Miracle-dz/UniFAR-FTUs huggingface dataset:
Perceptual quality-based model training under annotator label uncertainty

Annotators exhibit disagreement during data labeling, which can be termed as annotator label uncertainty. Annotator label uncertainty manifests in variations of labeling quality. Training with a single low-quality annotation per sample induces model reliability degradations. In this work, we first examine the effects of annotator label uncertainty in terms of the model's generalizability and prediction uncertainty. We observe that the model's generalizability and prediction uncertainty degrade with the presence of low-quality noisy labels. Meanwhile, our evaluation of existing uncertainty estimation algorithms indicates their incapability in response to annotator label uncertainty. To mitigate performance degradation, prior methods show that training models with labels collected from multiple independent annotators can enhance generalizability. However, they require massive annotations. Hence, we introduce a novel perceptual quality-based model training framework to objectively generate multiple labels for model training to enhance reliability, while avoiding massive annotations. Specifically, we first select a subset of samples with low perceptual quality scores ranked by statistical regularities of visual signals. We then assign de-aggregated labels to each sample in this subset to obtain a training set with multiple labels. Our experiments and analysis demonstrate that training with the proposed framework alleviates the degradation of generalizability and prediction uncertainty caused by annotator label uncertainty.
See me, feel me: methods to concurrently visualize and manipulate single DNA molecules and associated proteins

Direct visualization of DNA and proteins allows researchers to investigate DNA–protein interactions with great detail. Much progress has been made in this area as a result of increasingly sensitive single-molecule fluorescence techniques. At the same time, methods that control the conformation of DNA molecules have been improving constantly. The combination of both techniques has appealed to researchers ever since single-molecule measurements have become possible and indeed first implementations of such combined approaches have proven useful in the study of several DNA-binding proteins in real time. Here, we describe the technical state-of-the-art of various integrated manipulation-and-visualization methods. We first discuss methods that allow only little control over the DNA conformation, such as DNA combing. We then describe DNA flow-stretching approaches that allow more control, and end with the full control on position and extension obtained by manipulating DNA with optical tweezers. The advantages and limitations of the various techniques are discussed, as well as several examples of applications to biophysical or biochemical questions. We conclude with an outlook describing potential future technical developments in combining fluorescence microscopy with DNA micromanipulation technology.
Output-senstitive rendering and communication in dynamic virtual environments

The efficient rendering of large dynamic scenes is an important open problem. Optimization techniques for static scenes, such as output-sensitive visibility calculation, must be carefully adapted to dynamic models in order to remain effective. Distributed virtual environments pose a particular difficulty, because communication between the users must be minimized in addition to each user’s rendering time. We show how output-sensitive visibility calculation algorithms can be adapted to dynamic scenes, and used to reduce the communication requirements between workstations in a distributed virtual environment. The solution is based on temporal bounding volumes, guaranteed to contain the dynamic objects for some period of time. These volumes are inserted into a visibility algorithm’s main data structure instead of hidden dynamic objects. Subsequently a dynamic object is ignored until its bounding volume becomes visible or is no longer guaranteed to contain the object. In a distributed virtual environment, this saves not only the rendering of the object, but its update through a communication network too. We show an algorithm which combines this method with BSP tree based output-sensitive visibility calculation, and report on the implementation of our system.
Human Beta Defensins and Cancer: Contradictions and Common Ground

Human beta-defensins (hBDs, −1, 2, 3) are a family of epithelial cell derived antimicrobial peptides (AMPs) that protect mucosal membranes from microbial challenges. In addition to their antimicrobial activities, they possess other functions; e.g., cell activation, proliferation, regulation of cytokine/chemokine production, migration, differentiation, angiogenesis, and wound healing processes. It has also become apparent that defensin levels change with the development of neoplasia. However, inconsistent observations published by various laboratories make it difficult to reach a consensus as to the direction of the dysregulation and role the hBDs may play in various cancers. This is particularly evident in studies focusing on oral squamous cell carcinoma (OSCC). By segregating each hBD by cancer type, interrogating methodologies, and scrutinizing the subject cohorts used in the studies, we have endeavored to identify the “take home message” for each one of the three hBDs. We discovered that (1) consensus-driven findings indicate that hBD-1 and−2 are down- while hBD-3 is up-regulated in OSCC; (2) hBD dysregulation is cancer-type specific; (3) the inhibition/activation effect an hBD has on cancer cell lines is related to the direction of the hBD dysregulation (up or down) in the cancer from which the cell lines derive. Therefore, studies addressing hBD dysregulation in various cancers are not generalizable and comparisons should be avoided. Systematic delineation of the fate and role of the hBDs in a specific cancer type may lead to innovative ways to use defensins as prospective biomarkers for diagnostic/prognostic purposes and/or in novel therapeutic modalities.
Multiple-Instance Learning via Disjunctive Programming Boosting

Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with sets of pattern instead of individual patterns. This encompasses multiple instance learning as a special case. Our approach is based on a generalization of linear programming boosting and uses results from disjunctive programming to generate successively stronger linear relaxations of a discrete non-convex problem.
QCRI: Answer Selection for Community Question Answering - Experiments for Arabic and English

This paper describes QCRI’s participation in SemEval-2015 Task 3 “Answer Selection in Community Question Answering”, which targeted real-life Web forums, and was offered in both Arabic and English. We apply a supervised machine learning approach considering a manifold of features including among others word n-grams, text similarity, sentiment analysis, the presence of specific words, and the context of a comment. Our approach was the best performing one in the Arabic subtask and the third best in the two English subtasks.
A compact multi-band slot-ring microstrip patch antenna for wireless applications

Design of a printed microstrip patch antenna operating at multiple frequency bands is presented in this paper. The antenna has a very simple structure combining a microstrip patch, two rings and a slot. The antenna covers GPS (1.575 GHz), 4G/LTE/CDMA (2.1 GHz), and Wi-Fi (3.6/5.3 GHz) frequency bands with good impedance matching (2:1 VSWR) and radiation pattern performance. It has an omni-directional radiation pattern at most of the desired frequencies of operation. The antenna has good efficiency ranging from 60% to 98% and exhibits high peak gain values of 4.1 dBi, 5.7 dBi, 5.1 dBi and 7.9 dBi at 1.575 GHz, 2.1 GHz, 3.68 GHz and 5.37 GHz, respectively.
The Effect of Eavesdroppers on Network Connectivity: A Secrecy Graph Approach

This paper investigates the effect of eavesdroppers on network connectivity, using a wiretap model and percolation theory. The wiretap model captures the effect of eavesdroppers on link security. A link exists between two nodes only if the secrecy capacity of that link is positive. Network connectivity is defined in a percolation sense, i.e., connectivity exists if an infinite connected component exists in the corresponding secrecy graph. We consider uncertainty in location of eavesdroppers, which is modeled directly at the network level as correlated failures in the secrecy graph. Our approach attempts to bridge the gap between physical layer security under uncertain channel state information and network level connectivity under secrecy constraints. For square and triangular lattice secrecy graphs, we obtain bounds on the percolation threshold, which is the critical value of the probability of occurrence of an eavesdropper, above which network connectivity does not exist. For Poisson secrecy graphs, degree distribution and mean value of upper and lower bounds on node degree are obtained. Further, inner and outer bounds on the achievable region for network connectivity are obtained. Both analytic and simulation results show that uncertainty in location of eavesdroppers has a dramatic effect on network connectivity in a secrecy graph.
Two-dimentional direction-of-arrival estimation of coherent signals with L-sharped array

In this paper, a new method is proposed for two-dimensional (2-D) direction-of-arrivals (DOAs) estimation of multiple narrowband coherent signals impinging on an L-shaped sensor arrays structured by two uniform linear arrays (ULAs). The coherency of incident signals is decorrelated through subarray averaging technique, and the null space is obtained through linear operator of the cross-correlation matrix between the received data of two ULAs without eigendecomposition. The elevation angles and the quasi-azimuth angles are firstly decoupled and estimated, and the pair-matching of two groups of angles can be accomplished by using a novel method. Then by investigating the geometrical relationship, the azimuth angles can be obtained. Furthermore the asymptotic mean-square-error (MSE) of the estimated elevation and azimuth angles are derived, and the effectively of the proposed method is verified through numerical examples.
A self-powered WSAN for energy efficient heat distribution

The impact of IoT might significantly be increased by autonomous nodes with both sensing and actuating capabilities. This article describes the project of a wireless sensor and actuator network (WSAN) made up of autonomous nodes. Both the sensing and actuating nodes sense and communicate the temperature through the DASH7 coordinator. In addition the actuating node drives a motor to tune a valve controlling a radiator. Connectivity is provided by the above-mentioned low power protocol DASH7 running over a subGHz radio network. Nodes are powered by harvesters. The WSAN is intended to be a nearly unobtrusive component of a smart environment addressable by a gateway with edge-computing capabilities. Monitoring and actuating features are exposed by the network and are available to remote mobile clients. Thus an Internet of Things scenario is implemented with autonomous components, a gateway and a user friendly interface built on a simple Android application. The paper sketches the proposed architecture and is focused on the first node prototypes, their design challenges and preliminary measured performance. Requirements for self-sustainability and trade offs between service responsiveness and availability are discussed.
CXCR4 chemokine receptors (CD184) and α4β1 integrins mediate spontaneous migration of human CD34+ progenitors and acute myeloid leukaemia cells beneath marrow stromal cells (pseudoemperipolesis)

Summary. Marrow stromal cells play an important role in regulating the development and proliferation of haematopoietic stem cells (HSC) within the marrow microenvironment. However, the molecular mechanisms of stem cell–stromal cell interactions are not fully understood. We observed that mobilized peripheral blood and cord‐blood‐derived CD34+ progenitor cells, or CD34+ acute myeloid leukaemia (AML) cells spontaneously migrated beneath marrow stromal cells, an in vitro migration phenomenon termed pseudoemperipolesis. In contrast, the CD34+ myeloid leukaemia cell line, Kasumi‐1, did not display pseudoemperipolesis. Cord blood CD34+ cells had a higher capacity than granulocyte‐colony‐stimulating‐factor‐mobilized CD34+ cells for pseudoemperipolesis (28·7 ± 12%vs 18·1 ± 6·1% of input cells within 24 h, mean ± SD, n = 8), whereas 9·4 ± 12·6% (mean ± SD, n = 10) of input AML cells displayed this phenomenon. Pseudoemperipolesis of CD34+ progenitor and AML cells was significantly inhibited by pertussis toxin and antibodies to the CXCR4 chemokine receptor (CXCR4, CD184), but not control antibodies. Moreover, CD34+ and AML cell migration was significantly inhibited by a CS1 peptide that blocks α4β1 integrin binding, but not by a control peptide, in which the fibronectin binding motif was scrambled. Pseudoemperipolesis was associated with an increased proliferation of migrated CD34+ progenitor cells but not AML cells within the stromal layer, demonstrated by cell cycle analysis and cell division tracking. We conclude that α4β1 integrin binding and CXCR4 chemokine receptor activation are prerequisites for the migration of CD34+ haematopoietic progenitors and AML cells beneath marrow stromal cells. These observations suggest a central role of marrow stromal cells for HSC trafficking and homing within the marrow microenvironment.
Synaptic Activity in Serotonergic Neurons Is Required for Air-Puff Stimulated Flight in Drosophila melanogaster

Background Flight is an integral component of many complex behavioral patterns in insects. The giant fiber circuit has been well studied in several insects including Drosophila. However, components of the insect flight circuit that respond to an air-puff stimulus and comprise the flight central pattern generator are poorly defined. Aminergic neurons have been implicated in locust, moth and Drosophila flight. Here we have investigated the requirement of neuronal activity in serotonergic neurons, during development and in adults, on air-puff induced flight in Drosophila. Methodology/Principal Findings To target serotonergic neurons specifically, a Drosophila strain that contains regulatory regions from the TRH (Tryptophan Hydroxylase) gene linked to the yeast transcription factor GAL4 was used. By blocking synaptic transmission from serotonergic neurons with a tetanus toxin transgene or by hyperpolarisation with Kir2.1, close to 50% adults became flightless. Temporal expression of a temperature sensitive Dynamin mutant transgene (Shits) suggests that synaptic function in serotonergic neurons is required both during development and in adults. Depletion of IP3R in serotonergic neurons via RNAi did not affect flight. Interestingly, at all stages a partial requirement for synaptic activity in serotonergic neurons was observed. The status of serotonergic neurons was investigated in the central nervous system of larvae and adults expressing tetanus toxin. A small but significant reduction was observed in serotonergic cell number in adult second thoracic segments from flightless tetanus toxin expressing animals. Conclusions These studies show that loss of synaptic activity in serotonergic neurons causes a flight deficit. The temporal focus of the flight deficit is during pupal development and in adults. The cause of the flight deficit is likely to be loss of neurons and reduced synaptic function. Based on the partial phenotypes, serotonergic neurons appear to be modulatory, rather than an intrinsic part of the flight circuit.
Joint estimation of I/Q imbalance and channel response for MIMO OFDM system

In this paper, we study joint estimation of in-phase and quadrature-phase (I/Q) imbalance and channel response for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems using training sequence. A new class of optimal sequences, called circularly-shift orthogonal sequences, are introduced for estimating the MIMO channels. By using the newly proposed sequences, the channel coefficients can be obtained by multiplying the received vectors with an M × M unitary circulant matrix, which can be computed efficiently using FFT. Then, we develop a new method for jointly estimating the MIMO channel responses and I/Q imbalance. The proposed time-domain method needs only one OFDM training block. Simulation results show that the proposed method can accurately estimate both the I/Q imbalance and MIMO channel response.
Comorbid anxiety in children and adolescents with bipolar spectrum disorders: prevalence and clinical correlates.

OBJECTIVE Anxiety disorders are among the most common comorbid conditions in youth with bipolar disorder. We aimed to examine the prevalence and correlates of comorbid anxiety disorders among youth with bipolar disorder. METHOD As part of the Course and Outcome of Bipolar Youth study, 446 youth, ages 7 to 17 years, who met DSM-IV criteria for bipolar I disorder (n = 260) or bipolar II disorder (n = 32) or met operationalized criteria for bipolar disorder not otherwise specified (n = 154) were included. Subjects were evaluated for current and lifetime Axis I psychiatric disorders at intake using the Kiddie Schedule for Affective Disorders and Schizophrenia for School-Aged Children-Present and Lifetime version, and standardized instruments were used to assess functioning and family history. RESULTS Forty-four percent (n = 194) of the sample met DSM-IV criteria for at least 1 lifetime anxiety disorder, most commonly separation anxiety (24%) and generalized anxiety disorders (16%). Nearly 20% met criteria for 2 or more anxiety disorders. Overall, anxiety disorders predated the onset of bipolar disorder. Subjects with bipolar II disorder were more likely than subjects with bipolar I disorder or bipolar disorder not otherwise specified to have a comorbid anxiety disorder. After adjusting for confounding factors, youth with bipolar disorder with anxiety were more likely to have bipolar II disorder; longer duration of mood symptoms; more severe ratings of depression; and family history of depression, hopelessness, and somatic complaints during their worst lifetime depressive episode than those without anxiety. CONCLUSIONS Comorbid anxiety disorders are common in youth with bipolar disorder, and they most often predate bipolar disorder onset. Bipolar II disorder, a family history of depression, and more severe lifetime depressive episodes distinguish youth with bipolar disorder with comorbid anxiety disorders from those without. Careful consideration should be given to the assessment of comorbid anxiety in youth with bipolar disorder.
Adult Attention-Deficit Hyperactivity Disorder

tentative diagnostic criteria so that we are all discussing samples with the same attributes. What are the diagnostic criteria for ADHD in adults? Well, first, we must determine whether or not the patient had ADHD in childhood; childhood ADHD is a mandatory prerequisite for diagnosing ADHD in adults. If this is so, the diagnosis of childhood ADHD must almost always be made retrospectively. How? One can query the adult about the DSMIV symptoms of ADHD in children. We know nothing about the reliability of patients’ memories, but it appears that they are often fuzzy about specific diagnostic cues. On our Utah criteria, we have tried multiple ways to get around this problem. In the event that the patient can convince us that his recollection of DSM-IV cues is accu-
A modular, flexible and virtualizable framework for IEEE 802.11

Wireless networks are extensively deployed due to their low cost and configuration easiness. However, they are not adapted to the new services and applications that are increasingly demanded by users. Current implementation of the IEEE 802.11 specification is supported in hardware devices and software developments, but they do not provide the adaptability that would enhance user experience in next generation networks. In this paper, we present a new wireless framework, based on the one currently supported by the Linux stack: mac80211. This new framework, named mac80211++, has been tailored to improve MAC features in terms of: (i) modularity, by defining different 802.11 MAC services; (ii) flexibility, by enabling dynamic configurability of the 802.11 MAC; (iii) virtualization, by managing parallel independent 802.11 MACs accessing the same system resources.
Stability analysis for the Null-Space-based Behavioral control for multi-robot systems

A wide number of mobile multi-robot systems makes use of behavior-based approaches to accomplish their missions. However, despite the advantages in term of flexibility and versatility, the behavior-based approaches often lack of a rigorous stability analysis; when the latter is present it is only valid for specific missions. A behavior based-approach for the control of different robotic systems, namely the null space-based behavioral control, has been recently proposed. In this paper, its general stability analysis is discussed following a Lyapunov-based approach; moreover, effective conditions are given to verify that the behaviors of specific missions are properly defined and merged. Finally, the stability of several missions for multi-robot systems is discussed.
Body Gestures and Spoken Sentences: A Novel Approach for Revealing User’s Emotions

In the last decade, there has been a growing interest in emotion analysis research, which has been applied in several areas of computer science. Many authors have contributed to the development of emotion recognition algorithms, considering textual or non verbal data as input, such as facial expressions, gestures or, in the case of multi-modal emotion recognition, a combination of them. In this paper, we describe a method to detect emotions from gestures using the skeletal data obtained from Kinect-like devices as input, as well as a textual description of their meaning. The experimental results show that the correlation existing between body movements and spoken user sentence(s) can be used to reveal user's emotions from gestures.
Analyzing Data Augmentation for Medical Images: A Case Study in Ultrasound Images

Data augmentation is one of the most effective techniques to improve the generalization performance of deep neural networks. Yet, despite often facing limited data availability in medical image analysis, it is frequently underutilized. This appears to be due to a gap in our collective understanding of the efficacy of different augmentation techniques across medical imaging tasks and modalities. One domain where this is especially true is breast ultrasound images. This work addresses this issue by analyzing the effectiveness of different augmentation techniques for the classification of breast lesions in ultrasound images. We assess the generalizability of our findings across several datasets, demonstrate that certain augmentations are far more effective than others, and show that their usage leads to significant performance gains.