An agroecological approach to preparation and use of a milk protein production baseline.

Commercial dairy production occurs in a complex management environment, but increasingly, the dairy manager is expected to provide detailed reporting of productivity and environmental outcomes, for which conventional research methods double-blind crossover or case:control trials are inappropriate. This paper demonstrates the development of a milk protein production monitoring tool using a temporal (baseline) control in longitudinal, census-type investigations of modulation of system performance in response to factor change. It utilises farm-derived current and historical data, and contrasts seasonal responses with those achieved on neighbouring farms in a 2 × 2 contingency table. The approach is then shown to be useful in assessing the effect of two approaches to moderating milk urea concentration. Firstly, milk urea content can be monitored as it falls due to reduced feed protein content, and this fall can be arrested when milk protein content starts to decline relative to the value expected for the herd at any lactation stage. Secondly, by providing a dietary intervention aimed at increasing the availability of metabolic energy in the last month before calving, udder development can be augmented, leading to greater protein secretion capacity, meaning greater utilisation of circulating amino acids, and thus more limited substrate for urea synthesis. Thus, the changing impact of differing nutrition practices on dairy herd nitrogen excretion to environment can be followed with daily precision. In principle this approach can provide useful insights into a wide range of practical management interventions.

Development of a new reference material for accurate measurements of lithium in Li-clays.

Currently, there are no national and international certified reference materials (CRM) in lithium clays that can make reliable and traceable lithium measurements for the International System of Units (SI). Hence, it is necessary to have references to meet the needs in terms of mining and activities that involve the use of lithium to favor the economy derived from its multiple uses and associated benefits in the exploration, exploitation, and handling of lithium ore. In this study, a candidate for reference material (RM) of Li in clays was developed and certified based on the provisions of ISO 17034:2016 and ISO Guide 35:2017. Different mass sizes of the RM (0.05, 0.1, and 0.25 g) were used to evaluate homogeneity. An isochronous study (short-term stability) was carried out in the assessment of stability, influenced by the effects of transport at different temperatures (20, 40, and 50 °C) for a determined time of 6 weeks, in addition to a classic (long-term) study for 19 weeks. The sample was treated using microwave-assisted acid digestion and Li measurements were performed using the analytical technique of Flame Atomic Absorption Spectrometry (FAAS). The CRM is homogeneous for the sample mass sizes of 0.05 and 0.1 g, and the mass fraction of w(Li) was stable in the RM for temperatures of 20, 40, and 50 °C. The determined period of validity was 3 years.

Ergonomic design of computer laboratory furniture: Mismatch analysis utilizing anthropometric data of university students.

Many studies have shown that ergonomically designed furniture improves productivity and well-being. As computers have become a part of students' academic lives, they will continue to grow in the future. We propose anthropometric-based furniture dimensions that are suitable for university students to improve computer laboratory ergonomics. We collected data from 380 participants and analyzed 11 anthropometric measurements, correlating them with 11 furniture dimensions. Two types of furniture were found and studied in different university computer laboratories: (1) a non-adjustable chair with a non-adjustable table and (2) an adjustable chair with a non-adjustable table. The mismatch calculation showed a significant difference between existing furniture dimensions and anthropometric measurements, indicating that 7 of the 11 existing furniture dimensions need improvement. The one-way ANOVA test with a significance level of 5% also showed a significant difference between the anthropometric data and existing furniture dimensions. All 11 dimensions were determined to match students' anthropometric data. The proposed dimensions were found to be more compatible and showed reduced mismatch percentages for nine furniture dimensions and nearly zero mismatches for seat width, backrest height, and under the hood for both males and females compared to the existing furniture dimensions. The proposed dimensions of the furniture set with adjustable seat height showed slightly improved match results for seat height and seat-to-table clearance, which showed zero mismatches compared with the non-adjustable furniture set. The table width and table depth dimensions were suggested according to Barnes and Squires' ergonomic work envelope model, considering hand reach. The positions of the keyboard and mouse are also suggested according to the work envelope. The monitor position and viewing angle were proposed according to OSHA guidelines. This study suggests that the proposed dimensions can improve comfort levels, reducing the risk of musculoskeletal disorders among students. Further studies on the implementation and long-term effects of the proposed dimensions in real-world computer laboratory settings are recommended.

Experimental insights into the stability of graphene oxide nanosheet and polymer hybrid coupled by ANOVA statistical analysis.

The synergistic potential of using graphene oxide (GO) nanosheets and hydrolyzed polyacrylamide (HPAM) as GO enhanced polymer hybrid (GOeP) for enhancing oil recovery (EOR) purposes has drawn attention. However, the hybridization method and stability of GOeP have not been comprehensively studied. To cover this gap, the current study evaluates the stability of GOeP under different conditions, including temperatures such as 60 and 80 °C, high and low salinities, and the presence of Mg2+ ions (6430 and 643 ppm). Hence, GO nanosheets were synthesized and characterized through XRD, Raman, FTIR, and DLS techniques. The performance of five preparation methods was assessed to determine their ability to produce stable hybrids. Zeta potential and sedimentation methods, coupled with the ANOVA statistical technique, were used for measuring and interpreting stability for 21 days. Results revealed that the stability of GOeP in the presence of brine is influenced by hydrolyzation duration, the composition of the water used in polymer hydrolyzation, the form of additives (being powdery or in aqueous solution), and the dispersion quality, including whether the GO solution was prediluted. The results revealed that the positive impact of higher temperatures on the long-term stability of GOeP is approximately seven times less significant than the reduction in stability caused by salinity. Under elevated salinity conditions, a higher Mg2+ concentration led to an 80% decrease in long-term stability, whereas the temperature impact was negligible. These findings highlight the potential of GOeP for EOR applications, offering insights into optimizing stability under challenging reservoir conditions.

Field Exploration for Colony Selection: Evaluating Hygienic Behavior in Apis cerana indica Colonies.

Hygienic behavior (HB) emerges as a pivotal trait, impacting colony resistance to diseases. This study aimed to understand the behavioral traits of Apis cerana indica colonies, with a focus on HB and other key characteristics crucial for colony health, and to screen and identify colonies with superior hygienic behavior and better performance to combat prevailing diseases and pests. This research spans a comprehensive field analysis with different seasons and locations, encompassing the distinct environmental and management factors that influence honey bee behavior. The inclusion of A. cerana indica colonies from various locations provides a novel perspective, offering valuable insights regarding the hygienic behavior of A. cerana indica. Several statistical analyses, including descriptive statistics, principal component analysis (PCA), and Aligned Rank Transformation-Analysis of Variance (ART-ANOVA) for repeated measures, shed light on the distribution of hive metrics, emphasizing the significance of considering seasonality and location-specific factors. PCA highlights unique characteristics in Tirupur and Coimbatore colonies, while correlation analyses uncover relationships among HB, honey, pollen, brood area, and adult population. Moreover, the study's nuanced findings gave the status of hygienic behavior of A. cerana indica colonies and identified colonies with better colony performance, which will be useful for future breeding programs with A. cerana indica.

Analysis and optimization of machining parameters of AZ91 alloy nanocomposite with the Influences of nano ZrO2 through vacuum diecast process.

The magnesium alloy composite is a vital material for automotive applications due to its features like high stiffness, superior damping resistance, high strength, and lightweight. Here, the motto of research is to establish the AZ91 alloy nanocomposite with the exposures of 0, 1, 3, and 5 volume percentages (vol%) of nano zirconium dioxide (ZrO2) particles (50nm) through fluid stir metallurgy route associated with 1x105 Pa vacuum die cast process. Exposures on structural morphology, hardness, and impact toughness of composite are analyzed and identified as the nano AZ91 alloy composite enclosed with 5vol% is homogenous particle dispersion, enhanced hardness (97.6HV), and optimum toughness of 21.2J/mm2. However, composite faces machining difficulties due to the hard abrasive particles with higher hardness, resulting in tool wear. This experiment predicts the optimum mill parameters during the end mill operation of magnesium alloy nanocomposite (AZ91/5vol%) by using a tungsten carbide coated end mill cutter to attain the maximum metal removal rate with low surface roughness and tool wear analyzed via the general linear model (GLM) ANOVA approach. The input conditions for end milling operation vary, like feed rate (0.1 -0.4mm/rev), depth of cut (0.05 -0.2mm), and spindle speed (250-1000rpm). During the ANOVA GLM approach, the L16 design experiment is fixed for further interaction analysis. The results predicted by the depth to cut and feed rate were dominant and played a major role in deciding the tool wear, surface roughness, and MRR.

Individual factors determine landing impacts in rested and fatigued cheerleaders.

High vertical ground reaction forces (VGRF) during landings following acrobatic elements in artistic gymnastics is associated with trunk and lower extremity injury risk. As similar data regarding injury risk factors in cheerleading are scarce, the purpose of this study was to assess VGRF in pop-off dismounts of rested and fatigued flyers in cheerleaders. Fifteen German cheerleaders were recruited for this study, including seven female flyers and eight male bases. It was expected that performance would change in fatiguing athletes, potentially increasing the risk for injuries. However, neither the mean VGRF (rested: 6.0 ± 1.9 BW, fatigued: 6.2 ± 1.3 BW, overall range: 2.1-14.9 BW) nor the individual VGRF-time courses of the flyers changed significantly after the workout. Instead, we show that the flyers' ability to land - but not the bases' ability to catch - significantly influences the maximum and time-resolved impacts.

Groundwater quality evaluation of the weathering mantle in crystalline basement aquifer system, southern Brazil.

Groundwater is the main source of water for more than 2 billion people worldwide. In southern Brazil, the Crystalline Basement Aquifer System is composed of strategic groundwater reservoirs. Groundwater is mostly taken from shallow wells, and it is often used without any treatment, which poses a risk to public health. The present study aims to evaluate shallow groundwater quality and the geochemistry of shallow and deep groundwater located in the municipality of Canguçu, southern Brazil. The physicochemical and microbiological parameters of groundwater samples collected from shallow wells were monitored and analyzed using ANOVA variance analysis and water quality index (CCME WQI) approaches. Also, the results were compared with secondary data from deep wells. The monitored shallow wells had thermotolerant coliforms, Escherichia coli, pH, potassium, manganese, iron, and nitrate in disagreement with the guidelines of the World Health Organization. Moreover, variance analysis showed that the parameters temperature, dissolved oxygen, pH, chloride, and magnesium were the most influenced by seasonal variations. According to the CCME WQI, most samples had good quality (60%), 28% had fair quality, and 12% had poor quality. In addition, the field campaigns with higher precipitation rates also presented fair quality. Therefore, most of the shallow groundwater quality is affected by surface pollutants from the urban area, aggravated in rainy periods. Whereas deep groundwater is influenced by geochemistry mechanisms. The results revealed the risk of water consumption for public health and the urgent need for better maintenance of these wells and water treatment implementation.

Process parameters optimization of EDM for hybrid aluminum MMC using hybrid optimization technique.

This study explores how machining parameters affect Surface Roughness (SR), Tool Wear Rate (TWR), and Material Removal Rate (MRR) during Electrical Discharge Machining (EDM) of a hybrid aluminum metal matrix composite (AMMC). The composite includes 6 % Silicon carbide (SiC) and 6 % Boron carbide (B4C) in an Aluminum 7075 (Al7075) matrix. A combined optimization approach was used to balance these factors, evaluating Pulse ON time, Current, Voltage, and Pulse OFF time. Response Surface Methodology (RSM) optimized single responses, while multi-response optimization employed a hybrid method combining the Entropy Weight Method (EWM), Taguchi approach, TOPSIS, and GRA. Analysis of Variance (ANOVA) assessed parameter significance, revealing substantial impacts on SR, MRR, and EWR. Based on TOPSIS and GRA, optimized parameters achieved a desirable balance: high MRR (0.4172, 0.5240 mm³/min), minimal EWR (0.0068, 0.0103 mm³/min), and acceptable SR (10.3877, 9.1924 µm) based on EWM-weighted priorities. Confirmation experiments validated a 15 % improvement in the closeness coefficient, and a 16 % improvement in the Grey relational grade, which considers combined SR, MRR, and EWR performance. Scanning Electron Microscope (SEM) analysis of surfaces machined with optimal parameters showed minimal debris, cracks, and no recast layer, indicating high surface integrity. This research enhances EDM optimization for AMMC, achieving efficiency in machining, minimizing tool wear, and meeting surface quality requirements.

Quantitative Prediction and Analysis of Rattle Index Using DNN on Sound Quality of Synthetic Sources with Gaussian Noise.

This study researched the prediction of the BSR noise evaluation quantitative index, Loudness N10, for sound sources with noise using statistics and machine learning. A total of 1170 data points was obtained from 130 automotive seats measured at 9-point positions, with Gaussian noise integrated to construct synthetic sound data. Ten physical quantities related to sound quality and sound pressure were used and defined as dB and fluctuation strength, considering statistical characteristics and Loudness N10. BSR quantitative index prediction was performed using regression analysis with K-fold cross-validation, DNN in hold-out, and DNN in K-fold cross-validation. The DNN in the K-fold cross-validation model demonstrated relatively superior prediction accuracy, especially when the data quantity was relatively small. The results demonstrate that applying machine learning to BSR prediction allows for the prediction of quantitative indicators without complex formulas and that specific physical quantities can be easily estimated even with noise.

Mixed reality technology for older adults: Evaluating the impact of a novel virtual humanoid coach in a community-based physical exercise program in the Philippines.

Physical inactivity among older adults remains a global burden, leading to a variety of health challenges and even mortality. This study evaluated the impact of a novel virtual humanoid coach-driven physical exercise program among older adults. A non-randomized (quasi) experimental research was conducted in two community senior centers. The recruited participants (n = 130) were primarily female older adults with a mean age of 66.40 and agreed to be purposively assigned either experimental or control groups. Trained healthcare providers performed health assessments in three time points using valid and reliable tools. Descriptive statistics, t-tests, and RM-ANOVA were used to quantitatively analyze the data using SPSS version 22. There are significant mean differences between the groups across all functional capacity assessments and Time 2-3 assessment of sleep quality. RM-ANOVA revealed significant differences in physical assessment over time between the two groups. The analyses of time and group interaction revealed significant improvement in health assessments among the members of the mixed reality group compared to the traditional groups. The impact of virtual coaches in community-based enhancing physical activity programs is comparable to the traditional mode and introduces a novel approach to promoting physical activity among older adults.

How strenuous is esports? Perceived physical exertion and physical state during competitive video gaming.

Introduction: Esports or competitive video gaming is a rapidly growing sector and an integral part of today's (youth) culture. Esports athletes are exposed to a variety of burdens, that can potentially impact an athlete's health and performance. Therefore, it is important that esports athletes are aware of (physical) burden and exertion associated with esports. For this purpose, a study was conducted to evaluate the influence of competitive video gaming on the perceived physical exertion and the perceived physical state (PEPS). Methods: Thirty-two healthy male esports athletes participated in two competitive video gaming sessions lasting 90-120 min, interrupted by a 10-minute passive sitting break. Repeated measures of perceived physical exertion (Borg Categorial Ratio-10 scale) and perceived physical state were recorded before, during, and after each video game session. Repeated measures ANOVA and Friedman's test were used for statistical analysis. Results: The results showed a significant difference in all dimensions of the PEPS (p < 0.05) as well as in Borg scale (p < 0.001). Post-hoc tests revealed significant increases in Borg scale between baseline measurements (T0: 1.0 ± 1.0) and after the first competitive video gaming session (T1: 2.4 ± 1.3, p < 0.001), as well as after the second competitive video gaming session (T3: 3.0 ± 1.7, p < 0.001). Furthermore, there was a significant reduction in perceived exertion between the measurement time after the first competitive video gaming session (T1) and the break (T2: 1.3 ± 1.2, p < 0.001). The PEPS dimensions activation, trained, and mobility showed similar significant changes in post-hoc analysis. Discussion: The results indicate that the perceived physical burden significantly increases during esports participation. As the duration of competitive video gaming extends, the perceived physical state decreases and perceived physical exertion increases. A passive break between two video game sessions can at least partially restore physical exertion and physical state. However, this break neither returns the scores to their baseline levels nor prevents a further decline in scores during the second video game session. Over time and with a lack of observation, this could result in health and performance limitations.

Optimizing Prostate Imaging Practices in Saudi Arabian Hospitals: A Comprehensive Analysis of PI-RADS Compliance in Multiparametric MRI

BACKGROUND: Prostate cancer, a significant contributor to male cancer mortality globally, demands improved diagnostic strategies. In Saudi Arabia, where the incidence is expected to double, this study assessed the compliance of multiparametric MRI (mpMRI) practices with Prostate Imaging-Reporting and Data System version 2 (PI-RADS v2) guidelines across diverse healthcare institutions. METHODS: A survey was distributed to the radiology departments of all tertiary referral hospitals in Saudi Arabia (n=60) to assess their compliance with the technical specifications outlined in PI-RADS v2. Statistical analysis included chi-square, Fisher exact, ANOVA, and Student t-tests to examine the collected data. RESULTS: The study revealed an overall commendable compliance rate of 95.23%. However, significant variations were observed in technical parameters, particularly between 1.5 Tesla and 3 Tesla scanners and tertiary versus non-tertiary hospitals. Notable adherence in certain sequences contrasted with discrepancies in T2-weighted and diffusion-weighted imaging parameters. CONCLUSION: These findings underscore the need for nuanced approaches to optimize prostate imaging protocols, considering field strength and institutional differences. The study contributes to the ongoing refinement of standardized mpMRI practices, aiming to enhance diagnostic accuracy and improve clinical outcomes in prostate cancer.

Integrated Wearable System for Monitoring Skeletal Muscle Force of Lower Extremities.

Continuous monitoring of lower extremity muscles is necessary, as the muscles support many human daily activities, such as maintaining balance, standing, walking, running, and jumping. However, conventional electromyography and physiological cross-sectional area methods inherently encounter obstacles when acquiring precise and real-time data pertaining to human bodies, with a notable lack of consideration for user comfort. Benefitting from the fast development of various fabric-based sensors, this paper addresses these current issues by designing an integrated smart compression stocking system, which includes compression garments, fabric-embedded capacitive pressure sensors, an edge control unit, a user mobile application, and cloud backend. The pipeline architecture design and component selection are discussed in detail to illustrate a comprehensive user-centered STIMES design. Twelve healthy young individuals were recruited for clinical experiments to perform maximum voluntary isometric ankle plantarflexion contractions. All data were simultaneously collected through the integrated smart compression stocking system and a muscle force measurement system (Humac NORM, software version HUMAC2015). The obtained correlation coefficients above 0.92 indicated high linear relationships between the muscle torque and the proposed system readout. Two-way ANOVA analysis further stressed that different ankle angles (p = 0.055) had more important effects on the results than different subjects (p = 0.290). Hence, the integrated smart compression stocking system can be used to monitor the muscle force of the lower extremities in isometric mode.

Multiple comparisons of treatment against control under unequal variances using parametric bootstrap.

In one-way analysis of variance models, performing simultaneous multiple comparisons of treatment groups with a control group may be of interest. Dunnett's test is used to test such differences and assumes equal variances of the response variable for each group. This assumption is not always met even after transformation. A parametric bootstrap (PB) method is developed here for comparing multiple treatment group means against the control group with unequal variances and unbalanced data. In simulation studies, the proposed method outperformed Dunnett's test in controlling the type I error under various settings, particularly when data have heteroscedastic variance and unbalanced design. Simulations show that power is often lower for the PB method than for Dunnett's test under equal variance, balanced data, or smaller sample size, but similar to or higher than for Dunnett's test with unequal variance, unbalanced data and larger sample size. The method is applied to a dataset concerning isotope levels found in elephant tusks from various geographical areas. These data have very unbalanced group sizes and unequal variances. This example illustrates that the PB method is easy to implement and avoids the need for transforming data to meet the equal variance assumption, simplifying interpretation of results.

Analysis of Face Milling of Hard Steel 55NiCrMoV7 by Studying Rough and Semi-Finished Machining and the Influence of Cutting Parameters on Macroscopic Chip Dimensions.

Hard milling is being increasingly used as an alternative to EDM due to its high productivity. The present paper presents the results of theoretical-experimental research on the face milling of hard steel 55NiCrMoV7. A comprehensive analysis of cutting temperatures and forces during single-tooth milling and a morphological examination of the resulting chips are conducted for roughing and semi-finishing operations. The temperature is analyzed in the chip formation area, and the detached chips and the cutting force are analyzed through their tangential, radial, and penetration components, depending on the contact angle of the cutter tooth with the workpiece. The analysis of chip morphology is carried out based on the dimensional and angular parameters of chip segmentation and their degree of segmentation. Based on the central composite design and the response surface method, it is shown that it is possible to mathematically model the dependence of the macroscopic dimensions of the detached chips on the cutting parameters. The determined process functions, the maximum chip curling diameter, and the maximum chip height allow for establishing the influence of the cutting parameters' values on the chips' macroscopic dimensions and, thus, guiding the cutting process in the desired direction.

Bayesian Analysis of Multi-Factorial Experimental Designs Using SEM.

Latent repeated measures ANOVA (L-RM-ANOVA) has recently been proposed as an alternative to traditional repeated measures ANOVA. L-RM-ANOVA builds upon structural equation modeling and enables researchers to investigate interindividual differences in main/interaction effects, examine custom contrasts, incorporate a measurement model, and account for missing data. However, L-RM-ANOVA uses maximum likelihood and thus cannot incorporate prior information and can have poor statistical properties in small samples. We show how L-RM-ANOVA can be used with Bayesian estimation to resolve the aforementioned issues. We demonstrate how to place informative priors on model parameters that constitute main and interaction effects. We further show how to place weakly informative priors on standardized parameters which can be used when no prior information is available. We conclude that Bayesian estimation can lower Type 1 error and bias, and increase power and efficiency when priors are chosen adequately. We demonstrate the approach using a real empirical example and guide the readers through specification of the model. We argue that ANOVA tables and incomplete descriptive statistics are not sufficient information to specify informative priors, and we identify which parameter estimates should be reported in future research; thereby promoting cumulative research.

Analyzing the long-term effects of e-glass mortar on sustainability and radiation shielding using ANOVA.

Significant investigations were performed on the use and impact on physical properties along with mechanical strength of the recycled and reused e-glass waste powder. However, it has been modeled how recycled display e-waste glass may affect the characteristics and qualities of dune sand mortar. This study investigates the long-term feasibility of using recycled display e-glass waste as a partial substitute for dune sand at varying percentages (5%, 10%, 15%, and 20%). The main focus is on evaluating its effectiveness in radiation shielding, strength properties, and durability for long-term development under the heating environmental process. Statistical analyses, including analysis of variance, are used to assess the significance of factors and their interactions on these characteristics. Additionally, a regression equation derived from the model offers insights into the quantitative relationship between the factors and properties. The results of the experiments led to the conclusion that the most effective proportion of e-glass waste to include in mortar is 20%, with the weight of dune sand. Including e-glass waste, they significantly increased the five characteristics of the mortar, making it suitable for high-strength mortar applications continue up to 68 MPa. The ANOVA model used in this study was trained using the same experimental research design and was critical in predicting the properties of the mortar. The model produced an accurate result with an R2 value greater than 0.99. E-glass replacements exhibit remarkable radiation shielding, characterized by pozzolanic activity and superior internal bonding due to its compact texture, contributing to enhanced long-term strength.

A comprehensive study on engineering and sustainability characteristics with emphasizing on 3R's approach in building construction.

The study assesses the mechanical efficiency, long-lasting characteristics, microstructure, and sustainability of sustainable concrete (SC) samples through several optimization methods, emphasizing the significance of the 3Rs (recycle, reuse, reduce) approach in the construction sector. The study uses advanced techniques like the Taguchi method, grey relational analysis (GRA), analysis of variance (ANOVA), and signal-noise ratio (SNR) to optimize parameters affecting the performance of SC. In this study, the properties of SC are assessed by considering various parameters. These parameters include the use of 10 %, 20 %, and 30 % of ground granulated blast furnace slag (GGBFS) as a replacement for fly ash (FA). Additionally, six different binder contents ranging from 300 kg/m3 to 600 kg/m3 are examined. The study also investigates three different molarities of sodium hydroxide (NaOH) (8 M, 12 M, and 16 M), three different ratios of alkaline activators (AA) (1.5, 2.0, and 2.5), three different AA to-binder ratios (0.30, 0.35, and 0.40), and curing temperature (CT) of 30 °C, 60 °C, and 90 °C. The study includes fresh properties such as fresh density (FD) and slump, mechanical properties such as tensile strength (TS), flexural strength (FS), modulus of elasticity (MOE), and compressive strength (CS), and durability studies such as dry density (DD), impact strength, water absorption (WA), and sorptivity. The blended proportions were obtained using the Taguchi method. The study shows that GGBFS accelerates geopolymerization in FA-based concrete, reducing setting time and early-age CS. FA is crucial for setting time, workability, and CS enhancement. GGBFS increases the densities of fresh and hardened concrete, with a highly correlated increase, allowing accurate hardened density prediction with a coefficient of 0.9057. The CS of the cube SC surpassed 40 MPa, irrespective of variables such as the AA ratio, CT, and NaOH molarity. The trail mix with a binder concentration of 600 kg/m3, 30 % GGBFS content, 12 M NaOH molarity, 1.5 AA ratio, 0.35 AA to binder ratio, and 90 °C CT exhibited the greatest strength. Mixtures containing 10 % GGBFS can attain a CS above 30 MPa after 28 days, making them suitable for structural purposes. The T18 mix exhibited a compact Calcium (alumino) silicate hydrate (C-A-S-H) and N-A-S-H gel, whereas the T3 mix displayed a varied and permeable structure. The study used GRA, ANOVA, and SNR methods to analyze properties varying by six variables, finding GGBFS content as the most influencing parameter. The study found that the SC had a lower sustainability score than the OPC mix, but had better energy efficiency.

Optimization of traction parameters for lumbar scoliosis.

BACKGROUND: Scoliosis is a high incidence disease that endangers the physical and mental health of adolescents. Traction therapy, as a conservative treatment plan, is helpful to improve the recovery speed of patients by studying the influence of different traction factors on the therapeutic effect. METHODS: Based on the thin layer CT data of the lumbar spine of a 16-year-old patient with scoliosis, Mimics21.0 was used to extract the 3D digital model, and Geomagic Wrap2021 was used to perform the smooth surface. After that, SolidWorks was used to manually construct the structures, such as the intervertebral disc, and Ansys17.0 was used to add constraints, ligaments, and other features. Three-factor ANOVA was carried out after an orthogonal experiment that considered traction mode, traction angle, and traction force was finished. RESULTS: ① A three-dimensional biomechanical model of lumbar scoliosis was created. ② The model's correctness was confirmed by comparing it to the corpse and other finite element models, as well as by verifying it under a range of working settings. ③ Traction force (P = 0.000), traction angle (P = 0.000), the interaction between traction force and traction angle (P = 0.000), and the interaction between traction mode and traction angle (P = 0.045) were all significant. ④ The interaction between traction force and traction angle has the most significant effect on Cobb, and traction with a certain angle is better than traditional axial traction. ⑤ Traction mode is not significant, but the interaction between traction mode and traction angle is significant. CONCLUSIONS: A certain angle of traction can aid in improving outcomes and the traction force can be suitably decreased in the clinical formulation of the traction plan. The uniformity of correcting effect is more favorable when higher fixation techniques like positive suspension or traction bed traction are used, as opposed to overhanging traction.