•High δ18O olivine in Karoo picrites indicate recycled source component.•Olivine are Ni-rich and Ca- and Mn-poor indicating a pyroxenite dominated source.•Mn and Zn in olivine are shown to be ...powerful discriminators of source mineralogy.•Source is a hybrid metasomatized pyroxenite with a recycled crust component.•Asthenospheric vs lithospheric location for this source is discussed.
Continental Flood Basalts (CFB) result from voluminous outpourings of magma that often precede continental break-up. Notwithstanding the petrogenetic importance of CFBs, the nature of the mantle source for such magmas is contentious, particularly with regard to picrites with Ni-rich olivine phenocrysts. Previous studies have suggested that Ni-rich olivines associated with plume volcanism in regions of thickened (>90 km) lithosphere are related to either source mineralogy differences (peridotite versus pyroxenite) or change in olivine-melt partitioning due to pressure increase. In order to evaluate these two hypotheses, we present trace element data for olivines from the Karoo CFB Tuli and Mwenezi picrites and the Etendeka CFB Horingbaai/LTZ-L type picrites, all of which erupted in regions of thickened (>90 km) lithosphere in southern Africa. Karoo picrite olivines are Ni-rich, Ca- and Mn-poor, and have low (<1.4) 100*Mn/Fe. These compositions are consistent with a pyroxenitic source. Etendeka Horingbaai/LTZ-L picrite olivines do not show Ni-enrichment, but are characterized by high Al and Cr, and high (>1.4) 100*Mn/Fe, which is more consistent with high temperature melting of a dominantly peridotitic source. We also show that the Karoo and Etendeka olivines are characterized by distinct Mn/Zn ratios of <13 and >15, respectively.
In addition, bulk rock geochemical data compilations and previously reported olivine δ18O for Karoo and Etendeka CFBs are discussed in order to further constrain source components based on previously described pyroxenite melt geochemical indices such as MgO–CaO systematics, FeO/MnO, Zn/Fe, and FC3MS (FeO/CaO–3*MgO/SiO2). These geochemical indices suggest a pyroxenite-dominated source for Karoo CFBs as well as for Etendeka ferropicrites whereas a peridotite-dominated source is indicated for Etendeka Horingbaai/LTZ-L type picrites analyzed in this study. Based on our data, Ni-enrichment of olivine in plume-related magmas in regions of thickened lithosphere in southern Africa is not ubiquitous. We therefore suggest that mineralogical variation of the source is a more likely major control of olivine chemistry and parent melt variations for Karoo and Etendeka CFBs. We also show that olivine Mn–Zn correlations are a useful discriminator for source variation and recommend the use of olivine Mn/Zn<13 for a pyroxenite-dominated source relative to olivine Mn/Zn>15 for a peridotite-dominated source.
Recent attempts to improve on the quality of psychological research focus on good practices required for statistical significance testing. The scrutiny of theoretical reasoning, though superordinate, ...is largely neglected, as exemplified here in a common misunderstanding of mediation analysis. Although a test of a mediation model X➔Z➔Y is conditional on the premise that the model applies, alternative mediators Z′, Z″, Z‴ etc. remain untested, and other causal models could underlie the correlation between X, Y, Z, researchers infer from a single significant mediation test that they have identified the true mediator. A literature search of all mediation analyses published in 2015 in Sciencedirect shows that the vast majority of studies neither consider alternative causal models nor alternative mediator candidates. Ignoring that mediation analysis is conditional on the truth of the focal mediation model, they pretend to have demonstrated that Z mediates the influence of X on Y. Recommendations are provided for how to overcome this dissatisfying state of affairs.
Many industrial processes contain both linear and nonlinear parts, and kernel principal component analysis (KPCA), widely used in nonlinear process monitoring, may not offer the most effective means ...for dealing with these nonlinear processes. This paper proposes a new hybrid linear-nonlinear statistical modeling approach for nonlinear process monitoring by closely integrating linear principal component analysis (PCA) and nonlinear KPCA using a serial model structure, which we refer to as serial PCA (SPCA). Specifically, PCA is first applied to extract PCs as linear features, and to decompose the data into the PC subspace and residual subspace (RS). Then, KPCA is performed in the RS to extract the nonlinear PCs as nonlinear features. Two monitoring statistics are constructed for fault detection, based on both the linear and nonlinear features extracted by the proposed SPCA. To effectively perform fault identification after a fault is detected, an SPCA similarity factor method is built for fault recognition, which fuses both the linear and nonlinear features. Unlike PCA and KPCA, the proposed method takes into account both linear and nonlinear PCs simultaneously, and therefore, it can better exploit the underlying process's structure to enhance fault diagnosis performance. Two case studies involving a simulated nonlinear process and the benchmark Tennessee Eastman process demonstrate that the proposed SPCA approach is more effective than the existing state-of-the-art approach based on KPCA alone, in terms of nonlinear process fault detection and identification.
In cancer cells, the aberrant conversion of pyruvate into lactate instead of acetyl-CoA in the presence of oxygen is known as the Warburg effect. The consequences and mechanisms of this metabolic ...peculiarity are incompletely understood. Here we report that p53 status is a key determinant of the Warburg effect. Wild-type p53 expression decreased levels of pyruvate dehydrogenase kinase-2 (Pdk2) and the product of its activity, the inactive form of the pyruvate dehydrogenase complex (P-Pdc), both of which are key regulators of pyruvate metabolism. Decreased levels of Pdk2 and P-Pdc in turn promoted conversion of pyruvate into acetyl-CoA instead of lactate. Thus, wild-type p53 limited lactate production in cancer cells unless Pdk2 could be elevated. Together, our results established that wild-type p53 prevents manifestation of the Warburg effect by controlling Pdk2. These findings elucidate a new mechanism by which p53 suppresses tumorigenesis acting at the level of cancer cell metabolism.
In order to deeply exploit intrinsic data feature information hidden among the process data, an improved kernel principal component analysis (KPCA) method is proposed, which is referred to as deep ...principal component analysis (DePCA). Specifically, motivated by the deep learning strategy, we design a hierarchical statistical model structure to extract multilayer data features, including both the linear and nonlinear principal components. To reduce the computation complexity in nonlinear feature extraction, the feature-samples' selection technique is applied to build the sparse kernel model for DePCA. To integrate the monitoring statistics at each feature layer, Bayesian inference is used to transform the monitoring statistics into fault probabilities, and then, two probability-based DePCA monitoring statistics are constructed by weighting the fault probabilities at all the feature layers. Two case studies involving a simulated nonlinear system and the benchmark Tennessee Eastman process demonstrate the superior fault detection performance of the proposed DePCA method over the traditional KPCA-based methods.
We evaluated the expression of biomarkers of innate and adaptive immune response in correlation with underlying conditions in 144 patients with chronic pulmonary aspergillosis (CPA). Patients with ...complete medical and radiological records, white cell counts, and a complete panel of CD3, CD4, CD8, CD19, and CD56 lymphocyte subsets were included. Eighty-four (58%) patients had lymphopenia. Six (4%) patients had lymphopenia in all five CD variables. There were 62 (43%) patients with low CD56 and 62 (43%) patients with low CD19. Ten (7%) patients had isolated CD19 lymphopenia, 18 (13%) had isolated CD56 lymphopenia, and 15 (10%) had combined CD19 and CD56 lymphopenia only. Forty-eight (33%) patients had low CD3 and 46 (32%) had low CD8 counts. Twenty-five (17%) patients had low CD4, 15 (10%) of whom had absolute CD4 counts <200/μL. Multivariable logistic regression showed associations between: low CD19 and pulmonary sarcoidosis (Odds Ratio (OR), 5.53; 95% Confidence Interval (CI), 1.43-21.33;
= 0.013), and emphysema (OR, 4.58; 95% CI; 1.36-15.38;
= 0.014), low CD56 and no bronchiectasis (OR, 0.27; 95% CI, 0.10-0.77;
= 0.014), low CD3 and both multicavitary CPA disease (OR, 2.95; 95% CI, 1.30-6.72;
= 0.010) and pulmonary sarcoidosis (OR, 4.94; 95% CI, 1.39-17.57;
= 0.014). Several subtle immune defects are found in CPA.
Multioutput regression of nonlinear and nonstationary data is largely understudied in both machine learning and control communities. This article develops an adaptive multioutput gradient radial ...basis function (MGRBF) tracker for online modeling of multioutput nonlinear and nonstationary processes. Specifically, a compact MGRBF network is first constructed with a new two-step training procedure to produce excellent predictive capacity. To improve its tracking ability in fast time-varying scenarios, an adaptive MGRBF (AMGRBF) tracker is proposed, which updates the MGRBF network structure online by replacing the worst performing node with a new node that automatically encodes the newly emerging system state and acts as a perfect local multioutput predictor for the current system state. Extensive experimental results confirm that the proposed AMGRBF tracker significantly outperforms existing state-of-the-art online multioutput regression methods as well as deep-learning-based models, in terms of adaptive modeling accuracy and online computational complexity.
While sexual violence has been present and prevalent on campus for decades, the work of recent college student activists has made it an issue of major societal and institutional concern. This book ...makes an important contribution to and provides a foundation for better contextualizing and understanding sexual violence. Each chapter in this edited volume focuses on populations that are not often centered in the discourse of campus sexual violence and accounts for individuals' intersecting identities and how they interlock with larger systems of domination. Challenging dominant ideologies concerning assumptions of white women as the only victims-survivors, the racialization of aggressors, and the deleterious rape myths present in both research and practice, this book draws attention to the complexities of sexual violence on the college campus by highlighting populations that are frequently invisible in research, reporting, and practice. The book places sexual violence on campus in a historical context, centering the experiences of populations relegated to the margins, and highlighting the relationship between racism, classism, homophobia, transphobia, and other forms of domination to sexual violence. The final chapters of the book explore how critical models of intervention and prevention and a critical analysis of existing institutional policies may be implemented across college campuses to better address sexual violence for multiple populations and identities in higher education. This book will expand educators' understanding of sexual violence to inform more effective policies, procedures, practice, and research that reaches beyond preventing sexual violence and addresses the dominant systems from which sexual violence stems, in an attempt to eradicate, not just prevent, the act and the issue.
A key characteristic of biological systems is the ability to update the memory by learning new knowledge and removing out-of-date knowledge so that intelligent decision can be made based on the ...relevant knowledge acquired in the memory. Inspired by this fundamental biological principle, this article proposes a multi-output selective ensemble regression (SER) for online identification of multi-output nonlinear time-varying industrial processes. Specifically, an adaptive local learning approach is developed to automatically identify and encode a newly emerging process state by fitting a local multi-output linear model based on the multi-output hypothesis testing. This growth strategy ensures a highly diverse and independent local model set. The online modeling is constructed as a multi-output SER predictor by optimizing the combining weights of the selected local multi-output models based on a probability metric. An effective pruning strategy is also developed to remove the unwanted out-of-date local multi-output linear models in order to achieve low online computational complexity without scarifying the prediction accuracy. A simulated two-output process and two real-world identification problems are used to demonstrate the effectiveness of the proposed multi-output SER over a range of benchmark schemes for real-time identification of multi-output nonlinear and nonstationary processes, in terms of both online identification accuracy and computational complexity.
There is a paucity of evidence surrounding the optimal antifungal therapy for use in chronic pulmonary aspergillosis (CPA) and the duration of therapy remains unclear. We retrospectively evaluated ...treatment outcomes, including change in quality of life scores (St George's Respiratory Questionnaire (QoL)), weight and Aspergillus IgG at 6 and 12 months following initiation of therapy in a cohort of 206 CPA patients referred to the UK National Aspergillosis Centre (NAC), Manchester between April 2013 and March 2015. One hundred and forty-two patients (69%) were azole naïve at presentation and 105 (74%) (Group A) were commenced on itraconazole, 27 (19%) on voriconazole, and 10 (7%) were not treated medically. The remainder (64 patients, 31%) had previously trialled, or remained on, azole therapy at inclusion (Group B) of whom 46 (72%) received itraconazole, 16 (25%) voriconazole, and 2 (3%) posaconazole. Initial therapy was continued for 12 months in 78 patients (48%) of those treated; the azole was changed in 62 (32%) patients and discontinued in 56 (29%) patients for adverse reactions (32, 57%), azole resistance (11, 20%), clinical failure (8, 14%) or clinical stability (5, 9%). Azole discontinuation rates were higher in Group B than in Group A (42% vs. 22%, p = 0.003). For all patients who survived, weight increased (median of 62.2Kg at baseline, to 64.8 at 12 months), mean Aspergillus IgG declined from 260 (baseline) to 154 (12 months) and QoL improved from 62.2/100 (baseline) to 57.2/100 (12 months). At 12 months, there was no difference in median survival between Groups A and B (95% vs. 91%, p = 0.173). The rate of emergence of resistance during therapy was 13% for itraconazole compared to 5% for voriconazole. Bronchial artery embolization was done in 9 (4.4%) patients and lobectomy in 7 (3.2%). The optimal duration of azole therapy in CPA is undetermined due to the absence of evidenced based endpoints allowing clinical trials to be undertaken. However we have demonstrated itraconazole and voriconazole are modestly effective for CPA, especially if given for 12 months, but fewer than 50% of patients manage this duration. This suggests extended therapy may be required for demonstrable clinical improvement.
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