Analysis of Data-Based Scientific Reasoning from a Product-Based and a Process-Based Perspective

In this study, we investigated participants’ reactions to supportive and anomalous data in the context of population dynamics. Based on previous findings on conceptions about ecosystems and responses to anomalous data, we assumed a tendency to confirm the initial prediction after dealing with contradicting data. Our aim was to integrate a product-based analysis, operationalized as prediction group changes with process-based analyses of individual data-based scientific reasoning processes to gain a deeper insight into the ongoing cognitive processes. Based on a theoretical framework describing a data-based scientific reasoning process, we developed an instrument assessing initial and subsequent predictions, confidence change toward these predictions, and the subprocesses data appraisal, data explanation, and data interpretation. We analyzed the data of twenty pre-service biology teachers applying a mixed-methods approach. Our results show that participants tend to maintain their initial prediction fully or change to predictions associated with a mix of different conceptions. Maintenance was observed even if most participants were able to use sophisticated conceptual knowledge during their processes of data-based scientific reasoning. Furthermore, our findings implicate the role of confidence changes and the influences of test wiseness.

How predictability affects habituation to novelty

One becomes accustomed to repeated exposures, even for a novel event. In the present study, we investigated how predictability affects habituation to novelty by applying a mathematical model of arousal that we previously developed, and through the use of psychophysiological experiments to test the model’s prediction. We formalized habituation to novelty as a decrement in Kullback-Leibler divergence from Bayesian prior to posterior (i.e., information gain) representing arousal evoked from a novel event through Bayesian update. The model predicted an interaction effect between initial uncertainty and initial prediction error (i.e., predictability) on habituation to novelty: the greater the initial uncertainty, the faster the decrease in information gain (i.e., the sooner habituation occurs). This prediction was supported by experimental results using subjective reports of surprise and event-related potential (P300) evoked by visual-auditory incongruity. Our findings suggest that in highly uncertain situations, repeated exposure to stimuli can enhance habituation to novel stimuli.

Simulation of the Progression of the COVID-19 Disease in Northwest Syria Using Basic and Adjusted SIR Model

Background: Syria has been experienced an armed conflict since 2011. At the time of writing, Northwest Syria is outside governmental control and facing the challenges of the COVID-19 pandemic. In this research, we studied the progression of the COVID-19 pandemic in northwest Syria. We studied the impact of wearing facial masks and discussed the results compared to the existing figures and facts. Methods: Based on available data and using the basic and adjusted SIR model, we estimated the value of the basic reproduction number () which gives an initial prediction of the disease progression. We studied the disease progression for one year (from July 2020 to July 2021) and simulated using the basic and adjusted SIR models. Results: We estimated that the for 2019-nCOV was 2.38, and the resulted figures were overestimated compared to the reported numbers and data concerning the COVID-19 pandemic. However, when adjusting the model by a preventive measure (in this case, wearing face masks), the results were significantly less and closer to the actual reported numbers. Conclusions: Hospital utilization throughout 365 days was projected depending on the basic and adjusted SIR model. The pandemic's peak in the studied area was predicted to arise in December 2020. The expected number of cases to be infected and admitted to hospitals and ICU in 365 days was 633636, 1901, and between 1141 and 2090, accordingly.

Prediction of the Void Ratio Parameter in Mineral Tailings Using Gene Expression Programming

Mineral tailing deposits are one of the most important issues in the field of geotechnical engineering. The void ratio of mineral tailings is an essential parameter for investigating the geotechnical behavior of tailings. However, there has not yet been a comprehensive empirical formulation for initial prediction of the void ratio of mineral tailings. In this study, the void ratio of various types of mineral waste is estimated by using gene expression programming (GEP). Therefore, taking into consideration the effective physical parameters that affect the estimation of this parameter, eight different models are presented. A reliable experimental database collected from different sources in the literature was applied to develop the GEP models. The performance of the developed GEP models was measured based on coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE). According to the results, the model with effective stress σ ′ , initial void ratio (e0), and parameters of R2 = 0.92, MAE = 0.109, and RMSE = 0.180 performed the best. Finally, a new empirical formulation for the initial prediction of the void ratio parameter is proposed based on the aforementioned analyses.

Street Crime during Covid-19 Pandemic in Perspective of Routine Activity Law Theory and it Influence on Indonesian Criminal Law

The initial prediction is that the condition of covid-19 pandemic will shake people's lives in all aspects, and this condition has a great potential for rising crime. With all of its character, it is very interesting to discuss how street crime developed during the Covid-19 pandemic. This study use a mixed research method, where data is collected from facts in the field, legal sources or applied regulations, associated with legal materials obtained from literature review research and overall data obtained from both primary data and secondary data. The conclusion from this research is that street crime during the Covid-19 Pandemic cannot be stated expressly decreased or increased for each region has dynamics that differ from one another according to the characteristics of the region. The correlation of PSBB policy during the Covid-19 Pandemic with the level of street crime in the perspective of routine activity theory can be seen from several street crimes that change the type and location of their objects / targets as well as the increasing number of drug and cybercrime cases that are striking. PSBB conditions during Pandemic Covid-19 against crimes that require a new system that is integrated with the internet, a pattern of punishment with massive amounts of assimilation to reduce the density of prison and a virtual court examination system that should be a part of the criminal justice system in Indonesia

How predictability affects habituation to novelty?

One becomes accustomed to repeated exposures, even for a novel event. In the present study, we investigated how predictability affects habituation to novelty by applying a mathematical model of arousal that we previously developed, and conducted a psychophysiological experiment to test the model prediction. We formalized habituation to novelty as a decrement in Kullback-Leibler divergence from Bayesian prior to posterior (i.e., information gain) representing arousal evoked from a novel event through Bayesian update. The model predicted an interaction effect between initial uncertainty and initial prediction error (i.e., predictability) on habituation to novelty: The greater the initial uncertainty, the faster the information gain decreases (i.e., the sooner one is habituated). Experimental results using subjective reports of surprise and event-related potential (P300) evoked by visual-auditory incongruity supported the model prediction. Our findings suggest that in highly uncertain situations, repeated exposure to stimuli may enhance habituation to novel stimuli.

Are the growth and survival of Acheta domesticus comparable when reared on okara, waste vegetables and premium animal feed?

The domesticated house cricket, Acheta domesticus (Linnaeus, 1758), has been lauded as a more sustainable protein source than traditional livestock to meet the ever-increasing demand for food. There is also a potential of using waste food, such as okara (soybean residue from the manufacture of soy milk and tofu) and waste vegetables which are commonly available in many parts of Southeast Asia, to feed these insects. Food wastage can be reduced while increasing the food supply if the crickets can grow and survive well on waste food. Thus, we investigated the viability of rearing A. domesticus on oligidic diets, specifically waste vegetables and okara, to optimise the use of waste food as feed to the crickets. We monitored cricket mortality and fresh weight of 32 individually housed crickets subjected to different diet treatments, every other day for 45 days. The crickets reared on Brassica rapa (xiao bai cai; XBC) and okara mixture did not grow and survive as well as those reared on the XBC and dog food mixture, contradicting our initial prediction that okara is a suitable cricket feed, even though it has been considered one of the best oligidic diets. We also did not find any evidence that crickets reared on mixed diets of XBC and okara food grew or survived better than single diets of XBC or okara. This showed that okara cannot always replace premium animal feed to rear A. domesticus crickets.

Currency Exposure and Time Scales: Application of Wavelet Method to Malaysian Non-financial Firms

The paper estimates the multiscale relationship between stock prices and exchange rates of 75 Malaysian non-financial firms by applying the wavelet analysis on daily data running from 1995 to 2016. The analysis is done for the overall sample and also by segregating the selected firms into 15 industries in Malaysia. Results from the ordinary least square (OLS) regression are also obtained for comparison purpose. The beta coefficients of exposure are shown to exhibit multiscale tendency in all analyses. Higher exposure is recorded at higher timescale for the overall and negative exposure, confirming the initial prediction of higher exposure in wider investment horizon. The study also shows higher wavelet exposure at high scale compared to the exposure obtained from the OLS estimate, providing support on the higher measurement power of the wavelet analysis to study the exposure level.