Natural Isotopes and Ion Compositions Identify Changes in Groundwater Flows Affecting Wetland Vegetation in the Drentsche Aa Brook Valley, The Netherlands

This study uses groundwater isotopes and ion composition to verify model simulations and ecohydrological studies in the Drentsche Aa nature reserve in The Netherlands, which is representative for the northwestern wetland areas in the Ice Marginal Landscape zone. At eight field sites, a total of 24 samples were analysed for their 13C, 14C, 2H, and 18O isotopes and ionic composition. The isotopes indicate that most of the fen peatlands in the area depend on the exfiltration of sub-regional groundwater flows, which confirmed the previous model simulations and ecohydrological studies. At three sites, isotopes and ionic composition indicate that the groundwater from the sub-regional system has been replaced by local infiltrated rainwater, due to nearby groundwater abstractions for drinking water, which influenced the success rates of the restoration measures. Furthermore, the evidence from chloride and 14C contents was found to indicate the presence of more saline groundwater, which are influenced by the groundwater flows near salt diapirs. Groundwater abstractions may enhance the upward flow of the saline groundwater to eventually exfiltrate at the wetlands, affecting the biodiversity of the nature reserve

A Novel Blended State Estimated Adaptive Controller for Voltage and Current Control of Microgrid against Unknown Noise

© 2013 IEEE. In this study, a novel blended state estimated adaptive controller is designed for voltage and current control of microgrid against unknown noise. The core feature of the microgrid (MG) is its ability to integrate more than one distributed energy resource into the main grid. The state of a microgrid may deteriorate due to many reasons, for example malicious cyber-attacks, disturbances, packet losses, etc. Therefore, it is necessary to achieve the true state of the system to enhance the control requirement and automation of the microgrid. To achieve the true state of a microgrid, this study proposes the use of an algorithm based on the unscented kalman filter (UKF). The proposed state estimator technique is developed using an unscented-transformation and sigma-points measurement technique capable of minimizing the mean and covariance of a nonlinear cost function to estimate the true state of a single-phase, three-phase single-source and three-phase multi-source microgrid system. The advantage of the proposed estimator over using extended kalman filter (EKF) is investigated in simulations. The results demonstrate that the use of the UKF estimator produces a superior estimation of the system compared with the use of the EKF. An adaptive PID controller is also developed and used in system conjunction with the estimator to regulate its voltage and current against the number of loads. Deviation in load parameters hamper the function of the MG system. The performance of the developed controller is also evaluated against number of loads. Results indicate the controller provides a more stable and high-tracking performance with the inclusion of the UKF in the system

Sequential quasi-Monte Carlo: Introduction for Non-Experts, Dimension Reduction, Application to Partly Observed Diffusion Processes

SMC (Sequential Monte Carlo) is a class of Monte Carlo algorithms for filtering and related sequential problems. Gerber and Chopin (2015) introduced SQMC (Sequential quasi-Monte Carlo), a QMC version of SMC. This paper has two objectives: (a) to introduce Sequential Monte Carlo to the QMC community, whose members are usually less familiar with state-space models and particle filtering; (b) to extend SQMC to the filtering of continuous-time state-space models, where the latent process is a diffusion. A recurring point in the paper will be the notion of dimension reduction, that is how to implement SQMC in such a way that it provides good performance despite the high dimension of the problem.Comment: To be published in the proceedings of MCMQMC 201

Black carbon as an additional indicator of the adverse health effects of airborne particles compared with PM10 and PM2.5.

Current air quality standards for particulate matter (PM) use the PM mass concentration [PM with aerodynamic diameters ≤ 10 μm (PM(10)) or ≤ 2.5 μm (PM(2.5))] as a metric. It has been suggested that particles from combustion sources are more relevant to human health than are particles from other sources, but the impact of policies directed at reducing PM from combustion processes is usually relatively small when effects are estimated for a reduction in the total mass concentration

The spread of chloramphenicol-resistant Neisseria meningitidis in Southeast Asia.

OBJECTIVES: Invasive disease caused by Neisseria meningitidis is a significant health concern globally, but our knowledge of the prevailing serogroups, antimicrobial susceptibility patterns, and genetics of N. meningitidis in Southeast Asia is limited. Chloramphenicol resistance in N. meningitidis has rarely been reported, but was first described in isolates from Vietnam in 1998. We aimed to characterise eight chloramphenicol resistant meningococcal isolates collected between 2007 and 2018 from diagnostic microbiology laboratories in Cambodia, Thailand and the Lao People's Democratic Republic (Laos). METHODS: Whole-genome sequencing was used to generate genome sequences from 18 meningococcal isolates including the eight chloramphenicol resistant isolates. We identified antimicrobial resistance genes present in these strains, and examined the phylogenetic relationships between strains. RESULTS: The eight resistant strains all contain the same chloramphenicol resistance gene first described in 1998, and are closely related to each other. Strains resistant to penicillin, tetracycline, and ciprofloxacin were also observed, including a chloramphenicol-resistant strain which has acquired penicillin and ciprofloxacin resistance. CONCLUSIONS: This study suggests that chloramphenicol-resistant N. meningitidis is more widespread than previously thought, and that the previously-identified resistant lineage is now found in multiple countries in Southeast Asia

Calsyntenin-1 mediates axonal transport of the amyloid precursor protein and regulates Aβ production

Understanding the mechanisms that control processing of the amyloid precursor protein (APP) to produce amyloid-β (Aβ) peptide represents a key area of Alzheimer's disease research. Here, we show that siRNA-mediated loss of calsyntenin-1 in cultured neurons alters APP processing to increase production of Aβ. We also show that calsyntenin-1 is reduced in Alzheimer's disease brains and that the extent of this reduction correlates with increased Aβ levels. Calsyntenin-1 is a ligand for kinesin-1 light chains and APP is transported through axons on kinesin-1 molecular motors. Defects in axonal transport are an early pathological feature in Alzheimer's disease and defective APP transport is known to increase Aβ production. We show that calsyntenin-1 and APP are co-transported through axons and that siRNA-induced loss of calsyntenin-1 markedly disrupts axonal transport of APP. Thus, perturbation to axonal transport of APP on calsyntenin-1 containing carriers induces alterations to APP processing that increase production of Aβ. Together, our findings suggest that disruption of calsyntenin-1-associated axonal transport of APP is a pathogenic mechanism in Alzheimer's disease

Grading antimicrobial susceptibility data quality: room for improvement.

In their Review of antimicrobial resistance in children in sub-Saharan Africa,1 Phoebe Williams and colleagues remark upon the poor quality of the studies included. We would like to highlight specific concerns regarding the reliability of some of the antimicrobial susceptibility data. By our assessment, only nine of the 18 studies included had no detectable errors or non-compliances to the reporting standards stated to have been used. Examples include reporting antimicrobial susceptibilities for which no breakpoints exist (eg, gentamicin susceptibility for Streptococcus pneumoniae and Salmonella species) or unexpected susceptibility patterns given the known intrinsic resistance of the pathogen (eg, amoxicillin and Klebsiella species; appendix). Identification of genuine meticillin-resistant Staphylococcus aureus was problematic with discordant cloxacillin and cefuroxime susceptibility patterns in two studies, suggesting non-adherence to standard methods

The Science and Practice of Carcinogen Identification and Evaluation

Several national and international health agencies have established programs with the aim of identifying agents and exposures that cause cancer in humans. Carcinogen identification is an activity grounded in the scientific evaluation of the results of human epidemiologic studies, long-term bioassays in experimental animals, and other data relevant to an evaluation of carcinogenicity and its mechanisms. In this commentary, after a brief discussion of the science basis common to the evaluation of carcinogens across different programs, we discuss in more detail the principles and procedures currently used by the IARC Monographs program