"Time Use of Mothers and Fathers in Hard Times and Better Times: The US Business Cycle of 2003-10"

The US economic crisis and recession of 2007-09 accelerated the convergence of women's and men's employment rates as men experienced disproportionate job losses and women's entry into the labor force gathered pace. Using the American Time Use Survey (ATUS) data for 2003-10, this study examines whether the narrowing gap in paid work over this period was mirrored in unpaid work, personal care, and leisure time. We find that the gender gap in unpaid work followed a U-pattern, narrowing during the recession but widening afterward. Through segregation analysis, we trace this U-pattern to the slow erosion of gender segregation in housework and, through a standard decomposition analysis of time use by employment status, show that this pattern was mainly driven by movement toward gender-equitable unpaid hours of women and men with the same employment status. In addition, gender inequality in leisure time increased over the business cycle.Economics of Gender; Unemployment; Time Use; Economic Crises

Optimization of deposition parameters for thin film lithium phosphorus oxynitride (LiPON)

Thin film of lithium phosphorus oxynitride (Lipon) was successfully deposited by radio frequency (RF) magnetron sputtering technique from Li3PO4 target. The power on the target was 150 W and optimal deposition pressure of N2/Ar = ~3/1 was of 2 mTorr. Analysis of the film was done by AFM, FTIR and Raman spectroscopy, which showed incorporation of nitrogen into the film as both triply, Nt, and doubly, Nd, coordinated form. The impedance spectroscopy measurements was carried out and revealed the ionic conductivity of the sample to be 8.6 × 10 − 8 S cm-1 for optimum RF power and gas flow conditions. The electrochemical properties investigations and further development of this work will be presented at the Meeting

International trade and wage discrimination : evidence from East Asia

This study explores the impact of competition from international trade on wage discrimination by sex in two highly open economies. If discrimination is costly, as posited in neoclassical theory based on Becker (1959), then increased industry competitiveness from international trade reduces the incentive for employers to discriminate against women. Alternatively, increased international trade may contribute to employment segregation and reduced bargaining power for women to achieve wage gains. The approach centers on comparing the impact of international trade on wage discrimination in concentrated and nonconcentrated sectors. The effect of international trade competition is expected to be more pronounced in concentrated sectors, where employers can use excess profits in the absence of trade to cover the costs of discrimination. Wage discrimination is proxied by the portion of the wage gap that cannot be explained by observable skill differences between men and women. The empirical model is estimated using a rich panel data set of residual wage gaps, trade ratios, and alternative measures of domestic concentration for Taiwan (China) and the Republic of Korea during the 1980s and 1990s. Results indicate that in contrast to the implications of neoclassical theory, competition from foreign trade in concentrated industries is positively associated with wage discrimination. These results imply that concerted efforts to enforce equal pay legislation and apply effective equal opportunity legislation are crucial for ensuring that women's pay gains will match those of men in a competitive environment.Economic Theory&Research,Water and Industry,Environmental Economics&Policies,Public Health Promotion,Health Monitoring&Evaluation,Health Monitoring&Evaluation,Water and Industry,Environmental Economics&Policies,Economic Theory&Research,TF054105-DONOR FUNDED OPERATION ADMINISTRATION FEE INCOME AND EXPENSE ACCOUNT

Plural temporalities of vision: temporalities and fragmentations in art and beyond

This thesis aims to look at various possible ways in which temporality is concerned in visual arts. I consider that time exceeds being an object of perception and leads to an emergence of a fragmented notion of 'otherness', which interrupts constitution of a projective difference between the subject and the object. I chose my examples from the contemporary art practices - since the early sixties - which have been critical of the ways in which art was understood as an object of a single thought or belief. My examples may look as if they were analysed according to a specific history. However, they are critical of conceptualisation of things according to a single order that introduces an illusionary belief of space and time as if they were concrete things. Rather, I consider an emergence of multiple temporalities communicating with its viewer significant since such an understanding introduces a sense of becoming replaced by being not only in art but also in everything. Fragmentation is considered not as a distorted version of unity but as that which introduces the divisibility of a conception of unity

Determination of input parameters of the neural network model, intended for phoneme recognition of a voice signal in the systems of distance learning

The article is devoted to the problem of voicesignals recognition means introduction in the system of distancelearning. The results of the conducted research determine theprospects of neural network means of phoneme recognition.It is also shown that the main diculties of creation of theneural network model, intended for recognition of phonemesin the system of distance learning, are connected with theuncertain duration of a phoneme-like element. Due to thisreason for recognition of phonemes, it is impossible to usethe most eective type of neural network model on the basisof a multilayered perceptron, at which the number of inputparameters is a xed value. To mitigate this shortcoming, theprocedure, allowing to transform the non-stationary digitizedvoice signal to the xed quantity of mel-cepstral coecients,which are the basis for calculation of input parameters ofthe neural network model, is developed. In contrast to theknown ones, the possibility of linear scaling of phoneme-like elements is available in the procedure. The number ofcomputer experiments conrmed expediency of the fact thatthe use of the oered coding procedure of input parametersprovides the acceptable accuracy of neural network recognitionof phonemes under near-natural conditions of the distancelearning system. Moreover, the prospects of further research inthe eld of development of neural network means of phonemerecognition of a voice signal in the system of distance learningis connected with an increase in admissible noise level. Besides,the adaptation of the oered procedure to various naturallanguages, as well as to other applied tasks, for instance, aproblem of biometric authentication in the banking sector, isalso of great interest

Evaluation of the functional status of patients with chronic obstructive pulmonary disease via the modeling approach

Background: Chronic obstructive pulmonary disease (COPD) is common worldwide. COPD has negative effects on the quality of life of the patient due to restrictions on daily activities. It can cause a major healthcare burden according to the stage and grade of disease.Objective: The purpose of this study was to determine the physical and psychological functional capacity factors affecting patients’ functional performance and to develop a COPD-specific functional status model using these factors.Methods: A group of randomly selected patients (n=183) diagnosed with COPD at a university hospital in Turkey comprised the study sample. Physical examinations were carried out on all patients and they completed questionnaires that included socio demographic and disease characteristics, the Hospital Anxiety and Depression Scale, Functional Performance Inventory and Short Form-36 Survey. The proposed theoretical model was analyzed in the LISREL program using the structural equation modeling approach.Results: We found that the independent latent variable of the physiological functional capacity yielded a significant positive effect on the dependent latent variable of functional performance, while the psychological functional capacity produced no significant effect.Conclusions: The COPD-specific functional status model should prove to be an effective and beneficial tool for issues such as treatment maintenance and for the preservation or improvement of patients’ quality of life. [Ethiop.J. Health Dev. 2019; 33(2):81-87]Keywords: Chronic obstructive pulmonary disease, functional status, functional performance, functional capacity, structural equation modelin

Modeling of the decision-making procedure for financing of cyber security means of cloud services by the medium of a bilinear multistep quality game with several terminal surfaces

The model is developed for the intellectualizeddecision-making support system on financing of cyber securitymeans of transport cloud-based computing infrastructures, giventhe limited financial resources. The model is based on the use ofthe theory of multistep games tools. The decision, which givesspecialists a chance to effectively assess risks in the financingprocesses of cyber security means, is found. The model differsfrom the existing approaches in the decision of bilinear multistepquality games with several terminal surfaces. The decision ofbilinear multistep quality games with dependent movements isfound. On the basis of the decision for a one-step game, foundedby application of the domination method and developed forinfinite antagonistic games, the conclusion about risks for playersis drawn. The results of a simulation experiment within programimplementation of the intellectualized decision-making supportsystem in the field of financing of cyber security means of cloudbasedcomputing infrastructures on transport are described. Confirmedduring the simulation experiment, the decision assumesaccounting a financial component of cyber defense strategy atany ratios of the parameters, describing financing process

Automated Screening of Brain Disorders: A Machine Learning Model for MRI Classification

This study investigated the potential of using convolutional neural networks (CNNs) for diagnosing brain diseases based on MRI scans. The aim was to compare the accuracy of CNNs to clinician diagnoses and explore their limitations. In the course of the research, the following theoretical methods were used (literature analysis, generalisation); diagnostic (anamnestic survey, the use of MRI); empirical (study of the experience of medical organisations, regulatory documentation); methods of mathematical statistics and deep machine learning. A high-performing CNN model was developed, exhibiting excellent accuracy for specific diseases such as dementia with Lewy bodies. However, challenges were identified with distinguishing meningiomas and ependymomas, suggesting the need for further training data and refinement. These results, together with the conclusions of the works of other authors, continue the path to the implementation of quality education and artificial intelligence in clinical settings. The possibilities of using AI in neurosurgery and neurology are expanding more and more. The main areas of application are diagnostics, models of outcomes and treatment. Further research should focus on improving AI techniques, increasing databases and involving more patients for each of the diseases, including a larger control group