This paper numerically investigates a 3D mesh independency study of a straight blade horizontal axis tidal turbine modelled using Computational Fluid Dynamics (CFD). The solution was produced by employing two turbulence models, the standard k-ε model and Shear Stress Transport (SST) in ANSYS CFX. Three parameters were investigated: mesh resolution, turbulence model, and power coefficient in the initial CFD, analysis. It was found that the mesh resolution and the turbulence model affect the power coefficient results. The power coefficients obtained from the standard k-ε model are 15% to 20% lower than the accuracy of the SST model. It can also be demonstrated that the torque coefficient increases with the increasing Tip Speed Ratio (TSR), but drops drastically after TSR = 5 and k-ε model failing to capture the non-linearity in the torque coefficient with the increasing TSR.

Recently Cold Bitumen Emulsion (CBE) mixture technologies have been developed to lower the pavement construction temperatures to reduce the environmental costs and control the gas emissions. Due to its poor early mechanical strength, active fillers (i.e. cement) have been used to obtain high early stiffness in order to have the potential for timely construction of the next layer. There is, however, a lack of understanding about the impact of active fillers nature on viscoelastic behaviour and fatigue damage resistance of CBE mastics. This study, therefore, aims to identify the influence of active fillers on the rheological properties and the resulted fatigue behaviour of CBE mastic, supported by chemical analysis for the filler-bitumen emulsion. For this aim, bitumen emulsion was mixed separately with seven fillers/blended fillers to prepare the CBE mastics. Various experiments include continuous pH monitoring tests (chemical reactivity of filler-bitumen emulsion), Strain sweep (SS) tests, Temperature-Frequency Sweep (TFS) tests, Time Sweep (TS) tests, and Linear Amplitude Sweep (LAS) tests were conducted on the CBE binder and the prepared mastics. Results show that the rheological performance and the fatigue damage resistance is not only dependent on the filler inclusions, but it significantly relies on filler type and chemistry. Based on that, the raise in complex shear modulus and the decrease in viscous components were associated with a significant enhancement in fatigue performance for specific filler.

We asked whether the level of peripheral fatigue would differ when three consecutive exercise trials were completed to task failure, and whether there would be delayed recovery in maximal voluntary contraction (MVC) force, neuromuscular activation and peripheral fatigue following task failure. Ten trained sport students performed three consecutive knee extension isometric trials (T1, T2, T3) to task failure without breaks between trials. T1 and T2 consisted of repeated 5-s contractions followed by 5-s rest. In T1, contractions were performed at a target force at 60% pre-exercise MVC. In T2, all contractions were MVCs, and task failure occurred at 50% MVC. T3 was a sustained MVC performed until force fell below 15% MVC. Evoked force responses to supramaximal electrical femoral nerve stimulation were recorded to assess peripheral fatigue. Electromyography signals were normalized to M-wave amplitude to assess neuromuscular activation. Lower levels of evoked peak forces were observed at T3 compared to T2 and T1. Within 5 s of task failure in T3, MVC force and neuromuscular activation recovered substantially without any recovery in evoked peak force. Neuromuscular activation 5-10 s after T3 was unchanged from pre-exercise values, but evoked peak forces were substantially reduced. These results challenge the existence of a critical peripheral fatigue threshold that reduces neuromuscular activation. Since neuromuscular activation changed independently of any change in evoked peak force, immediate recovery in force production after exercise is due to increased central recruitment and not to peripheral mechanisms.

Multiaxial fatigue experiments under asynchronous loadings with four different loading frequency ratios were carried out on 30CrMnSiA steel. The experimental results show that the fatigue life decreases when the axial or torsion frequency increases from 1 to 2, while there is no significant change when the axial or torsion frequency increases from 2 to 4. The surface crack paths are observed and show that cracks initiate on the maximum shear stress amplitude planes, propagate approximately tens of microns, and then turn to propagate along the maximum normal stress planes. The number of secondary cracks increases when the axial or torsion frequency increases. Subsequently, the Bannantine-Socie and Wang-Brown cycle counting methods along with various multiaxial fatigue criteria and Palmgren-Miner’s cumulative damage rule were used for fatigue life prediction. The experimental results are consistent with the fatigue life predicted by the Bannantine-Socie method with the section critical plane criterion for 30CrMnSiA steel under asynchronous loading paths.

A progressive FEA fatigue degradation model for composites was developed and implemented using a UMAT user material subroutine in Abaqus. Numerical results were compared to experimental strain field data from high frequency Digital Image Correlation (DIC) of split disk fatigue testing of pressure vessel cut outs with holes. The model correctly predicted the onset and evolution of damage in the matrix as well as the onset of fiber failure. The model use progressive failure analysis based on the maximum strain failure criterion, the cycle jump method and Miner sum damage accumulation rule. A parameter study on matrix properties was needed to capture the scatter in strain fields observed experimentally by DIC. S-N curve for the matrix material had to be lowered by 0% to 60% to capture the experimental scatter. The onset of local fiber failure had to be described by local S-N curves measured by DIC having 2.5 times greater strain than that of S-N curves found from standard coupon testing.

At present, failure definition and damage characteristic curve (DCC) analysis included in the framework to assess bitumen fatigue cracking performance have an inconsistency in ranking bitumen fatigue behaviour. This study utilized two types of self-healing polymers (STP and IPA1w) to modify the neat asphalt (NA), and research four different types of bitumens: NA, STP-modified bitumen, IPA1w-modified bitumen, and styrene-butadiene-styrene modified bitumen (SBSB), to evaluate the above-mentioned framework. All bitumens were subjected to short-term and long-term aging and tested utilizing the Linear amplitude sweep (LAS) test and simplified viscoelastic-continuum-damage (S-VECD) model. The results showed that the SBSB exhibited the highest numbers of loading cycles (in long-term aging analysis) to reach failure points at 25°C, 28°C, and 31°C which were 2290, 2340, and 2510, respectively. However, this bitumen failed to exhibit the best performance in terms of DCC assessment under the same conditions, confirming the above-mentioned inconsistency. Besides, the current failure criterion could not accurately predict bitumen fatigue behaviour under certain test conditions because two R2 values were below 0.1. As a result, this study proposed a new failure definition and failure criterion to overcome these issues. The proposed failure definition agreed with the DCC analysis to rank bitumen fatigue performance, and the proposed failure criterion showed R2 values higher than 0.9. The new framework presented the modified bitumen containing 0.5% of STP as the asphalt binder with the best fatigue cracking performance, according to the selected test conditions.

Background/Objectives: The aim of this study was to investigate feasibility and safety of neuromuscular electrical stimulation (NMES) in patients on extracorporeal membrane oxygenation (ECMO) and assess thoroughly any potential adverse events. Methods: We conducted a safety and feasibility study including 16 ICU patients on ECMO support who were admitted to the cardiac surgery ICU from January 2022 to December 2023. Patients underwent a 45-minute NMES session, still on ECMO support, that included a warm up phase of 5 minutes, a main phase of 35 minutes and a recovery phase of 5 minutes. NMES was implemented on vastus lateralis, vastus medialis, gastrocnemius and peroneus longus muscle of both lower extremities. Two stimulators delivered biphasic, symmetric impulses of 75 Hz, with 400 μsec pulse duration, 5 sec on (1,6 sec ramp up and 0,8 sec ramp down) and 21 sec off. The intensity levels aimed to cause visible contractions and be well tolerated. Primary outcomes of the study were feasibility and safety, evaluated by whether the NMES sessions were successfully achieved, and by any adverse events and complications. Secondary outcomes included indices of rhabdomyolysis from biochemical blood test, 24 hours after the application of NMES. Results: All patients successfully completed their 45-minute NMES session, without presenting hemodynamic deterioration, adverse events or signs of rhabdomyolysis. The majority of patients achieved type 4 and 5 quality of muscle contraction. Conclusions: NMES is a safe and feasible exercise methodology in patients supported with ECMO.

Systemic inflammation and coronary microvascular endothelial dysfunction are essential pathophysiological factors in heart failure with preserved ejection fraction (HFpEF) that support the use of statins. The pleiotropic properties of statins, such as anti-inflammatory, antihypertrophic, antifibrotic, and antioxidant effects, are generally accepted and may be beneficial in HF, especially in HFpEF. Numerous observational clinical trials have consistently shown a beneficial prognostic effect of statins in patients with HFpEF, while the results of two larger trials in patients with HFrEF have been controversial. Such differences may be related to a more pronounced impact of the pleiotropic properties of statins on the pathophysiology of HFpEF and pro-inflammatory comorbidities (arterial hypertension, diabetes mellitus, obesity, chronic kidney disease) that are more common in HFpEF. This review discusses the potential mechanisms of statin action that may be beneficial for patients with HFpEF, as well as clinical trials that have evaluated the statin effects on left ventricular diastolic function and clinical outcomes in patients with HFpEF.

Objective: This research was aimed to estimate the anti-fatigue effects of arecoline and elucidate its underlying mechanisms using a murine model of central fatigue precipitated by sleep deprivation (SD). Methods: Seventy-two male C57BL/6 mice were randomly allocated into six groups: a control group, a SD-induced fatigue model group, a group receiving Rhodiola Rosea capsules (2.5 mg/kg), and arecoline groups administered low, medium, and high doses (10, 20, and 40 mg/kg, respectively). Following 28 days of continuous administrations, the effects of arecoline on the mouse fatigue-related behaviors was assessed by the behavioral tests, including grip strength, rotarod performance, and weight-bearing swimming endurance. Enzyme-linked immunosorbent assays (ELISAs) were utilized to measure the levels of the relevant biochemical markers. Western blotting was employed to quantify the expression of nuclear factor erythroid 2-related factor (Nrf2), Kelch-like ECH-associated protein 1 (Keap1), heme oxygenase 1 (HO-1), sequestosome-1 (p62), and NADPH quinone oxidoreductase 1 (NQO1) in the gastrocnemius muscle. Results: Arecoline administration notably enhanced grip strength, delayed the onset of fatigue as evidenced by extended latencies in rotarod tests, and increased the duration of weight-bearing swimming in mice. In the elevated plus maze, arecoline significantly reduced both the number of entries and the total distance traveled in the open arms. Arecoline markedly decreased serum levels of creatine kinase, blood urea nitrogen, lactate dehydrogenase, triglycerides, and cholesterol, while elevated total testosterone, lactate dehydrogenase, and immunoglobulin G levels. Furthermore, it significantly increased superoxide dismutase(SOD), catalase(CAT), and glutathione peroxidase activity in the gastrocnemius muscle, reduced malondialdehyde levels, augmented hippocampal SOD and CAT activity, and elevated glycogen stores in both liver and muscle tissues. Neurotransmitter levels were significantly increased, cytokine levels were markedly reduced, and the expression of Nrf2, Keap1, NQO1, p62, and HO-1 in brain tissue was significantly upregulated. Conclusion: The current study for the first time demonstrated that arecoline has significant anti-fatigue activity, and its mechanism of action is related to elevate the levels of glucose and lipid metabolism, relieve oxidative stress damage, inhibit neuroinflammatory response, regulate neurotransmitter levels and Keap1/Nrf2/HO-1 signaling pathway. The current study provides a new insight into the potential of arecoline in prevention and improvement of fatigue.

The global increase of road infrastructure and its impact on the environment requires serious attention to develop sustainable and environmentally friendly road materials. One group of those materials is produced by using bitumen emulsion. However, there are still scientific and technical obstacles standing against its regular application. The bitumen emulsion formulation process and compositional optimization are subjected to a high number of degrees of freedom. Consequently, obtaining the desired product is mostly based on a series of random and tedious trials because of the enormous number of tests to be carried out. The current review of the physicochemical formulation may indeed be extensively used in helping to reduce the number of unnecessary experimentations as well as discuss the vital aspects in the bitumen emulsion production process. Among these, emulsion stability, viscosity, droplet size (and distribution), bitumen emulsion chemistry, the function of the emulsion components, surfactant type, acids or alkalis, and additives are all discussed and used to define the emulsion's physical properties and reactivity. Besides, current developments in the mechanisms of breaking and setting processes are also summarized. It is discussed how emulsions are graded based on their reactivity, particle charge, and physical features. Two emulsification techniques are outlined namely the colloid mill method and the High Internal Phase Ratio (HIPR) method. Furthermore, some emulsion formulation tools/theories were identified and are explained. In that way, optimized formulations can be used to offer a practical guide for bitumen emulsion manufacturers when trying to formulate a well-defined bitumen emulsion for its use in pavement infrastructure rather than simply to meet standard specifications. This review paper aims to enable the ultimate potential of the bitumen emulsion in the field of cold recycling technology by further following up the research progress of bitumen emulsion manufacturing, therefore, this paper reviews and discusses the literature available up to now on this topic, in road engineering and emulsion chemistry.

The prevalence of hepatitis B and delta viruses (HBV/HDV) among people who use drugs (PWUD) remains largely unknown. In the context of one Philadelphia-based harm reduction organization (HRO), this study aimed to assess HBV/HDV prevalence and facilitate linkage to care. Participants completed a demographic HBV/HDV risk factor survey and were screened for HBV and reflexively for HDV if positive for HBV surface antigen or isolated core antibody. Fisher’s exact tests and regression were used to understand relationships between risks and HBV blood markers. Of the 498 participants, 126 (25.3%) were susceptible to HBV, 52.6% had been vaccinated against HBV, and 17.9% had recovered from a past infection. Eleven (2.2%) participants tested positive for isolated HBV core antibody, 10 (2.0%) for HBV surface antigen, and one (0.2%) for HDV antibody. History of incarceration was associated with current HBV infection, while transactional sex and experience of homelessness were predictive of previous exposure. This study found high rates of current and past HBV infection, and a 10% HBV/HDV co-infection rate. Despite availability of vaccine, one quarter of participants remained vulnerable to infection. Findings demonstrate the need to improve low-threshold HBV/HDV screening, vaccination, and linkage to care among PWUD. The study also identified gaps in the HBV/HDV care cascade, including lack of point-of-care diagnostics and lack of support for HROs to provide HBV services.

Background and Objectives: Acute Heart Failure (AHF) is a common disease and a cause of high morbidity and mortality, constituting a major health problem. The main purpose of this study was to determine the impact of multiorgan ultrasound in identifying the pulmonary hypertension (PH) in patients admitted due to AHF, predict the evolution of the disease during hospitalization and identify areas of improvement in the care of patients with AHF. Materials and Methods: Patients were evaluated with a standard exam of lung ultrasound, echocardiography, inferior vena cava (IVC) and femoral, renal, hepatic, portal venous Doppler flow patterns at admission and on the day of discharge. Results: Thirty patients were enrolled during November 2021. The mean age was seventy-nine years (Standard Deviation – SD 13,4). Seven patients (23.3%) had a renal function worsening. Regarding ultrasound findings, venous excess ultrasonography score (VExUS) score was calculated at admission and at discharge, surprisingly remaining unchanged or even worsened in most of them (21 patients, 70.0%). The area under the curve for the Lung Score was 83.9% (p = 0.008), obtaining a cutoff value of 10 that showed a sensitivity of 82.6% and a specificity of 71.4% in the identification of intermediate and high PH. It was possible to monitor significant changes between both exams on the lung score (p <0.001), hepatic vein Doppler (p <0.001), portal vein Doppler (p = 0.030), intra-renal vein Doppler (p = 0.025) and VExUS score (p = 0.023), remaining similar the femoral vein Doppler (p = 0.177) and IVC (p = 0.132). Conclusions: Our study results suggest that performing serial multiorgan Point-of-Care ultrasound can help us to better identify high and intermediate probability of PH patients with AHF. Currently proposed multi-organ, venous Doppler scanning protocols, such as the VExUS score, should be further studied in different populations before expanding its use in AHF patients.

Rock materials failures are accompanied by the co-existence of various failure mechanisms, in-cluding rock fracturing, shearing, and compaction yield. These mechanisms manifest macro-scopically as multiple failure modes and nonlinear strength characteristics related to stress levels. Considering the limitations of current rock mechanics strength theories, which are primarily derived from single failure mechanisms, this study evaluates the applicability of alternative strength theories. Based on the extensional-strain criterion and the PMC (Paul-Mohr-Coulomb) model, a piecewise linear strength model was proposed that is suitable for analyzing multiple failure mechanisms in rocks and revealing the intrinsic mechanisms of multi-mechanism rock material failure. A multiple failure mechanism strength model in the form of inequalities was proposed, using the generalized shear stress, mean stress, and stress Lode angle as parameters. Strength tests conducted on sandstone and granite rock material samples under different stress conditions revealed distinct piecewise linear strength characteristics for both rock types, vali-dating the rationality and applicability of the multiple failure mechanism model. The findings construct a multi-mechanism failure model for rocks, providing enhanced predictive capabilities and aiding in the prevention of rock structural failures.

We generalize the point information gain (PIG) and derived quantities, i.e., point information gain entropy (PIE) and point information gain entropy density (PIED), for the case of the Rényi entropy and simulate the behavior of PIG for typical distributions. We also use these methods for the analysis of multidimensional datasets. We demonstrate the main properties of PIE/PIED spectra for the real data on the example of several images, and discuss further possible utilizations in other fields of data processing.

The Doppler band compensated by the keystone transform (KT) is limited. Therefore, it needs to be used in conjunction with the Doppler ambiguity compensation function to correct the range migration (RM) caused by maneuvering targets with Doppler ambiguity. However, the KT implemented by sinc interpolation suffers from significant performance loss at boundaries of compensation Doppler bands. Additionally, in a multi-target scenario, KT implementation methods occupy high complexity when the Doppler range of targets spans over two compensation Doppler bands. To address aforementioned issues, this study presents a variable Doppler starting point keystone transform (VDSPKT) method, where a new form of ambiguity compensation function is constructed, turning the Doppler starting point of the compensation band in KT variable. Firstly, the position of the compensation Doppler band is changed from fixed to adjustable as needed, enhancing the flexibility of KT. Crucially, the connection points of the compensation Doppler bands in sinc interpolation are reset, avoiding the performance loss at their boundaries. Also, the compensation band is adjusted to cover the narrow Doppler frequency range caused by targets, significantly improving the computational efficiency. Finally, the simulation results demonstrate that the proposed approach effectively addresses the performance degradation and high computational complexity of KT in the aforementioned scenarios, resulting in a computational load reduced by approximately 50% compared to traditional methods.

Background: Liver failure profoundly affects the immune system, leading to dysregulation of innate and adaptive immune responses. Body: This review explores the intricate relationship between liver function and immune homeostasis. The role of the liver as a central hub in immune response initiation is elucidated, emphasizing its involvement in hepatic inflammation induction and subsequent systemic inflammation. Cytokines, chemokines, growth factors, and lipid mediators orchestrate these immune processes, serving as both prognostic biomarkers and potential therapeutic targets in liver failure-associated immune dysregulation. Furthermore, the review delves into the mechanisms underlying immunosuppression in liver failure, encompassing alterations in innate immune cell functions such as neutrophils, macrophages, and natural killer cells (NK cells), as well as perturbations in adaptive immune responses mediated by B and T cells. Conclusion: Understanding the immunological consequences of liver failure is crucial for developing targeted therapeutic interventions and improving patient outcomes in liver disease management.

Extruded polystyrene (XPS) is frequently used in the construction of many different structures. It is therefore necessary to appropriately characterize its mechanical properties to ensure the safety of said structures. Among the available characterization tests, static bending tests are simple and easy to perform; owing to these characteristics, they should be performed more frequently than other tests. However, in static bending tests on XPS, there are several challenges owing to the high flexibility of XPS, and the chosen testing method and sample configuration affect the accuracy of characterization. In this study, three bending properties (Young’s modulus, proportional limit stress, and bending strength) of samples cut from an XPS panel were determined using three-point bending (TPB), four-point bending (FPB), and compression bending (CB) tests with varying sample span/depth ratios, and statistical analyses were performed to determine the relevance of the tests. The experimental results suggest that the TPB and CB tests were more feasible than the FPB test when the span/depth ratio was appropriately determined. However, clear differences were observed in the sample bending properties determined in these tests. In light of these findings, further studies should be conducted to elucidate these differences.

Panel data of our interest consist of a moderate number of panels, while the panels contain a small number of observations. An estimator of common breaks in panel means without a boundary issue for this kind of scenario is proposed. In particular, the novel estimator is able to detect a common break point even when the change happens immediately after the first time point or just before the last observation period. Another advantage of the elaborated change point estimator is that it results in the last observation in situations with no structural breaks. The consistency of the change point estimator in panel data is established. The results are illustrated through a simulation study. As a by-product of the developed estimation technique, a theoretical utilization for correlation structure estimation, hypothesis testing, and bootstrapping in panel data is demonstrated. A practical application to non-life insurance is presented as well.

The decompensation trajectory check is a basic step to assess the clinical course and to plan future therapy in hospitalized patients with acute heart failure (ADHF). Due to the atypical presentation and clinical complexity, trajectory checks can be challenging in the oldest old patients with acute HF. Point of care ultrasound (POCUS) proved to be helpful in the clinical decision-making of patients with dyspnea, but no study has attempted to verify its effectiveness in predicting determinants of HF in-hospital worsening. In this single-center prospective study, we consecutively enrolled patients aged 75 or older hospitalized with acutely decompensated HF in a tertiary care hospital. All the patients underwent complete clinical examination, blood tests, and POCUS including Lung Ultrasound, Focused Cardiac Ultrasound, Pleural Effusion score (PEFs), and Inferior Vena Cava (IVC) assessment. Out of 184 patients hospitalized with ADHF enrolled in the study, sixty experienced HF in-hospital worsening. No differences were found among patients with HF worsening and controls in terms of age, gender, frailty, and left ventricular ejection fraction. By multivariable logistic analysis, total PEFs [aOR: 1.15 (CI95% 1.02– 1.33), p = 0.043], and IVC collapsibility [aOR: 0.90 (CI95% 0.83 – 0.95), p = 0.039] emerged as independent predictors of acute HF worsening after extensive adjustment for potential confounders.

Aim: To investigate the effects of intensive physical exercise on retinal microvascular regulation in healthy volunteers by the adaptive optics retinal camera measurement. Methods: We included healthy volunteers (11 men and 14 women) aged 20.6± 0.9. Heart rate (HR) and systolic and diastolic blood pressure (SBP, DBP) were recorded before and after a submaximal physical exertion of continuously riding a training ergometer. The superior temporal retinal artery measurements were captured using the adaptive optics (AO) camera rtx1TM (Imagine Eyes, Orsay, France) without pupil dilatation. We compared measures of vessel diameter (VD), lumen diameter (LD), two walls (Wall 1, 2), wall-to-lumen ratio (WLR), and wall cross-sectional analysis (WCSA) before and immediately after the cessation of exercise. Results: Cardiovascular parameters: After exercise, SBP, DBP and HR changed significantly from 130.2±13.2 to 159.7±15.6 mm Hg, 81.2±6.3 to 77.1±8.2 mm Hg and 80.8±16.1 to 175.0±6.2 bpm, respectively (p < 0.002). Retinal microcirculation analysis: Before the exercise, the mean LD was 96.0±6.8, VD 118.5±8.3, WLR 0.234±0.02, WCSA 3802.8±577.6. The mean LD and Wall 1 did not change significantly after exercise but slightly decreased. The VD, Wall 2, WLR and WCSA decreased significantly (p

Heart failure is a prevalent cardiovascular condition with significant health implications, necessitating effective diagnostic strategies for timely intervention. This study explores the potential of continuous monitoring of non-invasive signals, specifically integrating Photoplethysmogram (PPG) and Electrocardiogram (ECG), for enhancing early detection and diagnosis of heart failure. Leveraging a dataset from the MIMIC-III database, encompassing 682 heart failure patients and 954 controls. Feature selection techniques were used to systematically select key features which were identified for their clinical relevance and significance in capturing cardiovascular dynamics and to reduce computational complexity and to decrease the chance of overfitting the ML algorithms. These features are then utilized to train and evaluate machine learning algorithms, resulting in a model with an impressive accuracy of 98%, sensitivity of 97.60%, specificity of 96.90%, and precision of 97.20%. The integrated approach outperforms single-signal strategies, showcas-ng its potential for early, precise, and non-invasive heart failure diagnosis. Furthermore, the study underscores the significance of continuous monitoring through wearables, emphasizing the benefits of integrating multiple signals for a comprehensive evaluation of cardiovascular health. The proposed approach holds promise for implementation in hardware systems to enable continuous monitoring, aiding in early detection and prevention of critical health conditions.

The high volume of water in molasses has made this study serious. The reason is that using molasses as a partial replacement without treatment significantly affects the rheological properties of the neat bitumen and increases the likelihood of moisture susceptibility of the hot-mix asphalt (HMA) pavement structure and create fractures of aggregate particles. Therefore, to use molasses as a partial replacement without affecting the structural integrity of the pavement, this study proposed a treatment method before blending it with petroleum-based bitumen. A series of experiment was conducted to accomplish the objective of this paper, including convectional tests, Fourier transform infrared (FTIR) test, amplitude and frequency sweep test, performance grade (PG) determination test, and multiple stress creep recovery (MSCR) tests. The IR spectra show that carbonyl index decreased with increasing molasses percent. There was PG improvement from the control grade to PG64 and PG70 when the base binder modified with 5-20% molasses and aged with rollingl thin film oven (RTFO) respectively. At the temperature 58oC nonrecoverable creep compliance at 3.2 kPa (Jnr3.2kPa) was decreased for each percent replacement. This led to improving the rutting potential. As well, at a temperature of 64oC the Jnr value was decreased only for 5% replacement, and then the Jnr value was gradually increased for the remaining percent replacement. Overall, this study revealed that treated molasses can be used as a partial replacement to enhance the rheological properties of the base bitumen and thus it can potentially be used to produce a sustainable bio-asphalt binder.

In regions with low-temperature action transverse cracks can appear in asphalt pavements as a result of thermal stresses that exceed the fracture strength of materials used in asphalt layers. To better understand thermal cracking phenomenon, strength properties of different asphalt mixtures were investigated. Four test methods were used to assess the influence of bitumen type and mixture composition on tensile strength properties of asphalt mixtures: tensile strength using the Thermal Stress Restrained Specimen Test (TSRST) and the Uniaxial Tension Stress Test (UTST), flexural strength using the Bending Beam Test (BBT) and fracture toughness using the Semi-Circular Bending Test (SCB). The strength reserve behavior of tested asphalt mixtures was assessed as well. The influence of cooling rate on strength reserve was investigated and correlations between results from different test methods were also analyzed and discussed. It was observed that the type of bitumen is a factor of crucial importance to low-temperature properties of the tested asphalt concretes. This conclusion was proved by all test methods that were used. It was also observed that the level of cooling rate influences the strength reserve and, in consequence, resistance to low-temperature cracking. It was concluded that reasonably good correlations were observed between strength results for the UTST, BBT and SCB test methods.

Heart failure is a global major healthcare problem with millions of hospitalizations annually and with a very high mortality. There is an increased interest in finding new and reliable biomarkers for the diagnostication, prognostication and therapeutical guidance of patients hospitalized for acute heart failure. There is data to sustain the role of CA 125, a worldwide used marker of ovarian cancer, in patients with heart failure. Several studies have shown links between CA 125 levels and congestion seen in acute heart failure, high mortality and readmission rates at 6 months follow up after discharge from acute heart failure and also a role of CA 125 in the guidance of heart failure therapy. There are also clinical trials that showed that several particularities of CA 125 make it even better than NTpro BNP ( a classical and more utilised marker of heart failure) in several scenarios of acute heart failure.

Bitumen is produced from non-renewable natural resources, continuously deplete and intrigues researchers to look for alternative binders. Annually, tons of waste engine oil (WEO) and crumb rubber (CR) are discarded unsustainably and pose a significant environmental threat. Adding these industrial waste products to asphalt provides a safe and cost-effective way for their disposal and improves the bitumen's performance in parallel. This study uses various combinations of waste engine oil and crumb rubber with 60/70 penetration grade bitumen to produce a partially synthetic bitumen. Adhesion being one of the critical characteristics of the bituminous binder has been assessed using the bitumen bond strength test along with physical and rheological properties. Results showed that waste engine oil with crumb rubber inclusion increases penetration and decreases the softening point, viscosity, complex modulus, and bonding strength. Additionally, polyphosphoric acid (PPA) in smaller dosages was also incorporated into the optimum percentage of CR + WEO to improve the properties of the binder. The results confirm that binder modification with waste engine oil and crumb rubber can be more effective with PPA. It is concluded that 35% of waste can replace the virgin binder giving a cost-effective and environmentally friendly solution.

Nanomaterials exhibit novel properties and profound attributes as an additive in asphalt binder modification. However, the application of nano-silica in asphalt binders and mixture modification is still limited and further research is required. Along these lines, in this work, nano-silica with a content from 2% to 8% and an increment of 2% were utilized in modifying the bitumen binder type C320, which is considered the most conventional type of bitumen used in Western Australia road asphalt mixtures. Various tests were performed to assess their properties including dynamic shear rheometer, penetration, softening point, and multiple stress creep recovery (MSCR) test. The extracted results revealed an increase in the strength and stiffness properties by lowering the penetration, improving the softening point, and increasing the complex shear modulus of all nano-silica modified bitumen samples. Interestingly, a relatively big content of nano-silica leads to a higher rutting resistance. Nevertheless, the rutting resistance was affected by the size of the nano-silica coated with the silane coupling agent. The ideal sample of nano-silica modified C320 was determined as NS-15nm (NS-A), which can improve the rutting resistance. Nevertheless, the rutting resistance of the modified asphalt mixtures needs to be further investigated in the future to elaborate on the impact of nano-silica as modified binders on the mechanical properties of Australian asphalt mixtures.

The task of weakly supervised point cloud semantic segmentation has received widespread attention and also has been widely used in autonomous driving, robotics, and modern industries. Due to the high dimensionality and large volume of point cloud data, many technical difficulties appeal to weakly supervised semantic processing, especially segmentation. However, weakly-supervised schemes usually provide only partial labelling information of the underlying point cloud data and thus need to effectively extract local features, geometric information, and contextual relationships only using these limited labelled data for supervised learning. To improve weakly-supervised semantic segmentation, we propose a novel segmentation network through the boundary-based feature aggregation based on a K-NN algorithm with down-sampling operation, and also introduce the smoothness loss and Siamese loss for effective segmentation. The experiments on public datasets demonstrate that our presented segmentation method exceeds most of the existing fully supervised and weakly-supervised methods in terms of mIoU. Specifically, our network has high segmentation accuracy on the labels of objects with similar geometrical structures, such as ceiling, wall, floor, chair and table, reaching 91.2%, 98.8%, 83.3%, 75.3% and 80.2%, respectively. Extensive experiments also illustrate its robustness, effectiveness, and generalization of the proposed weakly supervised segmentation network.

Circadian rhythm (CR) influences various physiological functions, including physical and cognitive performance, which fluctuate throughout the day. The present study aimed to investigate the combined and separate effects of CR and physical fatigue on cognitive and physical performance. A sample of 18 amateur athletes was subjected to a series of tests at three different times of the day: morning, afternoon, and evening. Fatigue was induced following isokinetic concentric exercise combined with a 20-minute treadmill run, followed by assessments of selected physical and cognitive tasks. Repeated measures ANOVA did not reveal an interaction between CR and fatigue in cognitive performance (p &gt; 0.05). However, a significant main effect of fatigue was observed in visual reaction time (VisRT) across all three time points. Moreover, peak torque (PT) and peak torque fatigue index (PTFI) showed significant differences between the three times of the day, peaking in the evening. Although we found no interaction between CR and physical fatigue state on selected cognitive parameters at the three times of day, a separate effect of fatigue on cognitive performance was identified. Additionally, physical parameters exhibited peak values occurring in the evening hours. Future research should further explore underlying mechanisms that potentially influence cognitive performance at different times of the day.

One of the major concerns in structural health management (SHM) is the early detection of a growing crack. Using this, future damage due to crack propagation can be mitigated or eliminated by implementing proper repair and maintenance. Acoustic Emission (AE) is a non-destructive testing (NDT) method with potential applications for locating and monitoring fatigue cracks. The research presented in this paper focuses on SHM using AE. A novel AE signal analysis approach was proposed in order to detect crack initiation and assess small crack lengths. Experimental investigation indicated that initiation of a crack could be identified through the statistical analysis of the resulting features of the AE signals. A probabilistic AE-based model for small fatigue crack sizing was developed and the uncertainties of the model were estimated. In addition, a probabilistic model validation approach was implemented to confirm accurate estimation of the results. The outcome of this research can be used to evaluate the integrity of structures under fatigue loading. The proposed approach can also be applied as an approach to manage health and assess prognosis of structures.

Analysis of Fatigue Strain, Fatigue Modulus and Fatigue Damage for the modeling of concrete plays a vital role in the evolution material behaviour which is heterogeneous and anisotropic in nature. In this paper, the Level-S nonlinear fatigue strain curve, fatigue modulus curve, residual strain curve of concrete in compression, tension, flexure and torsional fatigue loading were proposed using strain life approach. The parameters such as physical meaning, the ranges, and the impact on the shape of the curve were discussed. Then, the evolution model of fatigue modulus was established based on the fatigue strain evolution model, fatigue modulus evaluation model, residual strain evaluation model, secondary strain evaluation model. The hypothesis of fatigue modulus is inversely related with the fatigue strain amplitude. The fatigue evolution of concrete damages the bond between material grains, changed the orientation of structure of molecules and affects the elastic properties resulting in the reduction of material stiffness and modulus by utilizing strain life analysis, regarding stiffness degradation and inelastic deformation by formation of microcracking, macro cracking, cracking which is heterogeneous and anisotropic in nature . This paper presents the Fatigue Strain Life Model and analyses of fatigue strain, fatigue modulus and damage parameters of concrete which is capable of predicting stiffness degradation, inelastic deformation, strength reduction under fatigue loading. Hence, the obtainable results were compared with experimental results for the validation of the proposed model.

Aiming at effectively generating safe and reliable motion paths for quadruped robots, a hierar-chical path planning approach driven by dynamic 3D point cloud is proposed in this article. The developed path planning model is essentially constituted of two layers: global path planning layer and local path planning layer. At the global path planning layer, a new method is proposed for calculating terrain potential field based on point cloud height segmentation. Variable step size is employed to improve the path smoothness. At the local path planning layer, a real-time prediction method for potential collision area and a strategy for temporary target point selection is developed. Quadruped robot experiments were carried out in an outdoor complex environment. The experi-mental results verified that, for global path planning, the smoothness of the path is improved and the complexity of the passing ground is reduced. The effective step size is increased by a maxi-mum of 13.4 times, and the number of iterations is decreased by up to 1/6, compared with the traditional fixed step size planning algorithm. For local path planning, the path length is short-ened by 20%, more efficient dynamic obstacle avoidance and more stable velocity planning are achieved by using the improved dynamic window approach (DWA).

Poultry farming in Slovakia has a tradition and an irreplaceable position to ensure rational nutrition for the population. In terms of a nutritional value, poultrymeat (Galliformes) contains a high amount of proteins, essential amino acids, essential unsaturated fatty acids, minerals, vitamins and a low fat content. Poultrymeat production has a relatively short reproductive cycle and thus allows regulating the demand and supply. The poultry market also influences the development of domestic consumption. According to the Statistical Office of the Slovak Republic, the consumption of meat has witnessed a persistent increase over the last 10 years. [1] According to the 2023 AVEC (The Voice of European Meat Sector) annual report, the consumption of poultrymeat in Slovakia was 20.0 kg per person per year. The average consumption in the EU-27 (2021) was 23.4 kg, with the countries with the highest consumption being Portugal (37.8 kg), Ireland (36.0 kg), Hungary (33.5 kg) and Spain (29.9 kg). On the other hand, the countries with the lowest consumption of poultrymeat, apart from Slovakia, also include Austria and Greece with a consumption of 21.5, resp. 21.0 kg [2]. The breeding of broiler chickens, as well as the production and placing on the market of poultrymeat must comply with the requirements laid down by legislation, while the compliance is regularly checked by the competent authorities.

Bitumen aging is the major factor which contributes to the deterioration of the road pavement. Oxidation and volatilization are generally considered as the most important phenomena affecting aging in asphalt paving mixtures. The present study was carried to investigate whether various antioxidants provided by natural resources such as phospholipids, ascorbic acid as well as lignin from rice husk, could be used to reduce age hardening in asphalt binders. A selected bituminous material was modified by adding 2 % w/w of the anti-aging natural additives and subjected to accelerated oxidative aging regimes according to the Rolling Thin Film Oven Test (RTFOT) method. The effects of aging were evaluated based on changes in sol-gel transition temperature of modified bitumens measured through Dynamic Shear Rheology (DSR). Moreover, changes of Electron Paramagnetic Resonance (EPR) spectra were monitored on the bituminous fractions asphaltene and maltene separated by solvent extraction upon oxidative aging. The phospholipids-treated binder exhibited the highest resistance to oxidation and the lowest age-hardening effect compared to the other tested anti-oxidants. The combination of EPR and DSR techniques represents a promising method for elucidating the changes in associated complex properties of bitumen fractions promoted by addition of free radical scavengers borrowed by green resources.

Based on the dynamic strength variation mechanism of concrete under complex loading conditions, two approaches were devised: numerical testing and CT scanning, guided by the principle of minimizing energy dissipation. A methodology for calculating concrete's failure area and measuring its strength was developed. The analysis delves into the mechanisms behind failure patterns and variations in concrete specimen strength, focusing on crack initiation, development, and the resultant failure surface formed by crack propagation, along with the stress distribution in concrete specimens subjected to diverse loading conditions. Through evaluating the strength and computed failure area of concrete specimens, it is evident that the loading method influences both the strength and failure area of concrete specimens. In general, a larger failure area correlates with a higher measured strength.

This paper reassesses the detrimental effect on fatigue performance due to thicker sections based on extensive fatigue strength test database, taken from research program worldwide over the past half of a century in offshore oil &amp; gas and renewable industry. The data entries in the database have been evaluated to ensure its data integrity. Statistical analyses on these S-N data are performed with or without the thickness correction at different exposure level to corrosive environment, in order to re-evaluate the suitability of current standards in regard to the thickness effect. The study has concentrated on T-joint, transverse butt welded joint and tubular joint as these are the most commonly used joint types in the offshore wind industry. The analysis indicates general agreement of fatigue strength with the thickness effects in current standard for in air conditions but great conservatism for corrosive environment.

The Interdisciplinary Canadian Collaborative ME Research Network (ICanCME), established in 2019, aims to foster research in Canada and contribute to finding the causes and possible treatments for myalgic encephalomyelitis /chronic fatigue syndrome (ME/CFS), thereby reducing the impact of ME/CFS on the health of Canadians. The main objectives of this paper are to suggest standards for ME/CFS research for the collection of data from participants (Recommended Data Elements) and to consider other factors, such as design, language, cultural issues, equity, and diversity. Consensus of the relevant contents of this research guideline was reached during the ICanCME working group meetings and were based on existing guidelines. Members of the working group contributed to guideline development based on their respective expertise. The proposed research guidelines could improve research quality and advance knowledge in the field of ME/CFS, and ultimately benefit ME/CFS patients.

In this paper, the main characteristics of the natural bitumen of the Munaily-Mola oil sands were studied with comparison crude oil of Karazhanbas oil field. During the experiment, the density, heating value, ash content and elemental composition of natural bitumen were determined, and these parameters were compared with the properties of Karazhanbas crude oil. As well as oil, resin and asphaltene fractions of both hydrocarbons were separated and each of them were analyzed at a Fourier transform IR-spectroscopy Spectrum-65 with 450-4000 cm−1 range. According to these indicators, it is concluded that natural bitumen is a heavy hydrocarbon raw material with highly resin-asphaltene compounds. Like Karazhanbas oil, natural bitumen can be used as a raw material for various petrochemical products. By finding ways of effective processing of natural bitumen, it can be used in useful areas of the national economy.

Several mathematicians and physicists are working all over the globe to get a unified theory. However, most of them are discarding Einstein’s view at the very first step of their theories. This article provides a brief description about this. Also, on the basis of Koga’s theory we point out two reasons which might have caused Einstein’s failure to get a unified theory.

Artificial intelligence (AI) is increasingly being used to improve the quality control of point-of-care diagnostics. This is caused by a number of factors, including the following: 1. AI can accelerate and improve testing accuracy. In comparison to humans, AI technology can review data more quickly and precisely, reducing errors and improving overall quality assurance. 2. When it comes to improving POC test findings on healthcare issues such as infectious diseases or medical crises such as heart attacks, AI can be used for sophisticated predictive analytics and modeling that aid in better decision-making. 3. Artificial intelligence facilitates process automation, increasing productivity and lowering labor costs in labor-intensive tasks such as testing and analyzing samples collected at point-of-care facilities. 4. The use of AI enables organizations implementing these solutions to gain insights from large volumes of raw diagnostic data generated faster and more accurately, allowing them to build solid frameworks around preventive care initiatives and significantly influence public health outcomes.5. Artificial intelligence (AI) has been demonstrated to be a useful tool for real-time monitoring systems that identify any problems with test results early so that they can be corrected before affected patients receive inaccurate diagnoses or treatment plans based on false information provided by diagnostic tests performed at points of care such as clinics or hospitals.Using these technologies would allow healthcare organizations to spend less on labor while still receiving exact diagnoses and rapid treatment delivery at a fraction of the cost that manual approaches required earlier.

Heart failure (HF) is a growing issue in developed countries and most patients present with a reduced ejection fraction. This condition significantly impairs quality of life and represents a threat not only for patients, but also for the entire healthcare system due to its high management cost. In the last decade, new medical treatments and devices have been developed to reduce HF hospitalizations and improve prognosis, while reducing the overall mortality rate. Medical therapy does not achieve the same results in all patients and, whenever it fails, technology comes in handy: novel devices for the management of HF have reduced symptoms. They have also improved the treatment of fluid retention and life threatening arrhythmias. The present review article gives to the readers a comprehensive overview of the most recent and important findings that need to be considered in HF with reduced ejection fraction patients. Both novel medical treatments and devices have been presented and discussed.

The research of object classification and part segmentation is a hot topic in computer vision. A considerable number of studies have been carried out about deep learning on 3D point clouds. However,it is challenging to achieve effective feature learning due to sparsity of point clouds. Recently, a variety of Transformers have been adopted to improve point cloud processing and display great potential. Nevertheless, large numbers of Transformer layers tend to incur huge computational and memory costs. PointNet++ is one of the most influential neural architectures for point cloud understanding. Although the accuracy of PointNet++ has been largely surpassed by recent networks, this does not mean that PointNet++ has no potential.Thus, this paper offer two major contributions that significantly improve PointNet++ performance. Firstly, we introduce a novel contextual feature extraction (CFE) block that significantly enhances the feature extraction capabilities of PointNet++ networks. Secondly, to further enhance feature fusion, we seamlessly integrate a mutual learning (ML) block into the network architecture. By embedding these two innovative blocks within each layer of the network, we not only enrich the network's functionality but also impart it with greater robustness and adaptability. The specific experiments were conducted on the S3DIS (6-fold cross-validation) and Modelnet40 datasets with 86.5% and 92.7% accuracy, respectively, which proved that our model is comparable or even better than most existing methods for classification and segmentation tasks.

An untrained couch potato involuntarily forced to undergo a long strenuous exercise towards exhaustion will feel it at the end as a discomforting fatigue. A well-trained athlete will feel the same but after a longer time. Patients of various neurological diseases will do so much earlier. All may also finally experience muscle pain and soreness the next day.Muscle fatigue is an exercise-induced reduction in maximal voluntary muscle force. Muscle fatigability varies with muscle use, age and sex. It is commonly divided into two broad categories: peripheral and central fatigue. The first refers to the many processes in the fatiguing muscle(s), the second to subsequent processes in the central nervous system (CNS). Peripheral muscle fatigue can be caused by numerous different mechanisms, ranging from the accumulation of metabolites within muscle fibers to their damage. Central fatigue involves the inadequacy of the CNS to generate and maintain sufficiently strong motor command. There must of course be a mediator relating the two fatigue types, and this is the collection of small-diameter group III (Aδ) and IV (C) nerve fibers emanating from the muscle and distributing their activation effects throughout the CNS.Muscle fatigue develops during eventually exhausting exercise that goes along with activations of the cardio-vascular and respiratory system to supply oxygen and energy resources. While these functions are supported by a number of sensory afferents, fatigue-activated group III/IV muscle afferents have been proposed to contribute their share to cardio-vascular and ventilatory reflex responses that are mediated in the brainstem. Neural feedback from working skeletal muscle is a vital component in providing a high capacity for endurance exercise because muscle perfusion and O₂ delivery determine the fatigability of skeletal muscle (Amann 2012).The development of chronic muscle fatigue is related to muscle wasting mediated by aging, myopathies, muscle dystrophies, immobilization, insulin resistance, diseases associated with systemic inflammation (arthritis, sepsis, infections), trauma, cardio-vascular (heart failure) and respiratory disorders (chronic obstructive pulmonary disease (COPD)), chronic kidney failure, multiple sclerosis (MS), and, more recently, coronavirus disease 2019 (COVID-19).

In this paper, a continuous power management for a decentralized DC microgrid (DCMG) is proposed to achieve voltage regulation and power balance even under system uncertainty and voltage sensor failure. The DCMG system achieves a continuous power management through only the primary controller to reduce the computational burden of each power agent. To enhance the reliability and resilience of the DCMG system under voltage sensor failure, a DC bus voltage (DCV) sensor fault detection algorithm is proposed. In this algorithm, the DCV sensor failure is detected by comparing the measured DCV with the estimated DCV. When the power agent identifies the DCV sensor failure, it changes the operation properly according to the proposed control mode decision algorithm to maintain the stability of the DCMG system. When uncertain conditions such as the power variation of the distributed generations, sudden grid disconnection, DCV sensor failure, electricity price change, and critical battery status occur, the DCMG system is changed to transitional operation modes. These transitional operation modes are employed to transmit the power agent information to other agents without digital communication links (DCLs) and to accomplish power sharing even under such uncertain conditions. In the transitional operation modes of the DCMG system, the DCV levels are temporarily shifted to an appropriate level, enabling each power agent to detect the uncertainty conditions, and subsequently to determine its operation modes based on the DCV levels. Simulation and experimental results under different test conditions confirm the reliability and effectiveness of the proposed control scheme.

This study aimed to investigate the fatigue performance and interfacial strengthening mechanisms of Al6061-to-Cu dissimilar lap joints via electromagnetic pulse welding (EMPW). The load-bearing capacity of the joints at discharge voltages of 14 kV and 16 kV was superior to that of 12 kV. Furthermore, the fatigue life of the 14 kV joints was one order of magnitude higher compared to the 12 kV joints. SEM observation of the fatigue fracture surface revealed the presence of typical "tire-mark" fatigue striations only in the 14 kV joint, indicating higher ductility and the ability to withstand extended plastic deformation. Notably, ultra-fine nanocrystalline Al2Cu phase, amorphous phase, and numerous dislocations hindered EBSD acquisition in the transition zone. Nevertheless, dense low-angle grain boundaries (LAGBs) and refined grains were examined at the bonding interface. This suggests that the high-velocity collision caused severe plastic deformation and led to the formation of substructures. The interfacial strength was attributed not only to the "wave-like" or "inverted hook-like" diffusion layer but also to the presence of refined grains along the interface and nanocrystalline Al2Cu in the transition zone. Furthermore, the hybrid nanocrystalline-amorphous microstructure strengthened the joint by regulating the balance between strength and ductility.

The new slide roller burnishing (SRB) method has been developed to produce mirror-like surfaces. Unlike conventional roller burnishing (RB), SRB is implemented through a unique device that allows the axes of the deforming roller and the rotary workpiece to cross resulting in a relative sliding velocity that can be controlled (in magnitude and direction) by varying the crossing angle. In the present work, the effect of SRB on the fatigue behavior of AISI 316 steel fatigue specimens was investigated by comparing with a conventional RB using the basic correlation in surface engineering: finishing–surface integrity (SI)–operating behavior. To obtain a more representative picture of the comparison, we implemented each method (RB and SRB) with two combinations of governing factors: (A) a radius of the roller toroidal surface of 3 mm, a burnishing force of 250 N and feed rate of 0.05 mm/rev (RB-A and SRB-A) and (B) a radius of the roller toroidal surface of 4 mm, a burnishing force of 550 N and feed rate of 0.11 mm/rev (RB-B and SRB- B). Both SRB-A (crossing angle of –45°) and SRB-B (crossing angle of –30°) achieved mirror-finish surfaces. SRB-B lead to the greatest fatigue strength and, thus, the longest fatigue life among all tested processes. SRB-B created the deepest zone (&gt;0.5 mm) with residual compressive macro-stresses and a clearly defined modified surface layer, whose thickness of more than 20 m is about twice that created by the other three processes.

Road intersections are made of asphalt pavement, a popular road surface material used worldwide. The pavement may suffer deformities and deterioration, resulting in higher maintenance expenses and an elevated likelihood of road accidents, due to factors such as heavy vehicles and environmental variables like temperature and rainfall. To tackle these obstacles, researchers have devised several machine-learning algorithms and optimization techniques. These tools aim to forecast and scrutinize pavement deformation, with the goal of refining pavement design and maintenance approaches, as well as obtaining a more comprehensive comprehension of the factors that impact pavement effectiveness. This paper shows that heavy vehicles contribute significantly more to road erosion, and the retention and braking of vehicles greatly impact roadways. We also emphasize the statistical errors computed on the actual data range and demonstrate the results of the multilayer perceptron (MLP) model. The MLP model used the lath erosion standard to simulate future impact. Even though the model given is based on a small sample of data from one intersection, its estimates for road erosion in a year were found to be accurate when contrasted to real data. Controlling traffic flow can significantly improve road conditions, reducing erosion decay by reducing the time spent at intersections and other parameters. We conclude that machine learning can help control traffic flow, which can significantly improve road conditions, reducing vehicle time stretches at intersections.

Nasal polyposis is defined by a Th2-driven chronic inflammation of the nose and sinus with polyps visible in the nasal fossae. It is a prevalent disease with a significant impact on the HRQL. Allergy, allergic rhinitis, asthma, and aspirin intolerance are frequently associated. The management is individual. The first line of treatment is a long-term treatment with intranasal corticosteroids. Oral corticosteroids should be used with caution. When the medical treatment fails the patient is eligible for sinus surgery. In case of symptomatic recurrence after both medical treatment and ethmoidectomy, biologics are nowadays a very promising treatment effective on all the respiratory tract. Dupilumab seems in the literature the molecule of choice. However, besides the international guidelines published by EPOS and Euforea, the molecule prescribed depends also on the availability of it in each country and the criteria edited by the health authorities to get reimbursement. Long treatment is mandatory. Traditional medical treatment is necessary as a complement to biologics.

This paper seeks to model the crack propagation in of AAs (aluminum-alloys) 2524-T3 and 7050-T7452 subjected to fatigue loading at low temperature. Fatigue crack growth tests were performed on AAs 2524-T3 and 7050-T7452 subjected to constant-amplitude and actual random-spectra loading histories at room temperature of about 25 °C and at cryogenic temperature of -70 °C, respectively, to determine their crack growth properties and residual lives. The interaction mechanisms between cryogenic temperature and the fatigue load were deduced on the basis of the results of fractographic analysis. Temperature-dependent residual lives under actual random-spectrum load history were modeled based on a modified accumulation damage rule by accounting for the load interaction. Good correlation was achieved between the predictions and actual experiments, demonstrating the practical and effective use of the proposed method.

In this paper, we investigate a class of hierarchical variational inequalities (HVIPs, i.e., strongly monotone variational inequality problems defined on the solution set of multiple-set split common fixed point problems) with quasi-pseudocontractive mappings in real Hilbert spaces, which special cases can be found in many important engineering practical applications such as image recognizing, signal processing and machine learning. In order to solve HVIPs of potential application value, inspired by the primal-dual algorithm, we propose a novel accelerated cyclic iterative algorithm that combines the inertial method with a correction term and a self-adaptive step-size technique. Our approach eliminates the need for prior knowledge of the bounded linear operator norm. Under appropriate assumptions, we establish strong convergence of the algorithm. Finally, we apply our novel iterative approximation to solve multiple-set split feasibility problems and verify the effectiveness of the proposed iterative algorithm through numerical results.

Bayesian analysis for masked data under competing risk frameworks is studied for the purpose of assessing the impact of covariates on the hazard functions when the failure time is exactly observed for some subjects but only known to lie in an interval of time for the remaining subjects. Such data, known as partly interval-censored data, usually result from periodic inspection. Dirichlet and Gamma processes are assumed as priors for masking probabilities and baseline hazards. The Markov Chain Monte Carlo (MCMC) technique is employed for the implementation of the Bayesian approach. The effectiveness of the proposed model is tested through numerical studies, including simulated and real data sets.

The main purpose of this work was to tests of form and size of fatigue wear of the top layer of oil gear pump wheel (3PW-BPF-24). The object of tests was operated during a determined number of hours at strictly controlled operational and environmental parameters. A microscope of focal differentiation by Alicona InfiniteFocus G4 (with Focus-Variation optical measuring technology) was used for an identification, measurement and description of noticed superficial defects, which resulted from the fatigue process of the top layer and an earlier thermochemical treatment. The work was finished with an analysis of obtained results (based on the analysis of 3D scans) and conclusions concerning about optimization of the thermal treatment. Taking into consideration the presented results (suggestions) in the technology of improving strength properties of gear wheels (of this type oil pumps) may render it possible to obtain an appropriate fatigue endurance of the top layer, i.e. a minimization of observed superficial defects.

Background and objective: Iliopsoas abscess (IPA) is a rare condition with varied symptomology and etiology. Less than one-third of patients with IPA present on the emergency department (ED) admission with the traditional triad of fever, back pain, and restricted hip motion (or limp), leading to delays in diagnosis and management. This case report aims to bring awareness among healthcare professionals regarding the atypical presentation and introduce a potential differential diagnosis when evaluating patients with fever and back pain. The intention is to provide insights into the signs and symptoms that may indicate the presence of an iliopsoas abscess and prompt additional investigations. Case report: Here, we describe a case of primary iliopsoas abscess associated with drug-induced acute liver failure in our ED. The patient complained of pain in the left lumbar region and fatigue that started two weeks before this presentation, claiming that, during the previous night, the pain suddenly worsened. She had a fever, pain at palpation in the right hypochondriac and left lumbar regions, accompanied by fever and vomiting, jaundiced skin, and sclera at the examination in ED. On abdominal ultrasonography, the diagnosis of acute cholangitis was suspected. The laboratory test shows leukocytosis with neutrophilia, thrombocytosis, hepatocytolysis syndrome, and hyperbilirubinemia with the predominance of indirect bilirubin. We performed then abdominal and pelvic computed tomography, which confirmed the diagnosis of cholelithiasis observed with the diameter of the bile duct within normal limits but also showed an abscess-like collection fused to the interfibrillar level of the left iliopsoas muscle; a diagnosis we most likely would have been missed. After that, the patient was hospitalized in the General Surgery Department, and surgery drainage of the abscess was performed. The patient's evolution was excellent; she was discharged after 11 days. Conclusions: The case presented here exemplifies how iliopsoas abscess, a rare cause of back pain, can quickly go unrecognized, especially in the emergency department. Our experiences will raise awareness among doctors in emergency departments about this uncommon but essential diagnosis. With advancements in diagnostic tools and techniques, we aspire that more cases of iliopsoas abscess will be accurately diagnosed.

For multi-sensor integrated systems, such as a mobile mapping system (MMS), data fusion at sensor-level, i.e., the 2D-3D registration between optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for panoramic images and LiDAR point cloud collected by a MMS. We first introduce the system configuration and specification, including the coordinate systems of the MMS, the 3D LiDAR scanners, and the two panoramic camera models. We then establish the line-based transformation model for panoramic camera. Finally, the proposed registration method is evaluated for two types of camera models by visual inspection and quantitative comparison. The results demonstrate that the line-based registration method can significantly improve the alignment of the panoramic image and LiDAR datasets under either the ideal spherical or the rigorous panoramic camera model, though the latter is more reliable.

This review explores the crucial role of glycosphingolipids (GSLs) in the context of cardiovascular diseases (CVD), focusing on their biosynthesis, metabolic pathways, and implications for clinical outcomes. GSLs are pivotal in regulating a myriad of cellular functions that are essential for heart health and disease progression. Highlighting findings from both human cohorts and animal models, this review emphasizes the potential of GSLs as biomarkers and therapeutic targets. We advocate for more detailed mechanistic studies to deepen our understanding of GSL functions in cardiovascular health, which could lead to innovative strategies for diagnosis, treatment, and personalized medicine in cardiovascular care.

The present study analyses the influence of scratches and fatigue on the mechanical characteristics of aluminium alloys commonly used in the aviation industry: 2024-T4, 6061-T4, 6061-T4 uncoated, 6061-T6 uncoated, 7075-T0, and 7076-T6. 120 specimens were used for the study. Out of these, 60 samples were scratched, and the other 60 samples were also scratched under the same circumstances and then subjected to low-cycle fatigue (LCF) before undergoing the tensile test. Based on the statistical examination of the measured data, mathematical prediction models have been established. Compared to their unscratched counterparts, the results indicate a significant decrease in the mechanical properties of both scratched and scratched-fatigued sample sets. The LCF pre-treatment contributes to the negative impacts of scratches, resulting in a reduced value for the ultimate tensile strength and elongation at break. The results conclude that surface integrity plays an essential role in preserving aircraft components' structural strength.

The aim of the article is to identify and illustrate the most used psychological techniques in the field of cystic fibrosis (CF) and to help clinicians choosing the appropriate strategy among the various possibilities. The disease and its medical treatments can be difficult to tolerate and can cause anxiety about health status or feelings of hopelessness and stress. The prevalence of depression and anxiety is 2.3 times higher in adults with CF than in community samples. A strong correlation has been identified between elevated psychological distress and unfavorable health outcomes, including, among others, impaired lung function, reduced BMI, an increased incidence of pulmonary exacerbations, and an elevated risk of transplantation. The use of psychological interventions is useful in addressing these common distress in CF patients. Aware of the necessity to identify efficacious interventions for all levels of depression and anxiety in CF patients, this study presents an overview of the research on psychological interventions for patients with CF, in order to complement the treatments suggested by the international guidelines on mental health in CF cases. In fact, the aim of this study is to conduct a review and quantitative synthesis of the psychological intervention techniques that are currently available for individuals with CF.

This study investigates the fatigue behavior of cold-finished mild steel subjected to electrochemical hydrogen charging under controlled conditions. Samples were hydrogenated at constant time in a fixed electrolyte pH after which they underwent fatigue testing under constant loading condition with fixed frequency. The primary objective was to assess the impact of varying hydrogen permeation levels on the number of cycles to failure. The experimental results revealed a complex relationship between hydrogen concentration and fatigue life. Initially, as hydrogen permeation increased, the number of cycles to failure substantially decreased, demonstrating a detrimental effect of diffused hydrogen on fatigue resistance of samples. This decline in fatigue life was attributed to hydrogen embrittlement (HE) and hydrogen-enhanced decohesion (HEDE) phenomena, which collectively facilitate crack initiation and propagation. However, at high hydrogen concentrations, an unexpected increase in number of cycles to failure was observed suggesting the existence of a threshold hydrogen concentration beyond which the fatigue mechanisms may be altered, potentially due to saturation of hydrogen-related defects and mechanisms such as Hydrogen Enhance Localized Plasticity (HELP). The insights gained from this research have significant implications for the material's application in hydrogen-rich environments, such as those encountered in the energy and transportation industries.

According to the honeycomb structure, the preliminary design of bionic wheel hub for finite element analysis, in the working condition of a wheel by the force is through the spokes pointing to the center, the working condition of two wheel by the force is through the two spokes pointing to the center, and the ordinary wheel stress and displacement value results compared, observed the maximum stress value appears in the connection between the center of the wheel and the spokes, and predict the fatigue life of the preliminary design of bionic wheel. Using finite element analysis and response surface optimization analysis method for numerical simulation, through two optimization results show that, in the use of response surface analysis model optimization, the optimized bionic wheel maximum stress is 109.34MPa, compared with the ordinary wheel maximum stress 119.77MPa, the maximum stress reduced by 8.7%. The mass of the ordinary wheel is 34.02Kg, using the response surface optimization method, the optimized wheel mass is 29.89Kg, the mass reduced by 12.13%. The optimized wheel fatigue analysis, in the stress of 109.34MPa, load loading times at least 4.217e+005, in the position at the junction with the half shaft. In line with the national standard GB/T 5334-2021[16] for commercial vehicle wheel fatigue life requirements.

For successful reuse of old asphalt as reclaimed asphalt pavement (RAP) added to new bituminous mixtures it is necessary to improve some of its properties. This can be attained, for example, by adding an appropriate rejuvenating agent. The aim of this study was to evaluate the properties of a lab aged 35/50 pen grade bitumen, rejuvenated by addition of two varieties of rapeseed imidazo-line. Both short-term and long-term ageing were simulated using the Rolling Thin Film Oven Test (RTFOT) and Pressure Ageing Vessel (PAV), i.e. standard lab ageing methods. The first step in-cluded determination of the basic properties of the analysed pen grade bitumen. Fatigue cracking resistance of the bitumen was checked as the next step. The dynamic shear rheometer (DSR) test was carried out for this purpose, at the intermediate operating temperature of road pavements. The obtained data were then used to calculate the fatigue cracking critical temperature (FCCT). A ductility test was also carried out in a ductilometer, in which the applied tensile force was meas-ured. The obtained results demonstrated a beneficial effect of rapeseed imidazoline on the prop-erties of the tested pen grade bitumen after ageing, when added at a rate of 6% and more.

In this paper, the deformation behavior of S32750 duplex stainless steel during low cycle fatigue was studied by controlling number of cycles. The microstructure of the specimens under different cycles was characterized by optical microscope (OM), scanning electron microscope (SEM), electron backscatter diffraction (EBSD) and transmission electron microscope (TEM). Microhardness of two phases was measured by a digital microhardness instrument. The results showed that the microhardness of ferrite increases significantly after the first 4000 cycles, while the austenite shows a higher strain hardening rate after fatigue fracture, and the microhardness of ferrite and austenite increases by 23 HV and 87 HV, respectively. Two-phase kernel average misorientation (KAM) diagram showed that the continuous accumulation of plastic deformation easily leads to the initiation of cracks inside the austenite and at the phase boundaries. The evolution of dislocation morphology in two phases was obviously different. With the increase of cycle number, the dislocation in ferrite gradually transforms from dislocation bundles and dislocation array to sub-grain structure, while the dislocation in austenite gradually develops from dipole array to ordered Taylor lattice network structure.

Background: beta blockers of three generations are first-line drugs in the treatment of chronic heart failure (CHF). However, to date there is no clear understanding of the effect of beta blockers on myocardial energy metabolism disorders in CHF. The aim of the study: to conduct a study of beta-blockers of different generations on myocardial energy metabolism in the experimental CHF. Methods: CHF was modeled in white outbred rats by administering doxorubicin. The study drugs were administered intragastrically – new drug Hypertril (1-(β-phenylethyl)-4-amino-1,2,4-triazolium bromide)-3.5 mg/kg, metoprolol - 15 mg/kg, Nebivolol -10 mg/kg, Carvedilol 50 mg/kg, Bisoprolol, 10 mg/kg. In the myocardium, the main indices of energy metabolism were determined - ATP, ADP, AMP, malate, lactate, pyruvate, succinate dehydrogenase (SDH) activity, NAD-dependent malate dehydrogenase (NAD-MDH) activity. Results: traditional second-generation beta-blockers (Metoprolol and Bisoprolol) did not affect the studied indices of energy metabolism, and third-generation beta-blockers with additional properties - Carvedilol and, especially, Nebivalol and Hypertril improved myocardial energy metabolism. Conclusions: obtained results will help to expand our understanding of the effect of beta-blockers of various generations used to treat cardiovascular diseases on energy metabolism, and are also an experimental justification for the practical choice of these drugs in the complex therapy of CHF.

It has been known for nearly over 150 years that fatigue life data exhibits a considerable amount of variability. Furthermore, statistically modeling fatigue life adequately is challenging. Different empirical approaches have been used, each of which has merit; however, none is appropriate universally. Even when a sufficiently robust database exists, the scatter in the fatigue lives may be extremely large and difficult to characterize. The complications in empirical modeling are exacerbated for long life estimation when experimental observations are rare. The purpose of this work is to review traditional and more modern empirically based methodologies for estimating the cumulative distribution functions for fatigue life, given an applied load. To assess the applicability of the methods confidence bounds will be estimated. The analyses will be performed on an historic set of data for annealed aluminum wire tested in reverse torsion fatigue. These data are available in publications. It is recommended that a time dependent distribution function that is an based on principles of reliability that can be generalized for a variety of modeling applications should be considered for fatigue life estimation.

The point cloud is a form of three-dimensional data that comprises various detailed features at multiple scales. Due to this characteristic and its irregularity, point cloud analysis based on deep learning is challenging. While previous works utilize the sampling-grouping operation of PointNet++ for feature description and then explore geometry by means of sophisticated feature extractors or deep networks, such operations fail to describe multi-scale features effectively. Additionally, these techniques have led to performance saturation. And it is difficult for standard MLPs to directly "mine" point cloud. To address above problems, we propose the Detail Activation (DA) module, which encodes data based on Fourier transform after sampling and grouping. We activate the channels at different frequency levels from low to high in the DA module to gradually recover finer point cloud details. As training progresses, the proposed Point-MDA can uncover local and global geometries of point cloud progressively. Our experiments show that Point-MDA achieves superior classification accuracy, outperforming PointNet++ by 3.3% and 7.9% in terms of overall accuracy on the ModelNet40 and ScanObjectNN dataset, respectively. Furthermore, it accomplishes this without employing complicated operations, while exploring the full potential of PointNet++.

A software defined radio (SDR) is a communication system that makes use of components that can be configured through software, in contrast to traditional systems where these components are variable through hardware, these radio devices are much more versatile, this article describes the factors that must be considered when implementing a communication system based on Software Defined Radios (SDR), in order to reduce the attenuation factors and thus obtain the maximum distance for a transmission of data effectively in the UHF band. The calculations made for the first Fresnel zone and for the design of the Ground Plane type antennas used in the transmission/reception stages of the x40 bladeRF platforms are also presented. The tests were carried out at the facilities of the Huarangal Nuclear Center of the Peruvian Institute of Nuclear Energy, obtaining favorable results that allow ratifying the versatility and performance of the SDRs.

Although heart failure with preserved ejection fraction (HFpEF) has become the predominant heart failure subtype, it remains clinically under-recognized. This, has been attributed to the complex pathophysiological mechanisms that accompany individuals with several co-morbidities and symptoms and signs of HFpEF. Natriuretic peptides have been recognized to have important role in the diagnosis and monitoring of patients with heart failure with reduced ejection fraction (HFrEF), but their role in HFpEF remains controversial. Its seems that the role of NtproBNP in the diagnosis of HFpEF, is mainly driven by the pathophysiological characteristics of the patients.

Accurate classification of objects in 3D point clouds is a significant problem in several applications, such as autonomous navigation and augmented/virtual reality scenarios, which has become a research hot spot. In this paper, we presented a deep learning strategy for 3D object classification in augmented reality. The proposed approach is a combination of the GRU and LSTM. LSTM networks learn longer dependencies well, but due to the number of gates, it takes longer to train; on the other hand, GRU networks have a weaker performance than LSTM, but their training speed is much higher than GRU, which is The speed is due to its fewer gates. The proposed approach used the combination of speed and accuracy of these two networks. The proposed approach achieved an accuracy of 0.99 in the 4,499,0641 points dataset, which includes eight classes (unlabeled, man-made terrain, natural terrain, high vegetation, low vegetation, buildings, hardscape, scanning artifacts, cars). Meanwhile, the traditional machine learning approaches could achieve a maximum accuracy of 0.9489 in the best case.

As the penetration of renewable energies increases, their acceptance of the power grid system is becoming an important issue. In the case of South Korea, a 22.9kV transformer is frequently utilized to reduce the power loss of the generated renewable energy transmission, so the power quality at the point of common connection (PCC) is inevitably influenced by the nonlinearity of the transformer and the uncertainty of the inductance and resistance of the transmission line. In this paper, we present a point of common connection voltage-modulated direct power control (PCCVM-DPC) system that enhances power quality at the PCC. First, we present the mathematical dynamics of active and reactive power at the PCC side, which contains the step-up transformer’s nonlinearity, the grid voltage harmonics, and the parameter uncertainties. By analyzing the disturbance terms of the PCCVM-DPC system, we present the disturbance observer (DOB) for the PCCVM-DPC system. To assess the efficacy of our approach, we perform comparative studies of the PCCVM-DPC without DOB and PCCVM-DPC with DOB by constructing the simulation environment based on the commercial step-up transformer and ESS inverter datasheet. We have validated that the active and reactive power control performance of the PCCVM-DPC with DOB outperforms the PCCVM-DPC without DOB from the observation that the current total harmonic distortion reduced by more than 40% compared to the PCCVM-DPC without the DOB.

By enhancing the bitumen properties with the additives produced from wastes not only can be improved the performance of flexible pavements but also can be contributed to the environment. This research aims to produce a novel pyrolytic char from different wastes and to investigate the usability of this char as an additive in bitumen. In this study, firstly, the pyrolytic char was produced from co-pyrolysis of three different wastes including waste paper cups, polypropylene (PP) and polyethylene terephthalate (PET) wastes. Properties of the char were determined by using CHN (carbon, hydrogen, nitrogen) and Fourier transform infrared spectroscopy (FTIR) analyses. The high temperature rheological properties of binders were evaluated by using DSR (dynamic shear rheometer), RV (rotational viscometer), softening point and penetration tests. Additionally, specific gravity, storage stability, high temperature performance grades (PG) and temperature susceptibilities of binders were determined. Test results showed that this pyrolytic char enhanced the high temperature properties of neat bitumen by increasing softening point, viscosity, rutting resistance and high temperature PG. And, it can be said that the bituminous binder modified with this pyrolytic char had a good storage stability when it was used at 8% ratio in neat bitumen.

In this paper, ground tire rubber (GTR) was mechano-chemically modified with road bitumen 160/220 and subsequently treated using a microwave radiation. The combined impact of bitumen 160/220 content and microwave treatment on short-term devulcanization of GTR were studied by thermal camera, wavelength dispersive X-ray fluorescence spectrometry (WD-XRF), static headspace and gas chromatography-mass spectrometry (SHS-GC-MS), thermogravimetric analysis combined with Fourier transform infrared spectroscopy (TGA-FTIR), oscillating disc rheometer and static mechanical properties measurements. The obtained results showed that bitumen plasticizer prevent oxidation of GTR during microwave treatment and simultaneously improves processing and thermal stability of obtained reclaimed rubber.

The concept of Design Fatigue Factors (DFFs) was introduced for providing desired level of safety in structural fatigue design, often associated with damage calculated from S-N curves. Calculation of fatigue damage from S-N curves can be affected by multiple factors, e.g. types of weld class, corrosion condition, loading conditions, stress concentration on different geometries etc. Each of them can be subject to different level of uncertainties. This study intends to recalibrate the DFFs from a detailed reliability analysis by investigating the probabilistic models derived from the database of S-N curves that has been most frequently used in offshore wind industry. The results of such study indicate that the DFFs can be reduced substantially for the corrosive environmental fatigue models from current standards to the same level of target reliability.

Interactions between mobile robots and human operators in common areas require a high safety especially in terms of trajectory planning, obstacle avoidance and mutual cooperation. In this connection the crossings of planned trajectories, their uncertainty based on model fluctuations, system noise and sensor noise,play an outstanding role. This paper discusses the calculation of expected areas of interactions du ring human-robot navigation with respect to fuzzy and noisy information. Expected crossing points of possible trajectories are nonlinearily associated with positions and orientations of robot and human. The nonlinear transformation of a noisy system input, such as directions of motion of human and robot, to a system output, the expected area of intersection of their trajectories, is done by two methods: statistical linearization and the sigma-point-transformation. For both approaches fuzzy approximations are presented and the inverse problem is discussed where the input distribution parameters are computed from given output distribution parameters.

With the global increase of photovoltaic (PV) modules deployment in recent years, the need to explore and realize their reported failure mechanisms has become crucial. Despite PV modules being considered reliable devices, failures and extreme degradations often occur. Some degradations and failures can be minor and cause no critical harm if within the expected range. Others, may start mildly and then deteriorate faster to become catastrophic, especially in harsh environments. This paper conducts a state-of-the-art literature review to scan PV failures, types, and their root cause based on PV’s constructed components (from protective glass to junction-box). It outlines the hazardous consequences beyond PV module failures, describing what harm they can bring to the PV system. As we delve into the literature, it becomes clear that every component is vulnerable to certain types of failures; some can deteriorate within themselves, and others infect further PV components resulting in emerging more severe failures. In the end, the review briefly summarises PV failure detection techniques, emphasising electrical characterization techniques, and disclosing the need to engage more electrical parameters. Most importantly, this review can prepare the stage for the PV research community to identify the most prevalent degradation processes. This, in turn, encourages researchers to investigate them throughout modelling and experimental studies to forecast them at the early onset in order to protect the PV systems from hazardous malfunctions.

Leaf springs are critical components for the railway vehicle safety in which they are installed. Although these components are produced in high-strength alloyed steel and designed to operate under cyclic loading conditions in the high-cyclic fatigue region, their failure is still possible to occur and hence lead to economic and human catastrophes. The aim of this document is precisely to characterise the mechanical crack growth behaviour of the 51CrV4 spring steel representative of leaf springs under cyclic conditions, that is, crack propagation in mode I. The common fatigue crack growth prediction models (Paris and Walker) considering the effect of stress ratio and parameters such as propagation threshold, critical stress intensity factor and crack closure ratio are also determined using statistical methods, which resulted in good approximations with respect to the experimental results. Lastly, the fracture surfaces under the different test conditions were analysed using SEM, with no significant differences to declare. As a result of this research work, it is expected that the developed properties and fatigue crack growth prediction models can assist design and maintenance engineers in understanding fatigue behaviour in the initiation and propagation phase of cracks in leaf springs for railway freight wagons.

This paper employs the Finite Element Method (FEM) to simulate and analyze the effects of corrosion defect parameters on the stress and failure pressure of pipelines. It investigates how the boundary conditions of the pipeline model influence stress and examines the sensitivity of failure pressure to corrosion defect parameters. A nonlinear regression equation has been developed from a dataset obtained through simulation experiments to predict the failure pressure of corroded pipelines. To validate the effects of corrosion defect parameters on failure pressure, a hydrostatic test platform for an API 5L X65 pipeline with corrosion defects was established to measure stress levels and failure pressures across varying corrosion defects. The study reveals that failure pressure is negatively correlated with corrosion length and depth, while positively correlated with corrosion width. Among these parameters, corrosion depth exerts a more significant influence on the pipeline's failure pressure than corrosion length and width. Within the range of corrosion defect parameters examined, the maximum deviation of the prediction equation's results from the simulation results is 8.71%, with an average deviation of 5.81%. The standard deviation of the fitted residuals is 0.01837. Additionally, the maximum deviation between the predicted results and experimental measurements is 8.39%, with an average deviation of 7.77%. The strong agreement between the predicted results from the equation and the actual measured data underscores the effectiveness of the nonlinear regression equation.

In 2011, it was reviewed that there is a strong co-occurrence between major depression and chronic fatigue syndrome (CFS), with fatigue and physio-somatic symptoms being key symptoms of depression, and depressive symptoms appearing during the course of CFS. Moreover, the comorbidity between both conditions may in part be explained by activated immune-inflammatory pathways, including increased translocation of Gram-negative bacteria and increased levels of pro-inflammatory cytokines, such as interleukin (IL)-1. Nevertheless, the possible involvement of activated microglia in this comorbidity has remained unclear. This paper aims to review microglial disturbances in major depression, CFS and their comorbidity. A comprehensive literature search was conducted using the PubMed / MEDLINE database to identify studies that are relevant to this current review. Depressed patients present neuroinflammatory alterations, probably related to microglial activation, while animal models show that a microglial response to immune challenges including lipopolysaccharides is accompanied by depressive-like behaviors. Recent evidence from preclinical studies indicate that activated microglia have a key role in the onset of fatigue. In chronic inflammatory conditions, such as infections and senescence, microglia orchestrate an inflammatory microenvironment thereby causing fatigue. In conclusion, based on our review we may posit that shared immune-inflammatory pathways and activated microglia underpin comorbid depression and CFS and that activated microglia are the main orchestrators of this comorbidity. As such, microglial activation and neuro-inflammation may be promising targets to treat the overlapping manifestations of both depression and CFS.

Post-mortem characterisation is a pivotal tool to trace back to the origin of structural failures in modern engineering analyses. This work presents a comparison of both the crack propagation profiles and the rupture roughness profiles based on areal parameters for total fracture area. Notched and smooth samples made of weather-resistant structural steel (10HNAP), popular S355J2 structural steel and aluminium alloy AA2017A under bending, torsion, and combined bending-torsion are investigated. After the fatigue tests, fatigue fractures are measured with an optical profilometer, and the relevant surface parameters are critically compared. The results show a great impact of the loading scenario on both the local profiles and the total fracture areas. In this work, the results of both approaches (local and total fracture zones) for specimens with different geometries are investigated. For all specimens, measured texture parameters decreased in the following order: total area, rupture area, and propagation area.

The wave energy converter (WEC) technology constantly develops new designs and models. To encourage its development within the energy sector, research is required to improve current designs and create durable and effective devices. However, it is also crucial to investigate the suitability of a WEC to a site-specific sea condition as this can impact its optimal power absorption and constructability. This study evaluates and compares the efficiency of a heaving buoy with varied geometries in one of the most energetic places along the Mexican coast. A statistical analysis of the wave climate on the coast of Ensenada during the last 42 years is performed to define the conditions to which the device is subjected. The location of the WEC in shallow waters is chosen using a computational model which solves the modified mild slope equation in its elliptic shape. The heaving buoy floater is studied using three distinct geometries: a semi-sphere, a cylinder, and a proposed rounded semi-rectangle. The hydrodynamic response of the three geometries is then analysed in the frequency and time domain using ANSYS AQWA. The hydrodynamic study involves the assessment of the floating body dynamics, exerted forces, the power absorbed as well as the suitability of the proposed power take-off (PTO) system. Findings reveal that the proposed geometry absorbs the most energy, with an annual power of 135.11 MW, and that the transmission PTO design is appropriate for this type of technology.

(1) Background: LUS has emerged as a simple, rapid and non-invasive method for the dynamic assessment of pulmonary congestion, a major prognostic factor and a therapeutic target in AHF. (2) Methods: In the single-center prospective observational study, 42 patients hospitalized for AHF in the post-emergency polyvalent medicine department of CHU Grenoble were successively included between May 2021 and July 2022. Clinical examination, LUS and electrolyte panel results were collected daily. Vital status was assessed 30 days after the last LUS. The primary endpoint was the evolution of the number of B-lines according to the dose of diuretic administered ; (3) Results: We performed 188 LUS. Our patients were elderly (85.8 [SD 8.1]) and comorbid. The median number of B-lines decreased from 17 at admission to 7 in the middle of the hospital stay, then stagnated until discharge. Simultaneously, the median dose of diuretics, initially stable at a maximum of 40 mg/d IV, decreased to 20mg/d IV by the end of hospital stay. Patients with CKD had a higher mean number of B-lines at entry (24.2 [SD 11.6]) compared to those without CKD (8.2 [SD 8.8]). However, the evolution of B-lines number was independent of creatinine levels. 30-day all-causes mortality was significantly related to the number of B-lines at discharge (15.2 [SD 10.1] in deceased patients versus 3.9 [SD 5.4] in living patients, p

With the global warming and the frequent occurrences of harsh environments, mooring line failures are frequent. Response analysis of the platform structure and its residual mooring system under multiple mooring line failures is needed. Therefore, it is necessary to investigate the change law of platform motion response after mooring line failure to find out the reasons for the change. Studies for different failure combinations of mooring lines show that the variation of the steady-state equilibrium position of the platform is closely related to the stiffness, with a clear functional. The duration and amplitude of the transient response are mainly influenced by the Morison drag force. And it was found that the suspended mooring line reduced the motion responses. It is also found that the mooring line failure increased the effective tension and suspension length of the riser. Based on the improved Dezert-Smarandache theory (DSmT), it is calculated that mooring line failure has little effect on the failure probability in different zones of the riser.

Excessive oxidative stress and exercise-induced fatigue reduce physical performance and can lead to dysfunction in antioxidant systems within muscular and hepatic tissues. Integrating natural substances with exercise may mitigate fatigue via anti-oxidant effects. This study aims to compare and evaluate the effects of exercise and supplementation with Sundarbans honey vs energy drinks on the strength, anxiety physiological profiles, and hepatic antioxidant capacity in mice undergoing extraneous exercise and fatigue. Forty-eight four-week-old Swiss albino mice were randomly assigned to one of eight groups: (1) Control, (2) Speed™ (Sp), (3) Royal Tiger™ (RT), (4) Sundarbans Honey (SH), (5) Exercise (Ex), (6) Exercise + Sundarbans Honey (Ex+SH), (7) Exercise + Speed™ (Ex+Sp), and (8) Exercise + Royal Tiger™ (Ex+RT). Supplements were administered via oral gavage: Sp (2.5 ml/kg BW), RT (2.5 ml/kg BW), and SH (1 g/kg BW), four times a week for 60 days. Mice in the Ex, Ex+SH, Ex+Sp, and Ex+RT groups underwent daily swimming and running. The strength, fatigue, anxiety levels, lipid profiles, and antioxidant biomarkers were evaluated post-treatment. The SH, Ex, and Ex+SH groups exhibited significantly enhanced physical performance (p<0.05). Plasma lipid profiles, including LDL, triglycerides, total cholesterol, and fatigue-related biomarkers (ALP, AST, ALT, LDH, CK, LA, BUN, and glucose) were markedly increased in the Sp and RT groups but decreased in the SH, Ex, and Ex+SH groups compared to control (p<0.05). Exercise-induced fatigue elevated the Nrf2/HO-1 antioxidant defense system in liver tissue. IL-6 levels were reduced in the SH, Ex, and Ex+SH groups (p<0.05). These findings indicate that regular exercise combined with SH supplementation increases strength and improves lipid profiles, reducing exercise-induced oxidative stress and fatigue via modulation of the Nrf2/HO-1 pathway in liver tissue. These results highlight SH supplementation’s potential as a complementary strategy to enhance exercise outcomes and mitigate exercise-induced stress.

Background: The adoption of self-care behaviors among patients with congestive heart failure (CHF) is essential for the management of their health condition. However, there is a lack of tools for estimating self-care in CHF patients. We aim to develop and validate the Hippocratic heart failure self-care scale (HHFSCS). Methods: the scale includes 22 items which are reviewed by a committee of experts. Individuals indicate the frequency at which they follow each self-behavior on a five-point Likert scale. Adult patients with CHF (n=250) from a General Hospital, in Athens, were participated in the study from June 2020 to March 2021. Reliability coefficients and Explanatory Factor Analysis (EFA), using a Varimax rotation and the Principal Components Method were used to assess the psychometric measurements. Results: The Cronbach’s alpha coefficient of the HHFSCS was 0.807. The exploratory factor analysis identified two domains that accounted for 88.44% of the variance of the scale items; however, each sub-scale could not be used as an independent scale. Finally, the test-retest showed a significant strong correlation (r=0.973, p&lt;0.001). Conclusions: The HHFSCS is a reliable and valid tool for assessing self-behaviors in CHF patients. Health professionals can use it in their clinical practice to improve the management of patient’s health conditions.

This paper proposes a novel single-stage buck-boost three-Level neutral-point-clamped (NPC) inverter with two independent dc sources coupled for the grid-tied photovoltaic (PV) application, which can effectively solve the unbalanced operational conditions generally appeared between two coupled independent PV sources induced by the unequal irradiation and temperature distribution. The proposed control scheme can simultaneously guarantee the maximum power point (MPP) operation of both PV sources and maintain the output waveform quality. Compared to the traditional two-stage PV inverter, the proposed NPC inverter could reduce the PV array voltage requirement and dc-link capacitors’ voltage rating, meanwhile show the advantage in operational efficiency. MATLAB simulations and the captured experimental results are presented to show the performance of the proposed three-level inverter.

This paper examines a persuasion game between two agents with one-sided asymmetric information, where the informed agent can reveal her private information prior to playing a Battle-of-the-Sexes coordination game. We find that in the presence of strategic uncertainty in coordination there exists an equilibrium where there is no 'unraveling' of information. We provide a purification argument for this mixed strategy equilibrium to strengthen the central result, which is robust to several extensions, including both-sided asymmetric information and imprecise information revelation.

Recent works in mechanical fatigue consider that a threshold of entropy exists, the fracture fatigue entropy. The determination of this quantity is usually done considering empirical models for the mechanical power estimation. In this paper, we experimentally observe the existence of a threshold of entropy and exergy in low cycle fatigue for a flat Al-2024 specimen avoiding the use of a model, solely measuring the heat generated during a fatigue test. Results are then compared considering various hypotheses (1D heat dissipation with convection and radiation considered as heat sources, and, heat transfer from a fin with convection and radiation as boundary conditions) to an empirical mechanical model known in the literature and deviations between them are discussed.

Athletes are exposed to high-intensity loads to promote athletic performance, however without appropriate evaluation for its effects. This study investigates the effects of four types of exhaustion exercises on Heart Rate Variability (HRV) and Poincaré features as markers of central fatigue; Creatine Kinase (CK) and blood lactate concentrations ([LA-]b) as biomarkers of peripheral fatigue. To achieve this purpose, ten healthy volunteers were exposed to exhaustive exercise using isotonic-, isometric-, aerobic-, and anaerobic-fatigue protocols. HRV Poincaré features, standard deviation of instantaneous beat-to-beat R-R interval variability (SD1) and standard deviation of continuous long-term R-R interval variability (SD2) variables were collected. Central fatigue was tested through the sympathetic stress index (SS) and the sympathetic and parasympathetic index (SS/SD1). Blood samples were collected at the beginning and at the end of the exercises to determine CK and [LA-]b. The SD1 decreased in each exercise protocol, while the SS and SS/SD1 increased. [LA-]b and CK increased at the end of each protocol and correlated with SD1 and SS/SD1. HRV, CK, and [LA^-]_b are acute markers to detect, both central and peripheral fatigue; sensitive to the type, duration, and intensity of exercise, being HRV a novel noninvasive marker, simple and useful for sports coaches and athletes.

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

TThe aim of the work is to present a newly developed stand and methodology of accelerated tests of fatigue strength of flexible propellers and fins. The paper presents the design and concepts of the measuring elements used in the research. Test methodology and water stressing were devel-oped. The mechanical properties of the following materials were presented: Arnitel EL-550 and QUEO 8230 with the addition of PP / EVA 50/50 (polypropylene / ethylene-vinyl acetate) - in the proportion of 70/30 (QUEO 8230 / additive). The constructed test stand and a new method of fa-tigue testing of biomimetic fins made it possible to determine the number of fin movement cy-cles under a given load, which may facilitate the determination of a warranty for a newly intro-duced product. The current consumption by the fin drive and video monitoring allowed for the selection of the range of the number of movement cycles and the determination of the moment of fatigue cracks until the fin structure loses its capacity. During the analysis, the test results showed that the fins made of Arnitel EL-550 did not show changes in the measured values of the current and the force generated by the fin. For a fin made of QUEO 8230, at 35,000 cycles, there is a decrease in the current and force consumed, which indicates the initiation of fatigue damage to the fin. The performed tests can be the basis for the development of standards for the fatigue strength of flexible propellers.

We investigate the impact of aging on exchangeable inter-arrival times in mixed renewal processes, exploring its implications for reliability and survival analysis. In this study, first, we revisit the definition of renewal point processes, where inter-event time intervals are considered as exchangeable non-negative random variables. Then, we define the concept of statistical aging as latency in the observational process of event counting. Latency affects event detection but preserves exchangeability. However, it may alter the statistical properties of inter-event time intervals. Our analytical and numerical assessments highlight the significance of aging in exchangeable lifetimes, offering insights into key metrics such as the failure survival function, renewal function, and hazard rate function. Through archetypal examples and empirical findings, we illustrate the implications of aging on renewal processes. In particular, employing a Bayesian perspective, we analyze high-frequency currency exchange rate data to assess the impact of aging on volatility risk evaluation. This study contributes novel insights to the literature of renewal theory and survival analysis, emphasizing the role of latency aging in stochastic point processes under exchangeability assumption.

We consider a Cauchy problem for differential equations in a Hilbert space $X$. The problem is stated in a time interval $I$, which can be finite or infinite. Weuse a fixed point argument for history-dependent operators to prove the unique solvability of the problem. Then, we state and prove convergence criteria for both a general fixed point problem and thecorresponding Cauchy problem. These criteria provide necessary and sufficient conditions on a sequence $\{u_n\}$ which guarantee its convergence to the solution of the corresponding problem, in the space of both continuous and continuously differentiable functions. We then specify our results in the study of a particular differential equation governed by two nonlinear operators. Finally, we provide an application in viscoelasticity and give a mechanical interpretation of the corresponding convergence result.

First came the digital banks without offices, and then the “fintech” companies that combined technology and finance to achieve greater efficiency and new business models. Later was the turn of transport and logistics, understood as the sector whose economic activities derived from the transport of people and goods, while on the one hand, it has had a new spring thanks to factors such as online sales. Then, perhaps catalyzed by the pandemic scenario, the turn has reached education, where years ago was only a complement of traditional education, now is a central part with multiple modern methodologies. Numerous studies exist about using or implementing these e-learning procedures, but technical analysis is barely found in references. This work aims to analyze the digital transformation of the main sectors of our society, including finances, transport, and education, together with several examples of how technology was helping to fight the pandemic scenario.

In the case of solid slabs made of reinforced concrete that are usually subjected to bending, large areas of the structure are stressed well below their load-bearing capacity. Contrary to this are shell structures, which can bridge large spans with little material if designed according to the force flow. To improve the efficiency of ceiling slabs, we want to utilize the shell load-bearing behavior on a smaller scale by resolving the solid interior accordingly. In order to be able to study a wide range of such constructions virtually, a parametric multiobjective simulation environment is being developed in an ongoing research project. The basic analysis approaches which were implemented are presented in this paper. The basic workflow, the used programs and material models and their calibration on the tests on textile-reinforced concrete (TRC) samples are described.

The fatigue delamination damage is one of the most important fatigue failure modes of laminated composite structures. However, the developments of the theoretical framework, mathematical/physical model and numerical simulation of fatigue delamination are still challenging issues, and there is a lack of systematic classification. This article reviews the experimental phenomena of the onset and propagation stage of delamination under fatigue loading, and summarizes the commonly used phenomenological models for laminated composite structures. The research methods, general modeling formulas and development prospects of the phenomenological models are presented in detail. In the light of the analysis of finite element model (FEM) for the laminated composite structures, a number of simulation methods of fatigue delamination crack propagation damage model are carefully classified. Furthermore, within the theoretical framework of strength theory model (SM), fracture mechanics model (FM), damage mechanics model (DM) and hybrid model (HM), the complete procedure, application, capability assessment, advantages and limitations of the models are also discussed in detail. Finally, several valuable suggestions are given for the research interests, and challenging technical problems that need to be overcome on the fatigue delamination prediction of laminated composite structures in the future.

Steel structures, such as bridges, must be continuously maintained. Due to increasing trac loads, design and execution shortcomings, many steel bridges are subject to various types of damage, such as cracks. The bridges must be maintained by crack removal and re-welding the cracks. During this work, the bridge is closed for trac in order to suppress the crack ank movement during welding. As a result, trac loads on other routes are higher, which increases further damage on detour routes and subsequently additional welding work and costs on theses structures. Therefore, the aim is to provide a method that allows welding work on steel structures under running trac, respectively under cyclic loads. First, measurements at a representative steel bridge were conducted to derive gap opening parameters of amplitude and frequency for welding tests under cyclic loads. In a test setup for reproducible and comparable welding tests, specimen were welded under cyclic loads. Deep grinding of the root layer allowed defect-free welding within the range of 0.1 mm amplitude at a frequency of 2 Hz loadings. For such welds, the weld quality and the fatigue strength was comparable to the standard requirements.

In this paper, we present a new stress calculation method for flexible structures, particularly, the tensile armors, and apply it to flexible riser fatigue analysis. The method is based on a 3-dimensional curved bar theory. First, the tensile armor center line was described as a cylindrical helix curve, its bended curve length and bending migration length were derived and studied under different friction scenarios. Second, the tensile and bending stiffness was given with consideration of frictional hysteretic effect, and verified through FEA analysis results. Third, we presented the stress calculation formula for tensile armor under tension and bending load. All stress components are considered, including tensile, bending and shear stresses. Fourth, the method was benchmarked with published experimental results on a flexible prototype tension and bending tests, and comparisons showed general agreements. Fifth, the method is further applied to a 8” flexible riser for fatigue assessment and lifetime extension evaluation, and showed the flexible riser has sufficient remaining fatigue life, and is suitable to continue its service under the current operating conditions. Last, conclusions are drawn. It concluded that the presented tensile armor stress calculation method and modelling techniques are valid for flexible riser fatigue analysis. This method is time efficient, and can be implemented into other multi-scale models for riser dynamic analysis. It is also applicable to other similar helix structure stress analysis, such as wire ropes, submarine hoses, and subsea umbilicals.

Natural cellulose hydrogels have been widely used to enhance mechanical properties. However, existing natural fiber composite hydrogels are not reusable, limiting their potential applications. To address this issue, we designed and prepared a polyvinyl alcohol/glycerol /bamboo microfibril double network tough hydrogel using a simple method. The bamboo microfibril and polyvinyl alcohol form a tight and rigid network through hydrogen bonding, improving mechanical properties. The prepared polyvinyl alcohol/glycerol/bamboo microfibril double network tough hydrogel has the advantages of reusability and fatigue resistance. Furthermore, both the elastic modulus and toughness of the hydrogel increase with increasing bamboo microfibril content. We also demonstrated that the hydrogel can be recast after cyclic compression, maintaining its recyclability, stability, and certain stiffness and toughness. Our study highlights the potential of hydrogels for controllable mechanical properties, fatigue resistance and shows that polyvinyl alcohol/glycerol/bamboo microfibril hydrogel has broad value for plasticity and reuse.

This paper aims to provide an overall review of degradation, damage evolution and fatigue models in the literature of various engineering materials, mostly metals, and composites.

Reliable fatigue design rules affect the proactive identification of safety parameters in aerospace industry. Numerous fatigue crack initiation and propagation models, linear and nonlinear, have been developed for designing purposes or estimation of the remaining life of aging airplanes. Depending on the adopted assumptions, the accuracy varies for different loading histories, loading types, and materials. Semi empirical models are simple but yield significant inaccuracies. Models with better theoretical basis provide better accuracy, but implementation in real conditions is problematic. In the present work, a review of author’s recent fatigue crack initiation and propagation models based on physical mechanisms is presented and improvements are proposed. Verification of the models on test results is provided and discussed.

In Nature, it is common for living plants and non-living plant tissues to consist of materials with anisotropic multilayer and non-homogenous structure. The structure of tissues determines their self-shaping and self-folding capabilities in response to a stimulus in order to activate different functionalities. Predetermined movements are realized according to changes in environmental conditions, which trigger the fibrous anisotropic structure of the plants’ material. In this study, we present the fabrication process of low-cost anisotropic multilayer materials that are capable of realizing complex movements caused by small temperature changes (<40 ^oC). The mismatch in the thermo-mechanical properties between three or more anisotropic thin layers creates responsive materials that alter their shape owing to the developed internal stresses. Isotropic layers can perform only bending movements, whereas anisotropic multilayer materials can perform bending, twisting or complex combined modes. The movements of the material can be controlled by forming anisotropic homogenous metallic strips over an anisotropic polymer. As a result, inexpensive responsive materials can be developed to passively react to a very broad range of thermal requirements. We studied the major parameters that affect the sensitivity of the developed materials, as well as their failure modes and crack formation under thermal fatigue conditions.

Lymphedema is a chronic and debilitating disease that affects up to 250 million patients worldwide. Recent advances in understanding its pathophysiology, along with improved diagnosis and microsurgical techniques, have enhanced our ability to cope with the challenging task of treating this disease. This review provides an overview of the disease from a surgeon's point of view, including existing imaging modalities used for preoperative assessment, as well as surgical procedures used in its treatment. Advantages and drawbacks of various existing modalities used for pre or intraoperative assessment of lymphatic vessels are discussed. Lymphedema treatment has shifted from palliative debulking procedures (liposuction and direct excision) to those aimed at restoring lymphatic flow and countering the pathophysiology of the disease (lymphaticovenous anastomosis and vascularized lymph node transfer). A combination of both approaches can result in a synergistic benefit for patients and are discussed in this review. Despite recent advances, some controversies persist, and further studies are needed to better define surgical treatment algorithms.

Based on the nonlinear failure criterion and modified tangential technique, the upper bound solutions of supporting pressure on the deep tunnel face were obtained under pore water pressure conditions. The influence of parameters on the supporting pressure and collapse range was investigated according to the unlimited block failure mechanism. It is found that the upper bound solutions of supporting pressure increase with the growth of the nonlinear coefficient and pore water pressure coefficient. The collapse range of the tunnel face scales out with the increase of the nonlinear coefficient and shrinks when increasing the pore water pressure coefficient. Moreover, with the increase of the nonlinear coefficient, the impact strength on supporting pressure and collapse range declines gradually. According to the calculating results, it is manifest that both the pore water pressure and nonlinear criterion factors have negative impacts on the stability of the tunnel face. Thus, more attention should be paid to these parameters to ensure face stability in deep tunnel construction.