Search results for: water distribution networks

Authors: Orkide Donma, Mustafa M. Donma

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Association between insulin resistance (IR) and hematological parameters has long been a matter of interest. Within this context, body mass index (BMI), red blood cells, white blood cells and platelets were involved in this discussion. Parameters related to platelets associated with IR may be useful indicators for the identification of IR. Platelet indices such as mean platelet volume (MPV), platelet distribution width (PDW) and plateletcrit (PCT) are being questioned for their possible association with IR. The aim of this study was to investigate the association between platelet (PLT) count as well as PLT indices and the surrogate indices used to determine IR in morbid obese (MO) children. A total of 167 children participated in the study. Three groups were constituted. The number of cases was 34, 97 and 36 children in the normal BMI, MO and metabolic syndrome (MetS) groups, respectively. Sex- and age-dependent BMI-based percentile tables prepared by World Health Organization were used for the definition of morbid obesity. MetS criteria were determined. BMI values, homeostatic model assessment for IR (HOMA-IR), alanine transaminase-to-aspartate transaminase ratio (ALT/AST) and diagnostic obesity notation model assessment laboratory (DONMA-lab) index values were computed. PLT count and indices were analyzed using automated hematology analyzer. Data were collected for statistical analysis using SPSS for Windows. Arithmetic mean and standard deviation were calculated. Mean values of PLT-related parameters in both control and study groups were compared by one-way ANOVA followed by Tukey post hoc tests to determine whether a significant difference exists among the groups. The correlation analyses between PLT as well as IR indices were performed. Statistically significant difference was accepted as p-value < 0.05. Increased values were detected for PLT (p < 0.01) and PCT (p > 0.05) in MO group compared to those observed in children with N-BMI. Significant increases for PLT (p < 0.01) and PCT (p < 0.05) were observed in MetS group in comparison with the values obtained in children with N-BMI (p < 0.01). Significantly lower MPV and PDW values were obtained in MO group compared to the control group (p < 0.01). HOMA-IR (p < 0.05), DONMA-lab index (p < 0.001) and ALT/AST (p < 0.001) values in MO and MetS groups were significantly increased compared to the N-BMI group. On the other hand, DONMA-lab index values also differed between MO and MetS groups (p < 0.001). In the MO group, PLT was negatively correlated with MPV and PDW values. These correlations were not observed in the N-BMI group. None of the IR indices exhibited a correlation with PLT and PLT indices in the N-BMI group. HOMA-IR showed significant correlations both with PLT and PCT in the MO group. All of the three IR indices were well-correlated with each other in all groups. These findings point out the missing link between IR and PLT activation. In conclusion, PLT and PCT may be related to IR in addition to their identities as hemostasis markers during morbid obesity. Our findings have suggested that DONMA-lab index appears as the best surrogate marker for IR due to its discriminative feature between morbid obesity and MetS.

Keywords: children, insulin resistance, metabolic syndrome, plateletcrit, platelet indices

Procedia PDF Downloads 109

Authors: M. R. Akbari, M. Sadeghi, R. Faghihi, M. A. Mosleh-Shirazi, A. R. Khorrami-Moghadam

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Proton radiotherapy (PRT) is becoming an established treatment modality for cancer. The localized tumors, the same as undifferentiated thyroid tumors are insufficiently handled by conventional radiotherapy, while protons would propose the prospect of increasing the tumor dose without exceeding the tolerance of the surrounding healthy tissues. In spite of relatively high advantages in giving localized radiation dose to the tumor region, in proton therapy, secondary neutron production can have significant contribution on integral dose and lessen advantages of this modality contrast to conventional radiotherapy techniques. Furthermore, neutrons have high quality factor, therefore, even a small physical dose can cause considerable biological effects. Measuring of this neutron dose is a very critical step in prediction of secondary cancer incidence. It has been found that FLUKA Monte Carlo code simulations have been used to evaluate dose due to secondaries in proton therapy. In this study, first, by validating simulated proton beam range in water phantom with CSDA range from NIST for the studied proton energy range (34-54 MeV), a proton therapy in thyroid gland cancer was simulated using FLUKA code. Secondary neutron dose equivalent of some organs and tissues after the target volume caused by 34 and 54 MeV proton interactions were calculated in order to evaluate secondary cancer incidence. A multilayer cylindrical neck phantom considering all the layers of neck tissues and a proton beam impinging normally on the phantom were also simulated. Trachea (accompanied by Larynx) had the greatest dose equivalent (1.24×10-1 and 1.45 pSv per primary 34 and 54 MeV protons, respectively) among the simulated tissues after the target volume in the neck region.

Keywords: FLUKA code, neutron dose equivalent, proton therapy, thyroid gland

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Authors: Shamsul Chowdhury

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The objective of this paper is to present the detailed analysis of the turbulent wave boundary layer produced by progressive finite-amplitude waves theory. Most of the works have done for the mass transport in the turbulent boundary layer assuming the eddy viscosity is not time varying, where the sediment movement is induced by the mean velocity. Near the ocean bottom, the waves produce a thin turbulent boundary layer, where the flow is highly rotational, and shear stress associated with the fluid motion cannot be neglected. The magnitude and the predominant direction of the sediment transport near the bottom are known to be closely related to the flow in the wave induced boundary layer. The magnitude of water particle velocity at the Crest phase differs from the one of the Trough phases due to the non-linearity of the waves, which plays an important role to determine the sediment movement. The non-linearity of the waves become predominant in the surf zone area, where the sediment movement occurs vigorously. Therefore, in order to describe the flow near the bottom and relationship between the flow and the movement of the sediment, the analysis was done using the non-linear boundary layer equation and the finite amplitude wave theory was applied to represent the velocity fields in the turbulent wave boundary layer. At first, the calculation was done for turbulent wave boundary layer by two-dimensional model where throughout the calculation is non-linear. But Stokes second order wave profile is adopted at the upper boundary. The calculated profile was compared with the experimental data. Finally, the calculation is done based on various modes of the velocity and turbulent energy. The mean velocity is found to differ from condition of the relative depth and the roughness. It is also found that due to non-linearity, the absolute value for velocity and turbulent energy as well as Reynolds stress are asymmetric. The mean velocity of the laminar boundary layer is always positive but in the turbulent boundary layer plays a very complicated role.

Keywords: wave boundary, mass transport, mean velocity, shear stress

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Authors: Fikiru Temesgen Gelata

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Food security, adaptation, and climate change mitigation are all problems that can be resolved simultaneously with Climate-Smart Agriculture (CSA). This study examines determinants of climate-smart agriculture (CSA) practices among smallholder farmers, aiming to understand the factors guiding adoption decisions and evaluate the impact of CSA on smallholder farmer income in the study areas. For this study, three-stage sampling techniques were applied to select 230 smallholders randomly. Mann-Kendal test and multinomial endogenous switching regression model were used to analyze trends of decrease or increase within long-term temporal data and the impact of CSA on the smallholder farmer income, respectively. Findings revealed education level, household size, land ownership, off-farm income, climate information, and contact with extension agents found to be highly adopted CSA practices. On the contrary, erosion exerted a detrimental impact on all the agricultural practices examined within the study region. Various factors such as farming methods, the size of farms, proximity to irrigated farmlands, availability of extension services, distance to market hubs, and access to weather forecasts were recognized as key determinants influencing the adoption of CSA practices. The multinomial endogenous switching regression model (MESR) revealed that joint adoption of crop rotation and soil and water conservation practices significantly increased farm income by 1,107,245 ETB. The study recommends that counties and governments should prioritize addressing climate change in their development agendas to increase the adoption of climate-smart farming techniques.

Keywords: climate-smart practices, food security, Oincome, MERM, Ethiopia

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Authors: Tanya Kaur Bedi, Shankha Pratim Bhattacharya

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The US Environmental Protection Agency defines indoor air pollution as “The air quality within and around buildings, especially as it relates to the health and comfort of building occupants”. According to the 2021 report by the Energy Policy Institute at Chicago, Indian residents, a country which is home to the highest levels of air pollution in the world, lose about 5.9 years from life expectancy due to poor air quality and yet has numerous dwellings dependent on natural ventilation. Currently the urban population spends 90% of the time indoors, this scenario raises a concern for occupant health and well-being. This study attempts to demonstrate the causal relationship between the indoor air pollution and its determining aspects. Detailed indoor air pollution audits were conducted in residential buildings located in Kolkata, India in the months of December and January 2021. According to the air pollution knowledge assessment city program in India, Kolkata is also the second most polluted mega-city after Delhi. Although the air pollution levels are alarming year-long, the winter months are most crucial due to the unfavourable environmental conditions. While emissions remain typically constant throughout the year, cold air is denser and moves slower than warm air, trapping the pollution in place for much longer and consequently is breathed in at a higher rate than the summers. The air pollution monitoring period was selected considering environmental factors and major pollution contributors like traffic and road dust. This study focuses on the relationship between the built environment and the spatial-temporal distribution of air pollutants in and around it. The measured parameters include, temperature, relative humidity, air velocity, particulate matter, volatile organic compounds, formaldehyde, and benzene. A total of 56 rooms were audited, selectively targeting the most dominant middle-income group in the urban area of the metropolitan. The data-collection was conducted using a set of instruments positioned in the human breathing-zone. The study assesses the relationship between indoor air pollution levels and factors determining natural ventilation and air pollution dispersion such as surrounding environment, dominant wind, openable window to floor area ratio, windward or leeward side openings, and natural ventilation type in the room: single side or cross-ventilation, floor height, residents cleaning habits, etc.

Keywords: indoor air quality, occupant health, air pollution, architecture, urban environment

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Authors: Hatem Abou-Senna, Essam Radwan

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With increasing traffic and limited resources, accommodating left-turning traffic has been a challenge for traffic engineers as they seek balance between intersection capacity and safety; these are two conflicting goals in the operation of a signalized intersection that are mitigated through signal phasing techniques. Hence, to increase the left-turn capacity and reduce the delay at the intersections, the Florida Department of Transportation (FDOT) moves forward with a vision of optimizing intersection control using innovative intersection designs through the Transportation Systems Management & Operations (TSM&O) program. These alternative designs successfully eliminate the left-turn phase, which otherwise reduces the conventional intersection’s (CI) efficiency considerably, and divide the intersection into smaller networks that would operate in a one-way fashion. This study focused on the Crossover Displaced Left-turn intersections (XDL), also known as Continuous Flow Intersections (CFI). The XDL concept is best suited for intersections with moderate to high overall traffic volumes, especially those with very high or unbalanced left turn volumes. There is little guidance on determining whether partial XDL intersections are adequate to mitigate the overall intersection condition or full XDL is always required. The primary objective of this paper was to evaluate the overall intersection performance in the case of different partial XDL designs compared to a full XDL. The XDL alternative was investigated for 4 different scenarios; partial XDL on the east-west approaches, partial XDL on the north-south approaches, partial XDL on the north and east approaches and full XDL on all 4 approaches. Also, the impact of increasing volume on the intersection performance was considered by modeling the unbalanced volumes with 10% increment resulting in 5 different traffic scenarios. The study intersection, located in Orlando Florida, is experiencing recurring congestion in the PM peak hour and is operating near capacity with volume to a capacity ratio closer to 1.00 due to the presence of two heavy conflicting movements; southbound and westbound. The results showed that a partial EN XDL alternative proved to be effective and compared favorably to a full XDL alternative followed by the partial EW XDL alternative. The analysis also showed that Full, EW and EN XDL alternatives outperformed the NS XDL and the CI alternatives with respect to the throughput, delay and queue lengths. Significant throughput improvements were remarkable at the higher volume level with percent increase in capacity of 25%. The percent reduction in delay for the critical movements in the XDL scenarios compared to the CI scenario ranged from 30-45%. Similarly, queue lengths showed percent reduction in the XDL scenarios ranging from 25-40%. The analysis revealed how partial XDL design can improve the overall intersection performance at various demands, reduce the costs associated with full XDL and proved to outperform the conventional intersection. However, partial XDL serving low volumes or only one of the critical movements while other critical movements are operating near or above capacity do not provide significant benefits when compared to the conventional intersection.

Keywords: continuous flow intersections, crossover displaced left-turn, microscopic traffic simulation, transportation system management and operations, VISSIM simulation model

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Authors: Sara Rejeb, Catherine Duveau, Tabea Rebafka

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To monitor the production process of turbofan aircraft engines, multiple measurements of various geometrical parameters are systematically recorded on manufactured parts. Engine parts are subject to extremely high standards as they can impact the performance of the engine. Therefore, it is essential to analyze these databases to better understand the influence of the different parameters on the engine's performance. Self-organizing maps are unsupervised neural networks which achieve two tasks simultaneously: they visualize high-dimensional data by projection onto a 2-dimensional map and provide clustering of the data. This technique has become very popular for data exploration since it provides easily interpretable results and a meaningful global view of the data. As such, self-organizing maps are usually applied to aircraft engine condition monitoring. As databases in this field are huge and complex, they naturally contain multiple missing entries for various reasons. The classical Kohonen algorithm to compute self-organizing maps is conceived for complete data only. A naive approach to deal with partially observed data consists in deleting items or variables with missing entries. However, this requires a sufficient number of complete individuals to be fairly representative of the population; otherwise, deletion leads to a considerable loss of information. Moreover, deletion can also induce bias in the analysis results. Alternatively, one can first apply a common imputation method to create a complete dataset and then apply the Kohonen algorithm. However, the choice of the imputation method may have a strong impact on the resulting self-organizing map. Our approach is to address simultaneously the two problems of computing a self-organizing map and imputing missing values, as these tasks are not independent. In this work, we propose an extension of self-organizing maps for partially observed data, referred to as missSOM. First, we introduce a criterion to be optimized, that aims at defining simultaneously the best self-organizing map and the best imputations for the missing entries. As such, missSOM is also an imputation method for missing values. To minimize the criterion, we propose an iterative algorithm that alternates the learning of a self-organizing map and the imputation of missing values. Moreover, we develop an accelerated version of the algorithm by entwining the iterations of the Kohonen algorithm with the updates of the imputed values. This method is efficiently implemented in R and will soon be released on CRAN. Compared to the standard Kohonen algorithm, it does not come with any additional cost in terms of computing time. Numerical experiments illustrate that missSOM performs well in terms of both clustering and imputation compared to the state of the art. In particular, it turns out that missSOM is robust to the missingness mechanism, which is in contrast to many imputation methods that are appropriate for only a single mechanism. This is an important property of missSOM as, in practice, the missingness mechanism is often unknown. An application to measurements on one type of part is also provided and shows the practical interest of missSOM.

Keywords: imputation method of missing data, partially observed data, robustness to missingness mechanism, self-organizing maps

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Authors: R. M. Rajapaksa

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Construction industry is one of the key players in driving the economy of a country to achieve its prosperity. However, a dispute is one of the crucial factors which prevent the completion of construction contracts within the budgeted cost, scheduled time, and accepted quality. Disputes are inevitable in the construction contract. Accordingly, a study has been undertaken to identify the factors affecting contractual disputes in construction projects in Sri Lanka. The study was a mixed approach with major qualitative and minor quantitative. Qualitative study was set in the form of in-depth interviews with eighteen participants, and quantitative study was conducted using a questionnaire with twenty-four respondents from previously implemented projects by the National Water Supply & Drainage Board representing the employer, engineer and the Contractor to identify the factors affecting contractual disputes and to verify most critical factors respectively. Data analysis for qualitative and quantitative studies was carried out by means of transcribing, code & categorizeand average score methods, respectively. The study reveals that there are forty factors affecting the contractual disputes in construction contracts in Sri Lanka. The finding further illustrates that conflicting decisions by inexperience personnel in the higher position of the Employer, ambiguities resulting inadequate descriptions of the preliminary/general items in price schedule, unfair valuation and late confirmation of variations, unfair determination due to lack of experience of the Engineer/Consultant, under certification of progress payments, unfair grant of EOT & application of delay damages, unreasonable claims for variation of works, errors/discrepancies/ambiguities in the contract conditions and discrepancies & errors in designs & specifications are the most critical factors affecting contractual disputes. Finally, the study proposed remedial measures to most critical factors affecting contractual disputes.

Keywords: dispute, contractual, factors, employer, engineer, contractor, construction projects

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Authors: Vibha Devi, Shabina Khanam

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Hemp (Cannabis sativa) possesses a rich content of ω-6 linoleic and ω-3 linolenic essential fatty acid in the ratio of 3:1, which is a rare and most desired ratio that enhances the quality of hemp oil. These components are beneficial for the development of cell and body growth, strengthen the immune system, possess anti-inflammatory action, lowering the risk of heart problem owing to its anti-clotting property and a remedy for arthritis and various disorders. The present study employs supercritical fluid extraction (SFE) approach on hemp seed at various conditions of parameters; temperature (40 - 80) °C, pressure (200 - 350) bar, flow rate (5 - 15) g/min, particle size (0.430 - 1.015) mm and amount of co-solvent (0 - 10) % of solvent flow rate through central composite design (CCD). CCD suggested 32 sets of experiments, which was carried out. As SFE process includes large number of variables, the present study recommends the application of resampling techniques for cross-validation of the obtained data. Cross-validation refits the model on each data to achieve the information regarding the error, variability, deviation etc. Bootstrap and jackknife are the most popular resampling techniques, which create a large number of data through resampling from the original dataset and analyze these data to check the validity of the obtained data. Jackknife resampling is based on the eliminating one observation from the original sample of size N without replacement. For jackknife resampling, the sample size is 31 (eliminating one observation), which is repeated by 32 times. Bootstrap is the frequently used statistical approach for estimating the sampling distribution of an estimator by resampling with replacement from the original sample. For bootstrap resampling, the sample size is 32, which was repeated by 100 times. Estimands for these resampling techniques are considered as mean, standard deviation, variation coefficient and standard error of the mean. For ω-6 linoleic acid concentration, mean value was approx. 58.5 for both resampling methods, which is the average (central value) of the sample mean of all data points. Similarly, for ω-3 linoleic acid concentration, mean was observed as 22.5 through both resampling. Variance exhibits the spread out of the data from its mean. Greater value of variance exhibits the large range of output data, which is 18 for ω-6 linoleic acid (ranging from 48.85 to 63.66 %) and 6 for ω-3 linoleic acid (ranging from 16.71 to 26.2 %). Further, low value of standard deviation (approx. 1 %), low standard error of the mean (< 0.8) and low variance coefficient (< 0.2) reflect the accuracy of the sample for prediction. All the estimator value of variance coefficients, standard deviation and standard error of the mean are found within the 95 % of confidence interval.

Keywords: resampling, supercritical fluid extraction, hemp oil, cross-validation

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Authors: Redvan Ghasemlounia, Elham Ansari, Hikmet Kerem Cigizoglu

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Hydrological modeling in arid and semi-arid regions is very important. Iran has many regions with these climate conditions such as Chaharmahal and Bakhtiari province that needs lots of attention with an appropriate management. Forecasting of hydrological parameters and estimation of hydrological events of catchments, provide important information that used for design, management and operation of water resources such as river systems, and dams, widely. Discharge in rivers is one of these parameters. This study presents the application and comparison of some estimation methods such as Feed-Forward Back Propagation Neural Network (FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) to predict the daily flow discharge of the Soolegan River, located at Chaharmahal and Bakhtiari province, in Iran. In this study, Soolegan, station was considered. This Station is located in Soolegan River at 51° 14՜ Latitude 31° 38՜ longitude at North Karoon basin. The Soolegan station is 2086 meters higher than sea level. The data used in this study are daily discharge and daily precipitation of Soolegan station. Feed Forward Back Propagation Neural Network(FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) models were developed using the same input parameters for Soolegan's daily discharge estimation. The results of estimation models were compared with observed discharge values to evaluate performance of the developed models. Results of all methods were compared and shown in tables and charts.

Keywords: ANN, multi linear regression, Bayesian network, forecasting, discharge, gene expression programming

Procedia PDF Downloads 563

Authors: Parisa Mansour

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Introduction: Early diagnosis of coronavirus disease (COVID-19) is extremely important to isolate and treat patients in time, thus preventing the spread of the disease, improving prognosis and reducing mortality. High-resolution computed tomography (HRCT) chest imaging and artificial intelligence (AI)-based analysis of HRCT chest images can play a central role in the treatment of patients with COVID-19. Objective: To investigate different chest HRCT findings in different stages of COVID-19 pneumonia and to evaluate the potential role of artificial intelligence in the quantitative assessment of lung parenchymal involvement in COVID-19 pneumonia. Materials and Methods: This retrospective observational study was conducted between May 1, 2020 and August 13, 2020. The study included 2169 patients with COVID-19 who underwent chest HRCT. HRCT images showed the presence and distribution of lesions such as: ground glass opacity (GGO), compaction, and any special patterns such as septal thickening, inverted halo, mark, etc. HRCT findings of the breast at different stages of the disease (early: andlt) 5 days, intermediate: 6-10 days and late stage: >10 days). A CT severity score (CTSS) was calculated based on the extent of lung involvement on HRCT, which was then correlated with clinical disease severity. Use of artificial intelligence; Analysis of CT pneumonia and quot; An algorithm was used to quantify the extent of pulmonary involvement by calculating the percentage of pulmonary opacity (PO) and gross opacity (PHO). Depending on the type of variables, statistically significant tests such as chi-square, analysis of variance (ANOVA) and post hoc tests were applied when appropriate. Results: Radiological findings were observed in HRCT chest in 1438 patients. A typical pattern of COVID-19 pneumonia, i.e., bilateral peripheral GGO with or without consolidation, was observed in 846 patients. About 294 asymptomatic patients were radiologically positive. Chest HRCT in the early stages of the disease mostly showed GGO. The late stage was indicated by such features as retinal enlargement, thickening and the presence of fibrous bands. Approximately 91.3% of cases with a CTSS = 7 were asymptomatic or clinically mild, while 81.2% of cases with a score = 15 were clinically severe. Mean PO and PHO (30.1 ± 28.0 and 8.4 ± 10.4, respectively) were significantly higher in the clinically severe categories. Conclusion: Because COVID-19 pneumonia progresses rapidly, radiologists and physicians should become familiar with typical TC chest findings to treat patients early, ultimately improving prognosis and reducing mortality. Artificial intelligence can be a valuable tool in treating patients with COVID-19.

Keywords: chest, HRCT, covid-19, artificial intelligence, chest HRCT

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Authors: Praniil Nagaraj

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This paper proposes a method to collect homeless data using crowdsourcing and presents an approach to analyze the data, demonstrating its potential to strengthen existing and future policies aimed at promoting socio-economic equilibrium. This paper's contributions can be categorized into three main areas. Firstly, a unique method for collecting homeless data is introduced, utilizing a user-friendly smartphone app (currently available for Android). The app enables the general public to quickly record information about homeless individuals, including the number of people and details about their living conditions. The collected data, including date, time, and location, is anonymized and securely transmitted to the cloud. It is anticipated that an increasing number of users motivated to contribute to society will adopt the app, thus expanding the data collection efforts. Duplicate data is addressed through simple classification methods, and historical data is utilized to fill in missing information. The second contribution of this paper is the description of data analysis techniques applied to the collected data. By combining this new data with existing information, statistical regression analysis is employed to gain insights into various aspects, such as distinguishing between unsheltered and sheltered homeless populations, as well as examining their correlation with factors like unemployment rates, housing affordability, and labor demand. Initial data is collected in San Francisco, while pre-existing information is drawn from three cities: San Francisco, New York City, and Washington D.C., facilitating the conduction of simulations. The third contribution focuses on demonstrating the practical implications of the data processing results. The challenges faced by key stakeholders, including charitable organizations and local city governments, are taken into consideration. Two case studies are presented as examples. The first case study explores improving the efficiency of food and necessities distribution, as well as medical assistance, driven by charitable organizations. The second case study examines the correlation between micro-geographic budget expenditure by local city governments and homeless information to justify budget allocation and expenditures. The ultimate objective of this endeavor is to enable the continuous enhancement of the quality of life for the underprivileged. It is hoped that through increased crowdsourcing of data from the public, the Generosity Curve and the Need Curve will intersect, leading to a better world for all.

Keywords: crowdsourcing, homelessness, socio-economic policies, statistical analysis

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Authors: Arif Tri Setyanto, Aditya Nanda Priyatama, Nugraha Arif Karyanta, Fadjri Kirana A., Afia Fitriani, Rini Setyowati, Moh.Abdul Hakim

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The Basic Health Research Report by the Ministry of Health (2018) shows an increase in the prevalence of mental health disorders in the adolescent and early adult age ranges. Supporting this finding, data on the psychological examination of the student health service unit at one State University recorded 115 cases of moderate and severe health problems in the period 2016 - 2019. More specifically, the highest number of cases was experienced by clients in the age range of 21-23 years or equivalent, with the mid-semester stage towards the end. Based on the distribution of cases experienced and the disorder becomes a psychological problem experienced by students. A total of 29% or the equivalent of 33 students experienced anxiety disorders, 25% or 29 students experienced problems ranging from mild to severe, as well as other classifications of disorders experienced, including adjustment disorders, family problems, academics, mood disorders, self-concept disorders, personality disorders, cognitive disorders, and others such as trauma and sexual disorders. Various mental health disorders have a significant impact on the academic life of students, such as low GPA, exceeding the limit in college, dropping out, disruption of social life on campus, to suicide. Based on literature reviews and best practices from universities in various countries, one of the effective ways to prevent and treat student mental health disorders is to implement a mental health monitoring system in universities. This study uses a participatory action research approach, with a sample of 423 from a total population of 32,112 students. The scale used in this study is the Beck Depression Inventory (BDI) to measure depression and the Taylor Minnesota Anxiety Scale (TMAS) to measure anxiety levels. This study aims to (1) develop a digital-based health monitoring system for students' mental health situations in the mental health category. , dangers, or those who have mental disorders, especially indications of symptoms of depression and anxiety disorders, and (2) implementing a mental health monitoring system in universities at the beginning and end of each semester. The results of the analysis show that from 423 respondents, the main problems faced by all coursework, such as thesis and academic assignments. Based on the scoring and categorization of the Beck Depression Inventory (BDI), 191 students experienced symptoms of depression. A total of 24.35%, or 103 students experienced mild depression, 14.42% (61 students) had moderate depression, and 6.38% (27 students) experienced severe or extreme depression. Furthermore, as many as 80.38% (340 students) experienced anxiety in the high category. This article will review this review of the student mental health service system on campus.

Keywords: monitoring system, mental health, psychological problems, students

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Authors: M. Chukhryaeva, R. Skhalyakho, J. Kagazegeva, E. Pocheshkhova, L. Yepiskopossyan, O. Balanovsky, E. Balanovska

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The Middle East is crossroad of different populations at different times. The Kurds are of particular interest in this region. Historical sources suggested that the origin of the Kurds is associated with Medes. Therefore, it was especially interesting to compare gene pool of Kurds with other supposed descendants of Medes-Tats. Yezidis are ethno confessional group of Kurds. Yezidism as a confessional teaching was formed in the XI-XIII centuries in Iraq. Yezidism has caused reproductively isolation of Yezidis from neighboring populations for centuries. Also, isolation helps to retain Yezidian caste system. It is unknown how the history of Yezidis affected its genу pool because it has never been the object of researching. We have examined the Y-chromosome variation in Yezidis and Kurdish males to understand their gene pool. We collected DNA samples from 90 Yezidi males and 24 Kurdish males together with their pedigrees. We performed Y-STR analysis of 17 loci in the samples collected (Yfiler system from Applied Biosystems) and analysis of 42 Y-SNPs by real-time PCR. We compared our data with published data from other Kurdish groups and from European, Caucasian, and West Asian populations. We found that gene pool of Yezidis contains haplogroups common in the Middle East (J-M172(xM67,M12)- 24%, E-M35(xM78)- 9%) and in South Western Asia (R-M124- 8%) and variant with wide distribution area - R-M198(xM458- 9%). The gene pool of Kurdish has higher genetic diversity than Yezidis. Their dominants haplogroups are R-M198- 20,3 %, E-M35- 9%, J-M172- 9%. Multidimensional scaling also shows that the Kurds and Yezidis are part of the same frontier Asian cluster, which, in addition, included Armenians, Iranians, Turks, and Greeks. At the same time, the peoples of the Caucasus and Europe form isolated clusters that do not overlap with the Asian clusters. It is noteworthy that Kurds from our study gravitate towards Tats, which indicates that most likely these two populations are descendants of ancient Medes population. Multidimensional scaling also reveals similarity between gene pool of Yezidis, Kurds with Armenians and Iranians. The analysis of Yezidis pedigrees and their STR variability did not reveal a reliable connection between genetic diversity and caste system. This indicates that the Yezidis caste system is a social division and not a biological one. Thus, we showed that, despite many years of isolation, the gene pool of Yezidis retained a common layer with the gene pool of Kurds, these populations have common spectrum of haplogroups, but Yezidis have lower genetic diversity than Kurds. This study received primary support from the RSF grant No. 16-36-00122 to MC and grant No. 16-06-00364 to EP.

Keywords: gene pool, haplogroup, Kurds, SNP and STR markers, Yezidis

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Authors: Areej Al-Hamad, Yasin Yasin, Kateryna Metersky

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This mixed-method systematic review and meta-analysis provide an encompassing understanding of the barriers, facilitators, and predictors of refugee women's employment and economic inclusion. The study sheds light on the complex interplay of sociocultural, personal, political, and environmental factors influencing these outcomes, underlining the urgent need for a multifaceted, tailored approach to devising strategies, policies, and interventions aimed at boosting refugee women's economic empowerment. Our findings suggest that sociocultural factors, including gender norms, societal attitudes, language proficiency, and social networks, profoundly shape refugee women's access to and participation in the labor market. Personal factors such as age, educational attainment, health status, skills, and previous work experience also play significant roles. Political factors like immigration policies, regulations, and rights to work, alongside environmental factors like labor market conditions, availability of employment opportunities, and access to resources and support services, further contribute to the complex dynamics influencing refugee women's economic inclusion. The significant variability observed in the impacts of these factors across different contexts underscores the necessity of adopting population and region-specific strategies. A one-size-fits-all approach may prove to be ineffective due to the diversity and unique circumstances of refugee women across different geographical, cultural, and political contexts. The study's findings have profound implications for policy-making, practice, education, and research. The insights garnered a call for coordinated efforts across these domains to bolster refugee women's economic participation. In policy-making, the findings necessitate a reassessment of current immigration and labor market policies to ensure they adequately support refugee women's employment and economic integration. In practice, they highlight the need for comprehensive, tailored employment services and interventions that address the specific barriers and leverage the facilitators identified. In education, they underline the importance of language and skills training programs that cater to the unique needs and circumstances of refugee women. Lastly, in research, they emphasize the need for ongoing investigations into the multifaceted factors influencing refugee women's employment experiences, allowing for continuous refinement of our understanding and interventions. Through this comprehensive exploration, the study contributes to ongoing efforts aimed at creating more inclusive, equitable societies. By continually refining our understanding of the complex factors influencing refugee women's employment experiences, we can pave the way toward enhanced economic empowerment for this vulnerable population.

Keywords: refugee women, employment barriers, systematic review, employment facilitators

Procedia PDF Downloads 86

Authors: Elisabetta Cianfanelli, Margherita Tufarelli, Paolo Pupparo

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The dialectical mediation between desires and objects or between mass production and consumption continues to evolve over time. This relationship is influenced both by variable geometries of contexts that are distant from the mere design of product form and by aspects rooted in the very definition of industrial design. In particular, the overcoming of macro-areas of innovation in the technological, social, cultural, formal, and morphological spheres, supported by recent theories in critical and speculative design, seems to be moving further and further away from the design of the formal dimension of advanced products. The articulated fabric of theories and practices that feed the definition of “hyperobjects”, and no longer objects describes a common tension in all areas of design and production of industrial products. The latter are increasingly detached from the design of the form and meaning of the same in mass productions, thus losing the quality of products capable of social transformation. For years we have been living in a transformative moment as regards the design process in the definition of the industrial product. We are faced with a dichotomy in which there is, on the one hand, a reactionary aversion to the new techniques of industrial production and, on the other hand, a sterile adoption of the techniques of mass production that we can now consider traditional. This ambiguity becomes even more evident when we talk about industrial products, and we realize that we are moving further and further away from the concepts of "form" as a synthesis of a design thought aimed at the aesthetic-emotional component as well as the functional one. The design of forms and their contents, as statutes of social acts, allows us to investigate the tension on mass production that crosses seasons, trends, technicalities, and sterile determinisms. The design culture has always determined the formal qualities of objects as a sum of aesthetic characteristics functional and structural relationships that define a product as a coherent unit. The contribution proposes a reflection and a series of practical experiences of research on the form of advanced products. This form is understood as a kaleidoscope of relationships through the search for an identity, the desire for democratization, and between these two, the exploration of the aesthetic factor. The study of form also corresponds to the study of production processes, technological innovations, the definition of standards, distribution, advertising, the vicissitudes of taste and lifestyles. Specifically, we will investigate how the genesis of new forms for new meanings introduces a change in the relative innovative production techniques. It becomes, therefore, fundamental to investigate, through the reflections and the case studies exposed inside the contribution, also the new techniques of production and elaboration of the forms of the products, as new immanent and determining element inside the planning process.

Keywords: industrial design, product advanced design, mass productions, new meanings

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Authors: V. P. Borker, K. S. Rane, A. J. Bhobe, R. S. Karmali

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Effluent of dye industries contains chemicals and organic dyes. Sometimes they are thrown in the water bodies without any treatment. This leads to environmental pollution and is detrimental to flora and fauna. Semiconducting oxide zinc oxide with wide bandgap 3.37 eV is used as a photocatalyst in degrading organic dyes using UV radiations. It generates electron-hole pair on exposure to UV light. If degradation is aimed at solar radiations, bandgap of zinc oxide is to be reduced so as to utilize visible radiation. Thus, in present study, zinc oxide, ZnO is synthesized from zinc oxalate, N doped zinc oxide, ZnO₁₋ₓNₓ from hydrazinated zinc oxalate, cadmium doped zinc oxide Zn₀.₉Cd₀.₁₀ and magnesium-doped zinc oxide Zn₀.₉Mg₀.₁₀ from mixed metal oxalate and hydrazinated mixed metal oxalate. The precursors were characterized by FTIR. They were decomposed to form oxides and XRD were recorded. The compounds were monophasic. Bandgap was calculated using Diffuse Reflectance Spectrum. The bandgap of ZnO was reduced to 3.24 because of precursor method of synthesis leading large surface area. The bandgap of Zn₀.₉Cd₀.₁₀ was 3.11 eV and that of Zn₀.₉Mg₀.₁₀ 3.41 eV. The lowest value was of ZnO₁₋ₓNₓ 3.09 eV. These oxides were used to degrade methylene blue, a model dye in sunlight. ZnO₁₋ₓNₓ was also used to degrade effluent of industry manufacturing colours, crayons and markers. It was observed that ZnO₁₋ₓNₓ acts as a good photocatalyst for degradation of methylene blue. It can degrade the solution within 120 minutes. Similarly, diluted effluent was decolourised using this oxide. Some colours were degraded using ZnO. Thus, the use of these two oxides could mineralize effluent. Lesser bandgap leads to more electro hole pair thus helps in the formation of hydroxyl ion radicals. These radicals attack the dye molecule, fragmentation takes place and it is mineralised.

Keywords: cadmium doped zinc oxide, dye degradation, dye effluent degradation, N doped zinc oxide, zinc oxide

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Authors: Laura Elena De León Prado, Dora Alicia Cortés Hernández, Javier Sánchez

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Among the different cancer treatments that are currently used, hyperthermia has a promising potential due to the multiple benefits that are obtained by this technique. In general terms, hyperthermia is a method that takes advantage of the sensitivity of cancer cells to heat, in order to damage or destroy them. Within the different ways of supplying heat to cancer cells and achieve their destruction or damage, the use of magnetic nanoparticles has attracted attention due to the capability of these particles to generate heat under the influence of an external magnetic field. In addition, these nanoparticles have a high surface area and sizes similar or even lower than biological entities, which allow their approaching and interaction with a specific region of interest. The most used magnetic nanoparticles for hyperthermia treatment are those based on iron oxides, mainly magnetite and maghemite, due to their biocompatibility, good magnetic properties and chemical stability. However, in order to fulfill more efficiently the requirements that demand the treatment of magnetic hyperthermia, there have been investigations using ferrites that incorporate different metallic ions, such as Mg, Mn, Co, Ca, Ni, Cu, Li, Gd, etc., in their structure. This paper reports the synthesis of nanosized Mg_xMn_1-xFe₂O₄ (x = 0.3 and 0.4) ferrites by sol-gel method and their evaluation in terms of heating capability and in vitro hemolysis to determine the potential use of these nanoparticles as thermoseeds for the treatment of cancer by magnetic hyperthermia. It was possible to obtain ferrites with nanometric sizes, a single crystalline phase with an inverse spinel structure and a behavior near to that of superparamagnetic materials. Additionally, at concentrations of 10 mg of magnetic material per mL of water, it was possible to reach a temperature of approximately 45°C, which is within the range of temperatures used for the treatment of hyperthermia. The results of the in vitro hemolysis assay showed that, at the concentrations tested, these nanoparticles are non-hemolytic, as their percentage of hemolysis is close to zero. Therefore, these materials can be used as thermoseeds for the treatment of cancer by magnetic hyperthermia.

Keywords: ferrites, heating capability, hemolysis, nanoparticles, sol-gel

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Authors: G. Zakharov, Z. Aslamazashvili, M. Chikhradze, D. Kvaskhvadze, N. Khidasheli, S. Gvazava

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Traditional technologies for processing iron-containing industrial waste, including steel-rolling production, are associated with significant energy costs, the long duration of processes, and the need to use complex and expensive equipment. Waste generated during the industrial process negatively affects the environment, but at the same time, it is a valuable raw material and can be used to produce new marketable products. The study of the effectiveness of self-propagating high-temperature synthesis (SHS) methods, which are characterized by the simplicity of the necessary equipment, the purity of the final product, and the high processing speed, is under the wide scientific and practical interest to solve the set problem. The work presents technological aspects of the production of Ferro boron by the method of SHS - metallurgy from iron-containing wastes of rolled production for alloying of cast iron and results of the effect of alloying element on the degree of boron assimilation with liquid cast iron. Features of Fe-B system combustion have been investigated, and the main parameters to control the phase composition of synthesis products have been experimentally established. Effect of overloads on patterns of cast ligatures formation and mechanisms structure formation of SHS products was studied. It has been shown that an increase in the content of hematite Fe₂O₃ in iron-containing waste leads to an increase in the content of phase FeB and, accordingly, the amount of boron in the ligature. Boron content in ligature is within 3-14%, and the phase composition of obtained ligatures consists of Fe₂B and FeB phases. Depending on the initial composition of the wastes, the yield of the end product reaches 91 - 94%, and the extraction of boron is 70 - 88%. Combustion processes of high exothermic mixtures allow to obtain a wide range of boron-containing ligatures from industrial wastes. In view of the relatively low melting point of the obtained SHS-ligature, the positive dynamics of boron absorption by liquid iron is established. According to the obtained data, the degree of absorption of the ligature by alloying gray cast iron at 1450°C is 80-85%. When combined with the treatment of liquid cast iron with magnesium, followed by alloying with the developed ligature, boron losses are reduced by 5-7%. At that, uniform distribution of boron micro-additives in the volume of treated liquid metal is provided. Acknowledgment: This work was supported by Shota Rustaveli Georgian National Science Foundation of Georgia (SRGNSFG) under the GENIE project (grant number № CARYS-19-802).

Keywords: self-propagating high-temperature synthesis, cast iron, industrial waste, ductile iron, structure formation

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Authors: Rima Alfaraj, Abeer Alarawi, Murtadha AlTammar

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The global energy landscape heavily relies on the oil and gas industry, which faces the critical challenge of reducing its carbon footprint. To address this issue, the integration of advanced materials like aerogels has emerged as a promising solution to enhance sustainability and environmental performance within the industry. This study thoroughly examines the application of aerogel-based technologies in the oil and gas sector, focusing particularly on their role in carbon capture and storage (CCS) initiatives. Aerogels, known for their exceptional properties, such as high surface area, low density, and customizable pore structure, have garnered attention for their potential in various CCS strategies. The review delves into various fabrication techniques utilized in producing aerogel materials, including sol-gel, supercritical drying, and freeze-drying methods, to assess their suitability for specific industry applications. Beyond fabrication, the practicality of aerogel materials in critical areas such as flow assurance, enhanced oil recovery, and thermal insulation is explored. The analysis spans a wide range of applications, from potential use in pipelines and equipment to subsea installations, offering valuable insights into the real-world implementation of aerogels in the oil and gas sector. The paper also investigates the adsorption and storage capabilities of aerogel-based sorbents, showcasing their effectiveness in capturing and storing carbon dioxide (CO₂) molecules. Optimization of pore size distribution and surface chemistry is examined to enhance the affinity and selectivity of aerogels towards CO₂, thereby improving the efficiency and capacity of CCS systems. Additionally, the study explores the potential of aerogel-based membranes for separating and purifying CO₂ from oil and gas streams, emphasizing their role in the carbon capture and utilization (CCU) value chain in the industry. Emerging trends and future perspectives in integrating aerogel-based technologies within the oil and gas sector are also discussed, including the development of hybrid aerogel composites and advanced functional components to further enhance material performance and versatility. By synthesizing the latest advancements and future directions in aerogel used for CCS applications in the oil and gas industry, this review offers a comprehensive understanding of how these innovative materials can aid in transitioning towards a more sustainable and environmentally conscious energy landscape. The insights provided can assist in strategic decision-making, drive technology development, and foster collaborations among academia, industry, and policymakers to promote the widespread adoption of aerogel-based solutions in the oil and gas sector.

Keywords: CCS, porous, carbon capture, oil and gas, sustainability

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Authors: Augustine O. Ani, Ifeyinwa E. Ezemagu, Eunice A. Akuru

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A seven-week study was conducted to evaluate the response of grower turkeys to varying dietary levels of Moringa oleifera leaf meal (MOLM) in a humid tropical environment. A total of 90 twelve weeks old male and female grower turkeys were randomly divided into five groups of 18 birds each in a completely randomized design (CRD) and assigned to five caloric (2.57-2.60 Mcal/kg ME) and isonitrogenous (19.95% crude protein) diets containing five levels (0, 15, 20, 25 and 30%) of MOLM, respectively. Each treatment was replicated three times with 6 birds per replicate housed in a deep litter pen of fresh wood shavings measuring 1.50m x 1.50m. Feed and water were provided to the birds' ad libitum. Parameters measured were: final live weight (FLW) daily weight gain (DWG), daily feed intake (DFI), feed conversion ratio (FCR), protein efficiency ratio (PER), packed cell volume (PCV), haemoglobin concentration (Hb), red blood cell (RBC) count, white blood cell (WBC) count, mean cell volume (MCV), mean cell haemoglobin (MCH) and mean cell haemoglobin concentration (MCHC), feed cost / kg weight gain and apparent nutrient retention. Results showed that grower turkeys fed 20% MOLM diet had significantly (p < 0.05) higher FLW and DWG values (4410.30 g and 34.49 g, respectively) and higher DM and NFE retention values (67.28 and 58.12%, respectively) than turkeys fed other MOLM diets. Feed cost per kg gain decreased significantly (p < 0.05) with increasing levels of MOLM in the diets. The PCV, Hb, WBC, MCV, MCH and MCHC values of grower turkeys fed 20% MOLM diet were significantly (p < 0.05) higher than those of grower turkeys fed other diets. It was concluded that a diet containing 20% MOLM is adequate for the normal growth of grower turkeys in the tropics.

Keywords: Diets, grower turkeys, Moringa oleifera leaf meal, response, tropical environment

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Authors: Aicha Assal, El Mostapha Lotfi

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Rapid industrialization and population growth are currently the main causes of energy and environmental problems associated with wastewater treatment. Wastewater treatment plants (WWTPs) aim to treat wastewater before discharging it into the environment, but they are not yet capable of treating non-biodegradable contaminants such as heavy metals. Toxic heavy metals can disrupt biological processes in WWTPs. Consequently, it is crucial to combine additional physico-chemical treatments with WWTPs to ensure effective wastewater treatment. In this study, the authors examined the pretreatment process for urban wastewater generated by the El Jadida WWTP in order to assess its treatment efficiency. Various physicochemical and spatiotemporal parameters of the WWTP's raw and treated water were studied, including temperature, pH, conductivity, biochemical oxygen demand (BOD5), chemical oxygen demand (COD), suspended solids (SS), total nitrogen, and total phosphorus. The results showed an improvement in treatment yields, with measured performance values of 77% for BOD5, 63% for COD, and 66% for TSS. However, spectroscopic analyses revealed persistent coloration in wastewater samples leaving the WWTP, as well as the presence of heavy metals such as Zn, cadmium, chromium, and cobalt, detected by inductively coupled plasma optical emission spectroscopy (ICP-OES). To remedy these staining problems and reduce the presence of heavy metals, a new low-cost, environmentally-friendly eggshell-based solution was proposed. This method eliminated most heavy metals such as cobalt, beryllium, silver, and copper and significantly reduced the amount of cadmium, lead, chromium, manganese, aluminium, and Zn. In addition, the bioadsorbent was able to decolorize wastewater by up to 84%. This adsorption process is, therefore, of great interest for ensuring the quality of wastewater and promoting its reuse in irrigation.

Keywords: WWTP, wastewater, heavy metals, decoloration, depollution, COD, BOD5

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Authors: M. Naimi, M. B. Khaled

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The aim of the present work was to test in vitro inhibition of food pathogens and spoilage bacteria by crude bacteriocins from autochthonous lactic acid bacteria. Thirty autochthonous lactic acid bacteria isolated previously, belonging to the genera: Lactobacillus, Carnobacterium, Lactococcus, Vagococcus, Streptococcus, and Pediococcus, have been screened by an agar spot test and a well diffusion assay against Gram-positive and Gram-negative harmful bacteria: Bacillus cereus, Bacillus subtilis ATCC 6633, Escherichia coli ATCC 8739, Salmonella typhimurium ATCC 14028, Staphylococcus aureus ATCC 6538, and Pseudomonas aeruginosa under conditions means to reduce lactic acid and hydrogen peroxide effect to select bacteria with high bacteriocinogenic potential. Furthermore, crude bacteriocins semiquantification and heat sensitivity to different temperatures (80, 95, 110°C, and 121°C) were performed. Another exploratory test concerning the response of St. aureus ATCC 6538 to the presence of crude bacteriocins was realized. It has been observed by the agar spot test that fifteen candidates were active toward Gram-positive targets strains. The secondary screening demonstrated an antagonistic activity oriented only against St. aureus ATCC 6538, leading to the selection of five isolates: Lm14, Lm21, Lm23, Lm24, and Lm25 with a larger inhibition zone compared to the others. The ANOVA statistical analysis reveals a small variation of repeatability: Lm21: 0.56%, Lm23: 0%, Lm25: 1.67%, Lm14: 1.88%, Lm24: 2.14%. Conversely, slight variation was reported in terms of inhibition diameters: 9.58± 0.40, 9.83± 0.46, and 10.16± 0.24 8.5 ± 0.40 10 mm for, Lm21, Lm23, Lm25, Lm14and Lm24, indicating that the observed potential showed a heterogeneous distribution (BMS = 0.383, WMS = 0.117). The repeatability coefficient calculated displayed 7.35%. As for the bacteriocins semiquantification, the five samples exhibited production amounts about 4.16 for Lm21, Lm23, Lm25 and 2.08 AU/ml for Lm14, Lm24. Concerning the sensitivity the crude bacteriocins were fully insensitive to heat inactivation, until 121°C, they preserved the same inhibition diameter. As to, kinetic of growth , the µmax showed reductions in pathogens load for Lm21, Lm23, Lm25, Lm14, Lm24 of about 42.92%, 84.12%, 88.55%, 54.95%, 29.97% in the second trails. Inversely, this pathogen growth after five hours displayed differences of 79.45%, 12.64%, 11.82%, 87.88%, 85.66% in the second trails, compared to the control. This study showed potential inhibition to the growth of this food pathogen, suggesting the possibility to improve the hygienic food quality.

Keywords: exploratory test, lactic acid bacteria, crude bacteriocins, spoilage, pathogens

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Authors: Susana P. Dias, Andrea Gomes, Fernanda M. Ferreira, Marta F. Henriques

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Thymus mastichina L. is an endogenous medicinal and aromatic plant of the Mediterranean flora. It has been used empirically over the years as a natural preservative in food. Nowadays, the antimicrobial activity of its bioactive compounds, such as essential oils and extracts, has been well recognized. The main purpose of this study was to evaluate the antimicrobial effect of Thymus mastichina ethanolic and aqueous extracts on pathogens and spoilage microorganisms present in cheese during ripening. The effect that the extract type and its concentration has on the development of Staphylococcus aureus, Escherichia coli, and Yarrowia lipolytica populations during 24 hours, was studied 'in vitro' using appropriate culture media. The results achieved evidenced the antimicrobial activity of T. mastichina extracts against the studied strains, and the concentration of 2 mg/mL (w/v) was selected and used directly on the cheese surface during ripening. In addition to the microbiological evaluation in terms of total aerobic bacteria, Enterobacteriaceae, yeasts (particularly Y. lipolytica) and molds, the treated cheeses physicochemical evaluation (humidity, aw, pH, colour, and texture) was also performed. The results were compared with cheeses with natamicyn (positive control) and without any treatment (negative control). The physicochemical evaluation showed that the cheeses treated with ethanolic extract of Thymus mastichina, except the fact that they lead to a faster water loss during ripening, did not present considerable differences when compared to controls. The study revealed an evident antimicrobial power of the extracts, although less effective than the one shown by the use of natamycin. For this reason, the improvement of the extraction methods and the adjustment of the extract concentrations will contribute to the use of T. mastichina as a healthier and eco-friendly alternative to natamycin, that is also more attractive from an economic point of view.

Keywords: antimicrobial activity, cheese, ethanolic extract, Thymus mastichina

Procedia PDF Downloads 177

Authors: T. Garlan, I. Gabelotaud, S. Lucas, E. Marchès

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Production of a global sedimentological seabed map has been initiated in 1995 to provide the necessary tool for searches of aircraft and boats lost at sea, to give sedimentary information for nautical charts, and to provide input data for acoustic propagation modelling. This original approach had already been initiated one century ago when the French hydrographic service and the University of Nancy had produced maps of the distribution of marine sediments of the French coasts and then sediment maps of the continental shelves of Europe and North America. The current map of the sediment of oceans presented was initiated with a UNESCO's general map of the deep ocean floor. This map was adapted using a unique sediment classification to present all types of sediments: from beaches to the deep seabed and from glacial deposits to tropical sediments. In order to allow good visualization and to be adapted to the different applications, only the granularity of sediments is represented. The published seabed maps are studied, if they present an interest, the nature of the seabed is extracted from them, the sediment classification is transcribed and the resulted map is integrated in the world map. Data come also from interpretations of Multibeam Echo Sounder (MES) imagery of large hydrographic surveys of deep-ocean. These allow a very high-quality mapping of areas that until then were represented as homogeneous. The third and principal source of data comes from the integration of regional maps produced specifically for this project. These regional maps are carried out using all the bathymetric and sedimentary data of a region. This step makes it possible to produce a regional synthesis map, with the realization of generalizations in the case of over-precise data. 86 regional maps of the Atlantic Ocean, the Mediterranean Sea, and the Indian Ocean have been produced and integrated into the world sedimentary map. This work is permanent and permits a digital version every two years, with the integration of some new maps. This article describes the choices made in terms of sediment classification, the scale of source data and the zonation of the variability of the quality. This map is the final step in a system comprising the Shom Sedimentary Database, enriched by more than one million punctual and surface items of data, and four series of coastal seabed maps at 1:10,000, 1:50,000, 1:200,000 and 1:1,000,000. This step by step approach makes it possible to take into account the progresses in knowledge made in the field of seabed characterization during the last decades. Thus, the arrival of new classification systems for seafloor has improved the recent seabed maps, and the compilation of these new maps with those previously published allows a gradual enrichment of the world sedimentary map. But there is still a lot of work to enhance some regions, which are still based on data acquired more than half a century ago.

Keywords: marine sedimentology, seabed map, sediment classification, world ocean

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Authors: Jolanta Jonak, Sylvia Tolczyk

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Educational systems are tasked with preparing students for future success in academic or work environments. Schools strive to achieve this goal, but often it is challenging as conventional teaching approaches are often ineffective in increasingly diverse educational systems. In today’s ever-increasing global society, educational systems become increasingly diverse in terms of cultural and linguistic differences, learning preferences and styles, ability and disability. Through increased understanding of disabilities and improved identification processes, students having some form of disabilities tend to be identified earlier than in the past, meaning that more students with identified disabilities are being supported in our classrooms. Also, a large majority of students with disabilities are educated in general education environments. Due to cognitive makeup and life experiences, students have varying learning styles and preferences impacting how they receive and express what they are learning. Many students come from bi or multilingual households and with varying proficiencies in the English language, further impacting their learning. All these factors need to be seriously considered when developing learning opportunities for student's. Educators try to adjust their teaching practices as they discover that conventional methods are often ineffective in reaching each student’s potential. Many teachers do not have the necessary educational background or training to know how to teach students whose learning needs are more unique and may vary from the norm. This is further complicated by the fact that many classrooms lack consistent access to interventionists/coaches that are adequately trained in evidence-based approaches to meet the needs of all students, regardless of what their academic needs may be. One evidence-based way for providing successful education for all students is by incorporating cognitive approaches and strategies that tap into affective, recognition, and strategic networks in the student's brain. This can be done through Differentiated Instruction (DI). Differentiated Instruction is increasingly recognized model that is established on the basic principles of Universal Design for Learning. This form of support ensures that regardless of the students’ learning preferences and cognitive learning profiles, they have opportunities to learn through approaches that are suitable to their needs. This approach improves the educational outcomes of students with special needs and it benefits other students as it accommodates learning styles as well as the scope of unique learning needs that are evident in the typical classroom setting. Differentiated Instruction also is recognized as an evidence-based best practice in education and is highly effective when it is implemented within the tiered system of the Response to Intervention (RTI) model. Recognition of DI becomes more common; however, there is still limited understanding of the effective implementation and use of strategies that can create unique learning environments for each student within the same setting. Through employing knowledge of a variety of instructional strategies, general and special education teachers can facilitate optimal learning for all students, with and without a disability. A desired byproduct of DI is that it can eliminate inaccurate perceptions about the students’ learning abilities, unnecessary referrals for special education evaluations, and inaccurate decisions about the presence of a disability.

Keywords: differentiated instruction, universal design for learning, special education, diversity

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Authors: Mitakshara Sharma, S. K. Nema, Sanjeev Narang

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Diabetes mellitus (DM) is a group of metabolic disorders characterized by metabolic abnormalities, chronic hyperglycaemia and long term macrovascular & microvascular complications. Vascular complications are due to platelet hyperactivity and dysfunction, increased inflammation, altered coagulation and endothelial dysfunction. Large proportion of patients with Type II DM suffers from preventable vascular angiopathies, and there is need to develop risk factor modifications and interventions to reduce impact of complications. These complications are attributed to platelet activation, recognised by increase in Platelet Volume Indices (PVI) including Mean Platelet Volume (MPV) and Platelet Distribution Width (PDW). The current study is prospective analytical study conducted over 2 years. Out of 1100 individuals, 930 individuals fulfilled inclusion criteria and were segregated into three groups on basis of glycosylated haemoglobin (HbA1C): - (a) Diabetic, (b) Non-Diabetic and (c) Subjects with Impaired fasting glucose (IFG) with 300 individuals in IFG and non-diabetic groups & 330 individuals in diabetic group. Further, diabetic group was divided into two groups on the basis of presence or absence of known diabetes related vascular complications. Samples for HbA1c and PVI were collected using Ethylene diamine tetraacetic acid (EDTA) as anticoagulant and processed on SYSMEX-X-800i autoanalyser. The study revealed gradual increase in PVI from non-diabetics to IFG to diabetics. PVI were markedly increased in diabetic patients. MPV and PDW of diabetics, IFG and non diabetics were (17.60 ± 2.04)fl, (11.76 ± 0.73)fl, (9.93 ± 0.64)fl and (19.17 ± 1.48)fl, (15.49 ± 0.67)fl, (10.59 ± 0.67)fl respectively with a significant p value 0.00 and a significant positive correlation (MPV-HbA1c r = 0.951; PDW-HbA1c r = 0.875). MPV & PDW of subjects with diabetes related complications were higher as compared to those without them and were (17.51±0.39)fl & (15.14 ± 1.04)fl and (20.09 ± 0.98) fl & (18.96 ± 0.83)fl respectively with a significant p value 0.00. There was a significant positive correlation between PVI and duration of diabetes across the groups (MPV-HbA1c r = 0.951; PDW-HbA1c r = 0.875). However, a significant negative correlation was found between glycaemic levels and total platelet count (PC- HbA1c r =-0.164). This is multi-parameter and comprehensive study with an adequately powered study design. It can be concluded from our study that PVI are extremely useful and important indicators of impending vascular complications in all patients with deranged glycaemic control. Introduction of automated cell counters has facilitated the availability of PVI as routine parameters. PVI is a useful means for identifying larger & active platelets which play important role in development of micro and macro angiopathic complications of diabetes leading to mortality and morbidity. PVI can be used as cost effective markers to predict and prevent impending vascular events in patients with Diabetes mellitus especially in developing countries like India. PVI, if incorporated into protocols for management of diabetes, could revolutionize care and curtail the ever increasing cost of patient management.

Keywords: diabetes, IFG, HbA1C, MPV, PDW, PVI

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Authors: Tanira Kingi, Oscar Montes Oca, Reina Tamepo

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The introduction of the Climate Change Response (Zero Carbon) Amendment Act (2019) and the National Policy Statement for Freshwater Management (2020) both contain underpinning statements that refer to the principles of the Treaty of Waitangi and cultural concepts of stewardship and environmental protection. Maori interests in New Zealand’s agricultural, forestry, fishing and horticultural sectors are significant. The organizations that manage these investments do so on behalf of extended family groups that hold inherited interests based on genealogical connections (whakapapa) to particular tribal units (iwi and hapu) and areas of land (whenua) and freshwater bodies (wai). This paper draws on the findings of current research programmes funded by the New Zealand Agricultural Greenhouse Gas Research Centre (NZAGRC) and the Our Land & Water National Science Challenge (OLW NSC) to understand the impact of cultural knowledge and imperatives on agricultural GHG and freshwater mitigation and land-use change decisions. In particular, the research outlines mitigation and land-use change scenario decision support frameworks that model changes in emissions profiles (reductions in biogenic methane, nitrous oxide and nutrient emissions to freshwater) of agricultural and forestry production systems along with impacts on key economic indicators and socio-cultural factors. The paper also assesses the effectiveness of newly introduced partnership arrangements between Maori groups/organizations and key government agencies on policy co-design and implementation, and in particular, decisions to adopt mitigation practices and to diversify land use.

Keywords: co-design and implementation of environmental policy, indigenous environmental knowledge, Māori land tenure and agribusiness, mitigation and land use change decision support frameworks

Procedia PDF Downloads 219

Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey

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Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.

Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method

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Authors: Arámbula-Villa Gerónimo, García-Lara Kenia Y., Figueroa-Cárdenas J. D., Pérez-Robles J. F., Jiménez-Sandoval S., Salazar-López R., Herrera-Corredor J. A.

Abstract:

The nixtamalization process (thermal-alkaline method) improves the nutritional part of the corn grain. In this process, the using of Ca(OH)₂ is basic, although the chemical mechanisms between this alkali and the carbohydrates (starch), proteins, lipids, and fiber have not been fully identified. In this study, the native corn starch was taken as a model, and it was subjected to cooking with different concentrations of lime (nixtamalization process) and specific studies of FTIR and XRD were carried out to identify the formation of chemical compounds, and the physical, physicochemical, rheological (paste) and structural properties of material obtained were determined. The FTIR spectra showed the formation of calcium-starch complexes. The treatments with Ca(OH)₂ showed a band shift towards 1675 cm⁻¹ and a band in 1436 cm⁻¹ (COO⁻), indicating the oxidation of starch. Three bands were identified (1575, 1550, and 1540 cm⁻¹) characteristics of carboxylic acid salts for three types of coordinated structures: monodentate, pseudo-bridged, and bidentate. The XRD spectra of starch treated with Ca(OH)₂ showed a peak corresponding to CaCO₃ (29.40°). The oxidation of starch was favored with low concentrations of Ca(OH)₂, producing carboxyl and carbonyl groups and increasing the residual CaCO₃. The increased concentration of Ca(OH)₂ showed the formation of calcium carboxylates, with a decrease in relative crystallinity and residual CaCO₃. Samples with low concentrations of Ca(OH)₂ slowed the onset of gelatinization and increased the swelling of the granules and the peak viscosity. The higher concentrations of Ca(OH)₂ difficulted the water absorption and decreased the viscosity rate and peak viscosity. These results can be used to improve the quality characteristics of the dough and tortillas and to get better acceptance by consumers.

Keywords: maize starch, nixtamalization, gelatinization, calcium carboxylates

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