Feature Extraction Techniques for Human Emotion Identification from Face Images

Emotion recognition has been one of the stimulating issues over the years due to the irregularities in the complexity of models and unpredictability between expression categories. So many Emotion detection algorithms have developed in the last two decades and still facing problems in accuracy, complexity and real-world implementation. In this paper, we propose two feature extraction techniques: Mouth region-based feature extraction and Maximally Stable Extremal Regions (MSER) method. In Mouth based feature extraction method mouth area is calculated and based on that value the emotions are classified. In the MSER method, the features are extracted by using connecting components and then the extracted features are given to a simple ANN for classification. Experimental results shows that the Mouth area based feature extraction method gives 86% accuracy and MSER based feature extraction method outperforms it by achieving 89% accuracy on DEAP. Thus, it can be concluded that the proposed methods can be effectively used for emotion detection

Resolving Octant Degeneracy at LBL experiment by combining Daya Bay Reactor Setup

Long baseline Experiment (LBL) have promised to be a very powerful experimental set up to study various issues related to Neutrinos. Some ongoing and planned LBL and medium baseline experiments are - T2K, MINOS, NOvA, LBNE, LBNO etc. But the long baseline experiments are crippled due to presence of some parameter degeneracies, like the Octant degeneracy. In this work, we first show the presence of Octant degeneracy in LBL experiments, and then combine it with Daya Bay Reactor experiment, at different values of CP violation phase. We show that the Octant degeneracy in LBNE can be resolved completely with this proposal.Comment: 4 pages, 8 figure

In vitro activities of novel 4-HPR derivatives on a panel of rhabdoid and other tumor cell lines

<p>Abstract</p> <p>Background</p> <p>Rhabdoid tumors (RTs) are aggressive pediatric malignancies with poor prognosis. N-(4-hydroxy phenyl) retinamide (4-HPR or fenretinide) is a potential chemotherapeutic for RTs with activity correlated to its ability to down-modulate Cyclin D1. Previously, we synthesized novel halogen-substituted and peptidomimetic-derivatives of 4-HPR that retained activity in MON RT cells. Here we analyzed the effect of 4-HPR in inhibiting the growth of several RT, glioma, and breast cancer cell lines and tested their effect on cell cycle, apoptosis and Cyclin D1 expression.</p> <p>Methods</p> <p>Effect of compounds on RT cell cycle profiles, and cell death were assessed by MTS cell survival assays and FACS analysis. The effects of treatment on Cyclin D1 expression were determined by immunoblotting. The efficacy of these compounds on glioma and breast cancer cell lines was also determined using MTS assays.</p> <p>Results</p> <p>Low micromolar concentrations of 4-HPR derivatives inhibited cell survival of all RT cells tested. The 4-HPR derivatives altered RT cell cycle profiles and induced high levels of cell death that was correlated with their potency. ATRA exhibited high IC₅₀values in all cell lines tested and did not cause cell death. In MON RT cells, the iodo-substituted compounds were more active than 4-HPR in inducing cell cycle arrest and apoptosis. Additionally, the activity of the compounds correlated with their ability to down-modulate Cyclin D1: while active compounds reduced Cyclin D1 levels, inactive ATRA did not. In glioma and breast cancer cell lines, 4-HPR and 4-HPR derivatives showed variable efficacy.</p> <p>Conclusions</p> <p>Here we demonstrate, for the first time, that the inhibitory activities of novel halogen-substituted and peptidomimetic derivatives of 4-HPR are correlated to their ability to induce cell death and down-modulate Cyclin D1. These 4-HPR derivatives showed varied potencies in breast cancer and glioma cell lines. These data indicate that further studies are warranted on these derivatives of 4-HPR due to their low IC₅₀s in RT cells. These derivatives are of general interest, as conjugation of halogen radioisotopes such as ¹⁸F, ¹²⁴I, or ¹³¹I to 4-HPR will allow us to combine chemotherapy and radiotherapy with a single drug, and to perform PET/SPECT imaging studies in the future.</p

Evolving toward a human-cell based and multiscale approach to drug discovery for CNS disorders

A disruptive approach to therapeutic discovery and development is required in order to significantly improve the success rate of drug discovery for central nervous system (CNS) disorders. In this review, we first assess the key factors contributing to the frequent clinical failures for novel drugs. Second, we discuss cancer translational research paradigms that addressed key issues in drug discovery and development and have resulted in delivering drugs with significantly improved outcomes for patients. Finally, we discuss two emerging technologies that could improve the success rate of CNS therapies: human induced pluripotent stem cell (hiPSC)-based studies and multiscale biology models. Coincident with advances in cellular technologies that enable the generation of hiPSCs directly from patient blood or skin cells, together with methods to differentiate these hiPSC lines into specific neural cell types relevant to neurological disease, it is also now possible to combine data from large-scale forward genetics and post-mortem global epigenetic and expression studies in order to generate novel predictive models. The application of systems biology approaches to account for the multiscale nature of different data types, from genetic to molecular and cellular to clinical, can lead to new insights into human diseases that are emergent properties of biological networks, not the result of changes to single genes. Such studies have demonstrated the heterogeneity in etiological pathways and the need for studies on model systems that are patient-derived and thereby recapitulate neurological disease pathways with higher fidelity. In the context of two common and presumably representative neurological diseases, the neurodegenerative disease Alzheimer’s Disease (AD), and the psychiatric disorder schizophrenia (SZ), we propose the need for, and exemplify the impact of, a multiscale biology approach that can integrate panomic, clinical, imaging, and literature data in order to c

Electrochemical analysis of nitrite contamination in water using SnTe@GO modified glassy carbon electrode

1313-1320An electrochemically active tin telluride (SnTe) decorated graphene oxide (GO) (SnTe@GO) nanocomposite has been synthesized through simple experimental method and used the same for surface modification of glassy carbon electrode, thus developed a new efficient SnTe@GO/GCE which in turn has been demonstrated as a sensor for identification and quantification of nitrite species in water samples. Common analytical techniques are employed and established the physiochemical properties of SnTe@GO nanocomposite. The electrocatalytic activity of SnTe@GO/GCE has been examined towards sensing and quantification of nitrite through Cyclic Voltammetry and Differential Pulse Voltammetry techniques. The obtained results revel that SnTe@GO/GCE exhibited high sensitivity with wide linear range such as 9.8-162 mM and detection limit found to be 0.079 µM. In addition, in order to inspect the real time application of SnTe@GO/GCE, it is also employed and determined the concentration of nitrite in drinking water, pond water and well water samples which are collected from Rayapuram, Muttukadu and Guindy during the specific period. The LOD observed for drinking water collected from Rayapuram, Chennai are 1.63 μM, pond water collected from Muttukadu, Kanchipuram 2.5 μM, and the well water collected from Guindy, Chennai are 1.25 μM, and thus proves that the newly designed SnTe@GO/GCE is an excellent sensor for nitrite species even in real water sample analysis

Electrochemical analysis of nitrite contamination in water using SnTe@GO modified glassy carbon electrode

An electrochemically active tin telluride (SnTe) decorated graphene oxide (GO) (SnTe@GO) nanocomposite has been synthesized through simple experimental method and used the same for surface modification of glassy carbon electrode, thus developed a new efficient SnTe@GO/GCE which in turn has been demonstrated as a sensor for identification and quantification of nitrite species in water samples. Common analytical techniques are employed and established the physiochemical properties of SnTe@GO nanocomposite. The electrocatalytic activity of SnTe@GO/GCE has been examined towards sensing and quantification of nitrite through Cyclic Voltammetry and Differential Pulse Voltammetry techniques. The obtained results revel that SnTe@GO/GCE exhibited high sensitivity with wide linear range such as 9.8-162 mM and detection limit found to be 0.079 µM. In addition, in order to inspect the real time application of SnTe@GO/GCE, it is also employed and determined the concentration of nitrite in drinking water, pond water and well water samples which are collected from Rayapuram, Muttukadu and Guindy during the specific period. The LOD observed for drinking water collected from Rayapuram, Chennai are 1.63 μM, pond water collected from Muttukadu, Kanchipuram 2.5 μM, and the well water collected from Guindy, Chennai are 1.25 μM, and thus proves that the newly designed SnTe@GO/GCE is an excellent sensor for nitrite species even in real water sample analysis

Design Process and Utilization of a Novel Clinical Decision Support System for Neuropathic Pain in Primary Care: Mixed Methods Observational Study

Background: Computerized clinical decision support systems (CDSSs) have emerged as an approach to improve compliance of clinicians with clinical practice guidelines (CPGs). Research utilizing CDSS has primarily been conducted in clinical contexts with clear diagnostic criteria such as diabetes and cardiovascular diseases. In contrast, research on CDSS for pain management and more specifically neuropathic pain has been limited. A CDSS for neuropathic pain has the potential to enhance patient care as the challenge of diagnosing and treating neuropathic pain often leads to tension in clinician-patient relationships. Objective: The aim of this study was to design and evaluate a CDSS aimed at improving the adherence of interprofessional primary care clinicians to CPG for managing neuropathic pain. Methods: Recommendations from the Canadian CPGs informed the decision pathways. The development of the CDSS format and function involved participation of multiple stakeholders and end users in needs assessment and usability testing. Clinicians, including family medicine physicians, residents, and nurse practitioners, in three academic teaching clinics were trained in the use of the CDSS. Evaluation over one year included the measurement of utilization of the CDSS; change in reported awareness, agreement, and adoption of CPG recommendations; and change in the observed adherence to CPG recommendations. Results: The usability testing of the CDSS was highly successful in the prototype environment. Deployment in the clinical setting was partially complete by the time of the study, with some limitations in the planned functionality. The study population had a high level of awareness, agreement, and adoption of guideline recommendations before implementation of CDSS. Nevertheless, there was a small and statistically significant improvement in the mean awareness and adoption scores over the year of observation (P=.01 for mean awareness scores at 6 and 12 months compared with baseline, for mean adoption scores at 6 months compared with baseline, and for mean adoption scores at 12 months). Documenting significant findings related to diagnosis of neuropathic pain increased significantly. Clinicians accessed CPG information more frequently than they utilized data entry functions. Nurse practitioners and first year family medicine trainees had higher utilization than physicians. Conclusions: We observed a small increase in the adherence to CPG recommendations for managing neuropathic pain. Clinicians utilized the CDSS more as a source of knowledge and as a training tool than as an ongoing dynamic decision support

Multidrug-Resistant Organism Infections in US Nursing Homes: A National Study of Prevalence, Onset, and Transmission across Care Settings, October 1, 2010-December 31, 2011

Objective.To understand the prevalence of multidrug-resistant organism (MDRO) infections among nursing home (NH) residents and the potential for their spread between NHs and acute care hospitals (ACHs).Methods.Descriptive analyses of MDRO infections among NH residents using all NH residents in the Long-Term Care Minimum Data Set (MDS) 3.0 between October 1, 2010 and December 31, 2011.Results.Analysis of MDS data revealed a very high volume of bidirectional patient flow between NHs and ACHs, indicating the need to study MDRO infections in NHs as well as in hospitals. A total of 4.24% of NH residents had an active MDRO diagnosis on at least 1 MDS assessment during the study period. This rate significantly varied by sex, age, urban/rural status, and state. Approximately 2% of NH discharges to ACHs involved a resident with an active diagnosis of infection due to MDROs. Conversely, 1.8% of NH admissions from an ACH involved a patient with an active diagnosis of infection due to MDROs. Among residents who acquired an MDRO infection during the study period, 57% became positive in the NH, 41% in the ACH, and 2% in other settings (eg, at a private home or apartment).Conclusion.Even though NHs are the most likely setting where residents would acquire MDROs after admission to an NH (accounting for 57% of cases), a significant fraction of NH residents acquire MDRO infection at ACHs (41%). Thus, effective MDRO infection control for NH residents requires simultaneous, cooperative interventions among NHs and ACHs in the same community.</jats:sec