Application of artificial neural networks and multivariate statistics to estimate UCS using textural characteristics

Before any rock engineering project, mechanical parameters of rocks such as uniaxial compressive strength and young modulus of intact rock get measured using laboratory or in-situ tests, but in some situations preparing the required specimens is impossible. By this time, several models have been established to evaluate UCS and E from rock substantial properties. Artificial neural networks are powerful tools which are employed to establish predictive models and results have shown the priority of this technique compared to classic statistical techniques. In this paper, ANN and multivariate statistical models considering rock textural characteristics have been established to estimate UCS of rock and to validate the responses of the established models, they were compared with laboratory results. For this purpose a data set for 44 samples of sandstone was prepared and for each sample some textural characteristics such as void, mineral content and grain size as well as UCS were determined. To select the best predictors as inputs of the UCS models, this data set was subjected to statistical analyses comprising basic descriptive statistics, bivariate correlation, curve fitting and principal component analyses. Results of such analyses have shown that void, ferroan calcitic cement, argillaceous cement and mica percentage have the most effect on USC. Two predictive models for UCS were developed using these variables by ANN and linear multivariate regression. Results have shown that by using simple textural characteristics such as mineral content, cement type and void, strength of studied sandstone can be estimated with acceptable accuracy. ANN and multivariate statistical UCS models, revealed responses with 0.87 and 0.76 regressions, respectively which proves higher potential of ANN model for predicting UCS compared to classic statistical models. Keywords: Textural characteristics, Uniaxial compressive strength, Predictive models, Artificial neural networks, Multivariate statistic

Brain Gains: a literature review of short-term medical missions to low and middle-income countries.

BackgroundHealthcare professionals’ participation in short-term medical missions to low and middle income countries (LMIC) to provide healthcare has become common over the past 50 years yet little is known about the quantity and quality of these missions. The aim of this study was to review medical mission publications over 25 years to better understand missions and their potential impact on health systems in LMICs.MethodsA literature review was conducted by searching Medline for articles published from 1985–2009 about medical missions to LMICs, revealing 2512 publications. Exclusion criteria such as receiving country and mission length were applied, leaving 230 relevant articles. A data extraction sheet was used to collect information, including sending/receiving countries and funding source.ResultsThe majority of articles were descriptive and lacked contextual or theoretical analysis. Most missions were short-term (1 day – 1 month). The most common sending countries were the U.S. and Canada. The top destination country was Honduras, while regionally Africa received the highest number of missions. Health care professionals typically responded to presenting health needs, ranging from primary care to surgical relief. Cleft lip/palate surgeries were the next most common type of care provided.ConclusionsBased on the articles reviewed, there is significant scope for improvement in mission planning, monitoring and evaluation as well as global and/or national policies regarding foreign medical missions. To promote optimum performance by mission staff, training in such areas as cross-cultural communication and contextual realities of mission sites should be provided. With the large number of missions conducted worldwide, efforts to ensure efficacy, harmonisation with existing government programming and transparency are needed

A bonded particle model for analysis of the flaw orientation effect on crack propagation mechanism in brittle materials under compression

In this paper, implementation of a bonded particle model (BPM) using PFC2D was proposed to study the effect of the flaw orientation on the crack propagation mechanism in brittle materials such as rocks under various compressive loads. For this purpose, several pre-cracked rock specimens with different orientation of flaw under uniaxial and biaxial loads were modeled in PFC2D (bonded particle model) and crack propagation processes were monitored. According to the results, by varying the flaw inclination angle (β), two types of the secondary crack propagation mechanism were detected. Also, it was concluded that the confinement stress affected the crack initiation and propagation mechanism and the increase of it made the crack initiation angle steeper

Early-life stress elicits peripheral and brain immune activation differently in wild type and 5xFAD mice in a sex-specific manner

BackgroundThe risk of developing Alzheimer’s disease (AD) is modulated by genetic and environmental factors. Early-life stress (ELS) exposure during critical periods of brain development can impact later brain function and health, including increasing the risk of developing AD. Microglial dysfunction and neuroinflammation have been implicated as playing a role in AD pathology and may be modulated by ELS. To complicate matters further, sex-specific effects have been noted in response to ELS and in the incidence and progression of AD.MethodsHere, we subjected male and female mice with either a wild type or 5xFAD familial AD-model background to maternal separation (MS) from postnatal day 2 to 14 to induce ELS.ResultsWe detected hippocampal neuroinflammatory alterations already at postnatal day 15. By 4 months of age, MS mice presented increased immobility time in the forced swim test and a lower discrimination index in the novel object recognition memory test compared to controls. We found altered Bdnf and Arc expression in the hippocampus and increased microglial activation in the prefrontal cortex due to MS in a sex-dependent manner. In 5xFAD mice specifically, MS exacerbated amyloid-beta deposition, particularly in females. In the periphery, the immune cell population was altered by MS exposure.ConclusionOverall, our results demonstrate that MS has both short- and long-term effects on brain regions related to memory and on the inflammatory system, both in the brain and periphery. These ELS-related effects that are detectable even in adulthood may exacerbate pathology and increase the risk of developing AD via sex-specific mechanisms