Position Variables Research Articles

154Physical inactivity, socioeconomic position and type 2 diabetes in Nepal: a structural equation modelling analysis

Abstract Background Type 2 diabetes mellitus (T2DM) is emerging as a major public health challenge in Nepal. Behavioural, social and economic changes are likely to play a part in the rise of this chronic disease, as they are in many developing countries. A better understanding of the relationship between physical activity (PA), social and economic factors and T2DM can inform the design of prevention programs. Methods This study analysed data from 1977 Nepalese adults aged 40-69 years from the 2013 WHO STEPS survey. Socioeconomic position was determined based on education, occupation and ethnic group. Participants’ fasting blood glucose level was used to ascertain their diabetes status. Structural equation modelling was conducted to identify the regression pathways between PA, socioeconomic position, anthropometric and metabolic variables and T2DM. Results The overall prevalence of T2DM was 9% with almost double the burden among urban residents (17 %). Socioeconomic position (0.338), waist circumference (0.250), triglycerides (0.115) and hypertension (0.129) had a statistically significant direct effect on T2DM. PA had an indirect effect on T2DM mediated by waist circumference (-0.015). The indirect effects of socioeconomic position on T2DM were mediated by body mass index, waist circumference, triglycerides and total cholesterol. Conclusion Policies and programs to address T2DM in Nepal should address the factors contributing to unhealthy weight status, particularly among those of higher socioeconomic status. Key message Among Nepalese adults, higher socioeconomic position has a significant direct effect on T2DM, while both PA and higher socioeconomic position have significant indirect effects.

Healthy aging determinants and disability among older adults: SABE Colombia.

ABSTRACTObjective.To identify the main factors associated with disability in older adults in Colombia, adjusted according to structural and intermediary determinants of healthy aging.Methods.This study used cross-sectional data from 23 694 adults over 60 years of age in the SABE Colombia nationwide survey. Structural determinants such as demographic and socioeconomic position variables were analyzed. Intermediary variables were classified into three blocks: intrinsic capacity, physical and built environment, and health care systems. Data analysis employed multivariate logistic regression.Results.The prevalence of overall disability was 21% for activities of daily living, 38% for instrumental activities of daily living, and 33% for mobility disability. Disability was associated with sociodemographic structural determinants such as older age, female sex, rural residence, never married/divorced, living alone, low educational level, and Indigenous/Black ethnicity. With regard to determinants of socioeconomic position, net low income, poor socioeconomic stratum, insufficient income perception, and a subsidized health insurance scheme exerted a major influence on disability. Intermediary determinants of intrinsic capacity, such as poor self-rated health, multimorbidity, low grip strength, sedentary lifestyle, early childhood economic adversity, no social support, and no participation in activities, were significantly associated with disability.Conclusions.Actions that affect the main factors associated with disability, such as reducing health inequities through policies, strategies, and activities, can contribute significantly to the well-being and quality of life of Colombian older adults.

UAV Formation Obstacle Avoidance Control Algorithm Based on Improved Artificial Potential Field and Consensus

Aiming at the problem of UAV formation's obstacle avoidance and the consensus of position and velocity in a 3D obstacle environment, a novel distributed obstacle avoidance control algorithm for cooperative formation based on the improved artificial potential field (IAPF) and consensus theory is proposed in this paper. First, the particle model of the UAV and the dynamic model of the second-order system are established, and the topological structure of the communication network of the system is described with the knowledge of graph theory. Second, the attractive potential field function containing the coordination gains factor, the repulsive potential field function containing the influence factor of the repulsive force and the planning angle, and the potential field function between the UAVs containing the communication weight are defined. Then, the variables of position and velocity in the consensus protocol are improved by the reference vector of the formation center and the expected velocity, respectively, and a new formation obstacle avoidance control protocol is designed by combining the IAPF and the theory of consensus. Finally, the Lyapunov function is used to prove the stable convergence of the algorithm. The simulation results show that this method can not only prevent the UAV from colliding with each other while avoiding static and dynamic obstacles but also enable the UAV to quickly restore the expected formation and achieve the consensus of the relative distance, relative height, and velocity.

Innovative Non-Irradiating and Non-Invasive Per Fraction Control System in Radiotherapy: Surface-Guided Radiation Therapy Experience of Casablanca Cancer Center

Purpose: Evaluation of the added value of radiotherapy guided by the cutaneous
 
 surface in the positioning and monitoring of the radiotherapy
 
 Patients and Methods: This study included 21 consecutive patients treated with an
 
 accelerator dedicated to "True Beam®" stereotactic radiotherapy whose sessions were
 
 monitored by an Optical Surface Monitoring System: "OSMS®". Excluded from our
 
 study were treatments controlled exclusively by radiological imaging (IGRT).
 
 Positioning variabilities were compared between conventional imaging and skin
 
 surface infrared (OSMS) monitoring. Conventional imaging was in the form of
 
 standard radiography (KV) performed during the treatment session or three-
 
 dimensional by a series of Cone Beam computerized tomography (CBCT) scanned
 
 images made at the beginning and end of The total time of the session and
 
 the positioning variability’s in the 3 planes were
 
 14
 
 Results: The results of our study show that the cutaneous surface monitoring allowed
 
 to obtain a faster alignment of the patient with an improvement in the overall time of
 
 the session with a mean at 32% [14.5-49.27%], likewise a sub-millimeter positioning
 
 quality for all locations with a median longitudinal distance of 0.02 cm [0-0.66], 01
 
 cm verticality [0-0.32] and laterality 0.02 cm [0-0.77] This benefit is significantly
 
 greater for cerebral and Head and neck’s localizations
 
 21
 
 Conclusion: Optical Surface Monitoring System (OSMS®) is a non-invasive and non-
 
 irradiating means that allows reliable and fast

Conservative Potentials for a Lattice-Mapped Coarse-Grained Scheme.

The conservative potential, arising from a coarse-grain (CG) mapping scheme for nonbonded atomistic particles, is studied. This is a bottom-up approach from first-principles that maps atomistic particles to fluid element-like subcells whose centers lie on a regular, cubic lattice. Unlike standard CG mapping schemes, the current one uses dynamic labeling which on-the-fly changes the CG labels of the particles. The subcells can also be different sizes and shapes, in principle. Equilibrium atomistic molecular dynamics trajectories for different Lennard-Jones fluids are calculated and converted to CG ones, from which CG probability distribution functions are calculated. Correlation studies show position and mass CG variables are uncoupled in a given subcell, as are different vector components of position. Furthermore, the strongest coupling occurs with neighboring cells in specific directions, and the resulting distribution is well described by a multivariate Gaussian. This implies the CG potential has a generalized quadratic form, whose derivative can be determined analytically. A microscopic rationalization is provided for the signs and relative magnitudes of different correlation coefficients, and in some cases, a connection is made with bulk properties of the fluid. We argue the generalized quadratic form should be robust to changes in the particulars of the CG scheme, as well as the nature of the atomistic intermolecular potential. Only a few potential parameters need to be calculated from the underlying atomistic system. This is significant because it indicates the transferability of this form to other, more complex systems. This transferability will be tested in future work, where mapping schemes with fuzzy boundaries will be considered.

The impact of match venue on performance indicators and tactical behaviour in youth soccer players

ABSTRACT This study analysed the effects of changing the match venue on match-related physiological, physical, and tactical responses on youth soccer age-dependent. Fifty outfield U-17 (n = 25) and U-20 (n = 25) youth players were monitored over the 2020 competitive season. Players’ and teams’ match demands were monitored by GPS devices, allowing the generation of physiological (heart rate), physical (distances, sprints, and accelerations), and tactical (positional variables) match-related variables. These variables were compared by a two-way analysis of variance (age category x match venue). The analysis indicated that the effect of match venue on players’ and teams’ responses was age-dependent. Specifically, higher heart rate, total distance, distance in all speed thresholds, and sprints were observed in home matches, although this effect was observed only in the U-17 group (except for the heart rate and total distance). Younger players also presented higher exploratory tactical behaviour, while less spatial exploration was observed in home matches. Also, teams adopted a more in-depth tactical positioning in away matches. We conclude that older, and hence more experient, youth soccer players tend to adopt more stable physiological, physical, and tactical responses in home and away matches, although the responses and the performance tend to be higher in home matches.

Motion Analysis of Match Play in U14 Male Soccer Players and the Influence of Position, Competitive Level and Contextual Variables.

This study aimed to investigate match running performance in U14 male soccer players in Norway, and the influence of position, competitive level and contextual factors on running performance. Locomotion was monitored in 64 different U14 players during 23 official matches. Matches were played at two different competitive levels: U14 elite level (n = 7) and U14 sub-elite level (n = 16). The inclusion criterion was completed match halves played in the same playing position. The variables’ influence on match running performance was assessed using mixed-effect models, pairwise comparisons with Bonferroni correction, and effect size. The results showed that the U14 players, on average, moved 7645 ± 840 m during a match, of which 1730 ± 681 m (22.6%) included high-intensity running (HIR, 13.5–18.5 km·h−1) and sprinting (>18.5 km·h−1). Wide midfielders (WM) and fullbacks (FB) covered the greatest sprint distance (569 ± 40 m) and, in addition to the centre midfield position (CM), also covered the greatest total distance (TD) (8014 ± 140 m) and HIR distance (1446 ± 64 m). Centre forwards (CF) performed significantly more accelerations (49.5 ± 3.8) compared other positions. TD (7952 ± 120 m vs. 7590 ± 94 m) and HIR (1432 ± 57 m vs. 1236 ± 43 m) were greater in U14 elite-level matches compared with sub-elite matches. Greater TD and sprint distances were performed in home matches, but, on the other hand, more accelerations and decelerations were performed in matches played away or in neutral locations. Significantly higher TD, HIR and sprinting distances were also found in lost or drawn matches. In conclusion, physical performance during matches is highly related to playing position, and wide positions seem to be the most physically demanding. Further, competitive level and contextual match variables are associated with players’ running performance.

Comparison of Emotional Intelligence and Mental Toughness of Youth Soccer Players in Terms of Position and Soccer Experience Variables

The aim of this research was the comparison of mental toughness (MT) and emotional intelligence (EI) of youth soccer players based on their soccer experience and player positions. Participants of the study composed of totally 458 youth male soccer players who are between 17-20 years old (x̅=17,75) and 1-14 (x̅=7,22) years of soccer experiences. Data obtained by using demographic questionnaire, Sport Mental Toughness Questionnaire (MTIS), and Trait Emotional Intelligence Questionnaire (TEIQ). According to homogeneity and normality test results, The One-way ANOVA was used for the analysis of data. The findings demonstrated that there is no significant difference between sports age and position variables in terms of MT. In addition, results indicated that soccer experience make differences on well-being and emotionality subscales of TEIQ. Besides, according to player positions and TEIQ subscales, there were significant differences between sociability. In conclusion, soccer experience is one of the factors that influence well-being and emotionality positively. Moreover, it observed that midfield players’ social abilities are higher than winger players and defensive midfield players.

Reliability-based Design Optimization of Laminated Composite Structures under Delamination and Material Property Uncertainties

Delamination is a major type of defects from manufacturing process in laminated composite structures, exhibiting uncertain characteristics which are represented by mixed random variables of continuous in-plane position and delamination size, as well as discrete through-the-thickness position, which should be considered in the design phase of composite structures. Thus, this paper presents a reliability-based design framework for optimal design of composite stacking sequence, for the first time to consider both delamination and material property uncertainties from manufacturing process. Mixed continuous-discrete random variables are involved, and a reliability analysis method is newly proposed to tackle this mixed-variable problem, maintaining high levels of both accuracy and efficiency. The formula of total probability is first employed to formulate the reliability constraint so that discrete and continuous random variables are decoupled; Monte Carlo simulation is then used for reliability analysis with respect to continuous random variables, and a surrogate modelling approach based on Gaussian process regression model is adopted to reduce computation costs. As design variables of ply angles are limited to a discrete set, a genetic algorithm with some proposed improvements is used to handle discrete design variables. Consequently, an optimization framework is devised for composite laminate design under uncertainties from manufacturing process, which is verified via case studies of a cantilever composite plate and can also be extended as a general solution for other composite laminates. With integrated consideration of manufacturing limitations and imperfections as well as structural performances, the presented framework provides a valuable tool in composite structure design.

A Quantized Hill’s Dynamical System

In this paper, we present a modified version of Hill’s dynamical system that is called the quantized Hill’s three-body problem in the sense that the equations of motion for the classical Hill’s problem are now derived under the effects of quantum corrections. To do so, the position variables and the parameters that correspond to the quantum corrections of the respective quantized three-body problem are scaled appropriately, and then by taking the limit when the parameter of mass ratio tends to zero, we obtain the relevant equations of motion for the spatial quantized Hill’s problem. Furthermore, the Hamiltonian formula and related equations of motion are also derived.

Evaluating the Performance of Hyperspectral Leaf Reflectance to Detect Water Stress and Estimation of Photosynthetic Capacities

Advanced techniques capable of early, rapid, and nondestructive detection of the impacts of drought on fruit tree and the measurement of the underlying photosynthetic traits on a large scale are necessary to meet the challenges of precision farming and full prediction of yield increases. We tested the application of hyperspectral reflectance as a high-throughput phenotyping approach for early identification of water stress and rapid assessment of leaf photosynthetic traits in citrus trees by conducting a greenhouse experiment. To this end, photosynthetic CO2 assimilation rate (Pn), stomatal conductance (Cond) and transpiration rate (Trmmol) were measured with gas-exchange approaches alongside measurements of leaf hyperspectral reflectance from citrus grown across a gradient of soil drought levels six times, during 20 days of stress induction and 13 days of rewatering. Water stress caused Pn, Cond, and Trmmol rapid and continuous decline throughout the entire drought period. The upper layer was more sensitive to drought than middle and lower layers. Water stress could also bring continuous and dynamic changes of the mean spectral reflectance and absorptance over time. After trees were rewatered, these differences were not obvious. The original reflectance spectra of the four water stresses were surprisingly of low diversity and could not track drought responses, whereas specific hyperspectral spectral vegetation indices (SVIs) and absorption features or wavelength position variables presented great potential. The following machine-learning algorithms: random forest (RF), support vector machine (SVM), gradient boost (GDboost), and adaptive boosting (Adaboost) were used to develop a measure of photosynthesis from leaf reflectance spectra. The performance of four machine-learning algorithms were assessed, and RF algorithm yielded the highest predictive power for predicting photosynthetic parameters (R2 was 0.92, 0.89, and 0.88 for Pn, Cond, and Trmmol, respectively). Our results indicated that leaf hyperspectral reflectance is a reliable and stable method for monitoring water stress and yield increase, with great potential to be applied in large-scale orchards.

When and how do elite soccer players sprint in match play? A longitudinal study in a professional soccer league

ABSTRACT The aims of this study were to examine the periods in which the maximum speed actions occurred during elite soccer matches and analyse these actions considering the effect of playing position and different contextual variables. Performance-related variables (VMAX: maximum speed; Vo: starting speed; SPD: sprinting distance; ACCMAX: maximum acceleration; DECMAX: maximum deceleration) and sprint-related contextual variables (trajectory, ball possession, role, field area in which the action occurred) from each maximum speed action were collected. The first 15 minutes of each match half elicited most maximum speed actions (44.6% of cases), regardless of playing position (likelihood ratio, LR=13.95; p=0.95). However, playing position had a significant effect on the role of the action (Chi-Squared, χ2=50.68; p=0.001) and the field area in which the sprint occurred (χ2=26.54; p=0.001). Regarding the effect of different contextual variables on the sprint-related performance variables, no significant effect from any contextual variable on ACCMAX, DECMAX or Vo was found (p > 0.05). Nevertheless, the contextual variables had a significant effect on SPD (from ball possession: sprints without ball > sprints with ball; trajectory: non-linear sprints > linear sprints; role: offensive sprints > defensive sprints) and VMAX (from ball possession: sprints without ball > sprints with ball; playing position: midfielders < other positions).

Designing facilitated task constraints for different age groups in soccer: The impact of floaters’ rules

This study compared the influence of changing floaters’ rules on player positioning in small-sided games (SSG) played by different age groups. A total of 48 youth soccer players (24 U-13 and 24 U-14) took part in the study, playing three different SSGs: regular 3vs3, 1-floater condition (one floater playing for both teams), and 2-floater condition (one floater per team, with alternate participation). Positional data were collected by 5 Hz GPS devices, generating individual (spatial exploration index) and collective (team’s length, width, length per width ratio, and stretching index) positional variables. The results revealed that the 2-floater format significantly reduced the length (p = 0.001), and both formats with floaters increased the width (p &lt; 0.001). Also, the 1-floater format presented the lowest stretching index (p &lt; 0.001). Concerning age-group differences, older players presented higher values of length (p &lt; 0.001), length per width ratio (p &lt; 0.001), and spatial exploration index (p &lt; 0.001) than their younger counterparts. The 2-floater SSG format is a more facilitated and simplified version of numerically unbalanced SSGs, which might be considered by coaches when designing tasks adjusted to the level of the athletes.

Identifying the predictors of turnover intention based on psychosocial factors of nurses during the COVID-19 outbreak.

AimsBecause of the direct contact nurses have with patients, they are exposed to more stressful events during the outbreak of infectious diseases, which increases their turnover intention, highly impacting not only nurses, but also patients and organizations. The present study aimed to identify the predictors of turnover intention based on psychosocial factors in nurses of Ardabil pre‐hospital emergency and educational and medical centres during the COVID‐19 outbreak.DesignThe present descriptive‐analytical study was conducted in June, 2020.MethodsA total of 479 nurses working in Ardabil pre‐hospital emergency and educational and medical centres to fight COVID‐19 were recruited for this study using the census method. Data were collected using the Demographic Information Questionnaire, Turnover Intention Questionnaire, Weiss & Marmar Impact of Event Scale‐Revised (IES‐R), General Health Questionnaire (12 C‐GHQ) and Job Content Questionnaire (JCQ). Data were analysed with SPSSv.22 software using correlation, t test, analysis of variance, multiple regression and descriptive tests.ResultsThe mean turnover intention score of nurses was 41.73 with a standard deviation of 12.11. The results of correlation coefficient revealed a positive relationship between PTSD, general health, job demand and job strain with turnover intention (p ≤ .01) and a positive and significant relationship between social support and turnover intention (p ≤ .01). Multiple regression analysis showed that the variables of gender, marital status, work position, decision latitude, social support, job strain, general health and post‐traumatic stress disorder (PTSD) were predictors of turnover intention.ConclusionJob stressors during the COVID‐19 outbreak have led to an increase in nurses’ turnover intention. Identifying and managing the factors related to job stressors will make it possible to prevent nurses’ turnover intention in such critical situations.

Spatiotemporal modelling of soil moisture in an Atlantic forest through machine learning algorithms

AbstractUnderstanding the spatiotemporal behaviour of soil moisture in tropical forests is fundamental because it mediates processes such as infiltration, groundwater recharge, runoff and evapotranspiration. This study aims to model the spatiotemporal dynamics of soil moisture in an Atlantic forest remnant (AFR) through four machine learning algorithms, as these dynamics represent an important knowledge gap under tropical conditions. Random forest (RF), support vector machine, average neural network and weighted k‐nearest neighbour were studied. The abilities of the models were evaluated by means of root mean square error, mean absolute error, coefficient of determination (R2) and Nash‐Sutcliffe efficiency (NS) for two calibration approaches: (a) chronological and (b) randomized. The models were further compared with a multilinear regression (MLR). The study period spans from September 2012 to November 2019 and relies on variables representing the weather, geographical location, forest structure, soil physics and morphology. RF was the best algorithm for modelling the spatiotemporal dynamics of the soil moisture with an NS of 0.77 and R2 of 0.51 in the randomized approach. This finding highlights the ability of RF to generalize a dataset with contrasting weather conditions. Kriging maps highlighted the suitability of RF to track the spatial distribution of soil moisture in the AFR. Throughfall (TF), potential evapotranspiration (ETo), longitude (Long), diameter at breast height (DBH) and species diversity (H) were the most important variables controlling soil moisture. MLR performed poorly in modelling the spatiotemporal dynamics of soil moisture due to the highly nonlinear condition of this process.Highlights Modelling soil moisture in an Atlantic forest through machine learning. Machine learning algorithms are powerful tools to address the spatiotemporal dynamics of soil moisture. Climate, position and forest variables drive the spatiotemporal pattern of soil moisture. Random forest is the best algorithm to simulate soil moisture dynamics.

The Role of Intrapersonal-, Interpersonal-, Family-, and School-Level Variables in Predicting Bias-Based Cybervictimization

This study investigated whether social position (e.g., gender, migration, family status), intrapersonal-level (e.g., online risk behaviors, motives of Internet use), interpersonal-level (e.g., victimization and bullying), family-level (e.g., parental mediation), and class-level (e.g., teachers’ mediation, ethnic diversity) variables predict bias-based cybervictimization. Self-report questionnaires were completed by 1,018 Austrian adolescents (52.3% girls), aged 12 to 17 years ([Formula: see text] = 13.55, SD = 0.88). The logistic part of a multilevel zero-inflated Poisson model showed that higher levels of offline victimization and a higher proportion of immigrants in classes were predictors for students reporting at least one form of bias-based cybervictimization. The Poisson part of the model showed that being a girl, higher levels of cybervictimization, lower levels of avoiding online risks, and more discussions about media use with teachers in classes were predictors for students reporting a higher number of bias-based cybervictimization. Implications for prevention are discussed.

Towards the Dependence on Parameters for the Solution of the Thermostatted Kinetic Framework

A complex system is a system involving particles whose pairwise interactions cannot be composed in the same way as in classical Mechanics, i.e., the result of interaction of each particle with all the remaining ones cannot be expressed as a sum of its interactions with each of them (we cannot even know the functional dependence of the total interaction on the single interactions). Moreover, in view of the wide range of its applications to biologic, social, and economic problems, the variables describing the state of the system (i.e., the states of all of its particles) are not always (only) the usual mechanical variables (position and velocity), but (also) many additional variables describing e.g., health, wealth, social condition, social rôle ⋯, and so on. Thus, in order to achieve a mathematical description of the problems of everyday’s life of any human society, either at a microscopic or at a macroscpoic scale, a new mathematical theory (or, more precisely, a scheme of mathematical models), called KTAP, has been devised, which provides an equation which is a generalized version of the Boltzmann equation, to describe in terms of probability distributions the evolution of a non-mechanical complex system. In connection with applications, the classical problems about existence, uniqueness, continuous dependence, and stability of its solutions turn out to be particularly relevant. As far as we are aware, however, the problem of continuous dependence and stability of solutions with respect to perturbations of the parameters expressing the interaction rates of particles and the transition probability densities (see Section The Basic Equations has not been tackled yet). Accordingly, the present paper aims to give some initial results concerning these two basic problems. In particular, Theorem 2 reveals to be stable with respect to small perturbations of parameters, and, as far as instability of solutions with respect to perturbations of parameters is concerned, Theorem 3 shows that solutions are unstable with respect to “large” perturbations of interaction rates; these hints are illustrated by numerical simulations that point out how much solutions corresponding to different values of parameters stay away from each other as t→+∞.

Volumetric cone-beam computed tomography evaluation and risk factor analysis of external apical root resorption with clear aligner therapy.

To investigate the prevalence and severity of external apical root resorption (EARR) volumetrically with clear aligner therapy using cone-beam computed tomography (CBCT) as well as determine the possible risk factors and develop a prediction model for EARR. In this retrospective study, 320 incisors from 40 Class II patients treated with aligners (Invisalign) were included in this study. CBCT images were obtained at pretreatment (T0) and posttreatment (T1). Root volume was calculated by three-dimensional reconstruction of CBCT images, and apical tooth movement was measured from superimposed CBCT images. Changes in root volume were compared using paired t-tests, and the relationship between root volume loss and potential risk factors was analyzed by multiple linear regression. All of the measured incisors showed root volume loss, with an average of 11.48 ± 6.70 mm3, and the prevalence of severe resorption was 0.625%. The prediction model for EARR included variables of posttreatment sagittal root position (SRP), extraction, tooth type, and apical intrusion and extrusion displacements, with an R2 of 0.51. Age, sex, duration, pretreatment SRP, attachment, advancement, and retraction movements were excluded from the model. Most incisors showed mild to moderate resorption during aligner treatment; only a minimal percentage showed severe resorption. Posttreatment SRP (which showed the highest association with EARR), extraction, tooth type, and apical intrusion and extrusion displacements were risk factors for EARR.

Three-dimensional positional accuracy of intraoral and laboratory implant scan bodies

Statement of problemIn the implant digital workflow, scan bodies provide the 3D position of digital implants in the virtual dental arch. However, limited evidence is available on scan body accuracy, selection, and usage. PurposeThe purpose of this in vitro study was to evaluate the 3D positional accuracy of 4 intraoral and 6 laboratory scan body systems to the implants and laboratory replicas of an implant system under various torque magnitudes. Material and methodsTen test groups comprising 4 intraoral (I): Medentika L-Series (MS), Straumann CARES Mono (SM), Core 3D (CO), Straumann RC (SS); and 6 laboratory (L): Nobel Procera Pos Locator (NP), Sirona InPost (SR), Amann Girrbach (AG), Straumann CARES Mono (SM), Core 3D (CO), Straumann RC (SS) scan bodies were derived from 7 scan body systems. Of these, 3 systems (SM, CO, SS) are used for both intraoral and laboratory applications. The scan bodies were tested on Straumann Bone Level Regular CrossFit implants or laboratory replicas. Eight test groups allowed for the variation of torque application (5, 10, and 15 Ncm), while 2 test groups (NP, SR) were hand positioned only. Prefabricated metal abutments (ME) for both implants and laboratory replicas served as controls. A coordinate measuring machine measured four 3D positional accuracy variables: vertical linear distortion (dz), 2D tolerance displacement (dr), global linear distortion (dR), and scan body height discrepancy (ΔH) (n=10). The data were analyzed with 2-way analysis of variance tests and post hoc analysis with Tukey tests (α=.05). ResultsFor both intraoral and laboratory test groups, 2-way ANOVA found that the system had a significant effect on all distortion variables (P<.001), while torque magnitude had a significant effect only on dz and ΔH (P<.001). Overall, mean dz ranged from 5 ±12 μm for L-AG at 15 Ncm to 23 ±14 μm for L-AG at 5 Ncm. Mean dr ranged from 5 ±4 μm for I-SM at 15 Ncm to 73 ±41 μm for L-SS at 10 Ncm, and mean dR ranged from 11 ±6 μm for I-SM at 10 Ncm to 74 ±41 μm for L-SS at 10 Ncm. Mean ΔH ranged from -5 ±10 μm for I-SM at 15 Ncm to 23 ±14 μm for L-AG at 5 Ncm. Among intraoral test groups, for dz and ΔH, all the test groups except for I-SM at 15 Ncm and I-MS at 10 and 15 Ncm were significantly more positive than the control (P<.001). For dr, I-SS at 5, 10, and 15 Ncm was significantly different from the control (P<.001). For dR, only I-SS at 5 Ncm was significantly different from the control (P<.001). Among laboratory test groups, for dz and ΔH, L-AG at 5 Ncm and L-CO at 15 Ncm were significantly more positive than the control (P<.001). For dr, L-SS at 10 and 15 Ncm were significantly different from the control (P<.001). For dR, only L-SS at 10 Ncm was significantly different from the control (P<.001). Intraoral and laboratory systems show comparable 3D positional accuracy. ConclusionsOverall, I-SS and L-SS were the least accurate. The system tested had a significant effect on 3D positional accuracy, while torque magnitude had no consistent effect across all systems.

Controllable thermal state design method of flexible shapes of piston cooling galleries

The uneven temperature field is a great contributor to abnormal deformations and local damages of the piston. The piston gallery cooling is one of the effective ways to achieve an acceptable temperature field of the piston head. However, the traditional design of piston cooling gallery cannot accurately control the local thermal state of the piston, such as the temperature in the piston ring zone. In this paper, a flexible design model is adopted to control local thermal state of piston cooling gallery, and 10 parameters are used to completely determine the cross-section shape and the position of the cooling gallery. The maximum temperature and the maximum temperature gradient of the piston are employed as optimization targets to describe the thermal state of the whole piston. Most importantly, the temperature of the first ring zone is adopted as controllable target to monitor the local thermal state of the piston ring zone. The optimal structure variables and position variables were acquired by a Multi-Objective Genetic Algorithm technique. The results show that support vector machine for regression (SVR) model has a very excellent generalization ability with the determination coefficient greater than 0.90 and the relative deviation less than 7%. The SVR model can quickly obtain the cooling performance of each sample point to save calculation cost. The results illustrate that the controllable thermal state design method is effective, resulting in decreasing thermal load of the piston and adding reliability of the engine. For special focusing on the maximum temperature of the first ring zone, three distinctive optimal solutions (denoted A, B, C) are much lower than original model and other optimization models. Solution A has the lowest the temperature of the first ring zone in three optimal solutions to meet stricter cooling requirements of ring zone. Meanwhile, the temperature of the piston is also affected by the controllable thermal state design method, which have the large reduction with 5.40%. The temperature and temperature gradient are contradictory relationship. Thus, solution A possesses highest temperature gradient, which is 11841.3 °C/m. On the contrary, solution C pay attention to optimize the thermal strength of the piston, its temperature gradient is 11445.7 °C/m. The maximum temperature of the piston and the maximum temperature of the first ring zone are 356.5 °C and 298.3 °C, respectively. Solution B is a compromise between the solution A and the solution C, which is a design solution at which three optimization objectives are sufficiently satisfied. The controllable thermal state design method is adopted to control the design goal of the one or more feature regions of the piston.