Miracle-dz/UniFAR-FTUs huggingface dataset:
Competition as a structuring force in leaf miner communities

The role of competition in structuring communities of herbivorous insects is still debated. Despite this, few studies have simultaneously investigated the strength of various forms of competition and their effect on community composition. In this study, we examine the extent to which different types of competition will affect the presence and abundance of individual leaf miner species in local communities on oak trees Quercus robur. We first use a laboratory experiment to quantify the strength of intra- and interspecific competition. We then conduct a large-scale field experiment to determine whether competition occurring in one year extends to the next. Finally, we use observational field data to examine the extent to which mechanisms of competition uncovered in the two experiments actually reflect into patterns of co-occurrence in nature. In our experiment, we found direct competition at the leaf-level to be stronger among conspecific than among heterospecific individuals. Indirect competition among conspecifics lowered the survival and weight of larvae of T. ekebladella, both at the branch and the tree-level. In contrast, indirect competition among heterospecifics was only detected in one out of three species pairs examined. In the field experiment, the presence of a given moth species in one year affected the relative abundance of leaf miner species in the next year. Nevertheless, patterns of competition observed in these experiments did not translate into repulsion among free-ranging leaf miners: conspecific larvae of four leaf-mining species were aggregated on the same trees, shoots and leaves. In contrast, heterospecific larvae were only aggregated at the tree-level. We propose that despite the fact that leaf miners do compete and that such effects extend through time, the incidence and strength of competition is relatively small at realistic densities. Hence, competition will likely be of minor importance in shaping the distribution of leaf miners in a natural setting.
Large-Scale Mobile Fitness App Usage Analysis for Smart Health

Understanding essential factors that influence urban citizens' workout activities, both aerobic and training, is important for public policy development and city planning. Mobile fitness app usage data, which describes who works out at what time and place, provides a good opportunity to figure out these key factors that influence human workout activities. This article investigates the mobile fitness app usage data from more than 14,000 cellular towers and 4000 users. Based on solid analysis, we find that temporal factors, such as the day of the week and the time of day, affect human workout activities, while location is another key factor. In addition, mobility factors, such as moving range and regularity of mobility, also influence human workout activities. Finally, personal income is another fundamental factor that we find influences human workout activities.
Deubiquitylation and stabilization of p21 by USP11 is critical for cell-cycle progression and DNA damage responses

Significance Previous studies have demonstrated that p21 occupies a central position in cell-cycle regulation and DNA damage responses. As an unstable protein, the regulation of p21 stability has been extensively investigated over the past 20 years. Although p21 degradation by the ubiquitin-proteasome pathway has been well characterized, it is unclear whether ubiquitylated p21 can be recycled. Here, we identify USP11 as a deubiquitylase that directly removes p21 polyubiquitylation and stabilizes p21 protein, revealing that cellular p21 protein is finely regulated by a dynamic balance of USP11-mediated stabilization and proteasome-mediated degradation. Meanwhile, we also provide evidence that the USP11-p21 axis plays a crucial role in G1/S transition under physiological conditions and in regulating the balance between cytostasis and apoptosis. p21WAF1/CIP1 is a broad-acting cyclin-dependent kinase inhibitor. Its stability is essential for proper cell-cycle progression and cell fate decision. Ubiquitylation by the multiple E3 ubiquitin ligase complexes is the major regulatory mechanism of p21, which induces p21 degradation. However, it is unclear whether ubiquitylated p21 can be recycled. In this study, we report USP11 as a deubiquitylase of p21. In the nucleus, USP11 binds to p21, catalyzes the removal of polyubiquitin chains conjugated onto p21, and stabilizes p21 protein. As a result, USP11 reverses p21 polyubiquitylation and degradation mediated by SCFSKP2, CRL4CDT2, and APC/CCDC20 in a cell-cycle–independent manner. Loss of USP11 causes the destabilization of p21 and induces the G1/S transition in unperturbed cells. Furthermore, p21 accumulation mediated by DNA damage is completely abolished in cells depleted of USP11, which results in abrogation of the G2 checkpoint and induction of apoptosis. Functionally, USP11-mediated stabilization of p21 inhibits cell proliferation and tumorigenesis in vivo. These findings reveal an important mechanism by which p21 can be stabilized by direct deubiquitylation, and they pinpoint a crucial role of the USP11-p21 axis in regulating cell-cycle progression and DNA damage responses.
Use of Non‐Vitamin K Antagonist Oral Anticoagulants 2008–2016: A Danish Nationwide Cohort Study

We aimed to provide detailed utilization data on the total use of non‐vitamin K antagonist oral anticoagulants (NOACs) since their introduction in 2008. Using the nationwide Danish National Prescription Registry, we identified all individuals filling prescriptions for NOACs 2008–2016. We reported the development in incident and prevalent users and explored baseline characteristics and treatment persistence according to treatment indication. A total of 126,691 NOAC users were identified within the Danish population of 5.7 million inhabitants. The annual incidence and prevalence increased rapidly reaching 10 and 17 per 1000 individuals in 2016. Patients received NOACs due to atrial fibrillation (AF) (43%), venous thromboembolism (VTE) prophylaxis after arthroplastic surgery (17%), VTE (12%) and no registered indication (28%). The most frequently used NOAC was rivaroxaban (n = 52,431), followed by dabigatran (n = 47,067), apixaban (n = 27,116) and edoxaban (n = 77). The proportion of AF and VTE patients initiating low‐dose NOACs were between 23% and 50%. Patients treated with NOAC for VTE primarily received rivaroxaban. We observed a trend towards increased use of apixaban and rivaroxaban at the expense of dabigatran. Treatment persistence was highly dependent on treatment indication. Persistence to NOAC after 3 years was only 62% in AF compared to 28% for VTE. We documented an accelerating increase in the use of all four NOACs in the first 8 years after introduction. We have identified areas requiring further attention, including reasons for missing indications, potential inappropriate dosing and low long‐term persistence with NOACs in patients with AF.
Energy harvesting and computing enabled data broadcasting in mobile social networks

With the wide use of mobile phones, data broadcasting in mobile social networks benefits from the cooperative relaying among users. The performance of data broadcasting is often affected by 2 tough challenges, ie, inefficient data broadcasting caused by limited communication ranges of devices and intermittent network connectivity, and uncooperative data delivery as the energy cost for data broadcasting and algorithm computing. This paper explores the collaboration of communication, computing, and energy to improve the performance of data broadcasting and cope with the energy cost for communication and computation. We propose a data broadcasting scheme with the cooperation of communication and computing, which contains the relay selection and data dissemination algorithms. In the relay selection algorithm, social knowledge is exploited to measure user's capacity of data broadcasting, and the relay selection is formulated as a maximum weighted independent set problem. The data dissemination is integrated with algorithm computing by using edge computing among the relay nodes. Moreover, an energy allocation scheme under limited energy constrains is proposed to balance the energy consumed by data broadcasting and algorithm computing. With the aid of base station, we integrate radio frequency–based energy harvesting and beamforming technologies into mobile social networks. A Markov decision process–based energy transmission scheme is designed to supplement devices' energy capacity. Finally, simulation results indicate that the proposed schemes effectively improve the performance of data broadcasting and provide energy supplement for communication and computation.
A NOVEL APPROACH FOR MEASURING THERMAL CONDUCTIVITY OF ELECTRO-SPUN NANOFIBERS

The ability to replace metals, ceramics, and composites with polymer nanofibers can lead to more desirable applications in heat exchangers, energy storage, and biomedical fields. Research into thermal transport within polymer nanofibers has increased for such applications, with the need to develop new techniques to measure and understand such properties. Polymers with high thermal conductivity have been a growing asset in desired heat transfer devices. Much effort has gone into developing advanced thermal conductivity measurement techniques; however, there is still a lack of fundamental understanding between the relationship of structures and thermal transport properties in polymer nanofibers. The purpose of this thesis is to contribute to the further understanding of the thermal effects and conductivity capabilities of polymer nanofibers, and to supply a novel method of measurement to the research community.
Fluorescence as a biological feedback signal for energy optimising spectra for greenhouse LED-illumination

The introduction of LED-lighting for greenhouses has enabled new ways of controlling the light, both spectrum and intensity, to save energy and increase crop production. We have investigated a new method of automatically tuning the spectrum based on biological feedback. More specifically, we have performed experiments in order to evaluate if steady-state chlorophyll a fluorescence, measured at canopy level, can be a candidate signal to be used as feedback for spectrum optimisation. The experimental results show a strong correlation between fluorescence and photosynthetic rate, both in the case when one LED colour is used at a time, and under various background light. This indicates that fluorescence can indeed be used as an indirect measure of growth. Furthermore, we have investigated different methods of evaluating how much the different diodes in the armature enhance the fluorescence and short term photosynthetic rate. At different background light, one LED colour at a time was changed, and the consequent change in fluorescence was measured. We refer to the fluorescence gain, for the specific LED colour, as the change in fluorescence divided by the change in photon flux, caused by the specific LED colour. When comparing the fluorescence gains for the different LED colours, the mutual relation was constant for a given plant species, independent of the background light spectra. Hence, if implementing the suggested controller for a predefined intensity, aiming to find the optimal spectra for maximised plant growth, the controller will maximise the intensity input to the most efficient LED colour and minimise the intensity to all other LEDs. When evaluating the performance of the different LED colours, as a function of different intensity levels, changes were noticed in the mutual relations of the fluorescence gains. For cucumber, we found that when passing the light level where the photosynthesis saturate, no further changes in the mutual relation of the fluorescence gains were noticed. This opens up for using our method, i.e. comparing the fluorescence gains caused by excitation of light of different colours, to determine the light level where light saturation occurs.
Analog–Digital Beamforming in the MU-MISO Downlink by Use of Tunable Antenna Loads

We investigate the performance of multiuser multiple-input-single-output (MU-MISO) downlink in the presence of the mutual coupling effect at the transmitter. Contrary to traditional approaches that aim at eliminating this effect, in this paper we propose a joint analog–digital (AD) beamforming scheme that exploits this effect to further improve the system performance. A jointly optimal AD beamformer is first obtained by iteratively maximizing the minimum received signal-to-interference-plus-noise ratio in the digital domain, followed by an optimization on the load impedance of each antenna element in the analog domain. We further introduce a decoupled low-complexity approach, with which existing closed-form beamforming schemes can also be efficiently applied. For the consideration of hardware imperfections in practice, we study the case where the analog load values are quantized, and propose a sequential search scheme based on greedy algorithm to efficiently obtain the desired quantized load values. Moreover, we also investigate the imperfect channel state information (CSI) scenarios, where we prove the optimality for closed-form beamformers, and further propose the robust schemes for two typical CSI error models. Simulation results show that with the proposed schemes the mutual coupling effect can be exploited to further improve the performance for both perfect CSI and imperfect CSI.
Direct and Standard Injection of Sewage Sludge in a Supercritical Water Gasification System - Optimization of the Energy Efficiency Using Pinch Analysis

Supercritical Water Gasification is a promising technology to convert wet biomass into syngas. One of the challenges of this technology is the coke formation during heating-up of the wet biomass to its supercritical condition. Literature studies show that coke is the result of polymerization reactions that takes place at sub-critical conditions. It also states that a fast heat up of the wet biomass can minimize this unwanted coke formation. An option to achieve a fast heating rate is by direct injection of the relatively unheated wet biomass feed into supercritical water. Incomplete heating up of the wet biomass increases the waste heat in the product gas which will significantly reduce the energy efficiency. Parametric studies of some operating parameters are done to investigate the influence of this direct injection on the process performance. Results from this investigation show that a SCWG process with direct injection will have an efficiency reduction of approximately 7~16% in comparison to the standard (premixed) injection system. Using a feed with 8 wt% and 20 wt% dry matter at 600 °C and 25MPa, the thermal efficiencies of the system are 13.8 % and 65.5 respectively. Preliminary pinch analysis shows that these numbers can be improved to around 20 % and 70 %.
Performance optimization of ERP-based BCIs using dynamic stopping

Brain-computer interfaces based on event-related potentials face a trade-off between the speed and accuracy of the system, as both depend on the number of iterations. Increasing the number of iterations leads to a higher accuracy but reduces the speed of the system. This trade-off is generally dealt with by finding a fixed number of iterations that give a good result on the calibration data. We show here that this method is sub optimal and increases the performance significantly in only one out of five datasets. Several alternative methods have been described in literature, and we test the generalization of four of them. One method, called rank diff, significantly increased the performance over all datasets. These findings are important, as they show that 1) one should be cautious when reporting the potential performance of a BCI based on post-hoc offline performance curves and 2) simple methods are available that do boost performance.
NTUA-SLP at SemEval-2018 Task 2: Predicting Emojis using RNNs with Context-aware Attention

In this paper we present a deep-learning model that competed at SemEval-2018 Task 2 “Multilingual Emoji Prediction”. We participated in subtask A, in which we are called to predict the most likely associated emoji in English tweets. The proposed architecture relies on a Long Short-Term Memory network, augmented with an attention mechanism, that conditions the weight of each word, on a “context vector” which is taken as the aggregation of a tweet’s meaning. Moreover, we initialize the embedding layer of our model, with word2vec word embeddings, pretrained on a dataset of 550 million English tweets. Finally, our model does not rely on hand-crafted features or lexicons and is trained end-to-end with back-propagation. We ranked 2nd out of 48 teams.
Adaptive Noise Canceling using Convolved Reference Noise Based on Independent Component Analysis

This paper presents adaptive noise canceling(ANC) using convolved reference noise. In many practical ANC applications, the reference noise has channel distortion, which may degrade its performance. If the distortion includes nonminimum-phase parts, the inverse cannot be implemented as a causal filter. Therefore, the conventional ANC system may not provide a satisfactory performance. In this paper, we propose the delayed ANC system to deal with the problem, and derive learning rules for the adaptive FIR and IIR filter coefficients based on independent component analysis(ICA). Simulation results show that the proposed algorithms are adequate for the considered situations.
MLS Pressure Extrapolation for the Boundary Handling in Divergence-Free SPH

We propose a novel method to predict pressure values at boundary particles in incompressible divergence-free SPH simulations (DFSPH). Our approach employs Moving Least Squares (MLS) to predict the pressure at boundary particles. Therefore, MLS computes hyperplanes that approximate the pressure field at the interface between fluid and boundary particles. We compare this approach with two previous techniques. One previous technique mirrors the pressure from fluid to boundary particles. The other one extrapolates the pressure from fluid to boundary particles, but uses a gradient that is computed with Smoothed Particle Hydrodynamics (SPH). We motivate that gradient-based extrapolation is more accurate than mirroring. We further motivate that our proposed MLS gradient is less error prone than the SPH gradient at the boundary. In our experiments, we indicate artifacts in previous approaches. We show that these artifacts are significantly reduced with our approach resulting in simulation steps that can be twice as large compared to previous methods. We further present challenging and complex scenarios to illustrate the capabilities of the proposed boundary handling. CCS Concepts •Computing methodologies → Physical simulation; Massively parallel and high-performance simulations;
The negative feedback dysregulation effect: losses of motor control in response to negative feedback

ABSTRACT Negative feedback has paradoxical features to it. This form of feedback can have informational value under some circumstances, but it can also threaten the ego, potentially upsetting behaviour as a result. To investigate possible consequences of the latter type, two experiments (total N = 159) presented positive or negative feedback within a sequence-prediction task that could not be solved. Following feedback, participants had to control their behaviours as effectively as possible in a motor control task. Relative to positive feedback, negative feedback undermined control in a manner suggesting emotional upset (Experiment 1). These reactions lasted for at least three seconds and were especially pronounced among people reporting that they typically lose control in the context of their negative emotions (Experiment 2). The findings document a novel form of behavioural dysregulation that occurs in response to negative feedback while also highlighting the utility of motor control perspectives on self-control.
Dynamically Updatable Ternary Segmented Aging Bloom Filter for OpenFlow-Compliant Low-Power Packet Processing

OpenFlow, the main protocol for software-defined networking, requires large-sized rule tables and frequent updating. For fast packet processing, rule tables are often implemented with ternary content-addressable memory (TCAM) in the OpenFlow. To deal with TCAM power problems, many network applications employ bloom filters (BFs) to reduce the redundant operations of table-lookup and for low power consumption. However, applying traditional BFs to an OpenFlow switch leads to problems, such as unsupported dynamic update, large space overhead, and the rule-set expansion of ternary data. In this paper, we propose a dynamically updatable ternary segmented aging bloom filter (TSA-BF). The TSA-BF consists of two parts: a segmented aging BF algorithm (SA-BF) and a ternary prefix-tagging encoder (TPE). First, in the SA-BF, we develop an automatic update scheme using the mechanisms of content-aging and buffer-segmenting. The SA-BF ages and deletes its contents automatically, thus eliminating the costly communication overhead and enabling dynamic updating. It also achieves space efficiency by the developed partial-deletion mechanism. Second, in the TPE, we encode ternary prefix-rules into uniquely decodable binary code words. The TPE prevents the rule-set expansion of ternary-data in the OpenFlow environment. Simulation results show that the SA-BF alone can save 37% of space overhead, compared with state-of-the-art techniques. In an environment with the ternary prefix-rules, the TSA-BF can save another 93% of space overhead, compared with the best-performance scheme. Hence, the proposed TSA-BF is highly suited to the requirements of emerging high-performance TCAM-based packet processing in the OpenFlow, which considers dynamic update and power efficiency.
Performance of common spatial pattern under a smaller set of EEG electrodes in brain-computer interface on chronic stroke patients: A multi-session dataset study

Brain-computer interface (BCI) uses non-muscular channel of the nervous system for communication. Common Spatial Pattern (CSP) is a popular spatial filtering method used to reduce the effect of volume conduction on EEG signals. It is thought that CSP requires a large number of electrodes to be effective. Using a 20-session dataset of motor imagery BCI usage by 5 stroke patients, we demonstrated that after channel selection, CSP can still maintain a high accuracy with low number of electrodes using a newly proposed channel selection method called CSP-rank (higher than 90% with 8 electrodes). The results showed that using only the first session for channel selection, a high accuracy can be maintained in subsequent sessions. CSP-rank has been compared to the popular support vector machine recursive feature elimination (SVM-RFE). The results showed that the CSP-rank required less electrodes to maintain accuracy higher than 90% (a minimum of 8 compared to 12 of SVM-RFE) and it attained a higher maximum accuracy (91.7% compared with 90.7% of SVM-RFE). This could support clinicians to apply more BCI in routine rehabilitation.
Spatiotemporal estimation of activation times of fractionated ECGs on complex heart surfaces

Identification of electrical activation or depolarization times on sparsely-sampled complex heart surfaces is of importance to clinicians and researchers in cardiac electrophys-iology. We introduce a spatiotemporal approach for activation time estimation which combines prior results using spatial and temporal methods with our own progress on gradient estimation on triangulated surfaces. Results of the method applied to simulated and canine heart data suggest that improvements are possible using this novel combined approach.