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Durum wheat-vetch intercropping in Mediterranean agroecological systems: Effects on yield, nitrogen balance, and farm profitability
Cereal–legume intercropping offers a viable pathway for advancing the agroecological transition of Mediterranean farming systems from conventional monocultures to more diversified and sustainable agroecosystems. However, field-based evaluations, particularly involving underutilized species and contrasting input levels, remain limited. This study assessed the performance of a low-input intercropping system combining durum wheat and common vetch (Vicia sativa L.), compared to fertilized and unfertilized sole crops, over two growing seasons (2022–2024) in Southern Italy. Compared to the input-intensive monoculture, the intercropping system matched or exceeded grain yield in 2022–2023 (3.31 vs. 3.03 t ha−1) and was comparable in 2023–2024 (2.67 vs. 2.79 t ha−1), despite a sharp decline in rainfall (314.6 mm vs. 673.6 mm) and a rise in mean temperature (15.47 °C vs. 13.58 °C), which increased drought stress. Protein content was comparable or higher (13.9 % vs. 12.3 % in 2022–2023; 12.4 % vs. 12.3 % in 2023–2024), and nitrogen uptake increased by 15.2 kg ha−1 (91.3 vs. 76.1 kg ha−1) in 2022–2023 and 11.9 kg ha−1 in 2023–2024 (66.6 vs. 54.7 kg ha−1). Common vetch demonstrated the highest nitrogen accumulation and contributed up to 124.6 kg N ha−1 via crop residues, enhancing nutrient cycling. Land Equivalent Ratios (1.62 and 1.35) confirmed superior land-use efficiency. Economically, intercropping achieved the highest contribution margin (€280.6 ha−1), outperforming the fertilized wheat monoculture (€47.5 ha−1), despite additional seed separation costs. While absolute performance declined under drought, intercropping remained competitive or superior to monocultures across all metrics, reinforcing its potential as a resilient, low-input solution for Mediterranean agriculture. Further research, supported by long-term field trials, should aim to validate these benefits, improve legume drought tolerance, and refine species combinations to enhance resilience and adaptability in dry Mediterranean environments
Determination of the strong coupling and its running from measurements of inclusive jet production
The value of the strong coupling αS is determined in a comprehensive analysis at next-to-next-to-leading order accuracy in quantum chromodynamics. The analysis uses double-differential cross section measurements from the CMS Collaboration at the CERN LHC of inclusive jet production in proton-proton collisions at centre-of-mass energies of 2.76, 7, 8, and 13 TeV, combined with inclusive deep-inelastic data from HERA. The value αS(mZ)=0.1176−0.0016+0.0014 is obtained at the scale of the Z boson mass. By using the measurements in different intervals of jet transverse momentum, the running of αS is probed for energies between 100 and 1600 GeV
Search for bosons of an extended Higgs sector in b quark final states in proton-proton collisions at sqrt{s} = 13 TeV
A search for beyond-the-standard-model neutral Higgs bosons decaying to a pair of bottom quarks, and produced in association with at least one additional bottom quark, is performed with the CMS detector. The data were recorded in proton-proton collisions at a centre-of-mass energy of 13 TeV at the CERN LHC and correspond to an integrated luminosity of 36.7–126.9 fb−1, depending on the probed mass range. No signal above the standard model background expectation is observed. Upper limits on the production cross section times branching fraction are set for Higgs bosons in the mass range of 125–1800 GeV. The results are interpreted in benchmark scenarios of the minimal supersymmetric standard model, as well as suitable classes of two-Higgs-doublet models
Search for high-mass resonances in a final state comprising a gluon and two hadronically decaying W bosons in proton-proton collisions at sqrt{s} = 13 TeV
A search for high-mass resonances decaying into a gluon, g, and two W bosons is presented. A Kaluza-Klein gluon, gKK, decaying in cascade via a scalar radion R, gKK → gR → gWW, is considered. The final state studied consists of three large-radius jets, two
of which contain the products of hadronically decaying W bosons, and the third one the
hadronization products of the gluon. The analysis is performed using proton-proton collision data at √s = 13 TeV collected by the CMS experiment at the CERN LHC during 2016–2018, corresponding to an integrated luminosity of 138 fb−1. The masses of the gKK and R candidates are reconstructed as trijet and dijet masses, respectively. These are used for event categorization and signal extraction. No excess of data events above the standard
model background expectation is observed. Upper limits are set on the product of the gKK
production cross section and its branching fraction via a radion R to gWW. This is the first
analysis examining the resonant WW+jet signature and setting limits on the two resonance
masses in an extended warped extra-dimensional model
An analytical and bibliometric approach to decision-making in sustainable luxury supply chains
The transition to sustainability is a key objective of global policies. However, the implementation and adoption of sustainable practices in supply chains vary significantly across market sectors. Research highlights the luxury sector as particularly critical, with key stakeholders - supply chain managers and consumers - requiring further investigation to better understand the barriers to adopting sustainable production processes and accepting green products. This study explores the current managerial capabilities and perspectives on integrating sustainable practices within luxury supply chains. A bibliometric analysis was conducted using the Scopus database and VOSviewer software to identify keyword clusters and their interrelationships. Six clusters were identified and analyzed, offering insights into effective strategies for overcoming specific managerial barriers. Practical contributions include an actionable playbook in which the sustainable luxury paradigm serves as an enabler for enhancing consumer value while creating managerial opportunities to align profitability with sustainability in circular supply chains
INTEGRATED PROCEDURES FOR KNOWLEDGE AND MONITORING OF EXISTING BUILDINGS: APPLICATION TO CASE STUDIES
The existing buildings knowledge is a crucial issue to ensure their conservation and preservation. To this end, a detailed survey is very frequently required, focused on dimensions, construction and materials details, crack patterns, presence of any damage and degradation.
However, very often the number and quality of information depend on the analysis level to be performed. In fact, in many cases some investigations are unnecessary resulting in a waste of economic resources and time. For this reason, it may be needed to apply multi-level and integrated procedures, in order to improve the knowledge of an existing building, coherently with the analysis level required.
To this scope a multidisciplinary methodology integrating historical-critical analysis, morphological evolution, destructive and non-destructive tests, and structural monitoring is developed and applied within the PON GENESIS Project. Some case studies are investigated, in order to apply and validate the proposed methodology. In particular, in this paper the preliminary results obtained on two archetypes recurrent within the historical center of Matera, the historical building “San Rocco HUB” in Matera, and the Castel “Pirro del Balzo” in Venosa are presented. The obtained results will be used in future to calibrate more refined numerical
models to assess the seismic vulnerability of the case studies considered, and to validate the multidisciplinary integrated methodology proposed
H-cocharacters and a class of H-algebras with almost polynomial growth
In this paper we consider the natural action of a bialgebra H on the algebra UT2(W) corresponding to a given simple H-module W. We prove that these algebras generate varieties with almost polynomial growth of H-codimensions. This generalizes the known results concerning graded algebras and algebras with derivations. In this context, we introduce the space of Y-proper polynomials and we study the sequence of the corresponding cocharacters, which is of independent interest
Gas forming of a deep drawn component for reshaping purposes
In the present work, the reshaping route is investigated by subjecting a 5754 deep drawn part (simulating an End-of-Life component) to a further deformation stage by gas forming, considered flexible enough to bring the End-of-Life to a new shape, thus eliminating the residual feature from the primary forming operation. The reshaping route was numerically simulated according to a sequential approach using the commercial finite element code Abaqus. Thanks to the numerical approach, it was possible to evaluate the properties of the reshaped part in terms of: i) the achieved strain; ii) the geometrical profile; iii) the thickness distribution. Moreover, it was possible to evaluate how the position of the deep drawn feature affected the properties of the reshaped part in terms of thickness uniformity and residuals from the primary forming operation. Being the working temperature one of the main parameters for the gas forming process, its effect was also investigated in order to find the best compromise between the energy demand of the reshaping process and the quality of the reshaped component
Application of a physically informed neural network for the recovery of vertical greenhouse gas profiles in the Mediterranean Basin
During March 2025, three intrusions of Saharan dust affected southern Italy, with observable effects on atmospheric
composition and, in particular, on greenhouse gases. A recent study conducted by the Institute of Methodologies for
Environmental Analysis of the National Research Council of Italy (CNR-IMAA) documented these events through
integrated in situ and remote sensing observations. Significant variations in CH4 and CO2 concentrations were detected in
correspondence with the dust transport episodes. In this work, we propose an approach based on Physics-Informed
Neural Networks (PINNs) to retrieve the vertical profile of CH4. The results are evaluated against high-precision groundbased
measurements from CNR-IMAA, in order to assess the model’s predictive accuracy and its sensitivity to
atmospheric variations associated with the presence of mineral aerosols