Search results for: peak estimation

Authors: Nana Bolashvili, Vakhtang Geladze, Tamazi Karalashvili, Nino Machavariani, George Geladze, Davit Kartvelishvili, Ana Karalashvili

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Fresh water is the major natural resource of Georgia. The average perennial sum of the rivers' runoff in Georgia is 52,77 km³, out of which 9,30 km³ inflows from abroad. The major volume of transit river runoff is ascribed to the Chorokhi river. Average perennial runoff in Western Georgia is 41,52 km³, in Eastern Georgia 11,25 km³. The indices of Eastern and Western Georgia were calculated with 50% and 90% river runoff respectively, while the same index calculation for other countries is based on a 50% river runoff. Out of total volume of resources, 133,2 m³/sec (4,21 km³) has been geologically prospected by the State Commission on Reserves and Acknowledged as reserves available for exploitation, 48% (2,02 km³) of which is in Western Georgia and 2,19 km³ in Eastern Georgia. Considering acknowledged water reserves of all categories per capita water resources accounts to 2,2 m³/day, whereas high industrial category -0. 88 m³ /day fresh drinking water. According to accepted norms, the possibility of using underground water reserves is 2,5 times higher than the long-term requirements of the country. The volume of abundant fresh-water reserves in Georgia is about 150 m³/sec (4,74 km³). Water in Georgia is consumed mostly in agriculture for irrigation purposes. It makes 66,4% around Georgia, in Eastern Georgia 72,4% and 38% in Western Georgia. According to the long-term forecast provision of population and the territory with water resources in Eastern Georgia will be quite normal. A bit different is the situation in the lower reaches of the Khrami and Iori rivers which could be easily overcome by corresponding financing. The present day irrigation system in Georgia does not meet the modern technical requirements. The overall efficiency of their majority varies between 0,4-0,6. Similar is the situation in the fresh water and public service water consumption. Organization of the mentioned systems, installation of water meters, introduction of new methods of irrigation without water loss will substantially increase efficiency of water use. Besides new irrigation norms developed from agro-climatic, geographical and hydrological angle will significantly reduce water waste. Taking all this into account we assume that for irrigation agricultural lands in Georgia is necessary 6,0 km³ water, 5,5 km³ of which goes to Eastern Georgia on irrigation arable areas. To increase water supply in Eastern Georgian territory and its population is possible by means of new water reservoirs as the runoff of every river considerably exceeds the consumption volume. In conclusion, we should say that fresh water resources by which Georgia is that rich could be significant source for barter exchange and investment attraction. Certain volume of fresh water can be exported from Western Georgia quite trouble free, without bringing any damage to population and hydroecosystems. The precise volume of exported water per region/time and method/place of water consumption should be defined after the estimation of different hydroecosystems and detailed analyses of water balance of the corresponding territories.

Keywords: GIS, management, rivers, water resources

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Authors: Swati Mishra

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In recent years, there has been an explosion in Gold NanoParticle (GNP) research, with a rapid increase in publications in diverse fields, including imaging, bioengineering, and molecular biology. GNPs exhibit unique physicochemical properties, including surface plasmon resonance (SPR) and bind amine and thiol groups, allowing surface modification and use in biomedical applications. Nanoparticle functionalization is the subject of intense research at present, with rapid progress being made towards developing biocompatible, multi-functional particles. In the present study, the photochemical method has been done to functionalize various-shaped GNPs like nanostars by the molecules like ninhydrin. Ninhydrin is bactericidal, virucidal, fungicidal, antigen-antibody reactive, and used in fingerprint technology in forensics. The GNPs functionalized with ninhydrin efficiently will bind to the amino acids on the target protein, which is of eminent importance during the pandemic, especially where long-term treatments of COVID- 19 bring many side effects of the drugs. The photochemical method is adopted as it provides low thermal load, selective reactivity, selective activation, and controlled radiation in time, space, and energy. The GNPs exhibit their characteristic spectrum, but a distinctly blue or redshift in the peak will be observed after UV irradiation, ensuring efficient ninhydrin binding. Now, the bound ninhydrin in the GNP carrier, upon chemically reacting with any amino acid, will lead to the formation of Rhumann purple. A common method of GNP production includes citrate reduction of Au [III] derivatives such as aurochloric acid (HAuCl4) in water to Au [0] through a one-step synthesis of size-tunable GNPs. The following reagents are prepared to validate the approach. Reagent A solution 1 is0.0175 grams ninhydrin in 5 ml Millipore water Reagent B 30 µl of HAuCl₄.3H₂O in 3 ml of solution 1 Reagent C 1 µl of gold nanostars in 3 ml of solution 1 Reagent D 6 µl of cetrimonium bromide (CTAB) in 3 ml of solution1 ReagentE 1 µl of gold nanostars in 3 ml of ethanol ReagentF 30 µl of HAuCl₄.₃H₂O in 3 ml of ethanol ReagentG 30 µl of HAuCl₄.₃H₂O in 3 ml of solution 2 ReagentH solution 2 is0.0087 grams ninhydrin in 5 ml Millipore water ReagentI 30 µl of HAuCl₄.₃H₂O in 3 ml of water The reagents were irradiated at 254 nm for 15 minutes, followed by their UV Visible spectroscopy. The wavelength was selected based on the one reported for excitation of a similar molecule Pthalimide. It was observed that the solution B and G deviate around 600 nm, while C peaks distinctively at 567.25 nm and 983.9 nm. Though it is tough to say about the chemical reaction happening, butATR-FTIR of reagents will ensure that ninhydrin is not forming Rhumann purple in the absence of amino acids. Therefore, these experiments, we achieved the functionalization of gold nanostars with ninhydrin corroborated by the deviation in the spectrum obtained in a mixture of GNPs and ninhydrin irradiated with UV light. It prepares them as a carrier molecule totake up amino acids for targeted delivery or germicidal action.

Keywords: gold nanostars, ninhydrin, photochemical method, UV visible specgtroscopy

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Authors: S. Cichosz, A. Masek

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A new cellulose hybrid modification approach, which is undoubtedly a scientific novelty, is introduced. The study reports the properties of cellulose (Arbocel UFC100 – Ultra Fine Cellulose) and characterizes cellulose filled polymer composites based on an ethylene-norbornene copolymer (TOPAS Elastomer E-140). Moreover, the approach of physicochemical two-stage cellulose treatment is introduced: solvent exchange (to ethanol or hexane) and further chemical modification with maleic anhydride (MA). Furthermore, the impact of the drying process on cellulose properties was investigated. Suitable measurements were carried out to characterize cellulose fibers: spectroscopic investigation (Fourier Transform Infrared Spektrofotometer-FTIR, Near InfraRed spectroscopy-NIR), thermal analysis (Differential scanning calorimetry, Thermal gravimetric analysis ) and Karl Fischer titration. It should be emphasized that for all UFC100 treatments carried out, a decrease in moisture content was evidenced. FT-IR reveals a drop in absorption band intensity at 3334 cm-1, the peak is associated with both –OH moieties and water. Similar results were obtained with Karl Fischer titration. Based on the results obtained, it may be claimed that the employment of ethanol contributes greatly to the lowering of cellulose water absorption ability (decrease of moisture content to approximately 1.65%). Additionally, regarding polymer composite properties, crucial data has been obtained from the mechanical and thermal analysis. The highest material performance was noted in the case of the composite sample that contained cellulose modified with MA after a solvent exchange with ethanol. This specimen exhibited sufficient tensile strength, which is almost the same as that of the neat polymer matrix – in the region of 40 MPa. Moreover, both the Payne effect and filler efficiency factor, calculated based on dynamic mechanical analysis (DMA), reveal the possibility of the filler having a reinforcing nature. What is also interesting is that, according to the Payne effect results, fibers dried before the further chemical modification are assumed to allow more regular filler structure development in the polymer matrix (Payne effect maximum at 1.60 MPa), compared with those not dried (Payne effect in the range 0.84-1.26 MPa). Furthermore, taking into consideration the data gathered from DSC and TGA, higher thermal stability is obtained in case of the materials filled with fibers that were dried before the carried out treatments (degradation activation energy in the region of 195 kJ/mol) in comparison with the polymer composite samples filled with unmodified cellulose (degradation activation energy of approximately 180 kJ/mol). To author’s best knowledge this work results in the introduction of a novel, new filler hybrid treatment approach. Moreover, valuable data regarding the properties of composites filled with cellulose fibers of various moisture contents have been provided. It should be emphasized that plant fiber-based polymer bio-materials described in this research might contribute significantly to polymer waste minimization because they are more readily degraded.

Keywords: cellulose fibers, solvent exchange, moisture content, ethylene-norbornene copolymer

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Authors: Ife Elegbeleye, Nnditshedzeni Eric, Regina Maphanga, Femi Elegbeleye, Femi Agunbiade

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The global potential of other renewable energy sources such as wind, hydroelectric, bio-mass, and geothermal is estimated to be approximately 13 %, with hydroelectricity constituting a larger percentage. Sunlight provides by far the largest of all carbon-neutral energy sources. More energy from the sunlight strikes the Earth in one hour (4.3 × 1020 J) than all the energy consumed on the planet in a year (4.1 × 1020 J), hence, solar energy remains the most abundant clean, renewable energy resources for mankind. Photovoltaic (PV) devices such as silicon solar cells, dye sensitized solar cells are utilized for harnessing solar energy. Polyene-diphenylaniline organic molecules are important sets of molecules that has stirred many research interest as photosensitizers in TiO₂ semiconductor-based dye sensitized solar cells (DSSCs). The advantages of organic dye molecule over metal-based complexes are higher extinction coefficient, moderate cost, good environmental compatibility, and electrochemical properties. The polyene-diphenylaniline organic dyes with basic configuration of donor-π-acceptor are affordable, easy to synthesize and possess chemical structures that can easily be modified to optimize their photocatalytic and spectral properties. The enormous interest in polyene-diphenylaniline dyes as photosensitizers is due to their fascinating spectral properties which include visible light to near infra-red-light absorption. In this work, density functional theory approach via GPAW software, Avogadro and ASE were employed to study the effect of methoxy functionalized group on the spectral properties of polyene-diphenylaniline dyes and their photons absorbing characteristics in the visible region to near infrared region of the solar spectrum. Our results showed that the two-phenyl based complexes D5 and D7 exhibits maximum absorption peaks at 750 nm and 850 nm, while D9 and D11 with methoxy group shows maximum absorption peak at 800 nm and 900 nm respectively. The highest absorption wavelength is notable for D9 and D11 containing additional polyene and methoxy groups. Also, D9 and D11 chromophores with the methoxy group shows lower energy gap of 0.98 and 0.85 respectively than the corresponding D5 and D7 dyes complexes with energy gap of 1.32 and 1.08. The analysis of their electron injection kinetics ∆Ginject into the band gap of TiO₂ shows that D9 and D11 with the methoxy group has higher electron injection kinetics of -2.070 and -2.030 than the corresponding polyene-diphenylaniline complexes without the addition of polyene group with ∆Ginject values of -2.820 and -2.130 respectively. Our findings suggest that the addition of functionalized group as an extension of the organic complexes results in higher light harvesting efficiencies and bathochromic shift of the absorption spectra to higher wavelength which suggest higher current densities and open circuit voltage in DSSCs. The study suggests that the photocatalytic properties of organic chromophores/complexes with donor-π-acceptor configuration can be enhanced by the addition of functionalized groups.

Keywords: renewable energy resource, solar energy, dye sensitized solar cells, polyene-diphenylaniline organic chromophores

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Authors: Ibrahim A. Adeniran, Rui F. Zhu, Man S. Wong

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Owing to the insufficiency in the spatial representativeness and continuity of in situ temperature measurements from weather stations (WS), the use of temperature measurement from WS for large-range diurnal analysis in heterogenous landscapes has been limited. This has made the accurate estimation of land surface temperature (LST) from remotely sensed data more crucial. Moreover, the study of dynamic interaction between the atmosphere and the physical surface of the Earth could be enhanced at both annual and diurnal scales by using optimal LST data derived from satellite sensors. The tradeoff between the spatial and temporal resolution of LSTs from satellite’s thermal infrared sensors (TIRS) has, however, been a major challenge, especially when high spatiotemporal LST data are recommended. It is well-known from existing literature that polar satellites have the advantage of high spatial resolution, while geostationary satellites have a high temporal resolution. Hence, this study is aimed at designing a framework for the cross-comparison of LST data from polar and geostationary satellites in a heterogeneous landscape. This could help to understand the relationship between the LST estimates from the two satellites and, consequently, their integration in diurnal LST analysis. Landsat-8 satellite data will be used as the representative of the polar satellite due to the availability of its long-term series, while the Himawari-8 satellite will be used as the data source for the geostationary satellite because of its improved TIRS. For the study area, Hong Kong Special Administrative Region (HK SAR) will be selected; this is due to the heterogeneity in the landscape of the region. LST data will be retrieved from both satellites using the Split window algorithm (SWA), and the resulting data will be validated by comparing satellite-derived LST data with temperature data from automatic WS in HK SAR. The LST data from the satellite data will then be separated based on the land use classification in HK SAR using the Global Land Cover by National Mapping Organization version3 (GLCNMO 2013) data. The relationship between LST data from Landsat-8 and Himawari-8 will then be investigated based on the land-use class and over different seasons of the year in order to account for seasonal variation in their relationship. The resulting relationship will be spatially and statistically analyzed and graphically visualized for detailed interpretation. Findings from this study will reveal the relationship between the two satellite data based on the land use classification within the study area and the seasons of the year. While the information provided by this study will help in the optimal combination of LST data from Polar (Landsat-8) and geostationary (Himawari-8) satellites, it will also serve as a roadmap in the annual and diurnal urban heat (UHI) analysis in Hong Kong SAR.

Keywords: automatic weather station, Himawari-8, Landsat-8, land surface temperature, land use classification, split window algorithm, urban heat island

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Authors: Gautam, Gurcharan Singh, Mandeep Kaur, Yogesh Aggarwal, Sanjeev Naval

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The present ground reality scenario of suffering of humanity shows the evidence of failure to take wrong decisions to shape the civilization with Irresponsibilities in the history. A strong positive will of right responsibilities make the right civilization structure which affects itself and the whole world. Present suffering of humanity shows and reflect the failure of past decisions taken to shape the true culture with right social structure of society, due to unplanned system of Indian civilization and its rapid disaster of population make the failure to face all kind of problems which make the society sufferer. Our India is still suffering from disaster like earthquake, floods, droughts, tsunamis etc. and we face the uncountable disaster of deaths from the beginning of humanity at the present time. In this research paper our focus is to make a Disaster Resistance Structure having the solution of dense populated urban cities area by high vertical expansion HYBRID STRUCTURE. Our efforts are to analyse the Reinforced Concrete Hybrid Structure at different seismic zones, these concrete frames were analyzed using the response spectrum method to calculate and compare the different seismic displacement and drift. Seismic analysis by this method generally is based on dynamic analysis of building. Analysis results shows that the Reinforced Concrete Building at seismic Zone V having maximum peak story shear, base shear, drift and node displacement as compare to the analytical results of Reinforced Concrete Building at seismic Zone III and Zone IV. This analysis results indicating to focus on structural drawings strictly at construction site to make a HYBRID STRUCTURE. The study case is deal with the 10 story height of a vertical expansion Hybrid frame structure at different zones i.e. zone III, zone IV and zone V having the column 0.45x0.36mt and beam 0.6x0.36mt. with total height of 30mt, to make the structure more stable bracing techniques shell be applied like mage bracing and V shape bracing. If this kind of efforts or structure drawings are followed by the builders and contractors then we save the lives during earthquake disaster at Bhuj (Gujarat State, India) on 26th January, 2001 which resulted in more than 19,000 deaths. This kind of Disaster Resistance Structure having the capabilities to solve the problems of densely populated area of cities by the utilization of area in vertical expansion hybrid structure. We request to Government of India to make new plans and implementing it to save the lives from future disasters instead of unnecessary wants of development plans like Bullet Trains.

Keywords: history, irresponsibilities, unplanned social structure, humanity, hybrid structure, response spectrum analysis, DRIFT, and NODE displacement

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Authors: Man-Yu Wong, Siyu Zhou, Zhiqiang Cao

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In quality of life, health service utilization is an important determinant of medical resource expenditures on Colorectal cancer (CRC) care, a better understanding of the increased utilization of health services is essential for optimizing the allocation of healthcare resources to services and thus for enhancing the service quality, especially for high expenditure on CRC care like Hong Kong region. In assessing the association between the health-related quality of life (HRQOL) and health service utilization in patients with colorectal neoplasm, count data models can be used, which account for over dispersion or extra zero counts. In our data, the HRQOL evaluation is a self-reported measure obtained from a questionnaire completed by the patients, misreports and variations in the data are inevitable. Besides, there are more zero counts from the observed number of clinical consultations (observed frequency of zero counts = 206) than those from a Poisson distribution with mean equal to 1.33 (expected frequency of zero counts = 156). This suggests that excess of zero counts may exist. Therefore, we study tests for detecting zero-inflation in models with measurement error in covariates. Method: Under classical measurement error model, the approximate likelihood function for zero-inflation Poisson regression model can be obtained, then Approximate Maximum Likelihood Estimation(AMLE) can be derived accordingly, which is consistent and asymptotically normally distributed. By calculating score function and Fisher information based on AMLE, a score test is proposed to detect zero-inflation effect in ZIP model with measurement error. The proposed test follows asymptotically standard normal distribution under H0, and it is consistent with the test proposed for zero-inflation effect when there is no measurement error. Results: Simulation results show that empirical power of our proposed test is the highest among existing tests for zero-inflation in ZIP model with measurement error. In real data analysis, with or without considering measurement error in covariates, existing tests, and our proposed test all imply H0 should be rejected with P-value less than 0.001, i.e., zero-inflation effect is very significant, ZIP model is superior to Poisson model for analyzing this data. However, if measurement error in covariates is not considered, only one covariate is significant; if measurement error in covariates is considered, only another covariate is significant. Moreover, the direction of coefficient estimations for these two covariates is different in ZIP regression model with or without considering measurement error. Conclusion: In our study, compared to Poisson model, ZIP model should be chosen when assessing the association between condition-specific HRQOL and health service utilization in patients with colorectal neoplasm. and models taking measurement error into account will result in statistically more reliable and precise information.

Keywords: count data, measurement error, score test, zero inflation

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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

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Authors: Ginpreet Kaur, Mohammad Yasir Usmani, Mohammed Kamil Khan

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Diabetes mellitus is a disease with a high global burden and results in significant morbidity and mortality. In India, the number of people suffering with diabetes is expected to rise from 19 to 57 million in 2025. At present, interest in herbal remedies is growing to reduce the side effects associated with conventional dosage form like oral hypoglycemic agents and insulin for the treatment of diabetes mellitus. Our aim was to investigate the antidiabetic activities of combinatorial extract of N. sativa & C. cassia in Streptozotocin induced type-I Diabetic Rats. Thus, the present study was undertaken to screen postprandial glucose excursion potential through α- glucosidase inhibitory activity (In Vitro) and effect of combinatorial extract of N. sativa & C. cassia in Streptozotocin induced type-I Diabetic Rats (In Vivo). In addition changes in body weight, plasma glucose, lipid profile and kidney profile were also determined. The IC50 values for both extract and Acarbose was calculated by extrapolation method. Combinatorial extract of N. sativa & C. cassia at different dosages (100 and 200 mg/kg orally) and Metformin (50 mg/kg orally) as the standard drug was administered for 28 days and then biochemical estimation, body weights and OGTT (Oral glucose tolerance test) were determined. Histopathological studies were also performed on kidney and pancreatic tissue. In In-Vitro the combinatorial extract shows much more inhibiting effect than the individual extracts. The results reveals that combinatorial extract of N. sativa & C. cassia has shown significant decrease in plasma glucose (p<0.0001), total cholesterol and LDL levels when compared with the STZ group The decreasing level of BUN and creatinine revealed the protection of N. sativa & C. cassia extracts against nephropathy associated with diabetes. Combination of N. sativa & C. cassia significantly improved glucose tolerance to exogenously administered glucose (2 g/kg) after 60, 90 and 120 min interval on OGTT in high dose streptozotocin induced diabetic rats compared with the untreated control group. Histopathological studies shown that treatment with N. sativa & C. cassia extract alone and in combination restored pancreatic tissue integrity and was able to regenerate the STZ damaged pancreatic β cells. Thus, the present study reveals that combination of N. sativa & C. cassia extract has significant α- glucosidase inhibitory activity and thus has great potential as a new source for diabetes treatment.

Keywords: lipid levels, OGTT, diabetes, herbs, glucosidase

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Authors: Adrián Esteban Ortiz-Valera, Angélica Lozano

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In developing countries, informal trade is relevant, but it has been little studied in urban freight transport (UFT) context, although it is a challenge due to the non- contemplated demand it produces and the operational limitations it imposes. Hence, UFT operational improvements (initiatives) and freight attraction models must consider informal trade for developing countries. Afour phasesapproach for characterizing the commercial areas in developing countries (considering both formal and informal establishments) is proposed and applied to ten areas in Mexico City. This characterization is required to calculate real freight trip attraction and then select and/or adapt suitable initiatives. Phase 1 aims the delimitation of the study area. The following information is obtained for each establishment of a potential area: location or geographic coordinates, industrial sector, industrial subsector, and number of employees. Phase 2 characterizes the study area and proposes a set of indicators. This allows a broad view of the operations and constraints of UFT in the study area. Phase 3 classifies the study area according to seven indicators. Each indicator represents a level of conflict in the area due to the presence of formal (registered) and informal establishments on the sidewalks and streets, affecting urban freight transport (and other activities). Phase 4 determines preliminary initiatives which could be implemented in the study area to improve the operation of UFT. The indicators and initiatives relation allows a preliminary initiatives selection. This relation requires to know the following: a) the problems in the area (congested streets, lack of parking space for freight vehicles, etc.); b) the factors which limit initiatives due to informal establishments (reduced streets for freight vehicles; mobility and parking inability during a period, among others), c) the problems in the area due to its physical characteristics; and d) the factors which limit initiatives due to regulations of the area. Several differences in the study areas were observed. As the indicators increases, the areas tend to be less ordered, and the limitations for the initiatives become higher, causing a smaller number of susceptible initiatives. In ordered areas (similar to the commercial areas of developed countries), the current techniquesfor estimating freight trip attraction (FTA) can bedirectly applied, however, in the areas where the level of order is lower due to the presence of informal trade, this is not recommended because the real FTA would not be estimated. Therefore, a technique, which consider the characteristics of the areas in developing countries to obtain data and to estimate FTA, is required. This estimation can be the base for proposing feasible initiatives to such zones. The proposed approach provides a wide view of the needs of the commercial areas of developing countries. The knowledge of these needs would allow UFT´s operation to be improved and its negative impacts to be minimized.

Keywords: freight initiatives, freight trip attraction, informal trade, urban freight transport

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Authors: Kimuel Suyat, Francis Aldrine Uy, John Paul Carreon

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The Philippines, composed of many islands, is connected with approximately 8030 bridges. Continuous evaluation of the structural condition of these bridges is needed to safeguard the safety of the general public. With most bridges reaching its design life, retrofitting and replacement may be needed. Concerned government agencies allocate huge costs for periodic monitoring and maintenance of these structures. The rising volume of traffic and aging of these infrastructures is challenging structural engineers to give rise for structural health monitoring techniques. Numerous techniques are already proposed and some are now being employed in other countries. Vibration Analysis is one way. The natural frequency and vibration of a bridge are design criteria in ensuring the stability, safety and economy of the structure. Its natural frequency must not be so high so as not to cause discomfort and not so low that the structure is so stiff causing it to be both costly and heavy. It is well known that the stiffer the member is, the more load it attracts. The frequency must not also match the vibration caused by the traffic loads. If this happens, a resonance occurs. Vibration that matches a systems frequency will generate excitation and when this exceeds the member’s limit, a structural failure will happen. This study presents a method for calculating dynamic fragility through the use of vibration-based monitoring system. Dynamic fragility is the probability that a structural system exceeds a limit state when subjected to dynamic loads. The bridge is modeled in SAP2000 based from the available construction drawings provided by the Department of Public Works and Highways. It was verified and adjusted based from the actual condition of the bridge. The bridge design specifications are also checked using nondestructive tests. The approach used in this method properly accounts the uncertainty of observed values and code-based structural assumptions. The vibration response of the structure due to actual loads is monitored using installed sensors on the bridge. From the determinacy of these dynamic characteristic of a system, threshold criteria can be established and fragility curves can be estimated. This study conducted in relation with the research project between Department of Science and Technology, Mapúa Institute of Technology, and the Department of Public Works and Highways also known as Mapúa-DOST Smart Bridge Project deploys Structural Health Monitoring Sensors at Zamora Bridge. The bridge is selected in coordination with the Department of Public Works and Highways. The structural plans for the bridge are also readily available.

Keywords: structural health monitoring, dynamic characteristic, threshold criteria, traffic loads

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Authors: Ciwang Teyra, A. H. Y. Lai

Abstract:

Introduction: Indigenous LGBTQ individuals face with significant life stress such as racial and gender discrimination and microaggressions, which may lead to negative impacts of their mental health. Although studies relevant to Taiwanese indigenous LGBTQpeople gradually increase, most of them are primarily conceptual or qualitative in nature. This research aims to fulfill the gap by offering empirical quantitative evidence, especially investigating the impact of racial and gender microaggressions on mental health among Taiwanese indigenous LGBTQindividuals with an intersectional perspective, as well as examine whether social support can help them to cope with microaggressions. Methods: Participants were (n=200; mean age=29.51; Female=31%, Male=61%, Others=8%). A cross-sectional quantitative design was implemented using data collected in the year 2020. Standardised measurements was used, including Racial Microaggression Scale (10 items), Gender Microaggression Scale (9 items), Social Support Questionnaire-SF(6 items); Patient Health Questionnaire(9-item); and Generalised Anxiety Disorder(7-item). Covariates were age, gender, and perceived economic hardships. Structural equation modelling (SEM) was employed using Mplus 8.0 with the latent variables of depression and anxiety as outcomes. A main effect SEM model was first established (Model1).To test the moderation effects of perceived social support, an interaction effect model (Model 2) was created with interaction terms entered into Model1. Numerical integration was used with maximum likelihood estimation to estimate the interaction model. Results: Model fit statistics of the Model 1:X2(df)=1308.1 (795), p<.05; CFI/TLI=0.92/0.91; RMSEA=0.06; SRMR=0.06. For Model, the AIC and BIC values of Model 2 improved slightly compared to Model 1(AIC =15631 (Model1) vs. 15629 (Model2); BIC=16098 (Model1) vs. 16103 (Model2)). Model 2 was adopted as the final model. In main effect model 1, racialmicroaggressionand perceived social support were associated with depression and anxiety, but not sexual orientation microaggression(Indigenous microaggression: b = 0.27 for depression; b=0.38 for anxiety; Social support: b=-0.37 for depression; b=-0.34 for anxiety). Thus, an interaction term between social support and indigenous microaggression was added in Model 2. In the final Model 2, indigenous microaggression and perceived social support continues to be statistically significant predictors of both depression and anxiety. Social support moderated the effect of indigenous microaggression of depression (b=-0.22), but not anxiety. All covariates were not statistically significant. Implications: Results indicated that racial microaggressions have a significant impact on indigenous LGBTQ people’s mental health. Social support plays as a crucial role to buffer the negative impact of racial microaggression. To promote indigenous LGBTQ people’s wellbeing, it is important to consider how to support them to develop social support network systems.

Keywords: microaggressions, intersectionality, indigenous population, mental health, social support

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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.

Procedia PDF Downloads 49

Authors: Hussain Bohra, Pradyuman Sharma

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This study highlights the significance of Balance Sheet Indicators on the corporate performance in the case of Indian manufacturing companies. Balance sheet indicators show the actual financial health of the company and it helps to the external investors to choose the right company for their investment and it also help to external financing agency to give easy finance to the manufacturing companies. The period of study is 2000 to 2014 for 813 manufacturing companies for which the continuous data is available throughout the study period. The data is collected from PROWESS data base maintained by Centre for Monitoring Indian Economy Pvt. Ltd. Panel data methods like fixed effect and random effect methods are used for the analysis. The Likelihood Ratio test, Lagrange Multiplier test and Hausman test results proof the suitability of the fixed effect model for the estimation. Return on assets (ROA) is used as the proxy to measure corporate performance. ROA is the best proxy to measure corporate performance as it already used by the most of the authors who worked on the corporate performance. ROA shows return on long term investment projects of firms. Different ratios like Current Ratio, Debt-equity ratio, Receivable turnover ratio, solvency ratio have been used as the proxies for the Balance Sheet Indicators. Other firm specific variable like firm size, and sales as the control variables in the model. From the empirical analysis, it was found that all selected financial ratios have significant and positive impact on the corporate performance. Firm sales and firm size also found significant and positive impact on the corporate performance. To check the robustness of results, the sample was divided on the basis of different ratio like firm having high debt equity ratio and low debt equity ratio, firms having high current ratio and low current ratio, firms having high receivable turnover and low receivable ratio and solvency ratio in the form of firms having high solving ratio and low solvency ratio. We find that the results are robust to all types of companies having different form of selected balance sheet indicators ratio. The results for other variables are also in the same line as for the whole sample. These findings confirm that Balance sheet indicators play as significant role on the corporate performance in India. The findings of this study have the implications for the corporate managers to focus different ratio to maintain the minimum expected level of performance. Apart from that, they should also maintain adequate sales and total assets to improve corporate performance.

Keywords: balance sheet, corporate performance, current ratio, panel data method

Procedia PDF Downloads 237

Authors: Ho Yin Wickson Cheung, Liora Malki-Epshtein

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Outdoor air pollution presents a significant challenge for public health globally, especially in urban areas, with road traffic acting as the primary contributor to air pollution. Several studies have documented the antagonistic relation between traffic-related air pollution (TRAP) and the impact on health, especially to the vulnerable group of population, particularly young pupils. Generally, TRAP could cause damage to their brain, restricting the ability of children to learn and, more importantly, causing detrimental respiratory issues in later life. Butlittle is known about the specific exposure of children at school during the school day and the impact this may have on their overall exposure to pollution at a crucial time in their development. This project has set out to examine the air quality across primary schools in South-East London and assesses the variability of data found based on their geographic location and surroundings. Nitrogen dioxide, PM contaminants, and carbon dioxide were collected with diffusion tubes and portable monitoring equipment for eight schools across three local areas, that are Greenwich, Lewisham, and Tower Hamlets. This study first examines the geographical features of the schools surrounding (E.g., coverage of urban road structure and green infrastructure), then utilize three different methods to capture pollutants data. Moreover, comparing the obtained results with existing data from monitoring stations to understand the differences in air quality before and during the pandemic. Furthermore, most studies in this field have unfortunately neglected human exposure to pollutants and calculated based on values from fixed monitoring stations. Therefore, this paper introduces an alternative approach by calculating human exposure to air pollution from real-time data obtained when commuting within related areas (Driving routes and field walking). It is found that schools located highly close to motorways are generally not suffering from the most air pollution contaminants. Instead, one with the worst traffic congested routes nearby might also result in poor air quality. Monitored results also indicate that the annual air pollution values have slightly decreased during the pandemic. However, the majority of the data is currently still exceeding the WHO guidelines. Finally, the total human exposures for NO2 during commuting in the two selected routes were calculated. Results illustrated the total exposure for route 1 were 21,730 μm/m3 and 28,378.32 μm/m3, and for route 2 were 30,672 μm/m3 and 16,473 μm/m3. The variance that occurred might be due to the difference in traffic volume that requires further research. Exposure for NO2 during commuting was plotted with detailed timesteps that have shown their peak usually occurred while commuting. These have consolidated the initial assumption to the extremeness of TRAP. To conclude, this paper has yielded significant benefits to understanding air quality across schools in London with the new approach of capturing human exposure (Driving routes). Confirming the severity of air pollution and promoting the necessity of considering environmental sustainability for policymakers during decision making to protect society's future pillars.

Keywords: air pollution, schools, pupils, congestion

Procedia PDF Downloads 91

Authors: H. Hruschka

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This paper presents the first comparison of the performance of the restricted Boltzmann machine and the deep belief net on binary market basket data relative to binary factor analysis and the two best-known topic models, namely Dirichlet allocation and the correlated topic model. This comparison shows that the restricted Boltzmann machine and the deep belief net are superior to both binary factor analysis and topic models. Managerial implications that differ between the investigated models are treated as well. The restricted Boltzmann machine is defined as joint Boltzmann distribution of hidden variables and observed variables (purchases). It comprises one layer of observed variables and one layer of hidden variables. Note that variables of the same layer are not connected. The comparison also includes deep belief nets with three layers. The first layer is a restricted Boltzmann machine based on category purchases. Hidden variables of the first layer are used as input variables by the second-layer restricted Boltzmann machine which then generates second-layer hidden variables. Finally, in the third layer hidden variables are related to purchases. A public data set is analyzed which contains one month of real-world point-of-sale transactions in a typical local grocery outlet. It consists of 9,835 market baskets referring to 169 product categories. This data set is randomly split into two halves. One half is used for estimation, the other serves as holdout data. Each model is evaluated by the log likelihood for the holdout data. Performance of the topic models is disappointing as the holdout log likelihood of the correlated topic model – which is better than Dirichlet allocation - is lower by more than 25,000 compared to the best binary factor analysis model. On the other hand, binary factor analysis on its own is clearly surpassed by both the restricted Boltzmann machine and the deep belief net whose holdout log likelihoods are higher by more than 23,000. Overall, the deep belief net performs best. We also interpret hidden variables discovered by binary factor analysis, the restricted Boltzmann machine and the deep belief net. Hidden variables characterized by the product categories to which they are related differ strongly between these three models. To derive managerial implications we assess the effect of promoting each category on total basket size, i.e., the number of purchased product categories, due to each category's interdependence with all the other categories. The investigated models lead to very different implications as they disagree about which categories are associated with higher basket size increases due to a promotion. Of course, recommendations based on better performing models should be preferred. The impressive performance advantages of the restricted Boltzmann machine and the deep belief net suggest continuing research by appropriate extensions. To include predictors, especially marketing variables such as price, seems to be an obvious next step. It might also be feasible to take a more detailed perspective by considering purchases of brands instead of purchases of product categories.

Keywords: binary factor analysis, deep belief net, market basket analysis, restricted Boltzmann machine, topic models

Procedia PDF Downloads 168

Authors: Hsiang-Yu Yuan, Marc Baguelin, Kin O. Kwok, Nimalan Arinaminpathy, Edwin Leeuwen, Steven Riley

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Traditional syndromic surveillance for influenza has substantial public health value in characterizing epidemics. Because the relationship between syndromic incidence and the true infection events can vary from one population to another and from one year to another, recent studies rely on combining serological test results with syndromic data from traditional surveillance into epidemic models to make inference on epidemiological processes of influenza. However, despite the widespread availability of serological data, epidemic models have thus far not explicitly represented antibody titre levels and their correspondence with immunity. Most studies use dichotomized data with a threshold (Typically, a titre of 1:40 was used) to define individuals as likely recently infected and likely immune and further estimate the cumulative incidence. Underestimation of Influenza attack rate could be resulted from the dichotomized data. In order to improve the use of serosurveillance data, here, a refinement of the concept of the stratified immunity within an epidemic model for influenza transmission was proposed, such that all individual antibody titre levels were enumerated explicitly and mapped onto a variable scale of susceptibility in different age groups. Haemagglutination inhibition titres from 523 individuals and 465 individuals during pre- and post-pandemic phase of the 2009 pandemic in Hong Kong were collected. The model was fitted to serological data in age-structured population using Bayesian framework and was able to reproduce key features of the epidemics. The effects of age-specific antibody boosting and protection were explored in greater detail. RB was defined to be the effective reproductive number in the presence of stratified immunity and its temporal dynamics was compared to the traditional epidemic model using use dichotomized seropositivity data. Deviance Information Criterion (DIC) was used to measure the fitness of the model to serological data with different mechanisms of the serological response. The results demonstrated that the differential antibody response with age was present (ΔDIC = -7.0). The age-specific mixing patterns with children specific transmissibility, rather than pre-existing immunity, was most likely to explain the high serological attack rates in children and low serological attack rates in elderly (ΔDIC = -38.5). Our results suggested that the disease dynamics and herd immunity of a population could be described more accurately for influenza when the distribution of immunity was explicitly represented, rather than relying only on the dichotomous states 'susceptible' and 'immune' defined by the threshold titre (1:40) (ΔDIC = -11.5). During the outbreak, RB declined slowly from 1.22[1.16-1.28] in the first four months after 1st May. RB dropped rapidly below to 1 during September and October, which was consistent to the observed epidemic peak time in the late September. One of the most important challenges for infectious disease control is to monitor disease transmissibility in real time with statistics such as the effective reproduction number. Once early estimates of antibody boosting and protection are obtained, disease dynamics can be reconstructed, which are valuable for infectious disease prevention and control.

Keywords: effective reproductive number, epidemic model, influenza epidemic dynamics, stratified immunity

Procedia PDF Downloads 229

Authors: Showkat Ahmad Bhat, Iqra Reyaz, Falaque ul Afshan, Ahmad Arif Reshi, Muneeb U. Rehman, Manzoor R. Mir, Sabhiya Majid, Sonallah, Sheikh Bilal, Ishraq Hussain

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Background: Gastric cancer is the fourth most common cancer and the second leading cause of worldwide cancer-related deaths, with a wide variation in incidence rates across different geographical areas. The current view of cancer is that a malignancy arises from a transformation of the genetic material of a normal cell, followed by successive mutations and by chain of alterations in genes such as DNA repair genes, oncogenes, Tumor suppressor genes. Minerals are necessary for the functioning of several transcriptional factors, proteins that recognize certain DNA sequences and have been found to play a role in gastric cancer. Material Methods:The present work was a case control study and its aim was to ascertain the role of minerals and promoter hypermethylation of CpG islands of DAP-K gene in Gastric cancer patients among the Kashmiri population. Serum was extracted from all the samples and mineral estimation was done by AAS from serum, DNA was also extracted and was modified using bisulphite modification kit. Methylation-specific PCR was used for the analysis of the promoter hypermethylation status of DAP-K gene. The epigenetic analysis revealed that unlike other high risk regions, Kashmiri population has a different promoter hypermethylation profile of DAP-K gene and has different mineral profile. Results: In our study mean serum copper levels were significantly different for the two genders (p<0.05), while as no significant differences were observed for iron and zinc levels. In Methylation-specific PCR the methylation status of the promoter region of DAP-K gene was as 67.50% (27/40) of the gastric cancer tissues showed methylated DAP-K promoter and 32.50% (13/40) of the cases however showed unmethylated DAP-K promoter. Almost all 85% (17/20) of the histopathologically confirmed normal tissues showed unmethylated DAP-K promoter except only in 3 cases where DAP-K promoter was found to be methylated. The association of promoter hypermethylation with gastric cancer was evaluated by χ2 (Chi square) test and was found to be significant (P=0.0006). Occurrence of DAP-K methylation was found to be unequally distributed in males and females with more frequency in males than in females but the difference was not statistically significant (P =0.7635, Odds ratio=1.368 and 95% C.I=0.4197 to 4.456). When the frequency of DAP-K promoter methylation was compared with clinical staging of the disease, DAP-K promoter methylation was found to be certainly higher in Stage III/IV (85.71%) compared to Stage I/ II (57.69%) but the difference was not statistically significant (P =0.0673). These results suggest that DAP-K aberrant promoter hypermethylation in Kashmiri population contributes to the process of carcinogenesis in Gastric cancer and is reportedly one of the commonest epigenetic changes in the development of Gastric cancer.

Keywords: gastric cancer, minerals, AAS, hypermethylation, CpG islands, DAP-K gene

Procedia PDF Downloads 493

Authors: Junjun Chen, Yingxiu Li

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The occupational well-being of school principals has played a vital role in the pursuit of individual and school wellness and success. However, principals’ well-being worldwide is under increasing threat because of the challenging and complex nature of their work and growing demands for school standardisation and accountability. Pressure is particularly acute in the post-pandemicfuture as principals attempt to deal with the impact of the pandemic on top of more regular demands. This is particularly true in Hong Kong, as school principals are increasingly wedged between unparalleled political, social, and academic responsibilities. Recognizing the semantic breadth of well-being, scholars have not determined a single, mutually agreeable definition but agreed that the concept of well-being has multiple dimensions across various disciplines. The multidimensional approach promises more precise assessments of the relationships between well-being and other concepts than the ‘affect-only’ approach or other single domains for capturing the essence of principal well-being. The multiple-dimension well-being concept is adopted in this project to understand principal well-being in this study. This study aimed to understand the situation of principal well-being and its influential drivers with a sample of 670 principals from Hong Kong and Mainland China. An online survey was sent to the participants after the breakout of COVID-19 by the researchers. All participants were well informed about the purposes and procedure of the project and the confidentiality of the data prior to filling in the questionnaire. Confirmatory factor analysis and structural equation modelling performed with Mplus were employed to deal with the dataset. The data analysis procedure involved the following three steps. First, the descriptive statistics (e.g., mean and standard deviation) were calculated. Second, confirmatory factor analysis (CFA) was used to trim principal well-being measurement performed with maximum likelihood estimation. Third, structural equation modelling (SEM) was employed to test the influential factors of principal well-being. The results of this study indicated that the overall of principal well-being were above the average mean score. The highest ranking in this study given by the principals was to their psychological and social well-being (M = 5.21). This was followed by spiritual (M = 5.14; SD = .77), cognitive (M = 5.14; SD = .77), emotional (M = 4.96; SD = .79), and physical well-being (M = 3.15; SD = .73). Participants ranked their physical well-being the lowest. Moreover, professional autonomy, supervisor and collegial support, school physical conditions, professional networking, and social media have showed a significant impact on principal well-being. The findings of this study will potentially enhance not only principal well-being, but also the functioning of an individual principal and a school without sacrificing principal well-being for quality education in the process. This will eventually move one step forward for a new future - a wellness society advocated by OECD. Importantly, well-being is an inside job that begins with choosing to have wellness, whilst supports to become a wellness principal are also imperative.

Keywords: well-being, school principals, quantitative, influential factors

Procedia PDF Downloads 58

Authors: Ekemini M. Okon, Reuben C. Okocha, Babatunde T. Adesina, Judith O. Ehigie, Babatunde M. Falana, Boluwape T. Okikiola

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Antimicrobial resistance (AMR) has evolved to become a significant threat to global public health and food safety. The development of AMR in animals has been associated with antimicrobial overuse. In recent years, the number of antimicrobials used in food animals such as fish and poultry has escalated. It, therefore, becomes imperative to understand the patterns of AMR in fish and poultry and map out future directions for better surveillance efforts. This study used the Preferred Reporting Items for Systematic reviews and Meta-Analyses(PRISMA) to assess the trend, patterns, and spatial distribution for AMR research in Egypt, Nigeria, and South Africa. A literature search was conducted through the Scopus and Web of Science databases in which published studies on AMR between 1989 and 2021 were assessed. A total of 172 articles were relevant for this study. The result showed progressive attention on AMR studies in fish and poultry from 2018 to 2021 across the selected countries. The period between 2018 (23 studies) and 2021 (25 studies) showed a significant increase in AMR publications with a peak in 2019 (28 studies). Egypt was the leading exponent of AMR research (43%, n=74) followed by Nigeria (40%, n=69), then South Africa (17%, n=29). AMR studies in fish received relatively little attention across countries. The majority of the AMR studies were on poultry in Egypt (82%, n=61), Nigeria (87%, n=60), and South Africa (83%, n=24). Further, most of the studies were on Escherichia and Salmonella species. Antimicrobials frequently researched were ampicillin, erythromycin, tetracycline, trimethoprim, chloramphenicol, and sulfamethoxazole groups. Multiple drug resistance was prevalent, as demonstrated by antimicrobial resistance patterns. In poultry, Escherichia coli isolates were resistant to cefotaxime, streptomycin, chloramphenicol, enrofloxacin, gentamycin, ciprofloxacin, oxytetracycline, kanamycin, nalidixic acid, tetracycline, trimethoprim/sulphamethoxazole, erythromycin, and ampicillin. Salmonella enterica serovars were resistant to tetracycline, trimethoprim/sulphamethoxazole, cefotaxime, and ampicillin. Staphylococcusaureus showed high-level resistance to streptomycin, kanamycin, erythromycin, cefoxitin, trimethoprim, vancomycin, ampicillin, and tetracycline. Campylobacter isolates were resistant to ceftriaxone, erythromycin, ciprofloxacin, tetracycline, and nalidixic acid at varying degrees. In fish, Enterococcus isolates showed resistance to penicillin, ampicillin, chloramphenicol, vancomycin, and tetracycline but sensitive to ciprofloxacin, erythromycin, and rifampicin. Isolated strains of Vibrio species showed sensitivity to florfenicol and ciprofloxacin, butresistance to trimethoprim/sulphamethoxazole and erythromycin. Isolates of Aeromonas and Pseudomonas species exhibited resistance to ampicillin and amoxicillin. Specifically, Aeromonashydrophila isolates showed sensitivity to cephradine, doxycycline, erythromycin, and florfenicol. However, resistance was also exhibited against augmentinandtetracycline. The findings constitute public and environmental health threats and suggest the need to promote and advance AMR research in other countries, particularly those on the global hotspot for antimicrobial use.

Keywords: antibiotics, antimicrobial resistance, bacteria, environment, public health

Procedia PDF Downloads 165

Authors: Suliman Al-Fayoumi, Sherri Amberg, Huafeng Zhou, Jack W. Singer, James P. Dean

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Pacritinib is an oral kinase inhibitor with specificity for JAK2, FLT3, IRAK1, and CSF1R. In clinical studies, pacritinib was well tolerated with clinical activity in patients with myelofibrosis. The most frequent adverse events (AEs) observed with pacritinib are gastrointestinal (diarrhea, nausea, and vomiting; mostly grade 1-2 in severity) and typically resolve within 2 weeks. A human ADME mass balance study demonstrated that pacritinib is predominantly cleared via hepatic metabolism and biliary excretion (>85% of administered dose). The major hepatic metabolite identified, M1, is not thought to materially contribute to the pharmacological activity of pacritinib. Hepatic diseases are known to impair hepatic blood flow, drug-metabolizing enzymes, and biliary transport systems and may affect drug absorption, disposition, efficacy, and toxicity. This phase 1 study evaluated the pharmacokinetics (PK) and safety of pacritinib and the M1 metabolite in study subjects with mild, moderate, or severe hepatic impairment (HI) and matched healthy subjects with normal liver function to determine if pacritinib dosage adjustments are necessary for patients with varying degrees of hepatic insufficiency. Study participants (aged 18-85 y) were enrolled into 4 groups based on their degree of HI as defined by Child-Pugh Clinical Assessment Score: mild (n=8), moderate (n=8), severe (n=4), and healthy volunteers (n=8) matched for age, BMI, and sex. Individuals with concomitant renal dysfunction or progressive liver disease were excluded. A single 400 mg dose of pacritinib was administered to all participants. Blood samples were obtained for PK evaluation predose and at multiple time points postdose through 168 h. Key PK parameters evaluated included maximum plasma concentration (Cmax), time to Cmax (Tmax), area under the plasma concentration time curve (AUC) from hour zero to last measurable concentration (AUC0-t), AUC extrapolated to infinity (AUC0-∞), and apparent terminal elimination half-life (t1/2). Following treatment, pacritinib was quantifiable for all study participants at 1 h through 168 h postdose. Systemic pacritinib exposure was similar between healthy volunteers and individuals with mild HI. However, there was a significant difference between those with moderate and severe HI and healthy volunteers with respect to peak concentration (Cmax) and plasma exposure (AUC0-t, AUC0-∞). Mean Cmax decreased by 47% and 57% respectively in participants with moderate and severe HI vs matched healthy volunteers. Similarly, mean AUC0-t decreased by 36% and 45% and mean AUC0-∞ decreased by 46% and 48%, respectively in individuals with moderate and severe HI vs healthy volunteers. Mean t1/2 ranged from 51.5 to 74.9 h across all groups. The variability on exposure ranged from 17.8% to 51.8% across all groups. Systemic exposure of M1 was also significantly decreased in study participants with moderate or severe HI vs. healthy participants and individuals with mild HI. These changes were not significantly dissimilar from the inter-patient variability in these parameters observed in healthy volunteers. All AEs were grade 1-2 in severity. Diarrhea and headache were the only AEs reported in >1 participant (n=4 each). Based on these observations, it is unlikely that dosage adjustments would be warranted in patients with mild, moderate, or severe HI treated with pacritinib.

Keywords: pacritinib, myelofibrosis, hepatic impairment, pharmacokinetics

Procedia PDF Downloads 275

Authors: Antonio Pratelli, Lorenzo Brocchini, Reginald Roy Souleyrette

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A rotary is a traffic circle intersection where vehicles entering from branches give priority to circulating flow. Vehicles entering the intersection from converging roads move around the central island and weave out of the circle into their desired exiting branch. This creates merging and diverging conflicts among any entry and its successive exit, i.e., a section. Therefore, rotary capacity models are usually based on the weaving of the different movements in any section of the circle, and the maximum rate of flow value is then related to each weaving section of the rotary. Nevertheless, the single-section capacity value does not lead to the typical performance characteristics of the intersection, such as the entry average delay which is directly linked to its level of service. From another point of view, modern roundabout capacity models are based on the limitation of the flow entering from the single entrance due to the amount of flow circulating in front of the entrance itself. Modern roundabouts capacity models generally lead also to a performance evaluation. This paper aims to incorporate a modern roundabout capacity model into an old rotary capacity method to obtain from the latter the single input capacity and ultimately achieve the related performance indicators. Put simply; the main objective is to calculate the average delay of each single roundabout entrance to apply the most common Highway Capacity Manual, or HCM, criteria. The paper is organized as follows: firstly, the rotary and roundabout capacity models are sketched, and it has made a brief introduction to the model combination technique with some practical instances. The successive section is deserved to summarize the TRRL old rotary capacity model and the most recent HCM-7th modern roundabout capacity model. Then, the two models are combined through an iteration-based algorithm, especially set-up and linked to the concept of roundabout total capacity, i.e., the value reached due to a traffic flow pattern leading to the simultaneous congestion of all roundabout entrances. The solution is the average delay for each entrance of the rotary, by which is estimated its respective level of service. In view of further experimental applications, at this research stage, a collection of existing rotary intersections operating with the priority-to-circle rule has already started, both in the US and in Italy. The rotaries have been selected by direct inspection of aerial photos through a map viewer, namely Google Earth. Each instance has been recorded by location, general urban or rural, and its main geometrical patterns. Finally, conclusion remarks are drawn, and a discussion on some further research developments has opened.

Keywords: mixed methods, old rotary and modern roundabout capacity models, total capacity algorithm, level of service estimation

Procedia PDF Downloads 53

Authors: Łukasz Ambroziak

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Although the impact of the production fragmentation on trade flows has been examined many times since the 1990s, the research was not comprehensive because of the limitations in traditional trade statistics. Early 2010s the complex databases containing world input-output tables (or indicators calculated on their basis) has made available. It increased the possibilities of examining the production sharing in the world. The trade statistic in value-added terms enables us better to estimate trade changes resulted from the internationalisation and globalisation as well as benefits of the countries from international trade. In the literature, there are many research studies on this topic. Unfortunately, trade in value added of the Central and Eastern European Countries (CEECs) has been so far insufficiently studied. Thus, the aim of the paper is to present changes in value added trade of the CEECs (Bulgaria, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia and Slovenia) in the period of 1995-2011. The concept 'trade in value added' or 'value added trade' is defined as the value added of a country which is directly and indirectly embodied in final consumption of another country. The typical question would be: 'How much value added is created in a country due to final consumption in the other countries?' The data will be downloaded from the World Input-Output Database (WIOD). The structure of this paper is as follows. First, theoretical and methodological aspects related to the application of the input-output tables in the trade analysis will be studied. Second, a brief survey of the empirical literature on this topic will be presented. Third, changes in exports and imports in value added of the CEECs will be analysed. A special attention will be paid to the differences in bilateral trade balances using traditional trade statistics (in gross terms) on one side, and value added statistics on the other. Next, in order to identify factors influencing value added exports and value added imports of the CEECs the generalised gravity model, based on panel data, will be used. The dependent variables will be value added exports and imports. The independent variables will be, among others, the level of GDP of trading partners, the level of GDP per capita of trading partners, the differences in GDP per capita, the level of the FDI inward stock, the geographical distance, the existence (or non-existence) of common border, the membership (or not) in preferential trade agreements or in the EU. For comparison, an estimation will also be made based on exports and imports in gross terms. The initial research results show that the gravity model better explained determinants of trade in value added than gross trade (R2 in the former is higher). The independent variables had the same direction of impact both on value added exports/imports and gross exports/imports. Only value of coefficients differs. The most difference concerned geographical distance. It had smaller impact on trade in value added than gross trade.

Keywords: central and eastern European countries, gravity model, input-output tables, trade in value added

Procedia PDF Downloads 221

Authors: Zhao Gao, Eran Edirisinghe

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The production of an accurate sketch of a suspect based on a verbal description obtained from a witness is an essential task for most criminal investigations. The criminal investigation system employs specifically trained professional artists to manually draw a facial image of the suspect according to the descriptions of an eyewitness for subsequent identification. Within the advancement of Deep Learning, Recurrent Neural Networks (RNN) have shown great promise in Natural Language Processing (NLP) tasks. Additionally, Generative Adversarial Networks (GAN) have also proven to be very effective in image generation. In this study, a trained GAN conditioned on textual features such as keywords automatically encoded from a verbal description of a human face using an RNN is used to generate photo-realistic facial images for criminal investigations. The intention of the proposed system is to map corresponding features into text generated from verbal descriptions. With this, it becomes possible to generate many reasonably accurate alternatives to which the witness can use to hopefully identify a suspect from. This reduces subjectivity in decision making both by the eyewitness and the artist while giving an opportunity for the witness to evaluate and reconsider decisions. Furthermore, the proposed approach benefits law enforcement agencies by reducing the time taken to physically draw each potential sketch, thus increasing response times and mitigating potentially malicious human intervention. With publically available 'CelebFaces Attributes Dataset' (CelebA) and additionally providing verbal description as training data, the proposed architecture is able to effectively produce facial structures from given text. Word Embeddings are learnt by applying the RNN architecture in order to perform semantic parsing, the output of which is fed into the GAN for synthesizing photo-realistic images. Rather than the grid search method, a metaheuristic search based on genetic algorithms is applied to evolve the network with the intent of achieving optimal hyperparameters in a fraction the time of a typical brute force approach. With the exception of the ‘CelebA’ training database, further novel test cases are supplied to the network for evaluation. Witness reports detailing criminals from Interpol or other law enforcement agencies are sampled on the network. Using the descriptions provided, samples are generated and compared with the ground truth images of a criminal in order to calculate the similarities. Two factors are used for performance evaluation: The Structural Similarity Index (SSIM) and the Peak Signal-to-Noise Ratio (PSNR). A high percentile output from this performance matrix should attribute to demonstrating the accuracy, in hope of proving that the proposed approach can be an effective tool for law enforcement agencies. The proposed approach to criminal facial image generation has potential to increase the ratio of criminal cases that can be ultimately resolved using eyewitness information gathering.

Keywords: RNN, GAN, NLP, facial composition, criminal investigation

Procedia PDF Downloads 138

Authors: Seyed Hossein Hosseini, Seyed Majid Hashemzadeh

Abstract:

Solar energy is one of the remarkable renewable energy sources that have particular characteristics such as unlimited, no environmental pollution, and free access. Generally, solar energy can be used in thermal and photovoltaic (PV) types. The cost of installation of the PV system is very high. Additionally, due to dependence on environmental situations such as solar radiation and ambient temperature, electrical power generation of this system is unpredictable and without power electronics devices, there is no guarantee to maximum power delivery at the output of this system. Maximum power point tracking (MPPT) should be used to achieve the maximum power of a PV string. MPPT is one of the essential parts of the PV system which without this section, it would be impossible to reach the maximum amount of the PV string power and high losses are caused in the PV system. One of the noticeable challenges in the problem of MPPT is the partial shading conditions (PSC). In PSC, the output photocurrent of the PV module under the shadow is less than the PV string current. The difference between the mentioned currents passes from the module's internal parallel resistance and creates a large negative voltage across shaded modules. This significant negative voltage damages the PV module under the shadow. This condition is called hot-spot phenomenon. An anti-paralleled diode is inserted across the PV module to prevent the happening of this phenomenon. This diode is known as the bypass diode. Due to the performance of the bypass diode under PSC, the P-V curve of the PV string has several peaks. One of the P-V curve peaks that makes the maximum available power is the global peak. Model-based Global MPPT (GMPPT) methods can estimate the optimal point with higher speed than other GMPPT approaches. Centralized, modular, and interleaved DC-DC converter topologies are the significant structures that can be used for GMPPT at a PV string. there are some problems in the centralized structure such as current mismatch losses at PV sting, loss of power of the shaded modules because of bypassing by bypass diodes under PSC, needing to series connection of many PV modules to reach the desired voltage level. In the modular structure, each PV module is connected to a DC-DC converter. In this structure, by increasing the amount of demanded power from the PV string, the number of DC-DC converters that are used at the PV system will increase. As a result, the cost of the modular structure is very high. We can implement the model-based GMPPT through the multi-input interleaved boost DC-DC converter to increase the power extraction from the PV string and reduce hot-spot and current mismatch error in a PV string under different environmental condition and variable load circumstances. The interleaved boost DC-DC converter has many privileges than other mentioned structures, such as high reliability and efficiency, better regulation of DC voltage at DC link, overcome the notable errors such as module's current mismatch and hot spot phenomenon, and power switches voltage stress reduction.

Keywords: solar energy, photovoltaic systems, interleaved boost converter, maximum power point tracking, model-based method, partial shading conditions

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Authors: Hongmei Wang, Ziyun Xiang, Ying liu, Li Yu, Dongsheng Yue

Abstract:

Intro: The COVID-19 (Corona Virus Disease 2019) has greatly changed the global economic, political and financial ecology. The mutation of the coronavirus in the UK in December 2020 has brought new panic to the world. Deep learning was performed on Chest Computed tomography (CT) of COVID-19 and Influenza and describes their characteristics. The predominant features of COVID-19 pneumonia was ground-glass opacification, followed by consolidation. Lesion density: most lesions appear as ground-glass shadows, and some lesions coexist with solid lesions. Lesion distribution: the focus is mainly on the dorsal side of the periphery of the lung, with the lower lobe of the lungs as the focus, and it is often close to the pleura. Other features it has are grid-like shadows in ground glass lesions, thickening signs of diseased vessels, air bronchi signs and halo signs. The severe disease involves whole bilateral lungs, showing white lung signs, air bronchograms can be seen, and there can be a small amount of pleural effusion in the bilateral chest cavity. At the same time, this year's flu season could be near its peak after surging throughout the United States for months. Chest CT for Influenza infection is characterized by focal ground glass shadows in the lungs, with or without patchy consolidation, and bronchiole air bronchograms are visible in the concentration. There are patchy ground-glass shadows, consolidation, air bronchus signs, mosaic lung perfusion, etc. The lesions are mostly fused, which is prominent near the hilar and two lungs. Grid-like shadows and small patchy ground-glass shadows are visible. Deep neural networks have great potential in image analysis and diagnosis that traditional machine learning algorithms do not. Method: Aiming at the two major infectious diseases COVID-19 and influenza, which are currently circulating in the world, the chest CT of patients with two infectious diseases is classified and diagnosed using deep learning algorithms. The residual network is proposed to solve the problem of network degradation when there are too many hidden layers in a deep neural network (DNN). The proposed deep residual system (ResNet) is a milestone in the history of the Convolutional neural network (CNN) images, which solves the problem of difficult training of deep CNN models. Many visual tasks can get excellent results through fine-tuning ResNet. The pre-trained convolutional neural network ResNet is introduced as a feature extractor, eliminating the need to design complex models and time-consuming training. Fastai is based on Pytorch, packaging best practices for in-depth learning strategies, and finding the best way to handle diagnoses issues. Based on the one-cycle approach of the Fastai algorithm, the classification diagnosis of lung CT for two infectious diseases is realized, and a higher recognition rate is obtained. Results: A deep learning model was developed to efficiently identify the differences between COVID-19 and influenza using chest CT.

Keywords: COVID-19, Fastai, influenza, transfer network

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Authors: Neha Batra Bali, Monika Tomar, Vinay Gupta

Abstract:

A reagentless biosensor for detection of urea based on ZnO-CuO composite thin film is presented in following work. Biosensors have immense potential for varied applications ranging from environmental to clinical testing, health care, and cell analysis. Immense growth in the field of biosensors is due to the huge requirement in today’s world to develop techniques which are both cost effective and accurate for prevention of disease manifestation. The human body comprises of numerous biomolecules which in their optimum levels are essential for functioning. However mismanaged levels of these biomolecules result in major health issues. Urea is one of the key biomolecules of interest. Its estimation is of paramount significance not only for healthcare sector but also from environmental perspectives. If level of urea in human blood/serum is abnormal, i.e., above or below physiological range (15-40mg/dl)), it may lead to diseases like renal failure, hepatic failure, nephritic syndrome, cachexia, urinary tract obstruction, dehydration, shock, burns and gastrointestinal, etc. Various metal nanoparticles, conducting polymer, metal oxide thin films, etc. have been exploited to act as matrix to immobilize urease to fabricate urea biosensor. Amongst them, Zinc Oxide (ZnO), a semiconductor metal oxide with a wide band gap is of immense interest as an efficient matrix in biosensors by virtue of its natural abundance, biocompatibility, good electron communication feature and high isoelectric point (9.5). In spite of being such an attractive candidate, ZnO does not possess a redox couple of its own which necessitates the use of electroactive mediators for electron transfer between the enzyme and the electrode, thereby causing hindrance in realization of integrated and implantable biosensor. In the present work, an effort has been made to fabricate a matrix based on ZnO-CuO composite prepared by pulsed laser deposition (PLD) technique in order to incorporate redox properties in ZnO matrix and to utilize the same for reagentless biosensing applications. The prepared bioelectrode Urs/(ZnO-CuO)/ITO/glass exhibits high sensitivity (70µAmM⁻¹cm⁻²) for detection of urea (5-200 mg/dl) with high stability (shelf life ˃ 10 weeks) and good selectivity (interference ˂ 4%). The enhanced sensing response obtained for composite matrix is attributed to the efficient electron exchange between ZnO-CuO matrix and immobilized enzymes, and subsequently fast transfer of generated electrons to the electrode via matrix. The response is encouraging for fabricating reagentless urea biosensor based on ZnO-CuO matrix.

Keywords: biosensor, reagentless, urea, ZnO-CuO composite

Procedia PDF Downloads 269

Authors: Richard Sogah

Abstract:

The significance of transport infrastructure investments for economic growth and development has been central to the World Bank’s strategy for poverty reduction. Among the conventional surface transport infrastructures, road infrastructure is significant in facilitating the movement of human capital goods and services. When transport projects (i.e., roads, super-highways) are implemented, they come along with some negative social values (costs), such as increased noise and air pollution for local residents living near these facilities, displaced individuals, etc. However, these projects also facilitate better utilization of existing capital stock and generate other observable benefits that can be easily quantified. For example, the improvement or construction of roads creates employment, stimulates revenue generation (toll), reduces vehicle operating costs and accidents, increases accessibility, trade expansion, safety improvement, etc. Aside from these benefits, travel time savings (TTSs) which are the major economic benefits of urban and inter-urban transport projects and therefore integral in the economic assessment of transport projects, are often overlooked and omitted when estimating the benefits of transport projects, especially in developing countries. The absence of current and reliable domestic travel data and the inability of replicated models from the developed world to capture the actual value of travel time savings due to the large unemployment, underemployment, and other labor-induced distortions has contributed to the failure to assign value to travel time savings when estimating the benefits of transport schemes in developing countries. This omission of the value of travel time savings from the benefits of transport projects in developing countries poses problems for investors and stakeholders to either accept or dismiss projects based on schemes that favor reduced vehicular operating costs and other parameters rather than those that ease congestion, increase average speed, facilitate walking and handloading, and thus save travel time. Given the complex reality in the estimation of the value of travel time savings and the presence of widespread informal labour activities in Sub-Saharan Africa, we construct a “nationally ranked distribution of time values” and estimate the value of travel time savings based on the area beneath the distribution. Compared with other approaches, our method captures both formal sector workers and individuals/people who work outside the formal sector and hence changes in their time allocation occur in the informal economy and household production activities. The dataset for the estimations is sourced from the World Bank, the International Labour Organization, etc.

Keywords: road infrastructure, transport projects, travel time savings, congestion, Sub-Sahara Africa

Procedia PDF Downloads 79

Authors: Chao-Yang Huang, Rwey-Hua Cherng, Chung-Lin Fu, Yuan-Lung Lo

Abstract:

Solar energy is one of the replaceable choices to reduce the CO2 emission produced by conventional power plants in the modern society. As an island which is frequently visited by strong typhoons and earthquakes, it is an urgent issue for Taiwan to make an effort in revising the local regulations to strengthen the safety design of photovoltaic systems. Currently, the Taiwanese code for wind resistant design of structures does not have a clear explanation on photovoltaic systems, especially when the systems are arranged in arrayed format. Furthermore, when the arrayed photovoltaic system is mounted on the rooftop, the approaching flow is significantly altered by the building and led to different pressure pattern in the different area of the photovoltaic system. In this study, L-shape arrayed photovoltaic system is mounted on the ground of the wind tunnel and then mounted on the building rooftop. The system is consisted of 60 PV models. Each panel model is equivalent to a full size of 3.0 m in depth and 10.0 m in length. Six pressure taps are installed on the upper surface of the panel model and the other six are on the bottom surface to measure the net pressures. Wind attack angle is varied from 0° to 360° in a 10° interval for the worst concern due to wind direction. The sampling rate of the pressure scanning system is set as high enough to precisely estimate the peak pressure and at least 20 samples are recorded for good ensemble average stability. Each sample is equivalent to 10-minute time length in full scale. All the scale factors, including timescale, length scale, and velocity scale, are properly verified by similarity rules in low wind speed wind tunnel environment. The purpose of L-shape arrayed system is for the understanding the pressure characteristics at the corner area. Extreme value analysis is applied to obtain the design pressure coefficient for each net pressure. The commonly utilized Cook-and-Mayne coefficient, 78%, is set to the target non-exceedance probability for design pressure coefficients under Gumbel distribution. Best linear unbiased estimator method is utilized for the Gumbel parameter identification. Careful time moving averaging method is also concerned in data processing. Results show that when the arrayed photovoltaic system is mounted on the ground, the first row of the panels reveals stronger positive pressure than that mounted on the rooftop. Due to the flow separation occurring at the building edge, the first row of the panels on the rooftop is most in negative pressures; the last row, on the other hand, shows positive pressures because of the flow reattachment. Different areas also have different pressure patterns, which corresponds well to the regulations in ASCE7-16 describing the area division for design values. Several minor observations are found according to parametric studies, such as rooftop edge effect, parapet effect, building aspect effect, row interval effect, and so on. General comments are then made for the proposal of regulation revision in Taiwanese code.

Keywords: aerodynamic force coefficient, ground-mounted, roof-mounted, wind tunnel test, photovoltaic

Procedia PDF Downloads 105

Authors: Ewa Szarek-Gwiazda, Agata Z. Wojtal, Agnieszka Pociecha, Andrzej Kownacki, Dariusz Ciszewski

Abstract:

Mining of metal ores is one of the largest sources of heavy metals, which deteriorate aquatic systems. The response of organisms to environmental changes can be well recorded in sediments of the affected water bodies and may be reconstructed basing on analyses of organisms remains. The present study aimed at response of diatoms, Cladocera and Chronomidae communities to impact of Zn-Pb mine water discharge recorded in sediment cores of small subsidence ponds on the Chechło River floodplain (Silesia–Krakow Region, southern Poland). We hypothesis various response of the above groups to high metal concentrations (Cd, Pb, Zn, and Cu). The investigated ponds were formed either during the peak of the ore exploitation (DOWN) or after mining cessation (UP). Currently, the concentrations of dissolved metals (in µg g-1) in water reached up to 0.53 for Cd, 7.3 for Pb and up to 47.1 for Zn. All the sediment cores from subsidence ponds were heavily polluted with Cd 6.7–612 μg g−1, Pb 0.1–10.2 mg g−1, and Zn 0.5–23.1 mg g−1. Core sediments varied also in respect to pH 5.8-7.1 and concentrations of organic matter (5.7-39.8%). The impact of high metal concentrations was expressed by the occurrence of metal tolerant taxa like diatoms – Nitzschia amphibia, Sellaphora nigri, and Surirella brebisonii var. kuetzingii; Cladocera – Chydorus sphaericus (dominated in cores from all ponds), and Chironomidae – Chironomus and Cricotopus especially in the DOWN ponds. Statistical analysis exhibited a negative impact of metals on some taxa of diatoms and Cladocera, but only on Polypedilum sp. from Chironomidae. Abundance of such diatoms like Gomphonema utae, Staurosirella pinnata, Eunotia bilunaris, and Cladocera like Alona, Chydorus, Graptoleberis, and Pleuroxus decreased with increasing Pb concentration. However, the occurrence or dominance of more sensitive species of diatoms and Cladocera indicates their adaptation to higher metal loads, which was facilitated by neutral pH and slightly alkaline waters. Diatom assemblages were generally resistant to Zn, Pb, Cu, and Cd pollution as indicated by their large similarity to populations from non-contaminated waters. Comparison with reference objects clearly indicates the dominance of Achnanthidium minutissimum, Staurosira venter, and Fragilaria gracilis in very diverse assemblages of unpolluted waters. The distribution of the Cladocera and Chironomidae taxa depended on the habitat type. The DOWN ponds with stagnant water and overgrown with macrophytes were more suitable for Cladocerans (14 taxa, higher diversity) than the UP ponds with river water flowing through their centre and with a small share of macrophytes (8 taxa). The Chironominae, mainly Chironomus and Microspectra, were abundant in cores from the UP ponds with muddy bottom. Inversely, the density of Orthocladiinae, especially genus Cricotopus, were related to the organic matter content and dominated in cores from the DOWN ponds. The presence of diatoms like Nitzschia amphibia, Sellaphora nigri, and Surirella brebisonii var. kuetzingii, Cladocerans Bosmina longirostris, Chydorus sphaericus, littoral cladocerans, Alona affinis, A. rectangularis as well as Chironomidae Chironomus sp. (UP ponds) and Psecrotanypus varius (DOWN ponds) indicate the influence of the water trophy on their distribution.

Keywords: Chironomidae, cladocerans, diatoms, metals, Zn-Pb mine, sediment cores, subsidence ponds

Procedia PDF Downloads 36