Search results for: weighted equilibrium

Authors: Te Kīpa Kēpa B. Morgan, Oliver W. Mcmillan, Dylan N. Taute, Tumanako N. Fa'aui

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Epistemologies are ways of knowing. Indigenous Peoples are aware that they do not perceive and experience the world in the same way as others. So it is important when empowering Indigenous epistemologies, such as that of the New Zealand Māori, to also be able to represent a scientific understanding within the same analysis. A geothermal development assessment tool has been developed by adapting the Mauri Model Decision Making Framework. Mauri is a metric that is capable of representing the change in the life-supporting capacity of things and collections of things. The Mauri Model is a method of grouping mauri indicators as dimension averages in order to allow holistic assessment and also to conduct sensitivity analyses for the effect of worldview bias. R-shiny is the coding platform used for this Vision Mātauranga research which has created an expert decision support tool (DST) that combines a stakeholder assessment of worldview bias with an impact assessment of mauri-based indicators to determine the sustainability of proposed geothermal development. The initial intention was to develop guidelines for quantifying mātauranga Māori impacts related to geothermal resources. To do this, three typical scenarios were considered: a resource owner wishing to assess the potential for new geothermal development; another party wishing to assess the environmental and cultural impacts of the proposed development; an assessment that focuses on the holistic sustainability of the resource, including its surface features. Indicator sets and measurement thresholds were developed that are considered necessary considerations for each assessment context and these have been grouped to represent four mauri dimensions that mirror the four well-being criteria used for resource management in Aotearoa, New Zealand. Two case studies have been conducted to test the DST suitability for quantifying mātauranga Māori and other biophysical factors related to a geothermal system. This involved estimating mauri0meter values for physical features such as temperature, flow rate, frequency, colour, and developing indicators to also quantify qualitative observations about the geothermal system made by Māori. A retrospective analysis has then been conducted to verify different understandings of the geothermal system. The case studies found that the expert DST is useful for geothermal development assessment, especially where hapū (indigenous sub-tribal grouping) are conflicted regarding the benefits and disadvantages of their’ and others’ geothermal developments. These results have been supplemented with evaluations for the cumulative impacts of geothermal developments experienced by different parties using integration techniques applied to the time history curve of the expert DST worldview bias weighted plotted against the mauri0meter score. Cumulative impacts represent the change in resilience or potential of geothermal systems, which directly assists with the holistic interpretation of change from an Indigenous Peoples’ perspective.

Keywords: decision support tool, holistic geothermal assessment, indigenous knowledge, mauri model decision-making framework

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Authors: Kang Lin Peng

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Space tourism emerged in 2001 and became famous in 2021, following the development of space technology. The space market is twisted because of the excess demand. Space tourism is currently rare and extremely expensive, with biased luxury product pricing, which is the seller’s market that consumers can not bargain with. Spaceship companies such as Virgin Galactic, Blue Origin, and Space X have been charged space tourism prices from 200 thousand to 55 million depending on various heights in space. There should be a reasonable price based on a fair basis. This study aims to derive a spacetime pricing model, which is different from the general pricing model on the earth’s surface. We apply general relativity theory to deduct the mathematical formula for the space tourism pricing model, which covers the traditional time-independent model. In the future, the price of space travel will be different from current flight travel when space travel is measured in lightyear units. The pricing of general commodities mainly considers the general equilibrium of supply and demand. The pricing model considers risks and returns with the dependent time variable as acceptable when commodities are on the earth’s surface, called flat spacetime. Current economic theories based on the independent time scale in the flat spacetime do not consider the curvature of spacetime. Current flight services flying the height of 6, 12, and 19 kilometers are charging with a pricing model that measures time coordinate independently. However, the emergence of space tourism is flying heights above 100 to 550 kilometers that have enlarged the spacetime curvature, which means tourists will escape from a zero curvature on the earth’s surface to the large curvature of space. Different spacetime spans should be considered in the pricing model of space travel to echo general relativity theory. Intuitively, this spacetime commodity needs to consider changing the spacetime curvature from the earth to space. We can assume the value of each spacetime curvature unit corresponding to the gradient change of each Ricci or energy-momentum tensor. Then we know how much to spend by integrating the spacetime from the earth to space. The concept is adding a price p component corresponding to the general relativity theory. The space travel pricing model degenerates into a time-independent model, which becomes a model of traditional commodity pricing. The contribution is that the deriving of the space tourism pricing model will be a breakthrough in philosophical and practical issues for space travel. The results of the space tourism pricing model extend the traditional time-independent flat spacetime mode. The pricing model embedded spacetime as the general relativity theory can better reflect the rationality and accuracy of space travel on the universal scale. The universal scale from independent-time scale to spacetime scale will bring a brand-new pricing concept for space traveling commodities. Fair and efficient spacetime economics will also bring to humans’ travel when we can travel in lightyear units in the future.

Keywords: space tourism, spacetime pricing model, general relativity theory, spacetime curvature

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Authors: Jacob Schwartz, Maxim Durach, Aniruddha Mitra, Abbas Rashidi, Glen Sage, Atin Adhikari

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NIOSH (National Institute for Occupational Safety and Health) approved N95 respirators are commonly used by workers in construction sites where there is a large amount of dust being produced from sawing, grinding, blasting, welding, etc., both electrostatically charged and not. A significant portion of airborne particles in construction sites could be nanoparticles created beside coarse particles. The penetration of the particles through the masks may differ depending on the size and charge of the individual particle. In field experiments relevant to this current study, we found that nanoparticles of medium size ranges are penetrating more frequently than nanoparticles of smaller and larger sizes. For example, penetration percentages of nanoparticles of 11.5 – 27.4 nm into a sealed N95 respirator on a manikin head ranged from 0.59 to 6.59%, whereas nanoparticles of 36.5 – 86.6 nm ranged from 7.34 to 16.04%. The possible causes behind this increased penetration of mid-size nanoparticles through mask filters are not yet explored. The objective of this study is to identify causes behind this unusual behavior of mid-size nanoparticles. We have considered such physical factors as Boltzmann distribution of the particles in thermal equilibrium with the air, kinetic energy of the particles at impact on the mask, Stoke’s drag force, and electrostatic forces in the mask stopping the particles. When the particles collide with the mask, only the particles that have enough kinetic energy to overcome the energy loss due to the electrostatic forces and the Stokes’ drag in the mask can pass through the mask. To understand this process, the following assumptions were made: (1) the effect of Stoke’s drag depends on the particles’ velocity at entry into the mask; (2) the electrostatic force is proportional to the charge on the particles, which in turn is proportional to the surface area of the particles; (3) the general dependence on electrostatic charge and thickness means that for stronger electrostatic resistance in the masks and thicker the masks’ fiber layers the penetration of particles is reduced, which is a sensible conclusion. In sampling situations where one mask was soaked in alcohol eliminating electrostatic interaction the penetration was much larger in the mid-range than the same mask with electrostatic interaction. The smaller nanoparticles showed almost zero penetration most likely because of the small kinetic energy, while the larger sized nanoparticles showed almost negligible penetration most likely due to the interaction of the particle with its own drag force. If there is no electrostatic force the fraction for larger particles grows. But if the electrostatic force is added the fraction for larger particles goes down, so diminished penetration for larger particles should be due to increased electrostatic repulsion, may be due to increased surface area and therefore larger charge on average. We have also explored the effect of ambient temperature on nanoparticle penetrations and determined that the dependence of the penetration of particles on the temperature is weak in the range of temperatures in the measurements 37-42°C, since the factor changes in the range from 3.17 10-3K-1 to 3.22 10-3K-1.

Keywords: respiratory protection, industrial hygiene, aerosol, electrostatic force

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Authors: Edgar Santoyo, Daniel Perez-Zarate, Agustin Acevedo, Lorena Diaz-Gonzalez, Mirna Guevara

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Four new gas geothermometers have been derived from a multivariate geo chemometric analysis of a geothermal fluid chemistry database, two of which use the natural logarithm of CO₂ and H2S concentrations (mmol/mol), respectively, and the other two use the natural logarithm of the H₂S/H₂ and CO₂/H₂ ratios. As a strict compilation criterion, the database was created with gas-phase composition of fluids and bottomhole temperatures (BHTM) measured in producing wells. The calibration of the geothermometers was based on the geochemical relationship existing between the gas-phase composition of well discharges and the equilibrium temperatures measured at bottomhole conditions. Multivariate statistical analysis together with the use of artificial neural networks (ANN) was successfully applied for correlating the gas-phase compositions and the BHTM. The predicted or simulated bottomhole temperatures (BHTANN), defined as output neurons or simulation targets, were statistically compared with measured temperatures (BHTM). The coefficients of the new geothermometers were obtained from an optimized self-adjusting training algorithm applied to approximately 2,080 ANN architectures with 15,000 simulation iterations each one. The self-adjusting training algorithm used the well-known Levenberg-Marquardt model, which was used to calculate: (i) the number of neurons of the hidden layer; (ii) the training factor and the training patterns of the ANN; (iii) the linear correlation coefficient, R; (iv) the synaptic weighting coefficients; and (v) the statistical parameter, Root Mean Squared Error (RMSE) to evaluate the prediction performance between the BHTM and the simulated BHTANN. The prediction performance of the new gas geothermometers together with those predictions inferred from sixteen well-known gas geothermometers (previously developed) was statistically evaluated by using an external database for avoiding a bias problem. Statistical evaluation was performed through the analysis of the lowest RMSE values computed among the predictions of all the gas geothermometers. The new gas geothermometers developed in this work have been successfully used for predicting subsurface temperatures in high-temperature geothermal systems of Mexico (e.g., Los Azufres, Mich., Los Humeros, Pue., and Cerro Prieto, B.C.) as well as in a blind geothermal system (known as Acoculco, Puebla). The last results of the gas geothermometers (inferred from gas-phase compositions of soil-gas bubble emissions) compare well with the temperature measured in two wells of the blind geothermal system of Acoculco, Puebla (México). Details of this new development are outlined in the present research work. Acknowledgements: The authors acknowledge the funding received from CeMIE-Geo P09 project (SENER-CONACyT).

Keywords: artificial intelligence, gas geochemistry, geochemometrics, geothermal energy

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Authors: Eglal Y. Ali, Smita Rao, Anat Lubetzky, Wen Ling

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Background: Postural abnormalities, rigidity, clumsiness, and frequent falls are common among children with autism spectrum disorders (ASD). The central nervous system’s ability to process all reliable sensory inputs (weighting) and disregard potentially perturbing sensory input (reweighting) is critical for successfully maintaining standing postural control. This study examined how sensory inputs (visual and somatosensory) are weighted and reweighted to maintain standing postural control in children with ASD compared with typically developing (TD) children. Subjects: Forty (20 (TD) and 20 ASD) children and adolescents participated in this study. The groups were matched for age, weight, and height. Participants had normal somatosensory (no somatosensory hypersensitivity), visual, and vestibular perception. Participants with ASD were categorized with severity level 1 according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) and Social Responsiveness Scale. Methods: Using one force platform, the center of pressure (COP) was measured during quiet standing for 30 seconds, 3 times first standing on stable surface with eyes open (Condition 1), followed by randomization of the following 3 conditions: Condition 2 standing on stable surface with eyes closed, (visual input perturbed); Condition 3 standing on compliant foam surface with eyes open, (somatosensory input perturbed); and Condition 4 standing on compliant foam surface with eyes closed, (both visual and somatosensory inputs perturbed). Standing postural control was measured by three outcome measures: COP sway area, COP anterior-posterior (AP), and mediolateral (ML) path length (PL). A repeated measure mixed model Analysis of Variance was conducted to determine whether there was a significant difference between the two groups in the mean of the three outcome measures across the four conditions. Results: According to all three outcome measures, both groups showed a gradual increase in postural sway from condition 1 to condition 4. However, TD participants showed a larger postural sway than those with ASD. There was a significant main effect of condition on three outcome measures (p< 0.05). Only the COP AP PL showed a significant main effect of the group (p<0.05) and a significant group by condition interaction (p<0.05). In COP AP PL, TD participants showed a significant difference between condition 2 and the baseline (p<0.05), whereas the ASD group did not. This suggests that the ASD group did not weight visual input as much as the TD group. A significant difference between conditions for the ASD group was seen only when participants stood on foam regardless of the visual condition, suggesting that the ASD group relied more on the somatosensory inputs to maintain the standing postural control. Furthermore, the ASD group exhibited significantly smaller postural sway compared with TD participants during standing on the stable surface, whereas the postural sway of the ASD group was close to that of the TD group on foam. Conclusion: These results suggest that participants with high functioning ASD (level 1, no somatosensory hypersensitivity in ankles and feet) over-rely on somatosensory inputs and use a stiffening strategy for standing postural control. This deviation in the reweighting mechanism might explain the postural abnormalities mentioned above among children with ASD.

Keywords: autism spectrum disorders, postural sway, sensory weighting and reweighting, standing postural control

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Authors: Eglal Y. Ali, Smita Rao, Anat Lubetzky, Wen Ling

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Background: Postural abnormalities, rigidity, clumsiness, and frequent falls are common among children with autism spectrum disorders (ASD). The central nervous system’s ability to process all reliable sensory inputs (weighting) and disregard potentially perturbing sensory input (reweighting) is critical for successfully maintaining standing postural control. This study examined how sensory inputs (visual and somatosensory) are weighted and reweighted to maintain standing postural control in children with ASD compared with typically developing (TD) children. Subjects: Forty (20 (TD) and 20 ASD) children and adolescents participated in this study. The groups were matched for age, weight, and height. Participants had normal somatosensory (no somatosensory hypersensitivity), visual, and vestibular perception. Participants with ASD were categorized with severity level 1 according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) and Social Responsiveness Scale. Methods: Using one force platform, the center of pressure (COP) was measured during quiet standing for 30 seconds, 3 times first standing on stable surface with eyes open (Condition 1), followed by randomization of the following 3 conditions: Condition 2 standing on stable surface with eyes closed, (visual input perturbed); Condition 3 standing on a compliant foam surface with eyes open, (somatosensory input perturbed); and Condition 4 standing on a compliant foam surface with eyes closed, (both visual and somatosensory inputs perturbed). Standing postural control was measured by three outcome measures: COP sway area, COP anterior-posterior (AP), and mediolateral (ML) path length (PL). A repeated measure mixed model analysis of variance was conducted to determine whether there was a significant difference between the two groups in the mean of the three outcome measures across the four conditions. Results: According to all three outcome measures, both groups showed a gradual increase in postural sway from condition 1 to condition 4. However, TD participants showed a larger postural sway than those with ASD. There was a significant main effect of the condition on three outcome measures (p< 0.05). Only the COP AP PL showed a significant main effect of the group (p<0.05) and a significant group by condition interaction (p<0.05). In COP AP PL, TD participants showed a significant difference between condition 2 and the baseline (p<0.05), whereas the ASD group did not. This suggests that the ASD group did not weigh visual input as much as the TD group. A significant difference between conditions for the ASD group was seen only when participants stood on foam regardless of the visual condition, suggesting that the ASD group relied more on the somatosensory inputs to maintain the standing postural control. Furthermore, the ASD group exhibited significantly smaller postural sway compared with TD participants during standing on a stable surface, whereas the postural sway of the ASD group was close to that of the TD group on foam. Conclusion: These results suggest that participants with high-functioning ASD (level 1, no somatosensory hypersensitivity in ankles and feet) over-rely on somatosensory inputs and use a stiffening strategy for standing postural control. This deviation in the reweighting mechanism might explain the postural abnormalities mentioned above among children with ASD.

Keywords: autism spectrum disorders, postural sway, sensory weighting and reweighting, standing postural control

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Authors: Shabnam Najafi, Metin Turkay

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Network design problem (NDP) is used to determine the set of optimal values for certain pre-specified decision variables such as capacity expansion of nodes and links by optimizing various system performance measures including safety, congestion, and accessibility. The designed transportation network should improve objective functions defined for the system by considering the route choice behaviors of network users at the same time. The NDP studies mostly investigated the random demand and route selection constraints separately due to computational challenges. In this work, we consider both random demand and route selection constraints simultaneously. This work presents a nonlinear stochastic model for land use and road network design problem to address the development of different functional zones in urban areas by considering both cost function and air pollution. This model minimizes cost function and air pollution simultaneously with random demand and stochastic route selection constraint that aims to optimize network performance via road capacity expansion. The Bureau of Public Roads (BPR) link impedance function is used to determine the travel time function in each link. We consider a city with origin and destination nodes which can be residential or employment or both. There are set of existing paths between origin-destination (O-D) pairs. Case of increasing employed population is analyzed to determine amount of roads and origin zones simultaneously. Minimizing travel and expansion cost of routes and origin zones in one side and minimizing CO emission in the other side is considered in this analysis at the same time. In this work demand between O-D pairs is random and also the network flow pattern is subject to stochastic user equilibrium, specifically logit route choice model. Considering both demand and route choice, random is more applicable to design urban network programs. Epsilon-constraint is one of the methods to solve both linear and nonlinear multi-objective problems. In this work epsilon-constraint method is used to solve the problem. The problem was solved by keeping first objective (cost function) as the objective function of the problem and second objective as a constraint that should be less than an epsilon, where epsilon is an upper bound of the emission function. The value of epsilon should change from the worst to the best value of the emission function to generate the family of solutions representing Pareto set. A numerical example with 2 origin zones and 2 destination zones and 7 links is solved by GAMS and the set of Pareto points is obtained. There are 15 efficient solutions. According to these solutions as cost function value increases, emission function value decreases and vice versa.

Keywords: epsilon-constraint, multi-objective, network design, stochastic

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Authors: S. R. Dehghani, Y. S. Muzychka, G. F. Naterer

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The ice accretion of salt water on cold substrates creates brine-spongy ice. This type of ice is a mixture of pure ice and liquid brine. A real case of creation of this type of ice is superstructure icing which occurs on marine vessels and offshore structures in cold and harsh conditions. Transient heat transfer through this medium causes phase changes between brine pockets and pure ice. Salt rejection during the process of transient heat conduction increases the salinity of brine pockets to reach a local equilibrium state. In this process the only effect of passing heat through the medium is not changing the sensible heat of the ice and brine pockets; latent heat plays an important role and affects the mechanism of heat transfer. In this study, a new analytical model for evaluating heat transfer through brine-spongy ice is suggested. This model considers heat transfer and partial solidification and melting together. Properties of brine-spongy ice are obtained using properties of liquid brine and pure ice. A numerical solution using Method of Lines discretizes the medium to reach a set of ordinary differential equations. Boundary conditions are chosen using one of the applicable cases of this type of ice; one side is considered as a thermally isolated surface, and the other side is assumed to be suddenly affected by a constant temperature boundary. All cases are evaluated in temperatures between -20 C and the freezing point of brine-spongy ice. Solutions are conducted using different salinities from 5 to 60 ppt. Time steps and space intervals are chosen properly to maintain the most stable and fast solution. Variation of temperature, volume fraction of brine and brine salinity versus time are the most important outputs of this study. Results show that transient heat conduction through brine-spongy ice can create a various range of salinity of brine pockets from the initial salinity to that of 180 ppt. The rate of variation of temperature is found to be slower for high salinity cases. The maximum rate of heat transfer occurs at the start of the simulation. This rate decreases as time passes. Brine pockets are smaller at portions closer to the colder side than that of the warmer side. A the start of the solution, the numerical solution tends to increase instabilities. This is because of sharp variation of temperature at the start of the process. Changing the intervals improves the unstable situation. The analytical model using a numerical scheme is capable of predicting thermal behavior of brine spongy ice. This model and numerical solutions are important for modeling the process of freezing of salt water and ice accretion on cold structures.

Keywords: method of lines, brine-spongy ice, heat conduction, salt water

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Authors: Majid Farsadrouh Rashti, Alireza Mohammadinejad, Amir Shafiee Kisomi

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Lead (Pb²⁺), a cation, is a prime constituent of the majority of the industrial effluents such as mining, smelting and coal combustion, Pb-based painting and Pb containing pipes in water supply systems, paper and pulp refineries, printing, paints and pigments, explosive manufacturing, storage batteries, alloy and steel industries. The maximum permissible limit of lead in the water used for drinking and domesticating purpose is 0.01 mg/L as advised by Bureau of Indian Standards, BIS. This becomes the acceptable 'safe' level of lead(II) ions in water beyond which, the water becomes unfit for human use and consumption, and is potential enough to lead health problems and epidemics leading to kidney failure, neuronal disorders, and reproductive infertility. Superabsorbent hydrogels are loosely crosslinked hydrophilic polymers that in contact with aqueous solution can easily water and swell to several times to their initial volume without dissolving in aqueous medium. Superabsorbents are kind of hydrogels capable to swell and absorb a large amount of water in their three-dimensional networks. While the shapes of hydrogels do not change extensively during swelling, because of tremendously swelling capacity of superabsorbent, their shape will broadly change.Because of their superb response to changing environmental conditions including temperature pH, and solvent composition, superabsorbents have been attracting in numerous industrial applications. For instance, water retention property and subsequently. Natural-based superabsorbent hydrogels have attracted much attention in medical pharmaceutical, baby diapers, agriculture, and horticulture because of their non-toxicity, biocompatibility, and biodegradability. Novel superabsorbent hydrogel nanocomposites were prepared by graft copolymerization of acrylamide and itaconic acid in the presence of nanoclay (laponite), using methylene bisacrylamide (MBA) and potassium persulfate, former as a crosslinking agent and the second as an initiator. The superabsorbent hydrogel nanocomposites structure was characterized by FTIR spectroscopy, SEM and TGA Spectroscopy adsorption of metal ions on poly (AAm-co-IA). The equilibrium swelling values of copolymer was determined by gravimetric method. During the adsorption of metal ions on polymer, residual metal ion concentration in the solution and the solution pH were measured. The effects of the clay content of the hydrogel on its metal ions uptake behavior were studied. The NC hydrogels may be considered as a good candidate for environmental applications to retain more water and to remove heavy metals.

Keywords: adsorption, hydrogel, nanocomposite, super adsorbent

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Authors: Jitka Rychtarikova

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Regional differences in mortality in the Czech Republic (CR) may be moderate from a broader European perspective, but important discrepancies in life expectancy can be found between smaller territorial units. In this study territorial units are based on Administrative Districts of Municipalities with Extended Powers (MEP). This definition came into force January 1, 2003. There are 205 units and the city of Prague. MEP represents the smallest unit for which mortality patterns based on life tables can be investigated and the Czech Statistical Office has been calculating such life tables (every five-years) since 2004. MEP life tables from 2009-2013 for males and females allowed the investigation of three main life cycles with the use of temporary life expectancies between the exact ages of 0 and 35; 35 and 65; and the life expectancy at exact age 65. The results showed regional survival inequalities primarily in adult and older ages. Consequently, only mortality indicators for adult and elderly population were related to census 2011 unlinked data for the same age groups. The most relevant socio-economic factors taken from the census are: having a partner, educational level and unemployment rate. The unemployment rate was measured for adults aged 35-64 completed years. Exploratory spatial data analysis methods were used to detect regional patterns in spatially contiguous units of MEP. The presence of spatial non-stationarity (spatial autocorrelation) of mortality levels for male and female adults (35-64), and elderly males and females (65+) was tested using global Moran’s I. Spatial autocorrelation of mortality patterns was mapped using local Moran’s I with the intention to depict clusters of low or high mortality and spatial outliers for two age groups (35-64 and 65+). The highest Moran’s I was observed for male temporary life expectancy between exact ages 35 and 65 (0.52) and the lowest was among women with life expectancy of 65 (0.26). Generally, men showed stronger spatial autocorrelation compared to women. The relationship between mortality indicators such as life expectancies and socio-economic factors like the percentage of males/females having a partner; percentage of males/females with at least higher secondary education; and percentage of unemployed males/females from economically active population aged 35-64 years, was evaluated using multiple regression (OLS). The results were then compared to outputs from geographically weighted regression (GWR). In the Czech Republic, there are two broader territories North-West Bohemia (NWB) and North Moravia (NM), in which excess mortality is well established. Results of the t-test of spatial regression showed that for males aged 30-64 the association between mortality and unemployment (when adjusted for education and partnership) was stronger in NM compared to NWB, while educational level impacted the length of survival more in NWB. Geographic variation and relationships in mortality of the CR MEP will also be tested using the spatial Durbin approach. The calculations were conducted by means of ArcGIS 10.6 and SAS 9.4.

Keywords: Czech Republic, mortality, municipality, socio-economic factors, spatial analysis

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Authors: A. Bortkiewcz, A. Dudarewicz, P. Małecki, M. Kłaczyński, T. Wszołek, Małgorzata Pawlaczyk-Łuszczyńska

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Low-frequency noise (LFN) has been recognized as a special environmental pollutant. It is usually considered a broadband noise with the dominant content of low frequencies from 10 Hz to 250 Hz. A growing body of data shows that LFN differs in nature from other environmental noises, which are at comparable levels but not dominated by low-frequency components. The primary and most frequent adverse effect of LFN exposure is annoyance. Moreover, some recent investigations showed that LFN at relatively low A-weighted sound pressure levels (40−45 dB) occurring in office-like areas could adversely affect the mental performance, especially of high-sensitive subjects. It is well documented that high-frequency noise disturbs various types of human functions; however, there is very little data on the impact of LFN on well-being and health, including the cardiovascular system. Heart rate variability (HRV) is a sensitive marker of autonomic regulation of the circulatory system. Walker and co-workers found that LFN has a significantly more negative impact on cardiovascular response than exposure to high-frequency noise and that changes in HRV parameters resulting from LFN exposure tend to persist over time. The negative reactions of the cardiovascular system in response to LFN generated by wind turbines (20-200 Hz) were confirmed by Chiu. The scientific aim of the study is to assess the relationship between the spectral-temporal characteristics of LFN and the activity of the autonomic nervous system, considering the subjective assessment of annoyance, sensitivity to this type of noise, and cognitive and general health status. The study will be conducted in 20 male students in a special, acoustically prepared, constantly supervised room. Each person will be tested 4 times (4 sessions), under conditions of non-exposure (sham) and exposure to noise of wind turbines recorded at a distance of 250 meters from the turbine with different frequencies and frequency ranges: acoustic band 20 Hz-20 kHz, infrasound band 5-20 Hz, acoustic band + infrasound band. The order of sessions of the experiment will be randomly selected. Each session will last 1 h. There will be a 2-3 days break between sessions to exclude the possibility of the earlier session influencing the results of the next one. Before the first exposure, a questionnaire will be conducted on noise sensitivity, general health status using the GHQ questionnaire, hearing organ status and sociodemographic data. Before each of the 4 exposures, subjects will complete a brief questionnaire on their mood and sleep quality the night before the test. After the test, the subjects will be asked about any discomfort and subjective symptoms during the exposure. Before the test begins, Holter ECG monitoring equipment will be installed. HRV will be analyzed from the ECG recordings, including time and frequency domain parameters. The tests will always be performed in the morning (9-12) to avoid the influence of diurnal rhythm on HRV results. Students will perform psychological tests 15 minutes before the end of the test (Vienna Test System).

Keywords: neurovegetative control, heart rate variability (HRV), cognitive processes, low frequency noise

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Authors: Rida Wanbha Nongbri, Sabuj Kumar Mandal

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The Sustainable Development Goals (SDGs) for 2016-2030 were adopted in response to Millennium Development Goals (MDGs) which focused on access to sustainable water and sanitations. For over a decade, water has been a significant subject that is explored in various facets of life. Our day-to-day life is significantly impacted by water poverty at the socio-economic level. Reducing water poverty is an important policy challenge, particularly in emerging economies like India, owing to its population growth, huge variation in topology and climatic factors. To design appropriate water policies and its effectiveness, a proper measurement of water poverty is essential. In this backdrop, this study uses the Alkire Foster (AF) methodology to estimate a multidimensional water poverty index for India at the household level. The methodology captures several attributes to understand the complex issues related to households’ water deprivation. The study employs two rounds of Indian Human Development Survey data (IHDS 2005 and 2012) which focuses on 4 dimensions of water poverty including water access, water quantity, water quality, and water capacity, and seven indicators capturing these four dimensions. In order to quantify water deprivation at the household level, an AF dual cut-off counting method is applied and Multidimensional Water Poverty Index (MWPI) is calculated as the product of Headcount Ratio (Incidence) and average share of weighted dimension (Intensity). The results identify deprivation across all dimensions at the country level and show that a large proportion of household in India is deprived of quality water and suffers from water access in both 2005 and 2012 survey rounds. The comparison between the rural and urban households shows that higher ratio of the rural households are multidimensionally water poor as compared to their urban counterparts. Among the four dimensions of water poverty, water quality is found to be the most significant one for both rural and urban households. In 2005 round, almost 99.3% of households are water poor for at least one of the four dimensions, and among the water poor households, the intensity of water poverty is 54.7%. These values do not change significantly in 2012 round, but we could observe significance differences across the dimensions. States like Bihar, Tamil Nadu, and Andhra Pradesh are ranked the most in terms of MWPI, whereas Sikkim, Arunachal Pradesh and Chandigarh are ranked the lowest in 2005 round. Similarly, in 2012 round, Bihar, Uttar Pradesh and Orissa rank the highest in terms of MWPI, whereas Goa, Nagaland and Arunachal Pradesh rank the lowest. The policy implications of this study can be multifaceted. It can urge the policy makers to focus either on the impoverished households with lower intensity levels of water poverty to minimize total number of water poor households or can focus on those household with high intensity of water poverty to achieve an overall reduction in MWPI.

Keywords: .alkire-foster (AF) methodology, deprivation, dual cut-off, multidimensional water poverty index (MWPI)

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Authors: Thiwanka Weerakkody, Lakmali Handagiripathira, Poshitha Dabare, Thisari Guruge

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The determination of gross alpha and beta activity in water is important in a wide array of environmental studies and these parameters are considered in international legislations on the quality of water. This technique is commonly applied as screening method in radioecology, environmental monitoring, industrial applications, etc. Measuring of Gross Alpha and Beta emitters by using iSolo alpha beta counting system is an adequate nuclear technique to assess radioactivity levels in natural and waste water samples due to its simplicity and low cost compared with the other methods. Twelve water samples (Six samples of commercially available bottled drinking water and six samples of industrial waste water) were measured by standard method EPA 900.0 consisting of the gas-less, firm wear based, single sample, manual iSolo alpha beta counter (Model: SOLO300G) with solid state silicon PIPS detector. Am-241 and Sr90/ Y90 calibration standards were used to calibrate the detector. The minimum detectable activities are 2.32mBq/L and 406mBq/L, for alpha and beta activity, respectively. Each of the 2L water samples was evaporated (at low heat) to a small volume and transferred into 50mm stainless steel counting planchet evenly (for homogenization) and heated by IR lamp and the constant weighted residue was obtained. Then the samples were counted for gross alpha and beta. Sample density on the planchet area was maintained below 5mg/cm. Large quantities of solid wastes sludges and waste water are generated every year due to various industries. This water can be reused for different applications. Therefore implementation of water treatment plants and measuring water quality parameters in industrial waste water discharge is very important before releasing them into the environment. This waste may contain different types of pollutants, including radioactive substances. All these measured waste water samples having gross alpha and beta activities, lower than the maximum tolerance limits for industrial waste water discharge of industrial waste in to inland surface water, that is 10-9µCi/mL and 10-8µCi/mL for gross alpha and beta respectively (National Environmental Act, No. 47 of 1980). This is according to extraordinary gazette of the democratic socialist republic of Sri Lanka in February 2008. The measured water samples were below the recommended radioactivity levels and do not pose any radiological hazard when releasing the environment. Drinking water is an essential requirement of life. All the drinking water samples were below the permissible levels of 0.5Bq/L for gross alpha activity and 1Bq/L for gross beta activity. The values have been proposed by World Health Organization in 2011; therefore the water is acceptable for consumption of humans without any further clarification with respect to their radioactivity. As these screening levels are very low, the individual dose criterion (IDC) would usually not be exceeded (0.1mSv y⁻¹). IDC is a criterion for evaluating health risks from long term exposure to radionuclides in drinking water. Recommended level of 0.1mSv/y expressed a very low level of health risk. This monitoring work will be continued further for environmental protection purposes.

Keywords: drinking water, gross alpha, gross beta, waste water

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Authors: Belcher Fulele, W. A. A. Ddamba

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Study of solvent systems contributes to the understanding of intermolecular interactions that occur in binary mixtures. These interactions involves among others strong dipole-dipole interactions and weak van de Waals interactions which are of significant application in pharmaceuticals, solvent extractions, design of reactors and solvent handling and storage processes. Binary mixtures of solvents can thus be used as a model to interpret thermodynamic behavior that occur in a real solution mixture. Densities of pure DFM, n-alkanes (n-pentane, n-hexane, n-heptane and n-octane) and amides (N-methylformamide, N-ethylformamide, N,N-dimethylformamide and N,N-dimethylacetamide) as well as their [DFM + ((C5-C8) n-alkane or amide)] binary mixtures over the entire composition range, have been reported at temperature 293.15, 298.15 and 303.15 K and atmospheric pressure. These data has been used to derive the thermodynamic properties: the excess molar volume of solution, apparent molar volumes, excess partial molar volumes, limiting excess partial molar volumes, limiting partial molar volumes of each component of a binary mixture. The results are discussed in terms of possible intermolecular interactions and structural effects that occur in the binary mixtures. The variation of excess molar volume with DFM composition for the [DFM + (C5-C7) n-alkane] binary mixture exhibit a sigmoidal behavior while for the [DFM + n-octane] binary system, positive deviation of excess molar volume function was observed over the entire composition range. For each of the [DFM + (C5-C8) n-alkane] binary mixture, the excess molar volume exhibited a fall with increase in temperature. The excess molar volume for each of [DFM + (NMF or NEF or DMF or DMA)] binary system was negative over the entire DFM composition at each of the three temperatures investigated. The negative deviations in excess molar volume values follow the order: DMA > DMF > NEF > NMF. Increase in temperature has a greater effect on component self-association than it has on complex formation between molecules of components in [DFM + (NMF or NEF or DMF or DMA)] binary mixture which shifts complex formation equilibrium towards complex to give a drop in excess molar volume with increase in temperature. The Prigogine-Flory-Patterson model has been applied at 298.15 K and reveals that the free volume is the most important contributing term to the excess experimental molar volume data for [DFM + (n-pentane or n-octane)] binary system. For [DFM + (NMF or DMF or DMA)] binary mixture, the interactional term and characteristic pressure term contributions are the most important contributing terms in describing the sign of experimental excess molar volume. The mixture systems contributed to the understanding of interactions of polar solvents with proteins (amides) with non-polar solvents (alkanes) in biological systems.

Keywords: alkanes, amides, excess thermodynamic parameters, Prigogine-Flory-Patterson model

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Authors: Muhammad Karim Ahmadzai

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Floods are natural phenomena and are an integral part of the water cycle. The majority of them are the result of climatic conditions, but are also affected by the geology and geomorphology of the area, topography and hydrology, the water permeability of the soil and the vegetation cover, as well as by all kinds of human activities and structures. However, from the moment that human lives are at risk and significant economic impact is recorded, this natural phenomenon becomes a natural disaster. Flood management is now a key issue at regional and local levels around the world, affecting human lives and activities. The majority of floods are unlikely to be fully predicted, but it is feasible to reduce their risks through appropriate management plans and constructions. The aim of this Case Study is to identify, and map areas of flood risk in the Khinch District of Panjshir Province, Afghanistan specifically in the area of Peshghore, causing numerous damages. The main purpose of this study is to evaluate the contribution of remote sensing technology and Geographic Information Systems (GIS) in assessing the susceptibility of this region to flood events. Panjsher is facing Seasonal floods and human interventions on streams caused floods. The beds of which have been trampled to build houses and hotels or have been converted into roads, are causing flooding after every heavy rainfall. The streams crossing settlements and areas with high touristic development have been intensively modified by humans, as the pressure for real estate development land is growing. In particular, several areas in Khinch are facing a high risk of extensive flood occurrence. This study concentrates on the construction of a flood susceptibility map, of the study area, by combining vulnerability elements, using the Analytical Hierarchy Process/ AHP. The Analytic Hierarchy Process, normally called AHP, is a powerful yet simple method for making decisions. It is commonly used for project prioritization and selection. AHP lets you capture your strategic goals as a set of weighted criteria that you then use to score projects. This method is used to provide weights for each criterion which Contributes to the Flood Event. After processing of a digital elevation model (DEM), important secondary data were extracted, such as the slope map, the flow direction and the flow accumulation. Together with additional thematic information (Landuse and Landcover, topographic wetness index, precipitation, Normalized Difference Vegetation Index, Elevation, River Density, Distance from River, Distance to Road, Slope), these led to the final Flood Risk Map. Finally, according to this map, the Priority Protection Areas and Villages and the structural and nonstructural measures were demonstrated to Minimize the Impacts of Floods on residential and Agricultural areas.

Keywords: flood hazard, flood risk map, flood mitigation measures, AHP analysis

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Authors: Ferzat Anka

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Many types of problems can be solved using traditional analytical methods. However, these methods take a long time and cause inefficient use of resources. In particular, different approaches may be required in solving complex and global engineering problems that we frequently encounter in real life. The bigger and more complex a problem, the harder it is to solve. Such problems are called Nondeterministic Polynomial time (NP-hard) in the literature. The main reasons for recommending different metaheuristic algorithms for various problems are the use of simple concepts, the use of simple mathematical equations and structures, the use of non-derivative mechanisms, the avoidance of local optima, and their fast convergence. They are also flexible, as they can be applied to different problems without very specific modifications. Thanks to these features, it can be easily embedded even in many hardware devices. Accordingly, this approach can also be used in trend application areas such as IoT, big data, and parallel structures. Indeed, the metaheuristic approaches are algorithms that return near-optimal results for solving large-scale optimization problems. This study is focused on the new metaheuristic method that has been merged with the chaotic approach. It is based on the chaos theorem and helps relevant algorithms to improve the diversity of the population and fast convergence. This approach is based on Chimp Optimization Algorithm (ChOA), that is a recently introduced metaheuristic algorithm inspired by nature. This algorithm identified four types of chimpanzee groups: attacker, barrier, chaser, and driver, and proposed a suitable mathematical model for them based on the various intelligence and sexual motivations of chimpanzees. However, this algorithm is not more successful in the convergence rate and escaping of the local optimum trap in solving high-dimensional problems. Although it and some of its variants use some strategies to overcome these problems, it is observed that it is not sufficient. Therefore, in this study, a newly expanded variant is described. In the algorithm called Ex-ChOA, hybrid models are proposed for position updates of search agents, and a dynamic switching mechanism is provided for transition phases. This flexible structure solves the slow convergence problem of ChOA and improves its accuracy in multidimensional problems. Therefore, it tries to achieve success in solving global, complex, and constrained problems. The main contribution of this study is 1) It improves the accuracy and solves the slow convergence problem of the ChOA. 2) It proposes new hybrid movement strategy models for position updates of search agents. 3) It provides success in solving global, complex, and constrained problems. 4) It provides a dynamic switching mechanism between phases. The performance of the Ex-ChOA algorithm is analyzed on a total of 8 benchmark functions, as well as a total of 2 classical and constrained engineering problems. The proposed algorithm is compared with the ChoA, and several well-known variants (Weighted-ChoA, Enhanced-ChoA) are used. In addition, an Improved algorithm from the Grey Wolf Optimizer (I-GWO) method is chosen for comparison since the working model is similar. The obtained results depict that the proposed algorithm performs better or equivalently to the compared algorithms.

Keywords: optimization, metaheuristic, chimp optimization algorithm, engineering constrained problems

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Authors: Tingneyuc Sekac, Sujoy Kumar Jana, Indrajit Pal, Dilip Kumar Pal

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Tectonism induced Tsunami, landslide, ground shaking leading to liquefaction, infrastructure collapse, conflagration are the common earthquake hazards that are experienced worldwide. Apart from human casualty, the damage to built-up infrastructures like roads, bridges, buildings and other properties are the collateral episodes. The appropriate planning must precede with a view to safeguarding people’s welfare, infrastructures and other properties at a site based on proper evaluation and assessments of the potential level of earthquake hazard. The information or output results can be used as a tool that can assist in minimizing risk from earthquakes and also can foster appropriate construction design and formulation of building codes at a particular site. Different disciplines adopt different approaches in assessing and monitoring earthquake hazard throughout the world. For the present study, GIS and Remote Sensing potentials were utilized to evaluate and assess earthquake hazards of the study region. Subsurface geology and geomorphology were the common features or factors that were assessed and integrated within GIS environment coupling with seismicity data layers like; Peak Ground Acceleration (PGA), historical earthquake magnitude and earthquake depth to evaluate and prepare liquefaction potential zones (LPZ) culminating in earthquake hazard zonation of our study sites. The liquefaction can eventuate in the aftermath of severe ground shaking with amenable site soil condition, geology and geomorphology. The latter site conditions or the wave propagation media were assessed to identify the potential zones. The precept has been that during any earthquake event the seismic wave is generated and propagates from earthquake focus to the surface. As it propagates, it passes through certain geological or geomorphological and specific soil features, where these features according to their strength/stiffness/moisture content, aggravates or attenuates the strength of wave propagation to the surface. Accordingly, the resulting intensity of shaking may or may not culminate in the collapse of built-up infrastructures. For the case of earthquake hazard zonation, the overall assessment was carried out through integrating seismicity data layers with LPZ. Multi-criteria Evaluation (MCE) with Saaty’s Analytical Hierarchy Process (AHP) was adopted for this study. It is a GIS technology that involves integration of several factors (thematic layers) that can have a potential contribution to liquefaction triggered by earthquake hazard. The factors are to be weighted and ranked in the order of their contribution to earthquake induced liquefaction. The weightage and ranking assigned to each factor are to be normalized with AHP technique. The spatial analysis tools i.e., Raster calculator, reclassify, overlay analysis in ArcGIS 10 software were mainly employed in the study. The final output of LPZ and Earthquake hazard zones were reclassified to ‘Very high’, ‘High’, ‘Moderate’, ‘Low’ and ‘Very Low’ to indicate levels of hazard within a study region.

Keywords: hazard micro-zonation, liquefaction, multi criteria evaluation, tectonism

Procedia PDF Downloads 244

Authors: Ehsan Javanmardemamgheisi, Javad Mehr, Jason Ali-Lavroff, Damien Holloway, Michael Davis

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During the last decades, a growing interest in faster and more efficient waterborne transportation has led to the development of high-speed vessels for both commercial and military applications. To satisfy this global demand, a wide variety of arrangements of high-speed crafts have been proposed by designers. Among them, high-speed catamarans have proven themselves to be a suitable Roll-on/Roll-off configuration for carrying passengers and cargo due to widely spaced demi hulls, a wide deck zone, and a high ratio of deadweight to displacement. To improve passenger comfort and crew workability and enhance the operability and performance of high-speed catamarans, mitigating the severity of motions and structural loads using Ride Control Systems (RCS) is essential.In this paper, a set of towing tank tests was conducted on a 2.5 m scaled model of a 112 m Incat Tasmania high-speed catamaran in irregular head seas to investigate the effect of different ride control algorithms including linear and nonlinear versions of the heave control, pitch control, and local control on motion responses and passenger comfort of the full-scale ship. The RCS included a centre bow-fitted T-Foil and two transom-mounted stern tabs. All the experiments were conducted at the Australian Maritime College (AMC) towing tank at a model speed of 2.89 m/s (37 knots full scale), a modal period of 1.5 sec (10 sec full scale) and two significant wave heights of 60 mm and 90 mm, representing full-scale wave heights of 2.7 m and 4 m, respectively. Spectral analyses were performed using Welch’s power spectral density method on the vertical motion time records of the catamaran model to calculate heave and pitch Response Amplitude Operators (RAOs). Then, noting that passenger discomfort arises from vertical accelerations and that the vertical accelerations vary at different longitudinal locations within the passenger cabin due to the variations in amplitude and relative phase of the pitch and heave motions, the vertical accelerations were calculated at three longitudinal locations (LCG, T-Foil, and stern tabs). Finally, frequency-weighted Root Mean Square (RMS) vertical accelerations were calculated to estimate Motion Sickness Dose Value (MSDV) of the ship based on ISO 2631-recommendations. It was demonstrated that in small seas, implementing a nonlinear pitch control algorithm reduces the peak pitch motions by 41%, the vertical accelerations at the forward location by 46%, and motion sickness at the forward position by around 20% which provides great potential for further improvement in passenger comfort, crew workability, and operability of high-speed catamarans.

Keywords: high-speed catamarans, ride control system, response amplitude operators, vertical accelerations, motion sickness, irregular waves, towing tank tests.

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Authors: Mohammed El Raey, Moustafa Osman Mohammed

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The spatial-ecological modeling is relating sustainable dispersions with social development. Sustainability with spatial-ecological model gives attention to urban environments in the design review management to comply with Earth’s System. Naturally exchange patterns of ecosystems have consistent and periodic cycles to preserve energy flows and materials in Earth’s System. The probabilistic risk assessment (PRA) technique is utilized to assess the safety of industrial complex. The other analytical approach is the Failure-Safe Mode and Effect Analysis (FMEA) for critical components. The plant safety parameters are identified for engineering topology as employed in assessment safety of industrial ecology. In particular, the most severe accidental release of hazardous gaseous is postulated, analyzed and assessment in industrial region. The IAEA- safety assessment procedure is used to account the duration and rate of discharge of liquid chlorine. The ecological model of plume dispersion width and concentration of chlorine gas in the downwind direction is determined using Gaussian Plume Model in urban and ruler areas and presented with SURFER®. The prediction of accident consequences is traced in risk contour concentration lines. The local greenhouse effect is predicted with relevant conclusions. The spatial-ecological model is also predicted the distribution schemes from the perspective of pollutants that considered multiple factors of multi-criteria analysis. The data extends input–output analysis to evaluate the spillover effect, and conducted Monte Carlo simulations and sensitivity analysis. Their unique structure is balanced within “equilibrium patterns”, such as the biosphere and collective a composite index of many distributed feedback flows. These dynamic structures are related to have their physical and chemical properties and enable a gradual and prolonged incremental pattern. While this spatial model structure argues from ecology, resource savings, static load design, financial and other pragmatic reasons, the outcomes are not decisive in artistic/ architectural perspective. The hypothesis is an attempt to unify analytic and analogical spatial structure for development urban environments using optimization software and applied as an example of integrated industrial structure where the process is based on engineering topology as optimization approach of systems ecology.

Keywords: spatial-ecological modeling, spatial structure orientation impact, composite structure, industrial ecology

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Authors: Dongwoo Kang, Yunsung Yoo, Injun Kim, Jongin Lee, Jinwon Park

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Since industrial revolution, energy usage by human-beings has been drastically increased resulting in the enormous emissions of carbon dioxide into the atmosphere. High concentration of carbon dioxide is well recognized as the main reason for the climate change by breaking the heat equilibrium of the earth. In order to decrease the amount of carbon dioxide emission, lots of technologies have been developed. One of the methods is to capture carbon dioxide after combustion process using liquid type absorbents. However, for some nations, captured carbon dioxide cannot be treated and stored properly due to their geological structures. Also, captured carbon dioxide can be leaked out when crust activities are active. Hence, the method to convert carbon dioxide as stable and useful products were developed. It is usually called CCU, that is, Carbon Capture and Utilization. There are several ways to convert carbon dioxide into useful substances. For example, carbon dioxide can be converted and used as fuels such as diesel, plastics, and polymers. However, these types of technologies require lots of energy to make stable carbon dioxide into a reactive one. Hence, converting it into metal carbonates salts have been studied widely. When carbon dioxide is captured by alkanolamine-based liquid absorbents, it exists as ionic forms such as carbonate, carbamate, and bicarbonate. When adequate metal ions are added, metal carbonate salt can be produced by ionic reaction with fast reaction kinetics. However, finding metal sources can be one of the problems for this method to be commercialized. If natural resources such as calcium oxide were used to supply calcium ions, it is not thought to have the economic feasibility to use natural resources to treat carbon dioxide. In this research, high concentrated industrial wastewater produced from refined salt production facility have been used as metal supplying source, especially for calcium cations. To ensure purity of final products, calcium ions were selectively separated in the form of gypsum dihydrate. After that, carbon dioxide is captured using alkanolamine-based absorbents making carbon dioxide into reactive ionic form. And then, high purity calcium carbonate salt was produced. The existence of calcium carbonate was confirmed by X-Ray Diffraction (XRD) and Scanning Electron Microscopy (SEM) images. Also, carbon dioxide loading curves for absorption, conversion, and desorption were provided. Also, in order to investigate the possibility of the absorbent reuse, reabsorption experiments were performed either. Produced calcium carbonate as final products is seemed to have potential to be used in various industrial fields including cement and paper making industries and pharmaceutical engineering fields.

Keywords: alkanolamine, calcium carbonate, climate change, seawater, industrial wastewater

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Authors: Kirsi Snellman, Johannes Gartner, , Katja Upadaya

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A transition towards a future where the economy serves society so that it evolves within the safe operating space of the planet calls for fundamental changes in the way managers think, feel and act, and make decisions that relate to social and environmental issues. Sustainable decision-making in organizations are often challenging tasks characterized by trade-offs between environmental, social and financial aspects, thus often bringing forth ethical concerns. Although there have been significant developments in incorporating uncertainty into environmental decision-making and measuring constructs and dimensions in ethical behavior in organizations, the majority of sustainable decision-making models are rationalist-based. Moreover, research in psychology indicates that one’s readiness to make a decision depends on the individual’s state of mind, the feasibility of the implied change, and the compatibility of strategies and tactics of implementation. Although very informative, most of this extant research is limited in the sense that it often directs attention towards the rational instead of the emotional. Hence, little is known about the role of emotions in sustainable decision making, especially in situations where decision-makers evaluate a variety of options and use their feelings as a source of information in tackling the uncertainty. To fill this lacuna, and to embrace the uncertainty and perceived risk involved in decisions that touch upon social and environmental aspects, it is important to add emotion to the evaluation when aiming to reach the one right and good ethical decision outcome. This analysis builds on recent findings in moral psychology that associate feelings and intuitions with ethical decisions and suggests that emotions can sensitize the manager to evaluate the rightness or wrongness of alternatives if ethical concerns are present in sustainable decision making. Capturing such sensitive evaluation as triggered by intuitions, we suggest that rational justification can be complemented by using emotions as a tool to tune in to what feels right in making sustainable decisions. This analysis integrates ethical decision-making theories with recent advancements in emotion theories. It determines the conditions under which emotions play a role in sustainability decisions by contributing to a personal equilibrium in which intuition and rationality are both activated and in accord. It complements the rationalist ethics view according to which nothing fogs the mind in decision making so thoroughly as emotion, and the concept of cheater’s high that links unethical behavior with positive affect. This analysis contributes to theory with a novel theoretical model that specifies when and why managers, who are more emotional, are, in fact, more likely to make ethical decisions than those managers who are more rational. It also proposes practical advice on how emotions can convert the manager’s preferences into choices that benefit both common good and one’s own good throughout the transition towards a more sustainable future.

Keywords: emotion, ethical decision making, intuition, sustainability

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Authors: Ahmad S. Darwish, Tarek Lemaoui, Hanifa Taher, Inas M. AlNashef, Fawzi Banat

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This research reports a systematic top-down approach for designing neoteric hydrophobic solvents –particularly, deep eutectic solvents (DES) and ionic liquids (IL)– as furfural extractants from aqueous media for the application of sustainable biomass conversion. The first stage of the framework entailed screening 32 neoteric solvents to determine their efficacy against toluene as the application’s conventional benchmark for comparison. The selection criteria for the best solvents encompassed not only their efficiency in extracting furfural but also low viscosity and minimal toxicity levels. Additionally, for the DESs, their natural origins, availability, and biodegradability were also taken into account. From the screening pool, two neoteric solvents were selected: thymol:decanoic acid 1:1 (Thy:DecA) and trihexyltetradecyl phosphonium bis(trifluoromethylsulfonyl) imide [P₁₄,₆,₆,₆][NTf₂]. These solvents outperformed the toluene benchmark, achieving efficiencies of 94.1% and 97.1% respectively, compared to toluene’s 81.2%, while also possessing the desired properties. These solvents were then characterized thoroughly in terms of their physical properties, thermal properties, critical properties, and cross-contamination solubilities. The selected neoteric solvents were then extensively tested under various operating conditions, and an exceptional stable performance was exhibited, maintaining high efficiency across a broad range of temperatures (15–100 °C), pH levels (1–13), and furfural concentrations (0.1–2.0 wt%) with a remarkable equilibrium time of only 2 minutes, and most notably, demonstrated high efficiencies even at low solvent-to-feed ratios. The durability of the neoteric solvents was also validated to be stable over multiple extraction-regeneration cycles, with limited leachability to the aqueous phase (≈0.1%). Moreover, the extraction performance of the solvents was then modeled through machine learning, specifically multiple non-linear regression (MNLR) and artificial neural networks (ANN). The models demonstrated high accuracy, indicated by their low absolute average relative deviations with values of 2.74% and 2.28% for Thy:DecA and [P₁₄,₆,₆,₆][NTf₂], respectively, using MNLR, and 0.10% for Thy:DecA and 0.41% for [P₁₄,₆,₆,₆][NTf₂] using ANN, highlighting the significantly enhanced predictive accuracy of the ANN. The neoteric solvents presented herein offer noteworthy advantages over traditional organic solvents, including their high efficiency in both extraction and regeneration processes, their stability and minimal leachability, making them particularly suitable for applications involving aqueous media. Moreover, these solvents are more environmentally friendly, incorporating renewable and sustainable components like thymol and decanoic acid. This exceptional efficacy of the newly developed neoteric solvents signifies a significant advancement, providing a green and sustainable alternative for furfural production from biowaste.

Keywords: sustainable biomass conversion, furfural extraction, ionic liquids, deep eutectic solvents

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Authors: Hwang Ho Kim, Do Gyun Kim, Jin Young Choi, Sang Chul Park

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Since tire production process is very complicated, company-wide management of it is very difficult, necessitating considerable amounts of capital and labors. Thus, productivity should be enhanced and maintained competitive by developing and applying effective production plans. Among major processes for tire manufacturing, consisting of mixing component preparation, building and curing, the mixing process is an essential and important step because the main component of tire, called compound, is formed at this step. Compound as a rubber synthesis with various characteristics plays its own role required for a tire as a finished product. Meanwhile, scheduling tire mixing process is similar to flexible job shop scheduling problem (FJSSP) because various kinds of compounds have their unique orders of operations, and a set of alternative machines can be used to process each operation. In addition, setup time required for different operations may differ due to alteration of additives. In other words, each operation of mixing processes requires different setup time depending on the previous one, and this kind of feature, called sequence dependent setup time (SDST), is a very important issue in traditional scheduling problems such as flexible job shop scheduling problems. However, despite of its importance, there exist few research works dealing with the tire mixing process. Thus, in this paper, we consider the scheduling problem for tire mixing process and suggest an efficient particle swarm optimization (PSO) algorithm to minimize the makespan for completing all the required jobs belonging to the process. Specifically, we design a particle encoding scheme for the considered scheduling problem, including a processing sequence for compounds and machine allocation information for each job operation, and a method for generating a tire mixing schedule from a given particle. At each iteration, the coordination and velocity of particles are updated, and the current solution is compared with new solution. This procedure is repeated until a stopping condition is satisfied. The performance of the proposed algorithm is validated through a numerical experiment by using some small-sized problem instances expressing the tire mixing process. Furthermore, we compare the solution of the proposed algorithm with it obtained by solving a mixed integer linear programming (MILP) model developed in previous research work. As for performance measure, we define an error rate which can evaluate the difference between two solutions. As a result, we show that PSO algorithm proposed in this paper outperforms MILP model with respect to the effectiveness and efficiency. As the direction for future work, we plan to consider scheduling problems in other processes such as building, curing. We can also extend our current work by considering other performance measures such as weighted makespan or processing times affected by aging or learning effects.

Keywords: compound, error rate, flexible job shop scheduling problem, makespan, particle encoding scheme, particle swarm optimization, sequence dependent setup time, tire mixing process

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Authors: Parminder Kaur Heer, Alexei Lapkin

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

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

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Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Model assessment, in the Bayesian context, involves evaluation of the goodness-of-fit and the comparison of several alternative candidate models for predictive accuracy and improvements. In posterior predictive checks, the data simulated under the fitted model is compared with the actual data. Predictive model accuracy is estimated using information criteria such as the Akaike information criterion (AIC), the Bayesian information criterion (BIC), the Deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). The goal of an information criterion is to obtain an unbiased measure of out-of-sample prediction error. Since posterior checks use the data twice; once for model estimation and once for testing, a bias correction which penalises the model complexity is incorporated in these criteria. Cross-validation (CV) is another method used for examining out-of-sample prediction accuracy. Leave-one-out cross-validation (LOO-CV) is the most computationally expensive variant among the other CV methods, as it fits as many models as the number of observations. Importance sampling (IS), truncated importance sampling (TIS) and Pareto-smoothed importance sampling (PSIS) are generally used as approximations to the exact LOO-CV and utilise the existing MCMC results avoiding expensive computational issues. The reciprocals of the predictive densities calculated over posterior draws for each observation are treated as the raw importance weights. These are in turn used to calculate the approximate LOO-CV of the observation as a weighted average of posterior densities. In IS-LOO, the raw weights are directly used. In contrast, the larger weights are replaced by their modified truncated weights in calculating TIS-LOO and PSIS-LOO. Although, information criteria and LOO-CV are unable to reflect the goodness-of-fit in absolute sense, the differences can be used to measure the relative performance of the models of interest. However, the use of these measures is only valid under specific circumstances. This study has developed 11 models using normal, log-normal, gamma, and student’s t distributions to improve the PCR stutter prediction with forensic data. These models are comprised of four with profile-wide variances, four with locus specific variances, and three which are two-component mixture models. The mean stutter ratio in each model is modeled as a locus specific simple linear regression against a feature of the alleles under study known as the longest uninterrupted sequence (LUS). The use of AIC, BIC, DIC, and WAIC in model comparison has some practical limitations. Even though, IS-LOO, TIS-LOO, and PSIS-LOO are considered to be approximations of the exact LOO-CV, the study observed some drastic deviations in the results. However, there are some interesting relationships among the logarithms of pointwise predictive densities (lppd) calculated under WAIC and the LOO approximation methods. The estimated overall lppd is a relative measure that reflects the overall goodness-of-fit of the model. Parallel log-likelihood profiles for the models conditional on equal posterior variances in lppds were observed. This study illustrates the limitations of the information criteria in practical model comparison problems. In addition, the relationships among LOO-CV approximation methods and WAIC with their limitations are discussed. Finally, useful recommendations that may help in practical model comparisons with these methods are provided.

Keywords: cross-validation, importance sampling, information criteria, predictive accuracy

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Authors: Ellis D. Cooper

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“Circularchy” is supposed to be an adjustable formal framework with enough expressive power to articulate biological theory about Earthly Life in the sense of multi-scale biological autonomy constrained by non-equilibrium thermodynamics. “Formal framework” means specifically a multi-sorted first-order-theorywithequality (for each sort). Philosophically, such a theory is one kind of “microlect,” which means a “way of speaking” (or, more generally, a “way of behaving”) for overtly expressing a “mental model” of some “referent.” Other kinds of microlect include “natural microlect,” “diagrammatic microlect,” and “behavioral microlect,” with examples such as “political theory,” “Euclidean geometry,” and “dance choreography,” respectively. These are all describable in terms of a vocabulary conforming to grammar. As aspects of human culture, they are possibly reminiscent of Ernst Cassirer’s idea of “symbolic form;” as vocabularies, they are akin to Richard Rorty’s idea of “final vocabulary” for expressing a mental model of one’s life. A formal microlect is presented by stipulating sorts, variables, calculations, predicates, and postulates. Calculations (a.k.a., “terms”) may be composed to form more complicated calculations; predicates (a.k.a., “relations”) may be logically combined to form more complicated predicates; and statements (a.k.a., “sentences”) are grammatically correct expressions which are true or false. Conclusions are statements derived using logical rules of deduction from postulates, other assumed statements, or previously derived conclusions. A circularchy is a formal microlect constituted by two or more sub-microlects, each with its distinct stipulations of sorts, variables, calculations, predicates, and postulates. Within a sub-microlect some postulates or conclusions are equations which are statements that declare equality of specified calculations. An equational bond between an equation in one sub-microlect and an equation in either the same sub-microlect or in another sub-microlect is a predicate that declares equality of symbols occurring in a side of one equation with symbols occurring in a side of the other equation. Briefly, a circularchy is a network of equational bonds between sub-microlects. A circularchy is solvable if there exist solutions for all equations that satisfy all equational bonds. If a circularchy is not solvable, then a challenge would be to discover the obstruction to solvability and then conjecture what adjustments might remove the obstruction. Adjustment means changes in stipulated ingredients (sorts, etc.) of sub-microlects, or changes in equational bonds between sub-microlects, or introduction of new sub-microlects and new equational bonds. A circularchy is modular insofar as each sub-microlect is a node in a network of equation bonds. Solvability of a circularchy may be conjectured. Efforts to prove solvability may be thwarted by a counter-example or may lead to the construction of a solution. An automated theorem-proof assistant would likely be necessary for investigating a substantial circularchy, such as one purported to represent Earthly Life. Such investigations (chains of statements) would be concurrent with and no substitute for simulations (chains of numbers).

Keywords: autonomy, first-order theory, mathematics, thermodynamics

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Authors: Aditya Sharma

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Profits earned from relative strength strategy of zero-cost portfolio i.e. taking long position in winner stocks and short position in loser stocks from recent past are termed as momentum profits. In recent times, there has been lot of controversy and concern about sources of momentum profits, since the existence of these profits acts as an evidence of earning non-normal returns from publicly available information directly contradicting Efficient Market Hypothesis. Literature review reveals conflicting theories and differing evidences on sources of momentum profits. This paper aims at re-examining the sources of momentum profits in Indian capital markets. The study focuses on assessing the effect of fundamental as well as behavioral sources in order to understand the role of investor behavior in stock returns and suggest (if any) improvements to existing behavioral asset pricing models. This Paper adopts calendar time methodology to calculate momentum profits for 6 different strategies with and without skipping a month between ranking and holding period. For each J/K strategy, under this methodology, at the beginning of each month t stocks are ranked on past j month’s average returns and sorted in descending order. Stocks in upper decile are termed winners and bottom decile as losers. After ranking long and short positions are taken in winner and loser stocks respectively and both portfolios are held for next k months, in such manner that at any given point of time we have K overlapping long and short portfolios each, ranked from t-1 month to t-K month. At the end of period, returns of both long and short portfolios are calculated by taking equally weighted average across all months. Long minus short returns (LMS) are momentum profits for each strategy. Post testing for momentum profits, to study the role market risk plays in momentum profits, CAPM and Fama French three factor model adjusted LMS returns are calculated. In the final phase of studying sources, decomposing methodology has been used for breaking up the profits into unconditional means, serial correlations, and cross-serial correlations. This methodology is unbiased, can be used with the decile-based methodology and helps to test the effect of behavioral and fundamental sources altogether. From all the analysis, it was found that momentum profits do exist in Indian capital markets with market risk playing little role in defining them. Also, it was observed that though momentum profits have multiple sources (risk, serial correlations, and cross-serial correlations), cross-serial correlations plays a major role in defining these profits. The study revealed that momentum profits do have multiple sources however, cross-serial correlations i.e. the effect of returns of other stocks play a major role. This means that in addition to studying the investors` reactions to the information of the same firm it is also important to study how they react to the information of other firms. The analysis confirms that investor behavior does play an important role in stock returns and incorporating both the aspects of investors’ reactions in behavioral asset pricing models help make then better.

Keywords: investor behavior, momentum effect, sources of momentum, stock returns

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Authors: Julio Jesus Salazar, Manuel Andres Jesus De Lama

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There are very few models that serve to analyze the use of water in the socio-economic process. On the supply side, the joint use of groundwater has been considered in addition to the simple limits on the availability of surface water. In addition, we have worked on waterlogging and the effects on water quality (mainly salinity). In this paper, a 'complex' water economy is examined; one in which demands grow differentially not only within but also between sectors, and one in which there are limited opportunities to increase consumptive use. In particular, high-value growth, the growth of the production of irrigated crops of high value within the basins of the case study, together with the rapidly growing urban areas, provides a rich context to examine the general problem of water management at the basin level. At the same time, the long-term aridity of nature has made the eco-environment in the basins located on the coast of Peru very vulnerable, and the exploitation and immediate use of water resources have further deteriorated the situation. The presented methodology is the optimization with embedded simulation. The wide basin simulation of flow and water balances and crop growth are embedded with the optimization of water allocation, reservoir operation, and irrigation scheduling. The modeling framework is developed from a network of river basins that includes multiple nodes of origin (reservoirs, aquifers, water courses, etc.) and multiple demand sites along the river, including places of consumptive use for agricultural, municipal and industrial, and uses of running water on the coast of Peru. The economic benefits associated with water use are evaluated for different demand management instruments, including water rights, based on the production and benefit functions of water use in the urban agricultural and industrial sectors. This work represents a new effort to analyze the use of water at the regional level and to evaluate the modernization of the integrated management of water resources and socio-economic territorial development in Peru. It will also allow the establishment of policies to improve the process of implementation of the integrated management and development of water resources. The input-output analysis is essential to present a theory about the production process, which is based on a particular type of production function. Also, this work presents the Computable General Equilibrium (CGE) version of the economic model for water resource policy analysis, which was specifically designed for analyzing large-scale water management. As to the platform for CGE simulation, GEMPACK, a flexible system for solving CGE models, is used for formulating and solving CGE model through the percentage-change approach. GEMPACK automates the process of translating the model specification into a model solution program.

Keywords: water economy, simulation, modeling, integration

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Authors: Renée M. Ripken, Johannes G. E. Gardeniers, Séverine Le Gac

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Controlling the multiphase behavior of aqueous biomass mixtures is essential when working in the biomass conversion industry. Here, the vapor/liquid equilibria (VLE) of ethylene glycol, glycerol, and xylitol were studied for temperatures between 25 and 200 °C and pressures of 1 to 10 bar. These experiments were performed in a microfluidic platform, which exhibits excellent heat transfer properties so that equilibrium is reached fast. Firstly, the saturated vapor pressure as a function of the temperature and the substrate mole fraction of the substrate was calculated using AspenPlus with a Redlich-Kwong-Soave Boston-Mathias (RKS-BM) model. Secondly, we developed a high-pressure and high-temperature microfluidic set-up for experimental validation. Furthermore, we have studied the multiphase flow pattern that occurs after the saturation temperature was achieved. A glass-silicon microfluidic device containing a 0.4 or 0.2 m long meandering channel with a depth of 250 μm and a width of 250 or 500 μm was fabricated using standard microfabrication techniques. This device was placed in a dedicated chip-holder, which includes a ceramic heater on the silicon side. The temperature was controlled and monitored by three K-type thermocouples: two were located between the heater and the silicon substrate, one to set the temperature and one to measure it, and the third one was placed in a 300 μm wide and 450 μm deep groove on the glass side to determine the heat loss over the silicon. An adjustable back pressure regulator and a pressure meter were added to control and evaluate the pressure during the experiment. Aqueous biomass solutions (10 wt%) were pumped at a flow rate of 10 μL/min using a syringe pump, and the temperature was slowly increased until the theoretical saturation temperature for the pre-set pressure was reached. First and surprisingly, a significant difference was observed between our theoretical saturation temperature and the experimental results. The experimental values were 10’s of degrees higher than the calculated ones and, in some cases, saturation could not be achieved. This discrepancy can be explained in different ways. Firstly, the pressure in the microchannel is locally higher due to both the thermal expansion of the liquid and the Laplace pressure that has to be overcome before a gas bubble can be formed. Secondly, superheating effects are likely to be present. Next, once saturation was reached, the flow pattern of the gas/liquid multiphase system was recorded. In our device, the point of nucleation can be controlled by taking advantage of the pressure drop across the channel and the accurate control of the temperature. Specifically, a higher temperature resulted in nucleation further upstream in the channel. As the void fraction increases downstream, the flow regime changes along the channel from bubbly flow to Taylor flow and later to annular flow. All three flow regimes were observed simultaneously. The findings of this study are key for the development and optimization of a microreactor for hydrogen production from biomass.

Keywords: biomass conversion, high pressure and high temperature microfluidics, multiphase, phase diagrams, superheating

Procedia PDF Downloads 197

Authors: Nadeen Felemban, Hamsa Banjer, Rabaah Jaafari

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One of the most common hazards in the pharmaceutical industry is the chemical hazard, which can cause harm or develop occupational health diseases/illnesses due to chronic exposures to hazardous substances. Therefore, a chemical agent management system is required, including hazard identification, risk assessment, controls for specific hazards and inspections, to keep your workplace healthy and safe. However, routine management monitoring is also required to verify the effectiveness of the control measures. Moreover, Betamethasone Valerate and Clobetasol Propionate are some of the APIs (Active Pharmaceutical Ingredients) with highly hazardous classification-Occupational Hazard Category (OHC 4), which requires a full containment (ECA-D) during handling to avoid chemical exposure. According to Safety Data Sheet, those chemicals are reproductive toxicants (reprotoxicant H360D), which may affect female workers’ health and cause fatal damage to an unborn child, or impair fertility. In this study, qualitative (chemical Risk assessment-qCRA) was conducted to assess the chemical exposure during handling of Betamethasone Valerate and Clobetasol Propionate in pharmaceutical laboratories. The outcomes of qCRA identified that there is a risk of potential chemical exposure (risk rating 8 Amber risk). Therefore, immediate actions were taken to ensure interim controls (according to the Hierarchy of controls) are in place and in use to minimize the risk of chemical exposure. No open handlings should be done out of the Steroid Glove Box Isolator (SGB) with the required Personal Protective Equipment (PPEs). The PPEs include coverall, nitrile hand gloves, safety shoes and powered air-purifying respirators (PAPR). Furthermore, a quantitative assessment (personal air sampling) was conducted to verify the effectiveness of the engineering controls (SGB Isolator) and to confirm if there is chemical exposure, as indicated earlier by qCRA. Three personal air samples were collected using an air sampling pump and filter (IOM2 filters, 25mm glass fiber media). The collected samples were analyzed by HPLC in the BV lab, and the measured concentrations were reported in (ug/m3) with reference to Occupation Exposure Limits, 8hr OELs (8hr TWA) for each analytic. The analytical results are needed in 8hr TWA (8hr Time-weighted Average) to be analyzed using Bayesian statistics (IHDataAnalyst). The results of the Bayesian Likelihood Graph indicate (category 0), which means Exposures are de "minimus," trivial, or non-existent Employees have little to no exposure. Also, these results indicate that the 3 samplings are representative samplings with very low variations (SD=0.0014). In conclusion, the engineering controls were effective in protecting the operators from such exposure. However, routine chemical monitoring is required every 3 years unless there is a change in the processor type of chemicals. Also, frequent management monitoring (daily, weekly, and monthly) is required to ensure the control measures are in place and in use. Furthermore, a Similar Exposure Group (SEG) was identified in this activity and included in the annual health surveillance for health monitoring.

Keywords: occupational health and safety, risk assessment, chemical exposure, hierarchy of control, reproductive

Procedia PDF Downloads 153