Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterizing the Aerobic and Anaerobic Energy Costs of Polynesian Dances

This study characterized both aerobic and anaerobic energy expenditure (EE) for several Polynesian dances in a group of experienced professional Polynesian dancers. Thirteen men and 17 women were tested using indirect calorimetry to assess aerobic EE (and converted to METs), and fingertip blood lactate to estimate anaerobic EE, during both resting and dancing activities. Total EE was then computed as the sum of both aerobic and anaerobic activity energy expenditure (AEE, or EE above resting). One sample t-tests compared mean MET values for each type of dance to the 3-MET and 6-MET thresholds for moderate and vigorous physical activity (MVPA), respectively. Mean MET values for all dances, except the Maori poi balls dance (Mean±SD: 3.7±1.1 METs; P=0.340), were significantly >3.0 METs (5.9±3.1 METS; P=0.005 for Maori haka; 6.5±2.4 METs for Hawaiian hula; 6.6±1.2 METs for Samoan sasa; 9.6±1.5 METs for Samoan slap; 8.3±1.8 METs for Tahitian; 6.0±2.3 METs for Tongan; 7.0±2.6 METs for Fijian; P<0.001). Mean METs for Samoan slap and Tahitian were also significantly >6.0 METs (P=0.002 and P<0.001, respectively). Aerobic and anaerobic AEE contributed an average of 83.4% and 16.6%, respectively, across all Polynesian dances, with Hawaiian hula being the most aerobic (88.7%) and Samoan slap being the least aerobic (74.2%). Thus, the Polynesian dances tested not only met the current MVPA intensity guidelines (i.e., ≥3.0 METs), each dance also had a large anaerobic EE. These data suggest that Polynesian dancing is an appropriate mode of aerobic exercise for health promotion and disease prevention.
Electromagnetic Torque Analysis for All-Harmonic-Torque Permanent Magnet Synchronous Motor

This paper proposed a new type of permanent magnet synchronous motor (PMSM) called all-harmonic-torque PMSM (AHT-PMSM) to enhance the electromagnetic torque by using all harmonics of the magnetomotive force. The stator windings structure, drive converter configurations, and control model of the AHT-PMSM are illustrated. The calculation process of the average electromagnetic torque (AET) and torque ripple for AHT-PMSM are also analyzed. It is demonstrated that the theoretical AET of AHT-PMSM is improved by 23% compared to that of the normal PMSM with sinusoidal (SIN-PMSM) supply. Finally, a 24-slot/4-pole AHT-PMSM and SIN-PMSM prototypes are manufactured and tested to validity the effectiveness of the torque enhancement techniques.
Towards a Battery Characterization Methodology for Performance Evaluation of Micro-Grid Systems

Stand-alone micro-grid (MG) systems have been widely studied and installed especially in remote and rural regions. These systems are composed of renewable energy sources (RES) and storage devices. The main component in these systems is the storage device (e.g., batteries), which is used in order to store extra-produced energy during the day for eventual usage at night. However, battery’s characterization according to their operating conditions is required to better identify its parameters and study their performance and behavior within MG systems. This paper introduces an instrumentation platform for battery characterization and modeling using recent sensing/actuating equipment. The platform was first deployed for gathering important battery’s parameters, which are then used for building a simplified battery model. This model is then integrated into the MG system for evaluation and validation. Simulation results compared to experimental results show the accuracy of the developed battery model.
CC chemokine ligand 2 (CCL2) enhances TTX-sensitive sodium channel activity of primary afferent neurons in the complete Freud adjuvant-induced inflammatory pain model

CC chemokine ligand 2 (CCL2) has been implicated in pathological pain, but the mechanism underlying the pronociceptive effect of CCL2 is not fully understood. Voltage-gated sodium (Nav) channels are important determinants of the excitability of sensory neurons. Hence we tested the hypothesis that CCL2 contributes to inflammatory pain via modulating Nav channel activity of primary afferent neurons. Chronic inflammatory pain was induced in rats by intraplantar injection of the complete Freud adjuvant (CFA) to one of the hind paws. Control rats received intraplantar injection of equal volume of saline. A significant increase of CCL2 mRNA and CCL2 receptor (CCR2) protein expression was detected in the ipsilateral dorsal root ganglion (DRG) in CFA-treated rats. Intraplantar injection of CCL2 protein in the control rats had minimal effect on the paw withdrawal threshold (PWT) in response to mechanical stimulation. However, in CFA-treated rats, intraplantar CCL2 led to an increase in pain responses. Patch-clamp recording of acutely dissociated DRG neurons revealed that CCL2 had minimum effect on the excitability of sensory neurons from control rats. However, CCL2 directly depolarized a large proportion of small to medium-sized sensory neurons from CFA-treated rats. In addition, CCL2 was found to enhance whole-cell TTX-sensitive sodium currents without significantly affecting the TTX-resistant sodium currents and the potassium currents. These results are in agreement with previous reports concerning the involvement of CCL2-CCR2 signaling in inflammatory hyperalgesia and further indicate that enhanced TTX-sensitive channel activity may partly underlie the pronociceptive effects of CCL2.
Twist1 Suppresses Cementoblast Differentiation

The transcription factor Twist1 is known to be closely associated with the formation of bone by mesenchymal stem cells and osteoblasts; however, the role of Twist1 in cementogenesis has not yet been determined. This study was undertaken to elucidate the roles of Twist1 in cementoblast differentiation by means of the gain- or loss-of-function method. We used alkaline phosphatase (ALP) and alizarin red S staining and quantitative real-time reverse transcriptase polymerase chain reaction (qRT-PCR) to determine whether the forced transient expression or knock-down of Twist1 in a mouse cementoblast cell line, OCCM-30, could affect cementogenic differentiation. Silencing Twist1 with small interference RNA (siRNA) enhanced the formation of mineralized tissue. The expression of several cementogenesis markers, such as bone sialoprotein (BSP), osteopontin (OPN), dentin matrix protein1 (DMP1), and dentin sialophosphoprotein (DSPP) mRNA, were upregulated. Transient Twist1 overexpression in OCCM-30 consistently suppressed mineralization capacity and downregulated the differentiation markers. These results suggest that the Twist1 transcription factor may play a role in regulating cementoblast differentiation.
Block Sparse Bayesian Learning Based Joint User Activity Detection and Channel Estimation for Grant-Free NOMA Systems

This paper concerns uplink grant-free nonorthogonal multiple access, where the handshaking procedure is not required to reduce control signaling overhead and transmission latency. In especially the dynamic scenarios, e.g., Internet of vehicles, the active users have to be identified and their channel state information needs to be estimated before performing multiuser detection. We investigate the joint user activity detection (UAD) and channel estimation (CE), which provides necessary information for data detection. In this paper, the joint UAD and CE is formulated as a block sparse signal recovery problem. First, the block orthogonal matching pursuit (BOMP) algorithm is studied for this problem, but its complexity grows with the fourth power of active user number, which hinders its application. Then, block sparse Bayesian learning (BSBL) is investigated to solve this problem, and in particular a low complexity message passing based implementation of BSBL with belief propagation and mean field is developed. The proposed message passing based BSBL (MP-BSBL) algorithm has a complexity independent of active user number, which can be significantly lower than that of the BOMP algorithm. In addition, MP-BSBL provides an estimate of the noise power, which can be readily used for data detection. Simulation results show that the MP-BSBL algorithm delivers almost the same performance as BOMP with the exact knowledge of active user number and can reach the performance bound for channel estimation.
Birth weight and anthropometric measurements of twins

Abstract Background: Genetic and environmental influences on anthropometric measures can be investigated by comparing dizygotic (DZ) versus monozygotic (MZ) twins. Investigating cohorts living in different geographical areas across the globe can identify the variation in heritability versus environment. Aims: (1) To investigate the association between birth weight and anthropometric measurements during adulthood; (2) to study the genetic and environmental influences on body measures including birth weight, weight and height among twins; and (3) to assess the variation in heritability versus environment among two cohorts of twins who lived in different geographical areas. Subjects and methods: Twins were collected from two twin registers. Data on birth weight, adult weight and height in 430 MZ and 170 DZ twins living in two geographically distinct parts of the world were collected. A genetic analysis was performed using MX software. Results: Birth weight was associated with weight, height and BMI. Both MZ and DZ twins with low birth weight had shorter height during their adult life (p = 0.001), but only MZ twins with lower birth weight were lighter at adulthood (p = 0.001). Intra-pair differences in birth weight were not associated with differences in adult height (p = 0.366) or weight (p = 0.796). Additive genetic effects accounted for 53% of the variance in weight, 43% in height and 55% in birth weight. The remaining variance was attributed to unique environmental effects (15% for weight, 13% for height and 45% for birth weight and only 16% for BMI). Variability was found to be different in the two cohorts. The best fitting model for birth weight and BMI was additive genetic and non-shared environment and for weight and height was additive genetic, non-shared environment (plus common Environment). Conclusions: Data suggests that the association between weight at birth and anthropometric measures in later life is influenced by both genetic and environmental factors. Living in different environments can potentially relate to variation found in the environment.
On the relevance of an in vitro reconstructed human epidermis model for drug screening in atopic dermatitis

Recent advances in the development of human‐based in vitro models offer new tools for drug screening and mechanistic investigations of new therapeutic agents. However, there is a lack of evidence that disease models respond favourably to potential drug candidates. Atopic dermatitis (AD) is a very common disease associated with an altered skin barrier and chronic inflammation. Here, we demonstrate that the AD‐like features of a reconstructed human epidermis (RHE) model treated with Th2 cytokines are reversed in the presence of molecules known to have a beneficial effect on damaged skin as a result of modulating various signalling cascades including the Liver X Receptors and JAK/STAT pathways. This work shows that standardized and reproducible RHE are relevant models for therapeutic research assessing new drug candidates aiming to restore epidermal integrity in an inflammatory environment.
Multichannel NOMA-ALOHA Game With Fading

Non-orthogonal multiple access (NOMA) can improve the spectral efficiency by exploiting the power domain and successive interference cancellation, and in order to improve the throughput, it can be applied to random access that plays a crucial role in the Internet of Things to support connectivity for a number of devices with sparse activity. In this paper, we formulate a game when NOMA is applied to ALOHA to decide users’ access or transmission probabilities. We consider a payoff function based on an energy-efficiency metric and drive the mixed strategy Nash equilibrium (NE). Once the NOMA-ALOHA game is successfully formulated, we generalize it to take into account users’ different fading and multiple orthogonal channels, which might be necessary for NOMA-ALOHA to support a number of users in a realistic environment. A distributed algorithm based on gradient play is derived to find the mixed strategy NE (or transmission probabilities) of multichannel NOMA-ALOHA with fading.
A Weighted K-SVD-Based Double Sparse Representations Approach for Wireless Channels Using the Modified Takenaka-Malmquist Basis

In this paper, a new double-sparse representation scheme for wireless channel is proposed based on the modified Takenaka-Malmquist basis (MTMB) functions. Given a series of wireless channel samples with different Doppler shifts, the MTMB functions are first generated from these samples, and then an initial dictionary is constructed by these functions. What is more, the completeness and orthogonality of this dictionary have been proved, which is the theoretical support that the dictionary can be used for the above sparsity model. Second, in order to make the MTMB functions fit into the sparsity model better, a training method is developed to obtain the adaptive public weighted MTMB (PWMTMB) functions based on the proposed weighted K-SVD algorithm. In this method, the unnecessary extra storage and computational complexity can be reduced by only storing the basis functions strongly associated with the wireless channels in the initial dictionary. Besides, different weights are given to the basis functions according to the prior information of these channels, so each has the proper level of influence in the weighted sparse coding stage of the weighted K-SVD algorithm. As a result, sparser representations of wireless channels can be achieved through these PWMTMB functions. In addition, the proposed method can also be implemented in parallel via updating multiple basis functions each time, forming the parallel PWMTMB (PPWMTMB) functions which can also be used as the sparse basis functions for these channels. Our results show that the PWMTMB and the PPWMTMB are able to suit these types of wireless channels, giving a sparse representation per each.
Multi-Agent Fully Decentralized Off-Policy Learning with Linear Convergence Rates

In this paper we develop a fully decentralized algorithm for policy evaluation with off-policy learning, linear function approximation, and $O(n)$ complexity in both computation and memory requirements. The proposed algorithm is of the variance reduced kind and achieves linear convergence. We consider the case where a collection of agents have distinct and fixed size datasets gathered following different behavior policies (none of which is required to explore the full state space) and they all collaborate to evaluate a common target policy. The network approach allows all agents to converge to the optimal solution even in situations where neither agent can converge on its own without cooperation. We provide simulations to illustrate the effectiveness of the method.
Impact of HACA on Immunomodulation and Treatment Toxicity Following ch14.18/CHO Long-Term Infusion with Interleukin-2: Results from a SIOPEN Phase 2 Trial

GD2-directed immunotherapies improve survival of high-risk neuroblastoma (NB) patients (pts). Treatment with chimeric anti-GD2 antibodies (Ab), such as ch14.18, can induce development of human anti-chimeric Ab (HACA). Here, we report HACA effects on ch14.18/CHO pharmacokinetics, pharmacodynamics and pain intensity in pts treated by long-term infusion (LTI) of ch14.18/CHO combined with IL-2. 124 pts received up to 5 cycles of ch14.18/CHO 10 days (d) infusion (10 mg/m2/d; d8–18) combined with s.c. IL-2 (6 × 106 IU/m2/d; d1–5, d8–12). HACA, treatment toxicity, ch14.18/CHO levels, Ab-dependent cellular- (ADCC) and complement-dependent cytotoxicity (CDC) were assessed using respective validated assays. HACA-negative pts showed a steadily decreased pain in cycle 1 (74% pts without morphine by d5 of LTI) with further decrease in subsequent cycles. Ch14.18/CHO peak concentrations of 11.26 ± 0.50 µg/mL found in cycle 1 were further elevated in subsequent cycles and resulted in robust GD2-specific CDC and ADCC. Development of HACA (21% of pts) resulted in strong reduction of ch14.18/CHO levels, abrogated CDC and ADCC. Surprisingly, no difference in pain toxicity between HACA-positive and -negative pts was found. In conclusion, ch14.18/CHO LTI combined with IL-2 results in strong activation of Ab effector functions. Importantly, HACA response abrogated CDC but did not affect pain intensity indicating CDC-independent pain induction.
A Popularity-Based Approach for Effective Cloud Offload in Fog Deployments

Recent research has put forward the concept of Fog computing, a deported intelligence for IoT networks. Fog clusters are meant to complement current cloud deployments, providing compute and storage resources directly in the access network – which is particularly useful for low-latency applications. However, Fog deployments are expected to be less elastic than cloud platforms, since elasticity in Cloud platforms comes from the scale of the data-centers. Thus, a Fog node dimensioned for the average traffic load of a given application will be unable to handle sudden bursts of traffic. In this paper, we explore such a use-case, where a Fog-based latency-sensitive application must offload some of its processing to the Cloud. We build an analytical queueing model for deriving the statistical response time of a Fog deployment under different request Load Balancing (LB) strategies, contrasting a naive, an ideal (LFU-LB, assuming a priori knowledge of the request popularity) and a practical (LRU-LB, based on online learning of the popularity with an LRU filter) scheme. Using our model, and confirming the results through simulation, we show that the LRU-LB achieves close-to-ideal performance, with high savings on Cloud offload cost with respect to a request-oblivious strategy in the explored scenarios.
Emotional Prosody Processing in Schizophrenic Patients: A Selective Review and Meta-Analysis

Emotional prosody (EP) has been increasingly recognized as an important area of schizophrenic patients’ dysfunctions in their language use and social communication. The present review aims to provide an updated synopsis on emotional prosody processing (EPP) in schizophrenic disorders, with a specific focus on performance characteristics, the influential factors and underlying neural mechanisms. A literature search up to 2018 was conducted with online databases, and final selections were limited to empirical studies which investigated the prosodic processing of at least one of the six basic emotions in patients with a clear diagnosis of schizophrenia without co-morbid diseases. A narrative synthesis was performed, covering the range of research topics, task paradigms, stimulus presentation, study populations and statistical power with a quantitative meta-analytic approach in Comprehensive Meta-Analysis Version 2.0. Study outcomes indicated that schizophrenic patients’ EPP deficits were consistently observed across studies (d = −0.92, 95% CI = −1.06 < δ < −0.78), with identification tasks (d = −0.95, 95% CI = −1.11 < δ < −0.80) being more difficult to process than discrimination tasks (d = −0.74, 95% CI = −1.03 < δ < −0.44) and emotional stimuli being more difficult than neutral stimuli. Patients’ performance was influenced by both participant- and experiment-related factors. Their social cognitive deficits in EP could be further explained by right-lateralized impairments and abnormalities in primary auditory cortex, medial prefrontal cortex and auditory-insula connectivity. The data pointed to impaired pre-attentive and attentive processes, both of which played important roles in the abnormal EPP in the schizophrenic population. The current selective review and meta-analysis support the clinical advocacy of including EP in early diagnosis and rehabilitation in the general framework of social cognition and neurocognition deficits in schizophrenic disorders. Future cross-sectional and longitudinal studies are further suggested to investigate schizophrenic patients’ perception and production of EP in different languages and cultures, modality forms and neuro-cognitive domains.
Advanced Driver's Alarms System through Multi-agent Paradigm

The incorporation of Advance Driver Assistance Systems (ADAS) is a growing trend in active safety systems. The current outlook of passive ADAS that, exclusively warning the driver, presents a reactive interaction model in which each system acts independently. The increasing of the amount of in-vehicle passive ADASs arises an interoperability issue against conflict situations that could affect driver's decision-making process negatively, diminishing their attention level. This paper proposes an architecture based on the multi-agent paradigm for designing driver-centered ADASs that operates through the data fusion. The principal goal is to design a hierarchical structure which can manage the knowledge acquisition process of all aspects involved in the driving scene such as the environment as well as the driver's behavior and state, providing support for building and testing reasoning models. An experimental method was performed to verify the feasibility of the proposed approach using the deployment of a warning ADAS which involves the interaction of several developed systems. Besides, the staging of one set of specific hazardous driving situations was designed to conduct an experimental assay with ten drivers in a driving simulation system. Regarding evaluation measurements, the analysis of the reaction time performed by the drivers and user questionnaires collected after each experimental session has shown promising results.
Performance Tradeoff in Relay Aided D2D-Cellular Networks

With the explosive growth of multitudinous wireless services and high-data-rate required applications, relay aided Device-to-Device (D2D) communications have attracted increasing attentions. In this correspondence, we investigate the performance tradeoff in relay aided D2D-cellular networks, where D2D users reuse the resource of cellular uplink transmissions. To optimize the performance of relay aided D2D communications, we first study the tradeoff between spectral efficiency (SE) and energy efficiency, and propose a source-relay joint power allocation scheme. The optimal transmit powers for both source and relay users are derived, based on which we further introduce a SE-variation function to explicitly evaluate the impact of enabling D2D communications on D2D-cellular networks. Theoretical analysis and simulation results demonstrate the viability of the proposed scheme and provide comprehensive insights into the coexistence of different systems.