Search results for: sequential linear programming

Authors: Mamta Rajbhar, Sanjay K. Mohanty

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India's progress in achieving replacement level of fertility is largely contingent on fertility reduction in the state of Uttar Pradesh as it accounts 17% of India's population with a low level of development. Though the TFR in the state has declined from 5.1 in 1991 to 3.4 by 2011, it conceals large differences in fertility level across districts. Using data from multiple sources this paper tests the hypothesis that the improvement in human development significantly reduces the fertility levels in districts of Uttar Pradesh. The unit of analyses is district, and fertility estimates are derived using the reverse survival method(RSM) while human development indices(HDI) are are estimated using uniform methodology adopted by UNDP for three period. The correlation and linear regression models are used to examine the relationship of fertility change and human development indices across districts. Result show the large variation and significant change in fertility level among the districts of Uttar Pradesh. During 1991-2011, eight districts had experienced a decline of TFR by 10-20%, 30 districts by 20-30% and 32 districts had experienced decline of more than 30%. On human development aspect, 17 districts recorded increase of more than 0.170 in HDI, 18 districts in the range of 0.150-0.170, 29 districts between 0.125-0.150 and six districts in the range of 0.1-0.125 during 1991-2011. Study shows significant negative relationship between HDI and TFR. HDI alone explains 70% variation in TFR. Also, the regression coefficient of TFR and HDI has become stronger over time; from -0.524 in 1991, -0.7477 by 2001 and -0.7181 by 2010. The regression analyses indicate that 0.1 point increase in HDI value will lead to 0.78 point decline in TFR. The HDI alone explains 70% variation in TFR. Improving the HDI will certainly reduce the fertility level in the districts.

Keywords: Fertility, HDI, Uttar Pradesh

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Authors: Majid Farsadrooh, Najmeh Sabbaghi, Seyed Mohammad Mostashari, Abolhasan Moradi

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Phenolic compounds are chief environmental contaminants on account of their hazardous and toxic nature on human health. The preparation of sensitive and potent chemosensors to monitor emerging pollution in water and effluent samples has received great consideration. A novel and versatile nanocomposite sensor based on poly pyrogallol is presented for the first time in this study, and its electrochemical behavior for simultaneous detection of hydroquinone (HQ), catechol (CT), and resorcinol (RS) in the presence of nitrite is evaluated. The physicochemical characteristics of the fabricated nanocomposite were investigated by emission-scanning electron microscopy (FE-SEM), energy-dispersive X-ray spectroscopy (EDS), and Brunauer-Emmett-Teller (BET). The electrochemical response of the proposed sensor to the detection of HQ, CT, RS, and nitrite is studied using cyclic voltammetry (CV), chronoamperometry (CA), differential pulse voltammetry (DPV), and electrochemical impedance spectroscopy (EIS). The kinetic characterization of the prepared sensor showed that both adsorption and diffusion processes can control reactions at the electrode. In the optimized conditions, the new chemosensor provides a wide linear range of 0.5-236.3, 0.8-236.3, 0.9-236.3, and 1.2-236.3 μM with a low limit of detection of 21.1, 51.4, 98.9, and 110.8 nM (S/N = 3) for HQ, CT and RS, and nitrite, respectively. Remarkably, the electrochemical sensor has outstanding selectivity, repeatability, and stability and is successfully employed for the detection of RS, CT, HQ, and nitrite in real water samples with the recovery of 96.2%–102.4%, 97.8%-102.6%, 98.0%–102.4% and 98.4%–103.2% for RS, CT, HQ, and nitrite, respectively. These outcomes illustrate that poly pyrogallol is a promising candidate for effective electrochemical detection of dihydroxybenzene isomers in the presence of nitrite.

Keywords: electrochemical sensor, poly pyrogallol, phenolic compounds, simultaneous determination

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Authors: Rahel Birhane Eshetu

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This research investigates the complex landscape of project management practices and operational challenges in conflict-affected areas, with a specific focus on Kewot Woreda in the North Shewa Zone of the Amhara region in Ethiopia. The study aims to identify essential project management methodologies, the significant operational hurdles faced, and the adaptive strategies employed by project managers in these challenging environments. Utilizing a mixed-methods approach, the research combines qualitative and quantitative data collection. Initially, a comprehensive literature review was conducted to establish a theoretical framework. This was followed by the administration of questionnaires to gather empirical data, which was then analyzed using statistical software. This sequential approach ensures a robust understanding of the context and challenges faced by project managers. The findings reveal that project managers in conflict zones encounter a range of escalating challenges. Initially, they must contend with immediate security threats and the presence of displaced populations, which significantly disrupt project initiation and execution. As projects progress, additional challenges arise, including limited access to essential resources and environmental disruptions such as natural disasters. These factors exacerbate the operational difficulties that project managers must navigate. In response to these challenges, the study highlights the necessity for project managers to implement formal project plans while simultaneously adopting adaptive strategies that evolve over time. Key adaptive strategies identified include flexible risk management frameworks, change management practices, and enhanced stakeholder engagement approaches. These strategies are crucial for maintaining project momentum and ensuring that objectives are met despite the unpredictable nature of conflict environments. The research emphasizes that structured scope management, clear documentation, and thorough requirements analysis are vital components for effectively navigating the complexities inherent in conflict-affected regions. However, the ongoing threats and logistical barriers necessitate a continuous adjustment to project management methodologies. This adaptability is not only essential for the immediate success of projects but also for fostering long-term resilience within the community. Concluding, the study offers actionable recommendations aimed at improving project management practices in conflict zones. These include the adoption of adaptive frameworks specifically tailored to the unique conditions of conflict environments and targeted training for project managers. Such training should focus on equipping managers with the skills to better address the dynamic challenges presented by conflict situations. The insights gained from this research contribute significantly to the broader field of project management, providing a practical guide for practitioners operating in high-risk areas. By emphasizing sustainable and resilient project outcomes, this study underscores the importance of adaptive management strategies in ensuring the success of projects in conflict-affected regions. The findings serve not only to enhance the understanding of project management practices in Kewot Woreda but also to inform future research and practice in similar contexts, ultimately aiming to promote stability and development in areas beset by conflict.

Keywords: project management practices, operational challenges, conflict zones, adaptive strategies

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Authors: Anton S. Perin, Vladimir M. Shandarov

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Compensation for the nonlinear diffraction of narrow laser beams with wavelength of 532 and the formation of photonic waveguides and waveguide circuits due to the contribution of pyroelectric effect to the nonlinear response of lithium niobate crystal have been experimentally demonstrated. Complete compensation for the linear and nonlinear diffraction broadening of light beams is obtained upon uniform heating of an undoped sample from room temperature to 55 degrees Celsius. An analysis of the light-field distribution patterns and the corresponding intensity distribution profiles allowed us to estimate the spacing for the channel waveguides. The observed behavior of bright soliton beams may be caused by their coherent interaction, which manifests itself in repulsion for anti-phase light fields and in attraction for in-phase light fields. The experimental results of this study showed a fundamental possibility of forming optically complex waveguide structures in lithium niobate crystals with pyroelectric mechanism of nonlinear response. The topology of these structures is determined by the light field distribution on the input face of crystalline sample. The optical induction of channel waveguide elements by interacting spatial solitons makes it possible to design optical systems with a more complex topology and a possibility of their dynamic reconfiguration.

Keywords: self-action, soliton, lithium niobate, piroliton, photorefractive effect, pyroelectric effect

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Authors: S. K. Ashiquer Rahman

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the paper concentrations on the importance of hourly compensation, emphasizing the significance of the unemployment rate. There are the two most important factors of a nation these are its unemployment rate and hourly compensation. These are not merely statistics but they have profound effects on individual, families, and the economy. They are inversely related to one another. When we consider the unemployment rate that will probably decline as hourly compensations in manufacturing rise. But when we reduced the unemployment rates and increased job prospects could result from higher compensation. That’s why, the increased hourly compensation in the manufacturing sector that could have a favorable effect on job changing issues. Moreover, the relationship between hourly compensation and unemployment is complex and influenced by broader economic factors. In this paper, we use panel data regression models to evaluate the expected link between hourly compensation and unemployment rate in order to determine the effect of hourly compensation on unemployment rate. We estimate the fixed effects model, evaluate the error components, and determine which model (the FEM or ECM) is better by pooling all 60 observations. We then analysis and review the data by comparing 3 several countries (United States, Canada and the United Kingdom) using panel data regression models. Finally, we provide result, analysis and a summary of the extensive research on how the hourly compensation effects on the unemployment rate. Additionally, this paper offers relevant and useful informational to help the government and academic community use an econometrics and social approach to lessen on the effect of the hourly compensation on Unemployment rate to eliminate the problem.

Keywords: hourly compensation, Unemployment rate, panel data regression models, dummy variables, random effects model, fixed effects model, the linear regression model

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Authors: Sepehr Lajevardi Esfahani, Shohre Rouhani, Zahra Ranjbar

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Graphene has gained much attention owing to its unique optical and electrical properties. Charge carriers in graphene sheets (GS) carry out a linear dispersion relation near the Fermi energy and behave as massless Dirac fermions resulting in unusual attributes such as the quantum Hall effect and ambipolar electric field effect. It also exhibits nondispersive transport characteristics with an extremely high electron mobility (15000 cm²/(Vs)) at room temperature. Recently, several progresses have been achieved in the fabrication of single- or multilayer GS for functional device applications in the fields of optoelectronic such as field-effect transistors ultrasensitive sensors and organic photovoltaic cells. In addition to device applications, graphene also can serve as reinforcement to enhance mechanical, thermal, or electrical properties of composite materials. Electrophoretic deposition (EPD) is an attractive method for development of various coatings and films. It readily applied to any powdered solid that forms a stable suspension. The deposition parameters were controlled in various thicknesses. In this study, the graphene electrodeposition conditions were optimized. The results were obtained from SEM, Ohm resistance measuring technique and AFM characteristic tests. The minimum sheet resistance of electrodeposited reduced graphene oxide layers is achieved at conditions of 2 V in 10 s and it is annealed at 200 °C for 1 minute.

Keywords: electrophoretic deposition (EPD), graphene oxide (GO), electrical conductivity, electro-optical devices

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Authors: Sam S. Hashemi

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The breakage of bonding between sand particles and their dislodgment from the borehole wall are among the main factors resulting in a borehole failure in poorly cemented granular formations. The grain debonding usually precedes the borehole failure and it can be considered as a sign that the onset of the borehole collapse is imminent. Detecting the bonding breakage point and introducing an appropriate failure criterion will play an important role in borehole stability analysis. To study the influence of different factors on the initiation of sand bonding breakage at the borehole wall, a series of laboratory tests was designed and conducted on poorly cemented sand samples. The total absorbed strain energy per volume of material up to the point of the observed particle debonding was computed. The results indicated that the particle bonding breakage point at the borehole wall was reached both before and after the peak strength of the thick-walled hollow cylinder specimens depending on the stress path and cement content. Three different cement contents and two borehole sizes were investigated to study the influence of the bonding strength and scale on the particle dislodgment. Test results showed that the stress path has a significant influence on the onset of the sand bonding breakage. It was shown that for various stress paths, there is a near linear relationship between the absorbed energy and the normal effective mean stress.

Keywords: borehole stability, experimental studies, poorly cemented sands, total absorbed strain energy

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Authors: Bahram Asghari Aghdam, Ali Mahjoub

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The purpose of this study is to evaluate the effect of emotional intelligence on the motivation and performance of East Azarbaijan the Red Crescent staff. In this study, EI is determined as the independent variable component of self awareness, self management, social awareness, and relations management, motivation and performance as dependent variables. The research method is descriptive-survey. In this study, simple random sampling method is used and research sample consists of 130 East Azarbaijan the Red Crescent staff that uses Cochran's formula 100 of them were selected and questionnaires were filled by them. Three types of questionnaires were used in this study for emotional intelligence, consisting of the Bradbury Travis and Jane Greaves standard questionnaire; and for motivation and performance a questionnaire is regulated by the researcher with help of professionals and experts in this field that consists of 33 questions about the motivation and 15 questions about performance and content validity were used to obtain the necessary credit. Reliability by using the Cronbach's alpha coefficient /948 was approved. Also, in this study to test the hypothesis of the Spearman correlation coefficient and linear regressions and determine fitness of variables' of structural equation modeling is used. The results show that emotional intelligence with coefficient /865, motivation and performance of in East Azerbaijan the Red Crescent employees has a positive effect. Based on Friedman Test ranking the most influence in motivation and performance of staff in respondents' opinion is in order of self-awareness, relations management, social awareness and self-management.

Keywords: emotional intelligence, self-awareness, self-management, social awareness, relations management, motivation, performance

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Authors: Forrest Kaatz, Adhemar Bultheel

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We use an informational statistical mechanics approach to study the catalytic thermodynamics of platinum and palladium cuboctahedral nanoclusters. Nanoclusters and their adatoms are viewed as chemical graphs with a nearest neighbor adjacency matrix. We use the Morse potential to determine bond energies between cluster atoms in a coordination type calculation. We use adsorbate energies calculated from density functional theory (DFT) to study the adatom effects on the thermodynamic quantities, which are derived from a Hamiltonian. Oxygen radical and molecular adsorbates are studied on platinum clusters and hydrogen on palladium clusters. We calculate the entropy, free energy, and total energy as the coverage of adsorbates increases from bridge and hollow sites on the surface. Thermodynamic behavior versus adatom coverage is related to the structural distribution of adatoms on the nanocluster surfaces. The thermodynamic functions are characterized using a simple adsorption model, with linear trends as the coverage of adatoms increases. The data exhibits size effects for the measured thermodynamic properties with cluster diameters between 2 and 5 nm. Entropy and enthalpy calculations of Pt-O2 compare well with previous theoretical data for Pt(111)-O2, and our Pd-H results show similar trends as experimental measurements for Pd-H2 nanoclusters. Our methods are general and may be applied to wide variety of nanocluster adsorbate systems.

Keywords: catalytic thermodynamics, palladium nanocluster absorbates, platinum nanocluster absorbates, statistical mechanics

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Authors: Salah Guettala, Nesreddine Djafarhenni, Akram Khelaifia, Rachid Chebili

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This study assesses the impact of infill walls' layout in both plan and elevation on the seismic behavior of a 3D reinforced concrete structure situated in a high seismic zone. A pushover analysis is conducted to evaluate the structure's seismic performance with various infill wall layouts, considering capacity curves, absorbed energy, inter-story drift, and performance levels. Additionally, torsional effects on the structure are examined through linear dynamic analysis. Fiber-section-based macro-modeling is utilized to simulate the behavior of infill walls. The findings indicate that the presence of infill walls enhances lateral stiffness and alters structural behavior. Moreover, the study highlights the importance of considering the effects of infill wall layout, as non-uniform layouts can degrade building performance post-earthquake, increasing inter-story drift and risk of damage or collapse. To mitigate such risks, buildings should adopt a uniform infill wall layout. Furthermore, asymmetrical placement of masonry infill walls introduces additional torsional forces, particularly when there's a lack of such walls on the first story, potentially leading to irregular stiffness and soft-story phenomena.

Keywords: RC structures, infll walls’ layout, pushover analysis, macro-model, fiber plastic hinge, torsion

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Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: batch bulk methyl methacrylate polymerization, adaptive sampling, machine learning, large margin nearest neighbor regression

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Authors: Jelena S. Kiurski, Vesna S. Kecić, Snežana M. Aksentijević

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The identification and evaluation of organic and inorganic pollutants were performed in a flexographic facility in Novi Sad, Serbia. Air samples were collected and analyzed in situ, during 4-hours working time at five sampling points by the mobile gas chromatograph and ozonometer at the printing of collagen casing. Experimental results showed that the concentrations of isopropyl alcohol, acetone, total volatile organic compounds and ozone varied during the sampling times. The highest average concentrations of 94.80 ppm and 102.57 ppm were achieved at 200 minutes from starting the production for isopropyl alcohol and total volatile organic compounds, respectively. The mutual dependences between target hazardous and microclimate parameters were confirmed using a multiple linear regression model with software package STATISTICA 10. Obtained multiple coefficients of determination in the case of ozone and acetone (0.507 and 0.589) with microclimate parameters indicated a moderate correlation between the observed variables. However, a strong positive correlation was obtained for isopropyl alcohol and total volatile organic compounds (0.760 and 0.852) with microclimate parameters. Higher values of parameter F than F_critical for all examined dependences indicated the existence of statistically significant difference between the concentration levels of target pollutants and microclimates parameters. Given that, the microclimate parameters significantly affect the emission of investigated gases and the application of eco-friendly materials in production process present a necessity.

Keywords: flexographic printing, indoor air, multiple regression analysis, pollution emission

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Authors: Naheem Olakunle Adesina

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The memristor is considered as one of the promising candidates for mamoelectronic engineering and applications. Owing to its high compatibility with CMOS, nanoscale size, and low power consumption, memristor has been employed in the design of commonly used circuits such as phase-locked loop (PLL). In this paper, we designed a memristor-based loop filter (LF) together with other components of PLL. Following this, we evaluated the noise-rejection feature of loop filter by comparing the noise levels of input and output signals of the filter. Our SPICE simulation results showed that memristor behaves like a linear resistor at high frequencies. The result also showed that loop filter blocks the high-frequency components from phase frequency detector so as to provide a stable control voltage to the voltage controlled oscillator (VCO). In addition, we examined the effects of temperature on the performance of the designed phase locked loop circuit. A critical temperature, where there is frequency drift of VCO as a result of variations in control voltage, is identified. In conclusion, the memristor is a suitable choice for nanoelectronic systems owing to a small area, low power consumption, dense nature, high switching speed, and endurance. The proposed memristor-based loop filter, together with other components of the phase locked loop, can be designed using memristive emulator and EDA tools in current CMOS technology and simulated.

Keywords: Fast Fourier Transform, hysteresis curve, loop filter, memristor, noise, phase locked loop, voltage controlled oscillator

Procedia PDF Downloads 186

Authors: Anon Paserakung, Chaloemphon Muangyen, Suban Foiklang, Yanin Opatpatanakit

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Improving nutritive values and digestibility of maize stover is an alternative way to increase their utilization in ruminant and reduce air pollution from open burning of maize stover in the northern Thailand. The present study, 2x3 factorial arrangements in completely randomized design was conducted to investigate the effect of maize stover components (whole and upper stover; cut above 5th node). Urea treatment at levels 0, 3, and 6% DM on dry matter digestibility and fermentation kinetics of maize stover using in vitro gas production. After 21 days of urea treatment, results illustrated that there was no interaction between maize stover components and urea treatment on 48h in vitro dry matter digestibility (IVDMD). IVDMD was unaffected by maize stover components (P > 0.05), average IVDMD was 55%. However, using whole maize stover gave higher cumulative gas and gas kinetic parameters than those of upper stover (P<0.05). Treating maize stover by ensiling with urea resulted in a significant linear increase in IVDMD (P<0.05). IVDMD increased from 42.6% to 53.9% when increased urea concentration from 0 to 3% and maximum IVDMD (65.1%) was observed when maize stover was ensiled with 6% urea. Maize stover treated with urea at levels of 0, 3, and 6% linearly increased cumulative gas production at 96h (31.1 vs 50.5 and 59.1 ml, respectively) and all gas kinetic parameters excepted the gas production from the immediately soluble fraction (P<0.50). The results indicate that maize stover treated with 6% urea enhance in vitro dry matter digestibility and fermentation kinetics. This study provides a practical approach to increasing utilization of maize stover in feeding ruminant animals.

Keywords: maize stover, urea treatment, ruminant feed, gas production

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Authors: Eunhye Cho, Hyuk-Hoon Kim, Sieun Lee, Minjung Kathy Chae

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Introduction: I-gel is a commonly used supraglottic advanced airway device in prehospital out-of-hospital cardiac arrest (OHCA) allowing for minimal interruption of continuous chest compression. However, previous studies have shown that prehospital supraglottic airway had inferior neurologic outcomes and survival compared to no advanced prehospital airway with conventional bag mask ventilation. We hypothesize that continuous compression with i-gel as an advanced airway may cause insufficient ventilation compared to 30:2 chest compression with conventional BVM. Therefore, we investigated the ventilation efficacy of i-gel with the initial arterial blood gas analysis in OHCA patients visiting our ER. Material and Method: Demographics, arrest parameters including i-gel insertion, initial arterial blood gas analysis was retrospectively analysed for 119 transported OHCA patients that visited our ER. Linear regression was done to investigate the association with i-gel insertion and initial pCO2 as a surrogate of prehospital ventilation. Result: A total of 52 patients were analysed for the study. Of the patients who visited the ER during OHCA, 24 patients had i-gel insertion and 28 patients had BVM as airway management in the prehospital phase. Prehospital i-gel insertion was associated with the initial pCO2 level (B coefficient 29.9, SE 10.1, p<0.01) after adjusting for bystander CPR, cardiogenic cause of arrest, EMS call to arrival. Conclusion: Despite many limitations to the study, prehospital insertion of i-gel was associated with high initial pCO2 values in OHCA patients visiting our ER, possibly indicating insufficient ventilation with prehospital i-gel as an advanced airway and continuous chest compressions.

Keywords: arrest, I-gel, prehospital, ventilation

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Authors: Selamawit Dires, Solomon Tesfamariam, Thomas Tannert

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Modern earthquake engineering and design encompass performance-based design philosophy. The main objective in performance-based design is to achieve a system performing precisely to meet the design objectives so to reduce unintended seismic risks and associated losses. Energy-based earthquake-resistant design is one of the design methodologies that can be implemented in performance-based earthquake engineering. In energy-based design, the seismic demand is usually described as the ratio of the hysteretic to input energy. Once the hysteretic energy is known as a percentage of the input energy, it is distributed among energy-dissipating components of a structure. The hysteretic to input energy ratio is highly dependent on the inherent damping of a structural system. In numerical analysis, damping can be modeled as stiffness-proportional, mass-proportional, or a linear combination of stiffness and mass. In this study, the effect of mathematical modeling of damping on the estimation of seismic energy demands is investigated by considering elastic-perfectly-plastic single-degree-of-freedom systems representing short to long period structures. Furthermore, the seismicity of Vancouver, Canada, is used in the nonlinear time history analysis. According to the preliminary results, the input energy demand is not sensitive to the type of damping models deployed. Hence, consistent results are achieved regardless of the damping models utilized in the numerical analyses. On the other hand, the hysteretic to input energy ratios vary significantly for the different damping models.

Keywords: damping, energy-based seismic design, hysteretic energy, input energy

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Authors: Yan-Wen Wang, Chu-Yang Chou, Jen-Cheng Wang, Min-Sheng Liao, Hsuan-Hsiang Hsu, Cheng-Ying Chou, Chen-Kang Huang, Kun-Chang Kuo, Joe-Air Jiang

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Performance-related parameters of high concentration photovoltaic (HCPV) modules (e.g. current and voltage) are required when estimating the maximum power point using numerical and approximation methods. The maximum power point on the characteristic curve for a photovoltaic module varies when temperature or solar radiation is different. It is also difficult to estimate the output performance and maximum power point (MPP) due to the special characteristics of HCPV modules. Based on the p-n junction semiconductor theory, a brand new and simple method is presented in this study to directly evaluate the MPP of HCPV modules. The MPP of HCPV modules can be determined from an irradiated I-V characteristic curve, because there is a non-linear relationship between the temperature of a solar cell and solar radiation. Numerical simulations and field tests are conducted to examine the characteristics of HCPV modules during maximum output power tracking. The performance of the presented method is evaluated by examining the dependence of temperature and irradiation intensity on the MPP characteristics of HCPV modules. These results show that the presented method allows HCPV modules to achieve their maximum power and perform power tracking under various operation conditions. A 0.1% error is found between the estimated and the real maximum power point.

Keywords: energy performance, high concentrated photovoltaic, maximum power point, p-n junction semiconductor

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Authors: Chiyoung Kim, Jaegeol Yim

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Bus service is often either main or the only public transportation available in cities. In metropolitan areas, both subways and buses are available whereas in the medium sized cities buses are usually the only type of public transportation available. Bus Information Systems (BIS) provide current locations of running buses, efficient routes to travel from one place to another, points of interests around a given bus stop, a series of bus stops consisting of a given bus route, and so on to users. Thanks to BIS, people do not have to waste time at a bus stop waiting for a bus because BIS provides exact information on bus arrival times at a given bus stop. Therefore, BIS does a lot to promote the use of buses contributing to pollution reduction and saving natural resources. BIS implementation costs a huge amount of budget as it requires a lot of special equipment such as road side equipment, automatic vehicle identification and location systems, trunked radio systems, and so on. Consequently, medium and small sized cities with a low budget cannot afford to install BIS even though people in these cities need BIS service more desperately than people in metropolitan areas. It is possible to provide BIS service at virtually no cost under the assumption that everybody carries a smartphone and there is at least one person with a smartphone in a running bus who is willing to reveal his/her location details while he/she is sitting in a bus. This assumption is usually true in the real world. The smartphone penetration rate is greater than 100% in the developed countries and there is no reason for a bus driver to refuse to reveal his/her location details while driving. We have developed a mobile app that periodically reads values of sensors including GPS and sends GPS data to the server when the bus stops or when the elapsed time from the last send attempt is greater than a threshold. This app detects the bus stop state by investigating the sensor values. The server that receives GPS data from this app has also been developed. Under the assumption that the current locations of all running buses collected by the mobile app are recorded in a database, we have also developed a web site that provides all kinds of information that most BISs provide to users through the Internet. The development environment is: OS: Windows 7 64bit, IDE: Eclipse Luna 4.4.1, Spring IDE 3.7.0, Database: MySQL 5.1.7, Web Server: Apache Tomcat 7.0, Programming Language: Java 1.7.0_79. Given a start and a destination bus stop, it finds a shortest path from the start to the destination using the Dijkstra algorithm. Then, it finds a convenient route considering number of transits. For the user interface, we use the Google map. Template classes that are used by the Controller, DAO, Service and Utils classes include BUS, BusStop, BusListInfo, BusStopOrder, RouteResult, WalkingDist, Location, and so on. We are now integrating the mobile app system and the web app system.

Keywords: bus information system, GPS, mobile app, web site

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Authors: Temnov D., Volgina E., Gerasimov D.

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Relaxation processes in polyvinylidene fluoride (PVDF) films were studied by the method of thermally stimulated fractional polarization currents (TSTF). The films were obtained by extrusion of a polymer melt followed by isometric annealing. PVDF granules of the Kynar-720 brand (Atofina Chemicals, USA) with a molecular weight of Mw=190,000 g•mol-1 were used for the manufacture of films. The annealing temperature was varied in the range from 120 °C to 170 °C in increments of 10 °C. The dependences of the degree of crystallinity of films (χ) and the intensity of thermally stimulated depolarization currents on the annealing temperature (Toc) are investigated. The TSTF spectra were obtained at the TSC II facility (Setaram, France). Measurements were carried out in a helium atmosphere, and the values of currents were determined by a Keithley electrometer. The annealed PVDF films were polarized at an electric field strength of 100 V/mm at a temperature of 31°C, after which they were cooled to 26°C, at which they were kept for 1 minute. During depolarization, the external field was removed, and the short-circuit sample was cooled to 0°C. The thermally stimulated short-circuit current was recorded during linear heating. Relaxation processes in PVDF films were studied in the temperature range from 0 – 70 °C. It is shown that the intensity curve of the peaks of TST FP has a course that is the reverse of the dependence of the degree of crystallinity on the annealing temperature. This allows us to conclude that the relaxation processes occurring in PVDF in the 35°C region are associated with the amorphous part of the structure of PVDF films between the layers of the spherulite crystalline phase.

Keywords: molecular and supramolecular structure, thermally stimulated currents, polyvinylidene fluoride films, relaxation processes

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Authors: Gianella Franco, Karen Suarez, María Quijano, Patricia Manzano

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Agro-industries generate large amounts of waste, which are mostly untapped. This research was carried out to use cocoa, coffee and orange industrial by-products to develop a dairy drink. The product was prepared by making a 10% aqueous extract of the mixture of cocoa and coffee beans shells and orange peel. Extreme Vertices Mixture Design was applied to vary the proportions of the ingredients of the aqueous extract, getting 13 formulations. Each formulation was mixed with skim milk and pasteurized. The attributes of taste, smell, color and appearance were evaluated by a semi-trained panel by multiple comparisons test, comparing the formulations against a standard marked as "R", which consisted of a coffee commercial drink. The formulations with the highest scores were selected to maximize the Total Polyphenol Content (TPC) through a process of linear optimization resulting in the formulation 80.5%: 18.37%: 1.13% of cocoa bean shell, coffee bean shell and orange peel, respectively. The Total Polyphenol Content was 4.99 ± 0.34 mg GAE/g of drink, DPPH radical scavenging activity (%) was 80.14 ± 0.05 and caffeine concentration of 114.78 mg / L, while the coffee commercial drink presented 3.93 ± 0.84 mg GAE / g drink, 55.54 ± 0.03 % and 47.44 mg / L of TPC, DPPH radical scavenging activity and caffeine content, respectively. The results show that it is possible to prepare an antioxidant - rich drink with good sensorial attributes made of industrial by-products.

Keywords: DPPH, polyphenols, waste, food science

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Authors: Aaditya U. Jhamb

Abstract:

Due to the current energy crisis that many countries are battling, energy-efficient buildings are the subject of extensive research in the modern technological era because of growing worries about energy consumption and its effects on the environment. The paper explores 8 factors that help determine energy efficiency for a building: (relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area, and glazing area distribution), with Tsanas and Xifara providing a dataset. The data set employed 768 different residential building models to anticipate heating and cooling loads with a low mean squared error. By optimizing these characteristics, machine learning algorithms may assess and properly forecast a building's heating and cooling loads, lowering energy usage while increasing the quality of people's lives. As a result, the paper studied the magnitude of the correlation between these input factors and the two output variables using various statistical methods of analysis after determining which input variable was most closely associated with the output loads. The most conclusive model was the Decision Tree Regressor, which had a mean squared error of 0.258, whilst the least definitive model was the Isotonic Regressor, which had a mean squared error of 21.68. This paper also investigated the KNN Regressor and the Linear Regression, which had to mean squared errors of 3.349 and 18.141, respectively. In conclusion, the model, given the 8 input variables, was able to predict the heating and cooling loads of a residential building accurately and precisely.

Keywords: energy efficient buildings, heating load, cooling load, machine learning models

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Authors: Soukaina Motia, Nadia El Alami El Hassani, Alassane Diouf, Benachir Bouchikhi, Nezha El Bari

Abstract:

Parabens are the antimicrobial molecules largely used in cosmetic products as a preservative agent. Among them, the methylparaben (MP) is the most frequently used ingredient in cosmetic preparations. Nevertheless, their potential dangers led to the development of sensible and reliable methods for their determination in environmental samples. Firstly, a sensitive and selective molecular imprinted polymer (MIP) based on screen-printed gold electrode (Au-SPE), assembled on a polymeric layer of carboxylated poly(vinyl-chloride) (PVC-COOH), was developed. After the template removal, the obtained material was able to rebind MP and discriminate it among other interfering species such as glucose, sucrose, and citric acid. The behavior of molecular imprinted sensor was characterized by Cyclic Voltammetry (CV), Differential Pulse Voltammetry (DPV) and Electrochemical Impedance Spectroscopy (EIS) techniques. Then, the biosensor was found to have a linear detection range from 0.1 pg.mL^-1 to 1 ng.mL^-1 and a low limit of detection of 0.12 fg.mL^-1 and 5.18 pg.mL^-1 by DPV and EIS, respectively. For applications, this biosensor was employed to determine MP content in four wastewaters in Meknes city and two cosmetic products (shower gel and shampoo). The operational reproducibility and stability of this biosensor were also studied. Secondly, another MIP biosensor based on tungsten trioxide (WO₃) functionalized by gold nanoparticles (Au-NPs) assembled on a polymeric layer of PVC-COOH was developed. The main goal was to increase the sensitivity of the biosensor. The developed MIP biosensor was successfully applied for the MP determination in wastewater samples and cosmetic products.

Keywords: cosmetic products, methylparaben, molecularly imprinted polymer, wastewater

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Authors: Vinicius Marzall, Jussanã Milograna

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The urban drainwatering remains a major challenge for most of the Brazilian cities. Not so different of the most part, Goiania, a state capital located in Midwest of the country has few legislations about the subject matter and only one registered solution of compensative techniques for drainwater. This paper clam to show some solutions which are adopted in other Brazilian cities with consolidated legislation, suggesting technics about detention tanks in a building sit. This study analyzed and compared the legislation of Curitiba, Porto Alegre e Sao Paulo, with the actual legislation and politics of Goiania. After this, were created models with adopted data for dimensioning the size of detention tanks using the envelope curve method considering synthetic series for intense precipitations and building sits between 250 m² and 600 m², with an impermeabilization tax of 50%. The results showed great differences between the legislation of Goiania and the documentation of the others cities analyzed, like the number of techniques for drainwatering applied to the reality of the cities, educational actions to awareness the population about care the water courses and political management by having a specified funds for drainwater subjects, for example. Besides, the use of detention tank showed itself practicable, have seen that the occupation of the tank is minor than 3% of the building sit, whatever the size of the terrain, granting the exit flow to pre-occupational taxes in extreme rainfall events. Also, was developed a linear equation to measure the detention tank based in the size of the building sit in Goiania, making simpler the calculation and implementation for non-specialized people.

Keywords: clean technology, legislation, rainwater management, urban drainwater

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Authors: Ravi Patel, Ravisinh Solanki, Dignesh Khunt

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A stability-indicating reverse phase high performance liquid chromatography (RP-HPLC) method was developed and validated for estimating Nirmatrelvir in its self-emulsifying drug delivery system (SEDDS). The separation of Nirmatrelvir and its degradation products was accomplished by employing an Agilent Zorbax Eclipse plus C18 (250 mm x 4.6 mm, 5 µm) column, through which the mobile phase 5 mM phosphate buffer (pH 4.0) as mobile phase A and Acetonitrile as mobile phase B in a ratio of (40:60 % v/v) was pumped at a flow rate of 1.0 mL/min, through the HPLC system. Chromatographic separation and elution were monitored by a photo-diode array detector at 210 nm. Stress studies have been employed to evaluate this method's ability to indicate stability. Nirmatrelvir was exposed to several stress conditions, such as acid, alkali, oxidative, photolytic, and thermal degradations. Significant degradation was observed during acid and alkali hydrolysis, and the resulting degradation product was successfully separated from the Nirmatrelvir peak, preventing any interference. Furthermore, the primary degradant produced under alkali degradation conditions was identified using UPLC-ESI-TQ-MS/MS. The method was validated in accordance with the International Council on Harmonization (ICH) and found to be selective, precise, accurate, linear, and robust. The apparent permeability of Nirmatrelvir SEDDS was 4.20 ± 0.21×10-6 cm/sec, and the average proportion of free drug recovered was 0.5%. The method developed in this study was feasible and accurate for routine quality control evaluation of Nirmatrelvir SEDDS.

Keywords: Nirmatrelvir, SEDDS, degradation study, HPLC, LC-MS/MS

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Authors: Kamran Siddique, Hiroyuki Asada, Yoshifumi Ogami

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The use of Micro Gas Turbine (MGT) as the engine in Unmanned Aerobic Vehicles (UAVs) and power source in Robotics is widespread these days. Research has been conducted in the past decade or so to improve the performance of different components of MGT. This type of engine has interrelated components which have non-linear characteristics. Therefore, the overall engine performance depends on the individual engine element’s performance. Computational Fluid Dynamics (CFD) is one of the simulation method tools used to analyze or even optimize MGT system performance. In this study, the compressor of the MGT is designed, and performance optimization is being done using CFD. Performance of the micro compressor is improved in order to increase the overall performance of MGT. A high value of pressure ratio is to be achieved by studying the effect of change of different operating parameters like mass flow rate and revolutions per minute (RPM) and aerodynamical and geometrical parameters on the pressure ratio of the compressor. Two types of compressor designs are considered in this study; 3D centrifugal and ‘planar’ designs. For a 10 mm impeller, the planar model is the simplest compressor model with the ease in manufacturability. On the other hand, 3D centrifugal model, although more efficient, is very difficult to manufacture using current microfabrication resources. Therefore, the planar model is the best-suited model for a micro compressor. So. a planar micro compressor has been designed that has a good pressure ratio, and it is easy to manufacture using current microfabrication technologies. Future work is to fabricate the compressor to get experimental results and validate the theoretical model.

Keywords: computational fluid dynamics, microfabrication, MEMS, unmanned aerobic vehicles

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Authors: Alireza Gholipour, Mergen H. Ghayesh, Anthony Zander, Stephen J. Nicholls, Peter J. Psaltis

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A three-dimensional numerical model of an atherosclerotic coronary ‎artery is developed for the determination of high-risk situation and ‎hence heart attack prediction. Employing the finite element method ‎‎(FEM) using ANSYS, fluid-structure interaction (FSI) model of the ‎artery is constructed to determine the shear stress distribution as well ‎as the von Mises stress field. A flexible model for an atherosclerotic ‎coronary artery conveying pulsatile blood is developed incorporating ‎three-dimensionality, artery’s tapered shape via a linear function for ‎artery wall distribution, motion of the artery, blood viscosity via the ‎non-Newtonian flow theory, blood pulsation via use of one-period ‎heartbeat, hyperelasticity via the Mooney-Rivlin model, viscoelasticity ‎via the Prony series shear relaxation scheme, and micro-calcification ‎inside the plaque. The material properties used to relate the stress field ‎to the strain field have been extracted from clinical data from previous ‎in-vitro studies. The determined stress fields has potential to be used as ‎a predictive tool for plaque rupture and dissection.‎ The results show that stress concentration due to micro-calcification ‎increases the von Mises stress significantly; chance of developing a ‎crack inside the plaque increases. Moreover, the blood pulsation varies ‎the stress distribution substantially for some cases.‎

Keywords: atherosclerosis, fluid-structure interaction‎, coronary arteries‎, pulsatile flow

Procedia PDF Downloads 172

Authors: Zeyad Suleiman Bataineh

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Introduction: civilian wars are associated with severe humanitarian effects that include loss of individuals and properties. Psychological dimensions are also included depression. Objectives: the main objectives of the present study were to investigate the depression level among Syrian patients who visited internal medicine clinics and other related variables. Methods and subjects: this study was conducted based on cross sectional study design. A total of 175 patients were involved. Patients were asked to fill a questionnaire to assess the level of depression that include demographic variables such as gender, age, educational level, and social status. Beck Aaron scale for depression was used. Participation in this study was voluntary, and all patients were informed about their rights to withdraw from the study without being negatively affected. Data were entered into excel spreading sheet for all participants. SPSS version 21 was used to analyze data. Data were described as means, the standard deviation for linear variables, frequencies, and percentages for categorical variables. The relationships between variables were evaluated using independent t test and One Way ANOVA test. Significance was considered at α≤0.05. Results: Depression was found in 152 (87%) of participants. The majority of participants with depression had moderate to severe depression. Depression was significantly associated gender, age, educational level, and social status (p<0.05). Conclusion: psychological rehabilitation is required for patients who experienced civilian wars.

Keywords: mental health, deprssion, health system, psychological dimension

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Authors: Kavita Goel, Donald Winchester

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In a world of information overload and work complexities, academics often struggle to create an online instructional environment enabling efficient and effective student learning. Research has established that students’ learning styles are different, some learn faster when taught using audio and visual methods. Attributes like prior knowledge and mental effort affect their learning. ‘Cognitive load theory’, opines learners have limited processing capacity. Cognitive load depends on the learner’s prior knowledge, the complexity of content and tasks, and instructional environment. Hence, the proper allocation of cognitive resources is critical for students’ learning. Consequently, a lecturer needs to understand the limits and strengths of the human learning processes, various learning styles of students, and accommodate these requirements while designing online assessments. As acknowledged in the cognitive load theory literature, visual and auditory explanations of worked examples potentially lead to a reduction of cognitive load (effort) and increased facilitation of learning when compared to conventional sequential text problem solving. This will help learner to utilize both subcomponents of their working memory. Instructional design changes were introduced at the case site for the delivery of the postgraduate business subjects. To make effective use of auditory and visual modalities, video recorded lectures, and key concept webinars were delivered to students. Videos were prepared to free up student limited working memory from irrelevant mental effort as all elements in a visual screening can be viewed simultaneously, processed quickly, and facilitates greater psychological processing efficiency. Most case study students in the postgraduate programs are adults, working full-time at higher management levels, and studying part-time. Their learning style and needs are different from other tertiary students. The purpose of the audio and visual interventions was to lower the students cognitive load and provide an online environment supportive to their efficient learning. These changes were expected to impact the student’s learning experience, their academic performance and retention favourably. This paper posits that these changes to instruction design facilitates students to integrate new knowledge into their long-term memory. A mixed methods case study methodology was used in this investigation. Primary data were collected from interviews and survey(s) of students and academics. Secondary data were collected from the organisation’s databases and reports. Some evidence was found that the academic performance of students does improve when new instructional design changes are introduced although not statistically significant. However, the overall grade distribution of student’s academic performance has changed and skewed higher which shows deeper understanding of the content. It was identified from feedback received from students that recorded webinars served as better learning aids than material with text alone, especially with more complex content. The recorded webinars on the subject content and assessments provides flexibility to students to access this material any time from repositories, many times, and this enhances students learning style. Visual and audio information enters student’s working memory more effectively. Also as each assessment included the application of the concepts, conceptual knowledge interacted with the pre-existing schema in the long-term memory and lowered student’s cognitive load.

Keywords: cognitive load theory, learning style, instructional environment, working memory

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Authors: S. Bouhouche, R. Drai, J. Bast

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This paper is concerned with a method for uncertainty evaluation of steel sample content using X-Ray Fluorescence method. The considered method of analysis is a comparative technique based on the X-Ray Fluorescence; the calibration step assumes the adequate chemical composition of metallic analyzed sample. It is proposed in this work a new combined approach using the Kalman Filter and Markov Chain Monte Carlo (MCMC) for uncertainty estimation of steel content analysis. The Kalman filter algorithm is extended to the model identification of the chemical analysis process using the main factors affecting the analysis results; in this case, the estimated states are reduced to the model parameters. The MCMC is a stochastic method that computes the statistical properties of the considered states such as the probability distribution function (PDF) according to the initial state and the target distribution using Monte Carlo simulation algorithm. Conventional approach is based on the linear correlation, the uncertainty budget is established for steel Mn(wt%), Cr(wt%), Ni(wt%) and Mo(wt%) content respectively. A comparative study between the conventional procedure and the proposed method is given. This kind of approaches is applied for constructing an accurate computing procedure of uncertainty measurement.

Keywords: Kalman filter, Markov chain Monte Carlo, x-ray fluorescence calibration and testing, steel content measurement, uncertainty measurement

Procedia PDF Downloads 283

Authors: Jennifer A. Kowalkowski

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Production agriculture (farming) is a physically, emotionally, and cognitively stressful occupation, where workers have little control over the stressors that impact both their work and their lives. In an occupation already rife with hazards, these occupational-related stressors have been shown to increase farm workers’ risks for illness, injury, disability, and death associated with their work. Despite efforts to mitigate the negative health effects from occupational-related stress (ORS) and to promote health and well-being (HWB) among farmers in the US, marked improvements have not been attained. Social support accessed through social networks has been shown to buffer against the negative health effects from stress, yet no studies have directly examined these relationships among farmers. The purpose of this study was to use social network analysis to explore the social networks of farm owner-operators and the social supports available to them for mitigating the negative health effects of ORS. A convenience sample of 71 farm owner-operators from a Midwestern County in the US completed and returned a mailed survey (55.5% response rate) that solicited information about their social networks related to ORS. Farmers reported an average of 2.4 individuals in their personal networks and higher levels of comfort discussing ORS with female network members. Farmers also identified few connections (3.4% density) and indicated low comfort with members of affiliation networks specific to ORS. Findings from this study highlighted that farmers accessed different social networks and resources for their personal HWB than for issues related to occupational(farm-related) health and safety. In addition, farmers’ social networks for personal HWB were smaller, with different relational characteristics than reported in studies of farmers’ social networks related to occupational health and safety. Collectively, these findings suggest that farmers conceptualize personal HWB differently than farm health and safety. Therefore, the same research approaches and targets that guide occupational health and safety research may not be appropriate for personal HWB for farmers. Interventions and programming targeting ORS and HWB have largely been offered through the same platforms or mechanisms as occupational health and safety programs. This may be attributed to the significant overlap between the farm as a family business and place of residence, or that ORS stems from farm-related issues. However, these assumptions translated to health research of farmers and farm families from the occupational health and safety literature have not been directly studied or challenged. Thismay explain why past interventions have not been effective at improving health outcomes for farmers and farm families. A close examination of findings from this study raises important questions for researchers who study agricultural health. Findings from this study have significant implications for future research agendas focused on addressing ORS, HWB, and health disparities for farmersand farm families.

Keywords: agricultural health, occupational-related stress, social networks, well-being

Procedia PDF Downloads 108