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A review of Mesozoic geodynamic evolution of the North Makran (SE Iran): A tale of a Neo-Tethyan ocean vanished due to two coexisting subduction zones
No full textThis paper presents a synthesis of the geological features of each tectonic unit of the North Makran (SE Iran), integrating results of multidisciplinary analyses, including structural and stratigraphic studies, petrographic and geochemical analyses, thermobarometric studies, as well as biostratigraphic and geochronological dating. This wealth of data forms the basis for a novel geodynamic model of the Jurassic - Eocene evolution of the NeoTethys realm, which evolved between the Arabian Plate and the Lut Block. The features of the North Makran tectonic units support the existence of a mid-ocean ridge setting during the Jurassic - Early Cretaceous. Contrary to previous interpretations, the data from these tectonic units suggests a single oceanic basin separating the Arabian and Lut continental margins, without the interposition of a microcontinental block. In the Early Cretaceous, subduction initiation is recorded by volcanic arc assemblages accommodating the convergence between the Arabian Plate and Lut Block. The nucleation of an intra-oceanic subduction marked the separation of the North Makran Ocean from the Neo-Tethys. The Late Cretaceous was characterized by plume-related magmatism and the onset of the convergence in the North Makran Ocean, inducing its subduction beneath the Lut Block. This subduction is recorded by volcanic arc assemblage and high pressure and low-temperature metamorphism within a subduction complex. Meanwhile, intra-oceanic subduction persisted within the Neo-Tethys, accompanied by a subduction complex and arc magmatism. The final closure of the North Makran Ocean occurred during the Late Cretaceous -Late Paleocene with the progressive amalgamation of the two subduction complexes and the deformation of the interposing oceanic lithosphere. This study suggests that the subduction of a seamount chain in the North Makran Ocean played a key role in the shortening and closure of this basin. This research emphasizes the importance of considering multiple factors in understanding the tectonic evolution of the Neo-Tethys realm
Patients with coronavirus disease 2019 and spontaneous pneumothorax: a propensity-matched, multicentre case-control study
No full textOBJECTIVES: Pneumothorax and pneumomediastinum have been frequently reported in coronavirus disease-19 (COVID-19), thus complicating the patient’s overall health-care management and survival rate. The goal of this study was to evaluate the outcomes of patients with COVID-19 who developed spontaneous pneumothorax (SPN) or spontaneous pneumomediastinum (SPM). METHODS: In this Italian multicentre retrospective cohort study, medical records of non-vaccinated COVID-19 patients, from March 2020 to May 2021, were analysed. To reduce the risk of bias due to unbalanced groups, a propensity score matching approach was applied using logistic regression to estimate propensity scores. Separate multivariable generalized linear models were then used to assess the risk of in-hospital death and other outcomes. RESULTS: A total of 474 patients were assessed, 72 of whom developed SPN or SPM. In separate multivariable generalized linear model regression analyses of the unmatched cohort, SPN [odds ratio (OR) 2.44, 95% confidence interval (CI) 1.7–5.55; P = 0.031] was associated with an increase in the in-hospital death rate, results confirmed even after matching the 2 cohorts. SPM (OR 1.21, 95% CI 1.13–1.30, P < 0.001) and SPN (OR 1.34, 95% CI 1.26–1.43, P < 0.001) were associated with an increase in the length of hospital stay. The risk of in-hospital death also increased with age, comorbidities (classified by the Charlson comorbidity index) and smoking habits. CONCLUSIONS: SPN in hospitalized COVID-19 patients may be associated with an increased risk of in-hospital death and prolonged hospitalization
PLAnt-based antiMIcrobial aNd circular PACKaging for plant products
No full textIn the Mediterranean area, a wide variety of fruits are produced, generating considerable amounts of waste and by-products along the entire supply chain. This represents both an environmental challenge and a valuable resource for bioactive molecules and bio-based materials. Therefore, it is essential to enhance the efficiency of the entire food chain and promote new valorization strategies through extraction, composite production, and bioconversion. The resulting products can be utilized in various fields, such as the packaging sector, offering an alternative to fossil-based products1. The PLAMINPACK project, funded by national research entities under the PRIMA program, aims to develop scalable bio-based compostable packaging materials (e.g., films, nets, and trays) derived from plant sources to prevent food spoilage and offer an alternative to commercial fossil-based packaging materials. Representative agricultural waste from fruit trees selected for this ongoing project includes those producing strawberries, tangerines, and dates plants (Figure). Interestingly, the fruits to be tested are strawberries, dates, and tangerines, ensuring a fully circular approach. Biocircular approach of PLAMINPACK project: The project involves an extended consortium consisting of nine partners from six different countries: Italy, Morocco, Germany, Greece, Tunisia, and France. Coatings based on chitosan obtained from insects and substrates based on bio-based polyesters are the polymeric materials investigated in the project
Exploration of the covariation signal between cortical bone and dentine volumes across the upper limb bones and anterior teeth in modern humans and relevance to evolutionary anthropology
No full textCortical bone and dentine are two mineralized tissues sharing a common embryological origin, developmental, and genetic background, distinct from those of enamel. Understanding their relationship is crucial to decipher the factors acting on their postnatal development, and shedding light on the evolutionary patterns of tissue proportions. Here, we investigate the coordinated variation between cortical bone and dentine volumes measured from arm and forearm bones (humeri, ulnae, radii) and upper anterior teeth (central incisors, lateral incisors, canines) of modern humans. Given the shared characteristics of cortical bone and dentine, we expect similarities in their postnatal development, which may lead to covariation between their volumes. The degree of bone-dentine covariation may be influenced by the physiological response of upper limb bones to mechanical loading. No such covariation is expected with enamel volumes, due to the greater developmental independence of bone and enamel. Our sample includes 55 adults of African and European ancestries from South African osteological collections. Principal component analysis of cortical thickness variation along the shafts of paired humeri, ulnae, and radii is used to assess asymmetry. Bone regions with bilateral asymmetry in cortical bone thickness are considered sensitive to functional loads, while regions with minimal bilateral variation likely reflect genetic influences during bone postnatal development. Statistical analyses reveal strong positive correlations between cortical bone and dentine volumes across all bones and teeth, and weaker correlations between cortical bone and enamel. We outline a complex pattern of bone-dentine covariation that varies by skeletal location and tooth type. Contrary to our expectations, the presumed functional sensitivity of bone regions does not influence the covariation signal. Additionally, the strength of the covariation appears to align with the developmental sequence of the anterior teeth, with the upper canines showing the strongest correlation with cortical bone volumes, followed by lateral and central incisors. These results provide insights into the functional and biological factors influencing the coordinated variation of cortical bone and dentine volumes during postnatal development. Further research on the cortical bone-dentine covariation across different skeletal parts, including lower limb elements, would enhance our understanding of the effects of both endogenous and exogenous factors on the development of the mineralized tissues
Survey experiences of city walls of Alessandria and Lucca: an overview
No full textIn military architecture, the city wall between towers or bastions have architectural-structural characteristics related to the defensive and offensive systems used. Such systems are boundaries of fortified cities at urban scale and differ in shape and size, structure, style, layering of techniques, and territorial relationship to the city. These distinctive elements may include tunnels built to facilitate the passage of people and armaments through networks of passages within the walls. In addition, given the
urban scale of city fortifications, they present a peculiar relationship with neighbouring vegetation. This latter requires ongoing control and maintenance to avoiding pervasive vegetation harmful to the wall's preservation and visibility. These artefacts are complex subjects to study through digital survey techniques, given their size, articulation and urban contextualisation. Integrating active and passive methodologies makes it possible to control these architectural structures' morphological complexity and scale variation while preserving their detail and overall accuracy. Within the PRIN 2022 INFORTREAT
project, we had the opportunity to survey portions of two different case studies: the walls of the citadel of Alessandria and the walls of Lucca. Each case study presented its own set of challenges in the 3D acquisition process, which we overcame through the application of established surveying processes. The initial comparison of the surveys underscores the significance of employing methodologies that incorporate metric control to ensure the reliability of data on these architectural systems. Another key
aspect pertains to the knowledge derived from these surveys, which deepens our understanding of the different building systems and lays the groundwork for a comparison with the principles outlined in military treatises. Furthermore, the optimisation of these surveys provides a foundation for the modelling of forms using parametric tool
Psychometric Evaluation of the Validity and Reliability of the Italian Version of the London Measure of Unplanned Pregnancy Amongst Postnatal Women
No full textBackground: Unplanned pregnancy is a public health issue and understanding women’s decision making aids practitioners in assessing fertility trends, contraception use, and family planning counselling. In Italy, Catholicism reinforces ‘natural reproduction’ and ‘traditional’ contraception, making it an ‘Imperfect Contraceptive Society.’ A valid and reliable measure of pregnancy intentionality is increasingly important, and the London Measure of Unplanned Pregnancy (LMUP) has proved effective. Objectives and Methods: This study comprised four stages: (1) English–Italian translation and back-translation to create the Italian version [LMUP-IT]; (2) online data collection from postnatal women; (3) evaluation of its psychometric properties (targeting, reliability, construct validity via CFA and measurement invariance with a UK sample, ‘known groups’ hypothesis testing); and (4) exploratory analysis of its associations with perinatal mental health. The sample comprised 450 postnatal women (Mage = 33.6 ± 4.5). Results: The LMUP-IT was shown to be reliable (ωT = 0.81, α = 0.76), with acceptable targeting. Measurement invariance testing confirmed consistency with the UK sample in factor structure, loadings, intercepts, and errors. LMUP-IT scores significantly correlated with well-known indicators of perinatal mental health. Conclusions: Overall, the LMUP-IT is a reliable measure of pregnancy intention in Italian for postpartum women. Understanding pregnancy intention will help healthcare professionals tailor interventions to better support women’s mental health during the transition to motherhood
Raffaello Bartelletti: un ingegnere romantico
No full textDefinire un ingegnere romantico piuttosto che positivista o empirista potrebbe sembrare una contraddizione in termini, dato che questi ultimi atteggiamenti sono tradizionalmente considerati più vicini alla scienza e alla tecnica. Tuttavia, ogni persona, al di là della fase storica e delle mode, è pur sempre una combinazione più o meno bilanciata di tendenze e inclinazioni, talvolta contrapposte. È così potuto accadere che per Raffaello Bartelletti l’appellativo di romantico abbia trovato tra noi autori un comune istintivo consenso, confermato successivamente nel corso della descrizione delle sue opere, in cui ci affioravano i ricordi del suo approccio metodologico, ma anche emotivo, e dei significati da lui riposti in ognuna di esse.
Per recuperare la memoria di fatti e situazioni con l’acquisizione della necessaria documentazione ci siamo avvalsi del prezioso supporto di quanti proseguono l’attività dello Studio Bartelletti e, in particolare, di Marco Pascucci che, più veterano tra i collaboratori e oggi custode dell’eredità professionale di Bartelletti, ci ha guidato nella raccolta e nell’elaborazione del materiale e delle informazioni essenziali.
Al termine di questo percorso, rievocazione sia tecnica sia di esperienza umana, siamo ancora più convinti che “ingegnere romantico” non sia semplicemente una definizione appropriata, ma la più autentica rappresentazione dell’essenza di Raffaello Bartelletti, un professionista il cui spirito e la cui visione rappresentano le prerogative di una figura per noi straordinaria e unica
Reinforcement Learning-Driven Digital Twin for Zero-Delay Communication in Smart Greenhouse Robotics
No full textThis study presents a networked cyber-physical architecture that integrates a Reinforcement Learning-based Digital Twin (DT) to enable zero-delay interaction between physical and digital components in smart agriculture. The proposed system allows real-time remote control of a robotic arm inside a hydroponic greenhouse, using a sensor-equipped Wearable Glove (SWG) for hand motion capture. The DT operates in three coordinated modes: Real2Digital, Digital2Real, and Digital2Digital, supporting bidirectional synchronization and predictive simulation. A core innovation lies in the use of a Reinforcement Learning model to anticipate hand motions, thereby compensating for network latency and enhancing the responsiveness of the virtual–physical interaction. The architecture was experimentally validated through a detailed communication delay analysis, covering sensing, data processing, network transmission, and 3D rendering. While results confirm the system’s effectiveness under typical conditions, performance may vary under unstable network scenarios. This work represents a promising step toward real-time adaptive DTs in complex smart greenhouse environments
Contrastive Dimension Importance Estimation with Pseudo-Irrelevance Feedback for Dense Retrieval
No full textRecent advances in Information Retrieval have leveraged high-dimensional embedding spaces to improve the retrieval of relevant documents. Moreover, the Manifold Clustering Hypothesis suggests that despite these high-dimensional representations, documents relevant to a query reside on a lower-dimensional, query-dependent manifold. While this hypothesis has inspired new retrieval methods, existing approaches still face challenges in effectively separating non-relevant information from relevant signals. We propose a novel methodology that addresses these limitations by leveraging information from both relevant and non-relevant documents. Our method, Eclipse, computes a centroid based on irrelevant documents as a reference to estimate noisy dimensions present in relevant ones, enhancing retrieval performance. Extensive experiments on three in-domain and one out-of-domain benchmarks demonstrate an average improvement of up to 21.03% (resp. 22.88%) in mAP(AP) and 12.04% (resp. 14.18%) in nDCG@10 w.r.t. the DIME-based baseline (resp. the baseline using all dimensions). Our results pave the way for more robust, pseudo-irrelevance-based retrieval systems in future IR research
Mask-RadarNet: Enhancing Radar Object Detection With Spatio-Temporal Context
No full textAs a cost-effective and robust technology, automotive radar has seen steady improvement during the last years. Radio frequency (RF) images, serving as a radar data format with rich semantic information, have attracted considerable interest in radar object detection. Previous RF-based models heavily rely on convolutional neural networks, leading to the high computational cost. To solve this problem, we propose a model called Mask-RadarNet to fully utilize the hierarchical semantic features from the RF image sequences. Mask-RadarNet exploits the combination of interleaved convolution and attention operations in the encoder. In addition, patch shift is introduced to Mask-RadarNet for efficient spatial-temporal feature learning. By shifting part of patches with a specific mosaic pattern in the temporal dimension, Mask-RadarNet achieves competitive performance while reducing the computational burden of the spatial-temporal modeling. In order to capture the spatial-temporal semantic contextual information, we design the class masking attention module (CMAM) in our encoder. Moreover, a lightweight auxiliary decoder is added to our model to aggregate prior maps generated from the CMAM. Experiments on the CRUW dataset demonstrate that the proposed Mask-RadarNet achieves state-of-the-art performance with relatively lower computational complexity and fewer parameters