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Unintended shape distortions, such as spring-in, spring-back, and warping, commonly occur during the curing process of laminate composites. The source of dimensional changes at the macro-scale is residual stress. The main triggers for residual stresses at this scale are anisotropic behavior and the constraint effect of individual plies and tooling constraints. Thermoelastic residual stresses are quasi-reversible, whereas non-thermoelastic residual stresses are permanent, and the underlying mechanisms contributing to them are highly intricate. The challenges associated with simulating the curing of large-scale parts to obtain reliable engineering data are significantly influenced by factors such as thermal anisotropy, polymerization shrinkage, tool–part interaction, resin flow, and compaction. A comprehensive grasp of the involved phenomena can facilitate the creation and application of numerical tools that model the curing process, providing essential information on geometry distortion that is crucial for the overall manufacturing of structural components and assemblies. To ensure that a numerical prediction tool is dependable in terms of both accuracy and precision, it is essential to have significant experimental backing throughout the entire process, from selecting the appropriate mathematical models to calibrating the calculations of distortion values.

The Inconel 718 superalloy, a precipitation-hardenable material, is of particular interest for applications involving components operating under extreme conditions due to its excellent mechanical properties, high corrosion resistance at temperatures up to 700 °C, and good workability. At high temperatures, thermal transfer processes are crucial for temperature distribution across the component’s section, structural transformations, and variations in the alloy’s properties. The history of accidental overheating events is critical for the microstructure and properties of the alloy. Studies on thermal transfer in the Inconel 718 alloy available in the literature typically focus on the alloy in its as-delivered state. The experimental research presented in this paper examines the influence of repeated overheating history on the thermal diffusivity of the alloy.

This paper aims to investigate using FOAM to analyze the dynamic instability in the APPR for ADFTV based on a dynamic model (DMADFTV). The DMADFTV considers the following aspects: AD kinematic nonuniformity (ADKN), AD geometric nonuniformity (ADGN) of inertial characteristics for the spinning movements (ICSM) of the AD elements (ADE), and the excitations induced by the gearbox–internal combustion engine modulations. The DMADFTV is considered the already-designed dynamic model developed by the first author of the ADFTV in a previous publication. This DMADFTV was used to compute the stationary frontiers of instability and the nonstationary spectral velocity amplitude (NSVA) versus nonstationary spectral amplitude (NSA) in the configuration space in transition through APPR, using the FOAM. The use of FOAM is much more versatile, from the analytical point of view, than the method of multiple scales and allows the computation of the NSA and the NSVA in the APPR. In contrast, these computations cannot be performed using the harmonic balance method. MATLAB Software R 2017 was developed based on DMADFTV and used the FOAM to compute the stationary frontiers of instability and the NSVA versus the NSA in transition through APPR for the ADFTV. The numerical results were compared with the experimental and numerical data published in the literature, finding agreements. The computation of the NSVA versus NSA in the configuration space using FOAM represents a method of detection of the chaotic manifestation of ADFTV.

Social isolation and loneliness greatly contribute to negative health consequences in older adults. Technological solutions can be an asset in promoting social connections and healthy behaviours. This paper presents an innovative structure for an Internet of Things (IoT) platform specifically tailored for older persons. The framework utilises a supervised learning algorithm to classify users into four identified profiles to facilitate the adoption and engagement of technology. The platform incorporates wearables, such as socks and smart bands, to track physical activity, and a messaging module to encourage social interaction. The platform processes the acquired data to quantify steps and deliver tailored interventions remotely to the older adults through the AGAPE Assistant, the mHealth solution of the platform. Furthermore, the AGAPE Assistant has a user interface design for older adults, with a focus on their specific needs. Additionally, improving digital literacy among older adults is crucial for maximizing the long-term compliance and benefits of such technological solutions. On the other hand, AGAPE Monitor is a web application used by formal caregivers to configure the tailored interventions. The platform’s usability was assessed using different usability scale questionnaires, which revealed a mild level of user satisfaction and acceptance. The proposed framework is currently being deployed on more than 112 older adults across three countries: Italy, Romania, and Portugal. The proposed framework provides a holistic solution to encourage active ageing by adopting technology, implementing hybrid interventions, and promoting social interactions.

Corn silk, derived from the stigmas of corn (Zea mays, Poaceae) flowers, possesses valuable bioactive compounds that can be harnessed for therapeutical, nutritional, and industrial purposes. This research aimed to optimize the extraction of bioactive compounds from corn silk, specifically flavonoids and total antioxidant capacity, by comparing it with classical extraction (infusion and maceration). The study identified significant factors influencing total flavonoid content (TFC) and antioxidant activity (assessed through an ABTS assay), including ethanol concentration, ultrasonic amplitude, and their quadratic interactions. This optimized combination of independent variables (37.89% ethanolic concentration, 48.58% ultrasound amplitude, and an extraction time of 38.72 min) yielded a balanced extraction, maximizing both TFC and antioxidant activity. Further analyses revealed significant total phenolic content, total flavonoid content (50.69 ± 0.36 mg GAE, 23.54 ± 0.01 mg QE, and 78.33 ± 0.94 mg TE/g extract, respectively), and potent in vitro antioxidant activity, affirming the efficacy of the optimized extraction. The study also explored the inhibitory effects on α-glucosidase (IC50 = 411.67 ± 25.39 µg/mL), acetylcholinesterase (IC50 = 1166.4 ± 399.38 µg/mL), and pancreatic lipase (IC50 = 1519.67 ± 209.04 µg/mL), showcasing potential antidiabetic and neuroprotective properties. While tyrosinase inhibition activity was not observed, the research emphasizes the nutraceutical potential of corn silk, offering valuable insights for its utilization and further exploration in the pharmaceutical and functional food industries.

Pinus cembra L., also known as Swiss pine, is one of the lesser studied coniferous species, despite literature pointing out its great potential to be used for medical purposes due to its high contents in active phytochemicals. The aim of this study is to phytochemically assess rhytidome and periderm extracts obtained from Swiss pine from various locations and altitudes, so as to be able to deduce the best locations for harvesting samples with the highest biological activity. After the plant was analyzed histo-anatomically, hydroalcoholic extracts were obtained using ultrasounds, a rotary evaporator, and dry freezing. After determining the total polyphenolic content (TPC) in each sample, they were tested for antioxidant and enzymatic activity, while taking note of the influence of the varying altitudes and different harvesting regions on the intensity of each activity. The results from the TPC analysis show that rhytidome samples collected from the highest altitude (2429 m) displayed the highest content of polyphenols, with a general tendency for the amount of polyphenolic content to be directly correlated to altitude, this finding being further supported by the antioxidant activity also growing directly proportionally with the altitude. Enzymatic inhibition activity was found to be moderate for α-glucosidase and low for α-amylase. Following our findings, we can safely say that Pinus cembra L. extracts can be a great source of compounds with antioxidant activity; however, further studies are warranted to best determine the true potential of this species.

(1) Background: Perianal fistula represents a chronic local suppuration, and recurrent or incorrectly treated, this pathology has a negative effect on the life of patients. (2) Methods: A 12-month prospective study was conducted with a study group (patients at the second presentation) and a control group (patients at the first presentation). The BTL-6000 brand laser has 50 times the maximum power of conventional laser devices with an unmatched wavelength of 1064 nm and a tissue penetration power of up to 10 cm. It is highly effective in speeding up healing and pain management (3) Results: Transcutaneous high-intensity laser therapy of perianal fistulas proved effective with a promising positive impact on both symptomatology and local signs in the study group. As for the patients in the control group, 37 of them required a second hospitalization due to the recurrence of symptoms and to whom the same laser therapy was applied. (4) Conclusions: A beneficial and positive effect was observed in our study, mainly on the symptoms determined by the appearance of the perianal fistula, both in the short- and long-term. High-frequency laser therapy is of major importance, considering the lower costs compared to surgery as well as the discomfort created during local treatments.

Processing wood leads to the accumulation of considerable amounts of forest waste, such as branches, leaves and especially bark. These byproducts can be exploited for their high content of biomolecules. Our aim was to histo-anatomically and phytochemically characterize the older oak bark and evaluate the potential biological activities. After the histo-anatomical characterization and processing the plant material, the aqueous and hydroalcoholic extracts were obtained using microwave-assisted extraction (MAE) and ultrasound-assisted extraction (UAE). After the quantification of the total polyphenol content (TPC) and the total tannins content (TTC), the bark extracts were evaluated for antioxidant, antimicrobial and enzyme inhibitory activity. In the transverse section, the rhytidome (the succession of periderms) and the dead secondary phloem can be observed. The results of the polyphenol content of the oak bark extracts show that the hydroethanolic oak bark obtained using MAE has the highest absolute value of the TPC (347.74 mg/g). In comparison with the extracts obtained using UAE, the bark extracts obtained using MAE showed a significantly higher TPC. The greatest antioxidant and antibacterial activity were also recorded for the tested extracts. For gram-positive bacteria, the MBC values ranged from 0.3 (S. aureus) to 5 mg/mL and the oak bark extract obtained using MAE showed good activity against C. krusei (MIC—2.5 mg/mL). Among the assayed enzyme inhibitory activities, the extracts showed a significant antidiabetic effect in vitro with the highest activity corresponding to an IC50 of 3.88 µg/mL. The older oak bark represents a potential source of compounds with antibacterial, antioxidant or antidiabetic activity, which can be exploited through the biorefining processes.

The present work aims to design a robust method to detect and certify the deterministic chaos or ergodic process for the forced torsional vibrations (FTV) of a double tripod industrial driveshaft (DTID) in transition through the principal parametric resonance region (PPRR) which is considered by the researchers in the field as one of the most important resonance regions for the systems having parametric excitations. The DTID’s model for FTV considers the following effects: nonuniformities of inertial characteristics of the DTID’s elements, the harmonic torque excitation induced by the asynchronous electrical motor used for a heavy-duty grain mill, and the harmonic reaction torque generated by different granulation of the substance needed to be milled. Based on these aspects, a model of the FTV for the DTID was designed which was a modified, physically consistent model already used by the authors to investigate the FTV of automotive driveshafts (homokinetic transmission). For the DTID elements, the dynamic instability for nonstationary FTV in the PPRR using time–history analysis (THA) was analyzed—THA represents the phase portraits. Time–history analysis is a detection method for possible chaotic dynamic behavior for the nonstationary FTV (NFTV) in transition through PPRR. If this dynamic behavior was seen, a new robust method LEA–PM was created to certify and confirm the deterministic chaos for the NFTV of DTID. The new method, LEA–PM, is composed of the Lyapunov exponent’s approach (LEA) coupled with the Poincaré Map (PM) applied to the global system of differential equations that describe the FTV of DTID in the PPRR. This new robust method, which embeds LEA and PM, LEA–PM, establishes if the mechanical system has a deterministic chaotic dynamic behavior (strange attractor) or an ergodic dynamic process in this resonant region. LEA represents a new method that includes not only the maximal Lyapunov exponent method (MLEM) but also new mathematical criteria that is “the sum of all Lyapunov exponents has to be negative” which, coupled with MLEM, indicates the presence of deterministic chaos (strange attractors). THA–LEA–PM had been used for the NFTV of DTID computing the phase portraits, the Lyapunov exponents, and representing the Poincaré Maps of the NFTV for the DTID’s elements in transition through PPRR, founding deterministic chaos or ergodic dynamic behavior. Based on the obtained results, numerical simulations revealed the pitting manifestations of the DTID’s elements, typical for the geared systems transmission, mentioned recently in experimental data research for the homokinetic transmissions. Using the new robust method, THA–LEA–PM (time–history analysis coupled with LEA–PM) can be used in future research for chaotic dynamic analysis of DTID’s NFTV transition through superharmonic resonances, subharmonic resonances, combination resonances, and internal resonances. Time–history analysis as a detection method for chaos and LEA–PM as a certifying method for deterministic chaos can be integrated as a design tool for DTID’s FTV control of the homokinetic transmission.

This research’s goal is to model and analyze the forced bending vibrating (FBV) movements for the elements of an automotive driveshaft using a perturbation technique, the asymptotic method approach (AMA), in the region of principal parametric resonance (PPR). The PPR region was chosen because the principal parametric resonance region is one of the essential resonance regions. The model of FBV movements for the automotive driveshaft (AD) considers the aspects of the following phenomena: geometric nonuniformity of the AD elements and shock excitation due to the road. To overcome the equations for the FBV movements of the AD elements, all inertia characteristics were reduced to the longitudinal ax of the midshaft using the variation of the geometric moments of inertia with the concurrent axis and Stener’s theorem. The midshaft of the AD was considered a Timoshenko simply supported beam with a concentrated mass at both ends and springs and dampers for linear and rotational movements at both ends. To determine the equations describing the FBV movements of the AD elements, Hamilton’s principle was used. After establishing the equations of motion for each AD element coupled with the specific boundary conditions, the amplitude and the phase angle were computed for stationary and nonstationary motion in the PPR region using the first order of the AMA, and the dynamic instability frontiers were determined based on the same equations. The dynamic behavior of the AD was investigated concerning the variation of the damping ratio and the variation of the parametric excitation coefficient. The AMA coupled with the model of FBV movements for the AD exhibits the future research directions for analyzing FBV movements for the AD in the regions of superharmonic resonances, subharmonic resonances, combination resonances, internal resonances, and simultaneous resonances. Additionally, the AMA can predict the endurance of the AD and design control of car damping systems.

(1) Background: The success of prosthetic treatment with implant support depends on the combined effort of the team doctor-technician, each of them being responsible for the validation of execution stages. (2) Methods: we composed an online questionnaire with 18 multiple choice questions, using the Google Forms application. It was filled out by an equal number of prosthodontic specialists and dental technicians. Differences and associations were evaluated by Likelihood Ratio test, Linear by Linear association test, Kruskal-Wallis H test, Pearson Chi-Square test and the Fisher’s Exact test. (3) Results: Differences and similarities were found between the statements of prosthodontic specialists and dental technicians. Years of experience are correlated with the number of restorations, impression techniques and types of restoration (p ≤ 0.05). Similar answers for both groups were registered for preferred screw retained type of prosthetic abutment and most frequently reported complications. (4) Conclusions: The different perspectives of the two members of the prosthodontic team regarding the leading role in the treatment plan, type of abutment, impression technique and prosthetic design of implant fixed restorations has been revealed in our study. Similar education curricula and standards for continuing training courses after graduation are necessary for prosthodontic specialists and technicians in Romania.

Pollen allergies are a cause of much suffering for an increasing number of individuals. Current pollen monitoring techniques are lacking due to their reliance on manual counting and classification of pollen by human technicians. In this study, we present a neural network architecture capable of distinguishing pollen species using data from an automated particle measurement device. This work presents an improvement over the current state of the art in the task of automated pollen classification, using fluorescence spectrum data of aerosol particles. We obtained a relative reduction in the error rate of over 48%, from 27% to 14%, for one of the datasets, with similar improvements for the other analyzed datasets. We also use a novel approach for doing hyperparameter tuning for multiple input networks.

Background: The mechanisms of periimplantitis are mostly based on biofilm-induced inflammatory lesions around dental implants. However, the host reaction, reflected by the intensity of the inflammatory response to bacterial products, is crucial for peri-implant bone destruction. The aim of this pilot study was to measure total antioxidant status (TAS), the amount of IL-6, IL-8 and TNF-α (tumor necrosis factor), salivary lactate dehydrogenase (LDH) levels and the correlation with one-year peri-implant bone loss. Methods: Seven consecutive patients (Group 1), with the presence of at least one prior inserted dental implant, and three healthy individuals, fully dentate (Group 0), were enrolled. IL-6, IL-8, TNF-α, TAS and LDH were determined in saliva of both groups. Peri-implant marginal bone loss (MBL) at one year compared to baseline was evaluated for Group 1. Results: A statistically significant positive correlation was found in Group 1 between MBL and the IL-8 (p = 0.033) and a strong negative correlation between MBL and TAS (p = 0.002), but no statistically significant differences of the assessed parameters were found between the two groups. Conclusions: In the limits of the present preliminary study, salivary TAS and proinflammatory cytokines could be associated with the risk of peri-implant bone loss over time.

(1) Background: The development of a biocompatible material for direct additive manufacturing of maxillofacial extraoral prosthesis is still a challenging task. The aim of the present study was to obtain a photocurable PDMS, with nano TiO2 inclusions, for directly 3D printing of extraoral, maxillofacial prosthesis. The biocompatibility of the newly obtained nanocomposite was also investigated; (2) Methods: 2.5% (m/m) titania nanoparticles (TiO2) oxide anatase and a photoinitiator, benzophenone (BF) 4.5% were added to commercially available PDMS for maxillofacial soft prostheses manufacturing. The three different samples (PDMS, PDMS-BF and PDMS-BF-TiO2) were assessed by dielectric curing analysis (DEA) based on their viscosities and curing times. In vitro micronucleus test (MNvit) was performed for genotoxicity assessment and three concentrations of each compounds (2 mg/L, 4 mg/L and 8 mg/L) were tested in duplicate and compared to a control; (3) Results: The nanocomposite PDMS-BP-TiO2 was fully reticulated within a few minutes under UV radiation, according to the dielectric analysis. PDMS-BF-TiO2 nanocomposite showed the lowest degree of cyto- and genotoxicity; (4) Conclusions: In the limits of the present study, the proposed ex situ preparation of a PDMS-BP-TiO2 offers an easy, simple, and promising technique that could be successfully used for 3D printing medical applications.

Background: A maxillofacial prosthesis, an alternative to surgery for the rehabilitation of patients with facial disabilities (congenital or acquired due to malignant disease or trauma), are meant to replace parts of the face or missing areas of bone and soft tissue and restore oral functions such as swallowing, speech and chewing, with the main goal being to improve the quality of life of the patients. The conventional procedures for maxillofacial prosthesis manufacturing involve several complex steps, are very traumatic for the patient and rely on the skills of the maxillofacial team. Computer-aided design and computer-aided manufacturing have opened a new approach to the fabrication of maxillofacial prostheses. Our review aimed to perform an update on the digital design of a maxillofacial prosthesis, emphasizing the available methods of data acquisition for the extraoral, intraoral and complex defects in the maxillofacial region and assessing the software used for data processing and part design. Methods: A search in the PubMed and Scopus databases was done using the predefined MeSH terms. Results: Partially and complete digital workflows were successfully applied for extraoral and intraoral prosthesis manufacturing. Conclusions: To date, the software and interface used to process and design maxillofacial prostheses are expensive, not typical for this purpose and accessible only to very skilled dental professionals or to computer-aided design (CAD) engineers. As the demand for a digital approach to maxillofacial rehabilitation increases, more support from the software designer or manufacturer will be necessary to create user-friendly and accessible modules similar to those used in dental laboratories.

In this paper, we investigated various physiological indicators on their ability to identify distracted and drowsy driving. In particular, four physiological signals are being tested: blood volume pulse (BVP), respiration, skin conductance and skin temperature. Data were collected from 45 participants, under a simulated driving scenario, through different times of the day and during their engagement on a variety of physical and cognitive distractors. We explore several statistical features extracted from those signals and their efficiency to discriminate between the presence or not of each of the two conditions. To that end, we evaluate three traditional classifiers (Random Forests, KNN and SVM), which have been extensively applied by the related literature and we compare their performance against a deep CNN-LSTM network that learns spatio-temporal physiological representations. In addition, we explore the potential of learning multiple conditions in parallel using a single machine learning model, and we discuss how such a problem could be formulated and what are the benefits and disadvantages of the different approaches. Overall, our findings indicate that information related to the BVP data, especially features that describe patterns with respect to the inter-beat-intervals (IBI), are highly associates with both targeted conditions. In addition, features related to the respiratory behavior of the driver can be indicative of drowsiness, while being less associated with distractions. Moreover, spatio-temporal deep methods seem to have a clear advantage against traditional classifiers on detecting both driver conditions. Our experiments show, that even though learning both conditions jointly can not compete directly to individual, task-specific CNN-LSTM models, deep multitask learning approaches have a great potential towards that end as they offer the second best performance on both tasks against all other evaluated alternatives in terms of sensitivity, specificity and the area under the receiver operating characteristic curve (AUC).

(1) Background: Occlusal vertical dimension (OVD) in the optimal maxillo–mandibular relationship is an important parameter to establish when complex dental rehabilitation has to be done. The optimal method to measure OVD is still a challenge in everyday practice. The aim of the present study was to test the reliability of the correlation between OVD and some anthropometric and cephalometric methods described in the literature. The validity of OVD registration using a facial scanner was also assessed. (2) Materials and Methods: 150 dentate participants, aged 20–25 years, were randomly selected using sealed envelopes. Anthropometric measurements between specific standard points were performed: Subnasion–Prementon (Sn–PM) and Subnasion–Gnation (Sn–Gn) in maximum intercuspation and in the rest mandibular position, right and left pupil to the corresponding chelion. The cephalometric measurements registered were the lower facial angle and the angle between mandibular and Frankfurt planes. The distance Sn–Gn in maximum intercuspation was compared to all other parameters. Facial scanning, with a mobile phone and installed dedicated application, was performed on ten subjects, randomly selected using the same method among the participants, and the obtained 3D files were analyzed. The digital measurements were compared, for validity, to the clinical measurements. Pearson’s correlation coefficient was used, for comparing clinical Sn–Gn in maximum intercuspation position to the other parameters. (3) Results: A strong agreement between all measured anthropometric parameters of the facial scan and clinical contact measurement method was registered. None of the measured parameters could predict the exact OVD. (4) Conclusions: In the limits of our study, the facial scanning could be used for predictable registration of OVD and the stored digital information could be preserved through life and use for oral rehabilitation. However, if OVD needs to be determined, several measurement methods, including cephalometric measurements, need to be used simultaneously to reach a final decision.