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Summary: Key predictors of three trajectory group membership of potentially preventable hospitalisations were age, the number of comorbidities, the presence of chronic obstructive pulmonary disease and congestive heart failure, and frailty risk at the occurrence of hip fracture. These predictors of their trajectory group could be used in targeting prevention strategies. Purpose: Although older adults with hip fracture have a higher risk of multiple readmissions after index hospitalisation, little is known about potentially preventable hospitalisations (PPH) after discharge. This study examined group-based trajectories of PPH during a five-year period after a hip fracture among older adults and identified factors predictive of their trajectory group membership. Methods: This retrospective cohort study was conducted using linked hospitalisation and mortality data in New South Wales, Australia, between 2013 and 2021. Patients aged ≥ 65 years who were admitted after a hip fracture and discharged between 2014 and 2016 were identified. Group-based trajectory models were derived based on the number of subsequent PPH following the index hospitalisation. Multinominal logistic regression examined factors predictive of trajectory group membership. Results: Three PPH trajectory groups were revealed among 17,591 patients: no PPH (89.5%), low PPH (10.0%), and high PPH (0.4%). Key predictors of PPH trajectory group membership were age, number of comorbidities, dementia, chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), frailty risk, place of incident, surgery, rehabilitation, and length of hospital stay. The high PPH had a higher proportion of patients with ≥ 2 comorbidities (OR: 1.86, 95% confidence interval (CI): 1.04–3.32) and COPD (OR: 2.97, 95%CIs: 1.76–5.04) than the low PPH, and the low and high PPHs were more likely to have CHF and high frailty risk as well as ≥ 2 comorbidities and COPD than the no PPH. Conclusions: Identifying trajectories of PPH after a hip fracture and factors predictive of trajectory group membership could be used to target strategies to reduce multiple readmissions. [ABSTRACT FROM AUTHOR]

Emotional support from family members may have an important effect on adolescent health outcomes, and has been identified as a target for policy to protect against the impacts of poverty and other early life adversities. However, few studies have assessed the extent to which poverty and adversity themselves influence the nature of emotional support that parents can provide to adolescents. We, therefore, aimed to investigate the impact of trajectories of income poverty and family adversities, including parental mental ill health, alcohol misuse and domestic violence across childhood developmental stages on young people's relationships with their families and perceived emotional support received. We analysed longitudinal data on 10,976 children from the nationally representative UK Millennium Cohort study. Exposure trajectories of poverty and family adversities were characterised using group-based multi-trajectory models (age 9 months–14 years). The outcomes were perceived emotional support and quality of family relationships, measured by the three-item Short Social Provisions Scale (SPS-3) and levels of parent–adolescent closeness and conflict, measured at age 14. ORs and 95% CIs were estimated using multivariable logistic regression models, adjusting for potential confounding factors. At age 14, the overall prevalence of low perceived emotional support was 13% (95% CI: 12, 14). Children of mothers with lower socioeconomic status (SES) were more likely to report low emotional support, with a clear social gradient (education—degree plus: 10.3% vs. no qualifications: 15.4%). Compared with children exposed to low levels of poverty and adversity, children in the persistent adversity trajectory groups experienced higher odds of low emotional support and low-quality parent–adolescent relationship; those exposed to both persistent poverty and poor parental mental health were particularly at increased risk of experiencing poor family relationships and low perceived emotional support (adjusted odds ratio 2·2; 95% CI 1·7–2·9). Low perceived emotional support and poor family relationships in adolescence are more prevalent among socially disadvantaged children and adolescents and those experiencing social adversity. Policies to improve levels of family support for UK adolescents should focus on improving modifiable determinants such as child poverty and family mental health. [ABSTRACT FROM AUTHOR]

Objective: White blood cells (WBC) play an important role in the inflammatory response of the body. Elevated WBC counts on admission in patients with subarachnoid hemorrhage (SAH) correlate with a poor prognosis. However, the role of longitudinal WBC trajectories based on repeated WBC measurements during hospitalization remains unclear. We explored the association between different WBC trajectory patterns and in-hospital mortality. Methods: We analyzed a cohort of consecutive patients with SAH between 2012 and 2020. Group-based trajectory modeling (GBTM) was used to group the patients according to their white blood cell patterns over the first 4 days. Stabilized inverse probability treatment weighting (sIPTW) was used to balance baseline demographic and clinical characteristics. We analyzed the association between the WBC trajectory groups and in-hospital mortality using a Cox proportional hazards model. Results: In total, 506 patients with SAH were included in this retrospective cohort. The final model identified two distinct longitudinal WBC trajectories. After adjusting for confounding factors, multivariate regression analysis suggested that an elevated longitudinal WBC trajectory increased the risk of in-hospital mortality (hazard ratio [HR], 2.476; 95% confidence interval [CI] 1.081–5.227; P = 0.024) before sIPTW, and (HR, 2.472; 95%CI 1.489–4.977; P = 0.018) after sIPTW. Conclusion: In patients with SAH, different clinically relevant groups could be identified using WBC trajectory analysis. The WBC count trajectory—initially elevated and then decreased— may lead to an increased risk of in-hospital mortality following SAH. [ABSTRACT FROM AUTHOR]

Objectives: Heart rate variability (HRV) is becoming more prevalent as a measurable parameter in wearable sleep-monitoring devices, which are simple and effective instruments for illness evaluation. Currently, most studies on investigating OSA severity and HRV have measured heart rates during wakefulness or sleep. Therefore, the objective of this study was to investigate the circadian rhythm of HRV in male patients with OSA and its value for the estimation of OSA severity using group-based trajectory modeling. Methods: Patients with complaints of snoring were enrolled from the Sleep Center of Shandong Qianfoshan Hospital. Patients were divided into 3 groups according to apnea hypopnea index (AHI in events/h), as follows: (<15, 15≤AHI<30, and ≥30). HRV parameters were calculated using 24 h Holter monitoring, which included time-domain and frequency-domain indices. Circadian differences in the standard deviation of normal to normal (SDNN) were evaluated for OSA severity using analysis of variance, trajectory analysis, and multinomial logistic regression. Results: A total of 228 patients were enrolled, 47 with mild OSA, 48 moderate, and 133 severe. Patients with severe OSA exhibited reduced triangular index and higher very low frequency than those in the other groups. Circadian HRV showed that nocturnal SDNN was considerably higher than daytime SDNN in patients with severe OSA. The difference among the OSA groups was significant at 23, 24, 2, and 3 o'clock sharp between the severe and moderate OSA groups (all P<0.05). The heterogeneity of circadian HRV trajectories in OSA was strongly associated with OSA severity, including sleep structure and hypoxia-related parameters. Among the low-to-low, low-to-high, high-to-low, and high-to-high groups, OSA severity in the low-to-high group was the most severe, especially compared with the low-to-low and high-to-low SDNN groups, respectively. Conclusions: Circadian HRV in patients with OSA emerged as low daytime and high nocturnal in SDNN, particularly in men with severe OSA. The heterogeneity of circadian HRV revealed that trajectories with low daytime and significantly high nighttime were more strongly associated with severe OSA. Thus, circadian HRV trajectories may be useful to identify the severity of OSA. [ABSTRACT FROM AUTHOR]

This paper presents the results of a study of ground-level ozone concentration variability in Crimea at the background environmental monitoring station (BEMS) of the Karadag State Nature Reserve for 2012–2021 with a more detailed analysis of the last 6 years from 2016 to 2021. A significantly high level of air pollution by ground-level ozone in the observation area was revealed, despite the absence of significant sources of anthropogenic pollution in the vicinity of the station. The relationship between the ground-level ozone concentration and meteorological parameters has been studied, and characteristic wind directions leading to increased levels of ground-level ozone pollution have been established. Intra-annual variations are analyzed, and factors causing a local summer minimum of ground-level ozone concentration in individual years are identified. Using the NOAA HYSPLIT model and ERA5 reanalysis meteorological fields, a spatial analysis of the atmospheric circulation pattern in the region has been carried out. The recurrence of episodes in which the permissible 8-h average ozone concentration level of 100 μg/m3, as recommended by World Health Organization (WHO), was exceeded has been assessed, and the possible causes of these episodes are identified. Mechanisms of long-range transport and their contribution to the ozone regime in the station area have been established. Annual trends in ground-level ozone concentration between 2012 and 2021 are assessed as statistically insignificant. [ABSTRACT FROM AUTHOR]

Human movement trajectories can reveal useful insights regarding the underlying mechanisms of human behaviors. Extracting information from movement trajectories, however, can be challenging because of their complex and dynamic nature. The current paper presents a Python toolkit developed to help users analyze and extract meaningful information from the trajectories of discrete rapid aiming movements executed by humans. This toolkit uses various open-source Python libraries, such as NumPy and SciPy, and offers a collection of common functionalities to analyze movement trajectory data. To ensure flexibility and ease of use, the toolkit offers two approaches: an automated approach that processes raw data and generates relevant measures automatically, and a manual approach that allows users to selectively use different functions based on their specific needs. A behavioral experiment based on the spatial cueing paradigm was conducted to illustrate how one can use this toolkit in practice. Readers are encouraged to access the publicly available data and relevant analysis scripts as an opportunity to learn about kinematic analysis for human movements. [ABSTRACT FROM AUTHOR]

Worldwide, women are over-represented in precarious and insecure employment arrangements. Importantly, the high unpaid labour demands women experience over the life course compromise paid labour force participation for women. This study explores the way different trajectories of time spent in unpaid labour throughout women's prime working and child-rearing years (from baseline age of 25–35 yrs to 42–52 yrs) are associated with indicators of precarious employment and labour force detachment later in life. We applied group-based trajectory modelling to 17 waves (2002–2018) of data from the Household Income and Labour Dynamics in Australia survey to identify trajectories in unpaid labour. We then examined associations between these estimated trajectories and employment outcomes in wave 19 (2019). Our study shows that chronic exposure to high amounts of unpaid labour over prime working-age years (compared to lower exposure levels) increases women's probability of precarious employment and labour force detachment later in prime working life. This provides evidence that ongoing inequity in the division of unpaid labour has considerable long-term implications for gender inequality in the paid labour force, and underscores the importance of urgently addressing how men and women share and prioritise time across both paid and unpaid labour domains. [ABSTRACT FROM AUTHOR]

In this study, the characteristics of azimuthally asymmetric equivalent potential temperature (θe) distributions in the outer core of tropical cyclones (TCs) encountering weak and strong vertical wind shear are examined using a Lagrangian trajectory method. Evaporatively forced downdrafts in the outer rainbands can transport low-entropy air downward, resulting in the lowest θe in the downshear-left boundary layer. Quantitative estimations of θe recovery indicate that air parcels, especially those originating from the downshear-left outer core, can gradually revive from a low entropy state through surface enthalpy fluxes as the parcels move cyclonically. As a result, the maximum θe is observed in the downshear-right quadrant of a highly sheared TC. The trajectory analyses also indicate that parcels that move upward in the outer rainbands and those that travel through the inner core due to shear make a dominant contribution to the midlevel enhancement of θe in the downshear-left outer core. In particular, the former plays a leading role in such θe enhancements, while the latter plays a secondary role. As a result, moist potential stability occurs in the middle-to-lower troposphere in the downshear-left outer core. [ABSTRACT FROM AUTHOR]

A comparative study of the sizes and spatial structure of single dielectric colloidal nanoparticles of lanthanum fluoride, doped with rare-earth neodymium ions (Nd3+:LaF3), and their conglomerates in an aqueous solution has been performed. Nanoparticles were synthesized by aqueous co-precipitation method with subsequent hydrothermal microwave (HTMW) treatment. Experiments were performed using three methods: transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA), and dynamic light scattering (DLS). An analysis of the results has shown that a stable colloidal solution of nanoparticles is formed during synthesis. The solution consists of single lanthanum fluoride nanoparticles, having a narrow (10–30 nm) size distribution, and nanoclusters formed on their basis. It is also shown that the spatial structure of nanoclusters cannot be described in terms of the fractal model, which is widely used to describe clusters formed in colloidal solutions of nanoparticles of various nature. [ABSTRACT FROM AUTHOR]

The complex interaction between emissions, meteorology, and atmospheric chemistry makes accurate predictions of particulate pollution difficult. Advanced data mining techniques can reveal potential laws, providing new possibilities for understanding the evolution and causes of air pollution. Based on the Granger method and block modeling analysis, this paper explored the intercity spillover effects of hourly PM2.5 in Hubei Province, China, to determine the specific role (i.e., overflow, limited overflow, bilateral, inflow, and limited inflow) of each city on regional pollution formation. Furthermore, a dynamic Apriori algorithm considering time-lag effects was used to mine the spatio-temporal associations of extreme PM2.5 pollution events among different cities. Results suggest that the northern and central cities with high-level PM2.5 concentration in Hubei have a significant spillover effect, whereas the eastern and southern cities generally play a role as the sink of pollutants. Based on the association rules of extreme PM2.5 pollution, four main pollutant transport channels were excavated and well matched with the trajectories extracted by the atmospheric model. This paper provides new insights for exploring the interaction of intercity particulate pollution, which is a supplement and cross-validation of the model results. [ABSTRACT FROM AUTHOR]

The paper presents data acquired by a comparative study of the vertical variability in the chemical composition and ratios of aerosol subdisperse fractions in snow layers chronologically correlated with the stratigraphically significant snowfall periods. These data highlight features of the concentrating of trace elements at reactive (geochemical) barriers in the snow profile. The ratio of three geochemically close groups of elements, such as siderophile, sulfophile, and lithophile elements, were found out to vary relatively little from one snow layer to another in the growing snow cover. Trajectory analysis of the transfer of air masses to which stratigraphically significant snowfalls were related to the observation site provides no evidence that the identified geochemical phenomenon can be explained by that the winter aerosol field that was formed above an urban area with different trajectories of air masses can be somehow inherited in the snow layers of the growing snow cover and thus affect the vertical distributions of trace elements. Evidence indicates that that the ratios of assemblages of trace elements in the discrete snow layers, which remain stable with the growth of the snow mass, can be employed as geochemical markers of stagnant zones in an urban heat island, and the method of geochemical sampling of a snow cover in its discrete layers at a rare network of urban meteorological observation sites is an efficient additional tool for studying microscale atmospheric processes and recovering information on characteristics of the transfer of pollutants in a spatially limited urban area. [ABSTRACT FROM AUTHOR]

We have studied the assessment of methane content in the near atmospheric layer of the Arctic seas and the sources of its emissions. Continuous atmospheric measurements of methane concentration and δ13C isotope signature in methane were carried out during two expeditions aboard the R/V Akademik Mstislav Keldysh in the summer and autumn of 2020. The minimum CH4 concentration (mean 1.937 ± 0.010 ppm) were obtained over the North and Norwegian Seas. The maximum CH4 concentration took place above the Kara (1.998 ± 0.030 ppm on average, maximum values are up to 2.000–2.040 ppm) and White (2.006 ± 0.030 ppm on average) seas. The average values of δ13C in the studied region were close to that typical for the Northern Hemisphere: –47.5‰. Regional changes in δ13C allowed CH4 sources to be identified and showed that the methane concentration in the surface atmospheric level is mainly affected by the direction of air-mass advection. [ABSTRACT FROM AUTHOR]

Objectives: In March 2020, the COVID-19 pandemic necessitated a rapid public health response which included mandatory working from home (WFH) for many employees. This study aimed to identify different trajectories of multisite musculoskeletal pain (MSP) amongst employees WFH during the COVID-19 pandemic and examined the influence of work and non-work factors. Methods: Data from 488 participants (113 males, 372 females and 3 other) involved in the Employees Working from Home (EWFH) study, collected in October 2020, April and November 2021 were analysed. Age was categorised as 18–35 years (n = 121), 36–55 years (n = 289) and 56 years and over (n = 78). Growth Mixture Modelling (GMM) was used to identify latent classes with different growth trajectories of MSP. Age, gender, working hours, domestic living arrangements, workstation comfort and location, and psychosocial working conditions were considered predictors of MSP. Multivariate multinomial logistic regression was used to identify work and non-work variables associated with group membership. Results: Four trajectories of MSP emerged: high stable (36.5%), mid-decrease (29.7%), low stable (22.3%) and rapid increase (11.5%). Decreased workstation comfort (OR 1.98, CI 1.02, 3.85), quantitative demands (OR 1.68, CI 1.09, 2.58), and influence over work (OR 0.78, CI 0.54, 0.98) was associated with being in the high stable trajectory group compared to low stable. Workstation location (OR 3.86, CI 1.19, 12.52) and quantitative work demands (OR 1.44, CI 1.01, 2.47) was associated with the rapid increase group. Conclusions: Findings from this study offer insights into considerations for reducing MSP in employees WFH. Key considerations include the need for a dedicated workstation, attention to workstation comfort, quantitative work demands, and ensuring employees have influence over their work. [ABSTRACT FROM AUTHOR]

Due to society aging, age-related issues such as mild cognitive impairments (MCI) and dementia are attracting the attention of health professionals, scientists and governments. Seniors suffering from such impairments notice a slight deterioration in their cognitive abilities, which may lead to memory loss and behavioural disorders. In consequence, such seniors refrain from doing their everyday outdoor activities. Technology, e.g. smartphones, wearables and artificial intelligence, can provide seniors and their relatives with a variety of monitoring tools. In a nutshell, locations are analysed and, under specific situations, alarms are raised so that caregivers urgently informed. In this context, the discovery and prediction of trajectories and behaviours play a key role in deploying effective monitoring solutions. In this paper, we present a real-time smartphone-based monitoring system, called SafeMove, to discover and predict elderly people behaviours by analyzing outdoor trajectories. This is achieved by firstly analysing the elder's mobility data previously collected using the proposed model called SpaceTime-Convolutional Neural Network (ST-CNN) in order to predict the most popular locations he/she might visit in the next time. Based on the predicted locations, the elder can be monitored in bounded region. Time and space-related variables, such as the distance traversed, the direction of the movements and the time spent, are analyzed in our abnormal behaviour detection (ABD) model that takes advantage of recurrent neural networks (RNNs). The effectiveness and the efficiency of our system for predicting the next location and detection the abnormal behaviors are evaluated using different datasets comprising real-world GPS trajectories. [ABSTRACT FROM AUTHOR]

Geospatial analytics increasingly rely on data fusion methods to extract patterns from data; however robust results are difficult to achieve because of the need for spatial and temporal regularization and latent structures within data. Tensor decomposition is a promising approach because it can accommodate multidimensional structure of data (e.g., trajectory information about users, locations, and time periods). To address these challenges, we introduce Multi-Type Clustering using Regularized tensor Decomposition (MCRD), an innovative method for data analysis that provides insight not just about groupings within data types (e.g., clusters of users), but also about the interactions between data types (e.g., clusters of users and locations) in the latent features of complex multi-type datasets. This is done by combining two innovations. First, a tensor representing spatiotemporal data is decomposed using a novel regularization method to account for structure within the data. Next, within- and cross-type groups are found through the application of novel hypergraph community detection methods to the decomposed results. Experimentation on both synthetic and real trajectory data demonstrates MCRD's capacity to reveal the within- and cross-type grouping in data, and MCRD outperforms related methods including tensor decomposition without regularization, unfolding of tensors, Laplacian regularization, and tensor block models. The robust and versatile analysis provided by combining new regularization and clustering techniques outlined in this paper likely have utility in geospatial analytics beyond the movement applications explicitly studied. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Anaesthesia / Journal Canadien d'Anesthésie is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of AIDS & Behavior is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

HIV care engagement is a dynamic process. We employed group-based trajectory modeling to examine longitudinal patterns in care engagement among people who were newly diagnosed with HIV and enrolled in the Ryan White program in Florida (n = 9,755) between 2010 and 2015. Five trajectories were identified (47.9% "in care" with 1–2 care visit(s) per 6 months, 18.0% "frequent care" with 3 or more care visits per 6 months, 11.0% "re-engage", 11.0% "gradual drop out", 12.6% "early dropout") based on the number of care attendances (including outpatient/case management visits, viral load or CD4 test) for each six-month during the first five years since diagnosis. Relative to "in care", people in the "frequent care" trajectory were more likely to be Hispanic/Latino and older at HIV diagnosis, whereas people in the three suboptimal care retention trajectories were more likely to be younger. Area deprivation index, rurality, and county health rankings were also strongly associated with care trajectories. Individual- and community-level factors associated to the three suboptimal care retention trajectories, if confirmed to be causative and actionable, could be prioritized to improve HIV care engagement. [ABSTRACT FROM AUTHOR]

Background: Life-threatening, space-occupying mass effect due to cerebral edema and/or hemorrhagic transformation is an early complication of patients with middle cerebral artery stroke. Little is known about longitudinal trajectories of laboratory and vital signs leading up to radiographic and clinical deterioration related to this mass effect.We curated a retrospective data set of 635 patients with large middle cerebral artery stroke totaling 95,463 data points for 10 longitudinal covariates and 40 time-independent covariates. We assessed trajectories of the 10 longitudinal variables during the 72 h preceding three outcomes representative of life-threatening mass effect: midline shift ≥ 5 mm, pineal gland shift (PGS) > 4 mm, and decompressive hemicraniectomy (DHC). We used a “backward-looking” trajectory approach. Patients were aligned based on outcome occurrence time and the trajectory of each variable was assessed before that outcome by accounting for cases and noncases, adjusting for confounders. We evaluated longitudinal trajectories with Cox proportional time-dependent regression.Of 635 patients, 49.0% were female, and the mean age was 69 years. Thirty five percent of patients had midline shift ≥ 5 mm, 24.3% of patients had PGS > 4 mm, and 10.7% of patients underwent DHC. Backward-looking trajectories showed mild increases in white blood cell count (10–11 K/UL within 72 h), temperature (up to half a degree within 24 h), and sodium levels (1–3 mEq/L within 24 h) before the three outcomes of interest. We also observed a decrease in heart rate (75–65 beats per minute) 24 h before DHC. We found a significant association between increased white blood cell count with PGS > 4 mm (hazard ratio 1.05, p value 0.007).Longitudinal profiling adjusted for confounders demonstrated that white blood cell count, temperature, and sodium levels appear to increase before radiographic and clinical indicators of space-occupying mass effect. These findings will inform the development of multivariable dynamic risk models to aid prediction of life-threatening, space-occupying mass effect.Methods: Life-threatening, space-occupying mass effect due to cerebral edema and/or hemorrhagic transformation is an early complication of patients with middle cerebral artery stroke. Little is known about longitudinal trajectories of laboratory and vital signs leading up to radiographic and clinical deterioration related to this mass effect.We curated a retrospective data set of 635 patients with large middle cerebral artery stroke totaling 95,463 data points for 10 longitudinal covariates and 40 time-independent covariates. We assessed trajectories of the 10 longitudinal variables during the 72 h preceding three outcomes representative of life-threatening mass effect: midline shift ≥ 5 mm, pineal gland shift (PGS) > 4 mm, and decompressive hemicraniectomy (DHC). We used a “backward-looking” trajectory approach. Patients were aligned based on outcome occurrence time and the trajectory of each variable was assessed before that outcome by accounting for cases and noncases, adjusting for confounders. We evaluated longitudinal trajectories with Cox proportional time-dependent regression.Of 635 patients, 49.0% were female, and the mean age was 69 years. Thirty five percent of patients had midline shift ≥ 5 mm, 24.3% of patients had PGS > 4 mm, and 10.7% of patients underwent DHC. Backward-looking trajectories showed mild increases in white blood cell count (10–11 K/UL within 72 h), temperature (up to half a degree within 24 h), and sodium levels (1–3 mEq/L within 24 h) before the three outcomes of interest. We also observed a decrease in heart rate (75–65 beats per minute) 24 h before DHC. We found a significant association between increased white blood cell count with PGS > 4 mm (hazard ratio 1.05, p value 0.007).Longitudinal profiling adjusted for confounders demonstrated that white blood cell count, temperature, and sodium levels appear to increase before radiographic and clinical indicators of space-occupying mass effect. These findings will inform the development of multivariable dynamic risk models to aid prediction of life-threatening, space-occupying mass effect.Results: Life-threatening, space-occupying mass effect due to cerebral edema and/or hemorrhagic transformation is an early complication of patients with middle cerebral artery stroke. Little is known about longitudinal trajectories of laboratory and vital signs leading up to radiographic and clinical deterioration related to this mass effect.We curated a retrospective data set of 635 patients with large middle cerebral artery stroke totaling 95,463 data points for 10 longitudinal covariates and 40 time-independent covariates. We assessed trajectories of the 10 longitudinal variables during the 72 h preceding three outcomes representative of life-threatening mass effect: midline shift ≥ 5 mm, pineal gland shift (PGS) > 4 mm, and decompressive hemicraniectomy (DHC). We used a “backward-looking” trajectory approach. Patients were aligned based on outcome occurrence time and the trajectory of each variable was assessed before that outcome by accounting for cases and noncases, adjusting for confounders. We evaluated longitudinal trajectories with Cox proportional time-dependent regression.Of 635 patients, 49.0% were female, and the mean age was 69 years. Thirty five percent of patients had midline shift ≥ 5 mm, 24.3% of patients had PGS > 4 mm, and 10.7% of patients underwent DHC. Backward-looking trajectories showed mild increases in white blood cell count (10–11 K/UL within 72 h), temperature (up to half a degree within 24 h), and sodium levels (1–3 mEq/L within 24 h) before the three outcomes of interest. We also observed a decrease in heart rate (75–65 beats per minute) 24 h before DHC. We found a significant association between increased white blood cell count with PGS > 4 mm (hazard ratio 1.05, p value 0.007).Longitudinal profiling adjusted for confounders demonstrated that white blood cell count, temperature, and sodium levels appear to increase before radiographic and clinical indicators of space-occupying mass effect. These findings will inform the development of multivariable dynamic risk models to aid prediction of life-threatening, space-occupying mass effect.Conclusions: Life-threatening, space-occupying mass effect due to cerebral edema and/or hemorrhagic transformation is an early complication of patients with middle cerebral artery stroke. Little is known about longitudinal trajectories of laboratory and vital signs leading up to radiographic and clinical deterioration related to this mass effect.We curated a retrospective data set of 635 patients with large middle cerebral artery stroke totaling 95,463 data points for 10 longitudinal covariates and 40 time-independent covariates. We assessed trajectories of the 10 longitudinal variables during the 72 h preceding three outcomes representative of life-threatening mass effect: midline shift ≥ 5 mm, pineal gland shift (PGS) > 4 mm, and decompressive hemicraniectomy (DHC). We used a “backward-looking” trajectory approach. Patients were aligned based on outcome occurrence time and the trajectory of each variable was assessed before that outcome by accounting for cases and noncases, adjusting for confounders. We evaluated longitudinal trajectories with Cox proportional time-dependent regression.Of 635 patients, 49.0% were female, and the mean age was 69 years. Thirty five percent of patients had midline shift ≥ 5 mm, 24.3% of patients had PGS > 4 mm, and 10.7% of patients underwent DHC. Backward-looking trajectories showed mild increases in white blood cell count (10–11 K/UL within 72 h), temperature (up to half a degree within 24 h), and sodium levels (1–3 mEq/L within 24 h) before the three outcomes of interest. We also observed a decrease in heart rate (75–65 beats per minute) 24 h before DHC. We found a significant association between increased white blood cell count with PGS > 4 mm (hazard ratio 1.05, p value 0.007).Longitudinal profiling adjusted for confounders demonstrated that white blood cell count, temperature, and sodium levels appear to increase before radiographic and clinical indicators of space-occupying mass effect. These findings will inform the development of multivariable dynamic risk models to aid prediction of life-threatening, space-occupying mass effect. [ABSTRACT FROM AUTHOR]

Objective: Breast cancer survivors (BCS) may experience problems to adjust to their situation after cancer treatment completion. In case of severe distress, an adjustment disorder (AD) might develop. This study investigates the course of AD symptoms during 1 year and its predictors in BCS up to 5 years post-treatment.Methods: BCS completed the Hospital Anxiety and Depression Scale (HADS) at baseline, 3, 6, and 12 months. HADS total scores were defined as no mental disorder (MD) symptoms (≤ 10), AD symptoms (11-14), and any other MD symptoms (≥ 15). Over the course of four assessments, symptom trajectories were a priori defined as no MD symptoms, AD symptoms, fluctuating AD symptoms below and above cut-offs, or any other MD symptoms. Complementary, latent class growth analysis (LCGA) was used to identify data-driven trajectories.Results: Among 293 BCS with complete data, the majority was classified as no MD symptoms (54.4%), followed by 37.5% in the fluctuating AD symptoms trajectory. Only 1.4% had AD symptoms, and 6.8% had any other MD symptoms. With LCGA (N = 459), three trajectories were found: stable no MD symptoms (58.6%), stable AD symptoms (32.9%), and high increasing any other MD symptoms (8.5%). Compared to BCS with no MD symptoms, BCS with fluctuating AD symptoms or any other MD symptoms were younger, less able to handle daily activities, and showed more social support discrepancy, neuroticism, and less optimism.Conclusions: Results of our study showed that AD symptoms in BCS up to 5 years post-treatment fluctuate over 1 year. It is thus important to appropriately assess AD over the course of 5 years post-treatment as AD symptoms can fluctuate. [ABSTRACT FROM AUTHOR]

The construction professionals attempt to enhance construction site visualization and modeling using unmanned aerial vehicle (UAV) technology. However, there is no research covering best flying and environmental variables for this purpose. This research aimed to determine the optimized flying and environmental variables for 2D dronography and 3D modeling for the construction progress monitoring. The research focused on building façade facing east and conducted an experimental study in the Eco-Home building at the University of Technology Malaysia. For 2D visualization, 900 photos were captured based on the three setpoints (20 m, 30 m, and 40 m) perpendicular to the building façade. Flying operation features of the employed drone (i.e., DJI Phantom4) enforced to set the first setpoint at 20 m perpendicular to the façade to get the whole façade in the required 80% of the photos. The 30 m and 40 m setpoints were defined based on the horizontal circles making the angle of 12° from the drone's z-ax to x-ax perpendicular to the façade. The images were analyzed using image color summarizer (ICS) software. The research found that the best distance is 30 m, and noontime is the best time for dronography. The proper temperature, humidity, lux, and wind speed to quality 2D image are; 38.1°, 55.5% Rh, 38,107 lx, and 0.1 m/s. The ICS software results were validated by applying the Image Processing Toolbox of MATLAB, particularly the thresholding-based image RGB pixel analyzing technique. The regression analysis showed 93% accuracy and completeness of the results. A trajectory optimization study has also been conducted, which determined that the drone could considerably control trajectories at the target positions and referenced velocity. The findings can significantly help the construction professionals to calibrate their drone's flying variables for quality 3D modeling the construction progress monitoring. [ABSTRACT FROM AUTHOR]

Purpose: Little research has investigated the correlation of changes in long-term apolipoprotein B/apolipoprotein A-I (ApoB/ApoA-I) ratio with risk of new-onset type 2 diabetes (T2D) among ordinary people. Therefore, the research took long-term ApoB/ApoA-I ratio trajectories as independent variables for exploring their association with the risk of newly diagnosed T2D. Methods: Altogether 5362 non-diabetic participants with a median age of 49 were enrolled in the cohort study. Their ApoB/ApoA-I ratio trajectories from 2016 to 2019 were analyzed and grouped using group-based trajectory modeling. The Kaplan–Meier approach was employed for calculating the newly diagnosed T2D-related incidence with different ApoB/ApoA-I ratio trajectories. A log-rank test was conducted for testing the presence of statistical difference in new-onset T2D incidence among the different ApoB/ApoA-I ratio trajectory groups. A multivariate Cox proportional hazards regression model was adopted for analyzing how ApoB/ApoA-I ratio trajectory changes affected new-onset T2D. Results: From 2016 to 2019, 199 patients developed T2D (3% in 3 years). The incidence of T2D was 2.0%, 3.28%, 5.86%, and 6.92% for low, middle, upper, and high ApoB/ApoA-I ratio trajectories, respectively. Following adjustment of underlying confounding factors, in contrast to low ApoB/ApoA-I ratio trajectory, new-onset T2D risk ratios and hazard ratio (HR) (95% confidence intervals [CI]) for the middle lower ApoB/ApoA-I ratio trajectory, and upper middle and high ApoB/ApoA-I ratio trajectories were [HR (95% CI)] 1.35(0.88–2.08), 1.98(1.27–3.09) and 2.42(1.35–4.34), respectively, indicating high and statistically significant risks of T2D. Conclusion: Variations of the ApoB/ApoA-I ratio trajectory exerted independent effects on the 3-year incidence of T2D. Long-term monitoring on the ApoB/ApoA-I ratio locus may help improve the identification on patients with T2D. [ABSTRACT FROM AUTHOR]

The frequency of forest fires has recently increased. Combustion aerosol can enter the stratosphere, which can have noticeable consequences for the climate. In this work, we examine the transport of combustion aerosol into the stratosphere in summer 2019, when numerous wildfires occurred in Siberia, Canada, and Alaska. According to lidar observations at the stratospheric lidar station of the V.E. Zuev Institute of Atmospheric Optics, Siberian Branch, Russian Academy of Sciences, in Tomsk in August 2019, layers of aerosol scattering were pronounced in the lower stratosphere. The analysis of back air mass trajectories calculated on the basis of satellite radiometric information about fires in the Northern Hemisphere and CALIPSO lidar data allows a conclusion that the aerosol layers observed result from transfer of the combustion products of Siberian wildfires into the stratosphere. [ABSTRACT FROM AUTHOR]

The discrete Fréchet distance (DFD) captures perceptual and geographical similarity between two trajectories. It has been successfully adopted in a multitude of applications, such as signature and handwriting recognition, computer graphics, as well as geographic applications. Spatial applications, e.g., sports analysis, traffic analysis, etc. require discovering similar subtrajectories within a single trajectory or across multiple trajectories. In this paper, we adopt DFD as the similarity measure, and study two representative trajectory analysis problems, namely, motif discovery and frequent pattern discovery. Due to the time complexity of DFD, these tasks are computationally challenging. We address that challenge with a suite of novel lower bound functions and a grouping-based solution. Our techniques apply directly when the analysis tasks are defined within the same or across multiple trajectories. An extensive empirical study on real trajectory datasets reveals that our approaches are 3 orders of magnitude faster than baseline solutions. [ABSTRACT FROM AUTHOR]

We present a comparative study of the ratio of aerosol fractions in the surface air and snow layers chronologically referenced to stratigraphically significant snowfalls. Trajectories of winter air masses were calculated using the NOAA HYSPLIT_4 model and NCEP/NCAR Reanalysis meteorological fields. The features of the formation of the winter aerosol field within the Ob–Tom interfluve are shown to be associated predominantly with winds with a southerly component. [ABSTRACT FROM AUTHOR]

Purpose: Maintaining or improving quality of life (QoL) in later life has become a major policy objective. Yet we currently know little about how QoL develops at older ages. The few studies that have modelled QoL change across time for older adults have used 'averaged' trajectories. However, this ignores the variations in the way QoL develops between groups of older adults. Methods: We took a theoretically informed 'capabilities approach' to measuring QoL. We used four waves of data, covering 6 years, from the New Zealand Health, Work and Retirement Study (NZHWR) (N = 3223) to explore whether distinct QoL trajectories existed. NZHWR is a nationally representative longitudinal study of community-dwelling adults aged 50 + in New Zealand. Growth mixture modelling was applied to identify trajectories over time and multinomial regressions were calculated to test baseline differences in demographic variables (including age, gender, ethnicity, education and economic living standards). Results: We found five QoL trajectories: (1) high and stable (51.94%); (2) average and declining (22.74%); (3) low and increasing (9.62%); (4) low and declining (10.61%); (5) low and stable (5.09%). Several differences across profiles in baseline demographic factors were identified, with economic living standards differentiating between all profiles. Conclusions: The trajectory profiles demonstrate that both maintaining and even improving QoL in later life is possible. This has implications for our capacity to develop nuanced policies for diverse groups of older adults. [ABSTRACT FROM AUTHOR]

Autonomous vehicles require high-level semantic maps, which contain the activities of pedestrians and cars, to ensure safe navigation. High-level semantics can be obtained from mobile probe sensor data. Analyzing pedestrian trajectories obtained from mobile probe data is an effective approach to avoid collisions between autonomous vehicles and pedestrians. Such analyses of pedestrian trajectories can generate new information such as pedestrian behaviors in violation of traffic regulations. However, pedestrian trajectories obtained from mobile probe data significantly sparse and noisy, making it challenging to analyze pedestrian activity. To address this issue, we propose multiple daily data and graph-based approaches to treat sparse and noisy data for estimating the flow of pedestrians based on mobile probe data. To improve the sparseness of the data, multiple daily data are fused. After that, a pedestrian graph is created to enhance the region’s coverage by connecting the sparse data indicating the flow of pedestrians. This proposed approach successfully obtained pedestrian trajectory data from the sparse and noisy data. Moreover, it was possible to identify the potential locations where pedestrians tend to cross the street by analyzing the pedestrian flow. The results indicate that 83% of well-known regions where pedestrians tend to cross the street corresponded with those extracted using the proposed approach. Furthermore, a high-level semantic map of the regions where pedestrians tend to cross the street along a 1-km road is presented. The trajectory information obtained using the proposed approach is expected to be essential for understanding different scenarios of the interactions between individuals and autonomous vehicles. [ABSTRACT FROM AUTHOR]

Despite demonstrated efficacy for HIV prevention, substantial challenges remain for the successful rollout of oral pre-exposure prophylaxis (PrEP), especially among adolescent girls and young women (AGYW). We characterized trajectories of PrEP adherence among 200 AGYW in South Africa and analyzed data from 22 qualitative interviews and 3 focus group discussions for explanatory purposes. Two adherence trajectory groups were identified: 52% with high early adherence that declined after month three and 48% with low adherence throughout. Adherence in the "consistently low" group was related to social support and logistical concerns, while the decrease in the "high declining" group corresponded to a change in the frequency of study visits from monthly to quarterly. PrEP support should be differentiated for those who need more frequent visits and adherence support initially versus later in PrEP use. Visits every month, when needed, should be considered for AGYW who need sustained support later into use. [ABSTRACT FROM AUTHOR]

The aim of this work is to study precipitation chemistry in the cross-border region between Turkey and Bulgaria, situated on the south-eastern part of the Balkan Peninsula. A total of 115 wet deposition samples were collected and analysed for pH values and major ions (Na+, Mg2+, Ca2+, K+, NH4+, Cl−, NO3−, and SO42−) throughout the summer and autumn seasons of 2014. The enrichment factor analysis and non-sea salt estimates were conducted to determine the possible sources of ions in the wet deposition for the sampling period. The trajectories of the cyclones affecting the area during the study period were also analysed by separating them in different groups. The minimum, average and maximum pH values for the first group of cyclones (CG1) are 4.30, 6.04, 7.40, and 4.00, 6.14, 7.43 for the second group cyclones (CG2), respectively. The non-sea salt fractions of the K+ ion were found to be 0.94 in CG1 and 0.90 in CG2. Also, the Mg2+ ion in CG1 and CG2 is 44% and 60% of the sea salt source. [ABSTRACT FROM AUTHOR]

Objective: To identify distinct trajectories of toxicity in colorectal cancer (CRC) patients after adjuvant chemotherapy and its impact on quality of life (QoL) and psychological symptoms. Methods: A prospective, multicenter study was conducted in 157 patients. A latent class analysis defined the unobserved latent constructs that can be predicted as symptom clusters, considering the intensity of four types of adverse events (AEs). Patients completed EORTC-QLQ-C30, BSI-18, PDRQ-9, and DRS scales. Results: Ninety-six percent had some degree of toxicity, with grades 3–4 being the most common: neurotoxicity (7.2%), hematological (13.1%), digestive (5.2%), and skin toxicity (1.4%). Three distinct latent classes were identified (high [72.5%], mild [16.9%], and low [10.6%] toxicity). Patients with high toxicity had the worst QoL scores and moderately high somatization and psychological distress scores. Conclusions: Adjuvant chemotherapy for CRC was associated with frequent toxicity that negatively impacted QoL and psychological wellbeing. [ABSTRACT FROM AUTHOR]

The Fukushima Daiichi Nuclear Power Plant (FDNPP) accident in March 2011 emitted a considerable amount of radioactive materials. This study isolated radiocesium-bearing microparticles (CsMPs), a form of radioactive materials emitted from the FDNPP at the early stage of the accident, from aerosols collected hourly on filter tapes at seven monitoring stations at the greater Kanto Region, including the Tokyo metropolitan area, on 15 March 2011. The aerosols had a spherical shape ~ 1 μm in diameter with activity of less than 1 Bq of 137Cs per particle. Their physical and chemical characteristics, including radioactivity ratio 134Cs/137Cs as well as chemical composition and state, are essentially the same as previously reported CsMPs. This study demonstrated that air parcels containing CsMPs emitted from the FDNPP were widespread over the greater Kanto Region, more than 250 km away from the FDNPP, during the daytime of 15 March. Trajectory analysis indicated that these particles were emitted from the reactor No. 2 of FDNPP between 14 March evening and 15 March early morning. The information obtained on the widespread distribution of CsMPs can be useful for assessing the actual impacts of radioactive contamination from the FDNPP accident on the environment and human health. [ABSTRACT FROM AUTHOR]

Road traffic environments are highly dynamic and volatile with a multitude of roadside and external environmental factors contributing to its dynamicity. Apart from infrastructure-related means such as traffic lights, planned and unplanned road events and different road networks, a core component which contributes towards the traffic environment is the human factor which is heavily overlooked in the current studies. Due to diverse travel patterns of day-to-day activities, the commuter behaviour is directly depicted in traffic patterns providing an opportunity to further explore human behaviours using road traffic. Conducting such analysis would reveal different commuter behavioural patterns that can be used for optimization and timely management of operations. However, to conduct such real-time behaviour analysis, large volumes of high-frequency data are required with high granularity, as well as, a suitable technology to manage such data. Addressing these needs, we propose an environment-driven commuter behavioural model that can be used to elucidate diverse behaviours in road traffic environments. We conceptualized, designed and developed an artificial intelligence based commuter behaviour profiling framework to detect diverse commuter behavioural profiles, fluctuating and routine patterns among commuters using traffic flow profiling and travel trajectory analysis. We evaluated the framework using 190 million data points captured from the Bluetooth sensor network of the Melbourne arterial road network, in the state of Victoria in Australia. The results demonstrate that traffic flow profiling of the proposed framework can provide insights on recurrent commuter behaviours that are distinct to a selected area with a high granularity. Moreover, traffic trajectory analysis provides insights on non-recurrent behaviours such as accidents with regard to how such incidents impact the dynamics of the network and how the impact is propagated through the network. Besides road traffic management, the proposed framework will enable real-time decision-making when planning road infrastructure and support decision-making of government and business entities to optimize operations. [ABSTRACT FROM AUTHOR]

We study five existing map construction algorithms, designed and tested with urban vehicle data in mind, and apply them to hiking trajectories with different terrain characteristics. Our main goal is to better understand the existing strategies and their limitations, in order to shed new light into the current challenges for map construction algorithms. We carefully analyze the results obtained by each algorithm focusing on the local details of the generated maps. Our analysis includes the characterization of 10 types of common artifacts, which occur in the results of more than one algorithm, and 7 algorithmic-specific artifacts, which are consequences of different algorithmic strategies. This allows us to extract systematic conclusions about the main challenges to fully automatize the construction of maps from trajectory data, to detect the strengths and weaknesses of the potential different strategies, and to suggest possible ways to design higher-quality map construction methods. We consider that this analysis will be of help for designing new and better methods that perform well in wider and more realistic contexts, not only for road map or hiking reconstruction, but also for other types of trajectory data. [ABSTRACT FROM AUTHOR]

Purpose: To identify distinct trajectories of total moderate-to-vigorous physical activity (MVPA) and sedentary behavior following a breast cancer diagnosis and their correlates.Methods: The analysis examined 3000 female breast cancer survivors within Kaiser Permanente Northern California between 2006 and 2013. Self-reported time spent on total MVPA and sedentary behaviors were assessed at baseline (mean = 1.8 months post-diagnosis) and at 6 and 24 months follow up. Trajectory groups were identified using group-based trajectory modeling and K-means for longitudinal data analysis. Trajectory groups were named by baseline activity level (high, medium, or low) and direction of change (increaser, decreaser, or maintainer).Results: Trajectory analyses identified three MVPA trajectories [high decreaser (7%), medium decreaser (35%), low maintainer (58%)] and four sedentary behavior trajectories [high maintainer (18%), high decreaser (27%), low increaser (24%), and low maintainer (31%)]. Women with higher education (ORs: 1.63-4.37), income (OR: 1.37), dispositional optimism (ORs: 1.60-1.86), and social support (OR: 1.33) were more likely to be high or medium decreasers of MVPA (all P < 0.05). High maintainers and high decreasers of sedentary behavior were more likely to have higher education (OR: 1.84) and social support (ORs: 1.42-1.86), but lower income (OR: 0.66; all P < 0.05).Conclusions: In the 24 months following breast cancer diagnosis, 42% of survivors decreased MVPA and 73% maintained or increased time on sedentary behavior. Socioeconomic status and stress coping at diagnosis predicted subsequent PA trajectory.Implications For Cancer Survivors: It is important to prioritize exercise intervention and counseling during early stage of breast cancer survivorship, especially in survivors who are at high risk of becoming physically inactive post-diagnosis. [ABSTRACT FROM AUTHOR]

We inquire how early in childhood children most at risk for problematic patterns of internalizing and externalizing behaviors can be accurately classified. Yearly measures of anxiety/depressive symptoms and aggressive behaviors (ages 6-13; n = 334), respectively, are used to identify behavioral trajectories. We then assess the degree to which limited spans of yearly information allow for the correct classification into the elevated, persistent pattern of the problem behavior, identified theoretically and empirically as high-risk and most in need of intervention. The true positive rate (sensitivity) is below 70% for anxiety/depressive symptoms and aggressive behaviors using behavioral information through ages 6 and 7. Conversely, by age 9, over 90% of the high-risk individuals are correctly classified (i.e., sensitivity) for anxiety/depressive symptoms, but this threshold is not met until age 12 for aggressive behaviors. Notably, the false positive rate of classification for both high-risk problem behaviors is consistently low using each limited age span of data (< 5%). These results suggest that correct classification into highest risk groups of childhood problem behavior is limited using behavioral information observed at early ages. Prevention programming targeting those who will display persistent, elevated levels of problem behavior should be cognizant of the degree of misclassification and how this varies with the accumulation of behavioral information. Continuous assessment of problem behaviors is needed throughout childhood in order to continually identify high-risk individuals most in need of intervention as behavior patterns are sufficiently realized. [ABSTRACT FROM AUTHOR]

Long-term measurements (2011–2018) of ambient sulphur dioxide (SO2) and meteorology were carried out at an urban site of Delhi, India, to study the seasonal and inter-annual variations of SO2 over Delhi. The average mixing ratio of SO2 was estimated as 2.26 ± 0.48 ppb for the entire study period. Mixing ratio of ambient SO2 was estimated as 2.19 ± 0.64 ppb, 2.07 ± 0.89 ppb, 2.49 ± 1.05 ppb and 2.27 ± 0.71 ppb during winter, pre-monsoon, monsoon and post-monsoon seasons, respectively. SO2 mixing ratio was recorded maxima during monsoon (2.49 ± 1.05 ppb) season, whereas minima during pre-monsoon season (2.07 ± 0.89 ppb). The mixing ratio of SO2 showed slightly increase in the trend during observational period. Surface wind speed and wind directions analysis indicates the influence of local sources on the mixing ratio of SO2 at the study site. Backward trajectories and potential source contributing factor (PSCF) analysis also showed the local as well as the regional sources (industrial activities, coal burning and thermal power plants etc.,) influencing the mixing ratio of SO2 over Delhi. [ABSTRACT FROM AUTHOR]

Many target tracking tasks require high spatial and temporal precision. High frame rate imaging at high spatial resolution is commonly used in these applications, but this approach is expensive and generates large amounts of data which can complicate implementation. When tracking a single object in motion, almost all of this information is unused. A technique has been developed to exploit this sparsity and track motion with a long exposure where absolute timing is encoded by modulating the exposure over time according to a de Bruijn sequence. This technique has been implemented in the Desert Fireball Network to track bright meteors entering the Earth's atmosphere for orbit determination and successful meteorite recovery. An alternate proof of concept implementation was also developed demonstrating tracking at 36 megapixels and 1000 Hz using a consumer camera with an inexpensive modulated light source and retroreflective target. The technique could be applied to other tracking problems requiring high temporal and spatial precision such as particle image velocimetry and space surveillance and tracking. [ABSTRACT FROM AUTHOR]

Purpose: To identify distinct diet trajectories after breast cancer (BC) diagnosis, and to examine the characteristics associated with diet trajectories. Methods: We analyzed 2865 Pathways Study participants who completed ≥ 2 food frequency questionnaires at the time of BC diagnosis (baseline), and at 6 and 24 months after baseline. Trajectory groups of fruit and vegetable (F/V) intake, % calories from dietary fat, and alcohol intake over 24 months were identified using group-based trajectory modeling. Associations between diet trajectories and sociodemographic, psychosocial, and clinical factors were analyzed using multinomial logistic regression. Results: Analyses identified 3 F/V trajectory groups, 4 dietary fat groups, and 3 alcohol groups. All 3 F/V trajectory groups reported slightly increased F/V intake post-diagnosis (mean increase = 0.2–0.5 serving/day), while 2 groups (48% of participants) persistently consumed < 4 servings/day of F/V. Dietary fat intake did not change post-diagnosis, with 45% of survivors maintaining a high-fat diet (> 40% of calories from fat). While most survivors consumed < 1 drink/day of alcohol at all times, 21% of survivors had 1.4-3.0 drinks/day at baseline and temporarily decreased to 0.1–0.5 drinks/day at 6 months. In multivariable analysis, diet trajectory groups were significantly associated with education (ORs: 1.93–2.49), income (ORs: 1.32–2.57), optimism (ORs: 1.93–2.49), social support (OR = 1.82), and changes in physical well-being (ORs: 0.58–0.61) and neuropathy symptoms after diagnosis (ORs: 1.29–1.66). Conclusions: Pathways Study participants reported slightly increasing F/V and decreasing alcohol intake after BC diagnosis. Nearly half of survivors consumed insufficient F/V and excessive dietary fat. It is important to prioritize nutrition counseling and education in BC survivors. [ABSTRACT FROM AUTHOR]

A new concept is proposed of estimating mesh similarity based on trajectory data. The model is formulated as an unsupervised learning method using a type of Gaussian process on a continuous coordinate system. This allows for the features of meshes and trajectories to be determined as the estimated latent coordinates that are different from geographic ones. The similarities of meshes and trajectories are represented through those of coordinates. In addition, this allows for easy visualisation. After introducing the coordinate estimation method with a type of Markov Chain Monte Carlo approach, the proposed method was verified using actual trajectory data from the city of Sendai, Japan. [ABSTRACT FROM AUTHOR]

In recent years, the phenomenon of eSports has been a growing trend and consequently, in addition to players, other groups of users, including coaches and analysts, took an interest in online video games and the data extracted from them. Among many types of video games, one of the most widely played is the MOBA (Multiplayer Online Battle Arena) League of Legend (LoL) game. Similary to traditional sports, players and coaches/analysts analyse all game events, such as, players' movements, to understand how they play to define new strategies and improve their performance. Our main goal is to get a better understanding of which visualizations techniques are more adequate to handle this type of spatio-temporal information data, associated to player performance analysis in video games. To address this goal, we inquired players to identify the analytical questions they need to support for performance analysis and designed the VisuaLeague prototype for the visualization of in-game player trajectories, using animated maps, and events during a LoL match. This paper presents a user study to evaluate the adequacy of animated maps and the analytical strategies followed by players when using spatio-temporal data to analyse player performance. The results support the adequacy of using the animated maps technique to convey information to users in this context. Moreover, they also point out towards a high degree of importance given to the spatio-temporal components of the data for player performance analysis. [ABSTRACT FROM AUTHOR]

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The transport of volcanic aerosol in the atmosphere after the eruptions of the Grimsvotn and Nabro volcanoes in 2011 is analyzed using the method of Lagrangian particle trajectories. It was impossible to identify volcanic aerosol after the Grimsvotn eruption using data of lidar observations over Tomsk and Vladivostok against the existing background aerosol. At that time there was strong horizontal mixing in the Northern Hemisphere atmosphere. Volcanic aerosol formed after the Nabro eruption was clearly manifested in the form of aerosol scattering peaks over Vladivostok and Tomsk. This is proved by data of the CALIPSO space lidar and by the satellite observations of sulfur dioxide with GOME-2. The dynamics of the eruptive aerosol cloud formation over the Northern Hemisphere is traced. [ABSTRACT FROM AUTHOR]

How do we decide which object to pick up when faced with two alternatives? Imagine one object is near, but needs to be carried a long distance, and the other object is far, but needs to be carried a short distance. You might predict that participants would favour the far object that needs to be carried a short distance. In other words, they would procrastinate and delay picking up an object to minimise physical effort. In actuality, participants prefer to carry the near object a long distance, which is called pre-crastination. Pre-crastination may be preferred to procrastination because picking up the first object hastens completion of the first goal of the task and, subsequently, decreases cognitive load. The goal of the current study was to further investigate the mechanisms of the pre-crastination effect. This was done by converting the primarily walking task used in the first study on pre-crastination to a reach-to-grasp task. This change enabled the measurement of the duration of information processing (i.e., reaction time) when participants decided which object to move. Surprisingly, participants exhibited a range of behaviours: about 40% pre-crastinated, 40% procrastinated, and 20% neither pre-crastinated nor procrastinated. We suggest that scaling the task down from a walking task to a reach-to-grasp task altered the physical effort, cognitive load, and the interaction between these task demands. This enabled some participants to pre-crastinate and others to procrastinate. There was an intriguing relationship between the duration of information processing and the behaviour of participants: participants with the shortest reaction time had the strongest tendency to pre-crastinate, and participants with the longest reaction time had the strongest tendency to procrastinate. These findings fit with the automatic pre-crastination response hypothesis; that the "decision" to pre-crastinate is automatic. This automaticity caused the short durations of information processing for participants who pre-crastinated. Participants who procrastinated had to, first, inhibit the automatic response to pre-crastinate, which caused long durations of information processing. [ABSTRACT FROM AUTHOR]

Zusammenfassung: Hintergrund: Depressivität ist ein häufiges Problem nach einem Schlaganfall, welches die Betroffenen sehr belastet. Übergeordnetes Ziel der Schlaganfallrehabilitation ist das Erreichen einer größtmöglichen Selbstbestimmung und Teilhabe am Leben in der Gesellschaft. In dieser Studie wurde untersucht, welchen Einfluss depressive Symptome auf den Verlauf der Teilhabe in der ambulanten Neurorehabilitation haben. Methodik: In einer multizentrischen Beobachtungsstudie wurden Schlaganfallrehabilitanden in 17 deutschen ambulanten neurologischen Rehabilitationszentren befragt. In der vorliegenden Studie wurden Daten zur Teilhabesituation und zu depressiven Symptomen ausgewertet, welche zu Beginn und zum Ende der Rehabilitation mittels Selbsteinschätzungsbögen erfasst wurden. Ergebnisse: Es wurden Daten von 342 Rehabilitanden berücksichtigt. In einer multinomialen logistischen Regressionsanalyse erwies sich insbesondere der Depressionswert zum Ende der Rehabilitation als guter Prädiktor für eine Teilhabeverbesserung, je niedriger die Depressivität, desto wahrscheinlicher war die Verbesserung der Teilhabe. Am Anfang der Reha unterschieden sich die Depressionswerte der Verbesserten und der Verschlechterten nicht signifikant. Diskussion: Es zeigte sich ein Zusammenhang zwischen Veränderung der Depressivität und Teilhabeveränderung. Behandlung depressiver Symptome durch frühzeitige psychotherapeutische und medikamentöse Behandlung und allgemeine Aktivitätsförderung könnte die Teilhabe also positiv beeinflussen. [ABSTRACT FROM AUTHOR]

Vessel Monitoring System (VMS) provides a new opportunity for quantified fishing research. Many approaches have been proposed to recognize fishing activities with VMS trajectories based on the types of fishing vessels. However, one research problem is still calling for solutions, how to identify the fishing vessel type based on only VMS trajectories. This problem is important because it requires the fishing vessel type as a preliminary to recognize fishing activities from VMS trajectories. This paper proposes fishing vessel type identification scheme (FVID) based only on VMS trajectories. FVID exploits feature engineering and machine learning schemes of XGBoost as its two key blocks and classifies fishing vessels into nine types. The dataset contains all the fishing vessel trajectories in the East China Sea in March 2017, including 10031 pre-registered fishing vessels and 1350 unregistered vessels of unknown types. In order to verify type identification accuracy, we first conduct a 4-fold cross-validation on the trajectories of registered fishing vessels. The classification accuracy is 95.42%. We then apply FVID to the unregistered fishing vessels to identify their types. After classifying the unregistered fishing vessel types, their fishing activities are further recognized based upon their types. At last, we calculate and compare the fishing density distribution in the East China Sea before and after applying the unregistered fishing vessels, confirming the importance of type identification of unregistered fishing vessels. [ABSTRACT FROM AUTHOR]

Urbanization leads to the expansion of construction land. The rapid and intense construction land expansion in the Jing-Jin-Tang (Beijing–Tianjin–Tangshan) region has had various impacts on the economic development and natural environments. Based on remote sensing images, trajectory analysis was used to depict the dynamic changes of land use types over past three decades and explore the impact of urban expansion on the environment. Adopting Tapio's decoupling analysis, we considered the relationship between the rate of change in areas of agricultural land occupied by construction land (ALO) and the non-agricultural GDP (NAGDP) growth rate to determine and compare the ecological consequences and economic impacts of urban expansion between cities with different industrial structures in the region. Our results show that: (1) during the study period, expansion of construction land in Beijing, Tianjin and Tangshan increased first and then decreased. (2) Early in the study period, most of areas converted to construction land had originally been agricultural land, but this gradually changed to include more other land use types. (3) The expansion of construction land not only occupies a large amount of agriculture land and ecological land, but also aggravates urban ecological problems. (4) The decoupling state of Tianjin was more ideal compared with those of Tangshan and Beijing. (5) Finally, the rate of change in ALO area began to decrease over the study period, even though the NAGDP growth rate continually increased in the whole region, meaning that the decoupling states were moving in an ideal direction. [ABSTRACT FROM AUTHOR]

Check-in facility in a location-based social network (LBSN) enables people to share location information as well as real-life activities. Analysing these historical series of check-ins to predict the future locations to be visited has been very popular in the research community. However, it has been found that people do not intend to share the privately visited locations and activities in a LBSN. Research into extrapolating unchecked locations from historical data is limited. Knowledge of hidden locations can have a wide range of benefits to society. It may help the investigating agencies in identifying possible places visited by a suspect, a marketing company in selecting potential customers for targeted marketing, for medical representatives in identifying areas for disease prevention and containment, etc. In this paper, we propose an Associative Location Prediction Model (ALPM), which infers privately visited unchecked locations from a published user trajectory. The proposed ALPM explores the association between a user’s checked-in data, the Hidden Markov Model and proximal locations around a published check-in for predicting the unchecked or hidden locations. We evaluate ALPM on real-world Gowalla LBSN dataset for the users residing in Beijing, China. Experimental results show that the proposed model outperforms the existing state-of-the-art work in the literature. [ABSTRACT FROM AUTHOR]

Depressive symptoms vary in severity and chronicity. We used group-based trajectory models to describe trajectories of depressive symptoms (measured using the Patient Health Questionnaire-9) and predictors of trajectory group membership among 1493 HIV-infected men (84%) and 292 HIV-infected women (16%). At baseline, 29% of women and 26% of men had depressive symptoms. Over a median of 30 months of follow-up, we identified four depressive symptom trajectories for women (labeled “low” [experienced by 56% of women], “mild/moderate” [24%], “improving” [14%], and “severe” [6%]) and five for men (“low” [61%], “mild/moderate” [14%], “rebounding” [5%], “improving” [13%], and “severe” [7%]). Baseline antidepressant prescription, panic symptoms, and prior mental health diagnoses were associated with more severe or dynamic depressive symptom trajectories. Nearly a quarter of participants experienced some depressive symptoms, highlighting the need for improved depression management. Addressing more severe or dynamic depressive symptom trajectories may require interventions that additionally address mental health comorbidities. [ABSTRACT FROM AUTHOR]

We present efficient algorithms for segmenting and classifying trajectories based on a movement model parameterised by a single parameter, like the Brownian bridge movement model. Segmentation is the problem of subdividing a trajectory into interior-disjoint parts such that each part is homogeneous in its movement characteristics. We formalise this using the likelihood of the model parameter, and propose a new algorithm for trajectory segmentation based on this. We consider the case where a discrete set of m parameter values is given and present an algorithm to compute an optimal segmentation with respect to an information criterion in O(nm) time for a trajectory with n sampling points. We also present an algorithm that efficiently computes the optimal segmentation if we allow the parameter values to be drawn from a continuous domain. Classification is the problem of assigning trajectories to classes of similar movement characteristics. The set of trajectories might for instance be the subtrajectories resulting from segmenting a trajectory, thus identifying movement phases. We give an algorithm to compute the optimal classification with respect to an information criterion in O(m2+kmlogm) time for m parameter values and k trajectories, assuming bitonic likelihood functions. We also show that classification is NP-hard if the parameter values are allowed to vary continuously and present an algorithm that solves the problem in polynomial time under mild assumptions on the input. [ABSTRACT FROM AUTHOR]

Motion anomaly detection through video analysis is important for delivering autonomous situation awareness in public places. Surveillance scene segmentation and representation is the preliminary step to implementation anomaly detection. Surveillance scene can be represented using Region Association Graph (RAG), where nodes represent regions and edges denote connectivity among the regions. Existing RAG-based analysis algorithms assume simple anomalies such as moving objects visit statistically unimportant or abandoned regions. However, complex anomalies such as an object encircles within a particular region (Type-I) or within a set of regions (Type-II). In this paper, we extract statistical features from a given set of object trajectories and train multi-class support vector machines (SVM) to deal with each type of anomaly. In the testing phase, a given test trajectory is categorized as normal or anomalous with respect to the trained models. Performance evaluation of the proposed algorithm has been carried out on public as well as our own datasets. We have recorded sensitivity as high as 86% and fall-out rate as low as 9% in experimental evaluation of the proposed technique. We have carried out comparative analysis with state-of-the-art techniques to benchmark the method. It has been observed that the proposed model is consistent and highly accurate across challenging datasets. [ABSTRACT FROM AUTHOR]