Exploring personhood in dining experiences of residents with dementia in long-term care facilities

Despite the shift toward using person-centered approaches in dementia care, the relevance and applicability of the concept “personhood” remains unclear in everyday practice and activities, such as mealtime experience for residents with dementia. Based on a qualitative study, this paper presents emergent themes at mealtimes that support or undermine personhood of twenty residents with dementia in two long-term care facilities. Methods of data collection included conversational interviews with residents with dementia, participant observations, focus groups with staff and examination of available documents. Data analysis identified eight themes: (1) outpacing/relaxed pace, (2) withholding/holding, (3) stimulation, (4) disrespect/respect, (5) invalidation/validation, (6) distancing/connecting, (7) disempowerment/empowerment, and (8) ignoring/inclusion. These findings raised questions about current practice and identified areas for improvement. Although staff approaches seemed to have the greatest impact on residents' experiences, the physical environment and organizational milieu were also responsible for hindering and facilitating staff to provide the best possible care and interaction.     

A simulation study of dispatch rules for reducing flow times in semiconductor wafer fabrication

Semiconductor wafer fabrication involves very complex process routing, and reducing flow times is very important. This study reports a search for better dispatch rules for achieving the goal of reducing flow times, while maintaining high machine utilization. We explored a new simulation-based dispatch rule and a queue prediction dispatch rule. Using simulation experiments and an industrial data set, we also compared several other dispatch rules commonly used in semiconductor manufacturing with our proposed dispatch rules. Among these rules, in addition to the simulation-based dispatching rule, the shortest-remaining-processing-time, earliest-due-date and leastslack rules also performed well in terms of reducing flow times. The reasons behind these good rules are discussed in this paper. Based on the previous works and this study, accurately predicting and effectively utilizing future flow times can improve the quality of production management decisions.     

Poverty affects access to regular source of primary care among the general population in Hong Kong

A territory‐wide two‐stage stratified random sample of 2,282 community‐dwelling Hong Kong adults were surveyed between 2014 and 2015 to investigate the association between poverty and regular source of primary care utilization. Poverty was operationalized by income‐poverty and deprivation. About 94% of our sample reported having regular source of primary care (Western and/or Chinese medical practitioner) and about 69% among them were in private sector. Multivariable logistic regression showed that people who were income‐poor and deprived were less likely to have regular source of primary care (income‐poor: OR = 0.523, p = .027; deprived: OR = 0.488, p = .007) and visit private primary care doctors (income‐poor: OR = 0.445, deprived: OR = 0.222, both p < .0001). Those who had chronic diseases were more likely to have regular source of primary care (multimorbid: OR = 10.709, p < .0001), but less likely to access care in the private sector (one chronic disease: OR = 0.690, p = .019; multimorbid: OR = 0.374, p < .0001) than those without. Further, being older and less skilled were significantly associated with less likelihood of visiting a private doctor. Path analysis showed that the number of chronic diseases had significant indirect effect on having regular source of primary care with being income‐poor and deprived as the mediators (β = ?.0183, p = .0016). Therefore, despite a public health‐care system that aims to deny no one from adequate health care for lack of means, regular source of primary care in Hong Kong is found to be pro‐rich. Future policies should tackle the problem of health‐care inequalities to meet the needs of the underprivileged.     

Structural Validation and Multiple Group Assessment of the Short Internalized Homonegativity Scale in Homosexual and Bisexual Men in 38 European Countries: Results From the European MSM Internet Survey

Internalized homonegativity (IH) is the internalization of negative attitudes and assumptions about homosexual people by homosexual people themselves. To measure IH, Smolenski, Diamond, Ross, and Rosser (2010) and Ross, Rosser, and Smolenski (2010) revised the Reactions to Homosexuality Scale (RHS) to develop the Short Internalized Homonegativity Scale (SIHS) with eight items. Using the European Men Who Have Sex With Men Internet Survey (EMIS) data, with an analytic sample of 130,718 gay and bisexual men in 38 European countries, we confirmed the validity of the SIHS scale in both training and validation data, in strata of Ross, Berg, et al.’s (2013) three “homosexual discrimination” country clusters, of age, and of education level. However, the performance was less adequate in comparison of gay versus bisexually identified individuals. The latent SIHS structure contains only minor variations across these three strata. The seven-item scale performed as well as the eight-item scale. The SIHS is a promising candidate for standard IH measures, which is invariant across cultural, age, and educational strata.     

The fiscal impact of immigration to welfare states of the Scandinavian type

In this paper, we examine the potential of immigration to strengthen fiscal sustainability, which is under pressure by an ageing population in many European countries. We look at a particularly challenging case, namely that of Denmark, which has extensive tax-financed welfare programmes that provide a high social safety net. The analysis is based on a forecast of the entire Danish economy made using a dynamic computable general equilibrium model with overlapping generations. We present life cycle estimates of the potential fiscal impact of immigration considering the cost of immigration on the margin as well as on average. The main conclusion is that immigrants from Western countries have a positive fiscal impact, while immigrants from non-Western countries have a large negative one, which is also the case when considering only non-refugee immigrants. The negative effect is caused by both a weak labour market performance and early retirement in combination with the universal Danish welfare schemes.     

Flood risk mapping and analysis using an integrated framework of machine learning models and analytic hierarchy process

In this study, a new approach of machine learning (ML) models integrated with the analytic hierarchy process (AHP) method was proposed to develop a holistic flood risk assessment map. Flood susceptibility maps were created using ML techniques. AHP was utilized to combine flood vulnerability and exposure criteria. We selected Quang Binh province of Vietnam as a case study and collected available data, including 696 flooding locations of historical flooding events in 2007, 2010, 2016, and 2020; and flood influencing factors of elevation, slope, curvature, flow direction, flow accumulation, distance from river, river density, land cover, geology, and rainfall. These data were used to construct training and testing datasets. The susceptibility models were validated and compared using statistical techniques. An integrated flood risk assessment framework was proposed to incorporate flood hazard (flood susceptibility), flood exposure (distance from river, land use, population density, and rainfall), and flood vulnerability (poverty rate, number of freshwater stations, road density, number of schools, and healthcare facilities). Model validation suggested that deep learning has the best performance of AUC = 0.984 compared with other ensemble models of MultiBoostAB Ensemble (0.958), Random SubSpace Ensemble (0.962), and credal decision tree (AUC = 0.918). The final flood risk map shows 5075 ha (0.63%) in extremely high risk, 47,955 ha (5.95%) in high-risk, 40,460 ha (5.02%) in medium risk, 431,908 ha (53.55%) in low risk areas, and 281,127 ha (34.86%) in very low risk. The present study highlights that the integration of ML models and AHP is a promising framework for mapping flood risks in flood-prone areas.     

The Value of Community Cohesion Among Vietnamese Students in Era of Urbanisation and Globalisation

The concept of community cohesion as applied in social research is about more than tackling social exclusion and also involves sustaining relationships of trust and neighbourly interaction. Community cohesion is a function of connections and relations maintained between individuals, groups and associations. It can be fostered through measures that build feelings of trust, safety and belonging between people and can form a basis for shared values and norms of behaviour. This concept originates from Emile Durkheim, who identified the interdependence between members of a social group who share solidarity, loyalties and responsibilities. In Vietnam, various idioms and proverbs about social solidarity and social cohesion express the significant role of community in the lives of individuals as well as an individual’s responsibilities towards the community. Recent public debates suggest that social cohesion is changing or fraying, especially among youth, owing to the social, economic and cultural impacts of globalisation and urbanisation. However, there is lack of research focusing on community cohesion among young people in general and students in particular in the Vietnamese context. This paper reports on a research project on student life conducted in twelve Hanoi universities, and with 484 research participants, utilizing surveys, interviews and focus groups. This paper aims to identify the current situation and trends in student values with regards to community, particularly their views on community participation, and their responsibilities to communities, friends and society in general. The findings suggest that in spite of significant changes associated with urban life and globalisation, students still positively value community cohesion and engage in practices that maintain solidarity, trust and interdependencies with a range of consociates.     

SPECTRAL ANALYSIS IN BUSINESS FORECASTING*

Although spectral analysis has previously been discussed in a number of business journals, the discussion has not been detailed enough for non-mathematicians. The objective of this paper is to review in detail the concepts and to go over the computations of spectral analysis as they pertain to forecasting. To gain insight into the model building technique of spectral analysis, a passing comparison with a familiar model–regression–is made. Regression analysis attempts to find a set of independent variables that shed some light on the dependent variable to be forecasted. In other words, if the independent variables have some functional relationship with the dependent variable, a reliable forecast of the dependent variable can then be made. Forecasting using spectral analysis, on the other hand, is based on the assumption that the variation of a time series can be explained by some mixture of sine and cosine waves. Model parameters can then be estimated for these waves and forecasts be made. These parameters have the same property of least squares as in ordinary regression analysis. A transformation of these parameters gives the spectra of the time series. The spectra are related to the explained variation present in regression analysis. An extension of the spectra gives a set of coefficients of an autoregressive forecasting model. This latter model is referred to as the Wiener-Kolmogorov forecasting model.     

Estimation of the parameters of the Gompertz distribution under the first failure-censored sampling plan

This article presents the goodness-of-fit tests for the Laplace distribution based on its maximum entropy characterization result. The critical values of the test statistics estimated by Monte Carlo simulations are tabulated for various window and sample sizes. The test statistics use an entropy estimator depending on the window size; so, the choice of the optimal window size is an important problem. The window sizes for yielding the maximum power of the tests are given for selected sample sizes. Power studies are performed to compare the proposed tests with goodness-of-fit tests based on the empirical distribution function. Simulation results report that entropy-based tests have consistently higher power than EDF tests against almost all alternatives considered.