Miracle-dz/UniFAR-FTUs huggingface dataset:
The dependence of galaxy clustering on tidal environment in the Sloan Digital Sky Survey

The influence of the Cosmic Web on galaxy formation and evolution is of great observational and theoretical interest. We investigate whether the Cosmic Web leaves an imprint in the spatial clustering of galaxies in the Sloan Digital Sky Survey (SDSS), using the group catalog of Yang et al. and tidal field estimates at $\sim2h^{-1}$Mpc scales from the Mass-Tides-Velocity data set of Wang et al. We use the $\textit{tidal anisotropy}$ $\alpha$ (Paranjape et al.) to characterise the tidal environment of groups, and measure the redshift-space 2-point correlation function (2pcf) of group positions and the luminosity- and colour-dependent clustering of group galaxies using samples segregated by $\alpha$. We find that all the 2pcf measurements depend strongly on $\alpha$, with factors of $\sim20$ between the large-scale 2pcf of objects in the most and least isotropic environments. To test whether these strong trends imply `beyond halo mass' effects for galaxy evolution, we compare our results with corresponding 2pcf measurements in mock catalogs constructed using a halo occupation distribution that only uses halo mass as an input. We find that this prescription qualitatively reproduces $\textit{all}$ observed trends, and also quantitatively matches many of the observed results. Although there are some statistically significant differences between our `halo mass only' mocks and the data -- in the most and least isotropic environments -- which deserve further investigation, our results suggest that if the tidal environment induces additional effects on galaxy properties other than those inherited from their host halos, then these must be weak.
Instrumental learning in social interactions: Trait learning from faces and voices

Recent research suggests that reinforcement learning may underlie trait formation in social interactions with faces. The current study investigated whether the same learning mechanisms could be engaged for trait learning from voices. On each trial of a training phase, participants (N = 192) chose from pairs of human or slot machine targets that varied in the (1) reward value and (2) generosity of their payouts. Targets were either auditory (voices or tones; Experiment 1) or visual (faces or icons; Experiment 2) and were presented sequentially before payout feedback. A test phase measured participant choice behaviour, and a post-test recorded their target preference ratings. For auditory targets, we found a significant effect of reward only on target choices, but saw higher preference ratings for more generous humans and slot machines. For visual targets, findings from previous studies were replicated: participants learned about both generosity and reward, but generosity was prioritised in the human condition. These findings provide one of the first demonstrations of reinforcement learning of reward with auditory stimuli in a social learning task, but suggest that the use of auditory targets does alter learning in this paradigm. Conversely, reinforcement learning of reward and trait information with visual stimuli remains intact even when sequential presentation introduces a delay in feedback.
JSSE 13 ( 2 ) The Social Sciences in Higher Education

Specialized journals examine the teaching and learning of the social sciences in Higher Education . These include, for example, the highly regarded Teaching Sociology, or, more recently the Journal of Political Science Education, Journal of Legal Education and International Journal of Pluralism and Economics Education, to name but a few. These journals capture a significant amount of knowledge and experience. However, there is little coherence in terms of research and a lack of a well-developed academic sub-discipline around Higher Education in the social sciences. Furthermore, most of the discourses within the cited journals
Modulation Doped SiGe – Si MQW for Low-Voltage High-Speed Modulators at 1 . 3 m

We propose a new type of light modulator at 1.3 and 1.55 m using a –modulation-doped SiGe–Si multiplequantum-well structure ( -MDMQW) integrated in a low-loss silicon-on-insulator (SOI) waveguide. The structure is embedded in the intrinsic region of a vertical p-i-n diode realized on SOI substrate. We present theoretical calculation of the effective index modulation determined by the variation of the confined hole concentration with an applied external field. A practical device is proposed and a calculation of optical modulation efficiency is presented. Estimation of on–off switching time based on evaluation of characteristic time of emission from localized levels in quantum wells and RC characteristics of the device are presented. This device presents the advantage of a broad optical bandwidth in comparison to the modulators based on quantumconfined Stark effect, low insertion loss, high-speed (above 1 GHz), and full compatibility with silicon technology.
Integration of eQTL and Machine Learning Methods to Dissect Causal Genes with Pleiotropic effects in Genetic Regulation Networks of Seed Cotton Yield

Expression quantitative trait loci (eQTL) provide a powerful means of investigating the biological basis of genome-wide association study (GWAS) results and exploring complex traits or phenotypes. In addition to identifying the causal gene in cis, eQTL analysis also reveals a large number of trans-regulated genes located on different chromosomes, which form a gene regulatory network (GRN) that complements the GWAS locus. However, the dissection of a GRN and the crosstalk underlying multiple agronomical traits, along with prioritizing important genes in eQTL-derived GRNs, remains a major challenge. In this study, we generated 558 transcriptional profiles of lint-bearing ovules at one day post-anthesis (DPA) from a selective core cotton germplasm, from which we identified 12,207 eQTLs. By integrating with a GWAS catalog, we found that 66 out of 187 (35.29%) known phenotypic GWAS loci are colocalized with 1,090 eQTLs, forming 38 major functional GRNs predominantly (30 out of 38) associated with seed size-related phenotypes. Of the eGenes, 34 were shared between at least two functional GRNs, exhibiting pleiotropic effects, such as NF-YB3, GRDP1, and IDD7. Narrow-sense heritability analysis showed that the heritability increased with combining the eQTLs with GRNs compared to those with previous yield trait GWAS loci. The extreme gradient boosting (XGBoost) machine learning approach was then applied to predict seed cotton yield phenotypes based on gene expression. Top-ranking eGenes (NF-YB3, FLA2, and GRDP1) derived by XGBoost with pleiotropic effects on yield traits were validated, along with their potential roles by correlation analysis, domestication selection analysis, and transgenic plants. This study provides insights into the mining of GRNs in relation to the pleiotropy of phenotype. The combination of eQTL and machine learning approaches is efficient in improving the genetic dissection of agricultural traits.
Investigating the Relationship Between Self-efficacy and Perceived Importance of Communication Skills Among Engineering Students

Zhen Zhao is a Ph.D student at Arizona State University in the Fulton Schools of Engineering Polytechnic School. He earned a B.S. in Computer Science and a M.S. in Software Engineering, both from XI’an Jiaotong University in China. He also received a M.S.E in Industrial Engineering from Arizona Stat University. Zhen’s research interest include engineering student mentor-ship ability development, engineering research center education and diversity impact evaluation, engineering student adaptability development, and engineering graduate student attrition. Combining strength of mathematics modeling and statistics, 5+ years experience in collegiate teaching, Zhen is passionate and dedicated in preparing future engineering work force.
Analyzing Aptitudes for Learning: Inductive Reasoning.

A major focus of the psychology of instruction is understanding and facilitating the changes in cognition and performance that occur as an individual moves from low to higher competence in a domain of knowledge and skill. A new program of research which examines the initial state of the learner as a component of this transition in competence is described in this 8-part document. Part 1 introduces two previous attempts to relate aptitude to instruction: differential aptitude tests and aptitude treatment interaction. Part 2 provides an overview of the two general research approaches to aptitude analysis, the cognitive correlates approach and the cognitive components approach. The approach taken in the present research effortis described as a task analytic approach that considers basic processes, executive strategies, and content knowledge in aptitude test performances of skilled and less skilled individuals. Part 3 considers the relationship between inductive reasoning and general ability. Common generic properties of inductive tasks are discussed as are different types of inductive items on aptitude tests. Part 4 outlines earlier theories on analogical reasoning performance. Problem features, processing models, item processing data and theory, item errors, and performance are analyzed for figural, numerical, and verbal analogy solutions in parts 5 through 7. A final part discusses results_ of research, concluding that a number of interrelated factorS differentiate high and low skill individuals. These factors include management of memory load, organization of an appropriate knowledge base, and procedural knowledge of task constraints. (LP) *********************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. *********************************************************************** 0 ANALYZING APTITUDES FOR LEARNING: INDUCTIVE REASONING
Verification of daily precipitation amount forecasts in Armenia by ERA‐Interim model

Verification of 12‐h daily precipitation amount forecasts is considered in Armenia making use of ERA‐Interim model output data. The performance of ERA‐Interim model is evaluated against observations of 30 meteorological stations of Armenia over the period 1996–2010. Daily precipitation amounts possess high spatio‐temporal variability in Armenia associated with complex orography. The verification results have shown that the mentioned variability of precipitation amounts is not reproduced appropriately by forecasted data of ERA‐Interim model.
A NEW RECORD OF PARASITIC NEMATODE APHELENCHOIDES MACROSPICA (APHELENCHIDA: APHELENCHOIDIDAE) FROM PAKISTAN

This paper report Aphelenchoides macrospica, that is discover for the first time in Pakistan. During a survey from village Sarai Naurang, District Lakki Marwat, Khyber Pakhtunkhwa from their rhizosphere of paper flower Bougainvillea spectabilis. A. macrospica belonging to the family Aphelenchoididae, and placed within Group 2: because of tail with one or sometimes two mucronate structure, based on four lateral lines, tail terminus shape and spicule features. A new record of parasitic nematode is briefly described and illustrated herein.
Peer Review of Writing: Learning from Revision using Peer Feedback and Reviewing Peers' Texts

To better understand the ways in which peer feedback can vary across contexts to shape learning outcomes, the current dissertation examined how student ability levels shapes peer review. Peer review involves opportunities to learn from receiving feedback and providing feedback. Both elements were considered within one larger experiment. A sample of 189 students enrolled in an Introduction to Psychological Science course participated in this experiment. As part of the requirements for class, students wrote a first draft of their paper, reviewed four peers' papers, revised their draft based on peer feedback, and wrote a new paper on a different topic. In this experiment, I manipulated to whom the students provided feedback and from whom they received feedback in order to observe the relationships between writer ability, quality of text reviewed, and ability of the feedback source. In the first study, I determined which types of comments had an impact on draft quality and whether there were differences in the amounts received and implemented depending on the writer ability and feedback source. In the second study, I examined the extent to which students could learn from reviewing peers' texts and how the ability of the writer and the quality of the text being reviewed influenced the amount of improvement. Based on the findings from the two studies, theoretical and pragmatic implications were offered.
Comparison of Sinuous and MAW Spiral Antennas for Wideband, Dual Polarized Multi-Arm Applications

Abstract : Recent requirements for wideband dual polarized antennas with good pattern circular symmetry have centered on two feed candidates: cavity backed Modulated Ann Width (MAW) spiral and Sinuous antennas. Both of these antennas are capable of arbitrarily wide bandwidth operation; practical bandwidths are limited by photo-etching and feedpoint considerations. The properties of these antennas appear not to be widely known and to date the useful range of design parameters have not been published. This paper will show and compare the properties of two corresponding models of the multi-arm MAW spiral and Sinuous antennas. The feeds will be compared for the four-ann case which yields dual circular polarization or orthogonal linear operation as well as six-arm versions which can provide both sum and difference mode operation.
Macroeconomic determinants of non-performing loans in Mongolia: the influence of currency mismatch and bank size

Non-performing loans (NPLs) is leading indicator of financial system health. Understanding the determinants of credit quality is essential to conducting stress test and macro prudential policy. The macroeconomic determinants of NPLs have been found to differ between countries and are potentially sensitive to model specification, particularly a mismatch between the loan currency (foreign/domestic) and sector orientation (tradeable/non-tradeable). This paper examines the macro-determinants of NPLs in Mongolia using monthly panel data for 14 banks between December 2003 and December 2019. Using a system GMM approach for the overall sample and subsamples isolating systemically important banks, I find foreign currency loan quality to be more sensitive to macroeconomic variables and big banks more exposed to the currency mismatch problem.
Two weight norm inequalities for fractional integral operators and commutators

In these lecture notes we describe some recent work on two weight norm inequalities for fractional integral operators, also known as Riesz potentials, and for commutators of fractional integrals. These notes are based on three lectures delivered at the 6th International Course of Mathematical Analysis in Andalucia, held in Antequera, Spain, September 8-12, 2014. They are, however, greatly expanded to include both new results and many details that I did not present in my lectures due to time constraints.
An Analysis of Students’ Brain Activity when Participating in Different Learning Activities

Scott Ramsay is an Associate Professor, Teaching Stream in the department of Materials Science and Engineering at the University of Toronto, in Toronto, Canada, and a registered professional engineer in Ontario. Scott earned his PhD in Materials Science and Engineering from the University of Toronto. Scott’s current primary academic interests are in improving the quality of undergraduate engineering education through the use of various reusable learning objects. Scott has taught extensively in Material Science, teaching courses ranging from introductory materials science to thermodynamics, diffusion, materials selection, manufacturing, biomaterials, and building science.
K-Models Clustering, a Generalization of K-Means Clustering

Abstract K-means operates by selecting initial cluster centers and then itera-tively assigning points to clusters base on the proximate cluster centerand updating cluster centers. If we regard ﬁnding good cluster centersas a statistical parameter estimation problem then estimating the pa-rameters of other statistical models yields a space of novel clusteringmethods. In this paper we prototype the idea using least squares ﬁt ofa line to members of a data partition in place of estimation of clustercenters. The method can accurately reconstruct lines used to gener-ate a given data set. The sum-of-squared-error statistic is an excellentquality measure for detecting discovery of a superior model. Data setswithout a linear structure show that the statistical model or modelsused must be adapted to the data. 1 Introduction Clustering is an exploratorytechnique fortentatively classifying data. Clus-tering algorithms are used to search for patterns in data, to reduce thesize of a data set by selecting representatives of clusters, and to generatehypotheses about the character of a data set. This study introduces K-models clustering, a natural generalization of K-means clustering[2, 5]. Thesimilarity measure that places data items in the same K-means cluster isproximity according to a distance measure. K-models clustering modiﬁesK-means by replacing proximity to a cluster center with minimal squarederror according to one of K statistical models.K-means selects a set of K initial cluster centers. It then iterativelyassigns points to clusters according to proximity to a cluster centers andthen recomputes cluster centers as the mean position of the cluster. Thiscontinues until points stop changing clusters and the ﬁnal collection ofclusters is reported. It is possible to take the point of view that the locationof the cluster centers is a parameterestimation problem. Once this has beendone, it is natural to ask what the consequences of replacing the parameterestimation problem for good cluster centers with parameter estimation for
Broadband Applications and the Digital Home

* Part One: Delivery to the home * Chapter 1: Broadband Access Technologies * Chapter 2: Satellite - A New Opportunity for Broadband Access * Part Two: Networking the Home * Chapter 3: Introducing Home Area Networks * Chapter 4: Broadband in the Home * Chapter 5: Residential Gateways * Chapter 6: Home Area Network Technologies * Chapter 7: Standards for Broadband Customer Premises Equipment * Part Three: Living in the Home * Chapter 8: Domesticating Broadband - What Really Matters to Consumers * Chapter 9: Is the Future Really Always-On? * Chapter 10: Digital Living - People Centred Innovation and Strategy * Chapter 11: Digital Homes - For Richer For Poorer, Who Are They For? * Part Four: Applications * Chapter 12: Clients, Servers and Broadband * Chapter 13: Bandwidth-on-Demand Networks - a Solution to Peer-to-Peer * Chapter 14: A 3-D Telepresence Collaborative Working Environment * Chapter 15: A Virtual Studio Production Chain * Part Five: The future digital home * Chapter 16: Personal Virtual Humans - from Inhabiting the TalkZone to Populating the Digital Home * Chapter 17: Hype and Reality in the Future Home
USE OF RESPONSE SURFACE METHODOLOGY AND ARTIFICIAL NEURAL NETWORK APPROACH FOR METHYLENE BLUE REMOVAL BY ADSORPTION ONTO WATER HYACINTH

The release of coloured effluents from various dying industries are of great concern due to the challenge involved in the treatment process. In present work, response surface methodology (RSM) and artificial neural network (ANN) were used to predict the color removal using adsorption process. Water hyacinth (WH) was used as an economical adsorbent for color removal from aqueous solution in a batch system. The individual effect of influential parameter viz. initial pH, MB (dye) concentration, and the adsorbent dose were studied using the central composite design of RSM. The RSM result was used as an input data along with final pH (non-controllable parameter) after adsorption to train the ANN model. Color removal of 96.649% was obtained experimentally at the optimized condition. A comparison between the experimental data and model results shows a high correlation coefficient (R2RSM = 0.99 and R2ANN = 0.98) and showed that the two models predicted MB removal indicating WH can be used as an adsorbent for color removal from dye wastewater.
Data Production Methods for Harmonized Patent Statistics: Patentee Name Harmonization

Patent documents are one of the most comprehensive data sources on technology development. As such, they provide a unique source of information to analyze and monitor technological performance. Patent indicators are now used by companies and by policy and government agencies alike to assess technological progress on the level of regions, countries, domains, and even specific entities such as companies, universities and individual inventors. In this paper, we develop a comprehensive method to achieve harmonization of patentee names in an automated way so that analysis at the level of patentees can be facilitated. The method has been applied to an extensive set of all patentee names found for all EPO patent applications published between 1978 and 2004 and all granted USPTO patents published between 1991 and 2003. As completeness (the extent to which the name-harmonization procedure is able to capture all name variants of the same patentee) and accuracy (the extent to which the name-harmonization procedure correctly allocates name variants to a single, harmonized patentee name) do not go hand in hand, priority has been given to accuracy. Before discussing in detail the methodology and its effects as applied to the EPO and USPTO patentee name list, we will first clarify the difference between patentee name harmonization and legal entity identification. In addition, we will briefly expand on the methods and approaches previously developed to address the issue of patentee name harmonization, in order to shed light on our specific contribution. Finally, future refinements and extensions are discussed.
Puntos críticos del tirón de arrancada en halterofilia

La finalidad de este estudio es analizar la tecnica en halterofilos de nivel internacio-nal, siguiendo las curvas de las fuerzas verticales. Este trabajo, con la ayuda de una plataforma de fuerzas y de un sistema de analisis de video en dos dimensiones, localiza los diferentes puntos criticos que intervienen en estas curvas a lo largo del tiron de arrancada en halterofilia. Seis halterofilos de nivel internacional han realizado tres pruebas de arrancada cada uno, utilizando cargas al 70%, 80% y 90% de sus marcas maximas. En el transcurso del tiron se notan tres puntos criticos: dos maximas (Tz I , Fz 1) y (Tz3, Fz3) separadas por un minimo (Tz2, Fz2). Dichos puntos traducen, desde un plano cinematico y dinamico las transiciones de las fases tecnicas. En el conjunto de los datos calculados, dos variables del sistema halterofilo-barra (Tz 3 I-Tz I y Fz I/Fz 0) y cuatro va-riables estudiadas sobre la cinematica de la barra (altura max., altura max./talla, al-tura max./longitud piernas y velocidad med.), presentan diferencias significativas entre las pruebas a lo largo del test de rango de Wilcoxon. La utilizacion de una matriz de correlaciones (test de Spear-man), asociada a una matriz de probabili-dades, demuestra correlaciones elevadas entre los diferentes puntos. Es necesario subrayar la importancia del punto critico (Tz I , Fz I ) con respecto a los otros puntos y sus repercusiones sobre las variables cinematicas de la barra (r = 0,83, P < 0,0 I ) para Fz1 y DV max. a 90% de la carga maxima). El primer pico de fuerza Fz I es alcanzado mas rapidamente y las relaciones de fuerza disminuyen (en concreto Fz 1 / Fz0), respectivamente igual, a 1,65 ± 0,10, despues 1,54 ± 0,08 a 70% y 90% maxim. La disminucion de la relacion de la fuerza Fz1 /Fz2 y el aumento de Fz3/FzI, con respecto a las variables cinematicas de la barra, son significativos de las posibilidades del halterofilo.