Miracle-dz/UniFAR-FTUs huggingface dataset:
Skybridge-3D-CMOS: A Vertically-Composed Fine-Grained 3D CMOS Integrated Circuit Technology

Parallel and monolithic 3D-integration directions offer pathways to realize 3D integrated circuits but still lead to layer-by-layer implementations. This mindset causes challenging connectivity and alignment between layers when connected in 3D, with a routing access that can be even worse than 2D-CMOS, which fundamentally limits their potential. To fully exploit the opportunities in the third dimension, we propose Skybridge-3D-CMOS (S3DC), a fine-grained 3D-integration approach that is directly composed in 3D, utilizing the vertical dimension vs. a layer-by-layer assembly mindset. S3DC uses a novel wafer fabric creation with direct 3D design and connectivity in the vertical dimension. It builds on a uniform vertical nanowire template that is processed as a single wafer, it incorporates specifically architected structures for realizing devices, circuits, and heat management in 3D. Novel 3D interconnect concepts, including within the silicon layers, enable significantly improved routing flexibility in three dimensions and a high-density 3D design paradigm overall. Intrinsic components for fabric-level heat management are introduced. Extensive bottom-up simulations and experiments have been presented to validate the key fabric-enabling concepts. Evaluations indicate up to 40x density and 10x performance-per-watt benefits against 16-nm 2D-CMOS for the circuits studied, benefits are also substantially beyond what was projected in other 3D directions.
Motion estimation via dynamic vision

Estimating the 3D motion of an object from a sequence of projections is of paramount importance in a variety of applications in control and robotics. Although "visual motion estimation" is an old problem, only recently tools from control and estimation theory have hinted at acceptable solutions. Moreover, the problem raises a number of issues of system theoretic interest, such as nonlinear estimation and identification on topological manifolds and observability in a projective geometric framework. In this paper we analyze a formulation of the visual motion estimation problem in terms of identification of nonlinear implicit systems with parameters on the so-called "essential manifold"; the estimation is performed either in the local coordinates or in the embedding space of the parameter manifold. <<ETX>>
Autism at the beginning: Microstructural and growth abnormalities underlying the cognitive and behavioral phenotype of autism

Autistic symptoms begin in the first years of life, and recent magnetic resonance imaging studies have discovered brain growth abnormalities that precede and overlap with the onset of these symptoms. Recent postmortem studies of the autistic brain provide evidence of cellular abnormalities and processes that may underlie the recently discovered early brain overgrowth and arrest of growth that marks the first years of life in autism. Alternative origins and time tables for these cellular defects and processes are discussed. These cellular and growth abnormalities are most pronounced in frontal, cerebellar, and temporal structures that normally mediate the development of those same higher order social, emotional, speech, language, speech, attention, and cognitive functions that characterize autism. Cellular and growth pathologies are milder and perhaps nonexistent in other structures (e.g., occipital cortex), which are known to mediate functions that are often either mildly affected or entirely unaffected in autistic patients. It is argued that in autism, higher order functions largely fail to develop normally in the first place because frontal, cerebellar, and temporal cellular and growth pathologies occur prior to and during the critical period when these higher order neural systems first begin to form their circuitry. It is hypothesized that microstructural maldevelopment results in local and short distance overconnectivity in frontal cortex that is largely ineffective and in a failure of long-distance cortical–cortical coupling, and thus a reduction in frontal–posterior reciprocal connectivity. This altered circuitry impairs the essential role of frontal cortex in integrating information from diverse functional systems (emotional, sensory, autonomic, memory, etc.) and providing context-based and goal-directed feedback to lower level systems.The authors were supported by funds from the National Institute of Mental Health (2-ROI-MH36840) and National Institute of Neurological Disorders and Stroke (2-ROI-NS19855) awarded to Eric Courchesne.
DART-MS: A new research tool for herbal medicine analysis

Direct analysis in real time (DART) possesses the merits of analyzing sample in its native status with minimal or even no sample pretreatment. In this review, we summarized the recent applications of DART in the field of herbal medicine analysis such as compound detection, species identification, metabolites profiling and initial quantification. DART with the characters of hyper-rapid, easy-hyphenated offers a new research tool for herbal medicines to complete the experimental process in a very simple but still reliable way. It is anticipated that more wide and deep applications of DART in herbal medicine analysis, as rapid quantification, high-throughput active compounds screening, rapid species identification, and fast illegal additives screening will be promising and foreseeable in the near future.
Nanowire Arrays Defined by Nanoimprint Lithography

We demonstrate the use of nanoimprint lithography to define arrays of vertical InP nanowires. Each nanowire is individually seeded from a catalyzing gold particle and then grown via vapor-liquid-solid growth in a metal-organic vapor phase epitaxy system. The diameter and position of each nanowire can be controlled to create engineered arrays, demonstrated with a hexagonal photonic crystal pattern. This combination of nanoimprint and self-assembly of nanostructures is attractive for photonics and electronics, as well as in life sciences.
Surface modification of PLGA microspheres.

Microspheres made of poly(lactic-co-glycolic acid) (PLGA) are biocompatible and biodegradable, rendering them a promising tool in the context of drug delivery. However, nonspecific adsorption of plasma proteins on PLGA micro- and nanospheres is a main limitation of drug targeting. Poly(L-lysine)-g-poly(ethylene glycol) (PLL-g-PEG), physisorbed on flat metal oxide surfaces, has previously been shown to suppress protein adsorption drastically. The goal of our work was to characterize the efficiency of the protein repellent character of PLL-g-PEG on PLGA microspheres and to show the feasibility of introducing functional groups on the PLGA microspheres via functionalized PLL-g-PEG. To quantify the adsorbed amount of protein, a semiquantitative method that uses confocal laser scanning microscopy (CLSM) was applied. The first part of the experiment confirms the feasibility of introducing specific functional groups on PLL-g-PEG-coated PLGA microspheres. In the second part of the experiment, PLL-g-PEG-coated PLGA microspheres show a drastic decrease of adsorbed proteins by two orders of magnitude in comparison to uncoated PLGA microspheres. Low protein-binding, functionalizable microspheres provide a fundamental basis for the design of drug delivery and biosensor systems.
New Information in Trending Topics of Tweets by Labelled Clusters

Twitter is a popular micro-blogging service, and one of the main means of spreading ideas and information throughout the web. In this system, participants post short status messages called tweets that are often available publicly. Recently, the exponential growth of tweets has started to draw the attention of researchers from various disciplines. Numerous research approaches in the data mining field have examined Twitter. How to automatically extract useful information from tweets has therefore become an important research topic. The aim of this paper is to bring up what's up which is a new approach of tweets mining. It is a more general approach that discovers many different trending topics from tweets in real-time. Trending topics have generated big interest not only for the users of Twitter but also for information seekers. Our trending topics are detected for a specific geographic town and compared with the top trending topics shown on Twitter. They are presented by labelled clusters that constitute an accurate description of each trending topic. Each cluster is labelled by an emerging trending topic and is composed of keywords that represent the properties of the trending topic.
Synthesis of Research: Extending Unbiased Stereology of Brain Ultrastructure to Three-dimensional Volumes

OBJECTIVE Analysis of brain ultrastructure is needed to reveal how neurons communicate with one another via synapses and how disease processes alter this communication. In the past, such analyses have usually been based on single or paired sections obtained by electron microscopy. Reconstruction from multiple serial sections provides a much needed, richer representation of the three-dimensional organization of the brain. This paper introduces a new reconstruction system and new methods for analyzing in three dimensions the location and ultrastructure of neuronal components, such as synapses, which are distributed non-randomly throughout the brain. DESIGN AND MEASUREMENTS Volumes are reconstructed by defining transformations that align the entire area of adjacent sections. Whole-field alignment requires rotation, translation, skew, scaling, and second-order nonlinear deformations. Such transformations are implemented by a linear combination of bivariate polynomials. Computer software for generating transformations based on user input is described. Stereological techniques for assessing structural distributions in reconstructed volumes are the unbiased bricking, disector, unbiased ratio, and per-length counting techniques. A new general method, the fractional counter, is also described. This unbiased technique relies on the counting of fractions of objects contained in a test volume. A volume of brain tissue from stratum radiatum of hippocampal area CA1 is reconstructed and analyzed for synaptic density to demonstrate and compare the techniques. RESULTS AND CONCLUSIONS Reconstruction makes practicable volume-oriented analysis of ultrastructure using such techniques as the unbiased bricking and fractional counter methods. These analysis methods are less sensitive to the section-to-section variations in counts and section thickness, factors that contribute to the inaccuracy of other stereological methods. In addition, volume reconstruction facilitates visualization and modeling of structures and analysis of three-dimensional relationships such as synaptic connectivity.
Doped HfO2 based nanoelectronic memristive devices for self-learning neural circuits and architecture

In this work we introduce a two-terminal memristive device using Mn doped HfO2. The devices can emulate synaptic behavior based on their transient characteristics. These properties can be exploited to show spike-timing based learning in a network of neurons and synapses. We use the device characteristics to simulate a 4×4 crossbar array of synapses and observe the evolution of the weights over time. The effect of device variability on the performance of synaptic weight update has been examined based on different test conditions of initial randomness and variation in percentage change of strength during spike-timing based updates. Some inferences have been drawn regarding the need of additional circuits for improving reliability of the cross-bar arrays. We believe this study is critical in assessing the design constraints and requirements necessary for integrating memristive devices in crossbars for spike based computations.
Enhancing Security of Software Defined Mobile Networks

Traffic volumes in mobile networks are rising and end-user needs are rapidly changing. Mobile network operators need more flexibility, lower network operating costs, faster service roll-out cycles, and new revenue sources. The 5th Generation (5G) and future networks aim to deliver ultra-fast and ultra-reliable network access capable of supporting the anticipated surge in data traffic and connected nodes in years to come. Several technologies have been developed to meet these emergent demands of future mobile networks, among these are software defined networking, network function virtualization, and cloud computing. In this paper, we discuss the security challenges these new technologies are prone to in the context of the new telecommunication paradigm. We present a multi-tier component-based security architecture to address these challenges and secure 5G software defined mobile network (SDMN), by handling security at different levels to protect the network and its users. The proposed architecture contains five components, i.e., secure communication, policy-based communication, security information and event management, security defined monitoring, and deep packet inspection components for elevated security in the control and the data planes of SDMNs. Finally, the proposed security mechanisms are validated using test bed experiments.
The role of the basal ganglia in the control of automatic visuospatial attention

Cognitive impairments in patients with basal ganglia dysfunction are primarily revealed where performance relies on internal, voluntary control processes. Evidence suggests that this also extends to impaired control of more automatic processes, including visuospatial attention. The present study used a non-predictive peripheral cueing paradigm to compare and contrast visuospatial deficits in patients with Parkinson's disease (PD) with those previously revealed in patients with Huntington's disease (HD) (Fielding et al., 2006a). Compared to age-matched controls, both PD and HD patients exhibited increased distractibility or poor fixation, however only PD patients responded erroneously to cue stimuli more frequently than control subjects. All subjects demonstrated initial facilitation for valid versus invalid cues following the shorter stimulus-onset asynchronies (SOAs) and a performance decrement at the longer SOAs (inhibition of return), although there was a clear differentiation between these groups for immediate SOAs. Unlike both control and PD subjects, where IOR manifested between 350 and 1000 msec, IOR was evident as early as 150 msec for HD patients. Further, for PD patients, spatially valid cues resulted in hyper-reflexivity following 150 msec SOAs, with saccadic latencies shorter than those generated in response to un-cued targets. Thus contrasting deficits were revealed in PD and HD, emphasizing the important contribution of the basal ganglia in the control of more automatic behaviors (JINS, 2006, 12, 657–667.)
Toward Effortless TV-to-Online (T2O) Experience: A Novel Metric Learning Approach

Shopping of the same or similar types of products as shown in the online TV programs has been highly desired by many people, especially the youth. To meet this eminent market need, we develop a prototype system to enable effortless TV-to-Online (T2O) experience. A key component of this system is the product search that maps specific items embedded in the video into a list of online merchants. The search performance mainly depends on the estimation of the distance or similarity between the queried item and all the curated items in the database. The simple Euclidean (EU) distance cannot capture the data characteristics, we therefore introduce distance metric learning (DML) to improve the distance estimation. Traditional DML methods only utilize the side information (e.g., similar/dissimilar constraints or relevance/irrelevance judgements) in the target domain, and may fail when the side information is scarce. Transfer metric learning (TML) can be adopted to leverage the side information from related domains. In this paper, we treat each domain equally and propose a novel Ranking-based Heterogeneous Multi-Task Metric Learning (RHMTML) framework, which adopts ranking-based loss, so the learned metric is particularly suitable for search. Extensive experiments demonstrate the effectiveness of our proposed method. We foresee that our approach would transform the emerging T2O trend in both TV and online video market.
Draft Genome Sequence of Thermogemmatispora onikobensis NBRC 111776T, an Aerial Mycelium- and Spore-Forming Thermophilic Bacterium Belonging to the Class Ktedonobacteria

ABSTRACT Here, we report the draft genome sequence of Thermogemmatispora onikobensis NBRC 111776T, an aerial mycelium- and spore-forming thermophilic bacterium belonging to the class Ktedonobacteria. The genome contains five biosynthetic gene clusters coding for secondary metabolites, such as terpene, thiopeptide, lantipeptide, nonribosomal peptide, and lassopeptide, suggesting the potential to produce secondary metabolites.
Towards Forgery-Resistant Touch-based Biometric Authentication on Mobile Devices

Mobile devices store a diverse set of private user data and have gradually become a hub to control users’ other personal Internet-of-Things devices. Access control on mobile devices is therefore highly important. The widely accepted solution is to protect access by asking for the correct password. However, password authentication is tedious, e.g., a user needs to input a password every time she wants to use the device. Moreover, existing biometrics such as face, fingerprint, and touch behaviors are vulnerable to forgery attacks. We propose a new touch-based biometric authentication system that is passive and secure against forgery attacks. In our touch-based authentication, a user’s touch behavior is a function of some random “secret”. The user can subconsciously know the secret while touching the device’s screen. However, an attacker cannot know the secret at the time of attacks, which makes it challenging to perform forgery attacks even if the attacker has already obtained the user’s touch behaviors. We evaluate our touch-based authentication system via collecting data from 25 subjects. Results are promising: the random secrets do not influence user experience and our system achieves 0.18 smaller Equal Error Rates (EERs) than previous touch-based authentication for targeted forgery attacks.
Frontotemporal and dopaminergic control of idea generation and creative drive

This article presents a three‐factor anatomical model of human idea generation and creative drive, focusing on interactions between the temporal lobes, frontal lobes, and limbic system. Evidence is drawn from functional imaging, drug studies, and lesion analysis. Temporal lobe changes, as in hypergraphia, often increase idea generation, sometimes at the expense of quality. Frontal lobe deficits may decrease idea generation, in part because of rigid judgments about an idea's worth. These phenomena are clearest in verbal creativity, and roughly parallel the pressured communication of temporal lobe epilepsy, mania, and Wernicke's aphasia—compared to the sparse speech and cognitive inflexibility of depression, Broca's aphasia, and other frontal lobe lesions. The phenomena also shape non‐linguistic creativity, as in that of frontotemporal dementia. The appropriate balance between frontal and temporal activity is mediated by mutually inhibitory corticocortical interactions. Mesolimbic dopamine influences novelty seeking and creative drive. Dopamine agonists and antagonists have opposite effects on goal‐directed behavior and hallucinations. Creative drive is not identical to skill—the latter depends more on neocortical association areas. However, drive correlates better with successful creative output than skill does. Traditional neuroscientific models of creativity, such as the left brain – right brain hemispheric model, emphasize skills primarily, and stress art and musical skill at the expense of language and mathematics. The three‐factor model proposed here predicts findings in a broad range of normal and pathological states and can be tested in many experimental paradigms. J. Comp. Neurol. 493:147–153, 2005. © 2005 Wiley‐Liss, Inc.
Expressive Visualization and Rapid Interpretation of Seismic Volumes

One of the most important resources in the world today is energy. Oil and gas provide two thirds of the world energy consumption, making the world completely dependent on it. Locating and recovering the remaining oil and gas reserves will be of high focus in society until competitive energy sources are found. The search for hydrocarbons is broadly speaking the topic of this thesis. Seismic measurements of the subsurface are collected to discover oil and gas trapped in the ground. Identifying oil and gas in the seismic measurements requires visualization and interpretation. Visualization is needed to present the data for further analysis. Interpretation is performed to identify important structures. Visualization is again required for presenting these structures to the user. This thesis investigates how computer assistance in producing high-quality visualizations and in interpretation can result in expressive visualization and rapid interpretation of seismic volumes. Expressive visualizations represent the seismic data in an easily digestible, intuitive and pedagogic form. This enables rapid interpretation which accelerates the finding of important structures.
UvA-DARE (Digital Academic Repository) American College of Rheumatology/European League against Rheumatism provisional definition of remission in rheumatoid arthritis for clinical trials

Felson, D.T. ; Smolen, J.S. ; Wells, G. ; Zhang, B. ; van Tuyl, L.H. D. ; Funovits, J.; Aletaha, D. ; Allaart, C.F. ; Bathon, J.; Bombardieri, S. ; Brooks, P.; Brown, A. ; Matucci-Cerinic, M. ; Choi, H. ; Combe, B. ; de Wit, M. ; Dougados, M. ; Emery, P.; Furst, D. ; Gomez-Reino, J.; Hawker, G. ; Keystone, E. ; Khanna, D. ; Kirwan, J.; Kvien, T.K. ; Landewé, R. ; Listing, J.; Michaud, K. ; Martin-Mola, E. ; Montie, P.; Pincus, T. ; Richards, P.; Siegel, J.N. ; Simon, L.S. ; Sokka, T. ; Strand, V. ; Tugwell, P.; Tyndall, A. ; van der Heijde, D. ; Verstappen, S. ; White, B. ; Wolfe, F. ; Zink, A. ; Boers, M.