Miracle-dz/UniFAR-FTUs huggingface dataset:
A Modularized IPT With Magnetic Shielding for a Wide-Range Ubiquitous Wi-Power Zone

A wide-range ubiquitous wireless power environment, called a ubiquitous Wi-power zone, where any electric devices can be charged by three-dimensional (3-D)-omnidirectional wireless charging, is newly proposed in this paper. By virtue of the proposed direct-quadrature (DQ) transmitting (Tx) coils composed of multiple Tx modules with same size, a ubiquitous Wi-power zone having the transmitting (Tx) coils can be provided over wide-range 3-D space. In this area, a number of electric devices can be simultaneously charged during operation. Therefore, the proposed IPT is expected to be the next generation of wireless power transfer (WPT), as the internet of things (IoT), mobile devices, and sensor technologies evolve. For magnetic shielding behind the Tx coils and high power efficient operation of the proposed DQ Tx coils, providing an evenly distributed magnetic field, a conductive plate is adopted, and the effects of the conductive plate for the dipole coil structure were thoroughly evaluated by a 3-D FEM simulation. To create the proposed ubiquitous Wi-power zone, simulation-based optimum design procedures are established based on four design considerations and the optimized number of modularizations for the DQ Tx coils can be found by an optimum point of figure of merit (FoM). The DQ Tx module composed of the DQ Tx coils and series resonant capacitors was adopted as a standard unit of the proposed IPT so that different sizes and shapes of 3-D space can be utilized for universal use of the proposed ubiquitous IPT; hence, a general solution to create the proposed ubiquitous IPT is provided in this paper. A prototype 5 × 5 modularized IPT composed of 25 DQ Tx modules having the same size of <inline-formula> <tex-math notation="LaTeX">${\text{10 cm}} \times {\text{10 cm}}\times {\text{2 cm}}$</tex-math></inline-formula> was fabricated and experimentally verified for a <inline-formula><tex-math notation="LaTeX">${\text{1 m}}\times {\text{1 m}}\times {\text{0.7 m}}$</tex-math></inline-formula> ubiquitous Wi-power zone. Experimental results showed that 95.5%, 92.1%, and 98.8% of high magnetic field uniformity for <inline-formula> <tex-math notation="LaTeX">$z_{1}= {\text{25}}$</tex-math></inline-formula> cm, 50 cm, and 75 cm, respectively, and 3-D omnidirectional wireless power delivery have been achieved; thus, meeting essential requirements for the proposed ubiquitous Wi-power zone. Nine Rx coils can be simultaneously charged with 14.2 W of total received load power and 8.2% power efficiency at <inline-formula><tex-math notation="LaTeX">$z_{1}= {\text{70}}$</tex-math></inline-formula> cm.
A Web-based system for annotation of dance multimodal recordings by dance practitioners and experts

Recent advances in technologies for capturing, analyzing and visualizing movement can revolutionize the way we create, practice, learn dance, and transmit bodily knowledge. The need for creating meaningful, searchable and re-usable libraries of motion capture and video movement segments can only be fulfilled through the collaboration of both technologists and dance practitioners. Towards this direction, manual annotations of these segments by dance experts can play a four-fold role: a) enrich movement libraries with expert knowledge, b) create "ground-truth" datasets for comparing the results of automated algorithms, c) fertilize a dialogue across dance genres and disciplines on movement analysis and conceptualization, and d) raise questions on the subjectivity and diversity of characterizing movement segments using verbal descriptions. The web-based application presented in this work, is an archival system with, browsing, searching, visualization, personalization and textual annotation functionalities. Its main objective is to provide access to a repository of multimodal dance recordings including motion capture data, video, and audio, with the aim to also support dance education. The tool has been designed and developed within an interdisciplinary project, following a user-centered, iterative design approach involving dance researchers and practitioners of four different dance genres.
Cardiomyocyte—Endothelial Cell Interactions in Cardiac Remodeling and Regeneration

The heart is a complex organ consisting of various cell types, each of which plays an important role in both physiological and pathophysiological conditions. The cells communicate with each other through direct cell-cell interactions and paracrine signaling, and both homotypic and heterotypic cell interactions contribute to the organized structure and proper function of the heart. Cardiomyocytes (CMs) and endothelial cells (ECs) are two of the most abundant cardiac cell types and they also play central roles in both cardiac remodeling and regeneration. The postnatal cell cycle withdrawal of CMs, which takes place within days or weeks after birth, represents the major barrier for regeneration in adult mammalian hearts, as adult CMs exhibit a very low proliferative capacity. Recent evidence highlights the importance of ECs not only as the most abundant cell type in the heart but also as key players in post-infarction remodeling and regeneration. In this MiniReview, we focus on blood vascular ECs and CMs and their roles and interactions in cardiac physiology and pathologies, with a special emphasis on cardiac regeneration. We summarize the known mediators of the bidirectional CM-EC interactions and discuss the related recent advances in the development of therapies aiming to promote heart repair and regeneration targeting these two cell types.
A Fast Simulation Method Using SPH and Wavelet for Sub-Particle-Scale Turbulent Flow

This paper presents a fast simulation method for turbulent flow which uses a particle method and wavelet analysis. To simulate fluid flow, the method uses smoothed particle hydrodynamics (SPH), which discretizes the fluid into a collection of particles, and detects regions where turbulent flow will occur by using wavelet analysis without a spatial grid. By taking the curl of wavelet noise, the turbulent flow is then appended as a divergence-free turbulence velocity field. Additionally, by using vortex subparticles, which characterize the vortex features of turbulence, a subparticle-scale representation of turbulent flow is proposed. Implementing almost all processes on a graphics processing unit (GPU), simulations are performed in near real time.
Second-Order Continuous-Time Algorithms for Economic Power Dispatch in Smart Grids

This paper proposes two second-order continuous-time algorithms to solve the economic power dispatch problem in smart grids. The collective aim is to minimize a sum of generation cost function subject to the power demand and individual generator constraints. First, in the framework of nonsmooth analysis and algebraic graph theory, one distributed second-order algorithm is developed and guaranteed to find an optimal solution. As a result, the power demand constraints can be kept all the time under appropriate initial condition. The second algorithm is under a centralized framework, and the optimal solution is robust in the sense that different initial power conditions do not change the convergence of the optimal solution. Finally, simulation results based on five-unit system, IEEE 30-bus system, and IEEE 300-bus system show the effectiveness and performance of the proposed continuous-time algorithms. The examples also show that the convergence rate of second-order algorithm is faster than that of first-order distributed algorithm.
Array of Gas Sensors Based on TiO2 Upon Temperature Modulation

The aim of this work is to demonstrate that thermal modulation improves the selectivity of TiO2 – based resistive-type gas sensors. The sensors operate upon sinusoidal temperature profile over a temperature range of 240–300°C. Sensor array is composed of nanocrystalline TiO2:Cr (0.1–10 at.% Cr). The switching from n-type to p-type conductivity occurs at about 1 at. % Cr. Electrical resistance responses to reducing and oxidizing gases such as: NO, NO2, H2, CH4, C3H8 (0–3000 ppm) are dynamically recorded and compared in order to assess cross-sensitivity as well as humidity interference. The results of the Principle Component Analysis, PCA demonstrate that reliable detection and classification of H2, and NOx have been achieved.
An Image-based Hair Styling System Using Layered Texture Pieces

We present an interactive system that allows the user to ﬁnely edit a hairstyle image so that the image can be naturally synthesized onto a given facial image. In our system, a hairstyle is composed by stacking texture pieces (textured belt-shaped polygons) that represent hair wisps. By warping these pieces, the user can perform typical manipulations for hairstyles, such as lengthening/shortening, combing (modiﬁcation of the ﬂows of hair) and scissoring. We demonstrate the effectiveness of our system through experimental results with various hairstyle images and facial images
Spectrogram-Based Automatic Modulation Recognition Using Convolutional Neural Network

We study a system for classifying modulation types with spectrograms obtained through short-time Fourier transform. AWGN-based carrier modulated signals and their spectrograms are generated. In order to extract features from spectrogram automatically, we learned our convolutional neural network model with the generated data. Even at low SNRs, the performance is fairly good, but additional modulation type applications and comparisons with others in various environments are necessary.
Fractional-Order Closed-Loop Model Reference Adaptive Control for Anesthesia

The design of a fractional-order closed-loop model reference adaptive control (FOCMRAC) for anesthesia based on a fractional-order model (FOM) is proposed in the paper. This proposed model gets around many difficulties, namely, unknown parameters, lack of state measurement, inter and intra-patient variability, and variable time-delay, encountered in controller designs based on the PK/PD model commonly used for control of anesthesia, and allows to design a simple adaptive controller based on the Lyapunov analysis. Simulations illustrate the effectiveness and robustness of the proposed control.
Reducing Vulnerability to Cyber-Physical Attacks in Water Distribution Networks

Cyber-Physical Systems (CPS), such as Water Distribution Networks (WDNs), deploy digital devices to monitor and control the behavior of physical processes. These digital devices, however, are susceptible to cyber and physical attacks, that may alter their functionality, and therefore the integrity of their measurements/actions. In practice, industrial control systems utilize simple control laws, which rely on various sensor measurements and algorithms which are expected to operate normally. To reduce the impact of a potential failure, operators may deploy redundant components; this however may not be useful, e.g., when a cyber attack at a PLC component occurs. In this work, we address the problem of reducing vulnerability to cyber-physical attacks in water distribution networks. This is achieved by augmenting the graph which describes the information flow from sensors to actuators, by adding new connections and algorithms, to increase the number of redundant cyber components. These, in turn, increase the \textit{cyber-physical security level}, which is defined in the present paper as the number of malicious attacks a CPS may sustain before becoming unable to satisfy the control requirements. A proof-of-concept of the approach is demonstrated over a simple WDN, with intuition on how this can be used to increase the cyber-physical security level of the system.
Layered Graphs: Applications and Algorithms

The computation of distances between strings has applications in molecular biology, music theory and pattern recognition. One such measure, called short reversal distance, has applications in evolutionary distance computation. It has been shown that this problem can be reduced to the computation of a maximum independent set on the corresponding graph that is constructed from the given input strings. The constructed graphs primarily fall into a class that we call layered graphs. In a layered graph, each layer refers to a subgraph containing, at most, some k vertices. The inter-layer edges are restricted to the vertices in adjacent layers. We study the MIS, MVC, MDS, MCV and MCD problems on layered graphs where MIS computes the maximum independent set; MVC computes the minimum vertex cover; MDS computes the minimum dominating set; MCV computes the minimum connected vertex cover; and MCD computes the minimum connected dominating set. MIS, MVC and MDS run in polynomial time if k=Θ(log|V|). MCV and MCD run in polynomial time ifk=O((log|V|)α), where α 0, then MIS, MVC and MDS run in quasi-polynomial time. If k=Θ(log|V|), then MCV and MCD run in quasi-polynomial time.
Extranodal lymphomas in the public health system in Chile: Analysis of 1251 patients from the National Adult Cancer Program

The aim of the study was to describe the clinical and epidemiological characteristics, anatomic and histologic distribution, and treatment results of extranodal lymphomas (ENLs), diagnosed and treated in the public health system in Chile. We included patients with ENL diagnosed from 1998 to 2014, in 17 cancer centers, registered prospectively in the database of the National Adult Cancer Program (PANDA) of the Ministry of Health. Treatment was based on the local protocols for each lymphoma subtype. Extranodal lymphoma was documented in 1215 of 4907 non‐Hodgkin lymphomas diagnosed in that period (25%). Median age was 59 years (range, 16‐95), and 55% were female. The gastrointestinal (GI) tract was the most common location (38%), followed by the head and neck (24%) and the skin (15%). B‐cell lymphomas accounted for 78% of cases, diffuse large B‐cell lymphoma being the most common histologic subtype (68%). Mycosis fungoides/Sezary syndrome was the most frequent T‐cell subtype (36%), followed by NK/T‐cell lymphomanasal type (24%). In comparison with western countries, Chile showed a significantly high prevalence of NK/T‐cell lymphoma nasal type, while the frequency of B‐cell ENL and the anatomic distribution appeared similar, being GI the most commonly involved site.
Heterogeneous dopamine signals support distinct features of motivated actions: implications for learning and addiction

Despite decades of research, investigations into effective neural and pharmacological therapies for many drugs of abuse, such as cocaine, have produced no FDA-approved approaches. This difficulty derives from the complexity of substance use disorders, which encompass a variety of behavioral, psychological, and neural circuit-based changes that occur as a result of repeated experience with the drug. Dopamine signaling has been demonstrated to play a key role in several aspects of drug abuse—from mediating its reinforcing properties and drug-seeking to triggering relapse—while also mediating a number of important aspects of normal (nondrug related) motivated behaviors and actions. Real-time recording methods such as in vivo voltammetry, electrophysiology, and calcium imaging demonstrate that the signaling properties of dopamine for motivationally relevant stimuli are highly dynamic and spatiotemporally circumscribed within afferent target regions. In this review, we identify the origins and functional consequences of heterogeneous dopamine release in the limbic system, and how these properties are persistently altered in the drug-experienced brain. We propose that these spatiotemporally parallel dopaminergic signals are simultaneously available to the animal, but that these circuits are impaired following prolonged drug experience by disrupting the location and content of dopamine signals in afferent target regions. These findings are discussed in the context of relapse and pathways to discovering new treatments for addiction disorders.
In vitro behavior and UV response of melanocytes derived from carriers of CDKN2A mutations and MC1R variants

Coinheritance of germline mutation in cyclin‐dependent kinase inhibitor 2A (CDKN2A) and loss‐of‐function (LOF) melanocortin 1 receptor (MC1R) variants is clinically associated with exaggerated risk for melanoma. To understand the combined impact of these mutations, we established and tested primary human melanocyte cultures from different CDKN2A mutation carriers, expressing either wild‐type MC1R or MC1RLOF variant(s). These cultures expressed the CDKN2A product p16 (INK4A) and functional MC1R. Except for 32ins24 mutant melanocytes, the remaining cultures showed no detectable aberrations in proliferation or capacity for replicative senescence. Additionally, the latter cultures responded normally to ultraviolet radiation (UV) by cell cycle arrest, JNK, p38, and p53 activation, hydrogen peroxide generation, and repair of DNA photoproducts. We propose that malignant transformation of melanocytes expressing CDKN2A mutation and MC1RLOF allele(s) requires acquisition of somatic mutations facilitated by MC1R genotype or aberrant microenvironment due to CDKN2A mutation in keratinocytes and fibroblasts.
Plant nutrient acquisition entices herbivore

Maize defense metabolites enable iron uptake and attract herbivore attention To survive in highly complex environments, plants universally rely on specialized, or secondary, metabolites to withstand abiotic challenges (for example, wax to limit transpiration) and biotic challenges (for example, glucosinolates to deter herbivores). These metabolites are lineage-specific, and functional studies usually consider them to have a singular function. However, the complexity of the environment is much larger than the number of secondary metabolites within a plant, indicating that individual specialized metabolites may need to have multiple roles. As the number of functions of a single metabolite increases, so does the number of proteins and processes affected, and there is no guarantee that all of these interactions are positive. On page 694 of this issue, Hu et al. (1) show that benzoxazinoids, a textbook example of specialized metabolites in maize, have a functional duality centered around iron acquisition. The benzoxazinoids aid the uptake of iron. However, this generates a penalty because the herbivore, western corn rootworm, senses benzoxazinoid–iron complexes as a cue to locate and consume maize plants. This presents an evolutionary quandary, whereby maize can acquire iron and be eaten or maize can starve itself of iron and avoid herbivory—most plants have metabolites that create a similar conundrum.
Deep Belief Networks Based Toponym Recognition for Chinese Text

In Geographical Information Systems, geo-coding is used for the task of mapping from implicitly geo-referenced data to explicitly geo-referenced coordinates. At present, an enormous amount of implicitly geo-referenced information is hidden in unstructured text, e.g., Wikipedia, social data and news. Toponym recognition is the foundation of mining this useful geo-referenced information by identifying words as toponyms in text. In this paper, we propose an adapted toponym recognition approach based on deep belief network (DBN) by exploring two key issues: word representation and model interpretation. A Skip-Gram model is used in the word representation process to represent words with contextual information that are ignored by current word representation models. We then determine the core hyper-parameters of the DBN model by illustrating the relationship between the performance and the hyper-parameters, e.g., vector dimensionality, DBN structures and probability thresholds. The experiments evaluate the performance of the Skip-Gram model implemented by the Word2Vec open-source tool, determine stable hyper-parameters and compare our approach with a conditional random field (CRF) based approach. The experimental results show that the DBN model outperforms the CRF model with smaller corpus. When the corpus size is large enough, their statistical metrics become approaching. However, their recognition results express differences and complementarity on different kinds of toponyms. More importantly, combining their results can directly improve the performance of toponym recognition relative to their individual performances. It seems that the scale of the corpus has an obvious effect on the performance of toponym recognition. Generally, there is no adequate tagged corpus on specific toponym recognition tasks, especially in the era of Big Data. In conclusion, we believe that the DBN-based approach is a promising and powerful method to extract geo-referenced information from text in the future.
Trend Analysis of a Database of Intravenous Pharmacokinetic Parameters in Humans for 1352 Drug Compounds

We report a trend analysis of human intravenous pharmacokinetic data on a data set of 1352 drugs. The aim in building this data set and its detailed analysis was to provide, as in the previous case published in 2008, an extended, robust, and accurate resource that could be applied by drug metabolism, clinical pharmacology, and medicinal chemistry scientists to a variety of scaling approaches. All in vivo data were obtained or derived from original references, either through the literature or regulatory agency reports, exclusively from studies utilizing intravenous administration. Plasma protein binding data were collected from other available sources to supplement these pharmacokinetic data. These parameters were analyzed concurrently with a range of physicochemical properties, and resultant trends and patterns within the data are presented. In addition, the date of first disclosure of each molecule was reported and the potential “temporal” impact on data trends was analyzed. The findings reported here are consistent with earlier described trends between pharmacokinetic behavior and physicochemical properties. Furthermore, the availability of a large data set of pharmacokinetic data in humans will be important to further pursue analyses of physicochemical properties, trends, and modeling efforts and should propel our deeper understanding (especially in terms of clearance) of the absorption, distribution, metabolism, and excretion behavior of drug compounds.