Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of a cognitive psychophysiological model for management of tic disorders: an open trial

Background Tic disorders, in particular chronic tic disorder and Tourette syndrome, affect about 1% of the population. The current treatment of choice is pharmacological or behavioural, addressing tics or the premonitory urges preceding tic onset. Aims The current study reports an open trial evaluating the effectiveness of a cognitive psychophysiological treatment addressing Tourette-specific sensorimotor activation processes rather than the tic. Method Forty-nine people with Tourette syndrome and 36 people with chronic tics completed 10 weeks of individual cognitive psychophysiological therapy. Outcome measures included two tic severity scales and psychosocial measures. Results Post-treatment both groups had significantly improved on the tic scales with strong effect sizes across tic locations and complex and simple tics, maintained at 6-month follow-up with further change in perfectionism and self-esteem. Conclusions The cognitive psychophysiological approach targeting underlying sensorimotor processes rather than tics in Tourette's and chronic tic disorder reduced symptoms with a large effect size.
Competing endogenous RNA network analysis identifies critical genes among the different breast cancer subtypes

Although competing endogenous RNAs (ceRNAs) have been implicated in many solid tumors, their roles in breast cancer subtypes are not well understood. We therefore generated a ceRNA network for each subtype based on the significance of both, positive co-expression and the shared miRNAs, in the corresponding subtype miRNA dys-regulatory network, which was constructed based on negative regulations between differentially expressed miRNAs and targets. All four subtype ceRNA networks exhibited scale-free architecture and showed that the common ceRNAs were at the core of the networks. Furthermore, the common ceRNA hubs had greater connectivity than the subtype-specific hubs. Functional analysis of the common subtype ceRNA hubs highlighted factors involved in proliferation, MAPK signaling pathways and tube morphogenesis. Subtype-specific ceRNA hubs highlighted unique subtype-specific pathways, like the estrogen response and inflammatory pathways in the luminal subtypes or the factors involved in the coagulation process that participates in the basal-like subtype. Ultimately, we identified 29 critical subtype-specific ceRNA hubs that characterized the different breast cancer subtypes. Our study thus provides new insight into the common and specific subtype ceRNA interactions that define the different categories of breast cancer and enhances our understanding of the pathology underlying the different breast cancer subtypes, which can have prognostic and therapeutic implications in the future.
Feedback stabilization of nonlinear systems with unknown control directions and time-delay

Global stabilization by state feedback is investigated for a class of time-delay nonlinear systems with unknown control directions. A dynamic state feedback control scheme is developed to achieve asymptotic state regulation with global stability. The proposed dynamic compensator employs, on one hand, the idea of the Nussbaum-gain functions to mitigate the effects of unknown control directions, and the Riccati-like gain update laws to counteract the time-delay nonlinearity, on the other hand. The proof of the closed-loop stability and state regulation is based on a novel construction of Lyapunov-Krasovskii functionals that are crucial in dealing with unknown control directions and time-delay nonlinearity.
Transition-based dependency parser with postponed determinations for Japanese sentences

Dependency analysis is recognized as a basic part of natural language processing. Transition-based dependency parsers transition between states in a deterministic way using local state information. Because most transition-based parsers are incremental, once they add an incorrect dependency between lexical tokens, this is never revised. Therefore, an incorrect final state is reached. To avoid the addition of incorrect dependencies, this paper reports the progress of research to develop a novel transition-based parser that postpones the determination of whether to add a dependency between a certain pair of lexical tokens.
Your solution, their problem—Their solution, your problem

Abstract Cultural heritage management is, in essence, a facet of social engineering, whereby physical remains of the past (and present) are selectively preserved based on values currently held by the population at large. Indeed, mid- and long-term protection of heritage sites can only occur if such places are “embraced” or “owned” by the community. However, public opinion, often colored by nostalgia, omits, consciously or unconsciously, places that do not fit the present value system. Thus, inevitably, there are places that need to be preserved that are identified by expert opinion, even if a community is apathetic or even antagonistic. Such differences of opinion allow conflicts to occur. Local planning and the implementation of planning priorities are inevitably caught up in it. The political dimension at the Local Government Authority (LGA) level further complicates matters, particularly as we move from one heritage to a multitude of “heritages. ” Over the past decade, the management of cultural heritage sites at the local government level has seen the decline of top-down, expert-driven studies, while bottom-up, community-driven, or at least community influenced, studies have increased. Both approaches have their failings and lead to gaps in the record. Furthermore, all too often heritage plans are limited. Great effort is expended focusing on the historic trends and themes of an area and on inventorying, evaluating and listing places deemed worth protecting. Yet, next to no effort is spent on implementation strategies, ranging from capacity building within the administering local government to education of property owners, wider stakeholders, public residents in the LGA and outside visitors. This paper discusses the pitfalls inherent in the various planning approaches and outlines strategies for LGA-level planning and management to maximize returns from heritage planning projects.
Fingertip-based Real Time Tracking and Gesture Recognition for Natural User Interfaces

The widespread deployment of Natural User Interface (NUI) systems in smart terminals such as phones, tablets and TV sets has heightened the need for robust multitouch, speech or facial recognition solutions. Air gestures recognition represents one of the most appealing technologies in the field. This work proposes a fingertip-based approach for hand gesture recognition. The novelty in the proposed system is the tracking principle, where an improved version of the multi-scale mode filtering (MSMF) algorithm is used, and in the classification step, where the proposed set of geometric features provides high discriminative capabilities. Empirically, we conducted an experimental study involving hand gesture recognition – on gestures performed by multiple persons against a variety of backgrounds – in which our approach achieved a global recognition rate of 95.66%.
The M-current contributes to high threshold membrane potential oscillations in a cell type-specific way in the pedunculopontine nucleus of mice

The pedunculopontine nucleus is known as a cholinergic nucleus of the reticular activating system, participating in regulation of sleep and wakefulness. Besides cholinergic neurons, it consists of GABAergic and glutamatergic neurons as well. According to classical and recent studies, more subgroups of neurons were defined. Groups based on the neurotransmitter released by a neuron are not homogenous, but can be further subdivided. The PPN neurons do not only provide cholinergic and non-cholinergic inputs to several subcortical brain areas but they are also targets of cholinergic and other different neuromodulatory actions. Although cholinergic neuromodulation has been already investigated in the nucleus, one of its characteristic targets, the M-type potassium current has not been described yet. Using slice electrophysiology, we provide evidence in the present work that cholinergic neurons possess M-current, whereas GABAergic neurons lack it. The M-current contributes to certain functional differences of cholinergic and GABAergic neurons, as spike frequency adaptation, action potential firing frequency or the amplitude difference of medium afterhyperpolarizations (AHPs). Furthermore, we showed that high threshold membrane potential oscillation with high power, around 20 Hz frequency is a functional property of almost all cholinergic cells, whereas GABAergic neurons have only low amplitude oscillations. Blockade of the M-current abolished the oscillatory activity at 20 Hz, and largely diminished it at other frequencies. Taken together, the M-current seems to be characteristic for PPN cholinergic neurons. It provides a possibility for modulating gamma band activity of these cells, thus contributing to neuromodulatory regulation of the reticular activating system.
A flexible cure rate model with dependent censoring and a known cure threshold

We propose a flexible cure rate model that accommodates different censoring distributions for the cured and uncured groups and also allows for some individuals to be observed as cured when their survival time exceeds a known threshold. We model the survival times for the uncured group using an accelerated failure time model with errors distributed according to the seminonparametric distribution, potentially truncated at a known threshold. We suggest a straightforward extension of the usual expectation–maximization algorithm approach for obtaining estimates in cure rate models to accommodate the cure threshold and dependent censoring. We additionally suggest a likelihood ratio test for testing for the presence of dependent censoring in the proposed cure rate model. We show through numerical studies that our model has desirable properties and leads to approximately unbiased parameter estimates in a variety of scenarios. To demonstrate how our method performs in practice, we analyze data from a bone marrow transplantation study and a liver transplant study. Copyright © 2016 John Wiley & Sons, Ltd.
Design and Implementation of a 1-5 GHz UWB Low Noise Amplifier in 0.18 μm CMOS

This paper presents a compact two-stage ultrawideband low-noise amplifier (LNA). A common-gate topology is adopted for the input stage to achieve wideband input matching, while a cascode stage is used as the second stage to provide power gain at high frequencies. A low power consumption and a small chip area are obtained by optimizing the performance of the LNA with tight constraint on biasing current and reducing the number of inductors to two. The LNA has been fabricated in a standard 0.18 μm CMOS technology for experimental verification. The LNA achieves a power gain of 11-13.7 dB and a noise figure of 5.0-6.5 dB in the frequency band 1-5 GHz. The measured third order (two-tone) input intercept point (IIP3) is -9.8 dBm at 4 GHz. The LNA consumes 9 mW with a 1.8 V supply, and it occupies an area of 0.78 mm2.
Critical load and congestion instabilities in scale-free networks

We study the tolerance to congestion failures in communication networks with scale-free topology. The traffic load carried by each damaged element in the network must be partly or totally redistributed among the remaining elements. Overloaded elements might fail on their turn, triggering the occurrence of failure cascades able to isolate large parts of the network. We find a critical traffic load above which the probability of massive traffic congestions destroying the network communication capabilities is finite.
LGBTQ+ Young Adults on the Street and on Campus: Identity as a Product of Social Context

ABSTRACT Lesbian, gay, bisexual, queer, and other sexual and gender minority (LGBTQ+) young adults face unique identity-related experiences based on their immersion in distinctive social contexts. The predominant framework of performing separate analyses on samples of LGBTQ+ young people by their primary social status obfuscates more holistic understandings of the role of social context. Using 46 in-depth interviews with LGBTQ+ college students and LGBTQ+ homeless young adults, we ask: How are LGBTQ+ young adults’ capacities for “doing” their gender and sexual identities shaped by their distinctive social contexts? In developing their identities, both groups of LGBTQ+ young adults navigated their social environments to seek out resources and support. Most college students described their educational contexts as conducive to helping them develop their identities, or “undo” rigid norms of gender and sexuality. Homeless young adults’ social environments, meanwhile, imposed complex barriers to self-expression that reinforced more normative expectations of “doing” gender and sexual identities.
Coupled analysis-synthesis dictionary learning for person re-identification

In this paper, we propose a novel coupled dictionary learning method, namely coupled analysis-synthesis dictionary learning, to improve the performance of person re-identification in the non-overlapping fields of different camera views. Most of the existing coupled dictionary learning methods train a coupled synthesis dictionary directly on the original feature spaces, which limits the representation ability of the dictionary. To handle the diversities of different original spaces, We first employ local Fisher discriminant analysis (LFDA) to learn a common feature space for close relationship of the same people in different views. In order to enhance the representation power of the coupled synthesis dictionary, we then learn a coupled analysis dictionary by transforming the common feature space into the coupled feature space. Experimental results on two publicly available VIPeR and CUHK01 datasets have validated the effectiveness of the proposed method.
Automatic Detection of Radiation Fields in Digital Radiographic Images

In computerized radiography (CR) imaging, collimation is frequently employed to shield body parts from unnecessary radiation exposure and minimize radiation scattering using X-ray opaque material. The radiation field is therefore the diagnostic region of interest which has been exposed directly to X-rays. We present an image analysis system for the recognition of the collimation, or equivalently, detection of the radiation field. The purpose is to (1) facilitate optimal tone scale enhancement, which can be driven only by the diagnostically useful part of the image data, and (2) minimize the viewing flare caused by the unexposed area. This system consists of three stages of operations: (1) pixel-level detection and classification of collimation boundary transition pixels; (2) line-level delineation of candidate collimation blades; and (3) region-level determination of the collimation configuration. This system has been reduced to practice and tested over 807 images of 11 exam types and a success rate in excess of 99% has been achieved for tone scale enhancement and masking. Due to the novel design of the system, its computational efficiency lends itself to online operations.
Pilot-based full-duplex spectrum-sensing and multichannel-MAC over non-time-slotted cognitive radio networks

In the non-time-slotted cognitive radio networks (CRNs), the synchronization between PUs and secondary users (SUs) cannot be guaranteed, resulting in two challenging problems: the reactivation-failure of PUs and the frequently unexpected hand-offs among SUs. The reactivation-failure of PUs is the incident that the SUs cannot detect the PUs' reactivation when the SUs are occupying the channels to transmit their data in non-time-slotted CRNs. The frequently unexpected handoffs among SUs are the events that the SU cannot distinguish between the PUs' reactivation and the other SUs' contention, thus causing many unexpected hand-offs among SUs, which severely degrade the achieved throughput of SUs in non-time-slotted CRNs. Employing the energy-detection based wireless full-duplex spectrum sensing schemes, the PUs' reactivation-failure problem can be efficiently solved, thus guaranteeing the required throughput of PUs. However, the key of CRNs is not only the throughput-guarantees for PUs, but also the throughput-boosts for SUs. To optimize the throughput of SUs in multichannel non-time-slotted CRNs, in this paper we develop the pilot-based full-duplex spectrum sensing (PF-SS) scheme and the pilot-based medium access control (P-MAC) protocol to not only guarantee the required throughput of PUs, but also significantly increase the throughput of SUs in multichannel non-time-slotted CRNs. Using the PF-SS scheme, the SUs can identify whether the PUs' signal or the SUs' signal, thus significantly reducing the frequently unexpected hand-offs among SUs. Then, based on the PF-SS scheme, the P-MAC protocol can significantly increase the throughput of SUs. We conduct extensive numerical analyses to show that our developed PF-SS scheme and P-MAC protocol can significantly increase the throughput of SUs while guaranteeing the required throughput for PUs in multichannel non-time-slotted CRNs.
TSMH Graph Cube: A novel framework for large scale multi-dimensional network analysis

As a representation of information, Multi-dimension network is more and more popular, such as web data and social network. With the increment of data source, the entities of the network become diverse. How to analyze these multi-dimensional heterogeneous networks effectively and efficiently is a big challenge. In this paper, we propose a Two-Step Multi-dimensional Heterogeneous (TSMH) Graph Cube framework. We use the meta path in heterogeneous network to guide the aggregation of the network and build the Entity Hyper Cube. For the cuboid in Entity Hyper Cube, we do dimension roll-up/drill down to build the Dimension Cube. In Entity Hyper Cube, we design meta path aggregation algorithms and propose materialization strategy. In Dimension Cube, we use hierarchical coding for entities and dimensions and it saves the process of join operations of entities and dimensions which greatly improve the efficiency of dimension operations. In addition, we propose more new Graph OLAP operations which can make network analysis more diverse. At last, we implement the framework in Spark. The results of experiments on real data set and synthetic data set confirm the efficiency and effectiveness of our framework.
Noninvasive Imaging of Islet Transplants with 111In-Exendin-3 SPECT/CT

Islet transplantation is a promising treatment for type 1 diabetic patients. However, there is acute as well as chronic loss of islets after transplantation. A noninvasive imaging method that could monitor islet mass might help to improve transplantation outcomes. In this study, islets were visualized after transplantation in a rat model with a dedicated small-animal SPECT scanner by targeting the glucagonlike peptide-1 receptor (GLP-1R), specifically expressed on β-cells, with 111In-labeled exendin-3. Methods: Targeting of 111In-exendin-3 to GLP-1R was tested in vitro on isolated islets of WAG/Rij rats. For in vivo evaluation, 400 or 800 islets were transplanted into the calf muscle of WAG/Rij rats (6–8 wk old). Four weeks after transplantation, SPECT/CT images were acquired 1 h after injection of 111In-labeled exendin-3. After SPECT acquisition, the muscles containing the transplant were analyzed immunohistochemically and autoradiographically. Results: The binding assay, performed on isolated islets, showed a linear correlation between the number of islets and 111In-exendin-3 accumulation (Pearson r = 0.98). In vivo, a 1.70 ± 0.44-fold difference in tracer uptake between 400 and 800 transplanted islets was observed. Ex vivo analysis of the islet transplant showed colocalization of tracer accumulation on autoradiography, with insulin-positive cells and GLP-1R expression on immunohistochemistry. Conclusion: 111In-exendin-3 accumulates specifically in the β-cells after islet transplantation and is a promising tracer for noninvasive monitoring of the islet mass.
Efficient identification of unitary quantum processes

Identifying an unknown unitary quantum process is a fundamental task in the development of quantum technology. In this paper, we propose an efficient identification algorithm for estimating unitary processes. In the method, input pure states are used and a fast quantum state tomography algorithm is developed to reconstruct the output states. Then the information of the output states is used to estimate the unitary process. The identification algorithm has computational complexity O(d3) for a d-dimensional system. Numerical results show that the proposed identification algorithm is much more efficient than the maximum likelihood estimation method and works well for input mixed states with high purity. An analytical upper bound for the identification error is also provided, and numerical simulations and experimental results on quantum optical systems verify the theoretical results.
TNFRSF1B Is Associated with ANCA in IBD

Abstract:The genetic basis of antineutrophil cytoplasmic antibody, an important biomarker of inflammatory bowel disease (IBD), has never been thoroughly examined on a genome-wide scale. In this study, we performed a 2-stage genome-wide association study (GWAS) on antineutrophil cytoplasmic antibody in IBD cases. In the 2959 IBD cases in the discovery stage, we observed an association between a variant in the gene TNFRSF1B with antineutrophil cytoplasmic antibody level (rs5745994, minor allele frequency = 0.028, beta = 18.12, 95% CI, 11.82–24.22, P = 1.89 × 10−8). This association was replicated in an independent cohort of 419 IBD cases (beta = 16.91, 95% CI, 6.13–27.69, P = 2.38 × 10−3). With a Q-value of 0.036, we performed a fixed-effect meta-analysis for the association of rs5745994 in both cohorts and observed a stronger association signal (beta = 17.81, 95% CI, 12.36–23.25, P = 8.97 × 10−10). TNFRSF1B gene codes for tumor necrosis factor (TNF) receptor 2 (TNFR2), thereby we examined the reported TNFRSF1B variant with serum TNFR2 level. We observed a negative association with serum TNFR2 level being 8.23 EU/mL in carriers and 9.12 EU/mL in noncarriers (P = 0.033). This finding indicates the functional role of identified TNFRSF1B variant in IBD serology and may be reflective of the underlying biological mechanisms that determine clinical expression and/or response to certain therapies.