An expert system for predicting the infiltration characteristics

Infiltration plays a fundamental role in streamflow, groundwater recharge, subsurface flow, and surface and subsurface water quality and quantity. This study includes a comparative analysis of the two machine learning techniques; M5P model tree (M5P) and Gene Expression Programming (GEP) in predictions of the infiltration characteristics. The models were trained and tested using the 7 combination (CMB1 – CMB7) of input parameters; moisture content (m), bulk density of soil (D), percentage of the silt (SI), sand (SA) & Clay (C), and time (t), with output parameters; cumulative infiltration (CI) and infiltration rate (IR). Results suggested that GEP has an edge over M5P to predict the IR and CI with R, RMSE & MAE values 0.9343, 15.9667 mm/hr & 8.7676 mm/hr, and 0.9586, 9.2522 mm and 7.7865 mm for IR and CI, respectively with CMB1. Although the M5P model also gave good results with R, RMSE & MAE values 0.9192, 14.1821 mm/hr, & 19.2497 mm/hr, and 0.8987, 11.2144 mm & 18.4328 mm for IR and CI, respectively, but lower than GEP. Furthermore, single-factor ANOVA and uncertainty analysis were used to show the significance of the predicted results and to find the most efficient soft computing techniques respectively.

Effects of climate change on soil organic matter chemical composition and carbon content in different physical fractions

<p>Soil organic matter (SOM) is composed of many pools with different properties (e.g. turnover times) which are generally used in biogeochemical models to predict carbon (C) dynamics. Physical fractionation methods are applied to isolate soil fractions that correspond to these pools. This allows the characterisation of chemical composition and C content of these fractions. There is still a lack of knowledge on how these individual fractions are affected by different climate change drivers, and therefore the fate of SOM remains elusive. We sampled soils from a multifactorial climate change experiment in a managed grassland in Austria four years after starting the experiment to investigate the response of SOM in physical soil fractions to temperature (eT: ambient and elevated by +3°C), atmospheric CO<sub>2</sub>-concentration (eCO<sub>2</sub>: ambient and elevated by +300 ppm) and to a future climate treatment (eT x eCO<sub>2</sub>: +3°C and + 300 ppm). A combination of slaking and wet sieving was used to obtain three size classes: macro-aggregates (maA, > 250 µm), micro-aggregates (miA, 63 µm – 250 µm) and free silt & clay (sc, < 63 µm). In both maA and miA, four different physical OM fractions were then isolated by density fractionation (using sodium polytungstate of ρ = 1.6 g*cm<sup>-3</sup>, ultrasonication and sieving): Free POM (fPOM), intra-aggregate POM (iPOM), silt & clay associated OM (SCaOM) and sand-associated OM (SaOM). We measured C and N contents and isotopic composition by EA-IRMS in all fractions and size classes and used a Pyrolysis-GC/MS approach to assess their chemical composition. For eCO<sub>2</sub> and eT x eCO<sub>2 </sub>plots, an isotope mixing-model was used to calculate the proportion of recent C derived from the elevated CO<sub>2 </sub>treatment. Total soil C and N did not significantly change with treatments.  eCO<sub>2</sub> decreased the relative proportion of maA-mineral-associated C and increased C in fPOM and iPOM. About 20% of bulk soil C was represented by the recent C derived from the CO<sub>2</sub> fumigation treatment. This significantly differed between size classes and density fractions (p < 0.001), which indicates inherent differences in OM age and turnover. Warming reduced the amount of new C incorporated into size classes. We found that each size class and fraction possessed a unique chemical fingerprint, but this was not significantly changed by the treatments. Overall, our results show that while climate change effects on total soil C were not significant after 4 years, soil fractions showed specific effects. Chemical composition differed significantly between size classes and fractions but was unaffected by simulated climate change. This highlights the importance to separate SOM into differing pools, while including changes to the molecular composition might not be necessary for improving model predictions.    </p>

A Just System? How Punitive Youth Justice Systems Increase the Risk of Crime

For children and young people who offend, contact with the justice system can lead to life-long offending, with evidence showing that the younger a child enters the justice system the more likely he/she is to have sustained contact and go on to reoffend (Australian Institute of Health and Welfare (AIHW), 2017). Local and international youth justice approaches that aim to rehabilitate or resocialise the child or young person often have more success in preventing reoffending (Elwick, Davis, Crehan, & Clay, 2013). So, what is it that makes an effective youth justice system, and how can we ensure that children and young people are diverted from the criminal justice system effectively and that those who offend do not continue into a life of crime?

Lagniappe: Comics Go to College

or many of us, reading comic books is a formative childhood experience. Indeed, we can “read” comics pictorially before we can actually read. Comics are often the first reading material we select for ourselves and buy with our own money. The small-town newsstand where my brother and I bought Archie comics in the mid-’70s is etched into a corner of my brain: the ring of the bell as we opened the wooden door, the mingled smells of newsprint and tobacco, and the furtive glances towards the counter whilewe read as many comics as possible just out of the proprietor’s sight. Since the 1930s, comics have been an integral part of the American scene. They have both influenced our collective imagination and reflected the eras in which they were published. From movies (The Matrix) to literature (Michael Chabon’s The Amazing Adventures of Kavalier & Clay) to art (Roy Lichtenstein), the footprint of comics on the culture at large is a deep one.