The measurement of soil moisture content allows assessment of soil water resources in the field of hydrology and agronomy. The second parameter in interaction with the radar signal is the geometric structure of the soil. Most traditional electromagnetic models consider natural surfaces as single scale zero mean stationary Gaussian random processes. Roughness behavior is characterized by statistical parameters like the Root Mean Square (RMS) height and the correlation length. Then, the main problem is that the agreement between experimental measurements and theoretical values is usually poor due to the large variability of the correlation function, and as a consequence, backscattering models have often failed to predict correctly backscattering. In this study, surfaces are considered as band-limited fractal random processes corresponding to a superposition of a finite number of one-dimensional Gaussian process each one having a spatial scale. Multiscale roughness is characterized by two parameters, the first one is proportional to the RMS height, and the other one is related to the fractal dimension. Soil moisture is related to the complex dielectric constant. This multiscale description has been adapted to two-dimensional profiles using the bi-dimensional wavelet transform and the Mallat algorithm to describe more correctly natural surfaces. We characterize the soil surfaces and sub-surfaces by a three layers geo-electrical model. The upper layer is described by its dielectric constant, thickness, a multiscale bi-dimensional surface roughness model by using the wavelet transform and the Mallat algorithm, and volume scattering parameters. The lower layer is divided into three fictive layers separated by an assumed plane interface. These three layers were modeled by an effective medium characterized by an apparent effective dielectric constant taking into account the presence of air pockets in the soil. We have adopted the 2D multiscale three layers small perturbations model including, firstly air pockets in the soil sub-structure, and then a vegetable canopy in the soil surface structure, that is to simulate the radar backscattering. A sensitivity analysis of backscattering coefficient dependence on multiscale roughness and new soil moisture has been performed. Later, we proposed to change the dielectric constant of the multilayer medium because it takes into account the different moisture values of each layer in the soil. A sensitivity analysis of the backscattering coefficient, including the air pockets in the volume structure with respect to the multiscale roughness parameters and the apparent dielectric constant, was carried out. Finally, we proposed to study the behavior of the backscattering coefficient of the radar on a soil having a vegetable layer in its surface structure.

Keywords: multiscale, bidimensional, wavelets, backscattering, multilayer, SPM, air pockets

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Authors: Sardorbek Numonov, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Dongeun Choi, Byung-Woo Hong

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The detection of curvilinear structures often plays an important role in the analysis of images. In particular, it is considered as a crucial step for the diagnosis of chronic respiratory diseases to localize the fissures in chest CT imagery where the lung is divided into five lobes by the fissures that are characterized by linear features in appearance. However, the characteristic linear features for the fissures are often shown to be subtle due to the high intensity variability, pathological deformation or image noise involved in the imaging procedure, which leads to the uncertainty in the quantification of anatomical or functional properties of the lung. Thus, it is desired to enhance the linear features present in the chest CT images so that the distinctiveness in the delineation of the lobe is improved. We propose a recursive diffusion process that prefers coherent features based on the analysis of structure tensor in an anisotropic manner. The local image features associated with certain scales and directions can be characterized by the eigenanalysis of the structure tensor that is often regularized via isotropic diffusion filters. However, the isotropic diffusion filters involved in the computation of the structure tensor generally blur geometrically significant structure of the features leading to the degradation of the characteristic power in the feature space. Thus, it is required to take into consideration of local structure of the feature in scale and direction when computing the structure tensor. We apply an anisotropic diffusion in consideration of scale and direction of the features in the computation of the structure tensor that subsequently provides the geometrical structure of the features by its eigenanalysis that determines the shape of the anisotropic diffusion kernel. The recursive application of the anisotropic diffusion with the kernel the shape of which is derived from the structure tensor leading to the anisotropic scale-space where the geometrical features are preserved via the eigenanalysis of the structure tensor computed from the diffused image. The recursive interaction between the anisotropic diffusion based on the geometry-driven kernels and the computation of the structure tensor that determines the shape of the diffusion kernels yields a scale-space where geometrical properties of the image structure are effectively characterized. We apply our recursive anisotropic diffusion algorithm to the detection of curvilinear structure in the chest CT imagery where the fissures present curvilinear features and define the boundary of lobes. It is shown that our algorithm yields precise detection of the fissures while overcoming the subtlety in defining the characteristic linear features. The quantitative evaluation demonstrates the robustness and effectiveness of the proposed algorithm for the detection of fissures in the chest CT in terms of the false positive and the true positive measures. The receiver operating characteristic curves indicate the potential of our algorithm as a segmentation tool in the clinical environment. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: anisotropic diffusion, chest CT imagery, chronic respiratory disease, curvilinear structure, fissure detection, structure tensor

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Authors: Areej Al-Hamad, Yasin Yasin, Kateryna Metersky

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This mixed-method systematic review and meta-analysis provide an encompassing understanding of the barriers, facilitators, and predictors of refugee women's employment and economic inclusion. The study sheds light on the complex interplay of sociocultural, personal, political, and environmental factors influencing these outcomes, underlining the urgent need for a multifaceted, tailored approach to devising strategies, policies, and interventions aimed at boosting refugee women's economic empowerment. Our findings suggest that sociocultural factors, including gender norms, societal attitudes, language proficiency, and social networks, profoundly shape refugee women's access to and participation in the labor market. Personal factors such as age, educational attainment, health status, skills, and previous work experience also play significant roles. Political factors like immigration policies, regulations, and rights to work, alongside environmental factors like labor market conditions, availability of employment opportunities, and access to resources and support services, further contribute to the complex dynamics influencing refugee women's economic inclusion. The significant variability observed in the impacts of these factors across different contexts underscores the necessity of adopting population and region-specific strategies. A one-size-fits-all approach may prove to be ineffective due to the diversity and unique circumstances of refugee women across different geographical, cultural, and political contexts. The study's findings have profound implications for policy-making, practice, education, and research. The insights garnered a call for coordinated efforts across these domains to bolster refugee women's economic participation. In policy-making, the findings necessitate a reassessment of current immigration and labor market policies to ensure they adequately support refugee women's employment and economic integration. In practice, they highlight the need for comprehensive, tailored employment services and interventions that address the specific barriers and leverage the facilitators identified. In education, they underline the importance of language and skills training programs that cater to the unique needs and circumstances of refugee women. Lastly, in research, they emphasize the need for ongoing investigations into the multifaceted factors influencing refugee women's employment experiences, allowing for continuous refinement of our understanding and interventions. Through this comprehensive exploration, the study contributes to ongoing efforts aimed at creating more inclusive, equitable societies. By continually refining our understanding of the complex factors influencing refugee women's employment experiences, we can pave the way toward enhanced economic empowerment for this vulnerable population.

Keywords: refugee women, employment barriers, systematic review, employment facilitators

Procedia PDF Downloads 43

Authors: Emily Rowe

Abstract:

Introduction: Balance assessments can be used to help evaluate a person’s risk of falls, determine causes of balance deficits and inform intervention decisions. It is widely accepted that instrumented quantitative analysis can be more reliable and specific than semi-qualitative ordinal scales or itemised scoring methods. However, the uptake of quantitative methods is hindered by expense, lack of portability, and set-up requirements. During stepping, foot placement is actively coordinated with the body centre of mass (COM) kinematics during pre-initiation. Based on this, the potential to use COM velocity just prior to foot off and foot placement error as an outcome measure of dynamic balance is currently being explored using complex 3D motion capture. Inertial sensors and pressure mats might be more practical technologies for measuring these parameters in clinical settings. Objective: The aim of this study was to test the criterion validity and test-retest reliability of a synchronised inertial sensor and pressure mat-based approach to measure foot placement error and COM velocity while stepping. Methods: Trials were held with 15 healthy participants who each attended for two sessions. The trial task was to step onto one of 4 targets (2 for each foot) multiple times in a random, unpredictable order. The stepping target was cued using an auditory prompt and electroluminescent panel illumination. Data was collected using 3D motion capture and a combined inertial sensor-pressure mat system simultaneously in both sessions. To assess the reliability of each system, ICC estimates and their 95% confident intervals were calculated based on a mean-rating (k = 2), absolute-agreement, 2-way mixed-effects model. To test the criterion validity of the combined inertial sensor-pressure mat system against the motion capture system multi-factorial two-way repeated measures ANOVAs were carried out. Results: It was found that foot placement error was not reliably measured between sessions by either system (ICC 95% CIs; motion capture: 0 to >0.87 and pressure mat: <0.53 to >0.90). This could be due to genuine within-subject variability given the nature of the stepping task and brings into question the suitability of average foot placement error as an outcome measure. Additionally, results suggest the pressure mat is not a valid measure of this parameter since it was statistically significantly different from and much less precise than the motion capture system (p=0.003). The inertial sensor was found to be a moderately reliable (ICC 95% CIs >0.46 to >0.95) but not valid measure for anteroposterior and mediolateral COM velocities (AP velocity: p=0.000, ML velocity target 1 to 4: p=0.734, 0.001, 0.000 & 0.376). However, it is thought that with further development, the COM velocity measure validity could be improved. Possible options which could be investigated include whether there is an effect of inertial sensor placement with respect to pelvic marker placement or implementing more complex methods of data processing to manage inherent accelerometer and gyroscope limitations. Conclusion: The pressure mat is not a suitable alternative for measuring foot placement errors. The inertial sensors have the potential for measuring COM velocity; however, further development work is needed.

Keywords: dynamic balance, inertial sensors, portable, pressure mat, reliability, stepping, validity, wearables

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Authors: Salwa Mohamed Salah Eldin, Howida Kamal Ibrahim

Abstract:

Introduction: Major depressive disorder affects high proportion of the world’s population presenting cost load in health care. Extended release venlafaxine is more convenient and could reduce discontinuation syndrome. The once daily dosing also reduces the potential for adverse events such as nausea due to reduced Cmax. Venlafaxine is an effective first-line agent in the treatment of depression. A once daily formulation was designed to enhance patient compliance. Complexing with a resin was suggested to improve loading of the water soluble drug. The formulated systems were thoroughly evaluated in vitro to prove superiority to previous trials and were compared to the commercial extended release product in experimental animals. Materials and Methods: Venlafaxine-resinates were prepared using Dowex®50WX4-400 and Dowex®50WX8-100 at drug to resin weight ratio of 1: 1. The prepared resinates were evaluated for their drug content, particle shape and surface properties and in vitro release profile in gradient pH. The release kinetics and mechanism were evaluated. Venlafaxine-Dowex® resinates were encapsulated using O/W solvent evaporation technique. Poly-ε-caprolactone, Poly(D, L-lactide-co-glycolide) ester, Poly(D, L-lactide) ester and Eudragit®RS100 were used as coating polymers alone and in combination. Drug-resinate microcapsules were evaluated for morphology, entrapment efficiency and in-vitro release profile. The selected formula was tested in rabbits using a randomized, single-dose, 2-way crossover study against Effexor-XR tablets under fasting condition. Results and Discussion: The equilibrium time was 30 min for Dowex®50WX4-400 and 90 min for Dowex®50WX8-100. The percentage drug loaded was 93.96 and 83.56% for both resins, respectively. Both drug-Dowex® resintes were efficient in sustaining venlafaxine release in comparison to the free drug (up to 8h.). Dowex®50WX4-400 based venlafaxine-resinate was selected for further encapsulation to optimize the release profile for once daily dosing and to lower the burst effect. The selected formula (coated with a mixture of Eudragit RS and PLGA in a ratio of 50/50) was chosen by applying a group of mathematical equations according to targeted values. It recorded the minimum burst effect, the maximum MDT (Mean dissolution time) and a Q24h (percentage drug released after 24 hours) between 95 and 100%. The 90% confidence intervals for the test/reference mean ratio of the log-transformed data of AUC0–24 and AUC0−∞ are within (0.8–1.25), which satisfies the bioequivalence criteria. Conclusion: The optimized formula could be a promising extended release form of the water soluble, short half lived venlafaxine. Being a multiple unit formulation, it lowers the probability of dose dumping and reduces the inter-subject variability in absorption.

Keywords: biodegradable polymers, cation-exchange resin, microencapsulation, venlafaxine hcl

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Authors: S. Sabatino, V. Calderaro, V. Galdi, G. Graber, L. Ippolito

Abstract:

Climate change is a rapidly growing global threat caused mainly by increased emissions of carbon dioxide (CO₂) into the atmosphere. These emissions come from multiple sources, including industry, power generation, and the transport sector. The need to tackle climate change and reduce CO₂ emissions is indisputable. A crucial solution to achieving decarbonization in the transport sector is the adoption of electric vehicles (EVs). These vehicles use lithium (Li-Ion) batteries as an energy source, making them extremely efficient and with low direct emissions. However, Li-Ion batteries are not without problems, including the risk of overheating and performance degradation. To ensure its safety and longevity, it is essential to use a battery management system (BMS). The BMS constantly monitors battery status, adjusts temperature and cell balance, ensuring optimal performance and preventing dangerous situations. From the monitoring carried out, it is also able to optimally manage the battery to increase its life. Among the parameters monitored by the BMS, the main ones are State of Charge (SoC), State of Health (SoH), and State of Power (SoP). The evaluation of these parameters can be carried out in two ways: offline, using benchtop batteries tested in the laboratory, or online, using batteries installed in moving vehicles. Online estimation is the preferred approach, as it relies on capturing real-time data from batteries while operating in real-life situations, such as in everyday EV use. Actual battery usage conditions are highly variable. Moving vehicles are exposed to a wide range of factors, including temperature variations, different driving styles, and complex charge/discharge cycles. This variability is difficult to replicate in a controlled laboratory environment and can greatly affect performance and battery life. Online estimation captures this variety of conditions, providing a more accurate assessment of battery behavior in real-world situations. In this article, a hybrid approach based on a neural network and a statistical method for real-time estimation of SoC, SoH, and SoP parameters of interest is proposed. These parameters are estimated from the analysis of a one-day driving profile of an electric vehicle, assumed to be divided into the following four phases: (i) Partial discharge (SoC 100% - SoC 50%), (ii) Partial discharge (SoC 50% - SoC 80%), (iii) Deep Discharge (SoC 80% - SoC 30%) (iv) Full charge (SoC 30% - SoC 100%). The neural network predicts the values of ohmic resistance and incremental capacity, while the statistical method is used to estimate the parameters of interest. This reduces the complexity of the model and improves its prediction accuracy. The effectiveness of the proposed model is evaluated by analyzing its performance in terms of square mean error (RMSE) and percentage error (MAPE) and comparing it with the reference method found in the literature.

Keywords: electric vehicle, Li-Ion battery, BMS, state-of-charge, state-of-health, state-of-power, artificial neural networks

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Authors: Anna Solovyeva, Ivan Levakin, Nickolai Galaktionov, Olga Podgornaya

Abstract:

Animals that reproduce asexually were thought to have the same genotypes within generations for a long time. However, some refuting examples were found, and mobile genetic elements (MGEs) or transposons are considered to be the most probable source of genetic instability. Dispersed nature and the ability to change their genomic localization enables MGEs to be efficient mutators. Hence the study of MGEs genomic impact requires an appropriate object which comprehends both representative amounts of various MGEs and options to evaluate the genomic influence of MGEs. Animals that reproduce asexually seem to be a decent model to study MGEs impact in genomic variability. We found a small marine trematode Himasthla elongata (Himasthlidae) to be a good model for such investigation as it has a small genome size, diverse MGEs and parthenogenetic stages in the lifecycle. In the current work, clonal diversity of cercaria was traced with an AFLP (Amplified fragment length polymorphism) method, diverse zones from electrophoretic patterns were cloned, and the nature of the fragments explored. Polymorphic patterns of individual cercariae AFLP-based fingerprints are enriched with retrotransposons of different families. The bulk of those sequences are represented by open reading frames of non-Long Terminal Repeats containing elements(non-LTR) yet Long-Terminal Repeats containing elements (LTR), to a lesser extent in variable figments of AFLP array. The CR1 elements expose both in polymorphic and conservative patterns are remarkably more frequent than the other non-LTR retrotransposons. This data was confirmed with shotgun sequencing-based on Illumina HiSeq 2500 platform. Individual cercaria of the same clone (i.e., originated from a single miracidium and inhabiting one host) has a various distribution of MGE families detected in sequenced AFLP patterns. The most numerous are CR1 and RTE-Bov retrotransposons, typical for trematode genomes. Also, we identified LTR-retrotransposons of Pao and Gypsy families among DNA transposons of CMC-EnSpm, Tc1/Mariner, MuLE-MuDR and Merlin families. We detected many of them in H. elongata transcriptome. Such uneven MGEs distribution in AFLP sequences’ sets reflects the different patterns of transposons spreading in cercarial genomes as transposons affect the genome in many ways (ectopic recombination, gene structure interruption, epigenetic silencing). It is considered that they play a key role in the origins of trematode clonal polymorphism. The authors greatly appreciate the help received at the Kartesh White Sea Biological Station of the Russian Academy of Sciences Zoological Institute. This work is funded with RSF 19-74-20102 and RFBR 17-04-02161 grants and the research program of the Zoological Institute of the Russian Academy of Sciences (project number AAAA-A19-119020690109-2).

Keywords: AFLP, clonal polymorphism, Himasthla elongata, mobile genetic elements, NGS

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