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Detecting early damage in civil structures is highly desirable. In the area of vibration-based damage detection, modal flexibility (MF)-based methods have proven to be promising tools for promptly identifying changes in the global structural behavior. Many of these methods have been developed for specific types of structures, giving rise to different approaches and damage-sensitive features (DSFs). Although structural type classification is an important part of the damage detection process, this part of the process has received little attention in most literature and often relies on the use of a-priori engineering knowledge. Moreover, in general, experimental validations are only performed on small-scale laboratory structures with controlled artificial damage (e.g., imposed stiffness reductions). This paper proposes data-driven criteria for structure-type classification usable in the framework of MF-based damage identification methods to select the most appropriate algorithms and DSFs for detecting and localizing structural anomalies. This paper also tests the applicability of the proposed classification criteria and the damage identification methods on full-scale reinforced concrete (RC) structures that have experienced earthquake-induced damage. The considered structures are a seven-story RC wall building and a five-story RC frame building, which were both tested on the large-scale University of California, San Diego-Network for Earthquake Engineering Simulation (UCSD-NEES) shaking table.

Smart devices for structural health monitoring provide edge computing capabilities to reduce wireless transmission and, thus, power consumption. Although effective algorithms have been proposed in the last few decades, traditional microcontrollers require heavy data flow between the memory and the central processing unit that involves a considerable fraction of the total energy consumption. Phase change memory has recently emerged as an attractive solution in the field of resistive non-volatile memory for analog in-memory computing, which is a valid approach to avoid data being conveyed among distinct elaboration units. However, it has never been envisaged in structural health monitoring applications. As this technology is still in an embryonic state, several challenges related to nonlinearities and nonidealities of the memory elements and the energy expenditure related to the memory reprogramming process may undermine its usage. In this paper, the application of a novel identification approach for civil infrastructures is investigated using phase change memories. The main computational core of the presented algorithm, consisting of 1-dimensional convolutions, is particularly suitable for implementations involving analog in-memory computing, thus showing the great potential of this technology for structural health monitoring applications. The test unit is an embedded phase change memory provided by STMicroelectronics and designed in 90-nm smart power bipolar complementary metal-oxide-semiconductor (CMOS)-double-diffused metal-oxide-semiconductor (DMOS) technology with a Ge-rich Ge-Sb-Te alloy for automotive applications. Experimental results obtained for a viaduct of an Italian motorway support the efficacy of the method. Moreover, the influence of nonidealities on the outcomes of damage identification based on both dynamic and quasi-static structural parameters is examined.

Objectives To evaluate the proportion of COVID‐19 infections among a population of Italian Dental workers across different geographical area of Italy and to analyze the impact of both the preventive measures/strategies adopted and the psychological influences. Subjects and Methods The current cross‐sectional survey was administered with a web‐based form. To be eligible for the study, participants had to be 18 years and being dentists or dental hygienists members of the Italian Society of Periodontology and Implantology (SIdP). A 23‐item questionnaire concerning positiveness to COVID‐19, clinical strategies and psychological attitude within the pandemic was administered. Sub‐group analysis was conducted according to geographical macro‐area. Results A total of 790 dentists and dental hygienists were included. A total of 4.7% participants developed a positive diagnosis to COVID‐19. The Northwest of Italy experienced almost double of COVID‐19‐positive participants (p

To investigate the clinical management of stage IV periodontitis patients among clinicians within the Italian Society of Periodontology and Implantology.A cross-sectional study was designed on a web-based anonymous survey. Comparison between ordinary members (OMs) versus active and certified members (ACMs) and comparison between members with at least 10 years of experience in periodontology (Ov10) and members with less than 10 years of experience in periodontology (Un10) were performed.A total of 324 out of 1362 members (response rate of 24%) responded to the questionnaire. ACMs and Ov10 more often reported their teams hold adequate skills to manage cases. Step I and II periodontal therapy took more time in the ACMs and Ov10 groups. ACMs used different strategies to perform step I-II therapy, and antibiotics were used less frequently than OMs. Unresponsive sites were treated more often with surgery by ACMs compared to OMs. ACMs adopted different treatment sequences compared to OMs. Ov10 group used more often CBCT, lateral cephalogram, and wax-up while Un10 group tend to avoid orthodontic therapy.More experienced members spent more time in step I and II of periodontal therapy, used more diagnostic tools, and performed more often surgery and orthodontics in the treatment of stage IV periodontitis patients.

In this paper, a new strategy for vibration-based structural health monitoring is proposed, specifically designed for smart sensors with edge computing capabilities organized in a line topology. This solution is aimed at maximizing resource optimization and enables the identification of modal parameters even for large or densely instrumented structures, where star-topology monitoring systems are typically unsuitable. In particular, an efficient data management procedure is proposed to reduce data transmission, thus improving efficiency and minimizing maintenance interventions for battery replacement in wireless applications. The maximum volume of transmitted data can be selected by the user, based on the specific requirements of the network. Although the considerable reduction of data size, the proposed approach enables accurate estimation of the structural parameters in challenging scenarios where other techniques generally fail. Modal parameters are identified in an online fashion, enabling near real-time detection and localization of early damage. Applications to a real case study instrumented with a dense sensor network show the effectiveness of the proposed approach and the possibility of localizing structural defects in slightly damaged civil structures.

Information on the presence and location of cracks in civil structures can be precious to support operators in making decisions related to structural management and scheduling informed maintenance. This paper investigates the efficacy of supervised machine learning to solve the inverse electrical impedance tomography problem and to reconstruct the conductivity distribution of a piezoresistive sensing film. This film consists of a conductive paint applied onto structural components, and operators can use its conductivity distribution to identify crack sizes and locations in the underlying structure. A deep neural network is employed to reconstruct a dense conductivity distribution within the painted area by using only voltage measurements collected at sparse boundary locations. Since one of the most challenging aspects of using supervised learning tools for real-world applications is generating a representative training dataset, this paper presents a new approach to test the suitability of synthetic datasets built using a finite element model of the sensing film. Results are reported for four sensing specimens fabricated with two different techniques (i.e., using carbon nanotubes and graphene nanosheets, respectively). Crack-like damage is induced to the substrate of the sensing film and identified using the proposed machine learning technique. Promising results are obtained as compared to conventional methods.

Objectives Primary focused question for this systematic review (SR) was “Which is the evidence about surfaces decontamination and protection masks for SARS‐Cov‐2 in dental practice?” Secondary question was “Which is the evidence about surfaces decontamination and protection masks against airborne pathogens and directly transmitted viral pathogens causing respiratory infections?” Materials and Methods PRISMA guidelines were used. Studies on surface decontamination and protective masks for SARS‐CoV‐2 in dental practice were considered. Studies on other respiratory viruses were considered for the secondary question. Results No studies are available for SARS‐CoV‐2. Four studies on surface disinfection against respiratory viruses were included. Ethanol 70% and sodium hypochlorite 0,5% seem to be effective in reducing infectivity by > 3log TCID. Four RCTs compared different types of masks on HCW. The single studies reported no difference for laboratory‐diagnosed influenza, laboratory‐diagnosed respiratory infection, and influenza‐like illness. A meta‐analysis was not considered appropriate. Conclusions There is lack of evidence on the efficacy of surface disinfection and protective masks to reduce the spread of SARS‐CoV‐2 or other respiratory viruses in dentistry. However, the consistent use of respirator and routine surface disinfection is strongly suggested. There is urgent need of data on the efficacy of specific protection protocols for dental HCW against viral infections.

BACKGROUND/AIM This study evaluated marginal soft tissue recession at implants with simultaneous lateral guided bone regeneration (GBR), at least five years after prosthetic loading. MATERIAL AND METHODS Patients treated with GBR at the time of implant placement and adherent to supportive periodontal therapy (SPT) program with at least 5 years of follow-up were re-examined in 5 clinical centers. At the last follow-up, clinical and radiographic data on peri-implant hard and soft tissue were collected. Multilevel analysis considering center, patient, and implant (brand, length, diameter, position) was performed. RESULTS A total of 96 patients and 195 augmented implants were included. The mean duration of SPT was 8.3 ± 3.1 years, while mean recall frequency was 4.5 ± 1.3 months. Sixty-five (33%) implants received soft tissue graft before prosthetic delivery. Twenty-one (11%) implants developed biological complications during the follow-up. No implant failure was reported. Mean difference in bone levels (ΔBL) was -0.7 ± 0.9 mm, while mean difference in keratinized tissue (ΔKT) was -0.4 ± 0.9 mm. Eighty-five (44%) implants showed recession (REC) of soft tissue margin (mean 0.6 ± 0.8 mm). The presence of REC was associated with use of non-resorbable membrane (p

Additive manufactured structures are replacing the corresponding ones realized with classical manufacturing technique. As for metallic structures, 3D printed components are generally subjected to dynamic loading conditions which can lead to fatigue failure. In this context, it is useful, and sometimes mandatory, to determine the fatigue life of such components through numerical simulation. The methods currently available in literature for the estimation of fatigue life were originally developed for metallic structures and, therefore, it is now necessary to verify their applicability also for components fabricated with different materials. To this end, in the current activity three of the most used spectral methods for the estimation of fatigue life were used to determine the fatigue life of a 3D printed Y-shaped specimen realized in polylactic acid subjected to random loads with the aim of determining their adaptability also for this kind of materials. To certify the accuracy of the numerical prediction, a set of experimental tests were conducted in order to obtain the real fatigue life of the component and to compare the experimental results with those numerically obtained. The obtained outcomes showed there is an excellent match between the numerical and the experimental data, thus certifying the possibility of using the investigated spectral methods to predict the fatigue life of additive manufactured components.

The industrial interest in additive manufacturing (AM) techniques is currently increasing for the realization of functional mechanical components. For this reason, the structural simulation of parts or complete structures made using this new manufacturing technique is gaining considerable importance. To realise accurate finite element models for the purpose of predicting the dynamic or static behaviour of the component printed and avoid unexpected failures, it is necessary to be aware of some mechanical and physical properties of the print material. Unfortunately, in the literature, it is very difficult to find all the data necessary to perform static or dynamic simulations of 3D printed parts. In this context, this activity aims to determine all these mechanical and physical properties for parts made in White-Pearl Polylactic-acid (PLA) Ultimaker filament using the Fused Filament Fabrication (FFF) technique. A set of printing parameters was chosen and kept constant in all tests which, based on literature data, maximizes the static strength and the fatigue limit of the component. Only the building direction was varied to increase the applicability of the obtained results to any geometry. The main results found for the horizontally moulded specimens (representing the best constructive solution) are the Ultimate Tensile Strength equal to 57.15 MPa, the elastic modulus 2606 MPa, the fatigue limit evaluated at $$2 \times 10^{6}$$ 2 × 10 6 cycles equal to 13.5 MPa, the damping and density of the material of 0.008 dimensionless value and 1.1246 g/cm3, respectively. Only thanks to the obtained results, finite element models can be developed for reliable static and dynamic analysis.

The purpose of this study was to assess the diagnostic accuracy and the inter-rater agreement among general dentists when staging and grading periodontitis cases with the aid of a software application (SA) developed by the Italian Society of Periodontology and Implantology.Ten general dentists were asked to independently assess 25 periodontitis cases using the SA. Accuracy was estimated using quadratic weighted kappa and examiners' percentage of agreement with a reference diagnosis provided by a gold standard examiner. Inter-rater agreement was evaluated using Fleiss kappa statistics.The overall case definition agreed with the reference diagnosis in 53.6% of cases. The agreements for each general dentist's pairwise comparisons against the reference definition were at least substantial in 100% of cases for stage, in 70% of cases for grade and in none of the cases for extent. Fleiss kappa was 0.818, 0.608, and 0.632 for stage, extent, and grade, respectively. The study recognized possible reasons that could lead to decreased accuracy using the SA.Supported by the SA, general dentists have reached substantial inter-rater agreement and highly accurate assignments of stage and grade. However, complete case definitions were correctly diagnosed in slightly over half of the cases.

Machine guards provide protection against the ejection of parts during operation, such as chips or workpiece fragments. They are considered safe if the impact resistance is at least as high as the resulting projectile energy in the worst case of damage. To protect the machine operator, the impact resistance of machine guards is determined according to ISO standards. The bisection method can be used to determine the impact resistance through impact tests. However, this method is inaccurate for a small number of impact tests and does not indicate uncertainties in the determination. Moreover, the result of testing is validated in different ways depending on the standard utilized for testing. Relevant uncertainties affecting impact testing and a new probabilistic approach for assessing the impact resistance using the Recht and Ipson equation are presented. With multiple impact tests at different initial velocities a Recht and Ipson best-fit curve and a confidence interval for a ballistic limit can be obtained, which is used to determine the impact resistance by defining a velocity reduction coefficient. This method can be applied to any machine guard made of ductile material. This paper validates the Recht and Ipson method by performing impact tests with a standardized 2.5 kg projectile on polycarbonate sheets of different thicknesses. Determination of the ballistic limit showed good agreement with experimental results. With the ballistic limits, the velocity reduction coefficients have been found to determine the impact resistances. Therefore, an alternative method for standardized tests to determine the impact resistance was found.

This paper proposes a novel method suitable for vibration-based damage identification of civil structures and infrastructures under ambient excitation. The damage-sensitive feature employed in the presented algorithm consists of a vector of multivariate autoregressive parameters estimated from the vibration responses collected at different locations of the analyzed structure. Outlier analysis and statistical pattern recognition are exploited for damage detection and localization. In particular, the Mahalanobis distance between a set of reference (i.e., “healthy”) and inspection parameters is evaluated. A threshold is then selected to determine whether the inspection vectors refer to damaged or undamaged conditions. The effectiveness of the proposed approach is proved using numerical simulations and experimental data from a benchmark test. The analysis results show that the largest values of Mahalanobis distance can be found in the proximity of those sensors closest to the damaged elements. Thus, the Mahalanobis distance applied to vectors of multivariate autoregressive parameters has proven to be a robust indicator for damage detection and localization.

Seismic assessment of a building will typically require consideration of its nonlinear force–displacement response. Such information can be estimated from pushover analysis, also referred to as nonlinear static analysis, in which the structure is analyzed for incrementally increasing lateral loads and the nonlinear structural behavior is accounted for during the analysis by updating the stiffness matrix at each load increment. A number of computer programs are now available to permit the application of pushover analysis in practice. However, it is argued that there is a need for simplified pushover analysis methods to permit independent checks of computer outputs and also to inform engineers of the key characteristics of the structural system being assessed. This work builds on previous contributions in the literature to provide a simplified pushover analysis approach for reinforced concrete (RC) frame structures. A novel procedure for the assessment of the displacement profile of RC frames is provided, with guidelines to account for different types of yielding mechanisms. By comparing force–displacement response predictions with those obtained from rigorous nonlinear static analyses for a range of frame configurations and mechanisms, it is shown that the proposed approach offers an effective means of undertaking simplified pushover analysis.

Recent developments in the field of smart sensing systems enable performing simple onboard operations which are increasingly used for the decentralization of complex procedures in the context of vibration-based structural health monitoring (SHM). Vibration data collected by multiple sensors are traditionally used to identify damage-sensitive features (DSFs) in a centralized topology. However, dealing with large infrastructures and wireless systems may be challenging due to their limited transmission range and to the energy consumption that increases with the complexity of the sensing network. Local DSFs based on data collected in the vicinity of inspection locations are the key to overcome geometric limits and easily design scalable wireless sensing systems. Furthermore, the onboard pre-processing of the raw data is necessary to reduce the transmission rate and improve the overall efficiency of the network. In this study, an effective method for real-time modal identification is used together with a local approximation of a damage feature, the interpolation error, to detect and localize damage due to a loss of stiffness. The DSF is evaluated using the responses recorded at small groups of sensors organized in a decentralized topology. This enables the onboard damage identification in real time thereby reducing computational effort and memory allocation requirements. Experimental tests conducted using real data confirm the robustness of the proposed method and the potential of its implementation onboard decentralized sensor networks.

Real-time structural health monitoring (SHM) acquires countless importance when applied to large-scale civil infrastructures, where the damage should be managed immediately to avoid both economic and human loss. Recent studies in the field of real-time identification of bridges generally assume linear time-varying (LTV) structural models, justified on the grounds that continuously varying traffic load may slightly change the structural behavior over time. Time-varying load also involves non-stationary input excitation, which cannot be modeled as Gaussian white noise, as in the traditional output-only identification methods, and may be characterized by time-varying frequency spectrum which could affect the effectiveness of commonly used identification algorithms. In this paper, the Modal Assurance Distribution (MAD) is employed for the dynamic identification of LTV structures. Based upon the instantaneous operating deflection shapes (ODSs) evaluated through the wavelet packet decomposition, the MAD represents the instantaneous ODS similarity between narrow-band signal components, highlighting the presence of time-varying modal responses. Compared to the most used traditional time-frequency representations (TFRs), representing the distribution of energy through the time-frequency plane, the MAD enables a clearer reading of the modal responses, facilitating their extraction for real-time damage identification. The practical application to a benchmark structure shows the potential of the MAD as a novel TFR which could give rise to a new family of system and damage identification methods.

For time-varying systems in structural engineering, such as bridges with vehicular traffic and structures during construction or seismic events, the application of traditional vibration-based identification methods may not be admissible, since the hypotheses of stationarity of the signal may be far from the real situation. Moreover, in some cases, real-time approaches to visualize the identified parameters are desirable to allow for a rapid decision-making process, which assumes the utmost importance for the early warning in structures near to excavation or demolition sites and strategic infrastructures after seismic events. Time-frequency representations have been largely used for the instantaneous identification of linear time-varying systems. However, traditional algorithms generally suffer from issues related to the identification of closely-spaced modes, which make the modal decomposition a non-trivial task. Moreover, by tracking only natural frequencies, some variations of the dynamic behavior could not be perceived, or the variations induced by other environmental and operational conditions could prevail over those due to a modification in the structural properties (e.g., due to ongoing damage). In this paper, a Decomposition Algorithm based on Modal Assurance (DAMA) is applied to separate modal responses, in order to allow a near real-time identification of modal parameters of structures with time-varying features. In particular, a Modal Assurance Distribution (MAD) obtained from the analysis of multi-variate signals is used to track the variations of modal parameters, considering both natural frequencies and modal shapes. The DAMA is applied to a full-scale structure subjected to a series of dynamic tests performed in different structural conditions. The analysis of multi-variate signals consisting of acceleration recordings collected at different locations of the structure allows the online identification of varying dynamic parameters, which can be used to assess the structural state of health.

Effective methods for vibration-based damage diagnosis in building structures are based on the estimation of structural deflections from identified modal flexibility (MF) matrices. However, most of the existing methods and previous studies that use MF-based deflections were developed by considering the case of buildings that can be modeled as planar structures (e.g. plan-symmetric buildings) both in the baseline and possibly damaged states. In an attempt to fill this research gap, a deflection-based method for output-only damage diagnosis in building structures tested under ambient vibrations is proposed in this paper. The method is applicable for simple rectangular plan-symmetric “box type” 3D building structures which may experience asymmetric damage, and it can be used for detecting, localizing and quantifying the damage. One of the main differences between the proposed and the existing methods is related to the inspection loads adopted to estimate the MF-based deflections. The inspection loads of the proposed method are more complex than the uniform translational loads adopted in the existing methods. Such proposed loads in fact can be assembled only after having estimated the position of the center of stiffness for each story of the structure. According to the proposed approach, the locations of the centers of stiffness are extracted from the experimentally-derived modal flexibility matrices, before performing the damage diagnosis process. The effectiveness and validity of the proposed method was demonstrated both through numerical analyses and by executing experimental ambient vibration tests on a frame building. The results of the proposed method were also compared with the existing approach which was developed for planar structures. This comparison (made both through numerical and experimental analyses) demonstrated that only the proposed approach can be used to perform a correct damage diagnosis process in plan-symmetric buildings which may experience asymmetric damage, especially when considering the damage quantification problem.

The purpose of the present study was to evaluate the radiographical outcomes, survival rate, and amount of bone formation around implants placed during graftless lateral sinus lift approach (GLSLA). Five patients (6 sinus augmentations) were consecutively treated with GLSLA. After Schneiderian membrane elevation and implant insertion, only blood clot was left to fill the new sinus compartment. After 4 months of healing, implants were functionally loaded. In all cases, samples were taken for biopsy at the time of second-stage surgery. The radiographical marginal bone variations and apical bone gain were assessed using cone beam-computed tomography taken 4 months after the surgery (at crown insertion) and after 4 years of loading. A total of 14 implants were placed in a mean initial residual bone height of 3.1 mm (range 1.6-4 mm). No failure was recorded, and all the implants were successfully loaded yielding a 100% survival rate. Vital bone formation was 33% according to the histomorphometry data. Four years after loading the mean radiographic bone remodeling was 1.3 mm. The mean ridge height was 7.6 mm and the mean apical bone gain amounted for 3.8 mm. Within the limitations of this study, the placement of dental implants in conjunction with GLSLA seems to be feasible and accompanied by high implant survival rate.

The Italian scientific societies of cardiology (SIC and ANMCO), cardiothoracic surgery, endodontics, and periodontology realized that a specific protocol addressing preoperative dental/peri-dental screening in patients undergoing elective cardiothoracic surgery was lacking in the literature. As a consequence, they projected and then realized in 2019 a consensus document to establish the modalities for such a diagnostic and therapeutic screening, whose related options and timing depend on the patient's physical conditions as well as the time available before surgery. A high level of agreement was reached by the experts involved in the release of the consensus document and each clinical issue was addressed adequately. Three tables were released, with the aim of sharing a standardized protocol for the perioperative dental/peri-dental screening of patients who are waiting for elective cardiothoracic procedures. The authors of the consensus document, which has been widely diffused by all the involved scientific societies, hope that it can be largely accepted and applied, during the multidisciplinary phase preceding cardiovascular surgery the most.

Condition monitoring of machines in non-stationary operations can be considered as one of the major challenges for the research in the field of rotating machinery diagnostics. The applications are ubiquitous: transport systems, energy systems, vehicles, production plants. On these grounds, the present work is devoted to measurement techniques and signal processing methods for the condition monitoring of bearings undergoing non-stationary operation conditions. Several types of experimental set ups are included in the present study and the advantages and drawbacks of each are discussed. For example, on one side an ad-hoc test rig for precision measurements is developed and utilized; on the other side, real scale measurement campaigns at operating non-stationary energy conversion systems (wind turbines) are performed. A special focus on energy systems is important because often in this kind of devices fault detection becomes much more challenging due to the interplay with electromechanical couplings. To face this drawback, the most advanced post-processing techniques need to be used. The application in the real field constitute an important part of this study because the fault diagnosis, and especially its interpretation, are much more challenging with respect to controlled laboratory conditions. The collected measurements are analysed through the most appropriate post-processing techniques employed for non-stationary signals. In the time domain, the statistical features of the signals are addressed through novelty indexes and principal component analysis. The results support that the Mahalanobis distance is an effective index in order to monitor the level of severity of the fault on the actual machine operation condition.

In civil engineering structures it is highly desirable to detect the presence of damage and changes in the global structural behavior at the earliest possible stage, and, among the many existing strategies for vibration-based damage detection, modal flexibility (MF)-based approaches are promising tools. However, in most of the existing studies, the experimental validation of such approaches has been performed on small-scale laboratory structures, where damage has been artificially imposed as stiffness reductions, for example by substituting some structural elements. It is thus important to continue to test the effectiveness of such MF-based approaches on full-scale structures characterized by more realistic damaged conditions. This paper focuses on the methods for output-only damage detection and localization that are based on the estimation of structural deflections from modal flexibility, and the objective of this paper is to test the applicability of such methods for locating damage in a full-scale reinforced concrete (RC) structure that has experienced earthquake-induced damage. The considered structure is a shear wall building that can be modeled as a bending moment-deflecting cantilever structure, and was tested on the large-scale University of California, San Diego—Network for Earthquake Engineering Simulation (UCSD-NEES) shaking table. Two approaches, which are based, respectively, on the estimation of the curvature and the damage-induced rotation from the deflections, have been applied and compared on the data of the considered case study. These approaches have been applied in different scenarios characterized by different data sets and by a different number of degrees-of-freedom measured on the considered structure.

An accumulating body of evidence supports an independent association between high blood pressure (BP) and periodontitis, possibly mediated by low-grade inflammation. This joint report by the Italian Society of Hypertension (SIIA) and the Italian Society of Periodontology and Implantology (SIdP) working group on Hypertension and Periodontitis (Hy-Per Group) provides a review of the evidence on this topic encompassing epidemiology, biological plausibility, relevance, magnitude, and treatment management. Consensus recommendations are provided for health professionals on how to manage BP in individuals showing signs of poor oral health. In summary, (1) large epidemiological studies highlight that individuals with periodontal diseases have increased risk for high/uncontrolled BP independent of confounders; (2) mechanistically, low-grade inflammation might have a causal role in the association; (3) BP profile and control might benefit from periodontal treatment in pre-hypertensive and hypertensive individuals; (4) oral health status should be evaluated as a potential risk factor for high/uncontrolled BP, and effective oral care should be included as an adjunct lifestyle measure during hypertension management. Further research is needed to optimize BP management in individuals with poor oral health.

Thanks to emerging techniques in the field of signal processing and due to improvements in smart sensing systems which enable the event‐triggered acquisition of high‐fidelity data at the occurrence of strong ground motion events, seismic structural health monitoring has grown considerably in the last few decades. In this paper, the modal assurance distribution, an alternative time‐frequency representation of the modal features of multivariate and multicomponent signals, is extended for application to short‐term nonstationary vibrational structural responses in which the system may manifest its nonlinear behavior. A general procedure for the extraction of the decoupled normal modes is presented, which allows the identification of instantaneous modal parameters in order to investigate in detail the structural behavior during earthquakes. Valuable information that cannot be recovered by means of traditional criteria can thus be exploited for accurate damage assessment. The results obtained for two case studies consisting of a numerical model with softening nonlinear behavior and a full‐scale experimental reinforced concrete benchmark show the potential and applicability of the method proposed for the integrity assessment of civil structures.

In the last years, different research on ballistic penetration of machine tools guards, as defined in EU Directive 2006/42/EC, were conducted in different worldwide laboratories. Even if the design of machine safety guards using the material/thickness are defined in annexes of ISO standardization, a revision of those annexes is expected in next years. Standardized tests have some limitations because they are performed using a given penetrator that impacts perpendicularly the surface of flat plates of about 500 mm x 500 mm. In this paper the influence of some design parameters will be investigated by polycarbonate sheets of 4mm thickness. The evaluation of ballistic limit for 4 mm sheets of 300 mm x 300 mm and 500 mm x 500 mm size will be presented. Moreover, the influence of constraint on ballistic limit of standardized 500 mm x 500 mm sheets will be also presented by two different constraint devices: one similar to a border hinge constraint, one to a border rigid clamping. Discussion of results will be presented with a view to review the ISO standardization annexes on ballistic penetration.

Introduction Open pyeloplasty has been the first-line treatment for uretero-pelvic junction obstruction for decades. In the last years, minimally-invasive surgery (MIS) has gained popularity in the pediatric's field. Furthermore, recently, a great extension of Robot-assisted laparoscopic pyeloplasty (RALP) has been seen in younger and lighter-weight children as well as in redo cases. Herein we provided a comprehensive review of primary and redo RALP performed in children, particularly focusing on the different distribution of outcomes among the ages. Evidence acquisition A systematic review of the literature was performed according to PRISMA recommendations and was conducted on surgical indication and technique, intraoperative nuances, peri- and postoperative outcomes of primary and redo RALP. Evidence synthesis Overall, 33 studies with 1448 patients were included for primary RALP and 7 studies with 101 patients for redo cases between 2000 and 2019. In particular, 4 studies aimed to compare RALP in different cohorts of children grouped on ages or weight and 4 studies evaluated technical feasibility and safety of RALP over laparoscopic and open approach in very young populations. Success rate for primary RALP was found >90% in all studies but one, with low complication rate and reoperative indication. In redo series, 96% of patients revealed a decreased hydronephrosis on postoperative imaging. Conclusions RALP offers excellent outcomes in the pediatric population. However, there is still a strong need for higher quality evidence in the form of prospective observational studies and clinical trials. The rising of new robotic systems, such as single-port platform, might further enhance the applications of RALP in children.

none 5 si Modal flexibility-based methods are recognized in the literature as effective methods for detecting damage in structures using vibration measurements. However, the application of such methods with output-only data (as is the case of civil structures tested under ambient excitations) is challenging, because the mass normalization factors required for assembling the modal flexibility matrix cannot be estimated directly from the data. To address this issue, a method for output-only damage detection and localization in building structures that can be applied with minimal or no a-priori information about the structural masses has been proposed in a previous work by the authors. In the method, to estimate the mass distribution and to assemble the proportional flexibility matrices, the modal orthogonality relationships that involve the mode shapes and the structural masses are used to form a system of equations, and through that system of equations, an inverse problem is solved for the estimation of the mass distribution. Reducing the number of available modes, however, reduces the number of available equations, while the number of unknowns (i.e., the number of degrees of freedom) stay the same; hence, the approach cannot be applied when the modal space is severely truncated. This paper proposes a technique for estimating the mass distribution and assembling proportional flexibility matrices from output-only vibration data that overcomes the mentioned limitations and that can be applied for any number of identified modes, including the case in which the modal space is severely truncated. The proposed technique is then integrated into the above-mentioned method for output-only damage detection in building structures, to verify the applicability of the whole procedure when considering the case of severely truncated modal spaces. Numerical simulations and experimental vibration tests were used to demonstrate the validity and effectiveness of the approaches proposed in this paper. mixed Bernagozzi G.; Mukhopadhyay S.; Betti R.; Landi L.; Diotallevi P.P. Bernagozzi G.; Mukhopadhyay S.; Betti R.; Landi L.; Diotallevi P.P.

The management of UCs remain controversial, especially for UCs with duplex collecting systems that still represent a great challenge in paediatric urology. Several approaches have been used and a shared management is not yet validated.Aim of our study is to evaluate the results of the endoscopic treatment of UC comparing ortothopic single-system UC and ectopic duplex-system UC over a 10-year period in a single referral tertiary center. Success was defined as resolution of dilation, lack of urinary infections and preservation of renal function.We retrospectively reviewed medical records of children with a diagnosis of UC who underwent endoscopic puncture at our division from January 2009 to January 2019. Patients were divided in two groups: Group A composed of patients with ectopic UC associated with renal duplex system and Group B with orthotopic UC in single collecting system.We identified 48 paediatric patients treated with transurethral primary endoscopic incision. Groups result homogeneous for clinical and pathological characteristics. The only statistical significative difference between the two samples was the age at diagnosis (p value with Yates correction = 0.01).We considered as a therapeutic success infections control and the elimination of obstruction with preservation of global kidney function. Based on that, our success rate after single (77%) or double (92%) endoscopic treatment is higher than data reported in literature. Differently from previous studies, vescico-ureteral reflux without UTIs was not considered as a failure of the procedure. The present study has some limitations: it is a retrospective and monocentric serie and it lacked a longer follow-up; on the other hand, it has been conducted on a quite large sample size and it is one of the few studies that compares the endoscopic treatment between orthotopic and ectopic UC.Our data report primary endoscopic puncture of ureterocele as a simple, effective, and safe procedure also in long-term follow up. This technique avoids the need for additional surgery in the majority of the patients, also in the case of an ectopic UC associated to a duplex system.