Search results for: weather prediction

Authors: C. Silveira, A. Ascenso, J. Ferreira, A. I. Miranda, P. Tuccella, G. Curci

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Poor air quality is one of the main environmental causes of premature deaths worldwide, and mainly in cities, where the majority of the population lives. It is a consequence of successive land cover (LC) and use changes, as a result of the intensification of human activities. Knowing these landscape modifications in a comprehensive spatiotemporal dimension is, therefore, essential for understanding variations in air pollutant concentrations. In this sense, the use of air quality models is very useful to simulate the physical and chemical processes that affect the dispersion and reaction of chemical species into the atmosphere. However, the modelling performance should always be evaluated since the resolution of the input datasets largely dictates the reliability of the air quality outcomes. Among these data, the updated LC is an important parameter to be considered in atmospheric models, since it takes into account the Earth’s surface changes due to natural and anthropic actions, and regulates the exchanges of fluxes (emissions, heat, moisture, etc.) between the soil and the air. This work aims to evaluate the performance of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), when different LC classifications are used as an input. The influence of two LC classifications was tested: i) the 24-classes USGS (United States Geological Survey) LC database included by default in the model, and the ii) CLC (Corine Land Cover) and specific high-resolution LC data for Portugal, reclassified according to the new USGS nomenclature (33-classes). Two distinct WRF-Chem simulations were carried out to assess the influence of the LC on air quality over Europe and Portugal, as a case study, for the year 2015, using the nesting technique over three simulation domains (25 km², 5 km² and 1 km² horizontal resolution). Based on the 33-classes LC approach, particular emphasis was attributed to Portugal, given the detail and higher LC spatial resolution (100 m x 100 m) than the CLC data (5000 m x 5000 m). As regards to the air quality, only the LC impacts on tropospheric ozone concentrations were evaluated, because ozone pollution episodes typically occur in Portugal, in particular during the spring/summer, and there are few research works relating to this pollutant with LC changes. The WRF-Chem results were validated by season and station typology using background measurements from the Portuguese air quality monitoring network. As expected, a better model performance was achieved in rural stations: moderate correlation (0.4 – 0.7), BIAS (10 – 21µg.m^-3) and RMSE (20 – 30 µg.m^-3), and where higher average ozone concentrations were estimated. Comparing both simulations, small differences grounded on the Leaf Area Index and air temperature values were found, although the high-resolution LC approach shows a slight enhancement in the model evaluation. This highlights the role of the LC on the exchange of atmospheric fluxes, and stresses the need to consider a high-resolution LC characterization combined with other detailed model inputs, such as the emission inventory, to improve air quality assessment.

Keywords: land use, spatial resolution, WRF-Chem, air quality assessment

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Authors: Strahinja Kovacevic, Milica Karadzic Banjac, Jasmina Vitas, Stefan Vukmanovic, Radomir Malbasa, Lidija Jevric, Sanja Podunavac-Kuzmanovic

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The present study deals with chemometric regression analysis of quality parameters and the radical scavenging ability of kombucha fermented kefir-like products obtained with winter savory (WS), peppermint (P), stinging nettle (SN) and wild thyme tea (WT) kombucha inoculums. Each analyzed sample was described by milk fat content (MF, %), total unsaturated fatty acids content (TUFA, %), monounsaturated fatty acids content (MUFA, %), polyunsaturated fatty acids content (PUFA, %), the ability of free radicals scavenging (RSA Dₚₚₕ, % and RSA.ₒₕ, %) and pH values measured after each hour from the start until the end of fermentation. The aim of the conducted regression analysis was to establish chemometric models which can predict the radical scavenging ability (RSA Dₚₚₕ, % and RSA.ₒₕ, %) of the samples by correlating it with the MF, TUFA, MUFA, PUFA and the pH value at the beginning, in the middle and at the end of fermentation process which lasted between 11 and 17 hours, until pH value of 4.5 was reached. The analysis was carried out applying univariate linear (ULR) and multiple linear regression (MLR) methods on the raw data and the data standardized by the min-max normalization method. The obtained models were characterized by very limited prediction power (poor cross-validation parameters) and weak statistical characteristics. Based on the conducted analysis it can be concluded that the resulting radical scavenging ability cannot be precisely predicted only on the basis of MF, TUFA, MUFA, PUFA content, and pH values, however, other quality parameters should be considered and included in the further modeling. This study is based upon work from project: Kombucha beverages production using alternative substrates from the territory of the Autonomous Province of Vojvodina, 142-451-2400/2019-03, supported by Provincial Secretariat for Higher Education and Scientific Research of AP Vojvodina.

Keywords: chemometrics, regression analysis, kombucha, quality control

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Authors: Chen-Yu Chen, Ping-Hsueh We, Wei-Mon Yan

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Over the past few centuries, human requirements for energy have been met by burning fossil fuels. However, exploiting this resource has led to global warming and innumerable environmental issues. Thus, finding alternative solutions to the growing demands for energy has recently been driving the development of low-carbon and even zero-carbon energy sources. Wind power and solar energy are good options but they have the problem of unstable power output due to unpredictable weather conditions. To overcome this problem, a reliable and efficient energy storage sub-system is required in future distributed-power systems. Among all kinds of energy storage technologies, the fuel cell system with hydrogen storage is a promising option because it is suitable for large-scale and long-term energy storage. The high-temperature proton exchange membrane fuel cell (HT-PEMFC) with metallic bipolar plates is a promising fuel cell system because an HT-PEMFC can tolerate a higher CO concentration and the utilization of metallic bipolar plates can reduce the cost of the fuel cell stack. However, the operating life of metallic bipolar plates is a critical issue because of the corrosion phenomenon. As a result, in this work, we try to apply different coating layer on the metal surface and to investigate the protection performance of the coating layers. The tested bipolar plates include uncoated SS304 bipolar plates, titanium nitride (TiN) coated SS304 bipolar plates and chromium nitride (CrN) coated SS304 bipolar plates. The results show that the TiN coated SS304 bipolar plate has the lowest contact resistance and through-plane resistance and has the best cell performance and operating life among all tested bipolar plates. The long-term in-situ fuel cell tests show that the HT-PEMFC with TiN coated SS304 bipolar plates has the lowest performance decay rate. The second lowest is CrN coated SS304 bipolar plate. The uncoated SS304 bipolar plate has the worst performance decay rate. The performance decay rates with TiN coated SS304, CrN coated SS304 and uncoated SS304 bipolar plates are 5.324×10⁻³ % h⁻¹, 4.513×10⁻² % h⁻¹ and 7.870×10⁻² % h⁻¹, respectively. In addition, the EIS results indicate that the uncoated SS304 bipolar plate has the highest growth rate of ohmic resistance. However, the ohmic resistance with the TiN coated SS304 bipolar plates only increases slightly with time. The growth rate of ohmic resistances with TiN coated SS304, CrN coated SS304 and SS304 bipolar plates are 2.85×10⁻³ h⁻¹, 3.56×10⁻³ h⁻¹, and 4.33×10⁻³ h⁻¹, respectively. On the other hand, the charge transfer resistances with these three bipolar plates all increase with time, but the growth rates are all similar. In addition, the effective catalyst surface areas with all bipolar plates do not change significantly with time. Thus, it is inferred that the major reason for the performance degradation is the elevated ohmic resistance with time, which is associated with the corrosion and oxidation phenomena on the surface of the stainless steel bipolar plates.

Keywords: coating layer, high-temperature proton exchange membrane fuel cell, metallic bipolar plate, performance degradation

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Authors: Abdullah Alenezi, Mane Alsudrawi, Rafat Misak

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Kuwait is faced with a potentially wide and harmful range of both natural and anthropogenic hazardous events such as dust storms, floods, fires, nuclear accidents, earthquakes, oil spills, tsunamis and other disasters. For Kuwait can be highly vulnerable to these complex environmental risks, an up-to-date and in-depth understanding of their typology, genesis, and impact on the Kuwaiti society is needed. Adequate anticipation and management of environmental crises further require a comprehensive system of decision support to the benefit of decision makers to further bridge the gap between (technical) risk understanding and public action. For that purpose, the Kuwait Institute for Scientific Research (KISR), intends to establish a decision support center for management of the environmental crisis in Kuwait. The center will support policy makers, stakeholders and national committees with technical information that helps them efficiently and effectively assess, monitor to manage environmental disasters using decision support tools. These tools will build on state of the art quantification and visualization techniques, such as remote sensing information, Geographical Information Systems (GIS), simulation and prediction models, early warning systems, etc. The center is conceived as a central facility which will be designed, operated and managed by KISR in coordination with national authorities and decision makers of the country. Our vision is that by 2035 the center will be recognized as a leading national source of scientific advice on national risk management in Kuwait and build unity of effort among Kuwaiti’s institutions, government agencies, public and private organizations through provision and sharing of information. The project team now focuses on capacity building through upgrading some KISR facilities manpower development, build strong collaboration with international alliance.

Keywords: decision support, environment, hazard, Kuwait

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Authors: Devansh Desai, Rahul Nigam

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

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

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Authors: Xin Wu, Yongfeng Zhao, Qingxiang Meng

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In China, quite low proportion of crop residues were used as feedstuff because of its poor palatability and low digestibility. Steam explosion is a physical and chemical feed processing technology which has great potential to improve sapidity and digestibility of crop residues. To investigate the effect of the steam explosion on chemical compositions and efficient energy values, crop residues (rice straw, wheat straw and maize stover) were processed by steam explosion (steam temperature 120-230°C, steam pressure 2-26kg/cm², 40min). Steam-exploded crop residues were regarded as treatment groups and untreated ones as control groups, nutritive compositions were analyzed and effective energy values were calculated by prediction model in INRA (1988, 2010) for both groups. Results indicated that the interaction between treatment and variety has a significant effect on chemical compositions of crop residues. Steam explosion treatment of crop residues decreased neutral detergent fiber (NDF) significantly (P < 0.01), and compared with untreated material, NDF content of rice straw, wheat straw, and maize stover lowered 21.46%, 32.11%, 28.34% respectively. Acid detergent lignin (ADL) of crop residues increased significantly after the steam explosion (P < 0.05). The content of crude protein (CP), ether extract (EE) and Ash increased significantly after steam explosion (P < 0.05). Moreover, predicted effective energy values of each steam-exploded residue were higher than that of untreated ones. The digestible energy (DE), metabolizable energy (ME), net energy for maintenance (NEm) and net energy for gain (NEg)of steam-exploded rice straw were 3.06, 2.48, 1.48and 0.29 MJ/kg respectively and increased 46.21%, 46.25%, 49.56% and 110.92% compared with untreated ones(P < 0.05). Correspondingly, the energy values of steam-exploded wheat straw were 2.18, 1.76, 1.03 and 0.15 MJ/kg, which were 261.78%, 261.29%, 274.59% and 1014.69% greater than that of wheat straw (P < 0.05). The above predicted energy values of steam exploded maize stover were 5.28, 4.30, 2.67 and 0.82 MJ/kg and raised 109.58%, 107.71%, 122.57% and 332.64% compared with the raw material(P < 0.05). In conclusion, steam explosion treatment could significantly decrease NDF content, increase ADL, CP, EE, Ash content and effective energy values of crop residues. The effect of steam explosion was much more obvious for wheat straw than the other two kinds of residues under the same condition.

Keywords: chemical compositions, crop residues, efficient energy values, steam explosion

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Authors: Fulufhelo Amanda Doboro, Kgomotso Sebeko, Stephen Njiro, Moritz Van Vuuren

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Ovine herpesvirus 2 (OvHV-2) genome obtained from the lymphopblastoid cell line of a BJ1035 cow was recently sequenced in the United States of America (USA). Information on the sequences of OvHV-2 genes obtained from South African strains from bovine or other African countries and molecular characterization of OvHV-2 is not documented. Present investigation provides information on the nucleotide and derived amino acid sequences and genetic diversity of Ov 7, Ov 8 ex2, ORF 27 and ORF 73 genes, of these genes from OvHV-2 strains circulating in South Africa. Gene-specific primers were designed and used for PCR of DNA extracted from 42 bovine blood samples that previously tested positive for OvHV-2. The expected PCR products of 495 bp, 253 bp, 890 bp and 1632 bp respectively for Ov 7, Ov 8 ex2, ORF 27 and ORF 73 genes were sequenced and multiple sequence analysis done on the selected regions of the sequenced PCR products. Two genotypes for ORF 27 and ORF 73 gene sequences, and three genotypes for Ov 7 and Ov 8 ex2 gene sequences were identified, and similar groupings for the derived amino acid sequences were obtained for each gene. Nucleotide and amino acid sequence variations that led to the identification of the different genotypes included SNPs, deletions and insertions. Sequence analysis of Ov 7 and ORF 27 genes revealed variations that distinguished between sequences from SA and reference OvHV-2 strains. The implication of geographic origin among SA sequences was difficult to evaluate because of random distribution of genotypes in the different provinces, for each gene. However, socio-economic factors such as migration of people with animals, or transportation of animals for agricultural or business use from one province to another are most likely to be responsible for this observation. The sequence variations observed in this study have no impact on the antibody binding activities of glycoproteins encoded by Ov 7, Ov 8 ex2 and ORF 27 genes, as determined by prediction of the presence of B cell epitopes using BepiPred 1.0. The findings of this study will be used for selection of gene candidates for the development of diagnostic assays and vaccine development as well.

Keywords: amino acid, genetic diversity, genes, nucleotide

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Authors: Adriana Postal, Silvio C. Sampaio, Marcio A. Villas Boas, Josué P. Castro

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This study deals with the estimation of reference evapotranspiration (ET₀) in an agricultural context, focusing on efficient irrigation management to meet the growing interest in the sustainable management of water resources. Given the importance of water in agriculture and its scarcity in many regions, efficient use of this resource is essential to ensure food security and environmental sustainability. The methodology used involved the application of artificial intelligence techniques, specifically Multilayer Perceptron (MLP) Artificial Neural Networks (ANNs), to predict ET₀ in the state of Paraná, Brazil. The models were trained and validated with meteorological data from the Brazilian National Institute of Meteorology (INMET), together with data obtained from a producer's weather station in the western region of Paraná. Two optimizers (SGD and Adam) and different meteorological variables, such as temperature, humidity, solar radiation, and wind speed, were explored as inputs to the models. Nineteen configurations with different input variables were tested; amidst them, configuration 9, with 8 input variables, was identified as the most efficient of all. Configuration 10, with 4 input variables, was considered the most effective, considering the smallest number of variables. The main conclusions of this study show that MLP ANNs are capable of accurately estimating ET₀, providing a valuable tool for irrigation management in agriculture. Both configurations (9 and 10) showed promising performance in predicting ET₀. The validation of the models with cultivator data underlined the practical relevance of these tools and confirmed their generalization ability for different field conditions. The results of the statistical metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Coefficient of Determination (R²), showed excellent agreement between the model predictions and the observed data, with MAE as low as 0.01 mm/day and 0.03 mm/day, respectively. In addition, the models achieved an R² between 0.99 and 1, indicating a satisfactory fit to the real data. This agreement was also confirmed by the Kolmogorov-Smirnov test, which evaluates the agreement of the predictions with the statistical behavior of the real data and yields values between 0.02 and 0.04 for the producer data. In addition, the results of this study suggest that the developed technique can be applied to other locations by using specific data from these sites to further improve ET₀ predictions and thus contribute to sustainable irrigation management in different agricultural regions. The study has some limitations, such as the use of a single ANN architecture and two optimizers, the validation with data from only one producer, and the possible underestimation of the influence of seasonality and local climate variability. An irrigation management application using the most efficient models from this study is already under development. Future research can explore different ANN architectures and optimization techniques, validate models with data from multiple producers and regions, and investigate the model's response to different seasonal and climatic conditions.

Keywords: agricultural technology, neural networks in agriculture, water efficiency, water use optimization

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

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

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

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Authors: Nehal F. Hassib, Rasha M. El Hossini, Inas M. Sayed, Maha R. Abouzeid, Nermeen A. Bayoumi, Aida M. Mosaad, Lamia K. Gadallah, Moataz Bellah A. T. Abdelbari, Heba A. El-Sayed, Hasnaa Elbendary, Ghada Abdel-Salam, Maha Zaki, Mostafa I. Mostafa, Mohamed S. Abdel-Hamid

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Enamel, the outermost layer of the tooth crown, is the hardest dental tissue and serves as a protective barrier. Amelogenesis, the process of enamel formation, is regulated by multiple genes to ensure normal, defect-free enamel. Defective enamel manifests as hypoplasia or as amelogenesis imperfecta (AI), which may occur in isolation or as part of a syndrome. This study presents 29 patients from 18 unrelated families (16 females and 13 males) who exhibited distinctive enamel abnormalities. We conducted thorough clinical examinations and requested laboratory and radiological investigations. Blood samples were collected for molecular analysis, utilizing a targeted panel for known AI variants and whole exome sequencing for unknown variants. Eleven variants linked to enamel anomalies were identified: four genes associated with isolated AI (WDR72, ACP4, SLC24A4, and FAM83H) and seven associated with syndromic forms, including enamel renal syndrome (FAM20A), tricho-dento-osseous syndrome (DLX3), Jalili syndrome (CNNM4), and others linked to neurological and mitochondrial disorders, skeletal dysplasia, and peroxisome disorders. Abnormal oral and dental phenotypes in individuals may indicate serious inherited disorders. Enamel defects have significant implications for aesthetics, function, and patients' psychological well-being. Dental examination, alongside clinical and molecular investigations, is crucial for the accurate diagnosis and prediction of inherited conditions.

Keywords: amelogenesis imperfecta, enamel defect, Enamel renal syndrome, DLX3, Jalili syndrome, WDR72, FAM83H, whole exome sequencing

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Authors: Oyatayo Kehinde Taofik, Ndabula Christopher

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Drainage basins are a central theme in the green economy. The rising challenges in flooding, erosion or sediment transport and sedimentation threaten the green economy. This has led to increasing emphasis on quantitative analysis of drainage basin parameters for better understanding, estimation and prediction of fluvial responses and, thus associated hazards or disasters. This can be achieved through direct measurement, characterization, parameterization, or modeling. This study applied the Remote Sensing and Geographic Information System approach of parameterization and characterization of the morphometric variables of Katsina – Ala basin using a 30 m resolution Shuttle Radar Topographic Mission (SRTM) Digital Elevation Model (DEM). This was complemented with topographic and hydrological maps of Katsina-Ala on a scale of 1:50,000. Linear, areal and relief parameters were characterized. The result of the study shows that Ala and Udene sub-watersheds are 4th and 5th order basins, respectively. The stream network shows a dendritic pattern, indicating homogeneity in texture and a lack of structural control in the study area. Ala and Udene sub-watersheds have the following values for elongation ratio, circularity ratio, form factor and relief ratio: 0.48 / 0.39 / 0.35/ 9.97 and 0.40 / 0.35 / 0.32 / 6.0. They also have the following values for drainage texture and ruggedness index of 0.86 / 0.011 and 1.57 / 0.016. The study concludes that the two sub-watersheds are elongated, suggesting that they are susceptible to erosion and, thus higher sediment load in the river channels, which will dispose the watersheds to higher flood peaks. The study also concludes that the sub-watersheds have a very coarse texture, with good permeability of subsurface materials and infiltration capacity, which significantly recharge the groundwater. The study recommends that efforts should be put in place by the Local and State Governments to reduce the size of paved surfaces in these sub-watersheds by implementing a robust agroforestry program at the grass root level.

Keywords: erosion, flood, mitigation, morphometry, watershed

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Authors: Sung-Jun Yoo, Kazuhide Ito

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In this study, a comprehensive computer simulated person (CSP) that integrates computational human model (virtual manikin) and respiratory tract model (virtual airway), was applied for estimation of indoor environmental quality. Moreover, an inclusive prediction method was established by integrating computational fluid dynamics (CFD) analysis with advanced CSP which is combined with physiologically-based pharmacokinetic (PBPK) model, unsteady thermoregulation model for analysis targeting micro-climate around human body and respiratory area with high accuracy. This comprehensive method can estimate not only the contaminant inhalation but also constant interaction in the contaminant transfer between indoor spaces, i.e., a target area for indoor air quality (IAQ) assessment, and respiratory zone for health risk assessment. This study focused on the usage of the CSP as an air/thermal quality sensor in indoors, which means the application of comprehensive model for assessment of IAQ and thermal environmental quality. Demonstrative analysis was performed in order to examine the applicability of the comprehensive model to the heating, ventilation, air conditioning (HVAC) control scheme. CSP was located at the center of the simple model room which has dimension of 3m×3m×3m. Formaldehyde which is generated from floor material was assumed as a target contaminant, and flow field, sensible/latent heat and contaminant transfer analysis in indoor space were conducted by using CFD simulation coupled with CSP. In this analysis, thermal comfort was evaluated by thermoregulatory analysis, and respiratory exposure risks represented by adsorption flux/concentration at airway wall surface were estimated by PBPK-CFD hybrid analysis. These Analysis results concerning IAQ and thermal comfort will be fed back to the HVAC control and could be used to find a suitable ventilation rate and energy requirement for air conditioning system.

Keywords: CFD simulation, computer simulated person, HVAC control, indoor environmental quality

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Authors: Alan Crowle, Philpp Thies

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As the floating offshore wind turbine industry continues to develop and grow, the capabilities of established port facilities need to be assessed as to their ability to support the expanding construction and installation requirements. This paper assesses current infrastructure requirements and projected changes to port facilities that may be required to support the floating offshore wind industry. Understanding the infrastructure needs of the floating offshore renewable industry will help to identify the port-related requirements. Floating Offshore Wind Turbines can be installed further out to sea and in deeper waters than traditional fixed offshore wind arrays, meaning that it can take advantage of stronger winds. Separate ports are required for substructure construction, fit-out of the turbines, moorings, subsea cables and maintenance. Large areas are required for the laydown of mooring equipment; inter-array cables, turbine blades and nacelles. The capabilities of established port facilities to support floating wind farms are assessed by evaluation of the size of substructures, the height of wind turbine with regards to the cranes for fitting of blades, distance to offshore site and offshore installation vessel characteristics. The paper will discuss the advantages and disadvantages of using large land-based cranes, inshore floating crane vessels or offshore crane vessels at the fit-out port for the installation of the turbine. Water depths requirements for import of materials and export of the completed structures will be considered. There are additional costs associated with any emerging technology. However part of the popularity of Floating Offshore Wind Turbines stems from the cost savings against permanent structures like fixed wind turbines. Floating Offshore Wind Turbine developers can benefit from lighter, more cost-effective equipment which can be assembled in port and towed to the site rather than relying on large, expensive installation vessels to transport and erect fixed bottom turbines. The ability to assemble Floating Offshore Wind Turbines equipment onshore means minimizing highly weather-dependent operations like offshore heavy lifts and assembly, saving time and costs and reducing safety risks for offshore workers. Maintenance might take place in safer onshore conditions for barges and semi-submersibles. Offshore renewables, such as floating wind, can take advantage of this wealth of experience, while oil and gas operators can deploy this experience at the same time as entering the renewables space The floating offshore wind industry is in the early stages of development and port facilities are required for substructure fabrication, turbine manufacture, turbine construction and maintenance support. The paper discusses the potential floating wind substructures as this provides a snapshot of the requirements at the present time, and potential technological developments required for commercial development. Scaling effects of demonstration-scale projects will be addressed, however, the primary focus will be on commercial-scale (30+ units) device floating wind energy farms.

Keywords: floating wind, port, marine construction, offshore renewables

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Authors: Ramzi Suleiman

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Recently, the author proposed an observationally-based relativity theory termed information relativity theory (IRT). The theory is simple and is based only on basic principles, with no prior axioms and no free parameters. For the case of a body of mass in uniform rectilinear motion relative to an observer, the theory transformations uncovered a matter-dark matter duality, which prescribes that the sum of the densities of the body's baryonic matter and dark matter, as measured by the observer, is equal to the body's matter density at rest. It was shown that the theory transformations were successful in predicting several important phenomena in small particle physics, quantum physics, and cosmology. This paper extends the theory transformations to the cases of rotating disks and spheres. The resulting transformations for a rotating disk are utilized to derive predictions of the radial distributions of matter and dark matter densities in rotationally supported galaxies based solely on their observed rotation curves. It is also shown that for galaxies with flattening curves, good approximations of the radial distributions of matter and dark matter and of the dark matter fraction could be obtained from one measurable scale radius. Test of the model on five galaxies, chosen randomly from the SPARC database, yielded impressive predictions. The rotation curves of all the investigated galaxies emerged as accurate traces of the predicted radial density distributions of their dark matter. This striking result raises an intriguing physical explanation of gravity in galaxies, according to which it is the proximal drag of the stars and gas in the galaxy by its rotating dark matter web. We conclude by alluding briefly to the application of the proposed model to stellar systems and black holes. This study also hints at the potential of the discovered matter-dark matter duality in fixing the standard model of elementary particles in a natural manner without the need for hypothesizing about supersymmetric particles.

Keywords: dark matter, galaxies rotation curves, SPARC, rotating disk

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Authors: Hasen Keder Edris, Ryuji Matsunaga, Toshi Yamanaka

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The issue of climate change and its impact is a major contemporary global concern. Ethiopia is one of the countries experiencing adverse climate change impact including frequent extreme weather events that are exacerbating drought and water scarcity. Due to this reason, the government of Ethiopia develops a strategic document which focuses on the climate resilience green economy. One of the major components of the strategic framework is designed to improve community adaptation capacity and mitigation of drought. For effective implementation of the strategy, identification of regions relative vulnerability to drought is vital. There is a growing tendency of applying Geographic Information System (GIS) and Remote Sensing technologies for collecting information on duration and severity of drought by direct measure of the topography as well as an indirect measure of land cover. This study aims to show an application of remote sensing technology and GIS for developing drought vulnerability index by taking lowland of Ethiopia as a case study. In addition, it assesses integrated Information Communication Technology (ICT) potential of Ethiopia lowland and proposes integrated solution. Satellite data is used to detect the beginning of the drought. The severity of drought risk prone areas of livestock keeping pastoral is analyzed through normalized difference vegetation index (NDVI) and ten years rainfall data. The change from the existing and average SPOT NDVI and vegetation condition index is used to identify the onset of drought and potential risks. Secondary data is used to analyze geographical coverage of mobile and internet usage in the region. For decades, the government of Ethiopia introduced some technologies and approach to overcoming climate change related problems. However, lack of access to information and inadequate technical support for the pastoral area remains a major challenge. In conventional business as usual approach, the lowland pastorals continue facing a number of challenges. The result indicated that 80% of the region face frequent drought occurrence and out of this 60% of pastoral area faces high drought risk. On the other hand, the target area mobile phone and internet coverage is rapidly growing. One of identified ICT solution enabler technology is telecom center which covers 98% of the region. It was possible to identify the frequently affected area and potential drought risk using the NDVI remote-sensing data analyses. We also found that ICT can play an important role in mitigating climate change challenge. Hence, there is a need to strengthen implementation efforts of climate change adaptation through integrated Remote Sensing and web based information dissemination and mobile alert of extreme events.

Keywords: climate changes, ICT, pastoral, remote sensing

Procedia PDF Downloads 315

Authors: Abderrhamane Jarou, Dominique Sauter, Christophe Aubrun

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Over the past decade, the growing demand for energy efficiency in buildings has attracted the attention of the control community. Failures in HVAC (heating, ventilation and air conditioning) systems in buildings can have a significant impact on the desired and expected energy performance of buildings and on the user's comfort as well. FTC is a recent technology area that studies the adaptation of control algorithms to faulty operating conditions of a system. The application of Fault-Tolerant Control (FTC) in HVAC systems has gained attention in the last two decades. The objective is to maintain the variations in system performance due to faults within an acceptable range with respect to the desired nominal behavior. This paper considers the so-called active approach, which is based on fault and identification scheme combined with a control reconfiguration algorithm that consists in determining a new set of control parameters so that the reconfigured performance is "as close as possible, "in some sense, to the nominal performance. Thermal models of buildings and their HVAC systems are described by non-linear (usually bi-linear) equations. Most of the works carried out so far in FDI (fault diagnosis and isolation) or FTC consider a linearized model of the studied system. However, this model is only valid in a reduced range of variation. This study presents a new fault diagnosis (FD) algorithm based on a bilinear observer for the detection and accurate estimation of the magnitude of the HVAC system failure. The main contribution of the proposed FD algorithm is that instead of using specific linearized models, the algorithm inherits the structure of the actual bilinear model of the building thermal dynamics. As an immediate consequence, the algorithm is applicable to a wide range of unpredictable operating conditions, i.e., weather dynamics, outdoor air temperature, zone occupancy profile. A bilinear fault detection observer is proposed for a bilinear system with unknown inputs. The residual vector in the observer design is decoupled from the unknown inputs and, under certain conditions, is made sensitive to all faults. Sufficient conditions are given for the existence of the observer and results are given for the explicit computation of observer design matrices. Dedicated observer schemes (DOS) are considered for sensor FDI while unknown input bilinear observers are considered for actuator or system components FDI. The proposed strategy for FTC works as follows: At a first level, FDI algorithms are implemented, making it also possible to estimate the magnitude of the fault. Once the fault is detected, the fault estimation is then used to feed the second level and reconfigure the control low so that that expected performances are recovered. This paper is organized as follows. A general structure for fault-tolerant control of buildings is first presented and the building model under consideration is introduced. Then, the observer-based design for Fault Diagnosis of bilinear systems is studied. The FTC approach is developed in Section IV. Finally, a simulation example is given in Section V to illustrate the proposed method.

Keywords: bilinear systems, fault diagnosis, fault-tolerant control, multi-zones building

Procedia PDF Downloads 172

Authors: Victor N. Anisimov, Igor E. Serov, Ksenia M. Kolkova, Natalia V. Galkina

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The problem of memorability of the advertising content is closely connected with the key issues of neuromarketing. The memorability of the advertising content contributes to the marketing effectiveness of the promoted product. Significant directions of studying the phenomenon of memorability are the memorability of the brand (detected through the memorability of the logo) and the memorability of the product offer (detected through the memorization of dynamic audiovisual advertising content - commercial). The aim of this work is to reveal the predictors of memorization of static and dynamic audiovisual stimuli (logos and commercials). An important direction of the research was revealing differences in psychophysiological correlates of memorability between static and dynamic audiovisual stimuli. We assumed that static and dynamic images are perceived in different ways and may have a difference in the memorization process. Objective methods of recording psychophysiological parameters while watching static and dynamic audiovisual materials are well suited to achieve the aim. The electroencephalography (EEG) method was performed with the aim of identifying correlates of the memorability of various stimuli in the electrical activity of the cerebral cortex. All stimuli (in the groups of statics and dynamics separately) were divided into 2 groups – remembered and not remembered based on the results of the questioning method. The questionnaires were filled out by survey participants after viewing the stimuli not immediately, but after a time interval (for detecting stimuli recorded through long-term memorization). Using statistical method, we developed the classifier (statistical model) that predicts which group (remembered or not remembered) stimuli gets, based on psychophysiological perception. The result of the statistical model was compared with the results of the questionnaire. Conclusions: Predictors of the memorability of static and dynamic stimuli have been identified, which allows prediction of which stimuli will have a higher probability of remembering. Further developments of this study will be the creation of stimulus memory model with the possibility of recognizing the stimulus as previously seen or new. Thus, in the process of remembering the stimulus, it is planned to take into account the stimulus recognition factor, which is one of the most important tasks for neuromarketing.

Keywords: memory, commercials, neuromarketing, EEG, branding

Procedia PDF Downloads 251

Authors: Pavel Borodkin, Nikolay Khrennikov, Azamat Gazetdinov

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The problem of ensuring of VVER type reactor equipment integrity is now most actual in connection with justification of safety of the NPP Units and extension of their service life to 60 years and more. First of all, it concerns old units with VVER-440 and VVER-1000. The justification of the VVER equipment integrity depends on the reliability of estimation of the degree of the equipment damage. One of the mandatory requirements, providing the reliability of such estimation, and also evaluation of VVER equipment lifetime, is the monitoring of equipment radiation loading parameters. In this connection, there is a problem of justification of such normative parameters, used for an estimation of the pressure vessel metal embrittlement, as the fluence and fluence rate (FR) of fast neutrons above 0.5 MeV. From the point of view of regulatory practice, a comparison of displacement per atom (DPA) and fast neutron fluence (FNF) above 0.5 MeV has a practical concern. In accordance with the Russian regulatory rules, neutron fluence F(E > 0.5 MeV) is a radiation exposure parameter used in steel embrittlement prediction under neutron irradiation. However, the DPA parameter is a more physically legitimate quantity of neutron damage of Fe based materials. If DPA distribution in reactor structures is more conservative as neutron fluence, this case should attract the attention of the regulatory authority. The purpose of this work was to show what radiation load parameters (fluence, DPA) on all VVER equipment should be under control, and give the reasonable estimations of such parameters in the volume of all equipment. The second task is to give the conservative estimation of each parameter including its uncertainty. Results of recently received investigations allow to test the conservatism of calculational predictions, and, as it has been shown in the paper, combination of ex-vessel measured data with calculated ones allows to assess unpredicted uncertainties which are results of specific unique features of individual equipment for VVER reactor. Some results of calculational-experimental investigations are presented in this paper.

Keywords: equipment integrity, fluence, displacement per atom, nuclear power plant, neutron activation measurements, neutron transport calculations

Procedia PDF Downloads 157

Authors: Lukasz Mierczak, Patrick Denke, Piotr Klimczyk, Stefan Siebert

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Due to the high complexity of the magnetization in electrical machines and influence of the manufacturing processes on the magnetic properties of their components, the assessment and prediction of hysteresis and eddy current losses has remained a challenge. In the design process of electric motors and generators, the power losses of stators and rotors are calculated based on the material supplier’s data from standard magnetic measurements. This type of data does not include the additional loss from non-sinusoidal multi-harmonic motor excitation nor the detrimental effects of residual stress remaining in the motor laminations after manufacturing processes, such as punching, housing shrink fitting and winding. Moreover, in production, considerable attention is given to the measurements of mechanical dimensions of stator and rotor cores, whereas verification of their magnetic properties is typically neglected, which can lead to inconsistent efficiency of assembled motors. Therefore, to enable a comprehensive characterization of motor materials and components, Brockhaus Measurements developed a range of in-line and offline measurement technologies for testing their magnetic properties under actual motor operating conditions. Multiple sets of experimental data were obtained to evaluate the influence of various factors, such as elevated temperature, applied and residual stress, and arbitrary magnetization on the magnetic properties of different grades of non-oriented steel. Measured power loss for tested samples and stator cores varied significantly, by more than 100%, comparing to standard measurement conditions. Quantitative effects of each of the applied measurement were analyzed. This research and applied Brockhaus measurement methodologies emphasized the requirement for advanced characterization of magnetic materials used in electric drives and automotive applications.

Keywords: magnetic materials, measurement technologies, permanent magnets, stator and rotor cores

Procedia PDF Downloads 140

Authors: Suneet Jagdev, Hrishabh Amrodia, Siddharth Menon, Abhishek Singh, Mansi Shivhare

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Delhi, the National Capital, has undergone a surge in development rate, consequently engendering an unprecedented increase in population. Over the years the city has transformed into a car-centric infrastructure with high-speed corridors, flyovers and fast lanes. A considerable section of the population is hankering to rehabilitate to the good old cycling days, in order to contribute towards a green environment as well as to maintain their physical well-being. Furthermore, an extant section of Delhi’s population relies on cycles as their primary means of commuting in the city. Delhi has the highest number of cyclists and second highest number of pedestrians in the country. However, the tumultuous problems of unregulated traffic, inadequate space on roads, adverse weather conditions stifle them to opt for cycling. Lately, the city has been facing a conglomeration of problems such as haphazard traffic movement, clogged roads, congestion, pollution, accidents, safety issues, etc. In 1957, Delhi’s cyclists accounted for 36 per cent of trips which dropped down to a mere 4 per cent in 2008. The declining rate is due to unsafe roads and lack of proper cycle lanes. Now as the 10 percent of the city has cycle tracks. There is also a lack of public recreational activities in the city. These conundrums incite the need of a covered elevated cycling bridge track to facilitate the safe and smooth cycle commutation in the city which would also serve the purpose of an alternate urban public space over the cycle bridge reducing the cost as well as the space requirement for the same, developing a user–friendly transportation and public interaction system for urban areas in the city. Based on the archival research methodologies, the following research draws information and extracts records from the data accounts of the Delhi Metro Rail Corporation Ltd. as well as the Centre for Science and Environment, India. This research will predominantly focus on developing a prototype design for high speed elevated bicycle lanes based on different road typologies, which can be replicated with minor variations in similar situations, all across the major cities of our country including the proposed smart cities. Furthermore, how these cycling lanes could be utilized for the place making process accommodating cycle parking and renting spaces, public recreational spaces, food courts as well as convenient shopping facilities with appropriate optimization. How to preserve and increase the share of smooth and safe cycling commute cycling for the routine transportation of the urban community of the polluted capital which has been on a steady decline over the past few decades.

Keywords: bicycle track, prototype, road safety, urban spaces

Procedia PDF Downloads 159

Authors: Esther Mafunda, Simbarashe Muparangi

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The present paper tests the applicability of the Regression Hypothesis on the pathological language dissolution of a Shona male adult with Broca’s aphasia. It particularly assesses the prediction of the Regression Hypothesis, which states that the process according to which language is forgotten will be the reversal of the process according to which it will be acquired. The main aim of the paper is to find out whether mirror symmetries between L1 acquisition and L1 dissolution of tense in Shona and, if so, what might cause these regression patterns. The paper also sought to highlight the practical contributions that Linguistic theory can make to solving language-related problems. Data was collected from a 46-year-old male adult with Broca’s aphasia who was receiving speech therapy at St Giles Rehabilitation Centre in Harare, Zimbabwe. The primary data elicitation method was experimental, using the probe technique. The TART (Test for Assessing Reference Time) Shona version in the form of sequencing pictures was used to access tense by Broca’s aphasic and 3.5-year-old child. Using the SPSS (Statistical Package for Social Studies) and Excel analysis, it was established that the use of the future tense was impaired in Shona Broca’s aphasic whilst the present and past tense was intact. However, though the past tense was intact in the male adult with Broca’s aphasic, a reference to the remote past was made. The use of the future tense was also found to be difficult for the 3,5-year-old speaking child. No difficulties were encountered in using the present and past tenses. This means that mirror symmetries were found between L1 acquisition and L1 dissolution of tense in Shona. On the basis of the results of this research, it can be concluded that the use of tense in a Shona adult with Broca’s aphasia supports the Regression Hypothesis. The findings of this study are important in terms of speech therapy in the context of Zimbabwe. The study also contributes to Bantu linguistics in general and to Shona linguistics in particular. Further studies could also be done focusing on the rest of the Bantu language varieties in terms of aphasia.

Keywords: Broca’s Aphasia, regression hypothesis, Shona, language dissolution

Procedia PDF Downloads 96

Authors: Paula Marín, Mohammad Saffari, Alvaro de Gracia, Luisa F. Cabeza, Svetlana Ushak

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Climate control represents an important issue when referring to energy consumption of buildings and associated expenses, both in installation or operation periods. The climate control of a building relies on several factors. Among them, localization, orientation, architectural elements, sources of energy used, are considered. In order to study the thermal behaviour of a building set up, the present study proposes the use of energy simulation program Energy Plus. In recent years, energy simulation programs have become important tools for evaluation of thermal/energy performance of buildings and facilities. Besides, the need to find new forms of passive conditioning in buildings for energy saving is a critical component. The use of phase change materials (PCMs) for heat storage applications has grown in importance due to its high efficiency. Therefore, the climatic conditions of Northern Chile: high solar radiation and extreme temperature fluctuations ranging from -10°C to 30°C (Calama city), low index of cloudy days during the year are appropriate to take advantage of solar energy and use passive systems in buildings. Also, the extensive mining activities in northern Chile encourage the use of large numbers of containers to harbour workers during shifts. These containers are constructed with lightweight construction systems, requiring heating during night and cooling during day, increasing the HVAC electricity consumption. The use of PCM can improve thermal comfort and reduce the energy consumption. The objective of this study was to evaluate the thermal and energy performance of containers of 2.5×2.5×2.5 m3, located in four cities of Chile: Antofagasta, Calama, Santiago, and Concepción. Lightweight envelopes, typically used in these building prototypes, were evaluated considering a container without PCM inclusion as the reference building and another container with PCM-enhanced envelopes as a test case, both of which have a door and a window in the same wall, orientated in two directions: North and South. To see the thermal response of these containers in different seasons, the simulations were performed considering a period of one year. The results show that higher energy savings for the four cities studied are obtained when the distribution of door and window in the container is in the north direction because of higher solar radiation incidence. The comparison of HVAC consumption and energy savings in % for north direction of door and window are summarised. Simulation results show that in the city of Antofagasta 47% of heating energy could be saved and in the cities of Calama and Concepción the biggest savings in terms of cooling could be achieved since PCM reduces almost all the cooling demand. Currently, based on simulation results, four containers have been constructed and sized with the same structural characteristics carried out in simulations, that are, containers with/without PCM, with door and window in one wall. Two of these containers will be placed in Antofagasta and two containers in a copper mine near to Calama, all of them will be monitored for a period of one year. The simulation results will be validated with experimental measurements and will be reported in the future.

Keywords: energy saving, lightweight construction, PCM, simulation

Procedia PDF Downloads 285

Authors: Oscar E. Cariceo, Claudia V. Casal

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Machine learning offers a set of techniques to promote social work interventions and can lead to support decisions of practitioners in order to predict new behaviors based on data produced by the organizations, services agencies, users, clients or individuals. Machine learning techniques include a set of generalizable algorithms that are data-driven, which means that rules and solutions are derived by examining data, based on the patterns that are present within any data set. In other words, the goal of machine learning is teaching computers through 'examples', by training data to test specifics hypothesis and predict what would be a certain outcome, based on a current scenario and improve that experience. Machine learning can be classified into two general categories depending on the nature of the problem that this technique needs to tackle. First, supervised learning involves a dataset that is already known in terms of their output. Supervising learning problems are categorized, into regression problems, which involve a prediction from quantitative variables, using a continuous function; and classification problems, which seek predict results from discrete qualitative variables. For social work research, machine learning generates predictions as a key element to improving social interventions on complex social issues by providing better inference from data and establishing more precise estimated effects, for example in services that seek to improve their outcomes. This paper exposes the results of a classification algorithm to predict cyberbullying among adolescents. Data were retrieved from the National Polyvictimization Survey conducted by the government of Chile in 2017. A logistic regression model was created to predict if an adolescent would experience cyberbullying based on the interaction and behavior of gender, age, grade, type of school, and self-esteem sentiments. The model can predict with an accuracy of 59.8% if an adolescent will suffer cyberbullying. These results can help to promote programs to avoid cyberbullying at schools and improve evidence based practice.

Keywords: cyberbullying, evidence based practice, machine learning, social work research

Procedia PDF Downloads 168

Authors: Shrawan Baghel, Helen Cathcart, Biall J. O'Reilly

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Amorphous drug formulations have great potential to enhance solubility and thus bioavailability of BCS class II drugs. However, the higher free energy and molecular mobility of the amorphous form lowers the activation energy barrier for crystallization and thermodynamically drives it towards the crystalline state which makes them unstable. Accurate determination of the crystallization tendency/kinetics is the key to the successful design and development of such systems. In this study, dipyridamole (DPM) and cinnarizine (CNZ) has been selected as model compounds. Thermodynamic fragility (m_T) is measured from the heat capacity change at the glass transition temperature (Tg) whereas dynamic fragility (m_D) is evaluated using methods based on extrapolation of configurational entropy to zero 〖(m〗_(D_CE )), and heating rate dependence of Tg 〖(m〗_(D_Tg)). The mean relaxation time of amorphous drugs was calculated from Vogel-Tammann-Fulcher (VTF) equation. Furthermore, the correlation between fragility and glass forming ability (GFA) of model drugs has been established and the relevance of these parameters to crystallization of amorphous drugs is also assessed. Moreover, the crystallization kinetics of model drugs under isothermal conditions has been studied using Johnson-Mehl-Avrami (JMA) approach to determine the Avrami constant ‘n’ which provides an insight into the mechanism of crystallization. To further probe into the crystallization mechanism, the non-isothermal crystallization kinetics of model systems was also analysed by statistically fitting the crystallization data to 15 different kinetic models and the relevance of model-free kinetic approach has been established. In addition, the crystallization mechanism for DPM and CNZ at each extent of transformation has been predicted. The calculated fragility, glass forming ability (GFA) and crystallization kinetics is found to be in good correlation with the stability prediction of amorphous solid dispersions. Thus, this research work involves a multidisciplinary approach to establish fragility, GFA and crystallization kinetics as stability predictors for amorphous drug formulations.

Keywords: amorphous, fragility, glass forming ability, molecular mobility, mean relaxation time, crystallization kinetics, stability

Procedia PDF Downloads 354

Authors: Olga Hernán-Vega, Patricia López-Rodríguez, David Escot-Bocanegra, Raúl Fernández-Recio, Ignacio Bravo

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Non-Cooperative Target Identification has become a key research domain in the Defense industry since it provides the ability to recognize targets at long distance and under any weather condition. High Resolution Range Profiles, one-dimensional radar images where the reflectivity of a target is projected onto the radar line of sight, are widely used for identification of flying targets. According to that, to face this problem, an approach to Non-Cooperative Target Identification based on the exploitation of Singular Value Decomposition to a matrix of range profiles is presented. Target Identification based on one-dimensional radar images compares a collection of profiles of a given target, namely test set, with the profiles included in a pre-loaded database, namely training set. The classification is improved by using Singular Value Decomposition since it allows to model each aircraft as a subspace and to accomplish recognition in a transformed domain where the main features are easier to extract hence, reducing unwanted information such as noise. Singular Value Decomposition permits to define a signal subspace which contain the highest percentage of the energy, and a noise subspace which will be discarded. This way, only the valuable information of each target is used in the recognition process. The identification algorithm is based on finding the target that minimizes the angle between subspaces and takes place in a transformed domain. Two metrics, F1 and F2, based on Singular Value Decomposition are accomplished in the identification process. In the case of F2, the angle is weighted, since the top vectors set the importance in the contribution to the formation of a target signal, on the contrary F1 simply shows the evolution of the unweighted angle. In order to have a wide database or radar signatures and evaluate the performance, range profiles are obtained through numerical simulation of seven civil aircraft at defined trajectories taken from an actual measurement. Taking into account the nature of the datasets, the main drawback of using simulated profiles instead of actual measured profiles is that the former implies an ideal identification scenario, since measured profiles suffer from noise, clutter and other unwanted information and simulated profiles don't. In this case, the test and training samples have similar nature and usually a similar high signal-to-noise ratio, so as to assess the feasibility of the approach, the addition of noise has been considered before the creation of the test set. The identification results applying the unweighted and weighted metrics are analysed for demonstrating which algorithm provides the best robustness against noise in an actual possible scenario. So as to confirm the validity of the methodology, identification experiments of profiles coming from electromagnetic simulations are conducted, revealing promising results. Considering the dissimilarities between the test and training sets when noise is added, the recognition performance has been improved when weighting is applied. Future experiments with larger sets are expected to be conducted with the aim of finally using actual profiles as test sets in a real hostile situation.

Keywords: HRRP, NCTI, simulated/synthetic database, SVD

Procedia PDF Downloads 354

Authors: Asma Abdullah, Awais Khan, Reem Al-Ghumlasi, Pritam Kumari, Yasir Nawaz

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Introduction: This study verified the potential applications of two Oblique Wing configurations that were initiated by the Germans Aerodynamicists during the WWII. Due to the end of the war, this project was not completed and in this research is targeting the revival of German Oblique biplane configuration. The research draws upon the use of two Oblique wings mounted on the top and bottom of the fuselage through a single pivot. The wings are capable of sweeping at different angles ranging from 0° at takeoff to 60° at cruising Altitude. The top wing, right half, behaves like a forward swept wing and the left half, behaves like a backward swept wing. Vice Versa applies to the lower wing. This opposite deflection of the top and lower wing cancel out the rotary moment created by each wing and the aircraft remains stable. Problem to better understand or solve: The purpose of this research is to investigate the potential of achieving improved aerodynamic performance and efficiency of flight at a wide range of sweep angles. This will help examine the most accurate value for the sweep angle at which the aircraft will possess both stability and better aerodynamics. Explaining the methods used: The Aircraft configuration is designed using Solidworks after which a series of Aerodynamic prediction are conducted, both in the subsonic and the supersonic flow regime. Computations are carried on Ansys Fluent. The results are then compared to theoretical and flight data of different Supersonic fighter aircraft of the same category (AD-1) and with the Wind tunnel testing model at subsonic speed. Results: At zero sweep angle, the aircraft has an excellent lift coefficient value with almost double that found for fighter jets. In acquiring of supersonic speed the sweep angle is increased to maximum 60 degrees depending on the mission profile. General findings: Oblique biplane can be the future fighter jet aircraft because of its high value performance in terms of aerodynamics, cost, structural design and weight.

Keywords: biplane, oblique wing, sweep angle, supercritical airfoil

Procedia PDF Downloads 278

Authors: Juan Du

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Climate change is one of the most crucial issues of this era, with contentious debates on it among scholars. But there are sparse studies on climate change discourse in China. Including China in the study of climate change is essential for a sociological understanding of climate change. China -- as a developing country and an essential player in tackling climate change -- offers an ideal case for studying climate change for scholars moving beyond developed countries and enriching their understandings of climate change by including diverse social settings. This project contrasts the macro- and micro-level understandings of climate change in China, which helps scholars move beyond a focus on climate skepticism and denialism and enriches sociology of climate change knowledge. The macro-level understanding of climate change is obtained by analyzing over 4,000 newspaper articles from various official outlets in China. State-controlled newspapers play an essential role in transmitting essential and high-quality information and promoting broader public understanding of climate change and its anthropogenic nature. Thus, newspaper articles can be seen as tools employed by governments to mobilize the public in terms of supporting the development of a strategy shift from economy-growth to an ecological civilization. However, media is just one of the significant factors influencing an individual’s climate change concern. Extreme weather events, access to accurate scientific information, elite cues, and movement/countermovement advocacy influence an individual’s perceptions of climate change. Hence, there are differences in the ways that both newspaper articles and the public frame the issues. The online forum is an informative channel for scholars to understand the public’s opinion. The micro-level data comes from Zhihu, which is China’s equivalence of Quora. Users can propose, answer, and comment on questions. This project analyzes the questions related to climate change which have over 20 answers. By open-coding both the macro- and micro-level data, this project will depict the differences between ideology as presented in government-controlled newspapers and how people talk and act with respect to climate change in cyberspace, which may provide an idea about any existing disconnect in public behavior and their willingness to change daily activities to facilitate a greener society. The contemporary Yellow Vest protests in France illustrate that the large gap between governmental policies of climate change mitigation and the public’s understanding may lead to social movement activity and social instability. Effective environmental policy is impossible without the public’s support. Finding existing gaps in understanding may help policy-makers develop effective ways of framing climate change and obtain more supporters of climate change related policies. Overall, this qualitative project provides answers to the following research questions: 1) How do different state-controlled newspapers transmit their ideology on climate change to the public and in what ways? 2) How do individuals frame climate change online? 3) What are the differences between newspapers’ framing and individual’s framing?

Keywords: climate change, China, framing theory, media, public’s climate change concern

Procedia PDF Downloads 131

Authors: Babatunde Dosumu, Obuks Ejohwomu, Akilu Yunusa-Kaltungo

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Cost estimation in construction is often difficult, particularly when dealing with risks and uncertainties, which are inevitable and peculiar to developing countries like Nigeria. Direct consequences of these are major deviations in cost, duration, and quality. The fundamental aim of this study is to develop a framework for assessing the impacts of risk on cost estimation, which in turn causes variabilities between contract sum and final account. This is very important, as initial estimates given to clients should reflect the certain magnitude of consistency and accuracy, which the client builds other planning-related activities upon, and also enhance the capabilities of construction industry professionals by enabling better prediction of the final account from the contract sum. In achieving this, a systematic literature review was conducted with cost variability and construction projects as search string within three databases: Scopus, Web of science, and Ebsco (Business source premium), which are further analyzed and gap(s) in knowledge or research discovered. From the extensive review, it was found that factors causing deviation between final accounts and contract sum ranged between 1 and 45. Besides, it was discovered that a cost estimation framework similar to Building Cost Information Services (BCIS) is unavailable in Nigeria, which is a major reason why initial estimates are very often inconsistent, leading to project delay, abandonment, or determination at the expense of the huge sum of money invested. It was concluded that the development of a cost estimation framework that is adjudged an important tool in risk shedding rather than risk-sharing in project risk management would be a panacea to cost estimation problems, leading to cost variability in the Nigerian construction industry by the time this ongoing Ph.D. research is completed. It was recommended that practitioners in the construction industry should always take into account risk in order to facilitate the rapid development of the construction industry in Nigeria, which should give stakeholders a more in-depth understanding of the estimation effectiveness and efficiency to be adopted by stakeholders in both the private and public sectors.

Keywords: cost variability, construction projects, future studies, Nigeria

Procedia PDF Downloads 209

Authors: Baladitya Swaika, Rahul Khatry

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Computer Adaptive Tests (CATs) is one of the most efficient ways for testing the cognitive abilities of students. CATs are based on Item Response Theory (IRT) which is based on item selection and ability estimation using statistical methods of maximum information selection/selection from posterior and maximum-likelihood (ML)/maximum a posteriori (MAP) estimators respectively. This study aims at combining both classical and Bayesian approaches to IRT to create a dataset which is then fed to a neural network which automates the process of ability estimation and then comparing it to traditional CAT models designed using IRT. This study uses python as the base coding language, pymc for statistical modelling of the IRT and scikit-learn for neural network implementations. On creation of the model and on comparison, it is found that the Neural Network based model performs 7-10% worse than the IRT model for score estimations. Although performing poorly, compared to the IRT model, the neural network model can be beneficially used in back-ends for reducing time complexity as the IRT model would have to re-calculate the ability every-time it gets a request whereas the prediction from a neural network could be done in a single step for an existing trained Regressor. This study also proposes a new kind of framework whereby the neural network model could be used to incorporate feature sets, other than the normal IRT feature set and use a neural network’s capacity of learning unknown functions to give rise to better CAT models. Categorical features like test type, etc. could be learnt and incorporated in IRT functions with the help of techniques like logistic regression and can be used to learn functions and expressed as models which may not be trivial to be expressed via equations. This kind of a framework, when implemented would be highly advantageous in psychometrics and cognitive assessments. This study gives a brief overview as to how neural networks can be used in adaptive testing, not only by reducing time-complexity but also by being able to incorporate newer and better datasets which would eventually lead to higher quality testing.

Keywords: computer adaptive tests, item response theory, machine learning, neural networks

Procedia PDF Downloads 175

Authors: Soledad Carinelli, Iñigo Fernández, José Luis González-Mora, Pedro A. Salazar-Carballo

Abstract:

Mastitis is the most relevant inflammatory disease in cattle, affecting the animal health and causing important economic losses on dairy farms. This disease takes place in the mammary gland or udder when some opportunistic microorganisms, such as Staphylococcus aureus, Streptococcus agalactiae, Corynebacterium bovis, etc., invade the teat canal. According to the severity of the inflammation, mastitis can be classified as sub-clinical, clinical and chronic. Standard methods for mastitis detection include counts of somatic cells, cell culture, electrical conductivity of the milk, and California test (evaluation of “gel-like” matrix consistency after cell lysed with detergents). However, these assays present some limitations for accurate detection of subclinical mastitis. Currently, haptoglobin, an acute phase protein, has been proposed as novel and effective biomarker for mastitis detection. In this work, an electrochemical biosensor based on polydopamine-modified magnetic nanoparticles (MNPs@pDA) for haptoglobin detection is reported. Thus, MNPs@pDA has been synthesized by our group and functionalized with hemoglobin due to its high affinity to haptoglobin protein. The protein was labeled with specific antibodies modified with alkaline phosphatase enzyme for its electrochemical detection using an electroactive substrate (1-naphthyl phosphate) by differential pulse voltammetry. After the optimization of assay parameters, the haptoglobin determination was evaluated in milk. The strategy presented in this work shows a wide range of detection, achieving a limit of detection of 43 ng/mL. The accuracy of the strategy was determined by recovery assays, being of 84 and 94.5% for two Hp levels around the cut off value. Milk real samples were tested and the prediction capacity of the electrochemical biosensor was compared with a Haptoglobin commercial ELISA kit. The performance of the assay has demonstrated this strategy is an excellent and real alternative as screen method for sub-clinical bovine mastitis detection.

Keywords: bovine mastitis, haptoglobin, electrochemistry, magnetic nanoparticles, polydopamine

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