Drones in Vegetable Crops: A Systematic Literature Review

In the context of increasing global population and climate change, modern agriculture must enhance production efficiency. Vegetables production is crucial for human nutrition and has a significant environmental impact. To address this challenge, the agricultural sector needs to modernize and utilize advanced technologies such as drones to increase productivity, improve quality, and reduce resource consumption. These devices, known as Unmanned Aerial Vehicles (UAV), with their agility and versatility play a crucial role in monitoring and spraying operations. They significantly contribute to enhancing the efficacy of precision farming. The aim of this review is to examine the critical role of drones as innovative tools to enhance management and yield of vegetable crops cultivation. This review was carried out using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) framework and involved the analysis of a wide range of research published from 2018 to 2023. According to the phases of Identification, Screening, and Eligibility, 132 papers were selected and analysed. These papers were categorized based on the types of drone applications in vegetable crop production, providing an overview of how these tools fit into the field of Precision Farming. Technological developments of these tools and data processing methods were then explored, examining the contributions of Machine and Deep Learning and Artificial Intelligence. Final considerations were presented regarding practical implementation and future technical and scientific challenges to fully harness the potential of drones in precision agriculture and vegetable crop production. The review pointed out the significance of drone applications in vegetable crops and the immense potential of these tools in enhancing cultivation efficiency. Drone utilization enables the reduction of input quantities such as herbicides, fertilizers, pesticides, and water but also the prevention of damages through early diagnosis of various stress types. These input savings can yield environmental benefits, positioning these technologies as potential solutions for the environmental sustainability of vegetable crops

Epidemiology of gastroenteropancreatic neuroendocrine neoplasms: a review and protocol presentation for bridging tumor registry data with the Italian association for neuroendocrine tumors (Itanet) national database

: Neuroendocrine neoplasms (NENs) are rare tumors with diverse clinical behaviors. Large databases like the Surveillance, Epidemiology, and End Results (SEER) program and national NEN registries have provided significant epidemiological knowledge, but they have limitations given the recent advancements in NEN diagnostics and treatments. For instance, newer imaging techniques and therapies have revolutionized NEN management, rendering older data less representative. Additionally, crucial parameters, like the Ki67 index, are missing from many databases. Acknowledging these gaps, the Italian Association for Neuroendocrine Tumors (Itanet) initiated a national multicenter prospective database in 2019, aiming to gather data on newly-diagnosed gastroenteropancreatic neuroendocrine (GEP) NENs. This observational study, coordinated by Itanet, includes patients from 37 Italian centers. The database, which is rigorously maintained and updated, focuses on diverse parameters including age, diagnostic techniques, tumor stage, treatments, and survival metrics. As of October 2023, data from 1,600 patients have been recorded, with an anticipation of reaching 3600 by the end of 2025. This study aims at understanding the epidemiology, clinical attributes, and treatment strategies for GEP-NENs in Italy, and to introduce the Itanet database project. Once comprehensive follow-up data will be acquired, the goal will be to discern predictors of treatment outcomes and disease prognosis. The Itanet database will offer an unparalleled, updated perspective on GEP-NENs, addressing the limitations of older databases and aiding in optimizing patient care. STUDY REGISTRATION: This protocol was registered in clinicaltriasl.gov (NCT04282083)

An adaptive Ritz formulation for progressive damage modelling in variable angle tow composite plates

In this work, an adaptive Ritz model for the analysis of variable angle tow composite plates featuring damage initiation and evolution under progressive loading is proposed, developed, implemented and tested. The plate kinematics is represented employing a first-order shear deformation theory, while the plate equilibrium equations at a given load step are obtained by minimizing the structure potential energy. The constitutive behaviour is modelled within the framework of continuum damage mechanics. In particular the initiation and evolution of damage, up to failure, are tracked by defining irreversible damage indices related to both fibres and matrix, both in tensile or compression loading. The discrete equations are then obtained by assuming a polynomial Ritz approximation of the primary kinematic variables in the energy minimization. Preliminary tests show how the application of the method as a single-domain approach induces the emergence of problematic spurious effects, related to Gibbs artefacts due to the inability of the selected polynomial basis to represent damage localization. An adaptive multi-domain technique is thus proposed to circumvent such issues, which has been successfully validated by benchmark tests. Eventually, original results about variable angle tow plates featuring damage evolution under progressive loading are presented

Model predictive control for multimode power-split hybrid electric vehicles: Parametric internal model with integrated mode switch and variable meshing losses

Model predictive control (MPC) is one of the most promising energy management strategies for hybrid electric vehicles. However, owing to constructive complexity, the multimode power-split powertrain requires dedicated mathematical tools to model the mode switch and transmission power losses within the internal model of the controller. Thus, the transmission losses are usually neglected and the mode switch is optimised through offline simulations. This paper proposes an MPC internal model relying on a parametric approach available in the literature, which provides a unique formulation for modelling any power-split transmission and assesses the transmission meshing losses. The objectives, which cover a gap in the literature, are: 1) to integrate the discrete problem of the mode switch in a continuous formulation of the internal model; 2) to compare MPC internal models with different complexity, and evaluate how the consideration of meshing losses and efficiency of the electric machines affect the controller performance. The results on a case study vehicle, i.e., the Chevrolet Volt, suggest that a simplified internal model deteriorates the fuel consumption performance by less than 2 %, while the integrated mode switch is comparable to the offline strategy

Aberrant DNA repair reveals a vulnerability in histone H3.3-mutant brain tumors

Pediatric high-grade gliomas (pHGG) are devastating and incurable brain tumors with recurrent mutations in histone H3.3. These mutations promote oncogenesis by dysregulating gene expression through alterations of histone modifications. We identify aberrant DNA repair as an independent mechanism, which fosters genome instability in H3.3 mutant pHGG, and opens new therapeutic options. The two most frequent H3.3 mutations in pHGG, K27M and G34R, drive aberrant repair of replication-associated damage by non-homologous end joining (NHEJ). Aberrant NHEJ is mediated by the DNA repair enzyme polynucleotide kinase 3 '-phosphatase (PNKP), which shows increased association with mutant H3.3 at damaged replication forks. PNKP sustains the proliferation of cells bearing H3.3 mutations, thus conferring a molecular vulnerability, specific to mutant cells, with potential for therapeutic targeting.Graphical Abstrac

Effectiveness and Safety of Biosimilars in Pediatric Non-infectious Uveitis: Real-Life Data from the International AIDA Network Uveitis Registry

IntroductionSince many biological drug patents have expired, biosimilar agents (BIOs) have been developed; however, there are still some reservations in their use, especially in childhood. The aim of the current study is to evaluate the efficacy and safety of tumor necrosis factor (TNF) inhibitors BIOs as treatment for pediatric non-infectious uveitis (NIU).MethodsData from pediatric patients with NIU treated with TNF inhibitors BIOs were drawn from the international AutoInflammatory Disease Alliance (AIDA) registries dedicated to uveitis and Behcet's disease. The effectiveness and safety of BIOs were assessed in terms of frequency of relapses, risk for developing ocular flares, best-corrected visual acuity (BCVA), glucocorticoids (GCs)-sparing effect, drug survival, frequency of ocular complications, and adverse drug event (AE).ResultsForty-seven patients (77 affected eyes) were enrolled. The BIOs employed were adalimumab (ADA) (89.4%), etanercept (ETA) (5.3%), and infliximab (IFX) (5.3%). The number of relapses 12 months prior to BIOs and at last follow-up was 282.14 and 52.43 per 100 patients/year. The relative risk of developing ocular flares before BIOs introduction compared to the period following the start of BIOs was 4.49 (95% confidence interval [CI] 3.38-5.98, p = 0.004). The number needed to treat (NNT) for ocular flares was 3.53. Median BCVA was maintained during the whole BIOs treatment (p = 0.92). A significant GCs-sparing effect was observed throughout the treatment period (p = 0.002). The estimated drug retention rate (DRR) at 12-, 24-, and 36-month follow-up were 92.7, 83.3, and 70.8%, respectively. The risk rate for developing structural ocular complications was 89.9/100 patients/year before starting BIOs and 12.7/100 patients/year during BIOs treatment, with a risk ratio of new ocular complications without BIOs of 7.1 (CI 3.4-14.9, p = 0.0003). Three minor AEs were reported.ConclusionsTNF inhibitors BIOs are effective in reducing the number of ocular uveitis relapses, preserving visual acuity, allowing a significant GCs-sparing effect, and preventing structural ocular complications.Trial RegistrationClinicalTrials.gov ID NCT05200715

The role of late adolescents' emotion regulation in the experience of COVID-19 lockdown: A longitudinal study

The COVID-19 pandemic may be considered a unique mass-trauma experience. This study examined the relations between Italian late adolescents' emotion regulation strategies, their anxiety states, and their experience of the lockdown (in terms of discomfort related to restrictions, capacities to create new functional daily routines, and to find positive changes in one's own life) during the first wave of this pandemic. We analysed how participants' reports of cognitive reappraisal and expressive suppression were associated with anxiety states during the 2020 Italian COVID-19 lockdown (large scale physical distancing and movement restrictions) and one month after the lockdown restrictions had been removed. We also examined how cognitive reappraisal, expressive suppression, and anxiety states were linked to late adolescents' experience of lockdown. The participants were 497 Italian adolescents, aged from 17 to 24 years (Mage  = 21.11, SD = 1.83). A longitudinal structural equation modelling showed that emotion regulation strategies and anxiety states were not associated across time. Cognitive reappraisal was positively associated with routine reorganization and positive changes. In contrast, participants' expressive suppression was negatively related to their discomfort related to restrictions, ability to functionally reorganise their daily routine, and ability to find positive changes related to the COVID-19 emergency. Anxiety was positively linked to discomfort related to restrictions. The findings are discussed in light of the current literature related to emotion regulation and anxiety. Limitations and implications for practice are presented

Economic Optimization of the Hydrogen Demand in a Hard-to-Abate Industrial Sector

Hydrogen is a zero-emission fuel that, if produced from renewable sources (so-called green hydrogen), can provide a significant contribution in the decarbonization of several sectors. The main drawback that still hinders its deployment is its high cost, as well as critical operational issues related to the entire supply chain, both for safety and efficiency reasons. Incentives and certification schemes are needed to support the green hydrogen. In this paper, with the aim to identify the green hydrogen supply chain and associated costs, an energy hub with electricity and hydrogen demands has been studied comparing the centralized green hydrogen production and distribution via trucks, against the installation of an on-site green hydrogen production plant made up of renewable power generation, an electricity storage system, and an electrolyzer. The problem was modeled and solved as a MILP optimization in MATLAB environment. Furthermore, a sensitivity analysis on the cost was carried out, which showed that even if the truck transportation cost for hydrogen is set at 0 a/kg, it is still more cost-effective to install an on-site electrolyzer to produce the required hydrogen