Search results for: hybrid adaptive modeling

Authors: Linghua Kong, Xinxia Chen, Mika Gissler, Catharina Lavebratt

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Background: Prenatal exposure to preeclampsia has been associated with an increased risk of offspring attention-deficit/hyperactivity disorders (ADHD), autism spectrum disorder (ASD), and intellectual disability. However, little is known about the association between prenatal exposure to severe preeclampsia and neurodevelopmental and psychiatric disorders in offspring. Objective: This study aimed to assess the risk of maternal preeclampsia combined with perinatal problems, specifically low birth weight and prematurity, on offspring neuropsychiatric disorders. Methods: All singleton live births in Finland between 1996 and 2014 (n=1 012 723) were followed up in nation-wide registries until 2018. Main exposures included pre-eclampsia, small for gestational age, and delivery before 34 gestational weeks. Offspring neurodevelopmental and psychiatric disorders (ICD-10 codes) were examined as outcomes variables. Offspring birth year, sex, maternal age at delivery, parity, marital status at birth, mother's country of birth, maternal smoking, maternal gestational diabetes, maternal use of psychotropic medication during pregnancy, and maternal systemic inflammatory diseases were used as covariates. Risks for neurodevelopmental and psychiatric disorders were estimated using Cox proportional hazards modeling. Results: Of the 1 012 723 offspring, 25 901 (2.6%) were exposed to preeclampsia, and 93 281 (9.2%) were diagnosed with a neuropsychiatric disorder. Compared to births unexposed to preeclampsia, small for gestational age or delivery before 34 gestational weeks, those exposed to preeclampsia only had a 21% increase in the likelihood of any neuropsychiatric disorders after adjusting for potential confounding (adjusted HR=1.21, 95% CI: 1.15-1.26), while exposure to preeclampsia combined with small for gestational age or delivery before 34 gestational weeks had a more than twofold increased risk of having a child with neuropsychiatric disorders (adjusted HR=2.16, 95% CI: 2.02-2.32). The adjusted HR for neuropsychiatric disorders in offspring with small for gestational age or delivery before 34 gestational weeks only was 1.79 (95% CI: 1.73-1.83). In addition, the risk estimate in offspring exposed to both preeclampsia and perinatal problems was greater than those only exposed to preeclampsia for having personality disorders (adjusted HR=1.66; 95% CI: 1.07-2.57), intellectual disabilities (adjusted HR=3.47; 95% CI: 2.86-4.22), specific developmental disorders (adjusted HR=2.91; 95% CI: 2.69-3.15), ASD (adjusted HR=1.75; 95% CI: 1.42-2.17), ADHD and conduct disorders (adjusted HR=2.00; 95%CI: 1.76-2.27), and other behavioral and emotional disorders (adjusted HR=2.09; 95% CI: 1.84-2.37). Conclusion: In utero exposure to severe preeclampsia increased the risk of several neurodevelopmental and psychiatric disorders in offspring. Our findings are relevant to women with hypertensive disorders with regard to pregnancy consultation and management and may yield effective clues for the prevention of neurodevelopmental and psychiatric disorders in childhood.

Keywords: low birth weight, neurodevelopmental disorders, preeclampsia, prematurity, psychiatric disorders

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Authors: Ella Tyuryumina, Alexey Neznanov

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Finding algorithms to predict the growth of tumors has piqued the interest of researchers ever since the early days of cancer research. A number of studies were carried out as an attempt to obtain reliable data on the natural history of breast cancer growth. Mathematical modeling can play a very important role in the prognosis of tumor process of breast cancer. However, mathematical models describe primary tumor growth and metastases growth separately. Consequently, we propose a mathematical growth model for primary tumor and primary metastases which may help to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoM-IV and corresponding software. We are interested in: 1) modelling the whole natural history of primary tumor and primary metastases; 2) developing adequate and precise CoM-IV which reflects relations between PT and MTS; 3) analyzing the CoM-IV scope of application; 4) implementing the model as a software tool. The CoM-IV is based on exponential tumor growth model and consists of a system of determinate nonlinear and linear equations; corresponds to TNM classification. It allows to calculate different growth periods of primary tumor and primary metastases: 1) ‘non-visible period’ for primary tumor; 2) ‘non-visible period’ for primary metastases; 3) ‘visible period’ for primary metastases. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. Thus, the CoM-IV model and predictive software: a) detect different growth periods of primary tumor and primary metastases; b) make forecast of the period of primary metastases appearance; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of BC and facilitate optimization of diagnostic tests. The following are calculated by CoM-IV: the number of doublings for ‘nonvisible’ and ‘visible’ growth period of primary metastases; tumor volume doubling time (days) for ‘nonvisible’ and ‘visible’ growth period of primary metastases. The CoM-IV enables, for the first time, to predict the whole natural history of primary tumor and primary metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on primary tumor sizes. Summarizing: a) CoM-IV describes correctly primary tumor and primary distant metastases growth of IV (T1-4N0-3M1) stage with (N1-3) or without regional metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and manifestation of primary metastases.

Keywords: breast cancer, exponential growth model, mathematical modelling, primary metastases, primary tumor, survival

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Authors: Shreya Saxena, Felix Miller-Molloy, Phillipa Bowen, Greg Fellows, Elizabeth Bowen

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Background: Complex fluid balance abnormalities are well-established post-neurosurgery and traumatic brain injury (TBI). The triple-phase response requires fluid management strategies reactive to urine output and sodium homeostasis as patients shift between Diabetes Insipidus (DI) and Syndrome of Inappropriate ADH (SIADH). It was observed, at a tertiary paediatric center, a relatively high prevalence of the above complications within a cohort of paediatric post-neurosurgical and TBI patients. An audit of the clinical practice against set institutional guidelines was undertaken and analyzed to understand why this was occurring. Based on those results, new guidelines were developed with structured educational packages for the specialist teams involved. This was then reaudited, and the findings were compared. Methods: Two independent audits were conducted across two time periods, pre and post guideline change. Primary data was collected retrospectively, including both qualitative and quantitative data sets from the CQUIN neurosurgical database and electronic medical records. All paediatric patients post posterior fossa (PFT) or supratentorial surgery or with a TBI were included. A literature review of evidence-based practice, initial audit data, and stakeholder feedback was used to develop new clinical guidelines and nursing standard operation procedures. Compliance against these newly developed guidelines was re-assessed and a thematic, trend-based analysis of the two sets of results was conducted. Results: Audit-1 January2017-June2018, n=80; Audit-2 January2020-June2021, n=30 (reduced operative capacity due to COVID-19 pandemic). Overall, improvements in the monitoring of both fluid balance and electrolyte trends were demonstrated; 51% vs. 77% and 78% vs. 94%, respectively. The number of clear fluid management plans documented postoperatively also increased (odds ratio of 4), leading to earlier recognition and management of evolving fluid-balance abnormalities. The local paediatric endocrine team was involved in the care of all complex cases and notified sooner for those considered to be developing DI or SIADH (14% to 35%). However, significant Na fluctuations (>12mmol in 24 hours) remained similar – 5 vs six patients – found to be due to complex pituitary hypothalamic pathology – and the recommended adaptive fluid management strategy was still not always used. Qualitative data regarding useability and understanding of fluid-balance abnormalities and the revised guidelines were obtained from health professionals via surveys and discussion in the specialist teams providing care. The feedback highlighted the new guidelines provided a more consistent approach to the post-operative care of these patients and was a better platform for communication amongst the different specialist teams involved. The potential limitation to our study would be the small sample size on which to conduct formal analyses; however, this reflects the population that we were investigating, which we cannot control. Conclusion: The revised clinical guidelines, based on audited data, evidence-based literature review and stakeholder consultations, have demonstrated an improvement in understanding of the neuro-endocrine complications that are possible, as well as increased compliance to post-operative monitoring of fluid balance and electrolytes in this cohort of patients. Emphasis has been placed on preventative rather than treatment of DI and SIADH. Consequently, this has positively impacted patient safety for the center and highlighted the importance of educational awareness and multi-disciplinary team working.

Keywords: post-operative, fluid-balance management, neuro-endocrine complications, paediatric

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Authors: Thammanoon Charmjuree, Yuosre F. Badir, Umar Safdar

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There is a consensus among innovation scholars that knowledge is a vital antecedent for firm’s innovation; e.g., process innovation. Recently, there has been an increasing amount of attention to more open approaches to innovation. This open model emphasizes the use of purposive flows of knowledge across the organization boundaries. Firms adopt open innovation strategy to improve their innovation performance by bringing knowledge into the organization (inbound open innovation) to accelerate internal innovation or transferring knowledge outside (outbound open innovation) to expand the markets for external use of innovation. Reviewing open innovation research reveals the following. First, the majority of existing studies have focused on inbound open innovation and less on outbound open innovation. Second, limited research has considered the possible interaction between both and how this interaction may impact the firm’s innovation performance. Third, scholars have focused mainly on the impact of open innovation strategy on product innovation and less on process innovation. Therefore, our knowledge of the relationship between firms’ inbound and outbound open innovation and how these two impact process innovation is still limited. This study focuses on the firm’s external technology acquisition (ETA) and external technology exploitation (ETE) and the firm’s process innovation performance. The ETA represents inbound openness in which firms rely on the acquisition and absorption of external technologies to complement their technology portfolios. The ETE, on the other hand, refers to commercializing technology assets exclusively or in addition to their internal application. This study hypothesized that both ETA and ETE have a positive relationship with process innovation performance and that ETE fully mediates the relationship between ETA and process innovation performance, i.e., ETA has a positive impact on ETE, and turn, ETE has a positive impact on process innovation performance. This study empirically explored these hypotheses in software development firms in Thailand. These firms were randomly selected from a list of Software firms registered with the Department of Business Development, Ministry of Commerce of Thailand. The questionnaires were sent to 1689 firms. After follow-ups and periodic reminders, we obtained 329 (19.48%) completed usable questionnaires. The structure question modeling (SEM) has been used to analyze the data. An analysis of the outcome of 329 firms provides support for our three hypotheses: First, the firm’s ETA has a positive impact on its process innovation performance. Second, the firm’s ETA has a positive impact its ETE. Third, the firm’s ETE fully mediates the relationship between the firm’s ETA and its process innovation performance. This study fills up the gap in open innovation literature by examining the relationship between inbound (ETA) and outbound (ETE) open innovation and suggest that in order to benefits from the promises of openness, firms must engage in both. The study went one step further by explaining the mechanism through which ETA influence process innovation performance.

Keywords: process innovation performance, external technology acquisition, external technology exploitation, open innovation

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Authors: Chandra Shekhar Prasad, Ludek Pesek Prasad

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In the present day fan blade of aero engine, turboprop propellers, gas turbine or steam turbine low-pressure blades are getting bigger, lighter and thus, become more flexible. Therefore, flutter, forced blade response and vibration related failure of the high aspect ratio blade are of main concern for the designers, thus need to be address properly in order to achieve successful component design. At the preliminary design stage large number of design iteration is need to achieve the utter free safe design. Most of the numerical method used for aeroelastic analysis is based on field-based methods such as finite difference method, finite element method, finite volume method or coupled. These numerical schemes are used to solve the coupled fluid Flow-Structural equation based on full Naiver-Stokes (NS) along with structural mechanics’ equations. These type of schemes provides very accurate results if modeled properly, however, they are computationally very expensive and need large computing recourse along with good personal expertise. Therefore, it is not the first choice for aeroelastic analysis during preliminary design phase. A reduced order aeroelastic model (ROAM) with acceptable accuracy and fast execution is more demanded at this stage. Similar ROAM are being used by other researchers for aeroelastic and force response analysis of turbomachinery. In the present paper new medium fidelity ROAM is successfully developed and implemented in numerical tool to simulated the aeroelastic stability phenomena in turbomachinery and well as flexible wings. In the present, a hybrid flow solver based on 3D viscous-inviscid coupled 3D panel method (PM) and 3d discrete vortex particle method (DVM) is developed, viscous parameters are estimated using boundary layer(BL) approach. This method can simulate flow separation and is a good compromise between accuracy and speed compared to CFD. In the second phase of the research work, the flow solver (PM) will be coupled with ROM non-linear beam element method (BEM) based FEM structural solver (with multibody capabilities) to perform the complete aeroelastic simulation of a steam turbine bladed disk, propellers, fan blades, aircraft wing etc. The partitioned based coupling approach is used for fluid-structure interaction (FSI). The numerical results are compared with experimental data for different test cases and for the blade cascade test case, experimental data is obtained from in-house lab experiments at IT CAS. Furthermore, the results from the new aeroelastic model will be compared with classical CFD-CSD based aeroelastic models. The proposed methodology for the aeroelastic stability analysis of gas turbine or steam turbine blades, or propellers or fan blades will provide researchers and engineers a fast, cost-effective and efficient tool for aeroelastic (classical flutter) analysis for different design at preliminary design stage where large numbers of design iteration are required in short time frame.

Keywords: aeroelasticity, beam element method (BEM), discrete vortex particle method (DVM), classical flutter, fluid-structure interaction (FSI), panel method, reduce order aeroelastic model (ROAM), turbomachinery, viscous-inviscid coupling

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Authors: Farzaneh Badinlou, Reza Kormi-Nouri, Monika Knopf, Kamal Kharrazi

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When we teach, we have two critical elements at our disposal to help students: learning styles as well as testing styles. There are many different ways in which educators can effectively teach their students; verbal learning and experience-based learning. Lecture as a form of verbal learning style is a traditional arrangement in which teachers are more active and share information verbally with students. In experienced-based learning as the process of through, students learn actively through hands-on learning materials and observing teachers or others. Meanwhile, standard testing or assessment is the way to determine progress toward proficiency. Teachers and instructors mainly use essay (requires written responses), multiple choice questions (includes the correct answer and several incorrect answers as distractors), or open-ended questions (respondents answers it with own words). The current study focused on exploring an effective teaching style and testing methods as the function of age over school ages. In the present study, totally 410 participants were selected randomly from four grades (2ⁿᵈ, 4ᵗʰ, 6ᵗʰ, and 8ᵗʰ). Each subject was tested individually in one session lasting around 50 minutes. In learning tasks, the participants were presented three different instructions for learning materials (learning by doing, learning by observing, and learning by listening). Then, they were tested via different standard assessments as free recall, cued recall, and recognition tasks. The results revealed that generally students remember more of what they do and what they observe than what they hear. The age effect was more pronounced in learning by doing than in learning by observing, and learning by listening, becoming progressively stronger in the free-recall, cued-recall, and recognition tasks. The findings of this study indicated that learning by doing and free recall task is more age sensitive, suggesting that both of them are more strategic and more affected by developmental differences. Pedagogically, these results denoted that learning by modeling and engagement in program activities have the special role for learning. Moreover, the findings indicated that the multiple-choice questions can produce the best performance for school-aged children but is less age-sensitive. By contrast, the essay as essay can produce the lowest performance but is more age-sensitive. It will be very helpful for educators to know that what types of learning styles and test methods are most effective for students in each school grade.

Keywords: experience-based learning, learning style, school-aged children, testing methods, verbal learning

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Authors: Coriolano Salvini, Ambra Giovannelli

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The use of renewable energy sources for electric power production leads to reduced CO2 emissions and contributes to improving the domestic energy security. On the other hand, the intermittency and unpredictability of their availability poses relevant problems in fulfilling safely and in a cost efficient way the load demand along the time. Significant benefits in terms of “grid system applications”, “end-use applications” and “renewable applications” can be achieved by introducing energy storage systems. Among the currently available solutions, CAES (Compressed Air Energy Storage) shows favorable features. Small-medium size plants equipped with artificial air reservoirs can constitute an interesting option to get efficient and cost-effective distributed energy storage systems. The present paper is addressed to the design and off-design analysis of the compression system of small size CAES plants suited to absorb electric power in the range of hundreds of kilowatt. The system of interest is constituted by an intercooled (in case aftercooled) multi-stage reciprocating compressor and a man-made reservoir obtained by connecting large diameter steel pipe sections. A specific methodology for the system preliminary sizing and off-design modeling has been developed. Since during the charging phase the electric power absorbed along the time has to change according to the peculiar CAES requirements and the pressure ratio increases continuously during the filling of the reservoir, the compressor has to work at variable mass flow rate. In order to ensure an appropriately wide range of operations, particular attention has been paid to the selection of the most suitable compressor capacity control device. Given the capacity regulation margin of the compressor and the actual level of charge of the reservoir, the proposed approach allows the instant-by-instant evaluation of minimum and maximum electric power absorbable from the grid. The developed tool gives useful information to appropriately size the compression system and to manage it in the most effective way. Various cases characterized by different system requirements are analysed. Results are given and widely discussed.

Keywords: artificial air storage reservoir, compressed air energy storage (CAES), compressor design, compression system management.

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Authors: Renata Martins Pacheco, João Claro

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Wildfires are becoming an increasing concern worldwide, causing substantial social, economic, and environmental disruptions. This situation is especially relevant in Mediterranean-climate regions, present in all the five continents of the world, in which fire is not only a natural component of the environment but also perhaps one of the most important evolutionary forces. The rise in wildfire occurrences and their associated impacts suggests the need for identifying knowledge gaps and enhancing the basis of scientific evidence on how managers and policymakers may act effectively to address them. Considering that the main goal of a systematic map is to collate and catalog a body of evidence to describe the state of knowledge for a specific topic, it is a suitable approach to be used for this purpose. In this context, the aim of this study is to systematically map the research trends in wildfire management practices in Mediterranean-climate regions. A total of 201 wildfire management studies were analyzed and systematically mapped in terms of their: Year of publication; Place of study; Scientific outlet; Research area (Web of Science) or Research field (Scopus); Wildfire phase; Central research topic; Main objective of the study; Research methods; and Main conclusions or contributions. The results indicate that there is an increasing number of studies being developed on the topic (most from the last 10 years), but more than half of them are conducted in few Mediterranean countries (60% of the analyzed studies were conducted in Spain, Portugal, Greece, Italy or France), and more than 50% are focused on pre-fire issues, such as prevention and fuel management. In contrast, only 12% of the studies focused on “Economic modeling” or “Human factors and issues,” which suggests that the triple bottom line of the sustainability argument (social, environmental, and economic) is not being fully addressed by fire management research. More than one-fourth of the studies had their objective related to testing new approaches in fire or forest management, suggesting that new knowledge is being produced on the field. Nevertheless, the results indicate that most studies (about 84%) employed quantitative research methods, and only 3% of the studies used research methods that tackled social issues or addressed expert and practitioner’s knowledge. Perhaps this lack of multidisciplinary studies is one of the factors hindering more progress from being made in terms of reducing wildfire occurrences and their impacts.

Keywords: wildfire, Mediterranean-climate regions, management, policy

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Authors: Sudha T., Naveen C.

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Dengue is a serious public health issue that causes significant annual economic and welfare burdens on nations. However, enhanced optimization techniques and quantitative modeling approaches can predict the incidence of dengue. By advocating for a data-driven approach, public health officials can make informed decisions, thereby improving the overall effectiveness of sudden disease outbreak control efforts. The National Oceanic and Atmospheric Administration and the Centers for Disease Control and Prevention are two of the U.S. Federal Government agencies from which this study uses environmental data. Based on environmental data that describe changes in temperature, precipitation, vegetation, and other factors known to affect dengue incidence, many predictive models are constructed that use different machine learning methods to estimate weekly dengue cases. The first step involves preparing the data, which includes handling outliers and missing values to make sure the data is prepared for subsequent processing and the creation of an accurate forecasting model. In the second phase, multiple feature selection procedures are applied using various machine learning models and optimization techniques. During the third phase of the research, machine learning models like the Huber Regressor, Support Vector Machine, Gradient Boosting Regressor (GBR), and Support Vector Regressor (SVR) are compared with several optimization techniques for feature selection, such as Harmony Search and Genetic Algorithm. In the fourth stage, the model's performance is evaluated using Mean Square Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) as assistance. Selecting an optimization strategy with the least number of errors, lowest price, biggest productivity, or maximum potential results is the goal. In a variety of industries, including engineering, science, management, mathematics, finance, and medicine, optimization is widely employed. An effective optimization method based on harmony search and an integrated genetic algorithm is introduced for input feature selection, and it shows an important improvement in the model's predictive accuracy. The predictive models with Huber Regressor as the foundation perform the best for optimization and also prediction.

Keywords: deep learning model, dengue fever, prediction, optimization

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Authors: Newton Muhury, Armando A. Apan, Tek Maraseni

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This study modelled the relationships between vegetation response and available water below the soil surface using the Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS) generated Normalised Difference Vegetation Index (NDVI) and soil water content (SWC) data. The Soil & Water Assessment Tool (SWAT) interface known as ArcSWAT was used in ArcGIS for the groundwater analysis. The SWAT model was calibrated and validated in SWAT-CUP software using 10 years (2001-2010) of monthly streamflow data. The average Nash-Sutcliffe Efficiency during the calibration and validation was 0.54 and 0.51, respectively, indicating that the model performances were good. Twenty years (2001-2020) of monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) and soil water content for 43 sub-basins were analysed using the WEKA, machine learning tool with a selection of two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The modelling results show that different types of vegetation response and soil water content vary in the dry and wet season. For example, the model generated high positive relationships (r=0.76, 0.73, and 0.81) between the measured and predicted NDVI values of all vegetation in the study area against the groundwater flow (GW), soil water content (SWC), and the combination of these two variables, respectively, during the dry season. However, these relationships were reduced by 36.8% (r=0.48) and 13.6% (r=0.63) against GW and SWC, respectively, in the wet season. On the other hand, the model predicted a moderate positive relationship (r=0.63) between shrub vegetation type and soil water content during the dry season, which was reduced by 31.7% (r=0.43) during the wet season. Our models also predicted that vegetation in the top location (upper part) of the sub-basin is highly responsive to GW and SWC (r=0.78, and 0.70) during the dry season. The results of this study indicate the study region is suitable for seasonal crop production in dry season. Moreover, the results predicted that the growth of vegetation in the top-point location is highly dependent on groundwater flow in both dry and wet seasons, and any instability or long-term drought can negatively affect these floodplain vegetation communities. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

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Authors: Moustafa Osman Mohammed

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Integration sustainability outcomes give attention to construction ecology in the design review of urban environments to comply with Earth’s System that is composed of integral parts of the (i.e., physical, chemical and biological components). Naturally, exchange patterns of industrial ecology have consistent and periodic cycles to preserve energy flows and materials in Earth’s System. When engineering topology is affecting internal and external processes in system networks, it postulated the valence of the first-level spatial outcome (i.e., project compatibility success). These instrumentalities are dependent on relating the second-level outcome (i.e., participant security satisfaction). Construction ecology approach feedback energy from resources flows between biotic and abiotic in the entire Earth’s ecosystems. These spatial outcomes are providing an innovation, as entails a wide range of interactions to state, regulate and feedback “topology” to flow as “interdisciplinary equilibrium” of ecosystems. The interrelation dynamics of ecosystems are performing a process in a certain location within an appropriate time for characterizing their unique structure in “equilibrium patterns”, such as biosphere and collecting a composite structure of many distributed feedback flows. These interdisciplinary systems regulate their dynamics within complex structures. These dynamic mechanisms of the ecosystem regulate physical and chemical properties to enable a gradual and prolonged incremental pattern to develop a stable structure. The engineering topology of construction ecology for integration sustainability outcomes offers an interesting tool for ecologists and engineers in the simulation paradigm as an initial form of development structure within compatible computer software. This approach argues from ecology, resource savings, static load design, financial other pragmatic reasons, while an artistic/architectural perspective, these are not decisive. The paper described an attempt to unify analytic and analogical spatial modeling in developing urban environments as a relational setting, using optimization software and applied as an example of integrated industrial ecology where the construction process is based on a topology optimization approach.

Keywords: construction ecology, industrial ecology, urban topology, environmental planning

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Authors: Soon Young Choi, Chan Hwan Kim, Chan Hong Park, Hyung Rae Kim, Myoung Hoon Lee, Hyeon-Yeong Park

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We performed the marine magnetic, bathymetry and seismic survey at the TA22 seamount (in the Lau basin, SW Pacific) for finding the submarine hydrothermal deposits in October 2009. We acquired magnetic and bathymetry data sets by suing Overhouser Proton Magnetometer SeaSPY (Marine Magnetics Co.), Multi-beam Echo Sounder EM120 (Kongsberg Co.). We conducted the data processing to obtain detailed seabed topography, magnetic anomaly, reduction to the pole (RTP) and magnetization. Based on the magnetic properties result, we analyzed submarine geology structure of TA22 seamount with post-processed seismic profile. The detailed bathymetry of the TA22 seamount showed the left and right crest parts that have caldera features in each crest central part. The magnetic anomaly distribution of the TA22 seamount regionally displayed high magnetic anomalies in northern part and the low magnetic anomalies in southern part around the caldera features. The RTP magnetic anomaly distribution of the TA22 seamount presented commonly high magnetic anomalies in the each caldera central part. Also, it represented strong anomalies at the inside of caldera rather than outside flank of the caldera. The magnetization distribution of the TA22 seamount showed the low magnetization zone in the center of each caldera, high magnetization zone in the southern and northern east part. From analyzed the seismic profile map, The TA22 seamount area is showed for the inferred small mounds inside each caldera central part and it assumes to make possibility of sills by the magma in cases of the right caldera. Taking into account all results of this study (bathymetry, magnetic anomaly, RTP, magnetization, seismic profile) with rock samples at the left caldera area in 2009 survey, we suppose the possibility of hydrothermal deposits at mounds in each caldera central part and at outside flank of the caldera representing the low magnetization zone. We expect to have the better results by combined modeling from this study data with the other geological data (ex. detailed gravity, 3D seismic, petrologic study results and etc).

Keywords: detailed bathymetry, magnetic anomaly, seamounts, seismic profile, SW Pacific

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Authors: Veenu Bala, Yashpal S. Chhonker, Bhavana Kushwaha, Rabi S. Bhatta, Gopal Gupta, Vishnu L. Sharma

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According to UNAIDS 2013 estimate nearly 52% of all individuals living with HIV are now women of reproductive age (15–44 years). Seventy-five percent cases of HIV acquisition are through heterosexual contacts and sexually transmitted infections (STIs), attributable to unsafe sexual behaviour. Each year, an estimated 500 million people acquire atleast one of four STIs: chlamydia, gonorrhoea, syphilis and trichomoniasis. Trichomonas vaginalis (TV) is exclusively sexually transmitted in adults, accounting for 30% of STI cases and associated with pelvic inflammatory disease (PID), vaginitis and pregnancy complications in women. TV infection resulted in impaired vaginal milieu, eventually favoring HIV transmission. In the absence of an effective prophylactic HIV vaccine, prevention of new infections has become a priority. It was thought worthwhile to integrate HIV prevention and reproductive health services including unintended pregnancy protection for women as both are related with unprotected sex. Initially, nonoxynol-9 (N-9) had been proposed as a spermicidal agent with microbicidal activity but on the contrary it increased HIV susceptibility due to surfactant action. Thus, to accomplish an urgent need of novel woman controlled non-detergent microbicidal spermicides benzenepropanamine analogues have been synthesized. At first, five benzenepropanamine-dithiocarbamate hybrids have been synthesized and evaluated for their spermicidal, anti-Trichomonas and anti-fungal activities along with safety profiling to cervicovaginal cells. In order to further enhance the scope of above study benzenepropanamine was hybridized with thiourea as to introduce anti-HIV potential. The synthesized hybrid molecules were evaluated for their reverse transcriptase (RT) inhibition, spermicidal, anti-Trichomonas and antimicrobial activities as well as their safety against vaginal flora and cervical cells. simulated vaginal fluid (SVF) stability and pharmacokinetics of most potent compound versus N-9 was examined in female Newzealand (NZ) rabbits to observe its absorption into systemic circulation and subsequent exposure in blood plasma through vaginal wall. The study resulted in the most promising compound N-butyl-4-(3-oxo-3-phenylpropyl) piperazin-1-carbothioamide (29) exhibiting better activity profile than N-9 as it showed RT inhibition (72.30 %), anti-Trichomonas (MIC, 46.72 µM against MTZ susceptible and MIC, 187.68 µM against resistant strain), spermicidal (MEC, 0.01%) and antifungal activity (MIC, 3.12–50 µg/mL) against four fungal strains. The high safety against vaginal epithelium (HeLa cells) and compatibility with vaginal flora (lactobacillus), SVF stability and least vaginal absorption supported its suitability for topical vaginal application. Docking study was performed to gain an insight into the binding mode and interactions of the most promising compound, N-butyl-4-(3-oxo-3-phenylpropyl) piperazin-1-carbothioamide (29) with HIV-1 Reverse Transcriptase. The docking study has revealed that compound (29) interacted with HIV-1 RT similar to standard drug Nevirapine. It may be concluded that hybridization of benzenepropanamine and thiourea moiety resulted into novel lead with multiple activities including RT inhibition. A further lead optimization may result into effective vaginal microbicides having spermicidal, anti-Trichomonas, antifungal and anti-HIV potential altogether with enhanced safety to cervico-vaginal cells in comparison to Nonoxynol-9.

Keywords: microbicidal, nonoxynol-9, reverse transcriptase, spermicide

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Authors: Amritee Bora, B. S. Mipun

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Land degradation is often used to describe the land environmental phenomena that reduce land’s original productivity both qualitatively and quantitatively. The study of land degradation vulnerability primarily deals with “Environmentally Sensitive Areas” (ESA) and the amount of topsoil loss due to erosion. In many studies, it is observed that the assessment of the existing status of land degradation is used to represent the vulnerability. Moreover, it is also noticed that in most studies, the primary emphasis of land degradation vulnerability is to assess its sensitivity to soil erosion only. However, the concept of land degradation vulnerability can have different objectives depending upon the perspective of the study. It shows the extent to which changes in land use land cover can imprint their effect on the land. In other words, it represents the susceptibility of a piece of land to degrade its productive quality permanently or in the long run. It is also important to mention that the vulnerability of land degradation is not a single factor outcome. It is a probability assessment to evaluate the status of land degradation and needs to consider both biophysical and human induce parameters. To avoid the complexity of the previous models in this regard, the present study has emphasized on to generate a simplified model to assess the land degradation vulnerability in terms of its current human population pressure, land use practices, and existing biophysical conditions. It is a “Mixed-Method” termed as the land degradation vulnerability index (LDVi). It was originally inspired by the MEDALUS model (Mediterranean Desertification and Land Use), 1999, and Farazadeh’s 2007 revised version of it. It has followed the guidelines of Space Application Center, Ahmedabad / Indian Space Research Organization for land degradation vulnerability. The model integrates the climatic index (Ci), vegetation index (Vi), erosion index (Ei), land utilization index (Li), population pressure index (Pi), and cover management index (CMi) by giving equal weightage to each parameter. The final result shows that the very high vulnerable zone primarily indicates three (3) prominent circumstances; land under continuous population pressure, high concentration of human settlement, and high amount of topsoil loss due to surface runoff within the study sites. As all the parameters of the model are amalgamated with equal weightage further with the help of regression analysis, the LDVi model also provides a strong grasp of each parameter and how far they are competent to trigger the land degradation process.

Keywords: population pressure, land utilization, soil erosion, land degradation vulnerability

Procedia PDF Downloads 143

Authors: Arthur Müller

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The study treats human dimensions of hunting by conducting statistical data analysis and providing decision-making support by examples of good prefectural governance and successful wildlife management, crucial to reduce pest species and sustain a stable hunter population in the future. Therefore it analyzes recent revision of wildlife legislation, reveals differences in administrative management structures, as well as socio-demographic characteristics of hunters in correlation with harvest trends of sika deer and wild boar in 47 prefectures in Japan between 1990 and 2013. In a wider context, Japan’s decentralized license hunting system might take the potential future role of a regional pioneer in East Asia. Consequently, the study contributes to similar issues in premature hunting systems of South Korea and Taiwan. Firstly, a quantitative comparison of seven mainland regions was conducted in Hokkaido, Tohoku, Kanto, Chubu, Kinki, Chugoku, and Kyushu. Example prefectures were chosen by a cluster analysis. Shifts, differences, mean values and exponential growth rates between trap and gun hunters, age classes and common occupation types of hunters were statistically exterminated. While western Japan is characterized by high numbers of aged trap-hunters, occupied in agricultural- and forestry, the north-eastern prefectures show higher relative numbers of younger gun-hunters occupied in the field of production and process workers. With the exception of Okinawa island, most hunters in all prefectures are 60 years and older. Hence, unemployed and retired hunters are the fastest growing occupation group. Despite to drastic decrease in hunter population in absolute numbers, Hunting Recruitment Index indicated that all age classes tend to continue their hunting activity over a longer period, above ten years from 2004 to 2013 than during the former decade. Associated with a rapid population increase and distribution of sika deer and wild boar since 1978, a number of harvest from hunting and culling also have been rapidly increasing. Both wild boar hunting and culling is particularly high in western Japan, while sika hunting and culling proofs most successful in Hokkaido, central and western Japan. Since the Wildlife Protection and Proper Hunting Act in 1999 distinct prefectural hunting management authorities with different power, sets apply management approaches under the principles of subsidiarity and guidelines of the Ministry of Environment. Additionally, the Act on Special Measures for Prevention of Damage Related to Agriculture, Forestry, and Fisheries Caused by Wildlife from 2008 supports local hunters in damage prevention measures through subsidies by the Ministry of Agriculture and Forestry, which caused a rise of trap hunting, especially in western Japan. Secondly, prefectural staff in charge of wildlife management in seven regions was contacted. In summary, Hokkaido serves as a role model for dynamic, integrative, adaptive “feedback” management of Ezo sika deer, as well as a diverse network between management organizations, while Hyogo takes active measures to trap-hunt wild boars effectively. Both prefectures take the leadership in institutional performance and capacity. Northern prefectures in Tohoku, Chubu and Kanto region, firstly confronted with the emergence of wild boars and rising sika deer numbers, demand new institution and capacity building, as well as organizational learning.

Keywords: hunting and culling harvest trends, hunter socio-demographics, regional comparison, wildlife management approach

Procedia PDF Downloads 254

Authors: Bao Li, Aike Qiao, Gaoyang Li, Youjun Liu

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Background: Lumped parameter model (LPM) is a common numerical model for hemodynamic calculation. LPM uses circuit elements to simulate the human blood circulatory system. Physiological indicators and characteristics can be acquired through the model. However, due to the different physiological indicators of each individual, parameters in LPM should be personalized in order for convincing calculated results, which can reflect the individual physiological information. This study aimed to develop an automatic and effective optimization method to personalize the parameters in LPM of the blood circulatory system, which is of great significance to the numerical simulation of individual hemodynamics. Methods: A closed-loop LPM of the human blood circulatory system that is applicable for most persons were established based on the anatomical structures and physiological parameters. The patient-specific physiological data of 5 volunteers were non-invasively collected as personalized objectives of individual LPM. In this study, the blood pressure and flow rate of heart, brain, and limbs were the main concerns. The collected systolic blood pressure, diastolic blood pressure, cardiac output, and heart rate were set as objective data, and the waveforms of carotid artery flow and ankle pressure were set as objective waveforms. Aiming at the collected data and waveforms, sensitivity analysis of each parameter in LPM was conducted to determine the sensitive parameters that have an obvious influence on the objectives. Simulated annealing was adopted to iteratively optimize the sensitive parameters, and the objective function during optimization was the root mean square error between the collected waveforms and data and simulated waveforms and data. Each parameter in LPM was optimized 500 times. Results: In this study, the sensitive parameters in LPM were optimized according to the collected data of 5 individuals. Results show a slight error between collected and simulated data. The average relative root mean square error of all optimization objectives of 5 samples were 2.21%, 3.59%, 4.75%, 4.24%, and 3.56%, respectively. Conclusions: Slight error demonstrated good effects of optimization. The individual modeling algorithm developed in this study can effectively achieve the individualization of LPM for the blood circulatory system. LPM with individual parameters can output the individual physiological indicators after optimization, which are applicable for the numerical simulation of patient-specific hemodynamics.

Keywords: blood circulatory system, individual physiological indicators, lumped parameter model, optimization algorithm

Procedia PDF Downloads 118

Authors: Misuk Kim, Seokho Kang, Jehyuk Lee, Hyunchang Cho, Sungzoon Cho

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In semiconductor manufacturing, virtual metrology (VM) refers to methods to predict properties of a wafer based on machine parameters and sensor data of the production equipment, without performing the (costly) physical measurement of the wafer properties (Wikipedia). Additional benefits include avoidance of human bias and identification of important factors affecting the quality of the process which allow improving the process quality in the future. It is however rare to find VM applied to other areas of manufacturing. In this work, we propose to use VM to copper clad laminate (CCL) manufacturing. CCL is a core element of a printed circuit board (PCB) which is used in smartphones, tablets, digital cameras, and laptop computers. The manufacturing of CCL consists of three processes: Treating, lay-up, and pressing. Treating, the most important process among the three, puts resin on glass cloth, heat up in a drying oven, then produces prepreg for lay-up process. In this process, three important quality factors are inspected: Treated weight (T/W), Minimum Viscosity (M/V), and Gel Time (G/T). They are manually inspected, incurring heavy cost in terms of time and money, which makes it a good candidate for VM application. We developed prediction models of the three quality factors T/W, M/V, and G/T, respectively, with process variables, raw material, and environment variables. The actual process data was obtained from a CCL manufacturer. A variety of variable selection methods and learning algorithms were employed to find the best prediction model. We obtained prediction models of M/V and G/T with a high enough accuracy. They also provided us with information on “important” predictor variables, some of which the process engineers had been already aware and the rest of which they had not. They were quite excited to find new insights that the model revealed and set out to do further analysis on them to gain process control implications. T/W did not turn out to be possible to predict with a reasonable accuracy with given factors. The very fact indicates that the factors currently monitored may not affect T/W, thus an effort has to be made to find other factors which are not currently monitored in order to understand the process better and improve the quality of it. In conclusion, VM application to CCL’s treating process was quite successful. The newly built quality prediction model allowed one to reduce the cost associated with actual metrology as well as reveal some insights on the factors affecting the important quality factors and on the level of our less than perfect understanding of the treating process.

Keywords: copper clad laminate, predictive modeling, quality control, virtual metrology

Procedia PDF Downloads 332

Authors: Javed Mohammed

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Right now, bio-medical infrastructure lags well behind the curve. Our healthcare system is dispersed and disjointed; medical records are a bit of a mess; and we do not yet have the capacity to store and process the crazy amounts of data coming our way from widespread whole-genome sequencing. And then there are privacy issues. Despite these infrastructure challenges, some researchers are plunging into bio medical Big Data now, in hopes of extracting new and actionable knowledge. They are doing delving into molecular-level data to discover bio markers that help classify patients based on their response to existing treatments; and pushing their results out to physicians in novel and creative ways. Computer scientists and bio medical researchers are able to transform data into models and simulations that will enable scientists for the first time to gain a profound under-standing of the deepest biological functions. Solving biological problems may require High-Performance Computing HPC due either to the massive parallel computation required to solve a particular problem or to algorithmic complexity that may range from difficult to intractable. Many problems involve seemingly well-behaved polynomial time algorithms (such as all-to-all comparisons) but have massive computational requirements due to the large data sets that must be analyzed. High-throughput techniques for DNA sequencing and analysis of gene expression have led to exponential growth in the amount of publicly available genomic data. With the increased availability of genomic data traditional database approaches are no longer sufficient for rapidly performing life science queries involving the fusion of data types. Computing systems are now so powerful it is possible for researchers to consider modeling the folding of a protein or even the simulation of an entire human body. This research paper emphasizes the computational biology's growing need for high-performance computing and Big Data. It illustrates this article’s indispensability in meeting the scientific and engineering challenges of the twenty-first century, and how Protein Folding (the structure and function of proteins) and Phylogeny Reconstruction (evolutionary history of a group of genes) can use HPC that provides sufficient capability for evaluating or solving more limited but meaningful instances. This article also indicates solutions to optimization problems, and benefits Big Data and Computational Biology. The article illustrates the Current State-of-the-Art and Future-Generation Biology of HPC Computing with Big Data.

Keywords: high performance, big data, parallel computation, molecular data, computational biology

Procedia PDF Downloads 344

Authors: Yu-Wen Chen, Szu-Wei Huang, Chung-Hsiang Mu, Kelvin Cheng

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This paper developed a data-driven based model to deal with the causality between the Continuous Emission Monitoring System (CEMS, by Environmental Protection Administration, Taiwan) in industrial factories, and the air quality around environment. Compared to the heavy burden of traditional numerical models of regional weather and air pollution simulation, the lightweight burden of the proposed model can provide forecasting hourly with current observations of weather, air pollution and emissions from factories. The observation data are included wind speed, wind direction, relative humidity, temperature and others. The observations can be collected real time from Open APIs of civil IoT Taiwan, which are sourced from 439 weather stations, 10,193 qualitative air stations, 77 national quantitative stations and 140 CEMS quantitative industrial factories. This study completed a causal inference engine and gave an air pollution forecasting for the next 12 hours related to local industrial factories. The outcomes of the pollution forecasting are produced hourly with a grid resolution of 1km*1km on IIoTC (Industrial Internet of Things Cloud) and saved in netCDF4 format. The elaborated procedures to generate forecasts comprise data recalibrating, outlier elimination, Kriging Interpolation and particle tracking and random walk techniques for the mechanisms of diffusion and advection. The solution of these equations reveals the causality between factories emission and the associated air pollution. Further, with the aid of installed real-time flue emission (Total Suspension Emission, TSP) sensors and the mentioned forecasted air pollution map, this study also disclosed the converting mechanism between the TSP and PM2.5/PM10 for different region and industrial characteristics, according to the long-term data observation and calibration. These different time-series qualitative and quantitative data which successfully achieved a causal inference engine in cloud for factory management control in practicable. Once the forecasted air quality for a region is marked as harmful, the correlated factories are notified and asked to suppress its operation and reduces emission in advance.

Keywords: continuous emission monitoring system, total suspension particulates, causal inference, air pollution forecast, IoT

Procedia PDF Downloads 58

Authors: Sangwoo Han, Saeed Khaleghi Rahimian, Ying Liu

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Vehicle electrification is gaining momentum, and many car manufacturers promise to deliver more electric vehicle (EV) models to consumers in the coming years. In controlling the battery pack, the battery management system (BMS) must maintain optimal battery performance while ensuring the safety of a battery pack. Tasks related to battery performance include determining state-of-charge (SOC), state-of-power (SOP), state-of-health (SOH), cell balancing, and battery charging. Safety related functions include making sure cells operate within specified, static and dynamic voltage window and temperature range, derating power, detecting faulty cells, and warning the user if necessary. The BMS often utilizes an RC circuit model to model a Li-ion cell because of its robustness and low computation cost among other benefits. Because an equivalent circuit model such as the RC model is not a physics-based model, it can never be a prognostic model to predict battery state-of-health and avoid any safety risk even before it occurs. A physics-based Li-ion cell model, on the other hand, is more capable at the expense of computation cost. To avoid the high computation cost associated with a full-order model, many researchers have demonstrated the use of a single particle model (SPM) for BMS applications. One drawback associated with the single particle modeling approach is that it forces to use the average current density in the calculation. The SPM would be appropriate for simulating drive cycles where there is insufficient time to develop a significant current distribution within an electrode. However, under a continuous or high-pulse electrical load, the model may fail to predict cell voltage or Li⁺ plating potential. To overcome this issue, a multi-particle reduced-order model is proposed here. The use of multiple particles combined with either linear or nonlinear charge-transfer reaction kinetics enables to capture current density distribution within an electrode under any type of electrical load. To maintain computational complexity like that of an SPM, governing equations are solved sequentially to minimize iterative solving processes. Furthermore, the model is validated against a full-order model implemented in COMSOL Multiphysics.

Keywords: battery management system, physics-based li-ion cell model, reduced-order model, single-particle and multi-particle model

Procedia PDF Downloads 86

Authors: Alessandro Balbo, Gianvito Colucci, Matteo Nicoli, Laura Savoldi

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Hydrogen is expected to become a game changer in the energy transition, especially enabling sector coupling possibilities and the decarbonization of hard-to-abate end-uses. The Italian National Recovery and Resilience Plan identifies hydrogen as one of the key elements of the ecologic transition to meet international decarbonization objectives, also including it in several pilot projects for the early development in Italy. This matches the European energy strategy, which aims to make hydrogen a leading energy carrier of the future, setting ambitious goals to be accomplished by 2030. The huge efforts needed to achieve the announced targets require to carefully investigate of their feasibility in terms of economic expenditures and technical aspects. In order to quantitatively assess the hydrogen potential within the Italian context and the feasibility of the planned investments and projects, this work uses the TEMOA-Italy energy system model to study pathways to meet the strict objectives above cited. The possible hydrogen development has been studied both in the supply-side and demand-side of the energy system, also including storage options and distribution chains. The assessment comprehends alternative hydrogen production technologies involved in a competition market, reflecting the several possible investments declined by the Italian National Recovery and Resilience Plan to boost the development and spread of this infrastructure, including the sector coupling potential with natural gas through the currently existing infrastructure and CO2 capture for the production of synfuels. On the other hand, the hydrogen end-uses phase covers a wide range of consumption alternatives, from fuel-cell vehicles, for which both road and non-road transport categories are considered, to steel, and chemical industries uses and cogeneration for residential and commercial buildings. The model includes both high and low TRL technologies in order to provide a consistent outcome for the future decades as it does for the present day, and since it is developed through the use of an open-source code instance and database, transparency and accessibility are fully granted.

Keywords: decarbonization, energy system optimization models, hydrogen, open-source modeling, TEMOA

Procedia PDF Downloads 79

Authors: Glaoui Hachemi

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Wind has been proven as a cost effective and reliable energy source. Technological advancements over the last years have placed wind energy in a firm position to compete with conventional power generation technologies. Algeria has a vast uninhabited land area where the south (desert) represents the greatest part with considerable wind regime. In this paper, an analysis of wind energy utilization as a viable energy substitute in six selected sites widely distributed all over the south of Algeria is presented. In this presentation, wind speed frequency distributions data obtained from the Algerian Meteorological Office are used to calculate the average wind speed and the available wind power. The annual energy produced by the Fuhrlander FL 30 wind machine is obtained using two methods. The analysis shows that in the southern Algeria, at 10 m height, the available wind power was found to vary between 160 and 280 W/m2, except for Tamanrasset. The highest potential wind power was found at Adrar, with 88 % of the time the wind speed is above 3 m/s. Besides, it is found that the annual wind energy generated by that machine lie between 33 and 61 MWh, except for Tamanrasset, with only 17 MWh. Since the wind turbines are usually installed at a height greater than 10 m, an increased output of wind energy can be expected. However, the wind resource appears to be suitable for power production on the south and it could provide a viable substitute to diesel oil for irrigation pumps and electricity generation. In this paper, a model of the wind turbine (WT) with permanent magnet generator (PMSG) and its associated controllers is presented. The increase of wind power penetration in power systems has meant that conventional power plants are gradually being replaced by wind farms. In fact, today wind farms are required to actively participate in power system operation in the same way as conventional power plants. In fact, power system operators have revised the grid connection requirements for wind turbines and wind farms, and now demand that these installations be able to carry out more or less the same control tasks as conventional power plants. For dynamic power system simulations, the PMSG wind turbine model includes an aerodynamic rotor model, a lumped mass representation of the drive train system and generator model. In this paper, we propose a model with an implementation in MATLAB / Simulink, each of the system components off-grid small wind turbines.

Keywords: windgenerator systems, permanent magnet synchronous generator (PMSG), wind turbine (WT) modeling, MATLAB simulink environment

Procedia PDF Downloads 317

Authors: Mohamed Abdelkareem

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Remote sensing data contributed on predicting the prospective areas of water resources. Integration of microwave and multispectral data along with climatic, hydrologic, and geological data has been used here. In this article, Sentinel-2, Landsat-8 Operational Land Imager (OLI), Shuttle Radar Topography Mission (SRTM), Tropical Rainfall Measuring Mission (TRMM), and Advanced Land Observing Satellite (ALOS) Phased Array Type L‐band Synthetic Aperture Radar (PALSAR) data were utilized to identify the geological, hydrologic and structural features of Wadi Asyuti which represents a defunct tributary of the Nile basin, in the eastern Sahara. The image transformation of Sentinel-2 and Landsat-8 data allowed characterizing the different varieties of rock units. Integration of microwave remotely-sensed data and GIS techniques provided information on physical characteristics of catchments and rainfall zones that are of a crucial role for mapping groundwater prospective zones. A fused Landsat-8 OLI and ALOS/PALSAR data improved the structural elements that difficult to reveal using optical data. Lineament extraction and interpretation indicated that the area is clearly shaped by the NE-SW graben that is cut by NW-SE trend. Such structures allowed the accumulation of thick sediments in the downstream area. Processing of recent OLI data acquired on March 15, 2014, verified the flood potential maps and offered the opportunity to extract the extent of the flooding zone of the recent flash flood event (March 9, 2014), as well as revealed infiltration characteristics. Several layers including geology, slope, topography, drainage density, lineament density, soil characteristics, rainfall, and morphometric characteristics were combined after assigning a weight for each using a GIS-based knowledge-driven approach. The results revealed that the predicted groundwater potential zones (GPZs) can be arranged into six distinctive groups, depending on their probability for groundwater, namely very low, low, moderate, high very, high, and excellent. Field and well data validated the delineated zones.

Keywords: GIS, remote sensing, groundwater, Egypt

Procedia PDF Downloads 77

Authors: Ravi Inder Singh

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Due to high heat transfer rate, high carbon utilizing efficiency, fuel flexibilities and other advantages numerous circulating fluidized bed boilers have grown up in India in last decade. Many companies like BHEL, ISGEC, Thermax, Cethar Limited, Enmas GB Power Systems Projects Limited are making CFBC and installing the units throughout the India. Due to complexity many problems exists in CFBC units and only few have been reported. Agglomeration i.e clinker formation in riser, loop seal leg and stripper ash coolers is one of problem industry is facing. Proper documentation is rarely found in the literature. Circulating fluidized bed (CFB) boiler bottom ash contains large amounts of physical heat. While the boiler combusts the low-calorie fuel, the ash content is normally more than 40% and the physical heat loss is approximately 3% if the bottom ash is discharged without cooling. In addition, the red-hot bottom ash is bad for mechanized handling and transportation, as the upper limit temperature of the ash handling machinery is 200 °C. Therefore, a bottom ash cooler (BAC) is often used to treat the high temperature bottom ash to reclaim heat, and to have the ash easily handled and transported. As a key auxiliary device of CFB boilers, the BAC has a direct influence on the secure and economic operation of the boiler. There are many kinds of BACs equipped for large-scale CFB boilers with the continuous development and improvement of the CFB boiler. These ash coolers are water cooled ash cooling screw, rolling-cylinder ash cooler (RAC), fluidized bed ash cooler (FBAC).In this study prototype of a novel stripper ash cooler is studied. The Circulating Fluidized bed Ash Coolers (CFBAC) combined the major technical features of spouted bed and bubbling bed, and could achieve the selective discharge on the bottom ash. The novel stripper ash cooler is bubbling bed and it is visible cold test rig. The reason for choosing cold test is that high temperature is difficult to maintain and create in laboratory level. The aim of study to know the flow pattern inside the stripper ash cooler. The cold rig prototype is similar to stripper ash cooler used industry and it was made after scaling down to some parameter. The performance of a fluidized bed ash cooler is studied using a cold experiment bench. The air flow rate, particle size of the solids and air distributor type are considered to be the key parameters of the operation of a fluidized bed ash cooler (FBAC) are studied in this.

Keywords: CFD, Eulerian-Eulerian, Eulerian-Lagraingian model, parallel simulations

Procedia PDF Downloads 490

Authors: Mazlum Çelik, Burcu Gürkan Ercan, Ahmet Ayaz, Hilal Yakut İpekoğlu, Furkan Baltacı, Mustafa Kurtoğlu, Bilge Kalkavan, Sinem Küçükyılmaz, Hikmet Çağrı Yardımcı, Şeyma Sevgican, Cemile Gökçe Elkovan, Bilal Çayır, Mehmet Emin Düzcan

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The earthquake research literature generally examines emotional, cognitive, and behavioral responses after an earthquake. Studies concerning the behavioral responses to earthquakes reveal that after the earthquake, people either flee in a panic or do not act according to the stereotype that they act irrationally and anti-socially and sometimes give rational and adaptive reactions. However, the rareness of research dealing with human behavior experiencing the earthquake moment makes it necessary to pay particular attention to these behavior patterns. In this direction, this study aims to examine human behavior indoors in case of rising earthquake intensity. In Turkey, located on geography in the earthquake zone, devastating earthquakes took place, such as in "Istanbul" with a magnitude of 7.4 in 1999 and in "Elazığ" with a magnitude of 6.8 in 2020. Occurred recently, the "Kahramanmaraş" earthquake affected 11 provinces, with a magnitude of 7.7 and 7.6 in 2023. In addition, there is expected to be a devastating earthquake in Istanbul, experts warn. For this reason, it is essential to understand human behavior for disaster risk. Management and pre-disaster preparedness to be effective and efficient and to take realistic measures to protect human life. Mazlum Çelik, Burcu Gürkan Ercan, Ahmet Ayaz, Hilal Yakut İpekoğlu, Furkan Baltacı, Mustafa Kurtoğlu, Bilge Kalkavan, Sinem Küçükyılmaz, Hikmet Çağrı Yardımcı, Şeyma Sevgican, Cemile Gökçe Elkovan, Bilal Çayır, Mehmet Emin Düzcan. In this study, which is currently part of a project supported by The Scientific and Technological Council of Turkey (TUBITAK), the indoor recordings during the earthquakes in Elazig on January 24, 2020, and in İzmir on October 30, 2020, are examined, and the people's behavior during the earthquake is analyzed. In this direction, video recordings taken from the YouTube archives of İzmir and Elazığ Disaster and Emergency Management Presidency (AFAD) Directorates and metropolitan municipalities are examined. The researchers have created an observation form in line with the information in the relevant literature to classify people's behavior during an earthquake. It is intended to determine the behavioral patterns by classifying according to the form and video analysis of the people heading toward the door, remaining stable, taking protective measures, turning to people, and engaging in "other" behaviors outside of these behaviors during the earthquake. A total of 60 video analyzes are carried out from Elazığ and İzmir. The descriptive statistic has been used with the SPSS 23.0 package program in the data analysis. It is found that in the event of an increase in the severity of the earthquake, unlike Elazığ, in İzmir, protective action is preferred to the act of remaining stable. In addition, it is observed that with the increase in the earthquake's intensity, women attempt to take more protective action while men head toward the door. In contrast, a rise is observed in the behavior of young people heading toward the door and taking protective actions, while there is a decrease in their behavior directing to people. These findings, unlike the literature, reveal that human behavior during earthquakes cannot be reduced to a single behavior pattern, such as drop-cover-hold-on. The results show that it is necessary to understand the behaviors of individuals during the earthquake and to develop practical policy proposals for combating earthquakes by considering sociocultural, geographical, and demographic variables.

Keywords: descriptive analysis, earthquake, human behaviour, disaster policy.

Procedia PDF Downloads 68

Authors: Melis Inalpulat, Levent Genc

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Land Use Land Cover (LULC) changes due to human activities and natural causes have become a major environmental concern. Assessment of temporal remote sensing data provides information about LULC impacts on environment. Land Surface Temperature (LST) is one of the important components for modeling environmental changes in climatological, hydrological, and agricultural studies. In this study, LULC changes (September 7, 1984 and July 8, 2014) especially in agricultural lands together with population changes (1985-2014) and LST status were investigated using remotely sensed and census data in South Marmara Watershed, Turkey. LULC changes were determined using Landsat TM and Landsat OLI data acquired in 1984 and 2014 summers. Six-band TM and OLI images were classified using supervised classification method to prepare LULC map including five classes including Forest (F), Grazing Land (G), Agricultural Land (A), Water Surface (W), and Residential Area-Bare Soil (R-B) classes. The LST image was also derived from thermal bands of the same dates. LULC classification results showed that forest areas, agricultural lands, water surfaces and residential area-bare soils were increased as 65751 ha, 20163 ha, 1924 ha and 20462 ha respectively. In comparison, a dramatic decrement occurred in grazing land (107985 ha) within three decades. The population increased % 29 between years 1984-2014 in whole study area. Along with the natural causes, migration also caused this increase since the study area has an important employment potential. LULC was transformed among the classes due to the expansion in residential, commercial and industrial areas as well as political decisions. In the study, results showed that agricultural lands around the settlement areas transformed to residential areas in 30 years. The LST images showed that mean temperatures were ranged between 26-32 °C in 1984 and 27-33 °C in 2014. Minimum temperature of agricultural lands was increased 3 °C and reached to 23 °C. In contrast, maximum temperature of A class decreased to 41 °C from 44 °C. Considering temperatures of the 2014 R-B class and 1984 status of same areas, it was seen that mean, min and max temperatures increased by 2 °C. As a result, the dynamism of population, LULC and LST resulted in increasing mean and maximum surface temperatures, living spaces/industrial areas and agricultural lands.

Keywords: census data, landsat, land surface temperature (LST), land use land cover (LULC)

Procedia PDF Downloads 371

Authors: Adan Valdez, Shawn Gallaher, James Morison, Jordan Aragon

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Global climate change has impacted atmospheric temperatures contributing to rising sea levels, decreasing sea ice, and increased freshening of high latitude oceans. This freshening has contributed to increased stratification inhibiting local mixing and nutrient transport and modifying regional circulations in polar oceans. In recent years, the Western Arctic has seen an increase in freshwater volume at an average rate of 397+-116 km3/year. The majority of the freshwater volume resides in the Beaufort Gyre surface lens driven by anticyclonic wind forcing, sea ice melt, and Arctic river runoff. The total climatological freshwater content is typically defined as water fresher than 34.8. The near-isothermal nature of Arctic seawater and non-linearities in the equation of state for near-freezing waters result in a salinity driven pycnocline as opposed to the temperature driven density structure seen in the lower latitudes. In this study, we investigate the relationship between freshwater content and remotely sensed dynamic ocean topography (DOT). In-situ measurements of freshwater content are useful in providing information on the freshening rate of the Beaufort Gyre; however, their collection is costly and time consuming. NASA’s Advanced Topographic Laser Altimeter System (ATLAS) derived dynamic ocean topography (DOT), and Air Expendable CTD (AXCTD) derived Freshwater Content are used to develop a linear regression model. In-situ data for the regression model is collected across the 150° West meridian, which typically defines the centerline of the Beaufort Gyre. Two freshwater content models are determined by integrating the freshwater volume between the surface and an isopycnal corresponding to reference salinities of 28.7 and 34.8. These salinities correspond to those of the winter pycnocline and total climatological freshwater content, respectively. Using each model, we determine the strength of the linear relationship between freshwater content and satellite derived DOT. The result of this modeling study could provide a future predictive capability of freshwater volume changes in the Beaufort-Chukchi Sea using non in-situ methods. Successful employment of the ICESat-2’s DOT approximation of freshwater content could potentially reduce reliance on field deployment platforms to characterize physical ocean properties.

Keywords: ICESat-2, dynamic ocean topography, freshwater content, beaufort gyre

Procedia PDF Downloads 58

Authors: Christoph Opperer

Abstract:

The rapid urbanization of modern societies and the need for sustainable urban development demand innovative solutions that meet both individual and collective needs while addressing environmental concerns. To address these challenges, this paper presents a study that explores the potential of spatial and energetic/ecological optimization to enhance the performance of urban settlements, focusing on both architectural and urban scales. The study focuses on the application of biological principles and self-organization processes in urban planning and design, aiming to achieve a balance between ecological performance, architectural quality, and individual living conditions. The research adopts a case study approach, focusing on a 10-hectare brownfield site in the south of Vienna. The site is surrounded by a small-scale built environment as an appropriate starting point for the research and design process. However, the selected urban form is not a prerequisite for the proposed design methodology, as the findings can be applied to various urban forms and densities. The methodology used in this research involves dividing the overall building mass and program into individual small housing units. A computational model has been developed to optimize the distribution of these units, considering factors such as solar exposure/radiation, views, privacy, proximity to sources of disturbance (such as noise), and minimal internal circulation areas. The model also ensures that existing vegetation and buildings on the site are preserved and incorporated into the optimization and design process. The model allows for simultaneous optimization at two scales, architectural and urban design, which have traditionally been addressed sequentially. This holistic design approach leads to individual and collective benefits, resulting in urban environments that foster a balance between ecology and architectural quality. The results of the optimization process demonstrate a seemingly random distribution of housing units that, in fact, is a densified hybrid between traditional garden settlements and allotment settlements. This urban typology is selected due to its compatibility with the surrounding urban context, although the presented methodology can be extended to other forms of urban development and density levels. The benefits of this approach are threefold. First, it allows for the determination of ideal housing distribution that optimizes solar radiation for each building density level, essentially extending the concept of sustainable building to the urban scale. Second, the method enhances living quality by considering the orientation and positioning of individual functions within each housing unit, achieving optimal views and privacy. Third, the algorithm's flexibility and robustness facilitate the efficient implementation of urban development with various stakeholders, architects, and construction companies without compromising its performance. The core of the research is the application of global and local optimization strategies to create efficient design solutions. By considering both, the performance of individual units and the collective performance of the urban aggregation, we ensure an optimal balance between private and communal benefits. By promoting a holistic understanding of urban ecology and integrating advanced optimization strategies, our methodology offers a sustainable and efficient solution to the challenges of modern urbanization.

Keywords: sustainable development, self-organization, ecological performance, solar radiation and exposure, daylight, visibility, accessibility, spatial distribution, local and global optimization

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Authors: Shu-Ling Wang

Abstract:

Background: Multiple studies showed early skin-to-skin contact (SSC) with mothers was beneficial to newborns such as breastfeeding and maternal childcare. In cases of newborns unable to have early SSC with mothers, fathers’ involvement could let early SSC continue without interruption. However, few studies had explored the effects of early SSC by fathers in comparison to early SSC with mothers. Paternal involvement of early SSC should be equally important in term of childcare and breastfeeding. The purpose of this study was to evaluate the efficacy of early SSC by fathers in particular in their support of breastfeeding. Methods: A quasi-experimental design was employed by the study. One hundred and forty-four father-infant pairs had participated the study, in which infants were assigned either to SSC with their fathers (n = 72) or to routine care (n = 72) as the control group. The study was conducted at a regional hospital in northern Taiwan. Participants included parents of both vaginal delivery (VD) and caesarean section birth (CS) infants. To be eligible for inclusion, infants must be over 37-week gestational ages. Data were collected twice: as pretest upon admission and as posttest with online questionnaire during first, second, and third postpartum months. The questionnaire included items for Breastfeeding Social Support, methods of feeding, and the mother-infant 24-hour rooming-in rate. The efficacy of early SSC with fathers was evaluated using the generalized estimating equation (GEE) modeling. Research Result: The primary finding was that SSC with fathers had positive impact on fathers’ support of breastfeeding. Analysis of the online questionnaire indicated that early SSC with fathers improved the support of breastfeeding than the control group (VD: t = -4.98, p < .001; CS: t = -2.37, p = .02). Analysis of mother-infant 24-hour rooming-in rate showed that SSC with fathers after CS had a positive impact on the rooming-in rate (χ² = 5.79, p = .02); however, with VD the difference between early SSC with fathers and the control group was insignificant (χ² = .23, p = .63). Analysis of the rate of exclusive breastfeeding indicated that early SSC with fathers had a higher rate than the control group during first three postpartum months for both delivery methods (VD: χ² = 12.51, p < .001 on 1st postpartum month, χ² = 8.13, p < .05 on 2nd postpartum month, χ² = 4.43, p < .05 on 3rd postpartum month; CS: χ² = 6.92, p < .05 on 1st postpartum month, χ² = 7.41, p < .05 on 2nd postpartum month, χ² = 6.24, p < .05 on 3rd postpartum month). No significant difference was found on the rate of exclusive breastfeeding with both methods of delivery between two groups during hospitalization. (VD: χ² =2 .00, p = .16; CS: χ² = .73, p = .39). Conclusion: Implementing early SSC with fathers has many benefits to both parents. The result of this study showed increasing fathers’ support of breastfeeding. This encourages our nursing personnel to focus the needs of father during breastfeeding, therefore further enhancing the quality of parental care, the rate and duration of breastfeeding.

Keywords: breastfeeding, skin-to-skin contact, support of breastfeeding, rooming-in

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Authors: S. Cencek, A. Markun

Abstract:

Noise assessment methods are regularly used in scope of Environmental Impact Assessments for planned projects to assess (predict) the expected noise emissions of these projects. Different noise assessment methods could be used. In recent years, we had an opportunity to collaborate in some noise assessment procedures where noise assessments of different laboratories have been performed simultaneously. We identified some significant differences in noise assessment results between laboratories in Slovenia. We estimate that despite good input Georeferenced Data to set up acoustic model exists in Slovenia; there is no clear consensus on methods for predictive noise methods for planned projects. We analyzed input data, methods and results of predictive noise methods for two planned industrial projects, both were done independently by two laboratories. We also analyzed the data, methods and results of two interlaboratory collaborative noise models for two existing noise sources (railway and motorway). In cases of predictive noise modelling, the validations of acoustic models were performed by noise measurements of surrounding existing noise sources, but in varying durations. The acoustic characteristics of existing buildings were also not described identically. The planned noise sources were described and digitized differently. Differences in noise assessment results between different laboratories have ranged up to 10 dBA, which considerably exceeds the acceptable uncertainty ranged between 3 to 6 dBA. Contrary to predictive noise modelling, in cases of collaborative noise modelling for two existing noise sources the possibility to perform the validation noise measurements of existing noise sources greatly increased the comparability of noise modelling results. In both cases of collaborative noise modelling for existing motorway and railway, the modelling results of different laboratories were comparable. Differences in noise modeling results between different laboratories were below 5 dBA, which was acceptable uncertainty set up by interlaboratory noise modelling organizer. The lessons learned from the study were: 1) Predictive noise calculation using formulae from International standard SIST ISO 9613-2: 1997 is not an appropriate method to predict noise emissions of planned projects since due to complexity of procedure they are not used strictly, 2) The noise measurements are important tools to minimize noise assessment errors of planned projects and should be in cases of predictive noise modelling performed at least for validation of acoustic model, 3) National guidelines should be made on the appropriate data, methods, noise source digitalization, validation of acoustic model etc. in order to unify the predictive noise models and their results in scope of Environmental Impact Assessments for planned projects.

Keywords: environmental noise assessment, predictive noise modelling, spatial planning, noise measurements, national guidelines

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