Miracle-dz/UniFAR-FTUs huggingface dataset:
Species-specific pharmacology of maximakinin, an amphibian homologue of bradykinin: putative prodrug activity at the human B2 receptor and peptidase resistance in rats

Maximakinin (MK), an amphibian peptide possessing the C-terminal sequence of bradykinin (BK), is a BK B2 receptor (B2R) agonist eliciting prolonged signaling. We reinvestigated this 19-mer for species-specific pharmacologic profile, in vivo confirmation of resistance to inactivation by angiotensin converting enzyme (ACE), value as a module for the design of fusion proteins that bind to the B2R in mammalian species and potential activity as a histamine releaser. Competition of the binding of [3H]BK to recombinant human myc-B2Rs in cells that express these receptors revealed that MK possessed a tenuous fraction (<0.1%) of the affinity of BK, despite being only ∼20-fold less potent than BK in a contractility assay based on the human isolated umbilical vein. These findings are reconciled by the generation of C-terminal fragments, like Lys-Gly-Pro-BK and Gly-Pro-BK, when the latent MK is incubated with human venous tissue (LC-MS), supporting activation via hydrolysis upstream of the BK sequence. At the rat recombinant myc-B2R, MK had a lesser affinity than that of BK, but with a narrower margin (6.2-fold, radioligand binding competition). Accordingly, MK (10 nM) stimulated calcium transients in cells that expressed the rat receptors, but not the human B2R. Recombinant MRGPRX2, a receptor that mediates cationic peptide-induced mast cell secretion, minimally responded by increased [Ca+2]i to MK at 10 µM. Enhanced green fluorescent protein fused to MK (EGFP-MK) labeled cells that expressed rat, but not human B2Rs. Intravenous MK induced dose-dependent hypotensive, vasodilator and tachycardic responses in anesthetized rats and the effects were antagonized by pretreatment with icatibant but not modified by pyrilamine or enalaprilat. Strong species-specific responses to the toxin-derived peptide MK and its prodrug status in the isolated human vein were evidenced. Accordingly, MK in the EGFP-MK fusion protein is a pharmacophore module that confers affinity for the rat B2R, but not for the human form of the B2R. MK is unlikely to be an efficient mast cell activator, but its resistance to inactivation by ACE was confirmed in vivo.
Prereaders’ eye movements during shared storybook reading are language-mediated but not predictive

ABSTRACT When viewing a visual scene, eye movements are often language-mediated: people look at objects as those objects are named. Eye movements can even reflect predictive language processing, moving to an object before it is named. Children are also capable of making language-mediated eye movements, even predictive ones, and prediction may be involved in language learning. The present study explored whether eye movements are language-mediated in a more naturalistic task – shared storybook reading. Research has shown that children fixate illustrations during shared storybook reading, ignoring text. The present study used high-precision eye-tracking to replicate this finding. Further, prereader participants showed increased likelihood of fixating relevant storybook illustrations as words were read aloud, indicating that their eye movements were language mediated like the adult participants. Language-mediated eye movements to illustrations were reactive, not predictive, in both participant groups.
Development of an intelligent modeling system for detailed design of steel Industrial plant structures

The primary program principles and techniques of the development of integrated CAD software for detailed design of steel Industrial plant structures, including the frame work, hierarchic data structure, 3D modeling algorithm and automatic generation of 2D drawings and CNC data, are introduced. An intelligent modeling system for detailed design is developed. In the modeling system, a 3D solid model can be easily constructed. Moreover, structure properties and design requirements are integrated into the intelligent model. Therefore, details of the structure can be designed automatically and edited visually according to design knowledge, and 2D drawings and CNC data can be generated automatically.
Dynamic synthesis for relaxed memory models

Modern architectures implement relaxed memory models which may reorder memory operations or execute them non-atomically. Special instructions called memory fences are provided, allowing control of this behavior. To implement a concurrent algorithm for a modern architecture, the programmer is forced to manually reason about subtle relaxed behaviors and figure out ways to control these behaviors by adding fences to the program. Not only is this process time consuming and error-prone, but it has to be repeated every time the implementation is ported to a different architecture. In this paper, we present the first scalable framework for handling real-world concurrent algorithms running on relaxed architectures. Given a concurrent C program, a safety specification, and a description of the memory model, our framework tests the program on the memory model to expose violations of the specification, and synthesizes a set of necessary ordering constraints that prevent these violations. The ordering constraints are then realized as additional fences in the program. We implemented our approach in a tool called DFence based on LLVM and used it to infer fences in a number of concurrent algorithms. Using DFence, we perform the first in-depth study of the interaction between fences in real-world concurrent C programs, correctness criteria such as sequential consistency and linearizability, and memory models such as TSO and PSO, yielding many interesting observations. We believe that this is the first tool that can handle programs at the scale and complexity of a lock-free memory allocator.
Leveraging predefined huffman dictionaries for high compression rate and ratio

The explosion of data, both in motion and in rest, along with the popularity of cloud computing, have resulted in the need for better in-line compression solutions. Current Huffman coding modes are optimal for a single metric: compression ratio (quality) or rate (performance). The ratio-focused mode, for example, further compresses the data by 15% as compared to the rate-focused mode, but takes 20% longer to execute. In this paper, we show how to balance the tradeoff between compression ratio and rate, without modifying existing standards and legacy decompression implementations. We present two Huffman encoding heuristics that achieve close-to-optimal compression rate and ratio (within 2%). Our proposed heuristics are practical - the first is better suited for hardware while the second for software implementations. We believe that such in-line compression heuristics can help enable the continued advancement of cloud computing and storage.
Active generators power dispatching control in smart grid

The main focus of this research work is implementing active and reactive power dispatching strategies for active generators in micro-grids. An active generator, which is a distributed generator, includes Voltage Source convertor (VSC) and their control systems. Moreover, the active generators have the power flow management capabilities based on frequency, voltage droop characteristics. The power for active generators can be extracted from renewable sources and proper integrated storages. In this research, grid integration methods and inverter control methods for the renewable resources have been studied. First task of the study was development of a VSC system. Active and reactive power control systems for power dispatching have been implemented in the VSC and so that it can work as an active generator. The power dispatching policy of the active generator is based on combination of droop and PID control method.
Influenza induces IL-8 and GM-CSF secretion by human alveolar epithelial cells through HGF/c-Met and TGF-α/EGFR signaling

The most severe complication of influenza is viral pneumonia, which can lead to the acute respiratory distress syndrome. Alveolar epithelial cells (AECs) are the first cells that influenza virus encounters upon entering the alveolus. Infected epithelial cells produce cytokines that attract and activate neutrophils and macrophages, which in turn induce damage to the epithelial-endothelial barrier. Hepatocyte growth factor (HGF)/c-Met and transforming growth factor-α (TGF-α)/epidermal growth factor receptor (EGFR) are well known to regulate repair of damaged alveolar epithelium by stimulating cell migration and proliferation. Recently, TGF-α/EGFR signaling has also been shown to regulate innate immune responses in bronchial epithelial cells. However, little is known about whether HGF/c-Met signaling alters the innate immune responses and whether the innate immune responses in AECs are regulated by HGF/c-Met and TGF-α/EGFR. We hypothesized that HGF/c-Met and TGF-α/EGFR would regulate innate immune responses to influenza A virus infection in human AECs. We found that recombinant human HGF (rhHGF) and rhTGF-α stimulated primary human AECs to secrete IL-8 and granulocyte macrophage colony-stimulating factor (GM-CSF) strongly and IL-6 and monocyte chemotactic protein 1 moderately. Influenza infection stimulated the secretion of IL-8 and GM-CSF by AECs plated on rat-tail collagen through EGFR activation likely by TGF-α released from AECs and through c-Met activated by HGF secreted from lung fibroblasts. HGF secretion by fibroblasts was stimulated by AEC production of prostaglandin E2 during influenza infection. We conclude that HGF/c-Met and TGF-α/EGFR signaling enhances the innate immune responses by human AECs during influenza infections.
Registration and Exploitation of Multi-pass Airborne

High resolution multi-pass, airborne Synthetic Aperture Radar (SAR) imagery is useful for surveillance and remote sensing applications. We present a technique for registering multiple high resolution SAR images, acquired from Unmanned Air Vehicles (UAVs) and other airborne platforms. A global aane transformation derived from the sensor acquisition parameters is used to automatically register the images, followed by a reenement to correct for translational errors. The registered SAR images are used for improving the accuracy of segmentation maps, and estimating heights of objects and target orientation angles.
Specification of epidermal cell fate in plant shoots

Land plants have evolved a single layer of epidermal cells, which are characterized by mostly anticlinal cell division patterns, formation of a waterproof coat called cuticle, and unique cell types such as stomatal guard cells and trichomes. The shoot epidermis plays important roles not only to protect plants from dehydration and pathogens but also to ensure their proper organogenesis and growth control. Extensive molecular genetic studies in Arabidopsis and maize have identified a number of genes that are required for epidermal cell differentiation. However, the mechanism that specifies shoot epidermal cell fate during plant organogenesis remains largely unknown. Particularly, little is known regarding positional information that should restrict epidermal cell fate to the outermost cell layer of the developing organs. Recent studies suggested that certain members of the HD-ZIP class IV homeobox genes are possible master regulators of shoot epidermal cell fate. Here, we summarize the roles of the regulatory genes that are involved in epidermal cell fate specification and discuss the possible mechanisms that limit the expression and/or activity of the master transcriptional regulators to the outermost cell layer in plant shoots.
Continuous Coordination : A New Paradigm to Support Globally Distributed Software Development Projects

English) Along with the rapid globalization of companies, th e globalization of software development has become a reality. Many software projects are no w distributed in diverse sites across the globe. The distance between these sites creates sev eral problems that did not exist for previously collocated teams. Problems with the coor dination of the activities, as well as with the communication between team members, emerge. Man y collaborative software engineering tools that have been used to date, in global softwa re development projects, exhibit a fundamental paradox: they are meant to support the collaborative activity of software development, but cause individuals and groups to wo rk more or less independently from one another. The underlying issue is that existing soft ware engineering tools, such as
Validity of a contact mat and accelerometric system to assess countermovement jump from flight time

ABSTRACT Countermovement jump (CMJ) height is an important parameter in physical performance. This study compared CMJ height measured using ChronoJump contact mat (CJ) and Myotest accelerometer (MT) systems with a force platform (FP). Thirty recreationally active adults (32.1 ± 10.4 years, 75.9 ± 12.0 kg, 173.2 ± 6.3 cm) completed a CMJ protocol where height was simultaneously recorded using the three systems. CJ and MT measures were strongly and significant correlated (r = 0.65, 0.66, respectively; p < 0.05) with FP. CJ-derived measures were not significantly different to FP measures (p > 0.05), yet MT-derived measures were significantly different from those obtained using the FP (p < 0.05). Systematic bias was observed between FP and the CJ and between FP and MT. This study demonstrates the validity of CJ and MT systems for the assessment of CMJ height. Systematic bias and between-device differences in measurement should be considered when interpreting and comparing data from these devices.
Mean-field analysis of data flows in wireless sensor networks

Wireless Sensor Networks (WSNs) are often used for environment monitoring, an application which requires reliable routing of messages from source to sink nodes via multi-hop networks. Prior to installing such WSNs, engineers commonly analyse the network using discrete event simulation (DES). Whilst sophisticated simulators such as Castalia and TOSSIM take into account many low-level features of WSNs, their biggest drawback is the lack of scalability. This inhibits design-time system optimisation for large or complex networks. In this paper, we discuss how Population CTMC (PCTMC) models, used in conjunction with mean-field analysis, can be used to mitigate this problem. To illustrate the potential of PCTMC models in the WSN domain, we present a PCTMC model for a failsafe, dynamic routing protocol, which we implemented in Castalia. We show that the mean-field solution for the model yields good qualitative agreement with corresponding low-level simulations, but at a fraction of the computational cost. In particular we see good agreement for average metrics describing buffer occupancy and data flow behaviour. Moreover, our PCTMC model produces good results when packets are lost due to channel interference, an important consideration for WSNs.
Non-verbal Behaviors Expressivity and Their Representation Pf-star Report 3

Embodied Conversational Agents (ECAs) are a powerful user interface paradigm, aiming to transfer the inherent richness of human-human interaction to human-computer interaction. ECAs are virtual embodied representations of humans that communicate multimodally with the user (or other agents) through voice, facial expression, gaze, gesture, and body movement. Effectiveness of an agent is dependent on her ability to suspend the user’s disbelief during an interaction. Our work aims at creating one ECA system called Greta, that would be able to interact with the user not only communicating information in a general deterministic way but exhibiting a consistent behavior with her personality and with contextual environment factors. In fact human individuals differ in their reasoning, their set of beliefs, goals, their emotive states, and also their way of expressing such information through the execution of specific behaviors. The behavior of one person depends not only on factors defining her individuality (such as her culture, her social and professional role, her personality and her experience), but also on a set of contextual (such as her interlocutor, the social conversation setting), and dynamic variables (belief, goal, emotion). We call these types of factors ‘influences’ in the sense that they affect the behaviors to be displayed. Influences may act at different levels: they may act on what to say and when as well on how to say it and to express it. Until now most ECA systems have concentrated solely on defining computational models of behavior selection – which behaviors to choose for a given communicative act. To increase believability and life-likeness of an agent, she has to express emotion and exhibit personality in a consistent manner [24]. In this document we will first briefly describe what happens in real life, how people differ in their behavior depending on different personality and situation (section 2). To do that we will introduce our taxonomy of behavioral influences in section 3. A general description of our system’s architecture will be presented in 4. After that we will provide an explanation of the two main components of the system, the Expressivity Specification Module and theAnimation Engine.
A coloured Petri net trust model

Public-key infrastructures are a prerequisite for security in distributed systems and for reliable electronic commerce. It is their goal to provide the authenticity of public keys. Formal models for public-key infrastructures (trust models) contribute decisively to a deeper understanding of the desirable design principles of these infrastructures. The trust model of the presented paper is based on the modelling technique of coloured Petri nets. These are a special class of high-level Petri nets with an intuitively appealing graphical representation and a few powerful primitives. Elaborate and well tested software is available.
Numerical valuation of high dimensional multivariate European securities

We consider the problem of pricing a contingent claim whose payoff depends on several sources of uncertainty. Using classical assumptions from the Arbitrage Pricing Theory, the theoretical price can be computed as the discounted expected value of future cash flows under the modified risk-neutral information process. Although analytical solutions have been developed elsewhere for a few particular option pricing problems, computing the arbitrage prices of securities under several sources of uncertainty is still an open problem in many instances. In this paper, we present efficient numerical techniques based upon Monte Carlo simulation for pricing European contingent claims depending on an arbitrary number of risk sources. We introduce in particular the method of quadratic resampling (QR), a new powerful error reduction technique for Monte Carlo simulation. Quadratic resampling can be efficiently combined with classical variance reduction methods such as importance sampling. Our numerical experiments show that the method is practical for pricing claims depending on up to one hundred underlying assets.
On Understanding How to Introduce an Innovation to an Open Source Project

We propose to research the introduction of Software Engineering inventions into Open Source projects (1) to help researchers with creating opportunities for evaluating their tools, methods and process designs in real-life settings, and (2) to help Open Source projects with improving their processes based on state-of-the-art knowledge. Such research will go beyond diffusion and dissemination of inventions to active introduction, and thus increase the chances of adoption. We will discuss the research approach, our preliminary insights, limitations of the approach, and why researchers interested in evaluating their own inventions should be interested in this research.
Blind channel estimation and interference management in MIMO-OFDM uplink communication

This paper addresses two majors problems in today's wireless network using MIMO-OFDM. In fact, the performances of such a network depend on the interference management and on the equalization. These two problems are closely linked to channel estimation algorithms. In this paper, we propose a resource sharing scenario combined with a blind channel estimation algorithm based on fourth order statistics of the received signal. The proposed scheme is compared to the existing T/OFDM scenario and simulation results show its outperformance.
Kernel methods in orthogonalization of multi-and hypervariate data

A kernel version of maximum autocorrelation factor (MAF) analysis is described very briefly, and applied to change detection in remotely sensed hyperspectral image (HyMap) data. The kernel version is based on a dual formulation also termed Q-mode analysis in which the data enter into the analysis via inner products in the Gram matrix only. In the kernel version the inner products are replaced by inner products between nonlinear mappings into higher dimensional feature space of the original data. Via kernel substitution also known as the kernel trick these inner products between the mappings are in turn replaced by a kernel function and all quantities needed in the analysis are expressed in terms of this kernel function. This means that we need not know the nonlinear mappings explicitly. Kernel PCA and MAF analyses handle nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via the kernel function and then performing a linear analysis in that space. An example shows the successful application of kernel MAF analysis to change detection in HyMap data covering a small agricultural area near Lake Waging-Taching, Bavaria, Germany.
A 2D Discrete Wavelet Transform Based 7-State Hidden Markov Model for Efficient Face Recognition

A novel Discrete Wavelet Transform (DWT) based on 7-States of Hidden Markov Model (HMM) for Face Recognition (FR) is proposed in this paper. To improve the accuracy of HMM based face recognition algorithm, DWT is used to replace Discrete Cosine Transform (DCT) for observation sequence vectors extraction. Extensive experiments have been conducted in our database and the FERET database shows that the proposed method can improve the accuracy significantly, especially when the face database is large and only few training images are available. As a novel point despite of five-state HMM used in pervious researches, we propose to use 7-state HMM to cover more specific details. A pre-processing procedure is introduced to reduce the complexity of the proposed system. It is evident from the outcome of these experiments that more information during training yield better results.
Informing API Design through Usability Studies of API Design Choices: A Research Abstract

Using APIs is a common and often difficult task for developers. Successful API designs can guide users of an API and reduce their dependence on documentation; however API design is far from a science. Usability lab studies have been shown to be successful at improving the usability of specific APIs; however these are expensive and not always possible to run for every API. This paper describes an approach to generalize from studies of specific APIs to investigate the usability impact of design choices that commonly arise in the creation of APIs. Based on these results we will inform the design of many new APIs. A preliminary usability study of whether or not to require constructor parameters confirms our belief that the answer to common design decisions is not always obvious, and making the wrong choice can have a strong negative impact on usability for large groups of API users
Expanded citations and projections of concepts

In our recent paper, we proposed a new kind of citations, called the expanded citations, which link scientific papers and concepts from them. The expanded citations are represented in RDF and can be processed by machines. In this paper, we use the expanded citations to introduce projections of concepts which can be useful in searching for publications. The analysis of the projections and their time evolution gives a knowledge about the role and the significance of the concept in a given domain.