Miracle-dz/UniFAR-FTUs huggingface dataset:
Explorer A Computational Cognitive Model of Syntactic Priming

The psycholinguistic literature has identified two syntactic adaptation effects in language production: rapidly decaying short-term priming and long-lasting adaptation. To explain both effects, we present an ACT-R model of syntactic priming based on a wide-coverage, lexicalized syntactic theory that explains priming as facilitation of lexical access. In this model, two well-established ACT-R mechanisms, base-level learning and spreading activation, account for long-term adaptation and short-term priming, respectively. Our model simulates incremental language production and in a series of modeling studies we show that it accounts for (a) the inverse frequency interaction; (b) the absence of a decay in long-term priming; and (c) the cumulativity of long-term adaptation. The model also explains the lexical boost effect and the fact that it only applies to short-term priming. We also present corpus data that verifies a prediction of the model, i.e., that the lexical boost affects all lexical material, rather than just heads.
Iron Oxides

DEFINITION Iron oxides are produced from ferrous sulfate by heat soaking, removal of water, decomposition, washing, filtration, drying and grinding. They are produced in either anhydrous or hydrated forms. Their range of hues includes yellows, reds, browns and blacks. The food-quality iron oxides are primarily distinguished from technical grades by their comparatively low levels of contamination by other metals; this is achieved by the selection and control of the source of the iron or by the extent of chemical purification during the manufacturing process.
Tribology of ball-and-socket total disc arthroplasty

Total disc arthroplasty (TDA) can be used to replace a degenerated intervertebral disc in the spine. There are different designs of TDAs, but one of the most common is a ball-and-socket combination. Contact between the bearing surfaces of such designs can result in high frictional torque, which can then result in wear and implant loosening. This study was designed to determine the effects of change in design factors, such as dimensions and material combinations, on friction and wear of ball-and-socket TDAs. Friction tests were carried out on generic models with ball radii 10, 12, 14 and 16 mm. Three material combinations were investigated; metal-on-metal, metal-on-polymer and for the first time polymer-on-metal. Wear tests were performed on metal-on-polymer Charite® TDAs and generic metal-on-metal models to compare the wear rate under the same conditions. Friction test results showed that polymer-on-metal TDAs create less friction than metal-on-polymer and metal-on-metal TDAs. Wear test results showed that under the same conditions, metal-on-metal TDAs create 23 times less wear debris than metal-on-polymer. The results were in agreement with studies on total hip arthroplasty (THA). The results of this work suggest possible alternatives for future TDA designs.
Priorities for Endometriosis Research

Endometriosis is an estrogen-dependent disorder where endometrial tissue forms lesions outside the uterus. Endometriosis affects an estimated 10% of women in the reproductive-age group, rising to 30% to 50% in patients with infertility and/or pain, with significant impact on their physical, mental, and social well-being. There is no known cure, and most current medical treatments are not suitable long term due to their side-effect profiles. Endometriosis has an estimated annual cost in the United States of $18.8 to $22 billion (2002 figures). Although endometriosis was first described more than 100 years ago, current knowledge of its pathogenesis, spontaneous evolution, and the pathophysiology of the related infertility and pelvic pain, remain unclear. A consensus workshop was convened following the 10th World Congress on Endometriosis to establish recommendations for priorities in endometriosis research. One major issue identified as impacting on the capacity to undertake endometriosis research is the need for multidisciplinary expertise. A total of 25 recommendations for research have been developed, grouped under 5 subheadings: (1) diagnosis, (2) classification and prognosis, (3) treatment and outcome, (4) epidemiology, and (5) pathophysiology. Endometriosis research is underfunded relative to other diseases with high health care burdens. This may be due to the practical difficulties of developing competitive research proposals on a complex and poorly understood disease, which affects only women. By producing this consensus international research priorities statement it is the hope of the workshop participants that researchers will be encouraged to develop new interdisciplinary research proposals that will attract increased funding support for work on endometriosis.
Shading Annotations in the Wild

Understanding shading effects in images is critical for a variety of vision and graphics problems, including intrinsic image decomposition, shadow removal, image relighting, and inverse rendering. As is the case with other vision tasks, machine learning is a promising approach to understanding shading - but there is little ground truth shading data available for real-world images. We introduce Shading Annotations in the Wild (SAW), a new large-scale, public dataset of shading annotations in indoor scenes, comprised of multiple forms of shading judgments obtained via crowdsourcing, along with shading annotations automatically generated from RGB-D imagery. We use this data to train a convolutional neural network to predict per-pixel shading information in an image. We demonstrate the value of our data and network in an application to intrinsic images, where we can reduce decomposition artifacts produced by existing algorithms. Our database is available at http://opensurfaces.cs. cornell.edu/saw.
Virtual Product Experience: Effects of Visual and Functional Control of Products on Perceived Diagnosticity and Flow in Electronic Shopping

The development of electronic commerce has been constrained by the inability of online consumers to feel, touch, and sample products through Web interfaces, as they are able to do in conventional in-store shopping. Previous academic studies have argued that this limitation could be partly alleviated by providing consumers with virtual product experience (VPE), to enable potential customers to experience products virtually. This paper discusses virtual control, a specific type of VPE implementation, and identifies its two dimensions: visual control and functional control. Visual control enables consumers to manipulate Web product images, to view products from various angles and distances; functional control enables consumers to explore and experience different features and functions of products. The individual and joint effects of visual and functional control were investigated in a laboratory experiment, the results of which indicated that visual and functional control increased the perceived diagnosticity (i.e., the extent to which a consumer believes the shopping experience is helpful to evaluate a product) of their corresponding attribute factors, and that both visual and functional control increased consumer overall perceived diagnosticity and flow.
Prolonged survival and improved glycemia in BioBreeding diabetic rats after early sustained exposure to glucagon‐like peptide 1

Type 1 diabetes (T1D) in both humans and BioBreeding (BB) rats is an autoimmune disease that results in complete destruction of islets and insulin dependency for life. Glucagon‐like peptide 1 (GLP‐1) promotes β cell proliferation and neogenesis and has a potent insulinotropic effect. We hypothesized that the expression of GLP‐1 before disease onset would increase islet mass, delay diabetes and prolong survival of BB rats.
Information theoretic evaluation of change prediction models for large-scale software

In this paper, we analyze the data extracted from several open source software repositories. We observe that the change data follows a Zipf distribution. Based on the extracted data, we then develop three probabilistic models to predict which files will have changes or bugs. The first model is Maximum Likelihood Estimation (MLE), which simply counts the number of events, i.e., changes or bugs, that happen to each file and normalizes the counts to compute a probability distribution. The second model is Reflexive Exponential Decay (RED) in which we postulate that the predictive rate of modification in a file is incremented by any modification to that file and decays exponentially. The third model is called RED-Co-Change. With each modification to a given file, the RED-Co-Change model not only increments its predictive rate, but also increments the rate for other files that are related to the given file through previous co-changes. We then present an information-theoretic approach to evaluate the performance of different prediction models. In this approach, the closeness of model distribution to the actual unknown probability distribution of the system is measured using cross entropy. We evaluate our prediction models empirically using the proposed information-theoretic approach for six large open source systems. Based on this evaluation, we observe that of our three prediction models, the RED-Co-Change model predicts the distribution that is closest to the actual distribution for all the studied systems.
Obtaining Better Non-Dominated Sets Using Volume Dominance

An important goal in multiobjective optimisation is to find a good set of non-dominated solutions that is both well-distributed and well-converged. Most multiobjective optimisation algorithms use the conventional Pareto dominance relationship. Over recent years, new approaches for the dominance relationship such as relaxed Pareto dominance, have been proposed. The interest in relaxed forms of Pareto dominance has been increasing due to their capability to find extreme values in the objective space. This paper conducts a short review on relaxed forms of Pareto dominance in the literature. A new form of relaxed Pareto dominance, called volume dominance, is presented afterward. The results based on comparison between volume dominance and Pareto dominance using SEAMO2, SPEA2 and NSGA2 show that the proposed volume dominance is capable of obtaining a better and smoother trade-off front, and it is more robust than Pareto dominance.
Energy tunneling in wire-loaded in substrate integrated waveguide

The Substrate Integrated Waveguides (SIWs), compared to the non-planar rectangular waveguides are flexible, compact, robust, easily manufactured and suitable for planar integration. SWI supports transmission of electromagnetic waves; they are also candidate in designing high speed circuits, antennas and couplers. In this paper, we propose a wire-loaded substrate integrated waveguide (SIW) structure that supports the energy-tunneling phenomenon. As anticipated, the proposed model supports energy tunneling depending upon the wire length. The resulting transmission response is, therefore, highly frequency selective. Hence, such configurations can be employed to design highly sensitive dielectric sensors and high frequency filters.
The Human 343delT HSPB5 Chaperone Associated with Early-onset Skeletal Myopathy Causes Defects in Protein Solubility*

Mutations of HSPB5 (also known as CRYAB or αB-crystallin), a bona fide heat shock protein and molecular chaperone encoded by the HSPB5 (crystallin, alpha B) gene, are linked to multisystem disorders featuring variable combinations of cataracts, cardiomyopathy, and skeletal myopathy. This study aimed to investigate the pathological mechanisms involved in an early-onset myofibrillar myopathy manifesting in a child harboring a homozygous recessive mutation in HSPB5, 343delT. To study HSPB5 343delT protein dynamics, we utilize model cell culture systems including induced pluripotent stem cells derived from the 343delT patient (343delT/343delT) along with isogenic, heterozygous, gene-corrected control cells (WT KI/343delT) and BHK21 cells, a cell line lacking endogenous HSPB5 expression. 343delT/343delT and WT KI/343delT-induced pluripotent stem cell-derived skeletal myotubes and cardiomyocytes did not express detectable levels of 343delT protein, contributable to the extreme insolubility of the mutant protein. Overexpression of HSPB5 343delT resulted in insoluble mutant protein aggregates and induction of a cellular stress response. Co-expression of 343delT with WT prevented visible aggregation of 343delT and improved its solubility. Additionally, in vitro refolding of 343delT in the presence of WT rescued its solubility. We demonstrate an interaction between WT and 343delT both in vitro and within cells. These data support a loss-of-function model for the myopathy observed in the patient because the insoluble mutant would be unavailable to perform normal functions of HSPB5, although additional gain-of-function effects of the mutant protein cannot be excluded. Additionally, our data highlight the solubilization of 343delT by WT, concordant with the recessive inheritance of the disease and absence of symptoms in carrier individuals.
Isolation of Mouse Endometrial Epithelial and Stromal Cells for In Vitro Decidualization

Decidualization is a progesterone-dependent differentiation process of endometrial stromal cells and is a prerequisite for successful embryo implantation. Although many efforts have been made to reveal the underlying mechanisms of decidualization, the exact signaling between the epithelial cells that are in contact with the embryo and the underlying stromal cells remains poorly understood. Therefore, studying decidualization in a way that takes both the epithelial and stromal cells into account could improve our knowledge about the molecular details of decidualization. For this purpose, in vivo models of artificial decidualization are physiologically the most relevant; however, manipulation of intercellular communication is limited. Currently, in vitro cultures of endometrial stromal cells are being used to investigate the modulation of decidualization by several signaling molecules. Conventionally, human or mouse endometrial stromal cells are used. However, the availability of human samples is very often limited. Furthermore, the use of murine tissues is accompanied with variety in the method of culturing. This study presents a validated and standardized method to obtain pure Endometrial Epithelial Cell (EEC) and Stromal Cell (ESC) cultures using adult intact mice treated with estrogen for three consecutive days. The protocol is optimized to improve the yield, viability, and purity of the cells and was further extended in order to study decidualization in a coculture of EEC and ESC. This model may be suitable to exploit the importance of both cell types in decidualization and to evaluate the contribution of significant signaling molecules secreted by EEC or ESC during the intercellular communication.
Discourse and Document-level Information for Evaluating Language Output Tasks

Evaluating the quality of language output tasks such as Machine Translation (MT) and Automatic Summarisation (AS) is a challenging topic in Natural Language Processing (NLP). Recently, techniques focusing only on the use of outputs of the systems and source information have been investigated. In MT, this is referred to as Quality Estimation (QE), an approach that uses machine learning techniques to predict the quality of unseen data, generalising from a few labelled data points. Traditional QE research addresses sentencelevel QE evaluation and prediction, disregarding document-level information. Documentlevel QE requires a different set up from sentence-level, which makes the study of appropriate quality scores, features and models necessary. Our aim is to explore documentlevel QE of MT, focusing on discourse information. However, the findings of this research can improve other NLP tasks, such as AS.
CO2 laser beam cutting of steels: Material issues

Laser beam cutting and its advantages along with its relevance to worldwide trends in manufacturing are introduced. Results of efforts to identify material-related factors that render steel suitable for laser cutting are described. Key material requirements for both hot-strip and discrete plate products have been summarized using data collected over several years based on anecdotal information as well as experimental results. It has become clear that near-zero residual stresses and a minimum level of residual elements (Cu, Ni, and Cr) are necessary to obtain clean pierces and consistent cut quality in thick (20–25 mm) plates, in both as-rolled and as-shot-blasted conditions using conventional CO2 laser cutting. A mechanism to explain why the presence of residual elements results in improved cut quality is proposed. Further work required to develop a better understanding of laser cutting has been highlighted and recent process developments that could significantly impact this technology have been outlined.
An infectious clone of the West Nile flavivirus.

West Nile (WN) virus is the most widespread among flaviviruses, but until recently it was not known on the American continent. We describe here design of a subgenomic replicon, as well as a full-length infectious clone of the lineage II WN strain, which appeared surprisingly stable compared to other flavivirus infectious clones. This infectious clone was used to investigate effects of 5'- and 3'-nonrelated sequences on virus replication and infectivity of synthetic RNA. While a long nonrelated sequence at the 3'-end delayed but did not prevent establishment of the productive infectious cycle, a much shorter extra sequence at the 5'-end completely abrogated virus replication. Replacement of the conserved 5'-adenosine residue substantially delayed, but did not prevent, establishment of virus infection. In all cases, the recovered virus had restored its authentic 5'- and 3'-end genome sequences. However, the presence of extensive nonrelated sequences at both 5'- and 3'-ends could not be repaired.
Data sharing in neuroimaging research

Significant resources around the world have been invested in neuroimaging studies of brain function and disease. Easier access to this large body of work should have profound impact on research in cognitive neuroscience and psychiatry, leading to advances in the diagnosis and treatment of psychiatric and neurological disease. A trend toward increased sharing of neuroimaging data has emerged in recent years. Nevertheless, a number of barriers continue to impede momentum. Many researchers and institutions remain uncertain about how to share data or lack the tools and expertise to participate in data sharing. The use of electronic data capture (EDC) methods for neuroimaging greatly simplifies the task of data collection and has the potential to help standardize many aspects of data sharing. We review here the motivations for sharing neuroimaging data, the current data sharing landscape, and the sociological or technical barriers that still need to be addressed. The INCF Task Force on Neuroimaging Datasharing, in conjunction with several collaborative groups around the world, has started work on several tools to ease and eventually automate the practice of data sharing. It is hoped that such tools will allow researchers to easily share raw, processed, and derived neuroimaging data, with appropriate metadata and provenance records, and will improve the reproducibility of neuroimaging studies. By providing seamless integration of data sharing and analysis tools within a commodity research environment, the Task Force seeks to identify and minimize barriers to data sharing in the field of neuroimaging.
Congestion Minimization By Using MFMP Routing Algorithm

Unlike traditional routing schemes that route all traffic along a single path, multipath routing strategies split the traffic among several paths in order to ease congestion. It has been widely recognized that multipath routing can be fundamentally more efficient than the traditional approach of routing along single paths. Yet, in contrast to the singlepath routing approach, most studies in the context of multipath routing focused on heuristic methods. We formalize problem (K-Path Routing) that incorporate major requirements of multipath routing. Then, we establish the intractability of these problems a max flow multipath routing algorithm that is designed to reduce latency, provide high throughput and balance traffic load. The max flow multipath algorithm is based on a Ford-Fulkerson algorithm. It consists of determining a set of disjoint paths that are loop free with maximum flow, then splitting network traffic among those paths on a round robin fashion. Through simulation we show that our algorithm performs well than a multi shortest path in terms of computational complexity. Finally establish efficient solutions with proven performance guarantees.
Idea Management Communities in the Wild: An Exploratory Study of 166 Online Communities

Idea Management (IM) communities have the potential to transform business and communities through innovation. However, building successful communities is a difficult endeavor that requires a significant amount of both community management and technological support. Doing this requires a good understanding of how IM systems are used and how users behave, as these are fundamental aspects for the design of effective technological support as well as devising community management strategies. In this paper, we study 166 IM communities in the “wild” — communities openly available on Ideascale, one of today's leading IM software platforms — to better understand how they are used in practice, and by whom. We do this via i) a qualitative analysis of community properties to identify community archetypes; ii) a quantitative analysis of user activity logs to identify patterns of collective and individual user behavior.
Predictive Compensator Optimization for Head Tracking Lag in Virtual Environments

Predictive compensators for VEs operate on current position and orientation measurements to extrapolate future positions and orientations based on kinematic and dynamic models of motion via Kalman filtering or other techniques. Perfect prediction, in principle, should remove all effects of sensor-to-display latency and intro - duce no additional artifacts (e.g., noise or overshoot) to the VE system. Notwithstanding, we presume that a practical predictor need neither remove all latency nor avoid all artifacts, it need only avoid making the user aware of those compensator imperfections. We examined the perceptual impact of plant noise parameterization for Kalman Filter predictive compensa- tion of time delays intrinsic to head tracked virtual envi- ronments (VEs). Subjects were tested in their ability to discriminate between the VE system's minimum latency and conditions in which artificially added latency was then predictively compensated back to the system mini- mum. Two head tracking predictors were parameterized off-line according to cost functions that minimized pre- diction errors in (1) rotation, and (2) rotation projected into translational displacement with emphasis on higher frequency human operator noise. These predictors were compared with a parameterization obtained from the VE literature for cost function (1). Results from 12 subjects showed that both parameterization type and amount of compensated latency affected discrimination. Analysis of the head motion used in the parameterizations and the subsequent discriminability results suggest that higher frequency predictor artifacts are contributory cues for dis - criminating the presence of predictive compensation.