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The blue light hazard (BLH) and luminous efficacy of a source ( η V ) are associated with the photobiological safety and energy saving of light-emitting diodes (LEDs), respectively. In this study, we used genetic algorithm (GA) to optimize the BLH, η V , and color rendering parameters of five-chip hybrid white LEDs. Based on the optimal results, we used five-chip LEDs to obtain the hybrid white light. Their peak wavelengths were 461.5 (blue), 523.9 (green), 588.2 (orange), 643.3 (red), and 694.2 nm (far-red), respectively. In practice, the blue light hazard efficiency of radiation (BLHER) of the hybrid white light was less than 0.10, which was lower than half of the most common light sources. The η V ranged from 51.6 to 115.6 lm/W at correlated color temperature (CCT) from 2700 to 6500 K. On average, the CIE general color rendering index (Ra), CIE special color rendering index for the ninth deep red test sample (R9), ANSI/IES TM-30 color fidelity index (Rf), and color gamut index (Rg) of hybrid white light were 91.3, 87.8, 83.3, and 96.7, respectively. The melanopic efficacy of luminous radiation ( K m e l , V ) was tunable in the range of 0.60 to 1.35 mW/lm. These results demonstrated that we used far-red LEDs to fabricate white light with low BLH and relatively high efficiency. [ABSTRACT FROM AUTHOR]

Background: Schizophrenia is a kind of serious mental illness. Due to the lack of an objective physiological data supporting and a unified data analysis method, doctors can only rely on the subjective experience of the data to distinguish normal people and patients, which easily lead to misdiagnosis. In recent years, functional Near-Infrared Spectroscopy (fNIRS) has been widely used in clinical diagnosis, it can get the hemoglobin concentration through the variation of optical intensity.Methods: Firstly, the prefrontal brain networks were constructed based on oxy-Hb signals from 52-channel fNIRS data of schizophrenia and healthy controls. Then, Complex Brain Network Analysis (CBNA) was used to extract features from the prefrontal brain networks. Finally, a classier based on Support Vector Machine (SVM) is designed and trained to discriminate schizophrenia from healthy controls. We recruited a sample which contains 34 healthy controls and 42 schizophrenia patients to do the one-back memory task. The hemoglobin response was measured in the prefrontal cortex during the task using a 52-channel fNIRS system.Results: The experimental results indicate that the proposed method can achieve a satisfactory classification with the accuracy of 85.5%, 92.8% for schizophrenia samples and 76.5% for healthy controls. Also, our results suggested that fNIRS has the potential capacity to be an effective objective biomarker for the diagnosis of schizophrenia.Conclusions: Our results suggested that, using the appropriate classification method, fNIRS has the potential capacity to be an effective objective biomarker for the diagnosis of schizophrenia. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the influence of a Smart-Phone Application (APP) Follow-up System (SPAFS) on medication compliance in patients treated for depression. Methods: Subjects aged 16-65 years old with depressive disorder, who regularly took antidepressant medications for at least one month were recruited from the Peking University Sixth Hospital and Beijing Hui Long Guan Hospital from July 1st, 2014, to April 30th, 2015. Two groups of patients were evaluated: SPAFS group (were willing to be online anytime, who received APP) and control group (agreed to adhere to traditional psychological clinical follow-up procedures). Results: One hundred and twenty-one patients were investigated, 57 in the SPAFS group (intervention group) and 64 in the control group. At the end of the 6-month follow-up, 17 patients in the control group and 4 patients in the intervention group discontinued their medication; there was a statistically significant difference (P<0.05). In the selfassessment of medication compliance, the scores in the intervention group (8.44±1.31) were significantly higher than those in the control group (6.95±2.73). The medication discontinuation rate in the intervention group was lower than that in the control group(P<0.05). The SDS scores in the intervention group were lower than those in the control group (P<0.05). The self-reported medication compliance scores in the intervention group were higher than those in the control group (P<0.05). The most common reasons for medication discontinuation in the control group were forgetting to take the medication, concerns about brain damage from long-term medication use, and the personal decision to discontinue medications when the medical condition appeared to improve. Conclusion: This study showed that the SPAFS improved medication compliance during the followup period in patients treated for depression. [ABSTRACT FROM AUTHOR]