Miracle-dz/UniFAR-FTUs huggingface dataset:
Caltech Faint Galaxy Redshift Survey. VIII. Analysis of the Field J0053+1234

The results of a spectroscopic investigation of a complete sample of objects with Ks<20 mag in a 2' by 7. ′3 field at J005325+1234 are reported. Redshifts were successfully obtained for 163 of the 195 objects in the sample; these redshifts lie in the range [0.173, 1.44] and have a median of 0.58 (excluding 24 Galactic stars). The redshift identifications are believed to be almost complete for z<0.8. Approximately one-half of the galaxies lie in five narrow redshift features with local velocity dispersions of ~300 km s-1. These narrow redshift "peaks" are primarily populated both by absorption-line galaxies and the most luminous galaxies in the sample, although the incidence of emission lines in the luminous galaxies increases with redshift. The estimated dynamical masses of these redshift peaks, and the sky distribution of the galaxies within them, appear similar to groups or poor clusters of galaxies in the local universe at various stages of virialization. Some groups of galaxies therefore form at epochs z>1.5, and the galaxies in such groups appear to be coeval and to show little sign of ongoing star formation. The galaxies outside the redshift peaks are also clustered, albeit more weakly, are less luminous and more frequently exhibit strong emission lines. These "isolated" galaxies therefore appear, on average, to form stars at later epochs than the strongly clustered galaxies. The galaxy spectral energy distributions (SEDs) derived from our UBVRIK photometry are also very closely correlated with the galaxy spectral types and luminosities. These results have strong implications for the analysis of redshift surveys at intermediate redshift. The sample is used to investigate the evolution of the combined galaxy luminosity function back to z=0.8. No significant change is found in the characteristic luminosity L*, and only weak color changes are detected, consistent with passive evolution. The blue galaxy-luminosity function is more dwarf rich than the red galaxy-luminosity function. No significant change in the comoving density is found in this sample out to z~1.4, assuming that the objects without redshifts (16% of the sample) are galaxies, essentially all of which have z>0.8. This suggests that mergers are not important among the objects in this sample. A population of extremely red objects with (R-K)>5 mag exists in the infrared-selected sample; all four such objects with redshifts are found to be absorption-line galaxies with z~1. Most of the very red objects therefore appear to be galaxies with z≳1 that are not heavily reddened by dust. A measure of the UV extinction at 2400 Å for the emission-line galaxies of a factor of 2 is obtained, implying only modest UV extinction in high-redshift star-forming galaxies.
Credit Constrained R&D Spending and Technological Change

Firms often rely on external financing in order to conduct R&D. We ask to what extent discriminatory behaviour of the funds provider affects the industry evolution. The model is based on an evolutionary framework by Nelson and Winter. A firm chooses the amount of its R&D spending in an adaptive fashion where technological improvement is essential for survival in the competitive market. Firms can finance their activities by using retained profits or applying for credit. However, they have a clear hierarchy in choosing the source of funds and saved profits are always used up first. There is endogenous discriminatory lending as the banking sector provides credit according to firms’ individual features. It compares profitability and market share across firms when assessing creditworthiness. The model is able to capture features of innovation and diffusion of technology. Results show that the availability of credit is crucial for technological change in a non-linear fashion and that the industry evolves faster if the bank focuses on market share in assessing creditworthiness.
Self-confidence and strategic behavior

We suggest that overconfidence (conscious or unconscious) is motivated in part by strategic considerations, and test this experimentally. We find compelling supporting evidence in the behavior of participants who send and respond to others’ statements of confidence about how well they have scored on an IQ test. In two-player tournaments where the higher score wins, a player is very likely to choose to compete when he knows that his own stated confidence is higher than the other player’s, but rarely when the reverse is true. Consistent with this behavior, stated confidence is inflated by males when deterrence is strategically optimal and is instead deflated (by males and females) when luring (encouraging entry) is strategically optimal. This behavior is consistent with the equilibrium of the corresponding signaling game. Overconfident statements are used in environments that seem familiar, and we present evidence that suggests that this can occur on an unconscious level.
Tests of factorial structure and measurement invariance for the Student Engagement Instrument: Evidence from middle and high school students

ABSTRACT While past research has shown the Student Engagement Instrument (SEI) to be an adequate measure of school engagement, this self-report questionnaire currently exists as a number of different versions, each comprising various subsets of the original 35 items. The first objective of this study was to use confirmatory factor analysis to assess the fit of different factorial structures with data acquired from 1,229 Portuguese adolescents in the 7th to 12th grades. Our second objective was then to test measurement invariance across gender and school year and to examine the psychometric properties of the factorial structure of the SEI with the best fit to our data. Our analyses revealed that the 15-item Brief-SEI structure fit our data best, and continued to fit the data well with the addition of two-higher order factors representing cognitive and psychological engagement. This higher-order model showed strict measurement invariance across gender and strong measurement invariance across school year. Internal consistency of the subscales was good and the subscales were correlated (albeit weakly) with academic performance. This study therefore provides a synthesis of current research on the SEI, and offers a validated instrument that is consistent with Appleton’s theoretical conceptualization of student engagement.
Multistate and Multistage Synchronization of Hindmarsh-Rose Neurons With Excitatory Chemical and Electrical Synapses

The new phenomena of the multistate synchronization of Hindmarsh-Rose (HR) neurons with both excitatory chemical and electrical synapses over the complex network are analytically studied. The regions for coupling strengths to achieve local synchronization are explicitly obtained. Such regions are characterized by the second largest eigenvalue λ2 of the electrical connection matrix and the number k of chemical signals each neuron receives. The dynamics of the multistate synchronization includes the coexistence of stable regular bursting and periodic/steady-state behaviors. Our theory predicts that recurrent networks formed by a certain cell types in layers 4 and 6 in cat area 17 could lead to multistate synchronization. These are in contrast with coupled oscillator systems or coupled map lattices where only single-state synchronization is found. It should also be noted that if the parameters of HR neurons are chosen resulting in an irregular (chaotic) bursting, then the coexistence state would contain chaotic attractor. Our method employed here is quite general. For instance, it can be immediately applied to other coupled nervous systems such as FitzHugh-Nagumo and Morris-Lecar nervous systems. The analytical tools and concepts needed include coordinate transformations, matrix measures, monotone dynamics and time averaging estimates.
Growth, efficiency, and yield of commercial broilers from 1957, 1978, and 20051

The effect of commercial selection on the growth, efficiency, and yield of broilers was studied using 2 University of Alberta Meat Control strains unselected since 1957 and 1978, and a commercial Ross 308 strain (2005). Mixed-sex chicks (n = 180 per strain) were placed into 4 replicate pens per strain, and grown on a current nutritional program to 56 d of age. Weekly front and side profile photographs of 8 birds per strain were collected. Growth rate, feed intake, and measures of feed efficiency including feed conversion ratio, residual feed intake, and residual maintenance energy requirements were characterized. A nonlinear mixed Gompertz growth model was used to predict BW and BW variation, useful for subsequent stochastic growth simulation. Dissections were conducted on 8 birds per strain semiweekly from 21 to 56 d of age to characterize allometric growth of pectoralis muscles, leg meat, abdominal fat pad, liver, gut, and heart. A novel nonlinear analysis of covariance was used to test the hypothesis that allometric growth patterns have changed as a result of commercial selection pressure. From 1957 to 2005, broiler growth increased by over 400%, with a concurrent 50% reduction in feed conversion ratio, corresponding to a compound annual rate of increase in 42 d live BW of 3.30%. Forty-two-day FCR decreased by 2.55% each year over the same 48-yr period. Pectoralis major growth potential increased, whereas abdominal fat decreased due to genetic selection pressure over the same time period. From 1957 to 2005, pectoralis minor yield at 42 d of age was 30% higher in males and 37% higher in females; pectoralis major yield increased by 79% in males and 85% in females. Over almost 50 yr of commercial quantitative genetic selection pressure, intended beneficial changes have been achieved. Unintended changes such as enhanced sexual dimorphism are likely inconsequential, though musculoskeletal, immune function, and parent stock management challenges may require additional attention in future selection programs.
Plasticity-Associated Gene Krox24/Zif268 Is Required for Long-Lasting Behavioral Effects of Cocaine

The extracellular signal-regulated kinases (ERKs) 1/2 pathway is stimulated by drugs of abuse in striatal neurons through coincident activation of dopamine D1 and glutamate NMDA receptors and is critical for long-lasting behavioral effects of these drugs. Although regulation of transcription is a major target of ERK, the precise mechanisms by which it contributes to behavioral alterations is not known. We examined the role of Zif268, an immediate-early gene induced by drugs of abuse under the control of ERK, in behavioral responses to cocaine using knock-in mutant mice in which Zif268 was replaced by LacZ. No biochemical or behavioral differences between mutant and wild-type mice were observed in basal conditions or in acute responses to cocaine injection. In contrast, locomotor sensitization to single or repeated cocaine injections was dramatically diminished in both heterozygous and homozygous Zif268 mutant mice. Conditioned place preference in response to cocaine was prevented in Zif268-deficient mice. This effect was not attributable to a general learning deficit because the mutant mice displayed normal conditioned place preference when food was used as reward. Our results provide direct genetic evidence for the requirement of Zif268 for long-lasting association of environmental context with specific behavioral responses after short exposures to cocaine. They also underline the common molecular machinery involved in long-lasting drug-induced behavioral alterations and the formation of other types of memory.
Observations of auroral medium frequency bursts

Auroral medium frequency (MF) bursts are broadband impulsive radio emissions observed at ground level during the breakup phase of auroral substorms. Measurements made in northern Canada during 1995–1996 show the seasonal and local time dependencies of MF burst emissions, provide case-study evidence for a null in the MF burst spectrum near twice the ionospheric electron gyrofrequency, and establish a correlation between MF burst and impulsive auroral hiss. High time resolution measurements reveal that MF bursts occur in 100–300 μs wave packets which sometimes appear periodic having a period close to the ionsopheric proton gyroperiod. The timescales of the MF burst wave packets are comparable to those of whistler solitary waves recently observed with the FAST satellite.
Fluorine Abundance Variations as a Signature of Enhanced Extra Mixing in Red Giants of the Globular Cluster M4

We show that enhanced extra mixing in low-mass red giants can result in a fluorine abundance that is correlated with abundance variations of other elements participating in H burning, such as C, N, O, and Na. This finding is used to explain the fluorine abundance variations recently found in bright red giants of the globular cluster M4.
Tablets as an educational tool for enhancing preschool science

ABSTRACT Information communication technologies (ICT) is increasingly being introduced in the preschool level, but questions have been raised regarding its potential to develop content knowledge or specific skills. This quasi-experimental study looked into the impact that hand-held tablets can have on science learning outcomes in five-year-olds. Four classes from two preschool institutions in Buenos Aires, Argentina, were selected for a six-week intervention. All four classes received training and an inquiry-based science teaching sequence, with one group from each institution also receiving tablets and specific guidance on how to incorporate them into their science lessons. Post-intervention test results showed significant improvements in science outcomes for all students, but no significant difference between the tablet-enhanced classrooms and those taught without ICT. Challenges and opportunities are discussed with regard to including tablets for teaching science at the preschool level.
Virulence Gene Profile and Multilocus Variable-Number Tandem-Repeat Analysis (MLVA) of Enteroinvasive Escherichia coli (EIEC) Isolates From Patients With Diarrhea in Kerman, Iran

Background Enteroinvasive Escherichia coli (EIEC) isolates cause dysentery in humans. Several virulence factors associated with EIEC pathogenesis have been characterized. Multilocus variable-number tandem-repeat analysis (MLVA) is a PCR-based method that has been used for genotyping bacterial pathogens. Objectives The aim of this study was to investigate the distribution of virulence factor genes in EIEC isolates from patients with diarrhea in Kerman, Iran, as well as the genetic relationships between these isolates. Patients and Methods A total of 620 diarrheic stool samples were collected from patients attending two hospitals in Kerman from June 2013 to August 2014. All isolates were confirmed as EIEC by PCR for the ipaH gene. The EIEC isolates were evaluated by PCR for the presence of nine virulence genes (ial, set1A, sen, virF, invE, sat, sigA, pic, and sepA). MLVA was performed for all EIEC isolates. Results A total of 11 EIEC isolates were identified, and all were positive for the ial gene. The invE and virF genes were observed in 81.8% of the isolates, while sen, sigA, and pic were detected in 72.7%, 63.6%, and 27.3% of the isolates, respectively. None of the isolates were positive for the sat, set, and sepA genes. Using MLVA, the 11 total isolates were divided into five types. Conclusions By studying the profiles of virulence genes and MLVA, it can be concluded that EIEC isolates do not have high heterogeneity and are derived from a limited number of clones.
Impact of carbon nanotube length on electron transport in aligned carbon nanotube networks

Here, we quantify the electron transport properties of aligned carbon nanotube (CNT) networks as a function of the CNT length, where the electrical conductivities may be tuned by up to 10× with anisotropies exceeding 40%. Testing at elevated temperatures demonstrates that the aligned CNT networks have a negative temperature coefficient of resistance, and application of the fluctuation induced tunneling model leads to an activation energy of ≈14 meV for electron tunneling at the CNT-CNT junctions. Since the tunneling activation energy is shown to be independent of both CNT length and orientation, the variation in electron transport is attributed to the number of CNT-CNT junctions an electron must tunnel through during its percolated path, which is proportional to the morphology of the aligned CNT network.
Efficient independent component analysis

Independent component analysis (ICA) has been widely used for blind source separation in many fields, such as brain imaging analysis, signal processing and telecommunication. Many statistical techniques based on M-estimates have been proposed for estimating the mixing matrix. Recently, several nonparametric methods have been developed, but in-depth analysis of asymptotic efficiency has not been available. We analyze ICA using semiparametric theories and propose a straightforward estimate based on the efficient score function by using B-spline approximations. The estimate is asymptotically efficient under moderate conditions and exhibits better performance than standard ICA methods in a variety of simulations.
Same Question, Different Answers: Theorizing Victim and Third Party Decisions to Report Crime to the Police

The current study attempts to address a key, but underdeveloped, area in crime reporting literature: the decisions of non-victims to report crime. Drawing on a theory of criminal justice decision-making, we argue that the decision to report a crime reflects a rational process, where the individual considers his or her goals, potential actions, and the relative ability of those actions to achieve the specified goals. Differences in each of these areas result in different decision-making processes for victims and third parties. We offer a preliminary test of our arguments using data from the National Crime Victimization Survey. In general, we find support for our expectations, with third party reporting decisions more heavily influenced by crime seriousness and less so by the offender’s relationship with the victim than are victim reporting decisions. In concluding, we argue that third party reporters should be focal points of future reporting analyses.
An Introduction to Classification and Regression Tree (CART) Analysis

Introduction A common goal of many clinical research studies is the development of a reliable clinical decision rule, which can be used to classify new patients into clinically-important categories. Examples of such clinical decision rules include triage rules, whether used in the out-of-hospital setting or in the emergency department, and rules used to classify patients into various risk categories so that appropriate decisions can be made regarding treatment or hospitalization. Traditional statistical methods are cumbersome to use, or of limited utility, in addressing these types of classification problems. There are a number of reasons for these difficulties. First, there are generally many possible " predictor " variables which makes the task of variable selection difficult. Traditional statistical methods are poorly suited for this sort of multiple comparison. Second, the predictor variables are rarely nicely distributed. Many clinical variables are not normally distributed and different groups of patients may have markedly different degrees of variation or variance. Third, complex interactions or patterns may exist in the data. For example, the value of one variable (e.g., age) may substantially affect the importance of another variable (e.g., weight). These types of interactions are generally difficult to model, and virtually impossible to model when the number of interactions and variables becomes substantial. Fourth, the results of traditional methods may be difficult to use. For example, a multivariate logistic regression model yields a probability of disease, which can be calculated using the regression coefficients and the characteristics of the patient, yet such models are rarely utilized in clinical practice. Clinicians generally do not think in terms of probability but, rather in terms of categories, such as " low risk " versus " high risk. " Regardless of the statistical methodology being used, the creation of a clinical decision rule requires a relatively large dataset. For each patient in the dataset, one variable (the dependent variable), records whether or not that patient had the condition which we hope to predic t accurately in future patients. Examples might include significant injury after trauma, myocardial infarction, or subarachnoid hemorrhage in the setting of headache. In addition, other variables record the values of patient characteristics which we believe might help us to predict the value of the dependent variable. For example, if one hopes to predict the presence of subarachnoid hemorrhage, a possible predictor variable might be whether or not the patient's headache was sudden in onset; another possible …
Kernel methods in steganalysis

Steganography is the art of covert communication. Its goal is achieved by hiding secret messages into innocuous objects such as digital images, audio files, etc. As any other technology, steganography can be used for malicious purpose. The need to detect steganographic objects give rise to steganalysis, a complementary task to steganography. The main focus of this dissertation is on steganalysis of JPEG images, as the JPEG image format is nowadays the most frequently used image format. In the first part of the dissertation, a detector recognizing six popular steganographic algorithms is presented. This detector is novel in many ways. First, it not only detects the presence of a secret message, but also assigns the image to a class according to the algorithm used to embed the message. Second, it detects stego content in single-compressed as well as in double-compressed JPEG images. Third, it offers superior accuracy in comparison to prior art. The detector is based on feature extraction and supervised training of two banks of multi-classifiers implemented by Support Vector Machines. The first bank targeted to single-compressed images contains a separate multi-classifier trained for each JPEG quality factor from a certain range. Another bank of multi-classifiers is trained for double-compressed images for the same range of primary quality factors. Multi-classifier banks are preceded by a pre-classifier detecting double-compression and estimating the primary quantization table. The second part of the dissertation presents a method for benchmarking security of steganographic algorithms. We argue that a good benchmark should be dependent only on the model chosen to represent cover and stego objects (feature set). While the KL divergence would be a preferable measure, because it is a fundamental quantity, there are practical difficulties in computing it. Therefore a Maximum Mean Discrepancy (MMD) is proposed as a measure of steganographic security, because it is well understood theoretically, and is numerically stable even in high-dimensional spaces.