Identification of soil quality indicators for assessing the effect of different tillage practices through a soil quality index in a semi-arid environment

Tillage is known to potentially affect soil quality in various ways. In this study, a soil quality index (SQI) was developed by quantifying several soil attributes either sensitive or insensitive to physical disturbance, using factor analysis as a dimension reduction technique, in order to discriminate different tillage systems. Soil properties including physical (MWD), chemical (pH, organic C, total N, available P and POM contents) and microbial (MBC, MBN, PCM, PNM and three enzymes) parameters were measured to establish a minimum data set (MDS) for the assessment of overall SQI. The soil attributes were determined on samples (0–20 cm depth) collected under moldboard (MP) and disk (DP) plows as conventional tillage (CT), and rotary (RP) and chisel (CP) plows as reduced tillage (RT) systems with a similar plant C input rate and cover crop over a period of six years (2005–2011) in a semi-arid calcareous soil (Calcixerepts) from Central Iran. Results indicated a clear difference in soil quality among the tillage systems with a significant increase of SQI under RT over time, particularly under CP practices. Although RT improved most soil microbial attributes, not all attributes contributed to SQI because of their close interrelationship. The final SQI consisted only of geometric mean of microbial activity (GMA, the square root of the product of PCM and PNM) and geometric mean of enzyme activity (GME, the cube root of the product of enzyme activities). Soil GME and GMA were found to be as key indicators contributing 55% and 36% to SQI, respectively. Therefore, the GME and GMA were the most important indicators effectively discriminating tillage systems, and could be used to monitor the enhancement of soil quality under RT in this semiarid environment. The influence of tillage year on SQI was greater than that of tillage practices. In conclusion, RT systems were characterized by a higher value of SQI, suggesting a good recovery of soil capacity and functions after abandoning CT in the studied area. Smallholder farmers should therefore be aware of the potential for high soil quality in future as a result of continuing RT systems, especially with surface tillage using CP practices.     

Bayesian Quantile Regression for Longitudinal Studies with Nonignorable Missing Data

Summary .  We study quantile regression (QR) for longitudinal measurements with nonignorable intermittent missing data and dropout. Compared to conventional mean regression, quantile regression can characterize the entire conditional distribution of the outcome variable, and is more robust to outliers and misspecification of the error distribution. We account for the within-subject correlation by introducing a   ℓ₂   penalty in the usual QR check function to shrink the subject-specific intercepts and slopes toward the common population values. The informative missing data are assumed to be related to the longitudinal outcome process through the shared latent random effects. We assess the performance of the proposed method using simulation studies, and illustrate it with data from a pediatric AIDS clinical trial.     

Bayesian Nonparametric Modeling for Comparison of Single-Neuron Firing Intensities

Summary .  We propose a fully inferential model-based approach to the problem of comparing the firing patterns of a neuron recorded under two distinct experimental conditions. The methodology is based on nonhomogeneous Poisson process models for the firing times of each condition with flexible nonparametric mixture prior models for the corresponding intensity functions. We demonstrate posterior inferences from a global analysis, which may be used to compare the two conditions over the entire experimental time window, as well as from a pointwise analysis at selected time points to detect local deviations of firing patterns from one condition to another. We apply our method on two neurons recorded from the primary motor cortex area of a monkey's brain while performing a sequence of reaching tasks.     

Fish community response to the longitudinal environmental gradient in Czech deep-valley reservoirs: Implications for ecological monitoring and management

Ecological quality assessment of non-natural water bodies is, in contrast to natural systems, less developed and requires determining biological indicators that reliably reflect environmental conditions and anthropogenic pressures. This study was motivated to propose fish indicators appropriate for assessment of reservoir ecosystems in central Europe. We analysed changes in water quality, total biomass and the taxonomic, trophic and size composition of fish communities along the longitudinal axes of four elongated, deep-valley reservoirs. Due to high nutrient inputs from their catchments, the reservoirs exhibited pronounced within-system gradients in primary productivity and water transparency. Although fish communities were similar among the reservoirs and dominated by few native species, the community structure and biomass systematically changed along the longitudinal axes of the reservoirs. The biomass and proportion of planktivores/benthivores in the fish community were highest at eutrophic sites near the river inflow and declined substantially towards deep, more oligotrophic sites close to the dam. The biomass and proportion of piscivores significantly increased downstream within the reservoirs alongside improving water quality. At species level, perch Perca fluviatilis and bream Abramis brama responded most sensitively, although in opposite directions, to the longitudinal environmental gradient. The major longitudinal changes in fish community characteristics were found to be consistent between pelagic and benthic habitats. The results of this study suggest that fish communities are appropriate indicators of eutrophication and can be used for ecological quality assessment of non-natural lentic water bodies, such as reservoirs. Moreover, our results underline the necessity to consider within-system gradients in water quality and the fish community when planning sampling programmes for deep-valley reservoirs.     

Pre-emptive Quality Control of a Misfolded Membrane Protein by Ribosome-Driven Effects

1. Download : Download high-res image (188KB)
2. Download : Download full-size image

     

The impacts of agricultural payments on groundwater quality: Spatial analysis on the case of Slovenia

The European Common Agricultural Policy still follows its primary goals, i.e. quality food at affordable prices and a decent standard of living for farmers, fifty years after its adoption. Moreover, this policy adapts to the changing needs of society and the new challenges, mostly preservation of the environment, nature and biodiversity in rural areas. Although the Common Agricultural Policy receives the largest share of European budget, the funds are decreasing over time, especially direct payments, which aim to provide basic income support to farmers in the European Union. On the other hand, agri-environmental payments are gaining importance. Policy decision-makers should be interested in the question of impacts of growing eco-conditionality of agricultural spending. New insights would help them to be successful in achieving the goals of sustainable agriculture. The purpose of this paper is to estimate the impacts of production support payments and rural development payments on the quality of groundwater. We use the small EU country Slovenia as an example. The baseline indicators are the level of nitrates and pesticides in groundwater, while the impacts were estimated using spatial error model. The results show that direct payments, coupled subsidies and investment grants raise the level of pesticides in groundwater, but do not have any statistically significant impact on the level of nitrates in groundwater. Furthermore, we did not find any statistically significant effects of agri-environmental payments on decrease of groundwater pollution with nitrates. However, our findings revealed that agri-environmental payments are effective in reducing pesticides in groundwater, although only to a limited extent. These results imply a problem of insufficient targeting of agri-environmental measures on the one hand, and suggest that greening of direct payments is necessary and entirely justified.     

Adaptive Neural Network-Based ECG Data Compression According to the Morphology

1IntroductionElbo（ECG）offersalotofilllcorralltinfondionforthediagnosisOfheartdis－eases．Berz1，seahaormalEChcax［lrins＞llleu＂knownsituations，thcycanbeCSUghtinthelongti1Ylecontin～11xHlltoriDg．ndterrnoultonngsystemwhichcanrecord24－hoUrECGdataisoneofeffectiveme～toprovidethefun～．AlthOUghthehag6scaleICmorestohavebeeddevelopepbedeavailabletostorelOngtboeECGdsta，itisveqdifficultyandtioublesomethatalopnUmbeOfdstaisprasersandstoredortiallsillltted．InthedigitedECGdata，thereare…     

High frequency residues: A new set of signals for detectability studies of an X-ray imaging system

A new set of signals for studying detectability of an X-ray imaging system is presented. The results obtained with these signals are intended to complement the NEQ results.The signals are generated from line spread profiles by progressively removing their lower frequency components and the resulting high frequency residues (HFRs) form the set of signals to be used in detectability studies. Detectability indexes for these HFRs are obtained using a non-prewhitening (NPW) observer and a series of edge images are used to obtain the HFRs, the covariance matrices required by the NPW model and the MTF and NPS used in NEQ calculations. The template used in the model is obtained by simulating the processes of blurring and sampling of the edge images. Comparison between detectability indexes for the HFRs and NEQ are carried out for different acquisition techniques using different beam qualities and doses.The relative sensitivity shown by detectability indexes using HFRs is higher than that of NEQ, especially at lower doses. Also, the different observers produce different results at high doses: while the ideal Bayesian observer used by NEQ distinguishes between beam qualities, the NPW used with the HFRs produces no differences between them.Delta functions used in HFR are the opposite of complex exponential functions in terms of their support in the spatial and frequency domains. Since NEQ can be interpreted as detectability of these complex exponential functions, detectability of HFRs is presented as a natural complement to NEQ in the performance assessment of an imaging system.