Miracle-dz/UniFAR-FTUs huggingface dataset:
Federal Reserve Bank of Dallas Globalization and Monetary Policy Institute Fiscal Stabilization with Partial Exchange Rate Pass-through Fiscal Stabilization with Partial Exchange Rate Pass-through

This paper examines the role of fiscal stabilization policy in a two-country framework that allows for a general degree of exchange rate pass-through. I derive analytical solutions for optimal monetary and fiscal policy which are shown to depend on the degree of pass-through. In the case of partial pass-through, an optimizing policy maker uses counter-cyclical fiscal stabilization in addition to monetary stabilization. However, in the extreme cases of complete or zero pass-through, the fiscal stabilization instrument is not employed. There is also no additional gain from the fiscal instrument in the case of coordination between the two countries. These results are due to the specific way the optimal fiscal policy rule affects marginal costs: Rather than being a substitute for monetary policy, fiscal policy complements it by increasing the correlation of the marginal cost terms within and across countries. This in turn makes monetary policy more effective at stabilizing them. have been greatly appreciated. I would also like to thank the Bradley Foundation at Texas A&M University for financial support and the Private Enterprise Research Center for hospitality. The views in this paper are those of the author and do not necessarily reflect the views of the Federal Reserve Bank of Dallas or the Federal Reserve System. Abstract This paper examines the role of …scal stabilization policy in a two-country framework that allows for a general degree of exchange rate pass-through. I derive analytical solutions for optimal monetary and …scal policy which are shown to depend on the degree of pass-through. In the case of partial pass-through, an optimizing policy maker uses counter-cyclical …scal stabilization in addition to monetary stabilization. However, in the extreme cases of complete or zero pass-through, the …scal stabilization instrument is not employed. There is also no additional gain from the …scal instrument in the case of coordination between the two countries. These results are due to the speci…c way the optimal …scal policy rule a¤ects marginal costs: Rather than being a substitute for monetary policy, …scal policy complements it by increasing the correlation of the marginal cost terms within and across countries. This in turn makes monetary policy more e¤ective at stabilizing them.
Insights into Molecular Features of Venerupis decussata Oocytes: A Microarray-Based Study

The production of Venerupis decussata relies on wild seed collection, which has been recently compromised due to recruitment failure and severe mortalities. To address this issue and provide an alternative source of seed, artificial spawning and larval rearing programs were developed. However, hatchery-based seed production is a relatively new industry and it is still underdeveloped. A major hurdle in the European clam seed production is the control of spawning and reproduction, which is further hindered by the impossibility of obtaining fertile gametes by gonadal “stripping”, as meiosis re-initiation is constrained to a maturation process along the genital ducts. In the present study, oocytes were collected from 15 females and microarray analyses was performed to investigate gene expression profiles characterizing released and stripped ovarian oocytes. A total of 198 differentially expressed transcripts between stripped and spawned oocytes were detected. Functional analysis carried out on these transcripts highlighted the importance of a few biological processes, which are most probably implicated in the control of oocyte competence. Significant differences were observed for transcripts encoding proteins involved in meiosis progression (e.g. dual specificity phosphatase CDC25), WNT signalling (e.g. frizzled class receptor 8, wingless-type MMTV integration site family member 4), steroid synthesis (e.g. progestin and adipoQ receptor family member 3, cytochrome P450-C17), mRNA processing (e.g. zinc finger protein XlCOF28), calcium regulation (e.g. regucalcin, calmodulin) and ceramide metabolism (ceramidase B, sphingomyelinase). This study provides new information on transcriptional profiles putatively associated with ovarian egg infertility, and suggests potential mechanisms regulating early oocyte development in clams. Genes which were differentially expressed between stripped and spawned oocytes might have a pivotal role during maturation process in the gonadal duct and could be interesting targets for further functional studies aiming to make ovarian oocytes fertilizable.
Fixed-Rank Rayleigh Quotient Maximization by an MPSK Sequence

Certain optimization problems in communication systems, such as limited-feedback constant-envelope beamforming or noncoherent M-ary phase-shift keying (MPSK) sequence detection, result in the maximization of a fixed-rank positive semidefinite quadratic form over the MPSK alphabet. This form is a special case of the Rayleigh quotient of a matrix and, in general, its maximization by an MPSK sequence is \mathcal{NP}-hard. However, if the rank of the matrix is not a function of its size, then the optimal solution can be computed with polynomial complexity in the matrix size. In this work, we develop a new technique to efficiently solve this problem by utilizing auxiliary continuous-valued angles and partitioning the resulting continuous space of solutions into a polynomial-size set of regions, each of which corresponds to a distinct MPSK sequence. The sequence that maximizes the Rayleigh quotient is shown to belong to this polynomial-size set of sequences, thus efficiently reducing the size of the feasible set from exponential to polynomial. Based on this analysis, we also develop an algorithm that constructs this set in polynomial time and show that it is fully parallelizable, memory efficient, and rank scalable. The proposed algorithm compares favorably with other solvers for this problem that have appeared recently in the literature.
Likelihood combination and recognition output voting for the decoding of non-native speech with multilingual HMMs

In this paper we report on the combination of multilingual Hidden Markov Models for the recognition of non-native speech. Using a digit recognition task as an example, we ﬁrst demonstrate the beneﬁts of bilingual acoustic models that incorporate training data from both the target language and the speakers’ native language, and then compare two diﬀerent recognizer combination methods, namely voting on recognition output (ROVER) and frame based, time synchronous likelihood combination. Finally, we demonstrate the usefulness of the proposed methods for speakers whose native language is not in the training data
3D facial model reconstruction on mobile devices using cloud

This paper presents a 3D facial model reconstruction from a single frontal face image for mobile devices using cloud. In this approach, we design a cloud to receive frontal facial images to reconstruct a corresponding 3D depth map from clients that can be smartphones, computers or any other Wi-Fi supported handsets through Wi-Fi connection. The depth map and texture are then transferred back to the sending client through the configured Wi-Fi connection. This setting makes applications light-weight, portable and fast-executive to be able to install on limited specification devices. The experimental results show the advantage and accuracy of the designed system.
Constructing Proofs in Symmetric Networks

This paper considers the problem of expressing predicate calculus in connectionist networks that are based on energy minimization. Given a firstorder-logic knowledge base and a bound k, a symmetric network is constructed (like a Boltzman machine or a Hopfield network) that searches for a proof for a given query. If a resolution-based proof of length no longer than k exists, then the global minima of the energy function that is associated with the network represent such proofs. The network that is generated is of size cubic in the bound k and linear in the knowledge size. There are no restrictions on the type of logic formulas that can be represented. The network is inherently fault tolerant and can cope with inconsistency and nonmonotonicity.
TIPsy tour guides: how microtubule plus-end tracking proteins (+TIPs) facilitate axon guidance

The growth cone is a dynamic cytoskeletal vehicle, which drives the end of a developing axon. It serves to interpret and navigate through the complex landscape and guidance cues of the early nervous system. The growth cone’s distinctive cytoskeletal organization offers a fascinating platform to study how extracellular cues can be translated into mechanical outgrowth and turning behaviors. While many studies of cell motility highlight the importance of actin networks in signaling, adhesion, and propulsion, both seminal and emerging works in the field have highlighted a unique and necessary role for microtubules (MTs) in growth cone navigation. Here, we focus on the role of singular pioneer MTs, which extend into the growth cone periphery and are regulated by a diverse family of microtubule plus-end tracking proteins (+TIPs). These +TIPs accumulate at the dynamic ends of MTs, where they are well-positioned to encounter and respond to key signaling events downstream of guidance receptors, catalyzing immediate changes in microtubule stability and actin cross-talk, that facilitate both axonal outgrowth and turning events.
New Algorithms for Adaptive Notch Smoothing

The problem of extraction/elimination of a nonstationary complex sinusoidal signal buried in noise is considered. This problem is usually solved using adaptive notch filtering (ANF) algorithms. It is shown that accuracy of signal estimation can be increased if the results obtained from ANF are further processed using a cascade of appropriately designed filters. The resulting adaptive notch smoothing (ANS) algorithms can be employed in many offline or nearly real-time online applications. Whenever signal frequency varies in a sufficiently smooth manner, the proposed fixed-interval and fixed-lag ANS algorithms, based on a new, quasi-linear model of frequency changes, outperform the existing solutions.
HMGB2 Loss upon Senescence Entry Disrupts Genomic Organization and Induces CTCF Clustering across Cell Types.

Processes like cellular senescence are characterized by complex events giving rise to heterogeneous cell populations. However, the early molecular events driving this cascade remain elusive. We hypothesized that senescence entry is triggered by an early disruption of the cells' three-dimensional (3D) genome organization. To test this, we combined Hi-C, single-cell and population transcriptomics, imaging, and in silico modeling of three distinct cells types entering senescence. Genes involved in DNA conformation maintenance are suppressed upon senescence entry across all cell types. We show that nuclear depletion of the abundant HMGB2 protein occurs early on the path to senescence and coincides with the dramatic spatial clustering of CTCF. Knocking down HMGB2 suffices for senescence-induced CTCF clustering and for loop reshuffling, while ectopically expressing HMGB2 rescues these effects. Our data suggest that HMGB2-mediated genomic reorganization constitutes a primer for the ensuing senescent program.
Evaluation of the Delivery Modes and Their Effects on the Antigenicity Properties of a Synthetic Multivalent Mycobacterial Gene in Mice

An ubiquitin conjugated multivalent mycobacterial gene vacIII (containing seven immunogenic mycobacterial epitopes or genes; esat-6 (P1), esat-6 (P2), phos1 (65-83), phos1 (129-137), phos1 (166-175), hsp 16.3 and mtb 8.4) was developed and packaged in different modes of antigen delivery systems including 1) DNA vaccination (pVaxVacIII), 2) oral vaccine strain Salmonella typhi Ty21a as a delivery vehicle for the DNA vaccine (StV3dvc) and 3) a recombinant S. typhi Ty21a (StV3) expressing the VacIII antigen on its surface using a synthetic version of the ice-nucleation protein (Inp) of Pseudomonas syringae. Immunization of C57BL/6 mice with pVaxVacIII elicited both humoral and cell-mediated responses although the overall effect tended to polar- ize towards the Th1 response (high IFN-γ and low IL-4). StV3dvc and StV3 (both of which were delivered orally) on the other hand triggered an immune response which polarized towards Th2. Thus the bacteria S. typhi Ty21a was able to modulate the immunological properties of the DNA vaccine candidate. In conclusion, the different delivery models altered the antigenicity properties of the synthetic multivalent mycobacterial gene. However, the level of immunity induced by different delivery models may be insufficient for protection against Mycobacterium infection.
Transcriptional Changes Caused by Bisphenol A in Oryzias javanicus, a Fish Species Highly Adaptable to Environmental Salinity

The Javanese medaka, Oryzias javanicus, is a fish highly adaptable to various environmental salinities. Here, we investigated the effects of the environmental pollutant bisphenol A (BPA; an endocrine disrupting chemical) on gene expression levels in this species acclimated to different salinities. Using cDNA microarrays, we detected the induction of differential expression of genes by BPA, and compared the transcriptional changes caused by chemical exposure at different salinities. There were marked transcriptional changes induced by BPA between treatments. While 533 genes were induced by a factor of more than two when O. javanicus was exposed to BPA in seawater, only 215 genes were induced in freshwater. Among those genes, only 78 were shared and changed significantly their expression in both seawater and freshwater. Those genes were mainly involved in cellular processes and signaling pathway. We then categorized by functional group genes specifically induced by BPA exposure in seawater or freshwater. Gene expression changes were further confirmed in O. javanicus exposed to various concentrations of BPA, using quantitative real-time reverse transcription PCR based on primer sets for 28 selected genes.
Annotating a large corpus with anaphoric links

This paper presents a one million word French corpus annotated with anaphoric links. The anaphoric expressions selected are mainly grammatical discourse phenomena for which a reliable annotation could be provided. The annotation scheme, defined in XML, encodes the orientation of the anaphoric relation by using a specific element for relating the anaphoric expression to its antecedent(s). A set of five semantic relations is used to type the anaphoric relation. As a rule, linguistic expressions selected are phrases, but the annotation scheme uses specific elements to deal with descriptive anaphors which occur in nominal ellipses and demonstrative anaphors. Special cases such as multiple antecedents, discontinuous elements or ambiguity are discussed.
Estimation of the SOC and the SOH of li-ion batteries, by combining impedance measurements with the fuzzy logic inference

This paper describes experimental results aiming at analyzing lithiumion batteries performances with aging, for different state of charge and temperatures. The results are provided from electrochemical impedance spectroscopy (EIS) measurements on new and aged cells. A climatic test chamber is used during experiments to simulate the conditions of the temperature. Experimental data are plotted over a broad spectrum of frequencies on Nyquist diagrams. We will also inspect the impact of the presence of a DC current during the EIS measurement. Finally, obtained results will be processed in a way to be used in a fuzzy logic system (FLS), to assess either the state of charge (SOC) or the state of health (SOH) of cells.
Modulation of myosin A expression by a newly established tetracycline repressor-based inducible system in Toxoplasma gondii.

We have developed a control system for regulating gene activation in Toxoplasma gondii. The elements of this system are derived from the Escherichia coli tetracycline resistance operon, which has been widely used to tightly control gene expression in eukaryotes. The tetracycline repressor (tetR) interferes with transcription initiation while the chimeric transactivator, composed of the tetR fused to the activating domain of VP16 transcriptional factor, allows tet-dependent transcription. Accordingly, tetracycline derivatives such as anhydrotetracycline, which we found to be well tolerated by T.gondii, can serve as effector molecules, allowing control of gene expression in a reversible manner. As a prerequisite to functionally express the tetR in T.gondii, we used a synthetic gene with change of codon frequency. Whereas no activation of transcription was achieved using the synthetic tetracycline-controlled transactivator, tTA2(s), the TetR(s )modulates parasite transcription over a range of approximately 15-fold as measured for several reporter genes. We show here that the tetR-dependent induction of the T.gondii myosin A transgene expression drastically down-regulates the level of endogenous MyoA. This myosin is under the control of a tight feedback mechanism, which occurs at the protein level.
Optimal object-based scalability for video content adaptation according to the usage environment

Efficient video content adaptation requires techniques for content analysis and the development of appropriate mechanisms for content scaling in terms of the network properties, terminal devices characteristics and users' preferences. In this paper, we propose an adaptive optimal rate distortion scheme able to allocate different priorities for each video object with respect to the users' needs, network platform capabilities and terminal characteristics without violating the target bit rate of the sequence. In this paper, we consider that video objects have been already detected by a content segmentation algorithm. The proposed scheme minimizes the effects of objects on non-interest compared to objects of interest.
Stochastic strategies for a swarm robotic assembly system

We present a decentralized, scalable approach to assembling a group of heterogeneous parts into different products using a swarm of robots. While the assembly plans are predetermined, the exact sequence of assembly of parts and the allocation of subassembly tasks to robots are determined by the interactions between robots in a decentralized fashion in real time. Our approach is based on developing a continuous abstraction of the system derived from models of chemical reactions and formulating the strategy as a problem of selecting rates of assembly and disassembly. These rates are mapped onto probabilities that determine stochastic control policies for individual robots, which then produce the desired aggregate behavior. This top-down approach to determining robot controllers also allows us to optimize the rates at the abstract level to achieve fast convergence to the specified target numbers of products. Because the method incorporates programs for assembly and disassembly, changes in demand can lead to reconfiguration in a seamless fashion. We illustrate the methodology using a physics-based simulator with examples involving 15 robots and two types of final products.
Humanoid motion planning for dynamic tasks

This paper addresses an integrated humanoid motion planning scheme including both advanced algorithmic motion planning technique and dynamic pattern generator so that the humanoid robot achieve tasks including dynamic motions. A two-stage approach is proposed for this goal. First, geometric and kinematic motion planner first computes collision-free paths for the humanoid robot. Then the dynamic pattern generator provides dynamically feasible humanoid motion including both locomotion and task execution such as object transportation or manipulation. If the generated dynamic motion causes collision due to dynamic movements, the planner go back to the planning stage to remove the collision by path reshaping. This iterative planning scheme enables robust planning against variation of task dynamics. Simulation results are provided to validate the proposed planning method
Interactive Subspace Clustering for Mining High-Dimensional Spatial Patterns

The unprecedented large size and high dimensionality of existing geographic datasets make complex patterns that potentially lurk in the data hard to find. Spatial data analysis capabilities currently available have not kept up with the need for deriving the full potential of these data. “Traditional spatial analytical techniques cannot easily discover new and unexpected patterns, trends and relationships that can be hidden deep within very large and diverse geographic datasets”(Miller and Han 2000). We are facing a datarich but knowledge-poor era. To bridge this gap, spatial data mining and knowledge discovery has been gaining momentum. Clustering is one of the most important tasks in data mining and knowledge discovery literature (Fayyad, Piatetsky-Shapiro et al. 1996). Spatial clustering has also long been used as an important process in geographic analysis (Openshaw, Charlton et al. 1987; Ester, Kriegel et al. 1996; Kang, Kim et al. 1997; Wang, Yang et al. 1997; Estivill-Castro and Lee 2000; Zhang and Murayama 2000; Harel and Koren 2001).
The Golem Group/University of California at Los Angeles autonomous ground vehicle in the DARPA grand challenge

This paper presents the Golem Group/University of California at Los Angeles entry to the 2005 DARPA Grand Challenge competition. We describe the main design principles behind the development of Golem 2, the race vehicle. The subsystems devoted to obstacle detection, avoidance, and state estimation are discussed in more detail. An overview of vehicle performance in the field is provided, including successes together with an analysis of the reasons leading to failures. © 2006 Wiley Periodicals, Inc.
High Speed Visual Saliency Computation on GPU

Visual saliency analysis provides a power tool for many applications. In this paper, we propose a practical and high performance GPU-based visual saliency computational model. Several novel ideas are introduced for saliency computations, such as the feature extraction as signed difference values in the lab color space and the feature fusion based on the information theory. For our implementation on the GPU, besides the programmable shaders we fully exploit other computational resources on the GPU to accelerate the computations. Our experimental results demonstrate the effectiveness of our saliency maps and indicate an order of magnitude speedup over the CPU-based implementation.