Miracle-dz/UniFAR-FTUs huggingface dataset:
A Review of Auditory Prediction and Its Potential Role in Tinnitus Perception

Abstract Background: The precise mechanisms underlying tinnitus perception and distress are still not fully understood. A recent proposition is that auditory prediction errors and related memory representations may play a role in driving tinnitus perception. It is of interest to further explore this. Purpose: To obtain a comprehensive narrative synthesis of current research in relation to auditory prediction and its potential role in tinnitus perception and severity. Research Design: A narrative review methodological framework was followed. Data Collection and Analysis: The key words Prediction Auditory, Memory Prediction Auditory, Tinnitus AND Memory, Tinnitus AND Prediction in Article Title, Abstract, and Keywords were extensively searched on four databases: PubMed, Scopus, SpringerLink, and PsychINFO. All study types were selected from 2000–2016 (end of 2016) and had the following exclusion criteria applied: minimum age of participants <18, nonhuman participants, and article not available in English. Reference lists of articles were reviewed to identify any further relevant studies. Articles were short listed based on title relevance. Study Sample: After reading the abstracts and with consensus made between coauthors, a total of 114 studies were selected for charting data. Results: The hierarchical predictive coding model based on the Bayesian brain hypothesis, attentional modulation and top-down feedback serves as the fundamental framework in current literature for how auditory prediction may occur. Predictions are integral to speech and music processing, as well as in sequential processing and identification of auditory objects during auditory streaming. Although deviant responses are observable from middle latency time ranges, the mismatch negativity (MMN) waveform is the most commonly studied electrophysiological index of auditory irregularity detection. However, limitations may apply when interpreting findings because of the debatable origin of the MMN and its restricted ability to model real-life, more complex auditory phenomenon. Cortical oscillatory band activity may act as neurophysiological substrates for auditory prediction. Tinnitus has been modeled as an auditory object which may demonstrate incomplete processing during auditory scene analysis resulting in tinnitus salience and therefore difficulty in habituation. Within the electrophysiological domain, there is currently mixed evidence regarding oscillatory band changes in tinnitus. Conclusions: There are theoretical proposals for a relationship between prediction error and tinnitus but few published empirical studies.
Design method for inductorless low-noise amplifiers with active shunt-feedback in 65-nm CMOS

We propose a design method for inductorless low-noise amplifiers with active shunt-feedback in 65-nm CMOS and analyze the characteristics. The gain of the NMOS should be larger than that of the PMOS for improvement of the voltage gain and the noise figure. A bandwidth of around 8 GHz was obtained in an analysis using a circuit simulation of the designed low-noise amplifier, which is higher than that of the conventional 0.13 μm CMOS type.
Functional aspects of competitive tennis

Tennis is a sport that is characterized by intermittent dynamics, with intervallic moderate and high-intensity efforts due to repetitive actions of short-duration and high intensity. This review analyzes aspects such as the game's temporal structure, oxygen consumption, heart rate, lactate levels, and the effects of playing in heat. Knowledge of the contextual and functional characteristics of competitive tennis provides important information for improving the design of players training programs.
Food Protein-Induced Enterocolitis Syndrome Causing Hypovolemic Shock and Methemoglobinemia

A 5-week-old previously healthy male presented with vomiting and diarrhea leading to hypovolemic shock and profound metabolic acidosis. He was subsequently found to have severe methemoglobinemia. The acidosis and shock improved with fluid resuscitation and methemoglobinemia was successfully treated with methylene blue. An extensive workup, including evaluations for infectious and metabolic etiologies, was unremarkable. However, a detailed dietary history revealed a recent change in diet, supporting a diagnosis of food protein-induced enterocolitis syndrome (FPIES). We present this case to highlight the importance of considering FPIES in an infant with vomiting and diarrhea, in the setting of a recent dietary change, leading to profound dehydration, metabolic acidosis, and methemoglobinemia. Diagnosis of FPIES, although difficult to make and one of exclusion, can be potentially life-saving.
Cook over IP: Adapting TCP for Cordless Kitchen Appliances

Cordless kitchens are the next big step in Smart Kitchens that are enabled by the Internet of Things (IoT) paradigm. The appliances in a cordless kitchen are powered by inductive power sources (PTx) that are integrated into kitchen counter-tops. The appliance and the PTx exchange control information using a near-field communication (NFC) channel. These appliances currently do not have Internet connectivity to enable smart cooking and control of the appliance from smartphones. Embedding a WiFi radio powered by batteries on the appliance is undesirable as batteries require recharging or replacement, and also increase the cost of the appliance. Therefore, we propose to connect the PTx to Internet and exploit the NFC channel for tunneling Internet traffic to the appliances. Due to the heavy magnetic fields induced by the PTx, this NFC channel has to be time-slotted, which is unique to the cordless kitchen appliances. This introduces many challenges on the communication, as the low data rates and high latencies of the NFC channel are aggravated by the slotting of the NFC channel. We focus on the TCP protocol as it is the most widely used transport protocol on the Internet. The performance of TCP is severely affected due to the time-slotted NFC channel. We identify two major problems that occur when TCP/IP is tunneled over the time-slotted NFC channel, namely spurious retransmissions of the TCP packets and packet drops at the NFC interface. Since most of the TCP/IP sessions in this environment are short, relying on TCP's natural course to adapt to long delays is not viable. To solve these, we propose a method to determine optimal TCP retransmission timeout values, and a channel sensing mechanism to avoid packet drops. In addition, we perform a detailed analysis to study the influence of parameters such as the contention window size, maximum segment size and NFC bit error rates. We implement and evaluate the solutions on a cordless kitchen testbed. We find that the proposed solutions almost completely eliminate the spurious retransmissions and packet drops. Furthermore, we achieve up to 53% lower end-to-end latency at 24 kbps in the NFC time-slotted mode.
Lessons Learned in Developing a Commercial FIV Vaccine: The Immunity Required for an Effective HIV-1 Vaccine

The feline immunodeficiency virus (FIV) vaccine called Fel-O-Vax® FIV is the first commercial FIV vaccine released worldwide for the use in domestic cats against global FIV subtypes (A–E). This vaccine consists of inactivated dual-subtype (A plus D) FIV-infected cells, whereas its prototype vaccine consists of inactivated dual-subtype whole viruses. Both vaccines in experimental trials conferred moderate-to-substantial protection against heterologous strains from homologous and heterologous subtypes. Importantly, a recent case-control field study of Fel-O-Vax-vaccinated cats with outdoor access and ≥3 years of annual vaccine boost, resulted in a vaccine efficacy of 56% in Australia where subtype-A viruses prevail. Remarkably, this protection rate is far better than the protection rate of 31.2% observed in the best HIV-1 vaccine (RV144) trial. Current review describes the findings from the commercial and prototype vaccine trials and compares their immune correlates of protection. The studies described in this review demonstrate the overarching importance of ant-FIV T-cell immunity more than anti-FIV antibody immunity in affording protection. Thus, future efforts in developing the next generation FIV vaccine and the first effective HIV-1 vaccine should consider incorporating highly conserved protective T-cell epitopes together with the conserved protective B-cell epitopes, but without inducing adverse factors that eliminate efficacy.
Ultrathin phase-change coatings on metals for electrothermally tunable colors

Metal surfaces coated with ultrathin lossy dielectrics enable color generation through strong interferences in the visible spectrum. Using a phase-change thin film as the coating layer offers tuning the generated color by crystallization or re-amorphization. Here, we study the optical response of surfaces consisting of thin (5–40 nm) phase-changing Ge2Sb2Te5 (GST) films on metal, primarily Al, layers. A color scale ranging from yellow to red to blue that is obtained using different thicknesses of as-deposited amorphous GST layers turns dim gray upon annealing-induced crystallization of the GST. Moreover, when a relatively thick (>100 nm) and lossless dielectric film is introduced between the GST and Al layers, optical cavity modes are observed, offering a rich color gamut at the expense of the angle independent optical response. Finally, a color pixel structure is proposed for ultrahigh resolution (pixel size: 5 × 5 μm2), non-volatile displays, where the metal layer acting like a mirror is used as a heate.
Finite Control-Set Predictive Power Control of BLDC Drive for Torque Ripple Reduction

Due to advantages as high efficiency and high power density, brushless direct current (BLDC) motor has been used in a wide variety of applications. However, in conventional 120º conducting drive operation it develops significant torque ripple as a result of phase commutation. To reduce torque undulations, in this paper is proposed a power control based on Finite Control-Set Model based Predictive Control (FCS-MPC). The relationship between the control of the power delivered to rotor and torque ripple reduction is presented. The effectiveness of commutation torque ripple reduction of proposed method is presented in comparison with conventional torque control strategy. The results of proposed predictive control approach demonstrate fast torque response with no adjustable gains needed and operates with model variables on stationary reference frame.
Context-Sensitive Prediction of Facial Expressivity Using Multimodal Hierarchical Bayesian Neural Networks

Objective automated affect analysis systems can be applied to quantify the progression of symptoms in neurodegenerative diseases such as Parkinson's Disease (PD). PD hampers the ability of patients to emote by decreasing the mobility of their facial musculature, a phenomenon known as ``facial masking. '' In this work, we focus on building a system that can predict an accurate score of active facial expressivity in people suffering from Parkinson's disease using features extracted from both video and audio. An ideal automated system should be able to mimic the ability of human experts to take into account contextual information while making these predictions. For example, patients exhibit different emotions with varying intensities when speaking about positive and negative experiences. We utilize a hierarchical Bayesian neural network framework to enable the learning of model parameters that subtly adapt to pre-defined notions of context, such as the gender of the patient or the valence of the expressed sentiment. We evaluate our formulation on a dataset of 772 20-second video clips of Parkinson's disease patients and demonstrate that training a context-specific hierarchical Bayesian framework yields an improvement in model performance in both multiclass classification and regression settings compared to baseline models trained on all data pooled together.
Clustering driving trip trajectory data based on pattern discovery techniques

Identifying patterns to characterize driving human driving styles from driving trip data is a promising and interesting area of research and application. To cluster the driving trips in a set of recorded GPS tracks, this paper presents an information theoretic approach to characterize them based on their occurrences of frequently detected patterns. The patterns are discovered through a statistical significance test on a generated set of spatio-temporal data and its associated attributes that represent the characteristics of recorded GPS data. For evaluating the performance of the proposed approach, a real dataset with ground truth information is tested to validate its clustering power and compare with other approaches. The result indicates the approach is effective and efficient to extract interpretable features to summarize the complex driving behaviors to form a good representation of driving styles for machine learning to achieve good performance.
Myopia-Inhibiting Concentrations of Muscarinic Receptor Antagonists Block Activation of Alpha2A-Adrenoceptors In Vitro.

Purpose Myopia is a refractive disorder that degrades vision. It can be treated with atropine, a muscarinic acetylcholine receptor (mAChR) antagonist, but the mechanism is unknown. Atropine may block α-adrenoceptors at concentrations ≥0.1 mM, and another potent myopia-inhibiting ligand, mamba toxin-3 (MT3), binds equally well to human mAChR M4 and α1A- and α2A-adrenoceptors. We hypothesized that mAChR antagonists could inhibit myopia via α2A-adrenoceptors, rather than mAChR M4. Methods Human mAChR M4 (M4), chicken mAChR M4 (cM4), or human α2A-adrenergic receptor (hADRA2A) clones were cotransfected with CRE/promoter-luciferase (CRE-Luc; agonist-induced luminescence) and Renilla luciferase (RLuc; normalizing control) into human cells. Inhibition of normalized agonist-induced luminescence by antagonists (ATR: atropine; MT3; HIM: himbacine; PRZ: pirenzepine; TRP: tropicamide; OXY: oxyphenonium; QNB: 3-quinuclidinyl benzilate; DIC: dicyclomine; MEP: mepenzolate) was measured using the Dual-Glo Luciferase Assay System. Results Relative inhibitory potencies of mAChR antagonists at mAChR M4/cM4, from most to least potent, were QNB > OXY ≥ ATR > MEP > HIM > DIC > PRZ > TRP. MT3 was 56× less potent at cM4 than at M4. Relative potencies of mAChR antagonists at hADRA2A, from most to least potent, were MT3 > HIM > ATR > OXY > PRZ > TRP > QNB > MEP; DIC did not antagonize. Conclusions Muscarinic antagonists block hADRA2A signaling at concentrations comparable to those used to inhibit chick myopia (≥0.1 mM) in vivo. Relative potencies at hADRA2A, but not M4/cM4, correlate with reported abilities to inhibit chick form-deprivation myopia. mAChR antagonists might inhibit myopia via α2-adrenoceptors, instead of through the mAChR M4/cM4 receptor subtype.
DORA: Optimizing Smartphone Energy Efficiency and Web Browser Performance under Interference

This paper proposes DORA — a dynamic frequency controller that maximizes the energy efficiency of smartphones subject to user satisfaction demands in the presence of memory interference stemmed from background processes and coscheduled applications. The proposed algorithm predicts the optimal energy-efficient frequency setting at runtime using staticallytrained performance, dynamic power, and leakage power models. The parameters of the models represent web page characteristics and dynamically varying architecture and system conditions. The algorithm is designed, implemented and extensively evaluated on a Google Nexus 5 smartphone using a variety of mobile web browsing workloads. The results show high prediction accuracies for the performance and power models of 97.5% and 96%, respectively. Overall, DORA improves the smartphone's energy efficiency by an average of 16% compared to the default Android frequency governor, interactive, while maintaining the desired levels of user satisfaction (web page load time).
Tissue-Specific Increase Of Insulin-Like Growth Factor I Gene Expression In Human Adipose Tissue After Abdominal Surgery

The growth hormone (GH)/insulin-like growth factor I (IGF-I) axis in catabolic conditions is believed to be severely altered, based on measurements of biochemical markers in plasma and clinical observations. To test the hypothesis that GH sensitivity may be differentially regulated in different tissues, we analysed GH receptor (GHR) and IGF-I gene expression in adipose tissue and skeletal muscle, before and after major surgery, and compared it with the corresponding gene products in plasma, IGF-I and GH-binding protein (GHBP). A significant increase (p<0.05) in IGF-I mRNA levels was found in adipose tissue after surgery whereas there were no changes in IGF-I mRNA levels in skeletal muscle or IGF-I concentrations in plasma. Furthermore, GHR mRNA levels did not change after surgery whereas GHBP in plasma decreased postoperatively (p<0.01). This study shows that catabolism induced by surgical trauma is associated with differential regulation of IGF-I gene expression in adipose tissue and skeletal muscle and that plasma measurements of IGF-I and GHBP may not accurately reflect changes in gene expression in different tissues. These observations may have implications in the planning and conduction of clinical studies in catabolic states. Ruth Wickelgren and Gunnel Hellgren contributed equally to this manuscript and should both be considered first
Normative Quadriceps and Hamstring Muscle Strength Values for Female, Healthy, Elite Handball and Football Players

Abstract Risberg, MA, Steffen, K, Nilstad, A, Myklebust, G, Kristianslund, E, Moltubakk, MM, and Krosshaug, T. Normative quadriceps and hamstring muscle strength values for female, healthy, elite handball and football players. J Strength Cond Res 32(8): 2314–2323, 2018—This study presents normative values for isokinetic knee extension and flexion muscle strength tests in 350 elite, female, handball (n = 150) and football (n = 200) players. Isokinetic concentric muscle strength tests at 60°·sec−1 were recorded bilaterally using a dynamometer. Peak torque (in Newton meter [N·m]), body mass normalized peak torque (N·m·kg−1), and hamstring to quadriceps ratio (H:Q ratio) for dominant and nondominant legs were recorded. The female elite players were 20.9 ± 4.0 years, started playing at the elite level at the age of 18.2 ± 2.7 years, with a mean of 9.7 ± 2.2 hours of weekly in-season training. Handball players demonstrated greater quadriceps muscle strength compared with football players (11.0%) (p < 0.001), also when normalized to body mass (4.1%) (p = 0.012), but not for weight-adjusted hamstring muscle strength. The H:Q ratio was higher on the dominant compared with the nondominant leg for handball players only (p = 0.012). The H:Q ratio was significantly lower for handball players (0.58) compared with football players (0.60) (p < 0.02). These normative values for isokinetic knee extension and flexion torques of healthy, elite, female handball and football players can be used to set rehabilitation goals for muscle strength after injury and enable comparison with uninjured legs. Significantly greater quadriceps muscle strength was found for handball players compared with football players, also when normalized to body mass.
Probing the Plasmon Coupling, Quantum Yield, and Effects of Tip Geometry of Gold Nanoparticle Using Analytical Models and FDTD Simulation

In this paper, we investigated the plasmon coupling, quantum yield (QY) and effect of tip geometry of gold nanoparticles (AuNPs) using finite-difference time-domain (FDTD) simulation. Standalone AuNPs spectra have been obtained using the most reliable electromagnetic theory such as Mie theory for spherical nanoparticle such as gold nanosphere (AuNS) and Mie–Gans theory for ellipsoidal AuNPs such as gold nanorod (AuNR). We reported the scattering cross section for standalone and coupling particle using the modified dielectric constant, where the size effect of small particles and the retardation effect of large particles have been taken into consideration for both the analytical calculation and FDTD simulation. Plasmon coupling effect of AuNS dimer of 80-nm diameter and AuNR dimer (side-by-side geometry) of aspect ratio 3.8 has been investigated using FDTD simulation. We also quantified the QY in terms of cluster to monomer ratio for AuNS and AuNR, which is analogous to the ratio of acceptor and donor chromophore in biological systems. The QY of monomer, dimer, and trimer of 40-nm diameter AuNS has been perceived using FDTD simulation, integrating the whole spectrum over 400–1000 nm wavelength regime. Additionally, effect of tip geometry of AuNPs has been investigated and significant field enhancement due to the variation in shapes such as AuNS, AuNR, gold dumbbell, and gold bipyramid has also been reported. The novelty of the paper lies in the presentation of a systematic study of the plasmon coupling of different sizes and shapes of AuNP, quantification of the QY, and probing the effect of tip geometry for a single material such as AuNP using the FDTD simulation. Moreover, we believe that our in-depth analysis of AuNP laid the foundation to determine the scattering cross-section, QY, and near-field enhancement for more complex structures and geometries of other novel materials. Conclusively, the investigation results demonstrate that plasmonic nanoparticle can be used as a molecular probe for bioimaging, sensing, cell signaling, and biological therapeutic intervention.
Solving Data Sparsity for Aspect Based Sentiment Analysis Using Cross-Linguality and Multi-Linguality

Efficient word representations play an important role in solving various problems related to Natural Language Processing (NLP), data mining, text mining etc. The issue of data sparsity poses a great challenge in creating efficient word representation model for solving the underlying problem. The problem is more intensified in resource-poor scenario due to the absence of sufficient amount of corpus. In this work we propose to minimize the effect of data sparsity by leveraging bilingual word embeddings learned through a parallel corpus. We train and evaluate Long Short Term Memory (LSTM) based architecture for aspect level sentiment classification. The neural network architecture is further assisted by the hand-crafted features for the prediction. We show the efficacy of the proposed model against state-of-the-art methods in two experimental setups i.e. multi-lingual and cross-lingual.