Search results for: optimal scheme

Authors: Lauren A. Bailey, Amber R. Childs, Nicola C. James, Murray I. Duncan, Alexander Winkler, Warren M. Potts

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Changes in behaviour and physiology are the most important responses of marine life to anthropogenic impacts such as climate change and over-fishing. Behavioural changes (such as a shift in distribution or changes in phenology) can ensure that a species remains in an environment suited for its optimal physiological performance. However, if marine life is unable to shift their distribution, they are reliant on physiological adaptation (either by broadening their metabolic curves to tolerate a range of stressors or by shifting their metabolic curves to maximize their performance at extreme stressors). However, since there are links between fish physiology and behaviour, changes to either of these traits may have reciprocal interactions. This paper reviews the current knowledge of the links between the behaviour and physiology of fishes, discusses these in the context of exploitation and climate change, and makes recommendations for future research needs. The review revealed that our understanding of the links between fish behaviour and physiology is rudimentary. However, both are hypothesized to be linked to stress responses along the hypothalamic pituitary axis. The link between physiological capacity and behaviour is particularly important as both determine the response of an individual to a changing climate and are under selection by fisheries. While it appears that all types of capture fisheries are likely to reduce the adaptive potential of fished populations to climate stressors, angling, which is primarily associated with recreational fishing, may induce fission of natural populations by removing individuals with bold behavioural traits and potentially the physiological traits required to facilitate behavioural change. Future research should focus on assessing how the links between physiological capacity and behaviour influence catchability, the response to climate change drivers, and post-release recovery. The plasticity of phenotypic traits should be examined under a range of stressors of differing intensity in several species and life history stages. Future studies should also assess plasticity (fission or fusion) in the phenotypic structuring of social hierarchy and how this influences habitat selection. Ultimately, to fully understand how physiology is influenced by the selective processes driven by fisheries, long-term monitoring of the physiological and behavioural structure of fished populations, their fitness, and catch rates are required.

Keywords: climate change, metabolic shifts, over-fishing, phenotypic plasticity, stress response

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Authors: Suleyman Ogul Ertugrul, Mustafa Turgut, Serkan Inandı, Mustafa Gorkem Coban, Mustafa Kıgılı, Ali Mert, Oguzhan Kesmez, Murat Ozancı, Caglar Uyulan

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In high-performance automotive engineering, the realistic simulation of suspension systems is crucial for enhancing vehicle dynamics and handling. This study focuses on the double wishbone suspension system, prevalent in racing vehicles due to its superior control and stability characteristics. Utilizing MATLAB and Adams Car simulation software, we conduct a comprehensive analysis of displacement behaviors and damper sizing under various dynamic conditions. The initial phase involves using MATLAB to simulate the entire suspension system, allowing for the preliminary determination of damper size based on the system's response under simulated conditions. Following this, manual calculations of wheel loads are performed to assess the forces acting on the front and rear suspensions during scenarios such as braking, cornering, maximum vertical loads, and acceleration. Further dynamic force analysis is carried out using MATLAB Simulink, focusing on the interactions between suspension components during key movements such as bumps and rebounds. This simulation helps in formulating precise force equations and in calculating the stiffness of the suspension springs. To enhance the accuracy of our findings, we focus on a detailed kinematic and dynamic analysis. This includes the creation of kinematic loops, derivation of relevant equations, and computation of Jacobian matrices to accurately determine damper travel and compression metrics. The calculated spring stiffness is crucial in selecting appropriate springs to ensure optimal suspension performance. To validate and refine our results, we replicate the analyses using the Adams Car software, renowned for its detailed handling of vehicular dynamics. The goal is to achieve a robust, reliable suspension setup that maximizes performance under the extreme conditions encountered in racing scenarios. This study exemplifies the integration of theoretical mechanics with advanced simulation tools to achieve a high-performance suspension setup that can significantly improve race car performance, providing a methodology that can be adapted for different types of racing vehicles.

Keywords: FSAE, suspension system, Adams Car, kinematic

Procedia PDF Downloads 51

Authors: Da Tao, Mingfu Qin, Wenkai Li, Tieyan Wang

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While the use of electronic personal health portals has gained increasing popularity in the healthcare industry, users usually experience difficulty in comprehending and correctly responding to personal health information, partly due to inappropriate or poor presentation of the information. The way personal health information is visualized may affect how users perceive and assess their personal health information. This study was conducted to examine the effects of information visualization format and visualization mode on the comprehension and perceptions of personal health information among personal health information users with eye tracking techniques. A two-factor within-subjects experimental design was employed, where participants were instructed to complete a series of personal health information comprehension tasks under varied types of visualization mode (i.e., whether the information visualization is static or dynamic) and three visualization formats (i.e., bar graph, instrument-like graph, and text-only format). Data on a set of measures, including comprehension performance, perceptions, and eye movement indicators, were collected during the task completion in the experiment. Repeated measure analysis of variance analyses (RM-ANOVAs) was used for data analysis. The results showed that while the visualization format yielded no effects on comprehension performance, it significantly affected users’ perceptions (such as perceived ease of use and satisfaction). The two graphic visualizations yielded significantly higher favorable scores on subjective evaluations than that of the text format. While visualization mode showed no effects on users’ perception measures, it significantly affected users' comprehension performance in that dynamic visualization significantly reduced users' information search time. Both visualization format and visualization mode had significant main effects on eye movement behaviors, and their interaction effects were also significant. While the bar graph format and text format had similar time to first fixation across dynamic and static visualizations, instrument-like graph format had a larger time to first fixation for dynamic visualization than for static visualization. The two graphic visualization formats yielded shorter total fixation duration compared with the text-only format, indicating their ability to improve information comprehension efficiency. The results suggest that dynamic visualization can improve efficiency in comprehending important health information, and graphic visualization formats were favored more by users. The findings are helpful in the underlying comprehension mechanism of visualized personal health information and provide important implications for optimal design and visualization of personal health information.

Keywords: eye tracking, information comprehension, personal health information, visualization

Procedia PDF Downloads 109

Authors: Soo Min Kim, Soo-Won Chae, Soung-Yon Kim, Haea Lee, Ju Yong Kang, Juneyong Lee, Seung-Ho Han

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Reverse total shoulder arthroplasty (RTSA) has become an effective treatment option for cuff tear arthropathy and massive, irreparable rotator cuff tears and indications for its use are expanding. Numerous methods for optimal fixation of the glenoid component have been suggested, such as inferior overhang, inferior tilt, to maximize initial fixation and prevent glenoid component loosening. The inferior tilt fixation of a glenoid component has been suggested, which is expected to decrease scapular notching and to improve the stability of a glenoid component fixation in reverse total shoulder arthroplasty. Inferior tilt fixation of the glenoid component has been suggested, which can improve stability and, because it provides the most uniform compressive forces and imparts the least amount of tensile forces and micromotion, reduce the likelihood of mechanical failure. Another study reported that glenoid component inferior tilt improved impingement-free range of motion as well as minimized the scapular notching. Several authors have shown that inferior tilt of a glenoid component reduces scapular notching. However, controversy still exists regarding its importance in the literature. In this study the influence of inferior tilt fixation on the primary stability of a glenoid component has been investigated. Finite element models were constructed from cadaveric scapulae and glenoid components were implanted with neutral and 10° inferior tilts. Most previous biomechanical studies regarding the effect of glenoid component inferior tilt used a solid rigid polyurethane foam or sawbones block, not cadaveric scapulae, to evaluate the stability of the RTSA. Relative micromotions at the bone-glenoid component interface, and the distribution of bone stresses under the glenoid component and around the screws were analyzed and compared between neutral and 10° inferior tilt groups. Contact area between bone and screws and cut surface area of the cancellous bone exposed after reaming of the glenoid have also been investigated because of the fact that cancellous and cortical bone thickness vary depending on the resection level of the inferior glenoid bone. The greater relative micromotion of the bone-glenoid component interface occurred in the 10° inferior tilt group than in the neutral tilt group, especially at the inferior area of the bone-glenoid component interface. Bone stresses under the glenoid component and around the screws were also higher in the 10° inferior tilt group than in the neutral tilt group, especially at the inferior third of the glenoid bone surface under the glenoid component and inferior scapula. Thus inferior tilt fixation of the glenoid component may adversely affect the primary stability and longevity of the reverse total shoulder arthroplasty.

Keywords: finite element analysis, glenoid component, inferior tilt, reverse total shoulder arthroplasty

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Authors: James Rate, Apostolos Pesiridis

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In this paper, the propulsion requirements required to achieve sustained hypersonic flight for commercial air transportation are evaluated. In addition, a design methodology is developed and used to determine the propulsive capabilities of both ramjet and scramjet engines. Twelve configurations are proposed for hypersonic flight using varying combinations of turbojet, turbofan, ramjet and scramjet engines. The optimal configuration was determined based on how well each of the configurations met the projected requirements for hypersonic commercial transport. The configurations were separated into four sub-configurations each comprising of three unique derivations. The first sub-configuration comprised four afterburning turbojets and either one or two ramjets idealised for Mach 5 cruise. The number of ramjets required was dependent on the thrust required to accelerate the vehicle from a speed where the turbojets cut out to Mach 5 cruise. The second comprised four afterburning turbojets and either one or two scramjets, similar to the first configuration. The third used four turbojets, one scramjet and one ramjet to aid acceleration from Mach 3 to Mach 5. The fourth configuration was the same as the third, but instead of turbojets, it implemented turbofan engines for the preliminary acceleration of the vehicle. From calculations which determined the fuel consumption at incremental Mach numbers this paper found that the ideal solution would require four turbojet engines and two Scramjet engines. The ideal mission profile was determined as being an 8000km sortie based on an averaging of popular long haul flights with strong business ties, which included Los Angeles to Tokyo, London to New York and Dubai to Beijing. This paper deemed that these routes would benefit from hypersonic transport links based on the previously mentioned factors. This paper has found that this configuration would be sufficient for the 8000km flight to be completed in approximately two and a half hours and would consume less fuel than Concord in doing so. However, this propulsion configuration still result in a greater fuel cost than a conventional passenger. In this regard, this investigation contributes towards the specification of the engine requirements throughout a mission profile for a hypersonic passenger vehicle. A number of assumptions have had to be made for this theoretical approach but the authors believe that this investigation lays the groundwork for appropriate framing of the propulsion requirements for sustained hypersonic flight for commercial air transportation. Despite this, it does serve as a crucial step in the development of the propulsion systems required for hypersonic commercial air transportation. This paper provides a methodology and a focus for the development of the propulsion systems that would be required for sustained hypersonic flight for commercial air transportation.

Keywords: hypersonic, ramjet, propulsion, Scramjet, Turbojet, turbofan

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Authors: Calister Wingang Makebe, Wilson Agwanande Ambindei, Zangue Steve Carly Desobgo, Abraham Billu, Emmanuel Jong Nso, P. Nisha

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Traditional liquid-state fermentation processes of Annona muricata L. juice can result in fluctuating product quality and quantity due to difficulties in control and scale up. This work describes a laboratory-scale batch fermentation process to produce a probiotic Annona muricata L. enzymatically extracted juice, which was modeled using the Doehlert design with independent extraction factors being incubation time, temperature, and enzyme concentration. It aimed at a better understanding of the traditional process as an initial step for future optimization. Annona muricata L. juice was fermented with L. acidophilus (NCDC 291) (LA), L. casei (NCDC 17) (LC), and a blend of LA and LC (LCA) for 72 h at 37 °C. Experimental data were fitted into mathematical models (Monod, Logistic and Luedeking and Piret models) using MATLAB software, to describe biomass growth, sugar utilization, and organic acid production. The optimal fermentation time was obtained based on cell viability, which was 24 h for LC and 36 h for LA and LCA. The model was particularly effective in estimating biomass growth, reducing sugar consumption, and lactic acid production. The values of the determination coefficient, R2, were 0.9946, 0.9913 and 0.9946, while the residual sum of square error, SSE, was 0.2876, 0.1738 and 0.1589 for LC, LA and LCA, respectively. The growth kinetic parameters included the maximum specific growth rate, µm, which was 0.2876 h-1, 0.1738 h-1 and 0.1589 h-1, as well as the substrate saturation, Ks, with 9.0680 g/L, 9.9337 g/L and 9.0709 g/L respectively for LC, LA and LCA. For the stoichiometric parameters, the yield of biomass based on utilized substrate (YXS) was 50.7932, 3.3940 and 61.0202, and the yield of product based on utilized substrate (YPS) was 2.4524, 0.2307 and 0.7415 for LC, LA, and LCA, respectively. In addition, the maintenance energy parameter (ms) was 0.0128, 0.0001 and 0.0004 with respect to LC, LA and LCA. With the kinetic model proposed by Luedeking and Piret for lactic acid production rate, the growth associated and non-growth associated coefficients were determined as 1.0028 and 0.0109, respectively. The model was demonstrated for batch growth of LA, LC, and LCA in Annona muricata L. juice. The present investigation validates the potential of Annona muricata L. based medium for heightened economical production of a probiotic medium.

Keywords: L. acidophilus, L. casei, fermentation, modelling, kinetics

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Authors: Yi-Fung Lin, Shiow-Ching Shun, Wen-Yu Hu

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Background: A skill mix model is regarded as one of the most effective methods of reducing nursing shortages, as well as easing nursing staff workloads and labor costs. Although this model shows several benefits for the health workforce, the relationship between the optimal model of skill mix and the patient mortality rate remains to be discovered. Objectives: This review aimed to explore the relationship between the skill mix model and patient mortality rate in acute care hospitals. Data Sources: A systematic search of the PubMed, Web of Science, Embase, and Cochrane Library databases and researchers retrieved studies published between January 1986 and March 2022. Review methods: Two independent reviewers screened the titles and abstracts based on selection criteria, extracted the data, and performed critical appraisals using the STROBE checklist of each included study. The studies focused on adult patients in acute care hospitals, and the skill mix model and patient mortality rate were included in the analysis. Results: Six included studies were conducted in the USA, Canada, Italy, Taiwan, and European countries (Belgium, England, Finland, Ireland, Spain, and Switzerland), including patients in medical, surgical, and intensive care units. There were both nurses and nursing assistants in their skill mix team. This main finding is that three studies (324,592 participants) show evidence of fewer mortality rates associated with hospitals with a higher percentage of registered nurse staff (range percentage of registered nurse staff 36.1%-100%), but three articles (1,122,270 participants) did not find the same result (range of percentage of registered nurse staff 46%-96%). However, based on appraisal findings, those showing a significant association all meet good quality standards, but only one-third of their counterparts. Conclusions: In light of the limited amount and quality of published research in this review, it is prudent to treat the findings with caution. Although the evidence is not insufficient certainty to draw conclusions about the relationship between nurse staffing level and patients' mortality, this review lights the direction of relevant studies in the future. The limitation of this article is the variation in skill mix models among countries and institutions, making it impossible to do a meta-analysis to compare them further.

Keywords: nurse staffing level, nursing assistants, mortality, skill mix

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Authors: Muhammad Tahir, Mushtaq Muhammad

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Capital structure is one of the key decisions taken by the financial managers. This study aims to investigate the factors influencing capital structure decision in Oil and Gas industry of Pakistan using secondary data from published annual reports of listed Oil and Gas Companies of Pakistan. This study covers the time-period from 2008-2014. Capital structure can be affected by profitability, firm size, growth opportunities, dividend payout, liquidity, business risk, and ownership structure. Panel data technique with Ordinary least square (OLS) regression model has been used to find the impact of set of explanatory variables on the capital structure using the Stata. OLS regression results suggest that dividend payout, firm size and government ownership have the most significant impact on financial leverage. Dividend payout and government ownership are found to have significant negative association with financial leverage however firm size indicated positive relationship with financial leverage. Other variables having significant link with financial leverage includes growth opportunities, liquidity and business risk. Results reveal significant positive association between growth opportunities and financial leverage whereas liquidity and business risk are negatively correlated with financial leverage. Profitability and managerial ownership exhibited insignificant relationship with financial leverage. This study contributes to existing Managerial Finance literature with certain managerial implications. Academically, this research study describes the factors affecting capital structure decision of Oil and Gas Companies in Pakistan and adds latest empirical evidence to existing financial literature in Pakistan. Researchers have studies capital structure in Pakistan in general and industry at specific, nevertheless still there is limited literature on this issue. This study will be an attempt to fill this gap in the academic literature. This study has practical implication on both firm level and individual investor/ lenders level. Results of this study can be useful for investors/ lenders in making investment and lending decisions. Further, results of this study can be useful for financial managers to frame optimal capital structure keeping in consideration the factors that can affect capital structure decision as revealed by this study. These results will help financial managers to decide whether to issue stock or issue debt for future investment projects.

Keywords: capital structure, multicollinearity, ordinary least square (OLS), panel data

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Authors: Iulia E. Falcan

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The transition of the European power sector towards a clean, renewable energy (RE) system faces the challenge of meeting power demand in times of low wind speed and low solar radiation, at a reasonable cost. This is likely to be achieved through a combination of 1) energy storage technologies, 2) development of the cross-border power grid, 3) installed overcapacity of RE and 4) dispatchable power sources – such as biomass. This paper uses NASA; derived hourly data on weather patterns of sixteen European countries for the past twenty-five years, and load data from the European Network of Transmission System Operators-Electricity (ENTSO-E), to develop a stochastic optimization model. This model aims to understand the synergies between the four classes of technologies mentioned above and to determine the optimal configuration of the energy technologies portfolio. While this issue has been addressed before, it was done so using deterministic models that extrapolated historic data on weather patterns and power demand, as well as ignoring the risk of an unbalanced grid-risk stemming from both the supply and the demand side. This paper aims to explicitly account for the inherent uncertainty in the energy system transition. It articulates two levels of uncertainty: a) the inherent uncertainty in future weather patterns and b) the uncertainty of fully meeting power demand. The first level of uncertainty is addressed by developing probability distributions for future weather data and thus expected power output from RE technologies, rather than known future power output. The latter level of uncertainty is operationalized by introducing a Conditional Value at Risk (CVaR) constraint in the portfolio optimization problem. By setting the risk threshold at different levels – 1%, 5% and 10%, important insights are revealed regarding the synergies of the different energy technologies, i.e., the circumstances under which they behave as either complements or substitutes to each other. The paper concludes that allowing for uncertainty in expected power output - rather than extrapolating historic data - paints a more realistic picture and reveals important departures from results of deterministic models. In addition, explicitly acknowledging the risk of an unbalanced grid - and assigning it different thresholds - reveals non-linearity in the cost functions of different technology portfolio configurations. This finding has significant implications for the design of the European energy mix.

Keywords: cross-border grid extension, energy storage technologies, energy system transition, stochastic portfolio optimization

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Authors: Ivan Maguire, Ciprian Briciu, Alan Barrett, Dara Kervick, Jens Ducrèe, Fiona Regan

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With the ever-increasing myriad of applications of which microfluidic devices are capable, reliable fluidic actuation development has remained fundamental to the success of these microfluidic platforms. There are a number of approaches which can be taken in order to integrate liquid actuation on microfluidic platforms, which can usually be split into two primary categories; active microvalves and passive microvalves. Active microvalves are microfluidic valves which require a physical parameter change by external, or separate interaction, for actuation to occur. Passive microvalves are microfluidic valves which don’t require external interaction for actuation due to the valve’s natural physical parameters, which can be overcome through sample interaction. The purpose of this paper is to illustrate how further improvements to past microvalve solutions can largely enhance systematic reliability and performance, with both novel active and passive microvalves demonstrated. Covered within this scope will be two alternative and novel microvalve solutions for centrifugal microfluidic platforms; a revamped pneumatic-dissolvable film active microvalve (PAM) strategy and a spray-on Sol-Gel based hydrophobic passive microvalve (HPM) approach. Both the PAM and the HPM mechanisms were demonstrated on a centrifugal microfluidic platform consisting of alternating layers of 1.5 mm poly(methyl methacrylate) (PMMA) (for reagent storage) sheets and ~150 μm pressure sensitive adhesive (PSA) (for microchannel fabrication) sheets. The PAM approach differs from previous SOLUBON™ dissolvable film methods by introducing a more reliable and predictable liquid delivery mechanism to microvalve site, thus significantly reducing premature activation. This approach has also shown excellent synchronicity when performed in a multiplexed form. The HPM method utilises a new spray-on and low curing temperature (70°C) sol-gel material. The resultant double layer coating comprises a PMMA adherent sol-gel as the bottom layer and an ultra hydrophobic silica nano-particles (SNPs) film as the top layer. The optimal coating was integrated to microfluidic channels with varying cross-sectional area for assessing microvalve burst frequencies consistency. It is hoped that these microvalving solutions, which can be easily added to centrifugal microfluidic platforms, will significantly improve automation reliability.

Keywords: centrifugal microfluidics, hydrophobic microvalves, lab-on-a-disc, pneumatic microvalves

Procedia PDF Downloads 188

Authors: M. Bučas, A. Skersonas, E. Ivanauskas, J. Lesutienė, N. Nika, G. Srėbalienė, E. Tiškus, J. Gintauskas, A.Šaškov, G. Martin

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Submerged vegetation enhances heterogeneity of sublittoral habitats; therefore, macrophyte stands are essential elements of aquatic ecosystems to maintain a diverse fish fauna. Fish-habitat relations have been extensively studied in streams and coastal waters, but in lakes and estuaries are still underestimated. The aim of this study is to assess temporal (diurnal and seasonal) patterns of fish juvenile assemblages associated with common submerged macrophyte habitats, which have significantly spread during the recent decade in the upper littoral part of the Curonian Lagoon. The assessment was performed by means of an upgraded pop-up net approach resulting in much precise sampling versus other techniques. The optimal number of samples (i.e., pop-up nets) required to cover>80% of the total number of fish species depended on the time of the day in both study sites: at least 7and 9 nets in the evening (18-24 pm) in the Southern and Northern study sites, respectively. In total, 14 fish species were recorded, where perch and roach dominated (respectively 48% and 24%). From multivariate analysis, water salinity and seasonality (temperature or sampling month) were primary factors determining fish assemblage composition. The southern littoral area, less affected by brackish water conditions, hosted a higher number of species (13) than in the Northern site (8). In the latter site, brackish water tolerant species (three-spined and nine-spined sticklebacks, spiny loach, roach, and round goby) were more abundant than in the Southern site. Perch and ruffe dominated in the Southern site. Spiny loach and nine-spined stickleback were more frequent in September, while ruffe, perch, and roach occurred more in July. The diel dynamics of the common species such as perch, roach, and ruffe followed the general pattern, but it was species specific and depended on the study site, habitat, and month. The species composition between macrophyte habitats did not significantly differ; however, it differed from the results obtained in 2005 at both study sites indicating the importance of expanded charophyte stands during the last decade in the littoral zone.

Keywords: diel dynamics, charophytes, pondweeds, herbivorous and benthivorous fishes, littoral, nursery habitat, shelter

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Authors: Hamed Kalhori, Lin Ye

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In this study, an inverse method was developed to reconstruct the magnitude and duration of impact forces exerted to a rectangular carbon fibre-epoxy composite honeycomb sandwich panel. The dynamic signals captured by Piezoelectric (PZT) sensors installed on the panel remotely from the impact locations were utilized to reconstruct the impact force generated by an instrumented hammer through an extended deconvolution approach. Two discretized forms of convolution integral are considered; the traditional one with an explicit transfer function and the modified one without an explicit transfer function. Deconvolution, usually applied to reconstruct the time history (e.g. magnitude) of a stochastic force at a defined location, is extended to identify both the location and magnitude of the impact force among a number of potential impact locations. It is assumed that a number of impact forces are simultaneously exerted to all potential locations, but the magnitude of all forces except one is zero, implicating that the impact occurs only at one location. The extended deconvolution is then applied to determine the magnitude as well as location (among the potential ones), incorporating the linear superposition of responses resulted from impact at each potential location. The problem can be categorized into under-determined (the number of sensors is less than that of impact locations), even-determined (the number of sensors equals that of impact locations), or over-determined (the number of sensors is greater than that of impact locations) cases. For an under-determined case, it comprises three potential impact locations and one PZT sensor for the rectangular carbon fibre-epoxy composite honeycomb sandwich panel. Assessments are conducted to evaluate the factors affecting the precision of the reconstructed force. Truncated Singular Value Decomposition (TSVD) and the Tikhonov regularization are independently chosen to regularize the problem to find the most suitable method for this system. The selection of optimal value of the regularization parameter is investigated through L-curve and Generalized Cross Validation (GCV) methods. In addition, the effect of different width of signal windows on the reconstructed force is examined. It is observed that the impact force generated by the instrumented impact hammer is sensitive to the impact locations of the structure, having a shape from a simple half-sine to a complicated one. The accuracy of the reconstructed impact force is evaluated using the correlation co-efficient between the reconstructed force and the actual one. Based on this criterion, it is concluded that the forces reconstructed by using the extended deconvolution without an explicit transfer function together with Tikhonov regularization match well with the actual forces in terms of magnitude and duration.

Keywords: honeycomb composite panel, deconvolution, impact localization, force reconstruction

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Authors: Clare Flood, Shareen Forbes

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Background: Type 1 diabetes mellitus (T1DM) is an autoimmune disorder affecting >400,000 people in the UK alone, with the global prevalence expected to double in the next decade. Islet transplant offers a minimally-invasive procedure with very low morbidity and almost no mortality, and is now as effective as whole pancreas transplant. The procedure was introduced to the UK in 2011 for patients with the most severe type 1 diabetes mellitus (T1DM) – those with unstable blood glucose, frequently occurring episodes of severe hypoglycemia and impaired awareness of hypoglycemia (IAH). Objectives: To evaluate the effectiveness of islet transplantation in improving glycemic control, reducing the burden of hypoglycemia and improving awareness of hypoglycemia through a single-centre cohort study at the Royal Infirmary of Edinburgh. Glycemic control and degree of hypoglycemic awareness will be determined and monitored pre- and post-transplantation to determine effectiveness of the procedure. Methods: A retrospective analysis of data collected over three years from the 16 patients who have undergone islet transplantation in Scotland. Glycated haemoglobin (HbA1c) was measured and continuous glucose monitoring systems (CGMS) were utilised to assess glycemic control, while Gold and Clarke score questionnaires tested IAH. Results: All patients had improved glycemic control following transplant, with optimal control seen visually at 3 months post-transplant. Glycemic control significantly improved, as illustrated by percentage time in hypoglycemia in the months following transplant (p=0.0211) and HbA1c (p=0.0426). Improved Clarke (p=0.0034) and Gold (p=0.0001) scores indicate improved glycemic awareness following transplant. Conclusion: While the small sample of islet transplant recipients at the Royal Infirmary of Edinburgh prevents definitive conclusions being drawn, it is indicated that through our retrospective, single-centre cohort study of 16 patients, islet transplant is capable of improving glycemic control, reducing the burden of hypoglycemia and IAH post-transplant. Data can be combined with similar trials at other centres to increase statistical power but from research in Edinburgh, it can be suggested that the minimally invasive procedure of islet transplantation offers selected patients with extremely unstable T1DM the incredible opportunity to regain control of their condition and improve their quality of life.

Keywords: diabetes, islet, transplant, CGMS

Procedia PDF Downloads 271

Authors: Tolulope Aremu

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This paper is based on the idea of using deep learning methodology for optimizing production yield by tuning a few key process parameters in a manufacturing environment. The study was explicitly on how to maximize production yield and minimize operational costs by utilizing advanced neural network models, specifically Long Short-Term Memory and Convolutional Neural Networks. These models were implemented using Python-based frameworks—TensorFlow and Keras. The targets of the research are the precision molding processes in which temperature ranges between 150°C and 220°C, the pressure ranges between 5 and 15 bar, and the material flow rate ranges between 10 and 50 kg/h, which are critical parameters that have a great effect on yield. A dataset of 1 million production cycles has been considered for five continuous years, where detailed logs are present showing the exact setting of parameters and yield output. The LSTM model would model time-dependent trends in production data, while CNN analyzed the spatial correlations between parameters. Models are designed in a supervised learning manner. For the model's loss, an MSE loss function is used, optimized through the Adam optimizer. After running a total of 100 training epochs, 95% accuracy was achieved by the models recommending optimal parameter configurations. Results indicated that with the use of RSM and DOE traditional methods, there was an increase in production yield of 12%. Besides, the error margin was reduced by 8%, hence consistent quality products from the deep learning models. The monetary value was annually around $2.5 million, the cost saved from material waste, energy consumption, and equipment wear resulting from the implementation of optimized process parameters. This system was deployed in an industrial production environment with the help of a hybrid cloud system: Microsoft Azure, for data storage, and the training and deployment of their models were performed on Google Cloud AI. The functionality of real-time monitoring of the process and automatic tuning of parameters depends on cloud infrastructure. To put it into perspective, deep learning models, especially those employing LSTM and CNN, optimize the production yield by fine-tuning process parameters. Future research will consider reinforcement learning with a view to achieving further enhancement of system autonomy and scalability across various manufacturing sectors.

Keywords: production yield optimization, deep learning, tuning of process parameters, LSTM, CNN, precision manufacturing, TensorFlow, Keras, cloud infrastructure, cost saving

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Authors: Nishanth Venugopal Menon, Chuah Yon Jin, Samantha Phey, Wu Yingnan, Zhang Ying, Vincent Chan, Kang Yuejun

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Cell Migration is a vital phenomenon that the cells undergo in various physiological processes like wound healing, disease progression, embryogenesis, etc. Cell migration depends primarily on the chemical and physical cues available in the cellular environment. The chemical cue involves the chemokines secreted and gradients generated in the environment while physical cues indicate the impact of matrix properties like nanotopography and stiffness on the cells. Mesenchymal Stem Cells (MSCs) have been shown to have a role wound healing in vivo and its migration to the site of the wound has been shown to have a therapeutic effect. In the field of stem cell based tissue regeneration of bones and cartilage, one approach has been to introduce scaffold laden with MSCs into the site of injury to enable tissue regeneration. In this work, we have studied the combinatorial impact of the substrate physical properties on MSC migration. A microfluidic in vitro model was created to perform the migration studies. The microfluidic model used is a three compartment device consisting of two cell seeding compartments and one migration compartment. Four different PDMS substrates with varying substrate roughness, stiffness and hydrophobicity were created. Its surface roughness and stiffness was measured using Atomic Force Microscopy (AFM) while its hydrphobicity was measured from the water contact angle using an optical tensiometer. These PDMS substrates are sealed to the microfluidic chip following which the MSCs are seeded and the cell migration is studied over the period of a week. Cell migration was quantified using fluorescence imaging of the cytoskeleton (F-actin) to find out the area covered by the cells inside the migration compartment. The impact of adhesion proteins on cell migration was also quantified using a real-time polymerase chain reaction (qRT PCR). These results suggested that the optimal substrate for cell migration would be one with an intermediate level of roughness, stiffness and hydrophobicity. A higher or lower value of these properties affected cell migration negatively. These observations have helped us in understanding that different substrate properties need to be considered in tandem, especially while designing scaffolds for tissue regeneration as cell migration is normally impacted by the combinatorial impact of the matrix. These observations may lead us to scaffold optimization in future tissue regeneration applications.

Keywords: cell migration, microfluidics, in vitro model, stem cell migration, scaffold, substrate properties

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Authors: Reenu Yadav, Abhay Asthana, S. K. Yadav

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Purpose: The aim of the present work was to develop an oral gel for brushing with an antimicrobial activity which will cure/protect from various periodontal diseases such as periodontitis, gingivitis, and pyorrhea. Methods: Plant materials procured from local suppliers, extracted and standardized. Screening of antimicrobial activity was carried out with the help of disk diffusion method. The gel was formulated by dried extracts of Beautea monosperma and Cordia obliquus. Gels were evaluated on various parameters and standardization of the formulation was performed. The release of drugs was studied in pH 6.8 using a mastication device.Total phenolic and flavonoid contents were estimated by folin-Ciocalteu and aluminium chloride method, and stability studies were performed (40°C and RH 75% ± 5% for 90 days) to assess the effect of temperature and humidity on the concentration of phenolic and flavonoid contents. The results of accelerated stability conditions were compared with that of samples kept at controlled conditions (RT). The control samples were kept at room temperature (25°C, 35% RH for 180 days). Results: Results are encouraging; extracts possess significant antimicrobial activity at very low concentration (15µg/disc, 20µg/disc and 15 µg/ disc) on oral pathogenic bacteria. The formulation has optimal characteristics, as well as has a pleasant appearance, fragrance, texture, and taste, is highly acceptable by the volunteers. The diffusion coefficient values ranged from 0.6655 to 0.9164. Since the R values of korsmayer papas were close to 1, Drug release from formulation follows matrix diffusion kinetics. Hence, diffusion was the mechanism of the drug release. Formulation follows non-Fickian transport mechanism. Most Formulations released 50 % of their contents within 25-30 minutes. Results obtained from the accelerated stability studies are indicative of a slight reduction in flavonoids and phenolic contents with time on long time storage. When measured degradation under ambient conditions, degradation was significantly lower than in accelerated stability study. Conclusion: Plant extracts possess compounds with antimicrobial properties can be used as. Developed formulation will cure/protect from various periodontal diseases. Further development and evaluations oral gel including the isolated compounds on the commercial scale and their clinical and toxicological studies are the future challenges.

Keywords: herbal gel, dental care, ambient conditions, commercial scale

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Authors: Ahmed S. Fayed, Umima M. Mansour

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Three polyvinyl chloride membrane sensors were developed for the electrochemical evaluation of ferrous, manganese and zinc ions. The sensors were used for assaying metal ions in cervical mucus (CM) of Egyptian river buffalo-cows (Bubalus bubalis) as their levels vary dependent on cyclical hormone variation during different phases of estrus cycle. The presented sensors are based on using ionophores, β-cyclodextrin (β-CD), hydroxypropyl β-cyclodextrin (HP-β-CD) and sulfocalix-4-arene (SCAL) for sensors 1, 2 and 3 for Fe²⁺, Mn²⁺ and Zn²⁺, respectively. Dioctyl phthalate (DOP) was used as the plasticizer in a polymeric matrix of polyvinylchloride (PVC). For increasing the selectivity and sensitivity of the sensors, each sensor was enriched with a suitable complexing agent, which enhanced the sensor’s response. For sensor 1, β-CD was mixed with bathophenanthroline; for sensor 2, porphyrin was incorporated with HP-β-CD; while for sensor 3, oxine was the used complexing agent with SCAL. Linear responses of 10^-7-10^-2 M with cationic slopes of 53.46, 45.01 and 50.96 over pH range 4-8 were obtained using coated graphite sensors for ferrous, manganese and zinc ionic solutions, respectively. The three sensors were validated, according to the IUPAC guidelines. The obtained results by the presented potentiometric procedures were statistically analyzed and compared with those obtained by atomic absorption spectrophotometric method (AAS). No significant differences for either accuracy or precision were observed between the two techniques. Successful application for the determination of the three studied cations in CM, for the purpose to determine the proper time for artificial insemination (AI) was achieved. The results were compared with those obtained upon analyzing the samples by AAS. Proper detection of estrus and correct time of AI was necessary to maximize the production of buffaloes. In this experiment, 30 multi-parous buffalo-cows were in second to third lactation and weighting 415-530 kg, and were synchronized with OVSynch protocol. Samples were taken in three times around ovulation, on day 8 of OVSynch protocol, on day 9 (20 h before AI) and on day 10 (1 h before AI). Beside analysis of trace elements (Fe²⁺, Mn²⁺ and Zn²⁺) in CM using the three sensors, the samples were analyzed for the three cations and also Cu²⁺ by AAS in the CM samples and blood samples. The results obtained were correlated with hormonal analysis of serum samples and ultrasonography for the purpose of determining of the optimum time of AI. The results showed significant differences and powerful correlation with Zn²⁺ composition of CM during heat phase and the ovulation time, indicating that the parameter could be used as a tool to decide optimal time of AI in buffalo-cows.

Keywords: PVC Sensors, buffalo-cows, cyclodextrins, atomic absorption spectrophotometry, artificial insemination, OVSynch protocol

Procedia PDF Downloads 219

Authors: Maximilian Elsen, Frank Tietze

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The development and diffusion of green technologies are crucial for achieving our ambitious climate targets. The Paris Agreement commits its members to develop strategies for achieving net zero greenhouse gas emissions by the second half of the century. Governments, executives, and academics are working on net-zero strategies and the business of rating organisations on their environmental, social and governance (ESG) performance has grown tremendously in its public interest. ESG data is now commonly integrated into traditional investment analysis and an important factor in investment decisions. Creating these metrics, however, is inherently challenging as environmental and social impacts are hard to measure and uniform requirements on ESG reporting are lacking. ESG metrics are often incomplete and inconsistent as they lack fully accepted reporting standards and are often of qualitative nature. This study explores the use of patent data for assessing the environmental performance of companies by focusing on their patented inventions in the space of climate change mitigation and adaptation technologies (CCMAT). The present study builds on the successful identification of CCMAT patents. In this context, the study adopts the Y02 patent classification, a fully cross-sectional tagging scheme that is fully incorporated in the Cooperative Patent Classification (CPC), to identify Climate Change Adaptation Technologies. The Y02 classification was jointly developed by the European Patent Office (EPO) and the United States Patent and Trademark Office (USPTO) and provides means to examine technologies in the field of mitigation and adaptation to climate change across relevant technologies. This paper develops sustainability-related metrics for firm-level patent portfolios. We do so by adopting a three-step approach. First, we identify relevant CCMAT patents based on their classification as Y02 CPC patents. Second, we examine the technological strength of the identified CCMAT patents by including more traditional metrics from the field of patent analytics while considering their relevance in the space of CCMAT. Such metrics include, among others, the number of forward citations a patent receives, as well as the backward citations and the size of the focal patent family. Third, we conduct our analysis on a firm level by sector for a sample of companies from different industries and compare the derived sustainability performance metrics with the firms’ environmental and financial performance based on carbon emissions and revenue data. The main outcome of this research is the development of sustainability-related metrics for firm-level environmental performance based on patent data. This research has the potential to complement existing ESG metrics from an innovation perspective by focusing on the environmental performance of companies and putting them into perspective to conventional financial performance metrics. We further provide insights into the environmental performance of companies on a sector level. This study has implications of both academic and practical nature. Academically, it contributes to the research on eco-innovation and the literature on innovation and intellectual property (IP). Practically, the study has implications for policymakers by deriving meaningful insights into the environmental performance from an innovation and IP perspective. Such metrics are further relevant for investors and potentially complement existing ESG data.

Keywords: climate change mitigation, innovation, patent portfolios, sustainability

Procedia PDF Downloads 83

Authors: M. G. Talasbayen, N. N. Dyussenbayev, Y. D. Kali, R. A. Zholbarysov, Y. N. Duissenbayev, I. Z. Mammadinova, S. M. Nuradilov

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Background. Hemorrhagic stroke is an acute cerebrovascular accident resulting from rupture of a cerebral vessel or increased permeability of the wall and imbibition of blood into the brain parenchyma. Arterial hypertension is a common cause of hemorrhagic stroke. Male gender and age over 55 years is a risk factor for intracerebral hemorrhage. Treatment of intracerebral hemorrhage is aimed at the primary pathophysiological link: the relief of coagulopathy and the control of arterial hypertension. Early surgical treatment can limit cerebral compression; prevent toxic effects of blood to the brain parenchyma. Despite progress in the development of neuroimaging data, the use of minimally invasive techniques, and navigation system, mortality from intracerebral hemorrhage remains high. Materials and methods. The study included 78 patients (62.82% male and 37.18% female) with a verified diagnosis of hemorrhagic stroke in the period from 2019 to 2021. The age of patients ranged from 25 to 80 years, the average age was 54.66±11.9 years. Demographic, brain CT data (localization, volume of hematomas), methods of treatment, and disease outcome were analyzed. Results. The retrospective analyze demonstrate that 78.2% of all patients underwent surgical treatment: decompressive craniectomy in 37.7%, craniotomy with hematoma evacuation in 29.5%, and hematoma draining in 24.59% cases. The study of the proportion of deaths, depending on the volume of intracerebral hemorrhage, shows that the number of deaths was higher in the group with a hematoma volume of more than 60 ml. Evaluation of the relationship between the time before surgery and mortality demonstrates that the most favorable outcome is observed during surgical treatment in the interval from 3 to 24 hours. Mortality depending on age did not reveal a significant difference between age groups. An analysis of the impact of the surgery type on mortality reveals that decompressive craniectomy with or without hematoma evacuation led to an unfavorable outcome in 73.9% of cases, while craniotomy with hematoma evacuation and drainage led to mortality only in 28.82% cases. Conclusion. Even though the multimodal approaches, the development of surgical techniques and equipment, and the selection of optimal conservative therapy, the question of determining the tactics of managing and treating hemorrhagic strokes is still controversial. Nevertheless, our experience shows that surgical intervention within 24 hours from the moment of admission and craniotomy with hematoma evacuation improves the prognosis of treatment outcomes.

Keywords: hemorragic stroke, Intracerebral hemorrhage, surgical treatment, stroke mortality

Procedia PDF Downloads 106

Authors: Volker Landersheim, Daria Manushyna, Thinh Pham, Dai-Duong Tran, Thomas Geury, Omar Hegazy, Steven Wilkins

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Air pollution is one of the emerging problems in our society. Targets of reduction of CO₂ emissions address low-carbon and resource-efficient transport. (Plug-in) hybrid electric propulsion concepts offer the possibility to reduce total cost of ownership (TCO) and emissions for public transport vehicles (e.g., bus application). In this context, typically, diesel engines are used to form the hybrid propulsion system of the vehicle. Though the technological development of diesel engines experience major advantages, some challenges such as the high amount of particle emissions remain relevant. Gaseous fuels (i.e., compressed natural gases (CNGs) or liquefied petroleum gases (LPGs) represent an attractive alternative to diesel because of their composition. In the framework of the research project 'Optimised Real-world Cost-Competitive Modular Hybrid Architecture' (ORCA), which was funded by the EU, two different hybrid-electric propulsion concepts have been investigated: one using a diesel engine as internal combustion engine and one using CNG as fuel. The aim of the current study is to analyze specific benefits for the aforementioned hybrid propulsion systems for predefined driving scenarios with regard to emissions and total cost of ownership in bus application. Engine models based on experimental data for diesel and CNG were developed. For the purpose of designing optimal energy management strategies for each propulsion system, maps-driven or quasi-static models for specific engine types are used in the simulation framework. An analogous modelling approach has been chosen to represent emissions. This paper compares the two concepts regarding their CO₂ and NOx emissions. This comparison is performed for relevant bus missions (urban, suburban, with and without zero-emission zone) and with different energy management strategies. In addition to the emissions, also the downsizing potential of the combustion engine has been analysed to minimize the powertrain TCO (pTCO) for plug-in hybrid electric buses. The results of the performed analyses show that the hybrid vehicle concept using the CNG engine shows advantages both with respect to emissions as well as to pTCO. The pTCO is 10% lower, CO₂ emissions are 13% lower, and the NOx emissions are more than 50% lower than with the diesel combustion engine. These results are consistent across all usage profiles under investigation.

Keywords: bus transport, emissions, hybrid propulsion, pTCO, CNG

Procedia PDF Downloads 147

Authors: Amir Shariffar, Haider Salman, Tanveer Siddique, Omar Manasreh

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According to the recent studies on metal-oxide memristors, researchers tend to improve the stability, endurance, and uniformity of resistive switching (RS) behavior in memristors. Specifically, the main challenge is to prevent abrupt ruptures in the memristor’s filament during the RS process. To address this problem, we are proposing a low-cost hybrid structure of metal oxide quantum dots (QDs) and thin films to control the formation of filaments in memristors. We aim to use metal oxide quantum dots because of their unique electronic properties and quantum confinement, which may improve the resistive switching behavior. QDs have discrete energy spectra due to electron confinement in three-dimensional space. Because of Coulomb repulsion between electrons, only a few free electrons are contained in a quantum dot. This fact might guide the growth direction for the conducting filaments in the metal oxide memristor. As a result, it is expected that QDs can improve the endurance and uniformity of RS behavior in memristors. Moreover, we use a hybrid structure of intrinsic n-type quantum dots and p-type thin films to introduce a potential barrier at the junction that can smooth the transition between high and low resistance states. A bottom-up approach is used for fabricating the proposed memristor using different types of metal-oxide QDs and thin films. We synthesize QDs including, zinc oxide, molybdenum trioxide, and nickel oxide combined with spin-coated thin films of titanium dioxide, copper oxide, and hafnium dioxide. We employ fluorine-doped tin oxide (FTO) coated glass as the substrate for deposition and bottom electrode. Then, the active layer composed of one type of quantum dots, and the opposite type of thin films is spin-coated onto the FTO. Lastly, circular gold electrodes are deposited with a shadow mask by using electron-beam (e-beam) evaporation at room temperature. The fabricated devices are characterized using a probe station with a semiconductor parameter analyzer. The current-voltage (I-V) characterization is analyzed for each device to determine the conduction mechanism. We evaluate the memristor’s performance in terms of stability, endurance, and retention time to identify the optimal memristive structure. Finally, we assess the proposed hypothesis before we proceed to the optimization process for fabricating the memristor.

Keywords: memristor, quantum dot, resistive switching, thin film

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Authors: Sakshi Gupta, Anupam Agrawal, Ekta Singla

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An exoskeleton design for rehabilitation purpose encounters many challenges, including ergonomically acceptable wearing technology, architectural design human-motion compatibility, actuation type, human-robot interaction, etc. In this paper, a passive architecture for upper limb exoskeleton is proposed for assisting in rehabilitation tasks. Kinematic modelling is detailed for task-based kinematic synthesis of the wearable exoskeleton for self-feeding tasks. The exoskeleton architecture possesses expansion and torsional springs which are able to store and redistribute energy over the human arm joints. The elastic characteristics of the springs have been optimized to minimize the mechanical work of the human arm joints. The concept of hybrid combination of a 4-bar parallelogram linkage and a serial linkage were chosen, where the 4-bar parallelogram linkage with expansion spring acts as a rigid structure which is used to provide the rotational degree-of-freedom (DOF) required for lowering and raising of the arm. The single linkage with torsional spring allows for the rotational DOF required for elbow movement. The focus of the paper is kinematic modelling, analysis and task-based synthesis framework for the proposed architecture, keeping in considerations the essential tasks of self-feeding and self-exercising during rehabilitation of partially healthy person. Rehabilitation of primary functional movements (activities of daily life, i.e., ADL) is routine activities that people tend to every day such as cleaning, dressing, feeding. We are focusing on the feeding process to make people independent in respect of the feeding tasks. The tasks are focused to post-surgery patients under rehabilitation with less than 40% weakness. The challenges addressed in work are ensuring to emulate the natural movement of the human arm. Human motion data is extracted through motion-sensors for targeted tasks of feeding and specific exercises. Task-based synthesis procedure framework will be discussed for the proposed architecture. The results include the simulation of the architectural concept for tracking the human-arm movements while displaying the kinematic and static study parameters for standard human weight. D-H parameters are used for kinematic modelling of the hybrid-mechanism, and the model is used while performing task-based optimal synthesis utilizing evolutionary algorithm.

Keywords: passive mechanism, task-based synthesis, emulating human-motion, exoskeleton

Procedia PDF Downloads 137

Authors: Alberto A. Escobar Puentes, G. Adriana García, Luis F. Cuevas G., Alejandro P. Zepeda, Fernando B. Martínez, Susana A. Rincón

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Snack foods are usually classified as ‘junk food’ because have little nutritional value. However, due to the increase on the demand and third generation (3G) snacks market, low price and easy to prepare, can be considered as carriers of compounds with certain nutritional value. Resistant starch (RS) is classified as a prebiotic fiber it helps to control metabolic problems and has anti-cancer colon properties. The active compound can be developed by chemical cross-linking of starch with phosphate salts to obtain a type 4 resistant starch (RS4). The chemical reaction can be achieved by extrusion, a process widely used to produce snack foods, since it's versatile and a low-cost procedure. Starch is the major ingredient for snacks 3G manufacture, and the seeds of sorghum contain high levels of starch (70%), the most drought-tolerant gluten-free cereal. Due to this, the aim of this research was to develop a snack (3G), with RS4 in optimal conditions extrusion (previously determined) from sorghum starch, and carry on a sensory, chemically and structural characterization. A sample (200 g) of sorghum starch was conditioned with 4% sodium trimetaphosphate/ sodium tripolyphosphate (99:1) and set to 28.5% of moisture content. Then, the sample was processed in a single screw extruder equipped with rectangular die. The inlet, transport and output temperatures were 60°C, 134°C and 70°C, respectively. The resulting pellets were expanded in a microwave oven. The expansion index (EI), penetration force (PF) and sensory analysis were evaluated in the expanded pellets. The pellets were milled to obtain flour and RS content, degree of substitution (DS), and percentage of phosphorus (% P) were measured. Spectroscopy [Fourier Transform Infrared (FTIR)], X-ray diffraction, differential scanning calorimetry (DSC) and scanning electron microscopy (SEM) analysis were performed in order to determine structural changes after the process. The results in 3G were as follows: RS, 17.14 ± 0.29%; EI, 5.66 ± 0.35 and PF, 5.73 ± 0.15 (N). Groups of phosphate were identified in the starch molecule by FTIR: DS, 0.024 ± 0.003 and %P, 0.35±0.15 [values permitted as food additives (<4 %P)]. In this work an increase of the gelatinization temperature after the crosslinking of starch was detected; the loss of granular and vapor bubbles after expansion were observed by SEM; By using X-ray diffraction, loss of crystallinity was observed after extrusion process. Finally, a snack (3G) was obtained with RS4 developed by extrusion technology. The sorghum starch was efficient for snack 3G production.

Keywords: extrusion, resistant starch, snack (3G), Sorghum

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Authors: Sangho Park, Mansoo Kim, Kyujung Chae, Junhyuk Yang

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The International Maritime Organization (IMO) recognized the problem of invasive species invasion and adopted the "International Convention for the Control and Management of Ships' Ballast Water and Sediments" in 2004, which came into force on September 8, 2017. In 2011, the IMO approved the "Guidelines for the Control and Management of Ships' Biofouling to Minimize the Transfer of Invasive Aquatic Species" to minimize the movement of invasive species by hull-attached organisms and required ships to manage the organisms attached to their hulls. Invasive species enter new environments through ships' ballast water and hull attachment. However, several obstacles to implementing these guidelines have been identified, including a lack of underwater cleaning equipment, regulations on underwater cleaning activities in ports, and difficulty accessing crevices in underwater areas. The shipping industry, which is the party responsible for understanding these guidelines, wants to implement them for fuel cost savings resulting from the removal of organisms attached to the hull, but they anticipate significant difficulties in implementing the guidelines due to the obstacles mentioned above. Robots or people remove the organisms attached to the hull underwater, and the resulting wastewater includes various species of organisms and particles of paint and other pollutants. Currently, there is no technology available to sterilize the organisms in the wastewater or stabilize the heavy metals in the paint particles. In this study, we aim to analyze the characteristics of the wastewater generated from the removal of hull-attached organisms and select the optimal treatment technology. The organisms in the wastewater generated from the removal of the attached organisms meet the biological treatment standard (D-2) using the sterilization technology applied in the ships' ballast water treatment system. The heavy metals and other pollutants in the paint particles generated during removal are treated using stabilization technologies such as thermal decomposition. The wastewater generated is treated using a two-step process: 1) development of sterilization technology through pretreatment filtration equipment and electrolytic sterilization treatment and 2) development of technology for removing particle pollutants such as heavy metals and dissolved inorganic substances. Through this study, we will develop a biological removal technology and an environmentally friendly processing system for the waste generated after removal that meets the requirements of the government and the shipping industry and lays the groundwork for future treatment standards.

Keywords: biofouling, ballast water treatment system, filtration, sterilization, wastewater

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Authors: S. Raja, K. M. Parammasivam, V. Aghilesh

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Fluid-structure interaction is a crucial consideration in the design of many engineering systems such as flight vehicles and bridges. Aircraft lifting surfaces and turbine blades can fail due to oscillations caused by fluid-structure interaction. Hence, it is focussed to study the fluid-structure interaction in the present research. First, the effect of free vibration over the panel is studied. It is well known that the deformation of a panel and flow induced forces affects one another. The selected panel has a span 300mm, chord 300mm and thickness 2 mm. The project is to study, the effect of cross-sectional area and the stiffener location is carried out for the same panel. The stiffener spacing is varied along both the chordwise and span-wise direction. Then for that optimal location the ideal stiffener length is identified. The effect of stiffener cross-section shapes (T, I, Hat, Z) over flutter velocity has been conducted. The flutter velocities of the selected panel with two rectangular stiffeners of cantilever configuration are estimated using MSC NASTRAN software package. As the flow passes over the panel, deformation takes place which further changes the flow structure over it. With increasing velocity, the deformation goes on increasing, but the stiffness of the system tries to dampen the excitation and maintain equilibrium. But beyond a critical velocity, the system damping suddenly becomes ineffective, so it loses its equilibrium. This estimated in NASTRAN using PK method. The first 10 modal frequencies of a simple panel and stiffened panel are estimated numerically and are validated with open literature. A grid independence study is also carried out and the modal frequency values remain the same for element lengths less than 20 mm. The current investigation concludes that the span-wise stiffener placement is more effective than the chord-wise placement. The maximum flutter velocity achieved for chord-wise placement is 204 m/s while for a span-wise arrangement it is augmented to 963 m/s for the stiffeners location of ¼ and ¾ of the chord from the panel edge (50% of chord from either side of the mid-chord line). The flutter velocity is directly proportional to the stiffener cross-sectional area. A significant increment in flutter velocity from 218m/s to 1024m/s is observed for the stiffener lengths varying from 50% to 60% of the span. The maximum flutter velocity above Mach 3 is achieved. It is also observed that for a stiffened panel, the full effect of stiffener can be achieved only when the stiffener end is clamped. Stiffeners with Z cross section incremented the flutter velocity from 142m/s (Panel with no stiffener) to 328 m/s, which is 2.3 times that of simple panel.

Keywords: stiffener placement, stiffener cross-sectional area, stiffener length, stiffener cross sectional area shape

Procedia PDF Downloads 293

Authors: Omarova Gulnara, Assubayeva Saltanat, Tugambay Symbat, Bulegenov Kanat

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The article discusses the problem of developing a methodology for studying thin and nanoscale gold in ores and placers of primary deposits, which will allow us to develop schemes for revealing dispersed gold inclusions and thus improve its recovery rate to increase the gold reserves of the Republic of Kazakhstan. The type of studied gold, is characterized by a number of features. In connection with this, the conditions of its concentration and distribution in ore bodies and formations, as well as the possibility of reliably determining it by "traditional" methods, differ significantly from that of fine gold (less than 0.25 microns) and even more so from that of larger grains. The mineral composition of rocks (metasomatites) and gold ore and the mineralization associated with them were studied in detail on the Kalba ore field in Kazakhstan. Mineralized zones were identified, and samples were taken from them for analytical studies. The research revealed paragenetic relationships of newly formed mineral formations at the nanoscale, which makes it possible to clarify the conditions for the formation of deposits with a particular type of mineralization. This will provide significant assistance in developing a scheme for study. Typomorphic features of gold were revealed, and mechanisms of formation and aggregation of gold nanoparticles were proposed. The presence of a large number of particles isolated at the laboratory stage from concentrates of gravitational enrichment can serve as an indicator of the presence of even smaller particles in the object. Even the most advanced devices based on gravitational methods for gold concentration provide extraction of metal at a level of around 50%, while pulverized metal is extracted much worse, and gold of less than 1 micron size is extracted at only a few percent. Therefore, when particles of gold smaller than 10 microns are detected, their actual numbers may be significantly higher than expected. In particular, at the studied sites, enrichment of slurry and samples with volumes up to 1 m³ was carried out using a screw lock or separator to produce a final concentrate weighing up to several kilograms. Free gold particles were extracted from the concentrates in the laboratory using a number of processes (magnetic and electromagnetic separation, washing with bromoform in a cup to obtain an ultracontentrate, etc.) and examined under electron microscopes to investigate the nature of their surface and chemical composition. The main result of the study was the detection of gold nanoparticles located on the surface of loose metal grains. The most characteristic forms of gold secretions are individual nanoparticles and aggregates of different configurations. Sometimes, aggregates form solid dense films, deposits, and crusts, all of which are confined to the negative forms of the nano- and microrelief on the surfaces of golden. The results will provide significant knowledge about the prevalence and conditions for the distribution of fine and nanoscale gold in Kazakhstan deposits, as well as the development of methods for studying it, which will minimize losses of this type of gold during extraction. Acknowledgments: This publication has been produced within the framework of the Grant "Development of methodology for studying fine and nanoscale gold in ores of primary deposits, placers and products of their processing" (АР23485052, №235/GF24-26).

Keywords: electron microscopy, microminerology, placers, thin and nanoscale gold

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Authors: Julia R. Beulig, Stefan Ohla, Detlev Belder

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In contrast to off-line analytical methods, lab-on-a-chip technology delivers direct information about the observed reaction. Therefore, microfluidic devices make an important scientific contribution, e.g. in the field of synthetic chemistry. Herein, the rapid generation of analytical data can be applied for the optimization of chemical reactions. These microfluidic devices enable a fast change of reaction conditions as well as a resource saving method of operation. In the presented work, we focus on the investigation of multiphase regimes, more specifically on a biphasic microfluidic droplet systems. Here, every single droplet is a reaction container with customized conditions. The biggest challenge is the rapid qualitative and quantitative readout of information as most detection techniques for droplet systems are non-specific, time-consuming or too slow. An exception is the electrospray mass spectrometry (ESI-MS). The combination of a reaction screening platform with a rapid and specific detection method is an important step in droplet-based microfluidics. In this work, we present a novel approach for synthesis optimization on the nanoliter scale with direct ESI-MS detection. The development of a droplet-based microfluidic device, which enables the modification of different parameters while simultaneously monitoring the effect on the reaction within a single run, is shown. By common soft- and photolithographic techniques a polydimethylsiloxane (PDMS) microfluidic chip with different functionalities is developed. As an interface for the MS detection, we use a steel capillary for ESI and improve the spray stability with a Teflon siphon tubing, which is inserted underneath the steel capillary. By optimizing the flow rates, it is possible to screen parameters of various reactions, this is exemplarity shown by a Domino Knoevenagel Hetero-Diels-Alder reaction. Different starting materials, catalyst concentrations and solvent compositions are investigated. Due to the high repetition rate of the droplet production, each set of reaction condition is examined hundreds of times. As a result, of the investigation, we receive possible reagents, the ideal water-methanol ratio of the solvent and the most effective catalyst concentration. The developed system can help to determine important information about the optimal parameters of a reaction within a short time. With this novel tool, we make an important step on the field of combining droplet-based microfluidics with organic reaction screening.

Keywords: droplet, mass spectrometry, microfluidics, organic reaction, screening

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Authors: Alfredo Fortunato, Carmelofrancesco Origlia, Sara Laurita, Rossella Nicoletti

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In the post-pandemic recovery phase of tourism, the role of a Destination Management Organization (DMO) as a coordinated management system of all the elements that make up a destination (attractions, access, marketing, human resources, brand, pricing, etc.) is also becoming relevant for local territories. The objective of a DMO is to maximize the visitor's perception of value and quality while ensuring the competitiveness and sustainability of the destination, as well as the long-term preservation of its natural and cultural assets, and to catalyze benefits for the local economy and residents. In carrying out the multiple functions to which it is called, the DMO can leverage a collective intelligence that comes from the ability to pool information, explicit and tacit knowledge, and relationships of the various stakeholders: policymakers, public managers and officials, entrepreneurs in the tourism supply chain, researchers, data journalists, schools, associations and committees, citizens, etc. The DMO potentially has at its disposal large volumes of data and many of them at low cost, that need to be properly processed to produce value. Based on these assumptions, the paper presents a conceptual framework for building an information system to support the DMO in the intelligent management of a tourist destination tested in an area of southern Italy. The approach adopted is data-informed and consists of four phases: (1) formulation of the knowledge problem (analysis of policy documents and industry reports; focus groups and co-design with stakeholders; definition of information needs and key questions); (2) research and metadatation of relevant sources (reconnaissance of official sources, administrative archives and internal DMO sources); (3) gap analysis and identification of unconventional information sources (evaluation of traditional sources with respect to the level of consistency with information needs, the freshness of information and granularity of data; enrichment of the information base by identifying and studying web sources such as Wikipedia, Google Trends, Booking.com, Tripadvisor, websites of accommodation facilities and online newspapers); (4) definition of the set of indicators and construction of the information base (specific definition of indicators and procedures for data acquisition, transformation, and analysis). The framework derived consists of 6 thematic areas (accommodation supply, cultural heritage, flows, value, sustainability, and enabling factors), each of which is divided into three domains that gather a specific information need to be represented by a scheme of questions to be answered through the analysis of available indicators. The framework is characterized by a high degree of flexibility in the European context, given that it can be customized for each destination by adapting the part related to internal sources. Application to the case study led to the creation of a decision support system that allows: •integration of data from heterogeneous sources, including through the execution of automated web crawling procedures for data ingestion of social and web information; •reading and interpretation of data and metadata through guided navigation paths in the key of digital story-telling; •implementation of complex analysis capabilities through the use of data mining algorithms such as for the prediction of tourist flows.

Keywords: collective intelligence, data framework, destination management, smart tourism

Procedia PDF Downloads 121

Authors: Taylan Kabbani, Ekrem Duman

Abstract:

The design of adaptive systems that take advantage of financial markets while reducing the risk can bring more stagnant wealth into the global market. However, most efforts made to generate successful deals in trading financial assets rely on Supervised Learning (SL), which suffered from various limitations. Deep Reinforcement Learning (DRL) offers to solve these drawbacks of SL approaches by combining the financial assets price "prediction" step and the "allocation" step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. In this paper, a continuous action space approach is adopted to give the trading agent the ability to gradually adjust the portfolio's positions with each time step (dynamically re-allocate investments), resulting in better agent-environment interaction and faster convergence of the learning process. In addition, the approach supports the managing of a portfolio with several assets instead of a single one. This work represents a novel DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem, or what is referred to as The Agent Environment as Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. More specifically, we design an environment that simulates the real-world trading process by augmenting the state representation with ten different technical indicators and sentiment analysis of news articles for each stock. We then solve the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which can learn policies in high-dimensional and continuous action spaces like those typically found in the stock market environment. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of deep reinforcement learning in financial markets over other types of machine learning such as supervised learning and proves its credibility and advantages of strategic decision-making.

Keywords: the stock market, deep reinforcement learning, MDP, twin delayed deep deterministic policy gradient, sentiment analysis, technical indicators, autonomous agent

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Authors: Uswah Ahmad Khan, Muhammad Moazam Fraz, Humayoon Shafique Satti, Qasim Aziz

Abstract:

Approximately 10-14% of the global population experiences a functional disorder known as irritable bowel syndrome (IBS). The disorder is defined by persistent abdominal pain and an irregular bowel pattern. IBS significantly impairs work productivity and disrupts patients' daily lives and activities. Although IBS is widespread, there is still an incomplete understanding of its underlying pathophysiology. This study aims to help characterize the phenotype of IBS patients by differentiating the comorbidities found in IBS patients from those in non-IBS patients using machine learning algorithms. In this study, we extracted samples coding for IBS from the UK BioBank cohort and randomly selected patients without a code for IBS to create a total sample size of 18,000. We selected the codes for comorbidities of these cases from 2 years before and after their IBS diagnosis and compared them to the comorbidities in the non-IBS cohort. Machine learning models, including Decision Trees, Gradient Boosting, Support Vector Machine (SVM), AdaBoost, Logistic Regression, and XGBoost, were employed to assess their accuracy in predicting IBS. The most accurate model was then chosen to identify the features associated with IBS. In our case, we used XGBoost feature importance as a feature selection method. We applied different models to the top 10% of features, which numbered 50. Gradient Boosting, Logistic Regression and XGBoost algorithms yielded a diagnosis of IBS with an optimal accuracy of 71.08%, 71.427%, and 71.53%, respectively. Among the comorbidities most closely associated with IBS included gut diseases (Haemorrhoids, diverticular diseases), atopic conditions(asthma), and psychiatric comorbidities (depressive episodes or disorder, anxiety). This finding emphasizes the need for a comprehensive approach when evaluating the phenotype of IBS, suggesting the possibility of identifying new subsets of IBS rather than relying solely on the conventional classification based on stool type. Additionally, our study demonstrates the potential of machine learning algorithms in predicting the development of IBS based on comorbidities, which may enhance diagnosis and facilitate better management of modifiable risk factors for IBS. Further research is necessary to confirm our findings and establish cause and effect. Alternative feature selection methods and even larger and more diverse datasets may lead to more accurate classification models. Despite these limitations, our findings highlight the effectiveness of Logistic Regression and XGBoost in predicting IBS diagnosis.

Keywords: comorbidities, disease association, irritable bowel syndrome (IBS), predictive analytics

Procedia PDF Downloads 119