Miracle-dz/UniFAR-FTUs huggingface dataset:
Holocene Climate Inferred from Oxygen Isotope Ratios in Lake Sediments, Central Brooks Range, Alaska

Abstract Analyses of sediment cores from two lakes in the central Brooks Range provide temperature and moisture balance information for the past ∼8500 cal yr at century-scale resolution. Two methods of oxygen isotope analysis are used to reconstruct past changes in the effective moisture (precipitation minus evaporation) and temperature. Effective moisture is inferred from oxygen isotope ratios in sediment cellulose from Meli Lake (area ∼0.13 km2, depth 19.4 m). The lake has a low watershed-to-lake-area ratio (7) and significant evaporation relative to input. Summer temperature shifts are based on oxygen isotope analyses of endogenic calcite from Tangled Up Lake (area ∼0.25 km2, depth 3.5 m). This basin has a larger watershed-to-lake-area ratio (91) and less evaporation relative to input. Sediment oxygen isotope analyses from the two sites indicate generally more arid conditions than present prior to ∼6000 cal yr B.P. Subsequently, the region became increasingly wet. Temperature variability is recorded minimally at centennial scale resolution with values that are generally cool for the past ∼6700 cal yr. The timing and direction of climate variability indicated by the oxygen isotope time series from Meli and Tangled Up lakes are consistent with previously established late Holocene glacier advances at ∼5000 cal yr B.P. in the central Brooks Range, and high lake-levels at Birch Lake since ∼5500 cal yr B.P. This unique use of oxygen isotopes reveals both moisture balance and temperature histories at previously undetected high-resolution temporal scales for northern Alaska during the middle to late Holocene.
INVESTIGATING THE EFFECTS OF FOREIGN DIRECT INVESTMENT ON EXPORT GROWTH IN CAMEROON

The theoretical relationship between FDI and export growth can be explained by using the flying geese model, Vernon’s product life cycle theory and the new growth model. These three theories have different explanatio recipient economy. First, MNE subsidiaries exploit the host country’s factor endowments for lowering production costs to increase their export competitiveness. Therefore, the host co export expansion by MNE subsidiaries is to be expected (capacity host country’s export can be increased by domestic firms through the spillover effects of FDI such as competition and transfer of knowledge (spillove potential effects of FDI inflows on export growth in Cameroon over the 1980 separate the effects of FDI into supply capacity hypothesis of th Using the Engle contributed to higher supply capacity and spillover effects in Cameroon, leading to hi growth during the period of study.
Hybrid simulated annealing and direct search method for nonlinear unconstrained global optimization

In this article we give a new approach of hybrid direct search methods with meta-heuristics of simulated annealing for finding a global minimum of a nonlinear function with continuous variables. First, we suggest a Simple Direct Search (SDS) method, which comes from some ideas of other well-known direct search methods. Since our goal is to find global minima and the SDS method is still a local search method, we hybridize it with the standard simulated annealing to design a new method, called Simplex Simulated Annealing (SSA) method, which is expected to have some ability to look for a global minimum. To obtain faster convergence, we first accelerate the cooling schedule in SSA, and in the final stage, we apply Kelley's modification of the Nelder-Mead method on the best solutions found by the accelerated SSA method to improve the final results. We refer to this last method as the Direct Search Simulated Annealing (DSSA) method. The performance of SSA and DSSA is reported through extensive numerical experiments on some well-known functions. Comparing their performance with that of other meta-heuristics shows that SSA and DSSA are promising in practice. Especially, DSSA is shown to be very efficient and robust.
Blurred And Compressed Trademark Image Retreival Under Noise And Orientation Based On Curvature Shape Descriptor ( Csd )

Digital images are a convenient media for describing and storing spatial, temporal, spectral, and physical components of information contained in a variety of domains (e.g. aerial/satellite images in remote sensing, medical images in telemedicine, fingerprints in forensics, museum collections in art history, and registration of trademarks and logos). Retrieval of digital images is one of the challenging issue in any Digital Image Processing system. Although advances in image compression algorithms have alleviated the storage requirement to some extent, the large volume of these images makes it difficult for a user to browse through the entire database. Therefore, an efficient and automatic procedure based on curvature shape descriptors is proposed, which make use shape descriptor along with compression techniques to make database feasible to store large number of images and retrieve image under noise, blurrring and orientation changes. In CSD approach, the image is subjected to compression and then later it is represented in its contour format by its coordinates and are mathematically processed for curvature evolution over various sigma levels so as to remove the unevenness caused by some external disturbances. For each sigma level, zero crossing points are evaluated which are used as the features for image retrieval along with arc length.
On the effect of reduced sampling rate and bitwidth on seizure detection

Ambulatory EEG requires signal processing algorithms which are efficient in terms of how much power they use in their computation, while at the same time providing accurate decision-making capabilities. Two methods of achieving this are to downsample the EEG and to perform bitwidth reduction on the data. The effect of performing both of these techniques to varying extents is investigated in this paper. Frequency, time and entropy based features are extracted from the data and used to train a Support Vector Machine (SVM) classification system. The effect of changing the overlap between successive epochs is also investigated.
The Diversity Paradox: Opportunities and Challenges of “Contact in Context” Across Development

As the United States diversifies, we review research on both the benefits and challenges of diversity in developmental science. Taking a “contact in context” approach, we focus on how structural and interpersonal diversity influence ethnic/racial developmental processes and outcomes from early childhood to adolescence. We also consider how a child’s own ethnicity/race may shape diversity experiences. We offer this review with the ultimate goal of optimizing benefits and minimizing challenges. We offer a “contact in context” conceptual model that integrates diversity at multiple levels, child ethnicity/race, and developmental changes over time. We conclude with recommendations for future research.
Red Roses and Gift Chocolates Are Judged More Positively in the U.S. Near Valentine’s Day: Evidence of Naturally Occurring Cultural Priming

Attitudes are not static, but constructed at the moment of the evaluation, incorporating temporary contextual influences. How do meaningful events that naturally occur within a culture, such as a national holiday, shape evaluative judgments of objects related to the holiday? We focused on evaluations of red roses and gift chocolates, which are everyday objects, but also iconic of Valentine’s Day in the U.S. We reasoned that if cultural events shape evaluations, then roses and chocolates would be evaluated differently near Valentine’s Day. Using a large and diverse U.S. sample, we found that as Valentine’s Day neared, evaluations of roses and chocolates (but not a comparison object) were evaluated more positively. Increases in positivity of roses and chocolates covaried with their increased cultural relevance, as quantified by the volume of web search queries involving these terms. These findings provide a demonstration of naturally occurring cultural priming by which the salience of cultural events shape evaluations.
On practice and contradiction

These early philosophical writings underpinned the Chinese revolutions and their clarion calls to insurrection remain some of the most stirring of all time. Drawing on a dizzying array of references from contemporary culture and politics, Zizek's firecracker commentary reaches unsettling conclusions about the place of Mao's thought in the revolutionary canon.
LARGE-SCALE IMPUTATION FOR COMPLEX SURVEYS

Much of the recent research into imputation methodology has focused on developing optimal procedures for a single variable or set of variables, where the patterns of missingness and underlying distributions follow standard distributions. In contrast, it is frequently necessary to impute for many variables from a single survey, with an even larger set of potential covariates and complex covariance structures among the variables to be imputed. Further, the imputations need to be completed in a relatively short time frame within a constrained budget. The analyst also is unlikely to be able to anticipate all of the important analyses for which the imputed data are to be used. This often prevents analysts from being able to produce optimal imputations for each variable. Instead, one tries to produce a set of imputed variables that minimize the attenuation of key relationships, hopefully reduces nonresponse bias, and satisfies the time and budgetary constraints.
Visualization for situation awareness

We explore techniques from visualization and computational geometry to make tactical information more intuitive to a military commander. To be successful, the commander must quickly grasp, and react to, changes in the evolving battle. Thus the commander must possess good situation awareness (SA). A particular problem is to reduce the information complexity entailed by understanding the positional and evolutionary potential of the many individual entities (micro states), each with its own organizational allegiance, capabilities, and attributes. The challenge is to combine the many individual microstates into a few integrated macrostates and then display this information to the commander in a way that is instantly meaningful. To improve the acquisition of SA, we apply principles of human visual perception. In particular, we exploit the organizational properties of gestalt figures and the phenomenon of global preference to create displays that allow the commander to quickly find and integrate relevant information on the location, identity, and concentration of friendly and enemy units. We postulate that an appropriate technical translation of this psychological concept is to consider the spatial arrangement of the units as a geometric density assignment problem, based, to the first order, on geometric proximity. The resulting density and clustering of units is represented using color. To further enhance the ability to grasp the evolving dynamics of an engagement, we compress the data into a short temporal sequence of images. For example, several days of maneuver may be compressed into a motion sequence of a few minutes. We report preliminary findings focusing on the computational geometry aspects, and on the visualization requirements. CR Categories: I.3. 3 [Computing Methodlogies]: Computer Graphics—Picutre/Image Generation; I.3. 5 [Computing Methodlogies]: Computer Graphics—Computational Geometry and Object Modeling; J.4 [Computer Applications]: Social and Behavioral Sciences cmh@cs.purdue. edu, Department of Computer Science, Purdue University. Partial support by NSF Grants CDA 92-23502 and CCR 95-05745, and by ONR Contract N00014-96-1-0635 is gratefully acknowledged. kimy@cs.purdue. edu, Department of Computer Science, Purdue University. Partial support by NSF Grants CDA 92-23502 and CCR 95-05745, and by ONR Contract N00014-96-1-0635 is gratefully acknowledged. zwinkler@arl.mil, U.S. Army Research Laboratory. jwalrath@arl.mil, U.S. Army Research Laboratory. pemmerman@emh3.arl.mil, U.S. Army Research Laboratory.
Summarizing Timelines Based on Content and Social Network

With the rapid growth of social network such as Twitter and SinaWeibo, more and more applications are designed for users to manage and serve for their social network platform. In this paper, we focus on the problem of summarization of timelines, which is useful for filtering out replicated posts and organizing posts in a more structured way. The content of short text is combined with social network for clustering posts. A corpus of Sina Weibo is annotated. Intensive experiments are conducted based on the corpus. We show that our method may achieve high precision and recall. The corpus is also shared for research community for further research.
Instruction Coalescing for 16-bit Code

In the embedded domain, memory usage and energy consumption are critical constraints. Embedded processors such as the ARM and MIPS provide a 16-bit instruction set (called Thumb in the case of the ARM cpu family) in addition to the 32-bit instruction set to address these concerns. Using 16-bit instructions one can achieve code size reduction and I-cache energy savings at the cost of performance. This paper presents a novel approach that enhances the performance of 16-bit Thumb code. We have observed that throughout Thumb code there exist Thumb instruction pairs that are equivalent to a single ARM instruction. We have developed enhancements to the processor microarchitecture and the Thumb instruction set to exploit this property. We enhance the Thumb instruction set by incorporating Augmenting eXtensions (AX). A Thumb instruction pair that can be combined into a single ARM instruction is replaced by an AXThumb instruction pair by the compiler. The AX instruction is coalesced with the immediately following Thumb instruction to generate a single ARM instruction at decode time. The enhanced microarchitecture ensures that coalescing does not introduce pipeline delays or increase cycle time thereby resulting in reduction of both instruction counts and cycle counts. Using AX instructions and coalescing hardware we are also able to support efficient predicated execution in 16 bit mode.
Using Phenomenology in Contemporary Arts Research and Pedagogy (Handbook for 3-day Workshop led by Jorella Andrews)

This three-day workshop introduced phenomenologically-based research and pedagogical methods and, in particular, a recently developed qualitative research methodology known as Interpretative Phenomenological Analysis (IPA). IPA is usually used by researchers in the social sciences who are carrying out primary, interview-based field work with small data sets. This workshop introduced IPA and also explored how it can be most effectively applied and adapted to benefit researchers working and teaching in the emerging fields of contemporary Asian Art Histories and Visual Culture. IPA is particularly valuable with respect to assembling primary source materials within emerging fields because it is designed to enable:  nuanced modes of interviewing key agents (artists, curators, audiences) and of self-interviewing  the capacity to work with gathered data in great detail, using a range of analytical
Musical Bass-Line Pattern Clustering and Its Application to Audio Genre Classification

This paper discusses a new approach for clustering musical bass-line patterns representing particular genres and its application to audio genre classification. Many musical genres are characterized not only by timbral information but also by distinct representative bass-line patterns. So far this kind of temporal features have not so effectively been utilized. In particular, modern music songs mostly have certain fixed bar-long bass-line patterns per genre. For instance, while frequently bass-lines in rock music have constant pitch and a uniform rhythm, in jazz music there are many characteristic movements such as walking bass. We propose a representative bass-line pattern template extraction method based on k-means clustering handling a pitchshift problem. After extracting the fundamental bass-line pattern templates for each genre, distances from each template are calculated and used as a feature vector for supervised learning. Experimental result shows that the automatically calculated bass-line pattern information can be used for genre classification effectively and improve upon current approaches based on timbral features.
Hybrid Equity-Interest Rate Model with Stochastic Interest Rate and Volatility

This paper presents an Equity-IR hybrid model that fits in the class of affine diffusion processes. In the absence of cash dividend payment, the moment generating function can be easily and rapidly computed. This allows for an efficient calibration of the model based on Vanilla European Options prices. In practice, cash dividend payments are common and are modeled via the piece-wise and escrowed approaches. We show how to compute Vanilla European Options prices efficiently in this case. The semi-analytical approximation pricing formulas obtained in the piece-wise approach are one of our primary results.In order to assess the semi-analytical pricing method, we compare the computed prices to those obtained via Monte Carlo simulation. Three discretization schemes are used: the two first ones, which have been introduced by Andersen, are the Quadratic Exponential (QE) and its extension with martingale correction QE-M. The last scheme is a new extension of the QE scheme denoted QE-I, that we introduced in order to allow the use of larger simulation time steps by comparison to QE and QE-M.
Does it get better? LGBTQ social work students and experiences with harmful discourse

Abstract Although the field of social work is grounded in social justice, the social work educational experience, including classrooms, may not live up to this value, especially for lesbian, gay, bisexual, transgender, and queer (LGBTQ) students. Using a qualitative phenomenological approach, this study examined the experiences of harmful discourse in social work classrooms for LGBTQ students. Findings indicate that students experienced being misgendered, tokenized, and erased through cis-/heteronormative language and classroom teachings. Although social work is guided by frameworks of social justice, microaggressions and discrimination may be vaguely glossed over, if addressed at all. This study highlights the gap between the values social work teaches and how social work education is delivered.
Forest-to-String SMT for Asian Language Translation: NAIST at WAT 2014

This paper describes the Nara Institute of Science and Technology’s (NAIST) submission to the 2014 Workshop on Asian Translation’s four translation tasks. All systems are based on forest-to-string (F2S) translation, in which the input sentence is first parsed using a syntactic parser, then a forest of possible syntactic analyses is translated into the target language. In addition to the baseline F2S system, we add rescoring using a recurrent neural network language model (RNNLM), which allows for more fluent output. The resulting system achieved the highest results in both automatic and manual evaluation for all four of the language pairs targeted by the workshop.
LOSSY IS LAZY

Shannon’s rate-distortion curve characterizes optimal lossy compression. I show here that the optimization principle that has to be solved to compute the rate-distortion function can be derived from a least effort principle: minimizing required thermodynamic effort necessitates the minimization of information (compatible with a given fidelity). Retaining less information costs less physical effort. In that sense, lossy compression is energy efficient, in other words, lossy is lazy.
Visualization in Low Dimensional Space by Tessellation of Linear Subspaces

The problem of nonlinear dimensionality reduction is most often formulated as an instance of semidefinite programming (SDP). However, the effectiveness of the SDP-based algorithms is limited by the computational complexity of the SDP solvers. Due to this limitation, some large-scale variations of the SDP-based methods have been proposed, which are relatively fast and scalable; however, they reduce the size of the SDP by some heuristic approximation, which results in suboptimal solutions. In this paper, we propose a novel method, which significantly reduces the size and the number of constraints of the SDP problem. We show the search space of the SDP problem can be restricted to a small face of the semidefinite cone. Crucially, the proposed formulation is not an approximation and very large SDP problems can be solved exactly and efficiently by this technique. In addition, unlike most methods, this algorithm provides a parametric mapping that allows out-of-sample test points to be sensibly mapped into the embedded space. 1 The proposed method We propose a method for learning a parametric mapping between the high-dimensional space and the embedded space, which can be used to map out-of-sample points. We model this parametric mapping as a linear transformation. Adapting an idea from Maximum Variance Unfolding (MVU) [1], we require the transformation to preserve the distances between neighboring points, while pulling non-neighbor points as far apart as possible to unfold the manifold of the data, which consequently reduces its dimensionality. Such a transformation may not even exist in general; however, when the dimensionality of the data exceeds its quantity, it is always possible to find it. In order to guarantee the existence of the desired transformation, we first map the points into a high-dimensional feature space by some function φ(·), and then explicitly search for it in that space. Consider a training dataset in a matrix form X = [x1, . ,xn]. We wish to learn a linear transformationW . Without loss of generality, we assume that the columns ofW can always be re-expressed as a linear combination of the data points in the feature space [2], W = φ(X)Ω, thus y = W>φ(x) = Ω>φ(X)>φ(x) = Ω>K(X,x) (1) where K(·, ·) is a kernel function. Crucially, y only depends on the inner products of the feature vectors, and the function φ(·) is not explicitly needed. Moreover, instead of W we need to learn Ω. Let K = K(X,X) denote an n × n kernel, and Y = [y1, . ,yn] be a matrix of points in the embedded space. Then it is clear that Y = Ω>K. Let S to be a set of pairs of neighbor points in the original space for which their pairwise distances should be preserved (i.e. ‖yi−yj‖ = τij , where τij is set by user which simply can be ‖xi−xj‖), and O is a set of pairs of non-neighbor points, which we would like to pull as far apart as possible. For each pair of points we have: ‖yi − yj‖ =‖Ω> (K(X,xi)−K(X,xj)) ‖ = (ki − kj)ΩΩ(ki − kj) =(ki − kj)A(ki − kj) = ((ki − kj)⊗ (ki − kj)) vec(A), (2)
The thermodynamic balance of the Weddell Gyre

The thermodynamic balance of the Weddell Gyre is assessed from an inverse estimate of the circulation across the gyre's rim. The gyre experiences a weak net buoyancy gain that arises from a leading‐order cancelation between two opposing contributions, linked to two cells of water mass transformation and diapycnal overturning. The lower cell involves a cooling‐driven densification of 8.4 ± 2.0 Sv of Circumpolar Deep Water and Antarctic Bottom Water near the gyre's southern and western margins. The upper cell entails a freshening‐driven conversion of 4.9 ± 2.0 Sv of Circumpolar Deep Water into lighter upper ocean waters within the gyre interior. The distinct role of salinity between the two cells stems from opposing salinity changes induced by sea ice production, meteoric sources, and admixture of fresh upper ocean waters in the lower cell, which contrasts with coherent reductions in salinity associated with sea ice melting and meteoric sources in the upper cell.