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A standard approach to study time-dependent stochastic processes is the power spectral density (PSD), an ensemble-averaged property defined as the Fourier transform of the autocorrelation function of the process in the asymptotic limit of long observation times, T → ∞ . In many experimental situations one is able to garner only relatively few stochastic time series of finite T, such that practically neither an ensemble average nor the asymptotic limit T → ∞ can be achieved. To accommodate for a meaningful analysis of such finite-length data we here develop the framework of single-trajectory spectral analysis for one of the standard models of anomalous diffusion, scaled Brownian motion. We demonstrate that the frequency dependence of the single-trajectory PSD is exactly the same as for standard Brownian motion, which may lead one to the erroneous conclusion that the observed motion is normal-diffusive. However, a distinctive feature is shown to be provided by the explicit dependence on the measurement time T, and this ageing phenomenon can be used to deduce the anomalous diffusion exponent. We also compare our results to the single-trajectory PSD behaviour of another standard anomalous diffusion process, fractional Brownian motion, and work out the commonalities and differences. Our results represent an important step in establishing single-trajectory PSDs as an alternative (or complement) to analyses based on the time-averaged mean squared displacement.

Despite advancements in the Internet of Things (IoT) and social networks, developing an intelligent service discovery and composition framework in the Social IoT (SIoT) domain remains a challenge. In the IoT, a large number of things are connected together according to the different objectives of their owners. Due to this extensive connection of heterogeneous objects, generating a suitable recommendation for users becomes very difficult. The complexity of this problem exponentially increases when additional issues, such as user preferences, autonomous settings, and a chaotic IoT environment, must be considered. For the aforementioned reasons, this paper presents an SIoT architecture with a personalized recommendation framework to enhance service discovery and composition. The novel contribution of this study is the development of a unique personalized recommender engine that is based on the knowledge-desire-intention model and is suitable for service discovery in a smart community. Our algorithm provides service recommendations with high satisfaction by analyzing data concerning users' beliefs and surroundings. Moreover, the algorithm eliminates the prevalent cold start problem in the early stage of recommendation generation. Several experiments and benchmarking on different datasets are conducted to investigate the performance of the proposed personalized recommender engine. The experimental precision and recall results indicate that the proposed approach can achieve up to an approximately 28% higher F-score than conventional approaches. In general, the proposed hybrid approach outperforms other methods.

Parthenium hysterophorus (congress grass) is a harmful weed and its pollen grains are important allergens. Due to its minute size and allergenic activity, this particular type of pollen is selected for the study. The aeropalynological survey was conducted for the year 2019 at Chauras Campus, Hemvati Nandan Bahuguna Garhwal University, Srinagar, Uttarakhand. It is located on the right bank of the Alaknanda river (30°13'35.81\"N & 78°48'11.05\"E; 560 m amsl). A Rotarod sampler was used for air sampling. The maximum pollen count was observed in July. To evaluate the correlation matrix in R software, correlations (Pearson's and Spearsman's) between pollen count and meteorological parameters have been calculated. Back trajectory analysis has also been done using NOAA HYSPLIT MODEL.

Maternal gestational diabetes (GDM) is an established risk factor for large size at birth, but its influence on intrauterine fetal growth in different ethnic populations is less well understood. Here, we examine the joint associations of GDM and ethnicity with longitudinal fetal growth in South Asian and White European origin women. This study included 10,705 singletons (4747 White European and 5958 South Asian) from a prospective cohort of women attending an antenatal clinic in Bradford, in the North of England. All women completed a 75-g oral glucose tolerance test at 26-28 weeks' gestation. Ultrasound measurements of fetal head circumference (HC), femur length (FL) abdominal circumference (AC), and estimated fetal weight (EFW), and corresponding anthropometric measurements at birth were used to derive fetal growth trajectories. Associations of GDM and ethnicity with these trajectories were assessed using multilevel fractional polynomial models. Eight hundred thirty-two pregnancies (7.8%) were affected by GDM: 10.4% of South Asians and 4.4% of White Europeans. GDM was associated with a smaller fetal size in early pregnancy [differences (95% CI) in mean HC at 12 weeks and mean AC and EFW at 16 weeks comparing fetuses exposed to GDM to fetuses unexposed (reference) = - 1.8 mm (- 2.6; - 1.0), - 1.7 mm (- 2.5; - 0.9), and - 6 g (- 10; - 2)] and a greater fetal size from 24 weeks' gestation through to term [differences (95% CI) in mean HC, AC, and EFW comparing fetuses exposed to GDM to those unexposed = 0.9 mm (0.3; 1.4), 0.9 mm (0.2; 1.7), and 7 g (0; 13) at 24 weeks]. Associations of GDM with fetal growth were of similar magnitude in both ethnic groups. Growth trajectories, however, differed by ethnicity with South Asians being smaller than White Europeans irrespective of GDM status. Consequently, South Asian fetuses exposed to GDM were smaller across gestation than fetuses of White Europeans without GDM. In both ethnic groups, GDM is associated with early fetal size deviations prior to GDM diagnosis, highlighting the need for novel strategies to diagnose pregnancy hyperglycemia earlier than current methods. Our findings also suggest that ethnic-specific fetal growth criteria are important in identifying hyperglycemia-associated pathological effects.

The Tibet Plateau is known as the “third pole” of the world, and its environmental change profoundly impacts East Asia and even the global climate. HDO is the stable isotope of water vapor, which acts as an ideal tracer for studying the water cycle, and which is commonly used for atmospheric circulation and climatic studies. To monitor the water vapor isotopic abundance in the Tibetan Plateau, a portable laser heterodyne radiometer was operated in Golmud in August 2019. The radiometer utilizes a narrow-linewidth 3.66 μm distributed feedback interband cascade laser as the local oscillator, the heterodyne module is been optimized and the radiometer performs with high resolution and stability in obtaining spectral data. Furthermore, the absorption spectra of atmospheric HDO and H2O are obtained, and the retrieval method for water vapor isotopic abundance is discussed. The optimal estimation method is adopted to retrieve the density of HDO and H2O. The average column density of H2O was 1.22 g/cm2, and the HDO/H2O ratio in Golmud was 178 ± 15 × 10−6 during the observation. For a better understanding of the retrieval, the retrieval errors are analyzed and compared. The results indicate that the smoothing error is significantly higher than the measurement error in this work. The backward trajectory analysis of atmospheric transport is used to investigate the relationship between water vapor density and atmospheric motion. The results indicate that the variation of H2O column density and HDO/H2O ratio have a relationship with atmospheric movements.

Aim Understanding temporal changes in aquatic communities is essential to address the freshwater biodiversity crisis. In particular, it is important to understand the patterns and drivers of spatial variation in local community dynamics, generalizing temporal trends from discrete locations to entire landscapes that are the main focus of management. Here, we present a framework for producing spatially continuous views of community dynamics, focusing on stream fish affected by hydropower development. Location River Sabor, NE Portugal. Methods We sampled stream fish at thirty sites between 2012 and 2019. Community trajectory analysis was used to quantify the directionality and velocity of community change, and the geometric resemblance of community trajectories between sites. Geostatistical models for stream networks were used to relate metrics describing community dynamics to environmental variables, while controlling for Euclidean and hydrologic spatial dependencies, and to map spatial variation in community dynamics across the watershed. Results Trajectories in multivariate space underlined strong temporal dynamics, with local communities deviating and returning to previous states, but without evidence for directional changes. Accordingly, directionality values were low and not consistently affected by environmental variables. The velocity of community change varied markedly across the watershed and it was strongly affected by stream order and elevation, with faster changes observed in lowland streams draining into hydroelectric reservoirs and with a high proportion of exotic species. Pairwise distances between community trajectories were strongly related to hydrologic and environmental distances between sites. Main conclusions Local stream fish communities were in a loose equilibrium across the watershed, but they fluctuated at a faster rate closer to a hydroelectric reservoir. Integrating community trajectory analysis and geostatistical modelling provides a relatively simple framework to understand how, where and why temporal community dynamics vary across dendritic stream networks and to visualize spatial patterns of community change over time in relation to anthropogenic impacts.

Abstract Background Home-based palliative care (HPC) is considered to moderate the problem of rising healthcare utilization of cancer patients at end-of-life. Reports however suggest a proportion of HPC patients continue to experience high care intensity. Little is known about differential trajectories of healthcare utilization in patients on HPC. Thus, we aimed to uncover the heterogeneity of healthcare utilization trajectories in HPC patients and identify predictors of each utilization pattern. Methods This is a cohort study of adult cancer patients referred by Singapore Health Services to HCA Hospice Service who died between 1st January 2018 and 31st March 2020. We used patient-level data to capture predisposing, enabling, and need factors for healthcare utilization. Group-based multi-trajectory modelling was applied to identify trajectories for healthcare utilization based on the composite outcome of emergency department (ED) visits, hospitalization, and outpatient visits. Results A total of 1572 cancer patients received HPC (median age, 71 years; interquartile range, 62–80 years; 51.1% female). We found three distinct trajectory groups: group 1 (31.9% of cohort) with persistently low frequencies of healthcare utilization, group 2 (44.1%) with persistently high frequencies, and group 3 (24.0%) that begin with moderate frequencies, which dropped over the next 9 months before increasing in the last 3 months. Predisposing (age, advance care plan completion, and care preferences), enabling (no medical subsidy, primary decision maker), and need factors (cancer type, comorbidity burden and performance status) were significantly associated with group membership. High symptom needs increased ED visits and hospitalizations in all three groups (ED visits, group 1–3: incidence rate ratio [IRR] 1.74–6.85; hospitalizations, group 1–3: IRR 1.69–6.60). High home visit intensity reduced outpatient visits in all three groups (group 1–3 IRR 0.54–0.84), while it contributed to reduction of ED visits (IRR 0.40; 95% CI 0.25–0.62) and hospitalizations (IRR 0.37; 95% CI 0.24–0.58) in group 2. Conclusions This study on HPC patients highlights three healthcare utilization trajectories with implications for targeted interventions. Future efforts could include improving advance care plan completion, supporting care preferences in the community, proactive interventions among symptomatic high-risk patients, and stratification of home visit intensity.

Diesel engine railway traffic causes atmosphere pollution due to the exhaust emission which may be harmful to the passengers as well as workers. In this study, the air quality and PM 10 concentrations were evaluated around a railway station in Northeast India where trains are operated with diesel engines. The gaseous pollutant (e.g. SO 2 , NO 2 , and NH 3 ) was collected and measured by using ultraviolet–visible spectroscopy. The advanced level characterizations of the PM10 samples were carried out by using ion chromatography, Fourier-transform infrared, X-ray diffraction, inductively coupled plasma optical emission spectrometry , X-ray photoelectron spectroscopy, field-emission scanning electron microscopy with energy-dispersive spectroscopy, and high-resolution transmission electron microscopy with energy-dispersive spectroscopy techniques to know their possible environmental contaminants. High-performance liquid chromatography technique was used to determine the concentration of polycyclic aromatic hydrocarbons to estimate the possible atmospheric pollution level caused by the rail traffic in the enclosure. The average PM 10 concentration was found to be 262.11 µg m −3 (maximum 24 hour) which indicates poor air quality (AQI category) around the rail traffic. The statistical and air mass trajectory analysis was also done to know their mutual correlation and source apportionment. This study will modify traditional studies where only models are used to simulate the origins.

To achieve controlled stress grinding and controlled grinding of the depth of modificative layer, coupled analysis of grinding force and grinding heat is required. Therefore, this paper investigated grinding force and energy partition to lay a foundation for the coupled analysis. Firstly, a new grinding force model based on the analyses of grain trajectory and grain workpiece contact. In the modeling of grinding force, critical grain indention depths for plowing and cutting were calculated and the grinding force models of a single grain were established. This model can analyze the contributions of sliding, plowing, and cutting to total grinding forces. Secondly, an energy partition model was established based on the analyses of grain trajectory and grain workpiece contact. In the modeling of energy partition, the real contact area ratio and the grain contact radius were calculated. Finally, experiments were pursued to validate the grinding force model by comparing the experimental measurements to the theoretical results. Comparisons showed reasonable agreement quantitatively.

1. Sex differences in mortality are pervasive in vertebrates, and usually result in shorter life spans in the larger sex, although the underlying mechanisms are still unclear. On the other hand, differences in frailty among individuals (i.e. individual heterogeneity), can play a major role in shaping demographic trajectories in wild populations. The link between these two processes has seldom been explored. 2. We used Bayesian survival trajectory analysis to study age-specific mortality trajectories in the Eurasian sparrowhawk (Accipiter nisus), a monogamous raptor with reversed sexual size dimorphism. We tested the effect of individual heterogeneity on age-specific mortality, and the extent by which this heterogeneity was determined by average reproductive output and wing length as measures of an individual's frailty. 3. We found that sex differences in age-specific mortality were primarily driven by the differences in individual heterogeneity between the two sexes. Females were more heterogeneous than males in their level of frailty. Thus, a larger number of females with low frailty are able to survive to older ages than males, with life expectancy for the least frail adult females reaching up to 4·23 years, while for the least frail adult males it was of 2·68 years. 4. We found that 50% of this heterogeneity was determined by average reproductive output and wing length in both sexes. For both, individuals with high average reproductive output had also higher chances to survive. However, the effect of wing length was different between the two sexes. While larger females had higher survival, larger males had lower chances to survive. 5. Our results contribute a novel perspective to the ongoing debate about the mechanisms that drive sex differences in vital rates in vertebrates. Although we found that variables that relate to the cost of reproduction and sexual dimorphism are at least partially involved in determining these sex differences, it is through their effect on the level of frailty that they affect age patterns of mortality. Therefore, our results raise the possibility that observed differences in age-specific demographic rates may in fact be driven by differences in individual heterogeneity.