Final Set Research Articles

Comparative Analysis of Linear and Nonlinear sEMG Methods for Detecting Muscle Fatigue During Dynamic Biceps Curls

Muscle fatigue, a key concern in sports science, rehabilitation, and occupational health, influences performance, injury risk, and provides insights into muscle functionality and endurance. Surface electromyography (sEMG) has emerged as a vital tool for non-invasively tracking muscle electrical activity and gauging health. As its application for muscle fatigue assessment grows, identifying the most accurate analytical methods is essential. Current sEMG analyses employ both linear and nonlinear metrics to measure fatigue onset and progression, yet research is ongoing to determine which method is most effective in the context of dynamic contractions. The study was aimed to evaluate the efficacy of established linear and nonlinear methods in measuring muscle fatigue caused by dynamic contractions through surface electromyography (sEMG) signals. A group of twelve healthy individuals completed biceps curls at a consistent pace of one repetition per four seconds, which constituted 75% of their 10-repetition maximum. Concurrently, sEMG signals were captured from the biceps brachii muscle at 1000 Hz. To assess the sEMG signals during the initial, middle, and final sets of 10 repetitions, three linear metrics—mean frequency, median frequency, and spectral moment ratio (SMR)—along with two nonlinear approaches, namely sample entropy and detrended fluctuation analysis (DFA), were utilized. The study's outcomes indicated notable shifts in the SMR values and the two DFA-derived scaling exponents across the exercise sets. These results indicated that SMR, sample entropy, and DFA are effective in gauging muscle fatigue, with sample entropy and DFA demonstrating heightened sensitivity to the fatigue levels when compared to the linear metrics.

Backcrossing Failure between Sikitita Olive and Its Male Parent Arbequina: Implications for the Self-Incompatibility System and Pollination Designs of Olive Orchards.

Backcrossing between Sikitita and its male parent Arbequina, offers the possibility to check the suitability of different self-incompatibility models proposed for olive. To determine Sikitita's response to self- and cross-pollination treatments, including pollination with its father Arbequina, we compared the parameters following pollen-pistil interaction, the resulting initial and final fruit set, and the paternity of the seeds produced under different crosses. The results showed that Sikitita behaves as a self-incompatible cultivar due to the inhibition of pollen tube growth in the pistil of self-pollinated flowers. This incompatibility reaction led to a significant reduction of self-fertilization and fruit set. Seed paternity analyses confirmed the self-incompatibility response of Sikitita. A similar incompatibility response was observed in Sikitita flowers when hand-pollinated with pollen of Arbequina and Koroneiki. On the contrary, cross-pollination with Arbosana gave excellent results, with analyses showing that pollen of Arbosana is largely preferred by Sikitita to father its seeds more than the pollen of other cultivars presented in the orchard. The backcross failure of Sikitita with Arbequina pollen suggests that the self-incompatibility system in olives is not of the gametophytic type. In contrast, pollination tests fit features of previously reported sporophytic self-incompatibility systems. However, some amendments are proposed, among them the incompatibility groups for Sikitita and Koroneiki.

Point-of-Care Ultrasound for the General Pediatric Resident: A Needs Assessment.

Point-of-care ultrasound (POCUS) is a valuable tool in pediatric care, but formalized education on POCUS is not a standard part of pediatric residency. Our primary objective was to conduct a needs assessment to determine pediatric residents' attitudes toward ultrasound education. A Likert scale-based survey was distributed to residents at 48 pediatric residency programs. Respondents were asked to rate their agreement to statements about ultrasound education at their respective programs. Participants were also asked to rank ultrasound indications in order of importance. Ninety-seven survey responses were included in the final data set. Sixty percent of respondents had not performed any ultrasound scans during residency. Ninety-two percent of respondents indicated an interest in ultrasound training during residency and that they desired a formal POCUS curriculum. Eighty-one percent of residents indicated that having more ultrasound education would make their programs more attractive to applicants. Pediatric residents recognize the utility of POCUS and desire additional education during training.

Defining a core outcome set for hypermobility spectrum disorders and hypermobile Ehlers-Danlos syndrome: A Delphi consensus study

The reported prevalence of hypermobility spectrum disorders (HSD) and hypermobile Ehlers-Danlos Syndrome (hEDS) is unclear due to complex presentations and lack of awareness amongst professionals, contributing to diagnostic and management uncertainties. Standardising an outcome measure to assess symptoms most important to patients should help determine the impact of interventions. This Delphi study aims to reach a consensus with stakeholders on the core outcome set for children and adults with HSD/hEDS. A three-round modified Delphi consensus study with a follow-up consensus meeting was used. Stakeholder groups consisted of (1) individuals with HSD/hEDS; (2) family/friends/carers and (3) healthcare professionals. Participants could belong to more than one stakeholder group. They rated 74 symptoms using a 9-point Likert scale: 1 “not important to 9 “critically important”. Symptoms achieving a consensus rating of ≥ 70.0% critical importance across all groups were included. In Round 1, 766 responses were received from 600 participants, reducing to 566 responses from 438 participants by Round 3, with 53 participating in the consensus meeting. Overall, 30 symptoms met the ≥ 70.0% critically important threshold to be included in the final core outcome set. These were categorised under the specialties of musculoskeletal and orthopaedics, social, pain, gynaecology and urology, negative affect, neurological, gastrointestinal and “other”. This study is the first to identify by consensus the core outcome set to be measured for patients with HSD/hEDS. The importance of these outcomes was confirmed by individuals living with the condition, their family, friends, carers and relevant healthcare professionals. Trial registration: IRAS ID: 326,855; East Midlands — Leicester South REC (reference: 23/EM/0143); Protocol registered with the COMET Initiative. Key Points• There is a lack of standardised outcome measure for HSD/hEDS research studies due to the heterogeneity of symptom presentations.• Symptoms across musculoskeletal and orthopaedics, social, pain, gynaecology and urology, negative affect, neurological, gastrointestinal and “other” specialties were identified as the core outcome set defined as ≥ 70.0% critically important to measure for individuals with HSD/hEDS.• There were a significant number of symptoms, widely recognised in the literature to be comorbid to HSD/hEDS, that reached a critical importance threshold of 50.0–69.9%, restricting the core outcome set to only those that met 70% or above may be limiting.

Designing usability/user experience heuristics to evaluate e-assessments administered to children

The application of electronic assessments (e-assessments) has increased, particularly among elementary-school-aged children. Paper-based assessments are frequently converted into digital formats for efficiency gains, with little thought given to their user experience (UX) and usability. Individual differences, particularly among young children, can inhibit test-takers from completing the assessment tasks that are not designed to match their needs and abilities. Consequently, studies have raised concerns about the generalizability and fairness of e-assessments. Whereas heuristic evaluation is a standard method for evaluating and enhancing the efficacy of a product with respect to a set of guidelines, more information is needed about its added value when designing e-assessments for children. This paper synthesizes heuristics on the basis of the literature and expert judgments to accommodate children's abilities for interacting with e-assessment platforms. We present a final set of 10 heuristics, validated and refined by applying a heuristic evaluation workshop and collecting 24 expert surveys. The results indicate that the derived heuristics can help evaluate the UX and usability-related aspects of e-assessments with 6- to 12-year-old children. Moreover, the present paper proposes recommendations for a framework for developing usability/UX heuristics that can be used to help researchers develop domain-specific heuristics in the future.

Evaluation of setting and hardening properties of accelerator and slag-silica fume-cements

Industrial solid waste is used as a supplementary cementitious material (SCM) to replace cement, promoting the recycling and improving resource and economic sustainability. In this study, an organic combination of SCMs was prepared, along with the preparation of composite cementitious materials (CCM) that can be tailored to the aluminum sulfate alkali-free liquid accelerators. The findings revealed that a combination of 30% SCMs, including 10% slag, 15% silica fume, and 5% treated hardened cement powder (T-HCP), was blended with cement to form a CCM. Under the influence of the accelerator, the initial setting time of CCM is 1 min 20 s and the final setting time of CCM is 3 min. The compressive strength at 1, 3, and 28 days reaches 17.2, 29.9, and 51.6 MPa, respectively. CCM can utilize SiO2 from silica fume and CaCO3 in T-HCP as the nucleus to facilitate the substantial generation of AFt and Ca(OH)2 in the initial stage. It can be seen that the use of SCM together with alkali-free liquid accelerators in shotcrete not only enables the utilization of solid waste but also greatly improves the performance of shotcrete.

Biocidal properties of gypsum stone modified with Reynoutria sachalinensis raw materials

The current stage of the construction industry development implies increased requirements for building materials to maintain and improve global environmental processes. The understanding by ecologists globally of the danger of anthropogenic impact on the global environment has been reflected in the formulation of Sustainable Development Goals (SDGs). Thus, scientists and engineers are turning to safe plant-based raw materials as innovative building materials. Of particular interest for practice is the use of Reynoutria sachalinensis, which may exhibit biocidal properties. The purpose of this study was to obtain a gypsum stone modified with an extract from the green mass of R. sachalinensis, as resistant coating to fouling by microscopic fungi. The results indicated 10% decrease in the required water addition to gypsum paste when using plant extract, a slowdown of the initial and final setting time of the modified gypsum paste samples compared to the control samples by 6 and 7 min, respectively, and a slight decrease in bending and compressive strengths of the samples of 12.5% and 6%. The 100% resistance of the modified samples to fouling by microscopic mould fungi was also revealed.

Guidelines to manage women with infertility: an e-Delphi study

Introduction: The psychosocial health problems associated with infertility is compounded in African women when prevailing cultural expectations emphasize the value of parenthood. Despite the social stigma these women endure, they are still mostly managed from a biomedical approach, especially in Ghana, the context of the study. Objective: This study explored the views of a panel of experts to reach consensus on holistic guidelines to manage women with infertility in Ghana. Methods: An e-Delphi technique was employed to retrieve information using a panel of 20 experts. Data collection was conducted in two rounds, and each participating expert was emailed the preliminary guidelines to rate based on certain criteria. Data analysis was done in accordance with the expert participants’ rating of and comments on the guidelines. Results: The final guidelines for holistic healthcare to manage women with infertility include the following interventions: Holistic healthcare assessment, psychological interventions, health education, spiritual support, relevant support from significant others; all within a therapeutic relationship. Conclusion: When healthcare providers use the final set of guidelines to manage women diagnosed with infertility, these women will receive holistic healthcare to attain optimal health and improved chances of conceiving. Keywords: Holistic approach; e-Delphi technique; psychosocial interventions; infertility.

WHO research agenda on the role of the institutional safety climate for hand hygiene improvement: a Delphi consensus-building study

BackgroundCreating and sustaining an institutional climate conducive to patient and health worker safety is a critical element of successful multimodal hand hygiene improvement strategies aimed at achieving best practices. Repeated...

A method for temperature sensor and model selection for machine tool thermal error modelling using ANFIS and ANN

AbstractThermal errors account for a significant part of the dimensional errors of components produced by precision machine tools. These errors are commonly compensated using predictions from temperature-based empirical models. The accuracy and robustness of these predictions are affected by the locations of temperature sensors used to obtain the model’s input data. Methods for sensor selection found in literature are often difficult to replicate and automate because they require tuning of several hyperparameters. This work presents a sensor and model selection approach that uses proper orthogonal decomposition (POD) and QR pivoting to select a subset of sensors that have been preinstalled in the machine tool as possible model inputs. These sensors are then sorted according to their correlation with the thermal error being modelled. The final set of inputs and thermal error model structure is chosen using Bayesian Information Criterion (BIC) to limit model overfitting. The approach was tested by modelling the Y-axis thermal error measured from air-cutting experiments performed under different spindle speeds and feed rates. This enabled determination of the structure and the choice inputs for Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) thermal error models. The accuracy of these models was compared to that of models trained using inputs selected by conventional approaches: the least absolute shrinkage and selection operator (LASSO), fuzzy c-means clustering (FCM), and principal component regression (PCR). The presented approach had better or comparable results to the conventional approaches while using fewer inputs. The presented approach is also well suited for automation compared to conventional approaches that require expert input.

B-036 Systematic Evaluation of Antibody-Antigen Interactions for Suitability in Immunoassays Using Parallel Microarray ELISA

Abstract Background A critical step in immunoassay development is the selection of the appropriate capture and detection antibodies. The use of suboptimal antibodies can drastically affect the quality of the final assay. Traditional selection methods involve a direct testing of potential antibodies in the final assay setting; a time-consuming and material-intensive exercise that is often too complex to test all possibilities. Alternatives, such as abstract K-on/K-off determinations via SPR or BLI can be costly and often show limited translatability to the ultimate assay format. Here, we describe a novel systematic approach to rapidly screen antibody-antigen interactions for key assay specifications and test for translatability of the findings. Methods Nanoliter volumes of potential capture antibodies were spotted onto the bottom of ELISA wells, generating a microarray of antibodies in each well (>11,000 spots per plate). For the analysis of capture antibody-antigen interactions, a titration series of biotinylated analyte in negative sample matrix was applied. Binding was visualized using strep-polyHRP, precipitating TMB and high resolution scanning of each ELISA well. Antibody pair performance was investigated using unlabeled analyte and biotinylated detection antibody options. Sensitivity, specificity, dynamic range, binding speed, binding strength and matrix compatibility were investigated using time courses, concentration ranges, dilutions, interferent spikes and pH/salt/detergent challenges. Signals were quantified to calculate and statistically compare each possible interaction. Results Antibody-antigen interactions were investigated via parallel microarray ELISA for two example immunoassays: the HBsAg and cTnI test. For both analytes, a panel of antibodies was screened revealing antibodies with diverse characteristics. Striking differences were observed depending on the sample matrix composition. Without optimization, antibodies could be identified showing dynamic assay ranges of 3-4 log orders. Time course experiments revealed high-affinity antibodies suitable for rapid diagnostic tests. For HBsAg, levels down to 0.01 IU/mL (∼40 pg/mL) could be reproducibly detected, which is well below the minimal requirement of 0.13 IU/mL. Reactivity against multiple virus serotypes could be confirmed. Interestingly, for the cTnI test, a strong synergistic effect was observed when specific monoclonal antibodies were combined in the capture mix, resulting in a 6-fold sensitivity enhancement compared to their separate performances. Finally, we show that the results obtained with the parallel microarray ELISA approach are highly translatable to the final assay format, ranging from bead-based dry-chemistry assays to chemiluminescent immunoassays. Conclusions The parallel microarray ELISA evaluation presents a robust and reliable method for identifying the best antibodies for an immunoassay. It allows for a systematic and quantitative screen of numerous antibody options within 1-2 weeks under real immunoassay conditions with minimal antibody amounts. This method has shown to be highly translatable and is customizable to accommodate required assay specifications.

Fresh and Hardened Properties of Alkali-Activated POFA-GGBFS Pastes Cured in Ambient Temperature – An Initial Mix Design

Weak soils are characterised by their high compressibility and low shear strength, which requires stabilisation to improve their compaction and strength characteristics before being used for construction projects. Recent trends in soil stabilisation show an increased interest in the application of waste-derived geopolymers as low-carbon materials to address the carbon emission problem related to cement production. This paper presents the preliminary findings of using Palm Oil Fuel Ash (POFA) and Ground Granulated Blast Furnace Slag (GGBFS) binary blends as geopolymer precursor materials. These binary waste material blends were activated using alkaline solutions, namely Sodium Hydroxide (NH) and Sodium Silicate (NS), to synthesise geopolymers at ambient temperatures. Three main factors were considered for the optimisation of the geopolymer mix design, as recommended by past research: alkali equivalent (8-11.5%), activator modulus (0-0.7), and slag replacement (fixed at 30%). Alkali equivalent and activator modulus parameters were varied and tested to establish its initial and final setting times, workability and strength properties, while the slag replacement percentage was set at 30%. This study aimed to determine the most influential parameters to produce the geopolymer material with the highest compressive strength and satisfactory setting times and workability. Single-source alkali activators (NH only) used on POFA-GGBFS produced specimens with smaller flow diameters, longer initial and final setting times, and lower compressive strength than specimens activated with NH and NS. Geopolymer specimens synthesised with NH and NS produce stiffer compounds possessing higher compressive strength values and explosive-type failure modes due to their higher silica content. At ambient temperatures, TM-Mix 2 (7% alkali equivalent and 0.7 activator modulus) produced the highest compressive strength value of 67.3 MPa at 28 days curing, flow diameter of 227 mm, with the initial and final setting time of 25 minutes and 45 minutes, respectively. Consequently, the results show that the preliminary POFA-GGBFS geopolymer mix design could produce sustainably sourced geopolymer compounds with adequate strength and acceptable setting time and workability. This study is part of a current investigation to further optimise the POFA-GGBFS mix design for the purpose of weak soil stabilisation.

A new performance evaluation indicator for the LEE Jong-wook Fellowship Program of Korea Foundation for International Healthcare to better assess its long-term educational impacts: a Delphi study.

The Dr. LEE Jong-wook Fellowship Program, established by the Korea Foundation for International Healthcare (KOFIH), aims to strengthen healthcare capacity in partner countries. The aim of the study was to develop new performance evaluation indicators for the program to better assess long-term educational impact across various courses and professional roles. A 3-stage process was employed. First, a literature review of established evaluation models (Kirkpatrick’s 4 levels, context/input/process/product evaluation model, Organization for Economic Cooperation and Development Assistance Committee criteria) was conducted to devise evaluation criteria. Second, these criteria were validated via a 2-round Delphi survey with 18 experts in training projects from May 2021 to June 2021. Third, the relative importance of the evaluation criteria was determined using the analytic hierarchy process (AHP), calculating weights and ensuring consistency through the consistency index and consistency ratio (CR), with CR values below 0.1 indicating acceptable consistency. The literature review led to a combined evaluation model, resulting in 4 evaluation areas, 20 items, and 92 indicators. The Delphi surveys confirmed the validity of these indicators, with content validity ratio values exceeding 0.444. The AHP analysis assigned weights to each indicator, and CR values below 0.1 indicated consistency. The final set of evaluation indicators was confirmed through a workshop with KOFIH and adopted as the new evaluation tool. The developed evaluation framework provides a comprehensive tool for assessing the long-term outcomes of the Dr. LEE Jong-wook Fellowship Program. It enhances evaluation capabilities and supports improvements in the training program’s effectiveness and international healthcare collaboration.

Flow and sensitivity analysis of MHD radiative hybrid nanofluid flow across a permeable wedge with slip condition: Response surface methodology

AbstractThis current paper has been written to investigate the effect of a hybrid Tiwari and Das nanofluid model along with optimizing the flow using sensitivity analysis. Heat transfer rates and skin friction assessments were examined with the supplementation of external effects like heat source, thermal radiation, buoyancy forces, velocity slip as well as magnetic effect with spherical‐shaped nanoparticles. The mathematical modeling was formulated using a system of nonlinear PDE. Similarity transformations were implemented in the governing equations for obtaining the final set of nondimensional equations which were then solved using bvp4c code in MATLAB. The results obtained were in close agreement with published results. Some of the significant results obtained included an increase in Nusselt number by 2.26% for an increase in velocity ratio parameter () from to 0.3 along with an increase in skin friction coefficient by 0.77% with magnetic () parameter to . The heat transfer profile was augmented by 0.79% with increasing radiation parameter to while an increase of 18.84% was observed for skin friction profile values recorded for the hybrid model as compared to the base fluid model. Nusselt number reduced by 0.51% for a transition to nanofluid model from regular fluid and by 1.76% for the hybrid model compared to the nanofluid model The unblocked face‐centered central composite design (CCD) was used for analyzing the sensitivity analysis of independent, continuous input parameters on the response parameters, skin friction coefficient, and Nusselt number. The high values for , and , for Nusselt number and skin friction coefficient values, respectively, validate the ANOVA results obtained using response surface methodology (RSM). Only shows positive sensitivity for both the Nusselt number and skin friction responses. The present hybrid nanofluid model finds extensive applications in bio‐toxicity studies, manufacturing of water heaters, and forging of hot exhaust valve heads.

Pluto: Sample Selection for Robust Anomaly Detection on Polluted Log Data

Log anomaly detection, critical in identifying system failures and preempting security breaches, finds irregular patterns within large volumes of log data. Modern log anomaly detectors rely on training deep learning models on clean anomaly-free log data. However, such clean log data requires expensive and tedious human labeling. In this paper, we thus propose a robust log anomaly detection framework, PlutoNOSPACE, that automatically selects a clean representative sample subset of the polluted log sequence data to train a Transformer-based anomaly detection model. Pluto features three innovations. First, due to localized concentrations of anomalies inherent in the embedding space of log data, Pluto partitions the sequence embedding space generated by the model into regions that then allow it to identify and discard regions that are highly polluted by our pollution level estimation scheme, based on our pollution quantification via Gaussian mixture modeling. Second, for the remaining more slightly polluted regions, we select samples that maximally purify the eigenvector spectrum, which can be transformed into the NP-hard facility location problem; allowing us to leverage its greedy solution with a (1-(1/e)) approximation guarantee in optimality. Third, by iteratively alternating between the above subset selection, a model re-training on the latest subset, and a subset filtering using dynamic training artifacts generated by the latest model, the data selected is progressively refined. The final sample set is used to retrain the final anomaly detection model. Our experiments on four real-world log benchmark datasets demonstrate that by retaining 77.7% (BGL) to 96.6% (ThunderBird) of the normal sequences while effectively removing 90.3% (BGL) to 100.0% (ThunderBird, HDFS) of the anomalies, Pluto provides a significant absolute F-1 improvement up to 68.86% (2.16% → 71.02%) compared to the state-of-the-art sample selection methods. The implementation of this work is available at https://github.com/LeiMa0324/Pluto-SIGMOD25.

Effect of Phosphoric Acid and Soluble Phosphate on the Properties of Magnesium Oxychloride Cement.

This study investigates the effects of phosphoric acid (H3PO4), potassium dihydrogen phosphate (KH2PO4) and sodium dihydrogen phosphate (NaH2PO4) admixtures on the setting time, compressive strength and water resistance of magnesium oxychloride cement (MOC). MOC samples incorporating different admixtures are prepared, and their hydration products and microstructures are studied via X-ray diffraction (XRD) and scanning electron microscopy (SEM). The results indicate that the addition of H3PO4, KH2PO4 and NaH2PO4 reduces the initial and final setting times and decreases the compressive strength. However, the compressive strength of MOC is higher than 30.00 MPa with the addition of 2.0 wt.% phosphoric acid and its phosphate after 14 days of air curing. The water resistance of modified MOC slurries is significantly improved. The softening coefficient of MOC with 2.0 wt.% H3PO4 is 1.2 after 14 days of water immersion, which is 3.44 times higher than that of the neat MOC. The enhancement in water resistance is attributed to the formation of amorphous gel facilitated by H3PO4, KH2PO4 and NaH2PO4. Furthermore, the improvement in water resistance is manifested as H3PO4 > KH2PO4 > NaH2PO4.

Feature selection via robust weighted score for high dimensional binary class-imbalanced gene expression data

In this paper, a robust weighted score for unbalanced data (ROWSU) is proposed for selecting the most discriminative features for high dimensional gene expression binary classification with class-imbalance problem. The method addresses one of the most challenging problems of highly skewed class distributions in gene expression datasets that adversely affect the performance of classification algorithms. First, the training dataset is balanced by synthetically generating data points from minority class observations. Second, a minimum subset of genes is selected using a greedy search approach. Third, a novel weighted robust score, where the weights are computed by support vectors, is introduced to obtain a refined set of genes. The highest scoring genes based on this approach are combined with the minimum subset of genes selected by the greedy search approach to form the final set of genes. The novel method ensures the selection of the most discriminative genes, even in the presence of skewed class distribution, thereby improving the performance of the classifiers. The performance of the proposed ROWSU method is evaluated on 7 gene expression datasets. Classification accuracy, sensitivity and F1-score are used as performance metrics to compare the proposed ROWSU algorithm with several other state-of-the-art methods. Boxplots and stability plots are also constructed for a better understanding of the results. The results show that the proposed method outperforms the existing feature selection procedures based on classification performance from k nearest neighbors (kNN) and random forest (RF) classifiers.

Nongenetic and Genetic Factors Associated with White Matter Brain Aging: Exposome-Wide and Genome-Wide Association Study.

Human brain aging is a complex process that affects various aspects of brain function and structure, increasing susceptibility to neurological and psychiatric disorders. A number of nongenetic (e.g., environmental and lifestyle) and genetic risk factors are found to contribute to the varying rates at which the brain ages among individuals. In this paper, we conducted both an exposome-wide association study (XWAS) and a genome-wide association study (GWAS) on white matter brain aging in the UK Biobank, revealing the multifactorial nature of brain aging. We applied a machine learning algorithm and leveraged fractional anisotropy tract measurements from diffusion tensor imaging data to predict the white matter brain age gap (BAG) and treated it as the marker of brain aging. For XWAS, we included 107 variables encompassing five major categories of modifiable exposures that potentially impact brain aging and performed both univariate and multivariate analysis to select the final set of nongenetic risk factors. We found current tobacco smoking, dietary habits including oily fish, beef, lamb, cereal, and coffee intake, length of mobile phone use, use of UV protection, and frequency of solarium/sunlamp use were associated with the BAG. In genetic analysis, we identified several SNPs on chromosome 3 mapped to genes IP6K1, GMNC, OSTN, and SLC25A20 significantly associated with the BAG, showing the high heritability and polygenic architecture of human brain aging. The critical nongenetic and genetic risk factors identified in our study provide insights into the causal relationship between white matter brain aging and neurodegenerative diseases.

STUDY OF THE INFLUENCE OF THE CHEMICAL COMPOSITION OF RAILWAY AXLE STEEL ON THE UNIFORMITY OF THE FINAL MICROSTRUCTURE

The relevance of the work. For modern railway transport, increasing the strength and operational reliability of rolling stock parts, in particular railway axles, is an urgent task. It is known that the inhomogeneity of the distribution of chemical elements in the structure of structural grade carbon steels is formed mainly during their crystallization and may subsequently affect the final structural state and set of properties. Purpose. Study of the influence of the chemical composition of steels for railway axles on the uniformity of the structure. Methodology. Experimental ingots of different chemical compositions with different amounts and ratios of the main chemical elements within the range of OS and EA1N were produced in laboratory conditions. The grain structure was studied on microsections after etching with nital. Chemical inhomogeneity (“traces” of the dendritic structure) − the distribution of chemical elements in the microstructure of cast samples was detected by etching in a hot solution of sodium picrate. Metallographic analysis was performed on a light (optical) microscope “Axiovert 200 M MAT” manufactured by “Carl Zeiss”. The results. The effect of changing the chemical composition of carbon steel, which is intended for the manufacture of railway axles, on the peculiarities of the formation of ferrite-pearlite heterogeneity and grain size is determined. It is shown that in samples of steels corresponding to the EA1N brand with a lower carbon content, the distribution of phases is uneven. The mechanism of formation of such a structure is explained from the point of view of two theories. In samples of steels with an average carbon content, which correspond to steel of the OS grade, the distribution of the pearlite and ferrite phases is more uniform, the relationship between the size and the degree of darkening of the pearlite areas with the order of the former dendritic branches has been established. Based on the results of the quantitative analysis of the final grain structure, it was established that OS steel with an average carbon content at different Mn/Si ratios has a more uniform grain structure. EA1N steel with a lower carbon content has a pronounced grain size, with an increase in the Mn/Si ratio, the largest maximum of the dependence of the distribution shifts to a larger grain size (smaller number). Practical results. Increasing the homogeneity of the final microstructure contributes to increasing the plasticity and viscosity of steel, which directly affects the reliability and durability of railway axles.

Physical and mechanical properties of special cementitious materials modified by nano-particles

Compared to ordinary Portland cement (OPC), sulphoaluminate/ferroaluminate cement (SAC/FAC) and aluminate cement (CAC) are the most promising repair materials due to their excellent early strengths, but the later strengths of SAC/FAC develop slowly, and the later strengths of CAC are obviously declined. This paper studied the effects of nano-SiO2 and nano-ZnO on the physical properties, mechanical properties and early hydration processes of three special cement-based materials and compared them with OPC-based materials. The strength development and early hydration mechanism were revealed by hydration heat, scanning electron microscopy and X-ray diffraction. The test results showed that with the increasing content of nano-SiO2, the setting time of the four cement pastes was gradually shortened, the fluidity of four fresh mortars was gradually reduced, and their compressive and flexural strengths at all ages were improved to different degrees. Nano-ZnO significantly prolonged the setting time of OPC paste and increased the fluidity of OPC mortar, which had a negative effect on its early compressive and flexural strengths, but enhanced its late strengths. After the addition of 1 % nano-ZnO, the initial and final setting time of OPC were about 12 times and 13.4 times that of ordinary OPC paste, respectively. The effect of incorporating nano-ZnO on the physico-mechanical properties of three special cements was similar to that of nano-SiO2. The strength loss of CAC mortar with two kinds of nanoparticles was greatly reduced. The incorporation of nano-SiO2 and nano-ZnO could promote the hydration process of three special cements, resulting in the denser microstructure and higher crystallinity of hydration products.