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This paper explores the concept of "Clip Thinking" in the context of the digital age and investigates whether it is a complimentary or contradictory approach. Clip Thinking refers to the tendency of individuals to consume information and ideas in short, fragmented, and easily digestible formats, often facilitated by social media platforms and digital technologies. While Clip Thinking offers benefits such as quick access to diverse perspectives and efficient information processing, it also raises concerns about shallow engagement, echo chambers, and reduced critical thinking skills. This study employs a mixed-methods approach, combining qualitative interviews and quantitative surveys, to gather insights from participants representing different age groups, educational backgrounds, and digital media consumption habits. The qualitative interviews delve into participants' motivations, habits, and experiences related to Clip Thinking, providing an in-depth understanding of the phenomenon. The quantitative surveys measure participants' information consumption patterns, cognitive abilities, and attitudes towards Clip Thinking. On one hand, participants appreciate the convenience and accessibility offered by short, clipped content. They find it easier to navigate the overwhelming information landscape, rapidly browse topics of interest, and connect with a broader range of ideas. On the other hand, concerns emerge regarding the potential for information overload, reduced attention spans, and a lack of depth in understanding complex issues. Participants express worries about the erosion of critical thinking skills and the creation of filter bubbles that reinforce pre-existing beliefs. By analyzing the data collected, this paper aims to provide a nuanced understanding of the impacts of Clip Thinking on individuals' cognitive processes, decision-making abilities, and overall information consumption habits. The study's conclusions will inform educators, policymakers, and media platforms about the challenges and opportunities associated with promoting a balanced information ecosystem in the digital age. [ABSTRACT FROM AUTHOR]

The purpose of this study was to investigate the effects of holding external loads on postural sway during upright stance across age decades. Sixty-five healthy adults (females, n = 35), aged 18-80 years were assessed in four conditions; (1) standing without holding a load, holding a load corresponding to 5% body mass in the (2) left hand, (3) right hand and (4) both hands. The centre of pressure (COP) path length and anteroposterior and mediolateral COP displacement were used to indirectly assess postural sway. External loading elicited reductions in COP measures of postural sway in older age groups only (P < 0.05). No changes were observed in younger or intermediate aged adults (P > 0.05). Holding external loads during standing is relevant to many activities of daily living (i.e. holding groceries). The reduction in postural sway may suggest this type of loading has a stabilising effect during quiet standing among older adults. [ABSTRACT FROM AUTHOR]

In children under 20 years, refractive development targets a cycloplegic refractive error of +0.5 to +1.5D , while presbyopes over 40 years generally have non-cycloplegic errors of ≥ +1D. Some papers suggest these periods are separated by a period of myopic refractive error (i.e., ≤ –0.50D), but this remains unclear. Hence, this work investigates the mean cycloplegic refractive error in adults aged between 20 – 40 years. In 2002 a cross-sectional study with stratified cluster sampling was performed on the population of Tehran, providing cycloplegic and non-cycloplegic refractive error data for the right eyes of 3,576 participants, aged 30.6 ± 18.6 years (range: 1–86 years). After grouping these data into age groups of 5 years, the refractive error histogram of each group was fitted to a Bigaussian function. The mean of the central, emmetropized peak was used to estimate the mean refractive error without the influence of myopia. The mean cycloplegic refractive error at the emmetropized peak decreased from +1.10 ± 0.11D (95 % confidence interval) to +0.50 ± 0.04D before 20 years and remains stable at that value until the age of 50 years. The non-cycloplegic refractive error also sees a stable phase at 0.00 ± 0.04D between 15 – 45 years. After 45 – 50 years both cycloplegic and non-cycloplegic refractive error become more hypermetropic over time, +1.14 ± 0.12D at 75 years. The cycloplegic refractive error in adults is about +0.50D between 20 – 50 years, disproving the existence of the myopic period at those ages. [ABSTRACT FROM AUTHOR]

Autism Spectrum Disorders (ASD) assessment relies on clinical rating scales to measure related social and behavioral changes, a subjective process which is prone to misdiagnosis. ASD heterogeneity of social and cognitive functioning has been associated with underlying neuro-anatomical alterations. Automatic medical imaging analyses have made possible quantification of these anatomical changes, yet these complex morphological patterns have been partially characterized by simple absolute scalar values. This paper presents a much more complete exploration of the global–local differences between ASD and control subjects using a multiscale descriptor that captures sub-visual spatial patterns. This analysis consists in three main steps: a pre-processing for segmenting the brain into a particular anatomical parcellation, a region-based characterization for capturing global–local folding/shape patterns, and a statistical analysis for quantifying differences between ASD and control individuals. A large data cohort (n = 1245) consisting in three different age groups, was used to perform this exploration. The analysis was carried out in the entire set of cortical and subcortical brain regions: (i) using two different brain parcellations, and (ii) separately for each age group. This characterization revealed statistically significant differences (p ¡ 0.05) in the ASD group compared to control individuals using two brain parcellations. These results demonstrate the representation is able to identify folding and shape differences for a particular age range in both parcellations, supporting the generalizability of these findings. • Quantification of brain folding/shape differences at different orientation, depths and circumvolution patterns in every cortical and subcortical brain region. • A statistical analysis for establishing brain differences between ASD and control individuals. • A more complete evaluation by assessing the representation with a larger population (n = 1245, three groups of age), and two different brain parcellations. • An anatomical–functional correlation, crucial for developing an unbiased quantification of the disease and a more accurate categorization. [ABSTRACT FROM AUTHOR]

Deep learning-based automatic sleep staging methods have been widely applied for sleep scoring and sleep diagnosis. However, most methods consider only a single temporal scale when dealing with sleep signals. Furthermore, these methods are limited to target only a single-age group or single dataset. In this paper, we propose a multi-scale temporally focused sleep staging model, MAGSleepNet, which can be used for multi-age groups simultaneously. MAGSleepNet consists of (1) a group age classification (GAC) module that can offer a preliminary screening on epidemic estimation of multiple age, (2) a dimensional expansion module (DEM) that can expand the dimension of the input signals, (3) a sequential multi-scale convolutional neural network (SMCNN) that extracts multi-scale features and short-time temporal information, and (4) sequence temporal encoder (STE) that extracts sequential temporal information. In addition, two auxiliary tasks are used to complement the short-time temporal information and to reassign the probabilities of different age groups to enhance the model robustness, respectively. The MAGSleepNet is evaluated in adult, child and infant, tested on MASS, CHAT, and CHFU datasets with accruacy of 86.7%, 80.1% and 66.5%, outperforming the state-of-the-art methods. Based on the excellent performance of the proposed method, it is expected to pave the way for automatic sleep staging methods with strong generalizability for multiple age groups. • A novel model is proposed for simultaneous sleep staging in multi-age groups. • The hierarchical architecture of model ensures the effective feature extraction. • An auxiliary task is used to provide temporal information on different scales. • Numerous experiments are conducted to evaluate the proposed model. [ABSTRACT FROM AUTHOR]

Diverse citizens need to be involved in net zero transitions to ensure policy interventions do not entrench inequalities for people from minoritised or disenfranchised groups and ensure public engagement with rapid social changes. This paper illustrates the importance of designing enjoyable engagement activities aimed at segmented citizen and community groups, to ensure a broad cross-section of society can participate in environmental debate and policymaking. We analysed an evaluation sample of 857 people, representing 10.3% of the 8302 people directly engaged with the ClairCity project from six European countries. Women were under-represented in our activities, and younger participants preferred non-traditional forms of engagement like online games. Across all activities, multiple regression analyses found statistically significant relationships between younger age groups and enjoyment, and a positive correlation between enjoyment and understanding of air quality. Behaviour change intention was also significantly positively correlated to understanding, with 74% of participants indicating they would make a behaviour change to improve air quality. While climate change and air pollution are serious issues, public engagement to raise awareness and improve participation in policymaking does not have to be. To fully realise citizen-led emissions reduction, policymakers need to co-create engagement activities which are enjoyable, inclusive, and attractive to diverse citizens representing regional demographics. Ultimately, the more enjoyable and relevant the engagement activities, the more understanding people gain about the issues, and are therefore more likely to make a change to individual or community behaviours to reduce air pollution and carbon emissions and improve public and environmental health. [Display omitted] • Diverse communities need representation in climate/air pollution policymaking. • One size does not fit all: different activities attracted different demographics. • Activity enjoyment was significantly positively correlated to understanding. • Understanding was significantly positively correlated to behaviour change intent. • Policymakers should plan enjoyable activities to enable social learning between groups. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries age continuously during usage due to their characteristics and the influence of various external factors, but as degradation deepens, it can lead to an apparent decrease in battery safety and reliability. Therefore, predicting remaining useful life from the current to end state and preventing possible dangerous incidents are essential for battery health management. A novel method from the perspective of providing aging features reference and balance prognostics speed and precision is proposed. Firstly, the used dataset is preprocessed in many ways. Then, through feature engineering, 79 features are extracted in the dataset from three perspectives: direct, evolution, statistics, and most representative 16 features are filtered to form the final feature set based on the method of combining discretization and importance. Feature engineering is established to find crucial information within the dataset that correlates highly with remaining life and represents most battery recession paths. Finally, the sparse autoencoder and Transformer integrated approach is proposed to build the life prediction model, and it can learn the temporal relationship between the feature set and remaining cycles quickly and accurately. According to the forecasting results of 62 batteries with different aging conditions, the error can reach 7.43% by only using the feature sequence under 30 cycle lengths. For early life prediction, the error of using the first 100 cycles data is at most 2.6%. • A novel aging feature filtering approach is proposed based on feature engineering. • A prediction model is established by using a sparse autoencoder and Transformer. • More accurate RUL and early life of a battery can be predicted by using fewer cycle data. • After the feature engineering presented in this paper, the final aging feature set selected has strong applicability. [ABSTRACT FROM AUTHOR]

Large-scale geotagged social media data have been increasingly used for exploring human movement patterns in cities. Challenges of this new data type, such as non-representative users and the lack of activity purposes, remain unsolved and limit its applications in exploring activity-based human patterns in cities. To deal with the above challenges, this paper proposed an analytical framework of social media data enrichment — by revealing the demographic composition of non-representative social media data users and inferring activity purposes of geotagged posts — for better exploring spatial-temporal patterns of human activity in cities. A deep learning model is employed to reveal social media users' age and gender groups from user names, profile images, biographies, and language settings. Eight types of activity purposes are inferred from embedded geo-location by spatially joining with fine-scale building and land use data. Using Greater London as the case study, this paper explores the temporal dynamics of activity purposes with heatmaps of hourly frequency of tweets and identifies spatial differences across age and gender groups using hotspots analysis (Getis–Ord Gi* statistics). This paper demonstrates the application of geotagged social media data in identifying spatial, temporal and demographic patterns of urban activities, which potentially helps shape better place-based and age/gender-sensitive urban policies and planning decisions. • Using large-scale geotagged social media data to understand patterns of urban activities. • A deep learning model is applied to infer demographic characteristics from metadata of social media users. • Utilising the _ne-level building uses and green space uses to infer activity purposes from geotagged social media data. • Revealing temporal and spatial patterns of eight types of urban activities across different age and gender groups. [ABSTRACT FROM AUTHOR]

This paper aims to evaluate the prevalence of REs in a clinic from Aguascalientes, Mexico by analysing clinical records from the local public health system. Refractive errors (REs) are quite common globally, but no data have been published regarding their frequency in clinics from Mexico. A priori, the frequency of ametropias should be high as admixture ancestry from this region is mainly European and Amerindian, the regions with high prevalence worldwide. This cross-sectional study was conducted on 2195 subjects from records of public optometry services during the year 2018. Information obtained included age, gender, sphere, cylinder and axis. The prevalence of myopia, hyperopia and astigmatism was determined by gender and age groups in paediatric and adult patients. Chi-square testing was applied to determine significant differences in prevalence across age groups and gender. A p-value <0.05 was considered significant. In subjects under 18 years of age, the prevalence of emmetropia, astigmatism, myopia and hyperopia was 20.1%, 51.1%, 7.0% and 11.8%, respectively. In adults, emmetropia was present at a frequency of 20.1%, while 57.1% presented astigmatism, 12.4% hyperopia and 8.6% presented myopia. A significant association was observed between the presence of REs and age and gender. In this first report of prevalence of REs from western Mexico, astigmatism was the most prevalent RE in children, adolescents and adults while the least common was myopia. Important differences were found in prevalence in comparison to national and international reports. [ABSTRACT FROM AUTHOR]

• Morbidity and mortality in children due to COVID-19 remained low • Adolescents had higher reported cases than younger children • Reported cases were lower in pediatric population than adult population • Testing protocols vary between countries; reflects bias in reported cases Few data on the COVID-19 epidemiological characteristics among the pediatric population in Africa exists. This paper examines the age and sex distribution of the morbidity and mortality rate in children with COVID-19 and compares it to the adult population in 15 Sub-Saharan African countries. A merge line listing dataset shared by countries within the Regional Office for Africa was analyzed. Patients diagnosed within 1 March and 1 September 2020 with a confirmed positive RT-PCR test for SARS-CoV-2 were analyzed. Children's data were stratified into three age groups: 0-4 years, 5-11 years, and 12-17 years, while adults were combined. The cumulative incidence of cases, its medians, and 95% confidence intervals were calculated. 9% of the total confirmed cases and 2.4% of the reported deaths were pediatric cases. The 12-17 age group in all 15 countries showed the highest cumulative incidence proportion in children. Adults had a higher case incidence per 100,000 people than children. The cases and deaths within the children's population were smaller than the adult population. These differences may reflect biases in COVID-19 testing protocols and reporting implemented by countries, highlighting the need for more extensive investigation and focus on the effects of COVID-19 in children. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) has a significant impact on the course of the COVID-19 pandemic from various aspects. This paper aims to explore the trends of AI applications and how they help predict and prevent the progress of COVID-19 in Saudi Arabia. The method used in this study is based on a narrative review of recent literature on AI and COVID-19 and on a survey conducted on 211 participants. Results show that AI is a crucial element to overcoming COVID 19. The use of COVID-19 related Apps that helped reduce the pandemic spread was more common among the age group participants ranging from 15 - 30. The study concluded that COVID-19 made a positive impact on everyone, and by the use of technology, things got much more comfortable to help in enduring any long-term health consequences. [ABSTRACT FROM AUTHOR]

• The first wave of COVID-19 in Malawi coincided with widespread political gatherings. • Mass gatherings and high-risk area repatriation were first wave main drivers. • COVID-19 was more prevalent in older people, men and urban areas. The COVID-19 pandemic in Malawi emerged amidst widespread anti-government demonstrations and subsequent mass gatherings. This paper describes the incidence and factors associated with the spread of the COVID-19 pandemic in Malawi. This was a retrospective study of public data analysing geopolitical and immigration activities that occurred between 02 April and 08 September 2020. The Chi-square test of independence was used to tabulate sex and age-related fatality ratios among deaths due to COVID-19-related complications. The drivers for COVID-19 spread were mass gatherings secondary to the country's political landscape and repatriation of citizens from high-risk areas coupled with minimum use of public health interventions. The prevalence was higher in people aged 50–59 years, males and in urban areas. Men had an increased risk of COVID-19-related deaths (Case Fatality Ratio: 1.58 (95% CI 1.11–2.22) compared with women. Furthermore, men and women aged ≥40 years were 16.1 times and 7.1 times more likely to die of COVID-related complications, respectively. Men aged ≥40 years had a 62% increased risk of deaths compared with women of the same age group. Mass political gatherings and cross-border immigration from high-risk areas were drivers for infection. Males, older age and urban residence were associated with increased COVID-19 morbidity and mortality. To control the spread of COVID-19 there is a need to regulate mass gatherings and repatriation of citizens, and strengthen the use of preventive health interventions. Men, the older age groups and urban areas should be prioritised for COVID-19 prevention strategies. [ABSTRACT FROM AUTHOR]

In the computer vision community, easy categorization of a person’s facial image into various age groups is often quite precise and is not pursued effectively. To address this problem, which is an important area of research, the present paper proposes an innovative method of age group classification system based on the Correlation Fractal Dimension of complex facial image. Wrinkles appear on the face with aging thereby changing the facial edges of the image. The proposed method is rotation and poses invariant. The present paper concentrates on developing an innovative technique that classifies facial images into four categories i.e. child image (0–15), young adult image (15–30), middle-aged adult image (31–50), and senior adult image (>50) based on correlation FD value of a facial edge image. [ABSTRACT FROM AUTHOR]

• An empirical multi-method study assessed park visitor patterns during 2018 summer heat. • Two differently characterized parks differ in their cooling function. • Temperature threshold of around 30 °C was identified where numbers for jogging and playing with children declined. • Age groups based activities in parks are linked to park design characteristics. Urban parks provide multiple ecosystem services to mitigate challenges from climate change and urbanisation. They promote health and well-being by providing space for physical activity and social interaction, which is particularly relevant for vulnerable groups such as children and older people. As a key element, park vegetation creates favourable environments, as it moderates heat, buffers noise and can be enjoyed by citizens. In this paper, we present the results of a multi-method empirical study conducted in the city of Leipzig, Germany, during the summer heat and drought period in July 2018. Visitation patterns were analysed through qualitative observation and structured counting in two differently characterised urban parks – a newly developed urban park on a former railway brownfield and a long-standing, older park with a mature tree population. The results indicate that park design elements are linked to park use activities and park user age groups such as young children, school children and older people. Young children were identified as mostly using playgrounds and natural lawn areas in the old park, while school children and teenagers tended to use the sports areas and semi-secluded spaces in the newly developed park to play sports or to meet in groups and socialize. For older people, sedentary activity was exclusively observed on benches, and non-sedentary activity such as jogging was nearly exclusively identified in the larger, more shaded older park. The number of counted park users, particularly numbers of children and older people, significantly declined at the highest temperature of approximately 30 °C. Considering the provision and availability of inclusive design elements that support these use behaviours may increase the motivation of all age groups to use green spaces and to benefit from the services they provide. Planning for a more effective and just provision of ecosystem services requires the consideration of age-specific design elements to invite use from all population groups equally and to contribute to distributional justice. [ABSTRACT FROM AUTHOR]

The age and gender information extracted from Electroencephalogram (EEG) has been used in various applications which are allocating a person to age and gender groups, identifying or authenticating a person and improving brain-computer interface systems. Besides this, the EEG-based automatic recognition of alcoholics greatly supports to the psychiatrists. However, one of the major challenges when using EEG is about storing and transmitting a huge amount of EEG data, leading to the need of using compression. Although lossy compression techniques give much higher compression ratio (CR) than lossless ones, they introduce the loss of information including the age, gender and alcoholic information in the reconstructed signals, which may reduce the performance of EEG-based age, gender and alcoholic recognition systems significantly. In this paper, the impact of lossy compression on the age, gender and alcoholic information extracted from EEG signals is examined in detail with different feature extraction and machine learning techniques. Our experimental results indicate that with an appropriate feature extraction technique, we could minimize the information loss in EEG compression and maintain the high performance of EEG-based age, gender and alcoholics recognition systems. [ABSTRACT FROM AUTHOR]

Despite the widespread of social media among all age groups in Arabic countries, the research directed towards Author Profiling (AP) is still in its early stages. This paper provides an Egyptian Dialect Gender Annotated Dataset (EDGAD) obtained from Twitter as well as a proposed text classification solution for the Gender Identification (GI) problem. The dataset consists of 70,000 tweets per gender. In text classification, a Mixed Feature Vector (MFV) with different stylometric and Egyptian Arabic Dialect (EAD) language-specific features is proposed, in addition to N-Gram Feature Vector (NFV). Ensemble weighted average is applied to the Random Forest (RF) with MFV and Logistic Regression (LR) with NFV. The achieved gender identification accuracy is 87.6%. [ABSTRACT FROM AUTHOR]

Polycyclic aromatic hydrocarbons (PAHs) are organic compounds composed of at least two benzene rings. This paper reviews the characteristics, sources and health risk of airborne particulate PAHs in Chinese cities. The airborne particulate PAH concentrations varied from 3.35 to 910 ng m−3, with an average of 75.0 ng m−3, and the pollution level of PAHs in northern cities was generally higher than that in southern cities. The PAH concentrations in different cities underwent similar seasonal variations, with high concentrations in the winter and relatively low concentrations in the summer. Many factors, such as meteorological conditions and source emissions, influenced the spatiotemporal pattern of PAHs. High temperatures, frequent flow exchanges, abundant rainfall and strong solar radiation reduced the level of particulate PAHs in the atmosphere. The historical changes in the level of airborne particulate PAHs in four cities were analyzed. The PAH concentrations in Beijing and Taiyuan presented a trend of first increasing and then decreasing, while the level of particulate PAHs in Nanjing and Guangzhou had a decreasing tendency from year 2000–2015. The airborne particulate PAHs in cities were derived from several sources, including coal combustion, vehicle emissions, coking industries, biomass burning and petroleum volatilization. The results of a health risk assessment indicated that the incremental lifetime cancer risk (ILCR) for people in the northern cities was higher than that for people in the other regions, especially during the cold season. Moreover, adults were at greater risk than people in other age groups, and the health risk to females was slightly higher than that to males. The potential risk of airborne particulate PAH exposure was relatively high in some cities, and controlling PAH emissions at the source should be required to prevent pollution. Image 1 • The contamination status of particulate PAHs in Chinese cities was reviewed. • Meteorological conditions and source emissions were the main factors influenced the spatiotemporal variations of PAHs. • Adults had higher potential risks than the other age groups. The concentrations, spatiotemporal variations, influencing factors and potential health risk of airborne particulate PAHs in Chinese cities were reviewed. [ABSTRACT FROM AUTHOR]

• Carry out the fracture experiment of concrete in low-temperature environment. • Determine the bilinear softening curve using the inverse analysis. • Find the influence of temperature on the softening curve and fracture parameters. • Validation the correctness of softening curves based on the double-K fracture model. The mode and fracture parameters of concrete at different temperature levels (20 °C, 0 °C, −20 °C, and −40 °C) were investigated using three-point bending fracture experiment in a low-temperature fracture test system. The three-point bending beams with the same sizes, 750 mm × 150 mm × 70 mm, were divided into two groups according to age: 28 days and 120 days. The bilinear softening parameters for each beam were determined using the inverse analysis; then, the fracture energy G F and characteristic length l ch were determined by the calculated softening curve. In addition, the fracture toughness including the initial fracture toughness K Ic ini , unstable fracture toughness K Ic un and cohesive toughness K Ic c were also analyzed. The experimental and calculation results show that the softening curve shape and fracture parameters of the concrete change significantly when the temperature decreases. Finally, the double-K fracture model was used to verify the validity of the bilinear softening curve calculated in this paper. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, boundary cubic rooted planar maps are investigated and exact enumerative formulae are given. First, an enumerative formula for boundary cubic inner-forest maps with the size (number of edges) as a parameter is derived. For the special case of boundary cubic inner-tree maps, a simple formula with two parameters is presented. Further, according to the duality, a corresponding result for outer-planar maps is obtained. Finally, some results for boundary cubic planar maps and general planar maps are obtained. Furthermore, two known Tutte''s formulae are easily deduced in the paper. [Copyright &y& Elsevier]

The worldwide burden of dementia is immense, and set to increase to unprecedented levels in the coming decades, due to population aging. In the absence of disease-modifying treatment, there is therefore a strong rationale to support the assumption that acting on modifiable risk factors, especially in midlife, is a good strategy for reducing the burden of dementia. Among these risk factors, nutrition is key, as it is fundamental to healthy aging, and has interrelated benefits on a number of organ systems, metabolic processes and health states that can all contribute to modifying the risk of dementia. In this paper, we review the methodological challenges of comparing studies of dietary interventions. We then discuss the effect of genetics and the environment on brain health, and review in particular the literature data on the effect of nutrition on cognition. We summarize the body of data reporting the largely beneficial effects of the Mediterranean diet on brain health, and the possible mechanisms that mediate these effects. Finally, we discuss future perspectives for further research in the field, notably the "gut-brain axis", thought to be a key mediator of the effect of nutrition on brain health. • The burden of dementia is huge and will affect 130 million persons by 2050. • Acting on modifiable risk factors, e.g. diet, is key to delaying or preventing AD. • Consistent evidence shows that the Mediterranean-type diet benefits brain health. • The "gut-brain axis" may mediate the effect of nutrition on brain health. [ABSTRACT FROM AUTHOR]

Conventional disease prediction models frequently have imbalanced or insufficient observed samples. In a real-world situation, the learned model from an imbalanced dataset may have poor generalization ability. In this paper, we use machine learning methods to investigate age adaptation in Diabetes Mellitus (DM) risk prediction. Typical machine learning algorithms for DM prediction include Linear Regression (LR), Logistic Regression, Polynomial Regression (PR), Neural Network (NN), Support Vector Machines (SVM), Random Forest (RF), and XGboost (XGB). Based on feature compensation and soft decision threshold adjustment, we propose a novel age adaptation algorithm. The results were validated using the publicly available Pima Indian Diabetes Dataset. The experimental results show that the disease risk prediction model's efficiency and accuracy are promising. The performance dropped for different age groups when using the original features. Using the compensated features, the accuracy rates for DM models were improved considerably. Age adaptation methods can be trained on one age group and adapted to another, solving the problem of data scarcity in a specific age range. [Display omitted] • Diabetes Mellitus risk prediction is studied with various machine learning models. • Feature distribution among different age groups are anlyzed. • A novel feature compensation network is proposed. • Generalization ability on unseen age groups is achieved. [ABSTRACT FROM AUTHOR]

This article investigates the influence of age structure on CO 2 emissions from household road transport by using an extended STIRPAT model plus data from 380 Norwegian municipalities for 2009, 2011 and 2013. After controlling for population, household income, age structures, household size, and different urban forms (urbanization, urban density, housing type, building density), the paper reveals that the age group responsible for the highest CO 2 emissions is 50–69, followed by 20–34 and 35–49. Moreover, compared with other groups, the road transport activities of age group 35–49 are highly constrained by household income. The paper also shows that there is an inverted U-shape relationship between household CO 2 road-related emissions and building densities. However, it indicates certain limitations on city planners when it comes to reducing household CO 2 road-related emissions by bringing the downtown area closer. Moreover, the paper also identifies a so-called compensatory mechanism supporting the hypothesis that building densities have positive effects. Furthermore, the coefficient of low-density housing is positive and significant, implying that the private gardens of low-density housing might not be the reason for the hypothesized compensatory mechanism. However, this remains a question worth investigating. • The extended STIRPAT model covers data from 380 Norwegian municipalities. • The highest CO 2 emissions group is age 50–69, followed by ages 20–34, and ages 35–49. • The net elasticity of income is negative. • There is an inverted U-shape relationship between household CO 2 emissions on the road and the building density. [ABSTRACT FROM AUTHOR]

In the study of theology relevant to contemporary advances in science and technology, the underpinnings with regards to the religious and spiritual outcomes have to be considered. In the case of humanoids for spiritual augmentation of children with various brain impairments, the religious implications to the children and their families require adequate support prior to the sessions. Hence, this paper provides a review of a monotheistic religion, Islam, that is, the perceptions on the use of robots for spiritual augmentation of special-needs children within the context of the Islamic faith. This is important to teachers and researchers in anticipating better outcomes and in contradicting the debate on psychedelic consequences. [ABSTRACT FROM AUTHOR]

This paper discuss about mock experiment on a typically developed child. The mock experiment is based on the previous work of the experimental framework on ASKNAO intervention. This is conducted as a preparation for the main experiment and to fine-tune the framework so that undesirable elements from the framework can be avoided. A typically developed child is used rather than an autism child because the typically developed child is able to handle the stress that occurs and capable of expressing his emotions freely. The findings of the experiment shows that the several adjustment need to be made on the previous framework in order to achieve a better result for the main experiment on an autism child. [ABSTRACT FROM AUTHOR]

Accurate, reliable and easy-to-use statistical methods in multifactorial age estimation from the skeleton remains a much-debated issue. In this paper, we explore the use of decision trees in adult age estimation. For this purpose, a dataset from 100 acetabula of South Africans, previously used for age estimation using transition analysis, were used to build a basic decision tree. A test sample of 25 individuals were then employed to assess the newly developed decision tree. Using the decision tree, 20 of the 25 individuals were classified into the correct age group (young, middle or older adults), with the remaining 5 falling within the adjacent age group. The decision tree provided a more accurate outcome as compared to the previous study using transition analysis. Although much research is still needed, this analysis suggests that decision trees may be usable in adult age estimation and may handle the non-linear relationship between chronological and biological age somewhat better than other traditional statistical methods. [ABSTRACT FROM AUTHOR]

• Software scrum development. • Software cost estimation is still a complex task. • Effort estimation techniques in scrum still has some flaws that need to be resolve. Scrum methodology is the most useful and adopted part of the agile methodology. Many organizations are adopting Scrum for the last decade to meet their software requirements. It is facilitating the software industries to develop software applications according to the user's requirements. Scrum helps to fulfill the customer's requirements by interacting with the client and developer. Instead of this, scrum still has some challenges that influence the cost of a scrum. These challenging factors include coordination, team size, change request, complexity, and issues in daily meeting sessions. Due to these factors mostly the cost and time exceed scrum-based projects. To overcome these issues from the accurate and precise estimation in the scrum project we have developed a web-based software system to estimate the effort of a user story as well as the budget. There are some sophisticated cost estimation techniques for scrum-based projects. But all estimation techniques have some limitations that make them less useful for estimation and overcoming the effects of these factors in the scrum. We have surveyed the multiple software industries to get the static findings of the survey. We have designed the 30 hypotheses that main aim to reveal how much the proposed estimation technique is valuable for the accuracy of estimation. For the inclusion of participants, we have set the age criteria to get the opinions of the most experienced programmers. The main aim of this paper is to provide knowledge about key challenging factors in Scrum that cause exceed in cost and time, and also briefly explain why existing scrum cost estimation techniques are not pertinent for projects. In the last, we propose a framework as a solution to manage these factors and control cost and time from exceeding. We also adopted this estimation technique in different case studies in software industries for findings and results. The technique calculates the efforts autonomously. We design a software-based estimation technique that collects inputs from team/s and estimates the cost and time of a project. In outcomes, we found that our cost estimation approach reduced the issues from scrum software project development and make it more proficient for estimation of projects. Our proposed estimation technique introduced the new concept of estimation that facilitate the client, software industry, and developers as well to meet the requirements of the client, fulfill the changes during the sprints/s development and deliver the project within the time and cost. [ABSTRACT FROM AUTHOR]

Age estimation from teeth by radiological analysis, in both children and adolescents, has wide applications in several scientific and forensic fields. In 2006, Cameriere et al. proposed a regression method to estimate chronological age in children, according to measurements of open apices of permanent teeth. Although several regression models are used to analyze the relationship between age and dental development, one serious limitation is the unavoidable bias in age estimation when regression models are used. The aim of this paper is to develop a full Bayesian calibration method for age estimation in children according to the sum of open apices, S, of the seven left permanent mandibular teeth. This cross-sectional study included 2630 orthopantomographs (OPGs) from healthy living Italian subjects, aged between 4 and 17 years and with no obvious developmental abnormalities. All radiographs were in digital format and were processed by the ImageJ computer-aided drawing program. The distance between the inner side of the open apex was measured for each tooth. Dental maturity was then evaluated according to the sum of normalized open apices (S). Intra- and inter-observer agreement was satisfactory, according to an intra-class correlation coefficient of S on 50 randomly selected OPGs. Mean absolute errors were 0.72 years (standard deviation 0.60) and 0.73 years (standard deviation 0.61) in boys and girls, respectively. The mean interquartile range (MIQR) of the calibrating distribution was 1.37 years (standard deviation 0.46) and 1.51 years (standard deviation 0.52) in boys and girls, respectively. Estimate bias was βERR=-0.005 and 0.003 for boys and girls, corresponding to a bias of a few days for all individuals in the sample. Neither of the βERR values was significantly different from 0 (p>0.682). In conclusion, the Bayesian calibration method overcomes problems of bias in age estimation when regression models are used, and appears to be suitable for assessing both age and age distribution in children according to tooth maturity. [ABSTRACT FROM AUTHOR]

This research proposes a methodology for digitizing street level accessibility with human sensing of wheelchair users. The dig- itization of street level accessibility is essential to develop accessibility maps or to personalize a route considering accessibility. However, current digitization methodologies are not su ffi cient because it requires a lot of manpower and therefore money and time cost. The proposed method makes it possible to digitize the accessibility semi-automatically. In this research, a three-axis accelerometer embedded on iPod touch sensed actions of nine wheelchair users across the range of disabilities and aged groups, in Tokyo, approximately 9 hours. This paper reports out attempts to estimate both environmental factors: the status of street and subjective factors: driver's fatigue from human sensing data using machine learning. [ABSTRACT FROM AUTHOR]

Process of Depression Detection Using Auto Encoder Network. [Display omitted] • An efficient machine learning algorithm for depression status detection based upon EDA is proposed. • The model is based on emotional context insensitivity during depression. • A set of features from different signal representations is extracted. • Optimal features subset and network configuration is identified. Depression is the leading mental illness/disorder around the world with global number reaching up to 300 million worldwide. This mental disorder is more prevalent in youngster of age group of 18–25 years especially in developing countries. Early diagnosis and treatment are required to this alarming problem specifically for an adolescent student suffering from these disorders who more often goes undiagnosed and hamper their progress at the critical movement of their life. The cheaper automatous system such as electrodermal (EDA) can help in with early diagnosis of depression disorder. In this paper, EDA based machine learning using autoencoder network (AEN) and deep neural networks (DNN) was developed for detecting level of depression among 38 university students. Developed AEN and DNN algorithm was able to classify five categories of depression with training of 96.5% and 94.5%, testing accuracy 95.2% and 94.2% while overall network accuracy was 94.0% and 92.0% with high sensitivity and specificity rate. [ABSTRACT FROM AUTHOR]

Human beings can easily categorize a person's age group from a facial image where as this ability has not been promising in the computer vision community. To address this problem very important area of research, the present paper proposes a novel scheme of age classification system using features derived from co-occurrence parameters using Rank based Edge Texture Unit (RETU). The Co-occurrence Matrix (CM) on RETU characterizes the relationship between the neighbouring edge values, while preserving local information. The novelty of the proposed RETU is it classifies the age of human into seven categories i.e. in the age groups of 1-10, 11-20, 21-30, 31-40, 41-50, 51-60, and greater than 60. The TU of the proposed RETU ranges from 0 to 17 and thus reduces overall complexity in evaluating features from CM. The co occurrence features extracted from the RETU provide complete facial image information for age classification purpose. The RETU reduces each 3×3 sub image into 2×2 sub image while preserving the texture features and thus reduces the overall dimensionality of the image. [ABSTRACT FROM AUTHOR]

Sex estimation is used in forensic anthropology to assist the identification of individual remains. However, the estimation techniques tend to be unique and applicable only to a certain population. This paper analyzed sex estimation on living individual child below 19 years old using the length of 19 bones of left hand applied for three classification techniques, which were Discriminant Function Analysis (DFA), Support Vector Machine (SVM) and Artificial Neural Network (ANN) multilayer perceptron. These techniques were carried out on X-ray images of the left hand taken from an Asian population data set. All the 19 bones of the left hand were measured using Free Image software, and all the techniques were performed using MATLAB. The group of age ''16-19'' years old and ''7-9'' years old were the groups that could be used for sex estimation with as their average of accuracy percentage was above 80%. ANN model was the best classification technique with the highest average of accuracy percentage in the two groups of age compared to other classification techniques. The results show that each classification technique has the best accuracy percentage on each different group of age. [ABSTRACT FROM AUTHOR]

Abstract: Mobile technology has been piloted in a range of health-related areas, allowing doctors to receive critically important patient information in an automated way. It is vital that the technology be adaptable, so that the right information is available to the right doctors. We investigate the use of smartphones and various user stereotypes functioning in a hospital environment, as these stereotypes can play an important role in designing and adapting the mobile user interface (MUI) for health care applications. This paper discusses how a user stereotype can be modeled and used for adapting MUI for health care applications in a hospital setting. An empirical study using questionnaires and interviews among 30 doctors is conducted in order to extract the characteristics of each user stereotype, in terms of age group, domain experience, and mobile technology use. The study confirms that there are three groups of doctors in hospitals: junior, intermediate, and experienced, corresponding to the hierarchical structure in place in the hospital setting. A set of context descriptor sentences is extracted from each group during the interview, in order to consider the context of use of smartphones in adapting the MUI for these applications. [Copyright &y& Elsevier]

Previous studies have demonstrated that populations differ from each other in size and proportion, and that these differences can affect metric assessment of sex. This paper establishes standards for determining sex from fragmentary and complete tibiae in the modern Croatian population. Measurements were taken on 180 tibiae (109 male and 71 female) from positively identified victims of the 1991-1995 War in Croatia. Six standard dimensions: length of the tibia (CML), maximum epiphyseal breadth of the proximal tibia (MPEB), maximum epiphyseal breadth of the distal tibia (MDEB), maximum diameter of the tibia at the nutrient foramen (MDNF), transverse diameter of the tibia at the nutrient foramen (TDNF), and circumference of the tibia at the nutrient foramen (CNF), were taken and subjected to different discriminant function analyses. The highest level of accuracy (91.1%) in the analyzed data set was achieved employing the variables: maximum epiphyseal breadth of the proximal tibia, maximum epiphyseal breadth of the distal tibia, maximum diameter of the tibia at the nutrient foramen, transverse diameter of the tibia at the nutrient foramen, and circumference of the tibia at the nutrient foramen. The second highest level of accuracy (90.6%) was achieved using a combination of only three variables: maximum epiphyseal breadth of the proximal tibia, maximum diameter of the tibia at the nutrient foramen, and circumference of the tibia at the nutrient foramen. The lowest accuracy (84.4%) was obtained when only one variable (maximum diameter of the tibia at the nutrient foramen) was employed. The results of this study show that the modern Croatian tibia is a good skeletal component for determining sex. Standardized coefficients of the discriminant functions generated in this study support the results of previous studies that found that breadth dimensions provide better separation of the sexes than length. [ABSTRACT FROM AUTHOR]

Abstract: This paper describes an experiment to examine whether a visual warning system can improve detection of moving machine hazards that could result in struck-by or pinning accidents. Thirty-six participants, twelve each in one of three age groups, participated in the study. A visual warning system capable of providing four different modes of warning was installed on a continuous mining machine that is used to mine coal. The speed of detecting various machine movements was recorded with and without the visual warning system. The average speed of detection for forward and reverse machine movements was reduced by 75% when using the flashing mode of the visual warning system. This translated to 0.485 m of machine travel for the fast speed condition of 19.8 m/min, which is significant in the context of the confined spaces of a mine. There were no statistically significant differences among age groups in the ability to detect machine movements for the visual warning modes in this study. The visual warning system shows promise as a safety intervention for reducing struck-by or pinning accidents involving continuous mining machines. The methods and results of this study could be applied to other moving machinery used in mining or other industries where moving machinery poses struck-by or pinning hazards. [Copyright &y& Elsevier]

Abstract: This paper examines the relationship between a respondent''s estimate of a traffic-related occurrence and his/her level of annoyance with it. Factors such as traffic flow, speeding, parked cars, standard of the sidewalk, and cyclists on the sidewalk are tested. The data was collected in 2008 from a questionnaire study sent to circa 1400 residents living along four arterial streets in Malmö, Sweden. The results indicate that the respondents seem to associate the estimate of occurrence with a rather corresponding or lower level of annoyance. Deviations from these main results are mainly found for the oldest (>64) age group where high estimate of occurrence is associated with low annoyance concerning some of the factors. [Copyright &y& Elsevier]

Abstract: It is a well-known fact that the length of an artery in situ and the length of an excised artery differs. Retraction of blood vessels is usually observed. This pre-tension plays crucial role in arterial biomechanics. It augments an artery wall load-bearing capacity. This paper presents the longitudinal pre-strain of the human aorta as an index of human age. The length of abdominal aortas was measured during autopsies before and after segment resection. The longitudinal pre-strain was calculated in 130 donors; 100 male and 30 female bodies. The pre-strain was defined as the ratio between in situ length and the length after the excision. The mean pre-strain was found to be 1.18±0.10 for male and 1.14±0.10 for female sample (mean±standard deviation). The age in the male group was 41.6±15.9 years; and 47.7±17.7 years in the female group. Statistical analysis revealed the correlation coefficient between age and pre-strain r =−0.821 and r =−0.839 in male and female group, respectively. The analysis also confirmed close correlation between aortic circumference and age; and between circumference and pre-strain. Linear and power law regression equations were employed and prediction intervals were computed. The power law estimates the age more accurately than linear one model. Nevertheless, especially for small values of the pre-strain (aged individuals) the linear model can be advantageous. [Copyright &y& Elsevier]

Abstract: Present translation systems play back their results with specific speed and volume regardless of the type of user. In this paper, we describe a personalized translation listening system by identifying user information. User groups are classified by age group after inputting speech. This suggested translation system gives the translated result back to the user, speaking at an emphasized speech based on the user''s age. The personalized translation listening system performs age recognition, speech recognition, language recognition, Google machine translation, and TTS web services. We showed the comparison of normal speech and emphasized speech by realizing a user-oriented translation system in a mobile device. A Mean Opinion Score was used for the experiment. Average score of the Mean Opinion Score experiment was 3.21. [Copyright &y& Elsevier]

Abstract: In this paper we investigate how schoolmates influence high school dropout intentions in Catalonia, Spain. Our analysis uses self-reported friends to identify possible peers by assuming that peer influence flows in one direction in cases where one student identifies another as a friend, but the other does not reciprocate. We first estimate the effects of education aspirations of non-reciprocating friends on students’ own education aspirations, with and without conditioning on a large set of personality and cognitive characteristics. We then investigate the extent to which the estimated effects are associated with friends’ height, weight, BMI, gender and cognitive ability. The estimated impact of non-reciprocating peers’ dropout intentions is small and generally not statistically significant: a 10 percentage point increase in the fraction of non-reciprocating peers that intend to drop out increases students’ chances of dropping out by about .2 percentage points. [Copyright &y& Elsevier]

Abstract: This paper examines the role of physical strength in the determination of the height wage premium by using the “Health 2000 in Finland” data that contain both self-reported information on the physical strenuousness of work, and information on muscle mass from medical examinations. The results suggest that there are generally no distinct differences in the height premium between four different work strain categories. We also find that muscle mass is positively associated with wages per se. The premium is both statistically and economically more significant for men than for women. In terms of occupational sorting, we observe that the shortest men do physically very demanding work and the tallest do sedentary work, even after controlling for the influences of age and education. [ABSTRACT FROM AUTHOR]

Abstract: This paper is a study of the growth status of 1406 North Korean refugee children and adolescents who were between 6 and 19.9 years of age at the time of their arrival in South Korea, during the years 1995–2007, as compared with that of their South Korean peers. Refugee children of 6.5 years of age were found to be taller and heavier than North Korean children of the same age residing in North Korea. On the other hand, all of the North Korean refugee boys and girls were shorter and weighed less than their South Korean peers. This disparity in height and weight growth status was smallest during the pre-teen years and then began to increase, peaking in the mid-teen years and decreasing in the late-teen years, with the late-teen disparity being still larger than the pre-teen one. This pattern of disparity suggests that the greatest gap observed in mid-teen years was caused by differences in growth tempos during the period of pubertal growth and that the final differences in body size between the North and South Korean adults were partly pubertal in origin. The mean height-for-age z-score (HAZ) and weight-for-age z-score (WAZ) of the North Korean refugee boys were significantly lower than those of the North Korean refugee girls, indicating that the girls’ growth status was better than that of the boys. In addition, the WAZ of the North Korean refugee children and adolescents was higher than their HAZ, indicating that their growth in height is poorer than that of weight. A regression analysis revealed that the mean HAZ of North Korean refugee children and adolescents born between 1995 and 1999, a period during which North Korea suffered a famine, was not statistically significantly lower than that of those born earlier. The time that the North Korean children and adolescents spent outside of North Korea before entering South Korea was discovered to have had a positive effect on their growth status, suggesting that they experienced some degree of catch-up growth while staying in transit countries. Among all the available socio-demographic variables, only four – sex, age at escape and measurement, time interval between escape from North Korea and arrival in South Korea, and year of escape – were found to be significant factors in their growth status. [Copyright &y& Elsevier]

Abstract: Two general trends, the tightening of time constraints and the ageing of the working population, are likely to raise sensitive problems implying adjustment of both work and workers'' characteristics. The statistical studies presented in this paper, referring to a French inter-professional survey conducted on health and work after fifty (11 213 employees), aim at verifying this assumption. The analyses presented are divided in four sub-questions: have part of employees over fifty been removed from time pressure situations? Is time pressure difficult to deal with for older workers (from their point of view)? Does intense time pressure imply increased prevalence of certain health disorders among senior employees? Does pressure increase the desire to end one''s professional life early? The results show that intense time pressure raises serious problems for most of the employees in their fifties who are exposed to them. 80% consider this constraint to be “difficult”. They systematically show more frequent rates for most types of physical or psychological health disorders. “Sheltering from the job”, which implies being shifted from work “under pressure” to a job “without pressure”, is not uncommon but only solves a minority of situations. Lastly, the option of earlier retirement is not particularly developed in age group in its fifties working “under pressure”. [Copyright &y& Elsevier]

Abstract: This paper analyses the impact of the 2003 European heatwave on excessive human mortality in Portugal, a country that presents a relatively high level of exposure to heatwave events. A total of 2399 excessive deaths are estimated in continental Portugal, which implies an increase of 58% over the expected deaths. When these values are split by gender, it is seen that women increase (79%), was considerably higher than that recorded for men (41%). The increment of mortality due to this heatwave was detected for all the 18 districts of the country, but its magnitude was significantly higher in the inner districts close to the Spanish border. When we split by gender all districts reveal significant mortality increments for women, while the impact in men''s excess deaths is not significant over 3 districts. Several temperature derived indices were used and evaluated in their capacity to explain, at the regional level, the excessive mortality (ratio between observed and expected deaths) by gender. It is shown that the best relationship is found for the total exceedance of extreme days, an index combining the length of the heatwave and its intensity. Both variables hold a linear relationship with r =0.79 for women and a poorer adjustment (r =0.50) for men. Additionally, availability of mortality data split by age also allowed obtaining detailed information on the structure of the population in risk, namely by showing that statistically significant increments are concentrated in the last three age classes (45–64, 65–74 and 75 or more). The use of air conditioning systems in some Portuguese hospitals had a major impact on the decrease (up to 40%) in excessive mortality values. A finer approach is relevant for prevention strategies, since it allows to identify better the target population of any preventive strategy regional and national authorities may be interested to implement. [Copyright &y& Elsevier]

This paper estimates the impact of demographic change on energy use and greenhouse gas emissions in Germany. Since old people display different consumption patterns than young people, an increase in the proportion of old people affects overall consumption patterns. Micro data from a household survey are used to identify age-specific consumption patterns and to project the impact of demographic change on the structure of total consumption expenditure up to the year 2030. The resulting final demand vectors are entered into an environmental input–output model, which allows the calculation of sectoral production, energy use and greenhouse gas emissions. The model results suggest that until 2030, demographic change raises the share of methane in total greenhouse gas emissions and does not contribute to reducing energy use and greenhouse gas emissions in Germany. The model is also used to explore the effects of redistributing income between age groups and a policy-induced switch from motor vehicle use to public transport. [Copyright &y& Elsevier]

The dynamics of rodent population in the area of East Urals Radioactive Trace (EURT) is one of the controversial issues, which are of key importance for the radiobiological and radioecological interpretation of the observed radiation effects. The objective of the paper is to evaluate the probability of migration in population of the herb field mouse (Sylvaemus uralensis Pall., 1811) based on 90Sr activity concentrations in the mouse bones. Radiometric data for bones of 768 mice captured at 9 sites in the EURT territory (with different environmental contamination levels) in 2001–2012 were used. The distribution of bone-seeking 90Sr in the juvenile age group of mice is used as a model of the width of radionuclide distribution in the bones of permanent inhabitants. Comparison of the model predictions and observations in different age and functional groups within the population structure allows simulating the probability of migration and evaluating the fraction of migrants. It is shown that the accumulation of 90Sr in bones correlates with soil contamination at the capture sites. Individual variability in the specific activity of 90Sr in the skeleton tends to increase with the age of animals. The rate of herb field mouse migration is estimated as 7 and 15% per year (for underyearlings and wintered individuals, respectively). The animals captured in the EURT area (all animals, including juvenile individuals) are "diluted" with animals from non-contaminated territories by 5–12%. The average half-time of substitution of the exposed population by migrants from non-contaminated territories is 8 years. Today, the fraction of descendants of the animals, that for generations have permanently inhabited the EURT territory since 1957, is negligible (on average-1.2% and not exceeding 17%). The proposed method of probabilistic analysis of 90Sr in the bones could be used to study migration activity of other species of rodents. • 90Sr activity concentration in rodent bones is an indicator of migration activity at the 90Sr contaminated territories. • Individual variability of 90Sr concentration in juvenile's bones corresponds to those of non-juvenile sedentary mice. • 90Sr concentration in bones of juvenile herb field mouse from EURT are lognormally distributed with CV = 44%. • The average half-time of substitution of the exposed population in EURT by migrants from "clean" territories is 8 years. • Fraction of descendants of the animals, who was resided generation-to-generation in EURT since the 1957, is not exceeding 17%. [ABSTRACT FROM AUTHOR]

This paper provides empirical evidence to support existing anecdotal studies regarding the mechanisms by which human communities become vulnerable to rapid changes in freshwater resources on the Seward Peninsula, Alaska. We interviewed adults, stratified by age, sex, and extended family, in Inupiat communities on the Seward Peninsula. Using categorical indices as part of a semi-structured interview we elicited a respondent''s perception of the availability and quality of freshwater resources in their community as well as their perception of change in the availability and quality of freshwater during the period of their lifetime in that community. Significant relationships were observed between age groups for the perception of change in the availability of the local water source and the perception of change in its quality—older generations perceiving more change than younger age groups. These perceptions of change were examined with respect to recent historic changes in precipitation and temperature on the Seward Peninsula. These findings suggest that individual perceptions are instrumental in determining whether or not change merits response. The findings also provide evidence that oral traditional knowledge systems have shifted from continuous to discontinuous transmission, distancing the users from traditional resources. We discuss the role of collective knowledge, through the transmission of knowledge from elders to subsequent generations, in aiding the development of a community''s ability to note and respond to changes in critical natural resources. [Copyright &y& Elsevier]

Abstract: This paper is a summary of findings of adult age-related craniofacial morphological changes. Our aims are two-fold: (1) through a review of the literature we address the factors influencing craniofacial aging, and (2) the general ways in which a head and face age in adulthood. We present findings on environmental and innate influences on face aging, facial soft tissue age changes, and bony changes in the craniofacial and dentoalveolar skeleton. We then briefly address the relevance of this information to forensic science research and applications, such as the development of computer facial age-progression and face recognition technologies, and contributions to forensic sketch artistry. [Copyright &y& Elsevier]

Hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) transforms anaerobically into N-nitroso compounds: hexahydro-1-nitroso-3,5-dinitro-1,3,5-triazine (MNX), hexahydro-1,3-dinitroso-5-nitro-1,3,5-triazine (DNX), and hexahydro-1,3,5-trinitroso-1,3,5-triazine (TNX). Exposure to these N-nitroso metabolites may occur in areas contaminated with explosives, as anaerobic degradation occurs via some bacteria and is one remediation strategy used for RDX. Few papers report acute oral toxicity and none have evaluated age dependent toxicity of RDX or its N-nitroso metabolites. Median lethal dose (LD50) was determined in deer mice (Peromyscus maniculatus) of three age classifications 21d, 50d, and 200d for RDX, MNX, and TNX using the US EPA up-and-down procedure (UDP). Hexahydro-1,3,5-trinitro-1,3,5-triazine and N-nitroso metabolites caused similar overt signs of toxicity. Median lethal dose for 21d deer mice were 136, 181, and 338mg/kg for RDX, MNX, and TNX, respectively. Median lethal dose for 50d deer mice were 319, 575, and 338mg/kg for RDX, MNX, and TNX, respectively. Median lethal dose for 200d deer mice were 158, 542, and 999mg/kg for RDX, MNX, and TNX, respectively. These data suggest that RDX is the most potent compound tested, and age dependent toxicity may exist for all compounds and could play a role in RDX and RDX N-nitroso metabolite ecological risk evaluation of terrestrial wildlife at RDX contaminated sites. [Copyright &y& Elsevier]