This study provides an integrated assessment of the health status of the striped venus clam Chamelea gallina along the western Adriatic coast by combining environmental data with physiological indices (survival in air and condition index), trace-element bioaccumulation, and biochemical biomarkers. Clams from northern, nutrient-rich areas showed longer survival in air during summer, coinciding with higher chlorophyll a and nitrate concentrations. In winter, northern sites showed a lower condition index, while several elements reached their highest concentrations at Goro, where clams also displayed a distinct antioxidant and detoxification biomarker profile. The integrated winter PCA indicated strong spatial co-variation among environmental conditions, elemental accumulation, and biochemical responses. Because these drivers covary along the Adriatic gradient, the observed patterns are best interpreted within a multiple-stressor framework rather than as responses to a single factor. These findings highlight the value of integrated monitoring for assessing the health and sustainability of this commercially important species under increasing environmental variability and anthropogenic pressure.
Efficient catalytic gasification is essential for improving producer gas quality by enhancing tar destruction, and thus more sustainable biomass-to-energy pathways. Iron oxides and spinel ferrites (MFe2O4) have attracted attention as gasification catalysts due to their redox versatility and structural stability, with the divalent cation playing a crucial role in oxygen mobility and metal-oxygen bond strength. In this work, the effect of Co and Mn as divalent cations in spinel ferrites was investigated and compared with hematite during biomass gasification. Catalysts were synthesized via wet impregnation method combined with microwave-assisted calcination, and characterized by XRD, XRF, BET, SEM/EDS, TGA, and Raman. Their performance was evaluated following the improvement of gas quality during gasification of residual forest biomass in a bench-scale bubbling fluidized bed reactor. The gasification conditions were 850 degrees C, equivalence ratio of 0.25 and air as gasifying agent. The results show that catalytic activity for gas quality improvement followed the sequence CoFe2O4 > MnFe2O4 > Fe2O3, mainly due to differences in M - O bond strength and redox flexibility. The Co-based catalyst exhibited the highest performance, increasing the H(2 )production by 115% and the H-2:CO molar ratio by 95%, while decreasing tar production by 66% relative to the reference condition. Process parameters such as CGE, CCE, gas yield and LHV were less affected by the catalyst than the producer gas composition. These results show the positive effect of divalent cations in spinel ferrites and contribute to the rational design of catalysts for efficient biomass to syngas conversion.
In 1998, Lütolf and Margot claimed, in a sidenote, that the projective plane of order 3 3 , also called the ternary plane, or PG(2,3 P G ( 2 , 3 ), cannot be the core of any minimally non-ideal clutter. In this paper, we show that, if \operatorname{\cal C} C is a minimally non-ideal clutter whose core is the PG(2,3) P G ( 2 , 3 ) then \operatorname{\cal C} C must be the blocker of the PG(2,3) P G ( 2 , 3 ) . Since no projective plane of order n \geq 3 n ≥ 3 is minimally non-ideal, the nonexistence of \operatorname{\cal C} C is a consequence of the fact that a clutter is minimally non-ideal if and only its blocker is minimally non-ideal.
We analyse the irrigation problem as an optimal control problem within the context of agricultural planning. By formulating irrigation as an optimal control system, we aim to optimize the water usage, while ensuring efficient agricultural productivity. A key parameter in our model is the percentage of water loss due to deep percolation, denoted by \beta β , which is difficult to estimate and sensitive to environmental perturbations. As a result, the problem becomes a parametric optimal linear-control one with an inequality state constraint. The main goal of this work consists in investigating how perturbations of \beta β affect the optimal solution and the optimal cost, with the help of parameter sensitivity analysis. To achieve this, we reformulate the parametric optimal linear-control problem as a finite-dimensional non-linear programming one for which we derive necessary and second-order sufficient optimality conditions. Additionally, we design a parameter sensitivity analysis. Numerical results are provided to illustrate the designed parameter sensitivity analysis which shows that as \beta β increases, the irrigation period of time and the irrigation water flow rate also increase.
In this paper, we develop an adaptive controller for rigid-body attitude tracking systems that combines a neural network architecture with an event-triggered mechanism. We design a quaternion-based nonlinear controller that employs a neural network to compensate for state-based disturbances and/or modeling errors. The attitude tracking error can be made arbitrarily small by appropriate tuning of the controller parameters. Using well-posed hybrid systems theory, we show that the proposed controller is robust to noise and does not suffer from chattering or unwinding phenomena. Afterwards, we extend our design to accommodate an event-triggered mechanism featuring a sample-and-hold of the state signal, which lowers the required number of controller updates sent to the actuators, and therefore reduces wear on moving mechanical parts. The proposed design renders a compact neighborhood of the null error set semi-globally asymptotically stable for the closed-loop system. Simulation results are presented to assess and illustrate the performance attained by our solution.
