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Climate change is increasing the frequency and severity of short-term (~1 y) drought events-the most common duration of drought-globally. Yet the impact of this intensification of drought on ecosystem functioning remains poorly resolved. This is due in part to the widely disparate approaches ecologists have employed to study drought, variation in the severity and duration of drought studied, and differences among ecosystems in vegetation, edaphic and climatic attributes that can mediate drought impacts. To overcome these problems and better identify the factors that modulate drought responses, we used a coordinated distributed experiment to quantify the impact of short-term drought on grassland and shrubland ecosystems. With a standardized approach, we imposed ~a single year of drought at 100 sites on six continents. Here we show that loss of a foundational ecosystem function-aboveground net primary production (ANPP)-was 60% greater at sites that experienced statistically extreme drought (1-in-100-y event) vs. those sites where drought was nominal (historically more common) in magnitude (35% vs. 21%, respectively). This reduction in a key carbon cycle process with a single year of extreme drought greatly exceeds previously reported losses for grasslands and shrublands. Our global experiment also revealed high variability in drought response but that relative reductions in ANPP were greater in drier ecosystems and those with fewer plant species. Overall, our results demonstrate with unprecedented rigor that the global impacts of projected increases in drought severity have been significantly underestimated and that drier and less diverse sites are likely to be most vulnerable to extreme drought.

Lifelines are critical infrastructure systems characterized by a high level of interdependency that can lead to cascading failures after any disaster. Many approaches can be used to analyze infrastructural interdependencies, but they are usually not able to describe the sequence of events during emergencies. Therefore, interdependencies need to be modeled also taking into account the time effects. The methodology proposed in this paper is based on a modified version of the Input-output Inoperability Model and returns the probabilities of failure for each node of the system. Lifelines are modeled using graph theory, while perturbations, representing a natural or man-made disaster, are applied to the elements of the network following predetermined rules. The cascading effects among interdependent networks have been simulated using a spatial multilayer approach, while the use of an adjacency tensor allows to consider the temporal dimension and its effects. The method has been tested on a case study based on the 2011 Fukushima Dai-ichi nuclear disaster. Different configurations of the system have been analyzed and their probability of occurrence evaluated. Two models of the nuclear power plant have been developed to evaluate how different spatial scales and levels of detail affect the results.

En el contexto educativo, se ha estudiado extensamente el discurso enseñante clásico, o discurso vertical de docente a alumno. Sin embargo, en la actualidad, el aprendizaje colaborativo ha cobrado mayor relevancia. Inicialmente las investigaciones sobre aprendizaje colaborativo se centraban en explorar los resultados y efectos de la colaboración. No obstante, estudios posteriores identificaron la necesidad de analizar el proceso mismo del trabajo colaborativo. Sin embargo, el análisis metodológico presenta desafíos debido a su complejidad. En ese sentido, se han propuesto diversas metodologías, desde enfoques cualitativos (análisis de datos textuales) hasta enfoques sistemáticos basados en categorías analíticas (análisis de datos categorizados). Reconocer dichas metodologías resulta crucial para mejorar la comprensión y avanzar hacia herramientas analíticas más eficaces (Campbell, 2021; Leguizamón et al., 2020). Por tal motivo, el objetivo del presente artículo es realizar una revisión bibliográfica sobre las diferentes metodologías de análisis del discurso colaborativo a partir de la consideración de casos paradigmáticos, representativos de la variedad de enfoques metodológicos existentes. Para ello se realizó una revisión bibliográfica panorámica de los últimos 10 años en las bases de datos: SciELO, Redalyc, ERIC y Scopus. Se incluyeron estudios empíricos que analizaban interacciones verbales en contextos colaborativos, tanto presenciales como virtuales, sincrónicos y asincrónicos. Del total de artículos recuperados, en esta revisión se analizan ocho casos particulares, aquellos que pueden considerarse paradigmáticos de los tipos señalados. Los resultados obtenidos muestran una amplia variedad de metodologías disponibles para analizar el discurso colaborativo. Dicha diversidad metodológica no solo enriquece la investigación al proporcionar múltiples vías de abordaje, sino que también permite a los investigadores validar sus resultados utilizando diferentes métodos.

BackgroundAlcohol use disorder (AUD) is a leading preventable cause of morbidity and mortality, but relapse rates are high even with available treatments. Insomnia is a robust predictor of relapse and pilot studies have shown that CBT for insomnia improves insomnia and daytime functioning in adults with AUD and insomnia. The impact of CBT for insomnia on relapse, however, is unclear. This trial will compare telemedicine-delivered CBT for insomnia (CBT-TM) with sleep hygiene education (SHE-TM) on improving insomnia/sleep, daytime symptom, and drinking outcomes in treatment-seeking AUD adults with insomnia. The study will also determine the effects of treatment on sleep mechanisms and their association with clinical outcomes.MethodsThis is a single-site randomized controlled trial with planned enrollment of 150 adults meeting criteria for both AUD and chronic insomnia. Eligible participants will be randomized 1:1 to 6 sessions of telemedicine-delivered Cognitive Behavioral Therapy for Insomnia (CBT-TM) or Sleep Hygiene Education (SHE-TM) with clinical assessments conducted at pre-treatment, post- treatment, and at 3, 6, and 12 months post-treatment. Overnight polysomnography will be conducted before and after treatment. Primary clinical outcomes will include post-treatment scores on the Insomnia Severity Index and the General Fatigue subscale of the Multidisciplinary Fatigue Inventory, and the percent of days abstinent (PDA) on the interview-administered Time Line Follow Back. EEG delta activity, derived from overnight polysomnography, will be the primary endpoint to assess the sleep homeostasis mechanism.DiscussionThis adequately powered randomized controlled trial will provide clinically relevant information about whether targeting insomnia is effective for improving treatment outcomes among treatment-seeking adults with AUD. Additionally, the study will offer new scientific insights on the impact of an evidence-based non-medication treatment for insomnia on a candidate mechanism of sleep dysfunction in this population - sleep homeostasis.Trial registrationCClinicalTrials.gov NCT # 04457674 . Registered on 07 July 2020.

Background: Mechanical ventilation significantly improves patient survival but is associated with complications, increasing healthcare costs and morbidity. Identifying optimal weaning times is paramount to minimize these risks, yet current methods rely heavily on clinical judgment, lacking specificity. Methods: This study introduces a novel multiparametric predictive score, the MUSVIP (MUltiparametric Score for Ventilation discontinuation in Intensive care Patients), aimed at accurately predicting successful extubation. Conducted at Santo Stefano Hospital’s ICU, this single-center, observational, prospective cohort study will span over 12 months, enrolling adult patients undergoing invasive mechanical ventilation. The MUSVIP integrates variables measured before and during a spontaneous breathing trial (SBT) to formulate a predictive score. Results: Preliminary analyses suggest an Area Under the Curve (AUC) of 0.815 for the MUSVIP, indicating high predictive capacity. By systematically applying this score, we anticipate identifying patients likely to succeed in weaning earlier, potentially reducing ICU length of stay and associated healthcare costs. Conclusion: This study’s findings could significantly influence clinical practices, offering a robust, easy-to-use tool for optimizing weaning processes in ICUs.

ABSTRACTVerticillium wilt of olive (VWO), caused by Verticillium dahliae, is a major concern in many olive-growing countries. An efficient VWO control measure is the use of tolerant/resistant cultivars. Low information is available about olive secondary metabolites and its relationship with VWO tolerance. In this study, a comprehensive metabolic profiling of the roots of six olive cultivars differing in their level of tolerance/susceptibility to VWO was addressed. Potential changes in the metabolite profiles due to the presence of the pathogen were also assessed. A strong relationship between the quantitative basal composition of the root secondary metabolic profile and VWO tolerance/susceptibility of olive varieties was found. Tolerant cultivars showed higher content of secoiridoids, while the susceptible ones presented greater amounts of verbascoside and methoxypinoresinol glucoside. The presence of V. dahliae only caused few significant variations mostly restricted to the earliest times after inoculation. Thus, a rapid activation of biochemical-based root defense mechanisms was observed.Key policy highlights Quantitative differences of secondary metabolites in roots contribute to explain the tolerance/susceptibility of olive cultivars to Verticillium dahliae.Higher basal content of secoiridoids correlate with tolerance, while greater concentration of verbascoside and methoxypinoresinol glucoside seem to be linked to susceptibility.Few alterations are observed in the olive root metabolic profiles in the presence of the pathogen.Changes in the root metabolic profile occur at early times after pathogen inoculation which suggests a rapid activation of a biochemical-based defense response against V. dahliae.

The holobiont concept has revolutionized our understanding of plant-associated microbiomes and their significance for the development, fitness, growth and resilience of their host plants. The olive tree holds an iconic status within the Mediterranean Basin. Innovative changes introduced in olive cropping systems, driven by the increasing demand of its derived products, are not only modifying the traditional landscape of this relevant commodity but may also imply that either traditional or emerging stresses can affect it in ways yet to be thoroughly investigated. Incomplete information is currently available about the impact of abiotic and biotic pressures on the olive holobiont, what includes the specific features of its associated microbiome in relation to the host’s structural, chemical, genetic and physiological traits. This comprehensive review consolidates the existing knowledge about stress factors affecting olive cultivation and compiles the information available of the microbiota associated with different olive tissues and organs. We aim to offer, based on the existing evidence, an insightful perspective of diverse stressing factors that may disturb the structure, composition and network interactions of the olive-associated microbial communities, underscoring the importance to adopt a more holistic methodology. The identification of knowledge gaps emphasizes the need for multilevel research approaches and to consider the holobiont conceptual framework in future investigations. By doing so, more powerful tools to promote olive’s health, productivity and resilience can be envisaged. These tools may assist in the designing of more sustainable agronomic practices and novel breeding strategies to effectively face evolving environmental challenges and the growing demand of high quality food products.

Living Archives perform a function of social memory sharing, which contributes to building social bonds, communities, and identities. This potential lays in the ability of Living Archives to put together an archival function, which allows with the conservation and transmission of memory, with an artistic, performative and creative function linked to the present. As part of the DARE-UIA (Digital environment for colaborative alliances to regenerate urban ecosystem in middle-sized cities) project, the creation of a living digital archive made possible to create a narrative that would consolidate the cultural memory of the Darsena district of the city of Ravenna. The aim of the project is to stimulate the urban regeneration of a suburban area of a city, enhancing its cultural memory and identity heritage, through digital heritage tools. The methodology used involves various digital storytelling actions necessary for the overall narrative using georeferencing systems (GIS), storymaps and 3D reconstructions for a transversal narration of historical content such as personal and institutional historical photos and to enhance the industrial archeology heritage of the neighborhood. The aim is the creation of an interactive and replicable narrative in similar contexts to the Darsena district in Ravenna. The Living Archive, in which all the digital contents are inserted, finds its manifestation towards the outside with the form of a museum spread throughout the neighborhood, making the contents usable on smartphones via QR codes and totems inserted on-site, creating thematic itineraries spread around the neighborhood. The construction of an interactive and engaging digital narrative has made possible to enhance the material and immaterial heritage of the neighborhood by recreating the community that has historically always distinguished it.

Introduction: Biogenic fraction of airborne PM10 dominated by bacteria and fungi, has been recognized as serious environmental and human health issues in cities.Methods: In the present study, we combined a high-throughput amplicon sequencing of the bacterial 16S rRNA gene and the fungal internal transcribed spacer (ITS) region, with elemental analysis of airborne particulate matter (PM10) to investigate the community compositions and structures of PM10-associated bacteria and fungi across four different seasons in three urban sites of Rome with differential pollution rate.Results: In this study, а clear seasonal shift of bacterial and fungal community structure driven by PM10 mass concentrations and environmental factors, such as temperature and precipitations, has been identified. In addition, the seasonal impact of local sources and long-range transported air masses on the community structures of the microbes has been also postulated. Our data revealed that the lack of precipitation and the subsequent resuspension of dust produced by vehicular traffic might contribute to the maximum abundance of soil-associated microbes in winter and summer. However, the increase of PM10 concentrations favoured also by climatic conditions, domestic heating and dust advection event from African desert further shaped the community structure of winter. Across three seasons, the pollutant removal-hydrogen oxidation bacteria and the opportunist-human pathogenic fungi progressively increased with pollution levels, in the sequence from green to residential and/or polluted area close to the traffic roads, with highest fraction during winter.Discussion: Hence, our results highlight a close interrelationship between pollution, climatic factors and abundance of certain bacterial and fungal predicted functional groups also with potential implications for human health.

Una mirada de los artículos de revisión bibliográfica sobre el aprendizaje colaborativo a nivel universitario publicados en los últimos cinco años permite constatar una ausencia de análisis comparativo sistemático de criterios analíticos explícitos y exhaustivos que permitan ordenar dichos aportes. Precisamente, el objetivo del presente trabajo fue proponer un modelo analítico referencial que permita una clara sistematización del corpus de artículos recuperados en el periodo 2018-2022. Para cumplir con dicho objetivo, se realizó una búsqueda bibliográfica en las bases de datos SciELO, Redalyc, Eric y Dialnet. Se recuperaron 71 investigaciones. En la primera parte del manuscrito se analizó este corpus de investigaciones en función de los criterios analíticos construidos o variables. En la segunda parte, se analizaron de forma inclusiva las variables del modelo propuesto. En función de esta sistematización, se seleccionaron 12 artículos que pueden ser considerados paradigmáticos de dichas variables y modalidades clasificatorias. A modo de conclusión, el modelo analítico propuesto permitió detectar la diversidad existente en los artículos publicados en los últimos cinco años. A pesar de esta gran variedad de investigaciones, el ordenamiento de los artículos según criterios clasificadores posibilita dilucidar ciertos patrones. Se encontraron investigaciones que estudian las interacciones que se dan en el proceso de colaboración, ciertas condiciones bajo las cuales el aprendizaje colaborativo resulta más eficiente y la efectividad de determinadas estrategias para apoyar los procesos interaccionales, regulatorios y metacognitivos de los estudiantes.

This paper introduces a methodology to compensate inertial Micro-Electro-Mechanical System (IMU-MEMS) time-varying calibration loss, induced by stress and aging. The approach relies on a periodic assessment of the sensor through specific stimuli, producing outputs which are compared with the response of a high-precision sensor, used as ground truth. At any re-calibration iteration, differences with respect to the ground truth are approximated by quantization-aware trained tiny neural networks, allowing calibration-loss compensations. Due to the unavailability of aging IMU-MEMS datasets, a synthetic dataset has been produced, taking into account aging effects with both linear and nonlinear calibration loss. Also, field-collected data in conditions of thermal stress have been used. A model relying on Dense and 1D Convolution layers was devised and compensated for an average of 1.97 g and a variance of 1.07 g2, with only 903 represented with 16 bit parameters. The proposed model can be executed on an intelligent signal processing inertial sensor in 126.4 ms. This work represents a step forward toward in-sensor machine learning computing through integrating the computing capabilities into the sensor package that hosts the accelerometer and gyroscope sensing elements. [ABSTRACT FROM AUTHOR]

Rotator cuff tears are among the most common orthopaedic injuries. If not treated, they can result in a massive irreparable tear because of tendon retraction and muscle atrophy. Mihata et al. in 2012 described the technique of superior capsular reconstruction (SCR) using fascia lata autograft. This has been considered an acceptable and effective method for treating irreparable massive rotator cuff tears. We describe an arthroscopically assisted superior capsular reconstruction (ASCR) technique using all soft anchors to preserve the bone stock and reduce possible hardware complications. Moreover, knotless anchors for the lateral fixation make the technique easier to reproduce.

Burkitt's lymphoma (BL) is defined as a highly invasive B-cell lymphoma, usually characterized by an excellent prognosis, more than 90% of children and adolescents being cured with highly dose-intensive multiagent chemotherapy. Primary ovarian localization without involvement of other organs is a rare manifestation of BL, especially in pediatric population. Symptoms at diagnosis are similar to other ovarian lesions and differential diagnosis may be challenging for clinicians. A 12-year-old girl was referred to our institution for abdominal pain and palpable mass observed by the pediatrician. Diagnostic work-up demonstrated a large mass arising from the right ovary, causing compression on abdominal aorta, inferior vena cava, ureters and bowel, with a second smaller lesion on the left ovary. At surgery, a 15 cm-large, ruptured mass arising from the right ovary was found, associated with a second lesion originating from the left ovary (8 cm) and multiple nodules of the greater omentum. Right salpingo-oophorectomy was performed, incisional biopsies were taken from the left ovary and omental nodules and peritoneal fluid samples were collected for cytology. Pathology revealed a Burkitt lymphoma and the patient underwent chemotherapy according to AIEOP LNH-97 Protocol, group R3 with Rituximab. Preoperative diagnosis of primary ovarian lymphoma is extremely difficult. Surgical exploration is often necessary in patients presenting with acute abdominal or pelvic pain; when the suspicion of primary ovarian lymphoma arises intraoperatively, every effort should be made to minimize invasive procedure in order to enhance post-operative recovery.