Miracle-dz/UniFAR-FTUs huggingface dataset:
Physical activity levels and body weight in a nationally representative sample in the European Union

Abstract Objectives The main objectives of this pan-European study were: (1) to identify different types of physical activity and the time devoted to them, (2) to assess physical activity/inactivity at work and in leisure time, and (3) to determine self-reported body weight and height. Design and subjects In each member state of the EU, approximately 1000 adults, aged 15 years or more, were selected to participate in an interview-assisted face-to-face questionnaire on physical activity and body weight. In each country, sample selection was quota-controlled to ensure national representativeness. Overall, 15 239 subjects in the EU completed the study. Results On average in the EU, nearly three-quarters of the population participate in some kind of activity. In general, the highest proportions of participants were found in the Nordic countries and the lowest in the southern ones. At the European level, the five most common activities include walking, gardening, cycling, keep fit and swimming. Higher participation rates were found among men, younger subjects and those with a higher level of education. The majority of Europeans fall within the normal body mass index (BMI) range but more than one-third are overweight (31%) or obese (10%) and 11% have a BMI below 20. Conclusions Several risk groups related to physical activity emerge from this survey: women, those with a lower level of education, older subjects, the overweight/obese and the underweight. Programmes to promote physical activity need to be tailored to the different groups identified in each country/region in order to increase adherence of non-participants and for the maintenance of those already engaged in activities.
High-Q RF inductors on standard silicon realized using wafer-level packaging techniques

Wafer level packaging (WLP) techniques have been used to integrate state of the art high Q on-chip inductors on top of a five-levels-of-metal (5LM) Cu damascene back-end of line (BEOL) silicon process using 20 /spl Omega/. cm Si wafers. The inductors are realized above passivation using thick post-processed low-K dielectric (BCB) and Cu layers. For a BCB/Cu-thickness of 16 /spl mu/m/10 /spl mu/m, a peak Q-factor of 34 at 4.3 GHz has been obtained for a 1 nH inductor (substrate contacts present at both ports) with a resonance frequency of 29 GHz; the Q-factor further tops 30 over the 2.1-5.4 GHz frequency range. If a substrate contact is present at only 1 port, Q/sub max/ increases to 38 at 4.7 GHz. Patterned polysilicon ground shields further improve this performance: a Q-factor increase of 90% is demonstrated at 7 GHz for a 2.25 nH inductor. A good agreement between measurements and 3-D simulations is demonstrated.
A Framework for Bus Trajectory Extraction and Missing Data Recovery for Data Sampled from the Internet

This paper presents a novel framework for trajectories’ extraction and missing data recovery for bus traveling data sampled from the Internet. The trajectory extraction procedure is composed of three main parts: trajectory clustering, trajectory cleaning and trajectory connecting. In the clustering procedure, we focus on feature construction and parameter selection for the fuzzy C-means clustering method. Following the clustering procedure, the trajectory cleaning algorithm is implemented based on a new introduced fuzzy connecting matrix, which evaluates the possibility of data belonging to the same trajectory and helps detect the anomalies in a ranked context-related order. Finally, the trajectory connecting algorithm is proposed to solve the issue that occurs in some cases when a route trajectory is incorrectly partitioned into several clusters. In the missing data recovery procedure, we developed the contextual linear interpolation for the cases of missing data occurring inside the trajectory and the median value interpolation for the cases of missing data outside the trajectory. Extensive experiments are conducted to demonstrate that the proposed framework offers a powerful ability to extract and recovery bus trajectories sampled from the Internet.
Phonocardiogram segmentation by using an hybrid RBF-HMM model

This paper is concerned to the segmentation of heart sounds by using Radial-Basis Functions for acoustical modelling, combined with a Hidden Markov Model for heart sounds sequence modelling. The idea behind the use of RBF's is to take advantage of the local approximations using exponentially decaying localized nonlinearities achieved by the Gaussian function, which increases the clustering power relatively to MLP's. This neural model can be advantageous over the global approximations to nonlinear input-output mappings provided by Multilayer Perceptrons (MLP's), especially when non-stationary processes need to be accurately modelled. The above described RBF's properties combined with the non-stationary statistical properties of Hidden Markov Models can help in the detection of the T-wave which is fundamental for the detection of the second heart sound. The feature vectors are based on a MFCC based representation obtained from a spectral normalisation procedure, which showed better performance than the MFCC representation alone, in an Isolated Speech Recognition framework. Experimental results were evaluated on data collected from five different subjects, using CardioLab system and a Dash family patient monitor. The ECG leads I, II and III and an electronic stethoscope signal were sampled at 977 samples per second.
Trust Management in Peer-to-Peer Networks

In recent years, various applications of Peer-to-Peer (P2P) computing have been widely used because of its unique advantages, which have play ed an important role in commerce, communications and other fields. The P2P system is essentially a distributed system, without central servers. Each peer is both client and server, who have the same status. However, some features of P2P networks, such as autonomy, dynamic, and heterogeneity lead to an important problem, namely unreliable quality of service. Unreliable quality of service is usually presented as providing false or unreliable service, impacting customer satisfaction. The establishment of trust models which evaluate s capabilities of peers can measure the service capacity of a peer, and identify malicious behavior, thereby reducing the risk of interaction and being an effective technique to ensure the overall availability of P2P networks. A trust model named METrust in P2P networks based on the recommendation is proposed. In METrust, a peer selects recommendation peers whose evaluation criteria are similar, and evaluation criteria of peers are determined through the AHP method (Analytic Hierarchy Process). Each peer in the network has a unique credibility of recommendation, and two trust parameters for updating the credibility of recommendation are introduced, namely updating range and updating strength. METrust proposes algorithms to compute the trust of peers. Simulations show that, the trust model METrust can identify malicious peers, and improve the quality of service in P2P networks effectively.
Mining Frequent Patterns with Screening ofNull Transactions Using Different Models

Frequent Pattern Mining plays an important role in the field of data mining community today. The concept of frequent pattern mining can be extended to dynamic databases and data streams. A data stream represents a massive input data that arrives at high speed and is unbounded. There are various data processing models in data streams. The challenge in frequent pattern mining is the presence of null transactions. Null transaction is a transaction that does not contain any itemset being examined. Most of the existing streaming algorithms did not consider the overhead of null transactions. Hence, they fail to discover the frequent patterns faster and occupy lot of memory space to represent frequent items. To overcome this issue, a new algorithm called Screening of Null Transactions-Frequent Pattern Mining over Data Streams (SNT-FPMoDS) has been proposed which extracts frequent patterns using landmark and sliding window models. Experimental results using real datasets on different models show that our proposed algorithm saves lot of computation time and memory.
Occurrence and Health-Risk Assessment of Trace Metals in Raw and Boiled Drinking Water from Rural Areas of China

In order to assess the exposure of rural residents to trace metals via drinking water ingestion, 222 drinking water samples of rural areas from 8 provinces in China were collected and 18 trace metals analyzed by inductively coupled plasma mass spectrometer (ICP-QMS). Based on metal concentrations, the health-risk assessment such as chronic daily intakes (CDI) and hazard quotient (HQ) were calculated. Results showed that most metals occurred in the drinking water at very low concentrations, indicating a general good quality, while the concentrations of As, Pb and Zn in some samples from Qinghai, Yunnan and Hunan provinces were higher than World Health Organization (WHO) and Chinese guidelines for drinking water. The values of CDI and HQ indicated a negligible health risk for most Chinese rural residents via drinking water. However, high concentrations of As in drinking water from Qinghai province would pose a serious risk to the local inhabitants. More attention and intensive study should be paid to Zn, Pb and As contents.
How can African agriculture adapt to climate change: Risk aversion in low-income countries: Experimental evidence from Ethiopia [in Amharic]

Agricultural production remains the main source of livelihood for rural communities in Sub-Saharan Africa, providing employment to more than 60 percent of the population and contributing about 30 percent of gross domestic product. With likely long-term changes in rainfall patterns and shifting temperature zones, climate change is expected to significantly affect agricultural production, which could be detrimental to the regionâ€™s food security and economic growth. An assessment of the factors influencing farm-level adaptation can facilitate the formation of policies and investment strategies that help moderate potential adverse consequences of long-term climate change. Because smallholder farmers tend to have a low capacity to adapt to changes in climatic conditions, policies that help these farmers adapt to global warming and associated climatic extremes are particularly important. This brief is based on a study that assesses smallholder farmersâ€™ adaptation to climate change in southern Africa. The study identifies farmersâ€™ perceptions of climate change and the determinants of farm- level adaptation strategies, and recommends policies that could help stabilize national and regional food production given the anticipated adverse effects of climate change. " from text
Exploring human mobility patterns using geo-tagged social media data at the group level

Abstract Exploring human mobility using social media data is an active research area related to many disciplines such as geography, urban planning and public health. We attempt to understand human mobility at the community level by analysing community mobility patterns across a significant time-span based on geo-tagged social media data. We take a typical college community, The Chinese University of Geosciences Wuhan (CUG Wuhan) community, as our research object. We identify more than 3757 CUG members with 81,059 geo-tagged Weibo messages in the period 2014–2015. We measure CUG group mobility patterns by analysing the spatio-temporal distribution of these messages and the activity patterns. We find that: (i) the students’ ‘active area’ in relation to their distance from CUG obeys a power-law distribution; (ii) heavy ‘check-in’ Weibo users do not, in fact, tend to be more active (in the physical world) than light ‘check-in’ Weibo users; (iii) mobility differences reflect gender differences.
Comparison of frequency of obesity in high risk non diabetic young individuals with low risk non diabetic young individuals.

OBJECTIVE To assess the body mass index and waist circumferences of high risk non diabetic young individuals and compare them with low risk non diabetic young individuals. METHOD A cross sectional, case control comparative study was conducted in the department of medicine, LUMHS from January 2008 to March 2009. Five hundred individuals 20-40 years of age were selected and divided into two groups i.e. Group A: high risk (250 individuals) and Group B: low risk (250 individuals) on the basis of same age and gender. Group A included those who had positive family history of type 2 DM in 1st degree relatives while group B had no family history of type 2 DM in 1st degree relatives. The blood pressure, BMI and Waist Circumference was measured and Fasting Blood Sugar was estimated in each individual. In each group 125 (50%) were males and 125 (50%) were females. RESULTS In group A 58% and in group B 28.8% individuals represented raised BMI whereas 42% in group A and 36% in group B individuals showed an increased waist circumference. Mean fasting blood glucose was significantly higher in Group A than in Group B (P = 0.001). CONCLUSION Impaired Fasting Glucose is strongly associated with family history of type 2 diabetes mellitus. Presence of obesity specially in high risk non-diabetic young individuals emphasize the need for routine health screening for early institution of preventive measures.
Improved outcomes for emergency department patients whose ambulance off-stretcher time is not delayed

To describe and compare characteristics and outcomes of patients who arrive by ambulance to the ED. We aimed to (i) compare patients with a delayed ambulance offload time (AOT) >30 min with those who were not delayed; and (ii) identify predictors of an ED length of stay (LOS) of >4 h for ambulance‐arriving patients.
Fouling detection based on analysis of ultrasonic guided waves using wavelet transform

Fouling detection is a relevant problem for chemical, oil, food and pharmaceutical industries. Fouling consists of the deposition of heavy organic materials and other dissolved solids or in suspension in fluid transport system. The ultrasonic guided waves present specific characteristics and have demonstrated good results in detection of flaws in pipelines. In this paper, the application of wavelet transform to analyze ultrasonic signals in order to detect fouling in pipelines is presented. A platform of tests has been used to emulate the fouling problem. The pipelines were used as a medium to guide ultrasonic waves and weekly measurements were used to observe the fouling process. The Daubechies 4 wavelet was applied to each measurement set. The results reveal that the variations of the energy-spectrum of the wavelet detail coefficients may provide an appropriate way to detect fouling, since it was observed that the increase of the fouling causes a notable reduction in the energy values.
Multimodal sensor fusion for attitude estimation of micromechanical flying insects: A geometric approach

In this paper, we study sensor fusion for the attitude estimation of micro aerial vehicles (MAVs), in particular mechanical flying insects. First, following a geometric approach, a dynamic observer is proposed which estimates attitude based on kinematic data available from different and redundant bio-inspired sensors such as halteres, ocelli, gravitometers, magnetic compass and light polarization compass. In particular, the traditional structure of complementary filters, suitable for multiple sensor fusion, is specialized to the Lie group of rigid body rotations SO(3). Then, a numerical implementation of the filter is provided for the specific case of inertial/magnetic navigation, i.e. when gravitometers, magnetometer and gyroscopes are available. Finally, the filter performance is experimentally tested via a 3 degrees-of-freedom robotic flapper and a custom-made set of inertial/magnetic sensors. Experimental results show good agreement, upon proper tuning of the filter, between the actual kinematics of the robotic flapper and the kinematics reconstructed from the inertial/magnetic sensors via the proposed filter.
Video artifacts for design: bridging the Gap between abstraction and detail

Video artifacts help bridge the gap between abstraction and detail in the design process. This paper describes how our use and re-use of video artifacts affected the re-design of a graphical editor for building, simulating, and analyzing Coloured Petri Nets. The two primary goals of the project were to create design abstractions that integrate recent advances in graphical interaction techniques and to explicitly support specific patterns of use of Petri nets in real-world settings. Using a participatory design process, we organized a series of video-based design activities that helped us manage the tension between finding useful design abstractions and specifying the details of the user interface. Video artifacts resulting from one activity became the basis for the next, facilitating communication among members of the multi-disciplinary design team. The video artifacts provided an efficient way of capturing and incorporating subtle aspects of Petri Nets In Use into our design and ensured that the implementation of our design principles was grounded in real-world work practices.
Multilevel multidimensional scaling on the GPU

We present Glimmer, a new multilevel visualization algorithm for multidimensional scaling designed to exploit modern graphics processing unit (GPU) hardware. We also present GPU-SF, a parallel, force-based subsystem used by Glimmer. Glimmer organizes input into a hierarchy of levels and recursively applies GPU-SF to combine and refine the levels. The multilevel nature of the algorithm helps avoid local minima while the GPU parallelism improves speed of computation. We propose a robust termination condition for GPU-SF based on a filtered approximation of the normalized stress function. We demonstrate the benefits of Glimmer in terms of speed, normalized stress, and visual quality against several previous algorithms for a range of synthetic and real benchmark datasets. We show that the performance of Glimmer on GPUs is substantially faster than a CPU implementation of the same algorithm. We also propose a novel texture paging strategy called distance paging for working with precomputed distance matrices too large to fit in texture memory.
Duration of lactation and incidence of type 2 diabetes.

CONTEXT Lactation is associated with improved glucose and insulin homeostasis, independent of weight change. OBJECTIVE To evaluate the association between lactation history and incidence of type 2 diabetes. DESIGN, SETTING, AND PARTICIPANTS Prospective observational cohort study of 83,585 parous women in the Nurses' Health Study (NHS) and retrospective observational cohort study of 73,418 parous women in the Nurses' Health Study II (NHS II). MAIN OUTCOME MEASURE Incident cases of type 2 diabetes mellitus. RESULTS In the NHS, 5145 cases of type 2 diabetes were diagnosed during 1,239,709 person-years of follow-up between 1986 and 2002, and in the NHS II, 1132 cases were diagnosed during 778,876 person-years of follow-up between 1989 and 2001. Among parous women, increasing duration of lactation was associated with a reduced risk of type 2 diabetes. For each additional year of lactation, women with a birth in the prior 15 years had a decrease in the risk of diabetes of 15% (95% confidence interval, 1%-27%) among NHS participants and of 14% (95% confidence interval, 7%-21%) among NHS II participants, controlling for current body mass index and other relevant risk factors for type 2 diabetes. CONCLUSIONS Longer duration of breastfeeding was associated with reduced incidence of type 2 diabetes in 2 large US cohorts of women. Lactation may reduce risk of type 2 diabetes in young and middle-aged women by improving glucose homeostasis.
DC-SIGN (CD209) Mediates Dengue Virus Infection of Human Dendritic Cells

Dengue virus is a single-stranded, enveloped RNA virus that productively infects human dendritic cells (DCs) primarily at the immature stage of their differentiation. We now find that all four serotypes of dengue use DC-SIGN (CD209), a C-type lectin, to infect dendritic cells. THP-1 cells become susceptible to dengue infection after transfection of DC-specific ICAM-3 grabbing nonintegrin (DC-SIGN), or its homologue L-SIGN, whereas the infection of dendritic cells is blocked by anti–DC-SIGN antibodies and not by antibodies to other molecules on these cells. Viruses produced by dendritic cells are infectious for DC-SIGN– and L-SIGN–bearing THP-1 cells and other permissive cell lines. Therefore, DC-SIGN may be considered as a new target for designing therapies that block dengue infection.
A pilot conceptualisation of the data space ecosystems for cultural heritage

The digital heritage sector is among the nine common European data spaces out- lined in the EU Data Act: Health, Industrial, Agriculture, Finance, Mobility, Green Deal, Energy, Public Administration, and Skills. The data space concept is complex, and being linked with the data ecosystem brings together methodologies and techniques from numerous domains: artiﬁcial intelligence (AI), text/data mining, data visualisation, mapping, image analysis, audio analysis, network analysis, and rights management. There is a need for clarifying data terminology in use for the GLAM ﬁeld and transferable methodology to strengthen its’ ongoing dataﬁcation and digital skill set. The paper oﬀers a comprehensive literature review (incl. EU Data (space) policy documents) on data spaces and data ecosystems aimed at (1) formulating the main challenges in data collection, data processing, and data maturity for heritage-related information systems and (2) justiﬁcation of the necessary mindset and digital skill set change for a mature museum. General conclusions are made as well as rec- ommendations for the Bulgarian GLAM sector.
Association of Methylenetetrahydrofolate Reductase Gene Polymorphism With Carotid Atherosclerosis Depending on Smoking Status in a Japanese General Population

Background and Purpose— The association of the methylenetetrahydrofolate reductase gene (MTHFR) with carotid atherosclerosis remains inconsistent. This may be due to small sample size and inappropriate analysis. We investigated the association of C677T/MTHFR with blood pressure and carotid atherosclerosis in a Japanese general population. Methods— Subjects (30 to 89 years of age; 1693 women, 1554 men) who gave informed consent were randomly selected from a general population in Suita, Japan. MTHFR genotypes were determined by TaqMan polymerase chain reaction. Carotid atherosclerosis was evaluated by high-resolution ultrasonography with atherosclerotic indexes of intimal-medial thickness (IMT), maximum IMT in the common carotid artery (CCA), plaque score, and stenosis (>50%). Results— Age-adjusted diastolic blood pressure was significantly higher in women with the TT genotype than in those with the CC genotype. In a recessive model (CC +CT versus TT), all adjusted odds ratios for hypertension and >50% stenosis in women were 1.42 and 3.42 (95% confidence intervals, 1.01 to 1.99 and 1.23 to 9.53), respectively. In women, maximum IMT in CCA for smokers with the TT genotype was significantly higher than for smokers with the CC genotype and nonsmokers with the TT genotype (P <0.05). Conclusions— Our study suggests that the MTHFR TT genotype is a risk factor for hypertension and carotid stenosis in women. Significant interactions between C677T/MTHFR and smoking on maximum IMT in CCA were observed in women but not in men. Smoking cessation for subjects with the TT genotype is important in the prevention of cerebrovascular disease.