Miracle-dz/UniFAR-FTUs huggingface dataset:
On Multi-Relational Link Prediction with Bilinear Models

We study bilinear embedding models for the task of multi-relational link prediction and knowledge graph completion. Bilinear models belong to the most basic models for this task, they are comparably efficient to train and use, and they can provide good prediction performance. The main goal of this paper is to explore the expressiveness of and the connections between various bilinear models proposed in the literature. In particular, a substantial number of models can be represented as bilinear models with certain additional constraints enforced on the embeddings. We explore whether or not these constraints lead to universal models, which can in principle represent every set of relations, and whether or not there are subsumption relationships between various models. We report results of an independent experimental study that evaluates recent bilinear models in a common experimental setup. Finally, we provide evidence that relation-level ensembles of multiple bilinear models can achieve state-of-the-art prediction performance.
CFH, VEGF and HTRA1 promoter genotype may influence the response to intravitreal ranibizumab therapy for neovascular age-related macular degeneration

Aims To investigate an association between genotype for three single nucleotide polymorphisms strongly associated with the development of age-related macular degeneration (AMD) and the early response to treatment with intravitreal ranibizumab for neovascular AMD. Methods Best corrected visual acuity letter score was recorded at baseline and each subsequent visit. Age, sex, smoking history, lesion type and the number of injections were also recorded. Genotypes were obtained for rs11200638 in HTRA1, rs1061170 in CFH and rs1413711 in VEGF. Data were analysed with treatment response at month 6 as both a binary (>5 letter improvement vs ≤5 letter gain) and a linear trait. Results This initial study cohort consisted of 104 Caucasian neovascular AMD patients treated with intravitreal ranibizumab. Trends towards a more favourable outcome were seen with the higher AMD risk genotypes in CFH and VEGF in both the linear and binary models and in HTRA1 in the linear model alone. For CFH, mean letter score change after 6 months was +1.6, +5.9 and +7.2 letters for the TT, TC and CC genotypes and a >5 letter gain was seen in 34.6%, 56.6% and 56%, respectively. For VEGF, mean letter score change after 6 months was +1.3, +5.8 and +7.4 letters for the TT, TC and CC genotypes and a >5 letter gain was seen in 40%, 55.8% and 51.9%, respectively. For HTRA1, mean letter score change was +2.2, +7.5 and +2.9 letters for the GG, GA and AA genotypes. Conclusions This study reports preliminary evidence suggesting that the higher AMD risk genotypes in CFH, VEGF and HTRA1 may influence the short-term response to treatment with ranibizumab for neovascular AMD.
Oxytocin Reduces Ethanol Self‐Administration in Mice

BACKGROUND Excessive ethanol (EtOH) consumption remains an important health concern and effective treatments are lacking. The central oxytocin system has emerged as a potentially important therapeutic target for alcohol and drug addiction. These studies tested the hypothesis that oxytocin reduces EtOH consumption. METHODS Male C57BL/6J mice were given access to EtOH (20% v/v) using a model of binge-like drinking ("drinking in the dark") that also included the use of lickometer circuits to evaluate the temporal pattern of intake as well as 2-bottle choice drinking in the home cage. In addition, EtOH (12% v/v) and sucrose (5% w/v) self-administration on fixed- and progressive-ratio schedules were also evaluated. A wide range of systemically administered oxytocin doses were tested (0 to 10 mg/kg) in these models. RESULTS Oxytocin (0, 0.3, 1, 3, or 10 mg/kg) dose dependently reduced EtOH consumption (maximal 45% reduction) in the binge drinking model, with lower effective doses having minimal effects on general locomotor activity. Oxytocin's effect was blocked by pretreatment with an oxytocin receptor antagonist, and the pattern of contacts (licks) at the EtOH bottle suggested a reduction in motivation to drink EtOH. Oxytocin decreased 2-bottle choice drinking without altering general fluid intake. Oxytocin also reduced operant responding for EtOH and sucrose in a dose-related manner. However, oxytocin decreased responding and motivation (breakpoint values) for EtOH at doses that did not alter responding for sucrose. CONCLUSIONS These results indicate that oxytocin reduces EtOH consumption in different models of self-administration. The effects are not likely due to a general sedative effect of the neuropeptide. Further, oxytocin reduces motivation for EtOH at doses that do not alter responding for a natural reward (sucrose). While some evidence supports a role for oxytocin receptors in mediating these effects, additional studies are needed to further elucidate underlying mechanisms. Nevertheless, these results support the therapeutic potential of oxytocin as a treatment for alcohol use disorder.
Scale-adaptive compressive tracking with feature integration

Abstract. Numerous tracking-by-detection methods have been proposed for robust visual tracking, among which compressive tracking (CT) has obtained some promising results. A scale-adaptive CT method based on multifeature integration is presented to improve the robustness and accuracy of CT. We introduce a keypoint-based model to achieve the accurate scale estimation, which can additionally give a prior location of the target. Furthermore, by the high efficiency of data-independent random projection matrix, multiple features are integrated into an effective appearance model to construct the naïve Bayes classifier. At last, an adaptive update scheme is proposed to update the classifier conservatively. Experiments on various challenging sequences demonstrate substantial improvements by our proposed tracker over CT and other state-of-the-art trackers in terms of dealing with scale variation, abrupt motion, deformation, and illumination changes.
mimiRNA: a microRNA expression profiler and classification resource designed to identify functional correlations between microRNAs and their targets

MOTIVATION microRNAs (miRNAs) are short non-coding RNAs that regulate gene expression by inhibiting target mRNA genes. Their tissue- and disease-specific expression patterns have immense therapeutic and diagnostic potential. To understand these patterns, a reliable compilation of miRNA and mRNA expression data is required to compare multiple tissue types. Moreover, with the appropriate statistical tools, such a resource could be interrogated to discover functionally related miRNA-mRNA pairs. RESULTS We have developed mimiRNA, an online resource that integrates expression data from 1483 samples and permits visualization of the expression of 635 human miRNAs across 188 different tissues or cell types. mimiRNA incorporates a novel sample classification algorithm, ExParser, that groups identical miRNA or mRNA experiments from separate sources. This enables mimiRNA to provide reliable expression profiles and to discover functional relations between miRNAs and mRNAs such as miRNA targets. Additionally, mimiRNA incorporates a decision tree algorithm to discover distinguishing miRNA features between two tissue or cell types. We validate the efficacy of our resource on independent experimental data and through biologically relevant analyses. AVAILABILITY http://mimirna.centenary. org.au. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Widespread finger skin metastases of melanoma

Metastatic melanoma is a fatal disease with a rapid systemic dissemination. Almost every organ might be affected, but lungs, liver, bone, brain, and skin are the most frequently involved sites. Intravascular microtumoral embolism is believed to account for the distant cutaneous metastases that might be the first manifestation of disease progression in most of the cases.
Equilibrium-based volatility models of the market portfolio rate of return (peacock tails or stotting gazelles)

We introduce a theoretical and empirical method of studying equilibrium-consistent volatility models. We implement it with the market portfolio’s return, which is central to financial risk management. Within an equilibrium framework, we study two families of such models. One is deterministic volatility, represented by current popular models. The other is in the “constant elasticity of variance” family, in which we propose new models. Theoretically, we show that, together with constant expected returns, the latter family tends to have better ability to forecast. Empirically, our proposed models, while as easy to implement as the popular ones, outperform them in three out-of-sample forecast evaluations of different time periods, by standard predictability criteria. This is true particularly during high-volatility periods, whether the market rises or falls.
Automatic large area reconstruction of building façades from spaceborne TomoSAR point clouds

Improved resolution of SAR sensors and advanced multipass interferometric techniques, such as tomographic SAR inversion (TomoSAR), opens up new possibilities of 4D (or even higher dimensional) imaging that can be potentially used to reconstruct dynamic models of entire cities, i.e., city models that can incorporate temporal (motion) behaviour along with the 3D information. Motivated by these chances, this paper presents an approach that systematically allows automatic reconstruction of building façades from 4D point cloud generated from tomographic SAR processing and put particular focus on robust reconstruction of large areas. The approach is modular and is illustrated/validated by examples using TomoSAR point clouds generated from a stack of TerraSAR-X high-resolution spotlight images from ascending orbit covering approx. 2 km2 high rise area in the city of Las Vegas.
Model Playground for Autistic Children: Teaching Social Skills through Tangible Collaboration

Children with autism often have difficulties in learning the social skills and norms of peer social interaction, which severely affect and limit their social lives. Aiming at addressing this issue, through design, we developed a digital-analogue model playground to help them understand and cope with the socially difficult situations experienced when they go to a physical playground to interact with peers. Based on therapists and parents' insights, we created the model playground with built in collaborative protocols providing immediate feedback to the children in terms of acceptable and unacceptable behaviour. Our design artefact was evaluated in a rehabilitation clinic for autistic children and demonstrates promising potential for digital-analogue devices as useful resources training peer social interaction. Our findings document that digital-analogue design devices can facilitate the development of social skills and norms through peer learning activities amongst children with autism.
Optimal Spatial Policies, Geography and Sorting

We study optimal spatial policies in quantitative trade and geography frameworks with spillovers and sorting of heterogeneous workers. We rst characterize ecient spatial transfers and the labor subsidies that would implement them. Then, we quantify the aggregate and distributional eects of implementing these policies in the U.S. economy. Under homogeneous workers and constant-elasticity spillovers, a constant labor subsidy over space restores efficiency regardless of micro heterogeneity in fundamentals and trade costs. In that case, the quantification suggests that the observed spatial transfers in the U.S. are close to ecient. Spillovers across heterogeneous workers create an additional rationale for place-specific subsidies to attain optimal sorting. Under heterogeneous workers, the quantication suggests that optimal spatial policies may require stronger redistribution towards low-wage cities than in the data, reduce wage inequality in larger cities, weaken spatial sorting by skill, and lead to signicant welfare gains. Spillovers across dierent types of workers are a key driving force behind these results.
xView: Objects in Context in Overhead Imagery

We introduce a new large-scale dataset for the advancement of object detection techniques and overhead object detection research. This satellite imagery dataset enables research progress pertaining to four key computer vision frontiers. We utilize a novel process for geospatial category detection and bounding box annotation with three stages of quality control. Our data is collected from WorldView-3 satellites at 0.3m ground sample distance, providing higher resolution imagery than most public satellite imagery datasets. We compare xView to other object detection datasets in both natural and overhead imagery domains and then provide a baseline analysis using the Single Shot MultiBox Detector. xView is one of the largest and most diverse publicly available object-detection datasets to date, with over 1 million objects across 60 classes in over 1,400 km^2 of imagery.
Inhibition of accelerated rejection mediated by alloreactive CD4+ memory T cells and prolonged allograft survival by arsenic trioxide

The aim of this study was to evaluate and determine the potential mechanisms of As2O3 in accelerated rejection mediated by alloreactive CD4+ memory T cells. Vascularized heterotopic cardiac transplantation from C57BL/6 mice to nude mice (pre-transferred CD4+ memory T cells) was performed on Day 0, and As2O3 was administered to recipient mice from Day 0 to 10. As a result, As2O3 could reduce the proliferation of allo-primed CD4+ memory T cells in vitro in MLR and the baseline rate of proliferation was restored by the addition of exogenous IL-2. In vivo, compared with the control[+] group, the mean survival time of cardiac allografts in the As2O3 group was prolonged from 5.8 ± 0.7 to 14.2 ± 2.5 days. Five days after transplantation, the relative gene expression of IL-2, IFN-γ and Foxp3 was reduced in the grafts by As2O3 treatment, but the expression of IL-10 and TGF-β was increased. Correspondingly, the proportions of CD4+ T cells, CD4+ memory T cells and regulatory T cells (Tregs), both in recipient spleens and lymph nodes, were lowered. These results indicate the potential of As2O3 as a novel immunosuppressant targeting CD4+ memory T cells.
Dynamic Heuristics: Greedy Search: A Mobile Information Retrieval Algorithm for Ambient Learning Systems

Research supervision services like providing study materials can be enhanced through mobile information retrieval algorithms. An example is semantic searching algorithms, which require the user to input one or two real world concepts. Systems that implement mobile learning approaches like ambient learning can use semantic searching algorithms to support research supervision services through mobile phones. However, there is low adoption of such approaches in some of the African universities. This has been attributed to limited technical limitations of mobile devices that include mobile phones. For instance, complex interfaces, restricted input and small screens on mobile phones make it difficult to enter search keywords when the user is in a hurry. As an attempt to address these limitations, this paper describes dynamic heuristics - greedy search algorithm that automatically generate search keywords. The algorithm can be used to allow flexible mobile information retrieval on a typical ambient learning system.
3D Carbon Scaffolds for Neural Stem Cell Culture and Magnetic Resonance Imaging

3D glassy carbon structures with percolated macropores are obtained by pyrolysis of chemically synthesized cryogels featuring tunable porosity. These batch‐fabricated structures are used as scaffolds for culturing neural stem cells (NSCs) and are characterized by magnetic resonance imaging (MRI). With the aid of MRI, the successful cultivation of NSCs on a glassy carbon surface and the precise 3D locations of these cell clusters within the opaque scaffold are demonstrated. MRI also yields pore morphology and porosity analyses, pre‐ and post‐pyrolysis. This integrated approach yields a complete 3D dataset of the NSC network, which enables the visual inspection of the morphological details of individual cell clusters without disturbing them or destroying the scaffold. Reported experimental methodology is expected to have an impact on studies designed to understand the mechanism of neurodegenerative disease (ND) development, and can serve as a protocol for the culture of various other types of cells that display compatibility with glassy carbon surfaces.
Saliency prediction based on new deep multi-layer convolution neural network

Recent advances in saliency detection have utilized deep learning to obtain high-level features to detect salient regions. These advances have demonstrated superior results over previous works that utilize hand-crafted low-level features for saliency detection. In this paper, we propose a new multilayer Convolutional Neural Network (CNN) model to learn high-level features for saliency detection. Compared to other methods, our method presents two merits. First, when performing features extraction, apart from the convolution and pooling step in our method, we add Restricted Boltzmann Machine (RBM) into the CNN framework to obtain more accurate features in intermediate step. Second, in order to deal with case of non-linear classification, we add the Deep Belief Network (DBN) classifier at the end of this model to classify the salient and non-salient regions. Quantitative and qualitative experiments on three benchmark datasets demonstrate that our method performs favorably against the state-of-the-art methods.
The predictive value of early response in patients with depressive disorders

Abstract Objective: Several randomized controlled trials have identified early response to psychotherapy as a predictor for later treatment outcome among patients with depressive disorders. However, supporting evidence under routine conditions is rare. This study evaluated the predictive value of early improvement for final outcomes in psychotherapy among depressive patients in the naturalistic setting of a German university outpatient clinic. Method: We used the method of percent symptom reduction to classify 639 patients with major depression or dysthymic disorder who underwent an average of 40.0 sessions (SD = 16.3) of naturalistic cognitive–behavioral therapy (CBT) as having either an early response or an early nonresponse. Results: Early response was a good predictor for final response and remission regarding depressive symptoms (OR = 8.75 and OR = 5.32, respectively), as well as overall psychological distress (OR = 3.95 and OR = 3.16, respectively). Early nonresponse was distinctly associated with later deterioration of both depressive (OR = 9.56) and general psychological symptomatology (OR = 4.92). Conclusions: Early response to psychotherapy has high predictive qualities for positive later treatment outcome in depressive patients under routine CBT. Therefore, early treatment effects should be considered in clinical decision-making and treatment planning in everyday clinical practice.
Strain Distribution Over Plaques in Human Coronary Arteries Relates to Shear Stress

It is well established that atherosclerotic plaques generally develop in low shear stress regions, including curved arterial segments and bifurcations. Once these plaques intrude into the lumen, the shear stress they are exposed to alters with hitherto unknown consequences. We hypothesize that in the more advanced stages of the disease, shear stress has an important impact on plaque composition in such a way that high shear stress enhances plaque vulnerability through its biological impact on the endothelium. We investigated this hypothesis by studying the relationship between shear stress and strain, a marker for plaque composition, in human coronary arteries.Copyright © 2007 by ASME
Discrepancy Analysis of a New Randomized Diffusion Algorithm for Weighted Round Matrices

For an arbitrary initial configuration of indivisible loads over vertices of a distributed network, we consider the problem of minimizing the discrepancy between the maximum and minimum load among all vertices. For this problem, diffusion-based algorithms are well studied because of its simplicity. This paper presents a new randomized diffusion-based algorithm inspired by multiple random walks. In our algorithm, at each vertex, each token $k$ ($k\in \{0,1,\ldots, X-1\}$) generate a random number in $[k/X, (k+1)/X)$, and moves to a vertex corresponding to the given probability distribution. Our algorithm is adaptive to any transition transition probabilities while almost all previous works are concerned with uniform transition probabilities. For this algorithm, we analyze the discrepancy between the token configuration and its expected value, and give an upper bound depending on the local 2-divergence of the transition matrix and $\sqrt{\log n}$, where $n$ is the number of vertices. The local 2-divergence is a measure which often appeared in previous works. We also give an upper bound of the local-2 divergence for any reversible and lazy transition matrix. These yield the following specific results. First, our algorithm achieves $O(\sqrt{d \log n})$ discrepancy for any $d$ regular graph, which matches the best result on previous works of diffusion model. Note that our algorithm does not need any assumption such as negative loads which are often assumed in previous works. Second, for general graphs with maximum degree $d_{\max}$, our algorithm achieves $O(\sqrt{ d_{\max} \log n})$ discrepancy using the transition matrix based on the metropolis hasting algorithm. Note that this algorithm does not need information of $d_{\max}$ while almost all previous works use it.
Long-Term Efficacy of Implantable Cardioverter Defibrillator in Repaired Tetralogy of Fallot　- Role of Anti-tachycardia Pacing.

BACKGROUND Tetralogy of Fallot (TOF) is one of the common congenital heart diseases (CHD) in implantable cardioverter defibrillator (ICD) recipients, but few studies have reported the long-term outcomes of and the anti-tachycardia pacing (ATP) efficacy in repaired TOF.Methods and Results:Twenty-one repaired TOF patients with an ICD implanted between April 2003 and March 2015 were investigated retrospectively. ICD therapy and clinical outcome were analyzed. Mean patient age was 39±11 years; 62% were male; and mean age at repair surgery was 9.4±6.8 years. During a median follow-up of 5.6 years (range, 2.6-8.4 years), no patients died. Appropriate ATP were delivered in 11 patients (52%), with appropriate shocks in 5 patients (24%) and inappropriate shocks in 5 patients (24%). The success rate of ATP was 98% for fast ventricular tachycardia (VT; cycle length ≤320 ms) and 98% for slow VT (cycle length >320 ms). ATP effectiveness increased from 81.5% with the first ATP attempt to 93.7% with the second ATP attempt, to 97.5% with the third ATP attempt, and to 98.6% with the fourth or successive ATP attempt (P<0.0001, Cochran-Armitage trend test). CONCLUSIONS ATP was highly effective in repaired TOF regardless of VT cycle length. Multiple ATP attempts could have an important role in VT termination, and the novel subcutaneous ICD without ATP capability should be used carefully.