bluuebunny/crossref_metadata_2025_split huggingface dataset:
Four reflections on the new global mental health priorities
Authors: Caldas-de-Almeida José Miguel 
Published: November 2019

Abstract
The discussion of the achievements and limitations of the strategies prioritised in global mental health that has taken place in recent years contributed to a unified vision for action that addresses the gaps still existing on prevention, treatment, quality of care and human rights protection. This editorial presents four reflections on the impact of this vision on the definition of future priorities, particularly in the areas of policy implementation, services reconfiguration and organisation, human rights and research. It concludes that further debate is needed to redefine the balance between priorities and strategies that can better promote an effective response to the needs of low and middle income countries, and to ensure an efficient coordination of efforts in the future.
Reflections on the next ten years of research, policy and implementation in global mental health
Authors: Lund Crick 
Published: November 2019

Abstract
Since the World Health Report 2001 focused on mental health for the first time, the field of global mental health has seen unprecedented growth in policy commitments and research. Yet many challenges remain, including a lack of substantial new financial investments from governments, ongoing human rights abuses suffered by people living with mental illness, weak health systems in low resource settings and large gaps in our knowledge regarding aetiology, prevention of mental illness and mental health promotion. Stark inequalities persist between high-income countries and low- and middle-income countries (LMIC) in research knowledge and service resources. This editorial sets out to reflect on progress to date, and suggest priorities and possible future trends for research, policy and service implementation, especially in LMIC.
Localized Anisotropic Domains Beneath Eastern North America
Authors: Li Yiran , Levin Vadim , Elkington Stephen , Hlavaty Janine 
Published: November 2019

AbstractSeismic anisotropy beneath eastern North America likely reflects both the remnant lithospheric fabrics and the present‐day deformation of the asthenosphere. We report new observations of splitting in core‐refracted shear phases observed over 3–5 years at 33 sites in New Jersey, New York, and states in the New England region and also include data from eight previously studied locations. Our data set emphasizes back azimuthal coverage necessary to capture the directional variation of splitting parameters expected from vertically varying anisotropy. We report single‐phase splitting parameters as well as station‐averaged values based on splitting intensity technique that incorporates all observed records regardless of whether they showed evidence of splitting or not. Trends of averaged fast shear wave polarizations appear coherent and are approximately aligned with absolute plate motion direction. The general disparity between the fast axes and the trend of surface tectonic features suggests a dominant asthenosphere contribution for the observed seismic anisotropy. Averaged delay values systematically increase from ~0.5 s in New Jersey to ~1.4 s in Maine. Splitting parameters vary at all sites, and neighboring stations often show similar patterns of directional variation. We developed criteria to group stations based on their splitting patterns and identified four domains with distinct anisotropic properties. Splitting patterns of three domains suggest a layered anisotropic structure that is geographically variable, outlining distinct regions in the continental mantle, for example, the Proterozoic lithosphere of the Adirondack Mountains. A domain coincident with the North Appalachian Anomaly displays virtually no splitting, implying that the lithospheric fabric was locally erased.
Drying in the Middle East During Northern Hemisphere Cold Events of the Early Glacial Period
Authors: Carolin S. A. , Ersek V. , Roberts W. H. G. , Walker R. T. , Henderson G. M. 
Published: November 2019

AbstractFew paleoclimate records exist to assess the central Middle East's response to natural forcing beyond the instrumental record. Here, we present a multiproxy stalagmite‐based climate reconstruction from Iran's semiarid northeast that spans 100–70,000 years before present. During severe cold (stadial) events in the North Atlantic at ≈88, 77, and 73 ka, stalagmite trace‐element data indicate anomalously dry periods at this location. Stadial event increases in the stalagmite oxygen isotopes mirror those in a published Iranian stalagmite 800 km to the west. A global climate model simulates drying across the Middle East region in response to stadial event forcing, in agreement with oxygen isotope enrichments in both Iranian records, caused by a smaller fractional loss of moisture on the trajectory upstream. The paleoproxies and model experiments are consistent in indicating a drier Middle East climate during the cold North Atlantic stadials.
The Impact of the Extreme 2015–2016 El Niño on the Mass Balance of the Antarctic Ice Sheet
Authors: Bodart J.A. , Bingham R.J. 
Published: November 2019

AbstractInterannual variations associated with El Niño‐Southern Oscillation can alter the surface‐pressure distribution and moisture transport over Antarctica, potentially affecting the contribution of the Antarctic ice sheet to sea level. Here, we combine satellite gravimetry with auxiliary atmospheric data sets to investigate interannual ice‐mass changes during the extreme 2015–2016 El Niño. Enhanced precipitation during this event contributed positively to the mass of the Antarctic Peninsula and West Antarctic ice sheets, with the mass gain on the peninsula being unprecedented within GRACE's observational record. Over the coastal basins of East Antarctica, the precipitation‐driven mass loss observed in recent years was arrested, with pronounced accumulation over Terre Adélie dominating this response. Little change was observed over Central Antarctica where, after a brief pause, enhanced mass‐loss due to weakened precipitation continued. Overall, precipitation changes over this period were sufficient to temporarily offset Antarctica's usual (approximately 0.4 mm yr−1) contribution to global mean sea level rise.
High‐Arsenic Groundwater in the Southwestern Bengal Basin Caused by a Lithologically Controlled Deep Flow System
Authors: Khan M. R. , Michael H. A. , Nath B. , Huhmann B. L. , Harvey C. F. , Mukherjee A. , Choudhury I. , Chakraborty M. , Ullah M. S. , Ahmed K. M. , Goodbred S. L. , Schlosser P. , Bostick B. C. , Mailloux B. J. , Ellis T. , van Geen A. 
Published: November 2019

AbstractElevated arsenic in Bengal Basin aquifers threatens human health. Most deep (>150 m) groundwater in Pleistocene aquifers is low in arsenic; however higher concentrations have been reported in the southwest border region. Here, we establish that this extensive arsenic contamination at depth is not associated with well failure. A combination of geochemistry and flow modeling constrains the factors that contribute to arsenic contamination at depth in this region. Deep groundwater in the affected area is younger (2.0 ± 0.6 kyr) than deep, low‐arsenic groundwater elsewhere (12.0 ± 4.0 kyr) based on radiocarbon. Stratigraphic data indicate pre‐Holocene deposition of the contaminated aquifers, but few low‐permeability strata. Numerical modeling indicates that this stratigraphic anomaly permits a natural flow system that transports shallow groundwater to depth. Thus, in areas lacking low‐permeability layers, arsenic contamination can occur in pre‐Holocene aquifers and is probably not an early sign of future deep contamination in regions with interbedded low‐permeability strata.
Viewing Forced Climate Patterns Through an AI Lens
Authors: Barnes Elizabeth A. , Hurrell James W. , Ebert‐Uphoff Imme , Anderson Chuck , Anderson David 
Published: November 2019

AbstractMany problems in climate science require extracting forced signals from a background of internal climate variability. We demonstrate that artificial neural networks (ANNs) are a useful addition to the climate science “toolbox” for this purpose. Specifically, forced patterns are detected by an ANN trained on climate model simulations under historical and future climate scenarios. By identifying spatial patterns that serve as indicators of change in surface temperature and precipitation, the ANN can determine the approximate year from which the simulations came without first explicitly separating the forced signal from the noise of both internal climate variability and model uncertainty. Thus, the ANN indicator patterns are complex, nonlinear combinations of signal and noise and are identified from the 1960s onward in simulated and observed surface temperature maps. This approach suggests that viewing climate patterns through an artificial intelligence (AI) lens has the power to uncover new insights into climate variability and change.
Impacts of Mesoscale Eddies on Phytoplankton Size Structure
Authors: Waga Hisatomo , Hirawake Toru , Ueno Hiromichi 
Published: November 2019

AbstractThe impact of mesoscale eddies on phytoplankton communities attracts considerable research attention because phytoplankton play numerous roles in marine ecosystems. Using remote sensing techniques, this study considered a synoptic relationship between phytoplankton size structure, which is a determinant of energy transfer efficiency in marine ecosystems, and mesoscale eddies, which are ubiquitous ocean features. We found clear spatial variation in the impacts of mesoscale eddies on phytoplankton size structure; phytoplankton communities with larger cell sizes were supported by anticyclonic eddies in oligotrophic regions and by cyclonic eddies in eutrophic regions. Differences in the phytoplankton size structure within these two types of mesoscale eddies became greater, accompanied by interannual trends in the phytoplankton size structure for 2003–2014. Our findings are the first to demonstrate the important linkage between mesoscale eddies and phytoplankton size structure on a global scale; this new knowledge might help better predict variability in marine ecosystems.
Gravity‐Induced Bubble Ripening in Porous Media and Its Impact on Capillary Trapping Stability
Authors: Xu Ke , Mehmani Yashar , Shang Luoran , Xiong Qingrong 
Published: November 2019

AbstractCapillary or residual trapping is considered one of the safest geologic CO2 storage mechanisms due to its hydrodynamic stability. We present a first study of the impact of gravity on Ostwald ripening in porous media and show it may render capillary trapping thermodynamically unstable. Gravity induces a vertical chemical potential gradient that leads to the upwards diffusion of CO2. Thus, bubbles at shallower depths grow at the expense of bubbles in deeper strata, leading to the formation of an overriding gas cap. We first develop a pore‐scale model for two bubbles trapped within adjacent pores and then upscale it to obtain a one‐dimensional continuum model. We use the latter to predict the macroscopic evolution of a trapped bubble population. Factors controlling the ripening process are isolated to assist in selecting CO2 storage sites. Gravity‐induced ripening may also play a role in geologic fluid emplacement and migration over millions of years.
A Parametric Numerical Analysis of Factors Controlling Ground Ruptures Caused by Groundwater Pumping
Authors: Frigo Matteo , Ferronato Massimiliano , Yu Jun , Ye Shujun , Galloway Devin , Carreón‐Freyre Dora , Teatini Pietro 
Published: November 2019

AbstractA modeling analysis is used to investigate the relative susceptibility of various hydrogeologic configurations to aseismic rupture generation due to deformation of aquifer systems accompanying groundwater pumping. An advanced numerical model (GEPS3D) is used to simulate rupture generation and propagation for three typical processes: (i) reactivation of a preexisting fault, (ii) differential compaction due to variations in thickness of aquifer/aquitard layers constituting the aquifer system, and (iii) tensile fracturing above a bedrock ridge that forms the base of the aquifer system. A sensitivity analysis is developed to address the relative importance of various factors, including aquifer depletion, aquifer thickness, the possible uneven distribution and depth below land surface of the aquifer/aquitard layers susceptible to aquifer‐system compaction, and the height of bedrock ridges beneath the aquifer system which contributes to thinning of the aquifer system. The rupture evolution is classified in two occurrences. In one, the rupture develops at either the top of the aquifer or at land surface and does not propagate. In the other, the developed rupture propagates from the aquifer top toward the land surface and/or from the land surface downward. The aquifer depth is the most important factor controlling rupture evolution. Specifically, the probability of a significant rupture propagation is higher when the aquifer top is near land surface. The numerical results are processed by a statistical regression analysis to provide a general methodology for a preliminary evaluation of possible ruptures development in exploited aquifer systems susceptible to compaction and accompanying land subsidence. A comparison with a few representative case studies in Arizona, USA, China, and Mexico supports the study outcomes.
Historic Flood Reconstruction With the Use of an Artificial Neural Network
Authors: Bomers A. , van der Meulen B. , Schielen R. M. J. , Hulscher S. J. M. H. 
Published: November 2019

AbstractThe uncertainty in flood frequency relations can be decreased by adding reconstructed historic flood events to the data set of measured annual maximum discharges. This study shows that an artificial neural network trained with a 1‐D/2‐D coupled hydraulic model is capable of reconstructing river floods with multiple dike breaches and inundations of the hinterland with high accuracy. The benefit of an artificial neural network is that it reduces computational times. With this network, the maximum discharge of the 1809 flood event of the Rhine River and its 95% confidence interval was reconstructed. The study shows that the trained artificial neural network is capable of reproducing the behavior of the hydraulic model correctly. The maximum discharge during the flood event was predicted with high accuracy even though the underlying input data are, due to the fact that the event occurred more than 200 years ago, uncertain. The confidence interval of the prediction was reduced by 43% compared to earlier predictions that did not use hydraulic models.
Novel role for mineralocorticoid receptors in control of a neuronal phenotype
Authors: McCann Katharine E. , Lustberg Daniel J. , Shaughnessy Emma K. , Carstens Kelly E. , Farris Shannon , Alexander Georgia M. , Radzicki Daniel , Zhao Meilan , Dudek Serena M. 
Published: November 2019

AbstractMineralocorticoid receptors (MRs) in the brain play a role in learning and memory, neuronal differentiation, and regulation of the stress response. Within the hippocampus, the highest expression of MRs is in area CA2. CA2 pyramidal neurons have a distinct molecular makeup resulting in a plasticity-resistant phenotype, distinguishing them from neurons in CA1 and CA3. Thus, we asked whether MRs regulate CA2 neuron properties and CA2-related behaviors. Using three conditional knockout methods at different stages of development, we found a striking decrease in multiple molecular markers for CA2, an effect mimicked by chronic antagonism of MRs. Furthermore, embryonic deletion of MRs disrupted afferent inputs to CA2 and enabled synaptic potentiation of the normally LTP-resistant synaptic currents in CA2. We also found that CA2-targeted MR knockout was sufficient to disrupt social behavior and alter behavioral responses to novelty. Altogether, these results demonstrate an unappreciated role for MRs in controlling CA2 pyramidal cell identity and in facilitating CA2-dependent behaviors.
Inhibition of PTP1B blocks pancreatic cancer progression by targeting the PKM2/AMPK/mTOC1 pathway
Authors: Xu Qi , Wu Ning , Li Xiangqian , Guo Chuanlong , Li Chao , Jiang Bo , Wang Huaizhi , Shi Dayong 
Published: November 2019

AbstractPancreatic cancer is a highly malignant cancer and lacks effective therapeutic targets. Protein-tyrosine phosphatase 1B (PTP1B), a validated therapeutic target for diabetes and obesity, also plays a critical positive or negative role in tumorigenesis. However, the role of PTP1B in pancreatic cancer remains elusive. Here, we initially demonstrated that PTP1B was highly expressed in pancreatic tumors, and was positively correlated with distant metastasis and tumor staging, and indicated poor survival. Then, inhibition of PTP1B either by shRNA or by a specific small-molecule inhibitor significantly suppressed pancreatic cancer cell growth, migration and colony formation with cell cycle arrest in vitro and inhibited pancreatic cancer progression in vivo. Mechanism studies revealed that PTP1B targeted the PKM2/AMPK/mTOC1 signaling pathway to regulate cell growth. PTP1B inhibition directly increased PKM2 Tyr-105 phosphorylation to further result in significant activation of AMPK, which decreased mTOC1 activity and led to inhibition of p70S6K. Meanwhile, the decreased phosphorylation of PRAS40 caused by decreased PKM2 activity also helped to inhibit mTOC1. Collectively, these findings support the notion of PTP1B as an oncogene and a promising therapeutic target for PDAC.
Biological and practical implications of genome-wide association study of schizophrenia using Bayesian variable selection
Authors: Rowe Benazir , Chen Xiangning , Wang Zuoheng , Chen Jingchun , Amei Amei 
Published: November 2019

AbstractGenome-wide association studies (GWAS) have identified over 100 loci associated with schizophrenia. Most of these studies test genetic variants for association one at a time. In this study, we performed GWAS of the molecular genetics of schizophrenia (MGS) dataset with 5334 subjects using multivariate Bayesian variable selection (BVS) method Posterior Inference via Model Averaging and Subset Selection (piMASS) and compared our results with the previous univariate analysis of the MGS dataset. We showed that piMASS can improve the power of detecting schizophrenia-associated SNPs, potentially leading to new discoveries from existing data without increasing the sample size. We tested SNPs in groups to allow for local additive effects and used permutation test to determine statistical significance in order to compare our results with univariate method. The previous univariate analysis of the MGS dataset revealed no genome-wide significant loci. Using the same dataset, we identified a single region that exceeded the genome-wide significance. The result was replicated using an independent Swedish Schizophrenia Case–Control Study (SSCCS) dataset. Based on the SZGR 2.0 database we found 63 SNPs from the best performing regions that are mapped to 27 genes known to be associated with schizophrenia. Overall, we demonstrated that piMASS could discover association signals that otherwise would need a much larger sample size. Our study has important implication that reanalyzing published datasets with BVS methods like piMASS might have more power to discover new risk variants for many diseases without new sample collection, ascertainment, and genotyping.
State-independent contextuality in classical light
Authors: Li Tao , Zeng Qiang , Zhang Xiong , Chen Tian , Zhang Xiangdong 
Published: November 2019

AbstractState-independent contextuality is a fundamental phenomenon in quantum mechanics, which has been demonstrated experimentally in different systems in recent years. Here we show that such contextuality can also be simulated in classical optical systems. Using path and polarization degrees of freedom of classical optics fields, we have constructed the classical trit (cetrit), here the term ‘cetrit’ is the classical counterpart of a qutrit in quantum systems. Furthermore, in classical optical systems we have simulated the violations of several Yu-Oh-like noncontextual inequalities in a state-independent manner by implementing the projection measurements. Our results not only provide new physical insights into the contextuality and also show the application prospects of the concepts developed recently in quantum information science to classical optical systems and optical information processes.
Strain-rate sensitive ductility in a low-alloy carbon steel after quenching and partitioning treatment
Authors: Frint Philipp , Kaiser Till , Mehner Thomas , Bruder Enrico , Scholze Mario , Mašek Bohuslav , Lampke Thomas , Wagner Martin F.-X. 
Published: November 2019

AbstractWe investigate an extraordinarily high ductility in a low alloy carbon steel at an elevated temperature after a quenching and partitioning (Q&P) treatment. The conventional (quenched and tempered) reference material does not show similar behavior. Interestingly, the Q&P treated material’s ductility is considerably reduced at increasing strain rates while strength remains almost constant. These results indicate the presence of a diffusion-controlled deformation mechanism at elevated temperatures. Our research shows that interlath retained austenite is more stable during deformation at higher temperatures, resulting in a delayed transformation to martensite and therefore to a more pronounced contribution to plastic deformation at (and in the vicinity of) the many interfaces inherently present in this multi-phase steel.
Polyacrylamide Bead Sensors for in vivo Quantification of Cell-Scale Stress in Zebrafish Development
Authors: Träber N. , Uhlmann K. , Girardo S. , Kesavan G. , Wagner K. , Friedrichs J. , Goswami R. , Bai K. , Brand M. , Werner C. , Balzani D. , Guck J. 
Published: November 2019

AbstractMechanical stress exerted and experienced by cells during tissue morphogenesis and organ formation plays an important role in embryonic development. While techniques to quantify mechanical stressesin vitroare available, few methods exist for studying stresses in living organisms. Here, we describe and characterize cell-like polyacrylamide (PAAm) bead sensors with well-defined elastic properties and size forin vivoquantification of cell-scale stresses. The beads were injected into developing zebrafish embryos and their deformations were computationally analyzed to delineate spatio-temporal local acting stresses. With this computational analysis-based cell-scale stress sensing (COMPAX) we are able to detect pulsatile pressure propagation in the developing neural rod potentially originating from polarized midline cell divisions and continuous tissue flow. COMPAX is expected to provide novel spatio-temporal insight into developmental processes at the local tissue level and to facilitate quantitative investigation and a better understanding of morphogenetic processes.