Miracle-dz/UniFAR-FTUs huggingface dataset:
Affective EEG-Based Person Identification Using the Deep Learning Approach

Electroencephalography (EEG) is another method for performing person identification (PI). Due to the nature of the EEG signals, EEG-based PI is typically done while a person is performing a mental task such as motor control. However, few studies used EEG-based PI while the person is in different mental states (affective EEG). The aim of this paper is to improve the performance of affective EEG-based PI using a deep learning (DL) approach. We proposed a cascade of DL using a combination of convolutional neural networks (CNNs) and recurrent neural networks (RNNs). CNNs are used to handle the spatial information from the EEG while RNNs extract the temporal information. We evaluated two types of RNNs, namely long short-term memory (LSTM) and gated recurrent unit (GRU). The proposed method is evaluated on the state-of-the-art affective data set DEAP. The results indicate that CNN-GRU and CNN-LSTM can perform PI from different affective states and reach up to 99.90%–100% mean correct recognition rate. This significantly outperformed a support vector machine baseline system that used power spectral density features. Notably, the 100% mean CRR came from 32 subjects in DEAP data set. Even after the reduction of the number of EEG electrodes from 32 to 5 for more practical applications, the model could still maintain an optimal result obtained from the frontal region, reaching up to 99.17%. Amongst the two DL models, we found that CNN-GRU and CNN-LSTM performed similarly while CNN-GRU expended faster training time. In conclusion, the studied DL approaches overcame the influence of affective states in EEG-Based PI reported in the previous works.
End-to-End Race Driving with Deep Reinforcement Learning

We present research using the latest reinforcement learning algorithm for end-to-end driving without any mediated perception (object recognition, scene understanding). The newly proposed reward and learning strategies lead together to faster convergence and more robust driving using only RGB image from a forward facing camera. An Asynchronous Actor Critic (A3C) framework is used to learn the car control in a physically and graphically realistic rally game, with the agents evolving simultaneously on tracks with a variety of road structures (turns, hills), graphics (seasons, location) and physics (road adherence). A thorough evaluation is conducted and generalization is proven on unseen tracks and using legal speed limits. Open loop tests on real sequences of images show some domain adaption capability of our method.
Toward a low hysteresis helical scale Jamming interface inspired by teleost fish scale morphology and arrangement

Inspired by teleost fish scale, this paper investigates the possibility of implementing stiffness control as a new source of robots dexterity and flexibility control. Guessing about the possibility of biological scale jamming in real fish, we try to understand the possible underlying actuation mechanism of such behavior by conducting experiments on a Cyprinus carpio fish skin sample. Bulking tests are carried out on an encapsulated skin sample, in thin latex rubber, for unjammed and vacuum jammed cases. For the first time, we observed biological scale jamming with very small hysteresis due to the unique scale morphology and jammed stacking formation. We call this unique feature “Geometrical Jamming” where the resisting force is due to the stacking formation rather than the interlocking friction force. Inspiring by this unique morphology and helical arrangement of the scale, in this research, we investigate different possible design and actuation mechanisms for an integrable scale jamming interface for stiffness control of continuum manipulators. A set of curved scales are 3D printed which maintain a helix formation when are kept in place and jammed with two thin fishing steel wires. The non-self locking jagged contact surfaces replicate inclined stacking formation of the jammed fish scale resulting in the same reversible low hysteresis characteristics, in contrast to the available interlocking designs. The effectiveness of the designs are shown for uniaxial elongation experiments and the results are compared with similar research. The contact surfaces, in our design, can be lubricated for further hysteresis reduction to achieve smooth, repeatable and accurate stiffness control in dynamic tasks.
Towards Real-Time, Continuous Decoding of Gripping Force From Deep Brain Local Field Potentials

Lack of force information and longevity issues are impediments to the successful translation of brain–computer interface systems for prosthetic control from experimental settings to widespread clinical application. The ability to decode force using deep brain stimulation electrodes in the subthalamic nucleus (STN) of the basal ganglia provides an opportunity to address these limitations. This paper explores the use of various classes of algorithms (Wiener filter, Wiener-Cascade model, Kalman filter, and dynamic neural networks) and recommends the use of a Wiener-Cascade model for decoding force from STN. This recommendation is influenced by a combination of accuracy and practical considerations to enable real-time, continuous operation. This paper demonstrates an ability to decode a continuous signal (force) from the STN in real time, allowing the possibility of decoding more than two states from the brain at low latency.
CD38 Is Robustly Induced in Human Macrophages and Monocytes in Inflammatory Conditions

Macrophages and their monocyte precursors mediate innate immune responses and can promote a spectrum of phenotypes from pro-inflammatory to pro-resolving. Currently, there are few markers that allow for robust dissection of macrophage phenotype. We recently identified CD38 as a marker of inflammatory macrophages in murine in vitro and in vivo models. However, it is unknown whether CD38 plays a similar marker and/or functional role in human macrophages and inflammatory diseases. Here, we establish that CD38 transcript and protein are robustly induced in human macrophages exposed to LPS (±IFN-γ) inflammatory stimuli, but not with the alternative stimulus, IL-4. Pharmacologic and/or genetic CD38 loss-of-function significantly reduced the secretion of inflammatory cytokines IL-6 and IL-12p40 and glycolytic activity in human primary macrophages. Finally, monocyte analyses in systemic lupus erythematosus patients revealed that, while all monocytes express CD38, high CD38 expression in the non-classical monocyte subpopulation is associated with disease. These data are consistent with an inflammatory marker role for CD38 in human macrophages and monocytes.
Multiplying very large integer in GPU with pascal architecture

Multiplication plays an important role in scientific computing and cryptography. When the size of multiplicands grow large (e.g. more than 100K-bit), the multiplication process become time consuming. In this paper, we present implementation techniques to multiply very large integer in state of the art GPU architecture. The implementation relies on Number Theoretic Transform with 64-bit prime. The implementation results show that multiplication of 768K-bit integer takes 1.37 milliseconds on GTX1070 (GPU with Pascal architecture). The work presented in this paper can be used to implement various advanced cryptosystem, including Homomorphic Encryption and Lattice based cryptography.
Increased Nrf2 expression by renal cell carcinoma is associated with postoperative chronic kidney disease and an unfavorable prognosis

Chronic kidney disease (CKD) is a worldwide health problem, and prevention of CKD is important for preservation of renal function after kidney surgery. There is evidence that transcription factor nuclear factor erythroid 2–related factor 2 (Nrf2) has a vital antioxidant and detoxifying role in protecting the kidneys against various diseases. Impaired activation of Nrf2 is associated with oxidative stress related to CKD, and Nrf2 is also a key player in the development of cancer. However, the clinical impact of Nrf2 has not been investigated in patients with renal cell carcinoma (RCC). A retrospective study was performed in 89 patients undergoing nephrectomy for RCC. The estimated glomerular filtration rate (eGFR) and serum uric acid (SUA) were investigated over time after surgery. We investigated Nrf2 protein expression in all tumors and single nucleotide polymorphisms (SNPs) of the Nrf2 gene in 7 tumors. In patients whose tumors showed higher Nrf2 expression, there was a more rapid decrease of eGFR and increase of SUA after nephrectomy. Multivariate analysis confirmed that increased Nrf2 expression was an independent poor prognostic factor related to shorter overall survival. Among the 7 tumor samples, an SNP on exon 5 of the Nrf2 gene in one tumor and three genotypes (C/C, C/A, and A/A) of rs6721961 at the promoter region of the Nrf2 gene were observed. Although the mechanisms underlying the influence of Nrf2 are still unclear, our findings suggested that elevated tumor expression of Nrf2 was associated with postoperative CKD and biologically aggressive RCC with an unfavorable prognosis.
Robust H∞ tracking consensus for nonlinear multi-agent systems with time-varying delay

The distributed robust H∞ consensus problem for second-order multi-agent systems with time-varying delay and nonlinear dynamics is considered in this paper. Considering the multi-agent systems with external disturbances and model uncertainty, the consensus control protocols are designed and analyzed. By Lyapunov functional theory and linear matrices inequality(LMI) method, some sufficient conditions are given to ensure the multi-agent systems can reach consensus with the given H∞ performance.
Personalizing Radiation Treatment Delivery in the Management of Breast Cancer

Long-term data establishes the efficacy of radiotherapy in the adjuvant management of breast cancer. New dose and fractionation schemas have evolved and are available, each with unique risks and rewards. Current efforts are ongoing to tailor radiotherapy to the unique biology of breast cancer. In this review, we discuss our efforts to personalize radiotherapy dosing using genomic data and the implications for future clinical trials. We also explore immune mechanisms that may contribute to a tumor's unique radiation sensitivity or resistance.
Simulation of a Trust and Reputation Based Mitigation Protocol for a Black Hole Style Attack on VANETs

From a security standpoint, VANETs (Vehicular ad hoc Networks) are vulnerable to attacks by malicious users, due to the decentralized and open nature of the wireless system. For many of these kinds of attacks detection is unfeasible, thus making it hard to produce security. Despite their characterization as dynamically reconfigurable networks, it is nonetheless essential to identify topology and population properties that can optimise mitigation protocols' deployment. In this paper, we provide an algorithmic definition and simulation of a trust and mitigation based protocol to contain a Black Hole style attack on a VANET. We experimentally show its optimal working conditions: total connectivity, followed by a random network; connection to external networks; early deployment of the protocol and ranking of the message. We compare results with those of existing protocols and future work shall focus on repeated broadcasting, opportunistic message forwarding and testing on real data.
Neural adaptive output-feedback control of non-affine nonlinear systems with unknown control direction

This paper presents a neuro-adaptive output feedback controller for a class of non-affine nonlinear systems. Firstly, by introducing the newly defined variables and applyling the mean value theorem, the non-affine dynamic is transformed into an affine form, and a finite time observer is designed to estimate the unknown states of the system. Secondly, based on the transformed system, by introducing the neural networks (NNs) and the Nussbaum-type function, the problem of lack of priori knowledge on the dynamic model and control direction is addressed. In addition, a barrier Lyapunov function(BLF) is introduced to guarantee the prescribed tracking performance of the control system. The stability of the closed-loop system is analyzed. Simulations are conducted to verify the effectiveness of the proposed control law.
ECOLOGIC WATER TRANSFUSION IN THE LOWER REACHES OF THE TARIM RIVER BASED ON CBERS/CCD IMAGE

Based on the ecological water transfusion data from the Bureau of Tarim River Administration and Management(TRAM),the information about the time of conveyance,duration,water volume and arrival were collected to analyze the processes and impacts of ecological water transfusion in the lower reaches of the Tarim River.Using CBERS/CCD remote sensing images(19.5 m spatial resolution) during 2000-2007,actual river channel inundated with water and water accumulated areas including the length and width of the water surface were extracted by photo interpretation and digital image analysis.The information was then associated with water transfusion data and used to monitor ecological water transfusion situation.The results show that the length of river channel inundated with water was 514.13 km,and the width of average river channel was about 42.23 m.Compared with field investigations,the accuracy of the results derived from remote sensing images was 97.5%. The relationship between water channel width and ecological water transfusion volume was positively correlated.The maximum river channel width was more than 50 m,which appeared in 2003 because of the maximum ecological water transfusion.However,the minimum river channel width was only 28.98 m in 2000 due to the minimum amount of ecological water transfusion. "Overflow" type of ecological water transfusion had been adopted by the TRAM.As the result,rather amount of water had been accumulated in the lowlands from the Daxihaizi Reservoir to Kardy.It was closely related to the ecological water volume and the distance from the reservoir.The total number of flow accumulated areas between the Daxihaizi Reservoir and Kardy reached to the 153 from 2000 to 2007,and the area was about 19.87 km2.In contrast,the number of flow accumulated areas was counted as only 43 from Kardy to the Tetima Lake,with an area of 8.32 km2.Overall,the results of remote sensing observation were in accordance with field measurements.However,there was certain uncertainty in our results,which might be associated with the quality of remote sensing images and the time differences between the exact time of water transfusion took place and the images were collected.We conclude that the remote sensing,Geography Information System(GIS),and Global Position System(GPS) may provide an accurate and convenient method to detect the ecological water transfusion process.
Candida albicans-Induced NETosis Is Independent of Peptidylarginine Deiminase 4

Neutrophils are the most abundant innate immune cells and the first line of defense against many pathogenic microbes, including the human fungal pathogen Candida albicans. Among the neutrophils’ arsenal of effector functions, neutrophil extracellular traps (NETs) are thought to be of particular importance for trapping and killing the large fungal filaments by means of their web-like structures that consist of chromatin fibers decorated with proteolytic enzymes and host defense proteins. Peptidylarginine deiminase 4 (PAD4)-mediated citrullination of histones in activated neutrophils correlates with chromatin decondensation and extrusion and is widely accepted to act as an integral process of NET induction (NETosis). However, the requirement of PAD4-mediated histone citrullination for NET release during C. albicans infection remains unclear. In this study, we show that although PAD4-dependent neutrophil histone citrullination is readily induced by C. albicans, PAD4 is dispensable for NETosis in response to the fungus and other common NET-inducing stimuli. Moreover, PAD4 is not required for antifungal immunity during mucosal and systemic C. albicans infection. Our results demonstrate that PAD4 is dispensable for C. albicans-induced NETosis, and they highlight the limitations of using histone citrullination as a marker for NETs and PAD4−/− mice as a model of NET-deficiency.
Trajectories of Growth and Serum DHEAS and IGF-1 Concentrations in Girls With a History of Premature Adrenarche: Attenuation of the Phenotype by Adulthood

Background: It has been speculated that premature adrenarche (PA) could lead to unfavorable outcome, including shorter adult stature, but longitudinal follow-up data are insufficient. Methods: This prospective case-control study included 30 PA and 42 control females who were born mostly full-term and appropriate for gestational age. They were examined first at the median age of 7.6 years and now at 18.1 years. Main outcome measures were height, body mass index (BMI), age at menarche, and serum dehydroepiandrosterone sulfate (DHEAS) and insulin-like growth factor 1 (IGF-1) concentrations. Results: The PA and control females had comparable mean (standard deviation) adult height [167.2 (6.8) vs. 164.5 (5.1) cm, P = 0.059] and median (25th–75th percentiles) BMI [22.8 (21.1–28.9) vs. 21.6 (19.8–24.3) kg/m2, P = 0.068, respectively]. Adult heights were comparable with the mid-parental heights in both study groups. The PA females were taller than the controls until the age of 12 years and they lacked a distinct pubertal growth spurt. Serum DHEAS and IGF-1 concentrations did not differ between the PA and control groups at the age of 18 years. Median (range) age at menarche was significantly lower in the PA than control females [11.5 (9.5–15.0) vs. 13.0 (10.0–15.0), P = 0.001]. Conclusions: Although PA girls have advanced growth and earlier pubertal development together with a tendency to be more overweight, their height, BMI, and serum DHEAS and IGF-1 concentrations are comparable to those of their peers at the age of 18 years. Our findings indicate a benign outcome of PA in appropriate for gestational age -born females concerning adult height and adrenal androgen secretion.
TREM2-Dependent Effects on Microglia in Alzheimer’s Disease

Alzheimer’s disease (AD) is a late-onset dementia characterized by the deposition of amyloid plaques and formation of neurofibrillary tangles (NFTs) which lead to neuronal loss and cognitive deficits. Abnormal protein aggregates in the AD brain are also associated with reactive microglia and astrocytes. Whether this glial response is beneficial or detrimental in AD pathology is under debate. Microglia are the resident innate immune cells in the central nervous system (CNS) that survey the surrounding environment. Genome-wide association studies (GWAS) have identified the R47H variant of triggering receptor expressed on myeloid cell 2 (TREM2) as a risk factor for late-onset AD (LOAD) with an odds ratio of 4.5. TREM2 is an immunoreceptor primarily present on microglia in the CNS that binds to polyanionic molecules. The transmembrane domain of TREM2 signals through DAP12, an adaptor protein that contains an immunoreceptor tyrosine-based activation motif (ITAM), which mediates TREM2 signaling and promotes microglial activation and survival. In mouse models of AD, Trem2 haplodeficiency and deficiency lead to reduced microglial clustering around amyloid β (Aβ) plaques, suggesting TREM2 is required for plaque-associated microglial responses. Recently, TREM2 has been shown to enhance microglial metabolism through the mammalian target of rapamycin (mTOR) pathway. Although aberrant metabolism has long been associated with AD, not much was known regarding how metabolism in microglia might affect disease progression. In this review, we discuss the role of TREM2 and metabolism in AD pathology, highlighting how TREM2-mediated microglial metabolism modulates AD pathogenesis.
The Goldilocks zone: Towards better understanding of neural network loss landscapes

We explore the loss landscape of fully-connected and convolutional neural networks using random, low-dimensional hyperplanes and hyperspheres. Evaluating the Hessian, H, of the loss function on these hypersurfaces, we observe 1) an unusual excess of the number of positive eigenvalues of H, and 2) a large value of Tr(H)/||H|| at a well defined range of configuration space radii, corresponding to a thick, hollow, spherical shell we refer to as the Goldilocks zone. We observe this effect for fully-connected neural networks over a range of network widths and depths on MNIST and CIFAR-10 datasets with the ReLU and tanh non-linearities, and a similar effect for convolutional networks. Using our observations, we demonstrate a close connection between the Goldilocks zone, measures of local convexity/prevalence of positive curvature, and the suitability of a network initialization. We show that the high and stable accuracy reached when optimizing on random, low-dimensional hypersurfaces is directly related to the overlap between the hypersurface and the Goldilocks zone, and as a corollary demonstrate that the notion of intrinsic dimension is initialization-dependent. We note that common initialization techniques initialize neural networks in this particular region of unusually high convexity/prevalence of positive curvature, and offer a geometric intuition for their success. Furthermore, we demonstrate that initializing a neural network at a number of points and selecting for high measures of local convexity such as Tr(H)/||H||, number of positive eigenvalues of H, or low initial loss, leads to statistically significantly faster training on MNIST. Based on our observations, we hypothesize that the Goldilocks zone contains an unusually high density of suitable initialization configurations.
Enhancing Transparency and Consent in the IoT

The development of the IoT raises specific questions in terms of privacy, especially with respect to information to users and consent. We argue that (1) all necessary information about collected data and the collecting devices should be communicated electronically to all data subjects in their range and (2) data subjects should be able to reply also electronically and express their own privacy choices. In this position paper, we take some examples of technologies and initiatives to illustrate our position (including direct and registry-based communications) and discuss them in the light of the GDPR and the WP29 recommendations.