Search results for: linear regression estimation

Authors: Jayahar Sivasubramanian

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Understanding laminar-turbulent transition process in hyper-sonic boundary layers is crucial for designing viable high speed flight vehicles. The study of transition becomes particularly important in the high speed regime due to the effect of transition on aerodynamic performance and heat transfer. However, even after many years of research, the transition process in hyper-sonic boundary layers is still not understood. This lack of understanding of the physics of the transition process is a major impediment to the development of reliable transition prediction methods. Towards this end, spatial Direct Numerical Simulations are conducted to investigate the instability waves generated by a localized disturbance in a hyper-sonic flat plate boundary layer. In order to model a natural transition scenario, the boundary layer was forced by a short duration (localized) pulse through a hole on the surface of the flat plate. The pulse disturbance developed into a three-dimensional instability wave packet which consisted of a wide range of disturbance frequencies and wave numbers. First, the linear development of the wave packet was studied by forcing the flow with low amplitude (0.001% of the free-stream velocity). The dominant waves within the resulting wave packet were identified as two-dimensional second mode disturbance waves. Hence the wall-pressure disturbance spectrum exhibited a maximum at the span wise mode number k = 0. The spectrum broadened in downstream direction and the lower frequency first mode oblique waves were also identified in the spectrum. However, the peak amplitude remained at k = 0 which shifted to lower frequencies in the downstream direction. In order to investigate the nonlinear transition regime, the flow was forced with a higher amplitude disturbance (5% of the free-stream velocity). The developing wave packet grows linearly at first before reaching the nonlinear regime. The wall pressure disturbance spectrum confirmed that the wave packet developed linearly at first. The response of the flow to the high amplitude pulse disturbance indicated the presence of a fundamental resonance mechanism. Lower amplitude secondary peaks were also identified in the disturbance wave spectrum at approximately half the frequency of the high amplitude frequency band, which would be an indication of a sub-harmonic resonance mechanism. The disturbance spectrum indicates, however, that fundamental resonance is much stronger than sub-harmonic resonance.

Keywords: boundary layer, DNS, hyper sonic flow, instability waves, wave packet

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Authors: Deepti Kumari, Upamanyu Hore

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Cities are an example of a human-modified environment with few fragments of urban green spaces, which are widely considered for urban biodiversity. The study aims to address the avifaunal diversity in urban parks based on the park size and their urbanization intensity. Also, understanding the key factors affecting species composition and structure as birds are a good indicator of a healthy ecosystem, and they are sensitive to changes in the environment. A 50 m-long line-transect method is used to survey birds in 39 urban parks in Delhi, India. Habitat variables, including vegetation (percentage of non-native trees, percentage of native trees, top canopy cover, sub-canopy cover, diameter at breast height, ground vegetation cover, shrub height) were measured using the quadrat method along the transect, and disturbance variables (distance from water, distance from road, distance from settlement, park area, visitor rate, and urbanization intensity) were measured using ArcGIS and google earth. We analyzed species data for diversity and richness. We explored the relation of species diversity and richness to habitat variables using the multi-model inference approach. Diversity and richness are found significant in different park sizes and their urbanization intensity. Medium size park supports more diversity, whereas large size park has more richness. However, diversity and richness both declined with increasing urbanization intensity. The result of CCA revealed that species composition in urban parks was positively associated with tree diameter at breast height and distance from the settlement. On the model selection approach, disturbance variables, especially distance from road, urbanization intensity, and visitors are the best predictors for the species richness of birds in urban parks. In comparison, multiple regression analysis between habitat variables and bird diversity suggested that native tree species in the park may explain the diversity pattern of birds in urban parks. Feeding guilds such as insectivores, omnivores, carnivores, granivores, and frugivores showed a significant relation with vegetation variables, while carnivores and scavenger bird species mainly responded with disturbance variables. The study highlights the importance of park size in urban areas and their urbanization intensity. It also indicates that distance from the settlement, distance from the road, urbanization intensity, visitors, diameter at breast height, and native tree species can be important determining factors for bird richness and diversity in urban parks. The study also concludes that the response of feeding guilds to vegetation and disturbance in urban parks varies. Therefore, we recommend that park size and surrounding urban matrix should be considered in order to increase bird diversity and richness in urban areas for designing and planning.

Keywords: diversity, feeding guild, urban park, urbanization intensity

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Authors: Nguyen J. M., Lucas G., Ruan S., Digonnet H., Antonioli D.

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Introduction: Deep Learning (DL) is a very powerful tool for analyzing image data. But for tabular data, it cannot compete with machine learning methods like XGBoost. The research question becomes: can tabular data be transformed into images that can be analyzed by simple CNNs (Convolutional Neuron Networks)? Will DL be the absolute tool for data classification? All current solutions consist in repositioning the variables in a 2x2 matrix using their correlation proximity. In doing so, it obtains an image whose pixels are the variables. We implement a technology, DeepNIC, that offers the possibility of obtaining an image for each variable, which can be analyzed by simple CNNs. Material and method: The 'ROP' (Regression OPtimized) model is a binary and atypical decision tree whose nodes are managed by a new artificial neuron, the Neurop. By positioning an artificial neuron in each node of the decision trees, it is possible to make an adjustment on a theoretically infinite number of variables at each node. From this new decision tree whose nodes are artificial neurons, we created the concept of a 'Random Forest of Perfect Trees' (RFPT), which disobeys Breiman's concepts by assembling very large numbers of small trees with no classification errors. From the results of the RFPT, we developed a family of 10 statistical information criteria, Nguyen Information Criterion (NICs), which evaluates in 3 dimensions the predictive quality of a variable: Performance, Complexity and Multiplicity of solution. A NIC is a probability that can be transformed into a grey level. The value of a NIC depends essentially on 2 super parameters used in Neurops. By varying these 2 super parameters, we obtain a 2x2 matrix of probabilities for each NIC. We can combine these 10 NICs with the functions AND, OR, and XOR. The total number of combinations is greater than 100,000. In total, we obtain for each variable an image of at least 1166x1167 pixels. The intensity of the pixels is proportional to the probability of the associated NIC. The color depends on the associated NIC. This image actually contains considerable information about the ability of the variable to make the prediction of Y, depending on the presence or absence of other variables. A basic CNNs model was trained for supervised classification. Results: The first results are impressive. Using the GSE22513 public data (Omic data set of markers of Taxane Sensitivity in Breast Cancer), DEEPNic outperformed other statistical methods, including XGBoost. We still need to generalize the comparison on several databases. Conclusion: The ability to transform any tabular variable into an image offers the possibility of merging image and tabular information in the same format. This opens up great perspectives in the analysis of metadata.

Keywords: tabular data, CNNs, NICs, DeepNICs, random forest of perfect trees, classification

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Authors: S. K. Appiah, E. N. Aidoo, D. Asamoah Owusu, M. W. Nuonabuor

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Urbanization remains one of the unique predominant factors which is linked to the destruction of urban environment and its associated cases of soil contamination by heavy metals through the natural and anthropogenic activities. These activities are important sources of toxic heavy metals such as arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), manganese (Mn), and lead (Pb), nickel (Ni) and zinc (Zn). Often, these heavy metals lead to increased levels in some areas due to the impact of atmospheric deposition caused by their proximity to industrial plants or the indiscriminately burning of substances. Information gathered on potentially hazardous levels of these heavy metals in soils leads to establish serious health and urban agriculture implications. However, characterization of spatial variations of soil contamination by heavy metals in Ghana is limited. Kumasi is a Metropolitan city in Ghana, West Africa and is challenged with the recent spate of deteriorating soil quality due to rapid economic development and other human activities such as “Galamsey”, illegal mining operations within the metropolis. The paper seeks to use both univariate and multivariate geostatistical techniques to assess the spatial distribution of heavy metals in soils and the potential risk associated with ingestion of sources of soil contamination in the Metropolis. Geostatistical tools have the ability to detect changes in correlation structure and how a good knowledge of the study area can help to explain the different scales of variation detected. To achieve this task, point referenced data on heavy metals measured from topsoil samples in a previous study, were collected at various locations. Linear models of regionalisation and coregionalisation were fitted to all experimental semivariograms to describe the spatial dependence between the topsoil heavy metals at different spatial scales, which led to ordinary kriging and cokriging at unsampled locations and production of risk maps of soil contamination by these heavy metals. Results obtained from both the univariate and multivariate semivariogram models showed strong spatial dependence with range of autocorrelations ranging from 100 to 300 meters. The risk maps produced show strong spatial heterogeneity for almost all the soil heavy metals with extremely risk of contamination found close to areas with commercial and industrial activities. Hence, ongoing pollution interventions should be geared towards these highly risk areas for efficient management of soil contamination to avert further pollution in the metropolis.

Keywords: coregionalization, heavy metals, multivariate geostatistical analysis, soil contamination, spatial distribution

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Authors: Soheila Sadeghi

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Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

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Authors: Neha Gupta, Sonika Verma, Seema Puri, Nikhil Tandon, Narendra K. Arora

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The concurrent increasing prevalence of underweight and overweight/obesity among children with changing lifestyle and the rapid transitioning society has necessitated the need for a unifying/multi-level approach to understand the determinants of the problem. The present community-based cross-sectional research study was conducted to assess the associations between lifestyle behavior and food environment of the child at household, neighborhood, and school with the BMI of children (6-12 year old) (n=612) residing in three rural clusters of Palwal district, Haryana. The study used innovative and robust methods for assessing the lifestyle and various components of food environment in the study. The three rural clusters selected for the study were located at three different locations according to their access to highways in the SOMAARTH surveillance site. These clusters were significantly different from each other in terms of their socio-demographic and socio-economic profile, living conditions, environmental hygiene, health seeking behavior and retail density. Despite of being different, the quality of living conditions and environmental hygiene was poor across three clusters. The children had higher intakes of dietary energy and sugars; one-fifth share of the energy being derived from unhealthy foods, engagement in high levels of physical activity and significantly different food environment at home, neighborhood and school level. However, despite having a high energy intake, 22.5% of the recruited children were thin/severe thin, and 3% were overweight/obese as per their BMI-for-age categories. The analysis was done using multi-variate logistic regression at three-tier hierarchy including individual, household and community level. The factors significantly explained the variability in governing the risk of getting thin/severe thin among children in rural area (p-value: 0.0001; Adjusted R2: 0.156) included age (>10years) (OR: 2.1; 95% CI: 1.0-4.4), the interaction between minority category and poor SES of the household (OR: 4.4; 95% CI: 1.6-12.1), availability of sweets (OR: 0.9; 95% CI: 0.8-0.99) and cereals (OR: 0.9; 95% CI: 0.8-1.0) in the household and poor street condition (proxy indicator of the hygiene and cleanliness in the neighborhood) (OR: 0.3; 95% CI: 0.1-1.1). The homogeneity of other factors at neighborhood and school level food environment diluted the heterogeneity in the lifestyles and home environment of the recruited children and their households. However, it is evident that when various individual factors interplay at multiple levels amplifies the risk of undernutrition in a rural community. Conclusion: These rural areas in Haryana are undergoing developmental, economic and societal transition. In correspondence, no improvements in the nutritional status of children have happened. Easy access to the unhealthy foods has become a paradox.

Keywords: transition, food environment, lifestyle, undernutrition, overnutrition

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Authors: Su Hui Tsai, Weir Sen Lin, Rhay Hung Weng

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There are numerous outpatient departments at hospitals with enormous amounts of outpatients. Although the work of outpatient nursing staff does not include the ward, emergency and critical care units that involve patient life-threatening conditions, the work is cumbersome and requires facing and dealing with a large number of outpatients in a short period of time. Therefore, nursing staff often do not feel satisfied with their work and cannot identify with their professional role, leading to intentions to leave their job. Thus, the main purpose of this study is to explore the correlation between the job satisfaction and role identity of nursing staff with turnover intention. This research was conducted using a questionnaire, and the subjects were outpatient nursing staff in three regional hospitals in Southern Taiwan. A total of 175 questionnaires were distributed, and 166 valid questionnaires were returned. After collecting the data, the reliability and validity of the study variables were confirmed by confirmatory factor analysis. The influence of role identity and job satisfaction on nursing staff’s turnover intention was analyzed by descriptive analysis, one-way ANOVA, Pearson correlation analysis and multiple regression analysis. Results showed that 'role identity' had significant differences in different types of marriages. Job satisfaction of 'grasp of environment' had significant differences in different levels of education. Job satisfaction of 'professional growth' and 'shifts and days off' showed significant differences in different types of marriages. 'Role identity' and 'job satisfaction' were negatively correlated with turnover intention respectively. Job satisfaction of 'salary and benefits' and 'grasp of environment' were significant predictors of role identity. The higher the job satisfaction of 'salary and benefits' and 'grasp of environment', the higher the role identity. Job satisfaction of 'patient and family interaction' were significant predictors of turnover intention. The lower the job satisfaction of 'patient and family interaction', the higher the turnover intention. This study found that outpatient nursing staff had the lowest satisfaction towards salary structure. It is recommended that bonuses, promotion opportunities and other incentives be established to increase the role identity of outpatient nursing staff. The results showed that the higher the job satisfaction of 'salary and benefits' and 'grasp of environment', the higher the role identity. It is recommended that regular evaluations be conducted to reward nursing staff with excellent service and invite nursing staff to share their work experiences and thoughts, to enhance nursing staff’s expectation and identification of their occupational role, as well as instilling the concept of organizational service and organizational expectations of emotional display. The results showed that the lower the job satisfaction of 'patient and family interaction', the higher the turnover intention. It is recommended that interpersonal communication and workplace violence prevention educational training courses be organized to enhance the communication and interaction of nursing staff with patients and their families.

Keywords: outpatient, job satisfaction, turnover, intention

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Authors: Mohammad Ali Tabibi, Farzad Nazemi, Nasrin Salimian

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Background: Peritoneal dialysis (PD) is a prevalent renal replacement therapy for patients with end-stage renal disease. Despite its benefits, PD patients often experience reduced physical activity and physical function, which can negatively impact dialysis adequacy and overall health outcomes. Despite the known benefits of maintaining physical activity in chronic disease management, the specific interplay between physical inactivity, physical function, and dialysis adequacy in PD patients remains underexplored. Understanding this relationship is essential for developing targeted interventions to enhance patient care and outcomes in this vulnerable population. This study aims to assess the impact of physical inactivity on dialysis adequacy and functional health in PD patients. Methods: This cross-sectional study included 135 peritoneal dialysis patients from multiple dialysis centers. Physical inactivity was measured using the International Physical Activity Questionnaire (IPAQ), while physical function was assessed using the Short Physical Performance Battery (SPPB). Dialysis adequacy was evaluated using the Kt/V ratio. Additional variables such as demographic data, comorbidities, and laboratory parameters were collected to control for potential confounders. Statistical analyses were performed to determine the relationships between physical inactivity, physical function, and dialysis adequacy. Results: The study cohort comprised 70 males and 65 females with a mean age of 55.4 ± 13.2 years. A significant proportion of the patients (65%) were categorized as physically inactive based on IPAQ scores. Inactive patients demonstrated significantly lower SPPB scores (mean 6.2 ± 2.1) compared to their more active counterparts (mean 8.5 ± 1.8, p < 0.001). Dialysis adequacy, as measured by Kt/V, was found to be suboptimal (Kt/V < 1.7) in 48% of the patients. There was a significant positive correlation between physical function scores and Kt/V values (r = 0.45, p < 0.01), indicating that better physical function is associated with higher dialysis adequacy. Also, there was a significant negative correlation between physical inactivity and physical function (r = -0.55, p < 0.01). Additionally, physically inactive patients had lower Kt/V ratios compared to their active counterparts (1.3 ± 0.3 vs. 1.8 ± 0.4, p < 0.05). Multivariate regression analysis revealed that physical inactivity was an independent predictor of reduced dialysis adequacy (β = -0.32, p < 0.01) and poorer physical function (β = -0.41, p < 0.01) after adjusting for age, sex, comorbidities, and dialysis vintage. Conclusion: This study underscores the critical role of physical activity and physical function in maintaining adequate dialysis in peritoneal dialysis patients. These findings highlight the need for targeted interventions to promote physical activity in this population to improve their overall health outcomes. Future research should focus on developing and evaluating exercise programs tailored for PD patients to enhance their physical function and dialysis adequacy. The findings suggest that interventions aimed at increasing physical activity and improving physical function may enhance dialysis adequacy and overall health outcomes in this population. Further research is warranted to explore the mechanisms underlying these associations and to develop targeted strategies for enhancing patient care.

Keywords: inactivity, physical function, peritoneal dialysis, dialysis adequacy

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Authors: Mrinalini Ranjan, Sudheesh Chethil

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Epilepsy is a common neurological disorder characterised by the recurrence of seizures. Electroencephalogram (EEG) signals are complex biomedical signals which exhibit nonlinear and nonstationary behavior. We use two methods 1) Detrended Fluctuation Analysis (DFA) and 2) Recurrence Plots (RP) to capture this complex behavior of EEG signals. DFA considers fluctuation from local linear trends. Scale invariance of these signals is well captured in the multifractal characterisation using detrended fluctuation analysis (DFA). Analysis of long-range correlations is vital for understanding the dynamics of EEG signals. Correlation properties in the EEG signal are quantified by the calculation of a scaling exponent. We report the existence of two scaling behaviours in the epileptic EEG signals which quantify short and long-range correlations. To illustrate this, we perform DFA on extant ictal (seizure) and interictal (seizure free) datasets of different patients in different channels. We compute the short term and long scaling exponents and report a decrease in short range scaling exponent during seizure as compared to pre-seizure and a subsequent increase during post-seizure period, while the long-term scaling exponent shows an increase during seizure activity. Our calculation of long-term scaling exponent yields a value between 0.5 and 1, thus pointing to power law behaviour of long-range temporal correlations (LRTC). We perform this analysis for multiple channels and report similar behaviour. We find an increase in the long-term scaling exponent during seizure in all channels, which we attribute to an increase in persistent LRTC during seizure. The magnitude of the scaling exponent and its distribution in different channels can help in better identification of areas in brain most affected during seizure activity. The nature of epileptic seizures varies from patient-to-patient. To illustrate this, we report an increase in long-term scaling exponent for some patients which is also complemented by the recurrence plots (RP). RP is a graph that shows the time index of recurrence of a dynamical state. We perform Recurrence Quantitative analysis (RQA) and calculate RQA parameters like diagonal length, entropy, recurrence, determinism, etc. for ictal and interictal datasets. We find that the RQA parameters increase during seizure activity, indicating a transition. We observe that RQA parameters are higher during seizure period as compared to post seizure values, whereas for some patients post seizure values exceeded those during seizure. We attribute this to varying nature of seizure in different patients indicating a different route or mechanism during the transition. Our results can help in better understanding of the characterisation of epileptic EEG signals from a nonlinear analysis.

Keywords: detrended fluctuation, epilepsy, long range correlations, recurrence plots

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Authors: Vladislav Grigorovitch, Marina Grigorovitch, David Pearlmutter, Erez Gal

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The concept of “electric island” is involved with achieving the balance between the self-power generation ability of each educational institution and energy consumption demand. Photo-Voltaic (PV) solar system installed on the roofs of educational buildings is a common way to absorb the available solar energy and generate electricity for self-consumption and even for returning to the grid. The main objective of this research is to develop and implement an “electric island” monitoring infrastructure for promoting energy efficiency in educational buildings. A microscale monitoring methodology will be developed to provide a platform to estimate energy consumption performance classified by rooms and subspaces rather than the more common macroscale monitoring of the whole building. The monitoring platform will be established on the experimental sites, enabling an estimation and further analysis of the variety of environmental and physical conditions. For each building, separate measurement configurations will be applied taking into account the specific requirements, restrictions, location and infrastructure issues. The direct results of the measurements will be analyzed to provide deeper understanding of the impact of environmental conditions and sustainability construction standards, not only on the energy demand of public building, but also on the energy consumption habits of the children that study in those schools and the educational and administrative staff that is responsible for providing the thermal comfort conditions and healthy studying atmosphere for the children. A monitoring methodology being developed in this research is providing online access to real-time data of Interferential Therapy (IFTs) from any mobile phone or computer by simply browsing the dedicated website, providing powerful tools for policy makers for better decision making while developing PV production infrastructure to achieve “electric islands” in educational buildings. A detailed measurement configuration was technically designed based on the specific conditions and restriction of each of the pilot buildings. A monitoring and analysis methodology includes a large variety of environmental parameters inside and outside the schools to investigate the impact of environmental conditions both on the energy performance of the school and educational abilities of the children. Indoor measurements are mandatory to acquire the energy consumption data, temperature, humidity, carbon dioxide and other air quality conditions in different parts of the building. In addition to that, we aim to study the awareness of the users to the energy consideration and thus the impact on their energy consumption habits. The monitoring of outdoor conditions is vital for proper design of the off-grid energy supply system and validation of its sufficient capacity. The suggested outcomes of this research include: 1. both experimental sites are designed to have PV production and storage capabilities; 2. Developing an online information feedback platform. The platform will provide consumer dedicated information to academic researchers, municipality officials and educational staff and students; 3. Designing an environmental work path for educational staff regarding optimal conditions and efficient hours for operating air conditioning, natural ventilation, closing of blinds, etc.

Keywords: sustainability, electric island, IOT, smart building

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Authors: Thao Nguyen, Maximiliano Hyon, Sany Rajagukguk, Anna Melkonyan

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Introduction: Type 2 Diabetes is a well-established risk factor for severe SARS-CoV-2 infection. Uncontrolled hyperglycemia in patients with established or newly diagnosed diabetes is associated with poor outcomes, including increased mortality and hospital length of stay. Objectives: Our study aims to compare three different glycemic management strategies and their association with clinical outcomes in patients hospitalized for moderate to severe SARS-CoV-2 infection. Identifying optimal glycemic management strategies will improve the quality of patient care and improve their outcomes. Method: This is a retrospective observational study on patients hospitalized at Adventist Health White Memorial with severe SARS-CoV-2 infection from 11/1/2020 to 02/28/2021. The following inclusion criteria were used: positive SARS-CoV-2 PCR test, age >18 yrs old, diabetes or random glucose >200 mg/dL on admission, oxygen requirement >4L/min, and treatment with glucocorticoids. Our exclusion criteria included: ICU admission within 24 hours, discharge within five days, death within five days, and pregnancy. The patients were divided into three glycemic management groups: Group 1, managed solely by the Primary Team, Group 2, by Pharmacy; and Group 3, by Endocrinologist. Primary outcomes were average glucose on Day 5, change in glucose between Days 3 and 5, and average insulin dose on Day 5 among groups. Secondary outcomes would be upgraded to ICU, inpatient mortality, and hospital length of stay. For statistics, we used IBM® SPSS, version 28, 2022. Results: Most studied patients were Hispanic, older than 60, and obese (BMI >30). It was the first CV-19 surge with the Delta variant in an unvaccinated population. Mortality was markedly high (> 40%) with longer LOS (> 13 days) and a high ICU transfer rate (18%). Most patients had markedly elevated inflammatory markers (CRP, Ferritin, and D-Dimer). These, in combination with glucocorticoids, resulted in severe hyperglycemia that was difficult to control. Average glucose on Day 5 was not significantly different between groups primary vs. pharmacy vs. endocrine (220.5 ± 63.4 vs. 240.9 ± 71.1 vs. 208.6 ± 61.7 ; P = 0.105). Change in glucose from days 3 to 5 was not significantly different between groups but trended towards favoring the endocrinologist group (-26.6±73.6 vs. 3.8±69.5 vs. -32.2±84.1; P= 0.052). TDD insulin was not significantly different between groups but trended towards higher TDD for the endocrinologist group (34.6 ± 26.1 vs. 35.2 ± 26.4 vs. 50.5 ± 50.9; P=0.054). The endocrinologist group used significantly more preprandial insulin compared to other groups (91.7% vs. 39.1% vs. 65.9% ; P < 0.001). The pharmacy used more basal insulin than other groups (95.1% vs. 79.5% vs. 79.2; P = 0.047). There were no differences among groups in the clinical outcomes: LOS, ICU upgrade, or mortality. Multivariate regression analysis controlled for age, sex, BMI, HbA1c level, renal function, liver function, CRP, d-dimer, and ferritin showed no difference in outcomes among groups. Conclusion: Given high-risk factors in our population, despite efforts from the glycemic management teams, it’s unsurprising no differences in clinical outcomes in mortality and length of stay.

Keywords: glycemic management, strategies, hospitalized, SARS-CoV-2, outcomes

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Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei

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Background and Aims: This meta-analysis aimed to evaluate the effect of vitamin D supplementation on key metabolic and cardiovascular parameters, such as glycated hemoglobin (HbA1C), fasting blood sugar (FBS), low-density lipoprotein (LDL), high-density lipoprotein (HDL), systolic blood pressure (SBP), and total vitamin D levels in patients with Type 2 diabetes mellitus (T2DM). Methods: A systematic search was performed across databases, including PubMed, Scopus, Embase, Web of Science, Cochrane Library, and ClinicalTrials.gov, from January 1990 to January 2024. A total of 4,177 relevant studies were initially identified. Using an unsupervised K-means clustering algorithm, publications were grouped based on common text features. Maximum entropy classification was then applied to filter studies that matched a pre-identified training set of 139 potentially relevant articles. These selected studies were manually screened for relevance. A parallel manual selection of all initially searched studies was conducted for validation. The final inclusion of studies was based on full-text evaluation, quality assessment, and meta-regression models using random effects. Sensitivity analysis and publication bias assessments were also performed to ensure robustness. Results: The unsupervised K-means clustering algorithm grouped the patients based on their responses to vitamin D supplementation, using key biomarkers such as HbA1C, FBS, LDL, HDL, SBP, and total vitamin D levels. Two primary clusters emerged: one representing patients who experienced significant improvements in these markers and another showing minimal or no change. Patients in the cluster associated with significant improvement exhibited lower HbA1C, FBS, and LDL levels after vitamin D supplementation, while HDL and total vitamin D levels increased. The analysis showed that vitamin D supplementation was particularly effective in reducing HbA1C, FBS, and LDL within this cluster. Furthermore, BMI, weight gain, and disease duration were identified as factors that influenced cluster assignment, with patients having lower BMI and shorter disease duration being more likely to belong to the improvement cluster. Conclusion: The findings of this machine learning-assisted meta-analysis confirm that vitamin D supplementation can significantly improve glycemic control and reduce the risk of cardiovascular complications in T2DM patients. The use of automated screening techniques streamlined the process, ensuring the comprehensive evaluation of a large body of evidence while maintaining the validity of traditional manual review processes.

Keywords: HbA1C, T2DM, SBP, FBS

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Authors: Joel Niklaus, Matthias Sturmer

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The publication of judicial proceedings is a cornerstone of many democracies. It enables the court system to be made accountable by ensuring that justice is made in accordance with the laws. Equally important is privacy, as a fundamental human right (Article 12 in the Declaration of Human Rights). Therefore, it is important that the parties (especially minors, victims, or witnesses) involved in these court decisions be anonymized securely. Today, the anonymization of court decisions in Switzerland is performed either manually or semi-automatically using primitive software. While much research has been conducted on anonymization for tabular data, the literature on anonymization for unstructured text documents is thin and virtually non-existent for court decisions. In 2019, it has been shown that manual anonymization is not secure enough. In 21 of 25 attempted Swiss federal court decisions related to pharmaceutical companies, pharmaceuticals, and legal parties involved could be manually re-identified. This was achieved by linking the decisions with external databases using regular expressions. An automated re-identification system serves as an automated test for the safety of existing anonymizations and thus promotes the right to privacy. Manual anonymization is very expensive (recurring annual costs of over CHF 20M in Switzerland alone, according to an estimation). Consequently, many Swiss courts only publish a fraction of their decisions. An automated anonymization system reduces these costs substantially, further leading to more capacity for publishing court decisions much more comprehensively. For the re-identification system, topic modeling with latent dirichlet allocation is used to cluster an amount of over 500K Swiss court decisions into meaningful related categories. A comprehensive knowledge base with publicly available data (such as social media, newspapers, government documents, geographical information systems, business registers, online address books, obituary portal, web archive, etc.) is constructed to serve as an information hub for re-identifications. For the actual re-identification, a general-purpose language model is fine-tuned on the respective part of the knowledge base for each category of court decisions separately. The input to the model is the court decision to be re-identified, and the output is a probability distribution over named entities constituting possible re-identifications. For the anonymization system, named entity recognition (NER) is used to recognize the tokens that need to be anonymized. Since the focus lies on Swiss court decisions in German, a corpus for Swiss legal texts will be built for training the NER model. The recognized named entities are replaced by the category determined by the NER model and an identifier to preserve context. This work is part of an ongoing research project conducted by an interdisciplinary research consortium. Both a legal analysis and the implementation of the proposed system design ESRA will be performed within the next three years. This study introduces the system design of ESRA, an end-to-end system for re-identification and anonymization of Swiss court decisions. Firstly, the re-identification system tests the safety of existing anonymizations and thus promotes privacy. Secondly, the anonymization system substantially reduces the costs of manual anonymization of court decisions and thus introduces a more comprehensive publication practice.

Keywords: artificial intelligence, courts, legal tech, named entity recognition, natural language processing, ·privacy, topic modeling

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Authors: Samuel N. Forjuoh, Marcia G. Ory, Jaewoong Won, Samuel D. Towne, Suojin Wang, Chanam Lee

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The public health burden of obesity is well established as is the influence of physical activity (PA) on the health and wellness of individuals who are obese. This study examined the influence of selected demographic, health, and socioenvironmental factors on the walking behaviors of middle-aged and older overweight and obese adults. Online and paper surveys were administered to community-dwelling overweight and obese adults aged ≥ 50 years residing in four cities in central Texas and seen by a family physician in the primary care clinic from October 2013 to June 2014. Descriptive statistics were used to characterize participants’ anthropometric and demographic data as well as their health conditions and walking, socioenvironmental, and more broadly defined PA behaviors. Then Pearson chi-square tests were used to assess differences between participants who reported walking the recommended ≥ 150 minutes for any purpose in a typical week as a proxy to meeting the U.S. Centers for Disease Control and Prevention’s PA guidelines and those who did not. Finally, logistic regression was used to predict walking the recommended ≥ 150 minutes for any purpose, controlling for covariates. The analysis was conducted in 2016. Of the total sample (n=253, survey response rate of 6.8%), the majority were non-Hispanic white (81.7%), married (74.5%), male (53.5%), and reported an annual household income of ≥ $50,000 (65.7%). Approximately, half were employed (49.6%), or had at least a college degree (51.8%). Slightly more than 1 in 5 (n=57, 22.5%) reported walking the recommended ≥150 minutes for any purpose in a typical week. The strongest predictors of walking the recommended ≥ 150 minutes for any purpose in a typical week in adjusted analysis were related to education and a high favorable perception of the neighborhood environment. Compared to those with a high school diploma or some college, participants with at least a college degree were five times as likely to walk the recommended ≥ 150 minutes for any purpose (OR=5.55, 95% CI=1.79-17.25). Walking the recommended ≥ 150 minutes for any purpose was significantly associated with participants who disagreed that there were many distracted drivers (e.g., on the cell phone while driving) in their neighborhood (OR=4.08, 95% CI=1.47-11.36) and those who agreed that there are sidewalks or protected walkways (e.g., walking trails) in their neighborhood (OR=3.55, 95% CI=1.10-11.49). Those employed were less likely to walk the recommended ≥ 150 minutes for any purpose compared to those unemployed (OR=0.31, 95% CI=0.11-0.85) as were those who reported some difficulty walking for a quarter of a mile (OR=0.19, 95% CI=0.05-0.77). Other socio-environmental factors such as having care-giver responsibilities for elders, someone to walk with, or a dog in the household as well as Walk Score™ were not significantly associated with walking the recommended ≥ 150 minutes for any purpose in a typical week. Neighborhood perception appears to be an important factor associated with the walking behaviors of middle-aged and older overweight and obese individuals. Enhancing the neighborhood environment (e.g., providing walking trails) may promote walking among these individuals.

Keywords: determinants of walking, obesity, older adults, physical activity

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Authors: Monu Ojha, Rahul Rana, Satywati Sharma, Kavya Dashora

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The global production rate of plastics has increased enormously and global demand for polyethylene resins –High-density polyethylene (HDPE), Linear low-density polyethylene (LLDPE) and Low-density polyethylene (LDPE) is expected to rise drastically, with very high value. These get accumulated in the environment, posing a potential ecological threat as they are degrading at a very slow rate and remain in the environment indefinitely. The aim of the present study was to investigate the potential of commonly found soil microbes like Bacillus subtilus, Aspergillus niger, Pseudomonas fluroscence for their ability to biodegrade LDPE in the lab on solid and liquid media conditions as well as in presence of 1% salt in the soil. This study was conducted at Indian Institute of Technology, Delhi, India from July to September where average temperature and RH (Relative Humidity) were 33 degrees Celcius and 80% respectively. It revealed that the weight loss of LDPE strip obtained from market of approximately 4x6 cm dimensions is more in liquid broth media than in solid agar media. The percentage weight loss by P. fluroscence, A. niger and B. subtilus observed after 80 days of incubation was 15.52, 9.24 and 8.99% respectively in broth media and 6.93, 2.18 and 4.76 % in agar media. The LDPE strips from same source and on the same were subjected to soil in presence of above microbes with 1% salt (NaCl: obtained from commercial table salt) with temperature and RH 33 degree Celcius and 80%. It was found that the rate of degradation increased in the soil than under lab conditions. The rate of weight loss of LDPE strips under same conditions given in lab was found to be 32.98, 15.01 and17.09 % by P. fluroscence, A. niger and B. subtilus respectively. The breaking strength was found to be 9.65N, 29N and 23.85 N for P. fluroscence, A. niger and B. subtilus respectively. SEM analysis conducted on Zeiss EVO 50 confirmed that surface of LDPE becomes physically weak after biological treatment. There was the increase in the surface roughness indicating Surface erosion of LDPE film. FTIR (Fourier-transform infrared spectroscopy) analysis of the degraded LDPE films showed stretching of aldehyde group at 3334.92 and 3228.84 cm-1,, C–C=C symmetric of aromatic ring at 1639.49 cm-1.There was also C=O stretching of aldehyde group at 1735.93 cm-1. N=O peak bend was also observed which corresponds to 1365.60 cm-1, C–O stretching of ether group at 1217.08 and 1078.21 cm-1.

Keywords: microbial degradation, LDPE, Aspergillus niger, Bacillus subtilus, Peudomonas fluroscence, common salt

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Authors: A. Zapata, Orlando Arroyo, R. Bonett

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Over the last two decades, the growing demand for housing in Latin American countries has led to the development of construction projects based on low and medium-rise buildings with thin reinforced concrete walls. This system, known as Thin Walls Reinforced Concrete Buildings (TWRCB), uses walls with thicknesses from 100 to 150 millimetres, with flexural reinforcement formed by welded wire mesh (WWM) with diameters between 5 and 7 millimetres, arranged in one or two layers. These walls often have irregular structural configurations, including combinations of rectangular shapes. Experimental and numerical research conducted in regions where this structural system is commonplace indicates inherent weaknesses, such as limited ductility due to the WWM reinforcement and thin element dimensions. Because of its complexity, numerical analyses have relied on two-dimensional models that don't explicitly account for the floor system, even though it plays a crucial role in distributing seismic forces among the resilient elements. Nonetheless, the numerical analyses assume a rigid diaphragm hypothesis. For this purpose, two study cases of buildings were selected, low-rise and mid-rise characteristics of TWRCB in Colombia. The buildings were analyzed in Opensees using the MVLEM-3D for walls and shell elements to simulate the slabs to involve the effect of coupling diaphragm in the nonlinear behaviour. Three cases are considered: a) models without a slab, b) models with rigid slabs, and c) models with flexible slabs. An incremental static (pushover) and nonlinear dynamic analyses were carried out using a set of 44 far-field ground motions of the FEMA P-695, scaled to 1.0 and 1.5 factors to consider the probability of collapse for the design base earthquake (DBE) and the maximum considered earthquake (MCE) for the model, according to the location sites and hazard zone of the archetypes in the Colombian NSR-10. Shear base capacity, maximum displacement at the roof, walls shear base individual demands and probabilities of collapse were calculated, to evaluate the effect of absence, rigid and flexible slabs in the nonlinear behaviour of the archetype buildings. The pushover results show that the building exhibits an overstrength between 1.1 to 2 when the slab is considered explicitly and depends on the structural walls plan configuration; additionally, the nonlinear behaviour considering no slab is more conservative than if the slab is represented. Include the flexible slab in the analysis remarks the importance to consider the slab contribution in the shear forces distribution between structural elements according to design resistance and rigidity. The dynamic analysis revealed that including the slab reduces the collapse probability of this system due to have lower displacements and deformations, enhancing the safety of residents and the seismic performance. The strategy of including the slab in modelling is important to capture the real effect on the distribution shear forces in walls due to coupling to estimate the correct nonlinear behaviour in this system and the adequate distribution to proportionate the correct resistance and rigidity of the elements in the design to reduce the possibility of damage to the elements during an earthquake.

Keywords: thin wall reinforced concrete buildings, coupling slab, rigid diaphragm, flexible diaphragm

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Authors: Donald Wright

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The ultimate goal of this study is to reinvigorate the philosophical underpinnings the study of urbanization with scientific data with the goal of circumventing what seems an inevitable future clash between rural and urban populations. To that end urban infrastructure must be sustainable economically, politically and ecologically over the course of several generations as cities continue to grow with the incorporation of climate refugees. Our research will provide data concerning the projected increase in population over the coming two decades in Morocco, and the population will shift from rural areas to urban centers during that period of time. As a result, urban infrastructure will need to be adapted, developed or built to fit the demand of future internal migrations from rural to urban centers in Morocco. This paper will also examine how past experiences of internally displaced people give insight into the challenges faced by future migrants and, beyond the gathering of data, how people react to internal migration. This study employs four different sets of research tools. First, a large part of this study is archival, which involves compiling the relevant literature on the topic and its complex history. This step also includes gathering data bout migrations in Morocco from public data sources. Once the datasets are collected, the next part of the project involves populating the attribute fields and preprocessing the data to make it understandable and usable by machine learning algorithms. In tandem with the mathematical interpretation of data and projected migrations, this study benefits from a theoretical understanding of the critical apparatus existing around urban development of the 20th and 21st centuries that give us insight into past infrastructure development and the rationale behind it. Once the data is ready to be analyzed, different machine learning algorithms will be experimented (k-clustering, support vector regression, random forest analysis) and the results compared for visualization of the data. The final computational part of this study involves analyzing the data and determining what we can learn from it. This paper helps us to understand future trends of population movements within and between regions of North Africa, which will have an impact on various sectors such as urban development, food distribution and water purification, not to mention the creation of public policy in the countries of this region. One of the strengths of this project is the multi-pronged and cross-disciplinary methodology to the research question, which enables an interchange of knowledge and experiences to facilitate innovative solutions to this complex problem. Multiple and diverse intersecting viewpoints allow an exchange of methodological models that provide fresh and informed interpretations of otherwise objective data.

Keywords: climate change, machine learning, migration, Morocco, urban development

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Authors: Ritika Chaturvedi

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Introduction: Sexual objectification, characterized by the reduction of an individual to a mere object of sexual desire, remains a pervasive societal issue with profound repercussions on individual well-being. Such experiences, often rooted in systemic and cultural norms, have long-lasting implications for mental and emotional health. This study aims to explore the intricate relationship between experiences of sexual objectification and insidious trauma, further investigating the potential moderating effects of overexcitabilities as proposed by Dabrowski's theory of positive disintegration. Methodology: The research involved a comprehensive cohort of 204 women, spanning ages from 18 to 65 years. Participants were tasked with completing self-administered questionnaires designed to capture their experiences with sexual objectification. Additionally, the questionnaire assessed symptoms indicative of insidious trauma and explored overexcitabilities across five distinct domains: emotional, intellectual, psychomotor, sensory, and imaginational. Employing advanced statistical techniques, including multiple regression and moderation analysis, the study sought to decipher the intricate interplay among these variables. Findings: The study's results revealed a compelling positive correlation between experiences of sexual objectification and the onset of symptoms indicative of insidious trauma. This correlation underscores the profound and detrimental effects of sexual objectification on an individual's psychological well-being. Interestingly, the moderation analyses introduced a nuanced understanding, highlighting the differential roles of various overexcitabilities. Specifically, emotional, intellectual, and sensual overexcitabilities were found to exacerbate trauma symptomatology. In contrast, psychomotor overexcitability emerged as a protective factor, demonstrating a mitigating influence on the relationship between sexual objectification and trauma. Implications: The study's findings hold significant implications for a diverse array of stakeholders, encompassing mental health practitioners, educators, policymakers, and advocacy groups. The identified moderating effects of overexcitabilities emphasize the need for tailored interventions that consider individual differences in coping and resilience mechanisms. By recognizing the pivotal role of overexcitabilities in modulating the traumatic consequences of sexual objectification, this research advocates for the development of more nuanced and targeted support frameworks. Moreover, the study underscores the importance of continued research endeavors to unravel the intricate mechanisms and dynamics underpinning these relationships. Such endeavors are crucial for fostering the evolution of informed, evidence-based interventions and strategies aimed at mitigating the adverse effects of sexual objectification and promoting holistic well-being.

Keywords: sexual objectification, insidious trauma, emotional overexcitability, intellectual overexcitability, sensual overexcitability, psychomotor overexcitability, imaginational overexcitability

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Authors: Rupak Kumar Sarma, Ratul Saikia

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Macrophytes encompass major functional group in eutrophic wetland ecosystems. As a key functional element of freshwater lakes, they play a crucial role in regulating various wetland biogeochemical cycles, as well as maintain the biodiversity at the ecosystem level. The high carbon-rich underground biomass of macrophyte populations may harbour diverse microbial community having significant potential in maintaining different biogeochemical cycles. The present investigation was designed to study the macrophyte-microbe interaction in coupled nitrification and denitrification, considering Deepor Beel Lake (a Ramsar conservation site) of North East India as a model eutrophic system. Highly eutrophic sites of Deepor Beel were selected based on sediment oxygen demand and inorganic phosphorus and nitrogen (P&N) concentration. Sediment redox potential and depth of the lake was chosen as the benchmark for collecting the plant and sediment samples. The average highest depth in winter (January 2016) and summer (July 2016) were recorded as 20ft (6.096m) and 35ft (10.668m) respectively. Both sampling depth and sampling seasons had the distinct effect on variation in macrophyte community composition. Overall, the dominant macrophytic populations in the lake were Nymphaea alba, Hydrilla verticillata, Utricularia flexuosa, Vallisneria spiralis, Najas indica, Monochoria hastaefolia, Trapa bispinosa, Ipomea fistulosa, Hygrorhiza aristata, Polygonum hydropiper, Eichhornia crassipes and Euryale ferox. There was a distinct correlation in the variation of major sediment physicochemical parameters with change in macrophyte community compositions. Quantitative estimation revealed an almost even accumulation of nitrate and nitrite in the sediment samples dominated by the plant species Eichhornia crassipes, Nymphaea alba, Hydrilla verticillata, Vallisneria spiralis, Euryale ferox and Monochoria hastaefolia, which might have signified a stable nitrification and denitrification process in the sites dominated by the selected aquatic plants. This was further examined by a systematic analysis of microbial populations through culture dependent and independent approach. Culture-dependent bacterial community study revealed the higher population of nitrifiers and denitrifiers in the sediment samples dominated by the six macrophyte species. However, culture-independent study with bacterial 16S rDNA V3-V4 metagenome sequencing revealed the overall similar type of bacterial phylum in all the sediment samples collected during the study. Thus, there might be the possibility of uneven distribution of nitrifying and denitrifying molecular markers among the sediment samples collected during the investigation. The diversity and abundance of the nitrifying and denitrifying molecular markers in the sediment samples are under investigation. Thus, the role of different aquatic plant functional types in microorganism mediated nitrogen cycle coupling could be screened out further from the present initial investigation.

Keywords: denitrification, macrophyte, metagenome, microorganism, nitrification

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Authors: Margareth Guimaraes Lima, Marilisa Berti A. Barros, Deborah Carvalho Malta

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The relationship between physical activity (PA) and depression has been investigated, in both, observational and clinical studies: PA can integrate the treatments for depression; the physical inactivity (PI) may contribute to increase depression symptoms; and on the other hand, emotional problems can decrease PA. The main of this study was analyze the association among leisure and transportation PI and time watching television (TV) according to depression (minor and major), evaluated with the Patient Health Questionnaire (PHQ-9). The association was also analyzed by gender. This is a cross-sectional study. Data were obtained from the National Health Survey 2013 (PNS), performed with representative sample of the Brazilian adult population, in 2013. The PNS collected information from 60,202 individuals, aged 18 years or more. The independent variable were: leisure time physical inactivity (LTPI), considering inactive or insufficiently actives (categories were linked for analyzes), those who do not performed a minimum of 150 or 74 minutes of moderate or vigorous LTPA, respectively, by week; transportation physical inactivity (TPI), individuals who did not reached 150 minutes, by week, travelling by bicycle or on foot to work or other activities; daily time watching TV > 5 hours. The principal independent variable was depression, identified by PHQ-9. Individuals were classified with major depression, with > 5 symptoms, more than seven days, but one of the symptoms was “depressive mood” or “lack of interest or pleasure”. The others had minor depression. The variables used to adjustment were gender, age, schooling and chronic disease. The prevalence of LTPI, TPI and TV time were estimated according to depression, and differences were tested with Chi-Square test. Adjusted prevalence ratios were estimated using multiple Poisson regression models. The analyzes also had stratification by gender. Mean age of the studied population was 42.9 years old (CI95%:42.6-43.2) and 52.9% were women. 77.5% and 68.1% were inactive or insufficiently active in leisure and transportation, respectively and 13.3% spent time watching TV 5 > hours. 6% and 4.1% of the Brazilian population were diagnosed with minor or major depression. LTPI prevalence was 5% and 9% higher among individuals with minor and major depression, respectively, comparing with no depression. The prevalence of TPI was 7% higher in those with major depression. Considering larger time watching TV, the prevalence was 45% and 74% higher among those with minor and major depression, respectively. Analyzing by gender, the associations were greater in men than women and TPI was note be associated, in women. The study detected the higher prevalence of leisure time physical inactivity and, especially, time spent watching TV, among individuals with major and minor depression, after to adjust for a number of potential confounding factors. TPI was only associated with major disorders and among men. Considering the cross-sectional design of the research, these associations can point out the importance of the mental problems control of the population to increase PA and decrease the sedentary lifestyle; on the other hand, the study highlight the need of interventions by encouraging people with depression, to practice PA, even to transportation.

Keywords: depression, physical activity, PHQ-9, sedentary lifestyle

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Authors: Pellecchia M. T., Savarese G., Carpinelli L., Calabrese M.

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Introduction: Parkinson's disease (PD) is characterized by a progressive loss of autonomy which undoubtedly has a significant impact on the quality of life of caregivers, and parents are the main informal caregivers. Caring for a person with PD is associated with an increased risk of psychiatric morbidity and persistent anxiety-depressive distress. The aim of the study is to investigate the burden on caregivers of patients with PD, through the use of multidimensional scales and to identify their personological and environmental determinants. Methods: The study has been approved by the Ethic Committee of the University of Salerno and informed consent for participation to the study was obtained from patients and their caregivers. The study was conducted at the Neurology Department of the A.O.U. "San Giovanni di Dio and Ruggi D’Aragona" of Salerno between September 2020 and May 2021. Materials: The questionnaires used were: a) Caregiver Burden Inventory - CBI a questionnaire of 24 items that allow identifying five sub-categories of burden (objective, psychological, physical, social, emotional); b) Depression Anxiety Stress Scales Short Version - DASS-21 questionnaire consisting of 21 items and valid in examining three distinct but interrelated areas (depression, anxiety and stress); c) Family Strain Questionnaire Short Form - FSQ-SF is a questionnaire of 30 items grouped in areas of increasing psychological risk (OK, R, SR, U); d) Zarit Caregiver Burden Inventory - ZBI, consisting of 22 items based on the analysis of two main factors: personal stress and pressure related to his role; e) Life Satisfaction, a single item that aims to evaluate the degree of life satisfaction in a global way using a 0-100 Likert scale. Findings: N ° 29 caregivers (M age = 55.14, SD = 9.859; 69% F) participated in the study. 20.6% of the sample had severe and severe burden (CBI score = M = 26.31; SD = 22.43) and 13.8% of participants had moderate to severe burden (ZBI). The FSQ-SF highlighted a minority of caregivers who need psychological support, in some cases urgent (Area SR and Area U). The DASS-21 results show a prevalence of stress-related symptoms (M = 10.90, SD = 10.712) compared to anxiety (M = 7.52, SD = 10.752) and depression (M = 8, SD = 10.876). There are significant correlations between some specific variables and mean test scores: retired caregivers report higher ZBI scores (p = 0.423) and lower Life Satisfaction levels (p = -0.460) than working caregivers; years of schooling show a negative linear correlation with the ZBI score (p = -0.491). The T-Test indicates that caregivers of patients with cognitive impairment are at greater risk than those of patients without cognitive impairment. Conclusions: It knows the factors that affect the burden the most would allow for early recognition of risky situations and caregivers who would need adequate support.

Keywords: anxious-depressive axis, caregivers’ burden, Parkinson’ disease, psychological risks

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Authors: Peter. M. Kusen, Georg Wandrey, Christopher Probst, Dietrich Kohlheyer, Jochen Buchs, Jorg Pietruszkau

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Light as a stimulus provides the capability to develop regulation techniques for customizable gene expression. A great advantage is the extremely flexible and accurate dosing that can be performed in a non invasive and sterile manner even for high throughput technologies. Therefore, light regulation in a multiwell microbioreactor system was realized providing the opportunity to control gene expression with outstanding complexity. A light-regulated gene expression system in Saccharomyces cerevisiae was designed applying the strategy of caged compounds. These compounds are photo-labile protected and therefore biologically inactive regulator molecules which can be reactivated by irradiation with certain light conditions. The “caging” of a repressor molecule which is consumed after deprotection was essential to create a flexible expression system. Thereby, gene expression could be temporally repressed by irradiation and subsequent release of the active repressor molecule. Afterwards, the repressor molecule is consumed by the yeast cells leading to reactivation of gene expression. A yeast strain harboring a construct with the corresponding repressible promoter in combination with a fluorescent marker protein was applied in a Photo-BioLector platform which allows individual irradiation as well as online fluorescence and growth detection. This device was used to precisely control the repression duration by adjusting the amount of released repressor via different irradiation times. With the presented screening platform the regulation of complex expression procedures was achieved by combination of several repression/derepression intervals. In particular, a stepwise increase of temporally-constant expression levels was demonstrated which could be used to study concentration dependent effects on cell functions. Also linear expression rates with variable slopes could be shown representing a possible solution for challenging protein productions, whereby excessive production rates lead to misfolding or intoxication. Finally, the very flexible regulation enabled accurate control over the expression induction, although we used a repressible promoter. Summing up, the continuous online regulation of gene expression has the potential to synchronize gene expression levels to optimize metabolic flux, artificial enzyme cascades, growth rates for co cultivations and many other applications addicted to complex expression regulation. The developed light-regulated expression platform represents an innovative screening approach to find optimization potential for production processes.

Keywords: caged-compounds, gene expression regulation, optogenetics, photo-labile protecting group

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Authors: Saheed Shittu, Lolwa Alansari, Fahed Nattouf, Tawa Olukade, Naji Abdallah, Tamara Alshdafat, Sarra Amdouni

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Cesarean sections (CS), a highly regarded surgical intervention for improving fetal-maternal outcomes and serving as an integral part of emergency obstetric services, are not without complications. Although CS has many advantages, it poses significant risks to both mother and child and increases healthcare expenditures in the long run. The escalating global prevalence of CS, coupled with variations in rates among immigrant populations, has prompted an inquiry into the correlation between CS rates and the nationalities of women undergoing deliveries at Al-Wakra Hospital (AWH), Qatar's second-largest public maternity hospital. This inquiry is motivated by the notable CS rate of 36%, deemed high in comparison to the 34% recorded across other Hamad Medical Corporation (HMC) maternity divisions This is Qatar's first comprehensive investigation of Caesarean section rates and nationalities. A retrospective cross-sectional study was conducted, and data for all births delivered in 2019 were retrieved from the hospital's electronic medical records. The CS rate, the crude rate, and adjusted risks of Caesarean delivery for mothers from each nationality were determined. The common indications for CS were analysed based on nationality. The association between nationality and Caesarean rates was examined using binomial logistic regression analysis considering Qatari women as a standard reference group. The correlation between the CS rate in the country of nationality and the observed CS rate in Qatar was also examined using Pearson's correlation. This study included 4,816 births from 69 different nationalities. CS was performed in 1767 women, equating to 36.5%. The nationalities with the highest CS rates were Egyptian (49.6%), Lebanese (45.5%), Filipino and Indian (both 42.2%). Qatari women recorded a CS rate of 33.4%. The major indication for elective CS was previous multiple CS (39.9%) and one prior CS, where the patient declined vaginal birth after the cesarean (VBAC) option (26.8%). A distinct pattern was noticed: elective CS was predominantly performed on Arab women, whereas emergency CS was common among women of Asian and Sub-Saharan African nationalities. Moreover, a significant correlation was found between the CS rates in Qatar and the women's countries of origin. Also, a high CS rate was linked to instances of previous CS. As a result of these insights, strategic interventions were successfully implemented at the facility to mitigate unwarranted CS, resulting in a notable reduction in CS rate from 36.5% in 2019 to 34% in 2022. This proves the efficacy of the meticulously researched approach. The focus has now shifted to reducing primary CS rates and facilitating well-informed decisions regarding childbirth methods.

Keywords: maternal nationality, caesarean section rate variation, migrants, high-income country

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Authors: Kassahun Tilahun

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The purpose of the study was two-fold: to examine the socio-demographic and psychological predictors of well-being and formulate a socio-culturally sound approach explaining the meaning and experience of psychological well-being among Ethiopian adults. Ryan and Deci’s Self-Determination Theory was duly considered as a theoretical framework of the study. The study followed a sequential explanatory mixed method design. Both quantitative and qualitative data were obtained, via scales and open-ended questionnaires, from 438 civil servants working in Addis Ababa. 30 interviews were also conducted to gain further information. An in-depth analysis of the reliability and validity of instruments was made before employing them to the main study. The results showed that adults were better off in both their scores of psychological and subjective well-being. Besides, adults’ well-being was found to be quite a function of their gender, age, marital status, educational level and household income. Males had a healthier psychological well-being status than females, where as females were better in their subjective well-being. A significant difference in psychological well-being was also observed between emerging and young adults, in favor of the young; and between cohabitated and married adults, married being advantageous. A significant difference in subjective well-being measures was also noticed among single, cohabitated and married adults, in favor of the married adults in all measures. The finding revealed that happiness level of adults decrease as their educational status increases while the reverse is true to psychological well-being. Besides, as adults’ household income boosts, so do their psychological well-being and satisfaction in life. The regression analysis also produced significant independent contributions of household income to overall well-being of adults. As such, subjective well-being was significantly predicted by dummy variable of sex and marital status. Likewise, the agreeableness, conscientiousness, neuroticism and openness dimensions of personality were notable significant predictors of adults’ psychological well-being where as extraversion and agreeableness were significant predictors of their subjective well-being. Religiosity was also a significant predictor of adults’ psychological well-being. Besides, adults’ well-being was significantly predicted by the interaction between conscientiousness and religiosity. From goal pursuit dimensions, attainment of extrinsic life goals was a significant predictor of both psychological and subjective well-being. Importance and attainment of intrinsic life goals also significantly predicts adults’ psychological well-being. Finally, the subjective well-being of adults was significantly predicted by environmental mastery, positive relations with others, self-acceptance and overall psychological well-being scores of adults. The thematic analysis identified five major categories of themes, which are essential in explaining the psychological well-being of Ethiopian adults. These were; socio-cultural harmony, social cohesion, security, competence and accomplishment, and the self. Detailed discussion on the rational for including these themes was made and appropriate implications were proposed. Researchers are encouraged to expand the findings of this research and in turn develop a suitable approach taping the psychological well-being of adults living in countries like Ethiopia.

Keywords: psychological well-being, subjective well-being, adulthood, Ethiopia

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Authors: Marina Nechayeva, Malgorzata Marciniak, Vladimir Przhebelskiy, A. Dragutan, S. Lamichhane, S. Oikawa

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This presentation is a progress report on a faculty-student research collaboration at CUNY LaGuardia Community College (LaGCC) aimed at designing a small horizontal axis wind turbine optimized for the wind patterns on the roof of our campus. Our project combines statistical and engineering research. Our wind modeling protocol is based upon a recent wind study by a faculty-student research group at MIT, and some of our blade design methods are adopted from a senior engineering project at CUNY City College. Our use of genetic algorithms has been inspired by the work on small wind turbines’ design by David Wood. We combine these diverse approaches in our interdisciplinary project in a way that has not been done before and improve upon certain techniques used by our predecessors. We employ several estimation methods to determine the best fitting parametric probability distribution model for the local wind speed data obtained through correlating short-term on-site measurements with a long-term time series at the nearby airport. The model serves as a foundation for engineering research that focuses on adapting and implementing genetic algorithms (GAs) to engineering optimization of the wind turbine design using Blade Element Momentum Theory. GAs are used to create new airfoils with desirable aerodynamic specifications. Small scale models of best performing designs are 3D printed and tested in the wind tunnel to verify the accuracy of relevant calculations. Genetic algorithms are applied to selected airfoils to determine the blade design (radial cord and pitch distribution) that would optimize the coefficient of power profile of the turbine. Our approach improves upon the traditional blade design methods in that it lets us dispense with assumptions necessary to simplify the system of Blade Element Momentum Theory equations, thus resulting in more accurate aerodynamic performance calculations. Furthermore, it enables us to design blades optimized for a whole range of wind speeds rather than a single value. Lastly, we improve upon known GA-based methods in that our algorithms are constructed to work with XFoil generated airfoils data which enables us to optimize blades using our own high glide ratio airfoil designs, without having to rely upon available empirical data from existing airfoils, such as NACA series. Beyond its immediate goal, this ongoing project serves as a training and selection platform for CUNY Research Scholars Program (CRSP) through its annual Aerodynamics and Wind Energy Research Seminar (AWERS), an undergraduate summer research boot camp, designed to introduce prospective researchers to the relevant theoretical background and methodology, get them up to speed with the current state of our research, and test their abilities and commitment to the program. Furthermore, several aspects of the research (e.g., writing code for 3D printing of airfoils) are adapted in the form of classroom research activities to enhance Calculus sequence instruction at LaGCC.

Keywords: engineering design optimization, genetic algorithms, horizontal axis wind turbine, wind modeling

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Authors: Paula Quiterio, Arlete Apolinario, Celia T. Sousa, Joao Azevedo, Paula Dias, Adelio Mendes, Joao P. Araujo

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Nowadays one of the mankind's greatest challenges has been the supply of low-cost and environmentally friendly energy sources as an alternative to non-renewable fossil fuels. Hydrogen has been considered a promising solution, representing a clean and low-cost fuel. It can be produced directly from clean and abundant resources, such as sunlight and water, using photoelectrochemical cells (PECs), in a process that mimics the nature´s photosynthesis. Hematite (alpha-Fe2O3) has attracted considerable attention as a promising photoanode for solar water splitting, due to its high chemical stability, nontoxicity, availability and low band gap (2.2 eV), which allows reaching a high thermodynamic solar-to-hydrogen efficiency of 16.8 %. However, the main drawbacks of hematite such as the short hole diffusion length and the poor conductivity that lead to high electron-hole recombination result in significant PEC efficiency losses. One strategy to overcome these limitations and to increase the PEC efficiency is to use 1D nanostructures, such as nanotubes (NTs) and nanowires (NWs), which present high aspect ratios and large surface areas providing direct pathways for electron transport up to the charge collector and minimizing the recombination losses. In particular, due to the ultrathin walls of the NTs, the holes can reach the surface faster than in other nanostructures, representing a key factor for the NTs photoresponse. In this work, we prepared hematite NWs and NTs, respectively by hydrothermal process and electrochemical anodization. For hematite NWs growing, we studied the effect of variable hydrothermal conditions, different annealing temperatures and time, and the use of Ti and Sn dopants on the morphology and PEC performance. The crystalline phase characterization by X-ray diffraction was crucial to distinguish the formation of hematite and other iron oxide phases, alongside its effect on the photoanodes conductivity and consequent PEC efficiency. The conductivity of the as-prepared NWs is very low, in the order of 10-5 S cm-1, but after doping and annealing optimization it increased by a factor of 105. A high photocurrent density of 1.02 mA cm-2 at 1.45 VRHE was obtained under simulated sunlight, which is a very promising value for this kind of hematite nanostructures. The stability of the photoelectrodes was also tested, presenting good stability after several J-V measurements over time. The NTs, synthesized by fast anodizations with potentials ranging from 20-100 V, presented a linear growth of the NTs pore walls, with very low thicknesses from 10 - 18 nm. These preliminary results are also very promising for the use of hematite photoelectrodes on PEC hydrogen applications.

Keywords: hematite, nanotubes, nanowires, photoelectrochemical cells

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Authors: Saman Ahani, Aboozar Dehghan, Roham Vali, Hamid Salehian, Amin Ebrahimi

Abstract:

Pulsed-wave (PW) doppler ultrasonography is a non-invasive, relatively accurate imaging technique that can measure blood speed. The imaging could be obtained via the common carotid artery, as one of the main vessels supplying the blood of vital organs. In horses, factors such as susceptibility to depression of the cardiovascular system and their large muscular mass have rendered them vulnerable to changes in blood speed. One of the most important factors causing blood velocity changes is the administration of anesthetic drugs, including Ketamine and Acepromazine. Thus, in this study, the Pulsed-wave doppler technique was performed to assess the highest blood velocity in the common carotid artery following administration of Ketamine and Acepromazine. Six male and six female healthy Kurdish horses weighing 351 ± 46 kg (mean ± SD) and aged 9.2 ± 1.7 years (mean ± SD) were housed under animal welfare guidelines. After fasting for six hours, the normal blood flow velocity in the common carotid artery was measured using a Pulsed-wave doppler ultrasonography machine (BK Medical, Denmark), and a high-frequency linear transducer (12 MHz) without applying any sedative drugs as a control group. The same procedure was repeated after each individual received the following medications: 1.1, 2.2 mg/kg Ketamine (Pfizer, USA), and 0.5, 1 mg/kg Acepromizine (RACEHORSE MEDS, Ukraine), with an interval of 21 days between the administration of each dose and/or drug. The ultrasonographic study was done five (T5) and fifteen (T15) minutes after injecting each dose intravenously. Lastly, the statistical analysis was performed using SPSS software version 22 for Windows and a P value less than 0.05 was considered to be statistically significant. Five minutes after administration of Ketamine (1.1, 2.2 mg/kg) in both male and female horses, the blood velocity decreased to 38.44, 34.53 cm/s in males, and 39.06, 34.10 cm/s in females in comparison to the control group (39.59 and 40.39 cm/s in males and females respectively) while administration of 0.5 mg/kg Acepromazine led to a significant rise (73.15 and 55.80 cm/s in males and females respectively) (p<0.05). It means that the most drastic change in blood velocity, regardless of gender, refers to the latter dose/drug. In both medications and both genders, the increase in doses led to a decrease in blood velocity compared to the lower dose of the same drug. In all experiments in this study, the blood velocity approached its normal value at T15. In another study comparing the blood velocity changes affected by Ketamine and Acepromazine through femoral arteries, the most drastic changes were attributed to Ketamine; however, in this experiment, the maximum blood velocity was observed following administration of Acepromazine via the common carotid artery. Therefore, further experiments using the same medications are suggested using Pulsed-wave doppler measuring the blood velocity changes in both femoral and common carotid arteries simultaneously.

Keywords: Acepromazine, common carotid artery, horse, ketamine, pulsed-wave doppler ultrasonography

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Authors: Ayten Ekin Meşe, Selahattin Şentürk, Melike Duvanoğlu

Abstract:

Petroleum refineries are a highly complex process industry with continuous production and high operating costs. Physical separation of crude oil starts with the crude oil distillation unit, continues with various conversion and purification units, and passes through many stages until obtaining the final product. To meet the desired product specification, process parameters are strictly followed. To be able to ensure the quality of distillates, routine analyses are performed in quality control laboratories based on appropriate international standards such as American Society for Testing and Materials (ASTM) standard methods and European Standard (EN) methods. The cut point of distillates in the crude distillation unit is very crucial for the efficiency of the upcoming processes. In order to maximize the process efficiency, the determination of the quality of distillates should be as fast as possible, reliable, and cost-effective. In this sense, an alternative study was carried out on the crude oil distillation unit that serves the entire refinery process. In this work, studies were conducted with three different crude oil distillates which are Light Straight Run Naphtha (LSRN), Heavy Straight Run Naphtha (HSRN), and Kerosene. These products are named after separation by the number of carbons it contains. LSRN consists of five to six carbon-containing hydrocarbons, HSRN consist of six to ten, and kerosene consists of sixteen to twenty-two carbon-containing hydrocarbons. Physical properties of three different crude distillation unit products (LSRN, HSRN, and Kerosene) were determined using Near-Infrared Spectroscopy with multivariate calibration. The absorbance spectra of the petroleum samples were obtained in the range from 10000 cm⁻¹ to 4000 cm⁻¹, employing a quartz transmittance flow through cell with a 2 mm light path and a resolution of 2 cm⁻¹. A total of 400 samples were collected for each petroleum sample for almost four years. Several different crude oil grades were processed during sample collection times. Extended Multiplicative Signal Correction (EMSC) and Savitzky-Golay (SG) preprocessing techniques were applied to FT-NIR spectra of samples to eliminate baseline shifts and suppress unwanted variation. Two different multivariate calibration approaches (Partial Least Squares Regression, PLS and Genetic Inverse Least Squares, GILS) and an ensemble model were applied to preprocessed FT-NIR spectra. Predictive performance of each multivariate calibration technique and preprocessing techniques were compared, and the best models were chosen according to the reproducibility of ASTM reference methods. This work demonstrates the developed models can be used for routine analysis instead of conventional analytical methods with over 90% accuracy.

Keywords: crude distillation unit, multivariate calibration, near infrared spectroscopy, data preprocessing, refinery

Procedia PDF Downloads 134

Authors: Aleksandr I. Korobov, Natalia V. Shirgina, Aleksey I. Kokshaiskiy

Abstract:

The transformation of two types of acoustic waves can occur on a flat interface between two solids at oblique incidence of longitudinal and shear bulk acoustic waves (BAW). This paper presents the results of experimental studies of the properties of reflection and propagation of longitudinal wave and generation of second and third longitudinal and shear harmonics of BAW at oblique incidence of longitudinal BAW on a flat rough boundary between two solids. The experimental sample was a rectangular isosceles pyramid made of D16 aluminum alloy with the plane parallel bases cylinder made of D16 aluminum alloy pressed to the base. The piezoelectric lithium niobate transducer with a resonance frequency of 5 MHz was secured to one face of the pyramid to generate a longitudinal wave. Longitudinal waves emitted by this transducer felt at an angle of 45° to the interface between two solids and reflected at the same angle. On the opposite face of the pyramid, and on the flat side of the cylinder was attached longitudinal transducer with resonance frequency of 10 MHz or the shear transducer with resonance frequency of 15 MHz. These transducers also effectively received signal at a frequency of 5 MHz. In the spectrum of the transmitted and reflected BAW was observed shear and longitudinal waves at a frequency of 5 MHz, as well as longitudinal harmonic at a frequency harmonic of 10 MHz and a shear harmonic at frequency of 15 MHz. The effect of reversing changing of external pressure applied to the rough interface between two solids on the value of the first and higher harmonics of the BAW at oblique incidence on the interface of the longitudinal BAW was experimentally investigated. In the spectrum of the reflected signal from the interface, there was a decrease of amplitudes of the first harmonics of the signal, and non-monotonic dependence of the second and third harmonics of shear wave with an increase of the static pressure applied to the interface. In the spectrum of the transmitted signal growth of the first longitudinal and shear harmonic amplitude and non-monotonic dependence - first increase and then decrease in the amplitude of the second and third longitudinal shear harmonic with increasing external static pressure was observed. These dependencies were hysteresis at reversing changing of external pressure. When pressure applied to the border increased, acoustic contact between the surfaces improves. This increases the energy of the transmitted elastic wave and decreases the energy of the reflected wave. The second longitudinal acoustic harmonics generation was associated with the Hertz nonlinearity on the interface of two pressed rough surfaces, the generation of the third harmonic was caused by shear hysteresis nonlinearity due to dry friction on a rough interface. This study was supported by the Russian Science Foundation (project №14-22-00042).

Keywords: generation of acoustic harmonics, hysteresis nonlinearity, Hertz nonlinearity, transformation of acoustic waves

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Authors: Saheed A. Adekola, Mabel A. Charles-Davies, Ridwan A. Adekola

Abstract:

Background: Testosterone is a known androgenic and anabolic steroid, primarily secreted in the testes. It plays an important role in the development of testes and prostate and has a range of biological actions. There is evidence that exposure to mixed chemicals in the workplace leads to the generation of free radicals and inadequate antioxidants leading to oxidative stress, which may serve as an early indicator of a pathophysiologic state. Based on findings, testosterone shows direct antioxidant effects by increasing the activities of antioxidant enzymes like glutathione peroxidase, thus indirectly contributing to antioxidant capacity. Objective: To evaluate the antioxidant role of testosterone as well as the relationship between testosterone and oxidative stress biomarkers in males exposed to mixed chemicals in the automobile repair community. Methods: The study included 43 participants aged 22- 60years exposed to mixed chemicals (EMC) from the automobile repair community. Forty (40) apparently healthy, unexposed, age-matched controls were recruited after informed consent. Demographic, sexual and anthropometric characteristics were obtained from pre-test structured questionnaires using standard methods. Blood samples (10mls) were collected from each subject into plain bottles and sera obtained were used for biochemical analyses. Serum levels of testosterone and luteinizing hormone (LH) were determined by enzyme immunoassay method, EIA (Immunometrics UK.LTD). Levels of total antioxidant capacity (TAC), total plasma peroxide (TPP), Malondialdehyde (MDA), hydrogen peroxide (H2O2), glutathione peroxide (GPX), superoxide dismutase (SOD), glutathione-S-transferase (GST), and reduced glutathione (GSH) were determined using spectrophotometric methods respectively. Results obtained were analyzed using the Student’s t-test and Chi-square test for quantitative variables and qualitative variables respectively. Multiple regression was used to find associations and relationships between the variables. Results: Significant higher concentrations of TPP, MDA, OSI, H2O2 and GST were observed in EMC compared with controls (p < 0.001). Within EMC, significantly higher levels of testosterone, LH and TAC were observed in eugonadic when compared with hypogonadic participants (p < 0.001). Diastolic blood pressure, waist circumference, waist height ratio and waist hip ratio were significantly higher in participants EMC compared with the controls. Sexual history and dietary intake showed that the controls had normal erection during sex and took more vegetables in their diet which may therefore be beneficial. Conclusion: The significantly increased levels of total antioxidant capacity in males exposed to mixed chemicals despite their exposure may probably reflect the contributory antioxidant role testosterone that prevents oxidative stress.

Keywords: mixed chemicals, oxidative stress, antioxidant, hypogonadism testosterone

Procedia PDF Downloads 146