Wood is a renewable resource and it actively contributes to enhance energy production under a sustainable perspective. However, harvesting, transport and use of wood imply several consequences and impacts on environment. There are different ways for managing forests dedicated to wood production and a sustainable approach is fundamental to preserve the resource. In this context, Life Cycle Assessment (LCA) is a useful tool for estimating the environmental impacts related to renewable resources. Traditional coppice is a common approach for forest management in several areas, including southern Europe and, specifically, Italy, Spain and the Balkans. Due to different terrain conditions, different types of forest operations are considered for wood extraction from coppices, where the main product is firewood used in domestic heating. The aim of this work was to compare the main common systems for firewood production in two different terrain conditions ('flat/low steep' and 'steep/very steep' terrains), in a representative environment for Mediterranean area, located in central Italy, by means of LCA. Seven different impact categories were evaluated in a cradle-to-gate perspective taking into account all the operations carried out from the trees felling to the firewood storage at factory. Results showed that the extraction phase was the most important in terms of environmental burdens in firewood production and the use of heavy and high-power machines negatively influenced the emissions compared with manual operations. Finally, considering the general low-inputs involved in wood production in coppice, the transport of workers by car to the work site resulted on consistent contributions into environmental burdens. An additional analysis about the modifications of CH4 and N2O exchanges between soil and atmosphere, due to soil compaction in the extraction phase, was made and based on bibliographic information. Results showed a sensible difference between disturbed and undisturbed soil.
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http://dx.doi.org/10.1016/j.scitotenv.2016.04.041 | DOI Listing |
Bone
January 2025
ARTORG Centre for Biomedical Engineering Research, University of Bern, Bern, Switzerland.
Osteoporosis is the most common bone metabolic unbalance, leading to fragility fractures, which are known to be associated with structural changes in the bone. Cortical bone accounts for 80 % of the skeleton mass and undergoes remodeling throughout life, leading to changes in its thickness and microstructure. Although many studies quantified the different cortical bone structures using CT techniques (3D), they are often realised on a small number of samples.
View Article and Find Full Text PDFJ Affect Disord
January 2025
Department of Medicine and Surgery, Kore University of Enna, Italy; Oasi Research Institute-IRCCS, Troina, Italy. Electronic address:
Background: Clinical predictors of treatment-resistant depression could improve treatment strategies. Depressive symptom profiles at baseline are potential outcome predictors, but little evidence is available, and sex-specific profiles have been scarcely investigated.
Methods: Baseline symptom scores of 1294 patients with major depressive disorder were assessed by the Montgomery-Åsberg depression rating scale (MADRS) as part of a multicenter study by the "Group for the Studies of Resistant Depression".
J Mol Neurosci
January 2025
Lanzhou University Second Hospital, The Second Medical College of Lanzhou University, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, China.
Ischemic stroke leads to permanent damage to the affected brain tissue, with strict time constraints for effective treatment. Predictive biomarkers demonstrate great potential in the clinical diagnosis of ischemic stroke, significantly enhancing the accuracy of early identification, thereby enabling clinicians to intervene promptly and reduce patient disability and mortality rates. Furthermore, the application of predictive biomarkers facilitates the development of personalized treatment plans tailored to the specific conditions of individual patients, optimizing treatment outcomes and improving prognoses.
View Article and Find Full Text PDFPlants (Basel)
January 2025
College of Life and Environmental Sciences, Minzu University of China, Beijing 100081, China.
The concurrent environmental challenges of invasive species and soil microplastic contamination increasingly affect agricultural ecosystems, yet their combined effects remain underexplored. This study investigates the interactive impact of the legacy effects of Canada goldenrod ( L.) invasion and soil microplastic contamination on wheat ( L.
View Article and Find Full Text PDFJ Clin Med
January 2025
Clinical Trial and Biostatistics, Research and Innovation Unit, University Hospital of Ferrara, 44124 Ferrara, Italy.
A machine learning prognostic mortality scoring system was developed to address challenges in patient selection for clinical trials within the Intensive Care Unit (ICU) environment. The algorithm incorporates Red blood cell Distribution Width (RDW) data and other demographic characteristics to predict ICU mortality alongside existing ICU mortality scoring systems like Simplified Acute Physiology Score (SAPS). The developed algorithm, defined as a Mixed-effects logistic Random Forest for binary data (MixRFb), integrates a Random Forest (RF) classification with a mixed-effects model for binary outcomes, accounting for repeated measurement data.
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