The paper proposes a human explainable artificial intelligence approach for mapping the status of environmental phenomena from multisource geo data. It is both knowledge and data driven: it exploits remote sensing expert’s knowledge to define the contributing factors from which partial evidence of the environmental status can be computed. Furthermore, it aggregates the partial evidences to compute a map of the environmental status by adapting to a region of interest through a learning mechanism exploiting Volunteered Geographic Information (VGI), both from in situ observations and photointerpretation. The approach is capable to capture the specificities of local context as well as to cope with the subjectivity and incompleteness of expert’s knowledge. The proposal is exemplified to map the status of standing water areas (i.e. water bodies and river, human driven or natural hazard flooding) by considering satellite data and geotagged observations. Results of the validation experiments were performed in three areas of Northern Italy, characterized by distinct ecosystems. Results of the proposed methodological framework showed better performances than traditional approaches based on single spectral indexes thresholding. The use of expert’s knowledge, possibly imprecise/uncertain and incomplete, the need of few ground truth data for learning, and finally the explainability of learned rules are the distinguishing characteristics of the proposal with respect to traditional machine learning methods.

Predicting change from multivariate time series has relevant applications ranging from medical to engineering fields. Multisensory stimulation therapy in patients with dementia aims to change the patient’s behavioral state. For example, patients who exhibit a baseline of agitation may be paced to change their behavioral state to relaxed. This study aims to predict changes in behavioral state from the analysis of the physiological and neurovegetative parameters to support the therapist during the stimulation session. In order to extract valuable indicators for predicting changes, both handcrafted and learned features were evaluated and compared. The handcrafted features were defined starting from the CATCH22 feature collection, while the learned ones were extracted using a Temporal Convolutional Network, and the behavioral state was predicted through Bidirectional Long Short-Term Memory Auto-Encoder, operating jointly. From the comparison with the state-of-the-art, the learned features-based approach exhibits superior performance with accuracy rates of up to 99.42% with a time window of 70 seconds and up to 98.44% with a time window of 10 seconds.

In the current industrial landscape, increasingly pervaded by technological innovations, the adoption of optimized strategies for asset management is becoming a critical key success factor. Among the various strategies available, the “Prognostics and Health Management” strategy is able to support maintenance management decisions more accurately, through continuous monitoring of equipment health and “Remaining Useful Life” forecasting. In the present study, Convolutional Neural Network-based Deep Neural Network techniques are investigated for the Remaining Useful Life prediction of a punch tool, whose degradation is caused by working surface deformations during the machining process. Surface deformation is determined using a 3D scanning sensor capable of returning point clouds with micrometric accuracy during the operation of the punching machine, avoiding both downtime and human intervention. The 3D point clouds thus obtained are transformed into bidimensional image-type maps, i.e., maps of depths and normal vectors, to fully exploit the potential of convolutional neural networks for extracting features. Such maps are then processed by comparing 15 genetically optimized architectures with the transfer learning of 19 pre-trained models, using a classic machine learning approach, i.e., Support Vector Regression, as a benchmark. The achieved results clearly show that, in this specific case, optimized architectures provide performance far superior (MAPE=0.058) to that of transfer learning which, instead, remains at a lower or slightly higher level (MAPE=0.416) than Support Vector Regression (MAPE=0.857).

Continuous in-home monitoring of older adults living alone aims to improve their quality of life and independence, by detecting early signs of illness and functional decline or emergency conditions. To meet requirements for technology acceptance by seniors (unobtrusiveness, non-intrusiveness, privacy-preservation), this study presents and discusses a new smart sensor system for the detection of abnormalities during daily activities, based on ultra-wideband radar providing rich, not privacy-sensitive, information useful for sensing both cardiorespiratory and body movements, regardless of ambient lighting conditions and physical obstructions (through-wall sensing). The radar sensing is a very promising technology, enabling the measurement of vital signs and body movements at a distance, and thus meeting both requirements of unobtrusiveness and accuracy. In particular, impulse-radio ultra-wideband radar has attracted considerable attention in recent years thanks to many properties that make it useful for assisted living purposes. The proposed sensing system, evaluated in meaningful assisted living scenarios by involving 30 participants, exhibited the ability to detect vital signs, to discriminate among dangerous situations and activities of daily living, and to accommodate individual physical characteristics and habits. The reported results show that vital signs can be detected also while carrying out daily activities or after a fall event (post-fall phase), with accuracy varying according to the level of movements, reaching up to 95% and 91% in detecting respiration and heart rates, respectively. Similarly, good results were achieved in fall detection by using the micro-motion signature and unsupervised learning, with sensitivity and specificity greater than 97% and 90%, respectively.

Smart living, a concept that has gained increasing attention in recent years, revolves around integrating advanced technologies in homes and cities to enhance the quality of life for citizens. Sensing and human action recognition are crucial aspects of this concept. Smart living applications span various domains, such as energy consumption, healthcare, transportation, and education, which greatly benefit from effective human action recognition. This field, originating from computer vision, seeks to recognize human actions and activities using not only visual data but also many other sensor modalities. This paper comprehensively reviews the literature on human action recognition in smart living environments, synthesizing the main contributions, challenges, and future research directions. This review selects five key domains: Sensing Technology, Multimodality, Real-time Processing, Interoperability, and Resource-Constrained Processing, as they encompass the critical aspects required for successfully deploying human action recognition in smart living. These domains highlight the essential role that sensing and human action recognition play in successfully developing and implementing smart living solutions. This paper serves as a valuable resource for researchers and practitioners seeking to explore further and advance the field of human action recognition in smart living.

In implantology, among the key choices, to obtain predictable results, it’s essential to establish, using CBCT, the bone site where to insert the implants; these sites must be identified on the mucosa and secondarily, during the surgical phase, on the cortical bone. Surgical templates are a valid aid especially in complex cases which require sev-eral implants. In cases of single implant, on the other hand, surgical guides are rarely used and the implant is inserted freehand and the identification of the implant site on the oral mucosa is more difficult; for this reason the clinician uses the teeth in the arch as a ref-erence. This experimental study is based on the use of a thermo-printed mask, con-taining radiopaque references which, worn by edentulous patients during the execu-tion of the CBCT, helps to evaluate the identification of the implant sites on the patient when surgical guides are not used and the free hand technique is adopted. This method is certainly reserved for experienced operators capable of identifying the correct angle of the implants with the freehand technique. The level of experience remains fundamental in the clinician's decision whether or not to use surgical guides; in fact, doctors with little experience should use surgical guides even in the simplest cases to reduce the risk of error.

In implantology, among the key choices, to obtain predictable results, it is essential to establish, on the basis of radiographic examinations, the bone site where to insert the implants; these selected locations must be identified first on the mucosa and then on the cortical bone. Surgical guides represent a valid aid especially in complex cases with more than 3 or 4 implants, whereas in single implant cases they are rarely used. This study evaluates the clinical precision with which the implant sites, on the patient's mucosa, are identified in surgical procedures planned without any templates. The verification of this precision is carried out through thermo-printed templates with radiopaque references which could however help the clinician to identify these sites in a simple, rapid and economical way.

Burning Mouth Syndrome (BMS) is an idiopathic condition that manifests itself primarily with the onset of burning sensation. The aim of the research was to perform Photobiomodulation Therapy (PBM) using a diode laser on the oral mucosa of BMS patients, followed by an objective evaluation of the morphological changes in the vascular bed underlying the mucosa using polarized light videocapillaroscopy. A group of 40 patients were included in the study. The patients were randomly divided into two groups (using simple randomization): 20 patients were assigned to the laser group and 20 patients were assigned to the placebo group. Each patient of the laser group received 8 irradiations (with 4 Watt of power, wavelength 800nm, energy 1200 Joules, irradiation time for 300 seconds of time, energy density 50J/cm2 , 60 mW continuous wave laser, irradiance 180mW/cm2 ), twice a week, blinded to the type of irradiation administered, for four consecutive weeks. The patients in the placebo group underwent the same sessions as the others, the only difference being the non-emission of the laser. An initial check of the vascular bed was performed with a polarized light videocapillaroscope. This was followed by treatment with a therapeutic diode laser and a subsequent check with a videocapillaroscope. It was possible to observe that in the group of patients that underwent laser therapy, there was a lasting improvement in symptoms. The capillary oral bed in the placebo groups did not show any statistically significant difference (P>0.05). In the laser group we observed: in the buccal mucosa the diameter of the capillary had a reduction of 3μm; in the upper lip mucosa a reduction of 3μm; in the lower lip mucosa, there was a reduction of 3μm; in the dorsal lingual surface, there was a reduction of 2 μm. An increase in capillary length was also obtained in all irradiated regions in the laser group patients (P < 0.05). PBM induces microcirculatory changes that are still present at a distance of time, such as an improvement in the clinical picture. The improvement in the symptoms has been correlated to the reduction of the capillary diameter. Placebo effect only leads to a temporary improvement in symptoms that are unrelated to changes in the microcirculatory pattern.

The tradeoff between the design phase and the experimental setup is crucial to satisfy the accuracy requirement of Large Deployable Reflectors. Manufacturing errors and tolerances change the RMS of the reflecting surface and require careful calibration of the tie rod system to be able to fit into the initial design specifications. To give a possible solution to this problem, here two calibration methods, respectively for rigid and flexible ring truss support, are described. Starting from the acquired experimental data on the net nodal coordinates, the initial problem of satisfying the static equilibrium at the measured configuration is described. Then, two constrained optimization problems, for rigid and flexible ring truss support, are defined to meet RMS accuracy of the reflecting surface modifying the tie lengths. Finally, a case study to demonstrate the validity of the proposed methods is presented.

The Water-Cooled Lead Lithium (WCLL) Breeding Blanket (BB) is one of the two BB concepts candidate to be selected as driver blanket for the EU-DEMO fusion reactor. In this regards, the development of a sound architecture of the WCLL Central Outboard Blanket (COB) Segment, ensuring the fulfilment of the thermal and structural design requirements, is one of the main goals of the EUROfusion consortium. To this purpose, an exploratory research campaign has been launched to preliminarily investigate the thermo-mechanical performances of the Bottom Cap (BC) region of the WCLL COB segment, because of its peculiarities making its design different from the other regions. The assessment has been carried out considering the nominal BB operating conditions, the Normal Operation (NO) scenario, as well as a steady-state scenario derived from the in-box LOCA accident, the Over-Pressurization (OP) scenario. Starting from the reference geometric layout of the WCLL COB BC region, a first set of analysis has been launched in order to evaluate its structural performances under a previously calculated thermal field and to select potential geometric improvements. Then, the analysis of a more complete BC region has been conducted from both the thermal and structural standpoints, evaluating its structural behaviour in compliance with the RCC-MRx code. Finally, after some iterations and geometric updates, a promising geometric layout of the BC region has been obtained even though some criticalities still persist in the internal Stiffening Plates and First Wall. However, the obtained results clearly showed that the proposed layout is worthy to be further assessed to achieve a robust enough configuration. The work has been performed following a theoretical-numerical approach based on the Finite Element Method (FEM) and adopting the quoted Ansys commercial FEM code.

(1) Background: A growing number of communities are re-discovering the value of their streets as important public spaces for many aspects of daily life, thus creating the need for a transformation in the quality of streets. An emerging concept is to accommodate all users of the transportation system, a concept that has been labelled ‘complete streets’. (2) Methods: In this paper, we present sustainable complete streets design criteria that integrate complete streets by adding in socio-environmental design criteria related to aesthetics, environment, liveability, and safety. (3) Results: Proposed design criteria provide a street network which provides improvements in aesthetics, to recover historical urban character and realize historical area planning goals; environment, to increase permeable surfaces, reduce the heat island, and absorb traffic-related air pollution; liveability, to create a public space destination in the urban landscape; and safety, to improve the safety of all road users. and (4) Conclusions: The case study of the urban rehabilitation of the “Mostra d’Oltremare” area and of its cultural and architectural assets in Naples, Italy, highlights the practical application of the proposed criteria and the possibility of using these criteria in other urban contexts.

Introduction. Anesthesia is widely used in various fields of dentistry to reduce patient discomfort when the treatment would be painful. The dentist may need to infiltrate the anesthetic into multiple locations and this is usually done with the same needle which passes through the soft tissues several times to distribute the anesthetic solution over a larger area. The present study aims to evaluate, through a morphological analysis under a scanning electron microscope (SEM), how the beveled tip of a 30G needle, used to inject anesthetic several times into different areas of the vestibular mucosa, changes. Materials and methods. 30G needles with two different brands were tested, in vivo used for a variable number of sequential injections from 1 to 6 on 192 patients. The specimens were analyzed under SEM observation to evaluate any deformations induced by contact with the vestibular soft tissues. Results. The amount of deformation, measured along the axis parallel to the needle, was proportional to the number of injections. The protrusion of deformations, measured on an axis perpendicular to the needle, were maximum on the needles used 3 times. For the needles used 4,5 and 6 injections, no further increase in deformations was noted. Conclusion. From the data it seems that the tested needles are not produced to withstand multiple injections consequently after the first injection on soft tissues, they undergo a deformation which could increase the risk of injury to the mucosa itself or to nerves and vessels with which they come into contact. It would be advisable to use the single needle for a reduced number of injections.

An analysis of the curve of Spee in relation to muscle activity, assessed by electromyographic analysis, on a group of 16 young adults with previous fixed orthodontic treatment is proposed as a pilot study. Given the high incidence of this type of dental treatment, it is important to point out how, in this field of dentistry, there is a marked tendency to level and flatten this anatomical occlusal curve, as proposed by Andrews. If in orthodontics there is a standardized levelling of the curve of Spee, in the prosthetic and restorative field, the management of the curve of Spee requires greater attention and often even an individualized approach. The purpose of this study is to investigate what the levelling of the antero-posterior occlusal curve entails in terms of masticatory effectiveness and harmony. From the results obtained, it can be seen that in order to optimize the harmony of the stomatognathic apparatus, the curve of Spee is a parameter that requires individual attention: modifying it through standardized levelling has inevitable consequences.

This study examines change detection techniques in dense point clouds for the purpose of Cultural Heritage preservation, with a particular focus on the San Pietro Barisano Bell Tower in Matera, Italy. Dense point clouds, obtained via advanced laser scanning, offer detailed 3D representations of heritage structures, facilitating the precise monitoring changes over time. The investigation uses a variety of change detection algorithms, including the Iterative Closest Point (ICP) algorithm, which is renowned for its robust registration capabilities in aligning point clouds with high accuracy. The combination of ICP with deviation analysis and feature-based methods allows for the effective identification of alterations, including deformations, material loss, and surface degradation. This methodology establishes a comprehensive framework for the monitoring of Cultural Heritage, thereby enabling timely and targeted preservation efforts. The results emphasise the substantial contribution of dense point cloud analysis to the enhancement of heritage management and the safeguarding of vulnerable architectural sites.

Extreme atrophy of the maxilla poses still challenging for the clinicians. Some of the techniques used could be complex, risky, expensive, time consuming and should be performed, preferably, only by skilled surgeons. Most the commonly used techniques have been reported to have very high success percentages; however, sometimes complications may occur. In this regard, Premaxillary Device (PD) is a technique that has been devised to render more simple the reconstruction of extremely atrophic maxilla, trying to avoid more complicated and risky surgical procedures. Finite Element Analysis (FEA) allows evaluation of several differen aspects of dental implant biomechanics. Our results showed that the use of PD allows an optimal distribution of the stresses on the basal bone, avoiding tension peaks that could determine bone resorption or, even, implant failure. ANSYS has been used to perform this type of localized finite element analysis; with this type of analysis, it was possible to analyze the peri-crestal area of the plant more precisely and the PD through a more accurate reconstruction of the mesh element, which allowed us to mathematically solve the FEA solution. A most favorable biomechanical behavior has been found for the materials such as titanium alloys and reduce stress levels for bone, implants, screws, and abutments. Moreover, the stress values did not exceed bone strength limits for basal bone and titanium alloy. In conclusion, from a biomechanical point of view, PD could be considered a viable alternative for rehabilitation of severe atrophic maxilla.

Today, dental implantology is a reliable technique for the treatment of partial and total edentulism. The fixing of dentures on dental implants can be achieved by a number of different techniques. The choice of technique depends on the specific needs of the patient, the condition of the jawbone and the design of the prosthesis itself. Currently, the two most common types of prosthetic abutment connections are cemented or screwed connections, both of which have disadvantages and ad-vantages. The aim of this study is to analyze, with Finite Element Analysis (FEA), a new Cone Morse connection system between the prosthesis and implant. The connection retention has been analyzed by adopting three different approaches: analytical, in vitro and the FEA method. The systems formed by abutment, healing-cap, and crown with three different inclination conditions were modeled in 3D: 0°, 15° and 30°. With Ansys finite element software, the effect of tilt on system retention was studied. The FEA analysis showed comparable results with in vitro studies regarding the retention strength for an abutment-cap system with a taper of 4°, obtaining 66.6 N compared to 68 N calculated through an in vitro study. The inclination of the abutment affects the retention of the system because the hole made on the surface of the abutment, decreases the contact area between the components. The Cone Morse prosthesis implant connection system is the most stable and efficient system compared to the threaded or cemented system. Retention is influenced by factors such as abutment conicity, insertion strength and the contact surface be-tween components.

Previous studies on the mechanisms underlying willed actions reported that the premotor cortex may be involved in the construction of motor awareness. However, its exact role is still under investigation. Here we investigated the role of the dorsal premotor cortex (PMd) in motor awareness by modulating its activity applying inhibitory rTMS to PMd, before a specific motor awareness task (under three conditions: without stimulation, after rTMS and after sham stimulation). During the task, subjects had to trace straight lines to a given target, receiving a visual feedback of the line trajectories on a computer screen. Crucially, in most trials the trajectories on the screen were deviated and to produce straight lines, subjects had to correct their movements towards the opposite direction. After each trial, participants were asked to judge whether the line seen on the computer screen corresponded to the line actually drawn. Results show that participants in the no stimulation condition did not recognize the perturbation until 14 degrees of deviation. Importantly, active, but not sham, rTMS significantly modulated motor awareness, decreasing the amplitude of the angle at which participants became aware of the trajectory correction. These results suggest that PMd plays a crucial role in action self- monitoring.

The purpose of this study is to identify gender by highlighting common coordinates and discriminating coordinates in the two sexes through palatal rugoscopy, comparing sagittal sections of the hard palate and evaluating the assistance given by digital technology and its applicability in this method. In this study, 85 digital impressions were examined. The impressions were in .stl format. The palatal rugae, retroincisal papilla, and the palatal cusps of the second premolars were isolated using Meshmixer software (Autodesk Inc., San Rafael, CA, USA) by eliminating everything else from the scan. Then the impressions were aligned using the same software so as to be subsequently imported to Geomagic® Control 14 software (3D System, NC, USA). Results: 2,223 impression sections were studied and 145 coordinates that were present with a frequency greater than 50% in one or both groups were obtained: 52 discriminating traits (DT) in the male group, 29 discriminating traits in the female group, and 64 common traits (CT). The sum of all the coordinates found in the 57 impressions was 9,328: 4,569 in the male group and 4,759 in the female group (P=0). The DTs in the female group showed no statistically significant difference from the same coordinates in the male one (P=0.832). Statistically significant differences were observed in the DTs in the male group compared to the same coordinates in the female group (P=0.018). No statistically significant differences were observed in the frequency of DTs in both sexes (P=0.056). Further research in forensic odontology is needed to determine its scientific certainty. It is certain that digital technology may one day be a valuable support for the forensic odontologist but to date the lack of dedicated and certified programs limits its reliability.

Welding between two or more pieces of metal is a widely used practice in various fields of medicine such as dentistry which also makes use of the support of dental laboratories where complex welding procedures are applied. The welding techniques available today are many and also very different from each other; they often require very different background knowledge, just as the results obtained may differ. Welds can be made at various stages of making a product that will be used on the patient; for example some welds are made directly by the manufacturer during the industrial processing phase. We then move on to the more common welding techniques carried out in dental laboratories and finally we also arrive at the intraoral welding carried out by the clinician inside the patient's oral cavity. This enormous variety of conditions in which those who practice welding can find themselves presupposes the application of the most appropriate technique; this review looks at the different methods and fields of application.

Peri-implant bone resorption has been reported around some implants after loading and this could create problems for the long-term stability of peri-implant soft and hard tissues. The causes are still not completely known, but a relevant importance could be assumed by the presence of a bacterial contamination at the micro-gap level of the implant-abutment junction. In this regard, external and internal implant-abutment assemblies have been shown to be much more permeable to bacterial colonization than Cone-Morse or conical connections. A subcrestal implant placement could have aesthetic advantages allowing a better prosthetic emergence profile. In literature controversial experimental and clinical results have been reported about bone resorption around implants placed equicrestally and subcrestally. Interestingly, Finite Element Analysis (FEA) studies revealed to be extremely useful for assessing the peri-implant bone strain and stress. Thus, the aim of this study was a FEA evaluation of implants with a Cone-Morse implant-abutment assembly (Implacil De Bortoli, São Paulo, Brazil) inserted into a bone block model (width: 10 mm, vertical height: 17.5 mm, thickness of the cortical area: 1.5 mm) mimicking equicrestal and subcrestal placements (1 and 2 mm). The results demonstrated that maximum stresses were observed within the cortical bone around the equicrestally placed implants, the lowest in the implant placed 2-mm subcrestally and intermediate stresses within the implant placed 1-mm subcrestally. Cortical bone was more stressed under lateral loads than axial loads. In conclusion, this FEA study suggested that implant placement at -1 mm could be recommended.

Human exposure to carbon nanotubes (CNTs) can cause health issues due to their chemical–physical features and biological interactions. These nanostructures cause oxidative stress, also due to endogenous ROS production, which increases following mitochondrial impairment. The aim of this in vitro study was to assess the health effects, due to mitochondrial dysfunction, caused by a sub-chronic exposure to a non-acutely toxic dose of multi walled CNTs (raw and functionalised). The A549 cells were exposed to MWCNTs (2 µg mL^-1) for 36 days. Periodically, cellular dehydrogenases, pyruvate dehydrogenase kinase 1 (PDK1), cytochrome c release, permeability transition pore (mPTP) opening, transmembrane potential (Δψ m), apoptotic cells, and intracellular ROS were measured. The results, compared to untreated cells and to positive control formed by cells treated with MWCNTs (20 µg mL^-1), highlighted the efficiency of homeostasis to counteract ROS overproduction, but a restitutio ad integrum of mitochondrial functionality was not observed. Despite the tendency to restore, the mitochondrial impairment persisted. Overall, the results underlined the tissue damage that can arise following sub-chronic exposure to MWCNTs.

Background The main aim of reconstructive surgery (RS) is to restore the integrity of soft tissues damaged by trauma, surgery, congenital deformity, burns or infection. Microsurgical techniques consist of harvesting tissues that are separated from the vascular sources of the donor site and anastomosed to the vessels of the recipient site. In these procedures, there are some preoperative modifiable factors that have the potential to influence the outcome of the flap transfer and its anastomosis. Methods Chronic inflammatory anaemia (ACD) is a constant condition in patients who have undergone RS and correlates with the perfusion of the free flap. In RS, it is important to maintain good tissue oxyporesis, avoiding blood hyperviscosity. From January 2017 to September 2019, we studied 16 patients (16 males, mean age 38 years) who underwent microsurgical procedures for RS. Haemoglobin (Hb) levels, Corpuscular Indexes, Transferring saturation (TSAT) ferritin concentrations and creatinine clearance have been measured the first day after surgery (T0), after the first week (T1) and after five weeks (T2). At T0 all patients showed low hemoglobin levels (average 7.4 g/dl, STD 0,71range 6,2-7,4 g dL-1), with an MCV of 72, MCH 28, MCHC 33, RDW 16, Sideremy 35, Ferritin 28, Ret% 1,36, TRF 277 and Creatinine Clearance 119. . We assessed all patients for clinical status, medical history and comorbidities before starting therapy. Results. In collaboration between the two departments, we started a therapeutic protocol with erythropoietic stimulating agents (ESAs) (Binocrit 6000 UI/week) and intravenous iron every other day, on the second day after surgery. Thirteen patients received ESAs and FCM (500-1000 mg per session), three patients received ESAs and iron gluconate (1 vial every other day). No patients received blood transfusions. No side effects were observed and, most importantly, no limb or flap rejection. Conclusions Preliminary data from our protocol show an optimal therapeutic response in a surgical setting with limited data in the scientific literature. The enrolment of further patients will allow us to validate this therapeutic protocol with statistically significant data.

Monitoring the integrity of aeronautical structures is fundamental for safety. Structural Health Monitoring Systems (SHMS) perform real-time monitoring functions, but their performances must be carefully assessed. In this work the damage detection performances of a strain-based SHMS, were evaluated on a composite helicopter rotor blade root. The SHMS monitored the bonding between the central core and the surrounding antitorsional layer. A damage detection algorithm was trained through Finite Element analyses performed on the component. The effects of the loads variability and of damages were decoupled by including a load recognition step in the algorithm. Load recognition was accomplished in different ways: version#1 adopted an Artificial Neural Network (ANN) trained on blades in pristine condition; version#2 was trained also on damaged blades; version#3 adopted a calibration matrix method. Anomaly detection, damage assessment, and localization were performed by using an ANN. Results showed a higher load identification and anomaly detection accuracy for version#1 and version#2 compared to version#3. Gaussian noise reduced anomaly detection and damage assessment performances, and reduced damage localization accuracy for bigger damages. The damage detection performance were obtained for a fibre optic based-SHMS, including the trade-off between probability of detection and false alarm rate for different damage sizes.

Our understanding of the fate and distribution of micro- and nano- plastics in the marine environment and their impact on the biota compartment is limited by the intrinsic difficulties of conventional analytical techniques (light scattering, FT-IR, Raman, optical and electron microscopies) in the detection, quantification and chemical identification of small particles in liquid samples. Here we propose the use of optical tweezers, a technique awarded in 2018 with the Nobel prize, as an analytical tool for the study of micro- and nano- plastics in sea water. In particular, we exploit the combination of optical tweezers with Raman spectroscopy (Raman Tweezers, RTs) to optically trap plastic particles with sizes from tens of µm down to 90 nm and unambiguously reveal their chemical composition. RTs applications are shown on particles made of the most common plastic pollutants, including polyethylene, polypropylene, nylon and polystyrene, that are artificially fragmented and aged directly in seawater. RTs allow us to assess the size and shapes of microparticles (beads, fragments, fibers) and can be applied to investigate particles covered with organic layers. Furthermore, operating at the single particle level, RTs enable unambiguous distinction of plastic particles from marine microorganisms and seawater minerals, overcoming the capacities of standard Raman spectroscopy in liquid, limited to average measurements. Coupled to suitable extraction and concentration protocols, RTs could have a strong impact in the study of the fate of micro and nanoplastics in marine environment, as well as in the understanding of the fragmentation processes on a multi-scale level.

Silicon-based thin-films and nanostructures are of paramount importance in a wide range of applications, including microelectronics, photovoltaics, large area sensors, as well as biomedicine. The wide accessibility of silicon and its relatively low cost have driven a continuous improvement of the technology based on this element. Plasma technology has been widely used for the synthesis of coatings and nanostructures based on silicon. Moreover, it has given a fundamental contribution for continuously improving the control of the physicochemical properties of silicon-based materials, and for allowing the synthesis of nanometric structures with well-defined shape and morphology. In this work, we have reviewed the most interesting developments of plasma-assisted processed for the synthesis of Si-based materials, both inorganic and organic, in the last five years. A special attention has been given to the new techniques, or modifications of already existing ones, that open new possibilities for the synthesis of materials with new properties, as well as nanostructures with novel characteristics.

Ecological information of invasive alien species are crucial for their effective management. How-ever, they are often lacking in newly invaded ecosystems. This is the case of the European catfish Silurus glanis L. in Lake Maggiore where the species is present since 1990 but no scientific infor-mation are available on its ecology. To start filling this knowledge gap, 236 catfish (67 cm to 150 cm of total length) were collected, measured, and dissected for stomach content analyses from three localities and in two habitats (littoral vs. pelagic) in late autumn/early winter. NPUE and BPUE (individuals and biomass (g) per unit effort (m2)) of catfish was generally higher in littoral (NPUE > 0.01; BPUE > 96) than pelagic habitats (NPUE < 0.009; BPUE < 114) but catfish had, on average, larger sizes in pelagic habitats. Overall, 581 individual prey items were recorded belonging to12 taxa. Pelagic catfish specialized their diet exclusively on three prey fish (coregonids, shad and roach) whilst the diet of littoral catfish was more variable, and was dominated by crayfish, perch, and roach. These results highlighted for the first time the interaction of larger catfish with the lake’s pelagic food web, and thus possible consequences are discussed, including the potential contrasting role S. glanis may have for the lake’s fishery.

Unmanned aerial vehicles (UAVs), commonly known as drones, present a cost-effective solution for the swift collection of data from vast and remote areas that are otherwise difficult to access. The Mediterranean Basin, known for being a hot spot for plant biodiversity, hosts several habitats and taxa of significant naturalistic value. However, many of these areas are often inaccessible to botanists, making exploration and research challenging. The aim of this paper is to involve the utilization of drone surveys and open-source software for botanical research. Our primary goal is to show the effectiveness of these tools in the field and demonstrate their practical application in Natura 2000 sites. The protected area chosen for this research is Rocca di Novara, situated in northeastern Sicily. Thanks to our drone investigations, we were able to capture images of the mountain’s side that is inaccessible to humans. This allowed us to observe the habitat of some species in detail. One of the most fascinating discoveries was the reappearance of Saxifraga callosa subsp. australis, which had not been confirmed in this area for over 140 years. Using drones for botanical research can boost field research, making monitoring easier and more cost-effective over time, especially in Natura 2000 sites.

Backgound: Exosomes are extracellular nanovesicles, carriers of different biomolecules such as lipids, proteins, nucleic acids. Their composition and the fact that their release dramatically increases in case of tumorigenesis, opens different scenarios on the possible application in the research for new biomarkers.Methods: The most widely applied methodologies include ultracentrifugation techniques, size-based techniques, immunoaffinity capture-based techniques (mainly ELISA) and precipitation. To optimize the acquisition of exosomes from the reference sample, more techniques can be applied in sequence for a single extraction, determining an increase in labor time and costs. Results: The analysis of PSA-expressing exosomes provides an incredibly accurate way to discriminate between healthy patients and those with prostate disease. Specifically, IC-ELISA alone method achieved 98.57% sensitivity and 80.28% specificity in discriminating prostate cancer (PC) from benign prostatic hyperplasia (BPH).An immunocapture-based ELISA assay was performed to quantify and characterize carbonic anhydrase (CA) IX expression in exosomes. The results revealed that CA IX positive exosomes were 25-fold higher in plasma samples from PC patients than in those from healthy control. Conclusions: The analysis of PC-linked exosomes represents a promising diagnostic model that can effectively distinguish patients with PC from those with non-malignant prostatic disease, However, the use of exosome analysis in clinical practice is currently limited by several issues, including a lack of standardization in the analytical process and high costs, which are still too high for a large-scale use.

The rapid and accurate detection of viruses and the discovery of single nucleotide polymorphisms (SNPs) are crucial for disease management and understanding viral evolution. In this study, a pipeline for virus detection, validation, and SNP discovery from next-generation sequencing (NGS) data is presented. By integrating state-of-the-art bioinformatics tools with artificial intelligence, the pipeline processes raw sequencing data to identify viral sequences with high accuracy and sensitivity. Before aligning the reads to the reference genomes, quality control measures and adapter trimming are performed to ensure the integrity of the data. Unmapped reads are subjected to de novo assembly to reveal novel viral sequences and genetic elements. The effectiveness of the pipeline is demonstrated by the identification of virus sequences, illustrating its potential for the detection of known and emerging pathogens. SNP discovery is performed using a custom Python script that compares the entire population of sequenced viral reads to a reference genome. This approach provides a comprehensive overview of viral genetic diversity and identifies dominant variants and a spectrum of genetic variations. The robustness of the pipeline is confirmed by the recovery of complete viral sequences, which improves our understanding of viral genomics. This study highlights the synergy between traditional bioinformatics techniques and modern approaches, providing a robust tool for analyzing viral genomes and contributing to the broader field of viral genomics.

Energy system modelling is an essential practice to assist a set of heterogeneous stakeholders in the process of defining an effective and efficient energy transition. From the analysis of a set of open source energy system models, it has emerged that most models employ an approach directed at finding the optimal solution for a given set of constraints. On the contrary, a simulation model is a representation of a system that is used to reproduce and understand its behaviour under given conditions, without seeking an optimal solution. Given the lack of simulation models that are also fully open source, in this paper a new open source energy system model is presented. The developed tool, called Multi Energy Systems Simulator (MESS), is a modular, multi-node model that allows to investigate non optimal solutions by simulating the energy system. The model has been built having in mind urban level analyses. However, each node can represent larger regions allowing wider spatial scales to be be represented as well. MESS is capable of performing analysis on systems composed by multiple energy carriers (e.g. electricity, heat, fuels). In this work, the tool’s features will be presented by a comparison between MESS itself and an optimization model, in order to analyze and highlight the differences between the two approaches, the potentialities of a simulation tool and possible areas for further development.

We report on a new form of nanoscale carbon nitride in the shape of single layer half dome structures grown on the step edges of boron nitride sheets. The half dome structure grown on the step edges of boron nitride sheets. The half dome structures are formed spontaneously at high temperature using Iron oxide nanoparticles capped with tetremethylammonium hydroxide supported on BN sheets. During the combustion process the support, firstly, acted as a reducing agent, secondly, as a source of nitrogen that permitted the transformation of the organic capping agent in sp1 CN chains linked with sp2 CN domains. During the Ostwald ripening process smaller nanoparticles migrates towards bigger nanoparticles, when the nanoparticles come across the step edges of few layer boron nitride sheets the half dome structure is formed. This new method of synthesis has demonstrated for the first time the formation of half dome structures containing cyanopolyynes sp1 chains and sp2 carbon nitride domains.

After the influenza H1N1 pandemic of 2009, the seasonal A/Brisbane/59/2007 strain was replaced by the A/California/07/2009 strain for the influenza virus vaccine composition. After several seasons with no indications on the occurrence of antigenic drift, A/Michigan/45/2015 was chosen as the H1N1 vaccine strain for season 2017/2018. Since the immune response to influenza is shaped by the history of exposure to antigenically similar strains, the potential cross-protection between seasonal human influenza vaccine strains and the emerging pandemic strains was investigated. Human serum samples were tested by haemagglutination inhibition and single radial haemolysis assays against A/Brisbane/59/2007, A/California/07/2009, and A/Michigan/45/2015 strains. Strong cross-reactions between A/California/07/2009 and A/Michigan/45/2015 strains were observed in 2009/2010, most likely induced by the start of the 2009 pandemic, and the subsequent post-pandemic seasons from 2010/2011 onwards when A/California/07/2009 becomes the predominant strain. In 2014/2015 season, population immunity against A/California/07/2009 and A/Michigan/45/2015 strains increased again, associated with strong cross-reactions. While haemagglutination inhibition assay has a higher sensitivity for detection of new seasonal drift, the single radial haemolysis assay is an excellent tool to determine the presence of pre-existing immunity, allowing a potential prediction on the booster potential of influenza vaccines against newly emerging drifted strains.

Glioblastoma is a solid, infiltrating and the most frequent highly malignant primary brain tumor. Our aim was to find the prognostic value of mutations of IDH1, MGMT, EGFR, p53, ATRX, Ki67 genes and the correlation between sex, age, presenting with seizures, number of interventions, extent of resection with Overall Survival (OS), Progression Free Survival (PFS) and Karnofsky performance status (KPS) score. A randomized retrospective analysis of 122 patients treated by a single operator at Sapienza University of Rome, was carried out. After surgery patients followed standard treatment Stupp protocol [6]. Exclusion criteria were: patients with primitive brainstem and spinal cord gliomas and patients who underwent partial resections (resection < 90%) and cases of brain biopsy exclusively for diagnostic purposes. Statistical analysis with a simultaneous regression model was carried on by SPSS 25 ® (IBM) program. Results showed statistically significant survival increase in four groups: 1) patients treated with gross total resection (p< 0.03); 2) patients with methylated MGMT promoter (p<0.005); 3) patients with non EGFR amplification or EGFRvIII mutation (p<0.035); 4) mutated IDH1/IDH2 (p<0.0161). Higher survival rates (but not statistically significant) were observed also in patients with: age < 75 years, Ki 67 <10%, lesions in non eloquent areas, ATRX gene mutation and presentation with seizures.

Graphs are largely used in computer science to model relations, or associations, among entities the compose complex systems. More recently, they found a broad field of application in bioinformatics and medical informatics supporting modelling, analysis of many systems. The applications span from representing interactions among molecules within cells, to model the functions of the brains. In order to support research, algorithms from graph theory that are able to extract knowledge from network should be coupled to efficient visualisation techniques. Although the importance of such topic, we retain that many challenges should be faced in the futures, such as automated pathway and network layout to better match biologists’ needs, the developing of a standard able to give more and better choices to represent nodes, edges finally, the developing of automated mechanism able to improve the network navigation methods that help users manage large and complex networks with the goal to improve the usability.

(1) Background: This paper investigates the epidemiological risk related to temperature before and during COVID-19 in Italy; (2) Methods: Deaths in 2015-2019 and temperatures were correlated. Excess and COVID-19 deaths were examined to estimate the relationships with temperatures; (3) Results: Annual deaths were higher during the cold months (+45,000, SD = 4,700, S = 21). The scenario worsened during COVID-19. Mortality was higher during minimum temperature periods, although the curve moderately rose in the warmest months (r = -0.75, 95% CI = [-0.87; -0.56], S = 23). COVID-19 deaths showed a decreasing seasonality. Monthly excess deaths during COVID-19 were high (+4,200, IQR = [2,800; 8,000], S = 28) with a doubt of seasonality. COVID-19 mortality was correlated with regional latitude (r = 0.86, 95% CI = [0.68; 0.94], S = 20). Discrepancies between COVID-19 and excess deaths were found. The exposed population was subject to aging; (4) Conclusions: The epidemiological risk in Italy is seasonal and geographically dependent. Low and very high temperatures can lead to mortality peaks. Therefore, COVID-19 and any other epidemiological risk must be evaluated in light of this evidence. Health systems need to be strengthened during cold and extremely hot periods. Future research should investigate these phenomena at the causal level.

Neural or mental simulation of actions is a powerful tool for allowing cognitive agents to develop Prospection Capabilities that are crucial for learning and memorizing key aspects for challenging skills. In previous studies we developed an approach based on the animation of the redundant human Body Schema based on the Passive Motion Paradigm (PMP). In this paper we show that this approach can be easily extended to hyper-redundant serpentine robots as well as to hybrid configurations where the serpentine robot is functionally integrated with a traditional skeletal infrastructure. A simulation model is analyzed in detail showing that it incorporates spatio-temporal features discovered in the biomechanical studies of biological hydrostats like the elephant trunk or the octopus tentacles. It is proposed that such generative internal model can be the basis for a cognitive architecture appropriate for serpentine robots, independent of the underlying design and control technologies. Although robotic hydrostats have received a lot of attention in the last decades, the great majority of research activities have been focused on the actuation/sensorial/material technologies that can support the design of hyperredundant soft robots as well as the related control methodologies. The cognitive level of analysis has been limited to motion planning, without addressing synergy formation and metal time travel. This is where the contribution of the paper is focused on.

Ensuring safe and continuous autonomous navigation in long-term mobile robot applications is still challenging. To ensure a reliable representation of the current environment without the need for periodic re-mapping, updating the map is recommended. However, in case of incorrect estimation of robot pose, updating the map can lead to errors that prevent the robot localisation and jeopardize map accuracy. In this paper, we propose a safe LIDAR-based occupancy grid map updating algorithm for dynamic environments taking into account the uncertainties in the estimation of the robot’s pose. The proposed approach allows robust long-term operations as it can recover the robot’s pose, even when it gets lost, to continue the map update process providing a coherent map. Moreover, the approach is robust also to temporary changes in the map due to the presence of dynamic obstacles such as humans and other robots. Results highlighting map quality, localisation performance, and pose recovery, both in simulation and experiments, are reported.

This study investigates the effectiveness of a range of timber-based solutions for seismic and energy retrofitting of existing masonry buildings. These solutions are designed not only to prevent structural collapse during earthquakes but also to create integrated interventions that enhance thermo-physical performance and reduce emissions in existing buildings. Various case scenarios were considered and both mechanical and energetic behavior post-intervention were evaluated. Timber-engineered products serve as foundational components for the retrofit approach, encompassing one-dimensional vertical elements (strong-backs) and various types of panels (cross-laminated timber panels, laminated veneer lumber panels, and oriented strand board panels). The analyzed retrofit techniques share a common principle, involving the attachment of these timber-based elements to the building's wall surfaces through mechanical point-to-point connections. The proposed solutions integrate strong-backs and timber panels with membranes and insulation layers, yielding cohesive and highly effective interventions. Finite element modeling was employed to analyze the mechanical and thermal responses of the retrofitted walls. A comprehensive comparative analysis of various techniques was conducted to determine the most effective solution for each specific scenario.

The Italian Stone Pine (Pinus pinea L.) is one of the most employed ornamental trees in towns with Mediterranean climates. For example, in the city of Rome, Pinus is the most common genus, with more than 51,000 trees. This study investigates technical and economic features of maintenance operations of Stone Pines and evaluates the productivity and costs of the observed yards. Pruning and felling are the most frequent management operations of trees in towns and this study analyzes the features of these operations carried out in 14 work sites. The operations were carried out either with aerial platforms (19 trees) or ascending the crown by tree-climbing (6 trees). The operations were sampled with time studies (12 trees for pruning and 13 for felling). Work time was measured from the beginning of operations to the transport of the residual biomass to the collection and loading point, using centesimal stopwatches and video recording. The total residual biomass was weighed or assessed. Total observation time amounted to 63.1 hours. The evaluation of the costs of each work site considered the fixed and the variable costs and the costs for the labor force. A Multiple Linear Regression model (statistics: determination coefficient R2: 0.74, adjusted R2: 0.67, p-value < 0.001) which utilizes four regressors easily evaluable before the work, was adopted to predict the gross time of the operations. This paper can contribute to optimize trees maintenance methods in urban sites and to assess the potential residual wood biomass attainable from urban forestry maintenance in the city of Rome.

Idiopathic acute pancreatitis (IAP) presents a diagnostic challenge and refers to cases where the cause of acute pancreatitis remains uncertain despite a comprehensive diagnostic evalua-tion. Endoscopic ultrasound (EUS) has emerged as a valuable tool in the diagnostic workup of IAP. This review explores the pivotal role of EUS in detecting the actual cause of IAP, as-sessing its accuracy, timing, safety, and future technological improvement. Following PRISMA guidelines, 60 pertinent studies were selected and analysed. EUS emerges as a cru-cial diagnostic tool, particularly when conventional imaging fails. It can offer intricate visu-alization of the pancreas, biliary system, and adjacent structures. High accuracy of EUS is evident in detecting the actual causes of IAP such as microlithiasis, small bile duct stones, pancreas divisum, and small pancreatic tumors. Optimal timing for EUS is post-resolution of the acute phase of the disease. EUS, when conducted by experienced endoscopists, it boasts minimal safety concerns, and is crucial to prevent complications. EUS-guided interventions, including fine-needle aspiration, collection drainage, and biopsies, aid in cytological analy-sis. With high diagnostic accuracy, safety, and therapeutic potential, EUS is able to improve patient outcomes when managing IAP. Further refinement of EUS techniques and cost-effectiveness assessment of EUS-guided approaches need to be explored in multicenter prospective studies. This review underscores EUS as a transformative tool in unraveling IAP's enigma and advancing diagnostic and therapeutic strategies.

The COVID-19 appears as a catastrophic health risk with psychological, emotional, social and relational implications. From the early stages of the virus spread, the elderly population was identified as the most vulnerable and the health authorities have rightly focused on such frailest population. Conversely, less attention was paid to emotional and psychological dimension of children and adolescents. Actually, they were less at risk quoad vitam or quoad valetudinem, nevertheless they had to face a reality of anxiety, fears and uncertainties. The current study investigated state anxiety and emotion awareness in a healthy sample of older adolescents, 84 females and 64 males, aged 17 to 19, during the pandemic lockdown, using Self-rating Anxiety Scale and the Italian Emotion Awareness Questionnaire. An unexpected anxious phenomenology, impacting the anxiety ideo-affective domain, was found, while the somatic symptomatology appeared to be less severe. The highest anxiety symptom were the breathing difficulties. These findings supported the hypothesis that the COVID-19 pandemic may be a risk condition for an increased state anxiety in older adolescents and suggest the need to provide 1. an effective, empathic communication system with the direct participation of older adolescents, 2. a psychological counseling service for stress management of adolescents.

During embryonic development stem cells undergo the differentiation process so that they can specialise for different functions within the organism. Complex programs of gene transcription are crucial for this process to happen. Epigenetic modifications and the architecture of chromatin in the nucleus, by the formation of specific regions of active as well as inactive chromatin, allow the coordinated regulation of the genes for each cell fate. In this mini review, we discuss the current knowledge regarding the regulation of three-dimensional chromatin structure during neuronal differentiation. We also focus on the role played in neurogenesis by the nuclear lamina that ensures the tethering of the chromatin to the nuclear envelope.

We propose a novel interpretation of consciousness and an enlarged definition of locality, which provide a solution to the problem of the consistency of measurements in quantum mechanics: consciousness is a characteristics of the Universe as a whole. Besides its physical conse- quences, this interpretation has also moral implications: individuality comes out naturally to be just an accident functional to evolution which shaped past and present history through competition, and re- alizing this fact should enforce cooperation.

Recently, many independent research project focus on the study of the molecular basis of aging processes. I parallel, the different progression of many diseaes between sex is a hot topic research area. These studies require many data, models and tools for inferring aging and sex specific molecular machinaries. Among the others, the Genotype-Tissue Expression (GTEx) database is one of the preminent resources for the analysis of expression data related to tissues, sex and age. The current version of the database has a lot of querying interface that enable many analysis centered on the expression of genes on tissues. Despite this the database lacks on the analysis at sex/age level, thus the researcher has to download data and then write queries by hand. Nevertheless it lacks on the integration with existing protein interaction data. Therefore, the need for the introduction of tools enabling easy access and powerful analysis capabilities (i.e. state of the art network based analysis and integration), arises. We here present NOMA-DB a framework for the analysis of age related genes based on the GTEx database that enable easy querying at sex/age level, network based analysis. The framework is based on wrapping the GTEx database and on building an application logic level on top of existing data. The current version enables the analysis of genes by tissue, gene and age, thus it may be used in potentially future directions of analysis towards better comprehension of aging/sex-related molecular machineries based on the analysis of expression dat

In the paper, the authors express the Fuss–Catalan numbers as several forms in terms of the Catalan–Qi function, find some analytic properties, including the monotonicity, logarithmic convexity, complete monotonicity, and minimality, of the Fuss–Catalan numbers, and derive a double inequality for bounding the Fuss–Catalan numbers.

Inside hippocampal circuits, neuroplasticity events that individual cells may undergo during synaptic transmissions occur in the form of Long Term Potentiation (LTP) and Long Term Depression (LTD). The high density of NMDA receptors expressed on the surface of the dendritic CA1 spines confers to hippocampal CA3-CA1 synapses, the ability to easily undergo NMDA-mediated LTP and LTD, that is essential for some forms of explicit learning in mammals. Providing a comprehensive kinetic model that can be used for running computer simulations of the synaptic transmission process is currently a major challenge. Here, we propose a compartmentalized kinetic model for CA3-CA1 synaptic transmission. Our major goal was to tune our model in order to predict the functional impact caused by disease associated variants of NMDA receptors related to severe cognitive impairment. Indeed, for variants Glu413Gly and Cys461Phe, our model predicts negative shifts in the glutamate affinity and changes in the kinetic behavior, consistent with experimental data. These results pinpoint to the predictive power of this multiscale viewpoint, which aims to integrate the quantitative kinetic description of large interaction networks typical of system biology approaches with a focus on the quality of few, key, molecular interactions typical of structural biology ones.

The conformational state of the activation loop (A-loop) is pivotal for the activation of most protein kinases. Hence, the characterization of the conformational dynamics of the A-loop is important to increase our understanding of the molecular processes related to diseases and to support the discovery of small molecule kinase inhibitors. Here, we carry out a combination of Molecular Dynamics (MD) and Essential Dynamics (ED) analyses to fully map the effects of phosphorylation, ADP, and conformation disrupting (CD) inhibitors (i.e., CD532 and MLN8054) on the dynamics of the A-loop of Aurora-A. MD revealed that the stability of the A-loop in an open conformation is enhanced by single phospho-Thr-288, while paradoxically, the presence of second phosphorylation at Thr-287 decreases such stability and renders the A-loop more fluctuant in time and space. Moreover, we found that such post-translational modification has a significant effect on the direction of A-loop motions. ED analysis suggests that the presence of the phosphate moiety induces the dynamics of Aurora-A to sample two distinct energy minima, instead of a single large minimum, as in unphosphorylated Aurora-A states. This suggests that the conformational distributions of Aurora-A with both single and double phospho-threonine modifications are remarkably different from the unphosphorylated state. In the closed states, binding of CD532 and MLN8054 inhibitors has the effect of increasing the distance of the N- and C-lobes of the kinase domain of Aurora-A, and the angle analysis between those two lobes during MD simulations showed that the N- and C-lobes are kept more open in presence of CD532, compared to MLN8054. As the A-loop is a common feature of Aurora protein kinases, our studies provide a general description of the conformational dynamics of this structure upon phosphorylation and different ligands binding.

Dyslipidemia (Dys) is a disease characterised by abnormally high levels of lipids in the 1 blood. It causes the deposits of lipids on the arterial wall, leading to the insurgence of atherosclerosis, 2 i.e. the increased thickness of arterial walls, which finally increases the risk of cardiovascular diseases. 3 Dyslipidemia is as comorbidity of Type 2 Diabetes Mellitus (T2DM). A set of genes has been associated 4 with dyslipidemia, but examining the regulation of such genes in age and sex is still an open research 5 field. In this study, starting from publicly available databases, we select genes associated with 6 dyslipidemia and we analyse their basal level changes by means of age and sex. Also studying the 7 networks associated to the genes, we identify the rewiring changes showing that there exists a set of 8 genes whose expression changes with age in: artery tibial, artery aorta and blood. Finally, we report 9 about changes associated to gender atributes in the extracted data

During the last 150 years, the trout-culture industry focused on enhancing trout populations by stocking, in response to the growing anglers’ demand and the habitat degradation associated to the rapid urbanization and hydropower development. The industrialized north of Italy, home to the Italian Alpine and subalpine trout populations, is the source of most of the revenues of the national trout-culture industry. Its rapid growth and the massive introduction of non-native interfertile trouts eroded the genetic diversity of native lineages, leading to harsh confrontations between scientists, institutions, and sportfishing associations. We review here the state of art of the taxonomy and distribution of the northern Italian native trouts, presenting both scientific results and historical documentation. We think the only native trouts in this region are Salmo marmoratus, widespread in this region, plus small and fragmented populations of S. ghigii, present only in the Southwestern Alps. We strongly recommend the interruption of stocking of domesticated interfertile non-native trouts in this area, and recommend the adoption of Evolutionary Significant Units for salmonid fishery management. We further propose future research directions for a sustainable approach to the conservation and ecosystem management of the fishery resources and inland waters of northern Italy.

COVID-19 breakout in Italy has caused a huge number of severely ill patients with a serious increase in mortality. Although lungs seem to be the main target of the infection very few information are available about liver involvement in COVID-19 infection, that could possibly evocate a systemic disease targeting a lot of organs. Since now there are no reports of large series of histological evaluation of liver morphology in this setting. Knowledge of histological liver findings connected to clinical data is crucial in management of this disease.Post-mortem wedge liver biopsies from 48 patients died for COVID-19 infection were available from two main hospitals located in northern Italy, Lombardy; all sample were obtained during autopsies. No patient has a significant clinical complain of liver disease or signs of liver failure before and during hospitalization; for each of them laboratory data focused on liver were available. All liver samples showed minimal inflammation features; on the other side, many histological pictures compatible with vascular alterations were observed, characterized by portal vein braches number increase associated with lumen massive dilatation, partial or complete recent luminal thrombosis of portal and sinusoidal vessels, fibrosis of portal tract, focally severely enlarged and fibrotic. Our preliminary results concerning histological liver involvement in COVID-19 infection confirm the clinical impression that liver failure is not a main concern and this organ is not the target of significant inflammatory damage; histopatological findings are highly suggestive for marked alteration of intrahepatic blood vessel network secondary to systemic alterations induced by virus that could target, besides lung parenchyma, cardiovascular system, coagulation cascade or endothelial layer of blood vessels.

The EU has planned the phase-out of new vehicles based on internal combustion engines in favour of high efficiency electric cars by 2035 (Fit for 55 package). However, many doubts remain about the effectiveness of this choice for each Country of the Union in terms of CO2 emissions reduction, as each State is characterized by a different carbon intensity related to the production of electricity needed to manufacture and recharge vehicles. This study seeks to explore the Italian case. To this aim, carbon intensities related to the electricity production were calculated considering both the Italian electricity mix production at 2021 and those at 2035, envisaged considering two scenarios based on different introductions of renewable sources (RES). Afterwards, the values obtained were adopted for determining the CO2 emissions related to the whole production process of battery systems in Italy (emissions from mining and refining, scrap materials and final assembly included) by comparing some of the most up-to-date Life-Cycle Assessment (LCA) analysis related to the manufacturing cycle of the batteries. Finally, the results were adopted to calculate the starting carbon debit for A, B, C and M car segments for Mild Hybrid, Full Hybrid and Full Electric powertrains. At the same time, statistical road fuel/electricity consumption data were collected and overall CO2 emissions were calculated for the same vehicles for a defined mileage, so to determine break-even points with respect to the cumulative (i.e., from battery and road) carbon emissions. The results showed that advantages related to electric vehicles are significant only if a low carbon intensity related to electricity production is reached by means of a very high introduction of RES, thus keeping the door open for innovative powertrain technologies (plug-in), if fed with low carbon fuels.

Dementia is a major issue for healthcare systems worldwide, necessitating the development of creative and effective strategies for its management. This paper examines the use of Artificial Intelligence (AI) technologies in caring for and managing people with dementia. AI-driven solutions can improve diagnosis, personalize care, optimize medication management, and reduce the burden on caregivers. This paper discusses the implementation of an AI-based framework for creating videos related to people’s memories to support train-therapy or travel- therapy, a non-pharmacological intervention for Alzheimer’s disease patients

Prolonged fatigue is associated with non-pathological causes, and lacks an established therapeutic approach. The current study is aimed at assessing the efficacy of a new food supplement (Improve® Response) based on a chemically characterized pomegranate extract and hydro-soluble vitamins (B complex and C). UHPLC-HRMS analysis of pomegranate extract showed the presence of 59 compounds, with gallotannins and ellagitannins being the most abundant phytochemicals. For the clinical study, 58 subjects were randomized into two groups, 1 and 2 (n = 29, each), which received either the food supplement or placebo. The effects of the food supplement against fatigue were assessed via validated questionnaires, recorded at time intervals t0 (at baseline), t1 (after 28 days), t2 (56 days), and t3 (after follow-up) in combination with the analysis of biochemical markers at t0 and t2. Fatigue Severity Scale (FSS) questionnaire scores were significantly decreased at the t2 and t3 time intervals in subjects treated with the food supplements, while the effect of the food supplement on a 12-Item Short Form Survey (SF-12) was not considerable. Moreover, the food supplement did not significantly affect biochemical parameters associated with fatigue and stressed conditions. This study shows that the food supplement tested reduces prolonged fatigue following two months supplementation in healthy subjects with mild prolonged fatigue.

Acquired immunodeficiency syndrome (AIDS) has transitioned from a progressive, fatal disease to a chronic, manageable disease thanks to better defining of antiretroviral therapy, hence contributing to increased life expectancy. In parallel, a growing number of subjects without overt clinical signs of disease but living with chronic HIV infection (people living with HIV, PLWH) are experiencing early cardiovascular disease worldwide. However, a progressive increase in the prevalence of multiple comorbid diseases has been reported as these patients age, including cardiovascular disease (CVD). Cardiovascular mortality can be either directly related to the viral infection, a progressive reduction of response to the antiretroviral therapy, chronic inflammation or lifestyle-related. Cardiovascular ageing represents a relevant issue in the management of HIV-infected patients. Although the exact pathophysiological mechanism that leads PLWH to develop cardiovascular disease is not entirely understood, there is substantial evidence that they accumulate age-related conditions earlier than the general population. Furthermore, since the proportion of PLWH growing older than 50 years has progressively increased, this results in a complex interaction between disease-related pathophysiology and the exposition of a growing burden of cardiovascular risk factors. For this reason, we performed a systematic review of the genes most frequently associated with ageing in HIV-infected subjects, followed by a bioinformatic analysis to explore the biological impact of the genes related to ageing.

Since the integration of electronic devices and intelligent electronic devices into the power grid, power quality (PQ) has consistently remained a significant concern for system operators and experts. Maintaining high standards of power quality is crucial to prevent malfunctions and faults in electric assets and in connected loads. Recently, PQ studies have shifted their focus to a specific frequency range, previously not considered problematic, the supraharmonic 2kHz–150kHz range. This range is not populated by the harmonic components of the 50-60 Hz mains fundamental, but a combination of intentional emissions, switching and non-linearity by-products and various types of resonances. This paper aims to provide a detailed analysis of the impact of SH on power network operation and assets, focusing on the most relevant documented negative effects, namely power loss and heating of grid elements, aging of dielectric materials, failure of medium voltage (MV) cable terminations, and interference to equipment and to power line communication (PLC) technology in particular. Under some shareable assumptions limits are derived and compared to existing ones for harmonic phenomena, providing a clear identification of the primary issues associated with supraharmonics and suggestions for the standardization process. Strictly related is the problem of grid monitoring and assessment of SH distortion, discussing the suitability of normative requirements for instrument transformers (ITs) with specific focus on their accuracy.

The ovary is the major determinant of female reproductive health. Ovarian functions are mainly related to the primordial follicle pool, which is gradually loss with aging. Ovarian aging and reproductive dysfunctions share oxidative stress as common underlying mechanism. ROS signaling is essential for normal ovarian processes yet can contribute to various ovarian disorders when disrupted. Therefore, balance in the redox system is crucial for proper ovarian functions. In the present study, by focusing on mRNAs and ncRNAs described in the ovary and taking into account only validated ncRNA interactions, we built up an ovarian antioxidant ceRNA network, namely OvAnOx ceRNA, composed of 5 mRNAs (SOD1, SOD2, CAT, PRDX3, GR), 10 miRNAs and 5 lncRNAs (XIST, FGD5-AS1, MALAT1, NEAT1, SNHG1). Our bioinformatic analysis indicated that the components of the OvAnOx ceRNA not only contribute to antioxidant defence, but are also involved in other ovarian functions. Indeed, antioxidant enzymes encoded by mRNA of OvAnOx ceRNA operate within a regulatory network that impacts ovarian reserve, follicle dynamics, and oocyte maturation in normal and pathological conditions. The OvAnOx ceRNA represents a promising tool to unravel the complex dialogue between redox potential and ovarian signalling pathways involved in reproductive health, aging and diseases.

This paper explores the latest developments in electrolysis technology, a key player in the transition to sustainable energy systems. Electrolysis, despite currently contributing a small share to global hydrogen production, holds immense potential for producing green hydrogen. The study delves into the efficiency of electrolysis systems, emphasizing ongoing efforts to enhance energy conversion rates. It investigates the impact of high-temperature electrolysis on reducing electricity consumption, thus making the process more efficient. The paper discusses the various challenges in the research on water electrolysis and underscores the critical role electrolysis plays in integrating renewable energy sources. The study emphasizes the need for continuous advancements in electrolysis technology to bridge existing gaps, making a compelling case for its pivotal role in the green hydrogen revolution.

Background: The aim of this experimental work was to evaluate cheiloscopy potential: to confirm the individual uniqueness of lip prints, to verify the presence of recurrent patterns according to the Suzuki and Tsuchihashi classification and to search for characteristics that can be used in establishing the sex of a subject, with a focus on assessing the method's limitations. Methods: Lip prints were taken from a sample of 172 volunteers using liquid lipstick and transparent adhesive tape and were digitally analyzed. Results: 59 prints (35.3%) were not considered for Suzuki and Tsuchihashi classification due to quality errors and the impossibility of visualizing lip wrinkles in one or more sextants. All the digitized prints revealed themselves to be unique after having been analyzed using superimposition. Qualitatively valid prints indicated a prevalence of Type II in both male and female. A major problem was that the analysis of the same print by different operators often resulted in a different attribution of a Type. Conclusions: The potential of cheiloscopy lies mainly in the matching of prints, given their uniqueness, but the absence of a database greatly limits its use. Additionally, its use for sex identification does not seem to be reliable. It is necessary to establish an acquisition protocol for taking and analyzing prints that could reduce the errors committed by the operator.

Background: The aim of this experimental work was to confirm the individual uniqueness of lip prints, to verify the presence of recurrent patterns according to the Suzuki and Tsuchihashi classification and to search for characteristics that can be used in establishing the sex of a subject. Methods: Lip prints were taken from a sample of 172 volunteers using liquid lipstick and transparent adhesive tape and were digitally analyzed. Results: 59 prints (35.3%) were not considered for Suzuki and Tsuchihashi classification due to quality errors and the impossibility of visualizing lip wrinkles in one or more sextants, all the digitized prints revealed themselves to be unique after having been analyzed using superimposition. Qualitatively valid prints indicated a prevalence of Type II in both male and female and the presence of sex-linked features. A major problem was that the analysis of the same print by different operators often resulted in a different attribution of a Type. Conclusions: The potential of cheiloscopy lies mainly in the matching of prints, given their uniqueness, and can be a valid tool in gender determination but the absence of a database greatly limits its use. It is necessary to establish an acquisition protocol for taking and analyzing prints that could reduce the errors committed by the operator.

This article examines the evolution of bariatric surgery, with a focus on emerging technologies such as robotics and laparoscopy. In the case of gastric bypass, no significant differences have emerged between the two techniques in terms of hospitalization duration, weight loss, weight regain, or 30-day mortality. Robotic surgery, while requiring more time in the operating room, has been associated with lower rates of bleeding, mortality, transfusions, and infections. In revisional bariatric surgery, the robotic approach has shown fewer complications, shorter hospital stays, and a reduced need for conversion to open surgery. In the case of sleeve gastrectomy, robotic procedures have required more time and longer post-operative stays but have recorded lower rates of transfusions and bleeding compared to laparoscopy. However, robotic surgeries have proven to be more costly and potentially more complex in terms of post-operative complications. The review has also addressed the topic of the single anastomosis duodeno-ileal switch (SADIS), finding comparable results between robotic and laparoscopic techniques, although robotic procedures have required more time in the operating room. Robotic technology has proven to be safe and effective, albeit with slightly longer operating times in some cases.

In this work, we experimentally investigate mass and heat transport phenomena in a modular device while converting a solution salinity difference into a temperature difference. Operations occur under fixed total ambient pressure and without mechanical moving parts, thus realizing a fully static conversion. Provided that a constant salinity gradient can be imposed, the proposed device is able to generate a steady cooling capacity. Here, we purposely operate with environmentally benign and easily accessible sodium chloride water solutions only. A numerical model is finally elaborated, validated and used to explore a wider range of possible device configurations and operating conditions.

Precipitation patterns are critical for understanding the hydrological and climatological dynamics of any region. Sicily, the largest island of the Mediterranean sea, with its diverse topography and climatic conditions, serves as an ideal case study for analyzing precipitation data to gain insights into regional water resources, agricultural productivity, and climate change impacts. This paper employs advanced statistical physics methods, particularly Tsallis q-statistics, to analyze sub-hourly precipitation data from 2002 to 2023, provided by the Sicilian Agrometeorological Informative System (SIAS). We investigate several critical variables related to rainfall events, including duration, depth, maximum record, and inter-event time. The study spans two decades (2002-2012 and 2013-2023), analyzing the distributions of relevant variables. Additionally, we examine the simple returns of these variables to identify significant temporal changes, fitting these returns with q-Gaussian distributions. Our findings reveal the scale-invariant nature of precipitation events, the presence of long-range interactions and memory effects, characteristic of complex environmental processes.

The article delves into the crucial realm of compressing hydrogen in its gaseous state, a pivotal process for enhancing its viability in both civil and industrial sectors. The study initiates by providing a concise overview and comparison of diverse hydrogen storage methodologies, laying the groundwork with an in-depth analysis of hydrogen's thermophysical properties. It scrutinizes plausible configurations for hydrogen compression, aiming to strike a delicate balance between energy consumption, predominantly derived from the fuel itself, and the requisite number of compression stages. Notably, to render hydrogen storage competitive in terms of volume, pressures of at least 350 bar are deemed essential, albeit at an energy cost amounting to approximately 10% of the fuel's calorific value. Multi-stage compression emerges as a crucial strategy, not solely for energy efficiency, but also to curtail temperature rise, with an upper limit set at 200°C. This nuanced approach is underlined by the exploration of compression levels commonly cited in the literature, particularly 350 bar and 700 bar. Ultimately, the study advocates for a three-stage compression system as a pragmatic compromise, capable of achieving high-pressure solutions while keeping compression work below 10 MJ/kg, a threshold indicative of sustainable energy utilization.

Targeted cancer therapy has grown exponentially in the last decade, representing the largest frontier in the modern concept of precision medicine. This renaissance is largely due to our rapidly evolving ability to biochemically harness our immune systems to target cancer-specific antigens. Combined with an increasing armamentarium of surgical and non-invasive techniques for cancer mitigation we have upgraded cancer therapy from a non-specific assault on cell-division to a multi-modal, targeted approach. This renaissance has resulted in an increase in the perioperative footprint of patients with advanced cancer. The scope of the perioperative clinician has evolved from one of passive/reactive management of complications to a proactive approach that starts in the preoperative optimization phase and continues into the postoperative period. The perioperative world should not exist in a silo, and thus involvement of the oncology team is paramount. To provide safe oncologic care, it is essential to be up to date in newer cancer therapies, lest we act on erroneous and/or outdated information. Oncologists should weigh in on immune status, recent chemotherapeutic exposures, and potentially evolving toxicities. These might involve critical changes to perioperative infectious prophylaxis, steroid administration, and coagulopathy management. First, patients living beyond the typical life-expectancy for their cancer will carry a high burden of cancer-related downstream effects. General metabolic issues will include malnutrition, cachexia, and gastric outlet obstruction. Severe protein-calorie malnutrition, as well as hepatic and renal dysfunction can impact the metabolism and clearance of drugs. The cardiovascular, endocrinologic, pulmonary, and central nervous system implications of new cancer therapies will be discussed extensively below. Second, we have to enhance our ability to manage a cancer population who may be experiencing increasing novel chemotherapeutic toxicities. Newer agents differ from historical agents, which were blunt-force tools aimed at nonspecific destruction of cell-division. These drugs are efficacious but physiologically costly. Newer immunogenic therapies have a slightly improved acute safety profile, and a more complex chronic toxicity profile that may be overt or insidious. Chronic toxicities can present overtly or as a smoldering undertone to other active medical conditions such as sepsis, pneumonia, failure to thrive, or renal failure. The new therapies discussed in this review occur in the context of an overall increasingly multi-faceted cancer care machine. An example is screening for esophageal cancer in patients with Barrett's esophagus, or periodic chest CTs for patients with a strong history of tobacco use. These interventions are more likely to detect disease while it is still resectable, and resections will commonly accompany neo-adjuvant therapy. These approaches commonly involve new immunotherapies whose efficacy is higher-yield with a lower disease burden. In a recent example, the immune-checkpoint inhibitors (ICIs) ipilimumab plus nivolumab have significantly increased survival rate for squamous cell esophageal cancer when combined with standard chemotherapy. Surgical resection has evolved to one that often accompanies neoadjuvant chemo and radiation. The increasing efficacy of this approach may de-necessitate many major resections, and increase the number of sub-anatomic resections and minimally invasive procedures. Improved techniques - notably for hepatectomy, whipple procedure, prostatectomy, nephrectomy - have increased the safety profile and decreased the perioperative physiologic burden. This has enabled a broader subset of patients (due to cancer burden or due to medical comorbidities) to qualify for the operation, and increased the involvement of anesthesia and their perioperative services. With an increase in surgical candidacy comes an increase in post-surgical complications, and post-surgical maintenance such as drains, embolizations, imaging studies, etc. In the non-OR anesthesia realm, there have been considerable advancements in cancer “micro-treatments” such as hepatic metastasis embolization, tumor ablation, and peri-tumor vascular embolization. There are an ever-increasing number of IR-guided embolizations for bleeding tumors, aspiration of malignant effusions, and drainage of abscesses. This review serves to provide insight into new categories of chemotherapy and their perioperative implications.

Non-alcoholic fatty liver disease (NAFLD) affects up to a quarter of the adult population in many developed and developing countries. This spectrum of liver disease ranges from simple steatosis to nonalcoholic steatohepatitis (NASH) and cirrhosis. The incidence of NASH is projected to increase by up to 56% over the next 10 years. There is growing epidemiological evidence that NAFLD has become the fastest growing cause of hepatocellular carcinoma (HCC) in industrialized countries. The annual incidence of HCC varies between patients with NASH cirrhosis and patients with noncirrhotic NAFLD. In this review, NAFLD/NASH-associated HCC will be described, including its epidemiology, risk factors promoting hepatocarcinogenesis, and management of HCC in patients with obesity and associated metabolic comorbidities, including preventive strategies and therapeutic approaches to address this growing problem.

The outbreak of coronavirus disease-19 (COVID-19) has infected more than 11 million people and has claimed more than 530.000 deaths world-wide. In July 2020, still, there is no specific treatment for disease caused by the novel coronavirus. In the search to curb the global pandemic COVID-19, some eastern and developing countries have approved various treatment with controversial efficacy, among that the use of the antimalarial Hydroxychloroquine (HCQ), so far with inconclusive clinical evidence of effectiveness. On the other hand, computer-based screening suggest that HCQs analog are promising molecules, to impair viral replication in vitro[1]. Therefore, what is emerging from this complex background, is the need to understand molecular mechanism beyond drugs that can be helpful against viral infection for this and future pandemic. The intent of this Brief Report is to highlight: i) the involvement of the Mitogen Activated Protein Kinase (MAPK) cascade in viral infection and ii) the urgent need to have molecular data on the effectiveness of the combination of MAPK inhibitors together with HCQ and HCQs analogs in curbing viral infection. We are convinced that a better understanding of the patterns of elicited molecular mechanisms will be critical for new molecular approaches to this severe disease

Dyslipidemia (Dys) is a disease characterised by abnormally high levels of lipids in the blood. It causes the deposits of lipids on the arterial wall leading to the insurgence of atherosclerosis, i.e. the increased thickness of arterial walls, which finally increases the risk of cardiovascular diseases. Dyslipidemia is a comorbidity of Type 2 Diabetes Mellitus (T2DM). A set of genes has been associated with dyslipidemia, but examining the regulation of such genes in age and sex is still an open research field. In this study, we select from publicly available databases the genes associated with dyslipidemia and analyse changes in the basal level of such genes by age and sex. Moreover, we also distinct differential rewiring of the related gene association network in males and females. Our results show that there exist a set of genes whose expression changes with age in artery tibial, artery aorta and blood. Moreover, there exist significant differences between sex.

Despite more than hundred years of research since Sir Sherrington’s studies on reflexes, his questions are still somehow unanswered. On what anatomical stage do the play of spinal reflex interaction take place? What are the physiological properties of this anatomical substrate? In this paper, we address these questions in light of the most advanced theory of motor control and the anatomical discoveries on the fascia that are changing how we think about control of action and perception. There are two sides of the problem: the neurological (reflex) connections that are at the base of movement, and the anatomical substrate that regulates and coordinates the movement. We recently advanced a hypothesis on how these two elements are connected and how they interplay. Here we further explain the concept of the somatic equilibrium point – SEP – and its central role in movement control and coordination. It is our belief that the concept of SEP explains how the neuro-mechanical control of movement is organized at peripheral level. At this level, intrafusal and extrafusal muscle fibres are combined in myofascial units, organized in anatomical directions. Myofascial units are closed systems whose behaviour can be affected by neural (voluntary) control or changes in external forces. SEPs represent the intrinsic equilibrium of the myofascial units, and are connected through the continuum of the fascia so that mechanical transfer of tension from segment to segment pre-adjust muscle fibers length and hence their excitation level. This is how coordination between segments is achieved. Finally, we suggest SEPs create the neurological representation of the referent configuration for action, and configurations are linked to the architecture of the fascial system.

The problem of real-time estimation of occupancy of buildings (number of people in various zones at every time instant) is relevant to a number of emerging applications that achieve high energy efficiency through feedback control. The measurement of CO2 concentration can be considered an important indicator that allows to define the occupation of closed and crowded spaces. Interesting cases can be school buildings and other buildings used in civil and residential (shopping centres, hospitals, etc.). This paper, starting from an experimental analysis in different classrooms of a University campus in real operating conditions, in different period of the year, proposes a possible correlation between CO2 concentration and the occupancy profile of the spaces. The acquired data are used to present some graphical correlations and to understand the most important variables or combination of them. Starting from an accurate analysis of the data, attempts are made to define a preliminary estimation method through the development of a mathematical models of occupancy dynamics in a building, which show interesting results.

Although hundreds of keV in energy gain have already been demonstrated in dielectric laser accelerators (DLAs), there remains challenge in creating structures that can confine electrons for multiple millimeters. We focus here on dual gratings with single sided drive, which have experimentally demonstrated energy modulation numerous times. Using a FTDT simulation to find the fields within various DLA structures and correlating these results with particle tracking simulation, we look at the impact of teeth height and width, as well as gap and offset, on the performance of these structures. We find a tradeoff between electron throughput and acceleration, but that for any given grating geometry there is a gap and offset that will allow some charge acceleration. For our 780 nm laser wavelength, this results in a 1200 nm optimal gap size for most gratings.

Due to the high computational burden and the high nonlinearity of the responses, crashworthiness optimizations are notoriously hard-to-solve challenges. Among various approaches, methods like the Successive Response Surface Method (SRSM) have stood out for their efficiency in enhancing baseline designs within a few iterations. However, these methods have limitations that restrict their application. Their minimum iterative resampling required is often computationally prohibitive. Furthermore, surrogate models are conventionally constructed using Polynomial Response Surface (PRS), a method that is poorly versatile, prone to overfitting, and incapable of quantifying uncertainty. Furthermore, the lack of continuity between successive response surfaces results in suboptimal predictions. This paper introduces the Multi-Fidelity Successive Response Surface (MF-SRS), a Gaussian process-based method, which leverages a nonlinear multi-fidelity approach for more accurate and efficient predictions compared to SRSM. After initial testing on synthetic problems, this method is applied to a real-world crashworthiness task: optimizing a bumper crossmember and crash box system. Results, benchmarked against SRSM and the Gaussian Process Successive Response Surface (GP-SRS) – a single-fidelity Gaussian process-driven extension of SRSM, show that MF-SRS offers distinct advantages. Specifically, it improves upon the specific energy absorbed optimum value achieved by SRSM by 14.1 %, revealing its potential for future applications.

Engineer-to-order manufacturing, characterized by highly customized products and complex workflows, presents unique challenges for warehouse management and operational efficiency. This paper explores the potential of a digital twin as a transformative solution for engineer-to-order environments in manufacturing companies realizing prefabricated building components. The paper outlines a methodology encompassing users’ requirement and the design to support development of a digital twin that integrates Internet of Things devices, Building Information Modeling, and Artificial Intelligence capabilities. It delves into the specific challenges of outdoor warehouse optimization and worker safety within the context of engineer-to-order manufacturing, and how the digital twin aims to address these issues through data collection, analysis, and visualization. The research is conducted through an in-depth analysis of the warehouse of Focchi S.p.A., a leading manufacturer of high-tech prefabricated building envelopes. Focchi's production processes and stakeholder interactions are investigated, and the paper identifies key user groups and their multiple requirements for the warehouse improvement. It also examines the potential of the digital twin to streamline communication, improve decision-making, and enhance safety protocols. While preliminary testing results are not yet available, the paper concludes by underlining the significant opportunities offered by a BIM, IoT, and AI-powered Digital Twin for engineer-to-order manufacturers. The research, developed within the IRIS project serves as a promising model for integrating digital technologies into complex warehouse environments, paving the way for increased efficiency, safety, and ultimately, a competitive edge in the market of manufacturing companies working in construction industry.

The transition to cleaner energy sources, particularly in hard-to-abate industrial sectors, often requires gradual integration of new technologies. Hydrogen, crucial for decarbonization, is explored as a fuel in blended combustions. Blending or replacing fuels impacts combustion stability and heat transfer rates due to differing densities. An extensive literature review examines blended combustion, focusing on hydrogen-methane mixtures. While industrial burners claim to accommodate up to 20% hydrogen, theoretical support is lacking. A novel thermodynamic analysis methodology is introduced, evaluating methane-hydrogen combustion using the Wobbe index. Findings highlight practical limitations beyond 25% hydrogen volume, necessitating a shift to "totally hydrogen" combustion. Blended combustion can be proposed as a medium-term strategy, acknowledging hydrogen's limited penetration. Higher percentages require burner and infrastructure redesign.

Diabetes mellitus (DM) is a metabolic disease characterized by chronic hyperglycemia associated with impaired carbohydrate, lipid and protein metabolism, with concomitant absence of insulin secretion or reduced sensitivity to its metabolic effects. Patients with diabetes mellitus have 30% more risk of developing heart failure and cardiovascular disease with respect to healthy people. Heart and cardiovascular problems are the first cause of death worldwide and the main complications which lead to high healthcare costs. Such complications can be delayed or avoided by taking prescribed medications in conjunction with a healthy lifestyle (i.e. diet and physical activity). The American College of Sports Medicine and the American Diabetes Association recommend that diabetic people reduce total sedentary time by incorporating physical activity in their weekly routine. This narrative literature review has the aim to summarize and present the main guidelines, pre-exercise cardiovascular screening recommendations, and considerations for patients with diabetes and comorbidities who are planning to participate in regular exercise regimens.

The AUC-ROC is a widespread measure to assess the performance of a binary classification model across various discrimination thresholds. Yet, it is not apt for unbalanced class problems and is misleading for early retrieval. For instance, link prediction in complex networks is an unbalanced early retrieval problem, whose goal is to offer a ranking of the nonobserved network links, prioritizing a small cohort of positive links (for which we are sure the labels are reliable) on top of a list largely populated by unlabeled links (for which the labels are uncertain). Differently from binary classification, here the evaluation focuses on how the predictor prioritizes the positive class, because the negative class does not exist and is replaced by an unlabeled class. For decades, scholars have been investigating the necessity to correct and to generalize the AUC-ROC to work for both unbalanced classification and early retrieval evaluation, this is requested in many applied domains of computational science. Here we propose the area under the magnified ROC (AUC-mROC), a new measure that adjusts the standard AUC-ROC to work for unbalanced early retrieval problems such as link prediction. Finally, we introduce the area under the generalized ROC (AUC-gROC), which unifies both AUC-mROC and AUC-ROC to provide a universal and reliable evaluation measure that can work for both classification and early retrieval problems, regardless of class proportion.This discovery represents a critical achievement, culminating in success after decades of contentious research. Its solution promises to significantly impact various domains within applied computational science.

In emergency situations, every second counts for an ambulance navigating through traffic. Efficient use of traffic light systems can play a crucial role in minimizing response time. This paper introduces a novel automated Real-Time Ambulance in an Emergency Detector (RTAIAED). The proposed system uses special Lookout Stations (LS) suitably positioned at a certain distance from each involved traffic light (TL), to obtain timely and safe transitions to green lights as the Ambulance in an Emergency (AIAE) approaches. The RTAIAED is particularly pertinent on one-way roads, addressing the challenge of regulating the sequence of traffic-lights-signals so as to minimize the time needed to safely grant the green signal to the AIAE. The proposed solution leverages a part-based model made of elementary detectors for video analysis, specifically realized with a customized YOLOv8 model, and for audio analysis, thanks to an additional neural network based on Mel Frequency Cepstral Coefficients (MFCCs). This way, the RTAIAED ensures the accurate and robust identification of an AIAE heading towards a traffic light in time to ensure a green light thanks to the strategic positioning of the LS detectors. Extensive experiments demonstrate the robustness of the approach and its reliable application in real-world scenarios thanks to its predictions in real-time, showcasing the ability to detect AIAEs even in challenging conditions such as noisy environments, nighttime, or adverse weather conditions, provided a suitable-quality camera is appropriately positioned. The proposed system can also find application in traffic flow management.

We investigate the influence of a self-propelling, out-of-equilibrium active particle on generalized elastic systems, including flexible and semiflexible polymers, fluid membranes, and fluctuating interfaces, while accounting for long-ranged hydrodynamic effects. We derive the fractional Langevin equation governing the dynamics of the active particle, as well as that of any other passive particle (or probe) bound to the elastic system. Our study explores the diffusional behavior emerging for both the active particle and a distant probe.

We address the unsolved question of how best to estimate the collision entropy, also called quadratic or second order Rényi entropy. Integer-order Rényi entropies are synthetic indices useful for the characterization of probability distributions. In recent decades, numerous studies have been conducted to arrive at their valid estimates starting from experimental data, so to derive suitable classification methods for the underlying processes, but optimal solutions have not been reached yet. Limited to the estimation of collision entropy, a one-line formula is presented here. The results of some specific Monte Carlo experiments give evidence of the validity of this estimator even for the very low densities of the data spread in high-dimensional sample spaces. The method strengths are unbiased consistency, generality and minimum computational cost.

The performance of ground heat exchangers systems depends on the knowledge of the thermal parameters of the ground like thermal conductivity, thermal capacity and diffusivity. The knowledge of these parameters often requires quite accurate experimental analysis, known under the name of Thermal Response Test (TRT). In this paper, after a general analysis of the various available types of TRT and the study of the theoretical basics of the method, the perspective of the definition of a simplified routine method of analysis based on the combination of a particular version of TRT and the routine geotechnical tests for the characterization of soil stratigraphy and of the ground characteristics, mandatory before the construction of a new buildings, even if limited to quite short drilling depth (lower than 30 m). The idea of developing TRT in connection with geotechnical test activity has the objective of promoting a widespread use of in-situ experimental analysis and of reducing TRT costs and time duration of the experimental analysis. The considerations exposed in the present paper lead to reconsider a particular variety of the TRT in particular the version known as Thermal Response Test while Drilling (TRTWD).

The effects on Raychaudhuri's equation of an intrinsically discrete or particle nature of spacetime are investigated, through consideration of null congruences emerging from, or converging to, a generic point of spacetime, i.e. in geometric circumstances somehow prototypical of singularity issues. This is done from an effective point of view, meaning through a (continuous) description of spacetime modified to embody the existence of an intrinsic discreteness on the small scale, adding to previous results for non-null congruences. Various expressions for the effective rate of change of expansion are derived. They in particular provide finite values for the limiting effective expansion and its rate of variation when approaching the focal point; this on top of resulting non vanishing the limiting cross-sectional area itself of the congruence.

(1) Background: Usually, the majority of patients suffering from vertigo and dizziness can be identified in four major categories: acute spontaneous vertigo, episodic (recurrent) vertigo, recurrent positional vertigo, chronic imbalance. Our purpose is to retrospectively evaluate the main causes of episodic vertigo and to find indications for a reliable clinical suspicion useful for a definitive diagnosis, comparing patients affected by different presenting symptomatology (acute vertigo, recurrent episodic vertigo, and imbalance) (2) Methods: we retrospectively evaluated the clinical records in a population of 249 consecutive patients observed for vertigo in our tertiary referral center in the period 1 January 2019 – 31 January 2020. On the basis of the reported clinical history, patients were divided into three groups: patients with first ever attack of vertigo, patients with recurrent vertigo and dizziness; patients with chronic imbalance. (3) Results: On the basis of the results of the instrumental examination, we arbitrary divided (for each type of symptoms) the patients in a group with a normal vestibular instrumental examination and a group of patients in which the clinical-instrumental evaluation showed some pathological results; a highly significant difference (p: 0.157) was found between recurrent and acute vertigo and between recurrent vertigo and imbalance. (4) Conclusions: patients with recurrent vertigo more frequently exhibit a negative otoneurological examination since they are often examined in the intercritical phase. A precise and in-depth research of the patient's clinical history is the key to suspect or make a diagnosis together with the search for some instrumental or clinical hallmark, especially in cases where the clinical picture does not fully meet the international diagnostic criteria.

Personalized medicine is an aspect of the P4 medicine (predictive, preventive, personalized and participatory) based precisely on the customization of all medical characters of each subject. In personalized medicine, the development of medical treatments and drugs is tailored to the individual characteristics and needs of each subject, according to the study of diseases at different scales from genotype to phenotype scale. To make concrete the goal of personalized medicine, it is necessary to employ high-throughput methodologies such as Next Generation Sequencing (NGS), Genome-Wide Association Studies (GWAS), Mass Spectrometry or Microarrays, that are able to investigate a single disease from a broader perspective. For example, by using genotyping microarrays (e.g. collections of Single Nucleotide Polymorphism - SNP) it is possible to uncover the reasons (i.e. mutation in genes) because a treatment works properly in some patients (for example absence of mutated genes), but it does not work (presence of mutated genes) in others. A side effect of high-throughput methodologies is the massive amount of data produced for each single experiment, that poses several challenges (e.g. high execution time and required memory) to bioinformatic software. Thus a main requirement of modern bioinformatic software is the use of good software engineering methods and efficient programming techniques, able to face those challenges, that include the use of parallel programming and efficient and compact data structures. Thus, to exploit all the potential of this massive amount of data in the short possible time (before that data becomes obsolete), the necessity to develop parallel software tools for efficient data collection and analysis arise. Moreover, due to the heterogeneity of the data produced by the different kinds of experimental platforms, it is necessary to automatize in a comprehensive software pipeline, the various steps that compose a bioinformatic analysis, such as: the preprocessing of raw data to remove noise or corrupted data; the annotation of data with external knowledge (e.g. Gene Ontology), and the integration of molecular data with clinical data. It should be noted that such steps are necessary to make statistical or data mining analysis more effective. This paper presents the design and the experimentation of a comprehensive software pipeline, named microPipe, for the preprocessing, annotation and analysis of microarray-based SNP genotyping data. A case study in pharmacogenomics is presented. The main advantages of using microPipe are: the reduction of errors that may happen when trying to make data compatible among different tools; the possibility to analyze in parallel huge datasets; the easy annotation and integration of data.

A growing area in neurosciences is focused on the modeling and analysis the complex system of connections in neural systems, i.e. the connectome. Here we focus on the representation of connectomes by using graph theory formalisms. The human brain connectomes are usually derived from neuroimages; the analyzed brains are co-registered in the image domain and brought to a common anatomical space. An atlas is then applied in order to define anatomically meaningful regions that will serve as the nodes of the network - this process is referred to as parcellation. Recently, it has been proposed to perform atlas-free random brain parcellation into nodes and align brains in the network space instead of the anatomical image space to define network nodes of individual brain networks. In the network domain, the question of comparison of the structure of networks arises. Such question is tackled by modeling the comparison of brain network as a network alignment (NA) problem. In this paper, we first defined the NA problem formally, then we applied three existing state of the art of multiple alignment algorithms (MNA) on diffusion MRI-derived brain networks and we compared the performances. The results confirm that MNA algorithms may be applied in cases of atlas-free parcellation for a fully network-driven comparison of connectomes.

Aim: The aim of this study is to evaluate the possibility of discriminating between the two sexes through the simultaneous use of cheiloscopy and palatine rugoscopy. Materials and methods: 80 palate and lip impressions (40 male and 40 female) were analyzed. The palate impressions were acquired using both analogue and digital methods. The lip impres-sions were first acquired analogically and then scanned. The morphology of the palatine rugae in the palate impressions was analyzed, with the exclusion of segmental rugae. The lip prints were analyzed in sextants and the morphology of the lip wrinkles was evaluated. Results: Palatine rugoscopy shows that women have more curvy rugae than men and that men have more rugae on the left side than on the right. Cheiloscopy gave no statistically significant re-sults. Discussion: Palatine rugoscopy showed some differences between the sexes, however, these re-sults were not solid enough for reliable sex discrimination. Differences between the results of dif-ferent studies can be attributed to ethnic and methodological variations. Cheiloscopy, on the other hand, did not provide statistically significant results for sex discrimination. Conclusions: Given the scant results obtained from palatine rugoscopy and the lack of statisti-cally relevant results in cheiloscopy, together with a lack of concordance among the data found in literature, it is believed that it is not possible to discriminate between the two sexes by using the two methods contemporarily. Further research is needed.

Background: CoronaVirus Disease 2019 (COVID-19) is the main discussed topic world-wide in 2020 and at the beginning of the Italian epidemic, scientists tried to understand the virus diffusion and the epidemic curve of positive cases with controversial findings and numbers. Objectives: In this paper, a data analytics study on the diffusion of COVID-19 in Lombardy Region and Campania Region is developed in order to identify the driver that sparked the second wave in Italy Methods: Starting from all the available official data collected about the diffusion of COVID-19, we analyzed google mobility data, school data and infection data for two big regions in Italy: Lombardy Region and Campania Region, which adopted two different approaches in opening and closing schools. To reinforce our findings, we also extended the analysis to the Emilia Romagna Region. Results: The paper aims at showing how different policies adopted in school opening / closing may have on the impact on the COVID-19 spread. Conclusions: The paper shows that a clear correlation exists between the school contagion and the subsequent temporal overall contagion in a geographical area.

In addition to CD4+ T lymphocytes, myeloid cells, and, particularly, differentiated macrophages, are targets of the human immunodeficiency virus type-1 (HIV-1) infection via interaction of gp120Env with CD4 and CCR5 or CXCR4. Both T cells and macrophages support virus replication although with substantial differences. In contrast to activated CD4+ T lymphocytes, HIV-1 replication in macrophages occurs in nondividing cells and it is characterized by virtual absence of cytopathicity both in vitro and in vivo. These general features should be considered in evaluating the role of cell-associated restriction factors aiming at preventing of curtailing virus replication in macrophages and T cells particularly in the context of designing strategies to tackle the viral reservoir in infected individuals receiving combination antiretroviral therapy. In this regard, we will here also discuss a model of reversible HIV-1 latency in primary human macrophages and the role of host factor determining restriction or reactivation of virus replication in myeloid cells.

Background: The aim of this study was to investigate a series of complete blood cell count – based biomarkers of systemic inflammation as predictors of clinical outcomes in patients who underwent first-line chemoimmunotherapy for advanced NSCLC. Methods: Consecutive patients with pathologically diagnosed stage III/IV NSCLC who underwent first-line chemoimmunotherapy were retrospectively enrolled. The clinical outcomes used for biomarker evaluation were Objective Response Rate (ORR) and Overall Survival (OS). Results: Non-responders had significantly higher values of neutrophil to lymphocyte ratio (NLR, median: 5.36; IQR: 2.78–10.82 vs. 3.31; IQR: 2.15–4.12, p = 0.019), neutrophil to monocyte ratio (NMR, median: 14.00; IQR: 8.82–21.20 vs. 9.20; IQR: 7.45–11.20, p = 0.013), and systemic inflammation index (SII, median: 1,395; IQR: 929–3,334 vs. 945; IQR: 552–1,373, p = 0.025), but only NLR and NMR remained independently related with clinical response in multivariate logistic regression. In univariate analysis white blood cells (OR:1.2202; 95% CI: 1.0339 - 1.4400, p=0.019), neutrophils (OR:1.2916; 95% CI: 1.0692 - 1.5604, p=0.008), NLR (OR:1.3601: 95% CI: 1.0949 - 1.6896, p=0.005) and NMR (OR:1.2159; 95% CI: 1.00396 - 1.4221, p=0.015) were significantly associated with survival; Cox regression models confirmed that neutrophils, NLR and MLR were independently associated with survival; NLR at a cut-off value of 4.0 showed the better AUC (0.749) in predicting survival. Conclusions: Baseline complete blood cell count biomarkers, especially the NLR, can predict clinical outcomes in patients with advanced NSCLC treated with first-line chemoimmunotherapy.

Qualtra, an innovative 10 MW geothermal power plant proposal, employs a closed-loop design to mitigate emissions, ensuring no direct release into the atmosphere. A thorough assessment utilizing energy and exergy analysis, Life Cycle Assessment (LCA), Exergo-economic and Exergo Environmental Analysis (EevA) was conducted. The LCA results, utilizing the ReCiPe 2016 midpoint methodology, encompass all the spectrum of environmental indicators provided. The technology implemented makes it possible to totally avoid direct atmospheric emissions from the Qualtra plant, so the environmental impact is mainly due to indirect emissions over the life cycle. The results obtained for the Global Warming Potential indicator is about 6.6 g CO2/kWh, notably lower compared to other conventional systems. Contribution analysis reveals that the construction phase dominates, accounting for over 90% of the impact in all LCA MidPoint categories. At the component level, a single score calculation incorporating normalization and weighting was executed. The resulting single score is then used into Exergo-Environmental Analysis (EEvA), highlighting the well system as the most impactful contributor, constituting approximately 45% of the total impact. Other substantial contributions to the environmental impact include the condenser (21%), the turbine (17%), and the HEGeo (14%). The Exergo-Economic analysis assesses cost distribution across major plant components, projecting an electricity cost of about 8.3 c€/kWh.

With the outbreak of the COVID-19 disease, the research community is producing unprecedented efforts dedicated to better understand and mitigate the affects of the pandemic. In this context, we review the data integration efforts required for accessing and searching genome sequences and metadata of SARS-CoV2, the virus responsible for the COVID-19 disease, which have been deposited into the most important repositories of viral sequences. Organizations that were already present in the virus domain are now dedicating special interest to the emergence of COVID-19 pandemics, by emphasizing specific SARS-CoV2 data and services. At the same time, novel organizations and resources were born in this critical period to serve specifically the purposes of COVID-19 mitigation, while setting the research ground for contrasting possible future pandemics. Accessibility and integration of viral sequence data, possibly in conjunction with the human host genotype and clinical data, are paramount to better understand the COVID-19 disease and mitigate its effects.

In a Water-Cooled Lithium-Lead (WCLL) Breeding Blanket (BB), the heat generated by the plasma thermal radiation and nuclear reactions is removed mainly by two components; namely, the First Wall (FW) and the Breeding Zone (BZ). The FW faces the neutrons and charged particles fluxes generated by the fusion reactions and the thermal radiation coming from the plasma. The present work takes into account the FW cooling system inspired by the WCLL BB 2018 design of DEMO 2017 baseline. Unlike the baseline where a Pressurized-Water Reactor (PWR) setup is used for the coolant, various setup between the Boiling Water Reactor (BWR) and the High-Pressure (HP) BWR are studied in the present work operating in the Two-Phase Flow (TPF) regime. The 3D model of the FW in the WCLL BB 2018 design is simplified into a 1D model and a steady state analysis is carried out to optimize the mass flow rate of the water and the number of parallel channels at the BB cells at different poloidal locations of the reactor, which helps not only in reducing the used coolant but also in improving the Tritium Breeding Ratio (TBR). The present work takes into account forced convection in the liquid only region, the subcooled boiling region, and the saturated boiling region using suitable empirical or semi-empirical models from the literature. The results are validated against the existing results in the literature. In the end, related conclusions are made regarding the pros and cons of the studied operating conditions.

Although many devices have recently been proposed for pressure regulation and energy harvesting in water distribution and transport networks, very few applications are still documented in the scientific literature. A new in-line Banki turbine with positive outflow pressure and a mobile regulating flap, named PRS, was installed and tested in a real water transport network for pressure and discharge regulation. The PRS turbine was directly connected to a 55 kW asynchronous generator with variable rotational velocity, coupled to an inverter. The start-up tests showed how automatic adjustment of the flap position and the impeller velocity variation are able to change the characteristic curve of the PRS according to the flow delivered by the water manager or to the pressure set-point assigned downstream or upstream of the system, still keeping good efficiency values in hydropower production.

This paper presents an innovative approach for improving the seismic protection of existing structures by introducing an additional dissipative structure (ADS). The seismic energy impacting the building can be dissipated through the contribution provided by the ADS, thereby reducing the need for the existing building to ensure its seismic capacity. This retrofitting technique is well-suited for structures facing architectural restrictions or challenging-to-update elements. It can help address foundation issues by applying loads to new external components. This paper describes the design of the ADS and proposes a displacement-based design procedure. The design process involves a non-linear static analysis and a simple procedure that must be iteratively repeated until the retrofitting target is achieved. This approach is simple and computationally efficient and can also be used for complex and irregular structures. Such structures are frequently encountered, and existing structures often exhibit unusual geometries and materials requiring extensive numerical modeling. The efficacy of the technique was evaluated using the case studiy of a school building located in central Italy. The results of numerical analyses indicated that owing to the ADS’s contribution, the seismic capacity of both buildings was enhanced, addressing the challenges associated with complex foundation interventions.

Plants offer a simpler and cheaper alternative to mammalian animal models for the study of Endoplasmic Reticulum glycoprotein folding Quality Control (ERQC). In particular, the Arabidopsis thaliana (At) innate immune response to bacterial peptides provides an easy means of assaying ERQC function in vivo. A number of mutants that are useful to study ERQC in planta have been described in the literature, but only for a subset of these mutants the innate immune response to bacterial elicitors has been measured beyond monitoring plant weight and some physio-pathological parameters related to the plant immune response. In order to probe deeper into the role of ERQC in the plant immune response, we monitored expression levels of the PHI-1 and RET-OX genes in the At ER α-Glu II rsw3 and the At UGGT uggt1-1 mutant plants, in response to bacterial peptides elf18 and flg22. The elf18 response was impaired in the rsw3 but not completely abrogated in the uggt1-1 mutant plants, raising the possibility that the latter enzyme is partly dispensable for ERF signalling. In the rsw3 mutant, seedling growth was impaired only by concomitant application of the At ER α-Glu II NB-DNJ inhibitor at concentrations above 500 nM, suggesting residual activity in this mutant. The study highlights the need for extending plant innate immune response studies to assays sampling EFR signalling at the molecular level.

The advent of immunotherapy and specifically of immune checkpoint inhibitors (ICIs) for the treatment of solid tumors has deeply transformed therapeutic algorithms in medical oncology. Approximately one third of patients treated with ICIs may develop immune-related adverse events, being the gastrointestinal tract often affected with different grades of mucosal inflammation. Checkpoint inhibitors colitis (CIC) presents with watery or bloody diarrhoea and in case of severe activity requires ICIs discontinuation. The pathogenesis of CIC is multifactorial and still partially unknow: anti-tumor activity that collaterally effects the colonic tissue and the upregulation of specific systemic inflammatory pathways (i.e., CD8+ cytotoxic and CD4+ T lymphocytes) are mainly involved. Many open issues remain on treatment timing and options, and biological treatment, above all with anti-TNF alpha, can be offered to these patients aiming to rapidly resume the oncological therapies. This review aims to summarize the pathogenetic mechanisms underlying CIC and to discuss evidenced-based management including the role of biological therapy.

“Non-Locality is most naturally incorporated into a theory in which there is a special frame of reference. One possible candidate for this special frame of reference is the one in which the Cosmic Microwave Background (CMB) is isotropic. However, other than the fact that a realistic interpretation of quantum mechanics requires a preferred frame and the CMB provides us with one, there is no readily apparent reason why the two should be linked” (L. Hardy). Starting from this remark we first argue that, given the present view of the vacuum, the basic tenets of Quantum Field Theory cannot guarantee that Einstein Special Relativity, with no preferred frame, is the physically realized version of relativity. Then, to try to understand the nature of the hypothetical preferred Σ−frame, we consider the so called ether-drift experiments, those precise optical measurements that try to detect in laboratory a small angular dependence of the two-way velocity of light and then to correlate this angular dependence with the direct CMB observations with satellites in space. By considering all experiments performed so far, from Michelson-Morley to the present experiments with optical resonators, and analyzing the small observed residuals in a modern theoretical framework, the long sought Σ− frame tight to the CMB naturally emerges. Finally, if quantum non-locality reflects some effect propagating at vastly superluminal speed vQI→∞, its ultimate origin could be hidden somewhere in the infinite speed cs→∞ of vacuum density fluctuations.

Regeneration of peripheral nerves depends on the ability of axons to navigate through an altered extracellular environment. It has been suggested that Schwann cells facilitate this process through their secretion of neuropeptides and proteases. Using the RT4-D6P2T Schwann cell line (RT4), we have previously shown that RT4 cultures endogenously express the neuropeptide PACAP, and respond to exogenous stimulation by inducing the expression of tissue plasminogen activator (tPA) and urokinase plasminogen activator (uPA) through PAC1 receptor activation. In this study, based on recent findings showing that doxycycline and minocycline act as positive allosteric modulators (PAMs) of the PAC1 receptor, we tested if treatment with these tetracyclines could induce the expression and activity of tPA and uPA in RT4 cells. Using ELISA and zymographic analyses, we demonstrate that doxycycline and minocycline reliably induce the secretion and activity of both tPA and uPA, which is paralleled by an increased expression levels, as shown by immunocytochemistry and Western blots. These actions were mediated, at least in part, by the PAC1 receptor, as PACAP6-38 mitigated tetracycline-induced expression and activity of tPA and uPA. We conclude that doxycycline and minocycline can act as PAMs of the PAC1 receptor to promote proteolytic activity in RT4 cells.

The energy transition is a challenge that affects all sectors, from transport to civil structures and industry. With reference to the industrial sector, the greatest need is the decarbonisation of industries energy-intensive, such as producers of iron and steel, aluminium, cement, petrochemicals, paper, etc. In particular, the steel industry is a hard to abate high-emissivity industry which due to chemical processes and high thermal demands (often above 500 °C) contributed to 7.4% of global CO₂ in the year 2021. This paper has explored the potential applications of hydrogen in the hard-to-abate sectors, highlighting its versatility and significance in decarbonization efforts. It provides an overview of hydrogen production methods, emphasizing the importance of sustainable and green hydrogen production. It reviews hydrogen production methods, storage, and potential in blended combustion. In the final part of the article, some considerations are introduced on the possible role of hydrogen in the steel sector (both as a supplementary fuel and as a reducing agent in innovative processes), showing how although there is potential for its inclusion as an element for the decarbonization, it is necessary to evaluate the energy balances of the various processes and the methods of hydrogen production very carefully, in order not to risk obtaining a marginal effect.

The outbreak of novel Coronavirus (SARS-COV-2 ) disease (COVID-19) in Wuhan has attracted worldwide attention. SARS-COV-2 known to share a similar clinical manifestation that includes various symptoms such as pneumonia, fever, breathing difficulty, and in particular, SARS-COV-2 also causes a severe in ammation state that leads to death. Consequently, massive and rapid research growth has been observed across the globe to elucidate the mechanisms of infections and disease progression in genotype and phenotype scale. Data Science is playing a pivotal role in in-silico analysis to draw hidden and novel insights about the SARS-COV-2 origin, pathogenesis, COVID-19 outbreak forecasting, medical diagnosis, and drug discovery. With the availability of multi-omics, radiological, biomolecular, and medical data urges to develop novel exploratory and predictive models or customise exiting learning models to t the current problem domain. The presence of many approaches generates the need for the systematic surveys to guide both data scientists and medical practitioners. We perform an elaborate study on the state-of-the-art data science method ologies in action to tackle the current pandemic scenario. We consider various active COVID-19 data analytics domains such as phylogeny analysis, SARS-COV-2 genome identication, protein structure prediction, host-viral protein interactomics, clinical imaging, epidemiological analysis, and most importantly (existing) drug discovery. We highlight types of data, their generation pipeline, and the data science models in use. We believe that the current study will give a detailed sketch of the road map towards handling COVID-19 like situation by leveraging data science in the future. We summarise our review focusing on prime challenges and possible future research directions .

The purpose of this finite element analysis (FEA) was to evaluate the stress experienced by both the prosthetic components and the bone in relation to varying cement thicknesses ranging from 20 to 60 μm, utilized in the attachment of a zirconia crown on a conometric cap. The study focused on two distinct types of implants (Cyroth and TAC, AoN Implants, Grisignano di Zocco, Italy) featuring a Morse cone connection. Detailed three-dimensional (3D) models were created to repre-sent the bone structure (cortical and trabecular) and the prosthetic components, encompassing the crown, cement, cap, abutment, and the implant. The two implants were placed in a 1.5 mm sub-crestal position and subjected to an inclined load of 200 N at 45° on the crown. The results re-vealed that an increase in cement thickness resulted in a reduction of von Mises stress on the cor-tical bone for both Cyroth and TAC implants, while the decrease in stress on the trabecular bone was relatively less pronounced. However, the TAC implant exhibited a higher stress field and de-formation in the apical area compared to the Cyroth implant. In summary, this study investigated the impact of cement thickness on stress transmission across prosthetic components and peri-implant tissues by means of FEA analysis, indicating that the 60 μm cement layer manifested higher stress values nearing the material strength limit.

This paper presents a new method to model the nonlinear behaviour of masonry double curvature structures, possibly reinforced by composite materials, by means of conventional elasto-plastic analyses. It is meant to be used in professional design, especially for assessment and retrofitting purposes, therefore based on the exploitation of the simplest nonlinear Finite Elements available in a commercial software, namely trusses with elasto-fragile and elasto-ductile behaviour (Cutoff Bars). The numerical static nonlinear analyses are carried out by considering elastic hexahedral elements for bricks and lumping nonlinearities on joints. These have been assumed in turn elastic-brittle and elastic-plastic by using 1D elements, respectively Point Contacts, under No-Tension Material hypothesis, and Cutoff Bars, assigning small tensile resistance to the material. The reinforcement, realised with FRP hooping strips, has been successfully modelled in a similar fashion, i.e. by applying perfectly bonded elastic-plastic Cutoff Bars at the extrados of the dome, where the debonding is accounted for in a conventional way limiting the tensile strength according to Italian Standards indications. The procedure is validated against benchmark models with the same geometry, using experimental data and more refined structural model results for comparison.