Miracle-dz/UniFAR-FTUs huggingface dataset:
Monetary Policy Models

I have written several papers for BPEA (2002; 1996; 1982) looking at the relation of multiple equation quantitative economic models to the process of monetary policy making. When the first of these papers was written, the impact of the rational expectations critique in undermining academic interest in quantitative modeling for monetary policy was apparent. Many, maybe most, economists took the Lucas critique to imply that the month-to-month business of choosing monetary policy actions in the light of current information was trivial or irrelevant. Economists were thought to have nothing useful to say about it. Economists were supposed to contemplate only the choice of policy rules, which were modeled as functions mapping the state of the economy into policy actions.
Parametricity and dependent types

Reynolds' abstraction theorem shows how a typing judgement in System F can be translated into a relational statement (in second order predicate logic) about inhabitants of the type. We (in second order predicate logic) about inhabitants of the type. We obtain a similar result for a single lambda calculus (a pure type system), in which terms, types and their relations are expressed. Working within a single system dispenses with the need for an interpretation layer, allowing for an unusually simple presentation. While the unification puts some constraints on the type system (which we spell out), the result applies to many interesting cases, including dependently-typed ones.
MicroRNA Expression Ratio Is Predictive of Head and Neck Squamous Cell Carcinoma

Purpose: The involvement of microRNAs in cancer and their potential as biomarkers of diagnosis and prognosis are becoming increasingly appreciated. We sought to identify microRNAs altered in head and neck squamous cell carcinoma (HNSCC) and to determine whether microRNA expression is predictive of disease. Experimental Design: RNA isolated from fresh-frozen primary tumors, fresh-frozen nondiseased head and neck epithelial tissues, and HNSCC cell lines was profiled for the expression of 662 microRNAs by microarray. The microRNAs that were both differentially expressed on the array and by quantitative reverse transcription-PCR were subsequently validated by quantitative reverse transcription-PCR using a total of 99 HNSCC samples and 14 normal epithelia. Results: A marked difference in microRNA expression pattern was observed between tumors and cell lines. Eighteen microRNAs were significantly altered in their expression between normal tissues and tumors. Four of these microRNAs were validated in the larger sample series, and each showed significant differential expression (P < 0.0001). Furthermore, an expression ratio of miR-221:miR-375 showed a high sensitivity (0.92) and specificity (0.93) for disease prediction. Conclusions: These data suggest that cultured tumor cell lines are inappropriate for microRNA biomarker identification and that the pattern of microRNA expression in primary head and neck tissues is reflective of disease status, with certain microRNAs exhibiting strong predictive potential. These results indicate that miR-221 and miR-375 should be evaluated further as diagnostic biomarkers because they may hold utility in defining broadly responsive prevention and treatment strategies for HNSCC.
Optimal Factorization in Lattice-Reduction-Aided and Integer-Forcing Linear Equalization

Lattice-reduction-aided (LRA) equalization is a very interesting multi-user equalization technique as it enables a lowcomplexity full-diversity detection. To this end, the multipleinput/multiple-output channel is factorized into a reduced variant and a unimodular integer matrix. Inspired by the closely related finite-field processing strategy of integer-forcing (IF) equalization, this factorization task has recently been relaxed to nonunimodular integer matrices. In this paper, the claim of a significant performance gain induced by the IF philosophy is revisited. For that purpose, lattice-basis-reduction approaches are reviewed; the optimal one with respect to channel equalization is identified. A fair comparison between unimodular LRA and IF strategy is given, complemented by detailed numerical results.
Reliable and energy-efficient multicast based on network coding for wireless sensor networks

An energy-efficient retransmission scheme is presented based on network coding technique for wireless sensor networks. This new scheme enables an intermediate node to first recover the loss packets requested by the nodes having better channel condition. In this way, these nodes do not need to keep their radio on during the whole retransmission process and thus get to resulting in consuming less energy. Simulation results show that the proposed approach can reduce energy consumption, comparing with the existing network coding based rescue schemes.
Improve performance of collaborative filtering systems using backward feature selection

In E-Commerce, recommender systems recommend to users those items that may they like and have not been seen by them. One of the most popular techniques in recommender systems is collaborative filtering. For the current user, collaborative filtering technique uses the rating information of similar users to recommends new items. Therefore, clustering methods can be performed to divide users into k clusters as users of each cluster are similar. In this paper, k-means clustering method is used to cluster users based on user-item matrix. But, the sparsity of user-item matrix leads to produce incorrect similarity values between different users. To decrease this undesirable effect, removing some of the items with much more zero rates than the other items, can be done before clustering method. By eliminating these features, k-means clustering produces clusters which include more similar users. In this paper, backward feature selection is used to remove the irrelevant features of user-item matrix. Simulation results on MovieLens dataset indicate that this method improves the performance of the recommender system.
Inkjet Printed, Self Powered, Wireless Sensors for Environmental, Gas, and Authentication-Based Sensing

In this paper, inkjet-printed flexible sensors fabricated on paper substrates are introduced as a system-level solution for ultra-low-cost mass production of UHF Radio Frequency Identification (RFID) Tags and wireless sensor nodes in a “green” approach that could be easily extended to other microwave and wireless applications. The authors briefly touch up the state-of-the-art area of fully integrated wireless sensor modules on paper and show several active and power scavenging platforms to power on wireless sensors that could potentially set the foundation for the truly convergent wireless sensor ad hoc networks of the future.
A simple coded ARQ for satellite broadcasting

We introduce a novel packet retransmission technique which improves the efficiency of automatic retransmission query (ARQ) protocols in the context of satellite broadcast/multicast systems. The proposed coded ARQ technique, similarly to fountain coding, performs transmission of redundant packets, which are made by linear combinations of the packets composing the source block. Differently from fountain codes, the packets for the linear combinations are selected on the basis of the retransmission requests coming from the user terminals. The selection is performed in a way that, at the terminals, the source packets can be recovered iteratively by means of simple back-substitutions. This work aims at providing a simple and efficient alternative to reliable multicast protocols based on erasure correction coding techniques.
Extending the JADE Framework for Semantic Peer-To-Peer Service Based Applications

One of the main challenges of multi-agent systems is to become the main means to support legacy systems interoperability and to make the realization of scalable distributed systems easy. In the last years, however, two technologies, peer-to-peer and service-oriented, have made an impressive progress and seem to have good chances of competing with multi-agent systems for the realization of scalable and interoperable systems. Conversely, neither of these two technologies is able to provide by themselves the autonomy and social and proactive capabilities of agents and thus the development of flexible adaptive distributed systems may be difficult. This chapter shows how JADE, one of the most known and used software framework for the development of multi-agent systems, has been extended with these technologies both to support the realization of multi-agent systems and to facilitate the interoperability with peer-to-peer and service-oriented systems.
A new G protein‐coupled receptor from a primitive metazoan shows homology with vertebrate aminergic receptors and displays constitutive activity in mammalian cells

Biogenic amine receptors mediate wide‐ranging hormonal and modulatory functions in vertebrates, but are largely unknown in primitive invertebrates. In a representative of the most basal multicellular animals possessing a nervous system, the cnidarian Renilla koellikeri, aminergic‐like receptors were previously characterized pharmacologically and found to engender control of the animal's bioluminescent and peristaltic reactions. Using degenerate oligonucleotides in a RT‐PCR strategy, we obtained a full‐length cDNA encoding a polypeptide with typical G protein‐coupled receptor (GPCR) characteristics and which displayed a significant degree of sequence similarity (up to 45%) to biogenic amine receptors, particularly dopamine and adrenergic receptors. The new receptor, named Ren1, did not resemble any one specific type of amine GPCR and thus could not be identified on the basis of sequence. Ren1 was expressed transiently and stably in cultured mammalian cells, as demonstrated by immunocytochemistry and western blotting. Functional analysis of transfected HEK293, LTK‐ and COS‐7 cells, based on both cAMP and Ca2+ signalling assays, revealed that Ren1 was not activated by any of the known biogenic amines tested and several related metabolites. The results indicated, however, that cells stably expressing Ren1 contained, on average, an 11‐fold higher level of cAMP than the controls, in the absence of agonist stimulation. The high basal cAMP levels were shown to be specific for Ren1 and to vary proportionally with the level of Ren1 expressed in the transfected cells. Taken together, the data suggested that Ren1 was expressed as a constitutively active receptor. Its identification provides a basis for examination of the early evolutionary emergence of GPCRs and their functional properties.
Shape and Texture Generation by Neural Network Creation Paradigm

Creation by Refinement (CBR) is a neural network 'creativity' paradigm which can create novel examples of a learned class of patterns. In theory, CBR solves the allalysis-resynthesis problem: CBR can generate synthetic forms which mimic arbitrary prototypes. In practice, this universality is tempered by the current absence of known bounds on the network training time and size required to learn particular problems. Nevertheless there is some consensus that neural networks may provide natural (and thus relatively efficient) representations of phenomena such as texture which are characterized by a 'fuzzy' structure. We consider the potential application of CBR to the problem of generating irregular shapes and textures , and show some preliminary experiments in this direction .
Classification of Approaches and Challenges of Frequent Subgraphs Mining in Biological Networks

Understanding the structure and dynamics of biological networks is one of the important challenges in system biology. In addition, increasing amount of experimental data in biological networks necessitate the use of efficient methods to analyze these huge amounts of data. Such methods require to recognize common patterns to analyze data. As biological networks can be modeled by graphs, the problem of common patterns recognition is equivalent with frequent sub graph mining in a set of graphs. In this paper, at first the challenges of frequent subgrpahs mining in biological networks are introduced and the existing approaches are classified for each challenge. then the algorithms are analyzed on the basis of the type of the approach they apply for each of the challenges.
Multithreaded Stochastic PDES for Reactions and Diffusions in Neurons

Cells exhibit stochastic behavior when the number of molecules is small. Hence a stochastic reaction-diffusion simulator capable of working at scale can provide a more accurate view of molecular dynamics within the cell. This article describes a parallel discrete event simulator, Neuron Time Warp-Multi Thread (NTW-MT), developed for the simulation of reaction diffusion models of neurons. To the best of our knowledge, this is the first parallel discrete event simulator oriented toward stochastic simulation of chemical reactions in a neuron. The simulator was developed as part of the NEURON project. NTW-MT is optimistic and thread based, which attempts to capitalize on multicore architectures used in high performance machines. It makes use of a multilevel queue for the pending event set and a single rollback message in place of individual antimessages to disperse contention and decrease the overhead of processing rollbacks. Global Virtual Time is computed asynchronously both within and among processes to get rid of the overhead for synchronizing threads. Memory usage is managed in order to avoid locking and unlocking when allocating and deallocating memory and to maximize cache locality. We verified our simulator on a calcium buffer model. We examined its performance on a calcium wave model, comparing it to the performance of a process based optimistic simulator and a threaded simulator which uses a single priority queue for each thread. Our multithreaded simulator is shown to achieve superior performance to these simulators. Finally, we demonstrated the scalability of our simulator on a larger Calcium-Induced Calcium Release (CICR) model and a more detailed CICR model.
Spherical parabolic blends for robot workspace trajectories

We present a new approach to generate workspace trajectories for multiple waypoints. To satisfy workspace constraints with constant-axis rotation, this method splines a given sequence of orientations, maintaining constant-axis within each segment. This improves on other approaches which are point-to-point or take indirect paths. We derive this approach by blending subsequent spherical linear interpolation phases, computing interpolation parameters so that rotational velocity is continuous. We show this method first on simulated manipulator and then perform a physical screwing task on a Schunk LWA4 robot arm. Finally, we provide permissively licensed software which implements this trajectory generation and tracking.
KELI: a key-value-with-links in-memory store for realtime applications

The emergence of advanced network technologies and decreasing DRAM costs have provided great opportunities for data centers to deploy high performance key-value in-memory stores for real-time applications. Although key-value model helps in-memory stores to simplify their query processing and data management mechanisms, its simplicity have applications to generate multiple item lookups to perform simple requests such as constructing HTML files. Such lookups are often executed sequentially and seriously affect the overall performance. In this paper, we introduce KELI, a novel in-memory key-value store that employs Key-value-with-Links, a simple but quite efficient data model, to solve this issue. On the top of the key-value model, KELI establishes links between items so instead of invoking expensive item lookups, it could simply follow those links to retrieve needed data. KELI also uses RDMA Read to implement link chasing to minimize searching overhead. Some experiments have been conducted to examine the performance of KELI. Their results indicate that KELI runs three times faster than Redis for data lookups. Furthermore, KELI runs seven times faster than Redis when handling real workloads generated by a practical application.
Accelerated cell divisions drive the outgrowth of the regenerating spinal cord in axolotls

Axolotls are unique in their ability to regenerate the spinal cord. However, the mechanisms that underlie this phenomenon remain poorly understood. Previously, we showed that resting stem cells in the axolotl spinal cord revert to a molecular state resembling embryonic neuroepithelial cells and functionally acquire rapid proliferative divisions during regeneration. Here we refine in space and time this increase in cell proliferation during regeneration, and identify a dynamic high-proliferation zone in the regenerating spinal cord. By tracking sparsely-labeled cells, we quantify cell influx into the regenerate. Taking a mathematical modelling approach, we integrate these quantitative biological datasets across cellular and tissue level to provide a mechanistic and quantitative understanding of regenerative spinal cord outgrowth. We find that the acceleration of the cell cycle is necessary and sufficient to drive the outgrowth of the regenerating spinal cord in axolotls.
MUSCLE ACTIVATION STRATEGIES DURING AN UNANTICIPATED STOPPING TASK

The purpose of this study was to determine how time constraints during stopping in sports affect lower limb muscle activation strategies in both the termination and stability steps. Rapid deceleration is common in both recreational and professional sport and has previously been associated with lower limb injury. To investigate control differences between anticipated and unanticipated stopping, total muscle activation and directed cocontraction ratios were used to analyse lower limb muscle activation. Increased plantar flexor and knee flexor activity was found during the pre-contact and weight acceptance phases of unanticipated stopping compared with anticipated stopping. These results support the hypothesis that lower limb muscle activity is altered when the task is unanticipated, which may place athletes at higher risk of lower limb injury in sport.
β-Site Amyloid Precursor Protein (APP)-cleaving Enzyme 1 (BACE1)-deficient Mice Exhibit a Close Homolog of L1 (CHL1) Loss-of-function Phenotype Involving Axon Guidance Defects*♦

Background: Little is known about BACE1 functions. Results: BACE1−/− mice have axon guidance defects similar to those of CHL1−/− mice; CHL1 undergoes BACE1-dependent processing in vivo; CHL1 and BACE1 co-localize in terminals and growth cones. Conclusion: BACE1 deficiency produces a CHL1 loss-of-function phenotype. Significance: BACE1 inhibition may cause axon guidance defects, adding a note of caution to BACE1 inhibitor drug development. BACE1 is the β-secretase enzyme that initiates production of the β-amyloid peptide involved in Alzheimer disease. However, little is known about the functions of BACE1. BACE1-deficient mice exhibit mild but complex neurological phenotypes suggesting therapeutic BACE1 inhibition may not be completely free of mechanism-based side effects. Recently, we have reported that BACE1 null mice have axon guidance defects in olfactory sensory neuron projections to glomeruli in the olfactory bulb. Here, we show that BACE1 deficiency also causes an axon guidance defect in the hippocampus, a shortened and disorganized infrapyramidal bundle of the mossy fiber projection from the dentate gyrus to CA3. Although we observed that a classical axon guidance molecule, EphA4, was cleaved by BACE1 when co-expressed with BACE1 in HEK293 cells, we could find no evidence of BACE1 processing of EphA4 in the brain. Remarkably, we discovered that the axon guidance defects of BACE1−/− mice were strikingly similar to those of mice deficient in a recently identified BACE1 substrate, the neural cell adhesion molecule close homolog of L1 (CHL1) that is involved in neurite outgrowth. CHL1 undergoes BACE1-dependent processing in BACE1+/+, but not BACE1−/−, hippocampus, and olfactory bulb, indicating that CHL1 is a BACE1 substrate in vivo. Finally, BACE1 and CHL1 co-localize in the terminals of hippocampal mossy fibers, olfactory sensory neuron axons, and growth cones of primary hippocampal neurons. We conclude that BACE1−/− axon guidance defects are likely the result of abrogated BACE1 processing of CHL1 and that BACE1 deficiency produces a CHL1 loss-of-function phenotype. Our results imply the possibility that axon mis-targeting may occur in adult neurogenic and/or regenerating neurons as a result of chronic BACE1 inhibition and add a note of caution to BACE1 inhibitor development.
Pose estimation in industrial machine vision systems under sensing dynamics: A statistical learning approach

This paper deals with the problem of pose estimation (i.e., estimating position and orientation of an moving target) for real-time visual servoing, where the vision hardware is assumed to have severely limited measurement capability. In other words, we aim to compensate the slow sensor dynamics in industrial machine vision systems. The common approach is to predict the present target motion by propagating the delayed estimates with the target dynamics. Such method is sometimes problematic since the target motion characteristics (i.e., target dynamics) may change from one visual servoing task to another. Therefore, this paper presents a method which is able to estimate the target pose as well as learn the target dynamics. We apply the Expectation-Maximization algorithm to simultaneously solve the pose estimation problem and the target dynamics modeling problem. Several techniques including the extended Kalman filter/smoother, the block coordinate descent method, and the convex optimization method are utilized to address this problem. The effectiveness of the proposed algorithm is demonstrated experimentally on a 6-DOF industrial robot.
Phygital Map: Accessing Digital Multimedia from Physical Map

We present an augmented map interface called Phygital (physical, digital) Map that enables users to access digital multimedia stored in various off-the-shelf devices from physically printed maps, such as wall-mounted maps and atlas books. While the rapidly expanding variety of multimedia devices has been facilitated capturing the real world events through various digital media, the interface for playback of these digital media is not well integrated into the physical world. Phygital map addresses this difficulty by providing an interface that is capable of triggering and controlling multimedia devices and the network data sources, based on interactions on a printed map surface. Key features of Phygital map are use of off-the-shelf devices for both media manipulations and the interface to make applications pervasive, an adoption of inexpensive positioning devices as tangible artifacts on maps, and an extensible infrastructure that can cope with varying devices built on growing number of middleware platforms. In this paper, we discuss the design and implementation of Phygital map, and the ease of using it for multimedia exploration applications.