Baggeogden6102

Advancements in sensing and network technologies have increased the amount of data being collected to monitor the worker conditions. In this study, we consider the use of time series methods to forecast physical fatigue using subjective ratings of perceived exertion (RPE) and gait data from wearable sensors captured during a simulated in-lab manual material handling task (Lab Study 1) and a fatiguing squatting with intermittent walking cycle (Lab Study 2). To determine whether time series models can accurately forecast individual response and for how many time periods ahead, five models were compared naïve method, autoregression (AR), autoregressive integrated moving average (ARIMA), vector autoregression (VAR), and the vector error correction model (VECM). For forecasts of three or more time periods ahead, the VECM model that incorporates historical RPE and wearable sensor data outperformed the other models with median mean absolute error (MAE) less then 1.24 and median MAE less then 1.22 across all participants for Lab Study 1 and Lab Study 2, respectively. These results suggest that wearable sensor data can support forecasting a worker's condition and the forecasts obtained are as good as current state-of-the-art models using multiple sensors for current time prediction.We report an organization's method for recruiting additional, specialized human resources during anomaly handling. The method has been tailored to encourage sharing adaptive capacity across organizational units. As predicted by Woods' theory, this case shows that sharing adaptive capacity allows graceful extensibility that is particularly useful when a system is challenged by frequent but unpredictably severe events. We propose that (1) the ability to borrow adaptive capacity from other units is a hallmark of resilient systems and (2) the deliberate adjustment adaptive capacity sharing is a feature of some forms of resilience engineering. Some features of this domain that may lead to discovery of resilience and promote resilience engineering in other settings, notably hospital emergency rooms.Decision-making during critical outbreak management may require standard strategies, but also more creative ones. Selleck compound W13 Our goal was to characterize the expert decision processes that take place during critical situations, where rule-based strategies and usual procedures cannot be satisfactorily applied. More specifically, we focused on the strategies experts use to deal with epidemiological problems, depending on the complexity of the situation. To this end, we carried out a simulated outbreak alert, to place two experts in a situation of epidemiological problem management, based on usual practice but also conducive to implementing creative solutions. To analyze the data, we considered not only the relevance of the solutions proposed by the experts, but also the four creativity criteria defined by Torrance (fluency, flexibility, elaboration and originality). Results allowed us to identify similarities but also differences between the solutions proposed by the experts, depending on their level of experience in this area.Recent studies have demonstrated that the outline shapes of deciduous upper and lower second molars and the deciduous upper first molar are useful for diagnosing hominin taxa-especially Homo neanderthalensis and Homo sapiens. Building on these studies, we use geometric morphometric methods to assess the taxonomic significance of the crown outline of the lower first deciduous molar (dm1). We test whether the crown shape of the dm1 distinguishes H. neanderthalensis from H. sapiens and explore whether dm1 crown shape can be used to accurately assign individuals to taxa. Our fossil sample includes 3 early H. sapiens, 7 Upper Paleolithic H. sapiens, and 13 H. neanderthalensis individuals. Our recent human sample includes 103 individuals from Africa, Australia, Europe, South America, and South Asia. Our results indicate that H. neanderthalensis dm1s cluster fairly tightly and separate well from those of Upper Paleolithic H. sapiens. However, we also found that the range of shapes in the recent human sample completely overlaps the ranges of all fossil samples. Consequently, results of the quadratic discriminant analysis based on the first 8 principal components (PCs) representing more than 90% of the variation were mixed. Lower dm1s were correctly classified in 87.3% of the individuals; the combined H. sapiens sample had greater success (90.2%) in assigning individuals than did the H. neanderthalensis sample (61.5%). When the analysis was run removing the highly variable recent human sample, accuracy increased to 84.6% for H. neanderthalensis, and 57.1% of Upper Paleolithic H. sapiens were classified correctly by using the first 4 PCs (70.3%). We conclude that caution is warranted when assigning isolated dm1 crowns to taxa; while an assignment to H. neanderthalensis has a high probability of being correct, assignment to Upper Paleolithic H. sapiens is less certain.

Pentraxin-3 (PTX-3) is involved in acute immunological responses and it is a pro-inflammatory protein and a novel biomarker of inflammatory diseases. It is demonstrated that PTX-3 is higher in cerebrospinal fluid (CSF) of aggressive Multiple Sclerosis (MS). Metabolomics, the identification of small endogenous molecules, offers a molecular profile of MS. Glatiramer acetate (GA) is a widely used treatment for (MS) but its mechanism of action is not completely defined. The aim of our study is to analyze PTX-3 and metabolomic profile in MS patients compared to controls and to investigate the effect of GA on PXT-3 and metabolic molecules during treatment in responder and not responder MS patients.

28 unrelated MS patients and 27 age-and sex-matched controls were recruited. In serum, PTX-3 levels were measured by ELISA and Metabolomic panel was evaluated trough Nuclear Magnetic Resonance (NMR). According to clinical practice patients started GA treatment; PTX-3 and metabolomic identification were performed befohe identification of responder patients to GA.Galectin-3 (Gal3) is expressed by microglia and performs functions including adhesion; activation of macrophages and fibroblasts, and mediates inflammatory responses in the hippocampus. The present study examined whether serum Gal3 levels predict hippocampal volume in a multi-ethnic, community-based sample. Results of a multiple linear regression (controlling for depression, serum creatinine level, age, BMI, total brain volume, MoCA score, sex, ethnicity, smoking status, history of diabetes) showed that Gal3 levels significantly predicted left (p = .027) but not right hippocampal volume. The relationship was stronger in men than women. Findings suggest this novel inflammatory biomarker is associated with human hippocampal volume.