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The immense demand of plastics worldwide has created a substantial pollution problem that appears not to have an end. New governmental policies and customers preferences towards environmental friendly materials require continued research on biodegradable materials derived from biological resource. In this work, residual palm oil (RPO) recovered from palm oil mill waste effluent was mixed with algae oil (AO) to produce rigid foam polyurethanes (bio-RFPU) at different ratios (AO/RPO) 10/90, 20/80, 30/70, 40/60 and 50/50 by one pot epoxidation and ring opening followed by polymerization with Methylene diphenyl diisocyanate(MDI). Prior to polymerization, significant improvement of 49% was found in the hydroxyl number of the RPO(AO) polyol when AO content was increased from 10 to 50%. Similarly, the homogeneous structure of the cell and the thermal stability of the final bio-RFPU was increased in the samples with 50% AO. Different characterization techniques such as scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), dynamic mechanical analysis (DMA) and compression/flexural tests were conducted, and the results presented. The thermal degradation profile of the samples containing 40 and 50% of AO was found to be similar to RFPU with fire retardant and insulation properties. The compressive strength and the biodegradability of the bio-RFPU increased 60% when AO was increased between samples with 10 and 50% AO. Therefore, the developed bio-RFPUs is expected to have great potential as core materials in industrial applications such as sandwich panels as well as in other insulation material.

A new green binder of Jatropha-oil based epoxy acrylate (AEJO) resin was able to replace coatings in non-ecology-friendly technologies. The epoxy acrylate coating was blended with nano zinc oxide to make hybrid nanocomposites as a corrosion protection coating applied to a mild steel panel. AEJO was synthesized and incorporated with different loadings (1, 3, 5, 7, and 9 wt %) of zinc oxide (ZnO) fillers. The AEJO/ZnO coating was applied on the mild steel substrates and characterized for corrosion protection performance by impedance spectroscopy (EIS) and salt spray tests. XRD analysis was conducted, and thermal properties by TGA were studied. The surface morphology of the hybrid coating was characterized by field emission scanning electron microscopy (FE-SEM). Incorporation of a 5 wt % ZnO loading showed significantly enhanced corrosion resistance through EIS as well as coating performance. This study provides green-based materials and protection to surface and interface engineering.

Continuously monitoring schizophrenia patients' psychiatric symptoms is crucial for in-time intervention and treatment adjustment. The Brief Psychiatric Rating Scale (BPRS) is a survey administered by clinicians to evaluate symptom severity in schizophrenia. The CrossCheck symptom prediction system is capable of tracking schizophrenia symptoms as measured by BPRS using passive sensing from mobile phones. We present results from a randomized control trial, where passive sensing data, self-reports, and clinician administered 7-item BPRS surveys are collected from 36 outpatients with schizophrenia. We show that our system can predict a symptom scale score based on a 7-item BPRS within +1.45 error on average. Finally, we discuss how well our predictive system reflects symptoms experienced by patients by reviewing a case study.

•Smartphone Sensing Methods (SSMs) permit continuous and real-time behavioral observation in the context of people's daily lives.•SSMs provide objective assessment of people's everyday behaviors, such as physical movement, social interactions, and other daily activities.•Research is needed to examine psychometric properties of SSM-based behavioral measures and ethical implications of sensor-based behavioral observation.

This paper describes a multicentre longitudinal cohort study to evaluate the predictive accuracy of a regularised Bayesian neural network model in a prognostic application. The study sample (n = 5442) comprises subjects treated with intraocular melanoma in two different centres in Liverpool and Paris. External validation was carried out by fitting the model to the data from Liverpool set and predicting for the data from Paris. The performance of the model in out-of-sample prediction was assessed statistically for discrimination of outcomes and calibration. It was also evaluated clinically by comparing against the accepted TNM staging system. The model had good discrimination with Harrell's C index > 0.7 up to ten years of follow-up. Calibration results were also good up to ten years using a Hosmer-Lemeshow type analysis (p > 0.05). The paper: 1) deals with the issue of missing data using methods that are well accepted in the literature; 2) proposes a framework for externally validating machine learning models applied to survival analysis; 3) applies accepted methods for dealing with missing data; 4) proposes an alternative staging system based on the model. The new staging system, which takes into account histopathologic information, has several advantages over the existing staging system.

Abstract. Gold mineralization at Kyaukpahto occurs as a stockworks/dissemination style with localized breccia zones in silicified sandstones of the Male Formation (Eocene). The mineralization appears to be closely associated with NNE‐SSW trending extensional faults probably related directly to the dextral movement of the Sagaing Fault system. Intense silicifica‐tion associated with sericitization, argillic alteration and decalcification is recognized in the Kyaukpahto gold deposit. The important ore minerals associated with the gold mineralization are pyrite, arsenopyrite and chalcopyrite with minor amounts of other sulfides. Gold occurs as free particles or locked with pyrite, arsenopyrite, chalcopyrite and tetrahedrite. Silver, copper, arsenic and antimony particularly appear to be good pathfinders and the best geochemical indicators of gold mineralization at Kyaukpahto. Electron microprobe analysis indicates that the fineness for the native gold ranges from 844 to 866. Present geological, mineralogical and geochemical investigations demonstrate that the Kyaukpahto gold deposit has been formed as a result of hydrothermal processes in a shallow level epithermal environment.