Miracle-dz/UniFAR-FTUs huggingface dataset:
Examining Teacher Talk During Transition Episodes in a Preschool Classroom

While scholars have highlighted the importance of the language environment in the preschool classroom, there remains a dearth of research on the precise nature of the language children encounter in these early academic settings, especially during transitions (i.e., periods when children are involved in personal or classroom activities as they move from one setting to another across the preschool day). This study examined a teacher’s linguistic practices during transitions in a preschool classroom located in a public school, based on video observations and transcripts of teacher talk. Overall, the study found that teacher talk during transition periods is significantly less rich than during other activity settings combined. However, results also suggest that teacher talk varies within transition type. Interestingly, the teacher still managed to a limited extent to seize opportunities to engage in rich extended conversations with students during transitions. These findings point to the need to include transitions in studies of teacher language in preschool, especially given the considerable amount of time spent in such instances throughout the day.
Space-Time Transmit Diversity Combined with Frequency-domain Equalization for Single-carrier Transmission

In a frequency-selective fading channel, the transmission performance of single-carrier (SC) transmission significantly degrades due to severe inter-symbol-interference (ISI). In this paper, the joint use of space-time transmit diversity (STTD), receive antenna diversity and frequency-domain minimum mean square error (MMSE) equalization in SC transmission is studied. Space-time encoding and decoding for frequency-domain MMSE equalization is proposed. The bit error rate (BER) performance of SC transmission is evaluated by computer simulation. It is found that joint use of STTD, receive antenna diversity and frequency-domain MMSE equalization can significantly improve the BER performance in a severe frequency-selective fading channel.
Seasonal and latitudinal variability of troposphere Δ14CO2: Post bomb contributions from fossil fuels, oceans, the stratosphere, and the terrestrial biosphere

During the mid‐1960s, large seasonal amplitudes were observed in surface measurements of Δ14C in the Northern Hemisphere. These seasonal oscillations were initially caused by stratosphere‐troposphere exchange, with the injection of bomb 14C into the troposphere during winter and spring mixing. Here we show how fossil, ocean, and terrestrial biosphere fluxes modified the stratospheric signal during the 1960s, and the evolution of each of these components in the post bomb era. In our analysis, we used the Goddard Institute for Space Studies (GISS) atmospheric tracer model, gross ocean CO2 fluxes from the Lawrence Livermore National Laboratory (LLNL) ocean model, and terrestrial CO2 fluxes from a biosphere‐atmosphere model driven by normalized difference vegetation index and surface air temperatures. We found that 14C‐depeleted respiration from the terrestrial biosphere partially canceled the 14C‐enriched stratosphere flux in the Northern Hemisphere in the mid and late 1960s. In more recent decades, our analysis suggested that the terrestrial biosphere contribution to the Δ14C seasonal cycle reversed phase, with the terrestrial biosphere currently releasing relatively 14C‐enriched CO2 that mixes with relatively depleted troposphere CO2. The timing of this reversal depended on the residence times of carbon within the footprint of the observation station. Measurements of Δ14C in respiration from tundra and boreal ecosystems in Alaska provide evidence that some boreal forests have undergone this transition, while some tundra ecosystems have not. We predict that over the next century, several features of the latitudinal profile of Δ14C will substantially change because of continued fossil fuel emissions in the Northern Hemisphere, and the partial release of bomb 14C that has accumulated in Southern Hemisphere oceans.
Proteomic Scan for Tyrosinase Peptide Antigenic Pattern in Vitiligo and Melanoma: Role of Sequence Similarity and HLA-DR1 Affinity1

Immune responses contribute to the pathogenesis of vitiligo and target melanoma sometimes associated with vitiligo-like depigmentation in some melanoma patients. We analyzed the sera from patients with vitiligo and cutaneous melanoma for reactivity toward tyrosinase peptide sequences 1) endowed with low level of similarity to human proteome, and 2) potentially able to bind HLA-DR1 Ags. We report that the tyrosinase autoantigen was immunorecognized with the same molecular pattern by sera from vitiligo and melanoma patients. Five autoantigen peptides composed the immunodominant anti-tyrosinase response: aa95–104FMGFNCGNCK; aa175–182 LFVWMHYY; aa176–190FVWMHYYVSMDALLG; aa222–236IQKLTGDENFTIPYW, and aa233–247 IPYWDWRDAEKCDIC. All of the five antigenic peptides were characterized by being (or containing) a sequence with low similarity level to the self proteome. Sera from healthy subjects were responsive to aa95–104FMGFNCGNCK, aa222–236IQKLTGDENFTIPYW, and aa233–247 IPYWDWRDAEKCDIC, but did not react with the aa175–182LFVWMHYY and aa176–190FVWMHYYVSMDALLG peptide sequences containing the copper-binding His180 and the oculocutaneous albinism I-A variant position F176. Our results indicate a clear-cut link between peptide immunogenicity and low similarity level of the corresponding amino acid sequence, and are an example of a comparative analysis that might allow to comprehensively distinguish the epitopic peptide sequences within a disease from those associated to natural autoantibodies. In particular, these data, for the first time, delineate the linear B epitope pattern on tyrosinase autoantigen and provide definitive evidence of humoral immune responses against tyrosinase.
Efficient image classification using sparse coding and random forest

Image representation and classifier are playing key roles in image classification. An effective combination of image representation and classifier could raise the accuracy of image classification. A novel image classification algorithm based on sparse coding and random forest is proposed in this paper. Sparse coding is adopted to train a dictionary of visual words and then to convert SIFT descriptors into sparse vectors. Afterward several pooling methods and spatial partition are used to pool these sparse vectors to represent images. Random forest, an efficient multiclass classifier, is employed to classify the sparse vectors of images. The outcome of the experiments demonstrates that the proposed algorithm outperforms the state-of-the-art in image classification using Caltech-101 and Scene-15 datasets.
Multiply Quantified Internally Headed Relative Clause in Japanese: A Skolem Term Based Approach

This paper presents an analysis of Internally Headed Relative Clause (IHRC) construction in Japanese within the framework of Combinatory Categorial Grammar [Steedman 2000]. Shimoyama [1999] argues that when an IHRC appears within the scope of a universal quantifier, the interpretation of the IHRC exemplifies E-type anaphora and that the LF representation of the IHRC should have a variable bound by the quantifier in the matrix clause. To accommodate this argument Shimoyama posits a free variable of a functional type to which the bound variable is applied, and whose denotation is determined by the context-dependent assignment function. However, since there is in principle no limit to the number of quantifiers in the matrix clause (and accordingly that of bound variables in the IHRC), the semantic type of the free variable would be highly ambiguous if the IHRC occurs within the scope of multiple quantifiers. The current analysis assumes that the interpretation of IHRCs exhibits an instance of generalized Skolem term [Steedman 2005], a term whose denotation varies with the value of bound variables introduced by scope-taking operators, but which is interpreted as a constant in the absence of such operators. This paper provides a straightforward account for the semantics of the construction without invoking the complexities of the type ambiguity of free variables.
LogDet Divergence based Metric Learning using Triplet Labels

Metric learning is fundamental to lots of learning algorithms and it plays significant roles in many applications. In this paper, we present a LogDet divergence based metric learning approach to a learn Mahalanobis distance over input space of the instances. In the proposed model, the most natural constraint triplets are used as the labels of the training samples. Meanwhile, in order to avoid overfitting problem, the model uses the LogDet divergence to regularize the obtained Mahalanobis matrix as close as possible to a given matrix. Besides, a cyclic iterative algorithm is presented to solve the objective function and accelerate the metric learning process. Furthermore, this paper constructs a novel dynamic triplets building strategy to guarantee that the most useful triplets are used in every training cycle. Experiments on benchmark data sets demonstrates the proposed model achieve an improved performance when compared with the state-of-theart methods.
Social Media Marketing Analytics: a Multicultural Approach Applied to the Beauty & cosmetics Sector

We present in this paper a multicultural approach to social media marketing analytics, applied in two Facebook brand pages: French (individualistic culture, the country home of the brand) versus Saudi Arabian (collectivistic culture, one of its country hosts), which are published by an international beauty & cosmetics firm. Using social network analysis and content analysis, we identify the most popular posts and the most influential users within these two brand pages and highlight the different communities emerging from brand and users interactions. These communities seem to be culture oriented when they are constructed around socialization branded posts and product-line oriented when advertising branded posts are concerned.
Markus Ehrnrooth Analyses of Flight to Quality in Financial Markets

of Master's Thesis From time to time prices of financial instruments react strongly and simultaneously. These sharp market movements are generally symptoms of risk aversion among investors and are called flight to quality, because investors rush to buy safe assets during them. This thesis studies the application of volatility-and correlation estimates derived from high frequency financial data to predict such flights to quality. The empirical part of the thesis is based on 5 minute data sampled from the period September 2004 to March 2008. Volatility-and correlation estimators based on high frequency data are presented and estimated. The challenges posed by high frequency data, as well as methods for mitigating their effects, are presented. The results concerning flight to quality prediction using the estimators built show that these may not be used reliably for flight to quality prediction. The indicators may however prove useful in more general risk management. Sidoantal: 85 Acknowledgements This thesis was written for the research department of Estlander & Rönnlund as an independent research project. The research department has over a long period of time been active in mathematical research in the field of financial markets in order to devise better financial products for the customers of Es-tlander & Rönnlund. There are several people to whom I wish to express my gratitude. First, I would like to thank my supervisor Ph.D Niclas Carlsson for his advice and insights that have helped me finish this thesis. Second, Martin Estlander deserves my special recognition. Without his enthusiasm for research and openness to new ideas, Estlander & Rönnlund would not be the academically orientated and research focused firm it is today. Third, I am grateful to Professor Ahti Salo for supervising this thesis. without you I would not have enjoyed working on this thesis half as much as I have. Finally, I want to thank my family and friends for their support and friendship. I am convinced you will keep me going in the future as well.
Experiences of racism and race-based traumatic stress: The moderating effects of cyberracism, racial/ethnic identity, and forgiveness

Race is a source of trauma that may result in a wide range of mental and physical health consequences (Pieterse, Todd, Neville, & Carter, 2012). In Chapter 1, I conduct a systematic review of research on race-based traumatic stress. Although studies have documented the link between perceived discrimination and race-based traumatic stress, there is a need to explore factors that can amplify or buffer this relationship. Thus, in Chapter 2, I examine three theorized moderators of the relationship between racial discrimination and race-based traumatic stress: cyberracism, racial/ethnic identity, and trait forgivingness. Data was collected from a sample of 397 African American community-based participants using Mechanical Turk. Results from the study revealed that perceptions of racism were significant and positively correlated to race-based traumatic stress symptoms (r = .62, p < .01). As predicted, cyberracism strengthened this relationship. Forgivingness buffered this relationship. Against my prediction, regardless of level of racial/ethnic identity, there was a similar association between perceived racial discrimination and race-based traumatic stress. I discuss implications for future research. I also discuss practical implications for practitioners, especially regarding habits of engaging social media during periods of intensified racial conflict on social media. INDEX WORDS: racial discrimination, racism, trauma, racial identity, ethnic identity, stress, social media, cyberracism, forgiveness EXPERIENCES OF RACISM AND RACE-BASED TRAUMATIC STRESS: THE MODERATING EFFECTS OF CYBER RACISM, RACIAL/ETHNIC IDENTITY, AND FORGIVENESS
Probing the Dynamics of Solvation and Structure of the OH- Ion in Aqueous Solution from Picosecond Transient Absorption Measurements

The reaction of intracomplex proton transfer (44BPY-.HO-H) → 44BPYH. + OH- that follows the photoreduction of 4,4’-bipyridine (44BPY) into its anion radical 44BPY- in the presence of 1,4-diazabicyclo[2.2. 2]octane (DABCO) is investigated in acetonitrile-water mixtures by using picosecond transient absorption. The dependence of the appearance kinetics of the 44BPYH. radical on the water content reveals a highly diffusional proton transfer process that is controlled by the dynamics of solvation of the released hydroxide ion. The results are interpreted on the basis of a two-step mechanism where an intermediate solvation complex (44BPYH.)OH-(H2O)3 is formed first before evolving toward a final four-water hydration structure OH-(H2O)4.
Downregulated MTAP expression in myxofibrosarcoma: A characterization of inactivating mechanisms, tumor suppressive function, and therapeutic relevance

Myxofibrosarcomas are genetically complex and involve recurrently deleted chromosome 9p, for which we characterized the pathogenically relevant target(s) using genomic profiling. In 12 of the 15 samples, we detected complete or partial losses of 9p. The only aggressiveness-associated, differentially lost region was 9p21.3, spanning the potential inactivated methylthioadenosine phosphorylase (MTAP) that exhibited homozygous (4/15) or hemizygous (3/15) deletions. In independent samples, MTAP gene status was assessed using quantitative- and methylation-specific PCR assays, and immunoexpression was evaluated. We applied MTAP reexpression or knockdown to elucidate the functional roles of MTAP and the therapeutic potential of L-alanosine in MTAP-preserved and MTAP-deficient myxofibrosarcoma cell lines and xenografts. MTAP protein deficiency (37%) was associated with MTAP gene inactivation (P < 0.001) by homozygous deletion or promoter methylation, and independently portended unfavorable metastasis-free survival (P = 0.0318) and disease-specific survival (P = 0.014). Among the MTAP-deficient cases, the homozygous deletion of MTAP predicted adverse outcome. In MTAP-deficient cells, MTAP reexpression inhibited cell migration and invasion, proliferation, and anchorage-independent colony formation and downregulated cyclin D1. This approach also attenuated the tube-forming abilities of human umbilical venous endothelial cells, attributable to the transcriptional repression of MMP-9, and abrogated the susceptibility to L-alanosine. The inhibiting effects of MTAP expression on tumor growth, angiogenesis, and the induction of apoptosis by L-alanosine were validated using MTAP-reexpressing xenografts and reverted using RNA interference in MTAP-preserved cells. In conclusion, homozygous deletion primarily accounts for the adverse prognostic impact of MTAP deficiency and confers the biological aggressiveness and susceptibility to L-alanosine in myxofibrosarcomas.
Classification of transient time-varying signals using DFT and wavelet packet based methods

The classification of transient time-varying signals is important for industrial, biomedical and military applications. The attack phase of piano sounds is used as an example for transient, time-varying signals in a real data application. Discrete Fourier transform and time-invariant wavelet packet based algorithms are used alternatively for feature extraction. The training set is used for determining an appropriate feature selection. A classifier checks whether the generated features are sufficient in order to identify the correct piano. Classification results are presented and discussed.
Nearly Maximum Flows in Nearly Linear Time

We introduce a new approach to the maximum flow problem in undirected, capacitated graphs using congestion-approximators: easy-to-compute functions that approximate the congestion required to route single-commodity demands in a graph to within some factor α. Our algorithm maintains an arbitrary flow that may have some residual excess and deficits, while taking steps to minimize a potential function measuring the congestion of the current flow plus an over-estimate of the congestion required to route the residual demand. Since the residual term over-estimates, the descent process gradually moves the contribution to our potential function from the residual term to the congestion term, eventually achieving a flow routing the desired demands with nearly minimal congestion after Õ(α<sup>2</sup>ε<sup>-2</sup> log<sup>2</sup> n) iterations. Our approach is similar in spirit to that used by Spielman and Teng (STOC 2004) for solving Laplacian systems, and we summarize our approach as trying to do for ℓ<sub>∞</sub>-flows what they do for ℓ<sub>∞</sub>-flows. Together with a nearly linear time construction of a no(1)-congestion-approximator, we obtain 1 + ε-optimal singlecommodity flows undirected graphs in time m<sup>1+o</sup>(1)ε<sup>-2</sup>, yielding the fastest known algorithm for that problem. Our requirements of a congestion-approximator are quite low, suggesting even faster and simpler algorithms for certain classes of graphs. For example, an α-competitive oblivious routing tree meets our definition, even without knowing how to route the tree back in the graph. For graphs of conductance φ, a trivial φ<sup>-1</sup>-congestionapproximator gives an extremely simple algorithm for finding Õ(mφ<sup>-1</sup>).
Empirical network performance evaluation of IPSec algorithms on windows operating systems implemented on a test-bed

With the growth of Internet in the recent decades, business environment have transformed to take advantage of the new opportunities offered by this global phenomenon. Fundamental changes have occurred to data and communications networks and one such change has been the use of Virtual Private Network (VPN) to establish organizational networks that may span many geographic locations. VPN solution is cost effect and provides all the benefits of traditional multi-site links; however performance has been identified as one of the major concerns of this technology. There are multiple mechanisms and algorithms with which VPNs can be implemented, each having its own strengths and weaknesses. In this research undertaking, three VPN techniques, namely DES, 3DES and AES, which are commonly used to implement IPSec VPNs are performance analyzed on test-bed setup. The VPN algorithms tested show that there may be performance differences when implemented with different Windows operating systems.
Neural Machine Translation from Simplified Translations

Text simplification aims at reducing the lexical, grammatical and structural complexity of a text while keeping the same meaning. In the context of machine translation, we introduce the idea of simplified translations in order to boost the learning ability of deep neural translation models. We conduct preliminary experiments showing that translation complexity is actually reduced in a translation of a source bi-text compared to the target reference of the bi-text while using a neural machine translation (NMT) system learned on the exact same bi-text. Based on knowledge distillation idea, we then train an NMT system using the simplified bi-text, and show that it outperforms the initial system that was built over the reference data set. Performance is further boosted when both reference and automatic translations are used to learn the network. We perform an elementary analysis of the translated corpus and report accuracy results of the proposed approach on English-to-French and English-to-German translation tasks.
Cognitive and Motivational Challenges in Writing: Studying the Relation With Writing Performance Across Students' Gender and Achievement Level

In the past, several assessment reports on writing repeatedly showed that elementary school students do not develop the essential writing skills to be successful in school. In this respect, prior research has pointed to the fact that cognitive and motivational challenges are at the root of the rather basic level of elementary students' writing performance. Additionally, previous research has revealed gender and achievement-level differences in elementary students' writing. In view of providing effective writing instruction for all students to overcome writing difficulties, the present study provides more in-depth insight into (a) how cognitive and motivational challenges mediate and correlate with students' writing performance and (b) whether and how these relations vary for boys and girls and for writers of different achievement levels. In the present study, 1,577 fifth- and sixth-grade students completed questionnaires regarding their writing self-efficacy, writing motivation, and writing strategies. In addition, half of the students completed two writing tests, respectively focusing on the informational or narrative text genre. Based on multiple group structural equation modeling (MG-SEM), we put forward two models: a MG-SEM model for boys and girls and a MG-SEM model for low, average, and high achievers. The results underline the importance of studying writing models for different groups of students in order to gain more refined insight into the complex interplay between motivational and cognitive challenges related to students' writing performance.
Variable Input Delay CMOS Logic Design for Low Dynamic Power Circuits

A gate that oers dier ent delays for dier ent input-output paths through it, is known as a variable input delay (VID) gate. The upper bound on this differential delay capability is specie d by the parameter \ub". These gates can be used to minimize the active power of a digital CMOS circuit by a path balancing and glitch ltering techniques discussed in recent publications. In this paper, we describe transistor sizing methods for three types of VID gates that satisfy given delay requirements. The three ways to obtain the differential delays are capacitance manipulation, nMOS transistor insertion, and CMOS transmission gate insertion. We also describe techniques for calculating the ub of each VID gate type. Finally, we outline an algorithm for quick determination of the transistor sizes for a gate for a given load capacitance.