Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiple GPI-Anchored Receptors Control GDNF-Dependent and Independent Activation of the c-Ret Receptor Tyrosine Kinase

Glial cell line-derived neurotrophic factor (GDNF) mediates neuronal survival through a receptor complex composed of the c-Retproto-oncogene and GFR alpha-1, a member of a family of GPI-anchored receptors. The extent of cross-talk between GDNF and GFR alpha receptors and its possible significance for c-Ret activation is presently unclear. Using chemical crosslinking we demonstrate here a specific interaction between GDNF and GFR alpha-2 expressed in COS cells, albeit of a lower affinity than the one between GDNF and GFR alpha-1. In addition, GFR alpha-2 mediated crosslinking of GDNF of c-Ret as well as ligand-dependent stimulation of c-Ret tyrosine phosphorylation. We also describe the isolation of a novel, more divergent member of the GFR alpha family, GFR alpha-3, which did not bind GDNF directly, but was able to mediate crosslinking of GDNF to c-Ret when both receptors were coexpressed in COS cells. Thus, all three GFR alpha receptors mediate GDNF binding to c-Ret with efficiencies GFR alpha-1 > GFR alpha-2 > GFR alpha-3. c-Ret showed high levels of constitutive tyrosine autophosphorylation upon overexpression in COS cells, which was inhibited in a dose-dependent manner by coexpression with any of the GFR alpha receptors, suggesting that GFR alpha s may also provide a gain control mechanism to increase the signal-to-noise ratio of the response to ligand. GFR alpha-2 showed a dynamic pattern of expression in rat brain, distinct from that of GFR alpha-1, characterized by high expression in cortex, basal forebrain, and specific layers of the olfactory bulb, and low or no expression in substantia nigra, cerebellum, and motor nuclei. GFR alpha-2, but not GFR alpha-3 mRNA expression was highly induced in several nuclei after stimulation with kainic acid. In contrast to GFR alpha-1 and GFR alpha-2, GFR alpha-3 expression in postnatal and adult brain was highly restricted. Developmentally regulated expression of GFR alpha-3 was, however, detected in several peripheral organs and ganglia. Together, these results indicate complementary roles for GFR alpha receptors in the regulation of c-Ret activity and the maintenance of distinct neuronal circuits in the central and peripheral nervous systems.
The Synthesis and Analysis of Color Images

I describe a method for performing the synthesis and analysis of digital color images. The method is based on two principles. First, image data are represented with respect to the separate physical factors, surface reflectance and the spectral power distribution of the ambient light, that give rise to the perceived color of an object. Second, the encoding is made efficient by using a basis expansion for the surface spectral reflectance and spectral power distribution of the ambient light that takes advantage of the high degree of correlation across the visible wavelengths normally found in such functions. Within this framework, the same basic methods can be used to synthesize image data for color display monitors and printed materials, and to analyze image data into estimates of the spectral power distribution and surface spectral reflectances. The method can be applied to a variety of tasks. Examples of applications include the color balancing of color images and the identification of material surface spectral reflectance when the lighting cannot be completely controlled.
Stochastic Designs in Event-Related fMRI

This article considers the efficiency of event-related fMRI designs in terms of the optimum temporal pattern of stimulus or trial presentations. The distinction between "stochastic" and "deterministic" is used to distinguish between designs that are specified in terms of the probability that an event will occur at a series of time points (stochastic) and those in which events always occur at prespecified time (deterministic). Stochastic designs may be "stationary," in which the probability is constant, or nonstationary, in which the probabilities change with time. All these designs can be parameterized in terms of a vector of occurrence probabilities and a prototypic design matrix that embodies constraints (such as the minimum stimulus onset asynchrony) and the model of hemodynamic responses. A simple function of these parameters is presented and used to compare the relative efficiency of different designs. Designs with slow modulation of occurrence probabilities are generally more efficient than stationary designs. Interestingly the most efficient design is a conventional block design. A critical point, made in this article, is that the most efficient design for one effect may not be the most efficient for another. This is particularly important when considering evoked responses and the differences among responses. The most efficient designs for evoked responses, as opposed to differential responses, require trial-free periods during which baseline levels can be attained. In the context of stochastic, rapid-presentation designs this is equivalent to the inclusion of "null events. "
Auto-JacoBin: Auto-encoder Jacobian Binary Hashing

Binary codes can be used to speed up nearest neighbor search tasks in large scale data sets as they are efficient for both storage and retrieval. In this paper, we propose a robust auto-encoder model that preserves the geometric relationships of high-dimensional data sets in Hamming space. This is done by considering a noise-removing function in a region surrounding the manifold where the training data points lie. This function is defined with the property that it projects the data points near the manifold into the manifold wisely, and we approximate this function by its first order approximation. Experimental results show that the proposed method achieves better than state-of-the-art results on three large scale high dimensional data sets.
Plasma modeling for ultrashort pulse laser ablation of dielectrics

In ultrashort pulse (<10ps) laser ablation of dielectrics, affected materials are first transformed into absorbing plasma with metallic properties and, then, the subsequent laser-plasma interaction causes material removals. For ultrashort-pulse laser ablation of dielectrics, this study proposes a model using the Fokker-Planck equation for electron density distribution, a plasma model for the optical properties of ionized dielectrics, and quantum treatments for electron heating and relaxation time. The free electron density distribution of the plasma within the pulse duration is then used to determine the ablation crater shape. The predicted threshold fluences and ablation depths for barium aluminum borosilicate and fused silica are in agreement with published experimental data. It is found that the significantly varying optical properties in time and space are the key factors determining the ablation crater shape. The effects of fluence and pulse duration are also studied.
On the Practicality of Low-Density Parity-Check Codes

Recent advances in coding theory have produced two classes of codes, turbo codes and low-density parity-check (LDPC) codes, which approach the Shannon limit of channel capacity while admitting efficient implementations of message encoding and decoding in software. Theoretic results about the latter have been shown to apply to the former, hence we examine the evolution of LDPC codes from their origin in Gallager’s 1963 thesis to their current incarnation as tornado codes developed by Luby, Mitzenmacher, Shokrollahi, and Spielman. After considering several analytic approaches to quantifying their performance, we discuss the practicality of LDPC codes, particularly those designed for the erasure channel, when applied to a number of current problems in networking.
Visualizing Summary Statistics and Uncertainty

The graphical depiction of uncertainty information is emerging as a problem of great importance. Scientific data sets are not considered complete without indications of error, accuracy, or levels of confidence. The visual portrayal of this information is a challenging task. This work takes inspiration from graphical data analysis to create visual representations that show not only the data value, but also important characteristics of the data including uncertainty. The canonical box plot is reexamined and a new hybrid summary plot is presented that incorporates a collection of descriptive statistics to highlight salient features of the data. Additionally, we present an extension of the summary plot to two dimensional distributions. Finally, a use‐case of these new plots is presented, demonstrating their ability to present high‐level overviews as well as detailed insight into the salient features of the underlying data distribution.
Fast Convention Formation in Dynamic Networks Using Topological Knowledge

In this paper, we design a distributed mechanism that is able to create a social convention within a large convention space for multiagent systems (MAS) operating on various topologies. Specifically, we investigate a language coordination problem in which agents in a dynamic MAS construct a common lexicon in a decentralized fashion. Agent interactions are modeled using a language game where every agent repeatedly plays with its neighbors. Each agent stochastically updates its lexicons based on the utility values of the received lexicons from its immediate neighbors. We present a novel topology-aware utility computation mechanism and equip the agents with the ability to reorganize their neighborhood based on this utility estimate to expedite the convention formation process. Extensive simulation results indicate that our proposed mechanism is both effective (able to converge into a large majority convention state with more than 90\% agents sharing a high-quality lexicon) and efficient (faster) as compared to state-of-the-art approaches for social conventions in large convention spaces.
Featureless spectra on the Moon as evidence of residual lunar primordial crust

We report the global distribution of areas exhibiting no absorption features (featureless or FL) on the lunar surface, based on the reflectance spectral data set obtained by the Spectral Profiler onboard Kaguya/SELENE. We found that FL sites are located in impact basins and large impact craters in the Feldspathic Highlands Terrane, while there are no FL sites in the Procellarum regions nor the South Pole‐Aitken basin. FL sites in each impact basin/crater are mainly found at the peak rings or rims, where the purest anorthosite (PAN) sites are also found. At the local scale, most of the FL and PAN points are associated with impact craters and peaks. Most of the FL spectra show a steeper (redder) continuum than the PAN spectra, suggesting the occurrence of space weathering effects. We propose that most of the material exhibiting a FL spectrum originate from space weathered PAN. Taking into account all the occurrence trends of FL sites on the Moon, we propose that both the FL and PAN materials were excavated from the primordial lunar crust during ancient basin formations below the megaregolith in the highlands. Since the FL and PAN sites are widely distributed over the lunar surface, our new data may support the existence of a massive PAN layer below the lunar surface.
Targeting the microRNA-21/AP1 axis by 5-fluorouracil and pirarubicin in human hepatocellular carcinoma

MicroRNAs function as oncomiRs and tumor suppressors in diverse cancers. However, the utility of specific microRNAs in predicting the clinical benefit of chemotherapy has not been well-established. Here, we investigated the correlation between microRNA-21 expression and hepatic arterial infusion chemotherapy with 5-fluorouracil and pirarubicin (HAIC) for hepatocellular carcinoma (HCC). We found that HCC patients with low microRNA-21 levels in tumors tended to have a longer time to recurrence and disease-free survival. We demonstrated that microRNA-21 suppression in combination with 5-fluorouracil and pirarubicin treatment inhibited tumor growth in subcutaneous xenograft mice models. Mechanistically, the AP-1 and microRNA-21-mediated axis was verified to be a therapeutic target of cytotoxic drugs and deregulation of this axis led to an enhanced cell growth in HCC. Taken together, our findings demonstrate that microRNA-21 is a chemotherapy responsive microRNA and can serve as a prognostic biomarker for HCC patients undergoing HAIC. Targeting microRNA-21 enhances the effect of chemotherapeutic drugs, thereby suggesting that microRNA-21 suppression in combination with HAIC may be a novel approach for HCC treatment.
Cognitive-Based Rules as a Means to Select Suitable Groupware Tools

Global software development projects have to deal with a variety of challenges with respect to communication and control. For this reason, processes that are crucially based on communication, such as requirement elicitation, have to be specially rethought to minimize critical situations. As requirement elicitation is a human-centred process, we propose using techniques from the field of cognitive psychology to define a new approach towards it. In short, we intend to reduce problems in communication by selecting a suite of elicitation techniques and groupware tools, according to stakeholders' preference in styles. In this article we introduce our approach and show the generation process of a set of preference rules of groupware tools
A Possible Geographic Origin of Endemic Hepatitis C Virus 6a in Hong Kong: Evidences for the Association with Vietnamese Immigration

Background Hepatitis C virus (HCV) 6a accounts for 23.6% of all HCV infections of the general population and 58.5% of intravenous drug users in Hong Kong. However, the geographical origin of this highly predominant HCV subgenotype is largely unknown. This study explores a hypothesis for one possible transmission route of HCV 6a to Hong Kong. Methods NS5A sequences derived from 26 HCV 6a samples were chosen from a five year period (1999–2004) from epidemiologically unrelated patients from Hong Kong. Partial-NS5A sequences (513-bp from nt 6728 to 7240) were adopted for Bayesian coalescent analysis to reconstruct the evolutionary history of HCV infections in Hong Kong using the BEAST v1.3 program. A rooted phylogenetic tree was drawn for these sequences by alignment with reference Vietnamese sequences. Demographic data were accessed from “The Statistic Yearbooks of Hong Kong”. Results Bayesian coalescent analysis showed that the rapid increase in 6a infections, which had increased more than 90-fold in Hong Kong from 1986 to 1994 correlated to two peaks of Vietnamese immigration to Hong Kong from 1978 to 1997. The second peak, which occurred from 1987 through 1997, overlapped with the rapid increase of HCV 6a occurrence in Hong Kong. Phylogenetic analyses have further revealed that HCV 6a strains from Vietnam may be ancestral to Hong Kong counterparts. Conclusions The high predominance of HCV 6a infections in Hong Kong was possibly associated with Vietnamese immigration during 1987–1997.
Towards monocular localization using ground points

This paper proposes a mobile robot localization approach based on a monocular vision system. The proposal operates in three main steps. First, image features are extracted from frames gathered at different positions. Second, the obtained features are classified as obstacles or ground points. Third, under the assumption of a flat floor, the ground point coordinates are computed and used to perform localization. The experimental results, performed both in simulation and real environments, validate the proposal.
Estrogen Shapes Dopamine-Dependent Cognitive Processes: Implications for Women's Health

The prefrontal cortex (PFC) is exquisitely sensitive to its neurochemical environment. Minor fluctuations in cortical dopamine (DA) can profoundly alter working memory, a PFC-dependent cognitive function that supports an array of essential human behaviors. Dopamine's action in the PFC follows an inverted U-shaped curve, where an optimal DA level results in maximal function and insufficient or excessive DA impairs PFC function. In animals, 17β-estradiol (the major estrogen in most mammals, referred to henceforth as estradiol) has been shown to enhance DA activity, yet no human study has adequately addressed whether estradiol's impact on cognition occurs by way of modulating specific neurochemical systems. Here we examined the effects of endogenous fluctuations in estradiol on working memory in healthy young women as a function of baseline PFC DA [indexed by catechol-O-methyltransferase (COMT) Val158Met genotype and, at a finer scale, COMT enzyme activity]. The results demonstrate that estradiol status impacts working memory function and, crucially, the direction of the effect depends on indices of baseline DA. Moreover, consistent with a DA cortical efficiency hypothesis, functional MRI revealed that inferred optimal DA was associated with reduced PFC activity sustained across task blocks and selectively enhanced PFC activity on trials with the greatest demand for cognitive control. The magnitude of PFC activity during high control trials was predictive of an individual's performance. These findings show that although estrogen, considered in isolation, may have unpredictable effects on cognitive performance, its influence is clarified when considered within a larger neuromodulatory framework. Given the clinical prevalence of dopaminergic drugs, understanding the relationship between estrogen and DA is essential for advancing women's health.
The ITHACA office object model: modeling and implementation

This paper presents an object-oriented approach to modeling an office, including both its content and the activities that are carried out within it. This is a part of a larger research effort---the ITHACA Project (Integrated Toolkit for Highly Advanced Computer Applications). Its purpose is to provide software engineers and application programmers with a generic framework within which to develop large, distributed office support systems. The set of interrelated models contains: the active object, the passive object and the procedure models. The active object model represents persons (or actors), organizational structures and their linkages through roles. Office facilities (e.g., cabinets, tables, tops-of-desks, wastebaskets) and information (e.g., documents, letters) are captured by the passive object model. The relationships among the various objects are expressed by both specified relationship attributes and other attributes that can be derived from them. The procedure model consists of office operators (e.g., Move, Edit, Create, Send) that are used as basic building blocks for defining office procedures.The model is presently being used to develop software for the ITHACA Project. A prototype of the active office object model has been developed, written in CooL---Combined object-oriented Language. The prototype will be used as a basis for developing a more complete systems architecture, also described in the paper.
Degenerate BESS Model: The possibility of a low energy strong electroweak sector

We discuss possible symmetries of eﬀective theories describing spinless and spin 1 bosons, mainly to concentrate on an intriguing phenomenological possibility: that of a hardly noticeable strong electroweak sector at relatively low energies. Speciﬁcally, a model with both vector and axial vector strong interacting bosons may possess a discrete symmetry imposing degeneracy of the two sets of bosons (degenerate BESS model). In such a case its eﬀects at low energies become almost invisible and the model easily passes all low energy precision tests. The reason lies essentially in the fact that the model automatically satisﬁes decoupling, contrary to models with only vectors. For large mass of the degenerate spin one bosons the model becomes identical at the classical level to the standard model taken in the limit of inﬁnite Higgs mass. For these reasons we have thought it worthwhile to fully develop the model, together with its possible generalizations, and to study the expected phenomenology. For instance, just because of its invisibility at low energy, it is conceivable that degenerate BESS has low mass spin one states and gives quite visible signals at existing or forthcoming accelerators.
Variational Optimization

We discuss a general technique that can be used to form a differentiable bound on the optima of non-differentiable or discrete objective functions. We form a unified description of these methods and consider under which circumstances the bound is concave. In particular we consider two concrete applications of the method, namely sparse learning and support vector classification.
A Forced Spectral Diversity Algorithm for Speech Dereverberation in the Presence of Near-Common Zeros

Blind identification of single-input multiple-output (SIMO) systems is not normally possible if common zeros exist in the channels. Studies of measured acoustic SIMO systems show that near-common zeros occur in such systems as encountered in the speech dereverberation task. We therefore introduce a method to add additional diversity to the SIMO system to be identified which we term forced spectral diversity (FSD) and we show that its use leads to an identification-equalization approach that gives improved dereverberation. As part of this work, we show the link between channel diversity and the effect of common zeros. We also define and discuss in more detail the concept and impact of near-common zeros. The proposed algorithm is presented specifically for a two-channel system where such near-common zeros exist.
A FUZZY BASED APPROACH FOR EARLY REQUIREMENT PRIORITIZATION

The importance of the prioritization in commercial software development has been analyzed by many researchers. The gathered requirements are required to be put into an order of some priority. In other words we can say that there is a need to prioritize the requirements. It is evident that most of the approaches and techniques proposed in recent research to prioritize the requirements have not been widely adopted. These approaches are too complex, time consuming, or inconsistent and difficult to implement In this paper we propose a fuzzy based approach for requirement prioritization in which requirement are prioritized in early phase of requirement engineering as post elicitation step. This category of prioritization is known as early requirement prioritization. The proposed fuzzy based approach considers the nature of requirements by modeling their attributes as fuzzy variables. As such, these variables are integrated into a fuzzy based inference system in which the requirements represented as input attributes and ranked via the expected value operator of a fuzzy variable.