Feature Selection Approaches for Optimising Music Emotion Recognition Methods

The high feature dimensionality is a challenge in music emotion recognition. There is no common consensus on a relation between audio features and emotion. The MER system uses all available features to recognize emotion; however, this is not an optimal solution since it contains irrelevant data acting as noise. In this paper, we introduce a feature selection approach to eliminate redundant features for MER. We created a Selected Feature Set (SFS) based on the feature selection algorithm (FSA) and benchmarked it by training with two models, Support Vector Regression (SVR) and Random Forest (RF) and comparing them against with using the Complete Feature Set (CFS). The result indicates that the performance of MER has improved for both Random Forest (RF) and Support Vector Regression (SVR) models by using SFS. We found using FSA can improve performance in all scenarios, and it has potential benefits for model efficiency and stability for MER task

Dynamic physical activity recommendation on personalised mobile health information service: A deep reinforcement learning approach

Mobile health (mHealth) information service makes healthcare management easier for users, who want to increase physical activity and improve health. However, the differences in activity preference among the individual, adherence problems, and uncertainty of future health outcomes may reduce the effect of the mHealth information service. The current health service system usually provides recommendations based on fixed exercise plans that do not satisfy the user specific needs. This paper seeks an efficient way to make physical activity recommendation decisions on physical activity promotion in personalised mHealth information service by establishing data-driven model. In this study, we propose a real-time interaction model to select the optimal exercise plan for the individual considering the time-varying characteristics in maximising the long-term health utility of the user. We construct a framework for mHealth information service system comprising a personalised AI module, which is based on the scientific knowledge about physical activity to evaluate the individual exercise performance, which may increase the awareness of the mHealth artificial intelligence system. The proposed deep reinforcement learning (DRL) methodology combining two classes of approaches to improve the learning capability for the mHealth information service system. A deep learning method is introduced to construct the hybrid neural network combing long-short term memory (LSTM) network and deep neural network (DNN) techniques to infer the individual exercise behavior from the time series data. A reinforcement learning method is applied based on the asynchronous advantage actor-critic algorithm to find the optimal policy through exploration and exploitation

A single dose of DNA vaccine based on conserved H5N1 subtype proteins provides protection against lethal H5N1 challenge in mice pre-exposed to H1N1 influenza virus

<p>Abstract</p> <p>Background</p> <p>Highly pathogenic avian influenza virus subtype H5N1 infects humans with a high fatality rate and has pandemic potential. Vaccination is the preferred approach for prevention of H5N1 infection. Seasonal influenza virus infection has been reported to provide heterosubtypic immunity against influenza A virus infection to some extend. In this study, we used a mouse model pre-exposed to an H1N1 influenza virus and evaluated the protective ability provided by a single dose of DNA vaccines encoding conserved H5N1 proteins.</p> <p>Results</p> <p>SPF BALB/c mice were intranasally infected with A/PR8 (H1N1) virus beforehand. Six weeks later, the mice were immunized with plasmid DNA expressing H5N1 virus NP or M1, or with combination of the two plasmids. Both serum specific Ab titers and IFN-γ secretion by spleen cells in vitro were determined. Six weeks after the vaccination, the mice were challenged with a lethal dose of H5N1 influenza virus. The protective efficacy was judged by survival rate, body weight loss and residue virus titer in lungs after the challenge. The results showed that pre-exposure to H1N1 virus could offer mice partial protection against lethal H5N1 challenge and that single-dose injection with NP DNA or NP + M1 DNAs provided significantly improved protection against lethal H5N1 challenge in mice pre-exposed to H1N1 virus, as compared with those in unexposed mice.</p> <p>Conclusions</p> <p>Pre-existing immunity against seasonal influenza viruses is useful in offering protection against H5N1 infection. DNA vaccination may be a quick and effective strategy for persons innaive to influenza A virus during H5N1 pandemic.</p

Label-free integrative pharmacology on-target of opioid ligands at the opioid receptor family

BACKGROUND: In vitro pharmacology of ligands is typically assessed using a variety of molecular assays based on predetermined molecular events in living cells. Many ligands including opioid ligands pose the ability to bind more than one receptor, and can also provide distinct operational bias to activate a specific receptor. Generating an integrative overview of the binding and functional selectivity of ligands for a receptor family is a critical but difficult step in drug discovery and development. Here we applied a newly developed label-free integrative pharmacology on-target (iPOT) approach to systematically survey the selectivity of a library of fifty-five opioid ligands against the opioid receptor family. All ligands were interrogated using dynamic mass redistribution (DMR) assays in both recombinant and native cell lines that express specific opioid receptor(s). The cells were modified with a set of probe molecules to manifest the binding and functional selectivity of ligands. DMR profiles were collected and translated to numerical coordinates that was subject to similarity analysis. A specific set of opioid ligands were then selected for quantitative pharmacology determination. RESULTS: Results showed that among fifty-five opioid ligands examined most ligands displayed agonist activity in at least one opioid receptor expressing cell line under different conditions. Further, many ligands exhibited pathway biased agonism. CONCLUSION: We demonstrate that the iPOT effectively sorts the ligands into distinct clusters based on their binding and functional selectivity at the opioid receptor family

Oscillatory criteria for Third-Order difference equation with impulses

AbstractIn this paper, we investigate the oscillation of Third-order difference equation with impulses. Some sufficient conditions for the oscillatory behavior of the solutions of Third-order impulsive difference equations are obtained

A preliminary analysis of the formation of travertine and travertine cones in the Jifei hot spring, Yunnan, China

The Jifei hot spring emerges in the form of a spring group in the Tibet–Yunnan geothermal zone, southwest of Yunnan Province, China. The temperatures of spring waters range from 35 to 81°C and are mainly of HCO3–Na·Ca type. The total discharge of the hot spring is about 10 L/s. The spring is characterized by its huge travertine terrace with an area of about 4,000 m2 and as many as 18 travertine cones of different sizes. The tallest travertine cone is as high as 7.1 m. The travertine formation and evolution can be divided into three periods: travertine terrace deposition period, travertine cone formation period and death period. The hydrochemical characteristics of the Jifei hot spring was analyzed and compared with a local non-travertine hot spring and six other famous travertine springs. The results indicate that the necessary hydrochemical conditions of travertine and travertine cones deposition in the Jifei area are (1) high concentration of HCO3 − and CO2; (2) about 52.9% deep source CO2 with significantly high PCO2 value; (3) very high milliequivalent percentage of HCO3 − (97.4%) with not very high milliequivalent percentage of Ca2+ (24.4%); and (4) a large saturation index of calcite and aragonite of the hot water

Effects of different treatment frequencies of electromagnetic stimulation for urinary incontinence in women:study protocol for a randomized controlled trial

Background: Urinary incontinence is highly prevalent in women while pelvic floor muscle training is recommended as the first-line therapy. However, the exact treatment regimen is poorly understood. Also, patients with pelvic floor muscle damage may have decreased muscle proprioception and cannot contract their muscles properly. Other conservative treatments including electromagnetic stimulation are suggested by several guidelines. Thus, the present study aims to compare the effectiveness of electromagnetic stimulation combined with pelvic floor muscle training as a conjunct treatment for urinary incontinence and different treatment frequencies will be investigated.Methods/design: This is a randomized, controlled clinical trial. We will include 165 patients with urinary incontinence from the outpatient center. Participants who meet the inclusion criteria will be randomly allocated to three groups: the pelvic floor muscle training group (active control group), the low-frequency electromagnetic stimulation group (group 1), and the high-frequency electromagnetic stimulation group (group 2). Both group 1 and group 2 will receive ten sessions of electromagnetic stimulation. Group 1 will be treated twice per week for 5 weeks while group 2 will receive 10 days of continuous treatment. The primary outcome is the change in International Consultation on Incontinence Questionnaire–Short Form cores after the ten sessions of the treatment, while the secondary outcomes include a 3-day bladder diary, pelvic floor muscle function, pelvic organ prolapse quantification, and quality of life assessed by SF-12. All the measurements will be assessed at baseline, after the intervention, and after 3 months of follow-up.Discussion: The present trial is designed to investigate the effects of a conjunct physiotherapy program for urinary incontinence in women. We hypothesize that this strategy is more effective than pelvic floor muscle training alone, and high-frequency electromagnetic stimulation will be superior to the low-frequency magnetic stimulation group

Overexpression of serine racemase in retina and overproduction of D-serine in eyes of streptozotocin-induced diabetic retinopathy

<p>Abstract</p> <p>Background</p> <p>Recent data indicate that inflammatory mechanisms contribute to diabetic retinopathy (DR). We have determined that serine racemase (SR) expression is increased by inflammatory stimuli including liposaccharide (LPS), amyloid β-peptide (A-beta), and secreted amyloid precursor protein (sAPP); expression is decreased by the anti-inflammatory drug, dexamethasone. We tested possibility that SR and its product, D-serine, were altered in a rat model of DR.</p> <p>Methods</p> <p>Intraperitoneal injection of streptozotocin (STZ; 70 mg/kg body weight) to Sprague-Dawley rats produced type-I diabetic mellitus (fasting blood sugar higher than 300 mg/dL). At 3 and 5 months after STZ or saline injection, retinas from some rats were subjected to cryosectioning for immunofluorescent analysis of SR and TUNEL assay of apoptosis. Retinal homogenates were used to detect SR levels and Jun N-terminal kinase (JNK) activation by immunoblotting. Aqueous humor and retina were also collected to assay for neurotransmitters, including glutamate and D-serine, by reverse-phase HPLC.</p> <p>Results</p> <p>Compared to saline-injected rats, STZ-injected (diabetic) rats showed elevation of SR protein levels in retinal homogenates, attributed to the inner nuclear layer (INL) by immunofluorescence. Aqueous humor fluid from STZ-injected rats contained significantly higher levels of glutamate and D-serine compared to controls; by contrast, D-serine levels in retinas did not differ. Levels of activated JNK were elevated in diabetic retinas compared to controls.</p> <p>Conclusions</p> <p>Increased expression of SR in retina and higher levels of glutamate and D-serine in aqueous humor of STZ-treated rats may result from activation of the JNK pathway in diabetic sequelae. Our data suggest that the inflammatory conditions that prevail during DR result in elevation of D-serine, a neurotransmitter contributing to glutamate toxicity, potentially exacerbating the death of retinal ganglion cells in this condition.</p