Nest box selection and reproduction of European Rollers in Central Italy: a 7-year study

Background: Changes and increased mechanisation of agricultural practices have influenced the biodiversity composition of farmland habitats and caused a decline of bird communities in many European countries. The removal of shrubs and large trees rich in natural cavities, has also led to a drastic decrease in nest site availability for cavity-nesting bird species. Nest-boxes are a common conservation tool used to improve nest-site availability, and have helped to reverse declines in many endangered bird populations. Nonetheless to maximize the results of such interventions it is crucial to know where nest-boxes should be sited. The objective of this study was to investigate the effectiveness of the nest-box program for the European Roller (Coracias garrulus) population of Lazio region (Central Italy). More specifically, we focused on what landscape features were preferred (or avoided) in the process of nest box selection and how they influenced population's breeding parameters. Particular attention was paid to identifying potential limitations and to provide management recommendations for future interventions. Methods: Using data from 70 nest boxes sited on power lines monitored over a 7-year period (representing 140 breeding attempts), we developed probability functions to evaluate if nest box location, in terms of distance from habitat resources and habitat composition and structure, had an effect on nest box occupancy and on the main reproductive parameters. Results: Nest boxes were more likely to be occupied if they were located near arable fields and in areas characterized by a higher amount of incoming solar radiation. Higher fledging success was associated with fallow fields and with a moderate/low habitat structural complexity. Higher breeding success was associated with solar radiation and with greater distance from urban areas. Conclusions: Our results highlight the importance of specific habitat variables in influencing nest occupancy, and show which drivers primarily affect species’ reproduction and persistence over time. Siting nest boxes in habitats where occupancy rate and fledging success is higher, such as in arable and fallow fields and on south-facing slopes where solar radiation is maximised, may help to extend the suitable habitat for rollers and facilitate its local expansion

Human protein C concentrates in adult septic patients

Some case reports and case series suggest that protein C concentrates may improve the outcome in patients with congenital or acquired protein C deficiency (not only in those with sepsis induced purpura fulminans). We reviewed the published literature on the use of protein C concentrates in adult septic patients and found that it is limited to less than 70 patients reported in observational studies with a 70% survival, and added our personal experience (two adult patients with sepsis and contraindications to recombinant activated protein C)

Scope and limitations of the TEMPO/EPR method for singlet oxygen detection: the misleading role of electron transfer

For many biological and biomedical studies, it is essential to detect the production of O-1(2) and quantify its production yield. Among the available methods, detection of the characteristic 1270-nm phosphorescence of singlet oxygen by time-resolved near-infrared (TRNIR) emission constitutes the most direct and unambiguous approach. An alternative indirect method is electron paramagnetic resonance (EPR) in combination with a singlet oxygen probe. This is based on the detection of the TEMPO free radical formed after oxidation of TEMP (2,2,6,6-tetramethylpiperidine) by singlet oxygen. Although the TEMPO/EPR method has been widely employed, it can produce misleading data. This is demonstrated by the present study, in which the quantum yields of singlet oxygen formation obtained by TRNIR emission and by the TEMPO/EPR method are compared for a set of well-known photosensitizers. The results reveal that the TEMPO/EPR method leads to significant overestimation of singlet oxygen yield when the singlet or triplet excited state of the photosensitizer is efficiently quenched by TEMP, acting as electron donor. In such case, generation of the TEMP+(center dot) radical cation, followed by deprotonation and reaction with molecular oxygen, gives rise to an EPR-detectable TEMPO signal that is not associated with singlet oxygen production. This knowledge is essential for an appropriate and error-free application of the TEMPO/EPR method in chemical, biological, and medical studies.The Spanish government (CTQ2012-32621, RyC-2007-00476, PFIS FI09/00312, Severo Ochoa Program SEV-2012-0267), the Carlos III Institute of Health (Grant RIRAAF, RETICS Program RD12/0013/0009), and the Generalitat Valenciana (Prometeo II/2013/005) are gratefully acknowledged for financial support. Dr. A. Vidal-Moya is acknowledged for his help with the EPR measurements.Nardi, G.; Manet, I.; Monti, S.; Miranda Alonso, MÁ.; Lhiaubet-Vallet, V. (2014). Scope and limitations of the TEMPO/EPR method for singlet oxygen detection: the misleading role of electron transfer. Free Radical Biology and Medicine. 77:64-70. https://doi.org/10.1016/j.freeradbiomed.2014.08.020S64707

AIDA: a tool for resiliency in smart manufacturing

One of the salient features of Industry 4.0 is that machines and other actors involved in the manufacturing process provide Industrial APIs that allow to inquire their status. In order to provide resilience, the manufacturing process should be able to automatically adapt to new conditions, considering new actors for the fulfillment of the manufacturing goals. As a single manufacturing process may include several of these actors, and their interfaces are often complex, this task cannot be easily accomplished in a completely manual way. In this work, we focus on the orchestration of Industrial APIs using Markov Decision Processes (MDPs). We present a tool implementing stochastic composition of processes and we demonstrate it in an Industry 4.0 scenario

Lockdown: How the COVID-19 Pandemic Affected the Fishing Activities in the Adriatic Sea (Central Mediterranean Sea)

The coronavirus disease 2019 (COVID-19) has brought a global socio-economic crisis to almost all sectors including the fishery. To limit the infection, governments adopted several containment measures. In Italy, Croatia, and Slovenia, a lockdown period was imposed from March to May 2020, during which many activities, including restaurants had to close or limit their business. All of this caused a strong reduction in seafood requests and consequently, a decrease in fishing activities. The aim of this study is to investigate the effects of the COVID-19 in the Northern and Central Adriatic fleet, by comparing the fishing activities in three periods (before, during, and after the lockdown) of 2019 and 2020. The use of the Automatic Identification System(AIS) data allowed us to highlight the redistribution of the fishing grounds of the trawlers, mainly located near the coasts during the 2020 lockdown period, as well as a reduction of about 50% of fishing effort. This reduction resulted higher for the Chioggia trawlers (−80%) and, in terms of fishing effort decrease, the large bottom otter trawl was the fishing segment mainly affected by the COVID-19 event. Moreover, by analysing the landings of the Chioggia fleet and the Venice lagoon fleets, it was possible to point out a strong reduction both in landings and profits ranging from −30%, for the small-scale fishery operating at sea, to −85%, for the small bottom otter trawl

A Comparative Evaluation of Deep Learning Techniques for Photovoltaic Panel Detection From Aerial Images

Solar energy production has significantly increased in recent years in the European Union (EU), accounting for 12% of the total in 2022. The growth in solar energy production can be attributed to the increasing adoption of solar photovoltaic (PV) panels, which have become cost-effective and efficient means of energy production, supported by government policies and incentives. The maturity of solar technologies has also led to a decrease in the cost of solar energy, making it more competitive with other energy sources. As a result, there is a growing need for efficient methods for detecting and mapping the locations of PV panels. Automated detection can in fact save time and resources compared to manual inspection. Moreover, the resulting information can also be used by governments, environmental agencies and other companies to track the adoption of renewable sources or to optimize energy distribution across the grid. However, building effective models to support the automated detection and mapping of solar photovoltaic (PV) panels presents several challenges, including the availability of high-resolution aerial imagery and high-quality, manually-verified labels and annotations. In this study, we address these challenges by first constructing a dataset of PV panels using very-high-resolution (VHR) aerial imagery, specifically focusing on the region of Piedmont in Italy. The dataset comprises 105 large-scale images, providing more than 9,000 accurate and detailed manual annotations, including additional attributes such as the PV panel category. We first conduct a comprehensive evaluation benchmark on the newly constructed dataset, adopting various well-established deep-learning techniques. Specifically, we experiment with instance and semantic segmentation approaches, such as Rotated Faster RCNN and Unet, comparing strengths and weaknesses on the task at hand. Second, we apply ad-hoc modifications to address the specific issues of this task, such as the wide range of scales of the installations and the sparsity of the annotations, considerably improving upon the baseline results. Last, we introduce a robust and efficient post-processing polygonization algorithm that is tailored to PV panels. This algorithm converts the rough raster predictions into cleaner and more precise polygons for practical use. Our benchmark evaluation shows that both semantic and instance segmentation techniques can be effective for detecting and mapping PV panels. Instance segmentation techniques are well-suited for estimating the localization of panels, while semantic solutions excel at surface delineation. We also demonstrate the effectiveness of our ad-hoc solutions and post-processing algorithm, which can provide an improvement up to +10% on the final scores, and can accurately convert coarse raster predictions into usable polygons

Vita della serva di Dio svor Giovanna Maria della Santissima Trinita : monaca carmelitana scalza del Monastere delle Sante Anna e Teresa ...

Copia digital : Junta de Castilla y León. Consejería de Cultura y Turismo, 2014Sign.: [cruz griega]4, 2 [cruz griega]4, A-Z4, 2A-2Z4, 3A-3F4

Human protein C concentrate in pediatric septic patients

Severe sepsis and septic shock are leading causes of morbidity and mortality in the pediatric population. Unlike what is suggested for the adult population, recombinant human activated protein C (rhAPC) is contraindicated in children. Long before rhAPC was considered for use in pediatric patients, case reports appeared on the safe administration of protein C zymogen. Therefore, we conducted a systemic review of currently available data on protein C zymogen (PC) use among children affected by severe sepsis or septic shock. A total number of 13 case series or case reports and a dose-finding study were found on the use of PC in the pediatric intensive care unit, reporting on 118 treated children, with an overall survival of 84%. There was no bleeding complication, the only reported complication being a single mild allergic reaction. These studies show that PC is safe, not associated with bleeding and possibly useful for improving coagulation abnormalities of sepsis

Decreasing mortality with drotrecogin alfa in high risk septic patients A meta-analysis of randomized trials in adult patients with multiple organ failure and mortality >40%

Objective. Sepsis is a complex inflammatory disease, rising in response to infection. Drotrecogin alfa, approved in 2001 for severe sepsis, has been withdrawn from the market. The aim of this study was to assess if drotrecogin alfa-activated can reduce mortality in the more severe septic patients. Methods. We searched PubMed, Embase, Scopus, BioMedCentral, and in Clinicaltrials. gov databases to identify every randomized study performed on drotrecogin alfa-activated in any clinical setting in humans, without restrictions on dose or time of administration. Our primary end-point was mortality rate in high risk patients. Secondary endpoints were mortality in all patients, in patients with an Acute Physiology and Chronic Health Evaluation (APACHE) 2 score ≥ 25 and in those with an APACHE 2 score ≤25. Results. Five trials were identified and included in the analysis. They randomized 3196 patients to drotrecogin alfa and 3111 to the control group. Drotrecogin alfa was associated with a reduction in mortality (99/263 [37.6%] vs 115/244 [47.1%], risk ratios (RR) = 0.80[0.65; 0.98], p = 0.03) in patients with multiple organ failure and a mortality risk in the control group of >40%, but not in the overall population or in lower risk populations. Conclusions. In high risk populations of patients with multiple organ failure and a mortality of >40% in the control group, Drotrecogin alfa may still have a role as a lifesaving treatment. No beneficial effect in low risk patients was found. An individual patient meta-analysis including all randomized controlled trial on sepsis is warranted, along with new studies on similar drugs such as protein C zymogen