Physical land degradation and loss of soil fertility: soil structural stability and bio-physical indicators

This study investigates the changes in soil fertility due to the different aggregate breakdown mechanisms and it analyses their relationships in different soil-plant systems, using physical aggregates behavior and organic matter (OM) changes as indicators. Three case studies were investigated: i) an organic agricultural soil, where a combined method, aimed to couple aggregate stability to nutrients loss, were tested; ii) a soil biosequence, where OM chemical characterisation and fractionation of aggregates on the basis of their physical behaviour were coupled and iii) a soils sequence in different phytoclimatic conditions, where isotopic C signature of separated aggregates was analysed. In agricultural soils the proposed combined method allows to identify that the severity of aggregate breakdown affected the quantity of nutrients lost more than nutrients availability, and that P, K and Mg were the most susceptible elements to water abrasion, while C and N were mainly susceptible to wetting. In the studied Chestnut-Douglas fir biosequence, OM chemical properties affected the relative importance of OM direct and indirect mechanisms (i.e., organic and organic-metallic cements, respectively) involved in aggregate stability and nutrient losses: under Douglas fir, high presence of carboxylate groups enhanced OM-metal interactions and stabilised aggregates; whereas under Chestnut, OM directly acted and fresh, more C-rich OM was preserved. OM direct mechanism seemed to be more efficient in C preservation in aggregates. The 13C natural abundance approach showed that, according to phytoclimatic conditions, stable macroaggregates can form both around partially decomposed OM and by organic-mineral interactions. In topsoils, aggregate resistance enhanced 13C-rich OM preservation, but in subsoils C preservation was due to other mechanisms, likely OM-mineral interactions. The proposed combined approach seems to be useful in the understanding of C and nutrients fate relates to water stresses, and in future research it could provide new insights into the complexity of soil biophysical processes.

The three-dimensional single-bin-size bin packing problem: combining metaheuristic and machine learning approaches

The Three-Dimensional Single-Bin-Size Bin Packing Problem is one of the most studied problem in the Cutting & Packing category. From a strictly mathematical point of view, it consists of packing a finite set of strongly heterogeneous “small” boxes, called items, into a finite set of identical “large” rectangles, called bins, minimizing the unused volume and requiring that the items are packed without overlapping. The great interest is mainly due to the number of real-world applications in which it arises, such as pallet and container loading, cutting objects out of a piece of material and packaging design. Depending on these real-world applications, more objective functions and more practical constraints could be needed. After a brief discussion about the real-world applications of the problem and a exhaustive literature review, the design of a two-stage algorithm to solve the aforementioned problem is presented. The algorithm must be able to provide the spatial coordinates of the placed boxes vertices and also the optimal boxes input sequence, while guaranteeing geometric, stability, fragility constraints and a reduced computational time. Due to NP-hard complexity of this type of combinatorial problems, a fusion of metaheuristic and machine learning techniques is adopted. In particular, a hybrid genetic algorithm coupled with a feedforward neural network is used. In the first stage, a rich dataset is created starting from a set of real input instances provided by an industrial company and the feedforward neural network is trained on it. After its training, given a new input instance, the hybrid genetic algorithm is able to run using the neural network output as input parameter vector, providing as output the optimal solution. The effectiveness of the proposed works is confirmed via several experimental tests.