Average Behavior Research Articles

Evaluation of early phase dose finding algorithms in heterogeneous populations

Evaluation of the relative performance of different dose-finding designs is typically carried out using extensive simulations averaged over broad ranges of potential scenarios. Unfortunately, such evaluation lacks rigor, is not reliable and, in general, is not reproducible. Under identical experimental conditions one study will show that method B improves upon method A, another study will show the converse. This does not allow the user to proceed with the conviction of having made the more suitable choice. The source of the problem stems from our failure to address the fact that, in practice, we are dealing with heterogeneous populations. Leaning upon the thinking, and tools, of causal inference, we show here how to address the issue of heterogeneity and how to obtain rigorous, reliable and reproducible evaluation. Causal evaluation allows us to eliminate biases and unneeded sources of variability. The focus changes so that we look at the individual studies themselves rather than average behavior over many studies, i.e., we make comparisons before we average rather than the usual practice which is the other way around. Theoretical justifications and numerical illustrations are provided.

Hydrodynamic and experimental characterization of pumps as turbines

To estimate the performance, efficacy, modes of operation, hydrodynamic instabilities, and methodologies for harnessing energy from the pump as turbine (PAT), it is necessary to characterize these hydraulic turbomachines in all their modes of operation using an experimental test rig that simulates actual operating conditions. In this process, the characteristic curve of four quadrants of a turbomachine is constructed, especially its five modes: pump mode, brake pump mode, turbine mode, brake turbine mode, and reverse pump mode. In addition, with dynamic sensors installed in the pump volute, it is possible to know the hydrodynamic phenomena within PAT, finding its average behavior and frequency response, which is a tool for diagnosing the machine’s condition.

One Relation for All Wavelengths: The Far-ultraviolet to Mid-infrared Milky Way Spectroscopic R(V)-dependent Dust Extinction Relationship

Dust extinction is one of the fundamental measurements of dust grain sizes, compositions, and shapes. Most of the wavelength-dependent variations seen in Milky Way extinction are strongly correlated with the single parameter R(V) = A(V)/E(B − V). Existing R(V)-dependent extinction relationships use a mixture of spectroscopic and photometry observations, and hence do not fully capture all the important dust features or continuum variations. Using four existing samples of spectroscopically measured dust extinction curves, we consistently measure the R(V)-dependent extinction relationship spectroscopically from the far-ultraviolet (FUV) to mid-infrared for the first time. Linear fits of A(λ)/A(V) dependent on R(V) are done using a method that fully accounts for their significant and correlated uncertainties. These linear parameters are fit with analytic wavelength-dependent functions to determine the smooth R(V) (2.3–5.6) and wavelength (912 Å–32 μm) dependent extinction relationship. This relationship shows that the FUV rise, 2175 Å bump, and the three broad optical features are dependent on R(V), but the 10 and 20 μm features are not. Existing literature relationships show significant deviations compared to this relationship especially in the FUV and infrared (IR). Extinction curves that clearly deviate from this relationship illustrate that this relationship only describes the average behavior versus R(V). We find tentative evidence that the relationship may not be linear with R(V)−1 especially in the ultraviolet (UV). For the first time, this relationship provides measurements of dust extinction that spectroscopically resolve the continuum and features in the UV, optical, and IR as a function of R(V), enabling detailed studies of dust grain properties and full spectroscopic accounting for the effects of dust extinction on astrophysical objects.

The mechanical alignment of dust (MAD)

Context. Observations of polarized light emerging from aligned dust grains are commonly exploited to probe the magnetic field orientation in astrophysical environments. However, the exact physical processes that result in a coherent large-scale grain alignment are still far from being fully constrained. Aims. In this work, we aim to investigate the impact of a gas-dust drift on a microscopic level, potentially leading to a mechanical alignment of fractal dust grains and subsequently to dust polarization. Methods. We scanned a wide range of parameters of fractal dust aggregates in order to statistically analyze the average grain alignment behavior of distinct grain ensembles. In detail, the spin-up efficiencies for individual aggregates were determined utilizing a Monte Carlo approach to simulate the collision, scattering, sticking, and evaporation processes of gas on the grain surface. Furthermore, the rotational disruption of dust grains was taken into account to estimate the upper limit of possible grain rotation. The spin-up efficiencies were analyzed within a mathematical framework of grain alignment dynamics in order to identify long-term stable grain alignment points in the parameter space. Here, we distinguish between the cases of grain alignment in the direction of the gas-dust drift and the alignment along the magnetic field lines. Finally, the net dust polarization was calculated for each collection of stable alignment points per grain ensemble. Results. We find the purely mechanical spin-up processes within the cold neutral medium to be sufficient enough to drive elongated grains to a stable alignment. The most likely mechanical grain alignment configuration is with a rotation axis parallel to the drift direction. Here, roundish grains require a supersonic drift velocity, while rod-like elongated grains can already align for subsonic conditions. We predict a possible dust polarization efficiency in the order of unity resulting from mechanical alignment. Furthermore, a supersonic drift may result in a rapid grain rotation where dust grains may become rotationally disrupted by centrifugal forces. Hence, the net contribution of such a grain ensemble to polarization drastically reduces. In the presence of a magnetic field, the drift velocity required for the most elongated grains to reach a stable alignment is roughly one order of magnitude higher compared to the purely mechanical case. We demonstrate that a considerable fraction of a grain ensemble can stably align with the magnetic field lines and report a possible dust polarization efficiency of 0.6–0.9, indicating that a gas-dust drift alone can provide the conditions required to observationally probe the magnetic field structure. We predict that magnetic field alignment is highly inefficient when the direction of the gas-dust drift and magnetic field lines are perpendicular. Conclusions. Our results strongly suggest that mechanical alignment has to be taken into consideration as an alternative driving mechanism where the canonical radiative torque alignment theory fails to account for the full spectrum of available dust polarization observations.

Cognitive Uncertainty

Abstract This article documents the economic relevance of measuring cognitive uncertainty: people’s subjective uncertainty over their ex ante utility-maximizing decision. In a series of experiments on choice under risk, the formation of beliefs, and forecasts of economic variables, we show that cognitive uncertainty predicts various systematic biases in economic decisions. When people are cognitively uncertain—either endogenously or because the problem is designed to be complex—their decisions are heavily attenuated functions of objective probabilities, which gives rise to average behavior that is regressive to an intermediate option. This insight ties together a wide range of empirical regularities in behavioral economics that are typically viewed as distinct phenomena or even as reflecting preferences, including the probability weighting function in choice under risk; base rate insensitivity, conservatism, and sample size effects in belief updating; and predictable overoptimism and -pessimism in forecasts of economic variables. Our results offer a blueprint for how a simple measurement of cognitive uncertainty generates novel insights about what people find complex and how they respond to it.

Multiple slot nano-jet impingement cooling of a sinusoidal hot surface by using active rotating cylinders under magnetic field

In this study, cooling performance of a multi-slot jet impingement system for a wavy surface are explored under the triple combined effects of using magnetic field (MG-F), double active rotating cylinders and nanofluid. Double rotating cylinders which provide additional cooling are used while Galerkin weighed residual finite element method is used for the solution of the governing equations. Effects of Rew (rotational Reynolds number, between −1000 and 1000), Ha (MG-F strength between 0 and 30), MG-F inclination (between 0 and 90) and sub-cooling temperature of the active cylinders (dT between 0 and 10) on the cooling performance are assessed. Rotations of the double cylinders generally provide higher Nusselt number (Nu) while 41% and 18.9% increment in the Nu is obtained when using pure fluid and nanofluid. The average Nu behavior is different when using MG-F depending upon the rotations are active or not. Average Nu is sharply reduced by about 25.1% without rotations but it rises by about 89% at Ha = 10 by using rotations. The impacts of sub-cooling is very effective when rotations are active while up to 37.9% rise of Nu is obtained at Rew = −1000. When no cylinders are used, using MG-F reduced the average Nu by about 15.4%. The best cooling performance case in the absence of MG-F with cylinders is obtained at Rew = −1000 and dT = 10.

Swapping in lattice-based cell migration models.

Cell migration is frequently modeled using on-lattice agent-based models (ABMs) that employ the excluded volume interaction. However, cells are also capable of exhibiting more complex cell-cell interactions, such as adhesion, repulsion, pulling, pushing, and swapping. Although the first four of these have already been incorporated into mathematical models for cell migration, swapping has not been well studied in this context. In this paper, we develop an ABM for cell movement in which an active agent can "swap" its position with another agent in its neighborhood with a given swapping probability. We consider a two-species system for which we derive the corresponding macroscopic model and compare it with the average behavior of the ABM. We see good agreement between the ABM and the macroscopic density. We also analyze the movement of agents at an individual level in the single-species as well as two-species scenarios to quantify the effects of swapping on an agent's motility.

Augmenting Epidemic Models with Graph Neural Networks

Conventional epidemic models are limited in their ability to capture the dynamics of real world epidemics in a sense that they either place restrictions on the models such as their topology and contact process for mathematical tractability or focus only on the average global behavior, which lacks details for further analysis. We propose a novel modeling approach that augments the conventional epidemic models using Graph Neural Networks to improve their expressive power while preserving useful mathematical structures. Simulation results show that our proposed model can predict spread times in both node-level and network-wide perspectives with high accuracy having median relative errors below 15% for a wide range of scenarios.

Academic Dishonesty in the Dental Faculty: Relations Among Students’ Behavior, Attitudes, and Interpretation

Background: Academic dishonesty is the most important educational concern. According to previous studies, it is more common in several groups of students. To prevent academic dishonesty, it is important to know the extent of the problem. Accordingly, this study was designed to investigate the behaviors, attitudes, and interpretations of dental students regarding exam fraud in the 2015-2016 academic years. Methods: For this purpose, a three-part questionnaire was prepared, including demographic characteristics and specific questions. The specific questions included students’ behavior, attitudes, and interpretation in the form of three scenarios. A total of 163 questionnaires were collected, and the statistical analysis was performed using SPSS, version 20. The Mann-Whitney U test and the Kruskal-Wallis test were used to analyze the data. Results: The students consisted of 90 males (55.2%) and 73 females (44.8%), and their average age was 22.72±2 years (22.3±2.87 and 23.23±2.37 years for boys and girls, respectively). The results revealed that around 65.6% of students were generally aware of the fraud problem in the faculty and knew the cheaters (63.1%). Further, 55.2% of students believed that instructors should prevent cheating during the exam. Data analyses demonstrated that there were no significant differences between boys and girls in all research variables. Finally, the average behavior proportion and attitude of the first-year students were higher than those of other students. Conclusion: Based on the findings, the rate of fraud was high in dentistry schools and possibly in other medical schools, highlighting the importance of the creating culture in changing students’ attitudes.

Analytic Theory for the Dynamics of Wide Quantum Neural Networks.

Parametrized quantum circuits can be used as quantum neural networks and have the potential to outperform their classical counterparts when trained for addressing learning problems. To date, much of the results on their performance on practical problems are heuristic in nature. In particular, the convergence rate for the training of quantum neural networks is not fully understood. Here, we analyze the dynamics of gradient descent for the training error of a class of variational quantum machine learning models. We define wide quantum neural networks as parametrized quantum circuits in the limit of a large number of qubits and variational parameters. Then, we find a simple analytic formula that captures the average behavior of their loss function and discuss the consequences of our findings. For example, for random quantum circuits, we predict and characterize an exponential decay of the residual training error as a function of the parameters of the system. Finally, we validate our analytic results with numerical experiments.

Student Behavior Ratings and Response to Tier 1 Reading Intervention: Which Students Do Not Benefit?

Core reading instruction and interventions have differential effects based on student characteristics such as cognitive ability and pre-intervention skill level. Evidence for differential effect based on affective characteristics is scant and ambiguous; however, students with problem behavior are more often non-responsive to core reading instruction and intensive reading interventions. In this study, we estimated the range of students’ behavior ratings in which a core reading instruction intervention was effective using a data set including 3,024 students in K-3. Data came from seven independent studies evaluating the Individualized Student Instruction (ISI) Tier 1 reading intervention and were pooled using integrative data analysis. We estimated Johnson–Neyman intervals of student behavior ratings that showed a treatment effect both at the within and between classroom level. ISI was effective in improving reading scores (b = 0.51, p = .020, d = 0.08). However, students with very low or very high behavior ratings did not benefit from the approaches (range of behavior rating factor scores: −0.95–2.87). At the classroom level, students in classrooms with a higher average of problem behaviors did not benefit from ISI (average classroom behavior rating factor score: 0.05–4.25). Results suggest differentiating instruction alone is not enough for students with behavior problems to grow in reading ability.

Astronomical seeing and wind speed distributions with ERA5 data at Lenghu site on the Tibetan Plateau

ABSTRACT In this paper, we present comprehensive night-time seeing statistics at the Lenghu site using data collected between 2018 and 2021 using a differential image motion monitor. The results show that the median seeing is 0.80 arcsec, which slightly larger than that previously reported due to climate change. Additionally, we investigated the annual, seasonal, and monthly seeing statistics, as well as possible hourly seeing trends in each season. The results demonstrate that the seeing at the Lenghu site is very stable, with monthly median seeing varying from 0.6 to 0.95 arcsec. The seasonal dependence of seeing shows obvious variations over different years. The best year of seeing was 2019 (0.74 arcsec), and the best seeing occurred in spring (0.68 arcsec) to early summer (June, 0.63 arcsec), while the worst seeing occurred in winter (0.80 arcsec). The minimum seeing value throughout the night is at approximately three hours before dawn. Furthermore, wind speed profiles, especially V200 (particularly the wind speed at 200 mbar), are important parameters for evaluating astronomical sites in terms of their suitability for adaptive optics. We first show the complete monthly average behaviours of the wind speed profile and V200 using the European Center for Medium-Range Weather Forecast reanalysis data sets. The results demonstrate the annual periodicity and variability of V200, and the yearly V200 modulation function is also provided. V200 maintains large values throughout the autumn (average: 35.01 m s−1) and winter (average: 34.33 m s−1), while the minimum V200 occurs in spring (average: 27.93 m s−1).

The Behavioral Diversity of Domestic Cats Living in Gampong Meurandeh and Gampong Teungoh

Family felidae, the order of carnivores, includes Felis Domestica. Domestic cats can be kept as pets, wild domestic cats typically cluster in close proximity to human settlements. Feral domestic cats typically make use of human food resources that have been left over. As a result, the purpose of this research is to determine the variety of domestic cat behaviors in the area of Gampong Meurandeh and Gampong Teungoh in the Langsa Lama District of Langsa City in Aceh. The method used to observe the average daily behavior of domestic cats is by using survey methods and scan sampling carried out at 15 minute intervals. There were three categories of the observed cat's daily behavior: affiliative behavior, self-preservation, and negative behavior. Based on the study's findings, differences in daily behavior based on Gampong differences and time differences were dominated by self-care behavior, then affiliative behavior and then negative behavior. The morning and afternoon feeding times of the cats and humans in the two villages were not significantly different.

Short-Time Behavior in Arithmetic Asian Option Price Under a Stochastic Volatility Model with Jumps

In this paper, we study the short-time behavior of the arithmetic average of Asian option price (AOP) derived from a general class of the stochastic volatility model with jumps. The AOP that rarely has explicit expression can reduce the volatility in the option price because of the average of the underlying asset price over the time interval. We consider the future average process in the model which is a non-adapted process. By using the Malliavin calculus operators, we get a non-adapted Itô formula, and also a decomposition formula of the option price in the model. We apply the decomposition formula to find the short-time limit of the arithmetic AOP and the implied volatility.

PENGARUH SARAPAN TERHADAP PERILAKU PERCAYA DIRI PESERTA DIDIK SD N 4 KUTOARJO

The purpose of this study was to measure the magnitude of the influence of Breakfast (Friendly Greetings with Smiles and Hugs) on the Confident Behavior of SDN 4 Kutoharjo Students in the First Semester of the 2021/2022 Academic Year. This type of research is quantitative. The instrument in this study is a questionnaire (questionnaire). The population of the study was 357 learners. The sample of this study was 177 learners. The prerequisite test in this study is the Normality Test with the Kolmogorov-Smirnov Test. The hypothesis test in this study is the Paired Sample t Test. The result of the study was that there were differences in the confident behavior of students of SDN 4 Kutoharjo in the first semester of the 2021/2022 Academic Year before after breakfast. Before breakfast, the average self-confidence behavior belongs to the low category. After breakfast, the average self-confident behavior belongs to the high category. Such differences include significant according to a significance of 0.000 and a count t [58.06] which is greater than ttable (1.97353). This means that there is a large and significant effect of breakfast on confident behavior.

A Short‐Term Pumping Strategy for Hydraulic Tomography Based on the Successive Linear Estimator

AbstractIn this study, the random finite element method, a finite element method with random field generation techniques, was applied to investigate the cross correlations between the observed head and hydraulic conductivity and specific storage at different locations and different times in pumping tests. The results show that the two cross correlations between the pumping well and the observation well reach their maximums before pumping reaches a steady state. Specifically, the cross correlation between the observed head and hydraulic conductivity is the greatest when the temporal derivative of the observed head does not change significantly, and that between the observed head and specific storage is the greatest when the temporal derivative (the rate) of the observed head is maximum. Based on the results of cross‐correlation analysis, a short‐term pumping strategy for hydraulic tomography is proposed to obtain the spatial distribution of hydraulic conductivity and specific storage using the successive linear estimator. Furthermore, this strategy was validated by Monte Carlo simulations. This paper points out that the sensitivity and cross‐correlation analyses report the ensemble (averaged) behaviors of any heterogeneous aquifers, which is not necessarily suitable for one realization. Furthermore, Monte Carlo simulation is suggested for validating any groundwater inverse modeling result.

Mapping the magnetocaloric effect at the microscale on a ferromagnetic shape memory alloy with infrared thermography

An innovative study of the magnetocaloric effect (MCE) was performed by mapping the effect based on direct measurements of the temperature change during magnetic field cycles with microscopic resolution (85 μm) on a Co-doped Ni–Mn–Ga bulk sample using infrared thermography on the whole sample. The MCE maps were constructed for different sample temperatures (T sample), cycling both on heating (from 272.8 K up to T sample, with T sample ⩽ 327.0 K) and on cooling (from 340.0 K down to T sample, with T sample ⩾ 266.8 K), cycling a 1.2 T magnetic field at each T sample value. The MCE maps were calculated to evaluate the amplitude of the effect at the microscale for all T sample values. This allows to analyze the contribution of each micrometric portion of the sample to the spatially heterogeneous behavior that was found. Significant differences of the MCE on heating and cooling are present associated to inhomogeneity dynamics, mostly near the structural transformation. The amplitude of the MCE and its inhomogeneity are both much more pronounced on the heating process. On the cooling process the effect behaves quite homogeneously since the structural transformation already occurred during the cooling to reach T sample. The behavior of the MCE at selected map coordinates was scrutinized, revealing significant differences amongst sample locations. Moreover, the extreme amplitudes of MCE registered for diverse micro-regions occur at different temperatures, suggesting that the structural transformation occurs at varying temperatures and with different magnitudes. The study innovates by constructing MCE maps to evaluate minority behaviors in the MCE in contrast with the average behavior of the effect. This study displays the capability to discriminate the behavior of the transformation at the microscale.

Effectiveness of Papaya Leaf Extract (Carica papaya L.) for the Treatment of Koi (Cyprinus rubrofuscus) Infected with Aeromonas hydrophila Bacteria

The purpose of this study was to analyze the effect of giving papaya leaf extract (Carica papaya) and the most effective dose in inhibiting Aeromonas hydrophila bacterial infection in Koi (Cyprinus rubrofuscus). This research is an experimental study with four treatments: Control Treatment (K): 0 ppm, Treatment A: 1000 ppm, Treatment B, and Treatment C: 1400 ppm. Data were processed using SPSS Version 24 with Analysis (ANOVA) and Kruskal-Wallis H. The results showed that giving papaya leaf extract had an effect on inhibiting Aeromonas hydrophila bacterial infection in koi. The condition of the fish improved on the 7th day after immersion; it was shown that the way they swam began to return to normal, and the clinical symptoms reduced due to infection. The lowest inhibition level was in the control treatment, the condition of the fish worsened every day, and the highest survival was in treatment B, namely 86.67%, the average behavior scale is 5.00, and the average morphological scale is 5.00. The average water quality temperature is 27.2-28.1˚C, the average pH is 7.1-7.2, the average dissolved oxygen is 5.7-5.8 ppm, and the ammonia is 0.25 ppm.

Influence of Design Variables on the Financial Feasibility of Rainwater Harvesting Systems

Extensive implementation of rainwater harvesting (RWH) systems can promote substantial improvement in urban water resource management. Therefore, establishing the financial feasibility of RWH systems is imperative for their dissemination. This study evaluated the influence of rainfall time series indicators (average annual rainfall, seasonality index and behaviour of periods without precipitation) and design variables (catchment area, rainwater demand, number of inhabitants, potable water demand and rainwater tank size) on the financial feasibility of RWH systems in eight Brazilian cities. Correlations between rainfall indicators and financial feasibility were introduced, along with sensitivity analysis of design variables. Financial feasibility was obtained in 30% to 70% of the simulated scenarios. Initial investment and operating costs varied significantly among the eight cities according to local prices. Systems with a catchment area of 200 m2 were capable of supplying, on average, 90.5% of the maximum rainwater consumption observed in this study. Local variation of potable water tariff schemes affected the financial feasibility of RWH systems. The number of inhabitants was the most influential design variable on the financial feasibility of RWH systems, followed by the rainwater tank size. Places with lower rainfall seasonality indexes and lower incidence and duration of dry periods are likely to lead to greater financial feasibility.

Central limit theorems for heat equation with time-independent noise: The regular and rough cases

In this paper, we investigate the asymptotic behavior of the spatial average of the solution to the parabolic Anderson model with time-independent noise in dimension [Formula: see text], as the domain of the integral becomes large. We consider three cases: (a) the case when the noise has an integrable covariance function; (b) the case when the covariance of the noise is given by the Riesz kernel; (c) the case of the rough noise, i.e. fractional noise with index [Formula: see text] in dimension d = 1. In each case, we identify the order of magnitude of the variance of the spatial integral, we prove a quantitative central limit theorem for the normalized spatial integral by estimating its total variation distance to a standard normal distribution, and we give the corresponding functional limit result.