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Drug-induced sleep endoscopy (DISE) is used for evaluating upper airway anatomy and determining airway obstruction patterns. It is typically performed with the patient in the supine position. Airway collapse severity is influenced by body position and level of consciousness; the resultant dynamic changes may vary across patients. In this study, we evaluated the severity of upper airway collapse through awake endoscopy and DISE and identified factors affecting the pattern of airway collapse severity. This study included 66 patients with obstructive sleep apnea. The patients underwent type 1 polysomnography, tongue strength assessment, awake endoscopy in the sitting and supine positions, and DISE. Group-based trajectory modeling was performed to identify patients with different collapse severity patterns in different body positions and at different levels of consciousness. Patient with similar severity trajectory were assigned to the same group. Two different severity trajectories (group 1 and group 2) were identified at the tongue base level. Tongue depression strength varied significantly between groups 1 and 2 (47.00 vs. 35.00 kPa; P =.047). During awake endoscopy, collapse severity was significantly higher in group 2 than in group 1. Group 1 had lower rapid eye movement/nonrapid eye movement apnea–hypopnea index ratios and higher tongue depression strength than did group 2. In patients with obstructive sleep apnea, tongue strength may vary depending on body position. Our results should be interpreted with caution because of the limited sample size. Future studies should investigate the effect of oropharyngeal rehabilitation on tongue strength and collapse severity. [ABSTRACT FROM AUTHOR]

• What is the primary question addressed by this study? The question addressed by the study must limited to only one sentence. This study assesses the rates, stability, and trajectories of clinically significant hoarding symptoms in older adults with depression (late-life depression). • What is the main finding of this study? The finding must be limited to two sentences. Hoarding symptoms were present in up to 33% of older adults with active depression in two independent cohorts. Hoarding severity was stable over time and did not co-vary with depression severity. • What is the meaning of the finding? The meaning of the finding must be limited to one sentence. Hoarding is a more common comorbidity in late life depression than previously suggested and should be considered in screening and management in this population, and the interaction of these conditions should be further characterized with attention to determining factors which may improve hoarding outcomes. Hoarding disorder (HD) is a debilitating neuropsychiatric condition that affects 2%–6% of the population and increases in incidence with age. Major depressive disorder (MDD) co-occurs with HD in approximately 50% of cases and leads to increased functional impairment and disability. However, only one study to date has examined the rate and trajectory of hoarding symptoms in older individuals with a lifetime history of MDD, including those with current active depression (late-life depression; LLD). We therefore sought to characterize this potentially distinct phenotype. We determined the incidence of HD in two separate cohorts of participants with LLD (n = 73) or lifetime history of MDD (n = 580) and examined the reliability and stability of hoarding symptoms using the Saving Inventory-Revised (SI-R) and Hoarding Rating Scale-Self Report (HRS), as well as the co-variance of hoarding and depression scores over time. HD was present in 12% to 33% of participants with MDD, with higher rates found in those with active depressive symptoms. Hoarding severity was stable across timepoints in both samples (all correlations >0.75), and fewer than 30% of participants in each sample experienced significant changes in severity between any two timepoints. Change in depression symptoms over time did not co-vary with change in hoarding symptoms. These findings indicate that hoarding is a more common comorbidity in LLD than previously suggested, and should be considered in screening and management of LLD. Future studies should further characterize the interaction of these conditions and their impact on outcomes, particularly functional impairment in this vulnerable population. [ABSTRACT FROM AUTHOR]

Visual motion segmentation (VMS) is an important and key part of many intelligent crowd systems. It can be used to figure out the flow behavior through a crowd and to spot unusual life-threatening incidents like crowd stampedes and crashes, which pose a serious risk to public safety and have resulted in numerous fatalities over the past few decades. Trajectory clustering has become one of the most popular methods in VMS. However, complex data, such as a large number of samples and parameters, makes it difficult for trajectory clustering to work well with accurate motion segmentation results. This study introduces a spatial-angular stacked sparse autoencoder model (SA-SSAE) with l2-regularization and softmax, a powerful deep learning method for visual motion segmentation to cluster similar motion patterns that belong to the same cluster. The proposed model can extract meaningful high-level features using only spatial-angular features obtained from refined tracklets (a.k.a 'trajectories'). We adopt l2-regularization and sparsity regularization, which can learn sparse representations of features, to guarantee the sparsity of the autoencoders. We employ the softmax layer to map the data points into accurate cluster representations. One of the best advantages of the SA-SSAE framework is it can manage VMS even when individuals move around randomly. This framework helps cluster the motion patterns effectively with higher accuracy. We put forward a new dataset with itsmanual ground truth, including 21 crowd videos. Experiments conducted on two crowd benchmarks demonstrate that the proposed model can more accurately group trajectories than the traditional clustering approaches used in previous studies. The proposed SA-SSAE framework achieved a 0.11 improvement in accuracy and a 0.13 improvement in the F-measure compared with the best current method using the CUHK dataset. [ABSTRACT FROM AUTHOR]

Waist circumference (WC) is linked to non-alcoholic fatty liver disease (NAFLD) incidence. However, the impact of longitudinal WC changes on NAFLD remains unclear. We investigated WC trajectories and NAFLD incidence in a large population-based cohort. We analyzed data from 2666 participants without NAFLD, who underwent biennial check-ups for 16 years, divided into a 6-year exposure period and a 10-year event accrual period. Participants were classified into increasing and decreasing WC trajectory groups during the median 5.9-year exposure period by group-based trajectory modeling. Multiple Cox proportional hazard regression analysis estimated the hazard ratio (HR) and 95 % confidence interval (CI) for incident NAFLD. During the median 9.7-year event accrual period, 799 participants developed NAFLD. The increasing WC trajectory group had a higher NAFLD risk than the decreasing group, with an HR of 1.20 (95 % CI: 1.02–1.42). After adjusting for confounders, the adjusted-HR was 1.28 (95 % CI: 1.07–1.53). Subgroup analyses revealed significant findings for groups, regardless of abdominal obesity status. An increasing WC trend was associated with a higher NAFLD risk, independent of abdominal obesity status. Monitoring WC changes may facilitate early detection of NAFLD risk groups and promote lifestyle modifications to prevent NAFLD onset. [Display omitted] • We studied the association of waist circum. (WC) with incident non-alcoholic fatty liver disease (NAFLD) over time. • Increasing WC posed greater risk of incident NAFLD in absence of abdominal obesity. • Women with abdominal obesity and decreasing WC had a lower risk of incident NAFLD. • Managing changes in WC could be a strategy to prevent the incidence of NAFLD. [ABSTRACT FROM AUTHOR]

The longitudinal trajectories of body mass index (BMI) can reflect the pattern of BMI changes. Lifetime risk quantifies the cumulative risk of developing a disease over the remaining life of a person. We aimed to identify the trajectory of BMI and explore its association with cardiovascular disease (CVD) in the Chinese population. A total of 68,603 participants with a mean age of 55.46 years were included from the Kailuan cohort in Tangshan, China, who were free of CVD and cancer and with repeated measurements of BMI from 2006 to 2010. A latent mixture model was used to identify BMI trajectories. An improved Kaplan-Meier estimator was used to predict the lifetime risk of CVD according to BMI trajectories. During a median follow-up of 7.0 years, 3325 participants developed CVD. Five BMI trajectories were identified at three index ages (35, 45, and 55) respectively. For index age 35 years, compared with the stable low-normal weight group (22.7% [95% CI, 20.0%–25.4%]), the stable high-normal weight (27.6% [25.6%–29.5%]), stable overweight (29.4% [27.4%–31.4%]), stable-low obesity (32.8% [30.0%–35.5%]), and stable-high obesity (38.9% [33.3%–44.5%]) groups had a higher lifetime risk of CVD (P < 0.05). We observed similar patterns for stroke and myocardial infarction. Similarly, the lifetime risk of CVD was higher in the long-term overweight and obese groups at 45 and 55 index ages. Long-term overweight and obesity were associated with an increased lifetime risk of CVD. Our findings could assist in predicting the population burden of CVD. • This is the first study to report the effect of BMI trajectory on lifetime risk of first CVD in a large population. • We identified 5 distinct trajectory patterns of BMI in current population. • The lifetime risk of CVD increased consistently with the level of BMI trajectory. [ABSTRACT FROM AUTHOR]

Objective: To investigate the associations between the prevalence, treatment, control of hypertension, and trajectories of cognitive performance among Chinese middle-aged and older adults.Design: An 8-year longitudinal study.Setting: China.Participants: Chinese middle-aged and older adults.Measurements: Data from the China Health and Retirement Longitudinal Study were utilized. Group-based trajectory modeling was performed to identify heterogeneous trajectories of episodic memory and executive function. Multinomial logistic regression models were established to examine the relationships between hypertension status and cognitive trajectories, stratified by sex.Results: Three episodic memory trajectories and four executive function trajectories were identified in males and females. Hypertension prevalence was associated with worse episodic memory and executive function trajectories in females. Compared with treated hypertensives, untreated hypertensives were more likely to have worse executive function trajectories, both in males and females. Among male treated hypertensives, those with uncontrolled blood pressure (BP) had worse episodic memory trajectories compared with their counterparts with controlled at standard targets, while females with uncontrolled BP demonstrated worse executive function trajectories compared with females controlled at standard targets. There was basically no significant difference in cognitive trajectory memberships between individuals with controlled hypertension corresponding to intensive or standard BP targets.Conclusions: The prevalence of hypertension was associated with worse cognitive trajectories, and the treatment and control of hypertension were related to more favorable cognitive trajectories. Intensive BP control target was not associated with additional benefit beyond the recognized protective effect of standard BP targets on cognitive trajectories. [ABSTRACT FROM AUTHOR]

Understanding changes in land use and land cover (LULC) is a prerequisite for the sustainable management of ecosystems, with implications for regulatory policy. In this study, we use a hierarchical approach to quantify long-term changes in LULC in the catchment of the largest Central-European shallow lake (Lake Balaton, Hungary). We evaluate changes over three centuries at the catchment and different spatial levels of the shoreline. Within this framework, we develop a methodology suitable for analysing land use transformations in the shoreline zone, typically affected by LULC changes stemming from mass tourism. Our findings indicate that LULC transformations at the catchment level were relatively minor compared to those observed along the shoreline, where urbanization driven by mass tourism emerged as a drivers of LULC changes. The dynamics of urbanization closely mirrored socio-political shifts and exhibited a strong dependence on distance from the shore. Temporal trajectories of LULC changes revealed that the most significant alterations occurred within the 0–500 m and 500–1000 m shoreline distance zones during the socialist era when the lake served as a focal point for tourism in Central and Eastern Europe. While the process of mass tourism-induced urbanization has declined significantly since the collapse of the socialist regime, the sprawl of urban (built up) areas into rural territories persist. Given the unregulated nature of urbanization at the forefront, we emphasize the importance for policy makers and local stakeholders to control further transformations of semi-natural and natural areas into built up areas along the shoreline. Achieving sustainable LULC management in lakes affected by mass tourism, such as Lake Balaton, necessitates robust legislative and administrative efforts in spatial planning and regulation. This endeavour should be pursued as a shared interest among residents and tourists alike. • Long-term changes in land transformation were quantified. • Temporal trajectories of land conversion depended on distance from lakeshore. • Urban land transformation by mass tourism was the main driver. • Changes corresponded with characteristic socio-political periods. • Tourism planning and land use regulation is required to reach sustainability goals. [ABSTRACT FROM AUTHOR]

Objective: To examine global disability trajectories in US military with and without traumatic brain injury (TBI) over the first decade following deployment to identify risk profiles for better intervention stratification, hopefully reducing long-term cost. Setting: Patients and participants were enrolled in combat or directly following medical evacuation at the time of injury and followed up every 6 months for 10 years. Participants: There are 4 main groups (n = 475), 2 primary and 2 exploratory: (1) combat-deployed controls without a history of blast exposure "non-blast- control" (n = 143), (2) concussive blast TBI "'blast-TBI" (n = 236) (primary), (3) combat-deployed controls with a history of blast exposure "blast-control" (n = 54), and (4) patients sustaining a combat concussion not from blast "non-blast-TBI" (n = 42) (exploratory). Design: Prospective, observational, longitudinal study. Main Measures: Combat concussion, blast exposure, and subsequent head injury exposure over the first decade post-deployment. Global disability measured by the Glasgow Outcome Scale Extended (GOSE). Results: Latent class growth analysis identified 4 main trajectories of global outcome, with service members sustaining combat concussion 37 to 49 times more likely to be in the worse disability trajectories than non-blast-controls (blast-TBI: odds ratio [OR] = 49.33; CI, 19.77-123.11; P <.001; non-blast-TBI: OR = 37.50; CI, 10.01-140.50; P <.001). Even blast-exposed-controls were 5 times more likely to be in these worse disability categories compared with non-blast-controls (OR = 5.00; CI, 1.59-15.99; P =.007). Adjustment for demographic factors and subsequent head injury exposure did not substantially alter these odds ratios. Conclusions: Very high odds of poor long-term outcome trajectory were identified for those who sustained a concussion in combat, were younger at the time of injury, had lower education, and enlisted in the Army above the risk of deployment alone. These findings help identify a risk profile that could be used to target early intervention and screen for poor long-term outcome to aid in reducing the high public health cost and enhance the long-term quality of life for these service members following deployment. [ABSTRACT FROM AUTHOR]

The accurate prediction of human movement trajectory has a variety of benefits for many applications such as optimizing nurse's trajectory in a hospital, optimizing movements of old or disabled people to minimize their routine efforts, etc. To perform human movement prediction, large amount of historical positioning data from sensors has to be collected and mined. We analyzed different human sequential movement prediction approaches and their limitations. In this work, we propose a new classifier named Apriori based Probability Tree Classifier (APTC) which predicts the human movement sequence patterns in indoor environment. The APTC classifier is integrated into Bagged J48 Machine learning algorithm which results in an ensemble model to predict the future human movement patterns. The patterns are mined based on spatial, temporal and social data which add more accuracy to our prediction. Our model also performs clustering mechanism to detect the abnormal patterns. [ABSTRACT FROM AUTHOR]

With the advent of online gaming, access to in-game data has become increasingly important for players as it provides great opportunities for them to reflect and improve upon their gameplay or to compare their performance with others. Some of the currently most popular games focus on strategy and tactics, requiring players to skillfully position and maneuver units in order to achieve victory in battle. However, current visualizations for retrospective analysis of battles and that are targeted toward players are mainly limited to heatmaps and hence are not well suited for conveying the flow of battle. By contrast, military planners and historians alike have long used maps to provide a concise visual overview of troop movements. In this article, we are proposing an algorithm for automatically creating such battle maps from tracked in-game data. Several parameters allow to adjust the level-of-detail in the resulting maps. To demonstrate the practicality of our approach for post hoc analysis, we apply it to actual gameplay data obtained from a massively multiplayer online game and collected preliminary feedback among players of the game through an online survey. [ABSTRACT FROM AUTHOR]

The small brown planthopper (SBPH, Laodelphax striatellus Fallén) is an important pest that causes severe yield losses in rice by transmitting viral plant diseases. For the proper management of this pest, therefore, it is necessary to understand its temporal and spatial dynamics by establishing a periodical monitoring system. A dataset, including the number of SBPHs by location, collection method [aerial collection net (AeCN) or light trap (LT)] and period (May–Aug.) for five years (2011–2015) was provided by the Rural Developmental Administration, and missing values were imputed using multiple imputation methods. Of the 15,848 individuals collected, approximately 47% and 52.9% were collected using the AeCN and LT methods, respectively. Large numbers of SBPHs were generally collected from western coastal regions using AeCNs but not LTs. A high incidence of migratory SBPHs was observed during Julian days 144–166 using the AeCN method, with slightly different migration periods in each year. Generally, the migratory SBPHs made up 39.4% of the total populations of SBPHs during those periods. According to clustering analysis, the migratory region was located along the western coastal regions. Putative migration paths were estimated by trajectory cluster analyses using meteorological data. Interestingly, an L-shaped trajectory path emerged as a potentially important route for migratory SBPHs, passing through major wheat cultivation areas in Henan, Anhui, Jiangsu, and Zhejiang provinces in China, where high densities of SBPHs occur from late May to early June. These results would provide valuable information to predict the incidence period of migratory SBPHs and establish a proactive management system against SBPH, including the basis for the detection of hazardous factors and decisions regarding appropriate pesticide treatment periods. [ABSTRACT FROM AUTHOR]

The white-backed planthopper Sogatella furcifera (Horváth) is a major pest of rice in Asia. In spring and summer, this species migrates thousands of kilometers northward from tropical and subtropical regions into temperate climate zones, such as northern China, Korean Peninsula, and Japan. Previous studies on the migration behavior of S. furcifera have been done mainly in southern and eastern China. However, the species' pattern of seasonal migration in northern China remains unknown. In northern China, occurrence and flight trajectories of S. furcifera migration across the Bohai Sea were studied on Beihuang Island (BH) in the center of the Bohai Strait from spring to autumn 2003–2016 using searchlight trapping and trajectory simulation. During the period 2003–2016, all S. furcifera adults were captured in July, August and September; the earliest capture occurred on 12 July 2013 and the latest on 26 September 2007. The longest annual migration span at BH was 60 d in 2014. Simulation of possible migration trajectories demonstrates that S. furcifera mainly migrates between Shandong Province and Liaoning Province (or the Korean Peninsula) in both directions. Overall, our research will contribute to a better understanding of the occurrence of S. furcifera in China and to the construction of a real-time prediction system in future. [ABSTRACT FROM AUTHOR]

The key objective that is envisaged for this paper is predicting the future changes of Sand Forest that will take place as a result of continued informal wood harvesting. A change prediction model was undertaken through the use of the IDRISI Land Change Modeller, to predict the changes that would occur by 2024 within Sand Forest, over a 10 year period from 2014 base data available. Using Markov chain, the anticipated loss in extent of Sand Forest that may occur from 2014 to 2024 is 10.51 km 2 , over the entire Maputaland. The change prediction model illustrates that the expected loss centres on the larger communities that have established road networks. However, as these resources become depleted, this may change after 2024. The ability of trajectory analysis to predict potential changes based on observed and quantified trends provides a new dynamic to conservation and management strategies. In understanding where and how much Sand Forest will be lost in the forthcoming 10 years, more appropriate and accurate recommendations on conservation and management can be made. Furthermore, priority areas can be more readily identified for both conservation and for management intervention. [ABSTRACT FROM AUTHOR]

Objectives: Depressive symptoms and anxiety are fairly common emotional outcomes after severe traumatic brain injury (TBI). Life satisfaction is a main factor in the general construct of subjective well-being. However, there is limited literature available on the interrelationship between emotional outcomes and life satisfaction post-severe TBI over time. The purpose of this study was to characterize distinct patterns of change in depressive symptoms, anxiety, and life satisfaction over 24 months after severe TBI and evaluate the interrelationship of different trajectory groups among them as well as associated subject characteristics. Methods: This prospective study used longitudinal data collected from the University of Pittsburgh Brain Trauma Research Center from survivors of severe TBI (N = 129). In addition to demographic and injury-related data, depressive symptoms, anxiety, and life satisfaction were collected at 3, 6, 12, and 24 months postinjury. A group-based trajectory model was performed to identify distinct longitudinal patterns of depressive symptoms, anxiety, and life satisfaction. The interrelationships of distinct trajectory groups were examined using χ² tests. A multivariate logistic regression model was used to examine the predictors of different emotional symptom trajectories. Results: The group-based trajectory model identified 2 distinct patterns of each of 3 outcomes: constantly low and constantly high depressive symptoms group (70.4% vs 29.6%), constantly low and constantly high anxiety group (69.1% vs 30.9%), and low-decreasing and high-stable life satisfaction groups (56.3% vs 43.7%). A strong pairwise association was observed between trajectory group membership for depressive symptoms and anxiety (P < .0001), depressive symptoms and life satisfaction (P < .0001), and anxiety and life satisfaction (P < .001). Subjects with increased severe injury were more likely to belong to the high-stable depressive symptoms group, while there were no significant associations between age, gender, race, education, marriage status and distinct depressive symptoms, anxiety, and life satisfaction trajectory groups. Conclusions: A group-based trajectory model revealed patterns of emotional symptoms that have not been fully explored among survivors of severe TBI. There appear to be distinct trajectory patterns for depressive symptoms, anxiety, and life satisfaction, respectively. There was strong interrelationship among emotional symptoms. The findings add to our understanding of psychosocial outcomes experienced over time after severe TBI. [ABSTRACT FROM AUTHOR]

Sports video research is a popular topic that has been applied to many prominent sports for a large spectrum of applications. In this paper we introduce a technology platform which has been developed for the tennis context, able to extract action sequences and provide support to coaches for players performance analysis during training and official matches. The system consists of an hardware architecture, devised to acquire data in the tennis context and for the specific domain requirements, and a number of processing modules which are able to track both the ball and the players, to extract semantic information from their interactions and automatically annotate video sequences. The aim of this paper is to demonstrate that the proposed combination of hardware and software modules is able to extract 3D ball trajectories robust enough to evaluate ball changes of direction recognizing serves, strokes and bounces. Starting from these information, a finite state machine based decision process can be employed to evaluate the score of each action of the game. The entire platform has been tested in real experiments during both training sessions and matches, and results show that automatic annotation of key events along with 3D positions and scores can be used to support coaches in the extraction of valuable information about players intentions and behaviours. [ABSTRACT FROM AUTHOR]

To investigate the associations of baseline body mass index (BMI) and longitudinal BMI trajectories with all-cause mortality among patients with type 2 diabetes mellitus (T2DM). We used data from the diabetes surveillance system of Yinzhou Health Information System with T2DM patients registered from 2010 to 2015. Participants aged ≥ 40 years were included and were followed up until September 30, 2021. The latent class growth mixture model was used to identify different changing patterns in BMI for 5 years from registration. Cox proportional hazards models were used to examine the associations of baseline BMI and 5-year BMI trajectories with all-cause mortality. We observed a nonlinear association between baseline BMI and all-cause mortality (P for nonlinearity < 0.001), with an increased risk of death for low but not high BMI. However, compared with participants with medium-stable BMI for 5 years from baseline, individuals with increasing BMI had higher mortality, with adjusted hazard ratios (95% confidence intervals) 1.21 (1.02;1.43) for early-increasing and 1.47 (1.19;1.80) for late-sharp increasing groups. These findings suggest that while obesity itself may not be associated with an increased risk for mortality, weight gain, and in particular rapid weight gain, is a risk factor for mortality among patients with T2DM. [ABSTRACT FROM AUTHOR]

Immune checkpoint inhibitor (ICI) has been emerged as a promising cancer treatment. However, ICI use induces immune-related adverse events, including diabetes mellitus. We compared the risk of new-onset diabetes between patients receiving an ICI and those receiving conventional chemotherapy (CC). Using a tertiary care hospital database, we included cancer patients without a previous history of diabetes who were treated with either CC or an ICI. One-to-five nearest neighbor propensity matching was applied, and the risk of diabetes was estimated using a Cox proportional hazards model. Latent class growth modeling was performed with a trajectory approach to determine distinct clusters that followed similar glucose trajectory patterns over time. Among 1326 subjects, 1105 received CC, and 221 received an ICI. The risk of new-onset diabetes was significantly higher in the ICI group than the CC group (adjusted hazard ratio 2.454, 95 % confidence interval 1.528–3.940; p < 0.001). The ICI group had a higher proportion of subjects in the trajectory cluster with an increasing glucose pattern than the CC group (10.4 % and 7.4 %, respectively). Within the ICI group, the subjects with an increasing glucose pattern were predominantly male and associated with enhanced lymphocytosis after ICI administration. ICI therapy is associated with an increased risk of incident diabetes compared with CC. The glucose levels of patients treated with an ICI, especially males and those with prominent lymphocytosis after ICI treatment, need to be monitored regularly to detect ICI-associated diabetes as early as possible. [Display omitted] • Incident diabetes risk was higher in immune checkpoint inhibitor (ICI) group than conventional chemotherapy (CC) group. • The ICI group had a higher proportion of subjects in the increasing glucose trajectory pattern than the CC group. • Glucose levels showed an uptrend shortly after ICI initiation in the increasing glucose trajectory cluster in the ICI group. • ICI users with an increasing glucose pattern were predominantly male and associated with enhanced lymphocytosis. [ABSTRACT FROM AUTHOR]

Extracting and analyzing outdoor humans’ activities represent a strong support for several applications fields, ranging from traffic management to marketing and social studies. Mobile users take their devices with them everywhere which leads to an increasing availability of persons’ traces used to recognize their activities. However, mobile environment is distinguished from one to another by its resources limitations. In this paper, we present a novel hybrid approach that combines activity recognition and prediction algorithms in order to online recognize users’ outdoor activities without draining the mobile resources. Our approach minimizes activity computations by wisely reducing the search frequency of activities, we demonstrate that our proposal is capable of reducing the battery consumption up to 60% while maintaining the same accuracy as its similar. [ABSTRACT FROM AUTHOR]

We report drag, side, and lift coefficients for two orientations of five non-spinning soccer balls (Brazuca, Cafusa, Jabulani, Teamgeist 2, and Vantaggio), measured using a wind tunnel. The air's speed range was 7 m/s to 35 m/s, covering most of the speeds of kicked soccer balls in real games. Trajectory analyses make use of our aerodynamic wind-tunnel data and show that the five balls we tested behave differently while in flight. We also show that in some cases, changing ball orientation leads to a significant change in flight trajectory. Turning off side and lift forces alter ranges and lateral deflections as fractions of ranges in excess of 10% for some balls. Because we have only two orientations for non-spinning balls, the work we present here is just the preliminary investigation of a much larger project in which we hope to have aerodynamic data for many more ball orientations. [ABSTRACT FROM AUTHOR]

We report drag, side, and lift coefficients for two orientations of five non-spinning soccer balls (Brazuca, Cafusa, Jabulani, Teamgeist 2, and Vantaggio), measured using a wind tunnel. The air's speed range was 7 m/s to 35 m/s, covering most of the speeds of kicked soccer balls in real games. Trajectory analyses make use of our aerodynamic wind-tunnel data and show that the five balls we tested behave differently while in flight. We also show that in some cases, changing ball orientation leads to a significant change in flight trajectory. Turning off side and lift forces alter ranges and lateral deflections as fractions of ranges in excess of 10% for some balls. Because we have only two orientations for non-spinning balls, the work we present here is just the preliminary investigation of a much larger project in which we hope to have aerodynamic data for many more ball orientations. [ABSTRACT FROM AUTHOR]

Sense of coherence ( SOC ), a concept reflecting meaningfulness, comprehensibility, and manageability of life, has been demonstrated to have strong connections to positive outcomes such as good health. However, less is known about how SOC changes over the second half of life as age-related deficits accumulate. We used longitudinal samples of mature adults that included the oldest-old to track change in SOC from age 55 to 101. Growth curves using an accelerated longitudinal design were estimated for 1809 individuals who contributed 4072 observations from five national Swedish surveys between 1991 and 2010/11. Results indicated that deficits in health and social resources were largely responsible for the precipitous decline in SOC after age 70. When controlling for these deficits, SOC increased continuously into advanced old age. We conclude that the capacity to comprehend, manage, and find meaning in life—the component elements of SOC —strengthens over the last years of life, suggesting a positive ontogenic development that runs parallel but opposite to the negative impact of health and social decline. [ABSTRACT FROM AUTHOR]

GPS tracking is a common empirical research method to gain information about human mobility behavior. Based on the recorded GPS trajectories it is possible to analyze and explain motion spatially, and temporally. More comprehensive explanations of specific movement patterns require the coupling with other survey techniques such as trip diaries, interviews, and questionnaires, which are widespread data acquisition methods in tourism research. However, GPS-based surveys require a high effort in the preparation and post-processing of the data, and expertise in both, information technologies and tourism research. In order to prepare the data for the analysis in geographic information systems a number of steps with different tools is necessary. In this paper the GimToP Toolkit (GTK) is presented that integrates the methodological approach and the technology in an easy-to-handle manner. The GTK combines trajectory data with digital questionnaires based on a mobile application that is used for the data collection and preprocessing tasks. Connected to a server, which offers a service-oriented architecture, the GTK has the ability to process the survey data and to provide interoperability for the analysis in other applications. This paper presents the components of the GTK and shows its usage during two field studies, which are carried out in the city of Wernigerode and the Harz National Park in Germany. The results offer new insights in the movement behavior of the tourists and can be used to support a more sustainable development of the destinations. [ABSTRACT FROM AUTHOR]

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Migration of the Mythimna turca population was monitored using a searchlight trap on Beihuang island, providing direct evidence that M. turca migrates across the Bohai Strait. Migratory trajectories demonstrated that M. turca mainly moved northward in prevailing southerly winds from June to August and moved southward during spells of north-easterly winds during September. [Display omitted] • The study showed that M. turca is a migratory insect. • M. turca migrated across the Bohai Sea in two distinct periods. • M. turca mainly moved northward in spring and summer and moved southward in autumn. The double line moth, Mythimna turca (Linnaeus, 1761) (Lepidoptera: Noctuidae), is an important widely distributed insect species. Studies on the moth in European countries have focused on population monitoring and in China on taxonomy of Mythimna and distribution surveys of M. turca. However, whether M. turca is a migratory insect is unknown. Here, migration of the moth population was monitored using a searchlight trap from 2004 to 2020 on Beihuang island, Northern China, providing direct evidence that M. turca migrates across the Bohai Strait seasonally, in late May to early September. Population dynamics, ovarian development, wind direction and possible migration trajectories were also analyzed. Most moths migrated in June and at the end of August and the beginning of September, and a few migrated in May, July and October. The average duration of this windborne migratory period of M. turca was 93 d. Migratory trajectories demonstrated that M. turca mainly moved northward in spells of southerly winds from June to August and moved southward in spells of northerly winds during September. This new key information about the ecology of M. turca population will aid the formulation of M. turca management strategies. [ABSTRACT FROM AUTHOR]

• Plantations and spontaneous forest regrowth may obscure semi-natural forest loss. • Forest trajectories since the 1780 s were synthetized in 1,728 sites at national level. • In Hungary 36% of forests are semi-natural and 33% are semi-natural continuous forest. • Nearly half of the semi-natural forest loss was due to conversion to arable land. • Landscape planning and sustainable management require assessment of forest continuity. Despite deforestation taking place globally, forest cover is increasing in many European landscapes. This increase, however, resulting from plantations and spontaneous forest regrowth, may obscure the generally declining trend of semi-natural forests, though the latter are essential for local and landscape-level conservation strategies and sustainable forest management. We assessed changes in semi-natural and secondary forest cover since the 18th century in Hungary, focusing on the continuity of semi-natural forests. The main trajectories of regional and country-scale forest transformations were reconstructed from the fine-scale site histories of 1,728 randomly selected sample localities. Historical and recent datasets were complemented with field data to estimate forest cover change for seven time periods between the 1780s and the 2010s. Total forest cover changes over these 230 years showed a U-shape curve (from 25% to 24%), leading to a forest minimum in the first half of the 20th century. Semi-natural and secondary forests exhibited strikingly different trends. The proportion of semi-natural forests decreased to 36% of the total forest area by the 2010s, driven mainly by conversion to arable land, while 88% of the actual semi-natural forests have remained continuous forest since the 18th century. Our results showed that when reconstructing landscape-scale historical forest cover change and continuity, the loss of semi-natural forests remains hidden if the calculations are limited to 'total forest cover change'. It would therefore be immensely important to distinguish between semi-natural and secondary forests, and between types of continuity in the assessments used for conservation-oriented landscape planning and sustainable forest management. [ABSTRACT FROM AUTHOR]

Graph-based intelligent systems are emerging in the field of transportation systems. Knowledge graphs help to provide semantic and interconnectivity capabilities to the intelligent transportation system. In this paper, we propose a graph-based method for detecting outliers in the trajectory. Normal and outlier graphs are constructed using directed weighted graphs. Then, comparison with source and target graphs leading to vectors is performed. The similarity measure is used, which measures common nodes and edges. The features are then used by the machine learning based algorithm to classify the trajectory. Instead of a manually tuned parameter, the tree-based pipeline optimization method selects the best classifier and its hyperparameter. Then, the tuned model is compared with the traditional algorithms, i.e., random forest, decision tree, Naïve Bayes, and KNN. To evaluate the system under real conditions, an experiment is performed on a real dataset of trajectories. The results show that the graph-based method performs well and achieves an F-value of 0.81, while the optimization model achieves an F-value of 0.87. The graph-based model matched with the learning method helps to detect outliers and deviation points of the trajectory with high precision. • We introduce a graph network similarity-based method. • We describe the identifiability of the trajectory-based network connected via ITS. • We propose a group trajectory detection method based on the pipeline optimization technique. • We detect the trajectory outliers based on deviation points. [ABSTRACT FROM AUTHOR]

Abstract: We present a summary of our investigations into the aerodynamics of soccer balls (association footballs). Using a ball launcher and high-speed cameras, we are able to determine drag and lift coefficients using trajectory analysis. Advantages of this approach over wind tunnels include studying balls in flight without a support rod, which may influence aerodynamic studies in wind tunnels, and the ability to determine lift coefficients in regions inaccessible by many wind tunnels. We have found lift coefficients for spin parameters between 0 and 1 and Reynolds numbers between 130,000 and 300,000. Launching a ball into a dust cloud allows for the study of boundary-layer separation, again without the need of a support rod, which is needed for wind-tunnel studies. We have found boundary-layer separation angles in and around the drag crisis. Anomalous behavior is seen just past the drag crisis. [Copyright &y& Elsevier]

Abstract: Purpose: More than 50% of youth living with HIV (YLH) have unprotected sex. In previous studies, we reported effects of a motivational interviewing-based multirisk reduction intervention, “Healthy Choices” in improving motivation, depression, and viral load in YLH. In this study, we report the effect of the intervention on increasing condom use. Methods: Six waves of longitudinal data (n = 142) across a period from baseline through 15 months postintervention were analyzed. The developmental trajectory modeling method was used for program effect evaluation. Results: The three groups detected with distinct sexual risks were: Persistent low sexual risk (PLSR), delayed high sexual risk, and high and growing sexual risk with regard to levels and time trajectories of condom use throughout the trial. Receiving Healthy Choices increased the likelihood to be in the PLSR group (63% vs. 32%, p < .01) and reduced the likelihood to be in the delayed high sexual risk group (16% vs. 50%, p < .05). Receiving the intervention was also associated with progressive reductions in no-condom sex for PLSR youth (adjusted β = −.325, p < .01) and high and growing sexual risk youth (adjusted β = −.364, p < .01). Conclusion: The motivational interviewing-based program Healthy Choices, when delivered in clinic settings, can prevent unprotected sex in subgroups of YLH, although more intensive interventions may be needed to change risk trajectories among those at highest risk of transmitting the AIDS virus. Developmental trajectory analysis provides an alternative approach to evaluate program effects for study samples that contain distinct subgroups. [Copyright &y& Elsevier]

Abstract: Video surveillance is becoming the technology of choice for monitoring crowded areas for security threats. While video provides ample information for human inspectors, there is a great need for robust automated techniques that can efficiently detect anomalous behavior in streaming video from single or multiple cameras. In this work we synergistically combine two state-of-the-art methodologies. The first is the ability to track and label single person trajectories in a crowded area using multiple video cameras, and the second is a new class of novelty detection algorithms based on spectral analysis of graphs. By representing the trajectories as sequences of transitions between nodes in a graph, shared individual trajectories capture only a small subspace of the possible trajectories on the graph. This subspace is characterized by large connected components of the graph, which are spanned by the eigenvectors with the low eigenvalues of the graph Laplacian matrix. Using this technique, we develop robust invariant distance measures for detecting anomalous trajectories, and demonstrate their application on real video data. [Copyright &y& Elsevier]

Abstract: Information regarding polychlorinated biphenyls (PCBs) in environmental media in Africa is limited. This paper presents results of a monitoring program conducted in KwaZulu-Natal Province, South Africa designed to characterize levels, trends and sources of airborne PCBs. Particulate and vapor samples were sampled over the 2004–2005 period at three sites. The total PCB concentration averaged 128±47pgm−3, and levels were highest in winter. Tri- through hexa-congeners predominated, and the vapor fraction was predominant. Several tetra- through hexa-chlorinated congeners had levels comparable to those at urban sites in the northern hemisphere, but hepta- through deca-congeners resembled levels at background sites. PCB source areas, deduced using spatial and temporal patterns, compositional information and trajectory analyses, likely included local, regional and global sources. Soils at three rural sites showed high PCB concentrations, and milk from a local dairy showed PCB concentrations comparable to USA levels in year 2000. [Copyright &y& Elsevier]

Sources of cations and anions present in early monsoon precipitation (rain) were identified at one location each in Kolkata city (urban), in Baidyabati (peri-urban) and Rishra (urban-industrial) towns by enrichment factor and Principal Component Analysis. Ingress of transboundary air into local atmosphere was assessed by back trajectory analysis of air masses to assess the role of regional air masses on local air quality. Average rainwater pH in Kolkata and Baidyabati were close to 6.7 but in Rishra, average pH was 6.1 and an acid rainfall event was recorded. Ammonia (NH 4 +) was the principal acid neutralizing cation, followed by Ca2+, Mg2+ and K+. Bicarbonate (HCO 3 −) was the dominating anion while SO 4 2− was also prominent. Crustal, marine sources and local emissions were identified to have contributed heavily to ions detected in rainwater. Air trajectory analysis revealed ingress of maritime air and air flowing over land masses to study sites, hinting to its role in influencing local atmospheric chemistry. Contribution of anthropogenic sources towards SO 4 2− and NO 3 − ions was predominant (>93% and > 97%, respectively) followed by marine and crustal sources. Factor analysis revealed the role of 3 major factors in governing rainwater chemistry, accounting for >90% of the total variance at all three sites. [Display omitted] • Crustal, marine sources and local anthropogenic emissions contributed heavily to ions. • Anthropogenic sources contributed >93% & >97%, respectively, to SO 4 = & NO 3 − in rain. • NH 4 + had highest share in total ions (44, 36, 28%) followed by SO 4 = and HCO 3 −. • NH 4 + was the principal acid-neutralizing cation followed by Ca2+, Mg2+ and K+. • Ingress of regional maritime & terrestrial air influenced atmospheric chemistry. [ABSTRACT FROM AUTHOR]

Abstract: The Global Positioning System (GPS) has been increasingly used during the past decade to monitor the movements of free-ranging animals. This technology allows to automatically relocate fitted animals, which often results into a high-frequency sampling of their trajectory during the study period. However, depending on the objective of trajectory analysis, this study may quickly become difficult, due to the lack of well designed computer programs. For example, the trajectory may be built by several “parts” corresponding to different behaviours of the animal, and the aim of the analysis could be to identify the different parts, and thereby the different activities, based on the properties of the trajectory. This complex task needs to be performed into a flexible computing environment, to facilitate exploratory analysis of its properties. In this paper, we present a new class of object of the R software, the class “ltraj” included in the package adehabitat, allowing the analysis of animals'' trajectories. We developed this class of data after an extensive review of the literature on the analysis of animal movements. This class of data facilitates the computation of descriptive parameters of the trajectory (such as the relative angles between successive moves, distance between successive relocations, etc.), graphical exploration of these parameters, as well a numerous tests and analyses developed in the literature (first passage time, trajectory partitioning, etc.). Finally, this package also contains numerous examples of animal trajectories, and a working example illustrating the use of the package. [Copyright &y& Elsevier]

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The 3D reconstruction of scenes containing independently moving objects from uncalibrated monocular sequences still poses serious challenges. Even if the background and the moving objects are rigid, each reconstruction is only known up to a certain scale, which results in a one-parameter family of possible, relative trajectories per moving object with respect to the background. In order to determine a realistic solution from this family of possible trajectories, this paper proposes to exploit the increased linear coupling between camera and object translations that tends to appear at false scales. An independence criterion is formulated in the sense of true object and camera motions being minimally correlated. The increased coupling at false scales can also lead to the destruction of special properties such as planarity, periodicity, etc. of the true object motion. This provides us with a second, ‘non-accidentalness’ criterion for the selection of the correct motion among the one-parameter family. [Copyright &y& Elsevier]

In this work, composition of wet deposition in Kaynarca, Turkey is studied by collecting precipitation samples during more than a 2-year period, August 1993-November 1995. Concentrations of the main cations Na[sup +], Mg[sup 2+], Ca[sup 2+], K[sup +], NH[sup +, sub 4] and the main anions Cl[sup -], NO[sup -, sub 3] and SO[sup 2-, sub 4] together with pH were studied. The average pH value at Kaynarca was near neutral, 5.59. Results indicated that SO[sup 2, sub 4] concentration in precipitation was very high, as was Ca[sup 2+], neutralizing the acidity. Acidic wet deposition samples were generally obtained in winter. Enrichment factors for sea and soil indicate the strong effects of sea and soil, specifically limestone on the composition of precipitation. Non-sea salt fractions of SO[sup 2-, sub 4] were found to range from 0.955 to 0.980, showing the effect of non-sea sources, especially emissions from fossil-fuel combustion, on the pH of samples. Trajectory analysis showed that cyclones originating from northwestern, central and eastern parts of Europe have generally high sulfate and nitrate concentrations and low pH. [ABSTRACT FROM AUTHOR]

Identification of patient subtypes from retrospective Electronic Health Record (EHR) data is fraught with inherent modeling issues, such as missing data and variable length time intervals, and the results obtained are highly dependent on data pre-processing strategies. As we move towards personalized medicine, assessing accurate patient subtypes will be a key factor in creating patient specific treatment plans. Partitioning longitudinal trajectories from irregularly spaced and variable length time intervals is a well-established, but open problem. In this work, we present and compare k-means approaches for subtyping opioid use trajectories from EHR data. We then interpret the resulting subtypes using decision trees, examining how each subtype is influenced by opioid medication features and patient diagnoses, procedures, and demographics. Finally, we discuss how the subtypes can be incorporated in static machine learning models as features in predicting opioid overdose and adverse events. The proposed methods are general, and can be extended to other EHR prescription dosage trajectories. [ABSTRACT FROM AUTHOR]

In the present research study, identification and analysis of sources of conventional as well as emerging air pollutants is presented through source apportionment and trajectory analysis. In this regard, an extensive monitoring campaign was done in Udaipur city of India for particulate matter (PM 2.5 and PM 10), gaseous pollutants (NO, NO 2 , NOx, O 3 , CO, NH 3 , SO 2), and selected volatile organic compounds i.e. Benzene, Ethyl Benzene, Toluene, and Xylene. The collected data was analyzed using positive matrix factorization (PMF), a well-known multivariate receptor model to predict the major sources of air pollution. The PMF resolved four dominant pollution sources/factors: petroleum/solvent extraction activities, vehicular emissions, fertilizer industry, and mining activities. More specifically, the petroleum industries contributed to emission of VOCs; vehicular emissions contributed mainly to CO, NO, NOx, and NO 2 ; fertilizer related activities dominated in emission of NH 3 and SO 2 ; and mining activities were observed to be associated with emissions of PM 10 , PM 2.5 , and O 3. Moreover, trajectories analysis (backward and forward) were performed using HYSPLIT model, which revealed that the wind direction and wind speed played significant role in varying concentrations of monitored pollutants. Overall, the present study provided a new insight for the source apportionment of monitored pollutants. Unlabelled Image • PMF was used for source apportionment of PM, gaseous pollutants, and VOCs in Udaipur. • Four factors were petroleum, vehicular emission, fertilizer, and mining activities. • Backward and forward trajectory was calculated using HYSPLIT Model. • Bivariate polar plots and conditional probability function were used in this study. [ABSTRACT FROM AUTHOR]

Long records of geophysical forcing have been used in numerous studies to estimate a statistical distribution of oil spill scenarios. Theresulting set of spill scenarios is then used as a basis for planning a robust response capability that should be able to handle all likely real spills. For model developers to be able to support these expectations there are a number of criteria that must be satisfied: (1) Models must develop and retain the data necessary to answer key response questions; (2) developers must understand the limitations in resolution imposed by the specific algorithms they use; and (3) the cardinality of the long geophysical records (with respect to modeled spill behavior) should be determined and the final collection of spill scenarios must span this set. This paper considers these specific constraints and discusses methods that can be used to quantify some aspects of the uncertainty in the output. [ABSTRACT FROM AUTHOR]

The spill response community is engaged in a technological rush towards computer-based, information-synthesis systems. Typically, they are modeled after many successful 'incident command' or 'command and control' systems that rely on micro- or mini-computer technology that is friendly and graphically oriented. Virtually all of these systems offer spill trajectory modeling components. What is typically lacking in this modeling output is any reliable way to estimate the uncertainty. This means that advice derived from the models is of questionablevalue, and when integrated into a complex response plan, the propagation of errors could seriously compromise the usefulness of results. It is shown that no single trajectory model run can provide the necessary information to respond in an optimal, 'minimum regret' strategy.However, a well-defined series of model runs used as the basis for trajectory analysis can provide the required information. A discussionof options suggests that the adoption of a minimum standard analysisprocedure would significantly improve the ability of integrated response systems to use the predictions of oil distributions. [ABSTRACT FROM AUTHOR]

Historical data and information collected during recent and ongoing oceanographic investigations of Prince William Sound, Alaska and adjacent coastal waters, are used for a preliminary analysis of the possibility of an oil spill at the southern end of Prince William Sound directly impacting the Copper River Delta (CRD). The CRD is an economically and ecologically important region located a few kilometers to the east of Prince William Sound. The prevailing winds and ocean currents both in the coastal and offshore regions of the northern Gulf of Alaska move toward the west, indicating that a spill off of Cape Hinchinbrook would be likely to be advected westward away from the CRD, thereby having no impact on the waters of the CRD. However, eastward excursions of the Alaska Coastal Current occur, in which case there is a possibility that a spill off of Cape Hinchinbrook would be advectedinto the waters of the CRD region. Eastward components of the flow field within the coastal current have been frequently observed during spring, summer and fall, periods that are often characterized by westerly wind events that interrupt the prevailing easterly wind field and westward setting current. These reversals appear to be quite persistent and may have alongshore length scales from about 10 to 100 km. Although these wind and current reversals are common knowledge amongstboat captains and commercial fisherman in the region, their input togovernment agencies has largely been disregarded because their observations are anecdotal information. However, the combination of empirical scientific evidence (ocean current structure) and anecdotal information (which is actually also empirical) provide a powerful argument, attesting to the importance of these reversals as possible transport mechanisms for the advection of oil into the CRD region. This preliminary analysis is partly responsible for the Alaska Department of Environmental Conservation mandating a trajectory study in which the spill [ABSTRACT FROM AUTHOR]