Miracle-dz/UniFAR-FTUs huggingface dataset:
A homozygous missense variant in VWA2, encoding an interactor of the Fraser-complex, in a patient with vesicoureteral reflux

Congenital anomalies of the kidney and urinary tract (CAKUT) are the most common cause (40–50%) of chronic kidney disease (CKD) in children. About 40 monogenic causes of CAKUT have so far been discovered. To date less than 20% of CAKUT cases can be explained by mutations in these 40 genes. To identify additional monogenic causes of CAKUT, we performed whole exome sequencing (WES) and homozygosity mapping (HM) in a patient with CAKUT from Indian origin and consanguineous descent. We identified a homozygous missense mutation (c.1336C>T, p.Arg446Cys) in the gene Von Willebrand factor A domain containing 2 (VWA2). With immunohistochemistry studies on kidneys of newborn (P1) mice, we show that Vwa2 and Fraser extracellular matrix complex subunit 1 (Fras1) co-localize in the nephrogenic zone of the renal cortex. We identified a pronounced expression of Vwa2 in the basement membrane of the ureteric bud (UB) and derivatives of the metanephric mesenchyme (MM). By applying in vitro assays, we demonstrate that the Arg446Cys mutation decreases translocation of monomeric VWA2 protein and increases translocation of aggregated VWA2 protein into the extracellular space. This is potentially due to the additional, unpaired cysteine residue in the mutated protein that is used for intermolecular disulfide bond formation. VWA2 is a known, direct interactor of FRAS1 of the Fraser-Complex (FC). FC-encoding genes and interacting proteins have previously been implicated in the pathogenesis of syndromic and/or isolated CAKUT phenotypes in humans. VWA2 therefore constitutes a very strong candidate in the search for novel CAKUT-causing genes. Our results from in vitro experiments indicate a dose-dependent neomorphic effect of the Arg446Cys homozygous mutation in VWA2.
Cytotoxic effect of Efavirenz in BxPC-3 pancreatic cancer cells is based on oxidative stress and is synergistic with ionizing radiation

The non-nucleoside reverse transcriptase inhibitor (NNRTI) Efavirenz is frequently used in human immunodeficiency virus treatment, but also efficient against cancer in mouse models. Its radiosensitizing effect makes it a promising drug for combination with radiotherapy. The efficacy of Efavirenz combined with irradiation was assessed with immunostaining of DNA-damage markers and colony formation assays in BxPC-3 pancreatic cancer cells. Gene expression and protein phosphorylation of the Efavirenz-sensitive BxPC-3 cells was compared to the resistant primary fibroblasts SBL-5. Oxidative stress, mitochondrial damage and cell death were studied with live-cell microscopy and flow cytometry. Combined Efavirenz and radiation significantly increased the number of γH2AX and phospho-ataxia telangiectasia mutated foci. Efavirenz and ionizing radiation had a synergistic effect using the clonogenic survival assay. Efavirenz selectively induced cell death in the BxPC-3 cells. The differing gene expression of cell cycle and apoptotic regulator genes in both cell cultures after Efavirenz treatment match with this selective effect against cancer cells. In the phosphoprotein array, an early phosphorylation of extracellular signal-related kinase 1/2 and p38 mitogen-activated protein kinase was notably detected in the cancer cells. The phosphorylation of AKT decreased in the cancer cells whereas it increased in the fibroblasts. Oxidative stress and mitochondrial membrane depolarization appeared in the cancer cells immediately after Efavirenz treatment, but not in the fibroblasts. Efavirenz has an anti-cancer effect against pancreatic cancer mainly by the induction of oxidative stress. The antitumor potential of Efavirenz and radiotherapy are additive.
Energy-efficiency resource allocation for cognitive heterogeneous networks with imperfect channel state information

In this study, the authors focus on the downlink resource allocation to optimise energy-efficiency (EE) of orthogonal frequency division multiplexing-based cognitive heterogeneous network (HetNet), where network service providers operate multi-radio access technologies. A more practical case is considered, in which imperfect channel state information (CSI) is available for wireless channels between secondary base stations and secondary users (SUs), primary users (PUs). Since imperfect CSI may result in outage in secondary networks and make collision occur in primary networks, a joint subcarrier and power allocation scheme for the cognitive HetNet is proposed to guarantee quality of service requirements for both SUs and PUs in probabilistic manners. Then the probabilistic EE optimisation scheme is approximated into a deterministic convex form, and the optimal solutions for the scheme are derived by double-loop iteration method. Afterwards, the authors develop a low-complexity algorithm in the presence of imperfect CSI with a small reduction of system performance. Simulation results are provided to show the impact of channel estimation error on the EE optimisation problem and to highlight the performance improvement from considering channel estimation error in the joint subcarrier and power allocation scheme for the cognitive HetNet system.
Reinforcement Learning from Imperfect Demonstrations

Robust real-world learning should benefit from both demonstrations and interactions with the environment. Current approaches to learning from demonstration and reward perform supervised learning on expert demonstration data and use reinforcement learning to further improve performance based on the reward received from the environment. These tasks have divergent losses which are difficult to jointly optimize and such methods can be very sensitive to noisy demonstrations. We propose a unified reinforcement learning algorithm, Normalized Actor-Critic (NAC), that effectively normalizes the Q-function, reducing the Q-values of actions unseen in the demonstration data. NAC learns an initial policy network from demonstrations and refines the policy in the environment, surpassing the demonstrator's performance. Crucially, both learning from demonstration and interactive refinement use the same objective, unlike prior approaches that combine distinct supervised and reinforcement losses. This makes NAC robust to suboptimal demonstration data since the method is not forced to mimic all of the examples in the dataset. We show that our unified reinforcement learning algorithm can learn robustly and outperform existing baselines when evaluated on several realistic driving games.
Open Source Platform Digital Personal Assistant

Nowadays Digital Personal Assistants (DPA) become more and more popular. DPAs help to increase quality of life especially for elderly or disabled people. In this paper we develop an open source DPA and smart home system as a 3- rd party extension to show the functionality of the assistant. The system is designed to use the DPA as a learning platform for engineers to provide them with the opportunity to create and test their own hypothesis. The DPA is able to recognize users' commands in natural language and transform it to the set of machine commands that can be used to control different 3rdparty application. We use smart home system as an example of such 3rd-party. We demonstrate that the system is able to control home appliances, like lights, or to display information about the current state of the home, like temperature, through a dialogue between a user and the Digital Personal Assistant.
Maximum likelihood detection of precoded SFBC in frequency-selective fading channels

In this paper, we derive the maximum likelihood detector (MLD) for precoded space-frequency block coded (SFBC) systems where orthogonal frequency division multiplexing (OFDM) is incorporated. The obtained results reveal that the precoding process can be exploited to construct low complexity MLD even when the channel frequency response is not equal across each SFBC block. The derived MLD structure is similar to the conventional Alamouti linear decoder except that the decoding matrix has to be selected from four possible matrices. However, the decoding matrix selection and symbols' detection can be performed jointly, which minimizes the additional computational complexity of the derived MLD as compared to the conventional Alamouti decoder. Monte Carlo simulation results show that the MLD outperforms the suboptimal detector reported in [1] by about 5 dB at bit error rate (BER) of 10−4 under various channel conditions.
Detection of stable community structures within gut microbiota co-occurrence networks from different human populations

Microbes in the gut microbiome form sub-communities based on shared niche specialisations and specific interactions between individual taxa. The inter-microbial relationships that define these communities can be inferred from the co-occurrence of taxa across multiple samples. Here, we present an approach to identify comparable communities within different gut microbiota co-occurrence networks, and demonstrate its use by comparing the gut microbiota community structures of three geographically diverse populations. We combine gut microbiota profiles from 2,764 British, 1,023 Dutch, and 639 Israeli individuals, derive co-occurrence networks between their operational taxonomic units, and detect comparable communities within them. Comparing populations we find that community structure is significantly more similar between datasets than expected by chance. Mapping communities across the datasets, we also show that communities can have similar associations to host phenotypes in different populations. This study shows that the community structure within the gut microbiota is stable across populations, and describes a novel approach that facilitates comparative community-centric microbiome analyses.
Pulsatile Flow Characterization in a Vessel Phantom With Elastic Wall Using Ultrasonic Particle Image Velocimetry Technique: The Impact of Vessel Stiffness on Flow Dynamics

This study aims to experimentally investigate the impact of vessel stiffness on the flow dynamics of pulsatile vascular flow. Vessel phantoms with elastic walls were fabricated using polyvinyl alcohol cryogel to result in stiffness ranging from 60.9 to 310.3 kPa and tested with pulsatile flows using a flow circulation set-up. Two-dimensional instantaneous and time-dependent flow velocity and shear rate vector fields were measured using ultrasonic particle image velocimetry (EchoPIV). The waveforms of peak velocities measured by EchoPIV were compared with the ultrasonic pulse Doppler spectrum, and the measuring accuracy was validated. The cyclic vessel wall motion and flow pressure were obtained as well. The results showed that vessel stiffening influenced the waveforms resulting from vessel wall distension and flow pressure, and the fields of flow velocity and shear rate. The stiffer vessel had smaller inner diameter variation, larger pulse pressure and median pressure. The velocity and shear rate maximized at peak systole for all vessels. The results showed a decrease in wall shear stress for a stiffer vessel, which can initiate the atherosclerotic process. Our study elucidates the impact of vessel stiffness on several flow dynamic parameters, and also demonstrates the EchoPIV technique to be a useful and powerful tool in cardiovascular research.
Influencing Factors of Macrosporous Ordering in TiO2 and ZrO2 Inverse Opals

TiO2 inverse opals, as well as used as photonic crystals, can be applied to the dye sensitized solar cells (DSSC), photocatalysis, and so on. In above applications, ordering of pore arrangement in TiO2 inverse opal is crucial as it determines the application effect of TiO2 inverse opal. In this paper, TiO2 inverse opals were prepared by infiltrating and removing of polystyrene (PS) colloidal crystal templates. Using scanning electron microscope (SEM), it is found that the pore structure of inverse opals can be tuned by using different heating temperature and different size of PS spheres, and ordering of pore arrangement is strongly affected by ordering of PS spheres alignment, heating temperature, and size of PS spheres.
The Effects of Exfoliated Nano-clay on the Extrusion Microcellular Foaming of Amorphous and Crystalline Nylon

This article demonstrates the effect of exfoliated nano-clay on the microcellular foam processing of amorphous and crystalline nylon. Amorphous and crystalline nylon 6 nanocomposites are prepared using a twin-screw extruder. The exfoliated nanocomposite structures are characterized by X-ray diffraction (XRD) and transmission electron microscopy (TEM). Nylon and its nanocomposites are foamed in extrusion using supercritical CO2. Subsequently, the cell morphologies of nylon and its nanocomposite foams are investigated. It appeared that the nano-clay not only enhanced cell nucleation, but also suppressed cell deterioration during the microcellular foaming of nylon.
Subjective memory complaints, mood and MCI: a follow-up study

Objectives: Subjective memory complaints (SMC) are common in older people and previous research has shown an association with mood problems, such as depression and anxiety. SMC form part of the criteria for many definitions of mild cognitive impairment (MCI), but there is controversy over whether they should be included as they may be related more strongly to mood than to objective cognitive impairment. This study aims to clarify the relationship between mood and SMC in people with MCI. Method: This paper reports an analysis of data from the Medical Research Council Cognitive Function and Ageing study. Structured interviews were conducted with community-dwelling older people to assess a range of aspects of cognitive functioning and mood. Data from two time points approximately 24 months apart were used in this analysis. At baseline, participants without dementia or severe cognitive impairment were categorised into three groups according to cognitive status. Mood was investigated by assessing symptoms of anxiety and depression which were defined using a diagnostic algorithm. Associations were tested using logistic regression and chi square analyses. Results: A clear association was shown between SMC and mood, both cross-sectionally and over time. The relationship between our two competing definitions of MCI suggested that mood problems were more strongly related to the presence of SMC than objective cognitive impairment. Conclusion: SMC may be a function of anxiety and depression rather than being related to objective cognitive function. This questions whether SMC should be included in definitions of MCI.
Subterranean ants (Hymenoptera, Formicidae) as prey of fossorial reptiles (Reptilia, Squamata: Amphisbaenidae) in Central Brazil

A diversidade de formigas no conteudo estomacal de repteis fossoriais foi comparada a riqueza de formigas subterrâneas coletadas com o uso de tecnicas tradicionais e modernas para sua coleta. Analisamos o trato alimentar de 64 especimes de anfisbenideos (4 Amphisbaena alba, 10 A. fuliginosa, 25 A. vermicularis e 25 Leposternon infraorbitale) coletados durante o resgate da fauna para a construcao da represa da Hidroeletrica da Serra da Mesa no Rio Tocantins (de 1992 a 1997), na cidade de Minacu, Goias, Brasil. Encontramos apenas cinco especies de formigas presentes nos conteudos estomacais aqui examinados, todas pertencentes a subfamilia das formigas-de-correicao, Ecitoninae. Ao contrario, as tecnicas tradicionais de coleta de formigas subterrâneas sao muito mais eficientes que o exame dos conteudos estomacais de repteis fossoriais, coletando uma fauna muito mais rica e diversa de formigas. A ocorrencia exclusiva de formigas-de-correicao no trato alimentar destes repteis fossoriais sugere que eles seguem trilhas quimicas deixadas pelas formigas a medida que se elas movimentam no interior e sobre o solo. Ainda, a ocorrencia das formigas-de-correicao epigeicas Eciton e Labidus nos conteudos estomacais analisados sugere que os anfisbenideos podem tambem forragear na superficie do solo.
Joint Source and Relay Precoding in Multiantenna Millimeter-Wave Systems

This paper considers the joint source and relay precoding design for millimeter-wave (mm-wave) systems under the assumption that the source, relay, and destination nodes are equipped with multiple antennas. We focus on the rate maximization problem with the per antenna power constraints at the source and relay while taking into account the computational complexity and sparse characteristics of mm-wave channels. We solve this problem as follows. First, the precoding problem is formulated by exploiting the sparse and low-rank structures of mm-wave channels which is nonconvex. Second, we reformulate this nonconvex problem into two semidefinite programming (SDP) subproblems, each having a rank one constraint. Third, we propose two algorithms to solve these two SDP subproblems: interior-point-based and low complexity algorithms. Finally, the original rate maximization problem is examined by iteratively utilizing the solutions of these SDP problems. The proposed interior-point-based method to solve the SDP problem uses the standard convex optimization tools followed by the random vector generation scheme to get the rank one solution. However, the proposed low complexity algorithm examines the SDP problem in one-dimensional spatial signal space (i.e., without rank relaxation) via a new augmented Lagrangian function method. Simulation results show that both algorithms achieve good performances, and the latter one is much faster than the former one with a slight decrease in performance. In addition, both algorithms achieve superior performances compared to the existing precoding design algorithms.
Soil microbial community dynamics and assembly under long‐term land use change

ABSTRACT We evaluated the bacterial and archaeal community dynamics and assembly in soils under forest, grassland and no‐till cropping, using a high‐throughput shotgun metagenomics approach. No significant alterations in alpha diversity were observed among different land uses, but beta diversity in grassland was lower than that observed in forest and no‐till soils. Grassland communities showed assembly that predominantly followed the neutral model, i.e. high homogenizing selection with moderate dispersion, leading to biotic homogenization. Both no‐till and forest soil communities were found to have assembly that predominantly followed a niche model, i.e. low rates of dispersal and weak homogenizing selection, resulting in maintenance of higher beta diversity relative to grasslands, indicating niche specialization or variable selection. Taken together, our results indicate that the patterns of assembly and their governing processes are dependent on the land use employed after deforestation, with consequences for taxa turnover and microbial functional potential.
Gait Speed Measurement for Elderly Patients with Risk of Frailty

The ageing of the population poses a threat to both public and private health and social systems. In the last 50 years, life expectancy has increased by an average of 20 years, and by the year 2050, life expectancy will exceed 90 years of age. However, quality of life in the last years of life is not guaranteed due to conditions such as functional decline and frailty, ultimately progressing to disability. Thus, the detection of such a condition in time is of utmost importance. This paper presents an ultrasonic sensor-based gait speed measurement device controlled via a mobile interface, which permits patients to self-assess physical performance. The system was developed and validated in an iterative process involving a total of 28 subjects (21 in the first round and 7 in the second one). After first evaluation at Hospital Universitario de Getafe, some technical problems arose whereas usability testing was well evaluated. The second version addressing the identified issues was technically validated at university premises with good and promising results. Future work envisages deployment of the system developed at subjects’ homes to be remotely and unobtrusively monitored.
Spatial Decision Assistance of Watershed Sedimentation (SDAS): Development and Application

This paper discusses the development and application of a spatial tool for erosion modeling named Spatial Decision Assistance of Watershed Sedimentation (SDAS). SDAS computes export (yield) of sediment from watershed as product of erosion rate and sediment delivery ratio (SDR). The erosion rate is calculated for each raster grid according to a digital elevation model, soil, rain fall depth, and land cover data using the Universal Soil Loss Equation. SDR calculation is carried out for each spatial unit. A spatial unit is the smallest sub-watershed considered in the model and generated according to the TauDEM algorithm. The size of one spatial unit is assigned by the user as the minimum number of raster grids. SDR is inversely proportional to sediment resident time and controlled by rainfall, slope, soil, and land cover. Application of SDAS is demonstrated in this paper by simulating the spatial distribution of the annual sediment yield across the Citarum watershed in the northwest of Java, Indonesia. SDAS calibration was carried out based on sediment discharge observations from the upper catchment. We considered factors for hillslope flow depth and for actual and effective rainfall duration to fit the computed sediment yield to the observed sediment discharge. The computed sediment yield agreed with the observation data with a 7% mean relative accuracy.
Multimodal decomposition for enhanced subtle emotion recognition

True human emotions may be revealed during brief moments of minute facial muscle movements. These so-called subtle emotions are low in intensity, sparse and short duration in nature. Despite such tiny presence, subtle emotions have shown to be useful for real-life applications including lie detection and clinical diagnosis. In this paper, we present a processing technique based on multimodal decomposition and emotion magnification that is viable to decompose and subsequently emphasize highly discriminative subtle emotions information. Through this method, promising results of 25–30% improvement in recognition performance are achieved. By further magnifying the decomposed emotion components, the subtle emotions intensity can be increased and further boost recognition performance by 3–4%.
Subspace Clustering With $K$ -Support Norm

Subspace clustering aims to cluster a collection of data points lying in a union of subspaces. Based on the assumption that each point can be approximately represented as a linear combination of other points, extensive efforts have been made to compute an affinity matrix in a self-expressive framework for describing the similarity between points. However, the existing clustering methods consider the average feature solutions, which would not be powerful enough to capture the intrinsic relationship between points. In this paper, we present the <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-support norm subspace clustering (KSC) method by utilizing <inline-formula> <tex-math notation="LaTeX">$k-$ </tex-math></inline-formula>support norm regularization. The <inline-formula> <tex-math notation="LaTeX">$k-$ </tex-math></inline-formula>support norm trades off the sparsity of <inline-formula> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula> norm and the uniform shrinkage of <inline-formula> <tex-math notation="LaTeX">$\ell _{2}$ </tex-math></inline-formula> norm to yield better predictive performance on the data connection. The theoretical analysis of KSC makes up a large proportion of paper. In the noise-free case, we provide the kEBD condition, which ensures the coefficient matrix to be block diagonal. If the data are corrupted, we prove the incompletion-grouping effect for KSC. Moreover, we provide the statistical recovery guarantee for both noise-free and noise cases. The theory analyses show the validity and feasibility of KSC, and the experimental results on multiple challenging databases demonstrate the effectiveness of the proposed algorithm.