Miracle-dz/UniFAR-FTUs huggingface dataset:
Phase-lags in large scale brain synchronization: Methodological considerations and in-silico analysis

Architecture of phase relationships among neural oscillations is central for their functional significance but has remained theoretically poorly understood. We use phenomenological model of delay-coupled oscillators with increasing degree of topological complexity to identify underlying principles by which the spatio-temporal structure of the brain governs the phase lags between oscillatory activity at distant regions. Phase relations and their regions of stability are derived and numerically confirmed for two oscillators and for networks with randomly distributed or clustered bimodal delays, as a first approximation for the brain structural connectivity. Besides in-phase, clustered delays can induce anti-phase synchronization for certain frequencies, while the sign of the lags is determined by the natural frequencies and by the inhomogeneous network interactions. For in-phase synchronization faster oscillators always phase lead, while stronger connected nodes lag behind the weaker during frequency depression, which consistently arises for in-silico results. If nodes are in anti-phase regime, then a distance π is added to the in-phase trends. The statistics of the phases is calculated from the phase locking values (PLV), as in many empirical studies, and we scrutinize the method’s impact. The choice of surrogates do not affects the mean of the observed phase lags, but higher significance levels that are generated by some surrogates, cause decreased variance and might fail to detect the generally weaker coherence of the interhemispheric links. These links are also affected by the non-stationary and intermittent synchronization, which causes multimodal phase lags that can be misleading if averaged. Taken together, the results describe quantitatively the impact of the spatio-temporal connectivity of the brain to the synchronization patterns between brain regions, and to uncover mechanisms through which the spatio-temporal structure of the brain renders phases to be distributed around 0 and π. Trial registration: South African Clinical Trials Register: http://www.sanctr. gov.za/SAClinicalbrnbspTrials/tabid/169/Default.aspx, then link to respiratory tract then link to tuberculosis, pulmonary; and TASK Applied Sciences Clinical Trials, AP-TB-201-16 (ALOPEXX): https://task.org. za/clinical-trials/.
Haematopoietic stem cell transplantation in systemic sclerosis

Abstract Three randomised controlled trials of haematopoietic stem cell transplantation (HSCT) in systemic sclerosis (SSc) demonstrated long-term survival benefits, induction of clinically meaningful, sustained improvement of forced vital capacity with improvements in skin thickening, vasculopathy and health-related quality of life, in contrast to a clinical decline in standard of care control groups. These benefits, however, must be weighed against the increased risk of transplant-related mortality. Further, with disease progression, severe extensive internal organ involvement and damage ensues, constituting an exclusion criterion for safety reasons, leaving a limited window whereby patients with SSc are eligible for HSCT. Although autologous HSCT offers the possibility of drug-free remission, relapse can occur, requiring re-initiation of disease modifying antirheumatic drugs. HSCT is also associated with secondary autoimmune diseases and gonadal failure. HSCT should be proposed for carefully selected patients with early rapidly progressive diffuse SSc whose clinical picture portends a poor prognosis for survival, but yet lacks advanced organ involvement.
PHASE RETRIEVAL FOR SIGNALS IN UNION OF SUBSPACES

We consider the phase retrieval problem for signals that belong to a union of subspaces. We assume that amplitude measurements of the signal of length n are observed after passing it through a random m × n supports M matrix1 We also assume that the signal belongs to the span of a single d-dimensional subspace out of R subspaces, where d ⩽ n. We assume the knowledge of all possible subspace, but the true subspace of the signal is unknown. We present an algorithm that jointly estimates the phase of the measurements and the subspace support of the signal. We discuss theoretical guarantees on the recovery of signals and present simulation results to demonstrate the empirical performance of our proposed algorithm. Our main result suggests that if properly initialized, then O(d + log R) random measurements are sufficient for phase retrieval if the unknown signal belongs to the union of R low-dimensional subspaces.
Distributed Triangle Detection via Expander Decomposition

We present improved distributed algorithms for triangle detection and its variants in the CONGEST model. We show that Triangle Detection, Counting, and Enumeration can be solved in $\tilde{O}(n^{1/2})$ rounds. In contrast, the previous state-of-the-art bounds for Triangle Detection and Enumeration were $\tilde{O}(n^{2/3})$ and $\tilde{O}(n^{3/4})$, respectively, due to Izumi and LeGall (PODC 2017). The main technical novelty in this work is a distributed graph partitioning algorithm. We show that in $\tilde{O}(n^{1-\delta})$ rounds we can partition the edge set of the network $G=(V,E)$ into three parts $E=E_m\cup E_s\cup E_r$ such that (a) Each connected component induced by $E_m$ has minimum degree $\Omega(n^\delta)$ and conductance $\Omega(1/\text{poly} \log(n))$. As a consequence the mixing time of a random walk within the component is $O(\text{poly} \log(n))$. (b) The subgraph induced by $E_s$ has arboricity at most $n^{\delta}$. (c) $|E_r| \leq |E|/6$. All of our algorithms are based on the following generic framework, which we believe is of interest beyond this work. Roughly, we deal with the set $E_s$ by an algorithm that is efficient for low-arboricity graphs, and deal with the set $E_r$ using recursive calls. For each connected component induced by $E_m$, we are able to simulate congested clique algorithms with small overhead by applying a routing algorithm due to Ghaffari, Kuhn, and Su (PODC 2017) for high conductance graphs.
Exploring the villus

The small intestinal villus and its associated epithelium includes enterocytes as the main cell type and differentiated goblet and argentaffin cells, while the invaginated crypt epithelium is the site of cell division and hence the origin of all epithelial components. Enterocytes form a cohesive monolayer which acts both as a permeability barrier between lumen and the interior, and an important gateway for nutrient digestion, absorption and transport. Differentiation and polarisation of enterocytes depends on cytoskeletal proteins that control cell shape and maintain functionally specialised membrane domains; extracellular matrix (ECM) receptors; channels and transporters regulating ion/solute transfer across the cell. The mesenchymally-derived basement membrane dynamically controls morphogenesis, cell differentiation and polarity, while also providing the structural basis for villi, crypts and the microvasculature of the lamina propria so that tissue morphology, crucially, is preserved in the absence of epithelium. Mucosal re-organisation requires immense cooperation between all elements within the lamina, including marked revisions of the microvasculature and extensive alterations to all basement membranes providing support for endodermal and mesenchymal components. In this context, subepithelial myofibroblasts fulfil important regulatory activities in terms of tissue morphogenesis; remodelling; control of epithelial cell development, polarity and functional attributes; and an intimate involvement in repair, inflammation and fibrosis. This paper reviews the main structural and functional aspects of the villus, including the epithelium and its outer glycocalyx and microvillous border; and subjacent to the epithelium, the basement membrane with its attached web of myo-fibroblasts together with the lamina propria core of the villi, and its microvasculature and lacteals. Finally, some comments on the rapidity with which the overall structure of the villi changes in their response to both external, and internal, influences.
The Evolution of Emotional Displays in Open Source Software Development Teams: An Individual Growth Curve Analysis

Software developers communicate and interact with each other in order to solve complex problems. Such communication often includes emotional displays that have been shown to influence team processes and performance. Yet, little is known about the evolution of team emotional displays. Hence, we investigate a sample of 1121 Open Source Software (OSS) projects from GitHub, using longitudinal data analysis. The results from growth curve analysis shows that the team emotional display decrease over time. This negative linear trend decelerates mid-term as suggested by a positive quadratic trend of time. Such deceleration diminishes toward the end as a negative cubic trend suggests.
Beyond Rehabilitation of Acuity, Ocular Alignment, and Binocularity in Infantile Strabismus

Infantile strabismus impairs the perception of all attributes of the visual scene. High spatial frequency components are no longer visible, leading to amblyopia. Binocularity is altered, leading to the loss of stereopsis. Spatial perception is impaired as well as detection of vertical orientation, the fastest movements, directions of movement, the highest contrasts and colors. Infantile strabismus also affects other vision-dependent processes such as control of postural stability. But presently, rehabilitative therapies for infantile strabismus by ophthalmologists, orthoptists and optometrists are restricted to preventing or curing amblyopia of the deviated eye, aligning the eyes and, whenever possible, preserving or restoring binocular vision during the critical period of development, i.e., before ~10 years of age. All the other impairments are thus ignored; whether they may recover after strabismus treatment even remains unknown. We argue here that medical and paramedical professionals may extend their present treatments of the perceptual losses associated with infantile strabismus. This hypothesis is based on findings from fundamental research on visual system organization of higher mammals in particular at the cortical level. In strabismic subjects (as in normal-seeing ones), information about all of the visual attributes converge, interact and are thus inter-dependent at multiple levels of encoding ranging from the single neuron to neuronal assemblies in visual cortex. Thus if the perception of one attribute is restored this may help to rehabilitate the perception of other attributes. Concomitantly, vision-dependent processes may also improve. This could occur spontaneously, but still should be assessed and validated. If not, medical and paramedical staff, in collaboration with neuroscientists, will have to break new ground in the field of therapies to help reorganize brain circuitry and promote more comprehensive functional recovery. Findings from fundamental research studies in both young and adult patients already support our hypothesis and are reviewed here. For example, presenting different contrasts to each eye of a strabismic patient during training sessions facilitates recovery of acuity in the amblyopic eye as well as of 3D perception. Recent data also demonstrate that visual recoveries in strabismic subjects improve postural stability. These findings form the basis for a roadmap for future research and clinical development to extend presently applied rehabilitative therapies for infantile strabismus.
The Impact of Age and Threshold Variation on Facial Recognition Algorithm Performance Using Images of Children

Facial recognition across ageing and in particular with images of children remains a challenging problem in a wide of range of operational settings. Yet, research examining algorithm performance with images of children is limited with minimal understanding of how age and age variation (i.e., age difference between images being compared) impacts on performance. Operationally, a fixed threshold based on images of adults may be used without considering that this could impact on performance with children. Threshold variation based on age and age variation may be a better approach when comparing images of children. This paper evaluates the performance of a commercial off-the-shelf (COTS) facial recognition algorithm to determine the impact that age (0–17 years) and age variation (0–10 years) has on a controlled operational dataset of facial images using both a fixed threshold and threshold variation approach. This evaluation shows that performance of children differs considerably across age and age variation, and in some operational settings, threshold variation may be beneficial for conducting facial recognition with children.
Quadrature Space-Frequency Index Modulation for Energy-Efficient 5G Wireless Communication Systems

This paper proposes a novel quadrature space-frequency index modulation (QSF-IM) scheme as a promising energy-efficient radio-access technology for the fifth generation (5G) wireless systems. Motivated by the potential energy saving of spatial modulation (SM) with the part of information being carried through antenna indexes, the proposed scheme further leverages the benefits of SM by applying the idea across the spatial and frequency domains. Moreover, by deploying dual antenna constellation for in-phase and quadrature-phase transmission, the proposed scheme can enhance data rate at no extra cost of energy consumption, leading to further improvement in energy efficiency. Theoretical bit error rate and achievable sum-rate of the proposed scheme over frequency-selective correlated Rician and Rayleigh fading channels are derived and are shown to have good agreement with simulations. Furthermore, the effectiveness of the proposed scheme is analyzed through a comprehensive list of performance metrics, including spectral efficiency (SE), energy efficiency (EE), cost efficiency (CE), and economic efficiency. Performance trade-offs between these metrics are thoroughly investigated. Compared with other existing schemes, the proposed QSF-IM scheme is demonstrated to offer better EE-SE and EE-CE tradeoffs, and can therefore be considered as a potential candidate for energy-spectral efficient 5G systems.
Effects of Voids on Mechanical and Thermal Properties of the Die Attach Solder Layer Used in High-Power LED Chip-Scale Packages

High-power light-emitting diode (LED) chip-scale packages (CSPs) prepared by the flip-chip technology have become one of the most promising light sources. The die attach solder layer always plays an important role in heat dissipation, mechanical support, and electronic conductivity. Among different types of solder materials, Sn-3.0Ag-0.5Cu (SAC305) solder alloy shows its great competitiveness on solderability and mechanical properties for the interconnection of high-power LED CSPs. However, reliability problems caused by voids in the SAC305 solder limit its wide application in the high-power LED chip-scale packaging process. Existence of the voids has been considered as one of the major issues causing chip-on-substrate level reliability problems in microelectronic and optoelectronic devices. In this paper, mechanical and thermal properties of SAC305 solder layers with arbitrary voids used in high-power LED CSPs are studied with both finite-element simulations and experiments. The results show that void size and void position within the solder layer are the two most critical issues on the shear strength of interconnection and the chip-on-substrate level thermal distribution in high-power LED CSPs.
Energy Efficiency of Access Control With Rate Constraints in Cognitive Radio Networks

In the next-generation cognitive radio networks, numerous secondary users will share the spectrum resource with the primary users. As it may not be possible to support all the communication rate requirements, there are many supporting sets for the secondary users as long as the communication rates of the primary users are guaranteed. In this paper, we study the maximum feasible set problem to access as many secondary users as possible, under the constraints of power budgets and communication rates in cognitive radio networks. In this interesting issue, the existing literature generally removes a subset of the secondary users so that the remaining users achieve the thresholds with communication rates and power budgets. However, the removal algorithms cause more interference when there are plenty of unsupported secondary users. We leverage the spectral radius of the network characteristic matrix as the admission price to access the new secondary user. Then, we design a hybrid access control algorithm to reduce the interference time and approximate the maximum network capacity. Moreover, different supported sets produce the different energy efficiency, even having the same network capacity, while all users require the high communication rates. Numerical results demonstrate that our algorithms provide the decent energy efficiency under the communication rate constraints.
Joint Resource Allocation for OFDM-Based Cognitive Two-Way Multiple AF Relays Networks With Imperfect Spectrum Sensing

In consideration of an orthogonal-frequency-division-multiplexing access cognitive two-way relay network with imperfect spectrum sensing, we propose a joint resource allocation algorithm to maximize the total transmission rate of secondary users (SUs) under maximum transmit power constraints and interference temperature constraints. To solve this joint optimization problem, we use the Lagrange dual decomposition method, discrete searching approach, and the Hungarian algorithm to obtain the optimal power allocation, the subcarrier pairing matrix, and the relay selection matrix. Moreover, the analyses of feasibility, sensitivity, convergence, and calculation complexity of the proposed algorithm are given. The effectiveness and validity of this algorithm with imperfect spectrum sensing are proved by the simulations of system performance and comparisons with the algorithm with perfect spectrum sensing. The results also indicate that our algorithm can provide protection for primary user (PU), while SUs and relays opportunistically access the spectrum occupied by PU.
Beam-On-Graph: Simultaneous Channel Estimation for mmWave MIMO Systems With Multiple Users

This paper is concerned with the channel estimation problem in multi-user millimeter wave wireless systems with large antenna arrays. We develop a novel simultaneous-estimation with iterative fountain training (SWIFT) framework, in which multiple users estimate their channels at the same time and the required number of channel measurements is adapted to various channel conditions of different users. To achieve this, we represent the beam direction estimation process by a graph, referred to as the beam-on-graph, and associate the channel estimation process with a code-on-graph decoding problem. Specifically, the base station (BS) and each user measure the channel with a series of random combinations of transmit/receive beamforming vectors until the channel estimate converges. As the proposed SWIFT does not adapt the BS’s beams to any single user, we are able to estimate all user channels, simultaneously. Simulation results show that SWIFT can significantly outperform the existing random beamforming-based approaches, which use a predetermined number of measurements, over a wide range of signal-to-noise ratios and channel coherence time. Furthermore, by utilizing the users’ order in terms of completing their channel estimation, our SWIFT framework can infer the sequence of users’ channel quality and perform effective user scheduling to achieve superior performance.
corseq: fast and efficient identification of favoured codons from next generation sequencing reads

Background Optimization of transgene expression can be achieved by designing coding sequences with the synonymous codon usage of genes which are highly expressed in the host organism. The identification of the so-called “favoured codons” generally requires the access to either the genome or the coding sequences and the availability of expression data. Results Here we describe corseq, a fast and reliable software for detecting the favoured codons directly from RNAseq data without prior knowledge of genomic sequence or gene annotation. The presented tool allows the inference of codons that are preferentially used in highly expressed genes while estimating the transcripts abundance by a new kmer based approach. corseq is implemented in Python and runs under any operating system. The software requires the Biopython 1.65 library (or later versions) and is available under the ‘GNU General Public License version 3’ at the project webpage https://sourceforge.net/projects/corseq/files. Conclusion corseq represents a faster and easy-to-use alternative for the detection of favoured codons in non model organisms.
Faster than Nyquist Transmission by Non-Orthogonal Time Division Multiplexing of Nyquist Sinc Sequences

One possibility to break down the capacity limit in optical transmission systems are higher spectral efficiencies, enabled by Faster-than-Nyquist signaling. Here we present the utilization of non-orthogonal time division multiplexing of sinc pulse sequences for this purpose. The mathematical expression, with a representation of the Nyquist sinc sequence by a cosine Fourier series and simulation results show that non-orthogonal time-division multiplexing increases the transmittable symbol rate by up to 25%.
Transcatheter Treatment of Bicuspid Aortic Valve Disease: Imaging and Interventional Considerations

Patients with bicuspid aortic valve disease have systematically been excluded from large randomized clinical trials investigating transcatheter aortic valve implantation (TAVI) due to their younger age, lower surgical risk and complex aortic anatomy. The asymmetric nature of the bicuspid valve orifice often accompanied by heavy regional calcification has led to concerns regarding valve positioning and expansion. Bicuspid aortic valve disease patients are at heightened risk of TAVI-related complications including coronary occlusion, aortic dissection and annular rupture, as well as the known risks of progressive aortopathy in these patients. These unique anatomical characteristics pose challenges for TAVI operators. However, with recent and ongoing refinements in implantation technique, improvements in pre-procedural imaging and iterations in device design, TAVI is emerging as a safe and feasible treatment option in this population. Paravalvular aortic regurgitation and high pacemaker rates have been the Achilles Heel for TAVI in bicuspid valve patients, yet newer generation devices are yielding promising results. Further studies are required before TAVI ultimately emerges as a viable option in low and intermediate surgical-risk patients with bicuspid valve disease. This review comprehensively summarizes the epidemiology, pathology and current evidence for TAVI in patients with bicuspid aortic valve disease. We also outline some practical tips for performing TAVI in these patients.
Automatic generation of ground truth for the evaluation of obstacle detection and tracking techniques

As automated vehicles are getting closer to becoming a reality, it will become mandatory to be able to characterise the performance of their obstacle detection systems. This validation process requires large amounts of ground-truth data, which is currently generated by manually annotation. In this paper, we propose a novel methodology to generate ground-truth kinematics datasets for specific objects in real-world scenes. Our procedure requires no annotation whatsoever, human intervention being limited to sensors calibration. We present the recording platform which was exploited to acquire the reference data and a detailed and thorough analytical study of the propagation of errors in our procedure. This allows us to provide detailed precision metrics for each and every data item in our datasets. Finally some visualisations of the acquired data are given.