Child malnutrition is not only a major contributor to child mortality and morbidity, but it can also determine socioeconomic status in adult life. The rate of under-five child malnutrition in Vietnam has significantly decreased, but associated inequality issues still need attention.This study aims to explore trends, contributing factors, and changes in inequalities for under-five child malnutrition in Vietnam between 2000 and 2011.Data were drawn from the Viet Nam Multiple Indicator Cluster Survey for the years 2000 and 2011. The dependent variables used for the study were stunting, underweight, and wasting of under-five children. The concentration index was calculated to see the magnitude of child malnutrition, and the inequality was decomposed to understand the contributions of determinants to child malnutrition. The total differential decomposition was used to identify and explore factors contributing to changes in child malnutrition inequalities.Inequality in child malnutrition increased between 2000 and 2011, even though the overall rate declined. Most of the inequality in malnutrition was due to ethnicity and socioeconomic status. The total differential decomposition showed that the biggest and second biggest contributors to the changes in underweight inequalities were age and socioeconomic status, respectively. Socioeconomic status was the largest contributor to inequalities in stunting.Although the overall level of child malnutrition was improved in Vietnam, there were significant differences in under-five child malnutrition that favored those who were more advantaged in socioeconomic terms. The impact of socioeconomic inequalities in child malnutrition has increased over time. Multifaceted approaches, connecting several relevant ministries and sectors, may be necessary to reduce inequalities in childhood malnutrition. Child malnutrition affects children's physical and cognitive development, diminishes immunity, and impacts child mortality and morbidity , 2. It iDoi Moi) and accordingly has shown big improvements in various health indicators. Child malnutrition in Vietnam has improved in general over the last couple of decades, from 41% in 1990 to 15.3% in 2013  wasting as forms of malnutrition indices. Hong  investigIn Vietnam, some studies show that child nutrition is affected by environmental, socioeconomic, and political factors , 13. In This study aims to provide updated information about inequality in Vietnamese child malnutrition, such as stunting, underweight, and wasting, since 2000, focusing only on children under age five. Specifically, two main points will be addressed in this study: 1) inequality in child malnutrition according to socioeconomic status in 2000 and 2011 and factors that contributed to the inequality in each year; 2) changes in inequalities in child malnutrition according to socioeconomic status between 2000 and 2011 and factors that contributed to the change in inequality across these years.We analyzed data from two rounds of the Multiple Indicator Cluster Survey (MICS), specifically from 2000 to 2011 in Vietnam, to examine the trends in socioeconomic inequalities for under-five child malnutrition , 20. TheThe outcome variable in this study was under-five child malnutrition categorized into underweight, stunting, and wasting. In the MICS data, these outcomes were measured and converted to z-scores. Since reference z-values measured by the US National Center for Health Statistics (NCHS) were available in both the 2000 and 2011 data, while the new WHO z-score standard values introduced in April 2006 were not available in the 2000 MICS . FollowiThe explanatory variables of interest in this study were as follows: child's age (months), child's sex, living area , ethnicity , mother's education level, and household socioeconomic status, all of which have been shown to be important determinants for child malnutrition , 1624)24) and wIn this study, we used the wealth asset index as a proxy for socioeconomic status. The wealth asset index was constructed by principal components analysis using information on the ownership of consumer goods, dwelling characteristics, water and sanitation, and other characteristics that are related to household wealth in both the 2000 and 2011 MICS data sets . The assTo measure the degree of socioeconomic inequality in under-five child underweight, stunting, and wasting, we used the CI , 26. Theh represents the values of under-five child malnutrition  of each observation, and r is the rank of the household socioeconomic status. The CIs of under-five child underweight, stunting, and wasting could range between −1 and +1. The CI takes a value of 0, if the distribution of under-five child underweight, stunting, and wasting prevalence is completely equal between the rich and the poor. If it is negative, it indicates that the concentration of under-five malnutrition is higher among the poor, and if it is positive it indicates that the concentration of under-five malnutrition is higher among the rich , the rich . To incry) to the set of k determinants (xk) can be represented as follows:In this study, we decomposed the CIs of under-five child underweight and stunting in 2000 and 2011. Decomposition of the CIs helps in understanding the contribution of the determinant variables to socioeconomic inequalities in the health outcome variable , 26. Forβk is the coefficient of xk and ɛ is the error term. y, and it can be written as follows:where y (the outcome variable); k (the kth determinant variable); Ck is the CI for xk, and GC∈ is the generalized concentration for the error term (ɛ). The element ∈/μ is an unexplained component . In the explained component, k on the total CI of y . Multivariable analysis was conducted with logistic regression for the binary outcome variables underweight, stunting, and wasting. All analysis used the survey-related commands in STATA, with weighting factors for children from the data set   with thedata set , 22. Thep>0.05) but differences in the CI for underweight and stunting were significant (p<0.001).p<0.05). The main factors that showed significant association with under-five child underweight were being older, belonging to a minority, having a mother with lower education, and belonging to a lower socioeconomic status group. The same factors were significantly associated with under-five child stunting and underweight, with the exception of living in rural areas, which was significantly associated with stunting. Factors significantly associated with under-five child wasting were living area and socioeconomic status.The determinants that made the biggest contribution to socioeconomic inequalities in under-five child stunting in 2000 and 2011 also showed the same pattern. Specifically, ethnicity, socioeconomic status, and mother's education level were the biggest contributors in 2000, although the influence of mother's education level on inequality in malnutrition disappeared in 2011. The contribution of socioeconomic status increased during the period 2000–2011 (from 50.9 to 66.9% for under-five child underweight and from 28.2 to 72.0% for under-five child stunting). In 2011, all variables contributed to widening socioeconomic status in malnutrition. The contributions of residuals were relatively low, suggesting that the decomposition model explained the socioeconomic inequality in malnutrition quite well.The contributions to the changes in the inequalities are presented as percentages, with positive percentages indicating a contribution to an increase in inequality and negative percentages indicating a contribution to a decrease in inequality. The total differential decomposition on socioeconomic inequality in underweight and stunting in Although the results of this study are drawn from cross-sectional data and therefore causality cannot be claimed, our paper lays the groundwork for unraveling the causes and changes of inequalities in malnutrition for Vietnamese children under five and highlights the links between socioeconomic inequalities and malnutrition. The findings of this research carry a few important policy implications.Doi Moi), and there were also major improvements in health status. This was not only the result of changes in the health sector but was also due to a combination of changes in income, lifestyle, and other factors (First of all, socioeconomic inequalities in Vietnamese under-five child malnutrition have significantly increased since 2000, although the overall prevalence of malnutrition itself declined. As mentioned, Vietnam experienced rapid economic growth after its dramatic economic reforms ( factors . However factors . ConsequSecondly, another finding from the decomposition of the CI was that most of the determinants made a positive contribution to the socioeconomic inequality in malnutrition. This means that the combined result of the marginal effect of each determinant on malnutrition and its distribution by socioeconomic status was to raise socioeconomic inequality in child malnutrition, with malnutrition being more prevalent among the poor. The result may occur either because particular determinants associated with higher malnutrition were more common among people with lower socioeconomic status or because some determinants associated with a lower malnutrition risk were more prevalent among people with higher socioeconomic status.The contribution presented as percentages of overall socioeconomic inequality clearly shows that most of the inequality in Vietnamese child malnutrition in both 2000 and 2011 was attributable to socioeconomic status and ethnicity. Socioeconomic status accounted for almost two-thirds of the total inequality in both underweight and stunting in 2000 and 2011, meaning that about 50.9 to 72.0% of socioeconomic status–related inequality in malnutrition can be explained by socioeconomic status itself. Ethnicity was ranked as the second contributor in both 2000 and 2011 even though the contribution declined significantly. Although Vietnam is a multi-ethnic country, the main ethnic group in Vietnam is Kinh, which comprises over 85% of the total population. Inferiority in the socioeconomic status of minorities has been a long-lasting problem in Vietnam. The ethnic minorities mostly live in mountainous or remote areas, where economic or cultural benefit cannot be reached easily. This study confirmed again that poor children are more likely to belong to minorities, who are consequently more likely to experience malnutrition. This result is consistent with Wagstaff's study, which proved that inequalities in household consumption and commune fixed effects were the biggest contributors to inequality in malnutrition . Even thOn the other hand, the contribution of mother's education sharply declined between 2000 and 2011. This result might be because those economically disadvantaged women were given more opportunities to get a better education, as the national economic levels increased and the position of women in society was elevated. Thus, upgrading mothers’ education might not be a policy priority for tackling child malnutrition.The results of the decomposition of changes in the CI of malnutrition showing how much of a contribution each determinant made to worsening the inequality in malnutrition between 2000 and 2011 yielded another key finding, that is, that the reasons for the changes in inequality for underweight and stunting between 2000 and 2011 were completely different. Socioeconomic status itself accounted for a big portion of the total change in the socioeconomic inequality of stunting, although it did not make a big contribution to underweight. A supporting reason for this can be thought as follows: underweight can be relatively easily corrected just by providing appropriate feeding, which does not demand difficult measures; however, stunting is an indicator of a more chronic malnutrition status . It cannThe results of the main determinants for the average level of malnutrition  and the This study has a caveat that commonly occurs in cross-sectional studies. The results must be interpreted with caution so that they are not interpreted as implying causality. In addition, unknown factors that were not included in our analysis also made a non-negligible contribution by worsening inequality in both underweight and stunting. This suggests a need for further studies to identify and tackle those factors. Despite these weaknesses, the findings from this study have some meaningful policy implications. First, like other studies, this study confirms that there is some trade-off between improvement in averages and improvement in distributions. Policy measures relying only on the country's average values can be misleading. In addition, this study drilled down to identify factors that contributed to the recognized inequalities and changes in inequalities over time, thereby enabling us to better judge where we have to focus in the future in order to tackle inequalities in child malnutrition.In order to address inequalities in child malnutrition in Vietnam, special attention should be given to the policy measures that narrow socioeconomic gaps between groups in the population. Our study confirms that most inequalities in Vietnamese children's malnutrition resulted from socioeconomic inequalities. To remedy this problem, the Vietnamese government needs to direct efforts towards raising socioeconomic status in minorities and focusing on older children. Specifically, investment in education, empowerment of economically disadvantaged groups, and creation of greater working opportunities would be important measures. There is a need for a comprehensive approach beyond the health sector with a sharing of efforts between other ministries.


This study aimed to investigate alcoholic beverages drinking and predictive factors among female students. The participants were 377 subjects from 3 high schools in a tourist province, of Thailand. Data collection was done through self-administered questionnaire. Scales of the questionnaire had reliability coefficients ranging from 0.84 – 0.88. The data were analyzed by using descriptive and inferential statistics. The findings revealed as follows. About half (51%) of them have ever drunk and 10.5% of drinkers have drunk once a week. In addition, 15.6% of drinkers began their first drink when they were under 10 years old. Risk factors for alcohol consumption of female student were age, GPA, drinker in family, peer pressure, advertisement and accessibility to alcoholic beverages while protective factors were perception of drinking impacts on family and moral values. Students who have a drinking family member were 4.6 times more likely to drink than those who do not have. Alcoholic beverage drinking is one of the causes of health problems, crimes, economics, and social problems. Both government and private sectors emphasize politically on alcoholic beverages drinking and participate in activities designed to prevent drinking . Alcohol industry is actively participated in social and school activities, including sport activities, through corporate social responsibility (CSR) program in order to reach out to the target group, who are youth and teenagers. The Thai National Statistical Office in Thailand reported that in 2007, Thai population older than 15 years old consumed alcoholic beverages about 14.9 million people (29.3%), while 15 – 24 years old age group who were drinkers about 2.3 million people (21.9%) . BetweenThe objective of this study was to investigate alcoholic beverages drinking and predictive factors among female students in high schools.This study was conducted as a cross-sectional survey among female students from 3 high schools in Chonburi province, in eastern Thailand. Chonburi is well-known as an important tourism area on the Gulf of Thailand. Three hundred and thirty-seven female students from grades 1 – 6 were recruited. Data collection was conducted between August and September 2010.The research instrument was the self-administered questionnaire, consisted of 6 parts: 1) alcoholic beverage drinking, 2) family factors: marital status of parents, drinker in family 3) peer pressure, 4) perception of alcoholic beverage advertisement, 5) accessibility to alcoholic beverages and 6) perception of drinking impacts on health, family, social and moral values. Content validity has been reviewed and approved from 3 experts, one in behavioral science, one in family medicine, and one in health policy. Data were verified with internal consistency reliability coefficients between 0.84 and 0.88. This study was approved by the Ethics Committee for Research in Human Subjects of the Faculty of Public Health, Mahidol University (Ref.No. MUPH 2010-131).The SPSS for windows was used in both descriptive and inferential statistical analysis of the collected data. The descriptive statistics were frequency, percent, and standard deviation. In addition, Chi-square, t-test, and Multiple Logistic Regression were applied in finding the factors correlating and predicting the alcoholic beverages drinking among female students. Significant level was set to be .05.The samples were between the age of 12 and 17 years old, with the average age was 15.2. Majority of samples (91%) lived with parents or relatives. Out of 377 female students, 74.5% lived with cohabited parent. More than 9 in 10 (92%) had at least one drinker in the family. Approximately 51% of female students have ever drunk. Female drinkers reported having their first drink between the age of 3 and 17 years old (Mean+S.D.= 12.50+2.32). Approximately 35% of female drinkers had their first alcoholic beverages drinking before high schools, and 15.6% began to drink alcoholic beverages when they were under 10 years old. Regarding the reasons that may encourage their first drinking, more than 56% of female student drinkers said they just wanted to try. Secondly, they started to drink in the party or because of peer pressure (38.1%). Wine or Spy (50.5%) is majority of alcoholic beverages which were chosen, followed by beer (25%) and alcoholic smoothies (15.1%) respectively. Approximately one-third (32.8%) of drinkers drank at home. This study reported that 37.3% of female drinkers drank with their parents or relatives, and more than half (56.2%) drank with their friends. More than 4 in 10 (46%) drank once in a few months, followed by few times a month (44%). One in ten (10%) of female drinkers drank once a week .In focusing on the family predictors, namely marital status of parents and drinker in family, the study found that drinking associated with drinker in family with statistical significance at .01. Nonetheless there was no correlation with marital status of parents . AdditioWith regard to the social predictors such as peer pressure, perception of alcoholic beverages advertisement, and accessibility to alcoholic beverages, comparing the perception scores by alcoholic beverages drinking indicated that drinkers had a higher mean score than non-drinkers, with statistical significance at .001. Referring to perception of drinking impact on health, family, social, and moral values, the difference were statistically significant at .001, with drinkers had less mean scores of drinking impacts than non-drinkers .The findings of association between predictors comprised of personal factors, family factors, social factors, and perception of drinking impacts and alcoholic beverages drinking among female students in high schools revealed that there were 10 predictors which were significantly associated with drinking. The significant predictors were age, GPA, drinker in family, peer pressure, advertisement, accessibility of alcoholic beverages, perceptions of drinking impacts on: health, family, social, and moral values. These variables were analyzed to see how it influences alcoholic beverages drinking, by using Multiple Logistic Regression.The results of analysis  revealed1)Students live with drinker in family are 4.6 times more likely to drink than those who out drinker in family.2)For each additional year the students was 1.98 time more likely to be a drinker or 98% [(1.98-1)*100] more likely to be a drinker.3)Each additional score for accessibility to alcoholic beverages means 1.274 times more likely to be drinker or 27.4% [(1.274-1)*100] more likely to be a drinker.4)Each additional score for peer pressure means 1.179 times more likely to be drinker or 18% [(1.179-1)*100] more likely to be a drinker.5)Each additional score for perceived alcohol advertisement means 1.065 times more likely to be drinker or 6.5% [(1.065-1)*100] more likely to be a drinker.6)Each additional score for perception of drinking impact on moral values means 0.906 times less likely to be drinker or 18% [(1-0.906)*100] less likely to be a drinker.7)Each additional score for perception of drinking impact on family means 0.820 times less likely to be drinker or 9.4% [(1-0.820)*100] less likely to be a drinker.Then, alcohol drinking of female students had risk factors such as age, drinker in family, peer pressure, perceived alcohol advertisement, and accessibility to alcoholic beverages, and protective factors, namely perception of drinking impact on family and moral values.The study indicated 50.9% of female students in high schools had ever drunk alcoholic beverages. This information indicated a higher rate than previous study of The results of this study indicated that about 35% of female students had their first drink of alcoholic beverage at the age under 13. It is consistent with the results of school girls surveyed in the United State of America, which indicated that nearly 1 in 4 started to drink for the first time before age 13. It was a higher percentage than the survey in 1960 which indicated only 7% of all girls . This is particularly disturbing since those who initiate alcohol drinking in early life are at increased risk of becoming problem drinkers . It woulThere are many factors that control drinking behavior such as perception of drinking impacts on family and moral values. However, the social problems that may influence the drinking behavior such as easy access to buy alcoholic beverages and peer pressure still exist. Other important factor that may increase the risk for alcohol abuse is parental acceptance of female students’ drinking together with high percent of having family members who drink alcohol (92%). Moreover, the alcoholic beverages advertisement has the indirect effect to the alcohol consumption of female students. The advertised issues have enhanced drinking by making their images as someone with modern life style, attractive person, or hero for the target groups, especially the young. Young people were stimulated to alcohol consumption by advertisement. This study found that 50% of female drinkers have the first drink as self-trial, and 38.1% of them from peer pressure. It is consistent with the study of In conclusion, the significant predictors toward alcoholic beverages drinking of female students would be more of challenging problems to families and policy regulators. This is especially troubling for each family in Thai society, to be concerned about drinking impacts on social, moral values, economics, and well-being both short and long terms, while family structure seems to be fragile. In reality, these families would be responsible for each problem in the future, which can be destroyed or may not rectify chronic social problems.


The study aimed to establish the prevalence of heavy drinking, evaluate correlations between heavy drinking and socio-demographic factors, physical and psychiatric conditions, and assess the impact of heavy drinking on quality of life and days of work-loss.Data from a nationally-representative cross-sectional sample were used. The sample comprised 6616 community-dwelling Singaporeans & Singapore Permanent Residents. The main instruments used were the World Mental Health Composite International Diagnostic Interview and EuroQol 5D. Heavy drinking was defined as consumption of 4 or more drinks, or 5 or more drinks in a day in women and men respectively.12.6% of all adult Singapore residents reported heavy drinking in the last 12 months, and 15.9% reported lifetime heavy-drinking. Strong gender, ethnic, age and income differences were seen. Heavy drinking was positively associated with major depression, the presence of any mood disorder, and with chronic pain. It was also strongly associated with alcohol dependence, alcohol abuse, and nicotine dependence. Heavy-drinkers reported lower quality of life compared to non-heavy drinkers, measured using the EuroQol 5D Visual Analogue Scale.Singapore has a relatively high prevalence of 12-month heavy drinking of 12.6%, and lifetime heavy drinking of 15.9%. Heavy drinking was positively associated with both physical and mental health conditions, and with declines in quality of life. Continued monitoring of heavy drinking behavior and sustained efforts to mitigate the risks associated with heavy drinking is needed. However, some patterns of alcohol consumption may be harmful even in the absence of alcohol abuse or dependence, and binge drinking is recognised as a potential cause of morbidity and mortality [Adverse effects of over-consumption of alcohol are well-documented, and two forms of alcohol use disorder- alcohol abuse and alcohol dependence, are classified in the Diagnostic and Statistical Manual of Mental Disorders, 4ortality -7.Binge drinking refers to high volume alcohol consumption over a short period of time, and is frequently defined as the consumption of four or more drinks at a single sitting for women, and of five or more drinks at a single sitting for men . Binge dSingapore is an island city-state in South-East Asia, with a multi-ethnic population of about 5 million, with 3.77 million Singapore citizens and Permanent Resident . The resIn this paper, we examine the prevalence of heavy drinking (as a proxy for binge drinking) using data from a nationally representative cross-sectional survey. We also evaluated correlations between heavy drinking and socio-demographic factors and the concomitant presence of self-reported physical conditions and psychiatric conditions (based on DSM-IV criteria). Finally, we assessed the impact of heavy drinking by evaluating differences in self-reported quality of life and days of work-loss.Data from the Singapore Mental Health Study (SMHS) were used. The design and conduct of this study have been previously described . BrieflyEthical approval was obtained from the Domain-Specific Review Board of the National Healthcare Group in Singapore prior to implementation of the study, and full informed consent was obtained from participants and parents/guardians of participants aged 18–20 years. A participant’s age and ethnicity were obtained from the National Registration Identity Card. Other socio-demographic information were self-reported, including marital status, highest educational level achieved, household income, type of current residence and occupational status. Data were collected as categorical responses.The diagnoses of mental disorders were based on the World Mental Health Composite International Diagnostic Interview version 3.0 (CIDI 3.0) . All intThe question of the CIDI 3.0 module on alcohol use: “During the last 12 months, what was the largest number of drinks you had had in one single day?” was used to determine heavy drinking. Men who answered 5 or more drinks a day and women who answered 4 or more drinks were considered to have a history of heavy drinking in the last 12 months. A drink was defined as a glass of wine, a can or bottle of beer or a shot or jigger of liquor either alone or in a mixed drink.All participants with history of heavy-drinking in the last 12 months were considered heavy drinkers over the lifetime. In addition, among those who were not heavy drinkers in the last 12 months, we used answers to the question: “Was there ever a year in your life when you drank more than you did in the past 12 months?” and: “On the days you drank during those years, about how many drinks did you usually have per day?”. Participants who reported that there was ever a year in their life where they drank more than they did in the last 12 months and who then reported 5 or more drinks a day (for men) or 4 or more drinks a day (for women) were considered heavy drinkers over the lifetime. We used this definition of heavy drinking as a proxy for binge drinking, since our questionnaire did not ascertain drinking volume over a single occasion.Participants were also asked if their doctor had informed them that they had any of 15 specific medical conditions which were relatively prevalent in Singapore. These were: a) high blood sugar/diabetes, b) high blood pressure/hypertension, c) chronic pain , d) cancer diagnosed in the last 3 years, e) neurological conditions , f) cardiovascular disorders , g) ulcers and chronic inflamed bowel diseases  and h) respiratory diseases .An index was created using health states defined by the EuroQoL 5D instrument  to assesAll data analyses were performed using weighted data. Mean and standard deviations were calculated for continuous variables, and frequencies and percentages for categorical variables. Logistic regression was used to assess the association between heavy drinking and socio-demographic variables, mental illnesses and physical disorders. Linear regression was used to assess the association between heavy drinking and work days lost and health-related quality of life as measured using the EuroQoL 5D index and the EuroQoL VAS in the EuroQoL 5D instrument. To account for the effects of complex sample design due to stratification and weighting, standard errors and significance tests were estimated using the Taylor series linearization method. Multivariate significance was evaluated using the Wald test based on design corrected coefficient variance-covariance matrices. Statistical significance was set at the conventional level of p < 0.05, using two-sided tests. Statistical analyses were carried out using the statistical packages Stata version 10.0  and the Statistical Analysis Software (SAS) system version 9.2 .From an initial study frame of 13,500 individuals, 9116 (67.5%) were identified, and of these, 6648 (72.9%) were successfully interviewed. 854 (9.4%) refused to participate, 664 (7.3%) were either not contactable or were deceased, 554 (6.1%) had moved to another location or country, and 396 (4.3%) were ineligible due to language barrier or inability to complete the interview. Subsequently, 32 completed interviews were voided during the quality review, leaving a total study population of 6616 individuals. The overall response rate for the study, excluding the ineligible 396 cases, was 75.9% (n = 6616).Participants in this study were almost equally divided between men and women. Malays and Indians were over-represented in this study to enable more stable and accurate ethnic-specific prevalence estimates of mental illnesses. 70% of the study population was younger than 50 years of age, and the majority of participants 81.6%) had at least secondary level education , and Malays were less likely to drink heavily than Chinese , while those with an “Others” ethnicity were more likely to drink heavily . Older people were much less likely to drink heavily , while participants with high personal income were more likely to drink heavily . Divorced or separated individuals were more likely to report lifetime heavy drinking compared to single persons , although the increased OR for 12-month heavy drinking was not significant. Married persons were less likely to report 12-month heavy drinking , although the decreased OR was not significant for lifetime heavy drinking . Bipolar disorder was more prevalent among lifetime heavy drinkers than non-heavy drinkers , although there was no associations seen with 12-month heavy drinking. Collectively, mood disorders were associated with both 12-month and lifetime heavy drinking . Obsessive-compulsive disorder and all anxiety disorders were associated with lifetime heavy drinking in bivariate analyses, but this association was no longer significant after adjustment. Alcohol abuse and overall alcohol use disorders were both significantly associated with 12-month and lifetime heavy drinking. The prevalence of nicotine dependence among 12-month heavy drinkers was 10.2%, and 9.6% among lifetime heavy drinkers, compared to non- heavy drinkers at 3.6 and 3.4% respectively. These associations remained significant after adjustment  . The associations seen with hypertension, cancer and respiratory conditions were no longer significant, suggesting that these were confounded by socio-demographic factors  . Similarly, there were differences in the proportion with mobility problems in these 3 groups (p = 0.0006), although pairwise comparisons were also not significant. Posthoc comparisons were significant for usual activities, where the proportion of lifetime heavy drinkers with alcohol use disorder who had problems with usual activity was significantly greater than that in non-lifetime heavy drinkers without alcohol use disorder, and for pain/discomfort, where both lifetime heavy drinkers with alcohol use disorder and lifetime heavy drinkers without alcohol use disorder had higher proportions reporting problems with pain and discomfort than among non-heavy drinkers without alcohol use disorder. No other posthoc comparisons were significant . Twelve-month heavy drinkers without alcohol use disorder aged 50–64 reported higher quality of life than older non- heavy drinkers in the 50–64 year age group, (p = 0.0078)  on the VAS. Among 12-month heavy -drinkers, significantly lower quality of life was reported only among those with alcohol use disorder (p = <0.0001). Lifetime and 12-month heavy drinkers with alcohol use disorder reported significantly lower quality of life in both the 18–34 year (p < 0.0001 and 0.0158 respectively) and the 35–49 year (p < 0.0001 and 0.037 respectively) age groups. No significant difference in quality of life was reported by lifetime and 12 month heavy drinkers without alcohol use disorder, except for lifetime heavy drinkers in the 35–49 year age group, which reported a significantly lower quality of life (p = 0.0315). No clear differences in self-reported loss in work days were seen, with or without stratification by age, except for 12 month heavy drinkers without alcohol use disorder in the 50–64 year age group, where they reported fewer days lost (p = 0.022)  in a single day, in contrast to the traditional binge drinking definition of 4 or 5 units over a single drinking episode. Our results therefore does not measure 12-month binge drinking rates, and direct comparisons with binge drinking rates cited in other studies are not possible. Because binge drinkers are heavy drinkers, but heavy drinkers need not be binge drinkers, our prevalence estimate may be an overestimate of the 12-month binge drinking rate, and serve as an upper estimate of the true binge drinking rate. The definition for 12- month heavy drinking (largest number of drinks in a single day) was different from lifetime heavy drinking . The lifetime heavy drinking estimate will underestimate the true prevalence of lifetime binge drinking. We believe 12-month heavy drinking is a better proxy for binge drinking than the lifetime one.Finally, we used face-to-face interviews for this study. Participants may not have reported accurate consumption rates because of their perceptions of the social acceptability of alcohol consumption. This may be so especially amongst females or Malays, where societal expectations are that they do not drink. Conversely, young males may have over-reported their consumption patterns. We have tried to reduce this misclassification bias by training our interviewers to administer the interviews in a sensitive and neutral manner, and using standard questionnaires.In summary, despite low reported rates of alcohol abuse and alcohol dependence, we find a relatively high prevalence of 12-month heavy drinking of 12.6%, and lifetime heavy drinking of 15.9%. Although these rates are lower compared to other countries, it is important to continue to monitor alcohol consumption trends. Efforts to improve awareness among the young of the ill effects of heavy drinking, and to mitigate harms associated with heavy drinking and intoxication also need to be continued.All authors declare that they have no conflicts of interests.SAC, MS and JV designed and conducted the study. W-YL conducted literature searches and provided summaries of previous research studies. EA, VYFH and W-Y Lim conducted the statistical analysis. W-Y Lim drafted the manuscript and all authors have contributed to and have approved the submission of this manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/13/992/prepub


Here we provide a reconstruction algorithm by using only local phase information. We also demonstrate that local phase alone can be effectively used to detect local motion. The local phase-based motion detector is akin to models employed to detect motion in biological vision, for example, the Reichardt detector. The local phase-based motion detection algorithm introduced here consists of two building blocks. The first building block measures/evaluates the temporal change of the local phase. The temporal derivative of the local phase is shown to exhibit the structure of a second order Volterra kernel with two normalized inputs. We provide an efficient, FFT-based algorithm for implementing the change of the local phase. The second processing building block implements the detector; it compares the maximum of the Radon transform of the local phase derivative with a chosen threshold. We demonstrate examples of applying the local phase-based motion detection algorithm on several video sequences. We also show how the locally detected motion can be used for segmenting moving objects in video scenes and compare our local phase-based algorithm to segmentation achieved with a widely used optic flow algorithm.Previous research demonstrated that FigureVisual motion detection is critical to the survival of animals. Many biological visual systems have evolved highly efficient/effective neural circuits to detect visual motion. Motion detection is performed in parallel with other visual coding circuits and starts already in the early stages of visual processing. In the retina of vertebrates, it is known that at least three types of Direction-Selective Ganglion Cells (DSGC) are responsible for signaling visual motion at this early stage . In flieThe small number of synapses between photoreceptors and direction-selective neurons suggests that the processing involved in motion detection is not highly complex but still very effective. In addition, the biological motion detection circuits are organized in a highly parallel way to enable fast, concurrent computation of motion. It is also interesting to note that the early stages of motion detection are carried out largely in the absence of spiking neurons, indicating that initial stages of motion detection are preferably performed in the “analog” domain. Taking advantage of continuous time processing may be critical for quickly processing motion since motion intrinsically elicits fast and large changes in the intensity levels, that is, large amounts of data under stringent time constraints.Modern, computer-based motion detection algorithms often employ optic flow techniques to estimate spatial changes in consecutive image frames , 5. AlthSeveral models for biological motion detection are available and their architecture is quite simple . The ReiIn this paper, we provide an alternative motion detection algorithm based on local phase information of the visual scene. Similar to mechanisms in other biological models, it operates in continuous time and in parallel. Moreover, the motion detection algorithm we propose can be efficiently implemented on parallel hardware. This is, again, similar to the properties of biological motion detection systems. Rather than focusing on velocity of motion, we focus on localization, that is, where the motion occurs in the visual field as well as the direction of motion. local phase information, thereby demonstrating the spectrum of the representational capability of phase information.It has been shown that images can be represented by their global phase alone . Here weThe Fourier shift property clearly suggests the relationship between the global shift of an image and the global phase shift in the frequency domain. We elevate this relationship by computing the change of local phase to indicate motion that appears locally in the visual scene. The local phases are computed using window functions that tile the visual field with overlapping segments, making it amenable for a highly parallel implementation. In addition, we propose a Radon-transform-based motion detection index on the change of local phases for the readout of the relation between local phases and motion.Interestingly, phase information has been largely ignored in the field of linear signal processing and for good reason. Phase-based processing is intrinsically non-linear. Recent researches, however, showed that phase information can be smartly employed in speech processing  and visuThis paper is organized as follows. In The use of complex valued transforms is widespread, for both representing and processing images. When represented in polar coordinates, the output of a complex valued transform of a signal can be split into amplitude and phase. In this section, we define two types of phases of an image: global phase and local phase. We then argue that both types of phases can faithfully represent an image and we provide a reconstruction algorithm that recovers the image from local phase information. This indicates that phase information alone can largely represent an image or video signal.It will become clear in the sections that follow that the use of phase for representing of image and video information leads to efficient ways to implement certain types of image/video processing algorithms, for example, motion detection algorithms.u = u,  ∈ ℝ2, is given byωx, ωy) ∈ ℝ2.Recall that the Fourier transform of a real valued image u can be expressed asu.In polar coordinates, the Fourier transform of u = u,  ∈ ℝ2, is called the global amplitude of u. The phase of the Fourier transform of an image u = u,  ∈ ℝ2, is called the global phase of u.The amplitude of the Fourier transform of an image It is known that the global phase of an image plays an important role in the representation of natural images . A classw = w,  ∈ ℝ2, is a real valued window function centered at  ∈ ℝ2. Typical choices of window functions include the Hann window and the Gaussian window. The (effectively) finite support of the window restricts the Fourier transform to local image analysis.The global phase indicates the offset of sinusoids of different frequencies contained in the entire image. However, it is not intuitive to relate the global phase to local image features such as edges and their position in an image. To study these local features, it is necessary to modify the Fourier transform such that it reflects properties of a restricted region of an image. It is natural to consider the Short-Time (-Space) Fourier Transform (STFT):A ∈ ℝ is the amplitude and ϕ is the phase of the STFT.Similarly to the Fourier transform, the STFT can be expressed in polar coordinates asu = u,  ∈ ℝ2, is called the local amplitude of u. The phase of the STFT of an image u = u,  ∈ ℝ2, is called the local phase of u.The amplitude of the STFT of an image w is a Gaussian window, the STFT of u evaluated at  can be equivalently viewed as the response of a complex-valued Gabor receptive field u.Note that when In this case, the window of the STFT clearly is given byl cortex .Amplitude and phase can be interpreted as measurements/projections of images that are indicative of their information content. Classically, when both the global amplitude and phase are known, it is straightforward to reconstruct the image. The reconstruction calls for computing the inverse Fourier transform given the global amplitude and phase. Similarly, when using local amplitude and phase, if the sampling functions form a basis or frame in a space of images, the reconstruction is provided by the formalism of wavelet theory, for example, using Gabor wavelets .Amplitude or phase represents partial information extracted from visual scenes. They are obtained via nonlinear sampling, that is, a nonlinear operation for extracting the amplitude and phase information from images. The nonlinear operation makes reconstruction from either amplitude or phase alone difficult. Earlier studies and recent development in solving quadratic constraints, however, suggest that it is possible to reconstruct images from global or local amplitude information , 19.While computing the amplitude requires a second order (quadratic) nonlinearity, computing the phase calls for higher order nonlinear operators (Volterra kernels). It is possible, however, to reconstruct up to a constant scale an image from its global phase information alone without explicitly using the amplitude information. An algorithm was provided for solving this problem in the discrete signal processing domain in . The algu = u,  ∈ ℝ2, can be reconstructed from its local phase alone. We first formulate the encoding of an image u by local phase, using the Gabor receptive fields as a special case. It is straightforward then to formulate the problem with local phase computed from other types of STFTs.Using a similar argument, we demonstrate in the following that, up to a constant scale, a bandlimited signal u = u, on the domain ℝ2, to be an element of a space of trigonometric polynomials ℋ of the formℋ, Ωx, Lx are the bandwidth and the order, respectively, of the space in the x dimension, and Ωy, Ly are the bandwidth and the order, respectively, of the space in the y dimension.Formally, we consider an image, ℋ is a Reproducing Kernel Hilbert Space with inner product , that is, those centered on the magenta line, are shown in We further illustrate an example of the block structure in dϕkl/dt) for low amplitude values Akl. The denoising is given byϵ > 0 is a constant, and  ∈ 𝔻2.Since the phase, and thereby the phase change, is noisier when the local amplitude is low, an additional denoising step can be employed to discount the measurements of  over a circular bounded domain C = {∣ ∈ 𝔻2,  ωx2 + ωy2 < π2}.We exploit the approximately linear structure of the phase derivative for blocks exhibiting motion by computing the Radon transform of (C is given byℛ(dϕkl/dt)) evaluated at a particular point  is essentially an integral of (dϕkl/dt) along a line oriented at angle π/2 + θ0 with the ωx axis and at distance |ρ0| along the (cos(θ0), sin(θ0)) direction from .The Radon transform of the change of phase in the domain k and l, we have (dϕkl/dt) = −vx(t)ωx − vy(t)ωy, we have𝔠 is a correction term due to different length of line integrals for different values of  in the bounded domain C.If, for a particular dϕkl/dt) for every block  at time t0, we compute the Phase Motion Indicator (PMI), defined askl is larger than a chosen threshold, motion is deemed to occur in block  at time t0.After computing the Radon transform of  domain. Instead, it appears to be more randomly distributed. Consequently, the PMI value is comparatively small for these blocks  where motion is detected, can be easily computed asMoreover, the direction of motion, for block , the maximum phase change over all  ∈ 𝔻2; that is,dϕkl/dt)| over all  ∈ 𝔻2 is comparable to the maximum obtained for blocks that cover the vehicles in motion.k, l) can provide a constraint to robustly estimate motion and its direction. Given the block structure employed in the computation of the local phase, it is natural to utilize phase change information from multiple sources.However,  suggestsk, l), (dϕkl/dt) = −vx(t)ωx − vy(t)ωy, then it is easy to see that (dϕkl/dt) will be zero on the line vx(t)ωx + vy(t)ωy = 0 and have opposite sign on either side of this line. For example, in Figures dϕkl/dt) clearly exhibits this property for blocks that cover a vehicle in motion. The PMI is a tool to evaluate this property.Indeed, if, for a particular block  is differentiable, we have a and b are, respectively, the real and imaginary parts of A00ejϕ00.Assuming that the local phase u, and the numerator is of the form of a second order Volterra kernel. This suggests that the time derivative of the local phase can be viewed as a second order Volterra kernel that processes two normalized spatially filtered inputs v1 and v2.We notice that the denominator of  is the sr1(t) = a and r2(t) = b, respectively, for a particular value of . The pair of Gabor filters that provide these outputs are the real and imaginary parts of wej(ωxx+ωyy)−. It also consists of a temporal high-pass g1(t) and temporal low-pass filter g2(t)  to , resulting in a video with a lower mean luminance and lower contrast. The motion detection results on the low-contrast video are shown in the bottom 3 panels of ϵ is 0, the phase detector should produce invariant responses to videos with different contrast. The curve shown here is mainly due to a nonzero ϵ. The ratios for the Reichardt motion detector and the Barlow-Levick motion detector are computed similarly and are shown in red and yellow, respectively. It is clear that the phase-based motion detector has a superior performance across a range of contrast values. At 20% contrast, the phase-based detector still has 50% of the PMI index value for full contrast video. As expected, the response of Barlow-Levick motion detector is linear with respect to contrast, and the Reichardt motion detector has a quadratic relation to contrast. For a fixed threshold value a larger ratio equates to a more consistent performance at lower contrast.To quantify how well each detector works under different contrast conditions, we computed the ratio of unthresholded output values of each motion detector between lower contrast and full contrast video. For example, in the case of phase-based motion detector, we computed, for each block, the ratio between the PMI index for the lower contrast video and that for the full contrast video. The ratios are then averaged across all blocks where motion is detected in the full contrast video. This average for different contrasts is shown in The second video was captured by a surveillance camera in a train station (“train station video”). The video was under moderate room light with a low noise level. The front side of the video had high contrast; illumination on the back side was quite low. The detected motion is shown in the video of The third video was a “thermal video” with large amount of background noise . The threshold for detecting motion was raised by 60% in order to mitigate the increased level of noise. The detected motion is shown in the video of The last example we show here was taken from a highway surveillance camera at night (“winterstreet video”). The overall illumination on the lower-left side was low whereas illumination was moderate on the upper-right side where the road was covered by snow. The detected motions are shown in the video in With a higher threshold, the phase-base motion detection algorithm is able to detect motion under noisy conditions. We added to the original “highway video” and “train station video” Gaussian white noise with standard deviation 5% of the maximum luminance range. The results are shown, respectively, in Figures We asked whether the detected motion signals in the video sequences can be useful for segmenting moving objects from the background. We applied a larger threshold to only signal motion for salient objects. The 32 × 32 blocks, however, introduce large boundaries around the moving objects. To reduce the boundary and to segment the moving object more closely to the actual object boundary, we applied the motion detection algorithm around the detected boundary with 16 × 16 blocks. If 16 × 16 blocks did not indicate motion, then the corresponding area was removed from the segmented object area.For comparison, we performed motion segmentation based on local motion detection based on an optic flow algorithm . The segWe employed a simple thresholding for both phase-based motion detection algorithms and optic flow based motion detection. More sophisticated algorithms may produce better segmentation results. Thus, the segmentation was purely based on motion cues and no postprocessing at pixel level was performed. The state-of-the-art results for the Change Detection 2014 dataset utilize multiple cues such as motion, color, and background extraction to segment objects and thereby achieve better results. We are exploring here, however, only the case where motion is the only cue for segmentation. Therefore, the ground truth information from the dataset was not applicable to our test. We will, therefore, only show the effectiveness of motion segmentation visually.We first applied motion based segmentation on 2-second segment of the “highway video.” The result using the local phase-based motion detection algorithm is shown in the video of We then applied the motion segmentation to a 2-second segment of the “train station video,” the “thermal video,” and the “winterstreet video.” The results are shown, respectively, in the videos of Figures These results show that for the purpose of detecting local motion and its use as a motion segmentation cue, the local phase-based motion detector works as good, if not better than a simple thresholding segmentation using an optic flow based algorithm. global phase information alone can be used to faithfully represent visual scenes. Here we provided a reconstruction algorithm of visual scenes by only using local phase information. More importantly, local phase information can be effectively used to detect local motion. Through a simple temporal derivative of the phase, we obtained a second order Volterra kernel that is applied on two normalized inputs. The structure of the second order Volterra kernel in the phase-based motion detector is akin to models employed to detect motion in biological vision, for example, the Reichardt detector [Previous research demonstrated thatdetector  and the detector . in silico as well as in modeling in vivo biological vision systems. This is consistent with other recent findings [We then proposed an efficient, FFT-based algorithm employing the change in local phase for detecting motion. In order to exploit the special structure of the change in phase in the frequency domain that is due to rigid motion, the phase-based motion detection algorithm also incorporates the Radon transform, a transform closely related to the Fourier transform. Based on the Radon transform, a motion indicator was proposed to robustly detect whether the phase change is caused by motion. Therefore, the algorithm can be efficiently implemented whenever the FFT is available/supported. We showed examples of applying the phase-based motion detection algorithm on several video sequences. We also showed that the locally detected motion can be used for segmenting moving objects in video scenes. We compared the segmentation of moving objects using our local phase-based algorithm to segmentation achieved using a widely used optic flow based algorithm. Our results suggest that spatial phase information may provide an efficient alternative to perform many visual tasksfindings .Note that phase information has been used for solving various visual tasks in the past. In fact, phase has been successfully employed in optic flow algorithms  and imag phase change is exploited for better detection of motion. On the contrary, the phase correlation method considers the structure of the phase itself. This also allowed us to make the motion detection a more local, continuous process rather than purely operating globally on discrete frames. Second, it explores the structure of the change of phase due to motion in the frequency domain rather than in the spatial domain, in which the key constraints of optic flow equations are based. Third, instead of focusing on estimating the exact velocity or shift, our method is centered on the detection of motion with a coarse local estimate of direction. This is the case in the first steps of biological motion detection in the retina or optic lobe of insects; we discussed the resemblance of the method presented here to those of biological models of motion detection.Our method differs from the above two cases in the following ways. First, it employs a simple temporal derivative/high-pass filtering on the phase to extract local phase changes. The structure of theThe proposed motion detection algorithm, however, shares several advantages with the other phase-based methods. For example, it is sensitive to motion that only induces a subpixel shift between frames and for very small differences in intensity. In addition, when compared to the amplitude, the local phase is robust under different contrast and illumination conditions. Consequently, the algorithm presented here can operate in a wide range of contrast/illumination conditions.Furthermore, once the local phase is extracted from each block, motion detection becomes a localized, temporal operation on the local phase of each block. This forms the basis for the highly parallel structure in the phase-based motion detection algorithm. By contrast, traditional optic flow techniques often rely on explicit comparisons across spatial locations, which increase, for example, memory complexity since all states must be made available to their neighbors.We also notice that, for each block, a large number of measurements of phase changes are obtained. From We also highlight the ease of implementation of the intrinsically parallel algorithm proposed here. The algorithm introduced in Finally, we argue that the change of phase, although highly nonlinear, can be obtained through a normalization (gain control) followed by a second order Volterra kernel. This separation of a higher order nonlinearity into gain control block and a lower order nonlinear filter can be used for modeling motion detection circuits in biological systems.Video S1: Video illustrating the evaluation of the Phase Motion Indicator (PMI) for the high-way video sequence. .Video S2: Full video for Figure 9. Motion detection of the “highway video” using the phase-based algorithm (left), the Reichardt motion detector (middle), and the Barlow-Levick motion detector (right).Video S3: Full video for Figure 11. Motion detection of the “train station video” using the phase-based algorithm (left), the Reichardt motion detector (middle), and the Barlow-Levick motion detector (right).Video S4: Full video for Figure 12. Motion detection of the “thermal video” using the phase-based algorithm (left), the Reichardt motion detector (middle), and the Barlow-Levick motion detector (right).Video S5: Full video for Figure 13. Motion detection of the “winterstreet video” using the phase-based algorithm (left), the Reichardt motion detector (middel), and the Barlow-Levick motion detector (right).Video S6: Full video for Figure 14. Phase-based motion detection applied on the “highway video” with added Gaussian white noise.Video S7: Full video for Figure 15. Phase-based motion detection applied on the “train sta-tion video” with added Gaussian white noise.Video S8a: Full video for Figure 16a. Segmentation of moving cars based on detected mo-tion in the “highway video” using the phase-based motion detection algorithm.Video S8b: Full video for Figure 16b. Segmentation of moving cars based on detected mo-tion in the “highway video” using optic flow algorithm.Video S9a: Full video for Figure 17a. Segmentation of moving cars based on detected mo-tion in the “highway video” using the phase-based motion detection algorithm.Video S9b: Full video for Figure 17b. Segmentation of moving cars based on detected mo-tion in the “train station video” using optic flow algorithm.Video S10a: Full video for Figure 18a. Segmentation of moving cars based on detected mo-tion in the “thermal video” using the phase-based motion detection algorithm.Video S10b: Full video for Figure 18b. Segmentation of moving cars based on detected mo-tion in the “thermal video” using optic flow algorithm.Video S11a: Full video for Figure 19a. Segmentation of moving cars based on detected mo-tion in the “winterstreet video” using the phase-based motion detection algorithm.Video S11b: Full video for Figure 19b. Segmentation of moving cars based on detected mo-tion in the “winterstreet video” using optic flow algorithm.


Grasses of the subfamily Pooideae, including important cereal crops and pasture grasses, are widespread in temperate zones. Seasonal regulation of developmental transitions coordinates the life cycles of Pooideae with the passing seasons so that flowering and seed production coincide with favorable conditions in spring. This review examines the molecular pathways that control the seasonal flowering responses of Pooideae and how variation in the activity of genes controlling these pathways can adapt cereals or grasses to different climates and geographical regions. The possible evolutionary origins of the seasonal flowering responses of the Pooideae are discussed and key questions for future research highlighted. These include the need to develop a better understanding of the molecular basis for seasonal flowering in perennial Pooideae and in temperate grasses outside the core Pooideae group. Grasses from the Pooideae subfamily, family Poaceae, occur widely in temperate regions . In addiA key factor underlying the adaptation of grasses to temperate climates is timing. Timing biological events to occur during specific seasons is the basis for stress avoidance strategies. For example, delaying flowering until after winter allows many grasses to avoid frost damage to cold sensitive reproductive organs see . AlternaThe study of the seasonal timing of biological phenomena is known as phenology. The broad topic of this review is the contribution of phenology to the success of Pooideae in temperate climates. We will highlight how different seasonal cues can adjust the developmental program of grasses to match seasonal cycles, using temperate cereals as examples, and then examine how naturally occurring variation in these responses drives adaptation to different geographical regions and climates. Then we will discuss how the molecular pathways controlling the seasonal flowering responses of temperate grasses might have evolved.Figure 1). As inflorescence development proceeds floral primordia appear on the developing spikelets and these develop into flowers, referred to as florets . Initially there is a delay of inflorescence initiation prior to winter. This delay is removed when plants over-winter, allowing inflorescence initiation to occur. Subsequently, increasing daylength and warmer temperatures accelerate development of the inflorescence in spring  are timed to optimally coordinate the plant life cycle with the changing seasons. This timing is achieved through the influence of seasonal changes in temperature and daylength on specific points in the developmental program  will influence grain yield of cereal crops because early flowering lines can produce grain before water becomes limiting whereas late flowering lines encounter drought stress, which reduces yield. There are many field studies that demonstrate indirect effects caused by the timing of flowering . Thus, sArabidopsis  is adapted to temperate climates and, like temperate grasses, flowers in response to vernalization (the prolonged cold of winter) and long days , which encodes a MADS box transcription factor that represses flowering  in nucleosomes at the FLC locus is required to maintain repression of FLC in vernalized plants  in the late afternoon (CO expression coincides with light and the protein is active. This activates transcription of FLOWERING LOCUS T (FT) in the leaves. FT encodes a phosphatidyl-ethanolamine binding protein (PEBP) that is translocated through the phloem from the leaves to the shoot apex  – also known as heme activator proteins (HAP) or CCAAT binding factors  are required (FLC-like gene 1 (FLM1)FLOWERING LOCUS M has also been implicated in the regulation of the high-temperature flowering response of Arabidopsis (High temperatures (>25°C) can activate expression of ansition . Elevaterequired . The FLCbidopsis . This gebidopsis .Arabidopsis also play important roles in regulating reproductive development in cereals. There are, however, few direct overlaps between Arabidopsis and cereals, with fundamental differences in the physiology of seasonal flowering responses and in the underlying molecular networks.As outlined in the next section, many of the classes of genes/proteins that regulate seasonal flowering responses in There exists considerable diversity in seasonal flowering responses amongst temperate cereals. Some lack the requirement for vernalization, others are daylength insensitive. For the purpose of this review we will consider the presence of a vernalization requirement combined with daylength sensitivity as being the archetypal flowering behavior of temperate cereals. This view is supported by molecular evidence (see subsequent sections) that reduced vernalization requirement and reduced daylength sensitivity are acquired states that have arisen on multiple occasions through mutation.VRN2 locus as a key gene controlling vernalization requirement in the cereals , the functional equivalent of FT in cereals  and constitutive expression of VRN2 down-regulates FT1  might be important. FT3 is normally expressed in short but not long days, and loss-of-function mutations in FT3 delay flowering primarily in short days  promotes inflorescence initiation . Vernalisensu stricto) is profoundly different to that of short-day treatment because vernalization at low temperatures slows growth. This is particularly evident with vernalization of imbibed seeds where plants can emerge from prolonged cold treatment with only one or two expanded leaves. In comparison plants exposed to several weeks of short days will have many leaves on the main stem and also secondary tillers. Thus, the term “short-day vernalization” should be interpreted with caution, as noted by The promotion of inflorescence initiation by vernalization is stronger than the effect of short days. For example, in experiments performed by VERNALIZATION1 (VRN1), a MADS box transcription factor gene related to the AP1/FRUITFULL genes of Arabidopsis . Daylength shift experiments, where wheat plants are shifted from short to long days, or vice versa, at different time points, show that the time from inflorescence initiation to the point when the terminal spikelet develops is a critical window for the acceleration of inflorescence development by long daylengths , which typically undergo inflorescence initiation in short days toward the end of winter. Instead longer days are likely to coincide with the inflorescence development and stem elongation stage (ylengths .PHOTOPERIOD1 (PPD1) and FT, the cereal FT equivalent , such that plants flower early irrespective of daylength  or PHYTOCLOCK1/LUX1 function, for example , which might cause increased transcriptional activity  alleles  in short-days, where inflorescence development is retarded (FLC-like MADS box genes (FLM) in regulating temperature responses in Arabidopsis and other plants . The concept of sub-dividing networks controlling developmental responses to specific phases/seasons is also important for the development of gene based models to predict flowering behavior of cereals and related grasses . Similar, though not identical, variation occurs in non-domesticated wheats, so variation in vernalization requirement mediated by VRN1 occurs independently of crop domestication . In wheat, a constitutive long-day flowering response is mediated mainly by active alleles of PPD1 that allow crops to be grown at times of year or at latitudes where short daylengths would otherwise limit cultivation. For example, breeding programs that are located at low-latitudes and focus on rapid cycling varieties  are likely to select cultivars with photoperiod insensitivity, which allows rapid flowering without long days. Conversely, a mutated version of the barley PPD1 gene occurs in many European barleys (ELF3 gene (MAT.a8) to breed barley cultivars that flower rapidly irrespective of daylength, which are well suited to short summer growing seasons at high latitudes , has also been utilized in crop breeding. The EPS2 gene  of barley encodes a PEBP that is distantly related to the FT gene family (HvCEN gene (Ala135 to Pro) delays flowering, and has been used to lengthen the inflorescence development phase of European spring barleys. Conversely, the wildtype allele predominates in autumn sown vernalization responsive barleys . Altering the duration of different developmental phases can have profound effects on plant physiology and plant architecture, and strongly influences major components of yield such as grain number per spike and grain size , ryegrass (Lolium sp.), fescue (Festuca sp.), and timothy grass (Phleum pretense) flower in response to vernalization and long days, though there is naturally occurring variation in vernalization and daylength requirements both between species of specific genera and within populations of individual species , timothy grass (Phleum pratense), and fescue , sorghum (Sorghum bicolor), and sugar cane (Saccharum officinarum). The second clade includes the Pooideae subfamily, together with the subfamilies Ehrhartoideae  and Bambusoideae (the bamboos) and is known as the BEP clade, with Bambusoideae widely accepted as the sister group to the Pooideae . The first clade includes tropical grass subfamilies and is known as the PACMAD , of which the Panicoideae subfamily includes crops such as maize . The vernalization response and long-day flowering are conserved features of the core Pooideae and Brachypodium . In contrast, rice does not require vernalization and flowers in response to shorter daylengths, similar to many grasses of the Panicoideae. Thus, it has been hypothesized that the vernalization and long-day flowering responses of grasses evolved in an ancestor of the Pooideae.Current knowledge of the molecular pathways that control flowering of temperate grasses comes from a restricted selection of cereals and pasture grasses, all members of a group informally termed the “core Pooideae” , or fromVRN1 gene function in the vernalization responses of temperate grasses such as ryegrass, fescue, and timothy grass , and the VRN1 gene of Brachypodium seems to have the same function. This suggests that the central role for VRN1 in the vernalization response of temperate grasses evolved early during the radiation of the Pooideae. Vernalization-induced flowering likely co-evolved with increased freezing tolerance  first intron, which has expanded relative to the equivalent region in the rice ortholog of VRN1  ortholog of GHD7 represses flowering in long-days and a similar function has been suggested for a Sorghum (S. bicolor) equivalent  down-regulates FT1 and FT2 in short days , might provide some indication of when the vernalization and long day flowering responses evolved during the radiation of the Pooideae. Additionally, a deeper understanding of the pathways controlling flowering in perennial Pooids can potentially offer further insights into the functions of key genes. Most importantly, ongoing research focussed directly on the Pooideae is essential if we are to develop a deeper understanding the reproductive biology of this important group of plants.Studying the molecular pathways controlling seasonal flowering responses in a broader range of Pooid species, particularly grasses outside the core Pooid group, will provide a clearer view of how these pathways evolved. Research in to basal Pooids, such as Siri Fjellheim, Scott Boden, and Ben Trevaskis wrote the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The androgenic adrenal steroids dehydroepiandrosterone (DHEA) and 4α-androstenedione (4-A) have significant biological activity, but it is unclear if the behavioral effects are unique or only reflections of the effects of testosterone (TS). Gonadally intact male Long-Evans rats were assigned to groups to receive supplements of DHEA, 4-A, TS, corticosteroid (CORT), all at 400 µg steroid/kg of body weight, or vehicle only for 5 weeks. All males were tested in a paradigm for sexual motivation that measures time and urinary marks near an inaccessible receptive female. It was found that DHEA and 4-A supplements failed to influence time near the estrous female in the same way TS supplements did, and, indeed, 5 weeks of 4-A administration reduced the time similar to the suppressive effects of CORT after 3 weeks. Further, animals treated with DHEA or 4-A left fewer urinary marks near an estrous female than TS and control groups. These results suggest that DHEA and 4-A are not merely precursors of sex hormones, and provide support for these steroids influencing the brain and behavior in a unique fashion that is dissimilar from the effects of TS on male sexual behavior. The androgenic adrenal steroids dehydroepiandrosterone (DHEA) and 4α-androstenedione (4-A) have significant biological activity, yet the nature of their significance, especially in the brain, remains uncertain. Similarly, these steroids’ direct effects on behavior have yet to be thoroughly explained, in contrast to the extensive research on the behavioral consequences of the androgen testosterone (TS), a potent sex steroid. Testosterone is used as a medical treatment for many conditions, most prominently sexual dysfunction. Illicit use to enhance athletic performance, particularly among men and boys, has been widespread since the 1980s [Still, there remains the possibility that DHEA and 4-A have unique impacts on complex behaviors, something that has been difficult to demonstrate. One approach is to employ a behavior that is highly sensitive to the sex steroids. Testosterone and its metabolites play a key role in both male and female interest in the opposite sex . Using ai.e., if a supplement group is similar to the vehicle group, it is concluded that the supplement had no effect on behavior. The TS-supplemented group is expected to represent the upper limit of sexual motivation, but also to serve as a measure of comparison for the DHEA and 4-A groups.The present experiment was designed to provide supplements of DHEA and 4-A and assess sexual motivation in intact male rats. Comparison conditions included supplements of either TS or corticosterone (CORT), presumably to be upper and lower limits of sexual motivation. CORT is included because there is substantial evidence that the hypothalamic-pituitary-adrenal axis (HPA) suppresses the hypothalamic-pituitary-gonadal (HPG) axis ,4. The vi.e., spending more time and urinary marking more near the receptive female. This would lend support to the hypothesis that these steroids merely affect behavior because they are likely metabolized into TS; they only impart effects after conversion, and therefore result in behavior similar to supplemental TS. If DHEA and 4-A animals behave more similarly to non-supplemented controls or even CORT animals, the support accrues to the androgenic adrenal steroids having unique effects on brain and behavior.The logic is that, if DHEA and 4-A serve only as precursors to TS, those males will behave similarly to the TS animals, Z ≥ 2.5) and each was replaced with the mean for that variable. All variables were evaluated for normality previous to multivariate analysis; no transformations were necessary. Four outliers were revealed in the open field data . Further analyses with main effects allowed comparisons between treatment groups at each week of testing and within treatment groups across the three weeks. Between group analyses revealed time differences among the hormone treatments during the first week of sexual motivation testing . Subsequent comparisons with Tukey’s HSD tests (p < 0.05) indicated that males administered TS spent more time near the estrous female than the other males, and males administered CORT spent less time near the estrous female than all other groups  in that TS animals spent more time near the estrous female, and the CORT animals spent less time near the estrous female, than all other groups. Comparisons of drug treatment at the third week of sexual motivation testing  revealed that males administered TS continued to spend more time near the estrous female than all other groups. The CORT group spent less time near the estrous female than other groups except for the 4-A animals. There were no differences between CORT and 4-A during the third week.Those differences were mirrored in the second week of testing  spent less time near the estrous female in week 3 compared to both weeks 1 and 2. Males administered DHEA  spent more time with the estrous female during week 3 when compared with week 1, but not week 2. Males administered CORT  spent less time near the estrous female during weeks 2 and 3 compared to week 1. Males receiving TS supplements  spent more time near the estrous female in week 3 when compared to week 2, although not to week 1. Vehicle control animals did not differ in this marker of sexual motivation across the three weeks of observation.Within-group main effects provided a snapshot of changes in time near the receptive female over the 3 weeks of sexual motivation testing. Results were that, whereas the TS rats showed increased motivation, each of the three adrenal supplement groups were less interested in the receptive females over weeks. Specifically, animals administered 4-A . Main effects allowed comparisons between treatment groups of total marks near each stimulus female. Between-group analyses showed significant differences of total urinary marks near the estrous female . Post hoc tests using Tukey’s HSD (p < 0.05) showed that animals receiving TS or vehicle marked significantly more near the estrous female than those animals receiving 4-A, DHEA, or CORT . Tukey’s post hoc analysis revealed that the CORT animals marked more near the nonestrous female than all other groups. DHEA-treated animals marked near the nonestrous female significantly more than 4-A-, vehicle-, and TS- animals. Numbers of marks near the non-estrous female were similar among the 4-A, TS, and vehicle groups.Between-group differences were also significant for total urinary marks near the nonestrous female . Males treated with 4-A, DHEA, TS, or vehicle marked significantly more near the estrous female than the nonestrous female . CORT-treated animals marked similarly near both stimulus females (p = 0.401).Within-group main effects revealed significant differences between marks near the estrous female and the nonestrous female within each treatment group .Numbers of lines crossed in the open field were totaled across the three weeks of testing. A univariate ANOVA revealed no significant differences among groups  and are without direct influences. Results from this experiment show that this is unlikely to be the case; DHEA and 4-A produced a behavioral footprint different than that of TS, indicating that they likely affect behavior directly and without requiring metabolic conversion. In agreement with previous findings ,11 that An important consideration for the different behavioral results yielded from TS, 4-A, and DHEA treatment is the complex metabolic cascade of the steroids. Our recent review  outlinedversus chronic exposure. This is made apparent in the differences between the CORT-treated group presented here and that of a previous study [A concern for all hormone research is the issue of acute us study . Males sus study . An interesting result in the current study is that while TS increased, and CORT and 4-A decreased, time spent in the proximity of a receptive female compared to vehicle-treated animals, TS and vehicle induced similar urinary marking near a receptive female while DHEA, 4A, and CORT supplements led to less marking. Both time spent near a receptive female and urinary marking near a receptive female are established as measures of sexual motivation, but it may be that they differ in mechanism such that they are affected by hormones on a different time course. It is also possible that different levels of hormones are required to affect each behavior such that the levels of TS we administered were enough to increase time spent near a receptive female, but not enough to increase urinary marking. Similarly, it is possible that the levels of DHEA supplements we used were enough to decrease urinary marking near a receptive female, but not enough to decrease time spent near the same female. In this light, DHEA appears to exhibit a unique effect on overall sexual motivation; while DHEA-treated males spent a similar amount of time near estrous females as vehicle-only males, they exhibited significantly less urinary marking than vehicle males in this area. These issues can be clarified in future studies utilizing varying doses and exposure periods.There are a few important limitations of the current study, some of which have been addressed above. In addition to those already mentioned, a significant limitation of our study is the lack of circulating hormone titers and reproductive organ weight data. Reproductive organ weights would provide a rudimentary measure of hormonal effect on the HPG axis, but circulating hormone measurements would provide definitive support for interpretation of the current results.There are considerable numbers of reports that 4-A and, particularly, DHEA have other functions than those evaluated here. In the brain, DHEA is a neurosteroid that influences a variety of behaviors, including cognition and mood . Still, N = 100) were experimentally naïve, gonadally intact male (n = 60) Long-Evans rats that were 9 weeks of age at the onset of the study. Each had been individually housed for at least 30 days in plastic cages measuring 48.3 cm × 25.4 cm × 20.3 cm with woodchip bedding. Females (n = 40) of the same age, strain and source as the experimental males were used as stimulus animals for the behavior tests. Standard rat chow and tap water were available to all animals ad libitum throughout the experiment. Animals were housed in a humidity-controlled colony maintained between 20 °C and 22 °C. Lighting was on a cycle of 12 h light and 12 h dark each day. The Institutional Animal Care and Use Committee of the University of Missouri-St. Louis approved all animal procedures.Animals  and suspended in olive oil. Males were subcutaneously injected with either 4-A, DHEA, TS, CORT or oil only (vehicle). Hormones were administered as 400 µg steroid/kg of body weight (bwt) . Estradin = 12) and SC injected with steroid supplements for 5 weeks. Each animal was behaviorally tested multiple times in the same paradigms. Sexual motivation testing was conducted over the last 3 weeks of supplementation with the result of a 5 × 3 factorial design with the main factor of hormone treatment  and time spent near stimulus female over 3 days of observation as the repeated measure. Urinary marking behavior data and locomotor activity data were summed over the three testing days due to notable variability across days. A 5 × 2 factorial design was used to analyze the urinary marking data, again using hormone treatment as the main factor and number of marks near the stimulus females as the dependent measures. The activity data resulted in a univariate ANOVA with hormone treatment as the main factor.Males were randomly assigned to 1 of 5 treatment groups  under general anesthesia using a single abdominal incision . Uterinen = 20) were induced to estrus with SC injections of estradiol benzoate and, 48 h later, with progesterone.Steroids were administered to males six days a week for five weeks. Injections began two weeks prior to testing, and continued for three weeks of behavioral testing. Females were used only as stimulus animals for behavioral measurement of male sexual motivation. All females were OVX, but half  for PC was used for the remainder of data analysis. Data analyzed for sexual motivation were time spent in the preference area of the estrous female over the three test sessions and total numbers of urinary markings near either stimulus female. Time spent in the neutral area was not considered in the analyses. Numbers of squares crossed provided the measure of general activity.p < 0.05.A repeated measures 5 × 3 ANOVA was used for time preference data from the sexual motivation apparatus. Main effects were calculated where applicable, and Tukey’s HSD method was used as a post hoc test to compare group means. A repeated measures 5 × 2 ANOVA was used for urinary marks using total marks near the stimulus females as dependent measures; again, Tukey’s HSD method was used for post hoc comparisons. Open field activity was analyzed using a one-way ANOVA using total activity scores across the three sessions. Probability value for all analyses was set at In summary, there has been very little published research exploring the effects of such adrenal steroids as a supplement to intact animals. In this study we sought evidence to support or refute the idea that the adrenal steroids simply serve to increase or maintain levels of TS and androgen-sensitive behaviors. Based on the results, it can be concluded that the adrenal supplements 4-A and DHEA leave behavioral “footprints” that are different from that of TS and therefore may be acting directly on the brain rather than serving only as substrates for sex steroids.


Though traditionally designed for entertainment purposes, video games are increasingly being used by psychologists to aid in our understanding of skill acquisition, cognitive capacity and plasticity, development and aging, and individual differences. Work by Green and Bavelier , now pubSpace Fortress has served as an invaluable research tool, and has revealed a great deal about the nature of skill acquisition and learning. However, as anyone who has played the game can attest, Space Fortress gameplay can be a frustrating and unenjoyable experience. Space Fortress was developed by psychologists, not professional game developers. Although it was similar to many arcade games at the time of its development, by today's standards Space Fortress is a relatively primitive game. It features rudimentary graphics, it lacks an engaging narrative, its level of difficulty does not adapt to the player's skill, and it is essentially the same “level” presented to the player over and over again . Modern video games feature realistic graphics, compelling stories, are adaptive, have changing demands, and allow the player to approach in-game problems in many different ways. They are designed to be motivating and challenging, but not so challenging as to arouse a high level of frustration. While many of these changes make the study of modern video games more appealing and interesting, the increased complexity and diversity of these games make performance within them more difficult to understand, and this introduces challenges when using video games as tools to achieve insight into cognitive processes. This Research Topic, containing 10 articles, and featuring 45 authors, highlights the promise and challenge of using commercial and custom video games to understand cognition.Many of the articles included in this Research Topic revolve around the theme of transfer of training from video games to other measures of perception and cognition, inspired by the now seminal work of Shawn Green, Daphne Bavelier, and others .The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.