Time Behavior Research Articles

First detection probability in quantum resetting via random projective measurements

We provide a general framework to compute the probability distribution of the first detection time of a ‘state of interest’ in a closed quantum system subjected to random projective measurements. In our ‘quantum resetting’ protocol, resetting of a state is not implemented by an additional classical stochastic move, but rather by the random projective measurement. We then apply this general framework to Poissonian measurement protocol with a constant rate r and demonstrate that exact results for can be obtained for a generic two level system. Interestingly, the result depends crucially on the detection schemes involved and we have studied two complementary schemes, where the state of interest either coincides or differs from the initial state. We show that at short times vanishes universally as as t → 0 in the first scheme, while it approaches a constant as t → 0 in the second scheme. The mean first detection time, as a function of the measurement rate r, also shows rather different behaviors in the two schemes. In the former, the mean detection time is a non-monotonic function of r with a single minimum at an optimal value , while in the later, it is a monotonically decreasing function of r, signaling the absence of a finite optimal value. These general predictions for arbitrary two level systems are then verified via explicit computation in the Jaynes–Cummings model of light–matter interaction. We also generalize our results to non-Poissonian measurement protocols with a renewal structure where the intervals between successive independent measurements are distributed via a general distribution and show that the short time behavior of is universal as long as . This universal t 2 law emerges from purely quantum dynamics that dominates at early times.

A comparative full-length transcriptomic resource provides insight into the perennial monocarpic mass flowering.

Perennial monocarpic mass flowering represents as a key developmental innovation in flowering time diversity in several biological and economical essential families, such as the woody bamboos and the shrubby Strobilanthes. However, molecular and genetic mechanisms underlying this important biodiversity remain poorly investigated. Here, we generated a full-length transcriptome resource incorporated into the BlueOmics database (http://blueomics.iflora.cn) for two Strobilanthes species, which feature contrasting flowering time behaviors. Using about 112 and 104 Gb Iso-seq reads together with ~185 and ~75 Gb strand-specific RNA seq data, we annotated 80 971 and 79 985 non-redundant full-length transcripts for the perennial polycarpic Strobilanthes tetrasperma and the perennial monocarpic Strobilanthes biocullata, respectively. In S. tetrasperma, we identified 8794 transcripts showing spatiotemporal expression in nine tissues. In leaves and shoot apical meristems at two developmental stages, 977 and 1121 transcripts were differentially accumulated in S. tetrasperma and S. biocullata, respectively. Interestingly, among the 33 transcription factors showing differential expression in S. tetrasperma but without differential expression in S.biocullata, three were involved potentially in the photoperiod and circadian-clock pathway of flowering time regulation (FAR1 RELATED SEQUENCE 12, FRS12; NUCLEAR FACTOR Y A1, NFYA1; PSEUDO-RESPONSE REGULATOR 5, PRR5), hence provides an important clue in deciphering the flowering diversity mechanisms. Our data serve as a key resource for further dissection of molecular and genetic mechanisms underpinning key biological innovations, here, the perennial monocarpic mass flowering.

Nonlinear WEC modeling using Sparse Identification of Nonlinear Dynamics (SINDy)

Modeling oscillating surge wave energy converter (OSWEC) systems to accurately predict their behavior has been a notoriously difficult challenge for the wave energy field. This is particularly challenging in realistic sea states where nonlinear WEC dynamics are common due to complex fluid-structure interaction, breaking waves, and other phenomena. Common modeling techniques for OSWECs include using potential flow theory to linearize the governing equations and ease computations, or using CFD to solve the full Navier-Stokes equations coupled with rigid body motion. However, both of these options have significant limitations. Potential flow theory breaks down in realistic sea conditions where nonlinear WEC dynamics are present, and CFD is often too computationally expensive for many applications such as real-time state prediction and optimal control, two areas of active research in the wave energy field. In particular, OSWEC dynamics are dominated by diffractive and viscous forces, often making common assumptions and linearization approximations (including small-body approximations) unreasonable, and CFD computationally intractable.
 To bridge this gap in modeling methods, we propose using Sparse Identification of Nonlinear Dynamics (SINDy) to build nonlinear reduced-order models (ROMs) that describe OSWEC behavior in response to large-amplitude regular waves. SINDy is an equation-free, data-driven algorithm that identifies dominant nonlinear functions present in system state dynamics using a library of nonlinear functions created from time series measurement data. The result is an ordinary differential equation (ODE) in time that can be solved from an initial condition to model and predict time behavior of the states. SINDy is parsimonious, meaning it uses a sparsity-promoting hyperparameter with the goal of only including the minimum number of terms to capture dominant dynamics, resulting in interpretable and generalizable results that are not overfit to the data. Using the discovered ROMs and integrating in time, not only can SINDy provide time series models and future state predictions of OSWEC dynamics, it can also give insights into which variables are critical in describing the underlying dynamics of the state. 
 In this study, we use SINDy to describe the nonlinear dynamics of a lab-scale OSWEC in a wave tank subjected to large-amplitude regular waves. We use nonlinear simulation data to generate kinematic, force, and torque data and use it as input to SINDy to identify ODEs that describe the measurement variables in time. We then integrate the ODEs to recreate the time series as well as predict future system behavior. We directly compare the resulting time series to the original data input to assess the accuracy of the SINDy model. We also interpret the dominant terms in the ODEs to gain insight on underlying mechanisms of the observed nonlinearity.
 Early results show SINDy is a promising tool for modeling nonlinear OSWEC dynamics. We are able to build ROMs for variables such as angular kinematics and the moment about the hinge that generate an accurate recreation of data measurements. We found strong dominance in cubic and quintic terms of the ROMs, suggesting higher-order nonlinearities in the system dynamics. These findings inspire future work in identifying underlying mechanisms driving nonlinearity.

Model Based Verification of Spiking Neural Networks in Cyber Physical Systems

Spiking Neural Networks (SNNs) have found increasing utility in designing safety-critical Cyber-Physical Systems (CPSs) such as implantable medical devices, autonomous vehicles, and space robotics due to their capability to operate on information represented in temporal coding and exhibit various behavioural modalities. Thus, there has been recent interest in formally verifying their timing behaviours and providing soundness guarantees of their diverse characteristics. However, beyond the simplistic Leaky Integrate and Fire (LIF) model, which only mimics 3 spiking behaviours, there is a lack of unifying methodology in literature to verify complex dynamics of biological neurons exhibiting 20 spiking behaviours as demonstrated by the pioneering work of Izhikevich. There is also a complete lack of formulation for the verification of SNN-based systems. This paper bridges these gaps by proposing a model-based approach for designing SNN-based controllers in CPS. We propose sound structural transformations translating any spiking neuron into networks of Timed Automata (TA), model the complex Izhikevich neural model and formally verify all 20 timing behaviours it exhibits for the first time. We then present two case studies that were modelled as SNNs using our approach: the PID controller, and the Car-Following controller, and subsequently attempt static model checking and statistical verification of their generated TA models for safety guarantees.

Tunneling time and Faraday/Kerr effects in systems

We review the generalization of tunneling time and anomalous behaviour of Faraday and Kerr rotation angles in parity and time systems. Similarities of two phenomena are discussed, both exhibit a phase transition-like anomalous behaviour in a certain range of model parameters. Anomalous behaviour of tunneling time and Faraday/Kerr angles in systems is caused by the motion of poles of scattering amplitudes in the energy/frequency complex plane.

How well do laboratory-derived estimates of time preference predict real-world behaviors? Comparisons to four benchmarks.

A large literature implicates time preference (i.e., how much an outcome retains value as it is delayed) as a predictor of a wide range of behaviors, because most behaviors involve sooner and delayed consequences. We aimed to provide the most comprehensive examination to date of how well laboratory-derived estimates of time preference relate to self-reports of 36 behaviors, ranging from retirement savings to flossing, in a test-rest design using a large sample (N = 1,308) and two waves of data collection separated by 4.5 months. Time preference is significantly-albeit modestly-associated with about half of the behaviors; this is true even when controlling for 15 other demographic variables and psychologically relevant scales. There is substantial variance in the strengths of associations that is not easily explained. Time preference's predictive validity falls in the middle of these 16 possible predictors. Finally, we ask time preference researchers (N = 55) to predict the variation in the relationship between time preference and behaviors, and although they are reasonably well-calibrated, these experts tend to overestimate the predictive power of time preference estimates. We discuss implications of invoking time preference as a predictor and/or determinant of behaviors with delayed consequences in light of our findings. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Experimental and theoretical investigation of adsorption and inhibition properties of 2-Amino-1,3,5-triazine-4,6-dithiol against corrosion in hydrochloric acid solution on mild steel

In this work, 2-Amino-1,3,5-triazine-4,6-dithiol (2-ATD) as novel and high efficiency corrosion inhibitor has been investigated for mild steel (MS) corrosion in 0.5 M HCl solution using electrochemical methods, scanning electron microscopy (SEM), energy disperse X-ray spectroscopy (EDX), atomic force microscopy (AFM) and quantum chemical calculation methods. Potentiodynamic polarization (PDP) curves indicate that 2-ATD is mixed type inhibitor, corrosion inhibition efficiency increased with increasing inhibitor concentration and reached its value of 96.5%. Evolution of exposure time versus corrosion behavior of 2-ATD is examined in corrosive medium. While corrosion potential (Ecorr) shifted more negative values, polarization resistances (Rp) decreased after 120 h exposure time due to the corrosion process. H2 volume is measured in uninhibited and inhibited solutions (10 mM 2-ATD) after 120 h exposure time. Very low volume (3.6 mL cm−2) of H2 is obtained on MS electrode in inhibited solution after 120 h of exposure, indicating that 2-ATD covers the entire surface against aggressive attack and retards the both anodic dissolution of MS and cathodic hydrogen evolution reactions. The adsorption process proposal is the Langmuir isotherm which is most suitable. Adsorption and thermodynamic parameters show that 2-ATD has a strong adsorption effect onto MS surface and includes mixed adsorption style (physical and chemical). Corrosion current density increases with increasing temperature and high activation energy (Ea) proves the strong adsorption of 2-ATD on the MS surface. Anti-corrosion mechanism of 2-ATD is described more detail with the potential of zero charge method. SEM, EDX and AFM analysis support the obtained results of electrochemical methods and confirm the existence of protective layer and strong adsorption of 2-ATD on the MS surface. Chronoamperometry test shows that current densities are almost constant whole experiment in the presence of organic film. Finally, quantum chemical calculation method of 2-ATD in blank solution is performed to investigate the active sites for possible attachment with MS surface.

How does temporal blurring alter movement timing?

Subjective uncertainty arises because the estimation of the timing of an event into the future is error prone. This impact of stimulus-bound uncertainty on movement preparation has often been investigated using reaction time tasks where a warning stimulus (WS) predicts the occurrence of a 'go' signal. The timing of the 'go' signal can be chosen from a particular probability distribution with a given variance or uncertainty. It has been repeatedly shown that reaction times covary with the shape of the used 'go' signal distribution. This is interpreted as evidence for temporal preparation. Moreover, the variance of the response time should always increase with the duration of the delay between the WS and the 'go' signal. This increasing variance has been interpreted as a consequence of the temporal 'blurring' of future events (scalar expectancy).The present paper tested the validity of the temporal 'blurring' hypothesis in humans with a simple oculomotor reaction time task where subjective and stimulus-bound uncertainties were increased. Subjective uncertainty about the timing of a 'go' signal was increased by lengthening the delay between the WS and the 'go' signal. Objective uncertainty was altered by increasing the variance of 'go' signal timing. Contrary to temporal blurring hypotheses, the study has shown that increasing the delay between events did not significantly increase movement timing variability. These results suggest that temporal blurring could not be a property of movement timing in an implicit timing context.Significance StatementIt is often assumed that the estimation of the timing of a distant future event is more error prone (or variable) than the estimation of a closer one. This phenomenon is referred to as temporal 'blurring'. Metaphorically, this could be compared in the spatial domain with the blurring of a visual stimulus when perceived at an increasing distance. Surprisingly, in the current oculomotor implicit timing task, movement variability actually decreased with the increasing temporal delay between a warning and an imperative 'go' signal. Therefore, temporal blurring is not a general property but depends on the precise context of timing behaviour.

Platinum Surface Oxide and Oxygen Reduction Reaction Kinetics during Transient Fuel Cell Operation

Pt surface oxide coverage (POC) and Oxygen Reduction Reaction (ORR) were measured under a range of operating conditions in a Proton Exchange Membrane Fuel Cell (PEMFC). Sensitivity analysis suggests that adsorption of sulfonate groups of the ionomer on the Pt surface plays an important role in POC and ORR kinetics. Although both Pt oxide growth and ORR activity decay follow a logarithm of time behavior, it is found that ORR kinetics are affected by at least two different types of Pt oxide. A semi-empirical ORR kinetic model is proposed taking into account the effect of ionomer and Pt oxide types. The model is capable of providing a quantitative prediction of POC and ORR activity over a range of potential, temperature, relative humidity, and time that is relevant to normal PEMFC operation.

Do Companies Consider Market Timing in Issuing Stock in Indonesia

The purpose of this research is to indicate equity market timing behavior on companies in Indonesia when those firms issued their share by using cumulative abnormal return as a proxy to predict market timing. Samples in this research are non-financial companies with seasonal or initial shares issued during 2014-2020 and listed on Indonesia Stock Exchange. The results of this study show that cumulative abnormal return before the shares are issued positively affects capital raised. In contrast, cumulative abnormal return after issuing shares negatively affects capital raised. This result shows that non-financial companies in Indonesia practice market timing behavior that can be indicated by using their stock's cumulative abnormal return.

Generic and Sensitive Anomaly Detection of Network Covert Timing Channels

Network covert timing channels can be maliciously used to exfiltrate secrets, coordinate attacks and propagate malwares, posing serious threats to cybersecurity. Current covert timing channels normally conduct small-volume transmission under the covers of various disguising techniques, making them hard to detect especially when a detector has little priori knowledge of their traffic features. In this paper, we propose a generic and sensitive detection approach, which can simultaneously (i) identify various types of channels without their traffic knowledge and (ii) maintain reasonable performance on small traffic samples. The basis of our approach is the finding that the short-term timing behavior of covert and legitimate traffic is significantly different from the perspective of inter-packet delays' variation. This phenomenon can be a generic reference to detect various channels because it is resistant to major channel disguising techniques which only mimic long-term traffic features, while it is also a sensitive reference to spot small-volume covert transmission since it can capture traffic anomalies in a fine-grained manner. To obtain the inner patterns of inter-packet delays' variation, we design a context-sensitive feature-extraction technique. This technique transforms each raw inter-packet delay into a discrete counterpart based on its contextual properties, thus extracting its variation features and reducing traffic data complexity. Then we learn legitimate variation patterns using a neural network model, and identify samples showing anomalous variation as covert. The experimental results show that our approach effectively detects all currently representative channels in the absence of their knowledge, presenting once to twice higher sensitivity than the state-of-the-art solutions.

Contribution to some aspects of the digestive tract anatomy and food evacuation of the Pacific fat sleeper Dormitator latrifrons

The development of feeding protocols and the study of gastric evacuation or passage of food through the digestive tract is essential to generate information on the digestive physiology of organisms, as they help to quantify the daily ration to avoid any poor diet. In this sense, the present work aims to demonstrate some basic aspects of the fish Dormitator latifrons digestive physiology by evaluating the transit of food through the intestinal tract as a function of time. In a completely randomized standard design, juveniles of D. latifrons were fed ad libitum with commercial pellets. Five conditioned organisms were sacrificed every hour after a single feeding. The food bolus was collected at each sampling point, using polynomial regression models to analyze the passage of food through time in the digestive tract. The passage of food showed a nonlinear behavior in time, being the simple exponential decay model of two parameters (R2 = 0.630; P < 0.0001) the best to explain the evacuation of food through the digestive tract. This knowledge will generate better feeding protocols for this species with commercial importance and aquaculture potential.

Using postural data and recurrent learning to monitor shoplifting activities in megastores

SummaryRecently, researchers have placed a great deal of emphasis on modeling activity patterns to better understand human behavior. Several approaches have been researched so far to develop automatic human activity recognition systems that infer detailed semantics from visual images, aiming to understand real human behavior patterns. However, there is still a need for a cost effective solution to distinguish human actions in the real‐world environment. With this encouragement, a novel approach is proposed to recognize shoplifting acts by examining the posture evidence of the human being. This approach begins by obtaining the two‐dimensional pose reflecting human's body joints as a skeleton from the recorded frames. Subsequently, a preprocessing step is used to preprocess skeleton data, which can handle the occlusion too. Postural feature generation is then used to extract pertinent features from such preprocessed skeletons. Finally, feature deduction is performed to downsize the derived features to a smaller dimension, and activity classification is performed on such reduced features to identify shoplifting behaviors in real time. A synthetic shoplifting dataset and real store recorded videos are used to conduct the experiments, the findings of which appear more promising than those obtained using other cutting‐edge methods, with an accuracy of 97.36% and 91.66% for synthesized and real store recorded inputs.

A Population-Based Analysis of the Temporal Association of Screen Time and Aggressive Behaviors in Adolescents

The recent widespread diffusion of screen-based devices among adolescents has raised questions about the effects of screen time on adolescent behavior, including aggressive behaviors. However, previous studies have been methodologically limited in their ability to distinguish between common vulnerability, concurrency, and lasting associations between screen time and aggression among adolescents, and findings are still inconsistent. To address this gap in the literature, time-varying direct and indirect associations between screen time and aggression were investigated. The sample included nearly 4,000 Canadian adolescents who participated in annual surveys for 5 consecutive years. Multilevel statistical models were applied to study between-person effects (common vulnerability), within-person effects (concurrency explaining a priming effect), and lagged-within-person effects (lasting effects explaining a learning process) of screen time (ie, social media use, television viewing, video game playing, computer use) on aggressive behaviors (ie, fighting, conduct problems, hostile thoughts). Screen time effects on aggression through hostility were further studied. Short-lived concurrent relations between different forms of screen time and aggressive behaviors suggested a priming effect. Social media use was further associated with longer lasting increases in conduct problems, suggesting a social learning process, while television viewing showed significant negative lagged-within-person association with hostility, showing a protective effect. Hostile thoughts mediated screen time and aggression associations mainly at between-person levels. The results suggest that the nature of the relation between screen time and aggressive behaviors depends on the type of digital platform through which such content is presented and suggest the need for policies focusing on protecting young users of digital media. Does Delaying Adolescent Substance Use Lead to Improved Cognitive Function and Reduce Risk for Addiction?; https://www.clinicaltrials.gov/: NCT01655615.

Анализ свойств региональных геодезических ГНСС-сетей, построенных относительным методом. Предельный случай

In this paper we continue to study the statistical properties of adjusted station coordinates in permanent geodetic networks. Analytical constructing the variance-covariance matrix of the measured vectors redundant set’s coordinates taking into account the covariances between vectors with common stations, is performed. The main attributes of this matrix are shown.Analytical modeling the adjustment of the measured vectors’ redundant set, which has such attributes, is performed. The variance-covariance matrix of the vector network’s adjusted coordinates is obtained and its properties are analyzed. It is shown that at using a simplified method for constructing such network, which neglects correlations between the errors of the measured baselines, the accuracy of its solution is overestimated, but the structure of the covariance matrix does not change. Analytical modeling of the network’s behavior in time is done, taking into account its possible internal dynamics, i.e. temporal changes of the geodetic stations’ relative positions that form it. It is shown that a dynamic vector solution has the same properties as the individual ones which make it, if they use redundant sets of measured vectors of the same type

Clustering of diet, physical activity and sedentary behaviour and related physical and mental health outcomes: a systematic review

BackgroundPhysical activity (PA), sedentary behaviour (SB) and diet play an important role in the physical and mental health of young people. Understanding how these behaviours cluster, and the impact of clusters on health is important for the development of public health interventions. This review examines the prevalence of clusters of PA, sedentary time, and dietary behaviours, and how clusters relate to physical and mental health indicators among children, adolescents and young adults.MethodsElectronic (PubMed, Web of Science and Scopus) and manual searches were conducted for articles that were (i) observational studies including children, adolescents and/or young adults aged 5–24 years, (ii) examined the 'patterning', ‘clustering’, or ‘co-existence’ of each of PA, dietary behaviour and SB, and (iii) published in English up to and including July 2022. In addition to information on clustering, data on physical and mental health outcomes were extracted where reported. Included studies were assessed using the Cochrane risk of bias for observational studies. A narrative synthesis was conducted due to high heterogeneity. This review was registered with PROSPERO (CRD42021230976).ResultsForty-nine cross-sectional studies and four prospective cohort studies from eighteen countries reporting data from 778,415 individual participants were included. A broad range of clusters (n = 172) were found (healthy, unhealthy, and mixed). Mixed clusters were common (n = 98), and clusters of high diet quality, low PA and high SB were more prevalent in girls, while mixed clusters of high PA, high SB and low diet quality were more prevalent in boys. Unhealthy clusters comprising low moderate to vigorous PA, low consumption of fruits and vegetables, and high screen time were prevalent, particularly in those from lower socioeconomic status families. Compared to those with healthy behavioural clusters, those with unhealthy and mixed clusters had a higher adiposity, higher risk of cardiovascular disease, poorer mental health scores, and lower cardiorespiratory fitness.ConclusionsPA, SB and diet cluster in healthy, unhealthy and mixed patterns in young people that differ across sociodemographic characteristics. Unhealthy clusters are associated with poorer health outcomes. Intervention strategies targeting un-clustering multiple unhealthy behaviours should be developed and evaluated for their impact on health outcomes.

Heritability of biting time behaviours in the major African malaria vector Anopheles arabiensis

BackgroundThe use of insecticide-treated nets for malaria control has been associated with shifts in mosquito vector feeding behaviour including earlier and outdoor biting on humans. The relative contribution of phenotypic plasticity and heritability to these behavioural shifts is unknown. Elucidation of the mechanisms behind these shifts is crucial for anticipating impacts on vector control.MethodsA novel portable semi-field system (PSFS) was used to experimentally measure heritability of biting time in the malaria vector Anopheles arabiensis in Tanzania. Wild An. arabiensis from hourly collections using the human landing catch (HLC) method were grouped into one of 3 categories based on their time of capture: early (18:00–21:00), mid (22:00–04:00), and late (05:00–07:00) biting, and placed in separate holding cages. Mosquitoes were then provided with a blood meal for egg production and formation of first filial generation (F1). The F1 generation of each biting time phenotype category was reared separately, and blood fed at the same time as their mothers were captured host-seeking. The resultant eggs were used to generate the F2 generation for use in heritability assays. Heritability was assessed by releasing F2 An. arabiensis into the PSFS, recording their biting time during a human landing catch and comparing it to that of their F0 grandmothers.ResultsIn PSFS assays, the biting time of F2 offspring (early: 18:00–21:00, mid: 22:00–04:00 or late: 05:00–07:00) was significantly positively associated with that of their wild-caught F0 grandmothers, corresponding to an estimated heritability of 0.110 (95% CI 0.003, 0.208). F2 from early-biting F0 were more likely to bite early than F2 from mid or late-biting F0. Similarly, the probability of biting late was higher in F2 derived from mid and late-biting F0 than from early-biting F0.ConclusionsDespite modest heritability, our results suggest that some of the variation in biting time is attributable to additive genetic variation. Selection can, therefore, act efficiently on mosquito biting times, highlighting the need for control methods that target early and outdoor biting mosquitoes.

Development and evaluation study of FLY-Kids: a new lifestyle screening tool for young children

Evaluating, discussing, and advising on young children’s lifestyles may contribute to timely modification of unhealthy behaviour and prevention of adverse health consequences. We aimed to develop and evaluate a new lifestyle screening tool for children aged 1–3 years. The lifestyle screening tool “FLY-Kids” was developed using data from lifestyle behaviour patterns of Dutch toddlers, age-specific lifestyle recommendations, target group analyses, and a Delphi process. Through 10 items, FLY-Kids generates a dashboard with an overview of the child’s lifestyle that can be used as conversation aid. FLY-Kids was completed by parents of children aged 1–3 years attending a regular youth healthcare appointment. Youth healthcare professionals (YHCP) then used the FLY-Kids dashboard to discuss lifestyle with the parents and provided tailored advice. Parents as well as YHCP evaluated the tool after use. Descriptive and correlation statistics were used to determine the usability, feasibility, and preliminary effect of FLY-Kids. Parents (N = 201) scored an average of 3.2 (out of 9, SD 1.6) unfavourable lifestyle behaviours in their children, while 3.0% complied with all recommendations. Most unfavourable behaviours were reported in unhealthy food intake and electronic screen time behaviour. Parents and YHCP regarded FLY-Kids as usable and feasible. The number of items identified by FLY-Kids as requiring attention was associated with the number of items discussed during the appointment (r = 0.47, p < 0.001). Conclusion: FLY-Kids can be used to identify unhealthy lifestyle behaviour in young children and guide the conversation about lifestyle in preventive healthcare settings. End-users rated FLY-Kids as helpful and user-friendly.What is Known:• A healthy lifestyle is important for optimal growth, development and overall health of young children (1-3 years).• Evaluating, discussing and advising on young children’s lifestyles may contribute to timely modification of unhealthy behaviour and prevention of adverse health consequences.What is New:• The new lifestyle screening tool FLY-Kids generates a dashboard with an overview of young children’s lifestyle that can be used as conversation aid between parents and youth healthcare professionals.• As parents and youth healthcare professionals rated FLY-Kids as helpful and user-friendly, and the number of items identified by FLY-Kids as requiring attention was associated with the number of items discussed during the appointment, FLY-Kids can be considered guiding the lifestyle discussion in preventive healthcare settings.

Global well-posedness of the Navier–Stokes equations in homogeneous Besov spaces on the half-space

Consider the Stokes equations in the half-space R+n, n≧2. It is shown that the negative of the Stokes operator defined on the homogeneous Besov space B˙p,q,σs(R+n) generates a bounded strongly continuous semigroup in B˙p,qs(R+n) provided that 1<p<∞, 1≦q<∞, and −1+1/p<s<1/p. As a by-product, the maximal Lq-regularity of the Stokes operator is obtained, admitting the limiting case q=1. This will be applied to develop the global well-posedness result for the incompressible Navier–Stokes equations in the maximal L1-regularity class provided that the initial data are small in B˙p,1−1+n/p(R+n) with n−1<p<∞. The dependence of the solution on initial data and the large time behavior of the solution are investigated.

Satellite uplink interference measurements in the 437 MHz UHF amateur radio band onboard LUME-1

Satellite operators struggle to communicate with their satellites over Europe in the UHF amateur band (430–440 MHz) due to high power in-orbit interference. Statistical characterisation of the interference beyond average interference levels using in-orbit measurements is useful for the design of suitable countermeasures. Some recent studies have started to investigate both the frequency and time behaviour of the interference, but more measurements are needed to cover the whole UHF amateur band. In this paper, we use the Local Mean Envelope (LME) method to analyse the time and frequency characteristics of in-orbit radio interference from the LUME-1 satellite, measured in the 437 MHz band. Satellite measurements were performed on a TOTEM Software-Defined Radio (SDR), in orbit over Europe and Antarctica and the results were downloaded for analysis on the ground. The average power spectrum and the variability of the LME for different time windows in the 437 MHz band are presented. The data analysis also includes the coefficient of variation of the LME to study the dispersion of the interference. The results are compared to previous measurements in the 435 MHz band using the same method. The new results are found to differ compared with previous measurements on the 435 MHz band. The bandwidth of the band-limited signals measured at 435 MHz was found to be 300 kHz, and at 437 MHz, 200 kHz wide for this dataset. Also, the interference power was found to be higher for 437 MHz. In both cases the interference behaviour is highly non-Gaussian, suggesting that typical communication countermeasures will not be sufficient. Although more measurements are needed for better spatial resolution, our findings may contribute to explaining why satellite operations are difficult on these bands. A better knowledge of the time and frequency variability of the interference can indicate which mitigation techniques are required and are efficient to improve satellite communication in that band.