Search results for: animal artificial insemination
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3046

Search results for: animal artificial insemination

166 Hiveopolis - Honey Harvester System

Authors: Erol Bayraktarov, Asya Ilgun, Thomas Schickl, Alexandre Campo, Nicolis Stamatios

Abstract:

Traditional means of harvesting honey are often stressful for honeybees. Each time honey is collected a portion of the colony can die. In consequence, the colonies’ resilience to environmental stressors will decrease and this ultimately contributes to the global problem of honeybee colony losses. As part of the project HIVEOPOLIS, we design and build a different kind of beehive, incorporating technology to reduce negative impacts of beekeeping procedures, including honey harvesting. A first step in maintaining more sustainable honey harvesting practices is to design honey storage frames that can automate the honey collection procedures. This way, beekeepers save time, money, and labor by not having to open the hive and remove frames, and the honeybees' nest stays undisturbed.This system shows promising features, e.g., high reliability which could be a key advantage compared to current honey harvesting technologies.Our original concept of fractional honey harvesting has been to encourage the removal of honey only from "safe" locations and at levels that would leave the bees enough high-nutritional-value honey. In this abstract, we describe the current state of our honey harvester, its technology and areas to improve. The honey harvester works by separating the honeycomb cells away from the comb foundation; the movement and the elastic nature of honey supports this functionality. The honey sticks to the foundation, because of the surface tension forces amplified by the geometry. In the future, by monitoring the weight and therefore the capped honey cells on our honey harvester frames, we will be able to remove honey as soon as the weight measuring system reports that the comb is ready for harvesting. Higher viscosity honey or crystalized honey cause challenges in temperate locations when a smooth flow of honey is required. We use resistive heaters to soften the propolis and wax to unglue the moving parts during extraction. These heaters can also melt the honey slightly to the needed flow state. Precise control of these heaters allows us to operate the device for several purposes. We use ‘Nitinol’ springs that are activated by heat as an actuation method. Unlike conventional stepper or servo motors, which we also evaluated throughout development, the springs and heaters take up less space and reduce the overall system complexity. Honeybee acceptance was unknown until we actually inserted a device inside a hive. We not only observed bees walking on the artificial comb but also building wax, filling gaps with propolis and storing honey. This also shows that bees don’t mind living in spaces and hives built from 3D printed materials. We do not have data yet to prove that the plastic materials do not affect the chemical composition of the honey. We succeeded in automatically extracting stored honey from the device, demonstrating a useful extraction flow and overall effective operation this way.

Keywords: honey harvesting, honeybee, hiveopolis, nitinol

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165 The Improved Therapeutic Effect of Trans-Cinnamaldehyde on Adipose-Derived Stem Cells without Chemical Induction

Authors: Karthyayani Rajamani, Yi-Chun Lin, Tung-Chou Wen, Jeanne Hsieh, Yi-Maun Subeq, Jen-Wei Liu, Po-Cheng Lin, Horng-Jyh Harn, Shinn-Zong Lin, Tzyy-Wen Chiou

Abstract:

Assuring cell quality is an essential parameter for the success of stem cell therapy, utilization of various components to improve this potential has been the primary goal of stem cell research. The aim of this study was not only to demonstrate the capacity of trans-cinnamaldehyde (TC) to reverse stress-induced senescence but also improve the therapeutic abilities of stem cells. Because of the availability and the promising application potential in regenerative medicine, adipose-derived stem cells (ADSCs) were chosen for the study. We found that H2O2 treatment resulted in the expression of senescence characteristics in the ADSCs, including decreased proliferation rate, increased senescence-associated- β-galactosidase (SA-β-gal) activity, decreased SIRT1 (silent mating type information regulation 2 homologs) expression and decreased telomerase activity. However, TC treatment was sufficient to rescue or reduce the effects of H2O2 induction, ultimately leading to an increased proliferation rate, a decrease in the percentage of SA-β-gal positive cells, upregulation of SIRT1 expression, and increased telomerase activity of the senescent ADSCs at the cellular level. Further recently it was observed that the ADSCs were treated with TC without induction of senescence, all the before said positives were observed. Moreover, a chemically induced liver fibrosis animal model was used to evaluate the functionality of these rescued cells in vivo. Liver dysfunction was established by injecting 200 mg/kg thioacetamide (TAA) intraperitoneally into Wistar rats every third day for 60 days. The experimental rats were separated into groups; normal group (rats without TAA induction), sham group (without ADSC transplantation), positive control group (transplanted with normal ADSCs); H2O2 group (transplanted with H2O2 -induced senescent ADSCs), H2O2+TC group (transplanted with ADSCs pretreated with H2O2 and then further treated with TC) and TC group (ADSC treated with TC without H2O2 treatment). In the transplantation group, 1 × 106 human ADSCs were introduced into each rat via direct liver injection. Based on the biochemical analysis and immunohistochemical staining results, it was determined that the therapeutic effects on liver fibrosis by the induced senescent ADSCs (H2O2 group) were not as significant as those exerted by the normal ADSCs (the positive control group). However, the H2O2+TC group showed significant reversal of liver damage when compared to the H2O2 group 1 week post-transplantation. Further ADSCs without H2O2 treatment but with just TC treatment performed much better than all the groups. These data confirmed that the TC treatment had the potential to improve the therapeutic effect of ADSCs. It is therefore suggested that TC has potential applications in maintaining stem cell quality and could possibly aid in the treatment of senescence-related disorders.

Keywords: senescence, SIRT1, adipose derived stem cells, liver fibrosis

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164 Navigating AI in Higher Education: Exploring Graduate Students’ Perspectives on Teacher-Provided AI Guidelines

Authors: Mamunur Rashid, Jialin Yan

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The current years have witnessed a rapid evolution and integration of artificial intelligence (AI) in various fields, prominently influencing the education industry. Acknowledging this transformative wave, AI tools like ChatGPT and Grammarly have undeniably introduced perspectives and skills, enriching the educational experiences of higher education students. The prevalence of AI utilization in higher education also drives an increasing number of researchers' attention in various dimensions. Departments, offices, and professors in universities also designed and released a set of policies and guidelines on using AI effectively. In regard to this, the study targets exploring and analyzing graduate students' perspectives regarding AI guidelines set by teachers. A mixed-methods study will be mainly conducted in this study, employing in-depth interviews and focus groups to investigate and collect students' perspectives. Relevant materials, such as syllabi and course instructions, will also be analyzed through the documentary analysis to facilitate understanding of the study. Surveys will also be used for data collection and students' background statistics. The integration of both interviews and surveys will provide a comprehensive array of student perspectives across various academic disciplines. The study is anchored in the theoretical framework of self-determination theory (SDT), which emphasizes and explains the students' perspective under the AI guidelines through three core needs: autonomy, competence, and relatedness. This framework is instrumental in understanding how AI guidelines influence students' intrinsic motivation and sense of empowerment in their learning environments. Through qualitative analysis, the study reveals a sense of confusion and uncertainty among students regarding the appropriate application and ethical considerations of AI tools, indicating potential challenges in meeting their needs for competence and autonomy. The quantitative data further elucidates these findings, highlighting a significant communication gap between students and educators in the formulation and implementation of AI guidelines. The critical findings of this study mainly come from two aspects: First, the majority of graduate students are uncertain and confused about relevant AI guidelines given by teachers. Second, this study also demonstrates that the design and effectiveness of course materials, such as the syllabi and instructions, also need to adapt in regard to AI policies. It indicates that certain of the existing guidelines provided by teachers lack consideration of students' perspectives, leading to a misalignment with students' needs for autonomy, competence, and relatedness. More emphasize and efforts need to be dedicated to both teacher and student training on AI policies and ethical considerations. To conclude, in this study, graduate students' perspectives on teacher-provided AI guidelines are explored and reflected upon, calling for additional training and strategies to improve how these guidelines can be better disseminated for their effective integration and adoption. Although AI guidelines provided by teachers may be helpful and provide new insights for students, educational institutions should take a more anchoring role to foster a motivating, empowering, and student-centered learning environment. The study also provides some relevant recommendations, including guidance for students on the ethical use of AI and AI policy training for teachers in higher education.

Keywords: higher education policy, graduate students’ perspectives, higher education teacher, AI guidelines, AI in education

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163 Development of a One Health and Comparative Medicine Curriculum for Medical Students

Authors: Aliya Moreira, Blake Duffy, Sam Kosinski, Kate Heckman, Erika Steensma

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Introduction: The One Health initiative promotes recognition of the interrelatedness between people, animals, plants, and their shared environment. The field of comparative medicine studies the similarities and differences between humans and animals for the purpose of advancing medical sciences. Currently, medical school education is narrowly focused on human anatomy and physiology, but as the COVID-19 pandemic has demonstrated, a holistic understanding of health requires comprehension of the interconnection between health and the lived environment. To prepare future physicians for unique challenges from emerging zoonoses to climate change, medical students can benefit from exposure to and experience with One Health and Comparative Medicine content. Methods: In January 2020, an elective course for medical students on One Health and Comparative Medicine was created to provide medical students with the background knowledge necessary to understand the applicability of animal and environmental health in medical research and practice. The 2-week course was continued in January 2021, with didactic and experiential activities taking place virtually due to the COVID-19 pandemic. In response to student feedback, lectures were added to expand instructional content on zoonotic and wildlife diseases for the second iteration of the course. Other didactic sessions included interprofessional lectures from 20 physicians, veterinarians, public health professionals, and basic science researchers. The first two cohorts of students were surveyed regarding One Health and Comparative Medicine concepts at the beginning and conclusion of the course. Results: 16 medical students have completed the comparative medicine course thus far, with 87.5% (n=14) completing pre-and post-course evaluations. 100% of student respondents indicated little to no exposure to comparative medicine or One Health concepts during medical school. Following the course, 100% of students felt familiar or very familiar with comparative medicine and One Health concepts. To assess course efficacy, questions were evaluated on a five-point Likert scale. 100% agreed or strongly agreed that learning Comparative Medicine and One Health topics augmented their medical education. 100% agreed or strongly agreed that a course covering this content should be regularly offered to medical students. Conclusions: Data from the student evaluation surveys demonstrate that the Comparative Medicine course was successful in increasing medical student knowledge of Comparative Medicine and One Health. Results also suggest that interprofessional training in One Health and Comparative Medicine is applicable and useful for medical trainees. Future iterations of this course could capitalize on the inherently interdisciplinary nature of these topics by enrolling students from veterinary and public health schools into a longitudinal course. Such recruitment may increase the course’s value by offering multidisciplinary student teams the opportunity to conduct research projects, thereby strengthening both the individual learning experience as well as sparking future interprofessional research ventures. Overall, these efforts to educate medical students in One Health topics should be reproducible at other institutions, preparing more future physicians for the diverse challenges they will encounter in practice.

Keywords: medical education, interprofessional instruction, one health, comparative medicine

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162 Insights on the Halal Status of Antineoplastic and Immunomodulating Agents and Nutritional and Dietary Supplements in Malaysia

Authors: Suraiya Abdul Rahman, Perasna M. Varma, Amrahi Buang, Zhari Ismail, Wan Rosalina W. Rosli, Ahmad Rashidi M. Tahir

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Background: Muslims has the obligation to ensure that everything they consume including medicines should be halal. With the growing demands for halal medicines in October 2012, Malaysia has launched the world's first Halal pharmaceutical standards called Malaysian Standard MS 2424:2012 Halal Pharmaceuticals-General Guidelines to serve as a basic requirement for halal pharmaceuticals in Malaysia. However, the biggest challenge faced by pharmaceutical companies to comply is finding the origin or source of the ingredients and determine their halal status. Aim: This study aims to determine the halal status of the antineoplastic and immunomodulating agents, and nutritional and dietary supplements by analysing the origin of their active pharmaceutical ingredients (API) and excipients to provide an insight on the common source and halal status of pharmaceutical ingredients and an indication on adjustment required in order to be halal compliance. Method: The ingredients of each product available in a government hospital in central of Malaysia and their sources were determined from the product package leaflets, information obtained from manufacturer, reliable websites and standard pharmaceutical references. The ingredients were categorised as halal, musbooh or haram based on the definition set in MS2424. Results: There were 162 medications included in the study where 123 (76%) were under the antineoplastic and immunomodulating agents group, while 39 (24%) were nutritional and dietary supplements. In terms of the medication halal status, the proportion of halal, musbooh and haram were 40.1% (n=65), 58.6% (n=95) and 1.2% (n=2) respectively. With regards to the API, there were 89 (52%) different active ingredient identified for antineoplastic and immunomodulating agents with the proportion of 89.9% (n=80) halal and 10.1% (n=9) were mushbooh. There were 83 (48%) active ingredient from the nutritional and dietary supplements group with proportion of halal and masbooh were 89.2% (n=74) and 10.8% (n=9) respectively. No haram APIs were identified in all therapeutic classes. There were a total of 176 excipients identified from the products ranges. It was found that majority of excipients are halal with the proportion of halal, masbooh and haram were at 82.4% (n=145), 17% (n=30) and 0.6% (n=1) respectively. With regards of the sources of the excipeints, most of masbooh excipients (76.7%, n = 23) were classified as masbooh because they have multiple possible origin which consist of animals, plant or others. The remaining 13.3% and 10% were classified as masbooh due to their ethanol and land animal origin respectively. The one haram excipient was gelatine of bovine-porcine origin. Masbooh ingredients found in this research were glycerol, tallow, lactose, polysorbate, dibasic sodium phosphate, stearic acid and magnesium stearate. Ethanol, gelatine, glycerol and magnesium stearate were the most common ingredients classified as mushbooh. Conclusion: This study shows that most API and excipients are halal. However the majority of the medicines in these products categories are mushbooh due to certain excipients only, which could be replaced with halal alternative excipients. This insight should encourage the pharmaceutical products manufacturers to go for halal certification to meet the increasing demand for Halal certified medications for the benefit of mankind.

Keywords: antineoplastic and immunomodulation agents, halal pharmaceutical, MS2424, nutritional and dietary supplements

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161 Analysis of Lesotho Wool Production and Quality Trends 2008-2018

Authors: Papali Maqalika

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Lesotho farmers produce significant quantities of Merino wool of a quality competitive on the global market and make a substantial impact on the economy of Lesotho. However, even with the economic contribution, the production and quality information and trends of this fibre has been recognised nor documented. This is a sombre shortcoming as Lesotho wool is unknown on international markets. The situation is worsened by the fact that Lesotho wool is auction together with South African wool, trading and benchmarking Lesotho wool are difficult not to mention attempts to advance its production and quality. Based on the information above, available data on Lesotho wool for 10 years were collected and analysed for trends to used in benchmarking where applicable. The fibre properties analysed include fibre diameter (fineness), vegetable matter and yield, application and price. These were selected because they are fundamental in determining fibre quality and price. Production of wool in Lesotho has increased slightly over the ten years covered by this study. It also became apparent that production and quality trends of Lesotho wool are greatly influenced by the farming practices, breed of sheep and climatic conditions. Greater adoption of the merino sheep breed, sheds/barns and sheep coats are suggested as ways to reduce mortality rate (due to extremely cold temperatures), to reduce the vegetable matter on the fibre thus improving the quality and increase yield per sheep and production as a whole. Some farming practices such as the lack of barns, supplementary feeding and veterinary care present constraints in wool production. The districts in the Highlands region were found to have the highest production of mostly wool, this being ascribed to better pastures, climatic, social and other conditions conducive to wool production. The production of Lesotho wool and its quality can be improved further, possibly because of the interventions the Ministry of Agriculture introduced through the Small Agricultural and Development Project (SADP) and other appropriate initiatives by the National Wool and Mohair Growers Association (NWMGA). The challenge however, remains the lack of direct involvement of the wool growers (farmers) in decisions making and policy development, this potentially influences and may lead to the reluctance to adopt the strategies. In some cases, the wool growers do not receive the benefits associated with the interventions immediately. Based on these discoveries; it is recommended that the relevant educators and researchers in wool and textile science, as well as the local wool farmers in Lesotho, be represented in policy and other decision making forums relating to these interventions. In this way, educational campaigns and training workshops will be demand driven with a better chance of adoption and success. This is because the direct beneficiaries will have been involved at inception and they will have a sense of ownership as well as intent to see them through successfully.

Keywords: lesotho wool, wool quality, wool production, lesotho economy, global market, apparel wool, database, textile science, exports, animal farming practices, intimate apparel, interventions

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160 Case-Based Reasoning for Modelling Random Variables in the Reliability Assessment of Existing Structures

Authors: Francesca Marsili

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The reliability assessment of existing structures with probabilistic methods is becoming an increasingly important and frequent engineering task. However probabilistic reliability methods are based on an exhaustive knowledge of the stochastic modeling of the variables involved in the assessment; at the moment standards for the modeling of variables are absent, representing an obstacle to the dissemination of probabilistic methods. The framework according to probability distribution functions (PDFs) are established is represented by the Bayesian statistics, which uses Bayes Theorem: a prior PDF for the considered parameter is established based on information derived from the design stage and qualitative judgments based on the engineer past experience; then, the prior model is updated with the results of investigation carried out on the considered structure, such as material testing, determination of action and structural properties. The application of Bayesian statistics arises two different kind of problems: 1. The results of the updating depend on the engineer previous experience; 2. The updating of the prior PDF can be performed only if the structure has been tested, and quantitative data that can be statistically manipulated have been collected; performing tests is always an expensive and time consuming operation; furthermore, if the considered structure is an ancient building, destructive tests could compromise its cultural value and therefore should be avoided. In order to solve those problems, an interesting research path is represented by investigating Artificial Intelligence (AI) techniques that can be useful for the automation of the modeling of variables and for the updating of material parameters without performing destructive tests. Among the others, one that raises particular attention in relation to the object of this study is constituted by Case-Based Reasoning (CBR). In this application, cases will be represented by existing buildings where material tests have already been carried out and an updated PDFs for the material mechanical parameters has been computed through a Bayesian analysis. Then each case will be composed by a qualitative description of the material under assessment and the posterior PDFs that describe its material properties. The problem that will be solved is the definition of PDFs for material parameters involved in the reliability assessment of the considered structure. A CBR system represent a good candi¬date in automating the modelling of variables because: 1. Engineers already draw an estimation of the material properties based on the experience collected during the assessment of similar structures, or based on similar cases collected in literature or in data-bases; 2. Material tests carried out on structure can be easily collected from laboratory database or from literature; 3. The system will provide the user of a reliable probabilistic description of the variables involved in the assessment that will also serve as a tool in support of the engineer’s qualitative judgments. Automated modeling of variables can help in spreading probabilistic reliability assessment of existing buildings in the common engineering practice, and target at the best intervention and further tests on the structure; CBR represents a technique which may help to achieve this.

Keywords: reliability assessment of existing buildings, Bayesian analysis, case-based reasoning, historical structures

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159 3D Design of Orthotic Braces and Casts in Medical Applications Using Microsoft Kinect Sensor

Authors: Sanjana S. Mallya, Roshan Arvind Sivakumar

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Orthotics is the branch of medicine that deals with the provision and use of artificial casts or braces to alter the biomechanical structure of the limb and provide support for the limb. Custom-made orthoses provide more comfort and can correct issues better than those available over-the-counter. However, they are expensive and require intricate modelling of the limb. Traditional methods of modelling involve creating a plaster of Paris mould of the limb. Lately, CAD/CAM and 3D printing processes have improved the accuracy and reduced the production time. Ordinarily, digital cameras are used to capture the features of the limb from different views to create a 3D model. We propose a system to model the limb using Microsoft Kinect2 sensor. The Kinect can capture RGB and depth frames simultaneously up to 30 fps with sufficient accuracy. The region of interest is captured from three views, each shifted by 90 degrees. The RGB and depth data are fused into a single RGB-D frame. The resolution of the RGB frame is 1920px x 1080px while the resolution of the Depth frame is 512px x 424px. As the resolution of the frames is not equal, RGB pixels are mapped onto the Depth pixels to make sure data is not lost even if the resolution is lower. The resulting RGB-D frames are collected and using the depth coordinates, a three dimensional point cloud is generated for each view of the Kinect sensor. A common reference system was developed to merge the individual point clouds from the Kinect sensors. The reference system consisted of 8 coloured cubes, connected by rods to form a skeleton-cube with the coloured cubes at the corners. For each Kinect, the region of interest is the square formed by the centres of the four cubes facing the Kinect. The point clouds are merged by considering one of the cubes as the origin of a reference system. Depending on the relative distance from each cube, the three dimensional coordinate points from each point cloud is aligned to the reference frame to give a complete point cloud. The RGB data is used to correct for any errors in depth data for the point cloud. A triangular mesh is generated from the point cloud by applying Delaunay triangulation which generates the rough surface of the limb. This technique forms an approximation of the surface of the limb. The mesh is smoothened to obtain a smooth outer layer to give an accurate model of the limb. The model of the limb is used as a base for designing the custom orthotic brace or cast. It is transferred to a CAD/CAM design file to design of the brace above the surface of the limb. The proposed system would be more cost effective than current systems that use MRI or CT scans for generating 3D models and would be quicker than using traditional plaster of Paris cast modelling and the overall setup time is also low. Preliminary results indicate that the accuracy of the Kinect2 is satisfactory to perform modelling.

Keywords: 3d scanning, mesh generation, Microsoft kinect, orthotics, registration

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158 An Agent-Based Approach to Examine Interactions of Firms for Investment Revival

Authors: Ichiro Takahashi

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One conundrum that macroeconomic theory faces is to explain how an economy can revive from depression, in which the aggregate demand has fallen substantially below its productive capacity. This paper examines an autonomous stabilizing mechanism using an agent-based Wicksell-Keynes macroeconomic model. This paper focuses on the effects of the number of firms and the length of the gestation period for investment that are often assumed to be one in a mainstream macroeconomic model. The simulations found the virtual economy was highly unstable, or more precisely, collapsing when these parameters are fixed at one. This finding may even suggest us to question the legitimacy of these common assumptions. A perpetual decline in capital stock will eventually encourage investment if the capital stock is short-lived because an inactive investment will result in insufficient productive capacity. However, for an economy characterized by a roundabout production method, a gradual decline in productive capacity may not be able to fall below the aggregate demand that is also shrinking. Naturally, one would then ask if our economy cannot rely on an external stimulus such as population growth and technological progress to revive investment, what factors would provide such a buoyancy for stimulating investments? The current paper attempts to answer this question by employing the artificial macroeconomic model mentioned above. The baseline model has the following three features: (1) the multi-period gestation for investment, (2) a large number of heterogeneous firms, (3) demand-constrained firms. The instability is a consequence of the following dynamic interactions. (a) A multiple-period gestation period means that once a firm starts a new investment, it continues to invest over some subsequent periods. During these gestation periods, the excess demand created by the investing firm will spill over to ignite new investment of other firms that are supplying investment goods: the presence of multi-period gestation for investment provides a field for investment interactions. Conversely, the excess demand for investment goods tends to fade away before it develops into a full-fledged boom if the gestation period of investment is short. (b) A strong demand in the goods market tends to raise the price level, thereby lowering real wages. This reduction of real wages creates two opposing effects on the aggregate demand through the following two channels: (1) a reduction in the real labor income, and (2) an increase in the labor demand due to the principle of equality between the marginal labor productivity and real wage (referred as the Walrasian labor demand). If there is only a single firm, a lower real wage will increase its Walrasian labor demand, thereby an actual labor demand tends to be determined by the derived labor demand. Thus, the second positive effect would not work effectively. In contrast, for an economy with a large number of firms, Walrasian firms will increase employment. This interaction among heterogeneous firms is a key for stability. A single firm cannot expect the benefit of such an increased aggregate demand from other firms.

Keywords: agent-based macroeconomic model, business cycle, demand constraint, gestation period, representative agent model, stability

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157 Row Detection and Graph-Based Localization in Tree Nurseries Using a 3D LiDAR

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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156 Development and Adaptation of a LGBM Machine Learning Model, with a Suitable Concept Drift Detection and Adaptation Technique, for Barcelona Household Electric Load Forecasting During Covid-19 Pandemic Periods (Pre-Pandemic and Strict Lockdown)

Authors: Eric Pla Erra, Mariana Jimenez Martinez

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While aggregated loads at a community level tend to be easier to predict, individual household load forecasting present more challenges with higher volatility and uncertainty. Furthermore, the drastic changes that our behavior patterns have suffered due to the COVID-19 pandemic have modified our daily electrical consumption curves and, therefore, further complicated the forecasting methods used to predict short-term electric load. Load forecasting is vital for the smooth and optimized planning and operation of our electric grids, but it also plays a crucial role for individual domestic consumers that rely on a HEMS (Home Energy Management Systems) to optimize their energy usage through self-generation, storage, or smart appliances management. An accurate forecasting leads to higher energy savings and overall energy efficiency of the household when paired with a proper HEMS. In order to study how COVID-19 has affected the accuracy of forecasting methods, an evaluation of the performance of a state-of-the-art LGBM (Light Gradient Boosting Model) will be conducted during the transition between pre-pandemic and lockdowns periods, considering day-ahead electric load forecasting. LGBM improves the capabilities of standard Decision Tree models in both speed and reduction of memory consumption, but it still offers a high accuracy. Even though LGBM has complex non-linear modelling capabilities, it has proven to be a competitive method under challenging forecasting scenarios such as short series, heterogeneous series, or data patterns with minimal prior knowledge. An adaptation of the LGBM model – called “resilient LGBM” – will be also tested, incorporating a concept drift detection technique for time series analysis, with the purpose to evaluate its capabilities to improve the model’s accuracy during extreme events such as COVID-19 lockdowns. The results for the LGBM and resilient LGBM will be compared using standard RMSE (Root Mean Squared Error) as the main performance metric. The models’ performance will be evaluated over a set of real households’ hourly electricity consumption data measured before and during the COVID-19 pandemic. All households are located in the city of Barcelona, Spain, and present different consumption profiles. This study is carried out under the ComMit-20 project, financed by AGAUR (Agència de Gestiód’AjutsUniversitaris), which aims to determine the short and long-term impacts of the COVID-19 pandemic on building energy consumption, incrementing the resilience of electrical systems through the use of tools such as HEMS and artificial intelligence.

Keywords: concept drift, forecasting, home energy management system (HEMS), light gradient boosting model (LGBM)

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155 Socio-Economic Transformation of Barpak Post-Earthquake Reconstruction

Authors: Sudikshya Bhandari, Jonathan K. London

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The earthquake of April 2015 was one of the biggest disasters in the history of Nepal. The epicenter was located near Barpak, north of the Gorkha district. Before the disaster, this settlement was a compact and homogeneous settlement manifesting its uniqueness through the social and cultural activities, and a distinct vernacular architecture. Narrow alleys with stone paved streets, buildings with slate roofs, and common spaces between the houses made this settlement socially, culturally, and environmentally cohesive. With the presence of micro hydro power plants, local economic activities enabled the local community to exist and thrive. Agriculture and animal rearing are the sources of livelihood for the majority of families, along with the booming homestays (where local people welcome guests to their home, as a business) and local shops. Most of these activities are difficult to find as the houses have been destroyed with the earthquake and the process of reconstruction has been transforming the outlook of the settlement. This study characterized the drastic transformation in Barpak post-earthquake, and analyzed the consequences of the reconstruction process. In addition, it contributes to comprehending a broader representation about unsustainability created by the lack of contextual post-disaster development. Since the research is based in a specific area, a case study approach was used. Sample houses were selected on the basis of ethnicity and house typology. Mixed methods such as key informant and semi structured interviews, focus groups, observations and photographs are used for the collection of data. The research focus is predominantly on the physical change of the house typology from vernacular to externally adopted designs. This transformation of the house entails socio-cultural changes such as social fragmentation with differences among the rich and the poor and decreases in the social connectivity within families and neighborhood. Families have found that new houses require more maintenance and resources that have increased their economic expenses. The study also found that the reconstructed houses are not thermally comfortable in the cold climate of Barpak, leading to the increased use of different sources of heating like electric heaters and more firewood. Lack of storage spaces for crops and livestock have discouraged them to pursue traditional means of livelihood and depend more on buying food from stores, ultimately making it less economical for most of the families. The transformation of space leading to the economic, social and cultural changes demonstrates the unsustainability of Barpak. Conclusions from the study suggest place based and inclusive planning and policy formations that include locals as partners, identifying the possible ways to minimize the impact and implement these recommendations into the future policy and planning scenarios.

Keywords: earthquake, Nepal, reconstruction, settlement, transformation

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154 Cytochrome B Diversity and Phylogeny of Egyptian Sheep Breeds

Authors: Othman E. Othman, Agnés Germot, Daniel Petit, Abderrahman Maftah

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Threats to the biodiversity are increasing due to the loss of genetic diversity within the species utilized in agriculture. Due to the progressive substitution of the less productive, locally adapted and native breeds by highly productive breeds, the number of threatened breeds is increased. In these conditions, it is more strategically important than ever to preserve as much the farm animal diversity as possible, to ensure a prompt and proper response to the needs of future generations. Mitochondrial (mtDNA) sequencing has been used to explain the origins of many modern domestic livestock species. Studies based on sequencing of sheep mitochondrial DNA showed that there are five maternal lineages in the world for domestic sheep breeds; A, B, C, D and E. Because of the eastern location of Egypt in the Mediterranean basin and the presence of fat-tailed sheep breeds- character quite common in Turkey and Syria- where genotypes that seem quite primitive, the phylogenetic studies of Egyptian sheep breeds become particularly attractive. We aimed in this work to clarify the genetic affinities, biodiversity and phylogeny of five Egyptian sheep breeds using cytochrome B sequencing. Blood samples were collected from 63 animals belonging to the five tested breeds; Barki, Rahmani, Ossimi, Saidi and Sohagi. The total DNA was extracted and the specific primer allowed the conventional PCR amplification of the cytochrome B region of mtDNA (approximately 1272 bp). PCR amplified products were purified and sequenced. The alignment of Sixty-three samples was done using BioEdit software. DnaSP 5.00 software was used to identify the sequence variation and polymorphic sites in the aligned sequences. The result showed that the presence of 34 polymorphic sites leading to the formation of 18 haplotypes. The haplotype diversity in five tested breeds ranged from 0.676 in Rahmani breed to 0.894 in Sohagi breed. The genetic distances (D) and the average number of pairwise differences (Dxy) between breeds were estimated. The lowest distance was observed between Rahmani and Saidi (D: 1.674 and Dxy: 0.00150) while the highest distance was observed between Ossimi and Sohagi (D: 5.233 and Dxy: 0.00475). Neighbour-joining (Phylogeny) tree was constructed using Mega 5.0 software. The sequences of the 63 analyzed samples were aligned with references sequences of different haplogroups. The phylogeny result showed the presence of three haplogroups (HapA, HapB and HapC) in the 63 examined samples. The other two haplogroups described in literature (HapD and HapE) were not found. The result showed that 50 out of 63 tested animals cluster with haplogroup B (79.37%) whereas 7 tested animals cluster with haplogroup A (11.11%) and 6 animals cluster with haplogroup C (9.52%). In conclusion, the phylogenetic reconstructions showed that the majority of Egyptian sheep breeds belonging to haplogroup B which is the dominant haplogroup in Eastern Mediterranean countries like Syria and Turkey. Some individuals are belonging to haplogroups A and C, suggesting that the crosses were done with other breeds for characteristic selection for growth and wool quality.

Keywords: cytochrome B, diversity, phylogheny, Egyptian sheep breeds

Procedia PDF Downloads 351
153 Application of IoTs Based Multi-Level Air Quality Sensing for Advancing Environmental Monitoring in Pingtung County

Authors: Men An Pan, Hong Ren Chen, Chih Heng Shih, Hsing Yuan Yen

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Pingtung County is located in the southernmost region of Taiwan. During the winter season, pollutants due to insufficient dispersion caused by the downwash of the northeast monsoon lead to the poor air quality of the County. Through the implementation of various control methods, including the application of permits of air pollution, fee collection of air pollution, control oil fume of catering sectors, smoke detection of diesel vehicles, regular inspection of locomotives, and subsidies for low-polluting vehicles. Moreover, to further mitigate the air pollution, additional alternative controlling strategies are also carried out, such as construction site control, prohibition of open-air agricultural waste burning, improvement of river dust, and strengthening of road cleaning operations. The combined efforts have significantly reduced air pollutants in the County. However, in order to effectively and promptly monitor the ambient air quality, the County has subsequently deployed micro-sensors, with a total of 400 IoTs (Internet of Things) micro-sensors for PM2.5 and VOC detection and 3 air quality monitoring stations of the Environmental Protection Agency (EPA), covering 33 townships of the County. The covered area has more than 1,300 listed factories and 5 major industrial parks; thus forming an Internet of Things (IoTs) based multi-level air quality monitoring system. The results demonstrate that the IoTs multi-level air quality sensors combined with other strategies such as “sand and gravel dredging area technology monitoring”, “banning open burning”, “intelligent management of construction sites”, “real-time notification of activation response”, “nighthawk early bird plan with micro-sensors”, “unmanned aircraft (UAV) combined with land and air to monitor abnormal emissions”, and “animal husbandry odour detection service” etc. The satisfaction improvement rate of air control, through a 2021 public survey, reached a high percentage of 81%, an increase of 46% as compared to 2018. For the air pollution complaints for the whole year of 2021, the total number was 4213 in contrast to 7088 in 2020, a reduction rate reached almost 41%. Because of the spatial-temporal features of the air quality monitoring IoTs system by the application of microsensors, the system does assist and strengthen the effectiveness of the existing air quality monitoring network of the EPA and can provide real-time control of the air quality. Therefore, the hot spots and potential pollution locations can be timely determined for law enforcement. Hence, remarkable results were obtained for the two years. That is, both reduction of public complaints and better air quality are successfully achieved through the implementation of the present IoTs system for real-time air quality monitoring throughout Pingtung County.

Keywords: IoT, PM, air quality sensor, air pollution, environmental monitoring

Procedia PDF Downloads 50
152 Near-Miss Deep Learning Approach for Neuro-Fuzzy Risk Assessment in Pipelines

Authors: Alexander Guzman Urbina, Atsushi Aoyama

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The sustainability of traditional technologies employed in energy and chemical infrastructure brings a big challenge for our society. Making decisions related with safety of industrial infrastructure, the values of accidental risk are becoming relevant points for discussion. However, the challenge is the reliability of the models employed to get the risk data. Such models usually involve large number of variables and with large amounts of uncertainty. The most efficient techniques to overcome those problems are built using Artificial Intelligence (AI), and more specifically using hybrid systems such as Neuro-Fuzzy algorithms. Therefore, this paper aims to introduce a hybrid algorithm for risk assessment trained using near-miss accident data. As mentioned above the sustainability of traditional technologies related with energy and chemical infrastructure constitutes one of the major challenges that today’s societies and firms are facing. Besides that, the adaptation of those technologies to the effects of the climate change in sensible environments represents a critical concern for safety and risk management. Regarding this issue argue that social consequences of catastrophic risks are increasing rapidly, due mainly to the concentration of people and energy infrastructure in hazard-prone areas, aggravated by the lack of knowledge about the risks. Additional to the social consequences described above, and considering the industrial sector as critical infrastructure due to its large impact to the economy in case of a failure the relevance of industrial safety has become a critical issue for the current society. Then, regarding the safety concern, pipeline operators and regulators have been performing risk assessments in attempts to evaluate accurately probabilities of failure of the infrastructure, and consequences associated with those failures. However, estimating accidental risks in critical infrastructure involves a substantial effort and costs due to number of variables involved, complexity and lack of information. Therefore, this paper aims to introduce a well trained algorithm for risk assessment using deep learning, which could be capable to deal efficiently with the complexity and uncertainty. The advantage point of the deep learning using near-miss accidents data is that it could be employed in risk assessment as an efficient engineering tool to treat the uncertainty of the risk values in complex environments. The basic idea of using a Near-Miss Deep Learning Approach for Neuro-Fuzzy Risk Assessment in Pipelines is focused in the objective of improve the validity of the risk values learning from near-miss accidents and imitating the human expertise scoring risks and setting tolerance levels. In summary, the method of Deep Learning for Neuro-Fuzzy Risk Assessment involves a regression analysis called group method of data handling (GMDH), which consists in the determination of the optimal configuration of the risk assessment model and its parameters employing polynomial theory.

Keywords: deep learning, risk assessment, neuro fuzzy, pipelines

Procedia PDF Downloads 266
151 How Whatsappization of the Chatbot Affects User Satisfaction, Trust, and Acceptance in a Drive-Sharing Task

Authors: Nirit Gavish, Rotem Halutz, Liad Neta

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Nowadays, chatbots are gaining more and more attention due to the advent of large language models. One of the important considerations in chatbot design is how to create an interface to achieve high user satisfaction, trust, and acceptance. Since WhatsApp conversations sometimes substitute for face-to-face communication, we studied whether WhatsAppization of the chatbot -making the conversation resemble a WhatsApp conversation more- will improve user satisfaction, trust, and acceptance, or whether the opposite will occur due to the Uncanny Valley (UV) effect. The task was a drive-sharing task, in which participants communicated with a textual chatbot via WhatsApp and could decide whether to participate in a ride to college with a driver suggested by the chatbot. WhatsAppization of the chatbot was done in two ways: By a dialog-style conversation (Dialog versus No Dialog), and by adding WhatsApp indicators – “Last Seen”, “Connected”, “Read Receipts”, and “Typing…” (Indicators versus No Indicators). Our 120 participants were randomly assigned to one of the four 2 by 2 design groups, with 30 participants in each. They interacted with the WhatsApp chatbot and then filled out a questionnaire. The results demonstrated that, as expected from the manipulation, the interaction with the chatbot was longer for the dialog condition compared to the no dialog. This extra interaction, however, did not lead to higher acceptance -quite the opposite, since participants in the dialog condition were less willing to implement the decision made at the end of the conversation with the chatbot and continue the interaction with the driver they chose. The results are even more striking when considering the Indicators condition. Both for the satisfaction measures and the trust measures, participants’ ratings were lower in the Indicators condition compared to the No Indicators. Participants in the Indicators condition felt that the ride search process was harder to operate, and slower (even though the actual interaction time was similar). They were less convinced that the chatbot suggested real trips and they trusted the person offering the ride and referred to them by the chatbot less. These effects were more evident for participants who preferred to share their rides using WhatsApp compared to participants who preferred chatbots for that purpose. Considering our findings, we can say that the WhatsAppization of the chatbot was detrimental. This is true for the both chatbot WhatsAppization methods – by making the conversation more a dialog and adding WhatsApp indicators. For the chosen drive-sharing task, the results were, in addition to lower satisfaction, less trust in the chatbot’s suggestion and even in the driver suggested by the chatbot, and lower willingness to actually undertake the suggested ride. In addition, it seems that the most problematic WhatsAppization method was using WhatsApp’s indicators during the interaction with the chatbot. The current study suggests that a conversation with an artificial agent should also not imitate a WhatsApp conversation very closely. With the proliferation of WhatsApp use, the emotional and social aspect of face-to face commination are moving to WhatsApp communication. Based on the current study’s findings, it is possible that the UV effect also occurs in WhatsAppization, and not only in humanization, of the chatbot, with a similar feeling of eeriness, and is more pronounced for people who prefer to use WhatsApp over chatbots. The current research can serve as a starting point to study the very interesting and important topic of chatbots WhatsAppization. More methods of WhatsAppization and other tasks could be the focus of further studies.

Keywords: chatbot, WhatsApp, humanization, Uncanny Valley, drive sharing

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150 Variability and Stability of Bread and Durum Wheat for Phytic Acid Content

Authors: Gordana Branković, Vesna Dragičević, Dejan Dodig, Desimir Knežević, Srbislav Denčić, Gordana Šurlan-Momirović

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Phytic acid is a major pool in the flux of phosphorus through agroecosystems and represents a sum equivalent to > 50% of all phosphorus fertilizer used annually. Nutrition rich in phytic acid can substantially decrease micronutrients apsorption as calcium, zink, iron, manganese, copper due to phytate salts excretion by human and non-ruminant animals as poultry, swine and fish, having in common very scarce phytase activity, and consequently the ability to digest and utilize phytic acid, thus phytic acid derived phosphorus in animal waste contributes to water pollution. The tested accessions consisted of 15 genotypes of bread wheat (Triticum aestivum L. ssp. vulgare) and of 15 genotypes of durum wheat (Triticum durum Desf.). The trials were sown at the three test sites in Serbia: Rimski Šančevi (RS) (45º19´51´´N; 19º50´59´´E), Zemun Polje (ZP) (44º52´N; 20º19´E) and Padinska Skela (PS) (44º57´N 20º26´E) during two vegetation seasons 2010-2011 and 2011-2012. The experimental design was randomized complete block design with four replications. The elementary plot consisted of 3 internal rows of 0.6 m2 area (3 × 0.2 m × 1 m). Grains were grinded with Laboratory Mill 120 Perten (“Perten”, Sweden) (particles size < 500 μm) and flour was used for the analysis. Phytic acid grain content was determined spectrophotometrically with the Shimadzu UV-1601 spectrophotometer (Shimadzu Corporation, Japan). Objectives of this study were to determine: i) variability and stability of the phytic acid content among selected genotypes of bread and durum wheat, ii) predominant source of variation regarding genotype (G), environment (E) and genotype × environment interaction (GEI) from the multi-environment trial, iii) influence of climatic variables on the GEI for the phytic acid content. Based on the analysis of variance it had been determined that the variation of phytic acid content was predominantly influenced by environment in durum wheat, while the GEI prevailed for the variation of the phytic acid content in bread wheat. Phytic acid content expressed on the dry mass basis was in the range 14.21-17.86 mg g-1 with the average of 16.05 mg g-1 for bread wheat and 14.63-16.78 mg g-1 with the average of 15.91 mg g-1 for durum wheat. Average-environment coordination view of the genotype by environment (GGE) biplot was used for the selection of the most desirable genotypes for breeding for low phytic acid content in the sense of good stability and lower level of phytic acid content. The most desirable genotypes of bread and durum wheat for breeding for phytic acid were Apache and 37EDUYT /07 No. 7849. Models of climatic factors in the highest percentage (> 91%) were useful in interpreting GEI for phytic acid content, and included relative humidity in June, sunshine hours in April, mean temperature in April and winter moisture reserves for genotypes of bread wheat, as well as precipitation in June and April, maximum temperature in April and mean temperature in June for genotypes of durum wheat.

Keywords: genotype × environment interaction, phytic acid, stability, variability

Procedia PDF Downloads 365
149 Hardware Implementation for the Contact Force Reconstruction in Tactile Sensor Arrays

Authors: María-Luisa Pinto-Salamanca, Wilson-Javier Pérez-Holguín

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Reconstruction of contact forces is a fundamental technique for analyzing the properties of a touched object and is essential for regulating the grip force in slip control loops. This is based on the processing of the distribution, intensity, and direction of the forces during the capture of the sensors. Currently, efficient hardware alternatives have been used more frequently in different fields of application, allowing the implementation of computationally complex algorithms, as is the case with tactile signal processing. The use of hardware for smart tactile sensing systems is a research area that promises to improve the processing time and portability requirements of applications such as artificial skin and robotics, among others. The literature review shows that hardware implementations are present today in almost all stages of smart tactile detection systems except in the force reconstruction process, a stage in which they have been less applied. This work presents a hardware implementation of a model-driven reported in the literature for the contact force reconstruction of flat and rigid tactile sensor arrays from normal stress data. From the analysis of a software implementation of such a model, this implementation proposes the parallelization of tasks that facilitate the execution of matrix operations and a two-dimensional optimization function to obtain a vector force by each taxel in the array. This work seeks to take advantage of the parallel hardware characteristics of Field Programmable Gate Arrays, FPGAs, and the possibility of applying appropriate techniques for algorithms parallelization using as a guide the rules of generalization, efficiency, and scalability in the tactile decoding process and considering the low latency, low power consumption, and real-time execution as the main parameters of design. The results show a maximum estimation error of 32% in the tangential forces and 22% in the normal forces with respect to the simulation by the Finite Element Modeling (FEM) technique of Hertzian and non-Hertzian contact events, over sensor arrays of 10×10 taxels of different sizes. The hardware implementation was carried out on an MPSoC XCZU9EG-2FFVB1156 platform of Xilinx® that allows the reconstruction of force vectors following a scalable approach, from the information captured by means of tactile sensor arrays composed of up to 48 × 48 taxels that use various transduction technologies. The proposed implementation demonstrates a reduction in estimation time of x / 180 compared to software implementations. Despite the relatively high values of the estimation errors, the information provided by this implementation on the tangential and normal tractions and the triaxial reconstruction of forces allows to adequately reconstruct the tactile properties of the touched object, which are similar to those obtained in the software implementation and in the two FEM simulations taken as reference. Although errors could be reduced, the proposed implementation is useful for decoding contact forces for portable tactile sensing systems, thus helping to expand electronic skin applications in robotic and biomedical contexts.

Keywords: contact forces reconstruction, forces estimation, tactile sensor array, hardware implementation

Procedia PDF Downloads 164
148 Seismic Perimeter Surveillance System (Virtual Fence) for Threat Detection and Characterization Using Multiple ML Based Trained Models in Weighted Ensemble Voting

Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey

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Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.

Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method

Procedia PDF Downloads 46
147 From Shelf to Shell - The Corporate Form in the Era of Over-Regulation

Authors: Chrysthia Papacleovoulou

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The era of de-regulation, off-shore and tax haven jurisdictions, and shelf companies has come to an end. The usage of complex corporate structures involving trust instruments, special purpose vehicles, holding-subsidiaries in offshore haven jurisdictions, and taking advantage of tax treaties is soaring. States which raced to introduce corporate friendly legislation, tax incentives, and creative international trust law in order to attract greater FDI are now faced with regulatory challenges and are forced to revisit the corporate form and its tax treatment. The fiduciary services industry, which dominated over the last 3 decades, is now striving to keep up with the new regulatory framework as a result of a number of European and international legislative measures. This article considers the challenges to the company and the corporate form as a result of the legislative measures on tax planning and tax avoidance, CRS reporting, FATCA, CFC rules, OECD’s BEPS, the EU Commission's new transparency rules for intermediaries that extends to tax advisors, accountants, banks & lawyers who design and promote tax planning schemes for their clients, new EU rules to block artificial tax arrangements and new transparency requirements for financial accounts, tax rulings and multinationals activities (DAC 6), G20's decision for a global 15% minimum corporate tax and banking regulation. As a result, states are found in a race of over-regulation and compliance. These legislative measures constitute a global up-side down tax-harmonisation. Through the adoption of the OECD’s BEPS, states agreed to an international collaboration to end tax avoidance and reform international taxation rules. Whilst the idea was to ensure that multinationals would pay their fair share of tax everywhere they operate, an indirect result of the aforementioned regulatory measures was to attack private clients-individuals who -over the past 3 decades- used the international tax system and jurisdictions such as Marshal Islands, Cayman Islands, British Virgin Islands, Bermuda, Seychelles, St. Vincent, Jersey, Guernsey, Liechtenstein, Monaco, Cyprus, and Malta, to name but a few, to engage in legitimate tax planning and tax avoidance. Companies can no longer maintain bank accounts without satisfying the real substance test. States override the incorporation doctrine theory and apply a real seat or real substance test in taxing companies and their activities, targeting even the beneficial owners personally with tax liability. Tax authorities in civil law jurisdictions lift the corporate veil through the public registries of UBO Registries and Trust Registries. As a result, the corporate form and the doctrine of limited liability are challenged in their core. Lastly, this article identifies the development of new instruments, such as funds and private placement insurance policies, and the trend of digital nomad workers. The baffling question is whether industry and states can meet somewhere in the middle and exit this over-regulation frenzy.

Keywords: company, regulation, TAX, corporate structure, trust vehicles, real seat

Procedia PDF Downloads 111
146 Knowledge Based Software Model for the Management and Treatment of Malaria Patients: A Case of Kalisizo General Hospital

Authors: Mbonigaba Swale

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Malaria is an infection or disease caused by parasites (Plasmodium Falciparum — causes severe Malaria, plasmodium Vivax, Plasmodium Ovale, and Plasmodium Malariae), transmitted by bites of infected anopheles (female) mosquitoes to humans. These vectors comprise of two types in Africa, particularly in Uganda, i.e. anopheles fenestus and Anopheles gambaie (‘example Anopheles arabiensis,,); feeds on man inside the house mainly at dusk, mid-night and dawn and rests indoors and makes them effective transmitters (vectors) of the disease. People in both urban and rural areas have consistently become prone to repetitive attacks of malaria, causing a lot of deaths and significantly increasing the poverty levels of the rural poor. Malaria is a national problem; it causes a lot of maternal pre-natal and antenatal disorders, anemia in pregnant mothers, low birth weights for the newly born, convulsions and epilepsy among the infants. Cumulatively, it kills about one million children every year in sub-Saharan Africa. It has been estimated to account for 25-35% of all outpatient visits, 20-45% of acute hospital admissions and 15-35% of hospital deaths. Uganda is the leading victim country, for which Rakai and Masaka districts are the most affected. So, it is not clear whether these abhorrent situations and episodes of recurrences and failure to cure from the disease are a result of poor diagnosis, prescription and dosing, treatment habits and compliance of the patients to the drugs or the ethical domain of the stake holders in relation to the main stream methodology of malaria management. The research is aimed at offering an alternative approach to manage and deal absolutely with problem by using a knowledge based software model of Artificial Intelligence (Al) that is capable of performing common-sense and cognitive reasoning so as to take decisions like the human brain would do to provide instantaneous expert solutions so as to avoid speculative simulation of the problem during differential diagnosis in the most accurate and literal inferential aspect. This system will assist physicians in many kinds of medical diagnosis, prescribing treatments and doses, and in monitoring patient responses, basing on the body weight and age group of the patient, it will be able to provide instantaneous and timely information options, alternative ways and approaches to influence decision making during case analysis. The computerized system approach, a new model in Uganda termed as “Software Aided Treatment” (SAT) will try to change the moral and ethical approach and influence conduct so as to improve the skills, experience and values (social and ethical) in the administration and management of the disease and drugs (combination therapy and generics) by both the patient and the health worker.

Keywords: knowledge based software, management, treatment, diagnosis

Procedia PDF Downloads 31
145 Interplay of Material and Cycle Design in a Vacuum-Temperature Swing Adsorption Process for Biogas Upgrading

Authors: Federico Capra, Emanuele Martelli, Matteo Gazzani, Marco Mazzotti, Maurizio Notaro

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Natural gas is a major energy source in the current global economy, contributing to roughly 21% of the total primary energy consumption. Production of natural gas starting from renewable energy sources is key to limit the related CO2 emissions, especially for those sectors that heavily rely on natural gas use. In this context, biomethane produced via biogas upgrading represents a good candidate for partial substitution of fossil natural gas. The upgrading process of biogas to biomethane consists in (i) the removal of pollutants and impurities (e.g. H2S, siloxanes, ammonia, water), and (ii) the separation of carbon dioxide from methane. Focusing on the CO2 removal process, several technologies can be considered: chemical or physical absorption with solvents (e.g. water, amines), membranes, adsorption-based systems (PSA). However, none emerged as the leading technology, because of (i) the heterogeneity in plant size, ii) the heterogeneity in biogas composition, which is strongly related to the feedstock type (animal manure, sewage treatment, landfill products), (iii) the case-sensitive optimal tradeoff between purity and recovery of biomethane, and iv) the destination of the produced biomethane (grid injection, CHP applications, transportation sector). With this contribution, we explore the use of a technology for biogas upgrading and we compare the resulting performance with benchmark technologies. The proposed technology makes use of a chemical sorbent, which is engineered by RSE and consists of Di-Ethanol-Amine deposited on a solid support made of γ-Alumina, to chemically adsorb the CO2 contained in the gas. The material is packed into fixed beds that cyclically undergo adsorption and regeneration steps. CO2 is adsorbed at low temperature and ambient pressure (or slightly above) while the regeneration is carried out by pulling vacuum and increasing the temperature of the bed (vacuum-temperature swing adsorption - VTSA). Dynamic adsorption tests were performed by RSE and were used to tune the mathematical model of the process, including material and transport parameters (i.e. Langmuir isotherms data and heat and mass transport). Based on this set of data, an optimal VTSA cycle was designed. The results enabled a better understanding of the interplay between material and cycle tuning. As exemplary application, the upgrading of biogas for grid injection, produced by an anaerobic digester (60-70% CO2, 30-40% CH4), for an equivalent size of 1 MWel was selected. A plant configuration is proposed to maximize heat recovery and minimize the energy consumption of the process. The resulting performances are very promising compared to benchmark solutions, which make the VTSA configuration a valuable alternative for biomethane production starting from biogas.

Keywords: biogas upgrading, biogas upgrading energetic cost, CO2 adsorption, VTSA process modelling

Procedia PDF Downloads 246
144 LaeA/1-Velvet Interplay in Aspergillus and Trichoderma: Regulation of Secondary Metabolites and Cellulases

Authors: Razieh Karimi Aghcheh, Christian Kubicek, Joseph Strauss, Gerhard Braus

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Filamentous fungi are of considerable economic and social significance for human health, nutrition and in white biotechnology. These organisms are dominant producers of a range of primary metabolites such as citric acid, microbial lipids (biodiesel) and higher unsaturated fatty acids (HUFAs). In particular, they produce also important but structurally complex secondary metabolites with enormous therapeutic applications in pharmaceutical industry, for example: cephalosporin, penicillin, taxol, zeranol and ergot alkaloids. Several fungal secondary metabolites, which are significantly relevant to human health do not only include antibiotics, but also e.g. lovastatin, a well-known antihypercholesterolemic agent produced by Aspergillus. terreus, or aflatoxin, a carcinogen produced by A. flavus. In addition to their roles for human health and agriculture, some fungi are industrially and commercially important: Species of the ascomycete genus Hypocrea spp. (teleomorph of Trichoderma) have been demonstrated as efficient producer of highly active cellulolytic enzymes. This trait makes them effective in disrupting and depolymerization of lignocellulosic materials and thus applicable tools in number of biotechnological areas as diverse as clothes-washing detergent, animal feed, and pulp and fuel productions. Fungal LaeA/LAE1 (Loss of aflR Expression A) homologs their gene products act at the interphase between secondary metabolisms, cellulase production and development. Lack of the corresponding genes results in significant physiological changes including loss of secondary metabolite and lignocellulose degrading enzymes production. At the molecular level, the encoded proteins are presumably methyltransferases or demethylases which act directly or indirectly at heterochromatin and interact with velvet domain proteins. Velvet proteins bind to DNA and affect expression of secondary metabolites (SMs) genes and cellulases. The dynamic interplay between LaeA/LAE1, velvet proteins and additional interaction partners is the key for an understanding of the coordination of metabolic and morphological functions of fungi and is required for a biotechnological control of the formation of desired bioactive products. Aspergilli and Trichoderma represent different biotechnologically significant species with significant differences in the LaeA/LAE1-Velvet protein machinery and their target proteins. We, therefore, performed a comparative study of the interaction partners of this machinery and the dynamics of the various protein-protein interactions using our robust proteomic and mass spectrometry techniques. This enhances our knowledge about the fungal coordination of secondary metabolism, cellulase production and development and thereby will certainly improve recombinant fungal strain construction for the production of industrial secondary metabolite or lignocellulose hydrolytic enzymes.

Keywords: cellulases, LaeA/1, proteomics, secondary metabolites

Procedia PDF Downloads 245
143 Viscoelastic Behavior of Human Bone Tissue under Nanoindentation Tests

Authors: Anna Makuch, Grzegorz Kokot, Konstanty Skalski, Jakub Banczorowski

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Cancellous bone is a porous composite of a hierarchical structure and anisotropic properties. The biological tissue is considered to be a viscoelastic material, but many studies based on a nanoindentation method have focused on their elasticity and microhardness. However, the response of many organic materials depends not only on the load magnitude, but also on its duration and time course. Depth Sensing Indentation (DSI) technique has been used for examination of creep in polymers, metals and composites. In the indentation tests on biological samples, the mechanical properties are most frequently determined for animal tissues (of an ox, a monkey, a pig, a rat, a mouse, a bovine). However, there are rare reports of studies of the bone viscoelastic properties on microstructural level. Various rheological models were used to describe the viscoelastic behaviours of bone, identified in the indentation process (e. g Burgers model, linear model, two-dashpot Kelvin model, Maxwell-Voigt model). The goal of the study was to determine the influence of creep effect on the mechanical properties of human cancellous bone in indentation tests. The aim of this research was also the assessment of the material properties of bone structures, having in mind the energy aspects of the curve (penetrator loading-depth) obtained in the loading/unloading cycle. There was considered how the different holding times affected the results within trabecular bone.As a result, indentation creep (CIT), hardness (HM, HIT, HV) and elasticity are obtained. Human trabecular bone samples (n=21; mean age 63±15yrs) from the femoral heads replaced during hip alloplasty were removed and drained from alcohol of 1h before the experiment. The indentation process was conducted using CSM Microhardness Tester equipped with Vickers indenter. Each sample was indented 35 times (7 times for 5 different hold times: t1=0.1s, t2=1s, t3=10s, t4=100s and t5=1000s). The indenter was advanced at a rate of 10mN/s to 500mN. There was used Oliver-Pharr method in calculation process. The increase of hold time is associated with the decrease of hardness parameters (HIT(t1)=418±34 MPa, HIT(t2)=390±50 MPa, HIT(t3)= 313±54 MPa, HIT(t4)=305±54 MPa, HIT(t5)=276±90 MPa) and elasticity (EIT(t1)=7.7±1.2 GPa, EIT(t2)=8.0±1.5 GPa, EIT(t3)=7.0±0.9 GPa, EIT(t4)=7.2±0.9 GPa, EIT(t5)=6.2±1.8 GPa) as well as with the increase of the elastic (Welastic(t1)=4.11∙10-7±4.2∙10-8Nm, Welastic(t2)= 4.12∙10-7±6.4∙10-8 Nm, Welastic(t3)=4.71∙10-7±6.0∙10-9 Nm, Welastic(t4)= 4.33∙10-7±5.5∙10-9Nm, Welastic(t5)=5.11∙10-7±7.4∙10-8Nm) and inelastic (Winelastic(t1)=1.05∙10-6±1.2∙10-7 Nm, Winelastic(t2) =1.07∙10-6±7.6∙10-8 Nm, Winelastic(t3)=1.26∙10-6±1.9∙10-7Nm, Winelastic(t4)=1.56∙10-6± 1.9∙10-7 Nm, Winelastic(t5)=1.67∙10-6±2.6∙10-7)) reaction of materials. The indentation creep increased logarithmically (R2=0.901) with increasing hold time: CIT(t1) = 0.08±0.01%, CIT(t2) = 0.7±0.1%, CIT(t3) = 3.7±0.3%, CIT(t4) = 12.2±1.5%, CIT(t5) = 13.5±3.8%. The pronounced impact of creep effect on the mechanical properties of human cancellous bone was observed in experimental studies. While the description elastic-inelastic, and thus the Oliver-Pharr method for data analysis, may apply in few limited cases, most biological tissues do not exhibit elastic-inelastic indentation responses. Viscoelastic properties of tissues may play a significant role in remodelling. The aspect is still under an analysis and numerical simulations. Acknowledgements: The presented results are part of the research project founded by National Science Centre (NCN), Poland, no.2014/15/B/ST7/03244.

Keywords: bone, creep, indentation, mechanical properties

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142 Technology Assessment of the Collection of Cast Seaweed and Use as Feedstock for Biogas Production- The Case of SolrøD, Denmark

Authors: Rikke Lybæk, Tyge Kjær

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The Baltic Sea is suffering from nitrogen and phosphorus pollution, which causes eutrophication of the maritime environment and hence threatens the biodiversity of the Baltic Sea area. The intensified quantity of nutrients in the water has created challenges with the growth of seaweed being discarded on beaches around the sea. The cast seaweed has led to odor problems hampering the use of beach areas around the Bay of Køge in Denmark. This is the case in, e.g., Solrød Municipality, where recreational activities have been disrupted when cast seaweed pile up on the beach. Initiatives have, however, been introduced within the municipality to remove the cast seaweed from the beach and utilize it for renewable energy production at the nearby Solrød Biogas Plant, thus being co-digested with animal manure for power and heat production. This paper investigates which type of technology application’s have been applied in the effort to optimize the collection of cast seaweed, and will further reveal, how the seaweed has been pre-treated at the biogas plant to be utilized for energy production the most efficient, hereunder the challenges connected with the content of sand. Heavy metal contents in the seaweed and how it is managed will also be addressed, which is vital as the digestate is utilized as soil fertilizer on nearby farms. Finally, the paper will outline the energy production scheme connected to the use of seaweed as feedstock for biogas production, as well as the amount of nitrogen-rich fertilizer produced. The theoretical approach adopted in the paper relies on the thinking of Circular Bio-Economy, where biological materials are cascaded and re-circulated etc., to increase and extend their value and usability. The data for this research is collected as part of the EU Interreg project “Cluster On Anaerobic digestion, environmental Services, and nuTrients removAL” (COASTAL Biogas), 2014-2020. Data gathering consists of, e.g., interviews with relevant stakeholders connected to seaweed collection and operation of the biogas plant in Solrød Municipality. It further entails studies of progress and evaluation reports from the municipality, analysis of seaweed digestion results from scholars connected to the research, as well as studies of scientific literature to supplement the above. Besides this, observations and photo documentation have been applied in the field. This paper concludes, among others, that the seaweed harvester technology currently adopted is functional in the maritime environment close to the beachfront but inadequate in collecting seaweed directly on the beach. New technology hence needs to be developed to increase the efficiency of seaweed collection. It is further concluded that the amount of sand transported to Solrød Biogas Plant with the seaweed continues to pose challenges. The seaweed is pre-treated for sand in a receiving tank with a strong stirrer, washing off the sand, which ends at the bottom of the tank where collected. The seaweed is then chopped by a macerator and mixed with the other feedstock. The wear down of the receiving tank stirrer and the chopper are, however, significant, and new methods should be adopted.

Keywords: biogas, circular bio-economy, Denmark, maritime technology, cast seaweed, solrød municipality

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141 Estimation of State of Charge, State of Health and Power Status for the Li-Ion Battery On-Board Vehicle

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

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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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140 Influence of Cryo-Grinding on Particle Size Distribution of Proso Millet Bran Fraction

Authors: Maja Benkovic, Dubravka Novotni, Bojana Voucko, Duska Curic, Damir Jezek, Nikolina Cukelj

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Cryo-grinding is an ultra-fine grinding method used in the pharmaceutical industry, production of herbs and spices and in the production and handling of cereals, due to its ability to produce powders with small particle sizes which maintain their favorable bioactive profile. The aim of this study was to determine the particle size distributions of the proso millet (Panicum miliaceum) bran fraction grinded at cryogenic temperature (using liquid nitrogen (LN₂) cooling, T = - 196 °C), in comparison to non-cooled grinding. Proso millet bran is primarily used as an animal feed, but has a potential in food applications, either as a substrate for extraction of bioactive compounds or raw material in the bakery industry. For both applications finer particle sizes of the bran could be beneficial. Thus, millet bran was ground for 2, 4, 8 and 12 minutes using the ball mill (CryoMill, Retsch GmbH, Haan, Germany) at three grinding modes: (I) without cooling, (II) at cryo-temperature, and (III) at cryo-temperature with included 1 minute of intermediate cryo-cooling step after every 2 minutes of grinding, which is usually applied when samples require longer grinding times. The sample was placed in a 50 mL stainless steel jar containing one grinding ball (Ø 25 mm). The oscillation frequency in all three modes was 30 Hz. Particle size distributions of the bran were determined by a laser diffraction particle sizing method (Mastersizer 2000) using the Scirocco 2000 dry dispersion unit (Malvern Instruments, Malvern, UK). Three main effects of the grinding set-up were visible from the results. Firstly, grinding time at all three modes had a significant effect on all particle size parameters: d(0.1), d(0.5), d(0.9), D[3,2], D[4,3], span and specific surface area. Longer grinding times resulted in lower values of the above-listed parameters, e.g. the averaged d(0.5) of the sample (229.57±1.46 µm) dropped to 51.29±1.28 µm after 2 minutes grinding without LN₂, and additionally to 43.00±1.33 µm after 4 minutes of grinding without LN₂. The only exception was the sample ground for 12 minutes without cooling, where an increase in particle diameters occurred (d(0.5)=62.85±2.20 µm), probably due to particles adhering to one another and forming larger particle clusters. Secondly, samples with LN₂ cooling exhibited lower diameters in comparison to non-cooled. For example, after 8 minutes of non-cooled grinding d(0.5)=46.97±1.05 µm was achieved, while the LN₂ cooling enabled collection of particles with average sizes of d(0.5)=18.57±0.18 µm. Thirdly, the application of intermediate cryo-cooling step resulted in similar particle diameters (d(0.5)=15.83±0.36 µm, 12 min of grinding) as cryo-milling without this step (d(0.5)=16.33±2.09 µm, 12 min of grinding). This indicates that intermediate cooling is not necessary for the current application, which consequently reduces the consumption of LN₂. These results point out the potential beneficial effects of millet bran grinding at cryo-temperatures. Further research will show if the lower particle size achieved in comparison to non-cooled grinding could result in increased bioavailability of bioactive compounds, as well as protein digestibility and solubility of dietary fibers of the proso millet bran fraction.

Keywords: ball mill, cryo-milling, particle size distribution, proso millet (Panicum miliaceum) bran

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139 Technology for Biogas Upgrading with Immobilized Algae Biomass

Authors: Marcin Debowski, Marcin Zielinski, Miroslaw Krzemieniewski, Agata Glowacka-Gil, Paulina Rusanowska, Magdalena Zielinska, Agnieszka Cydzik-Kwiatkowska

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Technologies of biogas upgrading are now perceived as competitive solution combustion and production of electricity and heat. Biomethane production will ensure broader application as energy carrier than biogas. Biomethane can be used as fuel in internal combustion engines or introduced into the natural gas transmission network. Therefore, there is a need to search for innovative, economically and technically justified methods for biogas enrichment. The aim of this paper is to present a technology solution for biogas upgrading with immobilized algae biomass. Reactor for biogas upgrading with immobilized algae biomass can be used for removing CO₂ from the biogas, flue gases and the waste gases especially coming from different industry sectors, e.g. from the food industry from yeast production process, biogas production systems, liquid and gaseous fuels combustion systems, hydrocarbon processing technology. The basis for the technological assumptions of presented technology were laboratory works and analyses that tested technological variants of biogas upgrading. The enrichment of biogas with a methane content of 90-97% pointed to technological assumptions for installation on a technical scale. Reactor for biogas upgrading with algae biomass is characterized by a significantly lower cubature in relation to the currently used solutions which use CO₂ removal processes. The invention, by its structure, assumes achieving a very high concentration of biomass of algae through its immobilization in capsules. This eliminates the phenomenon of lowering the pH value, i.e. acidification of the environment in which algae grow, resulting from the introduction of waste gases at a high CO₂ concentration. The system for introducing light into algae capsules is characterized by a higher degree of its use, due to lower losses resulting from the phenomenon of absorption of light energy by water. The light from the light source is continuously supplied to the formed biomass of algae or cyanobacteria in capsules by the light tubes. The light source may be sunlight or a light generator of a different wavelength of light from 300 nm to 800 nm. A portion of gas containing CO₂, accumulated in the tank and conveyed by the pump is periodically introduced into the housing of the photobioreactor tank. When conveying the gas that contains CO₂, it penetrates the algal biomass in capsules through the outer envelope, displacing, from the algal biomass, gaseous metabolic products which are discharged by the outlet duct for gases. It contributes to eliminating the negative impact of this factor on CO₂ binding processes. As a result of the cyclic dosing of gases containing carbon dioxide, gaseous metabolic products of algae are displaced and removed outside the technological system. Technology for biogas upgrading with immobilized algae biomass is suitable for the small biogas plant. The advantages of this technology are high efficiency as well as useful algae biomass which can be used mainly as animal feed, fertilizers and in the power industry. The construction of the device allows effective removal of carbon dioxide from gases at a high CO₂ concentration.

Keywords: biogas, carbon dioxide, immobilised biomass, microalgae, upgrading

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138 Synthesis and Characterization of Fibrin/Polyethylene Glycol-Based Interpenetrating Polymer Networks for Dermal Tissue Engineering

Authors: O. Gsib, U. Peirera, C. Egles, S. A. Bencherif

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In skin regenerative medicine, one of the critical issues is to produce a three-dimensional scaffold with optimized porosity for dermal fibroblast infiltration and neovascularization, which exhibits high mechanical properties and displays sufficient wound healing characteristics. In this study, we report on the synthesis and characterization of macroporous sequential interpenetrating polymer networks (IPNs) combining skin wound healing properties of fibrin with the excellent physical properties of polyethylene glycol (PEG). Fibrin fibers serve as a provisional biologically active network to promote cell adhesion and proliferation while PEG provides the mechanical stability to maintain the entire 3D construct. After having modified both PEG and Serum Albumin (used for promoting enzymatic degradability) by adding methacrylate residues (PEGDM and SAM, respectively), Fibrin/PEGDM-SAM sequential IPNs were synthesized as follows: Macroporous sponges were first produced from PEGDM-SAM hydrogels by a freeze-drying technique and then rehydrated by adding the fibrin precursors. Environmental Scanning Electron Microscopy (ESEM) and Confocal Laser Scanning Microscopy (CLSM) were used to characterize their microstructure. Human dermal fibroblasts were cultivated during one week in the constructs and different cell culture parameters (viability, morphology, proliferation) were evaluated. Subcutaneous implantations of the scaffolds were conducted on five-week old male nude mice to investigate their biocompatibility in vivo. We successfully synthesized interconnected and macroporous Fibrin/PEGDM-SAM sequential IPNs. The viability of primary dermal fibroblasts was well maintained (above 90%) after 2 days of culture. Cells were able to adhere, spread and proliferate in the scaffolds suggesting the suitable porosity and intrinsic biologic properties of the constructs. The fibrin network adopted a spider web shape that covered partially the pores allowing easier cell infiltration into the macroporous structure. To further characterize the in vitro cell behavior, cell proliferation (EdU incorporation, MTS assay) is being studied. Preliminary histological analysis of animal studies indicated the persistence of hydrogels even after one-month post implantation and confirmed the absence of inflammation response, good biocompatibility and biointegration of our scaffolds within the surrounding tissues. These results suggest that our Fibrin/PEGDM-SAM IPNs could be considered as potential candidates for dermis regenerative medicine. Histological analysis will be completed to further assess scaffold remodeling including de novo extracellular matrix protein synthesis and early stage angiogenesis analysis. Compression measurements will be conducted to investigate the mechanical properties.

Keywords: fibrin, hydrogels for dermal reconstruction, polyethylene glycol, semi-interpenetrating polymer network

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137 Moringa olifera Curate The Toxic Potential of CuO Nanoparticles in Oreochromis mossambicus

Authors: Farhat Jabeen, Muhammad Asad

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The study assessed the curative potential of Moringa olifera seeds against copper oxide nanoparticles induced toxicity in Oreochromis mossambicus. In order to investigate the curative potential of M. olifera seeds, firstly we examine its chemical composition, secondary metabolites, and bioactive compounds including hydroxyl-cinnamic acids, flavanols and hydroxybenzoic acids through standard methods and high performance liquid chromatography. In current study, the potential sub-lethal toxic dose of CuO-NPs (0.12 mg/l) was investigated through pilot experiment and three non-lethal doses (low=32, medium=48 and high=96 mg/l) of M. olifera were selected on the basis of its LC50 value for O. mossambicus. The experimental fish, O. mossambicus (n=100 of approximately 20 g each) were procured from Manawan Fisheries Complex, Lahore, and acclimatized for two weeks in glass aquaria. Experiment was conducted in accordance with the guidelines of Institutional Animal Ethics Committee, Government College University Faisalabad, Pakistan. During acclimatization and experimental period, fish received the commercial fish feed at 2.5% body weight daily. In order to assess the curative effect of M. olifera against CuO NPs induced toxicity, O. mossambicus were randomly divided into five groups and were designated as control (C) without any treatment, positive control (G*) exposed to potential toxic dose of CuO-NPs at 0.12 mg/l, and three treated groups namely G1, G2, and G3 co-treated with 0.12 mg/l of CuO-NPs plus different doses of M. olifera seed extract at 32, 48, and 96 mg/l, respectively for 56 days. Fish were exposed to waterborne CuO NPs and M. olifera seed extract. CuO-NPs treatment was ceased after 28 days but the doses of M. olifera were continued for 56 days. Blood was taken after 28 and 56 days through caudal venipuncture. Liver and intestine were taken for oxidative stress and histological studies after 56 days. In M. olifera seeds, moisture contents, crude protein, lipids, carbohydrates and ash were recorded as 3.8, 37.83, 32.52, 46.12, and 7.75%, respectively on dry weight basis. Total energy was recorded as 627.36 kcal/100g. Qualitative analysis of M. olifera seeds showed the presence of terpenoids, saponins, flavonoids, alkaloids and phenolics, while its quantitative analysis showed the considerable amount of total phenolics, flavonoids, saponins, and alkaloids as 134.75, 170.15, 1.57, and 0.4 µg/mg, respectively. Analysis of bioactive compounds in M. olifera seeds showed the presence of hydroxy-cinnamic acids (6.07 µg/ml), flavanols (71.72 µg/ml), and hydroxyl benzoic acids (97.82 µg/ml). The results showed that M. oliefera seed extract at 48 and 56 mg/l was able to cure against the toxic effects of CuO-NPs. The significant changes were observed in G* and G1 for sero-hepatic enzymes, anti-oxidants and histological profile. The investigations of this study showed that M. olifera is a good curative agent against potential induced toxicity of CuO-NPs in O. mossambicus. The curative effect of M. olifera is attributed to the presence of higher amount of secondary metabolites and bioactive compounds. This study suggested the use of M. olifera to curate different ailments in fish and other organisms.

Keywords: CuO nanoparticles, curative, Moringa olifera, Oreochromis mossambicus

Procedia PDF Downloads 109