Search results for: the statistical measure

Authors: Alena Kulikova, Tatjana Kanonire

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Intelligence research is one of the oldest fields of psychology. Many factors have made a research on intelligence, defined as reasoning and problem solving [1, 2], a very acute and urgent problem. Thus, it has been repeatedly shown that intelligence is a predictor of academic, professional, and social achievement in adulthood (for example, [3]); Moreover, intelligence predicts these achievements better than any other trait or ability [4]. The individual level, a comprehensive assessment of intelligence is a necessary criterion for the diagnosis of various mental conditions. For example, it is a necessary condition for psychological, medical and pedagogical commissions when deciding on educational needs and the most appropriate educational programs for school children. Assessment of intelligence is crucial in clinical psychodiagnostic and needs high-quality intelligence measurement tools. Therefore, it is not surprising that the development of intelligence tests is an essential part of psychological science and practice. Many modern intelligence tests have a long history and have been used for decades, for example, the Stanford-Binet test or the Wechsler test. However, the vast majority of these tests are based on the classic linear test structure, in which all respondents receive all tasks (see, for example, a critical review by [5]). This understanding of the testing procedure is a legacy of the pre-computer era, in which blank testing was the only diagnostic procedure available [6] and has some significant limitations that affect the reliability of the data obtained [7] and increased time costs. Another problem with measuring IQ is that classical line-structured tests do not fully allow to measure respondent's intellectual progress [8], which is undoubtedly a critical limitation. Advances in modern psychometrics allow for avoiding the limitations of existing tools. However, as in any rapidly developing industry, at the moment, psychometrics does not offer ready-made and straightforward solutions and requires additional research. In our presentation we would like to discuss the strengths and weaknesses of the current approaches to intelligence measurement and highlight “points of growth” for creating a test in accordance with modern psychometrics. Whether it is possible to create the instrument that will use all achievements of modern psychometric and remain valid and practically oriented. What would be the possible limitations for such an instrument? The theoretical framework and study design to create and validate the original Russian comprehensive computer test for measuring the intellectual development in school-age children will be presented.

Keywords: Intelligence, psychometrics, psychological measurement, computerized adaptive testing, multistage testing

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Authors: Chiu-Wen Chang, I-Yun Chang, Wei-Ting Chen, Hui-Ping Ho, Chao-Ying Pan, Joh-Jong Huang

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Dengue is a ‘community disease’ or ‘environmental disease’, as long as the environment exist suitable container (including natural and artificial) for mosquito breeding, once the virus invade will lead to the dengue epidemic. Surveillance of vector density is critical to effective infectious disease control and play an important role in monitoring the dynamics of mosquitoes in community, such as mosquito species, density, distribution area. The objective of this study was to examine the relationship in vector density survey (Breteau index, Adult index, House index, Container index, and Larvae index) form 2014 to 2016 in Kaohsiung City and evaluate the effects of introducing the Breeding Elimination and Appraisal Team (hereinafter referred to as BEAT) as an intervention measure on eliminating dengue vector breeding site started from May 2016. BEAT were performed on people who were suspected of contracting dengue fever, a surrounding area measuring 50 meters by 50 meters was demarcated as the emergency prevention and treatment zone. BEAT would perform weekly vector mosquito inspections and vector mosquito inspections in regions with a high Gravitrap index and assign a risk assessment index to each region. These indices as well as the prevention and treatment results were immediately reported to epidemic prevention-related units every week. The results indicated that, vector indices from 2014 to 2016 showed no statistically significant differences in the Breteau index, adult index, and house index (p > 0.05) but statistically significant differences in the container index and larvae index (p <0.05). After executing the integrated elimination work, container index and larvae index are statistically significant different from 2014 to 2016 in the (p < 0.05). A post hoc test indicated that the container index of 2014 (M = 12.793) was significantly higher than that of 2016 (M = 7.631), and that the larvae index of 2015 (M = 34.065) was significantly lower than that of 2014 (M = 66.867). The results revealed that effective vector density surveillance could highlight the focus breeding site and then implement the immediate control action (BEAT), which successfully decreased the vector density and the risk of dengue epidemic.

Keywords: Breteau index, dengue control, monitoring method, vector density

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Authors: Lucas Caldas, Pablo Paulse, Karla Hora

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Shipping containers are present in different Brazilian cities, firstly used for transportation purposes, but which become waste materials and an environmental burden in their end-of-life cycle. In the last decade, in Brazil, some buildings made partly or totally from shipping containers started to appear, most of them for commercial and office uses. Although the use of a reused container for buildings seems a sustainable solution, it is very important to measure the thermal and energy aspects when they are used as such. In this context, this study aims to evaluate the thermal and energy performance of an office building totally made from a 12-meter-long, High Cube 40’ shipping container in different Brazilian Bioclimatic Zones. Four different constructive solutions, mostly used in Brazil were chosen: (1) container without any covering; (2) with internally insulated drywall; (3) with external fiber cement boards; (4) with both drywall and fiber cement boards. For this, the DesignBuilder with EnergyPlus was used for the computational simulation in 8760 hours. The EnergyPlus Weather File (EPW) data of six Brazilian capital cities were considered: Curitiba, Sao Paulo, Brasilia, Campo Grande, Teresina and Rio de Janeiro. Air conditioning appliance (split) was adopted for the conditioned area and the cooling setpoint was fixed at 25°C. The coefficient of performance (CoP) of air conditioning equipment was set as 3.3. Three kinds of solar absorptances were verified: 0.3, 0.6 and 0.9 of exterior layer. The building in Teresina presented the highest level of energy consumption, while the one in Curitiba presented the lowest, with a wide range of differences in results. The constructive option of external fiber cement and drywall presented the best results, although the differences were not significant compared to the solution using just drywall. The choice of absorptance showed a great impact in energy consumption, mainly compared to the case of containers without any covering and for use in the hottest cities: Teresina, Rio de Janeiro, and Campo Grande. This study brings as the main contribution the discussion of constructive aspects for design guidelines for more energy-efficient container buildings, considering local climate differences, and helps the dissemination of this cleaner constructive practice in the Brazilian building sector.

Keywords: bioclimatic zones, Brazil, shipping containers, thermal and energy performance

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Authors: Meghan E. Murray, Carri R. Tolmie

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This study aims to identify potential factors and widely applicable best practices that can contribute to improving corporate social responsibility (CSR) and corporate performance for firms by exploring the relationship between transformational leadership, spiritual intelligence, and emotional intelligence. Corporate social responsibility is when companies are cognizant of the impact of their actions on the economy, their communities, the environment, and the world as a whole while executing business practices accordingly. The prevalence of CSR has continuously strengthened over the past few years and is now a common practice in the business world, with such efforts coinciding with what stakeholders and the public now expect from corporations. Because of this, it is extremely important to be able to pinpoint factors and best practices that can improve CSR within corporations. One potential factor that may lead to improved CSR is spiritual intelligence (SQ), or the ability to recognize and live with a purpose larger than oneself. Spiritual intelligence is a measurable skill, just like emotional intelligence (EQ), and can be improved through purposeful and targeted coaching. This research project consists of two studies. Study 1 is a case study comparison of a benefit corporation and a non-benefit corporation. This study will examine the role of SQ and EQ as moderators in the relationship between the transformational leadership of employees within each company and the perception of each firm’s CSR and corporate performance. Project methodology includes creating and administering a survey comprised of multiple pre-established scales on transformational leadership, spiritual intelligence, emotional intelligence, CSR, and corporate performance. Multiple regression analysis will be used to extract significant findings from the collected data. Study 2 will dive deeper into spiritual intelligence itself by analyzing pre-existing data and identifying key relationships that may provide value to companies and their stakeholders. This will be done by performing multiple regression analysis on anonymized data provided by Deep Change, a company that has created an advanced, proprietary system to measure spiritual intelligence. Based on the results of both studies, this research aims to uncover best practices, including the unique contribution of spiritual intelligence, that can be utilized by organizations to help enhance their corporate social responsibility. If it is found that high spiritual and emotional intelligence can positively impact CSR effort, then corporations will have a tangible way to enhance their CSR: providing targeted employees with training and coaching to increase their SQ and EQ.

Keywords: corporate social responsibility, CSR, corporate performance, emotional intelligence, EQ, spiritual intelligence, SQ, transformational leadership

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Authors: Laura Piedra-Muñoz, Ángeles Godoy-Durán, Emilio Galdeano-Gómez, Juan C. Pérez-Mesa

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The current agricultural system in some arid and semi-arid areas is not sustainable in the long term. In southeast Spain, groundwater is the main water source and is overexploited, while alternatives like desalination are still limited. The Water Plan for the Mediterranean Basins 2015-2020 indicates a global deficit of 73.42 hm3 and an overexploitation of the aquifers of 205.58hm3. In order to solve this serious problem, two major actions can be taken: increasing available water, and/or improving the efficiency of its use. This study focuses on the latter. The main aim of this study is to present the major factors related to water usage efficiency in farming. It focuses on Almería province, southeast Spain, one of the most arid areas of the country, and in particular on family farms as the main direct managers of water use in this zone. Many of these farms are among the most water efficient in Spanish agriculture, but this efficiency is not generalized throughout the sector. This work conducts a comprehensive assessment of water performance in this area, using on-farm water-use, structural, socio-economic and environmental information. Two statistical techniques are used: descriptive analysis and cluster analysis. Thus, two groups are identified: the least and the most efficient farms regarding water usage. By analyzing both the common characteristics within each group and the differences between the groups with a one-way ANOVA analysis, several conclusions can be reached. The main differences between the two clusters center on the extent to which innovation and new technologies are used in irrigation. The most water efficient farms are characterized by more educated farmers, a greater degree of innovation, new irrigation technology, specialized production and awareness of water issues and environmental sustainability. The research shows that better practices and policies can have a substantial impact on achieving a more sustainable and efficient use of water. The findings of this study can be extended to farms in similar arid and semi-arid areas and contribute to foster appropriate policies to improve the efficiency of water usage in the agricultural sector.

Keywords: cluster analysis, family farms, Spain, water-use efficiency

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Authors: Carolina Silva Ansélmo

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Airports are demand-generating poles that affect the flow of traffic around them. The airport access system must be fast, convenient, and adequately planned, considering its potential users. An airport with good ground access conditions can provide the user with a more satisfactory access experience. When several transport options are available, service providers must understand users' preferences and the expected quality of service. The present study focuses on airport access in a comparative scenario between bus, private vehicle, subway, taxi and urban mobility transport applications to São Paulo/Guarulhos International Airport. The objectives are (i) to identify the factors that influence the choice, (ii) to measure Willingness to Pay (WTP), and (iii) to estimate the market share for each modal. The applied method was Adaptive Choice-based Conjoint Analysis (ACBC) technique using Sawtooth Software. Conjoint analysis, rooted in Utility Theory, is a survey technique that quantifies the customer's perceived utility when choosing alternatives. Assessing user preferences provides insights into their priorities for product or service attributes. An additional advantage of conjoint analysis is its requirement for a smaller sample size compared to other methods. Furthermore, ACBC provides valuable insights into consumers' preferences, willingness to pay, and market dynamics, aiding strategic decision-making to provide a better customer experience, pricing, and market segmentation. In the present research, the ACBC questionnaire had the following variables: (i) access time to the boarding point, (ii) comfort in the vehicle, (iii) number of travelers together, (iv) price, (v) supply power, and (vi) type of vehicle. The case study questionnaire reached 213 valid responses considering the scenario of access from the São Paulo city center to São Paulo/Guarulhos International Airport. As a result, the price and the number of travelers are the most relevant attributes for the sample when choosing airport access. The market share of the selection is mainly urban mobility transport applications, followed by buses, private vehicles, taxis and subways.

Keywords: adaptive choice-based conjoint analysis, ground access to airport, market share, willingness to pay

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Authors: Louise Jones, Rafael De Andrade Moral, John C. Stephens

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Background: Minerals are an essential component of correct nutrition. Conserved hay/haylage is an important component of many horse's diets. Variations in the mineral content of conserved forage should be considered when assessing dietary intake. Objectives: This study describes the levels and differences in 15 commonly analysed minerals in conserved forage fed to horses in the United Kingdom (UK), Ireland (IRL), and France (FRA). Methods: Hay (FRA n=92, IRL n=168, UK n=152) and haylage samples (UK n=287, IRL n=49) were collected during 2017-2020. Mineral analysis was undertaken using inductively coupled plasma-mass spectrometry (ICP-MS). Statistical analysis was performed using beta regression, Gaussian, or gamma models, depending on the nature of the response variable. Results: There are significant differences in the mineral content of the UK, IRL, and FRA conserved forage samples. FRA hay samples had a significantly higher (p < 0.05) levels of Sulphur (0.16 ± 0.0051 %), Calcium (0.56 ± 0.0342%), Magnesium (0.16 ± 0.0069 mg/ kg DM), Iron (194 ± 23.0 mg/kg DM), Cobalt (0.21 ± 0.0244 mg/kg DM) and Copper (4.94 ± 0.196 mg/kg DM) content compared to hay from the other two countries. UK hay samples had significantly less (p < 0.05) Selenium (0.07 ± 0.0084 mg/kg DM), whilst IRL hay samples were significantly (p < 0.05) higher in Chloride (0.9 ± 0.026mg/kg DM) compared to hay from the other two countries. IRL haylage samples were significantly (p < 0.05) higher in Phosphorus (0.26 ± 0.0102 %), Sulphur (0.17 ± 0.0052 %), Chloride (1.01 ± 0.0519 %), Calcium (0.54 ± 0.0257 %), Selenium (0.17 ± 0.0322 mg/kg DM) and Molybdenum (1.47 ± 0.137 mg/kg DM) compared to haylage from the UK. Main Limitations: Forage samples were obtained from professional yards and may not be reflective of forages fed by most horse owners. Information regarding soil type, species of grass, fertiliser treatment, harvest, or storage conditions were not included in this study. Conclusions: At a DM intake of 2% body weight, conserved forage as sampled in this study will be insufficient to meet Zinc, Iodine, and Copper NRC maintenance requirements, and Se intake will also be insufficient for horses fed the UK conserved forage. Many horses receive hay/haylage as the main component of their diet; this study highlights the need to consider forage analysis when making dietary recommendations.

Keywords: conserved forage, hay, haylage, minerals

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Authors: Oyewole Charles Iledun, Shuaib Harira, Ezeogueri-Oyewole Anne Nnenna

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Due to high population pressure/human activities competing for agricultural land, the need to maximize the productivity of available land has become necessary; this has not been achievable in the tropics with monoculture systems where a single harvest per season is the practice. Thus, this study evaluates intercropping combination and tillage practice on yield and yield components of groundnut in a mixture with maize. The trial was conducted in the rainy seasons of 2020 and 2021 at the Kogi State University Students’ Research and Demonstration Farm, Latitude 70 301 and Longitude 70 091 E in the Southern Guinea Savannah agro-ecological zone of Nigeria. Treatment consisted of three tillage practices [as main plot factor] and five intercropping combinations [subplot factor] assigned to a 3 x 5 Factorial experiment replicated four times. Data were collected for growth, development, yield components, and yield of groundnut. Data collected were subjected to Statistical Analysis in line with Factorial Experiments. Means found to be statistically significant at 5 % probability were separated using the LSD method. Regarding yield components and yield related parameters in groundnuts, better performance was observed in cole cropped groundnut plots compared to the intercropped plots. However, intercropping groundnut with maize was generally advantageous, with LER greater than unity. Among the intercrops, the highest LERs were observed when one row of maize was cropped with one row of groundnut, with the least LER recorded in intercropping two rows of maize with one row of groundnut. For the tillage operations, zero tillage gave the highest LERs in both seasons, while the least LERs were recorded when the groundnut was planted on ridges. Since the highest LERs were observed when one row of maize was intercropped with one row of groundnut, this level of crop combination is recommended for the study area, while ridging may not be necessary to get good groundnut yield, particularly under similar soil conditions as obtained in the experimental area, and with similar rainfall observed during the experimental period.

Keywords: canopy height, leaf number, haulm yield / ha, pod yield / ha, harvest index and shelling percentage

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Authors: O. Antypenko, I. Vasilieva, S. Kovalenko

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Investigations for new effective and less toxic antimicrobials agents are always up-to-date. The tetrazole derivatives are quite interesting objects as for synthesis as well as for pharmacological screening. Thus, some derivatives of tetrazole demonstrated antimicrobial activity, namely 5-phenyl-tetrazolo[1,5-c]quinazoline was effective one against Staphylococcus aureus and Esherichia faecalis (MIC = 250 mg/L). Besides, investigation of the 9-bromo(chloro)-5-morpholin(piperidine)-4-yl-tetrazolo[1,5-c]quinazoline’s antimicrobial activity against Esherichia coli and Enterococcus faecalis, Pseudomonas aeruginosa and Staphylococcus aureus revealed that sensitivity of Gram-positive bacteria to the compounds was higher than that of Gram-negative bacteria. So, our previously synthesized, 31 derivatives of 1-(2-(1H-tetrazol-5-yl)-R1-phenyl)-3-R2-phenyl(ethyl)ureas were decided to test for their in vitro antibacterial activity against Gram-positive bacteria (Staphylococcus aureus ATCC 25923, Enterobacter aerogenes, Enterococcus faecalis ATCC 29212), Gram-negative bacteria (Pseudomonas aeruginosa ATCC 9027, Escherichia coli ATCC 25922, Klebsiella pneumoniae 68) and antifungal properties against Candida albicans ATCC 885653. Agar-diffusion method was used for determination of the preliminary activity compared to well-known reference antimicrobials. All the compounds were dissolved in DMSO at a concentration of 100 μg/disk, using inhibition zone diameter (IZD, mm) as a measure for the antimicrobial activity. The most active turned to be 3 structures, that inhibited several bacterial strains: 1-ethyl-3-(5-fluoro-2-(1H-tetrazol-5-yl)phenyl)urea (1), 1-(4-bromo-2-(1H-tetrazol-5-yl)-phenyl)-3-(4-(trifluoromethyl)phenyl)urea (2) and 1-(4-chloro-2-(1H-tetrazol-5-yl)phenyl)-3-(3-(trifluoromethyl)phenyl)urea (3). IZM (mm) was 40 (Escherichia coli), 25 (Klebsiella pneumonia) for compound 1; 12 (Pseudomonas aeruginosa), 15 (Staphylococcus aureus), 10 (Enterococcus faecalis) for compound 2; 25 (Staphylococcus aureus), 15 (Enterococcus faecalis) for compound 3. The most sensitive to the activity of the substances were Gram-negative bacteria Pseudomonas aeruginosa. While none of compound effected on Candida albicans. Speaking about, reference drugs: Amikacin (30 µg/disk) showed 27 and Ceftazide (30 µg/disk) 25 against Pseudomonas aeruginosa. That is, unfortunately, higher than studied 1-(2-(1H-tetrazol-5-yl)-R1-phenyl)-3-R2-phenyl(ethyl)ureas. Obtained results will be used for further purposeful optimization of the leading compounds in the more effective antimicrobials because of the ever-mounting problem of microorganism’s resistance.

Keywords: antimicrobial, antifungal, compounds, 1-(2-(1H-tetrazol-5-yl)-R1-phenyl)-3-R2-phenyl(ethyl)ureas

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Authors: Forouzan Salehi Fergeni

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Converting the movement intents of a person into commands for action employing brain signals like electroencephalogram signals is a brain-computer interface (BCI) system. When left or right-hand motions are imagined, different patterns of brain activity appear, which can be employed as BCI signals for control. To make better the brain-computer interface (BCI) structures, effective and accurate techniques for increasing the classifying precision of motor imagery (MI) based on electroencephalography (EEG) are greatly needed. Subject dependency and non-stationary are two features of EEG signals. So, EEG signals must be effectively processed before being used in BCI applications. In the present study, after applying an 8 to 30 band-pass filter, a car spatial filter is rendered for the purpose of denoising, and then, a method of analysis of variance is used to select more appropriate and informative channels from a category of a large number of different channels. After ordering channels based on their efficiencies, a sequential forward channel selection is employed to choose just a few reliable ones. Features from two domains of time and wavelet are extracted and shortlisted with the help of a statistical technique, namely the t-test. Finally, the selected features are classified with different machine learning and neural network classifiers being k-nearest neighbor, Probabilistic neural network, support-vector-machine, Extreme learning machine, decision tree, Multi-layer perceptron, and linear discriminant analysis with the purpose of comparing their performance in this application. Utilizing a ten-fold cross-validation approach, tests are performed on a motor imagery dataset found in the BCI competition III. Outcomes demonstrated that the SVM classifier got the greatest classification precision of 97% when compared to the other available approaches. The entire investigative findings confirm that the suggested framework is reliable and computationally effective for the construction of BCI systems and surpasses the existing methods.

Keywords: brain-computer interface, channel selection, motor imagery, support-vector-machine

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Authors: Wale Agbaje

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The aim of this research study is to assess the impact of financial statement fraud on profitability of some selected Nigerian manufacturing firms covering (2002-2016). The specific objectives focused on to ascertain the effect of incorrect asset valuation on return on assets (ROA) and to ascertain the relationship between improper expense recognition and return on assets (ROA). To achieve these objectives, descriptive research design was used for the study while secondary data were collected from the financial reports of the selected firms and website of security and exchange commission. The analysis of covariance (ANCOVA) was used and STATA II econometric method was used in the analysis of the data. Altman model and operating expenses ratio was adopted in the analysis of the financial reports to create a dummy variable for the selected firms from 2002-2016 and validation of the parameters were ascertained using various statistical techniques such as t-test, co-efficient of determination (R2), F-statistics and Wald chi-square. Two hypotheses were formulated and tested using the t-statistics at 5% level of significance. The findings of the analysis revealed that there is a significant relationship between financial statement fraud and profitability in Nigerian manufacturing industry. It was revealed that incorrect assets valuation has a significant positive relationship and so also is the improper expense recognition on return on assets (ROA) which serves as a proxy for profitability. The implication of this is that distortion of asset valuation and expense recognition leads to decreasing profit in the long run in the manufacturing industry. The study therefore recommended that pragmatic policy options need to be taken in the manufacturing industry to effectively manage incorrect asset valuation and improper expense recognition in order to enhance manufacturing industry performance in the country and also stemming of financial statement fraud should be adequately inculcated into the internal control system of manufacturing firms for the effective running of the manufacturing industry in Nigeria.

Keywords: Althman's Model, improper expense recognition, incorrect asset valuation, return on assets

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Authors: Pinel Sebastien, Bourrin François, De Madron Du Rieu Xavier, Ludwig Wolfgang, Arnau Pedro

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Heavy precipitation constitutes a major meteorological threat in the western Mediterranean. Research has investigated the relationship between the states of the Mediterranean Sea and the atmosphere with the precipitation for short temporal windows. However, at a larger temporal scale, the precursor signals of heavy rainfall in the sea and atmosphere have drawn little attention. Moreover, despite ongoing improvements in numerical weather prediction, the medium-term forecasting of rainfall events remains a difficult task. Here, we aim to investigate the influence of early-spring environmental parameters on the following autumnal heavy precipitations. Hence, we develop a machine learning model to predict extreme autumnal rainfall with a 6-month lead time over the Spanish Catalan coastal area, based on i) the sea pattern (main current-LPC and Sea Surface Temperature-SST) at the mesoscale scale, ii) 4 European weather teleconnection patterns (NAO, WeMo, SCAND, MO) at synoptic scale, and iii) the hydrological regime of the main local river (Rhône River). The accuracy of the developed model classifier is evaluated via statistical analysis based on classification accuracy, logarithmic and confusion matrix by comparing with rainfall estimates from rain gauges and satellite observations (CHIRPS-2.0). Sensitivity tests are carried out by changing the model configuration, such as sea SST, sea LPC, river regime, and synoptic atmosphere configuration. The sensitivity analysis suggests a negligible influence from the hydrological regime, unlike SST, LPC, and specific teleconnection weather patterns. At last, this study illustrates how public datasets can be integrated into a machine learning model for heavy rainfall prediction and can interest local policies for management purposes.

Keywords: extreme hazards, sensitivity analysis, heavy rainfall, machine learning, sea-atmosphere modeling, precipitation forecasting

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Authors: Wenpeng You, Maciej Henneberg

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Background: Sugar consumption has been overwhelmingly advocated as a major dietary offender to obesity prevalence. Meat intake has been hypothesized as an obesity contributor in previous publications, but a moderate amount of meat to be included in our daily diet still has been suggested in many dietary guidelines. Comparable sugar and meat exposure data were obtained to assess the difference in relationships between the two major food groups and obesity prevalence at population level. Methods: Population level estimates of obesity and overweight rates, per capita per day exposure of major food groups (meat, sugar, starch crops, fibers, fats and fruits) and total calories, per capita per year GDP, urbanization and physical inactivity prevalence rate were extracted and matched for statistical analysis. Correlation coefficient (Pearson and partial) comparisons with Fisher’s r-to-z transformation and β range (β ± 2 SE) and overlapping in multiple linear regression (Enter and Stepwise) were used to examine potential differences in the relationships between obesity prevalence and sugar exposure and meat exposure respectively. Results: Pearson and partial correlations (controlled for total calories, physical inactivity prevalence, GDP and urbanization) analyses revealed that sugar and meat exposures correlated to obesity and overweight prevalence significantly. Fisher's r-to-z transformation did not show statistically significant difference in Pearson correlation coefficients (z=-0.53, p=0.5961) or partial correlation coefficients (z=-0.04, p=0.9681) between obesity prevalence and both sugar exposure and meat exposure. Both Enter and Stepwise models in multiple linear regression analysis showed that sugar and meat exposure were most significant predictors of obesity prevalence. Great β range overlapping in the Enter (0.289-0.573) and Stepwise (0.294-0.582) models indicated statistically sugar and meat exposure correlated to obesity without significant difference. Conclusion: Worldwide sugar and meat exposure correlated to obesity prevalence at the same extent. Like sugar, minimal meat exposure should also be suggested in the dietary guidelines.

Keywords: meat, sugar, obesity, energy surplus, meat protein, fats, insulin resistance

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Authors: Kholood A. Baron

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While radiologist numbers specialized in spine interventional procedures are limited in Kuwait, the number of patients demanding these procedures is increasing rapidly. Due to this high demand, the workload of radiologists is increasing, which might represent a radiation exposure concern. During these procedures, the doctor’s hands are in very close proximity to the main radiation beam/ if not within it. The aim of this study is to measure the radiation dose for radiologists during several interventional procedures for the spine. Methods: Two doctors carrying different workloads were included. (DR1) was performing procedures in the morning and afternoon shifts, while (DR2) was performing procedures in the morning shift only. Comparing the radiation exposures that the hand of each doctor is receiving will assess radiation safety and help to set up workload regulations for radiologists carrying a heavy schedule of such procedures. Entrance Skin Dose (ESD) was measured via TLD (ThermoLuminescent Dosimetry) placed at the right wrist of the radiologists. DR1 was covering the morning shift in one hospital (Mubarak Al-Kabeer Hospital) and the afternoon shift in another hospital (Dar Alshifa Hospital). The TLD chip was placed in his gloves during the 2 shifts for a whole week. Since DR2 was covering the morning shift only in Al Razi Hospital, he wore the TLD during the morning shift for a week. It is worth mentioning that DR1 was performing 4-5 spine procedures/day in the morning and the same number in the afternoon and DR2 was performing 5-7 procedures/day. This procedure was repeated for 4 consecutive weeks in order to calculate the ESD value that a hand receives in a month. Results: In general, radiation doses that the hand received in a week ranged from 0.12 to 1.12 mSv. The ESD values for DR1 for the four consecutive weeks were 1.12, 0.32, 0.83, 0.22 mSv, thus for a month (4 weeks), this equals 2.49 mSv and calculated to be 27.39 per year (11 months-since each radiologist have 45 days of leave in each year). For DR2, the weekly ESD values are 0.43, 0.74, 0.12, 0.61 mSv, and thus, for a month, this equals 1.9 mSv, and for a year, this equals 20.9 mSv /year. These values are below the standard level and way below the maximum limit of 500 mSv per year (set by ICRP = International Council of Radiation Protection). However, it is worth mentioning that DR1 was a senior consultant and hence needed less fluoro-time during each procedure. This is evident from the low ESD values of the second week (0.32) and the fourth week (0.22), even though he was performing nearly 10-12 procedures in a day /5 days a week. These values were lower or in the same range as those for DR2 (who was a junior consultant). This highlighted the importance of increasing the radiologist's skills and awareness of fluoroscopy time effect. In conclusion, the radiation dose that radiologists received during spine interventional radiology in our setting was below standard dose limits.

Keywords: radiation protection, interventional radiology dosimetry, ESD measurements, radiologist radiation exposure

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Authors: Moses Mwangi, Geert Verbeke, Geert Molenberghs

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Cross-over designs are commonly used in randomized clinical trials to estimate efficacy of a new treatment with respect to a reference treatment (placebo or standard). The main advantage of using cross-over design over conventional parallel design is its flexibility, where every subject become its own control, thereby reducing confounding effect. Jones & Kenward, discuss in detail more recent developments in the analysis of cross-over trials. We revisit the simple piecewise linear mixed-effects model, proposed by Mwangi et. al, (in press) for its first application in the analysis of cross-over trials. We compared performance of the proposed piecewise linear mixed-effects model with two commonly cited statistical models namely, (1) Grizzle model; and (2) Jones & Kenward model, used in estimation of the treatment effect, in the analysis of randomized cross-over trial. We estimate two performance measurements (mean square error (MSE) and coverage probability) for the three methods, using data simulated from the proposed piecewise linear mixed-effects model. Piecewise linear mixed-effects model yielded lowest MSE estimates compared to Grizzle and Jones & Kenward models for both small (Nobs=20) and large (Nobs=600) sample sizes. It’s coverage probability were highest compared to Grizzle and Jones & Kenward models for both small and large sample sizes. A piecewise linear mixed-effects model is a better estimator of treatment effect than its two competing estimators (Grizzle and Jones & Kenward models) in the analysis of cross-over trials. The data generating mechanism used in this paper captures two time periods for a simple 2-Treatments x 2-Periods cross-over design. Its application is extendible to more complex cross-over designs with multiple treatments and periods. In addition, it is important to note that, even for single response models, adding more random effects increases the complexity of the model and thus may be difficult or impossible to fit in some cases.

Keywords: Evaluation, Grizzle model, Jones & Kenward model, Performance measures, Simulation

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Authors: Dumont Maxime, Correia Carlos, Sauvage Jean-François, Schwartz Noah, Gray Morgan

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Context: The concept of the segmented telescope is unavoidable to build extremely large telescopes (ELT) in the quest for spatial resolution, but it also allows one to fit a large telescope within a reduced volume of space (JWST) or into an even smaller volume (Standard Cubesat). Cubesats have tight constraints on the computational burden available and the small payload volume allowed. At the same time, they undergo thermal gradients leading to large and evolving optical aberrations. The pupil segmentation comes nevertheless with an obvious difficulty: to co-phase the different segments. The CubeSat constraints prevent the use of a dedicated wavefront sensor (WFS), making the focal-plane images acquired by the science detector the most practical alternative. Yet, one of the challenges for the wavefront sensing is the non-linearity between the image intensity and the phase aberrations. Plus, for Earth observation, the object is unknown and unrepeatable. Recently, several studies have suggested Neural Networks (NN) for wavefront sensing; especially convolutional NN, which are well known for being non-linear and image-friendly problem solvers. Aims: We study in this paper the prospect of using NN to measure the phasing aberrations of a segmented pupil from the focal-plane image directly without a dedicated wavefront sensing. Methods: In our application, we take the case of a deployable telescope fitting in a CubeSat for Earth observations which triples the aperture size (compared to the 10cm CubeSat standard) and therefore triples the angular resolution capacity. In order to reach the diffraction-limited regime in the visible wavelength, typically, a wavefront error below lambda/50 is required. The telescope focal-plane detector, used for imaging, will be used as a wavefront-sensor. In this work, we study a point source, i.e. the Point Spread Function [PSF] of the optical system as an input of a VGG-net neural network, an architecture designed for image regression/classification. Results: This approach shows some promising results (about 2nm RMS, which is sub lambda/50 of residual WFE with 40-100nm RMS of input WFE) using a relatively fast computational time less than 30 ms which translates a small computation burder. These results allow one further study for higher aberrations and noise.

Keywords: wavefront sensing, deep learning, deployable telescope, space telescope

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Authors: L. Kolatorova, J. Vitku, K. Adamcova, M. Simkova, M. Hill, A. Parizek, M. Duskova

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Endocrine disruptors (EDs) are substances leaching from various industrial products, which are able to interfere with the endocrine system. Their harmful effects on human health are generally well-known, and exposure during fetal development may have lasting effects. Fetal exposure and transplacental transport of bisphenol A (BPA) have been recently studied; however, less is known about alternatives such as bisphenol S (BPS), bisphenol F (BPF) and bisphenol AF (BPAF), which have started to appear in consumer products. The human organism is usually exposed to the mixture of EDs, out of which parabens are otherwise known to transfer placenta. The usage of many cosmetic, pharmaceutical and consumer products during the pregnancy that may contain parabens and bisphenols has led to the need for investigation. The aim of the study was to investigate the transplacental transport of BPA, its alternatives, and parabens, and to study their relation to fetal steroidogenesis. BPA, BPS, BPF, BPAF, methylparaben, ethylparaben, propylparaben, butylparaben, benzylparaben and 15 steroids including estrogens, corticoids, androgens and immunomodulatory ones were determined in 27 maternal (37th week of gestation) and cord plasma samples using liquid chromatography - tandem mass spectrometry methods. The statistical evaluation of the results showed significantly higher levels of BPA (p=0.0455) in cord plasma compared to maternal plasma. The results from multiple regression models investigated that in cord plasma, methylparaben, propylparaben and the sum of all measured parabens were inversely associated with testosterone levels. To our best knowledge, this study is the first attempt to determine the levels of alternative bisphenols in the maternal and cord blood, and also the first study reporting the simultaneous detection of bisphenols, parabens, and steroids in these biological fluids. Our study confirmed the transplacental transport of BPA, with likely accumulation in the fetal compartment. The negative association of cord blood parabens and testosterone levels highlights their possible risks, especially for the development of male fetuses. Acknowledgements: This work was supported by the project MH CR 17-30528 A from the Czech Health Research Council, MH CZ - DRO (Institute of Endocrinology - EÚ, 00023761) and by the MEYS CR (OP RDE, Excellent research - ENDO.CZ).

Keywords: bisphenol, endocrine disruptor, paraben, pregnancy, steroid

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Authors: Tondani Mudau, Sherine B. Van Wyk, Zuhayr Kafaar, Janan Dietrich

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Female adolescents residing in a patriarchal society such as South Africa are more inclined to embrace feminine ideologies. Internalizing these ideologies may expose female adolescents to mental health challenges such as depression and anxiety. This study explored whether the internalisation of adolescent femininity ideologies namely, objectified relationship with own body (ORB) and inauthentic self in relationships (ISR) predicted anxiety and depression in late female adolescents at Stellenbosch University. The sample of the study consisted of 1451 (18-24) female undergraduate and postgraduate students enrolled at Stellenbosch University. The mean age of the participants was 20 (SD=1.46), and most participants (39.7%) were first-year students. The study employed a cross-sectional quantitative research design. Data was collected through an online self-completion survey, the survey consisted of three sections, the first section asked biographical questions regarding age, gender, race and family background. The second section measured the internalisation of feminine ideologies by using the adolescent femininity ideology scale which has two subscales namely inauthentic self in relationship with others (ISR) and objectified relationship with one’s own body (ORB). The ISR scale had the Cronbach Alpha of 0.76, and the ORB scale had the Cronbach Alpha of 0.83. The third section measured mental health (depression and anxiety) by using the Hopkins Symptoms 25-checklist which had the Cronbach Alpha of 0.93. Data were analysed through multiple linear regression from IBM SPSS (Statistical Package for the Social Sciences Version 24). The overall results of the multiple linear regression showed that The AFIS combination accounted for 14% for anxiety as measured by the Hopkins Symptoms Checklist R² = .142, F (2, 682) = 56.431, p < .001. The combination also accounted for 24% for depression as measured by the Hopkins Symptoms Checklist R² = .239, F (2, 682) = 106.971, p < .0. The findings in this study affirm the objectification and feminist theory contentions that internalising femininity ideologies (ISR and ORB) predict negative mental health in female adolescents.

Keywords: adolescents, anxiety, depression, feminine ideologies, inauthentic self, mental health, self-objectification, South Africa

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Authors: Vera Lukasova, Eva Filova, Jana Dankova, Vera Sovkova, Matej Daniel, Michala Rampichova

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Proper bone implants should promote fast adhesion of cells, stimulate cell differentiation and support the formation of bone tissue. Nowadays titanium is used as a biocompatible material capable of bone tissue integration. This study was focused on comparison of bioactive properties of two titanium alloys - beta titanium alloy Ti36Nb6Ta and standard medical titanium alloy Ti6A14V. The advantage of beta titanium alloy Ti36Nb6Ta is mainly that this material does not contain adverse elements like vanadium or aluminium. Titanium alloys were sterilized in ethanol, placed into 48 well plates and seeded with porcine mesenchymal stem cells. Cells were cultivated for 14 days in standard growth cultivation media with osteogenic supplements. Cell metabolic activity was quantified using MTS assay (Promega). Cell adhesion on day 1 and cell proliferation on further days were verified immunohistochemically using beta-actin monoclonal antibody and secondary antibody conjugated with AlexaFluor®488. Differentiation of cells was evaluated using alkaline phosphatase assay. Additionally, gene expression of collagen I was measured by qRT-PCR. Porcine mesenchymal stem cells adhered and spread well on beta titanium alloy Ti36Nb6Ta on day 1. During the 14 days’ time period the cells were spread confluently on the surface of the beta titanium alloy Ti36Nb6Ta. The metabolic activity of cells increased during the whole cultivation period. In comparison to standard medical titanium alloy Ti6A14V, we did not observe any differences. Moreover, the expression of collagen I gene revealed no statistical differences between both titanium alloys. Therefore, a beta titanium alloy Ti36Nb6Ta promotes cell adhesion, metabolic activity, proliferation and collagen I expression equally to standard medical titanium alloy Ti6A14V. Thus, beta titanium is a suitable material that provides sufficient biocompatible properties. This project was supported by the Czech Science Foundation: grant No. 16-14758S.

Keywords: beta titanium alloy, biocompatibility, differentiation, mesenchymal stem cells

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Authors: Helena Bolini, Erick Esmerino, Adriano Cruz, Juliana Paixao

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The currently concern for health has increased demand for low-calorie ingredients and functional foods as probiotics. Understand the reasons that infer on food choice, besides a challenging task, it is important step for development and/or reformulation of existing food products. The use of appropriate multivariate statistical techniques, such as External Preference Map (PrefMap), associated with regression by Partial Least Squares (PLS) can help in determining those factors. Thus, this study aimed to determine, through PLS regression analysis, the sensory attributes considered drivers of liking in probiotic petit suisse cheeses, strawberry flavor, sweetened with different sweeteners. Five samples in same equivalent sweetness: PROB1 (Sucralose 0.0243%), PROB2 (Stevia 0.1520%), PROB3 (Aspartame 0.0877%), PROB4 (Neotame 0.0025%) and PROB5 (Sucrose 15.2%) determined by just-about-right and magnitude estimation methods, and three commercial samples COM1, COM2 and COM3, were studied. Analysis was done over data coming from QDA, performed by 12 expert (highly trained assessors) on 20 descriptor terms, correlated with data from assessment of overall liking in acceptance test, carried out by 125 consumers, on all samples. Sequentially, results were submitted to PLS regression using XLSTAT software from Byossistemes. As shown in results, it was possible determine, that three sensory descriptor terms might be considered drivers of liking of probiotic petit suisse cheese samples added with sweeteners (p<0.05). The milk flavor was noticed as a sensory characteristic with positive impact on acceptance, while descriptors bitter taste and sweet aftertaste were perceived as descriptor terms with negative impact on acceptance of petit suisse probiotic cheeses. It was possible conclude that PLS regression analysis is a practical and useful tool in determining drivers of liking of probiotic petit suisse cheeses sweetened with artificial and natural sweeteners, allowing food industry to understand and improve their formulations maximizing the acceptability of their products.

Keywords: acceptance, consumer, quantitative descriptive analysis, sweetener

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Authors: Andreas Aceranti, Simonetta Vernocchi, Marco Colorato, Daniel Zaccariello

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Our study explores the usefulness of implementing facial expression recognition capabilities and using the Facial Action Coding System (FACS) in contexts where the other person is wearing a mask. In the communication process, the subjects use a plurality of distinct and autonomous reporting systems. Among them, the system of mimicking facial movements is worthy of attention. Basic emotion theorists have identified the existence of specific and universal patterns of facial expressions related to seven basic emotions -anger, disgust, contempt, fear, sadness, surprise, and happiness- that would distinguish one emotion from another. However, due to the COVID-19 pandemic, we have come up against the problem of having the lower half of the face covered and, therefore, not investigable due to the masks. Facial-emotional behavior is a good starting point for understanding: (1) the affective state (such as emotions), (2) cognitive activity (perplexity, concentration, boredom), (3) temperament and personality traits (hostility, sociability, shyness), (4) psychopathology (such as diagnostic information relevant to depression, mania, schizophrenia, and less severe disorders), (5) psychopathological processes that occur during social interactions patient and analyst. There are numerous methods to measure facial movements resulting from the action of muscles, see for example, the measurement of visible facial actions using coding systems (non-intrusive systems that require the presence of an observer who encodes and categorizes behaviors) and the measurement of electrical "discharges" of contracting muscles (facial electromyography; EMG). However, the measuring system invented by Ekman and Friesen (2002) - "Facial Action Coding System - FACS" is the most comprehensive, complete, and versatile. Our study, carried out on about 1,500 subjects over three years of work, allowed us to highlight how the movements of the hands and upper part of the face change depending on whether the subject wears a mask or not. We have been able to identify specific alterations to the subjects’ hand movement patterns and their upper face expressions while wearing masks compared to when not wearing them. We believe that finding correlations between how body language changes when our facial expressions are impaired can provide a better understanding of the link between the face and body non-verbal language.

Keywords: facial action coding system, COVID-19, masks, facial analysis

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Authors: Sohyoung Won, Heebal Kim, Dajeong Lim

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Genomic prediction is an effective way to measure the abilities of livestock for breeding based on genomic estimated breeding values, statistically predicted values from genotype data using best linear unbiased prediction (BLUP). Using haplotypes, clusters of linked single nucleotide polymorphisms (SNPs), as markers instead of individual SNPs can improve the reliability of genomic prediction since the probability of a quantitative trait loci to be in strong linkage disequilibrium (LD) with markers is higher. To efficiently use haplotypes in genomic prediction, finding optimal ways to define haplotypes is needed. In this study, 770K SNP chip data was collected from Hanwoo (Korean cattle) population consisted of 2506 cattle. Haplotypes were first defined in three different ways using 770K SNP chip data: haplotypes were defined based on 1) length of haplotypes (bp), 2) the number of SNPs, and 3) k-medoids clustering by LD. To compare the methods in parallel, haplotypes defined by all methods were set to have comparable sizes; in each method, haplotypes defined to have an average number of 5, 10, 20 or 50 SNPs were tested respectively. A modified GBLUP method using haplotype alleles as predictor variables was implemented for testing the prediction reliability of each haplotype set. Also, conventional genomic BLUP (GBLUP) method, which uses individual SNPs were tested to evaluate the performance of the haplotype sets on genomic prediction. Carcass weight was used as the phenotype for testing. As a result, using haplotypes defined by all three methods showed increased reliability compared to conventional GBLUP. There were not many differences in the reliability between different haplotype defining methods. The reliability of genomic prediction was highest when the average number of SNPs per haplotype was 20 in all three methods, implying that haplotypes including around 20 SNPs can be optimal to use as markers for genomic prediction. When the number of alleles generated by each haplotype defining methods was compared, clustering by LD generated the least number of alleles. Using haplotype alleles for genomic prediction showed better performance, suggesting improved accuracy in genomic selection. The number of predictor variables was decreased when the LD-based method was used while all three haplotype defining methods showed similar performances. This suggests that defining haplotypes based on LD can reduce computational costs and allows efficient prediction. Finding optimal ways to define haplotypes and using the haplotype alleles as markers can provide improved performance and efficiency in genomic prediction.

Keywords: best linear unbiased predictor, genomic prediction, haplotype, linkage disequilibrium

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Authors: Vandana Mishra, Niladri Sekhar Dash, Jayshree Charkraborty

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This present paper focuses on the application of corpus linguistics techniques for critical discourse analysis (CDA) of Hindi newspapers. While Corpus linguistics is the study of language as expressed in corpora (samples) of 'real world' text, CDA is an interdisciplinary approach to the study of discourse that views language as a form of social practice. CDA has mainly been studied from a qualitative perspective. However, we can say that recent studies have begun combining corpus linguistics with CDA in analyzing large volumes of text for the study of existing power relations in society. The corpus under our study is also of a sizable amount (1 million words of Hindi newspaper texts) and its analysis requires an alternative analytical procedure. So, we have combined both the quantitative approach i.e. the use of corpus techniques with CDA’s traditional qualitative analysis. In this context, we have focused on the Keyword Analysis Sorting Concordance Lines of the selected Keywords and calculating collocates of the keywords. We have made use of the Wordsmith Tool for all these analysis. The analysis starts with identifying the keywords in the political news corpus when compared with the main news corpus. The keywords are extracted from the corpus based on their keyness calculated through statistical tests like chi-squared test and log-likelihood test on the frequent words of the corpus. Some of the top occurring keywords are मोदी (Modi), भाजपा (BJP), कांग्रेस (Congress), सरकार (Government) and पार्टी (Political party). This is followed by the concordance analysis of these keywords which generates thousands of lines but we have to select few lines and examine them based on our objective. We have also calculated the collocates of the keywords based on their Mutual Information (MI) score. Both concordance and collocation help to identify lexical patterns in the political texts. Finally, all these quantitative results derived from the corpus techniques will be subjectively interpreted in accordance to the CDA’s theory to examine the ways in which political news discourse produces social and political inequality, power abuse or domination.

Keywords: critical discourse analysis, corpus linguistics, Hindi newspapers, power relations

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Authors: Andy S.K. Cheng, Samuel Leung, Cindy Kwok, Hector Tsang

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Background: Telephone counselling is one of the essential interventions that can be found in most of the Employee Assistance Programs (EAP). The purposes of this study were to (1) explore the trend of the telephone counselling from 2003-2016 in Hong Kong; (2) explore which EAP issue requires more follow-up; and 3) examine the relationship between the EAP issues and demographic data such as gender and job ranking. Method: Date of EAP services usage was collected from EAP providers in Hong Kong during 2003-2016. EAP issues were categorized into two domains, namely workplace issues and personal issues. Each domain has 12 sub-categories. Two hypotheses were formulated in this study (1) there was a gender difference in EAP issues and the follow-up hours; and (2) there was a significant difference between job ranking, EAP issues and follow-up hours. Results: A total of eight hundred and ninety-three valid cases were identified for analysis. Of them, three hundred and forty-three cases sought for follow-up. The duration of follow-up by hours was calculated for each of the follow-up cases. The results of the study shows that the top three workplace issues that required the longest duration of follow-up were (1) workload, (2) supervisor-subordinate relationship; and (3) team member’s relationship. On the other hand, the top three personal issues that required the longest duration of follow-up were (1) parenting/parent-child relationship, (2) family care, and (3) marital relationship. Two-way ANOVA was performed to compare the total follow-up hours (excluding first intake) between gender and EAP issues. There was no statistical significance for gender (p =.891), but a statistically significant main effect for EAP issues (p <.001) was found. Post-hoc analysis (Tukey’s test) showed that total follow-up hour in personal issues was statistically significant higher than that in handling workplace issues (p <.001). However, there was no statistically significant interaction effect between gender and EAP issues (p=.879) and between job ranking and EAP issues (p=.843). Conclusion: Telephone counselling is a very common intervention in addressing EAP issues arising from workplace and personal level in Hong Kong. It was frequently used to handle interpersonal relationships and the service usage was independent of gender and job ranking.

Keywords: employee assistance program, follow-up time, interpersonal relationships, telephone counselling

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Authors: Maria A. Castillo H., Andres R. Leandro, Jose F. Bienvenido B.

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In 2015, Guatemala officially adopted the Sustainable Development Goals (SDG) according to the 2030 Agenda agreed by the United Nations Organization. In 2016, these objectives and goals were reviewed, and the National Priorities were established within the K'atún 2032 National Development Plan. In 2019 and 2021, progress was evaluated with 120 defined indicators, and the need to improve quality and availability of statistical data necessary for the analysis of sustainability indicators was detected, so the values to be reached in 2024 and 2032 were adjusted. The need for greater agricultural technology is one of the priorities established within SDG 2 "Zero Hunger". Within this area, protected agricultural production provides greater productivity throughout the year, reduces the use of chemical products to control pests and diseases, reduces the negative impact of climate and improves product quality. During the crisis caused by Covid-19, there was an increase in exports of fruits and vegetables produced in greenhouses from Guatemala. However, this information has not been considered in the 2021 revision of the Plan. The objective of this study is to evaluate the information available on Greenhouse Agricultural Production and its integration into the Sustainability Indicators for Guatemala. This study was carried out in four phases: 1. Analysis of the Goals established for SDG 2 and the indicators included in the K'atún Plan. 2. Analysis of Environmental, Social and Economic Indicator Models. 3. Definition of territorial levels in 2 geographic scales: Departments and Municipalities. 4. Diagnosis of the available data on technological agricultural production with emphasis on Greenhouses at the 2 geographical scales. A summary of the results is presented for each phase and finally some recommendations for future research are added. The main contribution of this work is to improve the available data that allow the incorporation of some agricultural technology indicators in the established goals, to evaluate their impact on Food Security and Nutrition, Employment and Investment, Poverty, the use of Water and Natural Resources, and to provide a methodology applicable to other production models and other geographical areas.

Keywords: greenhouses, protected agriculture, sustainable indicators, Guatemala, sustainability, SDG

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Authors: Semaw A., Awet H., Yohannes M.

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Background: Hepatitis B Virus (HBV) is a major global public health problem. Individuals living in Sub-Sahara Africa have 60% lifetime risk of acquiring HBV infection. Evidences showed that 80-90% of those born from infected mothers developed chronic HBV. Perinatal HBV transmission is a major determinant of HBV carrier status, its chronic squeal and maintains HBV transmission across generations. Method: Institution based cross-sectional study was conducted among 406 pregnant mothers attending Antenatal clinics at Mekelle and Ayder referral hospital from January 30 to April 1/2014. Epidata version 3.1 was used for data entry and SPSS version 21 statistical software was used for data cleaning, management and finally determine associated factors of hepatitis B surface antigen adjusting important confounders using multivariable logistic regression analysis at 5% level of significance. Result: The overall prevalence of hepatitis B surface antigen among pregnant women was 33 (8.1%). The socio-demographic characteristic of the study population showed that there is high positivity among secondary school 189 (46.6%). In the multivariable logistic regression analysis, history of a contact with individuals who had history of hepatitis B infection or jaundice and lifetime number of multiple sexual partners were found to be significantly associated with HBsAg positivity at AOR = 3.73 95%C.I (1.373-10.182) and AOR = 2.57 95%C.I (1.173-5.654), respectively. Moreover, Human Immunodeficiency Virus (HIV) and HBV confection rate was found 3.6%. Conclusion: This study has shown that HBV prevalence in pregnant women is highly prevalent (8.1%) in the study area. Contact with individuals who had a history of hepatitis or have jaundice and report of multiple lifetime sexual partnership were associated with hepatitis B infection. Education about HBV transmission and prevention as well as screening all pregnant mothers shall be sought to reduce the serious public health crisis of HBV.

Keywords: HBsAg, hepatitis B, pregnant women, prevalence

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Authors: Paola Causin, Andrea Aspri, Alessandro Benfenati

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Diffuse Optical Tomography (DOT) is an emergent medical imaging technique which employs NIR light to estimate the spatial distribution of optical coefficients in biological tissues for diagnostic purposes, in a noninvasive and non-ionizing manner. DOT reconstruction is a severely ill-conditioned problem due to prevalent scattering of light in the tissue. In this contribution, we present our research in adopting hybrid knowledgedriven/data-driven approaches which exploit the existence of well assessed physical models and build upon them neural networks integrating the availability of data. Namely, since in this context regularization procedures are mandatory to obtain a reasonable reconstruction [1], we explore the use of neural networks as tools to include prior information on the solution. 2. Materials and Methods The idea underlying our approach is to leverage neural networks to solve PDE-constrained inverse problems of the form 𝒒 ∗ = 𝒂𝒓𝒈 𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃), (1) where D is a loss function which typically contains a discrepancy measure (or data fidelity) term plus other possible ad-hoc designed terms enforcing specific constraints. In the context of inverse problems like (1), one seeks the optimal set of physical parameters q, given the set of observations y. Moreover, 𝑦̃ is the computable approximation of y, which may be as well obtained from a neural network but also in a classic way via the resolution of a PDE with given input coefficients (forward problem, Fig.1 box ). Due to the severe ill conditioning of the reconstruction problem, we adopt a two-fold approach: i) we restrict the solutions (optical coefficients) to lie in a lower-dimensional subspace generated by auto-decoder type networks. This procedure forms priors of the solution (Fig.1 box ); ii) we use regularization procedures of type 𝒒̂ ∗ = 𝒂𝒓𝒈𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃)+ 𝑹(𝒒), where 𝑹(𝒒) is a regularization functional depending on regularization parameters which can be fixed a-priori or learned via a neural network in a data-driven modality. To further improve the generalizability of the proposed framework, we also infuse physics knowledge via soft penalty constraints (Fig.1 box ) in the overall optimization procedure (Fig.1 box ). 3. Discussion and Conclusion DOT reconstruction is severely hindered by ill-conditioning. The combined use of data-driven and knowledgedriven elements is beneficial and allows to obtain improved results, especially with a restricted dataset and in presence of variable sources of noise.

Keywords: inverse problem in tomography, deep learning, diffuse optical tomography, regularization

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Authors: Bulcha Belay Etana, Benny Malengier, Debelo Oljira, Janarthanan Krishnamoorthy, Lieva Vanlangenhove

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Electromyography (EMG) is a technique used to measure the electrical activity of muscles. EMG can be used to assess muscle function in a variety of settings, including clinical, research, and sports medicine. The aim of this study was to develop a wearable textile sensor for EMG monitoring. The sensor was designed to be soft, stretchable, and washable, making it suitable for long-term use. The sensor was fabricated using a conductive thread material that was embroidered onto a fabric substrate. The sensor was then connected to a microcontroller unit (MCU) and a Wi-Fi-enabled module. The MCU was programmed to acquire the EMG signal and transmit it wirelessly to the Wi-Fi-enabled module. The Wi-Fi-enabled module then sent the signal to a server, where it could be accessed by a computer or smartphone. The sensor was able to successfully acquire and transmit EMG signals from a variety of muscles. The signal quality was comparable to that of commercial EMG sensors. The development of this sensor has the potential to improve the way EMG is used in a variety of settings. The sensor is soft, stretchable, and washable, making it suitable for long-term use. This makes it ideal for use in clinical settings, where patients may need to wear the sensor for extended periods of time. The sensor is also small and lightweight, making it ideal for use in sports medicine and research settings. The data for this study was collected from a group of healthy volunteers. The volunteers were asked to perform a series of muscle contractions while the EMG signal was recorded. The data was then analyzed to assess the performance of the sensor. The EMG signals were analyzed using a variety of methods, including time-domain analysis and frequency-domain analysis. The time-domain analysis was used to extract features such as the root mean square (RMS) and average rectified value (ARV). The frequency-domain analysis was used to extract features such as the power spectrum. The question addressed by this study was whether a wearable textile sensor could be developed that is soft, stretchable, and washable and that can successfully acquire and transmit EMG signals. The results of this study demonstrate that a wearable textile sensor can be developed that meets the requirements of being soft, stretchable, washable, and capable of acquiring and transmitting EMG signals. This sensor has the potential to improve the way EMG is used in a variety of settings.

Keywords: EMG, electrode position, smart wearable, textile sensor, IoT, IoT-integrated textile sensor

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Authors: Komal Khan, Hafsa Zaneb, Saima Masood, Muhammad Younus, Sanan Raza

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Cigarette smoke induces many physiological and pathological changes in respiratory tract like goblet cell hyperplasia and regional distention of airspaces. It is also associated with elevation of inflammatory profiles in different airway compartments. As probiotics are generally known to promote mucosal tolerance, it was postulated that prophylactic use of probiotics can be helpful in reduction of respiratory damage induced by cigarette smoke exposure. Twenty-four adult mice were randomly divided into three groups (cigarette-smoke (CS) group, cigarette-smoke+ Lactobacillus (CS+ P) group, control (Cn) group), each having 8 mice. They were exposed to cigarette smoke for 28 days (6 cigarettes/ day for 6 days/week). Wright-Giemsa staining of bronchoalveolar lavage fluid (BALF) was performed in three mice per group. Tissue samples of trachea and lungs of 7 mice from each group were processed by paraffin embedding technique for haematoxylin & eosin (H & E) and alcian blue- periodic acid-Schiff (AB-PAS) staining. Then trachea (goblet cell number, ratio and loss of cilia) and lungs (airspace distention) were studied. The results showed that the number of goblet cells was increased in CS group as a result of defensive mechanism of the respiratory system against irritating substances. This study also revealed that the cells of CS group having acidic glycoprotein were found to be higher in quantity as compared to those containing neutral glycoprotein. However, CS + P group showed a decrease in goblet cell index due to enhanced immunity by prophylactically used probiotics. Moreover, H & E stained tracheas showed significant loss of cilia in CS group due to propelling of mucous but little loss in CS + P group because of having good protective tracheal epithelium. In lungs, protection of airspaces was also much more evident in CS+ P group as compared to CS group having distended airspaces, especially at 150um distance from terminal bronchiole. In addition, a comprehensive analysis of inflammatory cells population of BALF showed neutrophilia and eosinophilia was significantly reduced in CS+ P group. This study proved that probiotics are found to be useful for reduction of changes in micro-architecture of the respiratory system. Thus, dietary supplementation of probiotic as prophylactic measure can be useful in achieving immunomodulatory effects.

Keywords: cigarette smoke, probiotics, goblet cells, airspace enlargement, BALF

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Authors: Barbara Farinon, Maurizio E. Picarella, Lorenzo Mancini, Andrea Mazzucato

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Italy is notoriously a secondary center of diversification for cultivated tomatoes (Solanum lycopersicum L.). The study of phenotypic and genetic diversity in landrace collections is important for germplasm conservation and biodiversity protection. Here, we set up to study the germplasm collected in the region of Lazio in Central Italy with a focus on the distinctiveness among landraces and the attribution of membership to unnamed accessions. Our regional collection included 30 accessions belonging to six different locally recognized landraces and 21 unnamed accessions. All accessions were gathered in Lazio and belonged to the collection held at the Regional Agency for the Development and Innovation of Agriculture in Lazio (ARSIAL, in the application of the Regional Act n. 15/2000, funded by Lazio Rural Development Plan 2014 – 2020 Agro-environmental Measure, Action 10.2.1) and at the University of Tuscia. We included 13 control genotypes as references. The collection showed wide phenotypic variability for several traits, such as fruit weight (range 14-277 g), locule number (2-12), shape index (0.54-2.65), yield (0.24-3.08 kg/plant), and soluble solids (3.4-7.5 °B). A few landraces showed uncommon phenotypes, such as potato leaf, colorless fruit epidermis, or delayed ripening. Multivariate analysis of 25 cardinal phenotypic variables grouped the named varieties and allowed to assign of some of the unnamed to recognized groups. A case study for distinctiveness is presented for the flattened-ribbed types that presented overlapping distribution according to the phenotypic data. Molecular markers retrieved by previous studies revealed differences compared to the phenotyping clustering, indicating that the named varieties “Scatolone di Bolsena” and “Pantano Romanesco” belong to the Marmande group, together with the reference landrace from Tuscany “Costoluto Fiorentino”. Differently, the landrace “Spagnoletta di Formia e Gaeta” was clearly distinct from the former at the molecular level. Therefore, a genotypic analysis of the analyzed collection appears needed to better define the molecular distinctiveness among the flattened-ribbed accessions, as well as to properly attribute the membership group of the unnamed accessions.

Keywords: distinctiveness, flattened-ribbed fruits, regional landraces, tomato

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