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This study evaluates the influence of different loading angles and the area of loading on the ensuing stress distribution and the physical response of a natural central incisor tooth, using a 3D finite element analysis. The CAD model of the incisor tooth assembly (including enamel, dentin, periodontal ligament, pulp, gingiva and jaw bone) was subject to an external (chewing) load of 100 N, over four different areas and at four different angles along the vertical. It was observed that the tooth experiences high von-Mises equivalent stresses and high bending when the load applied is closer to the incisal edge of the crown. Also, the stresses on the dentin, in general, increased with the increase in the loading angle regardless of the area of loading; with the highest stress (~70 MPa) generated at 45° angle. The percentage change observed in dentin von-Mises stresses was higher than that of enamel when the loading angle was increased from 0° to 45°, because of the higher stiffness of enamel and structural differences in enamel and dentin. The numerical results indicated that applying loads on incisal edge would simulate a severe loading condition for the incisor tooth.

Emerging sutureless wound-closure techniques have led to paradigm shifts in wound management. State-of-the-art biomaterials offer biocompatible and biodegradable platforms enabling high cohesion (toughness) and adhesion for rapid bleeding control as well as robust attachment of implantable devices. Tough bioadhesion stems from the synergistic contributions of cohesive and adhesive interactions. This Review provides a biomacromolecular design roadmap for the development of tough adhesive surgical sealants. We discuss a library of materials and methods to introduce toughness and adhesion to biomaterials. Intrinsically tough and elastic polymers are leveraged primarily by introducing strong but dynamic inter- and intramolecular interactions either through polymer chain design or using crosslink regulating additives. In addition, many efforts have been made to promote underwater adhesion

COVID-19 epidemic had a significant impact on many aspects of people lives, when these people urged to quarantine and lockdown to prevent the virus from spreading which had a major effect on people’s mental health, depression and stress. Many internal and environmental causes contribute to this stress, which has a detrimental impact on the body’s homeostasis. As a result, stress may have an impact on the body’s ability to conflict pathogens using its energy. Many recent studies have revealed strong associations between human mental stress and secretion of hormones, prohormones and/or immunological substances, part of these studies have confirmed the correlation between stress and the salivary CgA level, also Secretory IgA (sIgA) plays an important role in immunity by binding the surface molecules of pathogenic microorganisms and preventing adhesion and colonization. The aim of this study is to measure salivary chromogranin A as a stress biomarker as well as Secretory IgA levels among COVID-19 patients. 84 samples were collected from adults who have been divided into two groups: COVID-19 group consists of 42 patients and COVID-19 free group which consists of 42 subjects. All subjects undergo PCR test to confirm their healthy status, collection of unstimulated saliva was done and laboratory investigations was carried out to measure the salivary chromogranin A and Salivary IgA levels by the use of chromogranin A kit (human CGA ELISA kit) by alshakirate establishment for medical supply and SIgA kit (IgA saliva ELISA) by LDN company. SPSS version 21 was used for statistical analysis. Salivary chromogranin A was substantially greater in the COVID-19 group than in the COVID-19 free group, whereas secretory IgA was lower in the COVID-19 group, according to the statistical analysis. In conclusion a significant negative association was found between salivary chromogranin A and secretory IgA (p = 0.001).so, when the concentration of salivary chromogranin A elevated in the COVID-19 group, the level of secretory IgA reduced.

Heterocyclic compounds, such as benzimidazole derivatives, are a type of heterocyclic chemicals. Benzimidazole consists of a 6-atom benzene ring fused to the five-atom imidazole ring, which is an important structural property of this compound. A powerful inhibitor of various enzymes was used to investigate several pharmacological residences. Heterocyclic compounds, including benzimidazoles, are interested in being very effective compounds and are used in the preparation of many medicines, including as antiviral, anticancer, antiparasitic, antimicrobial, antihistamine, analgesic and as effective treatments for diabetes. Because of their stability, bioavailability, and have large organic activity, benzimidazole derivatives have multiple activities. Using various azole moieties, modifications to a few organic polymers was achieved. This article will discuss some of the current methodologies of synthesizing benzimidazoles and their pharmacological properties, as well as a variety of derivatives.

Background: Stenotrophomonas maltophilia is an aerobic, Gram-negative, no fermentative bacteria. It is an uncommon bacteria that is difficult to treat in people. The initial term was Bacterium bookeri, however it was eventually renamed to Pseudomonas maltophilia. It was resistant to multiple antibiotics, and its mechanisms also include acquired and intrinsic resistance. It is innately multi drug resistant (MDR) and found in watery and humid environments in the environment. Aim of study: The study amid to see if there were any antibiotic resistance genes in specimens that were found in S. maltophilia. Materials and methods: The S. maltophilia isolates were isolated and identified from 250 of clinical specimens, biochemically analyzed, susceptibility test by using Kirby-Bauer disk diffusion method and genetically screened for antibiotic resistance genes using a traditional (PCR). Results: The molecular profile revealed that (L1Q gene) was identified in 20 (100 %) of S. maltophilia isolates and (L2Q gene) was found in 20 (90 %) of S. maltophilia isolates for β- lactamase antibiotics, and (Aph gene) was found in 20 (15 %) of S. maltophilia isolates for aminoglycoside.

Oral diseases, while largely preventable, pose a major health burden for many countries and affect people throughout their lifetime, causing pain, discomfort and disfigurement. Mouth washing agents are an effective vehicle for antimicrobial compounds in reducing oral pathogens, managing dental plaque and maintaining proper oral health. Numerous plant extracts have been successfully incorporated into oral care products due to their antimicrobial properties, availability, and affordability. Tea plants and extracts are one of the most important natural compounds used in dental care products. The problem with tea extracts is their bitter taste, which could compromise their usage by people. So, it needs a kind of supplementation to be palatable, especially for the pediatric and geriatric populations. Hence a nonnutritive sweetener was added to tea extracts to suppress their bitter taste. This study aimed to determine the effect of nonnutritive sweeteners on the antifungal activity of black and green tea aqueous extracts against salivary C. albicans. The results showed that adding 1% of stevia and sucralose to the black and green tea aqueous extracts did not affect the antifungal activity against salivary C.

In this study, we synthesized new sulfamethoxazole azo derivative by converted the SMZ drug to diazonium salt and coupling it with salbutamol in the alkaline medium to form an orange water-soluble azo dye that has a maximum absorption at λmax 450 nm. This reaction was used in the spectrophotometric determination of SMZ drug. It was obeyed to beer-lambert,s low over concentration between (10–100 mg.L-1) with LOD (0.507 mg.L-1), LOQ (1.5 mg.L-1) and molar absorptivity (2332.2 L.mol-1.cm-1). The approach indicated great sensitivity for the assessment of chosen medicine. Another method, a new cloud point extraction approach, was successfully used to extract the SMZ medication in its pure form as well as in pharmaceutical formulations. Due to its features and structure, non-ionic surfactant, also known as 2-[4-(2,4,4-trimethylpentan-2-yl)phenoxy] ethanol, was chosen as the green extraction solvent in this study. The effect of several parameters on the CPE of Sulfamethoxazole, including as the type and volume of surfactant, salt, temperature, and incubation duration, was thoroughly researched, and a set of ideal conditions was established. The correlation coefficient (R2) for the calibration curve was found to be 0.9956. The limit of detection (LOD), limit of quantitation (LOQ) and molar absorptivity were 0.122 mgL-1, 0.403 mg.L-1 and 11319.41 L.mol-1.cm-1, respectively.

Serious infections, and rising resistant infections, by pathogenic bacteria, have become developing threats worldwide. There is an increasing need to develop and discover a new treatment options that can act effectively to cure infections, with lesser resistance, side effects and toxicity. Identification of new treatment options against pathogens is an important issue nowadays. Ellagic acid is a non-drug compound that has been shown to possess many biological activities and is presented in many red fruits and berries. This study aims to evaluate and measure the antimicrobial activity and the minimum bactericidal concentration (MBC) of ellagic acid on Methicillin-resistant Staphylococcus aureus (MRSA), Pseudomonas aeruginosa, and Escherichia coli. The antibacterial activity of ellagic acid was evaluated against ten purified bacterial isolates via agar disc diffusion assay, and minimum bactericidal concentration assay (MBC). The results show that ellagic acid was an effective antimicrobial compound against all the tested pathogens. The MBC range was shown to be between (1-2) mg/ml for MRSA, and E.coli, and between(1-1.5) mg/ml for P. aeruginosa. This current study has detected and proved the antimicrobial activity of ellagic acid against important and widely resistant pathogenic bacteria like MRSA, P. aeruginosa, and E.coli.

In this article, three elemental (dipole, loop, and meander) designs of an implanted biomedical device (IBD) antenna are studied to provide an enhanced understanding of fundamental (material and geometry) factors which would contribute to the regulation of a steady vital sign, with minimal effect on the surrounding tissue during monitoring and treatment. Dipole and Loop antennas are known to offer similar advantages in that they are both balanced antennas, while the Meander antenna is likely to offer better radiation resistance. The investigation was carried out through the design of experiments and finite element modeling of the temperature field due to the AC level applied (10 or 100mA), under the geometry of each given antenna type and three material options (Titanium, Cobalt Chromium, and Macor). Finally, a multi-criteria decision-making process is applied to select the optimal design under maximum field temperature, thermal conductivity, electrical conductivity, density, and specific heat attributes. The findings suggested that the Meander design made of Titanium would allow for a maximized overall performance with minimal thermal and radiation effects.

the role of nutrition in developing pre-diabetes among obese children and adolescents remains a major problem. Method: A cross-sectional study based on food frequency questionnaire data was conducted on obese children and adolescents aged 6–18 years at Al-Faiha Specialized Diabetes, Endocrine, and Metabolism Center (FDEMC) in Basra (South Iraq) from November 1, 2021, to the end of May 2022. This study aimed to assess dietary patterns for obese children and adolescents who are at risk for pre-diabetes. Results: 155 obese children and adolescents aged 6–18 years participated in the study, 60% of whom were males and 40% female. 40% (n=62) had Impaired fasting glucose (IFG), and 16.8% (n=26) had Impaired glucose tolerance (IGT). Regarding the dietary pattern, this study discovered that 58.7% (n=91) of the participants have a neutral eating habits score, followed by 40.0% (n=62) of them have an unhealthy eating habits score, while only 1.3% (n = 2) of participants have healthy eating habits. However, this study found significant static associations between dietary habits and education level, socio-economic status, and father education. Conclusion: Healthy eating habits, weight reduction, and increased physical activity are all factors that assist in preventing pre-diabetes and its complication such as type 2 diabetes mellitus.

Biomaterials are increasingly being designed and adapted to a wide range of structural applications, owing to their superior mechanical property-to-weight ratios, low cost, biodegradability, and CO2 capture. Bamboo, specifically, has an interesting anatomy with long tube-like vessels present in its microstructure, which can be exploited to improve its mechanical properties for structural applications. By filling these vessels with a resin, e.g. an applied external loading would be better distributed in the structure. One recent method of impregnating the bamboo is plastination, which was originally developed for preserving human remains. However, the original plastination process was found to be slow for bamboo impregnation application, while being also rather complicated/methodical for industrial adaptation. Accordingly, in this study, an improved plastination method was developed that is 40% faster and simpler than the original method. It also resulted in a 400% increase in open-vessel impregnation, as revealed by Micro-X-ray Computed Tomography imaging. The improved method involves three steps: acetone dehydration at room temperature, forced polymer impregnation with a single pressure drop to − 23 inHg, and polymer curing at 130 °C for 20 min. Bamboo plastinated using the new method was 60% stronger flexurally, while maintaining the same modulus of elasticity, as compared to the virgin bamboo. Most critically, it also maintained its biodegradability from cellulolytic enzymes after plastination, as measured by a respirometric technique. Fourier transform infrared-attenuated total reflection, and thermogravimetric analyses were conducted and showed that the plastinated bamboo’s functional groups were not altered significantly during the process, possibly explaining the biodegradability. Finally, using cone calorimetry, plastinated bamboo showed a faster ignition time, due to the addition of silicone, but a lower carbon monoxide yield. These results are deemed as a promising step forward for further improvement and application of this highly abundant natural fiber in engineering structures.

Electronically optimized bis-diazirine crosslinkers allow aliphatic polymers to be crosslinked with up to 10-fold improved efficacy, relative to earlier designs. Activation is achieved using modest temperatures or through UV or visible light.

Background: Appetite refers to the innate drive to eat food, which declines with aging. This condition is called anorexia of aging. Reduced appetite can result in malnutrition, which is associated with a lower body mass index (BMI). Aims of the study: To assess the differences between the anorexia of aging and selecting socio-demographic data among the elderly those residents in governmental geriatric care homes. Methodology: A descriptive, cross-sectional design has been carried out in the governmental geriatric care homes in Iraq Middle Euphrates governorates. The period of the study started (1 October 2020 to 27June 2021). A non- probability (purposive) sample was selected to obtain representative and accurate data for the (100) elderly individuals, living in geriatric care homes. Data were collected through both self-report and interviews approaches. Beside the Council of Nutrition Appetite Questionnaire (CNAQ), the socio-demographic and clinical characteristics sheets were included in the study tool and Statistical data analysis was performed using the IBM-Statistical Package of Social Science (SPSS) for Windows, version 24. Results: The study included 100 participants, more than half (65.0 %) of the study sample were males and (35%) were female with mean age (72) years old. the study findings indicate there are differences between anorexia of aging and age, marital status, BMI and smoking history. on differences between anorexia of aging and educational level. Conclusion: It has been concluded that older residents are at higher risk of anorexia associated with aging than the younger age, so they are more likely to suffer malnutrition and unintentional weight loss. Recommendations: The study recommended increasing interest and continuous follow-up to the nutritional status of the elderly, as well as the unmarried and smoker's elderly.

Thermophysiological comfort is known to play a primary role in maintaining thermal balance, which corresponds to a person’s satisfaction with their immediate thermal environment. Among the existing test methods, sweating torsos are one of the best tools to provide a combined measurement of heat and moisture transfer using non-isothermal conditions. This study presents a preliminary numerical model of a single sector sweating torso to predict the thermophysiological comfort properties of fabric systems. The model has been developed using COMSOL Multiphysics, based on the ISO 18640-1 standard test method and a single layer fabric system used in sportswear. A good agreement was observed between the experimental and numeral results over different exposure phases simulated by the torso test (R2 = 0.72 to 0.99). The model enables a systematic investigation of the effect of fabric properties (thickness, porosity, thermal resistance, and evaporative resistance), environmental conditions (relative humidity, air and radiant temperature, and wind speed), and physiological parameters (sweating rate) to gain an enhanced understanding of the thermophysiological comfort properties of the fabric system.

Ascites syndrome occurs in growing broiler chickens in all parts of the world, which is one of the important causes of losses in many flocks, and its prevalence has been seen mostly in meat herds. The most important factor in the occurrence of ascites syndrome is the lack of oxygen in body tissues (hypoxia). Increasing the growth rate requires increasing the volume of blood flowing in the body to deliver nutrients to the organs and expel gases and metabolic products. Therefore, this experiment was conducted to compare the effect of peppermint extract and probiotics on the biochemical factors of the blood of chickens caused by ascites. The treatments were divided into 8 groups of 7 male chickens with 3 repetitions in each group at 21 days. The experimental treatments included control and treatments of peppermint, probiotic, peppermint and probiotic, induced ascites, induced ascites and peppermint, induced ascites and probiotics, induced ascites and peppermint and probiotics. At the end of 42 days, the blood factors of uric acid, triglyceride, glucose, cholesterol, ALT, ALP, and AST were measured by blood sampling. The experimental treatments significantly affected the investigated traits (P

The emerging advancements in separation and classification of various biological matters (e.g., living cells and proteins) using magnetic levitation (MagLev) technology have proven to be effective for improving disease diagnostics. MagLev technique has the capacity to detect and separate useful diagnostic biomarkers from biocomplex environments (e.g., blood and plasma), minimizing the unpleasant daunting task of sample preparations and labeling procedures. Here, we demonstrate the capability of this technique combined with image analysis and machine learning approaches for discriminating the various types of multiple sclerosis (MS) as an important model disease. To arrive at a systematic expert system, we combined robust statistical analysis with machine learning to (1) detect and remove outliers from the raw MagLev image datasets; then (2) process the images and output a low dimensional representation of massive data without losing the main statistical features; and finally (3) predict the MS clinical disease type (Relapsing-Remitting, Primary–Progressive, or Secondary–Progressive) using a classifier. This is expected to improve MS diagnostics since the current practices rely solely on clinical observation and central nervous system imaging, making management approaches are often reactional and inefficient. Thus, there is a need to identify the disease type early on. MagLev is expected to improve MS diagnostics, thereby aiding in prognosis and guiding adequate treatment choices before the patient exhibits signs of permanent neurological deficits.

Barrett’s esophagus is a pre-malignant lesion that can progress to esophageal adenocarcinoma. We perform a multi-omic analysis of pre-cancer samples from 146 patients with a range of outcomes, comprising 642 person years of follow-up. Whole genome sequencing reveals complex structural variants and LINE-1 retrotransposons, as well as known copy number changes, occurring even prior to dysplasia. The structural variant burden captures the most variance across the cohort and genomic profiles do not always match consensus clinical pathology dysplasia grades. Increasing structural variant burden is associated with: high levels of chromothripsis and breakage-fusion-bridge events; increased expression of genes related to cell cycle checkpoint, DNA repair and chromosomal instability; and epigenetic silencing of Wnt signalling and cell cycle genes. Timing analysis reveals molecular events triggering genomic instability with more clonal expansion in dysplastic samples. Overall genomic complexity occurs early in the Barrett’s natural history and may inform the potential for cancer beyond the clinically discernible phenotype.

In this study, the process of thermoplastic material deposition during 3D printing has been investigated via a multiphysics approach, using numerical and experimental tools. Namely, through computational fluid dynamics modeling, details of the flow structure and heat transfer process of the deposited material from the nozzle head onto the bed have been investigated. Experimental trials were conducted to validate the results of the computational model, and a good conformity between the results was obtained, with error less than 8%. Both curling and fluid mechanical swing machine print patterns were captured, especially given the high-viscosity and non-Newtonian characteristics of the flow. In particular, in the conducted case on ABS, results indicated that the ratio of the extrudate diameter to the nozzle diameter is around 12%. At feed rates lower than 100 mm/min, the curling takes place, where the extruded material bends up against the direction of the injection at the nozzle. It was observed that the fluid mechanical swing machine pattern takes place at the feed rate-to-moving bed speed ratios higher than 1.0, and depending on the nozzle to bed gap. High fidelity numerical platforms are deemed critical to better comprehend and predict complex local phenomena taking place during fused filament fabrication, and accordingly to more reliably optimize the process parameters.

The present study deals with the development of α-SiAlON-4%Co and α-SiAlON-20%TiCN ceramic composites with desirable properties tailored for enhanced high-cutting tool performance. The effective medium theories and mean-field homogenization schemes are used to design and optimize the volume fractions, the interfacial thermal resistance, and reinforcement particle sizes while incorporating the influence of porosity on the effective properties of the ceramic composites. The designed composites are fabricated via the spark plasma sintering process. The ceramic samples are characterized/analyzed via scanning electron microscopy, energy dispersive spectroscopy, and x-ray diffraction. The effective thermal and structural properties of the composites are measured and compared to that of the computational predictions. The results indicate that excellent densification in α-SiAlON-based composites can be achieved by the use of spark plasma sintering process. Experimentally measured properties of SiAlON-20%TiCN composite compare well with that of the computational predictions and have shown significant enhancement in its effective thermal conductivity and fracture toughness. The measured properties of SiAlON-4%Co composite did not meet the predictions due to Co agglomeration and the large thermal mismatch between the matrix and the inclusion, which emphasizes the need to optimize the synthesis process and establish volume fraction limits of Co in α-SiAlON ceramic composites.

Context There is growing interest in the relation between repetitive concussions and mental health; however, studies on the relation between concussion frequency and adverse mental health outcomes among female and male youth are lacking. Objective To examine the association between self-reported concussion frequency and non-fatal suicidal behaviors among youth and to explore the potential interaction of biological sex. Design Retrospective cross-sectional survey. Setting National Youth Risk Behavior Surveillance System. Participants 28,442 United States secondary school students. Main Outcome Measure(s) Exposure variables included frequency of self-reported sport/recreation-related concussion within the previous 12-months (0, 1, ≥2). Outcome variables included feelings of self-reported sadness/hopelessness, suicidal ideation, planning, and attempts. Covariates included age, sex, race/ethnicity, bullying victimization, sexual orientation, and physical activity. Results Students that reported ≥2 concussions were at significantly greater odds of reporting suicidal attempts (AOR = 2.03 [95% CI = 1.43, 2.88]) when compared to students reporting a single concussive event during the past 12-months. However, sex interactions revealed that this finding may be driven by males; the strength of associations did not increase from single to multiple concussions among females. Conclusions Findings from the present study suggest that adolescents who self-reported concussion were at increased odds of reporting poor mental health and suicidal behaviors. Moreover, increased number of concussive events may be associated with significantly greater odds of reporting suicidal attempts, particularly among males. Irrespective of sex, health care professionals should closely monitor mental health behaviors in adolescents with repetitive concussions, especially those that occur in close temporal proximity.

Alternative fuel sources, such as hydrogen-enriched natural gas (HENG), are highly sought after by governments globally for lowering carbon emissions. Consequently, the recognition of hydrogen as a valuable zero-emission energy carrier has increased, resulting in many countries attempting to enrich natural gas with hydrogen; however, there are rising concerns over the safe use, storage, and transport of H2 due to its characteristics such as flammability, combustion, and explosivity at low concentrations (4 vol%), requiring highly sensitive and selective sensors for safety monitoring. Microfluidic-based metal–oxide–semiconducting (MOS) gas sensors are strong tools for detecting lower levels of natural gas elements; however, their working mechanism results in a lack of real-time analysis techniques to identify the exact concentration of the present gases. Current advanced machine learning models, such as deep learning, require large datasets for training. Moreover, such models perform poorly in data distribution shifts such as instrumental variation. To address this problem, we proposed a Sparse Autoencoder-based Transfer Learning (SAE-TL) framework for estimating the hydrogen gas concentration in HENG mixtures using limited datasets from a 3D printed microfluidic detector coupled with two commercial MOS sensors. Our framework detects concentrations of simulated HENG based on time-series data collected from a cost-effective microfluidic-based detector. This modular gas detector houses metal–oxide–semiconducting (MOS) gas sensors in a microchannel with coated walls, which provides selectivity based on the diffusion pace of different gases. We achieve a dominant performance with the SAE-TL framework compared to typical ML models (94% R-squared). The framework is implementable in real-world applications for fast adaptation of the predictive models to new types of MOS sensor responses.

Biomass pyrolysis generates significant amount hazardous gases (such as CH

Zirconia-Alumina composite coatings have been extensively used in the field of tribology applications. Particularly, the partially stabilized zirconia has been employed in the recent years due to the combination of high hardness and chemical stability at aggressive environment. To the best of the knowledge, there is a lack of literature pertaining to the comparative evaluation on the frictional-wear behavior of partially stabilized Zirconia-Alumina composite (PSZAC) and fused zirconia-Alumina coating (FZAC). Hence, the present article aims to evaluate the frictional-wear behavior of PSZAC and FZAC coatings on Aluminium-Silicon (Al-Si) alloy engineered using the atmospheric plasma-spray technique. Tribo-parameters like Applied load (10 N, 20 and 30 N) and sliding velocity (0.5 m/s, 1.0 m/s and 1.5 m/s) have been varied during the dry sliding wear measurement. Scanning Electron Microscopy (SEM) reveals the hybrid pattern of grain structure with a less porosity for the respective composite coatings. The crystalline nature and the surface roughness are examined using the XRD analyser and surface profilometer respectively. The wear resistance of the dual ceramic coatings is improved compared to the Al-Si surface under all dry sliding conditions. The wear rate and Coefficient of Friction (CoF) of the FZA coating are lower around 1.2 times compared to ZAC coating due its improved surface hardness and the solid lubricant tribo effect. The worn surface of FZA coating evidences a solid ceramic lubricative layer, which acts as a preventive tribo layer. Further, the Taguchi methodology is adopted to optimize the wear rate and the CoF with respect to the tribo factors, which predicts the minimal wear rate and CoF of 0.75 × 10− 4 gm− 1 and 0.352 respectively for FZA coatings with 94.9 % of desirability.

The aim of the present work is to study the suppressed torsional vibration of shafts, with a clamped boundary condition at either end, via single or multiple undamped absorbers. Structures with such features often suffer from failures (e.g. fatigue, wear) caused by excessive vibrations. The shaft considered is under the action of a harmonic point moment. A vibration design benchmark for torsional absorbers is presented. For both cases of the shaft with one and two absorbers, the variation of absorber parameters, including attaching position, moment of inertia and torsional stiffness, are investigated. The optimal values of the absorber control parameters are obtained. First, the governing equation for the torsional vibration of the shaft and its absorbers is derived in a dimensionless form. Next, the free and forced vibrations of the system are investigated and dimensionless natural frequencies are obtained. To absorb the identified natural frequencies, we compute the $${L}_{2}$$ norm of the angular displacement of the shaft at these frequencies and tune the parameters of the absorbers to minimize the norm. A detailed analytical solution framework for determining the torsional vibration response of a shaft equipped with torsional vibration absorbers is developed. Minimizing the established relations for the $${L}_{2}$$ norm of the shaft’s torsion is examined for a wide range of frequencies, as a criterion for determining its absorption frequency. Advantage of using two absorbers over a single absorber is highlighted. Validation of the analytical model is achieved by comparisons to both numerical and experimental results.

The integration of advanced manufacturing processes with ground-breaking Artificial Intelligence methods continue to provide unprecedented opportunities towards modern cyber-physical manufacturing processes, known as smart manufacturing or Industry 4.0. However, the “smartness” level of such approaches closely depends on the degree to which the implemented predictive models can handle uncertainties and production data shifts in the factory over time. In the case of change in a manufacturing process configuration with no sufficient new data, conventional Machine Learning (ML) models often tend to perform poorly. In this article, a transfer learning (TL) framework is proposed to tackle the aforementioned issue in modeling smart manufacturing. Namely, the proposed TL framework is able to adapt to probable shifts in the production process design and deliver accurate predictions without the need to re-train the model. Armed with sequential unfreezing and early stopping methods, the model demonstrated the ability to avoid catastrophic forgetting in the presence of severely limited data. Through the exemplified industry-focused case study on autoclave composite processing, the model yielded a drastic (88%) improvement in the generalization accuracy compared to the conventional learning, while reducing the computational and temporal cost by 56%.

Temperature and humidity measurements in electrochemical energy devices are essential for maximizing their overall performance under different operating conditions and avoiding hazardous consequences that may arise from the malfunction of these systems. Using sensors for in situ measurements of temperature and relative humidity (RH) is a promising approach for continuous monitoring and management of electrochemical power sources. Here, we report on the feasibility of using thread-based sensors for in situ measurements of temperature and RH in proton exchange membrane fuel cells (PEMFCs) as an example of electrochemical energy devices. Commodity threads are low-cost and flexible materials that hold great promise for the creation of complex three-dimensional (3D) circuits using well-established textile methods such as weaving, braiding, and embroidering. Ex situ and in situ characterization show that threads can be introduced in the gas diffusion layer (GDL) structure to inscribe water highways within the GDL with minimal impact on the GDL microstructure and transport properties. Fluorinated ethylene propylene (FEP) is coated on thread-based sensors to decouple the response to temperature and humidity; the resulting threads achieve a linear change of resistance with temperature (−0.31%/°C), while RH is monitored with a second thread coated with poly(dimethylsiloxane) (PDMS). The combination of both threads allows for minimally invasive and dynamically responsive monitoring of local temperature and RH within the electrode of PEMFCs.

Composite materials have been widely used in the aerospace industry and are critical for safe operations. However, the delamination, caused by cyclic loads and corrosive service environment, poses a serious threat to the structural integrity of composite laminates. The acoustic emission technique has been adopted to assess the structural integrity by characterizing damage location, type, and size. This article proposes and compares data-driven prognostic methods to quantify the delamination area efficiently and accurately. To address the problem of insufficient inspection data, the prediction model adopts the path length across the delamination area as the target value. The delamination area can then be estimated with the predicted path length based on formulated geometric relationships. This solution will augment the model training datasets, and consequently, avoid the overfitting problem during the training process. Experimental results on composite coupons demonstrate that the proposed ensemble learning-based model outperforms other state-of-the-art methods in terms of prediction accuracy and efficiency.

Inter-ply slippage is known to be an important mechanism taking place during forming processes of textile composites, especially with respect to multi-layer fabric lay-ups. The coefficient of friction between the plies strongly depends on the structure and the orientation of forming fabric. Despite many numerical and experimental investigations, this dependency and its effect on the interaction between the plies has been overlooked. In this paper, the effect of fiber orientation on the interlayer friction of a typical thermoplastic fabric prepreg at room temperature is investigated. Results, through a polar representation of data, revealed that both static and dynamic coefficients of friction are statistically dependent on the lay-up orientation, applied normal load, along with their interaction. Further, it was identified that the repeated frictional loading of the plies results in a hysteresis, particularly for asymmetric layups due to non-negligible movement and realignment of filaments at the micro-scale. Finally, an empirical model was developed using an interpolation function (for pressure dependency) combined with a Fourier series (for orientation dependency), to predict the coefficients of friction.

The manufacturing of composite structures is a highly complex task with inevitable risks, particularly associated with aleatoric and epistemic uncertainty of both the materials and processes, as well as the need for in-situ decision-making to mitigate defects during manufacturing. In the context of aerospace composites production in particular, there is a heightened impetus to address and reduce this risk. Current qualification and substantiation frameworks within the aerospace industry define tractable methods for risk reduction. In parallel, Industry 4.0 is an emerging set of technologies and tools that can enable better decision-making towards risk reduction, supported by data-driven models. It offers new paradigms for manufacturers, by virtue of enabling in-situ decisions for optimizing the process as a dynamic system. However, the static nature of current (pre-Industry 4.0) best-practice frameworks may be viewed as at odds with this emerging novel approach. In addition, many of the predictive tools leveraged in an Industry 4.0 system are black-box in nature, which presents other concerns of tractability, interpretability and ultimately risk. This article presents a perspective on the current state-of-the-art in the aerospace composites industry focusing on risk reduction in the autoclave processing, as an example system, while reviewing current trends and needs towards a Composites 4.0 future.

Motivated by a desire to develop flexible covalent adhesives that afford some of the same malleability in the adhesive layer as traditional polymer-based adhesives, we designed and synthesized two flexible, highly fluorinated bis-diazirines. Both molecules are shown to function as effective crosslinkers for polymer materials, and to act as strong adhesives when painted between two polymer objects of low surface energy, prior to thermal activation. Data obtained from lap-shear experiments suggests that greater molecular flexibility is correlated with improved mechanical compliance in the adhesive layer., Flexible, highly fluorinated covalent adhesives are synthesized, and are shown to afford comparable C–H insertion efficiency and adhesion strength relative to a rigid analogue, while providing improved mechanical compliance in the adhesion layer.

Ghada Khafagy, Inas El Sayed, Shimaa Abbas, Saeed Soliman Family Medicine Department, Faculty of Medicine, Cairo University, Cairo, EgyptCorrespondence: Ghada Khafagy 71st, Moez El-Dwla, Makram Ebeed, Nasr City, Cairo 11765, EgyptTel +20 1006393140Email ghada.khafagy@kasralainy.edu.egIntroduction: Polycystic ovary syndrome (PCOS) is a common disorder that affects women during their reproductive age. Previous studies have suggested that PCOS may be linked to some mental disorders.Aim: The study aimed to estimate the perceived stress among adolescents with PCOS and investigate the relationship between PCOS symptoms and perceived stress scale (PSS) in adolescents.Methods: This was a case control study with 72 participants (between 11 and 19 years); 36 adolescents with PCOS and 36 matched controls were recruited from family medicine and gynecological outpatient clinics at Cairo University hospitals. They participated in a structured interview using a pre-designed questionnaire. Full general examination was conducted, including anthropometric measures, acne staging, and hirsutism staging using the Ferriman–Gallwey score. We assessed the severity of stress over the previous month of interview using the 10-item perceived stress scale (PSS-10).Results: There was a statistically significant difference in PSS scores among adolescents with and without PCOS; most cases with severe PSS scores were found to have PCOS. The mean score of PSS was higher in PCOS adolescents (20.416) than in the non-PCOS control group (18.8), but with no statistical significance. There was no significant correlation between the severity of PSS in PCOS adolescents and BMI, WC, acne or hirsutism severity; there was only weak positive correlation between PSS score and DBP (r=0.167).Conclusion: PCOS adolescents have higher incidence of severe perceived stress; however, degree of PSS was independent of BMI, WC, acne or hirsutism severity and shows only weak correlations with DBP. Our results urge the need for implementing a holistic approach that should include stress reduction programs to help adolescents get ready for their adult life.Keywords: PSS, polycystic ovary syndrome, anxiety, adolescents

This article, through an industrial-level case study, presents workflows employed for decision-making to mitigate cracking of glass fibre reinforced polymer (GFRP) parts in tight radii corner locations, often resulting from displacement-controlled de-moulding processes. Namely, using process simulation to evaluate the cure cycle of the GFRP composite parts, it was possible to optimize the time of de-moulding and reduce the potential for part damage. It was observed that the most significant factors influencing the corner defect were boundary conditions of the part during de-moulding, the workshop temperature and part thickness. The poorest process design case was identified as hot workshop temperature, a laminate with thickness on the upper end of tolerances and a boundary condition where most sides are free, allowing for the development of larger moment forces at the tight corners. Further to this, a de-moulding time chart was developed to account for the changes in material properties as a function of temperature and material thickness, allowing for the in situ decision-making of technicians to reduce the occurrence of corner cracks.

Desired mechanical properties like microstructure, micro hardness and wear resistance are the key parameters for which low carbon steel (AISI 1006) are widely selected. Surface heat treatment applied to improve these properties; traditionally surface heat treatments like induction hardening, in recent time’s laser surface hardening. In this work, thermochemical treatment (liquid nitriding) by using mixture from 61% NaCN, 15% K2CO3 and 24% KCL and followed by Nd:YAG laser surface treatment was done . The laser parameter were energy (0.89, 2, 4 and 9) J, spot diameter (0.790 ,0.33, 0.283 and 0.224) mm, pulses duration (1, 2.33, 4.47 and 9.87) ms with fix wavelength 1604nm. Laser surface treatment cycle was melting the layer surface, holding and rapid cooling in air medium. Optical microscopy (OM) and scanning electron microscope (SEM) has been used to study the microstructures and cross-sectional of molted and heat affected zones respectively. The wear test was done to measure the wear rate by using pin -on-disk principles were satisfied. The result shown that increasing in laser energy effects to increase in the area of melted and heat affected zones of nitriding steel. Also increasing in laser energy led to increase micro hardness about 61%, while wear rate decrease about 40 % and increased depth of molted zone.

In recent years, there has been a significant global shift towards use of polymer matrix composite materials in a wide range of industries, including aerospace, automotive, marine, and sports, among others. Despite the rapid uptake and widespread adoption of this material technology, there are still technical challenges faced daily by manufactures due to the inherent complexities of different composite processing techniques. This paper aims at establishing a new scheme for better quality control management of resin transfer molding (RTM) processing for thermosetting composites, using a Bayesian belief network (BBN). The data were collected through knowledge engineering among the manufacturing experts with the help of real-life application history. A total of 13 governing factors for the RTM process, which would theoretically have a role on the final product quality, were identified. The sensitivity analysis of the BBN showed that the major contributing factors of the quality are the resin viscosity profile, part design features, resin cure peak temperature, and reinforcement permeability. The conditional probability tables were constructed using a quality index from industrial experts, and the causal relationships captured by the BBN were built using knowledge engineering. It is also shown how the basic BBN model can be further updated by integrating the interaction weights between the attributes that define the product quality.