Variable Path Research Articles

The Placement of Children in Need of Out-of-Home Care: Forms of Care and Differences in Attachment Security and Behavioral Problems in the Italian Context

The current paper investigated differences in secure attachment levels and behavioral problems among four groups of children in out-of-home care in Italy: closed adoption (child and birth parents not in contact following adoption), open adoption (child and birth parents still in contact after placement), foster care (child living temporarily with relatives or unrelated foster parents) and institutional care (child in residential care for large groups of children). One hundred and thirty children aged 10–19 were included in this study. The Attachment Interview for Childhood and Adolescence and the Achenbach Youth Self-Report were employed to measure participants’ secure attachment levels and behavioral problems. Both a multivariate analysis of covariance and measured variable path analysis were performed. Age, gender and time elapsed between the request for child protection and placement on out-of-home care were used as covariates. The results showed that adolescents in closed adoption had higher secure attachment scores than those in foster care and institutional care, while adolescents in open adoption scored significantly higher on problem behaviors than those in the other out-of-home care groups. Findings were discussed in terms of limitations and implications for future research.

Performance evaluation on full-scale proton exchange membrane fuel cell: Mutual validation of one-dimensional, three-dimensional and experimental investigations

The coupling of multiple physical processes such as gas multi-component transport, gas–liquid multiphase flow, and electrochemical reactions within the proton exchange membrane fuel cell (PEMFC) makes its hydrothermal management exceptionally complicated. Therefore, the complex heat and mass transfer processes in the full-scale PEMFC are investigated in single cell with single channel serpentine flow field (FF). Firstly, the reliability of the proposed three-dimensional (3D) computational fluid dynamics (CFD) numerical model is verified by using the experimental test results of a single cell. Among them, the trend of simulation and experiment performance curves is consistent, and the minimum error of current density is 0.665%. Secondly, the ionomer model of cathode catalyst layer (CCL) is considered in CFD simulation, which is closer to the actual working condition of fuel cell (FC). The resistance of ionomer film and liquid water film mainly affects the diffusion rate of oxygen in CCL, resulting in a decrease in both current density values and power density values. Subsequently, the electrochemical reaction platform of one-dimensional (1D) FC is constructed, and the performance curves of multi-scale FCs are analyzed. The results demonstrate that the error of stack level is the largest, followed by single cell and single channel is the smallest. Finally, the 1D numerical model and the 3D PEMFC multiphase flow CFD model are utilized to investigate the cell voltage losses in the bionic spider flow field, the variable path flow field, and the serpentine flow field, respectively, under different operating conditions.

Research on the mathematical model and design of a three loop controller for the oscillating scanning system of a laser line scanning galvanometer

The scanning vibration mirror system drives the scanning mirror fixed to it through the oscillation of the motor shaft, so as to control the reflected light to form a dynamic variable light path. The vibration mirror scanning system has higher controllability than the fixed optical path system and has been widely used.In this dissertation, after establishing the models of the core components of the scanning vibration mirror system, the mathematical model of the whole system is established.On this basis, simulation and theoretical analysis show that the system has some shortcomings, such as small bandwidth, low dynamic tracking accuracy, and the comprehensive dynamic performance of the system is easily affected by the input of external interference branches. A series correction controller and three closed-loop controller are designed for the above problems, respectively, and the control effects of the two controllers on the scanning vibration mirror system are studied through simulation experiments. By comparing the output response results of the system under the action of sinusoidal signals of different frequencies, it can be seen that the comprehensive effect of the three closed-loop controllers is better. Under the action of step signals, the overshoot of the three closed-loop correction controller correction system is 21.5% higher than that of the series controller correction system, the adjustment time is 82.7% less, and the steady-state error is significantly smaller. Therefore, it indicates that the three closed-loop correction system has good rapidity and steady-state accuracy.

Variability Parameters, Correlation Studies and Path Analysis of Yield and Yield-Related Traits in Rice (Oryza sativa L.): A Comprehensive Review

Rice, a staple food crop of global importance exhibits substantial diversity in terms of yield and other agronomic traits, influenced by genetic, environmental, and management factors. Variability parameters, including genotypic and phenotypic coefficients of variation, heritability, correlation, and path analysis provide crucial insights into the extent of trait variation and their potential for improvement through breeding programs. Furthermore, correlation studies unveil the interdependencies between different traits, shedding light on potential connections influencing yield. This analysis uncovers important trait associations, guiding breeders and researchers in the pursuit of crop improvement strategies. By identifying both positive and negative correlations, this research offers a deeper understanding of trait interplay and informs targeted trait selection efforts. Path analysis, a pivotal aspect of this review, describes the underlying causal relationships between traits and their direct and indirect effects on yield. This analysis facilitates the ranking of trait contributions and guides decisions for trait prioritization in breeding programs. By illuminating the pathways through which traits influence yield, path analysis enhances the precision of trait selection for improved rice cultivars. The synergy of variability parameters, correlation studies, and path analysis presents a holistic framework for unraveling the complexities of rice yield determination. Understanding these parameters enhances our ability to select and develop high-yielding and resilient rice varieties, contributing to food security and sustainable agriculture. This abstract delves into the significance of variability parameters in unraveling the complexities of rice yield and trait dynamics, guiding effective crop improvement strategies for the future. This review provides a valuable synthesis of existing knowledge, offering insights that can aid researchers, breeders, and agronomists in their pursuit of enhancing rice yield and overall agricultural sustainability.

Voxel-based variable width continuous spiral path planning for 3D printing

Discontinuous printing paths in 3D printing lead to wasted time in fabricating products. This paper proposes a voxel-based continuous spiral path planning algorithm for 3D printing parts with less time consumption. Interestingly, we found our method can also improve the surface qualities and mechanical properties of the printed parts. The proposed path planning strategy in this paper is based on voxels which is different from traditional path planning strategies in literature. Firstly, our proposed algorithm determines the voxel size by considering the printable width of the printer nozzle. It then generates discrete elements by voxelizing the model and creates spirals and line segments by restricting the print direction of the connectable discrete elements. Next, the algorithm employs the Euler circuit to generate continuous sub-paths for the spirals and line segments. It utilizes the depth-first traversal algorithm to traverse and open the continuous sub-paths, resulting in printable continuous paths. To maintain surface accuracy for complex models, contour lines are introduced on the model's exterior and connected internally to ensure global path continuity. Lastly, the algorithm controls the path width in different directions by adjusting the extrusion rate of the printhead, preventing path overlap. Experimental results demonstrate that the proposed algorithm outperforms traditional path planning algorithms and the Connected Fermat spirals algorithm. The proposed strategy effectively mitigates the negative effects of path discontinuity, reduces printing time, and improves printed accuracy, and mechanical properties.

Leveraging Instagram to enhance self-esteem: A self-affirmative intervention study and multilevel mediation analysis

Although studies have consistently indicated that heavier use of social networking sites (SNS) perpetuates poorer self-esteem outcomes, no study has examined potential intervention methods that can yield positive effects from SNS use. We hypothesized that viewing one's Instagram profile would have self-affirmative effects on self-perception because the profile typically showcases curated instrumental positive aspects of self. Furthermore, these self-affirmative effects would indirectly improve state self-esteem via enhanced clarity of self-concept. To test our hypothesis, we designed an experimental intervention study where one group viewed their Instagram profile regularly, while another group viewed a neutral abstract art profile. Using multilevel latent variable path analyses, we found that participants who viewed their own Instagram profiles felt more positive about themselves (i.e., higher state self-esteem), and their enhanced self-concept clarity mediated the relations between self-affirmative SNS use and state self-esteem. Our findings provide preliminary evidence for the guided use of SNS to boost self-esteem.

Daily stress, and mental health of professional degree graduate students in Chinese traditional medicine universities: the mediating role of learning career adaptation

BackgroundWith the expansion of professional degree graduate students’ enrollment in China education, the mental health of these professional degree graduate students in medical-related majors who are under pressure of study, scientific research, clinical practice, and employment should not be ignored. What is the mental health level of these graduate students under the effect of learning career adaptation (internal resources) in the face of daily stress (external factors)? The purpose of this study is to discuss the relationship between these variables, and the mediating role of learning career adaptation of professional degree graduate students in traditional Chinese medicine colleges, and universities, to provide a theoretical basis for improving the learning career adaptation of students, and improving the level of mental health.MethodsA cross-sectional survey was conducted among 1593 professional degree graduate students majoring in clinical medicine, traditional Chinese medicine, and nursing in five traditional Chinese medicine universities. Finally, 660 questionnaires were returned, with a recovery rate of 41.43%. The scores of daily stress, learning career adaptation, and mental health were measured by Daily Stressors Scale for graduate students, graduate-students learning career adaptation scale, and General Mental Health Questionnaire (GHQ-20). Descriptive statistics were used to analyze the status quo of daily stress, learning career adaptation, and mental health. Pearson correlation analysis were used to analyze the relationship between them. we undertake analyses using structural equation modeling to construct the latent variable path model of daily stress, learning career adaptation on mental health. The significance level of the mediating effect was tested by the non-parametric percentile bootstrap method.ResultsThe scores of mental health, daily stress, and learning career adaptation were 50.56 ± 10.80, 35.12 ± 19.55, and 67.13 ± 7.48 respectively. Daily stress was negatively correlated with the three dimensions of learning career adaptation: career confidence, focus on his career, and career control (P < 0.01). Daily stress was positively correlated with depression and anxiety (P < 0.01). Self-affirmation, depression, and anxiety were negatively correlated with career confidence, focus on his career, and career control (P < 0.05). Learning career adaptation plays a partial mediating role between daily stress, and mental health (p < 0.001), with an intermediate effect value of 0.127, representing 28.54% of the total effect.ConclusionsMental health, learning career adaption of medical-related professional degree graduate students in traditional Chinese medical universities were at a moderate degree, and an upper-middle level respectively, while daily stress is to a lesser extent. Learning career adaptation mediates the relationship between daily stress, and mental health partially. To some extent, it can buffer the impact of daily stress on mental health, especially anxiety. The educational administrator could take various measures to improve the mental health of professional degree graduate students. It can also enhance their learning career adaptation from the perspective of individuals, and organizations to improve their mental health.

Reappraisal of exceptionally preserved s-forms, striae, and fractures from late Paleozoic subglacial surfaces in paleofjords, NW Namibia

Determining the grounded ice dynamics of deep-time glaciations is limited by the scarcity of well-preserved subglacial erosional features and their irregular distribution. In particular, small-scale erosional features known as s-forms that are subglacially sculpted in bedrock by water and/or ice are rarely preserved from the pre-Cenozoic record. A detailed re-examination of two late Paleozoic (late Carboniferous–early Permian) glacially-polished, surfaces at the base of the Dwyka Gp. within paleofjords located in the Kaokoveld region of northwest Namibia reveals a range of erosional features including: complex, multi-directional striae that crosscut each other, crescentic markings, chattermark trails, sinuous furrows, linear furrows, transverse troughs, comma forms, sichelwannen, muschelbrüche, cavettos, a pothole, and rock drumlins. The first study location in the Sanitatis paleovalley is previously undescribed and consists of striae and fractures on a polished granite bedrock surface located on the paleovalley floor. Striae, crescentic markings, and chattermark trails indicate ice movement to the west/northwest (striae mean azimuth of 276°). The second location in the Hoarusib paleovalley was previously described and is located on a multi-level, resistant, quartzite bedrock ridge close to or on the valley wall. This location contains numerous s-forms, striae, and fractures, as well as onlapping glaciogenic sediments, including diamictite plastered within a pothole. Some of these features are superimposed on rock drumlins. These erosional features were likely formed by a combination of pressurized subglacial meltwater and glacial abrasion underneath a glacier as it flowed over and around a resistant bedrock outcrop. Orientations of striae and chattermark trails at the second location indicate a primary direction of ice movement toward the west/northwest (striae modal azimuth of 275°), a minor secondary movement to the southwest (255°), and abundant third-order striae indicating ice flow around bedrock obstacles. However, cross-cutting relations suggest the primary and secondary striae orientations are not related to two distinct glacial advances as previously thought. The complex relationships between striae, fractures, and s-forms suggest that a combination of pressure melting, abundant subglacial meltwater, debris-rich basal ice, and variable ice flow paths around resistant obstacles was required to form these features. We conclude that the study locations were overridden by relatively thick (>210 m) warm-based or polythermal glaciers that were confined to a network of fjords as ice receded and stagnated. The glaciers flowed west into present-day Brazil during the late Paleozoic and likely overtopped the paleovalley walls during times of ice maxima.

Attachment, stress and interactional justice

PurposeThis paper aims to examine how individuals' attachment dispositions relate to interactional justice perceptions, how work stressors moderate this association, and how together they associate with attitudes (satisfaction, turnover intention, commitment) and citizenship behaviors at work.Design/methodology/approachSurvey data were used in an observed variable path analysis examining mediation by interactional justice and moderation by stressors on the associations between attachment dimensions and work outcomes.FindingsAttachment avoidance was negatively related to interactional justice perceptions and attachment anxiety was also negatively related to interactional justice perceptions, but only under conditions of higher work stressors. Interactional justice mediated the associations between attachment avoidance and work outcomes, and between the interaction of attachment anxiety and work stressors on work outcomes.Practical implicationsThese findings are particularly relevant to multiple aspects of HR practice, including performance feedback, managing stressors, building resilience, reward allocation and recognition, designing wellness programs and other aspects of human resource management.Originality/valueThis research goes beyond contextual predictors of justice perceptions and demonstrates that jointly considering attachment dimensions and work stressors uniquely contributes to understanding the formation of justice perceptions and their combined influence on work attitudes and behavior.

Genetic Variability, Correlation and Path Coefficient Analysis in Advanced Matromorphic Generations of Garden Pea (Pisum sativum L.)

Background: Garden pea is an important leguminous vegetable crop but the lack of high yielding and stable varieties is the major constraint. There is a need to explore genetic variability for the crop improvement programs. Considering this, the current investigation was aimed to study the genetic variability and relationship among the yield and its contributing traits in advanced matromorphic progenies for effective production. Methods: A two year experiment was carried out at SKUAST- Chatha, Jammu during the cropping season of 2020-21 and 2021-22 to find out the genetic variability parameters, path coefficient and correlation studies for thirteen yield contributing traits in twenty two garden pea genotypes (twelve advanced matromorphic progenies and ten parental lines). Result: The results revealed high variability among the tested genotypes. The values of phenotypic coefficient of variation (PCV) were greater as compared to the genotypic coefficient of variation (GCV) for all the traits. High heritability along with genetic advance ( greater than 20%) was observed for all the traits whereas pod length (PL) and shelling percentage (SP) were exceptions. Pod yield per plant ( PYPP) had positive genotypic and phenotypic correlation with node at which first flower appears (NFFA), plant height(PH), internodal distance (ID), no. of pods per node (NPPN), pod length (PL), no. of seeds per pod(NSPP), no. of pods per plant (NPP), days to first picking (DFF), average pod weight (APW) and shelling percentage (SP). Positive direct effect on pod yield per plant (PYPP) was exhibited by traits viz., days to 50 per cent flowering (DFPF), node at which first flower appears (NFFA), internodal distance (ID), no. of pods per node (NPPN), pod width (PW), no. of seeds per pod (NSPP), no. of pods per plant (NPPP), days to first picking (DFP) and average pod weight (APW) in path coefficient analysis.

Direct and Indirect Effects of Yield Contributing Characters on Seed Yield in Green Gram (Vigna radiate L.)

The present investigation was carried out to assess the genetic variability parameters, correlation and path analysis in 21 green gram genotypes for 13 quantitative traits at field experimentation center, during kharif 2022 in Department of Genetics and Plant Breeding, Naini Agricultural Institute, Sam Higginbottom University of Agriculture Technology and Sciences, Uttar Pradesh in Randomized Block Design in three replications. Analysis of variance indicated high significant differences among the genotypes for all the traits. Green gram (Vigna radiata L.) is one of the important pulse crops because of its short growth duration, adaptation to low water requirement and soil fertility. Variability is a greater need for initiating a breeding program for yield and yield contributing traits. High seed yield per plant was recorded by SM-2029, SPM-2040, PHULEMOONG-95418, CO-8, CO-7. All the traits showed significant variation among the lines. High Genotypic Coefficient of Variance and Phenotypic Coefficient of Variance was recorded for Number of pods per plant, Number of clusters per plant, Number of primary branches and Plant height where Genotypic Coefficient of Variance exhibited at moderate level and Number of pods per plant exhibited highest percentage of broad sense heritability and also high in genetic advance followed by Plant height and Number of primary branches and Number of clusters per plant. The studies on Genotypic Coefficient of Variance and Phenotypic Coefficient of Variance indicated that the presence of high amount of variation and role of the environment on the expression of these traits. Seed index positively correlated to seed yield per plant at both phenotypic and genotypic levels. Seed index, Biological Yield and Number of Primary branches exhibited high positive direct effect to seed yield per plant at both phenotypic and genotypic path coefficient analysis. Correlation coefficients in most cases were higher than their phenotypic correlation coefficients indicating the association was largely due to genetic reason. At both genotypic and phenotypic levels, significant positive correlations were observed for Seed Index, Days to maturity, Days to 50% pod setting, Plant height, Number of pods per plant and Number of clusters per plant.

Improved bit-based filtering algorithm for regular constraint

In this paper, we propose an improved filtering algorithm for regular constraint, which demand that the sequence of all assignments for variables can be accepted by a Deterministic Finite Automaton (DFA) or a regular language. Regular constraint is a type of global constraint in Constraint Satisfaction Problems (CSPs) and a natural expression of deterministic patterns in planning and decision making, and it utilizes the properties of DFA to pre-specify the optional paths for multiple variables. Thus, it is sensible to improve the filtering algorithm that enforces Generalized Arc Consistency (GAC) for regular constraint in order to minimize memory and time consumption. With the goal in mind, we encode DFA using bit vectors and then devise a bit operations algorithm to maintain the domain consistency for regular constraint. Lastly, we carry out an experiment to compare to the state-of-the-art filtering algorithm. The experimental results demonstrates that the proposed algorithm significantly improves both memory and time.

Open Economy Neoclassical Growth Models and the Role of Life Expectancy

AbstractThis paper applies the Ramsey–Cass–Koopmans (RCK) growth model to an open economy so that, when calibrated with standard parameter values that are commonly used in the small open economy macroeconomic literature, the time paths of the model variables and the speeds of convergence implied by the model conform with empirical evidence. Open-economy versions of the RCK growth model lead to several counterfactual conclusions including: infinite speeds of convergence for physical capital and output; and unbalanced consumption and asset growth. We avoid these undesired results by extending the baseline model with human capital, international credit constraints, and finite horizons. Given its finite-horizons feature, our model allows us to study the growth implications of changes in life expectancy from the perspective of an open economy, as most of the existing theoretical-quantitative literature that focus on the relationship assumes a closed economy. The model predicts that increased life expectancy has positive but diminishing marginal effect on long-run output per capita. We find that, between 1960 and 2018, improvements in average life expectancy at birth raised long-run output per capita in sub-Saharan Africa, the OECD region, and Canada by an estimated 57.49 %, 14.94 %, and 11.58 %, respectively. In addition, if average life expectancy at birth in sub-Saharan African countries converges from its current level to the level in their OECD counterparts, the region’s long-run output per capita will increase by an estimated 22.89 %.

Influence of Genetic Variability Parameters, Character Association and Path Analysis for Grain Yield and its Attributing Traits in Kodo Millet Improvement

A set of 64 genotypes of kodo millet comprising of germplasm accessions and released varieties were evaluated for their genetic variability, heritability, genetic advance as per cent of mean, character associations and path coefficients using 11 agro-morphological traits during kharif 2022 in an Alpha Lattice Design with two replications. The analysis of variance revealed the presence of significant variations among the genotypes for all the traits evaluated. High PCV and GCV were observed for the traits viz., plant height, number of tillers, panicle length, peduncle length, thumb length, grain yield, and fodder yield. It indicated the presence of substantial variability and a low environmental influence on these traits. High heritability combined with high genetic advance as per cent of mean (GAM) was observed for plant height, peduncle length, panicle length, and fodder yield, which indicated the predominance of additive gene action and selection based on these traits would be more reliable. Grain yield exhibited significant and positive correlation with days to 50% flowering, number of tillers, panicle length, number of racemes, test weight and fodder yield. Genotypic path analysis revealed that highest direct positive effect on grain yield was exhibited by days to 50% flowering, number of tillers, panicle length, test weight and fodder yield. Hence, the above-mentioned traits exhibiting positive significant correlation and positive direct effect on grain yield could be considered as important traits to be included in the selection criteria to achieve genetic improvement of grain yield in kodo millet.

Subregional Anelastic Attenuation Model for California

ABSTRACT Ground-motion models (GMMs) typically include a source-to-site path model that describes the attenuation of ground motion with distance due to geometric spreading and anelastic attenuation. In contemporary GMMs, the anelastic component is typically derived for use in one or more broad geographical regions such as California or Japan, which necessarily averages spatially variable path effects within those regions. We extend that path modeling framework to account for systematic variations of anelastic attenuation for ten physiographic subregions in California that are defined in consideration of geological differences. Using a large database that is approximately doubled in size for California relative to Next Generation Attenuation (NGA)-West2, we find relatively high attenuation in Coast Range areas (North Coast, Bay area, and Central Coast), relatively low attenuation in eastern California (Sierra Nevada, eastern California shear zone), and state-average attenuation elsewhere, including southern California. As part of these analyses, we find for the North Coast region relatively weak ground motions on average from induced events (from the Geysers), similar attenuation rates for induced and tectonic events, and higher levels of ground-motion dispersion than other portions of the state. The proposed subregional path model appreciably reduces within-event and single-station variability relative to an NGA-West2 GMM for ground motions at large distance (RJB&amp;gt;100 km). The approach presented here can readily be adapted for other GMMs and regions.

Examination of Higher Education Teachers’ Self-Perception of Digital Competence, Self-Efficacy, and Facilitating Conditions: An Empirical Study in the Context of China

In the digital age, it is necessary for higher education teachers to improve their digital competence to face the challenges of the advancement of technology. Because there are few studies on the digital competence of higher education teachers in the context of Asia, the aim of this study was to describe Chinese higher education teachers’ self-perceptions of digital competence and investigate the effects of self-efficacy and facilitating conditions and how they predict teachers’ digital competence. For this purpose, a quantitative methodology was used. A final sample of 525 in-service higher education teachers from China completed the questionnaire. The data were analyzed using descriptive analysis, inferential analysis, and latent variable path analysis. The results indicate, first, that teachers’ general perception of digital competence was at a high level, and of the seven competence areas, values, ethics, and security, digital resources, and continuing professional development areas ranked among the top four, respectively, based on their means. Significant differences were observed in the digital competence of teachers with regard to different levels of education, disciplines, and institutional categories. Second, according to the results of structural equation modeling, facilitating conditions were positively and significantly correlated with teachers’ self-efficacy and digital competence. In addition, self-efficacy exerted a significantly positive impact on teachers’ digital competence. Finally, self-efficacy was found to mediate the relationship between facilitating conditions and teachers’ digital competence. Implications are suggested for developing teachers’ digital competence according to the findings of this study.

Embracing life's challenges: Developing a tool for assessing resilient mindset in second wave positive Psychology

The purpose of this study is to develop and validate the Resilient Mindset Scale (RMS), a brief tool designed to measure resilient mindset among Turkish individuals. Additionally, the study aims to explore the relationship between resilient mindset and mental well-being among adolescents and young adults, providing further evidence in this domain. The exploratory factor analysis, conducted with a sample of 327 participants, revealed that the RMS has a unidimensional structure consisting of six items that effectively measure core indicators of a resilient mindset. Subsequent confirmatory factor analysis, conducted with a sample of 338 participants, confirmed the one-factor structure, demonstrating a good-data model fit with strong factor loadings and internal reliability estimates. Further analyses demonstrated moderate to strong correlations between resilient mindset and mental well-being indicators. Moreover, the latent variables path model revealed that the measurement model had a moderate to strong predictive effect on positive academic functioning, psychological well-being, and psychological distress. These findings establish the psychometric reliability and validity of the RMS as a measurement tool for assessing a resilient mindset among adolescents and young adults. Mental health providers can integrate the concept of a resilient mindset into therapeutic approaches and interventions to foster resilience and enhance mental well-being.

A matheuristic algorithm for the maintenance planning problem at an electricity transmission system operator

When planning maintenance tasks involving the switching off of parts of the network, electricity transmission operators must evaluate and take into account the associated risks. The French operator, RTE, has developed a three-step approach in which they first calculate the risks in every possible scenario, then plan the maintenance tasks by optimizing some risk measures, and finally validate the plan. In this paper, we have addressed the second step, developing mathematical models that approximate the original problem as well as a matheuristic algorithm. It is composed of three phases, combining integer linear models in the first phase with metaheuristics such as Variable Neighbourhood Descent and Path Relinking in the second and third phases. The computational results obtained on the benchmarks provided by the company show that our algorithm improves on the best reported solutions for most of the test instances.

Modelling National Economic System: A Case of the Croatian Economy

Abstract In this study we evaluate a national economic model using a system dynamics approach. We use a set of macroeconomic data for a transition economy to validate the model behaviour in the past, and then simulate the alternative paths of key macroeconomic variables. Instead of studying only a fraction of the economy, or using simple and abstract models, we build a large-scale national economic model. As the study is based on system dynamics information feedback, it provides additional insights about the macroeconomic effects of the economic policy, making it a valuable tool for economic policy analysis. Such insights are instrumental for understanding the total effects of economic policies and their full economic consequences. To demonstrate this, we have simulated one actual economic policy intervention and its alternative scenario.

Inexpensive multi-plane particle image velocimetry based on defocusing: Proof of concept on two-component measurement

This paper presents a method for simultaneous particle image velocimetry (PIV) on parallel planes offset in depth. The method places images from two planes onto a different half of a camera sensor by using image splitting optics with variable optical path lengths. A shallow depth of field is achieved to ensure only one plane is in focus on each half of the sensor. Without needing additional lasers, the method is designed as an inexpensive means to increase the number of measurement plane(s) of single/multi-plane PIV setups and can be combined with existing plane discrimination approaches such as polarization and wavelength. The method is useful for studying instantaneous flow correlations on different planes while retaining high in-plane spatial resolution of typical planar PIV measurement. The measurement uncertainty caused by crosstalk from out-of-focus images is discussed. Experimental results from a laminar flow rig test indicate that the average measurement error of each velocity component is lower than 0.1 pixels per time step, with a 20 mm plane separation in depth and a 35 × 54 mm2 field of view. As an application with varying background scatter and out-of-plane flow motions, in-cylinder flow measurements in an optically accessible internal combustion engine were performed on two swirl planes simultaneously. Characteristics of the proposed method performing stereoscopic PIV measurements will be studied in future.