Search results for: solar panel efficiency technique

Authors: Sahar Heidary

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Radiography and radiotherapy have emerged as crucial pillars of modern medical practice, revolutionizing diagnostics and treatment for a myriad of health conditions. This abstract highlights the pivotal role of radiography and radiotherapy in favor of healthcare and society. Radiography, a non-invasive imaging technique, has significantly advanced medical diagnostics by enabling the visualization of internal structures and abnormalities within the human body. With the advent of digital radiography, clinicians can obtain high-resolution images promptly, leading to faster diagnoses and informed treatment decisions. Radiography plays a pivotal role in detecting fractures, tumors, infections, and various other conditions, allowing for timely interventions and improved patient outcomes. Moreover, its widespread accessibility and cost-effectiveness make it an indispensable tool in healthcare settings worldwide. On the other hand, radiotherapy, a branch of medical science that utilizes high-energy radiation, has become an integral component of cancer treatment and management. By precisely targeting and damaging cancerous cells, radiotherapy offers a potent strategy to control tumor growth and, in many cases, leads to cancer eradication. Additionally, radiotherapy is often used in combination with surgery and chemotherapy, providing a multifaceted approach to combat cancer comprehensively. The continuous advancements in radiotherapy techniques, such as intensity-modulated radiotherapy and stereotactic radiosurgery, have further improved treatment precision while minimizing damage to surrounding healthy tissues. Furthermore, radiography and radiotherapy have demonstrated their worth beyond oncology. Radiography is instrumental in guiding various medical procedures, including catheter placement, joint injections, and dental evaluations, reducing complications and enhancing procedural accuracy. On the other hand, radiotherapy finds applications in non-cancerous conditions like benign tumors, vascular malformations, and certain neurological disorders, offering therapeutic options for patients who may not benefit from traditional surgical interventions. In conclusion, radiography and radiotherapy stand as indispensable tools in modern medicine, driving transformative improvements in patient care and treatment outcomes. Their ability to diagnose, treat, and manage a wide array of medical conditions underscores their favor in medical practice. As technology continues to advance, radiography and radiotherapy will undoubtedly play an ever more significant role in shaping the future of healthcare, ultimately saving lives and enhancing the quality of life for countless individuals worldwide.

Keywords: radiology, radiotherapy, medical imaging, cancer treatment

Procedia PDF Downloads 69

Authors: Oluwabori Emmanuel Olukoyejo, Ogra Victor Ogra, Bosede Amodu, Tewogbade Adeoye Adedeji

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Background: Disorders of thyroid function are the second most common endocrine disorders worldwide, with a direct relationship with metabolic bone diseases. These metabolic bone complications are often subtle but manifest as bone pains and an increased risk of fractures. The gold standard for diagnosis, Dual Energy X-ray Absorptiometry (DEXA), is limited in this environment due to unavailability, cumbersomeness and cost. However, bone biomarkers have shown prospects in assessing alterations in bone remodeling, which has not been studied in this environment. Aim: This study evaluates serum levels of bone-specific alkaline phosphatase (bone-specific ALP), osteopontin and osteoprotegerin biomarkers of bone turnover in patients with disorders of thyroid function. Methods: This is a cross-sectional study carried out over a period of one and a half years. Forty patients with thyroid dysfunctions, aged 20 to 50 years, and thirty-eight age and sex-matched healthy euthyroid controls were included in this study. Patients were further stratified into hyperthyroid and hypothyroid groups. Bone-specific ALP, osteopontin, and osteoprotegerin, alongside serum total calcium, ionized calcium and inorganic phosphate, were assayed for all patients and controls. A self-administered questionnaire was used to obtain data on sociodemographic and medical history. Then, 5 ml of blood was collected in a plain bottle and serum was harvested following clotting and centrifugation. Serum samples were assayed for B-ALP, osteopontin, and osteoprotegerin using the ELISA technique. Total calcium and ionized calcium were assayed using an ion-selective electrode, while the inorganic phosphate was assayed with automated photometry. Results: The hyperthyroid and hypothyroid patient groups had significantly increased median serum B-ALP (30.40 and 26.50) ng/ml and significantly lower median OPG (0.80 and 0.80) ng/ml than the controls (10.81 and 1.30) ng/ml respectively, p < 0.05. However, serum osteopontin in the hyperthyroid group was significantly higher and significantly lower in the hypothyroid group when compared with the controls (11.00 and 2.10 vs 3.70) ng/ml, respectively, p < 0.05. Both hyperthyroid and hypothyroid groups had significantly higher mean serum total calcium, ionized calcium and inorganic phosphate than the controls (2.49 ± 0.28, 1.27 ± 0.14 and 1.33 ± 0.33) mmol/l and (2.41 ± 0.04, 1.20 ± 0.04 and 1.15 ± 0.16) mmol/l vs (2.27 ± 0.11, 1.17 ± 0.06 and 1.08 ± 0.16) mmol/l respectively, p < 0.05. Conclusion: Patients with disorders of thyroid function have metabolic imbalances of all the studied bone markers, suggesting a higher bone turnover. The routine bone markers will be an invaluable tool for monitoring bone health in patients with thyroid dysfunctions, while the less readily available markers can be introduced as supplementary tools. Moreover, bone-specific ALP, osteopontin and osteoprotegerin were found to be the strongest independent predictors of metabolic bone markers’ derangements in patients with thyroid dysfunctions.

Keywords: metabolic bone diseases, biomarker, bone turnover, hyperthyroid, hypothyroid, euthyroid

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Authors: Lekgowa Collen Makola, Cecil Naphtaly Moro Ouma, Sharon Moeno, Langelihle Dlamini

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In recent years, advancement in the field of nanotechnology has evolved new strategies to address energy and environmental issues. Amongst the developing technologies, visible-light-driven photocatalysis is regarded as a sustainable approach for energy production and environmental detoxifications, where transition metal oxides (TMOs) and metal-free carbon-based semiconductors such as graphitic carbon nitride (CN) evidenced notable potential in this matter. Herein, g-C₃N₄@WO₃@Ti₃C₂Tx three-component multijunction photocatalyst was fabricated via facile ultrasonic-assisted self-assembly, followed by calcination to facilitate extensive integrations of the materials. A series of different Ti₃C₂ wt% loading in the g-C₃N4@WO₃@Ti₃C₂Tx were prepared and represented as 1-CWT, 3-CWT, 5-CWT, and 7-CWT corresponding to 1, 3, 5, and 7wt%, respectively. Systematic characterization using spectroscopic and microscopic techniques were employed to validate the successful preparation of the photocatalysts. Enhanced optoelectronic and photoelectrochemical properties were observed for the WO₃@Ti₃C2@g-C₃N4 heterostructure with respect to the individual materials. Photoluminescence spectra and Nyquist plots show restrained recombination rates and improved photocarrier conductivities, respectively, and this was credited to the synergistic coupling effect and the presence of highly conductive Ti₃C2 MXene. The strong interfacial contact surfaces upon the formation of the composite were confirmed using XPS. Multiple charge transfer mechanisms were proposed for the WO3@Ti3C₂@g-C3N4, which couples Z-scheme and Schottky-junction mediated with Ti3C2 MXene. Bode phase plots show improved charge carrier life-times upon the formation of the multijunctional photocatalyst. Moreover, transient photocurrent density of 7-CWT is 40 and seven (7) times higher compared to that of g-C₃N4 and WO3, correspondingly. Unlike in the traditional Z-Scheme, the formed ternary heterostructure possesses interfaces through the metallic 2D Ti₃C₂ MXene, which provided charge transfer channels for efficient photocarrier transfers with carrier concentrations (ND) of 17.49×1021 cm-3 and 4.86% photo-to-chemical conversion efficiency. The as-prepared ternary g-C₃N₄@WO₃@Ti₃C₂Tx exhibited excellent photoelectrochemical properties with reserved redox band potential potencies to facilitate efficient photo-oxidation and -reduction reactions. The fabricated multijunction photocatalyst exhibits potentials to be used in an extensive range of photocatalytic process vis., production of valuable hydrocarbons from CO₂, production of H₂, and degradation of a plethora of pollutants from wastewater.

Keywords: photocatalysis, Z-scheme, multijunction heterostructure, Ti₃C₂ MXene, g-C₃N₄

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Authors: B. Casper

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The energy transition towards renewable energies and drastically reduced carbon dioxide emissions in Germany drives multiple sectors into a transformation process. Photovoltaic and on-shore wind power are predominantly feeding in the low and medium-voltage grids. The electricity grid is not laid out to allow an increasing feed-in of power in low and medium voltage grids. Electric mobility is currently in the run-up phase in Germany and still lacks a significant amount of charging stations. The additional power demand by e-mobility cannot be supplied by the existing electric grids in most cases. The future demands in heating and cooling of commercial and residential buildings are increasingly generated by heat-pumps. Yet the most important part in the energy transition is the storage of surplus energy generated by photovoltaic and wind power sources. Water electrolysis is one way to store surplus energy known as power-to-gas. With the vehicle-to-grid technology, the upcoming fleet of electric cars could be used as energy storage to stabilize the grid. All these processes use direct current (DC). The demand of bi-directional flow and higher efficiency in the future grids can be met by using DC. The Flexible Electrical Networks (FEN) research campus at RWTH Aachen investigates interdisciplinary about the advantages, opportunities, and limitations of DC grids. This paper investigates the impact of DC grids as a technological innovation on the urban form and urban life. Applying explorative scenario development, analyzation of mapped open data sources on grid networks and research-by-design as a conceptual design method, possible starting points for a transformation to DC medium voltage grids could be found. Several fields of action have emerged in which DC technology could become a catalyst for future urban development: energy transition in urban areas, e-mobility, and transformation of the network infrastructure. The investigation shows a significant potential to increase renewable energy production within cities with DC grids. The charging infrastructure for electric vehicles will predominantly be using DC in the future because fast and ultra fast charging can only be achieved with DC. Our research shows that e-mobility, combined with autonomous driving has the potential to change the urban space and urban logistics fundamentally. Furthermore, there are possible win-win-win solutions for the municipality, the grid operator and the inhabitants: replacing overhead transmission lines by underground DC cables to open up spaces in contested urban areas can lead to a positive example of how the energy transition can contribute to a more sustainable urban structure. The outlook makes clear that target grid planning and urban planning will increasingly need to be synchronized.

Keywords: direct current, e-mobility, energy transition, grid planning, renewable energy, urban planning

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Authors: Abiola O. Temitayo-Oboh, Olugbenga L. Abodunrin, Wasiu O. Adebimpe, Micheal C. Asuzu

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Introduction: Many women who are sexually active would prefer to avoid becoming pregnant but are not using any method of contraception. These women are considered to have an unmet need for contraception. In an ideal situation, all women who want to space or limit their births and are exposed to the risk of conception would use some kind of conception; in practice, however, some women fail to use contraception which put them at risk of having mistimed or unwanted births, induced abortion, or maternal death. This study, therefore, aimed to assess the determinants of unmet need for contraception among currently married women in rural and urban communities of Osun State, South-West Nigeria. Methods: This was an analytical cross-sectional comparative study, which was carried out among currently married women. Three hundred and twenty respondents each were selected for the rural and urban groups from four Local Government Areas using multi-stage sampling technique. Data were collected using a pre-tested semi-structured interviewer-administered questionnaire and focus group discussion (FGD) guide; data analysis was done with Statistical Package for Social Sciences (SPSS) version 17.0 and detailed content analysis method respectively. Statistical analysis of the difference between proportions was done by the use of the Chi-square test and T-test was used to compare the means of the continuous variables. The study also utilized descriptive, bivariate and multivariate analytical techniques to examine the effect of some variables on unmet need. Level of statistical significance was set at p-value < 0.05 for all values. Results: Two hundred and ninety-six (92.5%) of the rural and 306 (95.6%) of the urban study population had heard of contraception, 365 (57.0 %) of the total respondents had good knowledge [162 (50.6 %) for rural respondents and 203 (63.4 %) for urban respondents]. This difference was statistically significant (p < 0.001). Five hundred and twenty-one (81.4%) respondents had a positive attitude towards contraception [243 (75.9%) in the rural and 278 (86.9%) in the urban area], and the difference was also statistically significant (p < 0.001). Only 47 (14.7%) and 59 (18.4%) of rural and urban women were current contraceptive users respectively. The total unmet need for contraception among rural women was 138 (43.1%) of which 82 (25.6%) was for spacing and 56 (17.5%), for limiting. While the total unmet need for contraception among urban women was 145 (45.3%) of which 96 (30.0%) was for spacing and 49 (15.3%) for limiting. Number of living children, knowledge of contraceptive methods, discussion with health workers about family planning, couples discussion about family planning and availability of family planning services were found to be predictors of women’s unmet need for contraception (p < 0.05). Conclusion: It is, therefore, recommended that there is need to intensify reproductive health education in bridging the knowledge gap, improving attitude and modifying practices regarding use of contraception in Nigeria. Hence, this will help to enhance the utilization of family planning services among Nigerian women.

Keywords: contraception, married women, Nigeria, rural, urban, unmet need

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Authors: Sina Kazemi, Farshid Torabi, Todd Peterson

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Drilling in shale formations is frequently time-consuming, challenging, and fraught with mechanical failures such as stuck pipes or hole packing off when the cutting removal rate is not sufficient to clean the bottom hole. Crossing the heavy oil shale and sand reservoirs with active shale and microfractures is generally associated with severe fluid losses causing a reduction in the rate of the cuttings removal. These circumstances compromise a well’s integrity and result in a lower rate of penetration (ROP). This study presents collective results of field studies and theoretical analysis conducted on data from South Pars and North Dome in an Iran-Qatar offshore field. Solutions to complications related to drilling in shale formations are proposed through systemically analyzing and applying modeling techniques to select field mud logging data. Field data measurements during actual drilling operations indicate that in a shale formation where the return flow of polymer mud was almost lost in the upper dolomite layer, the performance of hole cleaning and ROP progressively change when higher string rotations are initiated. Likewise, it was observed that this effect minimized the force of rotational torque and improved well integrity in the subsequent casing running. Given similar geologic conditions and drilling operations in reservoirs targeting shale as the producing zone like the Bakken formation within the Williston Basin and Lloydminster, Saskatchewan, a drill bench dynamic modeling simulation was used to simulate borehole cleaning efficiency and mud optimization. The results obtained by altering RPM (string revolution per minute) at the same pump rate and optimized mud properties exhibit a positive correlation with field measurements. The field investigation and developed model in this report show that increasing the speed of string revolution as far as geomechanics and drilling bit conditions permit can minimize the risk of mechanically stuck pipes while reaching a higher than expected ROP in shale formations. Data obtained from modeling and field data analysis, optimized drilling parameters, and hole cleaning procedures are suggested for minimizing the risk of a hole packing off and enhancing well integrity in shale reservoirs. Whereas optimization of ROP at a lower pump rate maintains the wellbore stability, it saves time for the operator while reducing carbon emissions and fatigue of mud motors and power supply engines.

Keywords: ROP, circulating density, drilling parameters, return flow, shale reservoir, well integrity

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Authors: Milos Beran, Josef Drahorad, Ondrej Vltavsky, Martin Fronek, Jiri Sova

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While most nanofibers are produced using electrospinning, this technique suffers from several drawbacks, such as the requirement for specialized equipment, high electrical potential, and electrically conductive targets. Consequently, recent years have seen the increasing emergence of novel strategies in generating nanofibers in a larger scale and higher throughput manner. The centrifugal spinning is simple, cheap and highly productive technology for nanofiber production. In principle, the drawing of solution filament into nanofibers using centrifugal spinning is achieved through the controlled manipulation of centrifugal force, viscoelasticity, and mass transfer characteristics of the spinning solutions. Engineering efforts of researches of the Food research institute Prague and the Czech Technical University in the field the centrifugal nozzleless spinning led to introduction of a pilot plant demonstrator NANOCENT. The main advantages of the demonstrator are lower investment cost - thanks to simpler construction compared to widely used electrospinning equipments, higher production speed, new application possibilities and easy maintenance. The centrifugal nozzleless spinning is especially suitable to produce submicron fibers from polymeric solutions in highly volatile solvents, such as chloroform, DCM, THF, or acetone. To date, submicron fibers have been prepared from PS, PUR and biodegradable polyesters, such as PHB, PLA, PCL, or PBS. The products are in form of 3D structures or nanofiber membranes. Unique self-supporting nanofiber membranes were prepared from the biodegradable polyesters in different mixtures. The nanofiber membranes have been tested for different applications. Filtration efficiencies for water solutions and aerosols in air were evaluated. Different active inserts were added to the solutions before the spinning process, such as inorganic nanoparticles, organic precursors of metal oxides, antimicrobial and wound healing compounds or photocatalytic phthalocyanines. Sintering can be subsequently carried out to remove the polymeric material and transfer the organic precursors to metal oxides, such as Si02, or photocatalytic Zn02 and Ti02, to obtain inorganic nanofibers. Electrospinning is more suitable technology to produce membranes for the filtration applications than the centrifugal nozzleless spinning, because of the formation of more homogenous nanofiber layers and fibers with smaller diameters. The self-supporting nanofiber membranes prepared from the biodegradable polyesters are especially suitable for medical applications, such as wound or burn healing dressings or tissue engineering scaffolds. This work was supported by the research grants TH03020466 of the Technology Agency of the Czech Republic.

Keywords: polymeric nanofibers, self-supporting nanofiber membranes, biodegradable polyesters, active inserts

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Authors: Itee Chowdhury, Shikha Modi

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Introduction: Cancer is beginning to outpace cardiovascular disease as a cause of death affecting every major organ system with profound implications for perioperative management. Breast cancer is the most common cancer in women in India, accounting for 27% of all cancers. The small changes in analgesic management of cancer patients can greatly improve prognosis and reduce the risk of postsurgical cancer recurrence as opioid-based analgesia has a deleterious effect on cancer outcomes. Shortened postsurgical recovery time facilitates earlier return to intended oncological therapy maximising the chance of successful treatment. Literature reveals that the role of BIS since FDA approval has been assessed in various types of surgeries, but clinical data on its use in oncosurgical patients are scanty. Our study focuses on the role of BIS-guided anaesthesia for breast cancer surgery patients. Methods: A prospective randomized controlled study in patients aged 36-55years scheduled for modified radical mastectomy was conducted in 51 patients in each group who met the inclusion and exclusion criteria, and randomization was done by sealed envelope technique. In BIS guided anaesthesia group (B), sevoflurane was titrated to keep the BIS value 45-60, and thereafter if the patient showed hypertension/tachycardia, an opioid was given. In standard anaesthesia care (group C), sevoflurane was titrated to keep MAC in the range of 0.8-1, and fentanyl was given if the patient showed hypertension/tachycardia. Intraoperative opioid consumption was calculated. Postsurgery recovery characteristics, including Aldrete score, were assessed. Patients were questioned for pain, PONV, and recall of the intraoperative event. A comparison of age, BMI, ASA, recovery characteristics, opioid, and VAS score was made using the non-parametric Mann-Whitney U test. Categorical data like intraoperative awareness of surgery and PONV was studied using the Chi-square test. A comparison of heart rate and MAP was made by an independent sample t-test. #ggplot2 package was used to show the trend of the BIS index for all intraoperative time points for each patient. For a statistical test of significance, the cut-off p-value was set as <0.05. Conclusions: BIS monitoring led to reduced opioid consumption and early recovery from anaesthesia in breast cancer patients undergoing MRM resulting in less postoperative nausea and vomiting and less pain intensity in the immediate postoperative period without any recall of the intraoperative event. Thus, the use of a Bispectral index monitor allows for tailoring of anaesthesia administration with a good outcome.

Keywords: bispectral index, depth of anaesthesia, recovery, opioid consumption

Procedia PDF Downloads 127

Authors: Asad Hanif, Pavithra Parthasarathy, Zongjin Li

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Thermal insulating composites help to reduce the total power consumption in a building by creating a barrier between external and internal environment. Such composites can be used in the roofing tiles or wall panels for exterior surfaces. This study purposes to develop lightweight cement-based composites for thermal insulating applications. Waste materials like silica fume (an industrial by-product) and fly ash cenosphere (FAC) (hollow micro-spherical shells obtained as a waste residue from coal fired power plants) were used as partial replacement of cement and lightweight filler, respectively. Moreover, aerogel, a nano-porous material made of silica, was also used in different dosages for improved thermal insulating behavior, while poly vinyl alcohol (PVA) fibers were added for enhanced toughness. The raw materials including binders and fillers were characterized by X-Ray Diffraction (XRD), X-Ray Fluorescence spectroscopy (XRF), and Brunauer–Emmett–Teller (BET) analysis techniques in which various physical and chemical properties of the raw materials were evaluated like specific surface area, chemical composition (oxide form), and pore size distribution (if any). Ultra-lightweight cementitious composites were developed by varying the amounts of FAC and aerogel with 28-day unit weight ranging from 1551.28 kg/m³ to 1027.85 kg/m³. Excellent mechanical and thermal insulating properties of the resulting composites were obtained ranging from 53.62 MPa to 8.66 MPa compressive strength, 9.77 MPa to 3.98 MPa flexural strength, and 0.3025 W/m-K to 0.2009 W/m-K as thermal conductivity coefficient (QTM-500). The composites were also tested for peak temperature difference between outer and inner surfaces when subjected to heating (in a specially designed experimental set-up) by a 275W infrared lamp. The temperature difference up to 16.78 ^oC was achieved, which indicated outstanding properties of the developed composites to act as a thermal barrier for building envelopes. Microstructural studies were carried out by Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDS) for characterizing the inner structure of the composite specimen. Also, the hydration products were quantified using the surface area mapping and line scale technique in EDS. The microstructural analyses indicated excellent bonding of FAC and aerogel in the cementitious system. Also, selective reactivity of FAC was ascertained from the SEM imagery where the partially consumed FAC shells were observed. All in all, the lightweight fillers, FAC, and aerogel helped to produce the lightweight composites due to their physical characteristics, while exceptional mechanical properties, owing to FAC partial reactivity, were achieved.

Keywords: aerogel, cement-based, composite, fly ash cenosphere, lightweight, sustainable development, thermal conductivity

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Authors: Supria Sarkar, Vasit Sagan, Sourav Bhadra, Meghnath Pokharel, Felix B.Fritschi

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Soybean and their derivatives are very important agricultural commodities around the world because of their wide applicability in human food, animal feed, biofuel, and industries. However, the significance of soybean production depends on the quality of the soybean seeds rather than the yield alone. Seed composition is widely dependent on plant physiological properties, aerobic and anaerobic environmental conditions, nutrient content, and plant phenological characteristics, which can be captured by high temporal resolution remote sensing datasets. Planet scope (PS) satellite images have high potential in sequential information of crop growth due to their frequent revisit throughout the world. In this study, we estimate soybean seed composition while the plants are in the field by utilizing PlanetScope (PS) satellite images and different machine learning algorithms. Several experimental fields were established with varying genotypes and different seed compositions were measured from the samples as ground truth data. The PS images were processed to extract 462 hand-crafted vegetative and textural features. Four machine learning algorithms, i.e., partial least squares (PLSR), random forest (RFR), gradient boosting machine (GBM), support vector machine (SVM), and two recurrent neural network architectures, i.e., long short-term memory (LSTM) and gated recurrent unit (GRU) were used in this study to predict oil, protein, sucrose, ash, starch, and fiber of soybean seed samples. The GRU and LSTM architectures had two separate branches, one for vegetative features and the other for textures features, which were later concatenated together to predict seed composition. The results show that sucrose, ash, protein, and oil yielded comparable prediction results. Machine learning algorithms that best predicted the six seed composition traits differed. GRU worked well for oil (R-Squared: of 0.53) and protein (R-Squared: 0.36), whereas SVR and PLSR showed the best result for sucrose (R-Squared: 0.74) and ash (R-Squared: 0.60), respectively. Although, the RFR and GBM provided comparable performance, the models tended to extremely overfit. Among the features, vegetative features were found as the most important variables compared to texture features. It is suggested to utilize many vegetation indices for machine learning training and select the best ones by using feature selection methods. Overall, the study reveals the feasibility and efficiency of PS images and machine learning for plot-level seed composition estimation. However, special care should be given while designing the plot size in the experiments to avoid mixed pixel issues.

Keywords: agriculture, computer vision, data science, geospatial technology

Procedia PDF Downloads 137

Authors: Amit Das

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Background and significance of the study: Generally investors and market forecasters use financial statement for investigation while it awakens contribute to investing. The main vicinity of financial accounting and reporting practices recommends a few basic financial performance indicators, namely, return on capital employed, return on assets and earnings per share, which is associated considerably with share prices. It is principally true in case of Indian pharmaceutical companies also. Share investing is intriguing a financial risk in addition to investors look for those financial evaluations which have noteworthy shock on share price. A crucial intention of financial statement analysis and reporting is to offer information which is helpful predominantly to exterior clients in creating credit as well as investment choices. Sound financial performance attracts the investors automatically and it will increase the share price of the respective companies. Keeping in view of this, this research work investigates the impact of financial performance indicators on share price of pharmaceutical companies in India which is listed in the Bombay Stock Exchange. Methodology: This research work is based on secondary data collected from moneycontrol database on September 28, 2015 of top 101 pharmaceutical companies in India. Since this study selects four financial performance indicators purposively and availability in the database, that is, earnings per share, return on capital employed, return on assets and net profits as independent variables and one dependent variable, share price of 101 pharmaceutical companies. While analysing the data, correlation statistics, multiple regression technique and appropriate test of significance have been used. Major findings: Correlation statistics show that four financial performance indicators of 101 pharmaceutical companies are associated positively and negatively with its share price and it is very much significant that more than 80 companies’ financial performances are related positively. Multiple correlation test results indicate that financial performance indicators are highly related with share prices of the selected pharmaceutical companies. Furthermore, multiple regression test results illustrate that when financial performances are good, share prices have been increased steadily in the Bombay stock exchange and all results are statistically significant. It is more important to note that sensitivity indices were changed slightly through financial performance indicators of selected pharmaceutical companies in India. Concluding statements: The share prices of pharmaceutical companies depend on the sound financial performances. It is very clear that share prices are changed with the movement of two important financial performance indicators, that is, earnings per share and return on assets. Since 101 pharmaceutical companies are listed in the Bombay stock exchange and Sensex are changed with this, it is obvious that Government of India has to take important decisions regarding production and exports of pharmaceutical products so that financial performance of all the pharmaceutical companies are improved and its share price are increased positively.

Keywords: financial performance indicators, share prices, pharmaceutical companies, India

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Authors: Hossein Havaeji, Tony Wong, Thien-My Dao

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1. Research Problems and Research Objectives: Blockchain Technology-enabled Supply Chain System (BT-enabled SCS) is the system using BT to drive SCS transparency, security, durability, and process integrity as SCS data is not always visible, available, or trusted. The costs of operating BT in the SCS are a common problem in several organizations. The costs must be estimated as they can impact existing cost control strategies. To account for system and deployment costs, it is necessary to overcome the following hurdle. The problem is that the costs of developing and running a BT in SCS are not yet clear in most cases. Many industries aiming to use BT have special attention to the importance of BT installation cost which has a direct impact on the total costs of SCS. Predicting BT installation cost in SCS may help managers decide whether BT is to be an economic advantage. The purpose of the research is to identify some main BT installation cost components in SCS needed for deeper cost analysis. We then identify and categorize the main groups of cost components in more detail to utilize them in the prediction process. The second objective is to determine the suitable Supervised Learning technique in order to predict the costs of developing and running BT in SCS in a particular case study. The last aim is to investigate how the running BT cost can be involved in the total cost of SCS. 2. Work Performed: Applied successfully in various fields, Supervised Learning is a method to set the data frame, treat the data, and train/practice the method sort. It is a learning model directed to make predictions of an outcome measurement based on a set of unforeseen input data. The following steps must be conducted to search for the objectives of our subject. The first step is to make a literature review to identify the different cost components of BT installation in SCS. Based on the literature review, we should choose some Supervised Learning methods which are suitable for BT installation cost prediction in SCS. According to the literature review, some Supervised Learning algorithms which provide us with a powerful tool to classify BT installation components and predict BT installation cost are the Support Vector Regression (SVR) algorithm, Back Propagation (BP) neural network, and Artificial Neural Network (ANN). Choosing a case study to feed data into the models comes into the third step. Finally, we will propose the best predictive performance to find the minimum BT installation costs in SCS. 3. Expected Results and Conclusion: This study tends to propose a cost prediction of BT installation in SCS with the help of Supervised Learning algorithms. At first attempt, we will select a case study in the field of BT-enabled SCS, and then use some Supervised Learning algorithms to predict BT installation cost in SCS. We continue to find the best predictive performance for developing and running BT in SCS. Finally, the paper will be presented at the conference.

Keywords: blockchain technology, blockchain technology-enabled supply chain system, installation cost, supervised learning

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Authors: Rainner Roweder

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Theme: The present paper aims to analyze the specificity of the judicial evidence linked to the subjects of dignity and personality rights, otherwise known as moral rights, in the determination of the truth and formation of the judicial reasoning in cases concerning these areas. This research is about the way courts in Brazilian domestic law search for truth and handles evidence in cases involving moral rights that are abundant and important in Brazil. The main object of the paper is to analyze the effectiveness of the evidence in the formation of judicial conviction in matters related to morally controverted rights, based on the Brazilian, and as a comparison, the Latin American legal systems. In short, the rights of dignity and personality are moral. However, the evidential legal system expects a rational demonstration of moral rights that generate judicial conviction or persuasion. Moral, in turn, tends to be difficult or impossible to demonstrate in court, generating the problem considered in this paper, that is, the study of the moral demonstration problem as proof in court. In this sense, the more linked to moral, the more difficult to be demonstrated in court that right is, expanding the field of judicial discretion, generating legal uncertainty. More specifically, the new personality rights, such as gender, and their possibility of alteration, further amplify the problem being essentially an intimate manner, which does not exist in the objective, rational evidential system, as normally occurs in other categories, such as contracts. Therefore, evidencing this legal category in court, with the level of security required by the law, is a herculean task. It becomes virtually impossible to use the same evidentiary system when judging the rights researched here; therefore, it generates the need for a new design of the evidential task regarding the rights of the personality, a central effort of the present paper. Methodology: Concerning the methodology, the Method used in the Investigation phase was Inductive, with the use of the comparative law method; in the data treatment phase, the Inductive Method was also used. Doctrine, Legislative, and jurisprudential comparison was the technique research used. Results: In addition to the peculiar characteristics of personality rights that are not found in other rights, part of them are essentially linked to morale and are not objectively verifiable by design, and it is necessary to use specific argumentative theories for their secure confirmation, such as interdisciplinary support. The traditional pragmatic theory of proof, for having an obvious objective character, when applied in the rights linked to the morale, aggravates decisionism and generates legal insecurity, being necessary its reconstruction for morally charged cases, with the possible use of the “predictive theory” ( and predictive facts) through algorithms in data collection and treatment.

Keywords: moral rights, proof, pragmatic proof theory, insufficiency, Brazil

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Authors: André Jesus, Yanjie Zhu, Irwanda Laory

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Structural health monitoring is one of the most promising technologies concerning aversion of structural risk and economic savings. Analysts often have to deal with a considerable variety of uncertainties that arise during a monitoring process. Namely the widespread application of numerical models (model-based) is accompanied by a widespread concern about quantifying the uncertainties prevailing in their use. Some of these uncertainties are related with the deterministic nature of the model (code uncertainty) others with the variability of its inputs (parameter uncertainty) and the discrepancy between a model/experiment (systematic uncertainty). The actual process always exhibits a random behaviour (observation error) even when conditions are set identically (residual variation). Bayesian inference assumes that parameters of a model are random variables with an associated PDF, which can be inferred from experimental data. However in many Bayesian methods the determination of systematic uncertainty can be problematic. In this work systematic uncertainty is associated with a discrepancy function. The numerical model and discrepancy function are approximated by Gaussian processes (surrogate model). Finally, to avoid the computational burden of a fully Bayesian approach the parameters that characterise the Gaussian processes were estimated in a four stage process (modular Bayesian approach). The proposed methodology has been successfully applied on fields such as geoscience, biomedics, particle physics but never on the SHM context. This approach considerably reduces the computational burden; although the extent of the considered uncertainties is lower (second order effects are neglected). To successfully identify the considered uncertainties this formulation was extended to consider multiple responses. The efficiency of the algorithm has been tested on a small scale aluminium bridge structure, subjected to a thermal expansion due to infrared heaters. Comparison of its performance with responses measured at different points of the structure and associated degrees of identifiability is also carried out. A numerical FEM model of the structure was developed and the stiffness from its supports is considered as a parameter to calibrate. Results show that the modular Bayesian approach performed best when responses of the same type had the lowest spatial correlation. Based on previous literature, using different types of responses (strain, acceleration, and displacement) should also improve the identifiability problem. Uncertainties due to parametric variability, observation error, residual variability, code variability and systematic uncertainty were all recovered. For this example the algorithm performance was stable and considerably quicker than Bayesian methods that account for the full extent of uncertainties. Future research with real-life examples is required to fully access the advantages and limitations of the proposed methodology.

Keywords: bayesian, calibration, numerical model, system identification, systematic uncertainty, Gaussian process

Procedia PDF Downloads 326

Authors: Clement Yeboah

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Prior research concludes that environmental commitment positively drives organisational performance. Nonetheless, the nexus and conditions under which environmental commitment capabilities contribute to a firm’s performance are less understood. The purpose of this quantitative relational study was to examine the relationship between environmental commitment and 500 firms’ performances in Ghana. The researchers further seek to draw insights from the resource-based view to conceptualize environmental commitment and green procurement practices as resource capabilities to enhance firm performance. The researchers used insights from the contingent resource-based view to examine green leadership orientation conditions under which environmental commitment capability contributes to firm performance through green procurement practices. The study’s conceptual framework was tested on primary data from some firms in the Ghanaian market. PROCESS Macro was used to test the study’s hypotheses. Beyond that, green procurement practices mediated the association between environmental commitment capabilities and the firm’s performance. The study further seeks to find out whether green leadership orientation positively moderates the indirect relationship between environmental commitment capabilities and firm performance through green procurement practices. While conventional wisdom suggests that improved environmental commitment capabilities help improve a firm’s performance, this study tested this presumed relationship between environmental commitment capabilities and firm performance and provides theoretical arguments and empirical evidence to justify how green procurement practices uniquely and in synergy with green leadership orientation transform this relationship. The study results indicated a positive correlation between environmental commitment and firm performance. This result suggests that firms that prioritize environmental sustainability and demonstrate a strong commitment to environmentally responsible practices tend to experience better overall performance. This includes financial gains, operational efficiency, enhanced reputation, and improved relationships with stakeholders. The study's findings inform policy formulation in Ghana related to environmental regulations, incentives, and support mechanisms. Policymakers can use the insights to design policies that encourage and reward firms for their environmental commitments, thereby fostering a more sustainable and environmentally responsible business environment. The findings from such research can influence the design and development of educational programs in Ghana, specifically in fields related to sustainability, environmental management, and corporate social responsibility (CSR). Institutions may consider integrating environmental and sustainability topics into their business and management courses to create awareness and promote responsible practices among future business professionals. Also the study results can also promote the adoption of environmental accounting practices in Ghana. By recognizing and measuring the environmental impacts and costs associated with business activities, firms can better understand the financial implications of their environmental commitments and develop strategies for improved performance.

Keywords: firm’s performance, green procurement practice, environmental commitment, environmental management, sustainability

Procedia PDF Downloads 87

Authors: Zakir Hossain, Md. Saddam Hossain

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A nutritionally balanced diet and selection of appropriate species are important criteria in aquaculture. The present study was conducted to evaluate the effects of polyunsaturated fatty acids (PUFAs) and beta glucan containing diet on growth performance, feed utilization, maturation, immunity, early embryonic and larval development of endangered Pabdah catfish, Ompok pabda. In this study, squid extracted lipids and mushroom powder were used as the source of PUFAs and beta glucan, respectively, and formulated two isonitrogenous diets such as basal or control (CON) diet and treated (PBG) diet with maintaining 30% protein levels. During the study period, similar physicochemical conditions of water such as temperature, pH, and dissolved oxygen (DO) were 26.5±2 °C, 7.4±0.2, and 6.7±0.5 ppm, respectively in each cistern. The results showed that final mean body weight, final mean length gain, food conversion ratio (FCR), specific growth rate (SGR), food conversion efficiency (%), hepatosomatic index (HSI), kidney index (KI), and viscerosomatic index (VSI) were significantly (P<0.01 and P<0.05) higher in fish fed the PBG diet than that of fish fed the CON diet. The length-weight relationship and relative condition factor (K) of O. pabda were significantly (P<0.05) affected by the PBG diet. The gonadosomatic index (GSI), sperm viability, blood serum calcium ion concentrations (Ca²⁺), and vitellogenin level were significantly (P<0.05) higher in fish fed the PBG diet than that of fish fed the CON diet; which was used to the indication of fish maturation. During the spawning season, lipid granules and normal morphological structure were observed in the treated fish liver, whereas fewer lipid granules of liver were observed in the control group. Based on the immunity and stress resistance-related parameters such as hematological indices, antioxidant activity, lysozyme level, respiratory burst activity, blood reactive oxygen species (ROS), complement activity (ACH50 assay), specific IgM, brain AChE, plasma PGOT, and PGPT enzyme activity were significantly (P<0.01 and P<0.05) higher in fish fed the PBG diet than that of fish fed the CON diet. The fecundity, fertilization rate (92.23±2.69%), hatching rate (87.43±2.17 %) and survival (76.62±0.82%) of offspring were significantly higher (P˂0.05) in the PBG diet than in the control. Consequently, early embryonic and larval development was better in PBG treated group than in the control. Therefore, the present study showed that the polyunsaturated fatty acids (PUFAs) and beta glucan enriched experimental diet were more effective and achieved better growth, feed utilization, maturation, immunity, and spawning performances of O. pabda.

Keywords: polyunsaturated fatty acids, beta glucan, maturity, immunity, catfish

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Authors: S. H. Gasa, L. Singh, B. Pillay, A. O. Olaniran

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Wastewater treatment plants (WWTPs) have been implicated as the leading reservoir for antibiotic resistant bacteria (ARB), including Enterococci spp. and antibiotic resistance genes (ARGs), worldwide. Enterococci are a group of clinically significant bacteria that have gained much attention as a result of their antibiotic resistance. They play a significant role as the principal cause of nosocomial infections and dissemination of antimicrobial resistance genes in the environment. The main objective of this study was to ascertain the role of WWTPs in Durban, South Africa as potential reservoirs for antibiotic resistant Enterococci (ARE) and their related ARGs. Furthermore, the antibiogram and resistance gene profile of Enterococci species recovered from treated wastewater effluent and receiving surface water in Durban were also investigated. Using membrane filtration technique, Enterococcus selective agar and selected antibiotics, ARE were enumerated in samples (influent, activated sludge, before chlorination and final effluent) collected from two WWTPs, as well as from upstream and downstream of the receiving surface water. Two hundred Enterococcus isolates recovered from the treated effluent and receiving surface water were identified by biochemical and PCR-based methods, and their antibiotic resistance profiles determined by the Kirby-Bauer disc diffusion assay, while PCR-based assays were used to detect the presence of resistance and virulence genes. High prevalence of ARE was obtained at both WWTPs, with values reaching a maximum of 40%. The influent and activated sludge samples contained the greatest prevalence of ARE with lower values observed in the before and after chlorination samples. Of the 44 vancomycin and high-level gentamicin-resistant isolates, 11 were identified as E. faecium, 18 as E. faecalis, 4 as E. hirae while 11 are classified as “other” Enterococci species. High-level aminoglycoside resistance for gentamicin (39%) and vancomycin (61%) was recorded in species tested. The most commonly detected virulence gene was the gelE (44%), followed by asa1 (40%), while cylA and esp were detected in only 2% of the isolates. The most prevalent aminoglycoside resistance genes were aac(6')-Ie-aph(2''), aph(3')-IIIa, and ant(6')-Ia detected in 43%, 45% and 41% of the isolates, respectively. Positive correlation was observed between resistant phenotypes to high levels of aminoglycosides and presence of all aminoglycoside resistance genes. Resistance genes for glycopeptide: vanB (37%) and vanC-1 (25%), and macrolide: ermB (11%) and ermC (54%) were detected in the isolates. These results show the need for more efficient wastewater treatment and disposal in order to prevent the release of virulent and antibiotic resistant Enterococci species and safeguard public health.

Keywords: antibiogram, enterococci, gentamicin, vancomycin, virulence signatures

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Authors: C. Hall, J. Ramos, V. Ramasamy

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Hydrocarbon-based fuel vehicles are a major contributor to air pollution due to harmful emissions produced, leading to a demand for cleaner fuel types. A leader in this pursuit is hydrogen, with its application in vehicles producing zero harmful emissions and the only by-product being water. To compete with the performance of conventional vehicles, hydrogen gas must be stored on-board of vehicles in cylinders at high pressures (35–70 MPa) and have a short refueling duration (approximately 3 mins). However, the fast-filling of hydrogen cylinders causes a significant rise in temperature due to the combination of the negative Joule-Thompson effect and the compression of the gas. This can lead to structural failure and therefore, a maximum allowable internal temperature of 85°C has been imposed by the International Standards Organization. The technological solution to tackle the issue of rapid temperature rise during the refueling process is to decrease the temperature of the gas entering the cylinder. Pre-cooling of the gas uses a heat exchanger and requires energy for its operation. Thus, it is imperative to determine the least amount of energy input that is required to lower the gas temperature for cost savings. A validated universal thermodynamic model is used to identify an energy-efficient pre-cooling strategy. The model requires negligible computational time and is applied to previously validated experimental cases to optimize pre-cooling requirements. The pre-cooling characteristics include the location within the refueling timeline and its duration. A constant pressure-ramp rate is imposed to eliminate the effects of rapid changes in mass flow rate. A pre-cooled gas temperature of -40°C is applied, which is the lowest allowable temperature. The heat exchanger is assumed to be ideal with no energy losses. The refueling of the cylinders is modeled with the pre-cooling split in ten percent time intervals. Furthermore, varying burst durations are applied in both the early and late stages of the refueling procedure. The model shows that pre-cooling in the later stages of the refuelling process is more energy-efficient than early pre-cooling. In addition, the efficiency of pre-cooling towards the end of the refueling process is independent of the pressure profile at the inlet. This leads to the hypothesis that pre-cooled gas should be applied as late as possible in the refueling timeline and at very low temperatures. The model had shown a 31% reduction in energy demand whilst achieving the same final gas temperature for a refueling scenario when pre-cooling was applied towards the end of the process. The identification of the most energy-efficient refueling approaches whilst adhering to the safety guidelines is imperative to reducing the operating cost of hydrogen refueling stations. Heat exchangers are energy-intensive and thus, reducing the energy requirement would lead to cost reduction. This investigation shows that pre-cooling should be applied as late as possible and for short durations.

Keywords: cylinder, hydrogen, pre-cooling, refueling, thermodynamic model

Procedia PDF Downloads 96

Authors: Aminul Haque, Quazi Zahangir Hossain, Dilshad Sharmin Chowdhury

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The human migration is getting growing concern around the world, and recurrent disasters and climate change impact have great influence on migration. Bangladesh is one of the disaster prone countries that/and has greater susceptibility to stress migration by recurrent disasters and climate change. The study was conducted to investigate the factors that have a strong influence on current migration and changing pattern of life and livelihood means of the southwest coastal part of Bangladesh. Moreover, the study also revealed a strong relationship between disasters and migration and appropriate policy concern. To explore this relation, both qualitative and quantitative methods were applied to a questionnaire survey at household level and simple random sampling technique used in the sampling process along with different secondary data sources for understanding policy concern and practices. The study explores the most influential driver of migration and its relationship with social, economic and environmental drivers. The study denotes that, the environmental driver has a greater effect on the intention of permanent migration (t=1.481, p-value=0.000) at the 1 percent significance level. The significant number of respondents denotes that abrupt pattern of cyclone, flood, salinity intrusion and rainfall are the most significant environmental driver to make a decision on permanent migration. The study also found that the temporary migration pattern has 2-fold increased compared to last ten (10) years. It also appears from the study that environmental factors have a great implication on the changing pattern of the occupation of the study area and it has reported that about 76% of the respondent now in the changing modality of livelihood compare to their traditional practices. The study bares that the migration has foremost impact on children and women by increasing hardship and creating critical social security. The exposure-route of permanent migration is not smooth indeed, these migrations creating urban and conflict in Chittagong hill tracks of Bangladesh. The study denotes that there is not any safeguard of the stress migrant on existing policy and not have any measures for safe migration and resettlement rather considering the emergency response and shelter. The majority of (98%) people believes that migration is not to be the adoption strategies, but contrary to this young group of respondent believes that safe migration could be the adaptation strategy which could bring a positive result compare to the other resilience strategies. On the other hand, the significant number of respondents uttered that appropriate policy measure could be an adaptation strategy for being the formation of a resilient community and reduce the migration by meaningful livelihood options with appropriate protection measure.

Keywords: environmental driver, livelihood, migration, resilience

Procedia PDF Downloads 264

Authors: Sergey N. Ermoliev, Margarita A. Belousova, Aida D. Goncharenko

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Application of the diagnostic complex of highly informative functional methods (electromyography, reodentography, laser Doppler flowmetry, reoperiodontography, vital computer capillaroscopy, optical tissue oximetry, laser fluorescence diagnosis) allows to perform a multifactorial analysis of the dental status and to prescribe complex etiopathogenetic treatment. Introduction. It is necessary to create a complex of innovative highly informative and safe functional diagnostic methods for improvement of the quality of patient treatment by the early detection of stomatologic diseases. The purpose of the present study was to investigate the etiology and pathogenesis of functional disorders identified in the pathology of hard tissue, dental pulp, periodontal, oral mucosa and chewing function, and the creation of new approaches to the diagnosis of dental diseases. Material and methods. 172 patients were examined. Density of hard tissues of the teeth and jaw bone was studied by intraoral ultrasonic densitometry (USD). Electromyographic activity of masticatory muscles was assessed by electromyography (EMG). Functional state of dental pulp vessels assessed by reodentography (RDG) and laser Doppler flowmetry (LDF). Reoperiodontography method (RPG) studied regional blood flow in the periodontal tissues. Microcirculatory vascular periodontal studied by vital computer capillaroscopy (VCC) and laser Doppler flowmetry (LDF). The metabolic level of the mucous membrane was determined by optical tissue oximetry (OTO) and laser fluorescence diagnosis (LFD). Results and discussion. The results obtained revealed changes in mineral density of hard tissues of the teeth and jaw bone, the bioelectric activity of masticatory muscles, regional blood flow and microcirculation in the dental pulp and periodontal tissues. LDF and OTO methods estimated fluctuations of saturation level and oxygen transport in microvasculature of periodontal tissues. With LFD identified changes in the concentration of enzymes (nicotinamide, flavins, lipofuscin, porphyrins) involved in metabolic processes Conclusion. Our preliminary results confirmed feasibility and safety the of intraoral ultrasound densitometry technique in the density of bone tissue of periodontium. Conclusion. Application of the diagnostic complex of above mentioned highly informative functional methods allows to perform a multifactorial analysis of the dental status and to prescribe complex etiopathogenetic treatment.

Keywords: electromyography (EMG), reodentography (RDG), laser Doppler flowmetry (LDF), reoperiodontography method (RPG), vital computer capillaroscopy (VCC), optical tissue oximetry (OTO), laser fluorescence diagnosis (LFD)

Procedia PDF Downloads 280

Authors: Silvia Di Turi, Nicolandrea Calabrese, Francesca Caffari, Giulia Centi, Francesca Margiotta, Giovanni Murano, Laura Ronchetti, Paolo Signoretti, Lisa Volpe, Domenico Palladino

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Recent European policies have been set ambitious targets aimed at significantly reducing CO2 emissions by 2030, with a long-term vision of transforming existing buildings into Zero-Emissions Buildings (ZEmB) by 2050. This vision represents a key point for the energy transition as the whole building stock currently accounts for 36% of total energy consumption across the Europe, mainly due to their poor energy performance. The challenge towards Zero-Emissions Buildings is particularly felt in Italy, where a significant number of buildings with historical significance or situated within protected/constrained areas can be found. Furthermore, an estimated 70% of the national building stock are built before 1976, indicating a widespread issue of poor energy performance. Addressing the energy ineƯiciency of these buildings is crucial to refining a comprehensive energy renovation approach aimed at facilitating their energy transition. In this framework the current study focuses on analysing a challenging complex of buildings to be totally restored through significant energy renovation interventions. The goal is to recover these disused buildings situated in a significant archaeological zone of Rome, contributing to the restoration and reintegration of this historically valuable site, while also oƯering insights useful for achieving zeroemission requirements for buildings within such contexts. In pursuit of meeting the stringent zero-emission requirements, a comprehensive study was carried out to assess the complex of buildings, envisioning substantial renovation measures on building envelope and plant systems and incorporating renewable energy system solutions, always respecting and preserving the historic site. An energy audit of the complex of buildings was performed to define the actual energy consumption for each energy service by adopting the hourly calculation methods. Subsequently, significant energy renovation interventions on both building envelope and mechanical systems have been examined respecting the historical value and preservation of site. These retrofit strategies have been investigated with threefold aims: 1) to recover the existing buildings ensuring the energy eƯiciency of the whole complex of buildings, 2) to explore which solutions have allowed achieving and facilitating the ZEmB status, 3) to balance the energy transition requirements with the sustainable aspect in order to preserve the historic value of the buildings and site. This study has pointed out the potentiality and the technical challenges associated with implementing renovation solutions for such buildings, representing one of the first attempt towards realizing this ambitious target for this type of building.

Keywords: energy conservation and transition, complex of buildings in historic site, zero-emission buildings, energy efficiency recovery

Procedia PDF Downloads 76

Authors: Anne-Margré C. Vink

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Background: Food-related allergies and intolerances are frequently occurring in dogs. Diagnosis and monitoring according to ‘Golden Standard’ of elimination efficiency are time-consuming, expensive, and requires expert clinical setting. In order to facilitate rapid and robust, quantitative testing of intolerance, and determining the individual offending foods, a serological test is implicated. Method: As we developed Medisynx IgG Human Screening Test ELISA before and the dog’s immune system is most similar to humans, we were able to develop Medisynx IgG Dog Screening Test ELISA as well. In this study, 47 dogs suffering from Canine Atopic Dermatitis (CAD) and several secondary induced reactions were included to participate in serological Medisynx IgG Dog Screening Test ELISA (within < 0,02 % SD). Results were expressed as titers relative to the standard OD readings to diagnose alimentary induced diseases and monitoring the efficacy of an individual eliminating diet in dogs. Split sample analysis was performed by independently sending 2 times 3 ml serum under two unique codes. Results: The veterinarian monitored these dogs to check dog’ results at least at 3, 7, 21, 49, 70 days and after period of 6 and 12 months on an individual negative diet and a positive challenge (retrospectively) at 6 months. Data of each dog were recorded in a screening form and reported that a complete recovery of all clinical manifestations was observed at or less than 70 days (between 50 and 70 days) in the majority of dogs(44 out of 47 dogs =93.6%). Conclusion: Challenge results showed a significant result of 100% in specificity as well as 100% positive predicted value. On the other hand, sensitivity was 95,7% and negative predictive value was 95,7%. In conclusion, an individual diet based on IgG ELISA in dogs provides a significant improvement of atopic dermatitis and pruritus including all other non-specific defined allergic skin reactions as erythema, itching, biting and gnawing at toes, as well as to several secondary manifestations like chronic diarrhoea, chronic constipation, otitis media, obesity, laziness or inactive behaviour, pain and muscular stiffness causing a movement disorders, excessive lacrimation, hyper behaviour, nervous behaviour and not possible to stay alone at home, anxiety, biting and aggressive behaviour and disobedience behaviour. Furthermore, we conclude that a relatively more severe systemic candidiasis, as shown by relatively higher titer (class 3 and 4 IgG reactions to Candida albicans), influence the duration of recovery from clinical manifestations in affected dogs. These findings are consistent with our preliminary human clinical studies.

Keywords: allergy, canine atopic dermatitis, CAD, food allergens, IgG-ELISA, food-incompatibility

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Authors: Nima Samie, Sekaran Muniandy, Zahurin Mohamed, M. S. Kanthimathi

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Although number of indole containing compounds have been reported to have anticancer properties in vitro but only a few of them show potential as anticancer compounds in vivo. The current study was to evaluate the mechanism of cytotoxicity of selected indolic compound in vivo and in vitro. In this context, we determined the potency of the compound in the induction of apoptosis, cell cycle arrest, and cytoskeleton rearrangement. HT-29, WiDr, CCD-18Co, human monocyte/macrophage CRL-9855, and B lymphocyte CCL-156 cell lines were used to determine the IC50 of the compound using the MTT assay. Analysis of apoptosis was carried out using immunofluorescence, acridine orange/ propidium iodide double staining, Annexin-V-FITC assay, evaluation of the translocation of NF-kB, oxygen radical antioxidant capacity, quenching of reactive oxygen species content, measurement of LDH release, caspase-3/-7, -8 and -9 assays and western blotting. The cell cycle arrest was examined using flowcytometry and gene expression was assessed using qPCR array. Results displayed a potent suppressive effect on HT-29 and WiDr after 24 h of treatment with IC50 value of 2.52±0.34 µg/ml and 2.13±0.65 µg/ml respectively. This cytotoxic effect on normal, monocyte/macrophage and B-cells was insignificant. Dipping in the mitochondrial membrane potential and increased release of cytochrome c from the mitochondria indicated induction of the intrinsic apoptosis pathway by the compound. Activation of this pathway was further evidenced by significant activation of caspase-9 and 3/7. The compound was also shown to activate the extrinsic pathways of apoptosis via activation of caspase-8 which is linked to the suppression of NF-kB translocation to the nucleus. Cell cycle arrest in the G1 phase and up-regulation of glutathione reductase, based on excessive ROS production were also observed. These findings were further investigated for inhibitory efficiency of the compound on colonic aberrant crypt foci in male rats. Rats were divided in to 5 groups: vehicle, cancer control, positive control groups and the groups treated with 25 and 50 mg/kg of compounds for 10 weeks. Administration of compound suppressed total colonic ACF formation up to 73.4%. The results also showed that treatment with the compound significantly reduced the level of malondialdehyde while increasing superoxide dismutase and catalase activities. Furthermore, the down-regulation of PCNA and Bcl2 and the up-regulation of Bax was confirmed by immunohistochemical staining. The outcome of this study suggest sthat the indolic compound is a potent anti-cancer agent against colon cancer and can be further evaluated by animal trial.

Keywords: indolic compound, chemoprevention, crypt, azoxymethane, colon cancer

Procedia PDF Downloads 348

Authors: Jurriaan Gillissen

Abstract:

This work is concerned with stabilizing the numerical integration of the Navier-Stokes equation (NSE), backwards in time. Applications involve the detection of sources of, e.g., sound, heat, and pollutants. Stable reverse numerical integration of parabolic differential equations is also relevant for image de-blurring. While the literature addresses the reverse integration problem of the advection-diffusion equation, the problem of numerical reverse integration of the NSE has, to our knowledge, not yet been addressed. Owing to the presence of viscosity, the NSE is irreversible, i.e., when going backwards in time, the fluid behaves, as if it had a negative viscosity. As an effect, perturbations from the perfect solution, due to round off errors or discretization errors, grow exponentially in time, and reverse integration of the NSE is inherently unstable, regardless of using an implicit time integration scheme. Consequently, some sort of filtering is required, in order to achieve a stable, numerical, reversed integration. The challenge is to find a filter with a minimal adverse affect on the accuracy of the reversed integration. In the present work, we explore an adjoint gradient method (AGM) to achieve this goal, and we apply this technique to two-dimensional (2D), decaying turbulence. The AGM solves for the initial velocity field u0 at t = 0, that, when integrated forward in time, produces a final velocity field u1 at t = 1, that is as close as is feasibly possible to some specified target field v1. The initial field u0 defines a minimum of a cost-functional J, that measures the distance between u1 and v1. In the minimization procedure, the u0 is updated iteratively along the gradient of J w.r.t. u0, where the gradient is obtained by transporting J backwards in time from t = 1 to t = 0, using the adjoint NSE. The AGM thus effectively replaces the backward integration by multiple forward and backward adjoint integrations. Since the viscosity is negative in the adjoint NSE, each step of the AGM is numerically stable. Nevertheless, when applied to turbulence, the AGM develops instabilities, which limit the backward integration to small times. This is due to the exponential divergence of phase space trajectories in turbulent flow, which produces a multitude of local minima in J, when the integration time is large. As an effect, the AGM may select unphysical, noisy initial conditions. In order to improve this situation, we propose two remedies. First, we replace the integration by a sequence of smaller integrations, i.e., we divide the integration time into segments, where in each segment the target field v1 is taken as the initial field u0 from the previous segment. Second, we add an additional term (regularizer) to J, which is proportional to a high-order Laplacian of u0, and which dampens the gradients of u0. We show that suitable values for the segment size and for the regularizer, allow a stable reverse integration of 2D decaying turbulence, with accurate results for more then O(10) turbulent, integral time scales.

Keywords: time reversed integration, parabolic differential equations, adjoint gradient method, two dimensional turbulence

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Authors: David Oluigbo, Erik Hemberg, Nathan Shwatal, Wenqi Ding, Yin Yuan, Susanna Mierau

Abstract:

Introduction: Calcium imaging is an established technique in neuroscience research for detecting activity in neural networks. Bursts of action potentials in neurons lead to transient increases in intracellular calcium visualized with fluorescent indicators. Manual identification of cell bodies and their contours by experts typically takes 10-20 minutes per calcium imaging recording. Our aim, therefore, was to design an automated pipeline to facilitate and optimize calcium imaging data analysis. Our pipeline aims to accelerate cell body and contour identification and production of graphical representations reflecting changes in neuronal calcium-based fluorescence. Methods: We created a Python-based pipeline that uses OpenCV (a computer vision Python package) to accurately (1) detect neuron contours, (2) extract the mean fluorescence within the contour, and (3) identify transient changes in the fluorescence due to neuronal activity. The pipeline consisted of 3 Python scripts that could both be easily accessed through a Python Jupyter notebook. In total, we tested this pipeline on ten separate calcium imaging datasets from murine dissociate cortical cultures. We next compared our automated pipeline outputs with the outputs of manually labeled data for neuronal cell location and corresponding fluorescent times series generated by an expert neuroscientist. Results: Our results show that our automated pipeline efficiently pinpoints neuronal cell body location and neuronal contours and provides a graphical representation of neural network metrics accurately reflecting changes in neuronal calcium-based fluorescence. The pipeline detected the shape, area, and location of most neuronal cell body contours by using binary thresholding and grayscale image conversion to allow computer vision to better distinguish between cells and non-cells. Its results were also comparable to manually analyzed results but with significantly reduced result acquisition times of 2-5 minutes per recording versus 10-20 minutes per recording. Based on these findings, our next step is to precisely measure the specificity and sensitivity of the automated pipeline’s cell body and contour detection to extract more robust neural network metrics and dynamics. Conclusion: Our Python-based pipeline performed automated computer vision-based analysis of calcium image recordings from neuronal cell bodies in neuronal cell cultures. Our new goal is to improve cell body and contour detection to produce more robust, accurate neural network metrics and dynamic graphs.

Keywords: calcium imaging, computer vision, neural activity, neural networks

Procedia PDF Downloads 82

Authors: Éva Pintér, Péter Bagó, Nikolett Deutsch, Miklós Hetényi

Abstract:

The process of digital transformation has a profound influence on all sectors of the worldwide economy and the business environment. The influence of blockchain technology can be observed in the digital economy and e-government, rendering it an essential element of a nation's growth strategy. The banking industry is experiencing significant expansion and development of financial technology firms. Utilizing developing technologies such as artificial intelligence (AI), machine learning (ML), and big data (BD), these entrants are offering more streamlined financial solutions, promptly addressing client demands, and presenting a challenge to incumbent institutions. The advantages of digital transformation are evident in the corporate realm, and firms that resist its adoption put their survival at risk. The advent of digital technologies has revolutionized the business environment, streamlining processes and creating opportunities for enhanced communication and collaboration. Thanks to the aid of digital technologies, businesses can now swiftly and effortlessly retrieve vast quantities of information, all the while accelerating the process of creating new and improved products and services. Big data analytics is generally recognized as a transformative force in business, considered the fourth paradigm of science, and seen as the next frontier for innovation, competition, and productivity. Big data, an emerging technology that is shaping the future of the banking sector, offers numerous advantages to banks. It enables them to effectively track consumer behavior and make informed decisions, thereby enhancing their operational efficiency. Banks may embrace big data technologies to promptly and efficiently identify fraud, as well as gain insights into client preferences, which can then be leveraged to create better-tailored products and services. Moreover, the utilization of big data technology empowers banks to develop more intelligent and streamlined models for accurately recognizing and focusing on the suitable clientele with pertinent offers. There is a scarcity of research on big data analytics in the banking industry, with the majority of existing studies only examining the advantages and prospects associated with big data. Although big data technologies are crucial, there is a dearth of empirical evidence about the role of big data analytics (BDA) capabilities in bank performance. This research addresses a gap in the existing literature by introducing a model that combines the resource-based view (RBV), the technical organization environment framework (TOE), and dynamic capability theory (DC). This study investigates the influence of Big Data Analytics (BDA) utilization on the performance of market and risk management. This is supported by a comparative examination of Hungarian mobile banking services.

Keywords: big data, digital transformation, dynamic capabilities, mobile banking

Procedia PDF Downloads 64

Authors: Jakub Stelina, Janina Ciechanowicz-McLean

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Fifty years of existence and development of international environmental law brought a deep disappointment with efficiency and effectiveness of traditional command and control mechanisms of environmental regulation. Agenda 21 agreed during the first Earth Summit in Rio de Janeiro 1992 was one of the first international documents, which explicitly underlined the importance of public participation in environmental protection. This participation includes also the initiatives undertaken by business corporations in the form of private environmental standards setting. Twenty years later during the Rio 20+ Earth Summit the private sector obligations undertaken during the negotiations have proven to be at least as important as the ones undertaken by the governments. The private sector has taken the leading role in environmental standard setting. Among the research methods used in the article two are crucial in the analysis. The comparative analysis of law is the instrument used in the article to analyse the practice of states and private business companies in the field of sustainable development. The article uses economic analysis of law to estimate the costs and benefits of Corporate Social Responsibility Projects in the field of environmental protection. The study is based on the four premises. First is the role of social dialogue, which is crucial for both Corporate Social Responsibility and modern environmental protection regulation. The Aarhus Convention creates a procedural environmental human right to participate in administrative procedures of law setting and environmental decisions making. The public participation in environmental impact assessment is nowadays a universal standard. Second argument is about the role of precaution as a principle of modern environmental regulation. This principle can be observed both in governmental regulatory undertakings and also private initiatives within the Corporate Social Responsibility environmental projects. Even in the jurisdictions which are relatively reluctant to use the principle of preventive action in environmental regulation, the companies often use this standard in their own private business standard setting initiatives. This is often due to the fact that soft law standards are used as the basis for private Corporate Social Responsibility regulatory initiatives. Third premise is about the role of ecological education in environmental protection. Many soft law instruments underline the importance of environmental education. Governments use environmental education only to the limited extent due to the costs of such projects and problems with effects assessment. Corporate Social Responsibility uses various means of ecological education as the basis of their actions in the field of environmental protection. Last but not least Sustainable development is a goal of both legal protection of the environment, and economic instruments of companies development. Modern environmental protection law uses to the increasing extent the Corporate Social Responsibility. This may be the consequence of the limits of hard law regulation. Corporate Social Responsibility is nowadays not only adapting to soft law regulation of environmental protection but also creates such standards by itself, showing new direction for development of international environmental law. Corporate Social Responsibility in environmental protection can be good investment in future development of the company.

Keywords: corporate social responsibility, environmental CSR, environmental justice, stakeholders dialogue

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Authors: Sylvia Mac

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This ethnographic case study examines disaster capitalism, neoliberal market-based school reforms, and disability through the lens of Disability Studies in Education. More specifically, it explores neoliberalism and special education at a small, urban charter school in a large city in California and the (re)production of social inequality. The study uses Sociology of Special Education to examine the ways in which special education is used to sort and stratify disabled students. At a time when rhetoric surrounding public schools is framed in catastrophic and dismal language in order to justify the privatization of public education, small urban charter schools must be examined to learn if they are living up to their promise or acting as another way to maintain economic and racial segregation. The study concludes that neoliberal contexts threaten successful inclusive education and normalize poor, disabled students’ continued low achievement and poor post-secondary outcomes. This ethnographic case study took place at a small urban charter school in a large city in California. Participants included three special education students, the special education teacher, the special education assistant, a regular education teacher, and the two founders and charter writers. The school claimed to have a push-in model of special education where all special education students were fully included in the general education classroom. Although presented as fully inclusive, some special education students also attended a pull-out class called Study Skills. The study found that inclusion and neoliberalism are differing ideologies that cannot co-exist. Successful inclusive environments cannot thrive while under the influences of neoliberal education policies such as efficiency and cost-cutting. Additionally, the push for students to join the global knowledge economy means that more and more low attainers are further marginalized and kept in poverty. At this school, neoliberal ideology eclipsed the promise of inclusive education for special education students. This case study has shown the need for inclusive education to be interrogated through lenses that consider macro factors, such as neoliberal ideology in public education, as well as the emerging global knowledge economy and increasing income inequality. Barriers to inclusion inside the school, such as teachers’ attitudes, teacher preparedness, and school infrastructure paint only part of the picture. Inclusive education is also threatened by neoliberal ideology that shifts the responsibility from the state to the individual. This ideology is dangerous because it reifies the stereotypes of disabled students as lazy, needs drains on already dwindling budgets. If these stereotypes persist, inclusive education will have a difficult time succeeding. In order to more fully examine the ways in which inclusive education can become truly emancipatory, we need more analysis on the relationship between neoliberalism, disability, and special education.

Keywords: case study, disaster capitalism, inclusive education, neoliberalism

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Authors: Zuyong Chen, Jianghao Wu, Yanlai Zhang

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Flapping-wing micro aerial vehicle (FMAV) is a new type of aircraft by mimicking the flying behavior to that of small birds or insects. Comparing to the traditional fixed wing or rotor-type aircraft, FMAV only needs to control the motion of flapping wings, by changing the size and direction of lift to control the flight attitude. Therefore, its transmission system should be designed very compact. Lightweight design can effectively extend its endurance time, while engineering experience alone is difficult to simultaneously meet the requirements of FMAV for structural strength and quality. Current researches still lack the guidance of considering nonlinear factors of 3D printing material when carrying out topology optimization, especially for the tiny FMAV transmission system. The coupling of non-linear material properties and non-linear contact behaviors of FMAV transmission system is a great challenge to the reliability of the topology optimization result. In this paper, topology optimization design based on FEA solver package Altair Optistruct for the transmission system of FMAV manufactured by 3D Printing was carried out. Firstly, the isotropic constitutive behavior of the Ultraviolet (UV) Cureable Resin used to fabricate the structure of FMAV was evaluated and confirmed through tensile test. Secondly, a numerical computation model describing the mechanical behavior of FMAV transmission structure was established and verified by experiments. Then topology optimization modeling method considering non-linear factors were presented, and optimization results were verified by dynamic simulation and experiments. Finally, detail discussions of different load status and constraints were carried out to explore the leading factors affecting the optimization results. The contributions drawn from this article helpful for guiding the lightweight design of FMAV are summarizing as follow; first, a dynamic simulation modeling method used to obtain the load status is presented. Second, verification method of optimized results considering non-linear factors is introduced. Third, based on or can achieve a better weight reduction effect and improve the computational efficiency rather than taking multi-states into account. Fourth, basing on makes for improving the ability to resist bending deformation. Fifth, constraint of displacement helps to improve the structural stiffness of optimized result. Results and engineering guidance in this paper may shed lights on the structural optimization and light-weight design for future advanced FMAV.

Keywords: flapping-wing micro aerial vehicle, 3d printing, topology optimization, finite element analysis, experiment

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Authors: Parminder Kaur Heer, Alexei Lapkin

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Due to global challenges of increased competition and demand for more sustainable products/processes, there is a rising pressure on the industry to develop innovative processes. Through Process Intensification (PI) the existing and new processes may be able to attain higher efficiency. However, very few PI options are generally considered. This is because processes are typically analysed at a unit operation level, thus limiting the search space for potential process options. PI performed at more detailed levels of a process can increase the size of the search space. The different levels at which PI can be achieved is unit operations, functional and phenomena level. Physical/chemical phenomena form the lowest level of aggregation and thus, are expected to give the highest impact because all the intensification options can be described by their enhancement. The objective of the current work is thus, generation of numerous process alternatives based on phenomena, and development of their corresponding computer aided models. The methodology comprises: a) automated generation of process options, and b) automated generation of process models. The process under investigation is disintegrated into functions viz. reaction, separation etc., and these functions are further broken down into the phenomena required to perform them. E.g., separation may be performed via vapour-liquid or liquid-liquid equilibrium. A list of phenomena for the process is formed and new phenomena, which can overcome the difficulties/drawbacks of the current process or can enhance the effectiveness of the process, are added to the list. For instance, catalyst separation issue can be handled by using solid catalysts; the corresponding phenomena are identified and added. The phenomena are then combined to generate all possible combinations. However, not all combinations make sense and, hence, screening is carried out to discard the combinations that are meaningless. For example, phase change phenomena need the co-presence of the energy transfer phenomena. Feasible combinations of phenomena are then assigned to the functions they execute. A combination may accomplish a single or multiple functions, i.e. it might perform reaction or reaction with separation. The combinations are then allotted to the functions needed for the process. This creates a series of options for carrying out each function. Combination of these options for different functions in the process leads to the generation of superstructure of process options. These process options, which are formed by a list of phenomena for each function, are passed to the model generation algorithm in the form of binaries (1, 0). The algorithm gathers the active phenomena and couples them to generate the model. A series of models is generated for the functions, which are combined to get the process model. The most promising process options are then chosen subjected to a performance criterion, for example purity of product, or via a multi-objective Pareto optimisation. The methodology was applied to a two-step process and the best route was determined based on the higher product yield. The current methodology can identify, produce and evaluate process intensification options from which the optimal process can be determined. It can be applied to any chemical/biochemical process because of its generic nature.

Keywords: Phenomena, Process intensification, Process models , Process options

Procedia PDF Downloads 232