Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of instructional materials on decimal fractions to the conceptual change

Abstract This study investigates the effect on conceptual change of instructional materials about “decimal fractions” developed by adopting 4 stage constructivist learning model. The study was conducted with 30 students 6 th grade at a public elementary school in Trabzon during the spring term of 2008-2009 school year. Case study method was used in the study. The clinical interviews were made with 6 students just before the application and one month later. When the students’ responses to the interview questions after the application were investigated, it was identified that the number of students’ responses containing misconceptions was decreased at the end of the study. © 2011 Published by Elsevier Ltd. Keywords: Primary mathematics, decimal fractions, misconception, conceptual change, mathematics education 1. Introduction As mathematics is a cumulative branch of science, each concept learned is a step towards a new concept. Thus, a difficulty or incorrect information learned during a previous concept may cause difficulties while learning following concepts (Tirosh & Graeber, 1991). When students do not learn a concept in mathematics well or leave something missing, they face some problems and these problems may affect their future education. So, flaws in students’ learning may appear. If not corrected, these flaws may become misconceptions. In mathematics, it is important that misconceptions must be determined and ways to solve them must be found because prior concepts and information form a step towards following ones. Thus, a misconception regarded as unimportant in mathematics will cause misconceptions in following subjects (YOlmaz, 2007). Like many other subjects in mathematics, decimal fractions is a field in which misconceptions are frequently observed. Decimal fractions is one of the important concepts in mathematics because they can be read and written as in decimal system, they facilitate arithmetic operations and they are commonly used in measurement of length, area and in other fields of daily life (Baykul, 2001). Decimal fractions is one of the subjects which is difficult to understand on the part of students due to their abstractness. So, it has been a subject for research in a lot of domestic and foreign studies (Ardahan & Ersoy, 2002; Baki & Bell, 1997; Cankoy, 1998, 2000; Ersoy & Baugun, 2000;
Space-Time Diffusion Visualization using Bayesian Inference

Retail marketing geography has traditionally employed static gravity models for location analytics based on probabilistic consumer demand. Such models however, provide little insight into the dynamic space-time diffusionary processes and events within a store level trade area (SLTA) that lead up to the end state of market structure equilibrium condition which these models predict. In addition, attempts to display dynamic space-time events in GIS have produced visualizations that are perceptually complex and difficult to easily understand. Further those attempts fail to take advantage of transdisciplinary literature from psychology and brain science that suggest image simplicity and visual familiarity are the key elements to faster perception and better visuospatial understanding of objects, images and visualizations. We address these issues with our visualization model called Avatar. Avatar uses Bayesian inferences to link the Bass model to a spatial allocation methodology which is designed to provide faster and better visuospatial understanding of complex “geo-big-data”. We then introduce the steps necessary to create our Avatar, 3-D semaphoric space-time visualization diffusion object. Avatar was originally designed to visualize an ensemble model consisting of the integration of Bass, Huff and Berry concepts with a Bayesian inference framework for visualization of determinant attributes and demographics. In this way we can map the timed hierarchical diffusions of new innovative products throughout the SLTA as well as any evolving store network. Our approach is empirically supported by 5 years of panel data from the Southern California market. In addition, we provide priors linked to statistical demographic units (i.e. Census Blocks) for spatially allocating and distributing the Bass model forecasts through the SLTA. We conclude that our validated space-time diffusion visualization will potentially strengthen local “location analytics” and extend such analysis methodology across many spatial temporal domains.
Review Of Applied Mathematical Models For Describing The Behaviour Of Aqueous Humor In Eye Structures

Abstract In the paper, currently used methods for modeling the flow of the aqueous humor through eye structures are presented. Then a computational model based on rheological models of Newtonian and non-Newtonian fluids is proposed. The proposed model may be used for modeling the flow of the aqueous humor through the trabecular meshwork. The trabecular meshwork is modeled as an array of rectilinear parallel capillary tubes. The flow of Newtonian and non-Newtonian fluids is considered. As a results of discussion mathematical equations of permeability of porous media and velocity of fluid flow through porous media have been received.
The bright future: Imaging dynamic cellular events with quantum dots

Semiconductor quantum dots (QDs) are tiny light-emitting particles that have emerged as a new class of fluorescent labels for biology and medicine. Compared with traditional fluorescent probes, QDs have unique optical and electronic properties such as size-tuneable light emission, narrow and symmetric emission spectra, and broad absorption spectra that enable the simultaneous excitation of multiple fluorescence colours.
A general framework for functional regression modelling

Abstract Researchers are increasingly interested in regression models for functional data. This article discusses a comprehensive framework for additive (mixed) models for functional responses and/or functional covariates based on the guiding principle of reframing functional regression in terms of corresponding models for scalar data, allowing the adaptation of a large body of existing methods for these novel tasks. The framework encompasses many existing as well as new models. It includes regression for ‘generalized’ functional data, mean regression, quantile regression as well as generalized additive models for location, shape and scale (GAMLSS) for functional data. It admits many flexible linear, smooth or interaction terms of scalar and functional covariates as well as (functional) random effects and allows flexible choices of bases—particularly splines and functional principal components—and corresponding penalties for each term. It covers functional data observed on common (dense) or curve-specific (sparse) grids. Penalized-likelihood-based and gradient-boosting-based inference for these models are implemented in R packages refund and FDboost, respectively. We also discuss identifiability and computational complexity for the functional regression models covered. A running example on a longitudinal multiple sclerosis imaging study serves to illustrate the flexibility and utility of the proposed model class. Reproducible code for this case study is made available online.
Self-adaptive maximum-likelihood sequence estimation

The problem of estimating the most likely state sequence of a discrete-time finite-state Markov process with unknown parameters observed in independent noise arises in many important problems in digital communications, including self-adaptive equalization and adaptive multi-user detection. A maximum likelihood criterion over both the input sequence and the parameters is introduced for estimating the state sequence without using an embedded training sequence. Asymptotically, this estimator is close to the maximum-likelihood sequence estimator with completely known parameters. To facilitate the search for the most likely state sequence, we introduce computationally simple algorithms which are guaranteed to converge. Performance of the self-adaptive maximum-likelihood sequence estimator for the blind equalization problem is illustrated through numerical examples. <<ETX>>
Generalized bent-cable methodology for changepoint data: a Bayesian approach

ABSTRACT The choice of the model framework in a regression setting depends on the nature of the data. The focus of this study is on changepoint data, exhibiting three phases: incoming and outgoing, both of which are linear, joined by a curved transition. Bent-cable regression is an appealing statistical tool to characterize such trajectories, quantifying the nature of the transition between the two linear phases by modeling the transition as a quadratic phase with unknown width. We demonstrate that a quadratic function may not be appropriate to adequately describe many changepoint data. We then propose a generalization of the bent-cable model by relaxing the assumption of the quadratic bend. The properties of the generalized model are discussed and a Bayesian approach for inference is proposed. The generalized model is demonstrated with applications to three data sets taken from environmental science and economics. We also consider a comparison among the quadratic bent-cable, generalized bent-cable and piecewise linear models in terms of goodness of fit in analyzing both real-world and simulated data. This study suggests that the proposed generalization of the bent-cable model can be valuable in adequately describing changepoint data that exhibit either an abrupt or gradual transition over time.
Seasonality, Academic Calendar and School Drop-outs in Developing Countries∗

Rural families face tradeoffs when deciding whether to keep children in school or have them work in the field. School calendars can magnify this tradeoff by not accommodating agricultural harvesting cycles within the schedule. We show this misalignment has a significant and sizable effect on school continuation. In Bangladesh, a rise in seasonal labor demand due to the Aman paddy harvesting typically coincides with the yearly final examination of schools. Employing the lunar calendar variation of Ramadan school holidays as a natural experiment framework — that forced schools to re-schedule final examinations to a pre-harvest season in 1999 — and comparing it with a typical year of 2002, we find that annual exams overlapping with major local harvesting period inflate the school dropout by 6.5 to 8.4 percentage points between the agricultural and non-agricultural households. Age-specific cohort analysis using a nationally representative household survey also supports this evidence. Exploiting state-level academic calendar variation, we executed a similar analysis for India and found supporting evidence to validate our findings. Our paper suggests the careful design of school calendars in developing countries by adequately addressing local seasonality.
Adapting AIC to conditional model selection

In statistical settings such as regression and time series, we can condition on observed information when predicting the data of interest. For example, a regression model explains the dependent variables $y_1, \ldots, y_n$ in terms of the independent variables $x_1, \ldots, x_n$. When we ask such a model to predict the value of $y_{n+1}$ corresponding to some given value of $x_{n+1}$, that prediction's accuracy will vary with $x_{n+1}$. Existing methods for model selection do not take this variability into account, which often causes them to select inferior models. One widely used method for model selection is AIC (Akaike's Information Criterion \cite{Akaike}), which is based on estimates of the KL divergence from the true distribution to each model. We propose an adaptation of AIC that takes the observed information into account when estimating the KL divergence, thereby getting rid of a bias in AIC's estimate.
Coding sets with asymmetric information

We study the following one-way asymmetric transmission problem, also a variant of model-based compressed sensing: a resource-limited encoder has to report a small set $S$ from a universe of $N$ items to a more powerful decoder (server). The distinguishing feature is asymmetric information: the subset $S$ is comprised of i.i. d. samples from a prior distribution $\mu$, and $\mu$ is only known to the decoder. The goal for the encoder is to encode $S$ obliviously, while achieving the information-theoretic bound of $|S| \cdot H(\mu)$, i.e., the Shannon entropy bound. We first show that any such compression scheme must be {\em randomized}, if it gains non-trivially from the prior $\mu$. This stands in contrast to the symmetric case (when both the encoder and decoder know $\mu$), where the Huffman code provides a near-optimal deterministic solution. On the other hand, a rather simple argument shows that, when $|S|=k$, a random linear code achieves near-optimal communication rate of about $k\cdot H(\mu)$ bits. Alas, the resulting scheme has prohibitive decoding time: about ${N\choose k} \approx (N/k)^k$. Our main result is a computationally efficient and linear coding scheme, which achieves an $O(\lg\lg N)$-competitive communication ratio compared to the optimal benchmark, and runs in $\text{poly}(N,k)$ time. Our "multi-level" coding scheme uses a combination of hashing and syndrome-decoding of Reed-Solomon codes, and relies on viewing the (unknown) prior $\mu$ as a rather small convex combination of uniform ("flat") distributions.
Multi-gate organic neuron transistors for spatiotemporal information processing

Due to similar transmission characteristics of biological synaptic activities, neuromorphic behaviors simulated by organic electrochemical transistors (OECTs) is of great interest. In this letter, the fabrication and performance of multi-gate poly(3-hexylthiophene) (P3HT) OECTs with ion-gel gating are reported. The neuromorphic behaviors, such as dendrite correlated excitatory postsynaptic current (EPSC), paired pulse facilitation, and modulation, were simulated in the OECTs. These behaviors were observed to depend on the degree of temporal correlation and distance between the in-plane-gate and the channel. More importantly, by using dendritic integration from two different gates, spatiotemporally correlated outputs were also emulated. The spatial orientations of the input pulse are defined, and changing the orientation will result in a change in the EPSC amplitude. Our results provide a way to construct spatiotemporally neural network based on multi-gate OECTs.
Effect of graphene-oxide on the microstructure and charge carrier transport of polyaniline nanocomposites under low applied electric fields

We report a study on the preparation and characterization of polyaniline-graphene oxide (PANI-GO-X) nanocomposites focusing in the study of its structure, microstructure, and correlations with electrical transport properties under low applied electric fields. X-ray diffraction analysis showed evidence of graphene oxide (GO) blending between polyaniline fibers, and according to small angle X-ray scattering, the fractal dimensionality was quasi-one dimensional for all nanocomposites. Confocal Raman spectroscopy revealed that the addition of GO leads to a notorious decrease of the polaron population of polyaniline. A significant increase in resistivity was observed for PANI-GO-X nanocomposites with respect to pure polyaniline, in agreement with the decrease in the polaron population. The electrical transport mechanism could be explained by an Arrhenius behavior at high temperatures (T > 255 K) and a broad transition with a logarithmic dependence of the activation energy with temperature for the low temperatu.
Tandem Array of Repeated Genes

Succharomyces strains capable of fermenting maltose contain any one of five telomere-associated M A L loci. Each MAL locus is a complex of three genes encoding the three functions required to ferment maltose: maltose permease (GENE I), maltase (GENE 2) and the M A L trans-activator (GENE 3). All five loci have been cloned and all are highly sequence homologous over at least a 9.0 kbp region containing these GENEs (Charron et al., Genetics 122, 307-331, 1989). Our initial studies of strains carrying the M A W locus indicated the presence of linked, repeated MALhomologous sequences (Michels and Needleman, Mol. Gen. Genet. 191,225-230, 1983). Here we report our analysis of the centromere-proximal M A W-linked sequences and show that the complete M A W locus spans approximately 40 kbp and consists of tandemly arrayed, partial repeats of the three GENE sequences described above. In addition, the structure of the MAL3 locus is compared to that of three partially functional alleles of M A W . These alleles were shown to contain only M A W 1 and MAL32 and their structure suggests that they resulted from M A W deletions removing the sequences centromere-proximal to M A W I . The amplification and rearrangement of the telomere-linked MAL3 sequences are discussed in the context of studies on other telemere-associated sequences from yeast and other species.
P-CFT in Early Parkinson's Disease

The monoamine transporter was studied in 4 healthy controls and 5 patients with early Parkinson's disease (PD), who had not received any antiparkinsonian medication, by means of positron emission tomography (PET) using two novel ligands, ["CIP-CIT and ["CIP-CFT. Both ligands showed highest uptake in the striatum. There was intermediate accumulation of activity in the thalamus and midbrain, which was more marked for ["CIP-CIT than for [llC]P-CFT. In the cortical areas, uptake of both ligands was not different from that seen in the cerebellum. In the controls, the putamento-cerebellum and caudate-to-cerebellum ratios for [l'C]P-CFT were higher than those for [llC]P-CIT (putamen: 3.15 5 0.39 for ["CIP-CFT, and 1.84 i 0.10 for ["CIP-CIT caudate: 3.15 ? 0.31 for [llC]P-CFT, and 1.95 ? 0.17 for [l'CIP-CIT). Reduction from mean control value in PD patients was greater for [WIP-CFT (45% in the putamen contralateral to the predominant symptoms, P < 0.001) than for [11Cl/3-CIT (20%, P > 0.05). ["CIP-CFT uptake in the caudate nucleus was also diminished in PD patients (to 80% of the control mean, P < 0.05), whereas [llC]p-CIT was within normal range (reduced to 90% of the control mean). These results indicate that both ["CIP-CIT and ["Clp-CFT are useful PET ligands to study brain monoamine transporter in healthy controls and in patients with PD. However, [WIP-CFT seems superior to [llC]P-CIT in this respect.
Multislice First-Pass Myocart Conventional Clinical Scanne lial Perfusion Imaging on a r

A technique is demonstrated for the acquisition and processing of multislice, first-pass contrast-enhanced perfusion images in the myocardium. The acquisition is a modification of “keyhole” imaging in which time series images are acquired by sampling a limited segment of k-space, corresponding to the low spatial frequencies. In the modification demonstrated here, keyhole samples are divided into two groups that are sampled on alternate cardiac cycles. The alternate “missing” k-space portions are synthesized by Fourier interpolation. Visualization of contrast agent accumulation by image subtraction is demonstrated. A motion artifact reduction process using time domain Fourier filtering is used to reduce artifacts from respiration. Studies were performed on 46 patients at 1.5 T using gadoteridol (0.05-0.1 mmol/kg) injected into the right antecubital vein in conjunction with radionuclide imaging. Fully concordant studies were noted in 27 of these patients. Remaining studies were either partially or completely discordant for reasons relating to the differing natures of radionuclide versus MR contrast agent characteristics.
Factors InvolvedinCOX-2 Inhibition

BACKGROUND. Epidemiological studies have shown a decreased risk of prostate cancer among men who regularly take aspirin or other non-steroidal anti-inflammatory drugs (NSAIDs). In this study, we examined a dose-dependent effect of a cyclooxygenase-2 (COX-2) inhibitor, celecoxib against transgenic adenocarcinoma of the mouse prostate. METHODS. Efficacy of four different doses in parts per million of celecoxib, such as 200 ppm, 400 ppm, 600 ppm, and 1,000 ppm representing very low, moderate, and high doses, respectively were tested against adenocarcinoma of the mouse prostate using a transgenic adenocarcinoma of the mouse prostate (TRAMP) model assay. RESULTS. Dietary supplement of celecoxib at doses of 400 ppm, 600 ppm, and 1,000 ppm are most effective againstmPIN (mouse prostatic intraepithelial neoplasia) and adenocarcinoma of the prostate. Tumor growth inhibition by celecoxib was associated with increased rate of apoptosis. At 1,000 ppm, a complete inhibition of the PIN lesions was extended to limit the growth of adenocarcinoma (from 85% to 15%) and metastasis of the mouse prostate. The chemopreventive effect was significant (P< 0.01) at 400 ppm, 600 ppm, and 1,000 ppm doses compared to that at the lowest dose of 200 ppm and control. A dose-dependent effect on tumor growth inhibition was associated with reduced expression of NF-kBp65 and COX-2. CONCLUSIONS. Dietary supplementation of celecoxib at different doses provides evidence for the suppression of prostate adenocarcinoma tumor growth in a dose-dependent manner. Suppression of adenocarcinoma by celecoxib further limits the growth of metastatic prostate cancer. Prostate 66: 257–265, 2006. # 2005 Wiley-Liss, Inc.
Reply

We read with interest the article by Kamath et al. and the accompanying editorial by Forman and Lucey concerning a new prognostic score for cirrhosis.1,2 The investigators are to be congratulated for endeavoring to create more objective measures of prognosis than those in current use, which are susceptible to “manipulation” by concerned clinicians. However, we have a problem with the data as presented in Table 3. This gives the 3-month death rates for 4 groups of patients with varying MELD scores. They are (1) hospitalized patients, (2) ambulatory noncholestatic patients, (3) ambulatory primary biliary cirrhosis patients, and (4) historical controls. If the MELD score were the sole predictor of death, then survival should be the same for patients within each MELD group. However, this clearly is not the case. In each of the MELD categories ( 9, 10-19, 20-29), hospitalized patients appear to have an increased mortality compared with the 2 ambulatory groups, although statistical analysis of this was not done. We have performed an analysis of hospitalized versus ambulatory noncholestatic patients and found a statistically significant difference in survival for a MELD score 10-19 (P .0001). The difference for patients with a score 9 is not significant, whereas that for a score 20-29 is P . 06. It would be important to do a similar analysis for 12-month survival. Kamath et al. state that in-hospital survival was not affected by factors such as spontaneous bacterial peritonitis, variceal hemorrhage, ascites, and encephalopathy. Thus, there seem to be factors not measured by the investigators that may be influencing mortality in already hospitalized patients, an issue that could be important if the MELD score becomes the sole arbiter of priority listing for liver transplantation.
Phospholipase C-6 in Cultured Cortical Neurons

S. Shimohama, A. Akaike, Y. Tamura, H. Matsushima, T. Kume, S. Fujimoto, T. Takenawa, and J. Kimura Department of Neurology, Faculty of Medicine (S.S., H.M., J.K.), and Department of Pharmacology, Faculty of Pharmaceutical Sciences (A.A., T.K.), Kyoto University, and Department of Biochemistry, Kyoto Pharmaceutical University (S .F.), Kyoto, Department of Neurophamacology , Faculty of Pharmacy and Pharmaceutical Sciences, Fukuyama University, Fukuyama (Y .T.), and Department of Oncobiology , Medical Institute of Tokyo University, Tokyo (T.T.), Japan