The emerging association of canonical finger patterns and quantity-number linkage in early childhood

Through repeated use of fingers for counting and representing numerical magnitudes in early childhood, specific finger patterns become associated with mental representations of specific quantities. Although children as young as three years of age already use their fingers for representing numerical quantities, evidence on advantageous recognition of such canonical compared to non-canonical finger patterns as well as its association with numerical skills in young children is scarce. In this study, we investigated the performance of N=101 children aged around four years in canonical vs. non-canonical finger pattern recognition and its concurrent association with skills tapping into children’s’ knowledge about quantity-number linkage. Extending previous findings observed for older children, the present results indicated that despite considerable variability on the individual level performance in canonical finger pattern recognition was better compared to non-canonical finger pattern recognition on the group level. Moreover, both canonical and non-canonical finger pattern recognition was positively correlated with tasks tapping into quantity-number linkage. However, when controlling for verbal counting skills, correlations that remained significant were only found for canonical but not non-canonical finger pattern recognition performance. Overall, these results provide insights into the early onset and significance of the effect of canonicity in finger pattern recognition during early numerical development.

Materiality and the Prehistory of Number

Modern humans produce number systems with striking cross-cultural similarities. Understanding prehistoric numerical cognition, however, requires looking at when cognitive prerequisites emerged: morphological factors like parietal encephalization; abilities like quantity perception, language, concept formation and manipulation, categorization, and ordinality; and demographic factors suggesting societal motivations for numerical development. These establish the “probably not before” timeline for numerical emergence. The question is then approached from the earliest emergence of unambiguous numbers in Mesopotamia, clay tokens used in the late 4th millennium and subsequent numerical notations. With tokens and notations, the archaeological and textual evidence of precursor technologies like tallies and fingers form a sequence capable of elaborating the innate perceptual experience of quantity into simple counting sequences and complex mathematics. Along with the cognitive prerequisites, the sequence of material forms also provides insight into potential archaeological evidence (material forms and demographic factors) that might indicate numerical emergence in prehistoric times.

Experimental and Numerical Development on Multi-Material Joining Technology for Sandwich-Structured Composite Materials

Creating connection points for sandwich-structured composites without losing technical performance is key to realising optimal lightweight structures. The patented LiteWWeight® technology presents cost-effective connections on sandwich panels in a fraction of a few seconds without predrilling. Ultrasonic equipment is used to insert a thermoplastic fastener into the substrate material and partially melt it into the porous internal structure. This creates a highly interlocked connection (connection strength is above 500 N) suitable for semi-structural applications. This study focused on the simulation and experimental validation of this process, mainly on the interaction between the pin and the substrate material during the joining process. The dynamic thermo-mechanical model showed reasonable agreement with experimental methods such as process data, high-speed camera monitoring or computed tomography and allowed the prediction of the connection quality by evaluation of the degree of interlock. The connection strength prediction by the developed model was validated within several various process setups, resulting in a prediction accuracy between 94–99% depending on the setup.

The numerical development of MOC for analyzing the inclined pipelines using the experimental network of Babol Noshirvani University as a case study

Despite the applications of the MOC for analyzing the unsteady flows, using this method in networks with variable elevations still has many challenges. In this paper, by developing modified correlations as a computer code, the possibility of analyzing inclined pipelines has been evaluated. For validation and calibration, the results of MOC were compared with the results of EPANET software as well as experimental data. To extract experimental data, the water network of NIT with a constant head of 7 m three loops, and four inclined branches were employed. While evaluating the capabilities of the developed computer code, the results show that for all pipes, as the number of pressure fluctuations in a specific period increases, the intensity of the pressure fluctuations decreases, and the damping speed increases as well. Moreover, in inclined pipes, unlike noninclined pipes, the intensity of pressure fluctuations will increase as the elevation increases and the cross-sectional distance from the transient event increases as well. The evaluation of the effect of space steps on the accuracy of the solution to the MOC shows that in the study network, considering 20 segments for each pipe, the fastest response time with an error of less than 1% is obtained.

The quandary of diagnosing mathematical difficulties in a generally low performing population

ABSTRACT. Brazilian students’ mathematical achievement was repeatedly observed to fall below average levels of mathematical attainment in international studies such as PISA. Objective: In this article, we argue that this general low level of mathematical attainment may interfere with the diagnosis of developmental dyscalculia when a psychometric criterion is used establishing an arbitrary cut-off (e.g., performance<percentile 10) may result in misleading diagnoses. Methods: Therefore, the present study evaluated the performance of 706 Brazilian school children from 3rd to 5th grades on basic arithmetic operations addition, subtraction, and multiplication. Results: In line with PISA results, children presented difficulties in all arithmetic operations investigated. Even after five years of formal schooling, less than half of 5th graders performed perfectly on simple addition, subtraction, or multiplication problems. Conclusions: As such, these data substantiate the argument that the sole use of a psychometric criterion might not be sensible to diagnose dyscalculia in the context of a generally low performing population, such as Brazilian children of our sample. When the majority of children perform poorly on the task at hand, it is hard to distinguish atypical from typical numerical development. As such, other diagnostic approaches, such as Response to Intervention, might be more suitable in such a context.

Analysis of the real number of infected people by COVID-19: A system dynamics approach

At the beginning of 2020, the COVID-19 pandemic was able to spread quickly in Wuhan and in the province of Hubei due to a lack of experience with this novel virus. Additionally, authories had no proven experience with applying insufficient medical, communication and crisis management tools. For a considerable period of time, the actual number of people infected was unknown. There were great uncertainties regarding the dynamics and spread of the Covid-19 virus infection. In this paper, we develop a system dynamics model for the three connected regions (Wuhan, Hubei excl. Wuhan, China excl. Hubei) to understand the infection and spread dynamics of the virus and provide a more accurate estimate of the number of infected people in Wuhan and discuss the necessity and effectivity of protective measures against this epidemic, such as the quarantines imposed throughout China. We use the statistics of confirmed cases of China excl. Hubei. Also the daily data on travel activity within China was utilized, in order to determine the actual numerical development of the infected people in Wuhan City and Hubei Province. We used a multivariate Monte Carlo optimization to parameterize the model to match the official statistics. In particular, we used the model to calculate the infections, which had already broken out, but were not diagnosed for various reasons.