Miracle-dz/UniFAR-FTUs huggingface dataset:
Altered Expression and Uptake Activity of Spinal Glutamate Transporters after Nerve Injury Contribute to the Pathogenesis of Neuropathic Pain in Rats

The central glutamatergic system has been implicated in the pathogenesis of neuropathic pain, and a highly active central glutamate transporter (GT) system regulates the uptake of endogenous glutamate. Here we demonstrate that both the expression and uptake activity of spinal GTs changed after chronic constriction nerve injury (CCI) and contributed to neuropathic pain behaviors in rats. CCI induced an initial GT upregulation up to at least postoperative day 5 primarily within the ipsilateral spinal cord dorsal horn, which was followed by a GT downregulation when examined on postoperative days 7 and 14 by Western blot and immunohistochemistry. Intrathecal administration of the tyrosine kinase receptor inhibitor K252a and the mitogen-activated protein kinase inhibitor PD98059 for postoperative days 1–4 reduced and nearly abolished the initial GT upregulation in CCI rats, respectively. Prevention of the CCI-induced GT upregulation by PD98059 resulted in exacerbated thermal hyperalgesia and mechanical allodynia reversible by the noncompetitive NMDA receptor antagonist MK-801, indicating that the initial GT upregulation hampered the development of neuropathic pain behaviors. Moreover, CCI significantly reduced glutamate uptake activity of spinal GTs when examined on postoperative day 5, which was prevented by riluzole (a positive GT activity regulator) given intrathecally twice a day for postoperative days 1–4. Consistently, riluzole attenuated and gradually reversed neuropathic pain behaviors when the 4 d riluzole treatment was given for postoperative days 1–4 and 5–8, respectively. These results indicate that changes in the expression and glutamate uptake activity of spinal GTs may play a critical role in both the induction and maintenance of neuropathic pain after nerve injury via the regulation of regional glutamate homeostasis, a new mechanism relevant to the pathogenesis of neuropathic pain.
Semantically-Driven Workflow Generation Using Declarative Modeling for Processes in Software Engineering

Software engineering processes are a challenging domain for the application of workflow engines due to their high dynamicity, often evolutionary nature, abstract process models, and the informational and environmental dependencies of their activities. In order to offer automated and relevant process guidance to software developers, the operational-level guidance must be capable of situational adaptation as processes evolve. A declarative workflow modeling approach driven by semantic technology is described that contextually constructs workflows on-the-fly from candidate activities. Thus, automated process guidance in dynamic environments is facilitated while retaining correctness properties, simplifying modeling, and fostering reuse.
Reconstruction of 3D Planar Objects with Partial Occlusion

Lappeenranta University of Technology Department of Information Technology Igor Kuzivanov Reconstruction of 3D Planar Objects with Partial Occlusion Master’s thesis 2003 59 pages, 26 figures and 13 tables. Supervisors: Professor Heikki Kälviäinen and Dr Ville Kyrki.
Students as Protégés

This study provides insight into the factors that influence satisfaction with an Internet-based practitioner–student mentoring relationship that is part of an undergraduate business school curriculum. Practitioner mentors are especially important because they can help student protégés learn the skills needed for their professional development, encourage the formation of professional networks, and enhance the protégés’ satisfaction with their education. In this study, we examine a number of factors that can potentially influence satisfaction with the mentoring relationship, including the protégé’s networking to find a mentor, protégé trust in the mentor, protégé self-disclosure, the level of protégé understanding of the mentoring program’s objectives, and how effectively the mentor serves as a role model. Hypotheses were tested through a structural equation model. The results showed that mentoring relationship satisfaction was positively associated with networking to find a mentor, trust in the mentor, protégé self-disclosure, protégé understanding of the objectives of the mentoring program, and the degree to which the protégé viewed the mentor as a role model. In addition, mentor trust was positively associated with the level of protégé self-disclosure. Implications for theory and practice are discussed, and recommendations on how to strengthen satisfaction with practitioner–student mentoring relationships are provided.
Activity Monitoring and Prediction for Humans and NAO Humanoid Robots Using Wearable Sensors

While humans or biped humanoid robots perform activities such as jogging and running, an accident event such as a fall may occur. This might cause damage to the human body or to the structural components of the robot. For humans, immediate identification of a fall will allow fast responses, while for a robot, early prediction can be used to take corrective measures to prevent a fall. Modern wireless sensing devices can be attached to humans or robots to collect motion data. We propose: 1) methods to learn and predict different activities for humans and robots; and 2) software tools to realize these functions on embedded devices. Our contributions include: 1) detection of falls for both humans and robots within a unified framework; and 2) a novel software development environment for embedded systems. Our empirical evaluations demonstrate that with high accuracy different types of fall-events are predicted using the same learning algorithms for humans and biped humanoid robots.
Calicivirus from Novel Recovirus Genogroup in Human Diarrhea, Bangladesh

To identify unknown human viruses in the enteric tract, we examined 105 stool specimens from patients with diarrhea in Bangladesh. A novel calicivirus was identified in a sample from 1 patient and subsequently found in samples from 5 other patients. Phylogenetic analyses classified this virus within the proposed genus Recovirus.
Decoding error-correcting codes with Grobner bases

The decoding of arbitrary linear block codes is accomplished by solving a system of quadratic equations by means of Buchberger's algorithm for finding a Grobner basis. This generalizes the algorithm of Berlekamp-Massey for decoding Reed- Solomon, Goppa and cyclic codes up to half the true minimum distance by intro- ducing the unknown syndromes as variables. The complexity of this algorithm is exponential and the complexity coecient is measured under the assumption that the over-determined system of quadratic equations is semi-regular using the results of Bardet et al. (5). The complexity is compared to existing bounded distance decoding algorithms. Our method can be extended to complete and generic decoding, and to finding the minimum distance and the complete weight distribution.
A Spatial Analysis of Household Location Decisions in Maine

In recent years, the causes and consequences of land use change have emerged as significant policy issues. Accordingly, it is not surprising to witness the emergence of policies designed to manipulate both the drivers and consequences of land use change. “Smart growth” policies, which favor clustered development in established growth areas, are a notable example of such policies. Although smart growth policies are increasingly gaining in stature, there is limited empirical assessment of their feasibility and desirability. Critics of smart growth policies suggest that these policies may “require telling people that they may not live as they prefer to live, even if they can afford it (Hayward, 2002). " In this paper, the feasibility of adopting smart growth policies in Maine is assessed using novel data collected by the Maine State Planning Office. A random utility modeling framework is employed to examine household location decisions and identify the relative influence of environmental, economic, and social factors. This modeling framework enables us to consider the impact of alternative growth management policies on housing location decisions as well as to examine the influence of changes in individual and community characteristics. GIS data and modeling tools are employed to expand the consideration of the spatial aspects of location decisions. The final intended contribution of this research is to examine the consequences of spatial dependence in a random utility modeling framework.
Versioning of Conventional Schema in the tXSchema Framework

Schema versioning is an indispensable feature for applications using temporal databases and requiring an entire history of data and schema. tXSchema [7] is an infrastructure for constructing and validating temporal XML documents, but any explicit support for XML schema versioning is offered. A ôXSchema schema is composed of a conventional XML Schema document annotated with physical and logical annotations. All components of a ôXSchema schema can change over time to reflect changes in user requirements or in reference world of the database. In a previous work [10], we deal with versioning of logical and physical annotations. In this work, we study versioning of ôXSchema conventional schema: we propose a complete set of low-level primitives for changing such a schema and define their operational semantics.
Disorder, defects, and band gaps in ultrathin (001) MgO tunnel barrier layers

We report scanning tunneling spectroscopy studies of the electronic structure of $1.5\char21{}3\phantom{\rule{0.3em}{0ex}}\mathrm{nm}$ (001) textured MgO layers grown on (001) Fe. Thick MgO layers exhibit a bulklike band gap, $\ensuremath{\sim}5\char21{}7\phantom{\rule{0.3em}{0ex}}\mathrm{eV}$, and sparse, localized defect states with characteristics attributable to oxygen and, in some cases, Mg vacancies. Thin MgO layers exhibit an electronic structure indicative of interacting defect states forming band tails which in the thinnest case extend to $\ensuremath{\sim}\ifmmode\pm\else\textpm\fi{}0.5\phantom{\rule{0.3em}{0ex}}\mathrm{V}$ of the Fermi level. These vacancy defects are ascribed to compressive strain from the $\mathrm{Mg}\mathrm{O}∕\mathrm{Fe}$ lattice mismatch, accommodated as the MgO grows.
Design and Characterization of a Three-terminal Transcriptional Device Through Polymerase Per Second

In this paper, we provide an in silico input-output characterization of a three-terminal transcriptional device employing polymerase per second (PoPS) as input and output. The device is assembled from well-characterized parts of the bacteriophage ¿ switch transcriptional circuit. We draw the analogy between voltage and protein concentration and between current and PoPS to demonstrate that the characteristics of the three-terminal transcriptional device are qualitatively similar to those of a bipolar junction transistor (BJT). In particular, as it occurs in a BJT, the device can be tuned to operate either as a linear amplifier or as a switch. When the device operates as a linear amplifier, gains of twofolds can be obtained, which are considerably smaller than those obtained in a BJT (in which 100-fold amplification gains can be reached). This fact suggests that the parts extracted from natural transcriptional systems may be naturally designed mostly to process and store information as opposed to amplify signals.
Revenue Management Games

A well-studied problem in the literature on airline revenue (or yield) management is the optimal allocation of seat inventory among fare classes given a demand distribution for each class. In the literature thus far, passenger demand is an exogenous parameter. However, the seat allocation decisions of one airline affect the passenger demands for seats on other airlines. In this paper we examine the seat inventory control problem with two fare classes and two airlines under competition. Each airline chooses an optimal booking limit for the lower-fare class while taking into account the overflow of passengers from its competitor. We show that under certain conditions this 'revenue management game' has a pure-strategy Nash equilibrium, and for special cases we show that the equilibrium is unique. We also compare the total number of seats available in each fare class with, and without, competition. Analytical results for one special case as well as numerical examples demonstrate that, all else equal, under competition more seats are protected for higher-fare passengers than when a single airline acts as a monopoly or when airlines form an alliance to maximize overall profits.
Mining Opinion Attributes from Texts Using Multiple Kernel Learning

In this paper we propose a novel framework for recognizing complex opinion attributes from product reviews. Instead of focusing on linguistic properties of text fragments and their direct representations, we focus on these fragments' similarities which we obtain from multiple sources of lexical and semantic information. The problem is formulated as that of multiclass classification and is based on multiple similarity matrices. We apply multiple kernel learning algorithm which seeks optimal combinations of matrices using linear programming and support vector machines for classification. Experiments demonstrate benefits from multiple sources of information. Overall, the approach is promising especially in the case of reviews of product types with complex and wordy attribute expressions.
Definition of Fuzzy Pareto-Optimality by Using Possibility Theory

Pareto-optimality conditions are crucial when dealing with classic multi-objective optimization problems because we need to find out a set of optimal solutions rather than only one optimal solution to optimization problem with a single objective. Extensions of these conditions to the fuzzy domain have been discussed and ad- dressed in recent literature. This work presents a novel approach based on the use of possibility theory as a comparison index to define a fuzzily ordered set with a view to generating the necessary con- ditions for the Pareto-optimality of candidate solutions in the fuzzy domain. Making use of the conditions generated, one can charac- terize fuzzy efficient solutions by means of carefully chosen single- objective problems. The uncertainties are inserted into the formu- lation of the studied fuzzy multi-objective optimization problem by means of fuzzy coefficients in the objective function. Some numeri- cal examples are analytically solved to illustrate the efficiency of the proposed approach.
On the use of PMUs in power system state estimation

Synchronized phasor measurement units (PMUs) are becoming a reality in more and more power sys- tems, mainly at the transmission level. This paper presents, in a tutorial manner, the benefits that existing and future State Estimators (SE) can achieve by incorporating these de- vices in the monitoring process. After a review of the rele- vant PMU technological aspects and the associated deploy- ment issues (observability, optimal location, etc.), the alter- native SE formulations in the presence of PMUs are revis- ited. Then, several application environments are separately addressed, regarding the enhancements potentially brought about by the use of PMUs.
Multiresolution Multilateral Filtering for Local Similarity based Image Denoising

In this paper, we present a general framework for denoising of images corrupted with additive white Gaussian noise based on the idea of regional similarity. The proposed method adds an additional similarity function to the bilateral ﬁltering framework. The new similarity function is based on distance between pixels in a multidimensional feature space, whereby multiple feature maps describing various local regional characteristics can be utilized, giving higher weight to pixels having similar regional characteristics. The proposed framework is then extended into a multiresolution setting using wavelets and scale space. It is shown that the resulting multiresolution multilateral (MRM) ﬁltering algorithm not only eliminates coarse-grain noise but can also faithfully reconstruct anisotropic oscillatory patterns, particularly in the presence of high levels of noise
Performance and Variability Optimization Strategies in a Sub-200mV, 3.5pJ/inst, 11nW Subthreshold Processor

A robust, energy efficient subthreshold (sub-V<sub>th</sub>) processor has been designed and tested in a 0.13 mum technology. The processor consumes 11 nW at V<sub>dd</sub> = 160 mV and 3.5 pJ/inst at V<sub>dd</sub> = 350 mV. Variability and performance optimization techniques are investigated for sub-V<sub>th</sub> circuits.
An exploratory study of a reflecting team's influence on the family meaning system in the Self-Harm Intervention Family Therapy (SHIFT) trial

Introduction: The study aimed to explore a Reflecting Teams (RT) influence on the family meaning system in The Self-Harm Intervention Family Therapy (SHIFT) Trial where the referral problem is adolescent self-harm. Method: A multiple case study design was undertaken to examine the practice and influence of a RT across three different families by comparison of the pre and post RT dialogues and the discursive strategies utilised by the RT. An original analytical strategy was implemented, derived from Discursive Psychology, the pragmatic application of Positioning Theory and the Semantic Polarities Model, to capture subtle shifts within the family meaning system from recorded family therapy sessions. Results: The RT was instrumental in guiding and reinforcing the therapist’s influence; acting as a consultative team, a supervisory resource and a collaborative partner. The RT influenced change across cases through a range of discursive strategies: collaborative co-positioning of the family and therapy team, adopting an expert position regarding the management of risks and areas of continuing concern and also emphasising and reinforcing family strengths, progress, and resilience. Findings suggest that the RT may have a differential influence depending on the stage and context of therapy. Discussion: These novel findings are discussed in the context of existing literature and the specific contribution of the current study regarding adaptations to RT practice in response to the management of risk and stage of therapy. Limitations of the current research design are indicated with recommendations for future research.
Surface antigens of brain synapses: identification of minor proteins using polyclonal antisera

Antigenic proteins of brain synaptic plasma membranes (SPM) and postsynaptic densities (PSD) were characterized using antisera raised against SPM. Immunostaining of brain sections showed that the antigens were restricted to synapses, and electron microscopy revealed staining at both presynaptic terminals and PSDs. In primary brain cell cultures the antisera were also neuron-specific but the antigens were distributed throughout the entire neuronal plasma membrane, suggesting that some restrictive influence present in whole tissue is absent when neurons are grown dispersed. The antigenic proteins with which these antisera react were identified using SDS gel immunoblots. SPM and PSD differed from one another in their characteristic antigenic proteins. Comparison with amido-black stained gel blots showed that in both cases most of these did not correspond to known abundant proteins of SPM or PSDs revealed by conventional biochemical techniques. None of the antigens revealed by the polyclonal antisera were detected by any of a large series of monoclonal antibodies against SPM.
Detection of Oil Slicks in SAR Images using Hierarchical MRF

This study deals with hierarchical Markov Random Field (MRF) models and with their application for the segmentation of SAR images of oil spills, which are going to be segmented into three classes: denser oil, thinner oil and sea water. The proposed unsupervised scheme takes into account the variety of the laws in the distribution mixture of a SAR image in order to estimate MRF parameters. To obtain a more precise model of local and global characteristics of image content, a hierarchical model involving a pyramidal scheme is used. The main goal of this strongly filtered representation is to introduce a rough map which facilitates the detection in the upper high resolution level. The proposed segmentation procedure works as a sequential technique which combines communication between the different levels of the pyramid. Because of the noisy nature of the SAR images, a MRF scheme, which exploits its contextual analysis, is used. The investigation was carried out using an ERS-2/SAR image, collected on June 9 2000 over the South Adriatic Sea (orbit: 26858 frame: 451) and showing the presence of a large oil slick. From the full SAR scene, a subset, 1000times1500 pixel size, covering large part of the slick, was extracted to become our test image. Before applying the proposed scheme, the speckle noise was removed from the image by means of an adaptive filter . Using the proposed hierarchical MRF scheme, different segmentation experiments were carried out. The results of this study will be presented and discussed.
Algorithms and Methods for Organised Cybercrime Analysis

Law enforcement agencies reports that Organised Criminal Groups are moving more of their activities from traditional crime into the cyber domain. Where they form so-called Darknets, whose purpose is to act as marketplaces for illegal material, products, and services. These activities form a part of the Crime-as-aService business model, which drives the digital underground economy by providing services that facilitate almost any type of cybercrime. The challenge for law enforcement is knowing which entity to target for effectively taking down these network structures. This thesis seeks to use graph-based algorithms and methods to analyse network structures to identify interesting and relevant individuals within such networks. More specifically, it proposes Social Network Analysis (SNA) methods for the process of identification of such individuals. The thesis analyse each SNA method to identify those methods that identify the most central individuals within a network. Also, it will analyse how the usage of different graph construction techniques can be applied to the process of identification. The thesis contributions is to try to bridge the gap between law enforcement agencies and cybercrimials by proposing an improved way of prioritising individuals within these networks.
Detecting binocular half-occlusions: empirical comparisons of four approaches

Binocular half-occlusion points are those that are visible in one of the two views provided by a binocular imaging system. Due to their importance in binocular matching as well as subsequent interpretation tasks, a number of approaches have been developed for dealing with such points. In the current paper, we consider four methods that explicitly detect half-occlusions and report on a more uniform comparison than has previously been performed. Taking a disparity image and its associated match goodness image as input, we generate images that show the half-occluded points in the underlying scene. We quantitatively and qualitatively compare these methods under a variety of conditions.
GA-based dynamic manipulability optimization of a 2-DOF planar parallel manipulator

Dynamic manipulability is a very important issue that should be considered for problems of parallel manipulator design. In order to study the dynamic optimization of a 2-DOF planar parallel manipulator, which is used in a heavy duty hybrid machine, genetic algorithm (GA) is used in the dynamic manipulability optimization. Based on the kinematic analysis, the dynamic equation of the 2-DOF parallel manipulator is derived using the virtual work principle method. Furthermore, global dynamic manipulability (GDM) is introduced to measure the dynamic performance of the manipulator. Then the dynamic optimization based GA method is analyzed. From the numerical simulation, it is proved that the dynamic optimization considering GDM proposed in this paper can ameliorate the dynamic performance of the parallel manipulator well.