Miracle-dz/UniFAR-FTUs huggingface dataset:
Test–Retest Reliability of Mismatch Negativity (MMN) to Emotional Voices

A voice from kin species conveys indispensable social and affective signals with uniquely phylogenetic and ontogenetic standpoints. However, the neural underpinning of emotional voices, beyond low-level acoustic features, activates a processing chain that proceeds from the auditory pathway to the brain structures implicated in cognition and emotion. By using a passive auditory oddball paradigm, which employs emotional voices, this study investigates the test–retest reliability of emotional mismatch negativity (MMN), indicating that the deviants of positively (happily)- and negatively (angrily)-spoken syllables, as compared to neutral standards, can trigger MMN as a response to an automatic discrimination of emotional salience. The neurophysiological estimates of MMN to positive and negative deviants appear to be highly reproducible, irrespective of the subject’s attentional disposition: whether the subjects are set to a condition that involves watching a silent movie or do a working memory task. Specifically, negativity bias is evinced as threatening, relative to positive vocalizations, consistently inducing larger MMN amplitudes, regardless of the day and the time of a day. The present findings provide evidence to support the fact that emotional MMN offers a stable platform to detect subtle changes in current emotional shifts.
Fulfilling the taxonomic consequence after DNA Barcoding: Carychiumpanamaense sp. n. (Eupulmonata, Ellobioidea, Carychiidae) from Panama is described using computed tomographic (CT) imaging

Abstract Five years ago, the Panamanian evolutionary lineage (EL) C12 was uncovered along with four other ELs in an integrative phylogenetic investigation of worldwide Carychiidae. Since EL C12 lacked shell material post-molecular analysis to serve as a museum voucher, it remained undescribed. Now, after recent collection efforts of C12 and the congener, Carychiumzarzaae Jochum & Weigand, 2017 at their original Panamanian sites, C12 is morphologically described and formally assigned the name, Carychiumpanamaense Jochum, sp. n. In sync with recent taxonomic treatment of the genus, computed tomography (CT) is used in this work to differentiate shells of C.panamaensesp. n. from geographically-proximal, Caribbean, North and Central American congeners. Recent material of topotypic Carychiumjardineanum (Chitty, 1853) and undamaged C.zarzaae were additionally CT-scanned and assessed in the comparative analyses.
Designing and Evaluating Mobile Interaction: Challenges and Trends

Mobile technology has been rapidly gaining ground and has become intrinsic to our daily lives. As its importance within society continues to grow, features, functionalities and usage opportunities accompany such growth, turning mobile devices into essential tools. Faced with the role that mobile interactive technology has assumed, it is vital that ease of use also reaches new levels, attenuating the growing complexity within the critical status that they represent. Accordingly, mobile usability evaluation needs to re-invent itself to keep pace with this new phenomenon. This article reviews the current approaches and recent advances in the design and evaluation of mobile interaction and mobile user interfaces, addressing the challenges, the most significant results and the upcoming research directions.
The Role of the Pre-B Cell Receptor in B Cell Development, Repertoire Selection, and Tolerance

Around four decades ago, it had been observed that there were cell lines as well as cells in the fetal liver that expressed antibody μ heavy (μH) chains in the apparent absence of bona fide light chains. It was thus possible that these cells expressed another molecule(s), that assembled with μH chains. The ensuing studies led to the discovery of the pre-B cell receptor (pre-BCR), which is assembled from Ig μH and surrogate light (SL) chains, together with the signaling molecules Igα and β. It is expressed on a fraction of pro-B (pre-BI) cells and most large pre-B(II) cells, and has been implicated in IgH chain allelic exclusion and down-regulation of the recombination machinery, assessment of the expressed μH chains and shaping the IgH repertoire, transition from the pro-B to pre-B stage, pre-B cell expansion, and cessation.
Information Theoretic Security

Security is one of the most important issues in communications. Security issues arising in communication networks include confidentiality, integrity, authentication and non-repudiation. Attacks on the security of communication networks can be divided into two basic types: passive attacks and active attacks. An active attack corresponds to the situation in which a malicious actor intentionally disrupts the system. A passive attack corresponds to the situation in which a malicious actor attempts to interpret source information without injecting any information or trying to modify the information; i.e., passive attackers listen to the transmission without modifying it. Information Theoretic Security focuses on confidentiality issues, in which passive attacks are of primary concern. The information theoretic approach to achieving secure communication opens a promising new direction toward solving wireless networking security problems. Compared to contemporary cryptosystems, information theoretic approaches offer advantages such as eliminating the key management issue; are less vulnerable to the man-in-the-middle and achieve provable security that is robust to powerful eavesdroppers possessing unlimited computational resources, knowledge of the communication strategy employed including coding and decoding algorithms, and access to communication systems either through perfect or noisy channels. Information Theoretic Security surveys the research dating back to the 1970s which forms the basis of applying this technique in modern systems. It proceeds to provide an overview of how information theoretic approaches are developed to achieve secrecy for a basic wire-tap channel model as well as for its extensions to multiuser networks. It is an invaluable resource for students and researchers working in network security, information theory and communications.
3D Bone Biomimetic Scaffolds for Basic and Translational Studies with Mesenchymal Stem Cells

Mesenchymal stem cells (MSCs) are recognized as an attractive tool owing to their self-renewal and differentiation capacity, and their ability to secrete bioactive molecules and to regulate the behavior of neighboring cells within different tissues. Accumulating evidence demonstrates that cells prefer three-dimensional (3D) to 2D culture conditions, at least because the former are closer to their natural environment. Thus, for in vitro studies and in vivo utilization, great effort is being dedicated to the optimization of MSC 3D culture systems in view of achieving the intended performance. This implies understanding cell–biomaterial interactions and manipulating the physicochemical characteristics of biomimetic scaffolds to elicit a specific cell behavior. In the bone field, biomimetic scaffolds can be used as 3D structures, where MSCs can be seeded, expanded, and then implanted in vivo for bone repair or bioactive molecules release. Actually, the union of MSCs and biomaterial has been greatly improving the field of tissue regeneration. Here, we will provide some examples of recent advances in basic as well as translational research about MSC-seeded scaffold systems. Overall, the proliferation of tools for a range of applications witnesses a fruitful collaboration among different branches of the scientific community.
Sparse map-matching in public transit networks with turn restrictions

We investigate the following map-matching problem: given a sequence of stations taken by a public transit vehicle and given the underlying network, find the most likely geographical course taken by that vehicle. We provide a new algorithm and tool, which is based on a hidden Markov model and takes characteristics of transit networks into account. Our tool can be useful for the visualization of transit lines in map services, for transit data providers, and for an on-line matching of live passenger GPS data to a public transit vehicle. We evaluate our tool on real-world data, and compare it against two baselines. The shapes produced by our tool are very close to the true shapes. We have made our software publicly available, enabling full reproducibility of our results.
Consensus and Sectioning-Based ADMM With Norm-1 Regularization for Imaging With a Compressive Reflector Antenna

This paper presents three distributed techniques to find a sparse solution of the under-determined linear problem <inline-formula><tex-math notation="LaTeX">${\bf g}={\bf Hu}$</tex-math></inline-formula> with a norm-1 regularization, based on the Alternating Direction Method of Multipliers (ADMM). Each one of these techniques divide the matrix <inline-formula><tex-math notation="LaTeX">${\bf H}$</tex-math></inline-formula> into submatrices by rows, columns, or both rows and columns, leading to the so-called <italic>consensus</italic>-based ADMM, <italic>sectioning</italic>-based ADMM, and <italic>consensus and sectioning</italic>-based ADMM, respectively. They are validated for a particular millimeter-wave imaging problem based on the use of a Compressive Reflector Antenna (CRA). The CRA is a hardware designed to increase the sensing capacity of an imaging system and reduce the mutual information among measurements, allowing an effective imaging of sparse targets with the use of Compressive Sensing (CS) techniques. In previous works, the <italic>consensus</italic>-based ADMM has been proved to accelerate the imaging process, and the <italic>sectioning</italic>-based ADMM has shown the ability to potentially reduce the amount of information to be exchanged among the computational nodes, based on the system configuration. In this paper, the mathematical formulation and graphical interpretation of these two techniques, together with the <italic>consensus and sectioning</italic>-based ADMM approach, are presented. The imaging quality, the imaging time, the convergence, the communication efficiency among the computational nodes, and the computational complexity are analyzed and compared. The distributed capabilities of the ADMM-based approaches, together with the high sensing capacity of the CRA, allow the imaging of metallic targets in a 3D domain in quasi-real time with a reduced amount of information exchanged among the nodes.
Modeling Human Emotional Intelligence in Virtual Agents

A candidate framework for integration of theoretical, modeling and experimental approaches to understanding emotional intelligence is described. The framework includes three elements of a new kind that enable representation of emotional cognition: an emotional state, an appraisal, and a moral schema. These elements are integrated with the weak semantic cognitive map representing the values of emotional appraisals. The framework is tested on interpretation of results obtained in two new experimental paradigms that reveal general features of human emotional cognition, such as the emergence of subjectively perceived persistent roles of individual virtual actors. Implications concern heterogeneous human-robot teams.
DISTIL: a distributed in-memory data processing system for location-based services

Location-based services (LBS) have become an ubiquitous technology and spatio-temporal data generated by LBS is characterized by high volume and velocity. In recent times several projects, such as GeoSpark, SpatialSpark and LocationSpark, have focused on developing spatial data systems that take advantage of the distributed in-memory data processing capability of Spark. However, most of these systems assume immutable spatial data, and they do not support high throughput location data updates that are common in LBS. On the other hand, a few HBase-based systems, such as MD-HBase, have been proposed that support data updates. However, these systems do not take advantage of any distributed in-memory query processing frameworks. To address the challenges of high velocity location data, we propose DISTIL, a distributed in-memory spatio-temporal data processing system. Our system includes a distributed in-memory index and storage infrastructure that are built on a distributed in-memory programming paradigm called APGAS (Asynchronous Partitioned Global Address Space). In our system, the location records are distributed across a cluster of nodes, using the producer-consumer model. Our experimental evaluation demonstrates that DISTIL can support high throughput location updates, and low latency concurrent processing of spatio-temporal range queries.
Rehabilitation in chronic spatial neglect strengthens resting‐state connectivity

Rehabilitation of patients with chronic visuospatial neglect is underexplored, and little is known about neural mechanisms that can be exploited to promote recovery. In this study, we present data on resting‐state functional connectivity within the dorsal attention network (DAN) in chronic neglect patients as they underwent training in a virtual reality (VR) environment that improved left‐side awareness.
Diagnosis and treatment of migraine in the patient with depression

Background and purpose: Migraine headache is an enormous health care burden resulting in billions of dollars in workforce revenue lost and millions of lost workdays per year. Migraine headaches and depression are common comorbidities and require expertise in treatment and prevention. Methods: The aim of this article is to update the nurse practitioner (NP) on best clinical practices for managing the patient with migraine and previously diagnosed depression. This will include an overview of the pathophysiology of migraine, as well as criteria for diagnosis, treatment, prevention, and patient teaching. Conclusions: Migraine and depression are commonly linked and require expertise in treatment to achieve the best patient outcomes. Implications for Practice: Patients with migraine are more likely to have depression than the general population. Both conditions require optimal treatment and patient education to reduce overall disease burden. A better understanding of the relationship between depression and migraine will enable the NP to better manage patients with migraine and comorbid depression.
Electrolytic Surface Treatment for Improved Adhesion between Carbon Fibre and Polycarbonate

To achieve good mechanical properties of carbon fibre-reinforced polycarbonate composites, the fibre-matrix adhesion must be dialled to an optimum level. The electrolytic surface treatment of carbon fibres during their production is one of the possible means of adapting the surface characteristics of the fibres. The production of a range of tailored fibres with varying surface treatments (adjusting the current, potential, and conductivity) was followed by contact angle, inverse gas chromatography and X-ray photoelectron spectroscopy measurements, which revealed a significant increase in polarity and hydroxyl, carboxyl, and nitrile groups on the fibre surface. Accordingly, an increase in the fibre-matrix interaction indicated by a higher interfacial shear strength was observed with the single fibre pull-out force-displacement curves. The statistical analysis identified the correlation between the process settings, fibre surface characteristics, and the performance of the fibres during single fibre pull-out testing.
Targeting the CDA1/CDA1BP1 Axis Retards Renal Fibrosis in Experimental Diabetic Nephropathy

Targeting cell division autoantigen 1 (CDA1) is postulated to attenuate the profibrotic actions of transforming growth factor-β in diabetic nephropathy. This study has identified a regulatory protein for CDA1 and has then used genetic and pharmacological approaches to test in vivo whether strategies to target this pathway would lead to reduced renal injury. A novel protein, named CDA1BP1 (CDA1 binding protein 1), was identified as critical in regulating the profibrotic activity of CDA1. Genetic deletion of CDA1BP1 attenuated key parameters of renal fibrosis in diabetic mice. Furthermore, a series of short synthetic CDA1BP1 peptides competitively inhibited CDA1-CDA1BP1 binding in vitro with a hybrid peptide, CHA-050, containing a 12mer CDA1BP1 peptide and a previously known “cell-penetrating peptide,” dose-dependently reducing expression of collagens I and III in HK-2 cells. In vivo, a d–amino acid retro-inverso peptide, CHA-061, significantly attenuated diabetes-associated increases in the renal expression of genes involved in fibrotic and proinflammatory pathways. In a delayed intervention study, CHA-061 treatment reversed diabetes-associated molecular and pathological changes within the kidney. Specifically, CHA-061 significantly attenuated renal extracellular matrix accumulation and glomerular injury. Taken together, targeting the CDA1/CDA1BP1 axis is a safe, efficacious, and feasible approach to retard experimental diabetic nephropathy.
Introduction to the Special Issue: Applications of Internet of Things

This editorial introduces the special issue, entitled “Applications of Internet of Things”, of Symmetry. The topics covered in this issue fall under four main parts: (I) communication techniques and applications, (II) data science techniques and applications, (III) smart transportation, and (IV) smart homes. Four papers on sensing techniques and applications are included as follows: (1) “Reliability of improved cooperative communication over wireless sensor networks”, by Chen et al.; (2) “User classification in crowdsourcing-based cooperative spectrum sensing”, by Zhai and Wang; (3) “IoT’s tiny steps towards 5G: Telco’s perspective”, by Cero et al.; and (4) “An Internet of things area coverage analyzer (ITHACA) for complex topographical scenarios”, by Parada et al. One paper on data science techniques and applications is as follows: “Internet of things: a scientometric review”, by Ruiz-Rosero et al. Two papers on smart transportation are as follows: (1) “An Internet of things approach for extracting featured data using an AIS database: an application based on the viewpoint of connected ships”, by He et al.; and (2) “The development of key technologies in applications of vessels connected to the Internet”, by Tian et al. Two papers on smart home are as follows: (1) “A novel approach based on time cluster for activity recognition of daily living in smart homes”, by Liu et al.; and (2) “IoT-based image recognition system for smart home-delivered meal services”, by Tseng et al.
A Compiler for CPPNs: Transforming Phenotypic Descriptions Into Genotypic Representations

Biologically-inspired AI methods like evolutionary algo- rithms have shown great promise in creating complex structures yet these structures still pale in comparison to their natu- ral counterparts. The recently introduced generative encoding compositional pattern producing networks (CPPNs), which is based on the principles of how natural organisms develop, narrowed this gap by showing that it is possible to artiﬁ-cially evolve life-like patterns with regularities at a high-level of abstraction. As these generative and developmental systems (GDS) are asked to evolve increasingly complex struc- tures, the question of how to start evolution from a promising part of the search space becomes more and more impor- tant. To address this challenge, we introduce the concept of a CPPN-Compiler , which allows the user to directly compile a high-level description of the desired starting structure into the CPPN itself . In this paper, as proof of concept, the CPPN-Compiler is able to generate CPPN-encoded represen- tations from vector-based images that can serve as the starting point for further evolution. Importantly, the offspring of these compiled CPPNs show meaningful variations because they directly embody important domain-speciﬁc regularities like symmetry or repetition. Thus the results presented in this paper open up a new research direction in GDS, in which spe-cialized CPPN-Compilers for different domains could help to overcome the black box of evolutionary optimization.
What's the Game and Who's Got the Ball? Genre in Spoken Interaction

Humans engage in an enormous range of interaction types. Therefore, there is a need to consider genre when analyzing or modeling multimodal interaction. While some low level mechanisms may follow universal patterns, it is also possible that even basic interaction mechanisms, such as turn-taking, vary with the type and parameters of different interactions such as mode, content, and goal. Greater insight is needed into the characteristics of different interaction types in order to automatically generate or analyze spoken interaction. More focused interaction models are needed to generate human-machine dialogue beyond simple task-based scenarios, and these models require suitable interaction data. We discuss genre in spoken interaction, outline the characteristics of casual conversation, review available data, and describe ongoing work exploring the dynamics of task-based and social dialogue, and of ‘chat’ and ‘chunk’ subtypes of casual conversation in particular.
Ms1 RNA increases the amount of RNA polymerase in Mycobacterium smegmatis

Ms1 is a sRNA recently found in mycobacteria and several other actinobacterial species. Ms1 interacts with the RNA polymerase (RNAP) core devoid of sigma factors, which differs from 6S RNA that binds to RNAP holoenzymes containing the primary sigma factor. Here we show that Ms1 is the most abundant non‐rRNA transcript in stationary phase in Mycobacterium smegmatis. The accumulation of Ms1 stems from its high‐level synthesis combined with decreased degradation. We identify the Ms1 promoter, PMs1, and cis‐acting elements important for its activity. Furthermore, we demonstrate that PNPase (an RNase) contributes to the differential accumulation of Ms1 during growth. Then, by comparing the transcriptomes of wt and ΔMs1 strains from stationary phase, we reveal that Ms1 affects the intracellular level of RNAP. The absence of Ms1 results in decreased levels of the mRNAs encoding β and β′ subunits of RNAP, which is also reflected at the protein level. Thus, the ΔMs1 strain has a smaller pool of RNAPs available when the transcriptional demand increases. This contributes to the inability of the ΔMs1 strain to rapidly react to environmental changes during outgrowth from stationary phase.
Temperature-Corrected Fluidic Glucose Sensor Based on Microwave Resonator

In this paper, a fluidic glucose sensor that is based on a complementary split-ring resonator (CSRR) is proposed for the microwave frequency region. The detection of glucose with different concentrations from 0 mg/dL to 400 mg/dL in a non-invasive manner is possible by introducing a fluidic system. The glucose concentration can be continuously monitored by tracking the transmission coefficient S21 as a sensing parameter. The variation tendency in S21 by the glucose concentration is analyzed with equivalent circuit model. In addition, to eradicate the systematic error due to temperature variation, the sensor is tested in two temperature conditions: the constant temperature condition and the time-dependent varying temperature condition. For the varying temperature condition, the temperature correction function was derived between the temperature and the variation in S21 for DI water. By applying the fitting function to glucose solution, the subsidiary results due to temperature can be completely eliminated. As a result, the S21 varies by 0.03 dB as the glucose concentration increases from 0 mg/dL to 400 mg/dL.