Miracle-dz/UniFAR-FTUs huggingface dataset:
Joint Uplink and Downlink Coverage Analysis of Cellular-based RF-powered IoT Network

Ambient radio frequency (RF) energy harvesting has emerged as a promising solution for powering small devices and sensors in massive Internet of Things (IoT) ecosystem due to its ubiquity and cost efficiency. In this paper, we study joint uplink and downlink coverage of cellular-based ambient RF energy harvesting IoT where the cellular network is assumed to be the only source of RF energy. We consider a time division-based approach for power and information transmission where each time-slot is partitioned into three sub-slots: 1) charging sub-slot during which the cellular base stations (BSs) act as RF chargers for the IoT devices, which then use the energy harvested in this sub-slot for information transmission and/or reception during the remaining two sub-slots; 2) downlink sub-slot during which the IoT device receives information from the associated BS; and 3) uplink sub-slot during which the IoT device transmits information to the associated BS. For this setup, we characterize the joint coverage probability, which is the joint probability of the events that the typical device harvests sufficient energy in the given time slot and is under both uplink and downlink signal-to-interference-plus-noise ratio (SINR) coverage with respect to its associated BS. This metric significantly generalizes the prior art on energy harvesting communications, which usually focused on downlink or uplink coverage separately. The key technical challenge is in handling the correlation between the amount of energy harvested in the charging sub-slot and the information signal quality (SINR) in the downlink and uplink sub-slots. Dominant BS-based approach is developed to derive tight approximation for this joint coverage probability. Several system design insights including comparison with regularly powered IoT network and throughput-optimal slot partitioning are also provided.
LiDo RDF: From a Relational Database to a Linked Data Graph of Linguistic Terms and Bibliographic Data

Forty years ago the linguist Dr. Christian Lehmann developed a framework for documenting linguistic terms, concepts and bibliographic data that resulted in the LiDo Terminological and Bibliographical Database (LiDo TBD). Since 2006 students and linguistic researchers beneﬁt from the data by looking it up on the Web. Even though, the LiDo TBD is implemented as a relational database, its underlying framework aims at yielding a terminological network containing data nodes that are connected via speciﬁc relation edges in order to create an interrelated data graph. Now, with the emergence of Semantic Web technologies we were able to implement this pioneering work by converting the LiDo TBD relational database into a Linked Data graph. In this paper we present and describe the creation of the LiDo RDF dataset and introduce the LiDo RDF project. The goals of this project are to enable the direct use and reuse of the data both for the scientiﬁc research community and machine processing alike as well as to enable a valuable enrichment of already existing linguistic terminological and bibliographic data by including LiDo RDF in the LLOD cloud.
Long reads: their purpose and place

Abstract In recent years long-read technologies have moved from being a niche and specialist field to a point of relative maturity likely to feature frequently in the genomic landscape. Analogous to next generation sequencing, the cost of sequencing using long-read technologies has materially dropped whilst the instrument throughput continues to increase. Together these changes present the prospect of sequencing large numbers of individuals with the aim of fully characterizing genomes at high resolution. In this article, we will endeavour to present an introduction to long-read technologies showing: what long reads are; how they are distinct from short reads; why long reads are useful and how they are being used. We will highlight the recent developments in this field, and the applications and potential of these technologies in medical research, and clinical diagnostics and therapeutics.
Awareness is related to reduced post‐stimulus alpha power: a no‐report inattentional blindness study

Delineating the neural correlates of sensory awareness is a key requirement for developing a neuroscientific understanding of consciousness. A neural signal that has been proposed as a key neural correlate of awareness is amplitude reduction of 8–14 Hz alpha oscillations. Alpha oscillations are also closely linked to processes of spatial attention, providing potential alternative explanations for past results associating alpha oscillations with awareness. We employed a no‐report inattentional blindness (IB) paradigm with electroencephalography to examine the association between awareness and the power of 8–14 Hz alpha oscillations. We asked whether the alpha‐power decrease commonly reported when stimuli are perceived is related to awareness, or other factors that commonly confound awareness investigations, specifically task‐relevance and visual salience. Two groups of participants performed a target discrimination task at fixation while irrelevant non‐salient shape probes were presented briefly in the left or right visual field. One group was explicitly informed of the peripheral probes at the commencement of the experiment (the control group), whereas the other was not told about the probes until halfway through the experiment (IB group). Consequently, the IB group remained unaware of the probes for the first half of the experiment. In all conditions in which participants were aware of the probes, there was an enhanced negativity in the event‐related potential (the visual awareness negativity). Furthermore, there was an extended contralateral alpha‐power decrease when the probes were perceived, which was not present when they failed to reach awareness. These results suggest alpha oscillations are intrinsically associated with awareness itself.
Relationship between fruit and vegetable intake and the risk of metabolic syndrome and its disorders in Korean women according to menopausal status.

BACKGROUND AND OBJECTIVES The association between fruit and vegetable (FV) intake and risk of the metabolic syndrome (MetS) has not been elucidated fully, particularly by menopausal status. Method and Study Design: The study population was 2,999 women aged 40-64 years participating in the 4th Korea National Health and Nutrition Examination Survey. The definition of MetS and its components was based on the modified National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) for Koreans. Dietary data were assessed by a 24-hour recall. RESULTS Fruit intake was inversely related only to the risk of high blood pressure (BP), but not MetS. Total vegetable consumption was inversely associated with the MetS risk, and when combined with fruits, the inverse association was observed even in its features of high triglycerides (TG) and low HDLcholesterol as well as MetS. Assessing women by menopausal status revealed that the inverse association with the MetS risk was found only in postmenopausal women having greater total vegetables and total FV intake (aOR=0.47, 95% CI=0.29-0.75, p-trend=0.003 and aOR=0.54, 95% CI=0.35-0.85, p-trend=0.007, respectively). Analysis regarding MetS features showed that while the inverse association of total vegetables or total FV intake was observed with high TG risk in postmenopausal women, fruits intake was inversely associated with high BP risk in premenopausal women (aOR=0.54, 95% CI=0.37-0.79, p-trend=0.004). CONCLUSION Results suggest that while fruit intake was inversely associated with high BP in premenopausal women, greater dietary intake of vegetables and total FV may protect against the risk of MetS, particularly in postmenopausal women.
NON-THERMAL ELECTRON ACCELERATION IN LOW MACH NUMBER COLLISIONLESS SHOCKS. I. PARTICLE ENERGY SPECTRA AND ACCELERATION MECHANISM

Electron acceleration to non-thermal energies in low Mach number (Ms ≲ 5) shocks is revealed by radio and X-ray observations of galaxy clusters and solar flares, but the electron acceleration mechanism remains poorly understood. Diffusive shock acceleration, also known as first-order Fermi acceleration, cannot be directly invoked to explain the acceleration of electrons. Rather, an additional mechanism is required to pre-accelerate the electrons from thermal to supra-thermal energies, so they can then participate in the Fermi process. In this work, we use two- and three-dimensional particle-in-cell plasma simulations to study electron acceleration in low Mach number shocks. We focus on the particle energy spectra and the acceleration mechanism in a reference run with Ms = 3 and a quasi-perpendicular pre-shock magnetic field. We find that about 15% of the electrons can be efficiently accelerated, forming a non-thermal power-law tail in the energy spectrum with a slope of p ≃ 2.4. Initially, thermal electrons are energized at the shock front via shock drift acceleration (SDA). The accelerated electrons are then reflected back upstream where their interaction with the incoming flow generates magnetic waves. In turn, the waves scatter the electrons propagating upstream back toward the shock for further energization via SDA. In summary, the self-generated waves allow for repeated cycles of SDA, similarly to a sustained Fermi-like process. This mechanism offers a natural solution to the conflict between the bright radio synchrotron emission observed from the outskirts of galaxy clusters and the low electron acceleration efficiency usually expected in low Mach number shocks.
Proposal of Network Generation Model based on Latent Preference Topic

People select whom to follow on social networking sites based on the topics that interest them. In this paper, we propose a new generation model for complex networks to mimic people's following behavior. In our proposed model, a node selects a target node to make a directed link based on the latent topic. We examine the features of the networks generated by our model through computer simulation. In the simulations, we calculate the average path length, clustering coefficient, and power exponent, which are representative evaluation indices of the network, and check whether they satisfy the properties of complex networks.
Bayesian calculation of region-specific F ST to detect local adaptation

To validate our approach and to compare it to alternative measurements, we performed extensive simulations using the MSMS program (Ewing and Hermisson 2010), an extension of Hudson's ms (Hudson 2002) that allows coalescent simulations for a structured population under selection. Based on an island model (background FST is identical between populations) and a divergence model (background pairwise FST differs between populations), we used MSMS to sample 950 loci under a neutral scenario and 50 loci under population-specific directional selection with a fixed number of segregating sites (s=20). We repeated the simulations with different recombination rates, start of selection, and varying background population history (different coalescent times). We also performed this analysis with variable mutation rates across the genome to show that BlockFeST is also appropriate for gene scans where the number of SNPs generally differ between loci (Suppl. Figure S2).
The effect of supervised Tai Chi intervention compared to a physiotherapy program on fall-related clinical outcomes: a randomized clinical trial

Purpose: To assess some fall-related clinical variables (balance, gait, fear of falling, functional autonomy, self-actualization and self-efficacy) that might explain the fact that supervised Tai Chi has a better impact on preventing falls compared to a conventional physiotherapy program. Methods: The participants (152 older adults over 65 who were admitted to a geriatric day hospital program) were randomly assigned to either a supervised Tai Chi group or the usual physiotherapy. The presence of the clinical variables related to falls was evaluated before the intervention (T1), immediately after (T2), and 12 months after the end of the intervention (T3). Results: Both exercise programs significantly improved fall-related outcomes but only the Tai Chi intervention group decreased the incidence of falls. For both groups, most variables followed the same pattern, i.e. showed significant improvement with the intervention between T1 and T2, and followed by a statistically significant decrease at the T3 evaluation. However, self-efficacy was the only variable that improved solely with the Tai Chi intervention (p = 0.001). Conclusions: The impact of supervised Tai Chi on fall prevention can not be explained by a differential effect on balance, gait and fear of falling. It appeared to be related to an increase of general self-efficacy, a phenomenon which is not seen in the conventional physiotherapy program. Implications for Rehabilitation Each participant received a multidisciplinary intervention with either Tai Chi or physical therapy. Both interventions were associated with improved balance, gait, less fear of falling, improved functional autonomy and greater self actualisation. Only Tai Chi decreased the incidence of falls which appeared to be related to self-efficacy. Tai Chi seems to be a good alternative to physical therapy exercises to prevent falls in frail older people.
Human Capital and Migration Costs for Romanian Economic Development

The migration of labor force is one of the most important vectors of the globalization process. This phenomenon is deeply analyzed in the economic theory, usually being debated form different points of view. As main directions, there are, on one hand, the classical studies that reveal the advantages of the receiving countries and the disadvantages of the home countries, and on the other hand, some recent studies that note the benefic effects for all those involved into the process of free movement of labor force. Placing Romania in the context of the European and global economy depends on the human capital stock that the country will succeed to create and maintain. The great mobility of the people makes a country's human capital stock volatile, correlated to the economic stability and to the welfare state. Yet, the volatility still rests lower than in the case of the financial capital. This is why we may assume that the investments in human capital are more stable and with a higher return than attracting foreign capitals. The human capital is a huge magnet for the foreign firms which decide to relocate their production according to the abundance of the high skilled labor force from a certain region. Consequently, it is not necessary to look for the foreign financial capital in order to bring it inside the economy because it will come by itself when there are favorable conditions for high profit. The high productivities, the low costs and the abundance of the specialists are favorable arguments for profit.
Distinct regulation of Snail in two muscle lineages of the ascidian embryo achieves temporal coordination of muscle development

ABSTRACT The transcriptional repressor Snail is required for proper differentiation of the tail muscle of ascidian tadpole larvae. Two muscle lineages (B5.1 and B6.4) contribute to the anterior tail muscle cells, and are consecutively separated from a transcriptionally quiescent germ cell lineage at the 16- and 32-cell stages. Concomitantly, cells of these lineages begin to express Tbx6.b (Tbx6-r.b) at the 16- and 32-cell stages, respectively. Meanwhile, Snail expression begins in these two lineages simultaneously at the 32-cell stage. Here, we show that Snail expression is regulated differently between these two lineages. In the B5.1 lineage, Snail was activated through Tbx6.b, which is activated by maternal factors, including Zic-r.a. In the B6.4 lineage, the MAPK pathway was cell-autonomously activated by a constitutively active form of Raf, enabling Zic-r.a to activate Snail independently of Tbx6.b. As a result, Snail begins to be expressed at the 32-cell stage simultaneously in these two lineages. Such shortcuts might be required for coordinating developmental programs in embryos in which cells become separated progressively from stem cells, including germline cells. Summary: Constitutively active Raf facilitates direct activation of Snail by Zic-r.a, providing a gene circuit shortcut that allows temporal coordination of cellular developmental programs of distinct somatic lineages.
Defence Expenditure and Economic Growth in Turkey and Greece : A Cointegration Analysis

Bu calisma Turkiye ve Yunanistan’daki savunma harcamalari ile ekonomik gelisme arasindaki iliskiyi incelemektedir. Turkiye ve Yunanistan NATO ulkeleri icinde savunma yuku en agir olan iki ulkedir. Bununla birlikte bu ampirik calismanin sonuclari gostermektedir ki, Turkiye ve Yunanistan’in savunma harcamalari, ekonomik buyumelerine zararli gorunmemektedir. Aksine ekonomik buyumelerine yardim etmektedir.
Enhancing Top-Down Classification Method with Metaclassification for Large-scale Dataset

Large-scale hierarchical classification has thousands of classes. The most commonly used method for multiclassification is one-versus rest, which is inappropriate due to computational complexity. So, Top down Method is used instead, but it is not perfect because of an error-propagation problem. The error-propagation means the document are wrongly rejected at higher level, it cannot passed down. Metaclassification Method solves error-propagation problem but it has higher complexity. To overcome this problem, enhancing top method is proposed which combines Top down and Metaclassification methods. It uses score of all base classifiers along root to leaf and checks whether predicted label is correct label or not.
Prevalence of physical inactivity in nine rural INDEPTH Health and Demographic Surveillance Systems in five Asian countries

Background: Physical inactivity leads to higher morbidity and mortality from chronic non-communicable diseases (NCDs) such as stroke and heart disease. In high income countries, studies have measured the population level of physical activity, but comparable data are lacking from most low and middle-income countries. Objective: To assess the level of physical inactivity and its associated factors in selected rural sites in five Asian countries. Methods: The multi-site cross-sectional study was conducted in nine rural Health and Demographic Surveillance System (HDSS) sites within the INDEPTH Network in Bangladesh, India, Indonesia, Thailand, and Vietnam. Using the methodology from the WHO STEPwise approach to Surveillance (STEPS), about 2,000 men and women aged 25–64 years were selected randomly from each HDSS sampling frame. Physical activity at work and during leisure time, and on travel to and from places, was measured using the Global Physical Activity Questionnaire version 2 (GPAQ2). The total activity was calculated as the sum of the time spent in each domain of activities in metabolic equivalent-minutes per week, and was used to determine the level of physical activity. Multivariable logistic regression was used to assess demographic factors associated with a low level of physical activity. Results: The prevalence of physical inactivity ranged from 13% in Chililab HDSS in Vietnam to 58% in Filabavi HDSS in Vietnam. The majority of men were physically active, except in the two sites in Vietnam. Most of the respondents walked or cycled for at least 10 minutes to get from place to place, with some exceptions in the HDSSs in Indonesia and Thailand. The majority of respondents, both men and women, were inactive during their leisure time. Women, older age, and high level of education were significantly associated with physical inactivity. Conclusion: This study showed that over 1/4 men and 1/3 women in Asian HDSSs within the INDEPTH Network are physically inactive. The wide fluctuations between the two HDSS in Vietnam offer an opportunity to explore further urbanisation and environmental impacts on physical activity. Considering the importance of physical activity in improving health and preventing chronic NCDs, efforts need to be made to promote physical activity particularly among women, older people, and high education groups in these settings.
Smart home user's behavior prediction

Modern Smart Home solutions can be generally classified as sensor-based or user-directive based. Prediction of the User Behavior is a very promising approach because it improves usability of Smart Home devices critical for their future expansion. It requires an effective enough, cheap, flexible, and easy implemented algorithms. Such “light” algorithms previously developed for predicting of TV viewer activities could be easily adapted for Smart Home devices programming.
Setting-up a European cross-provider data collection on open online courses

While MOOCS have emerged as a new form of open online education around the world, research is stilling lagging behind to come up with a sound theoretical basis that can cover the impact of socio-economic background variables, ICT competences, prior experiences and lifelong learning profile, variance in intentions, environmental influences, outcome expectations, learning experience and economic return on taking and completing Massive Open Online Courses (MOOCs). The potential diversity of participants of MOOCs has been taken as a starting point to develop a theoretical model and survey instrument with the goal to establish a large-scale, cross-provider data collection of participants of (European) MOOCs. This article provides and overview of the theoretical model begin the project and reflects about first experiences with the cross-provider data collection.
A digital predistortion method for multi-band aggregation

In this paper, a cascaded digital predistortion (DPD) model is proposed for the linearization of power amplifier under the excitation of multi-band aggregated signals. Compared with a single-structure predistorter, the proposed model has a more reliable and stable performance. It consists of two cascaded DPDs, which use indirect learning structure and polynomial inverse method respectively. And one of them concentrates on compensating the nonlinearity of power amplifiers (PAs), the other one on the memory effect of PA. Finally, by testing three sorts of multiband signals, this model is verified to have a superior performance.
A Deeply-Recursive Convolutional Network For Crowd Counting

The estimation of crowd count in images has a wide range of applications such as video surveillance, traffic monitoring, public safety and urban planning. Recently, the convolutional neural network (CNN) based approaches have been shown to be more effective in crowd counting than traditional methods that use handcrafted features. However, the existing CNN-based methods still suffer from large number of parameters and large storage space, which require high storage and computing resources and thus limit the real-world application. Consequently, we propose a deeply-recursive network (DR-ResNet) based on ResNet blocks for crowd counting. The recursive structure makes the network deeper while keeping the number of parameters unchanged, which enhances network capability to capture statistical regularities in the context of the crowd. Besides, we generate a new dataset from the video-monitoring data of Beijing bus station. Experimental results have demonstrated that proposed method outperforms most state-of-the-art methods with far less number of parameters.