Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference

Lack of performance when it comes to continual learning over non-stationary distributions of data remains a major challenge in scaling neural network learning to more human realistic settings. In this work we propose a new conceptualization of the continual learning problem in terms of a temporally symmetric trade-off between transfer and interference that can be optimized by enforcing gradient alignment across examples. We then propose a new algorithm, Meta-Experience Replay (MER), that directly exploits this view by combining experience replay with optimization based meta-learning. This method learns parameters that make interference based on future gradients less likely and transfer based on future gradients more likely. We conduct experiments across continual lifelong supervised learning benchmarks and non-stationary reinforcement learning environments demonstrating that our approach consistently outperforms recently proposed baselines for continual learning. Our experiments show that the gap between the performance of MER and baseline algorithms grows both as the environment gets more non-stationary and as the fraction of the total experiences stored gets smaller.
AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks

Click-through rate (CTR) prediction, which aims to predict the probability of a user clicking on an ad or an item, is critical to many online applications such as online advertising and recommender systems. The problem is very challenging since (1) the input features (e.g., the user id, user age, item id, item category) are usually sparse and high-dimensional, and (2) an effective prediction relies on high-order combinatorial features (a.k.a. cross features), which are very time-consuming to hand-craft by domain experts and are impossible to be enumerated. Therefore, there have been efforts in finding low-dimensional representations of the sparse and high-dimensional raw features and their meaningful combinations. In this paper, we propose an effective and efficient method called the AutoInt to automatically learn the high-order feature interactions of input features. Our proposed algorithm is very general, which can be applied to both numerical and categorical input features. Specifically, we map both the numerical and categorical features into the same low-dimensional space. Afterwards, a multi-head self-attentive neural network with residual connections is proposed to explicitly model the feature interactions in the low-dimensional space. With different layers of the multi-head self-attentive neural networks, different orders of feature combinations of input features can be modeled. The whole model can be efficiently fit on large-scale raw data in an end-to-end fashion. Experimental results on four real-world datasets show that our proposed approach not only outperforms existing state-of-the-art approaches for prediction but also offers good explainability. Code is available at: \urlhttps://github.com/DeepGraphLearning/RecommenderSystems.
Resolution of Othello Syndrome After Subthalamic Nucleus Deep Brain Stimulation in 3 Patients with Parkinson's Disease

Psychiatric symptoms are historically thought a relative contraindication to DBS for advanced Parkinson's disease (PD). However, in the case of drug‐induced mental illness, DBS may provide an acceptable alternative for the treatment of motor symptoms. This allows reduction of pharmacological dopaminergic therapy that might otherwise cause negative psychiatric consequences. For example, DBS is increasingly used to ameliorate specific complications of PD treatment, such as impulse control disorders. We present a series of 3 cases of young male patients who developed Othello syndrome (OS) during treatment with dopamine agonists. In each case, the OS resolved with withdrawal of the offending drug. Subsequent treatment with bilateral STN DBS improved motor symptoms and allowed reduction in their dopaminergic drug regimen. We therefore propose that drug‐induced psychopathology may be an indication (rather than a contraindication) for DBS in selected cases.
Complexity in the Acceptance of Sustainable Search Engines on the Internet: An Analysis of Unobserved Heterogeneity with FIMIX-PLS

This paper analyses the complexity of user behaviour when facing the challenge of using sustainable applications, such as Internet search engines. This paper analyses an acceptance model using extended TAM (Technology Acceptance Model) with Trust as an added external variable. It was suggested that Trust indirectly influences the final Intention to Use with the perceptions of Utility and Ease of Use. To test the proposed model, a survey was carried out with users from different geographical areas of Spain (n=445). The second aim of this study was to understand the complexity of marketing segmentation by separating the application users into different user groups. Users were grouped by their preference of favorite Internet search engine. Unobserved heterogeneity was studied using FIMIX-PLS, and three different user behaviours with search engines were identified. These corresponded to the number of inhabitants who live in the user area. In this way, the impact that the environment has on user choice, acceptance, and use of this type of sustainable applications was shown. The results were checked using PLS-SEM and showed that the model for the adoption of sustainable search engines is explanatory and predictive because confidence and acceptance for this TAM were validated. The conclusions are interesting for developers of environmentally sustainable and responsible applications which want to coincide with current trends to ensure that users prefer them.
Dopamine Receptor D3 rs6280 is Associated with Aberrant Decision‐Making in Parkinson's Disease

The functional Ser9Gly single nucleotide polymorphism (SNP) in the dopamine D3 receptor gene is associated with impulse control disorders (ICD) in Parkinson's disease (PD) in Indian patients. Whether the same SNP modulates impulsivity in PD patients without active ICD is unknown. We aimed to compare decision‐making under uncertainty in PD patients with DRD3 p.S9G (rs6280) variants CT/CC or TT.
miR‐221‐3p inhibits oxidized low‐density lipoprotein induced oxidative stress and apoptosis via targeting a disintegrin and metalloprotease‐22

Oxidized low‐density lipoprotein (ox‐LDL)‐induced oxidative stress and apoptosis are considered as a critical contributor to atherosclerosis. MicroRNAs (miRNAs) have been reported versatile functions in all biological processes via directly suppressing target messenger RNA at a posttranscriptional level. Although miRNA‐221 has been implied to be involved in the regulation of atherosclerosis, the underlying mechanism remains unclear. Here, we showed that ox‐LDL treatment remarkably suppressed the expression of miR‐221‐3p in a concentration‐dependent and time‐dependent manner. Transfection of miR‐221‐3p mimic significantly reduced the foam cell formation and expression of lipid biomarkers, while transfection of the miR‐221‐3p inhibitor showed completely opposite effects. Moreover, miR‐221‐3p was also found to inhibit the process of cell apoptosis in macrophages. A disintegrin and metalloprotease‐22 (ADAM22) is predicted as a direct target of miR‐221‐3p, and silencing AMAM22 resulted in a reduced foam cell formation and cell apoptosis. Furthermore, silencing AMAM22 restored the stimulatory effect of the miR‐221‐3p inhibitor in ox‐LDL‐induced foam cell formation and apoptosis. These findings suggest that miR‐221‐3p inhibits ox‐LDL and apoptosis via directly targeting ADAM22.
NLP-Cube: End-to-End Raw Text Processing With Neural Networks

We introduce NLP-Cube: an end-to-end Natural Language Processing framework, evaluated in CoNLL’s “Multilingual Parsing from Raw Text to Universal Dependencies 2018” Shared Task. It performs sentence splitting, tokenization, compound word expansion, lemmatization, tagging and parsing. Based entirely on recurrent neural networks, written in Python, this ready-to-use open source system is freely available on GitHub. For each task we describe and discuss its specific network architecture, closing with an overview on the results obtained in the competition.
Optimization of Process Parameters, Microstructure, and Properties of Laser Cladding Fe-Based Alloy on 42CrMo Steel Roller

The mould foot roller is a key component of a continuous casting machine. In order to investigate the possibility of using laser cladding to repair mould foot roller, Fe-based powders and 42CrMo steel are used in this work. The laser cladding process parameters were optimized by orthogonal experiments. The chemical compositions, microstructure, properties of the cladding layer under the optimum process parameters, and substrate were systematically investigated by using optical microscopy (OM), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), microhardness test, wear test, and salt spray corrosion test. The results indicate that the primary factor affecting the width and depth of the cladding layer is laser power. The scanning speed also has a significant effect on the height of the cladding layer. The optimum process parameters for repairing the mould foot roller are 2 kW laser power, 4 mm/s scanning speed, and 15 g/min feeding rate of powder. Along the depth direction of the cladding layer, the microstructure of the coating gradually transforms from plane crystal, cell grains, or dendrites to equiaxed grains. The matrix is mainly martensite with retained austenite; the eutectic phase is composed of netlike M2B, particulate M23(C,B)6, and M7(C,B)3 phase. The hardness of the cladding layer is significantly improved, about three times that of the substrate. The weight loss of the cladding layer is just half that of the substrate. Its wear resistance and corrosion resistance have been significantly improved. The work period of the laser cladding-repaired foot roller is much longer than for the surfacing welding-repaired one. In summary, laser cladding technology can increase the life of mould foot rollers.
A Miniaturized Semantic Segmentation Method for Remote Sensing Image

In order to save the memory, we propose a miniaturization method for neural network to reduce the parameter quantity existed in remote sensing (RS) image semantic segmentation model. The compact convolution optimization method is first used for standard U-Net to reduce the weights quantity. With the purpose of decreasing model performance loss caused by miniaturization and based on the characteristics of remote sensing image, fewer down-samplings and improved cascade atrous convolution are then used to improve the performance of the miniaturized U-Net. Compared with U-Net, our proposed Micro-Net not only achieves 29.26 times model compression, but also basically maintains the performance unchanged on the public dataset. We provide a Keras and Tensorflow hybrid programming implementation for our model: this https URL
Optimized Construction of Protograph G-LDPC Codes by Modified EXIT Chart and MACE for New-Generation Wireless Communications

In this paper, a new systematic construction of optimized protograph generalized low-density parity-check codes with good decoding threshold and low error floor is proposed. First, a typical code graph is generated by combining an accumulate-repeat-accumulate seed protograph with a Tanner graph extension of a simple linear block node. Subsequently, it is analyzed and optimized theoretically, especially with the puncture mechanism, by a modified extrinsic information transfer chart and an asymptotic weight distribution. The generated graph is then extended to a base matrix by a copy-and-permute procedure, accompanied with the matrix split, which is optimized by a progressive edge growth for good randomness and girth property. Finally, the proposed code matrix is created by replacing “1” in the above base matrix with square circulant sub-matrices, the offsets of which are searched by a quasi-cyclic (QC)-oriented modified approximate cycle extrinsic message degree algorithm to improve the cycle relationship, especially for the compound cycles. Simulation results show that the codes exhibit excellent performance in both error floor and waterfall region on an additive white Gaussian noise channel. Moreover, they are also characterized by faster encoding due to the QC structure as well as lower decoding complexity and less latency, which make them a natural fit for new-generation power constrained wireless communications.
Sirtuin 3 attenuates amyloid-β induced neuronal hypometabolism

Alzheimer’s disease (AD) is manifested by regional cerebral hypometabolism. Sirtuin 3 (Sirt3) is localized in mitochondria and regulates cellular metabolism, but the role of Sirt3 in AD-related hypometabolism remains elusive. We used expression profiling and weighted gene co-expression network analysis (WGCNA) to analyze cortical neurons from a transgenic mouse model of AD (APPSwInd). Based on WGCNA results, we measured NAD+ level, NAD+/ NADH ratio, Sirt3 protein level and its deacetylation activity, and ATP production across both in vivo and in vitro models. To investigate the effect of Sirt3 on amyloid-β (Aβ)-induced mitochondria damage, we knocked down and over-expressed Sirt3 in hippocampal cells. WGCNA revealed Sirt3 as a key player in Aβ-related hypometabolism. In APP mice, the NAD+ level, NAD+/ NADH ratio, Sirt3 protein level and activity, and ATP production were all reduced compared to the control. As a result, learning and memory performance were impaired in 9-month-old APP mice compared to wild type controls. Using hippocampal HT22 cells model, Sirt3 overexpression increased Sirt3 deacetylation activity, rescued mitochondria function, and salvaged ATP production, which were damaged by Aβ. Sirt3 plays an important role in regulating Aβ-induced cerebral hypometabolism. This study suggests a potential direction for AD therapy.
Day‐to‐day fasting self‐monitored blood glucose variability is associated with risk of hypoglycaemia in insulin‐treated patients with type 1 and type 2 diabetes: A post hoc analysis of the SWITCH Trials

To investigate the association between day‐to‐day fasting self‐monitored blood glucose (SMBG) variability and risk of hypoglycaemia in type 1 (T1D) and type 2 diabetes (T2D), and to compare day‐to‐day fasting SMBG variability between treatments with insulin degludec (degludec) and insulin glargine 100 units/mL (glargine U100).
Limb lengthening and deformity correction with externally controlled motorized intramedullary nails: evaluation of 50 consecutive lengthenings

Background and purpose — Limb lengthening with an intramedullary motorized nail is a relatively new method. We investigated if lengthening nails are reliable constructs for limb lengthening and deformity correction in the femur and the tibia. Patients and methods — 50 lengthenings (34 Precice and 16 Fitbone devices) in 47 patients (mean age 23 years [11–61]) with ≥12 months follow-up are included in this study. 30 lengthenings were done due to congenital and 20 because of posttraumatic deformity (21 antegrade femora, 23 retrograde femora, 6 tibiae). Initial deformities included a mean shortening of 42 mm (25–90). In 15 patients, simultaneous axial correction was done using the retrograde nailing technique. Results — The planned amount of lengthening was achieved in all but 2 patients. 5 patients who underwent simultaneous axial correction showed minor residual deformity; unintentionally induced minor deformities were found in the frontal and sagittal plane. The consolidation index was 1.2 months/cm (0.6–2.5) in the femur and 2.5 months/cm (1.6–4.0) in the tibia. 2 femoral fractures occurred in retrograde femoral lengthenings after consolidation due to substantial trauma. There were 8 complications, all of which were correctable by surgery, with no permanent sequelae. Interpretation — Controlled acute axial correction of angular deformities and limb lengthening can be achieved by a motorized intramedullary nail. A thorough preoperative planning and intraoperative control of alignment are required to avoid residual and unintentionally induced deformity. In the femur relatively fast consolidation could be observed, whereas healing was slower in the tibia.
Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning

We address the problem of segmenting 3D multi-modal medical images in scenarios where very few labeled examples are available for training. Leveraging the recent success of adversarial learning for semi-supervised segmentation, we propose a novel method based on Generative Adversarial Networks (GANs) to train a segmentation model with both labeled and unlabeled images. The proposed method prevents over-fitting by learning to discriminate between true and fake patches obtained by a generator network. Our work extends current adversarial learning approaches, which focus on 2D single-modality images, to the more challenging context of 3D volumes of multiple modalities. The proposed method is evaluated on the problem of segmenting brain MRI from the iSEG-2017 and MRBrainS 2013 datasets. Significant performance improvement is reported, compared to state-of-art segmentation networks trained in a fully-supervised manner. In addition, our work presents a comprehensive analysis of different GAN architectures for semi-supervised segmentation, showing recent techniques like feature matching to yield a higher performance than conventional adversarial training approaches. Our code is publicly available at this https URL
Axonal Projections From the Middle Temporal Area in the Common Marmoset

Neural activity in the middle temporal (MT) area is modulated by the direction and speed of motion of visual stimuli. The area is buried in a sulcus in the macaque, but exposed to the cortical surface in the marmoset, making the marmoset an ideal animal model for studying MT function. To better understand the details of the roles of this area in cognition, underlying anatomical connections need to be clarified. Because most anatomical tracing studies in marmosets have used retrograde tracers, the axonal projections remain uncharacterized. In order to examine axonal projections from MT, we utilized adeno-associated viral (AAV) tracers, which work as anterograde tracers by expressing either green or red fluorescent protein in infected neurons. AAV tracers were injected into three sites in MT based on retinotopy maps obtained via in vivo optical intrinsic signal imaging. Brains were sectioned and divided into three series, one for fluorescent image scanning and two for myelin and Nissl substance staining to identify specific brain areas. Overall projection patterns were similar across the injections. MT projected to occipital visual areas V1, V2, V3 (VLP) and V4 (VLA) and surrounding areas in the temporal cortex including MTC (V4T), MST, FST, FSTv (PGa/IPa) and TE3. There were also projections to the dorsal visual pathway, V3A (DA), V6 (DM) and V6A, the intraparietal areas AIP, LIP, MIP, frontal A4ab and the prefrontal cortex, A8aV and A8C. There was a visuotopic relationship with occipital visual areas. In a marmoset in which two tracer injections were made, the projection targets did not overlap in A8aV and AIP, suggesting topographic projections from different parts of MT. Most of these areas are known to send projections back to MT, suggesting that they are reciprocally connected with it.
Monocot plastid phylogenomics, timeline, net rates of species diversification, the power of multi-gene analyses, and a functional model for the origin of monocots.

PREMISE OF THE STUDY We present the first plastome phylogeny encompassing all 77 monocot families, estimate branch support, and infer monocot-wide divergence times and rates of species diversification. METHODS We conducted maximum likelihood analyses of phylogeny and BAMM studies of diversification rates based on 77 plastid genes across 545 monocots and 22 outgroups. We quantified how branch support and ascertainment vary with gene number, branch length, and branch depth. KEY RESULTS Phylogenomic analyses shift the placement of 16 families in relation to earlier studies based on four plastid genes, add seven families, date the divergence between monocots and eudicots+Ceratophyllum at 136 Mya, successfully place all mycoheterotrophic taxa examined, and support recognizing Taccaceae and Thismiaceae as separate families and Arecales and Dasypogonales as separate orders. Only 45% of interfamilial divergences occurred after the Cretaceous. Net species diversification underwent four large-scale accelerations in PACMAD-BOP Poaceae, Asparagales sister to Doryanthaceae, Orchidoideae-Epidendroideae, and Araceae sister to Lemnoideae, each associated with specific ecological/morphological shifts. Branch ascertainment and support across monocots increase with gene number and branch length, and decrease with relative branch depth. Analysis of entire plastomes in Zingiberales quantifies the importance of non-coding regions in identifying and supporting short, deep branches. CONCLUSIONS We provide the first resolved, well-supported monocot phylogeny and timeline spanning all families, and quantify the significant contribution of plastome-scale data to resolving short, deep branches. We outline a new functional model for the evolution of monocots and their diagnostic morphological traits from submersed aquatic ancestors, supported by convergent evolution of many of these traits in aquatic Hydatellaceae (Nymphaeales).
A Meta-Analysis of Pulse Arrival Time Based Blood Pressure Estimation

The paper presents a preliminary meta-analysis of the sample correlation between pulse arrival time (PAT) and blood pressure (BP). The aim of the study was to verify sample correlation coefficient between PAT and BP using an affine model $ BP = a . PAT+b $ for systolic and diastolic blood pressure. The databases included in the search were the IEEE Xplore Digital Library, Springer Link and Google Scholar. Only papers from 2005 to 2017 wereincluded into analysis. The random-effects model was considered. The resulting sample correlation coefficient was equal to -0.82 (95 % CI; -0.89, -0.72) for systolic blood pressure and -0.64 (95% CI, -0.74 -0.51) for diastolic one. Egger’s regression test showed that there was no evidence of publication bias. Obtained 95% CI intervals for sample correlation coefficients for SBP and DBP are almost separate, which may indicate different relation between PAT and BP for systolic and diastolic pressure.