Miracle-dz/UniFAR-FTUs huggingface dataset:
IEEE 802.11ax: On Performance of Multi-Antenna Technologies with LDPC Codes

The implementation of low-density parity-check (LDPC) codes will be a mandatory feature in the 2019 IEEE 802.11ax amendment, the sixth generation of wireless local area networks (WLANs) for frequencies below 6 GHz. Orthogonal frequency division multiplexing multi-user multiple-input multiple-output (OFDM MU-MIMO) technologies for both downlink and uplink have been specified in Task Group (TG) 802.11ax meetings to improve the spectrum and area efficiency in ultra-dense WLANs. In this paper, we compare the performance of binary convolutional codes (BCC) and LDPC codes using different configurations of multi-antenna technologies taking into account both hardware and system impairments. We have concluded that on the most study cases, the implementation of LDPC codes in the IEEE 802.11ax physical layer allows power gains between 2.5 and 4.0 dB in relation to BCC with soft-decision Viterbi decoding.
Studying of Explosive Electron Emission From “Whisker” Cathode Using X-Ray Point-Projection Radiography

The results of direct observation of the initial phase of explosive electron emission using high-resolution X-ray radiography in X-pinch radiation are reported. The confirmation of common “Ecton” theory was not found within achieved temporal and spatial resolutions. A mechanism involving the surface breakdown of whiskers that leads to plasma development is proposed.
Validating a Trigger Tool for Detecting Adverse Drug Events in Elderly Patients With Multimorbidity (TRIGGER-CHRON)

Purpose The aims of the study were to evaluate the performance of an initial list developed to detect adverse drug events (ADEs) in elderly patients with multimorbidity in clinical practice, to explore the possibility of shortening the list, and to use this tool to study the incidence and characteristics of the ADEs among this population. Methods This observational study was conducted at 12 Spanish hospitals. A random sample of five charts from each hospital was selected weekly for retrospective review for a 12-week period. We included patients aged 65 years and older with multimorbidity, hospitalized more than 48 hours. Adverse drug events were detected using a list of 51 triggers previously selected by an expert panel by means of a modified Delphi method. The number of triggers identified and ADEs detected were recorded. The severity and preventability of the ADEs were evaluated. The positive predictive value (PPV) of each trigger was calculated and used to select the most efficient triggers. Results In 720 charts reviewed, 1430 positive triggers were identified that led to detect 215 ADEs in 178 patients (24.7%), of which 13% were serious. One hundred nineteen ADEs (55.3%) were preventable and mainly related to inadequate treatment monitoring and prescribing errors. Triggers with a PPV of 5% or less were eliminated, resulting in a final list of 32 triggers (TRIGGER-CHRON) with a PPV of 22.1%, which accounted for 98.9% of all ADEs detected and 98.6% of the preventable ADEs. Conclusions The shorter final validated TRIGGER-CHRON tool is an efficient list for identifying ADEs in elderly patients with multimorbidity, detecting ADEs in one-fourth of hospitalized patients in internal medicine or geriatric units.
Parental Perceptions of Emotional and Behavioral Difficulties Among Prepubertal Gender-Nonconforming Children

The purpose of this study was to better understand parents’ perceptions of how, if at all, their transgender and gender-nonconforming (TGNC) children exhibited common childhood emotional and behavioral concerns in relation to gender nonconformity/gender dysphoria (GD), and to identify ways in which evidence-based interventions (EBI) targeting emotional and behavioral concerns could be adapted to best serve TGNC children. Qualitative data were gathered from a targeted focus group activity with 40 parents (25 mothers, 15 fathers) of 24 TGNC children ages 4–11 years old. Parents of TGNC children described how 4 prespecified domains of emotional and behavioral problems (i.e., oppositional behavior, anger, sadness, and fears/worries) are characterized in the context of gender-nonconformity/GD. Parents also identified precipitants of these problems. Overall study findings indicate there is a role for EBI adaptation as parents identified many different examples of emotional and behavioral challenges emerging in unique and nuanced ways in TGNC children.
When do Words Matter? Understanding the Impact of Lexical Choice on Audience Perception using Individual Treatment Effect Estimation

Studies across many disciplines have shown that lexical choice can affect audience perception. For example, how users describe themselves in a social media profile can affect their perceived socio-economic status. However, we lack general methods for estimating the causal effect of lexical choice on the perception of a specific sentence. While randomized controlled trials may provide good estimates, they do not scale to the potentially millions of comparisons necessary to consider all lexical choices. Instead, in this paper, we first offer two classes of methods to estimate the effect on perception of changing one word to another in a given sentence. The first class of algorithms builds upon quasi-experimental designs to estimate individual treatment effects from observational data. The second class treats treatment effect estimation as a classification problem. We conduct experiments with three data sources (Yelp, Twitter, and Airbnb), finding that the algorithmic estimates align well with those produced by randomized-control trials. Additionally, we find that it is possible to transfer treatment effect classifiers across domains and still maintain high accuracy.
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers

The fundamental learning theory behind neural networks remains largely open. What classes of functions can neural networks actually learn? Why doesn't the trained network overfit when it is overparameterized? In this work, we prove that overparameterized neural networks can learn some notable concept classes, including two and three-layer networks with fewer parameters and smooth activations. Moreover, the learning can be simply done by SGD (stochastic gradient descent) or its variants in polynomial time using polynomially many samples. The sample complexity can also be almost independent of the number of parameters in the network. On the technique side, our analysis goes beyond the so-called NTK (neural tangent kernel) linearization of neural networks in prior works. We establish a new notion of quadratic approximation of the neural network (that can be viewed as a second-order variant of NTK), and connect it to the SGD theory of escaping saddle points.
Does the Appearance of a Robot Influence People's Perception of Task Criticality?

As home robot companions become more common, it is important to understand what types of tasks are considered critical to perform correctly. This paper provides working definitions of task criticality, physical and cognitive tasks with respect to robot task performance. Our research also suggests that although people's perceptions of task criticality is independent of robot appearances, their expectation that a robot performs tasks correctly is affected by it's appearance.
A Framework for Affect-Based Natural Human-Robot Interaction

In this paper we present a general framework for affective human-robot interaction that allows users to intuitively interact with a robot and takes into account their mental fatigue, thus simplifying the task or providing assistance when the user feels stressed. Interaction with the robot is achieved by naturally mapping user's forearm motion, detected with a smartwatch, into robot's motion. High-level commands can be provided by means of gestures. An approach based on affective robotics is used to adapt the level of robot's autonomy to the cognitive workload of the user. User's mental fatigue is detected from the analysis of heart rate, also measured by the smartwatch. The framework is general and can be applied to different robotic systems. In this paper, we consider its experimental validation on a wheeled mobile robot.
Low-Cost Wearable Technology Model to Control and Monitor Chronic Diseases for Healthcare

In this paper, we propose a low-cost wearable technology model to control and monitor chronic diseases for healthcare. We enhance prior models by focusing on low cost components, and we assess the current hardware and systems applications offered in the market. Our proposed model also emphasizes the application of real-time data analysis for the healthcare organization. The model consists of six components: 1. Data acquisition; 2. Data Processing; 3. Information Results; 4. Decision making Support; 5. Technology Platform; 6. Framework for personal data protection. The model was validated with a group of 12 females over 70 years who were diagnosed with tumors at different stages. The preliminary results show that the mean temperature difference between the armpits and malignant tumors is 0.7 ± 0.5, while the mean temperature difference between the armpits and benign tumors is 2.1 ± 0.5.
Estimation of Dimensions Contributing to Detected Anomalies with Variational Autoencoders

Anomaly detection using dimensionality reduction has been an essential technique for monitoring multidimensional data. Although deep learning-based methods have been well studied for their remarkable detection performance, their interpretability is still a problem. In this paper, we propose a novel algorithm for estimating the dimensions contributing to the detected anomalies by using variational autoencoders (VAEs). Our algorithm is based on an approximative probabilistic model that considers the existence of anomalies in the data, and by maximizing the log-likelihood, we estimate which dimensions contribute to determining data as an anomaly. The experiments results with benchmark datasets show that our algorithm extracts the contributing dimensions more accurately than baseline methods.
Airborne, Far-Field Calibrators for Cosmic Microwave Background Telescopes: POLOCALC

The POLarization Orientation CALibrator for Cosmology, POLOCALC [1], is a novel method to measure the absolute orientation of the polarization plane of the Cosmic Microwave Background (CMB) photons with arcsecond accuracy. POLOCALC will dramatically improve instrumental accuracy of CMB polarimeters by means of an artificial calibration source flying on high-altitude balloons and aerial drones. The source will make use of microwave emitters between 40 and 150 GHz coupled to precise polarizing filters. The orientation of the source polarization plane will be registered to absolute celestial coordinates by star cameras and gyroscopes with arcsecond accuracy. Existing and planned CMB polarization instruments looking for primordial B-mode signals need an independent, experimental method for systematics control on the absolute polarization orientation. The lack of such a method limits the accuracy of the detection of inflationary gravitational waves, the constraining power on the neutrino sector through measurements of gravitational lensing of the CMB, the possibility of detecting Cosmic Birefringence, and the ability to measure primordial magnetic fields. Sky signals used for calibration and direct measurements of the detector orientation cannot provide an accuracy better than 1°. POLOCALC will overcome the current limitations, enabling unprecedented measurements for cosmology and fundamental physics.
α-enolase is an antigenic target in primary Sjögren's syndrome.

OBJECTIVES Although anti-cyclic citrullinated peptides antibodies are specific markers for rheumatoid arthritis (RA), they might be present in other diseases. Our aim was to assess the native or citrullinated antigens recognised by patients with primary Sjögren's syndrome (pSS) and to evaluate their association with clinical and serological features. METHODS In an initial screening, we assessed the serum reactivity of 12 patients with pSS against native or in vitro citrullinated antigens of HEp-2 cells by immunoblotting. We identified a 47kDa band, which was preferentially recognised and corresponded to α-enolase. Thus, levels of IgA and IgG anti-native and citrullinated α-enolase antibodies were measured in 50 pSS patients, 20 RA patients and 20 healthy subjects (HS) by ELISA. RESULTS We identified α-enolase as predominant antigen recognised in pSS. These patients had higher levels of anti-citrullinated α-enolase IgG antibodies compared with RA or HS (p=0.003 and p<0.0001, respectively). Furthermore, there was an increase of IgG anti-citrullinated α-enolase vs IgG anti-non-citrullinated α-enolase antibodies in pSS patients (p=0.001), by contrast no difference was found in RA. The presence of IgA and IgG anti-non-citrullinated and anti-citrullinated α-enolase antibodies were not associated with any clinical manifestation whatsoever, including non-erosive arthritis among pSS, but an association of IgA anti-citrullinated α-enolase with anti-Ro/SSA antibodies was found. CONCLUSIONS We characterised α-enolase as a dominant antigen in lysates of HEp- 2 cells in pSS. Nevertheless, their precise role in pSS remains to be elucidated.
Parallel Channel Sounder for MIMO Channel Measurements

In order to address the challenges in MIMO channel measurement and modeling for 5G communication scenarios, a CDM-based parallel channel sounder is developed and evaluated in this article. Compared to traditional TDM-based channel sounders, our parallel channel sounder supports eight-by-eight (8 x 8) MIMO communications, 200 MHz RF bandwidth, 5 ns multipath time resolution, 36 dB dynamic range, and 2 kHz maximum Doppler shift at a speed of 350 km/h. To achieve these performance targets, a series of sophisticated technical solutions are proposed and analyzed to realize 32 ps synchronization accuracy, 51.36 Gb/s parallel data streaming, and high-precision calibration across multiple channels. Key functions and performance metrics are evaluated and verified in a microwave chamber. Real measurement results in a complex campus environment show that our CDM-based parallel channel sounder can capture more detailed channel characteristics, and therefore offer accurate PDPs and RMS delay spreads at both LoS and NLoS positions under MIMO communication scenarios.
Optimizing Cutoff Frequency in an Antipodal Vivaldi Antenna for GPR applications through a novel balun

In this work, an ultra-bandwidth antenna (UWB) is proposed for applications in ground penetrating radar (GPR). A novel Vivaldi antipodal antenna (AVA) with elliptical slot at the edges (ESE) made with FR4 is presented. The antenna was optimized by adjusting the geometry of the tapers and modifying the shape of the balun, with these modifications a lower cutoff frequency (LCF) around 1.5 GHz is achieved. Results from reflection coefficients, radiation pattern and gain are presented. The overall design and electromagnetic simulation of the antenna are made with a a commercially avalaible simulator.
Reducing Code Duplication by Identifying Fresh Domain Abstractions

When software components are developed iteratively, code frequently evolves in an inductive manner: a unit (class, method, etc.) is created and is then copied and modified many times. Such development often happens when variation points and, hence, proper domain abstractions are initially unclear. As a result, there may be substantial amounts of code duplication, and the code may be difficult to understand and maintain, warranting a redesign. We apply a model-based process to semi-automatically redesign an inductively-evolved industrial adapter component written in C++: we use reverse engineering to obtain models of the component, and generate redesigned code from the models. Based on our experience, we propose to use three models to help recover understanding of inductively-evolved components, and transform the components into redesigned implementations. Guided by a reference design, a component's code is analyzed and a legacy model is extracted that captures the component's functionality in a form close to its original structure. The legacy model is then unfolded, creating a flat model which eliminates design decisions by focusing on functionality in terms of external interfaces. Analyzing the variation points of the flat model yields a redesigned model and fresh domain abstractions to be used in the new design of the component.
A Dual Band Circularly Polarized Y-ShapedPatch Antenna for Wireless Communication Application

This study related to a Dual-band circularly-polarized (CP) micro strip patch antenna layout consisting of a single Y-shaped patch with rectangular ground plane fed by microstrip transmission line. This configuration is considered for bandwidth enhancement. A rectangle have been etched from the upper periphery of the ground to enhance the impedance bandwidth (IBW). In order toenhance the axial ratio bandwidth (ARBW) by a significant amount proper dimension of Y-shaped has been used. By using this structure the achievable IBW and center frequency $(\mathbf{f}_{\mathbf{c}})$ are 5.557 GHz (i.e. 4.933 GHz - 10.49 GHz, 72.05 %) and7.7 GHz respectively. The correspondingARBW are 742.5 MHz $(\mathbf{f}_{\mathbf{c}}\pmb{6.32}$ GHz, 11.75 %) and 1091.8 MHz ($\mathbf{f}_{\mathbf{c}}\ \pmb{8.32}$ GHz, 13.12%). The maximum simulated peak gain is 3.19 dBi at 8.64 GHz within the CP band. Proposed antenna happens to be suitable for ‘C’ and ‘X’ band wireless communication application.
Wireless Multi-Hop Networking for a Group of Exercisers Spread in a Sports Ground

Reliable and real-time vital signs monitoring is essential to promote health and prevent disease/injury for a group of exercisers spread in a sports ground such as schoolchildren and professional athletes. For that purpose, we developed a wireless vital signs collection system and confirmed it worked effectively, but unfortunately, it required an infrastructure of data forwarding nodes placed around the area of interest. We really wanted to realize it infrastructurelessly.Now, we are developing an infrastructureless multi-hop wireless network system which has the same vital sensing and wireless communication functions, and we have so far successfully conducted one indoor experiment and two outdoor experiments for footballer subjects. In this paper, we will outline the design concept and show the experimental results.
Hybrid MMSE Beamforming for Multiuser Millimeter-Wave Communication Systems

This letter investigates the hybrid analog and digital beamforming (HBF) design for multiuser millimeter-wave communication systems based on the minimum mean square error (MMSE) criterion. Using the alternating minimization method, the hybrid precoder of the base station (BS) and the hybrid combiners of the users are alternatively optimized. It is shown that both the optimized digital precoder of the BS and the digital combiners of the users have closed-form expressions, and their corresponding analog ones can be efficiently obtained via generalized eigen-decomposition. Simulation results show that the proposed MMSE HBF scheme has fast convergence and performs close to the fully digital beamforming.
Wiping Techniques and Anti-Forensics Methods

This paper presents a theoretical background of main research activity focused on the evaluation of wiping/erasure standards which are mostly implemented in specific software products developed and programming for data wiping. The information saved in storage devices often consists of metadata and trace data. Especially but not only these kinds of data are very important in the process of forensic analysis because they sometimes contain information about interconnection on another file. Most people saving their sensitive information on their local storage devices and later they want to secure erase these files but usually there is a problem with this operation. Secure file destruction is one of many Anti-forensics methods. The outcome of this paper is to define the future research activities focused on the establishment of the suitable digital environment. This environment will be prepared for testing and evaluating selected wiping standards and appropriate eraser software.
Artificial Empathy in Social Robots: An analysis of Emotions in Speech

Artificial speech developed using speech synthesizers has been used as the voice for robots in Human Robot Interaction (HRI). As humans anthropomorphize robots, an empathetically interacting robot is expected to increase the level of acceptance of social robots. Here, a human perception experiment evaluates whether human subjects perceive empathy in robot speech. For this experiment, empathy is expressed only by adding appropriate emotions to the words in speech. Also, humans' preferences for a robot interacting with empathetic speech versus a standard robotic voice are also assessed. The results show that humans are able to perceive empathy and emotions in robot speech, and prefer it over the standard robotic voice. It is important for the emotions in empathetic speech to be consistent with the language content of what is being said, and with the human users' emotional state. Analyzing emotions in empathetic speech using valence-arousal model has revealed the importance of secondary emotions in developing empathetically speaking social robots.
Developmental Changes in the Inhibition of Glycinergic Synaptic Currents by Niflumic Acid in Hypoglossal Motoneurons

Mammalian brainstem hypoglossal motoneurones (HMs) receive powerful synaptic glycinergic inputs and are involved in a variety of motor functions, including respiration, chewing, sucking, swallowing, and phonation. During the early postnatal development, subunit composition of chloride-permeable glycine receptors (GlyRs) changes leading to a decrease of “fetal” alpha2 and elevation of “adult” alpha1 GlyR subunits. It has been recently demonstrated that niflumic acid (NFA), a member of the fenamate class of non-steroidal anti-inflammatory drugs, is an efficient subunits-specific blocker of GlyRs. At a heterologous expression of different GlyR subunits it has been shown that blocking potency of NFA is more than one order higher for alpha2 GlyRs than for receptors formed by alpha1 subunit. To reveal the action of NFA on the synaptic activity we analyzed here the effects of NFA on the glycinergic inhibitory post-synaptic currents in the HMs from mouse brainstem slices. In the whole-cell patch clamp configuration, the amplitude and the frequency of glycinergic synaptic currents from two age groups have been analyzed: “neonate” (P2–P4) and “juvenile” (P7–P12). Addition of NFA in the presence of antagonists of glutamate and GABA receptors caused a decrease in the mean amplitude and frequency of synaptic events. The degree of the inhibition induced by NFA decreased with the postnatal development, being higher on the motoneurons from “neonate” brainstem slices in comparison with the “juvenile” age group. Analysis of the pair-pulse facilitation suggests the post-synaptic origin of NFA action. These observations provide evidence on the developmental changes in the inhibition by NFA of glycinergic synaptic transmission, which reflects increase in the alpha1 and decrease in the alpha2 GlyR subunits expression in synapses to hypoglossal motoneurons during the early stages of postnatal life.