Miracle-dz/UniFAR-FTUs huggingface dataset:
The herpes viral transcription factor ICP4 forms a novel DNA recognition complex

Abstract The transcription factor ICP4 from herpes simplex virus has a central role in regulating the gene expression cascade which controls viral infection. Here we present the crystal structure of the functionally essential ICP4 DNA binding domain in complex with a segment from its own promoter, revealing a novel homo-dimeric fold. We also studied the complex in solution by small angle X-Ray scattering, nuclear magnetic resonance and surface-plasmon resonance which indicated that, in addition to the globular domain, a flanking intrinsically disordered region also recognizes DNA. Together the data provides a rationale for the bi-partite nature of the ICP4 DNA recognition consensus sequence as the globular and disordered regions bind synergistically to adjacent DNA motifs. Therefore in common with its eukaryotic host, the viral transcription factor ICP4 utilizes disordered regions to enhance the affinity and tune the specificity of DNA interactions in tandem with a globular domain.
Apparent earth conductivity over coal mines as estimated from through-the-earth electromagnetic transmission tests

Electromagnet ic narrow-band s i g n a l s were t r ansmi t t ed through t h e e a r t h a t 27 c o a l mines l oca t ed throughout t h e United S t a t e s . From those Bur eau of Mines tests, apparent e a r t h conduc t iv i t y va lues were der ived based upon a homogeneous half-space model of t h e e a r t h . The der ived conduc t iv i t y va lues were found t o be i nve r se ly p ropor t i ona l t o t h e t r a n s m i t t e d frequency and mine depth. A l i n e a r r eg re s s ion model r e l a t i n g t h e logar i thm of t h e conduc t iv i t y t o t h e mine depth was formulated, and t h e r e s u l t s i n d i c a t e t h a t t h e mine depth can be an adequate pred i c t o r of t h e apparen t e a r t h conduc t iv i t y above c o a l mines. Apparent e a r t h conduc t iv i t y was found t o decrease w i th mine depth. l ~ l e c t r i c a l engineer , P i t t sbu rgh Research Center, Bureau of Mines, P i t t sbu rgh , PA.
Differential evolution particle swarm optimization algorithm for reduction of network loss and voltage instability

This paper introduces a differential evolution particle swarm optimization (DEPSO) method for dealing with optimal reactive power dispatch aiming at power loss reduction and voltage stability improvement. The optimum reactive power dispatch of power systems is to allocate reactive power control variables so that the objective function composed of power losses is minimized and the prescribed voltage limits are satisfied. The proposed method determines the optimum settings of reactive power control variables such as, generator excitation, tap changing transformers, and shunt compensation that reduces the power loss, while maintaining the voltage stability. IEEE-30 bus test system from the literature is used to exemplify the performance of the proposed method. Numerical results show that the proposed method is better than the other methods reported in the literature.
A comparison of network and application layer multicast for mobile IPv6 networks

In this paper we compare Network (IP multicast) and Application Layer Multicast (ALM) under a specific assumption: end hosts are wireless devices using the Mobile IPv6 (MIPv6) protocol. This comparison has three main goals. First, we analyze the implications of running multicast in a mobile, wireless network using Mobile IPv6 (MIPv6). Second, we run a number of simulations to verify whether the network performance issues are different than in wired networks. Finally, using these results, we try to identify the factors that have the most significant impact on performance. Our results indicate that although ALM can be designed to work on top of a wireless network running MIPv6, there are a number of additional performance penalties beyond what occurs in wired networks. Essentially, the advantage of using IP multicast grows even stronger in mobile networks. Nevertheless, we recognize that there are significant barriers to ubiquitous network layer multicast and therefore believe that a more hybrid approach combining both IP multicast and ALM would offer the best performance.
Mapping WordNet Domains, WordNet Topics and Wikipedia Categories to Generate Multilingual Domain Specific Resources

In this paper we present the mapping between WordNet domains and WordNet topics, and the emergent Wikipedia categories. This mapping leads to a coarse alignment between WordNet and Wikipedia, useful for producing domain-specific and multilingual corpora. Multilinguality is achieved through the cross-language links between Wikipedia categories. Research in word-sense disambiguation has shown that within a specific domain, relevant words have restricted senses. The multilingual, and comparable, domain-specific corpora we produce have the potential to enhance research in word-sense disambiguation and terminology extraction in different languages, which could enhance the performance of various NLP tasks.
Analysis of Multi-Temporal Geospatial Data Sets to Assess the Landscape Effects of Surface Mining

Geospatial data sets, especially digital elevation data, have proven useful for characterizing and analyzing land surface conditions. Digital elevation models are routinely used for describing the morphology of the land surface in terms of slope gradient and aspect. Additionally, the elevation data are useful for deriving parameters that describe the local drainage conditions such as watersheds and stream channels. When the element of time is added to the analysis through the use of multi-temporal topographic data, the effects of changes to the physical shape of the land surface may be studied. Such is the case with analysis of historical (pre-mining) and recent (post-mining) topographic and other geospatial data sets, including land cover maps derived from remote sensing. Nationwide geospatial data sets now exist with the required spatial and temporal resolution that allow for assessment of the effects of surface mining operations. Changes to the local landscape morphology are readily identified, and the effects to the surface drainage features are quantifiable, such as changes to local relief and drainage pattern and the total length of affected streams. Additionally, the visual impact of the movement of rock and soil materials may be assessed through viewshed analysis. Examples in both Appalachian and Western coalfields show the usefulness of analyzing detailed historical and recent geospatial data sets to better map and describe the effects of surface mining. Additional
Spectral Learning for Non-Deterministic Dependency Parsing

In this paper we study spectral learning methods for non-deterministic split head-automata grammars, a powerful hidden-state formalism for dependency parsing. We present a learning algorithm that, like other spectral methods, is efficient and non-susceptible to local minima. We show how this algorithm can be formulated as a technique for inducing hidden structure from distributions computed by forward-backward recursions. Furthermore, we also present an inside-outside algorithm for the parsing model that runs in cubic time, hence maintaining the standard parsing costs for context-free grammars.
Transcriptional activation by p53, but not induction of the p21 gene, is essential for oncogene‐mediated apoptosis.

The p53 tumor suppressor limits cellular proliferation by inducing either G1 arrest or apoptosis, depending on the cellular context. To determine if these pathways are mechanistically distinct, we have examined the effects of different p53 mutants in p53 null primary mouse embryo fibroblasts. We chose this system as it is highly physiological and ensures that the interpretation of the results will not be confounded by the presence of endogenous p53 or oncoproteins which target p53. Using single cell microinjection assays for both G1 arrest and apoptosis, with loss‐of‐function and chimeric gain‐of‐function mutants, we have demonstrated that transcriptional activation is critical for both processes. Replacement of the p53 activation domain with that of VP16, or replacement of the p53 oligomerization domain with that of GCN4, reconstituted both G1 arrest and apoptosis activities. However, despite the importance of transcriptional activation in both processes, the target gene requirements are different. The p21 cyclin‐dependent kinase inhibitor, which has been shown to be a direct target of p53 and a component of the radiation‐induced G1 arrest response, is dispensable for oncogene‐induced apoptosis, suggesting that these two p53‐dependent transcriptional pathways are distinct.
Understanding spatial patterns of diversity and productivity in alpine plant communities : application of high-resolution imagery in the French Alps

The central aim of this thesis is to contribute to current understanding of environmental drivers of plant diversity and productivity as well as of recent changes in vegetation structure in a temperate alpine context, the French Alps. My approach draws on methods from remote sensing and plant ecology by combining plot-based measures of plant diversity and climate data with high-resolution imagery. Chapter I demonstrates the importance of quantifying snow cover duration for predicting patterns of plant taxonomic and functional diversity, and also highlights the ongoing challenge of modeling spatial gross primary productivity dynamics in alpine landscapes. In Chapter II, I explore the utility of satellite imagery for quantifying environmental conditions experienced by alpine plant communities, and further show how metrics of snow cover duration and peak productivity can be used to differentiate habitat for dominant alpine plant communities. I also explore how functional diversity mediates NDVI responses to highly contrasting snow years. Chapter III provides new evidence of recent shifts occurring in high-elevation plant communities in the French Alps in response to climate and land-use change. Analysis of the forest-grassland ecotone in the Vercors Regional Park shows a strong dynamic of forest expansion in response to overall climate warming and local shifts in grazing-related land-use practices, which supports findings from other studies conducted elsewhere in the Alps and Pyrenees. In the second part of Chapter III, for the first time I present evidence of greening dynamics in a protected area of the French Alps, the Ecrins National Park. I propose that a decrease in snow cover duration and pronounced warming occurring in the 1980s likely contributed to increased canopy productivity in high alpine contexts, and are driving long-term greening in the absence of land-use change. Taken collectively, rather than pushing a specific aspect alpine ecology forward, my work helps to fill out our working knowledge of alpine plant communities and serves to solidify a number of field-based observations by carrying out robust spatial analyses.
Physiology of pregnancy and nutrient metabolism 1 – 3

Pregnancy consists of a series of small, continuous physiologic adjustments that affect the metabolism of all nutrients. The adjustments undoubtedly vary widely from woman to woman depending on her prepregnancy nutrition, genetic determinants of fetal size, and maternal lifestyle behavior. Studies of protein and energy metabolism illustrate the potential of adjusting the use of those nutrients to conserve a fetal supply. Adjustments in the metabolism of nitrogenous compounds are in place by the second quarter of pregnancy. During the last quarter of pregnancy, when fetal demands are greatest, those adjustments allow a positive nitrogen retention. The energy requirement of basal metabolism is influenced by maternal prepregnant nutrition and by fetal size. If maternal energy reserves are low at conception, the basal metabolic rate is downregulated to conserve energy. Also, women having larger babies tend to have greater increases in their basal metabolic rate and lower rates of maternal energy storage. Changes in maternal food and physical activity behaviors during gestation may augment the physiologic adjustments. However, the substantial variability in food intakes and physical activity makes it difficult to show those changes. Thresholds in the capacity to adjust nutrient use to the amount supplied exist for all nutrients. When intakes fall below the threshold, fetal growth and development is affected more than is maternal health. Efforts to achieve good maternal nutritional status preconception as well as throughout gestation best assure a good milieu for fetal growth and development. Am J Clin Nutr2000;71(suppl):1218S–25S.
Learning Vowels Using Self-Organization

This paper describes research that investigates the structure of human vowel systems through individual learning and self-organization. A population of agents that have to learn to imitate each other has been implemented. The agents can interact with each other through so-called imitation games: structured exchanges of sounds from which they can learn how to improve their repertoire of sounds. The architecture of the agents, the way they produce and perceive sounds and the workings of the imitation game are described in some detail. The results of experiments with artificial agents show that realistic vowel systems can be learned. Then it is described how the system can be extended to work with real signals and it is indicated that the results obtained in this way are similar to the ones obtained with the first system. It is also demonstrated that it is possible to learn vowels from a human speaker. Finally the relation to other linguistic work into the structure of vowel systems is described.
Analysis of the Clustering Properties of the Hilbert Space-Filling Curve

Several schemes for the linear mapping of a multidimensional space have been proposed for various applications, such as access methods for spatio-temporal databases and image compression. In these applications, one of the most desired properties from such linear mappings is clustering, which means the locality between objects in the multidimensional space being preserved in the linear space. It is widely believed that the Hilbert space-filling curve achieves the best clustering (Abel and Mark, 1990; Jagadish, 1990). We analyze the clustering property of the Hilbert space-filling curve by deriving closed-form formulas for the number of clusters in a given query region of an arbitrary shape (e.g., polygons and polyhedra). Both the asymptotic solution for the general case and the exact solution for a special case generalize previous work. They agree with the empirical results that the number of clusters depends on the hypersurface area of the query region and not on its hypervolume. We also show that the Hilbert curve achieves better clustering than the z curve. From a practical point of view, the formulas given provide a simple measure that can be used to predict the required disk access behaviors and, hence, the total access time.
Entity refinement using latent semantic indexing

Automated extraction of named entities is an important text analysis task. In addition to recognizing the occurrence of entity names, it is important to be able to label those names by type. Most entity extraction techniques categorize extracted entities into a few basic types, such as PERSON, ORGANIZATION, and LOCATION. This paper presents an approach for generating more fine-grained subdivisions of entity type. The technique of latent semantic indexing (LSI) is used to provide semantic context as an indicator of likely entity subtype. Tests were carried out on a collection of 5.5 million English-language news articles. At modest levels of recall, the accuracy of sub-type assignment was comparable to the accuracy with which the gross type was assigned by a state-of-the-art commercial entity extraction software package.
Selection of sublexical units for continuous speech recognition of basque

This paper describes the work carried out to select the most suitable set of Sublexical Units for Continuous Speech Recognition of Basque. Even if there are several dialects in Basque, only one of them has been used to choose the preliminary set of sounds. Bearing in mind this aim, a wide experimentation has been carried out to select Context Independent Phone-Like Units. Then, in order to obtain robust acoustic models for the language, the units have been evaluated with most of the dialectal variants of Basque. Finally, Decision-Trees based Context Dependent Sublexical Units are selected. For building the trees the classical methodology of Bahl and the efficient Growing and Pruning algorithm have been used.
Acceleration of Northern Ice Sheet Melt Induces AMOC Slowdown and Northern Cooling in Simulations of the Early Last Deglaciation

The cause of a rapid change in Atlantic Ocean circulation and northern cooling at the onset of Heinrich Stadial 1 ~18.5 ka is unclear. Previous studies have simulated the event using ice sheet and/or iceberg meltwater forcing, but these idealized freshwater fluxes have been unrealistically large. Here we use a different approach, driving a high‐resolution drainage network model with a recent time‐resolved global paleo‐ice sheet reconstruction to generate a realistic meltwater forcing. We input this flux to the Hadley Centre Coupled Model version 3 (HadCM3) climate model without adjusting the timing or amplitude and find that an acceleration in northern ice sheet melting (up to ~7.5 m/kyr global mean sea level rise equivalent) triggers a 20% reduction in the Atlantic Meridional Overturning Circulation. The simulated pattern of ocean circulation and climate change matches an array of paleoclimate and ocean circulation reconstructions for the onset of Heinrich Stadial 1, in terms of both rates and magnitude of change. This is achieved with a meltwater flux that matches constraints on sea level changes and ice sheet evolution around 19–18 ka. Since the rates of melting are similar to those projected for Greenland by 2200, constraining the melt rates and magnitude of climate change during Heinrich Stadial 1 would provide an important test of climate model sensitivity to future ice sheet melt.
Experiments in TREC 2007 Blog Opinion Task at CAS-ICT

This paper describes our participation in TREC 2007 Blog Track Tasks: Opinion retrieval and Polarity classification. As for Opinion retrieval task, a two-step approach is used to retrieve opinion relevant blog unit (that is blog post and its comments) given a query after filtering Spam blog and extracting blog unit. With Polarity Classification, Drag-push [1] based classifier is employed to get polarity of blog unit. Finally, we introduce all the runs submitted.
Pareto-optimization-based run-time task scheduling for embedded systems

Pareto-set-based optimization can be found in several different areas of embedded system design. One example is task scheduling, where different task mapping and ordering choices for a target platform will lead to different performance/cost tradeoffs. To explore this design space at runtime, a fast and effective heuristic is needed. We have modeled the problem as the well known Multiple Choice Knapsack Problem (MCKP) and have developed a fast greedy heuristic for the run-time task scheduling. To show the effectiveness of our algorithm, examples from randomly generated task graphs and realistic applications are studied. Compared to the optimal dynamic programming solver, the heuristic is more than ten times faster while the result is less than 5% away from the optimum. Moreover, due to its iterative feature, the algorithm is well suitable to be used as an online algorithm.
Structured Regression Gradient Boosting

We propose a new way to train a structured output prediction model. More specifically, we train nonlinear data terms in a Gaussian Conditional Random Field (GCRF) by a generalized version of gradient boosting. The approach is evaluated on three challenging regression benchmarks: vessel detection, single image depth estimation and image inpainting. These experiments suggest that the proposed boosting framework matches or exceeds the state-of-the-art.
Motion Onset Captures Attention

Although visual motion may seem salient, motion per se does not automatically attract attention. We show here, however, that the onset of motion does indeed attract attention. In three experiments, subjects identified target letters in displays that contained targets and distractors. There was no advantage for moving letters among static ones, but there was an advantage for objects that had recently started to move despite the fact that the motion was uninformative. If some additional time was allowed to elapse after motion onset, inhibition of return slowed responding to the item that had started to move—a further sign that the motion onset had captured attention. Finally, detection of target letters was found to be independent of the number of distractors in the display if the target had undergone motion onset, also indicative of attentional capture. We discuss the adaptive significance of sensitivity to onsets in the presence of a relative insensitivity to ongoing motion.
Learning with Tree-Averaged Densities and Distributions

We utilize the ensemble of trees framework, a tractable mixture over super-exponential number of tree-structured distributions [1], to develop a new model for multivariate density estimation. The model is based on a construction of tree-structured copulas - multivariate distributions with uniform on [0, 1] marginals. By averaging over all possible tree structures, the new model can approximate distributions with complex variable dependencies. We propose an EM algorithm to estimate the parameters for these tree-averaged models for both the real-valued and the categorical case. Based on the tree-averaged framework, we propose a new model for joint precipitation amounts data on networks of rain stations.
Translating Ocular Biomechanics into Clinical Practice: Current State and Future Prospects

Abstract Biomechanics is the study of the relationship between forces and function in living organisms and is thought to play a critical role in a significant number of ophthalmic disorders. This is not surprising, as the eye is a pressure vessel that requires a delicate balance of forces to maintain its homeostasis. Over the past few decades, basic science research in ophthalmology mostly confirmed that ocular biomechanics could explain in part the mechanisms involved in almost all major ophthalmic disorders such as optic nerve head neuropathies, angle closure, ametropia, presbyopia, cataract, corneal pathologies, retinal detachment and macular degeneration. Translational biomechanics in ophthalmology, however, is still in its infancy. It is believed that its use could make significant advances in diagnosis and treatment. Several translational biomechanics strategies are already emerging, such as corneal stiffening for the treatment of keratoconus, and more are likely to follow. This review aims to cultivate the idea that biomechanics plays a major role in ophthalmology and that the clinical translation, lead by collaborative teams of clinicians and biomedical engineers, will benefit our patients. Specifically, recent advances and future prospects in corneal, iris, trabecular meshwork, crystalline lens, scleral and lamina cribrosa biomechanics are discussed.