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This chapter analyzes the conjuncture of three events, originated in business efficiency, that have led to greater potential weaknesses of critical information infrastructures (CII). Modern societies depend on assets called “critical infrastructures”, which include financial services, energy, transportation, telecommunications, water supply, medical services, public administration, and so on. When these systems and utilities are operated, managed and/or controlled via computer networks, they become critical information infrastructures. The first event was the “internetization” of data-gathering and remote management of industrial control systems (ICS/SCADA) allowed businesses world wide to cut personnel costs and reduce time management. The second was the “privatization wave” of the 1980s, when, following the example of the United States, utilities were privatized in Europe and elsewhere, under the conviction that the private sector could be more efficient in delivering the same services. Finally, the emergence of transnational public–private partnerships (PPP) in the ownership, accountability, and governance of utilities and critical infrastructures further enlarged the sectors of CII and magnify the inherent vulnerabilities brought about by the “privatization wave”. In the end, the decision to “go private” for public utilities as CII hardly took into account what consequences such move could have had in terms of cybersecurity.

The chapter introduces how changes in advanced technology deeply affect international politics, this book theoretically engages with the overriding relevance of investments in technological research, and the ways in which they directly foster a country’s economic and military standing. The scholars and practitioners in the volume present important insights on the technical and social issues at the core of technology competition. The Introduction to Technology and International Relations emphasizes the importance of leadership styles, domestic political agendas and the relative weight of technologically driven countries in global affairs. It highlights the now widely shared belief among both developed and developing countries that technology will be the defining factor in international politics. The book also unpacks the complexity of real-life cases of key technological advances, including artificial intelligence, UAVs, satellites and the responses of governments and the private sector to rising technological challenges.

Gastroesophageal reflux disease (GERD) is a common digestive disorder that causes esophagitis and injuries to the esophageal mucosa. GERD symptoms are recurrent during pregnancy and their treatment is focused on lifestyle changes and nonprescription medicines. The aim of this study was to characterize the mechanism of action of a new patented medical device, an oral formulation containing hyaluronic acid, rice extract, and amino acids dispersed in a bioadhesive polymer matrix, by assessing its protective effects in in vitro and ex vivo models of esophageal mucosa damage. Acidic bile salts and pepsin cocktail (BSC) added to CP-A and COLO-680 N esophagus cells were used as an in vitro GERD model to evaluate the binding capacities, anti-inflammatory effects and reparative properties of the investigational product (IP) in comparison to a viscous control. Our results showed that the IP prevents cell permeability and tight junction dysfunction induced by BSC. Furthermore, the IP was also able to down-regulate IL-6 and IL-8 mRNA expression induced by BSC stimulation and to promote tissue repair and wound healing. The results were confirmed by ex vivo experiments in excised rat esophagi through the quantification of Evans Blue permeability assay. These experiments provided evidence that the IP is able to bind to the human esophagus cells, preventing the damage caused by gastroesophageal reflux, showing potential anti-irritative, soothing, and reparative properties.

With growing populations and pressing environmental problems, future economies will be increasingly plant-based. Now is the time to reimagine plant science as a critical component of fundamental science, agriculture, environmental stewardship, energy, technology and healthcare. This effort requires a conceptual and technological framework to identify and map all cell types, and to comprehensively annotate the localization and organization of molecules at cellular and tissue levels. This framework, called the Plant Cell Atlas (PCA), will be critical for understanding and engineering plant development, physiology and environmental responses. A workshop was convened to discuss the purpose and utility of such an initiative, resulting in a roadmap that acknowledges the current knowledge gaps and technical challenges, and underscores how the PCA initiative can help to overcome them., National Science Foundation 1916797 David W Ehrhardt, Kenneth D Birnbaum, Seung Yon Rhee; National Science Foundation 2052590 Seung Yon Rhee

Aging is a biological process determined by multiple cellular mechanisms, such as genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication, that ultimately concur in the functional decline of the individual. The evidence that the old population is steadily increasing and will triplicate in the next 50 years, together with the fact the elderlies are more prone to develop pathologies such as cancer, diabetes, and degenerative disorders, stimulates an important effort in finding specific countermeasures. Calorie restriction (CR) has been demonstrated to modulate nutrient sensing mechanisms, inducing a better metabolic profile, enhanced stress resistance, reduced oxidative stress, and improved inflammatory response. Therefore, CR and CR-mimetics have been suggested as powerful means to slow aging and extend healthy life-span in experimental models and humans. Taking into consideration the difficulties and ethical issues in performing aging research and testing anti-aging interventions in humans, researchers initially need to work with experimental models. The present review reports the major experimental models utilized in the study of CR and CR-mimetics, highlighting their application in the laboratory routine, and their translation to human research.

Disarmament and non-proliferation education is a key tool in curbing the spread of nuclear weapons, with a view to their elimination. This article examines the remarkable story of the International School on Disarmament and Research on Conflicts (ISODARCO) on the occasion of its fiftieth anniversary of continuous engagement in educational and training activities. ISODARCO offers a unique forum where nuclear experts from different backgrounds and approaches can meet, debate, and promote action as a transnational knowledge-based network of experts and, equally important, pass on their expertise to the ‘next generation of non-proliferation specialists’. The contribution of this small Italian NGO is indeed noteworthy, highly praised at the national and especially international level, and worth the attention of an audience broader than just non-proliferation and security experts.

Corporatisation of critical information infrastructure (CII) is rooted inthe ‘privatisation wave’ of the 1980s-90s, when the ground was laidfor outsourcing public utilities. Despite well-known risks relating toreliability, resilience, and accountability, commitment to efficiencyimperatives have driven governments to outsource key publicservices and infrastructures. A recent illustrative case with enormousimplications is the 2017 Swedish ICT scandal, where outsourcing ofCII caused major security breaches. With the transfer of the SwedishTransport Agency’s ICT system to IBM and subcontractors, classifieddata and protected identities were made accessible to non-vettedforeign private employees – sensitive data could thus now be inanyone’s hands. This case clearly demonstrates accountability gapsthat can arise in public-private governance of CII. QC 20220228

Computationally driven engineering of proteins aims to allow them to withstand an extended range of conditions and to mediate modified or novel functions. Therefore, it is crucial to the biotechnological industry, to biomedicine and to afford new challenges in environmental sciences, such as biocatalysis for green chemistry and bioremediation. In order to achieve these goals, it is important to clarify molecular mechanisms underlying proteins stability and modulating their interactions. So far, much attention has been given to hydrophobic and polar packing interactions and stability of the protein core. In contrast, the role of electrostatics and, in particular, of surface interactions has received less attention. However, electrostatics plays a pivotal role along the whole life cycle of a protein, since early folding steps to maturation, and it is involved in the regulation of protein localization and interactions with other cellular or artificial molecules. Short- and long-range electrostatic interactions, together with other forces, provide essential guidance cues in molecular and macromolecular assembly. We report here on methods for computing protein electrostatics and for individual or comparative analysis able to sort proteins by electrostatic similarity. Then, we provide examples of electrostatic analysis and fingerprints in natural protein evolution and in biotechnological design, in fields as diverse as biocatalysis, antibody and nanobody engineering, drug design and delivery, molecular virology, nanotechnology and regenerative medicine.

Chest X-ray (CXR) is perhaps the most frequently-performed radiological investigation globally. In this work, we present and study several machine learning approaches to develop automated CXR diagnostic models. In particular, we trained several Convolutional Neural Networks (CNN) on the CheXpert dataset, a large collection of more than 200k CXR labeled images. Then, we used the trained CNNs to compute embeddings of the CXR images, in order to train two sets of tree-based classifiers from them. Finally, we described and compared three ensembling strategies to combine together the classifiers trained. Rather than expecting some performance-wise benefits, our goal in this work is showing that the above two methodologies, i.e., the extraction of image embeddings and models ensembling, can be effective and viable to solve tasks that require medical imaging understanding. Our results in that perspective are encouraging and worthy of further investigation., Comment: Accepted at IJCNN 2021

Background Recently many serological assays for detection of antibodies to SARS-COV-2 virus were introduced on the market. Aim of this study was to assess the diagnostic performance of an automated CLIA for quantitative detection of anti-SARS-CoV-2 IgM and IgG antibodies. Methods A total of 354 sera, 89 from consecutive patients diagnosed with COVID-19 (43 mild, 32 severe and 13 critical) and 265 from asymptomatic and negative on rRT-PCR testing healthcare workers, were evaluated for IgM and IgG anti-SARS-CoV-2 antibodies with MAGLUMI immunoassay. Results The overall sensitivity and specificity were 86.5% (95%CI: 77.6–92.8) and 98.5% (95%CI:96.2–99.6), respectively. PPV, PPN, LR+, LR- and OR were 95.1 (95%CI: 87.8–98.6), 95.6 (95%CI: 92.4–97.7), 57.3 (95%CI: 21.6–152.1), 7.3 (95%CI: 4.31–12.4) and 418.6 (95%CI: 131.2–1335.2), respectively. The levels of SARS-CoV-2 IgM and IgG antibodies were 1.22 ​± ​1.2 AU/mL and 15.86 ​± ​24.83 AU/mL, 2.86 ​± ​2.4 AU/mL and 69.3 ​± ​55.5 AU/mL, 2.47 ​± ​1.33 AU/mL and 83.9 ​± ​83.9 AU/mL in mild, severe and critical COVID-19 groups, respectively. A significant difference in antibody levels between mild and severe/critical subjects has been shown. Conclusions The CLIA assay showed good diagnostic performance and a significant association between antibody levels and severity of the disease was found.

Essentials Between-lab variations of cut-off values in lupus anticoagulant detection are unknown. Cut-off values were calculated in 11 labs each testing plasma from 120 donors with 3 platforms. Major variation was observed even within the same platform. Cut-off values determined in different labs are not interchangeable. SummaryBackground Cut-off values for interpretation of lupus anticoagulant (LA) detection are poorly investigated. Aims (i) To assess whether results from healthy donors were normally distributed and (ii) the between-laboratories differences in cut-off values for screening, mixing and LA confirmation when calculated as 99th or 95th centiles, and (iii) to assess their impact on the detection rate for LA. Methods Each of 11 laboratories using one of the three widely used commercial platforms for LA detection was asked to collect plasmas from 120 healthy donors and to perform screening, mixing and LA confirmation with two methods (activated partial thromboplastin time [APTT] and dilute Russell viper venom [dRVV]). A common set of LA-positive or LA-negative freeze-dried plasmas was used to assess the LA detection rate. Results were centralized (Milano) for statistical analysis. Results and conclusions (i) Clotting times or ratios for healthy subjects were not normally distributed in the majority of cases. The take-home message is that cut-off values should be determined preferably by the non-parametric method based on centiles. (ii) There were relatively large inter-laboratory cut-off variations even within the same platform and the variability was marginally attenuated when results were expressed as ratios (test-to-normal pooled plasma). The take-home message is that cut-off values should be determined locally. (iii) There were differences between cut-off values calculated as 99th or 95th centiles that translate into a different LA detection rate (the lower the centile the greater the detection rate). The take-home message is that cut-off values determined as the 95th centile allow a better LA detection rate.

In an increasingly technology-dependent world, it is not surprising that STEM (Science, Technology, Engineering, and Mathematics) graduates are in high demand. This state of affairs, however, has made the public overlook the case that not only computing and artificial intelligence are naturally interdisciplinary, but that a huge portion of generated data comes from human–computer interactions, thus they are social in character and nature. Hence, social science practitioners should be in demand too, but this does not seem the case. One of the reasons for such a situation is that political and social science departments worldwide tend to remain in their “comfort zone” and see their disciplines quite traditionally, but by doing so they cut themselves off from many positions today. The authors believed that these conditions should and could be changed and thus in a few years created a specifically tailored course for students in Political Science. This paper examines the experience of the last year of such a program, which, after several tweaks and adjustments, is now fully operational. The results and students’ appreciation are quite remarkable. Hence the authors considered the experience was worth sharing, so that colleagues in social and political science departments may feel encouraged to follow and replicate such an example.

Background Agricultural pilots fly inside rural areas, usually, in runways without proper maintenance. Neglected runway maintenance contributes to increased exposure to shocks and vibrations. On the other hand, during cruise and spraying, the pilot is not exposed to the effect of the runway surface, and thus the exposure may be different. Objective The aim of this study is to investigate the factors that may increase occupational exposure to WBV in agricultural pilots. Method The methodology used in this study consisted of evaluating the exposure of WBV according to the runway surface quality and the stages of flight for a sample of four different agricultural aircraft models. Results The results confirmed that the magnitude of the vibration is significantly influenced by the runways surface quality and the stages of flight. This suggests the possibility to decrease the exposure to WBV improving runway maintenance and managing flight time. Relevance for the industry Based on the results of the present study, it was possible to define strategies to reduce whole-body vibration exposure and thus improve the working conditions of agricultural pilots.

Magnetic Resonance Imaging (MRI) is nowadays one of the most common medical imaging technology, due to its non-invasive nature and the many kind of supported sequences (modalities), that provide unique insights about a particular disease. However, it is not always possible to acquire all the sequences required, for several reasons such as prohibitive scan times or allergies to contrast agents. To overcome this problem and thanks to the recent improvements in Deep Learning, in the last few years researchers have been studying the application of Generative Adversarial Networks, a promising paradigm in deep learning, to generate the missing modalities. In this work we developed and trained two models of Generative Adversarial Networks, called MI-pix2pix and MI-GAN, to solve the problem of generating missing modalities for brain MRIs. In particular, our approaches are multi-input generative models, as they exploit as input several MRI modalities to generate the missing one. Our results are promising and show that the developed models are able to generate rather realistic and good quality images.

QuantiFERON -TB Gold plus (QFT-plus) represents the latest generation of interferon-gamma release assays (IGRAs), eliciting a response from CD8 T- cells in addition to CD4-T cells, with the aim to improve detection of latent M.tuberculosis infection (LTBI) with respect to its predecessor QuantiFERON-TB Gold In-Tube (QFT-GIT), even if no significant differences have been shown between the two tests (1, 2).….

The density of modern microprocessors is so high, that operating all their units at full power would destroy them by thermal runaway. Hence, thermal control is vital, but at the same time has to integrate with power/performance management, to not unduly limit computational speed. In addition, the controller must be simple and computationally light, as millisecond-scale response is required. Finally, since microprocessors face a variety of operating conditions, postsilicon tuning is an issue. We here present a solution, by exploiting event-based control and a hardware/software partition to maximize efficiency, lightness, and flexibility. We show experiments on real hardware, evidencing the obtained advantages over the state of the art.

The growing complexity of global interconnected risk suggests that a shift has occurred in the way emergency planners need to improve preparedness and response to cascading events. With reference to the literature from the physical, social and political sciences, this paper analyses extreme space weather events and cyberattacks. The goal of this work is to produce a replicable scenario-building process, based on cross-disciplinary understanding of vulnerability, that could be complementary to probabilistic hazard assessment. Our hypothesis is that the technological and human component of critical infrastructure could be the primary vector for the escalation of secondary emergencies. While not themselves having direct implications in terms of loss of life, elements that are common to different risks could provide particular challenges for disaster management. Our findings identify some vulnerable nodes, such as Global Navigation Satellite System technology and remote-control systems, that could act as paths for the escalations of events. We suggest that these paths may be common to various known and unknown threats. We propose two scenarios of Massive, OveRwhelming Disruption of OpeRations (M.OR.D.OR.) that could be used for testing emergency preparedness strategies, and increasing the response to highly complex, unknown events. The conclusions highlight the open challenges of seeking to increase societal resilience. The limitations of this work are described, as are the possible challenges for future research.

The Infrastructure Building Information Modeling (I-BIM) is a digital information management system utilized in the transport infrastructures construction, becoming increasingly important. BIM modeling aims at bringing improvements to all design stages. The use of BIM modeling will also provide cost reduction and control, increase awareness to data, design information availability and usability in each phase of infrastructure life cycle. Although the advanced modeling of the building components and systems leads to advantages well highlighted by practice and literature, in case of transportation infrastructures a critical analysis could show if this design methodology carries out the same benefits. The limited availability of infrastructure components libraries and the difficulty in assigning parameters to the geometries of the objects (many of them with unique characteristics) have been frequently quoted as main obstacles to the BIM use for the transport infrastructures. With this background, the problem is to understand which BIM-for-building features must be preserved in the production and management practices of each infrastructure model (classes, information exchanges and relationship between the classes and the spatial decomposition). This work is focused on the study of the I-BIM methodologies for the transport infrastructures (in particular railway infrastructures), analyzing a case study related to the port of Venice. The upward trend of goods quantity daily passing through the port infrastructures, led to the need to expand the container loading/unloading ship areas and, at the same time, to find a new and faster goods exit from the port areas, compared to the existing railway infrastructures. The authors developed a pre-feasibility study to identify the railway connection between the new port station and the existing line Padova – Mestre and to evaluate the difficulties and the ripeness of available means for an integrated design with the BIM tools

The deep sea is the largest biome on Earth but the least explored. Our knowledge of it comes from scattered sources spanning different spatial and temporal scales. Implementation of marine policies like the European Union’s Marine Strategy Framework Directive (MSFD) and support for Blue Growth in the deep sea are therefore hindered by lack of data. Integrated assessments of environmental status require tools to work with different and disaggregated datasets (e.g. density of deep-sea habitat-forming species, body-size distribution of commercial fishes, intensity of bottom trawling) across spatial and temporal scales. A feasibility study was conducted as part of the four-year ATLAS project to assess the effectiveness of the open-access Nested Environmental status Assessment Tool (NEAT) to assess deep-sea environmental status. We worked at nine selected study areas in the North Atlantic focusing on five MSFD descriptors (D1-Biodiversity, D3-Commercial fish and shellfish, D4-Food webs, D6-Seafloor integrity, D10-Marine litter). The objectives of the present study were to i) explore and propose indicators that could be used in the assessment of deep-sea environmental status, ii) evaluate the performance of NEAT in the deep sea, and iii) identify challenges and opportunities for the assessment of deep-sea status. Based on data availability, data quality and expert judgement, in total 24 indicators (one for D1, one for D3, seven for D4, 13 for D6, two for D10) were used in the assessment of the nine study areas, their habitats and ecosystem components. NEAT analyses revealed differences among the study areas for their environmental status ranging from “poor” to “high”. Overall, the NEAT results were in moderate to complete agreement with expert judgement, previous assessments, scientific literature on human-pressure gradients and expected management outcomes. We suggest that the assessment of deep-sea environmental status should take place at habitat and ecosystem level (rather than at species level) and at relatively large spatial scales, in comparison to shallow-water areas. Limited knowledge across space (e.g. distribution of habitat-forming species) and the scarcity of long-term data sets limit our knowledge about natural variability and human impacts in the deep sea preventing a more systematic assessment of habitat and ecosystem components in the deep sea. However, stronger cross-sectoral collaborations, the use of novel technologies and open data-sharing platforms will be critical for establishing environmental baseline indicator values in the deep sea that will contribute to the science base supporting the implementation of marine policies and stimulating Blue Growth., Sí

Background Major brain injury and uncontrolled blood loss remain the primary causes of early trauma-related mortality. One-quarter to one-third of trauma patients exhibit trauma-induced coagulopathy (TIC). Thromboelastometry (ROTEM) and thrombelastography (TEG) are valuable alternatives to standard coagulation testing, providing a more comprehensive overview of the coagulation process. Purpose Evaluating thromboelastographic profile, the incidence of fibrinolysis (defined as Ly30 > 3%) in severe trauma patients, and factors influencing pathological coagulation pattern. Methods Prospective observational 2 years cohort study on severe trauma patients assisted by Helicopter Emergency Medical System (HEMS) and Level 1 Trauma Center, in a tertiary referral University Hospital. Results Eighty three patients were enrolled, mean NISS (new injury severity score) 36 (± 13). Mean R value decreased from 7.25 (± 2.6) to 6.19 (± 2.5) min (p R from T0 to T1. In NISS 25–40 and NISS > 40 groups, changes in R value increased their significance (p = 0.04 and p T0 and 74 (92.5%) at T1. Hypercoagulation was present in 57 (71.3%) patients at T0, and in 66(82.5%) at T1. 9 (11.3%) patients had hyperfibrinolysis at T0, 7 (8.8%) patients at T1. Prevalence of StO2 T0 was greater in patients whose TEG worsened (7 patients, 46.7%) against whose TEG remained stable or improved (8 patients, 17.4%) from T0 to T1 (p = 0.02). 48 (57.8%) patients received T1 (p T0, nor other TEG pattern. Conclusion Our population is representative of a non-hemorrhagic severe injury subgroup. Almost all of our trauma population had coagulation abnormalities immediately after the trauma; pro-coagulant changes were the most represented regardless of the severity of injury. NISS appears to affect only R parameter on TEG. Hyperfibrinolysis has been found in a low percentage of patients. Hypoperfusion parameters do not help to identify patients with ongoing coagulation impairment. Small volume resuscitation and mild hypotermia does not affect coagulation, at least in the early post-traumatic phase.

Background Interest in studying the spatial distribution of gene expression in tissues is rapidly increasing. Spatial Transcriptomics is a novel sequencing-based technology that generates high-throughput information on the distribution, heterogeneity and co-expression of cells in tissues. Unfortunately, manual preparation of high-quality sequencing libraries is time-consuming and subject to technical variability due to human error during manual pipetting, which results in sample swapping and the accidental introduction of batch effects. All these factors complicate the production and interpretation of biological datasets. Results We have integrated an Agilent Bravo Automated Liquid Handling Platform into the Spatial Transcriptomics workflow. Compared to the previously reported Magnatrix 8000+ automated protocol, this approach increases the number of samples processed per run, reduces sample preparation time by 35%, and minimizes batch effects between samples. The new approach is also shown to be highly accurate and almost completely free from technical variability between prepared samples. Conclusions The new automated Spatial Transcriptomics protocol using the Agilent Bravo Automated Liquid Handling Platform rapidly generates high-quality Spatial Transcriptomics libraries. Given the wide use of the Agilent Bravo Automated Liquid Handling Platform in research laboratories and facilities, this will allow many researchers to quickly create robust Spatial Transcriptomics libraries.

Deep Learning is a promising approach to either automate or simplify several tasks in the healthcare domain. In this work, we introduce SegAN-CAT, an end-to-end approach to brain tumor segmentation in Magnetic Resonance Images (MRI), based on Adversarial Networks. In particular, we extend SegAN, successfully applied to the same task in a previous work, in two respects: (i) we used a different model input and (ii) we employed a modified loss function to train the model. We tested our approach on two large datasets, made available by the Brain Tumor Image Segmentation Benchmark (BraTS). First, we trained and tested some segmentation models assuming the availability of all the major MRI contrast modalities, i.e., T1-weighted, T1 weighted contrast enhanced, T2-weighted, and T2-FLAIR. However, as these four modalities are not always all available for each patient, we also trained and tested four segmentation models that take as input MRIs acquired with a single contrast modality. Finally, we proposed to apply transfer learning across different contrast modalities to improve the performance of these single-modality models. Our results are promising and show that not only SegAN-CAT is able to outperform SegAN when all the four modalities are available, but also that transfer learning can actually lead to better performances when only a single modality is available.

Sporadic small vessel disease (SVD) has high prevalence in aging population and stroke patients, but also in younger asymptomatic subjects. In this last group it can represents a prelude to stroke and cognitive impairment. Still nowadays, its pathogenesis is unclear. 35 consecutive patients with SVD at brain MRI and 35 age- and sex-matched controls, between January 2016 and February 2018, underwent an extended screening for thrombophilia, autoimmunity and evaluated levels of blood markers of inflammation and endothelial activation. Asymmetric DiMethyl Arginine (ADMA) levels proved higher in patients (70.44 ± 36.25 ng/ml vs. 46.58 ± 30.67 ng/ml; p = 0.004), also after controlling for confounding factors. ADMA levels showed positive correlation with Fazekas score (r = 0.304; p = 0.01). ROC curve analysis showed a moderate accuracy in discriminating patients and controls (AUC = 0.70; CI 0.57–0.82; p = 0.004): a cut-off of 46 ng/ml is associated with 80% sensitivity, but limited (54%) specificity. Higher ADMA levels characterize selected subjects with sporadic SVD, asymptomatic for vascular diseases and without latent inflammatory conditions or coagulopathy. This reinforces the hypothesis of the key role of endothelial dysfunction in SVD. Further studies should explore the cause-effect relationship between ADMA pathway and SVD.

Background Hemostasis is the dynamic equilibrium between coagulation and fibrinolysis. During pregnancy, the balance shifts toward a hypercoagulative state; however placental abruption and abnormal placentations may lead to rapidly evolving coagulopathy characterized by the increased activation of procoagulant pathways. These processes can result in hypofibrinogenemia, with fibrinogen levels dropping to 2 g/L or less and an associated increased risk of post-partum hemorrhage. The aim of the present study was to evaluate the concordance between two methods of functional fibrinogen measurement: the Thromboelastography (TEG) method (also known as FLEV) vs. the Clauss method. Three patient groups were considered: healthy volunteers; non-pathological pregnant patients; and pregnant patients who went on to develop postpartum hemorrhage. Methods A prospective observational study. Inclusion criteria were: healthy volunteer women of childbearing age, non-pathological pregnant women at term, and pregnant hemorrhagic patients subjected to elective or urgent caesarean section (CS), with blood loss exceeding 1000 mL. Exclusion criteria were age

SUMMARYThe prompt availability of reliable epidemiological information on emerging pandemics is crucial for public health policy-makers. Early in 2013, a possible new H1N1 epidemic notified by an intensive care unit (ICU) to GiViTI, the Italian ICU network, prompted the re-activation of the real-time monitoring system developed during the 2009–2010 pandemic. Based on data from 216 ICUs, we were able to detect and monitor an outbreak of severe H1N1 infection, and to compare the situation with previous years. The timely and correct assessment of the severity of an epidemic can be obtained by investigating ICU admissions, especially when historical comparisons can be made.

The objective of this study was to evaluate the effectiveness of the temporomandibular joint (TMJ) osteoarthritis treatment through articular injections of plasma rich in growth factors (PGRF)-Endoret. Thirteen patients (median age, 47.64 y; SD, 7.51; range, 40-64 y; male-female ratio, 2:11) with osteoarthritis of TMJ associated to chronic pain have been selected. They were treated with articular injections of PRGF-Endoret, measuring the maximum mouth opening and pain level before the first injection (t0), 30 days after just before the second (t1), and after 6 months (t2). Data were analyzed using the paired Student's t-test data. The visual analogue scale score at t0 is 7.69 (range, 4-10; SD, 1.9), whereas that at t1 is 1.54 (range, 0-5; SD, 1.74) and that at t2 is 0.23 (range, 0-2; SD, 0.65). These differences in the results are statistically highly significant (P < 0.0001 comparison t0-t1 and t0-t2 and P < 0.01 comparison t1-t2). In terms of maximum mouth opening, it reduced from 30.15 mm at t0 (range, 26-40 mm; SD, 4.44) to 37.54 mm at t1 (range, 31-51 mm; SD, 5.10), with an increase of 7.38 mm (range, 4-11 mm; SD, 2.02) and a highly significant difference (P < 0.0001). At t2, it was 39.54 mm (range, 34-51; SD, 4.55) with an increase of 9.38 mm (range, 5-12 mm; SD, 2.21) compared with t0 and that of 2.00 mm compared with t1. Both differences in the results are statistically significant (P < 0.0001 and P < 0.01, respectively). The articular injections of PRGF-Endoret represent a very efficient method to control pain and to improve the TMJ mobility.

Resveratrol (RES) is a polyphenolic compound found in grapes, peanuts, and in some berries. RES has been reported to exhibit antioxidant, anti-inflammatory, anti-proliferative properties, and to target mitochondrial-related pathways in mammalian cells and animal models. Therefore, RES is currently advised as supplement in the diet of elderly individuals. Although it is hypothesized that some of RES beneficial actions likely arise from its action on the skeletal muscle, the investigation of RES effects on this tissue remains still elusive. This study reports the effects of a 0,04% RES-supplemented diet for six months, on the skeletal muscle properties of C57/BL6 aging mice. The analysis of the morphology, protein expression, and functional-mechanical properties of selected skeletal muscles in treated compared to control mice, revealed that treated animals presented less tubular aggregates and a better resistance to fatigue in an ex-vivo contraction test, suggesting RES as a good candidate to reduce age-related alterations in muscle.

The paper describes a laboratory evaluation aimed at analyzing the mechanical performance of fiber-reinforced asphalt mixtures for road pavements. Reinforcement with four cellulose-based fiber types was taken into account. A control non-reinforced mixture was also tested for comparison purposes. The comparative mechanical characterization of materials was firstly based on indirect tensile dynamic tests aimed at assessing strength as well as stiffness and dynamic loading resistance, respectively. Such tests were carried out at 25°C and at fixed loading condition. Then, the most promising mixture was selected to study the long-term in-service properties. Fatigue resistance was assessed with four point bending tests at 25°C and 10 Hz, applying different stress levels. Experimental data were analyzed by means of both traditional and advanced energy methods. Results demonstrated that the proposed experimental approach allowed ascertaining the different contribution of the studied fibers.

In this work, following the same approach successfully applied to evolve Super Mario levels, we applied the CMA-ES to search the latent space of a GAN previously trained to generate DOOM levels. Combining a search algorithm with a model trained in a supervised setting, allows to take advantage from both these paradigms. From one hand, the GAN is able to generate contents exploiting the design patterns learned from all the examples it was trained from. On the other hand, the CMA-ES can effectively search this design space for specific contents that meet some given design objectives. In particular, we tested our approach evolving three very different type of levels: an arena level (i.e., few large areas), a labyrinth level (i.e., many corridors and small areas), and a complex level (i.e., a balanced mix of large and small areas). Our results show that the latent space of a GAN can be effectively searched by the CMA-ES to find DOOM levels that fit accurately the objectives but, at the same time, are also novel.

This paper presents a comprehensive research aimed at evaluating the feasibility of preparing bituminous mixes using slag aggregates only (EAF slag and LF slag from electric steelmaking), i.e. without any natural aggregate. Here, the second step of the experimental study, currently in progress, is presented, focusing on investigating possible countermeasures to the issues related to a reduced compactability of steel slag materials, such has been evidenced by the first phase of the research. To this aim, the effect of using a higher production temperature to prepare the steel slag mixtures has been analyzed in terms of volumetric properties as well as basic mechanical performance and durability. A reference mixture, prepared with natural virgin aggregate and cement as filler, was also investigated for comparison purposes. Basically, the main experimental findings showed that the mixes prepared with steel slags still suffered poor workability even when higher production temperature was used. This led to a higher strength but more brittle mechanical behavior whereas promising results were obtained in terms of water and aging resistance. Anyway, it is worth noting that the measured performance for the slag mixtures can be mostly considered acceptable according to the requirements usually adopted for material acceptance.

The objective of this article is to analyze comparatively the importance of intellectual capital and the impact of intellectual capital on the performance of Brazilian companies awarded the Rio Grande do Sul Quality Award in 2004 and 2017. A sample of 72% of the Brazilian companies that received this Quality Award of the Gaucho Quality and Productivity Program in 2004 and 70.5% in 2017 were investigated. It can be affirmed that intellectual capital continues to be an essential asset, but during this period there have been some changes concerning the level of presence and importance among the elements that compose it. Regarding the changes in the influence of intellectual capital on organizational performance between 2004 and 2017, the results showed that intellectual capital, through human, structural and client capital, practically still has the same level of influence on organizational performance.

We applied Generative Adversarial Networks (GANs) to learn a model of DOOM levels from human-designed content. Initially, we analyzed the levels and extracted several topological features. Then, for each level, we extracted a set of images identifying the occupied area, the height map, the walls, and the position of game objects. We trained two GANs: one using plain level images, one using both the images and some of the features extracted during the preliminary analysis. We used the two networks to generate new levels and compared the results to assess whether the network trained using also the topological features could generate levels more similar to human-designed ones. Our results show that GANs can capture intrinsic structure of DOOM levels and appears to be a promising approach to level generation in first person shooter games.

Even-though the last years have seen a “blossoming” of initiatives aiming to clarify the link between biodiversity (BD)-ecosystem functions (EF)-ecosystem services (ES)-human well-being (HWB), there is still a need for integrating the knowledge obtained by various research, making it useful for decision-makers. This contribution aims to show ways of gathering, representing and modelling these linkages to enable better decision-making based on available knowledge. This is achieved by: (i) conducting a systematic-review of contributions describing the links between BD–EF–ES–HWB and gathering the information into a database; (ii) organizing that information in a mind-map; (iii) showing, as an example, how a Bayesian Network model and scenarios can be built using the mind-map and database information. We show how gathering information into mind-maps works as a first step to the creation of a unified knowledge base, while Bayesian Network models allow for a better management of data uncertainty, commonly associated with the representation of complex models, as well as providing the possibility of creating future scenarios where assumptions can be tested. Thus, this contribution shows how available knowledge can be linked to improve our understanding of complex issues.

The aim of this study is to investigate thrombogenesis and the hypercoagulable changes in pregnant women affected by thrombophilia who received low-molecular-weight heparin (LWMH) prophylaxis. We included 21 pregnant women affected by thrombophilia treated with LWMH and 20 nontreated normal pregnant women as the control group. The sample group of thrombophilic pregnant women included different conditions (factor V Leiden mutation, protein C deficiency, protein S deficiency, antiphospholipid antibodies syndrome, and combined defects). Three blood samples were collected during pregnancy (i.e., at 16, 20, and 24 weeks) and tested for activated partial thromboplastin time and prothrombin fragment F1 + 2 (F1 + 2); anti-FXa activity was tested only in treated thrombophilic pregnant women. F1 + 2 levels progressively increased during pregnancy in both study groups. However, the F1 + 2 increase in women exposed to heparin prophylaxis was significantly lower than that in normal pregnant women in all 3 measurements carried out during gestation (p < 0.05); a statistically significant inverse correlation between F1 + 2 levels and anti-Xa activity (R = -0.8575, p < 0.05) was observed in treated women during pregnancy. Our findings suggest that F1 + 2 in addition to anti-Xa measurement could be used to adjust LWMH prophylaxis, at least in high-risk pregnant women.

Research and application concerning the use of environmentally friendly materials and technologies in road pavements have reached high relevance mainly due to the increasing public consciousness addressed to environmental protection and preservation. Warm Mix Asphalt (WMA) is a valid option in this regard. In fact, WMA is a cleaner asphalt concrete that can be prepared and compacted at lower temperatures than the traditional Hot Mix Asphalt (HMA). Moreover, the inclusion of recycled/waste materials in WMA can further enhance its environmental sustainability. Given this background, the present paper illustrates the overall results of a wide research study aimed at verifying the utilization feasibility of steel slags in warm-modified asphalt concretes. This was accomplished by investigating in the laboratory the midrange and high-service temperature properties of warm bituminous binders, as well as mastics and mixtures containing steel slag aggregates. The warm modification was performed using a chemical tensioactive additive; steel slags were produced in a metallurgical plant by electric arc furnace (EAF) treatment. To evaluate the combined effect of manufactured EAF steel slags and warm chemical additive, a comparative analysis was carried out taking into account unmodified binders as well as mastics and mixtures prepared with only natural aggregates. Binders, mastics and mixtures were studied in terms of stiffness, fatigue and permanent deformation resistance by carrying out dynamic tests on unaged and long-term aged samples. The results showed that cleaner materials prepared combining chemical warm technology and EAF steel slag aggregates seem to assure equal or even enhanced performance than the corresponding traditional hot mixed materials, demonstrating promising field applicability. In particular, the influence of lower mixing and compaction temperatures of the warm mixtures on stiffness, fatigue and rutting behaviour seemed to hide the contribution (positive or negative) due to the presence of EAF steel slag aggregates. In fact, the potential higher stiffness and rutting resistance of steel slag mixtures were limited whereas the possible lower fatigue resistance was positively counterbalanced.

Delay in diagnosing oral squamous cell carcinoma (OSCC) can be still identified as a major cause of its high morbidity and mortality. To date, the early diagnosis for OSCC is mainly based on clinical oral examination and there is an urgent need for reliable markers; thus, advancements in molecular technologies has set the stage for investigating new markers, as well as new diagnostic matrices. The aim of the present study is to investigate the presence of proteomic signatures of OSCC in saliva and their use as potential biomarkers for early and non-invasive diagnosis. Saliva from 45 OSCC patients and 30 healthy controls was analysed by SELDI-TOF mass spectrometry and ProteinChip® technology. A supervised multivariate statistical analysis (Classification and Regression Tree - CART) was used to build models for discriminating between OSCC and controls, and between early (ES-OSCC) and late stage (LS-OSCC) cancers. The peptide with 8041 Da mass was 22-fold more expressed in OSCC, thus being a suitable potential biomarker. Classification and regression analysis allowed to build a model that was capable of correctly classifying all cancers and controls in an independent testing set, using the 8041 m/z peak as splitter. Eleven peaks were also differently expressed between ES-OSCC and LS-OSCC, but, basing on these differences, it was not possible to build an algorithm to predict tumour staging. These findings confirm that saliva proteome in OSCC patients is different from healthy controls and these variations might reflect different stages of disease progression and are worthy of further validation as diagnostic and prognostic biomarkers. Copyright ©by BIOLIFE, s.a.s.

Explaining to young students what the European Union (EU) is and how it works can be challenging. Yet, the diffusion and success of “EU studies” push instructors to develop innovative methods to make the complex EU decision-making accessible to students. Role-playing may be helpful and the EU provides ample opportunities of simulating various levels of policy-making. This paper presents a format for a semester-long, role-playing simulation in which students act as EU Commission’s staff employees.

To evaluate olfactory function and clinical-neurological characteristics in a group of patients with mild head trauma.A total of 352 patients with MTBI underwent olfactory function evaluation. The site of head trauma, loss of consciousness20 min, memory loss, subjective presence or absence of olfaction and other clinical, neurological and radiological aspects were evaluated and compared with the olfactory dysfunction.A total of 33.5% patients enrolled in the study had an olfactory dysfunction. Eighty-seven percent of the patients had a diagnosis of anosmia whereas 13% had a diagnosis of hyposmia. Statistical analysis did not show a correlation between radiologically detected head lesions and different types of olfactory dysfunction (p 0.05). Besides, no difference between head lesion site and different olfactory dysfunction was reported (p = 0.5). Regarding olfactory sub-tests a low detection threshold was present in these patients.The possibility of olfactory dysfunction should be considered in any case of MTBI appears differently than expected, a minor head injury causes anosmia much more frequently than hyposmia.

Superhydrophobicity, the enhanced hydrophobicity of surfaces decorated with textures of suitable size, is associated with a layer of gas trapped within surface roughness. The reduced liquid/solid contact makes superhydrophobicity attractive for many technological applications. This gas layer, however, can break down with the liquid completely wetting the surface. Experiments have shown that the recovery of the "suspended" superhydrophobic state from the wet one is difficult. Self-recovery-the spontaneous restoring of the gas layer at ambient conditions-is one of the dreams of research in superhydrophobicity as it would allow to overcome the fragility of superhydrophobicity. In this work we have performed a theoretical investigation of the wetting and recovery processes on a set of surfaces characterized by textures of different dimensions and morphology in order to elucidate the optimal parameters for avoiding wetting and achieving self-recovery. Results show that texture size in the nanometer range is a necessary but not sufficient condition for self-recovery: the geometry plays a crucial role, nanopillars prevent self-recovery, while surfaces with square pores exhibit self-recovery even at large positive pressures. However, the optimal morphology for self-recovery, the square pore, is suboptimal for the functional properties of the surface, for example, high slippage. Our calculations show that these two properties are related to regions of the texture separated in space: self-recovery is controlled by the characteristics of the bottom surface, while wetting and slip are controlled by the cavity mouth. We thus propose a modular design strategy which combines self-recovery and good functional properties: Square pores surmounted by ridges achieve self-recovery even at 2 MPa and have a very small liquid/solid contact area. The macroscopic calculations, which allowed us to efficiently devise design criteria, have been validated by atomistic simulations, with the optimal texture showing self-recovery on atomic time scales, τ ∼ 2 ns.

Quality of life (QoL) is the sense of well-being perceived by people. The improvement of parkinsonian patient’s QoL is a crucial goal for clinicians involved in rehabilitative care. In order to provide an appropriate endpoint for the assessment of the effectiveness of rehabilitation treatments on QoL of patients with Parkinson’s Disease (PD), in this study we have first translated and then validated the Belastungsfragebogen Parkinson kurzversion (BELA-P-k). This tool allows evaluating separately two crucial aspects: i) the loss of personal autonomy in activities of daily life and ii) the psychological and psychosocial impact of the disease. The BELA-P-k was translated from Dutch into Italian. Subsequently 202 PD patients filled out the questionnaire. Patients were also evaluated by using the Parkinson Disease Questionnaire −39 (PDQ39), the Unified Parkinson’s Disease Rating Scale (UPDRS), the Mini Mental State Examination (MMSE) and the Frontal Assessment Battery (FAB). The internal consistency for total of two different scores Bothered by (Bb) and Need for Help (NfH) was excellent (p = 0.91) for both categories. The correlation between Bb and NfH categories was significant and strong, very-strong, ranging from 0.78 to 0.88 (all p

Gastrointestinal stromal tumors (GIST) are rare, with unpredictable behavior, most of them asymptomatic or nonspecific symptoms. They may arise in any place of digestive tube, and the standard treatment is the complete surgical resection, however recurrences and metastases are frequent. The following case is a report from an elderly patient with growing and painful abdominal mass on physical examination, and the result of complementary imaging tests suggests that this is GIST. Submitted to surgical therapy for resection of the lesion and follow-up with imatinib mesylate (Glivec®).