Activity Monitoring System Research Articles

RECOGNITION OF HUMAN ACTIVITY BY VIDEO DATA

The paper considers the problem solution of classifying the type of physical activity of a person according to visual data. The authors propose using of deep neural networks to determine the type of activity. The recognizing human activity from video data or a single image systems are currently actively used in various areas of human activity. As the example we can take the system for monitoring the effectiveness of enterprise employees. So solving the problem of recognizing human actions from visual data is an actual task. The authors developed an algorithm for determining the physical activity type by visual data based on the DenseNet121 and MobileNetV2 models. Then the deep neural network model was built and hyperparameters were selected, because pre-trained networks did not provide the required accuracy of detecting the type of physical activity. The software implementation of the model is made in the IDLE environment in the Python programming language. Experimental studies performed on a specialized UCF50 dataset containing 50 different types of human actions confirm the effectiveness of using the proposed approach to solve the problem. Additionally, the representativeness of the test data set was increased with the help of video sequences obtained from YouTube.
 Purpose – development of an algorithm for determining a person’s physical activity based on visual data.
 Methodology: in the work the methods of computer vision, deep learning methods and object-oriented programming methods were used.
 Results: an algorithm for tracking a person’s physical activity based on visual data using deep learning technologies has been developed.
 Practical implications: the obtained results can be used in human activity monitoring systems, for example, in tracking criminal activity, in medical diagnostics, in tracking the activity of office employees, etc.

Screening of Discrete Wavelet Transform Parameters for the Denoising of Rolling Bearing Signals in Presence of Localised Defects

Maintenance scheduling is a fundamental element in industry, where excessive downtime can lead to considerable economic losses. Active monitoring systems of various components are ever more used, and rolling bearings can be identified as one of the primary causes of failure on production lines. Vibration signals extracted from bearings are affected by noise, which can make their nature unclear and the extraction and classification of features difficult. In recent years, the use of the discrete wavelet transform for denoising has been increasing, but studies in the literature that optimise all the parameters used in this process are lacking. In the current article, the authors present an algorithm to optimise the parameters required for denoising based on the discrete wavelet transform and thresholding. One-hundred sixty different configurations of the mother wavelet, threshold evaluation method, and threshold function are compared on the Case Western Reserve University database to obtain the best combination for bearing damage identification with an iterative method and are evaluated with tradeoff and kurtosis. The analysis results show that the best combination of parameters for denoising is dmey, rigrSURE, and the hard threshold. The signals were then distributed in a 2D plane for classification through an algorithm based on principal component analysis, which uses a preselection of features extracted in the time domain.

Simulation-Based Fault Detection Remote Monitoring System for Small-Scale Photovoltaic Systems

A small-scale grid-connected PV system that is easy to install and is inexpensive as a remote monitoring system may cause economic losses if its failure is not found and it is left unattended for a long time. Thus, in this study, we developed a low-cost fault detection remote monitoring system for small-scale grid-connected PV systems. This active monitoring system equipped with a simulation-based fault detection algorithm accurately predicts AC power under normal operating conditions and notifies its failure when the measured power is abnormally low. In order to lower the cost, we used a single board computer (SBC) with edge computing as a data server and designed a monitoring system using openHAB, an open-source software. Additionally, we used the Shewhart control chart as a fault detection criterion and the ratio between the measured and predicted ac power for the normal operation data as an observation. As a result of the verification test for the actual grid-connected PV system, it was confirmed that the developed remote monitoring system was able to accurately identify the system failures in real-time, such as open circuit, short circuit, partial shading, etc.

Vibration Analysis for Damage Detection in Composite Plate by using Piezoelectric Sensors

This study focuses on an active monitoring method for damage detection applied to composite structures. Different specimens made up of fiber epoxy resin in the form of composite structures are studied. Wavelet analysis methods are adopted to post process the raw monitored signal. A new damage signature is introduced to determine the presence and extent of damage in composites, while eliminating the influence of different distances between the active actuator and active monitoring elements. The proposed method is shown to be effective, reliable, and straightforward for the specimens considered in the present study, which are composed of different materials and suffer various levels of damage. An online real-time active monitoring system for damage detection is described that is based on this research.

Self-Sustaining Landslide Mitigation Strategy through Long-Term Monitoring

In mountain areas, anthropic pressure is growing while, concurrently, landslide frequency in most of the mountain regions of the world is increasing due to a more extreme precipitation pattern and permafrost deglaciation. Because of budget constraints, the need to investigate innovative and low-cost countermeasures for landslide risk is becoming more and more pressing. In this context, the Passo della Morte area (North-East Italy) is a perfect benchmark case. It comprises an extensive, long-term database of monitoring data that allows for testing hypotheses and validating them. Based on this data, a strong correlation between the velocity of a displacement of a landslide and the discharge of the Rio Verde stream was found. According to this evidence, local authorities have started the construction of a completely innovative mitigation strategy. It is focused on the triggering factor by identifying a significant component of the flow rate of the stream that cuts through the landslide. In addition, aiming to reduce the cost of construction and maintenance, this mitigation strategy is coupled with a micro-hydropower plant that can provide economic revenue by exploiting the discharge itself to produce electricity. Considering the active monitoring system that will be used to verify the effectiveness of the countermeasure, the Passo della Morte case study could become a starting point for implementing this pioneering and low-cost mitigation solution in similar morphologies.

Automated Physical Distance Estimation and Crowd Monitoring Through Surveillance Video.

The contagious Corona Virus (COVID-19) transmission can be reduced by following and maintaining physical distancing (also known as COVID-19 social distance). The World Health Organisation (WHO) recommends preventing COVID-19 from spreading in public areas. On the other hand, people may not be maintaining the required 2-m physical distance as a mandated safety precaution in shopping malls and public places. The spread of the fatal disease may be slowed by an active monitoring system suitable for identifying distances between people and alerting them. This paper introduced a deep learning-based system for automatically detecting physical distance using video from security cameras. The proposed system introduced the TH-YOLOv5 for object detection and classification and Deepsort for tracking the detected people using bounding boxes from the video. TH-YOLOv5 included another prediction head to identify objects of varying sizes. The original prediction heads are then replaced with Transformer Heads (TH) to investigate the prediction capability of the self-attention mechanism. Then, we include the convolutional block attention model (CBAM) to identify attention areas in settings with dense objects. Pairwise L2 vectorized normalization was utilized to generate a three-dimensional feature space for tracking physical distances and the violation index, determining the number of individuals who follow the distance rules. We use the MS COCO and HumanCrowd, CityPersons, and Oxford Town Centre (OTC) data sets for training and testing. Experimental results demonstrate that the proposed system obtained a weighted mAP score of 89.5% and an FPS score of 29; both are computationally comparable.

Design of Piezopolymer Interdigital Transducers with Scaled Electrode Geometries Based on FEM Analysis

The design of interdigital transducers (IDT) for active structural health monitoring (SHM) systems often requires a tuning of their characteristics for specific applications. IDTs are generally preferred for the selectivity of Lamb’s guided modes, but the directivity of the radiation pattern is a design parameter that is often difficult to customize for complex mechanical structures. This work proposes a comprehensive experimental study of the IDT with regular geometry, highlighting the dimensional parameters that can optimize the overall performance. From this study, a scaled electrode geometry emerged as a possible solution to shape the directivity diagram while maintaining the selectivity of the guided wave modes. This study based on FEM simulators led to a more versatile design of IDTs built with piezopolymer films of polyvinylidene fluoride (PVDF). The experimental validation showed the directivity diagrams and the ultrasonic guided mode selection were in very good agreement with the simulations. Another outcome of the investigation was the off axis propagation due to the contribution of the bus bars for connecting the IDT fingers to the excitation electronic circuit.

Genome Assessment of Carbapenem- and Colistin-Resistant Escherichia coli from Patients in a Sentinel Hospital in China.

Antimicrobial-resistant (AMR) pathogens are a significant threat to public health worldwide. However, the primary carrier of AMR genes, particularly against last-resort antibiotics, is still only partially studied in Chinese hospitals. In a sentinel hospital in China, we collected 157 E. coli strains from patients between January and July 2021. One blaNDM-1-, nine blaNDM-5-, and one mcr-1-positive E. coli recovered from inpatients were identified as resistant to meropenem and colistin. There are 37 virulence genes discovered in the 11 strains, including astA in strain EC21Z-147 (O128: H4), which belongs to the enteroaggregative E. coli (EAEC). The blaNDM gene is distributed into distinct ST types, including ST48, ST616, ST410, ST711, and ST2003, while the mcr-1 gene was identified in ST117. The conjugative plasmids IncX3, IncI1-I, and IncI2 mediated the blaNDM-5 and mcr-1 genes detected among inpatients. Notably, the youngest age at which mcr-1-positive E. coli has been reported was at one day old, in a child in which the strain is closely related to strains with animal origins. Hospitals are major environments for the spread and dissemination of critical virulence and AMR genes, which requires active monitoring systems at the genome level to surveil the spread of virulence and AMR.

The Role of Micro Gas Turbines in Energy Transition

In the progressively rising decentralized energy market, micro gas turbines (MGT) are seen with great potential owing to their low emissions, fuel flexibility, and low maintenance. The current transformation in the landscape of electricity supply with an increasing share of fluctuant renewable energy resources and increasing complexity requires a reliable and energy-efficient power generation source to support the grid. In this scenario, small-scale power plants that are constructed based on micro gas turbines with up to 250 kW power range can play a substantial role in meeting the challenges of the modern electricity grid. Micro gas turbines provide a reliable and cost-effective power source with a quick load-following ability which can respond to demand peaks and compensate for intermittent renewable sources when they are not available. MGT units can work as a system together with renewables, or function as a stand-alone unit in off-grid operations. The features of micro gas turbines are compatible with the energy transition that is the carbon-free modern energy grid. The technology underlying MGTs offer hybridization with renewable energy sources, flexibility in operations and type of fuel, and promising low emission solutions that align with environmental concerns. However, there is a continuous need to improve energy efficiency with a pressing urge for reducing emissions. This paper provides a review of micro gas turbines’ characteristics which promote their role in future power and heat generation systems. A brief overview of the challenges to improving operational flexibility, reliability, and availability of MGTs while maintaining low environmental impact and lowering the costs is presented. A model for an active monitoring and control system of the micro gas turbines is proposed which could improve the reliability of MGT operation in the grid by means of AI methods.

Infection prevention and control in tertiary care hospitals of Bangladesh: results from WHO infection prevention and control assessment framework (IPCAF)

IntroductionInfection prevention and control (IPC) in healthcare settings is imperative for the safety of patients as well as healthcare providers. To measure current IPC activities, resources, and gaps at the facility level, WHO has developed the Infection Prevention and Control Assessment Framework (IPCAF). This study aimed to assess the existing IPC level of selected tertiary care hospitals in Bangladesh during the COVID-19 pandemic using IPCAF to explore their strengths and deficits.MethodsBetween September and December 2020, we assessed 11 tertiary-care hospitals across Bangladesh. We collected the information from IPC focal person and/or hospital administrator from each hospital using the IPCAF assessment tool.. The score was calculated based on eight core components and was used to categorize the hospitals into four distinct IPC levels– Inadequate, Basic, Intermediate, and Advanced. Key performance metrics were summarized within and between hospitals.ResultsThe overall median IPCAF score was 355.0 (IQR: 252.5–397.5) out of 800. The majority (73%) of hospitals scored as ‘Basic’ IPC level, while only 18% of hospitals were categorized as ‘Intermediate’. Most hospitals had IPC guidelines as well as environments, materials and equipments. Although 64% of hospitals had IPC orientation and training program for new employees, only 30% of hospitals had regular IPC training program for the staff. None of the hospitals had an IPC surveillance system with standard surveillance case definitions to track HAIs. Around 90% of hospitals did not have an active IPC monitoring and audit system. Half of the hospitals had inadequate staffing considering the workload. Bed occupancy of one patient per bed in all units was found in 55% of hospitals. About 73% of hospitals had functional hand hygiene stations, but sufficient toilets were available in only 37% of hospitals.ConclusionThe majority of sampled tertiary care hospitals demonstrate inadequate IPC level to ensure the safety of healthcare workers, patients, and visitors. Quality improvement programs and feedback mechanisms should be implemented to strengthen all IPC core components, particularly IPC surveillance, monitoring, education, and training, to improve healthcare safety and resilience.

Anogenital distance is associated with postpartum estrous activity, intensity of estrous expression, ovulation, and progesterone concentrations in lactating Holstein cows.

The objectives of this retrospective observational study were to determine the associations of anogenital distance (AGD) with (a) postpartum estrous activity, (b) diameter of the preovulatory follicle, (c) intensity of estrous expression, (d) postestrus ovulation, (e) corpus luteum (CL) size, and (f) concentrations of progesterone at estrus and on d 7 after estrus. Lactating Holstein cows (n = 178; 55 primiparous, 123 multiparous) were enrolled into the study during the first postpartum week. All cows were continuously monitored by a pedometer-based automated activity monitoring (AAM) system for estrus. Postpartum estrous activity was assessed using the AAM estrus alerts, in which cows with at least one true estrus alert (i.e., a relative increase in steps from each cow's baseline detected by the AAM and the presence of at least one follicle >15 mm, a CL <20 mm, or no CL detected by ultrasound) by the first 50 d in milk (DIM) were considered to have commenced estrous activity. At the estrus alert >60 DIM, ovulation was determined by ultrasound at 24 h, 48 h, and 7 d after estrus, and blood samples were collected at estrus alert and on d 7 after estrus for progesterone analysis. The AGD was measured from the center of the anus to the base of the clitoris and classified as either short- or long-AGD using 2 cut-points of 148 mm (predictive of the probability of pregnancy to first insemination; short-AGD, n = 115; long-AGD, n = 63) and 142 mm (the median AGD; short-AGD, n = 90; long-AGD, n = 88). Regardless of the cut-point used, early postpartum estrous activity by 50 DIM (67 vs. 54%), duration of estrus (11.6 vs. 9.7 h), and preovulatory follicle diameter (20 vs. 19 mm) were greater in short-AGD than in long-AGD cows. Increased peak of activity at estrus in short-AGD cows (354 vs. 258% mean relative increase) was affected by an interaction between AGD and parity in which multiparous long-AGD cows had lesser relative increase in activity than primiparous cows (217 vs. 386%, respectively). Mean progesterone concentration at estrus was lesser in short-AGD (0.47 vs. 0.61 ng/mL) than in long-AGD cows. The ovulatory response at 24 h did not differ, but at 48 h (91 vs. 78%) and on d 7 after estrus (97 vs. 84%) it was greater in short-AGD cows. Although CL diameter on d 7 after estrus did not differ, short-AGD cows had greater progesterone concentration 7 d after estrus than long-AGD cows (4.1 vs. 3.2 ng/mL, respectively). In conclusion, greater proportions of short-AGD cows commenced estrous activity by 50 DIM, had larger preovulatory follicles, exhibited greater duration of estrus, had reduced progesterone concentration at estrus, had greater ovulation rates and progesterone concentration 7 d after estrus compared with long-AGD cows, with no difference in CL size between AGD groups. Because all the differences in physiological characteristics of short-AGD cows reported herein favor improved reproductive outcomes, we infer that these are factors contributing to improved fertility reported in short-AGD cows compared with long-AGD cows.

PSXIII-B-9 Effects of Hemp (Cannabis Sativa) Supplementation on Behavior, Heart Rate, Hemogram and Serum Biochemistry Profiles of Beef cow-Calf Pairs During Weaning

Abstract Weaning is a stressful event that affects animal welfare and performance. This study examined the effects of industrial hemp (Cannabis sativa) supplementation on behavior, chute score and physiological responses of cow-calf pairs during weaning. Ten apparently healthy Angus cow-calf pairs, average BCS of 6.0, were randomly allocated to one of two groups for 7 days: Control (CON, 200g/head of commercial grower feed, n=10) and Hemp (HMP, 200g/head containing 80% commercial grower feed containing 20% hemp, n=10), daily. Hay and water were provided ad libitum. Chute and exit scores were recorded and blood samples were collected at d 0, 4 and 7 of the feeding period. Animal activity data was recorded using automated activity monitoring systems Moomonitor and IceQubes for cows and calves, respectively. At weaning, cow-calf pairs were separated abruptly and observed. Data was analyzed using Stata 14.2. Overall, rectal temperature, respiratory rate, rumination duration, rumen fluid pH and activity did not differ (P &amp;gt; 0.05) between treatments. Specifically, hemogram and serum biochemistry results did not differ (P &amp;gt; 0.05) between cow groups. However, resting duration tended to be greater in HEMP compared with CON (383.94±19.3 vs 298.60±16.1 mins/day, P = 0.06) cows. In addition, feeding duration was greater in HEMP compared with CON (473.8±24.5 vs 262.3±31.6 min/day) cows. In calves, heart rate was lower in HEMP compared with CON (62.67 vs 94.7 beats/min, P = 0.03). Hemoglobin concentration was smaller in HEMP compared with CON (12.6 vs 14.1mg/mL, P = 0.02). However, mean corpuscular hemoglobin concentration was greater in HEMP compared with CON (33.04 vs 32.04g/dl, P = 0.04). We concluded that hemp supplementation increased resting and feeding duration of cows, and reduced heart rate of calves during weaning. This is the first report on the use of hemp to improve welfare of cow-calf pairs during weaning.

Prevalence of Yersinia pestis among rodents captured in a semi-arid tropical ecosystem of south-western Zimbabwe.

This study assessed the prevalence of plague bacterium (Yersinia pestis) among rodents captured in Umzingwane and Nkayi districts, south-western Zimbabwe. A total of 44 rodents were captured on three consecutive days per trapping session in the study sites using a removal trapping method in April 2018. Captured rodents were euthanized, and blood samples were collected. The Giemsa stain method was used to detect plague bacteria. The trapping success was not significantly different (χ² = 1.50, df = 1, P = 0.221), 8.5% for the Nkayi district, while in the Umzingwane district, it was 8%. Overall, only one rodent species, i.e., Mastomys natalensis, tested positive for Y. pestis in the Umzingwane district, thus yielding a prevalence rate of 2.3% for the entire study area. This was the most important finding of a Y. pestis-positive rodent in a non-endemic wild area in the Umzingwane district. These results point to a low prevalence of Y. pestis in the study area and the importance of an active plague disease surveillance and monitoring system.

Novel hypnotics of Japanese traditional herbal medicines to caffeine-induced insomnia in Drosophila by using Newly-developed automated sleep and rhythm analysis system (AutoCircaS)

Sleep in Drosophila was defined in the year 2000 by using Drosophila Activity Monitor (DAM) system. But DAM is very small tube space and one fly per tube is very limited to analyze for fly social behavior. To overcome such demerits of DAM system, we developed a novel automated sleep and rhythm analysis system (AutoCircaS) which monitors and records any behaviors like social mating, sleep, and circadian rhythm in flies (Drosophila) and small fishes medaka (Oryzias latipes) in free space using the time-lapse (one frame per 10 sec) imaging. AutoCircaS can detect the caffeine-induced insomnia in flies in light–dark (LD) and constant dark (DD) conditions. Thus, using the AutoCircaS, we discovered that Japanese traditional herbal medicines, KyushinKannouGan-ki (KKG), NouKassei (NK) as well as, and Sansoninto, significantly improved caffeine-induced insomnia in flies. The data suggest that AutoCircaS is useful for sleep analysis of small animals and screening of new sedative-hypnotics from many origins.

S08-2 Reproducibility and validity of four physical activity questionnaires in 18 European union member states: the European Union Physical Activity and Sport Monitoring System (EUPASMOS) project

BackgroundThe successful promotion of health-enhancing physical activity (HEPA) requires reliable and valid prevalence data of physical activity (PA) to enable the design, implementation and evaluation of effective and cost-effective policies. As part of the development of a new integrated monitoring framework in Europe, the reliability and validity of the Eurobarometer, European Health Interview Survey (EHIS), International Physical Activity Questionnaire (IPAQ) and Global Physical Activity Questionnaire (GPAQ) were studied in the ongoing European Union Physical Activity and Sport Monitoring System project (EUPASMOS) among 18 European Union member states.MethodsPhysical activity (PA) and sedentary behavior (SB) were assessed among 80-100 adults per member state using the four questionnaires and the UKK RM42 accelerometer. Participants completed the questionnaires in random order and wore the accelerometer seven consecutive days on their right hip (during the day) and on their non-dominant wrist (overnight). Time spent in moderate-to-vigorous intensity physical activity (MVPA), sedentary behavior and adherence to the WHO PA guidelines were calculated based on the 5 methods. The reproducibility and validity of the four questionnaires were tested by using the Spearman's correlation coefficient (ρ) or Cohen's kappa coefficient (κ), dependent of the outcome measure.ResultsPreliminary results from the Netherlands (N = 91) showed that the correlations for reproducibility of all four questionnaires varied between 0.51 and 0.63 for MVPA, between 0.30 and 0.60 for the WHO PA guidelines and between 0.65 and 0.82 for SB. All correlations were statically significant (p > 0.05). Significant correlations for validity of the questionnaires were found for MVPA (ρ = 0.22-0.43) and the WHO PA guidelines (ρ = 0.19-0.25). The only exception was the association between the EHIS questionnaire and the WHO PA guidelines. For SB, only GPAQ and the EHIS questionnaire showed significant associations (ρ = 0.31-0.32).ConclusionsFirst analyses of the Dutch data within the EUPASMOS project showed that the four commonly used questionnaires in Europe are fairly to strongly reliable methods depending on the outcome measure. The four questionnaires are fairly valid methods, except the Eurobarometer and IPAQ when examining SB. It is of interest to examine the quality of these questionnaires in all 18 member states for national and European policy makers.

S08-1 Comparing physical activity measurement instruments across member states by means of a conversion factor: European Union Physical Activity and Sport Monitoring System (EUPASMOS) project

BackgroundThe successful promotion of health-enhancing physical activity (HEPA) requires authoritative information to enable the design, implementation and evaluation of effective and cost-effective policies. This includes reliable and valid prevalence data of physical activity (PA) that can be compared across European Union Member States populations regardless of the type of measurement instrument used. In order to enable comparison of PA prevalence data between different measurement instruments, an attempt was made to develop a conversion factor between commonly used questionnaires in Europe and accelerometry in the ongoing European Union Physical Activity and Sport Monitoring System project (EUPASMOS) among 18 member states.MethodsData of physical activity (PA) and sedentary behavior (SB) were collected in 18 member states using four questionnaires (Eurobarometer, European Health Interview Survey, International Physical Activity Questionnaire and Global Physical Activity Questionnaire) and the UKK RM42 accelerometer. The number of measured participants varied between 100 and 1000 among the 18 member states. Participants completed the questionnaires in random order and wore the accelerometer seven consecutive days on their right hip (during the day) and on their non-dominant wrist (overnight). Time spent in moderate-to-vigorous intensity physical activity and sedentary behavior were calculated based on these 5 measurement instruments. The comparison between methods will be examined by using sophisticated regression analyses.ResultsThe EUPASMOS project is in progress and the final data is collected in the last two member states. In the meantime, a model is being developed to examine whether a conversion factor can be calculated to compare prevalence data based on questionnaires and accelerometry. By developing a conversion factor, prevalence data can be compared between member states although the measurement instruments used differ between member states. In June 2020 the results from these analyses are expected.ConclusionsThese results will provide insight into the possibility to compare prevalence data of physical activity among member states, when using different measurement instruments within their monitoring systems.

S08 Do results from physical activity questionnaires (IPAQ, GPAQ, EHIS and Eurobarometer) and accelerometer tell same story - results from 18 countries in the EUPASMOS project

Physical activity (PA) is associated with reduced risk of many noncommunicable diseases while a high volume of sedentary behavior (SB) is also considered to increase the risk of these diseases. Accurate measurement of both PA and SB is crucial for estimating these risk factors, and accelerometers together with standardized questionnaires are suggested a feasible way to measure these behaviors. However, collecting raw acceleration data of PA, SB and sleep in a standardized and similar way on a large scale has not been done before. In the European Union Physical Activity and Sport Monitoring System project (EUPASMOS), this has been done for the first time in 18 EU Member States.

S08-3 Physical activity, sedentary behavior and sleep-time of Eupasmos-project participants in 16 European countries: European Union Physical Activity and Sport Monitoring System (EUPASMOS) project

Abstract Background Increasing number of studies use device-based measurements to report levels of physical activity (PA) and sedentary behavior (SB) of populations. The studies have used different devices, device placements and analysis methods, and thus the comparison of the results between studies and populations is very challenging. The purpose of the present study was to present preliminary results of PA, SB and sleep-time measured with a similar method among adults of 16 European countries. Methods The study is based on the Eupasmos-project where PA, SB and sleep-time of the participants (n = 6674) were measured by a tri-axial accelerometer 24/7 (UKK RM42, UKK Terveyspalvelut Oy, Tampere, Finland). Accelerometer was worn on an elastic hip-band during waking-hours and on a wrist-band attached to a non-dominant wrist during bed-time (sleeping). PA-parameters were based on mean amplitude deviation (MAD) of acceleration analyzed in 1min exponential moving average (epoch length 6s). Assessment of SB (e.g. sitting and laying down) and standing were based on the angle for posture estimation (APE). Sleep measurement was based on the movement of a non-dominant wrist during bed-time. Parameters analyzed were total daily times and different bout lengths of SB, standing, light PA, moderate-to-vigorous PA, sleep and mean number of daily steps. Results The preliminary analysis included 47-1952 participants/country. In all countries participants spent most of their waking-hours sedentary. On weekdays the country-mean of SB varied from 8h18min to 10h7min. Participants took on average 6907-9716 steps/day. Light PA varied from 3h46min to 5h10min and moderate-to-vigorous PA from 45 to 78min. Participants wore the device on their wrist (sleeping-time) 6h42min-8h37min on weekdays. Although the total times of these behaviors were quite similar between the countries, the variation increased when different bout lengths were analyzed: the longer the bout length, the larger the variation. The hour-by-hour pattern of these behaviors varied a lot between the countries as well. Conclusions General pattern of SB, PA and sleep-time was quite similar in all countries, but the deeper analysis revealed clear differences. To be able to compare levels and patterns of these behaviors it is essential to use the exactly same method in all participating countries.

Infant feeding policies and monitoring systems: A qualitative study of European Countries.

Implementation of the Global Strategy for Infant and Young Child Feeding varies widely among countries. Policymakers would benefit from insights into obstacles and enablers. Our aim was to explore the processes behind the development and implementation of national infant and young child feeding policies and monitoring systems in Europe. A qualitative study design was employed to analyze open text responses from six European countries (Croatia, Germany, Lithuania, Spain, Turkey and Ukraine) using inductive thematic analysis. Countries were selected based on their World Breastfeeding Trends Initiative scores on national policy and monitoring systems. The 33‐item online questionnaire was distributed to country representatives and completed by country teams. Key enablers and strengths included strong and continuous government commitment to infant and young child feeding, an operational national breastfeeding authority, a national and active monitoring and evaluation system, implementation of the International Code of Marketing of Breastmilk Substitutes in national legislation, the integration of skilled breastfeeding supporters, the implementation of the Baby‐friendly Hospital Initiative, and positive cultural norms and traditions supporting optimal infant and young child feeding. In some countries, UNICEF played a key role in funding and designing policies and monitoring systems. Weak government leadership, the strong influence of the industry, lack of adequate national legislation on the International Code and cultural norms which devalued breastfeeding were particularly noted as obstacles. Government commitment, funding and protection of optimal infant and young child feeding are essential to the implementation of strong national policies and monitoring systems.

SleepMat: a new behavioral analysis software program for sleep and circadian rhythms.

To develop a new publicly available software SleepMat that analyzes Drosophila Activity Monitoring system data. The software is built on Matlab platform, employs an easy-to-use graphic user interface, and is highly flexible to customize data inputs. This software provides large number of sleep and circadian parameters including period, actogram, anticipation, sleep amount, bout length, bout number, activity, sleep deprivation, latency, lifespan, and eduction results. This software will enable a user-friendly high throughput analysis of a broad range of sleep and circadian parameters that can be coupled to the power of Drosophila genetics.