Miracle-dz/UniFAR-FTUs huggingface dataset:
Information Systems Strategy and Information Systems Development: A Case Study

The purpose of this paper is to discuss both the findings of a case study into IS Strategy conducted in a medium sized financial institution, and the interpretive process used. The research methodology was based on the FMA framework and consisted of two iterations – the first using a Business Alignment Model for inquiring into the practices within the organisation. The second to provide insights into, and make sense of the actions of the stakeholders.
CpG‐DNA‐induced IFN‐α production involves p38 MAPK‐dependent STAT1 phosphorylation in human plasmacytoid dendritic cell precursors

Human plasmacytoid or CD4+CD11c− type 2 dendritic cell precursors (PDC) were identified as natural type I interferon (IFN)‐producing cells in response to viral and bacterial infection. They represent effector cells of innate immunity and link it to the distinct adaptive immunity by differentiating into mature DC. It has been reported that oligodeoxyribonucleotides containing unmethylated CpG motifs (CpG DNA) stimulate PDC to produce IFN‐α, but the molecular mechanisms involved remain unknown. We found that CpG‐DNA‐induced IFN‐α production in PDC was completely impaired by the inhibitor of the p38 mitogen‐activated protein kinase (MAPK) pathway. Expression of IFN regulatory factor (IRF)‐7 was enhanced by CpG‐DNA treatment, which was preceded by the phosphorylation of signal transducer and activator of transcription (STAT)1 on Tyr‐701, as well as its enhanced phosphorylation on Ser‐727. All of these events were also suppressed by the p38 MAPK inhibitor. STAT1, STAT2, and IRF‐9, components of IFN‐stimulated gene factor 3 (ISGF3), were recognized in the nuclear fraction of CpG‐DNA‐treated cells. Neither anti‐IFN‐α/β antibodies (Ab) nor anti‐IFNAR Ab suppressed STAT1 phosphorylation, enhancement of IRF‐7 expression, or IFN‐α production in the early phase of the culture. These results suggest that CpG DNA induces p38 MAPK‐dependent phosphorylation of STAT1 in a manner independent of IFN‐α/β, which may cause ISGF3 formation to increase the transcription of the IRF‐7 gene, thereby leading to IFN‐α production in human PDC.
Self-Stabilizing Micro Controller for Large-Scale Sensor Networks in Spite of Program Counter Corruptions Due to Soft Errors

For large installations of networked embedded systems it is important that each entity is self-stabilizing, because usually there is nobody to restart nodes that have hung up. Self-stabilization means to recover from temporary failures (soft errors) and adapt to a change of network topology caused by permanent failures. On the software side self-stabilizing algorithms must assume that the hardware is executing the software correctly. In this paper we discuss cases in which soft errors invalidate this assumption, especially in cases where CPU registers or the watchdog timer are affected by the fault. Based on the observation that a guaranteed self-stabilization is only possible as long as the watchdog-timer is working properly after temporary failures, we propose and compare three different approaches that meet the requirements of sensor networks, to solve this problem with a combination of hardware- and software-modifications: 1) A run-time verification of every watchdog access 2) A completely hardware-based approach, without any software modifications 3) A 2X byte code alignment, to realign a corrupted program counter Furthermore we determine the average code-size increase and evaluate necessary hardware-modifications that come along with each approach.
Curve fitting method for modeling and analysis of photovoltaic cells characteristics

This paper deals with the mathematical model to assess the performances of photovoltaic (PV) cells. The PV system characteristics are modeled and analyzed by using the curve fitting method referred to the different connections of PV cells and different solar irradiance. The results are compared with those resulting from measured data in a real case. Specific LabVIEW™ and Matlab™ software applications are implemented to prove the theoretical methods.
Do Japanese companies have a competitive strategy

Responding to Michael Porter’s claim that “Japanese companies rarely have a strategy”, this paper argues that the competitive advantage of Japanese enterprises is not to be found in traditional practices. Rather, it is due to the way these practices are upgraded and reinforced by ideological factors such as the “community of fate”, as well as the formation of governance structures that cultivate the development of contextual knowledge that leads to the efficient and effective production of complex products.
Run-Time Dynamic Data Type Transformations 1

Abstract: In the last years, complex applications from various domains are implemented in embedded devices. These applications make extended use of the dynamic memory to store dynamically allocated data structures. The implementation of these data structures affects the performance and the memory usage of the embedded system. A methodology for selecting the appropriate data structures at design time is the Dynamic Data Type Refinement (DDTR) methodology. In this paper we present an extension to this approach, by presenting a methodology for adapting the dynamic data structure implementations to the requirements of the embedded system at runtime. By implementing the proposed methodology to a set of various applications from different domains, we achieve a dynamic memory size reduction up to 32%.
Bridging Folksonomies and Domain Ontologies: Getting Out Non-taxonomic Relations

Social book marking tools are rapidly emerging on the Web as it can be witnessed by the overwhelming number of participants. In such spaces, users annotate resources by means of any keyword or tag that they find relevant, giving raise to lightweight conceptual structures \emph{aka} folksonomies. In this respect, needless to mention that ontologies can be of benefit for enhancing information retrieval metrics. In this paper, we introduce a novel approach for ontology learning from a \textit{folksonomy}, which provide shared vocabularies and semantic relations between tags. The main thrust of the introduced approach stands in putting the focus on the discovery of \textit{non-taxonomic} relationships. The latter are often neglected, even though they are of paramount importance from a semantic point of view. The discovery process heavily relies on triadic concepts to discover and select related tags and to extract and label non-taxonomically relationships between related tags and external sources for tags filtering and non-taxonomic relationships extraction. In addition, we also discuss a new approach to evaluate obtained relations in an automatic way against WordNet repository and presents promising results for a real world \textit{folksonomy}.
5 Constructing and Using Software Requirements Patterns

Software requirement reuse strategies are necessary to capitalize and reuse knowledge in the requirements engineering phase. The PABRE framework is designed to support requirement reuse through the use of software requirement patterns. It consists of a meta-model that describes the main concepts around the notion of pattern; a method to conduct the elicitation and documentation processes; a catalogue of patterns; and a tool that supports the catalogue’s management and use. In this chapter all these elements are presented in detail making emphasis on the construction, use and evolution of software requirement patterns. Furthermore, the chapter includes the construction of a catalogue of non-technical software requirement patterns for illustration purposes.
Decentralized Impedance Control of Nonredundant Multi-manipulator Systems

In this paper, we propose a decentralized control scheme for combined motion/force control of nonredundant multi-manipulator robotic systems, cooperatively grasping a rigid body in a prespecified position/force trajectory. The proposed control scheme uses the impedance method for modeling the internal force exerted by the end effectors to the object. The precise mathematical analysis of the overall dynamical system and the proposed controller are presented and the stability of the overall system is studied. The proposed controller, then, is applied to a cooperative system composed of two PUMA560 manipulators and the simulation results are presented to verify the proposed control scheme.
Anomaly Detection in Surveillance Video using Color Modeling

primary goal of this paper propose an algorithm for automatic detection of abnormal events in video surveillance scenarios. We specifically focus our attention on the event of object dropping in public places such as railway stations and airports etc. We look into how to distinguish events in surveillance video, and further what is a remarkable event. Analyzing surveillance data, without the knowledge of when and where or even if an interesting event has occurred which often takes place, is very time consuming labour. In this kind of analysis we are interested in extraordinary events, something that deviates from the normal.
Adaptive Flocking of a Swarm of Robots Based on Local Interactions

This paper presents a novel flocking strategy for a large-scale swarm of robots that enables the robots to navigate autonomously in an environment populated with obstacles. Robot swarms are often required to move toward a goal while adapting to changes in environmental conditions in many applications. Based on the observation of the swimming behavior of a school of tunas, we apply their unique patterns of behavior to the autonomous adaptation of the shape of robot swarms. Specifically, each robot dynamically selects two neighboring robots within its sensing range and maintains a uniform distance with them. This enables three neighboring robots to form a regular triangle and remain stable in the presence of obstacles. Therefore, the swarm can be split into multiple groups or re-united into one according to environmental conditions. More specifically, assuming that robots are not allowed to have individual identification numbers, a pre-determined leader, memories of previous perceptions and actions, and direct communications to each other, we verify the validity of the proposed algorithm using the in-house simulator. The results show that a swarm of robots repeats the process of partition and maintenance passing through multiple narrow passageways
utomatic selection of ROIs in functional imaging using aussian mixture models

We present an automatic method for selecting regions of interest (ROIs) of the information contained in three-dimensional functional brain images using Gaussian mixture models (GMMs), where each Gaussian D P ccepted 13 May 2009 eywords: PECT brain imaging classification omputer-aided diagnosis incorporates a contiguous brain region with similar activation. The novelty of the approach is based on approximating the grey-level distribution of a brain image by a sum of Gaussian functions, whose parameters are determined by a maximum likelihood criterion via the expectation maximization (EM) algorithm. Each Gaussian or cluster is represented by a multivariate Gaussian function with a center coordinate and a certain shape. This approach leads to a drastic compression of the information contained rves eases
Quaternion-Based Iterative Solution of Three-Dimensional Coordinate Transformation Problem

Three-dimensional coordinate transformation problem is the most frequent problem in photogrammetry, geodesy, mapping, geographical information science (GIS), and computer vision. To overcome the drawback that traditional solution of the problem based on rotation angles depends strongly on initial value of parameter, which makes the method ineffective in the case of super-large rotation angle, the paper adopts an unit quaternion to represent three-dimensional rotation matrix, then puts forward a quaternion-based iterative solution of the problem. The cases study shows that the quaternion-based solution has no dependence on the initial value of parameter and desirable result with fast speed. Thus it is valid for three-dimensional coordinate transformation of any rotation angle.
VAM . 10 State of the Art in Hardware Implementations of Cryptographic Algorithms

Project co-funded by the European Commission within the 6th Framework Programme Dissemination Level PU Public X PP Restricted to other programme participants (including the Commission services) RE Restricted to a group specified by the consortium (including the Commission services) CO Confidential, only for members of the consortium (including the Commission services) The information in this document is provided as is, and no warranty is given or implied that the information is fit for any particular purpose. The user thereof uses the information at its sole risk and liability. In this deliverable, we survey the state of the art of implementations of elliptic curve cryptography (short: ECC) based cryptographic algorithms. ECC offers equivalent security to RSA, however, for smaller key sizes. This often implies benefits such as high speed, low power consumption , or small certificates, which is especially useful in constrained environments (smart cards, mobile phones, PDAs, etc.). ECC is a mature technology nowadays and the algorithms to provide cryptographic services are standardized by various bodies, for instance [3, 46] etc. In the first chapter of this deliverable, we briefly introduce the most important concepts in the field of ECC. We list the most popular ECC algorithms and protocols and explain how the basic arithmetic operations work. In the remainder of this deliverable, we focus on high-speed and lightweight implementations of ECC in hardware. In the case of high-speed ECC implementations, practical applications may impose entirely different optimization goals. For instance, high performance could be more important than flexibility. An opposite scenario could be that a high flexibility with respect to key sizes and (or) curves could be required. However, for all scenarios and requirements it is important to take care of several important principles. Efficient coordinates for representing points together with a fast scalar multiplication algorithm must be chosen. Then, according to the capabilities of the selected multiplier architecture, an accurate scheduling of the scalar multiplication algorithm has to be determined. If possible, pipelining techniques should be applied. Today, ECC implementations on FPGAs require always a full reconfiguration of the FPGA if a, normally fixed parameter, is changed. Future implementations allowing on-the-fly reconfiguration could be an efficient solution and should help to recover the loss of flexibility. For versatile processors, more work could be done to take the best advantage of full size hardware while computing with smaller operands. We have identified that the open literature lacks multi-scalar multiplication …
Effective Coefficients in Anisotropic Porous Medium with Multiscale Log-Normal Conductivity

Effective coefficients problem is solved for the anisotropic medium. The conductivity is assumed to be a random multifractal of lognormal distribution. Dimensions of solution domain of the problem are considered to be large compared to the sizes of heterogeneities of the medium. Subgrid modeling approach, associated with problems of subsurface hydrodynamics is presented. Theoretical result is compared to the results of direct 3D numerical modeling and results of conventional perturbation theory.
Supersymmetric extensions of Calogero-Moser-Sutherland-like models: construction and some solutions

We introduce a new class of models for interacting particles. Our construction is based on Jacobians for the radial coordinates on certain superspaces. The resulting models contain two parameters determining the strengths of the interactions. This extends and generalizes the models of the Calogero-Moser-Sutherland type for interacting particles in ordinary spaces. The latter ones are included in our models as special cases. Using results which we obtained previously for spherical functions in superspaces, we obtain various properties and some explicit forms for the solutions. We present physical interpretations. Our models involve two kinds of interacting particles. One of the models can be viewed as describing interacting electrons in a lower and upper band of a quasi-one-dimensional semiconductor. Another model is quasi-two-dimensional. Two kinds of particles are confined to two different spatial directions, the interaction contains dipole-dipole or tensor forces.
Role of nanotechnology and gene delivery systems in TRAIL-based therapies

Since its identification as a member of the tumour necrosis factor (TNF) family, TRAIL (TNF-related apoptosis-inducing ligand) has emerged as a new avenue in apoptosis-inducing cancer therapies. Its ability to circumvent the chemoresistance of conventional therapeutics and to interact with cancer stem cells (CSCs) self-renewal pathways, amplified its potential as a cancer apoptotic agent. Many recombinant preparations of this death ligand and monoclonal antibodies targeting its death receptors have been tested in monotherapy and combinational clinical trials. Gene therapy is a new approach for cancer treatment which implies viral or non-viral functional transgene induction of apoptosis in cancer cells or repair of the underlying genetic abnormality on a molecular level. The role of this approach in overcoming the traditional barriers of radiation and chemotherapeutics systemic toxicity, risk of recurrence, and metastasis made it a promising platform for cancer treatment. The recent first Food Drug Administration (FDA) approved oncolytic herpes virus for melanoma treatment brings forth the potency of the cancer gene therapy approach in the future. Many gene delivery systems have been studied for intratumoural TRAIL gene delivery alone or in combination with chemotherapeutic agents to produce synergistic cancer cytotoxicity. However, there still remain many obstacles to be conquered for this different gene delivery systems. Nanomedicine on the other hand offers a new frontier for clinical trials and biomedical research. The FDA approved nanodrugs motivates horizon exploration for other nanoscale designed particles’ implications in gene delivery. In this review we aim to highlight the molecular role of TRAIL in apoptosis and interaction with cancer stem cells (CSCs) self-renewal pathways. Finally, we also aim to discuss the different roles of gene delivery systems, mesenchymal cells, and nanotechnology designs in TRAIL gene delivery.
Synthesis, Characterization, Antimicrobial, DNA Cleavage, and Antioxidant Studies of Some Metal Complexes Derived from Schiff Base Containing Indole and Quinoline Moieties

A new Schiff base of 5-chloro-3-phenyl-1H-indole-2-carboxyhydrazide and 3-formyl-2-hydroxy-1H-quinoline (HL), and its Cu(II), Co(II), Ni(II), Zn(II), Cd(II), and Hg(II) complexes have been synthesized and characterized in the light of microanalytical, IR, H1 NMR, UV-Vis, FAB-mass, ESR, XRD, and TGA spectral studies. The magnetic susceptibility measurements and low conductivity data provide evidence for monomeric and neutral nature of the complexes. On the basis of spectral studies and analytical data, it is evident that the Schiff base acts as tridentate ligand. The Cu(II), Co(II), and Ni(II) complexes were octahedral, whereas Zn(II), Cd(II), and Hg(II) complexes were tetrahedral in nature. The redox behavior of the Cu(II) complex was investigated by electrochemical method using cyclic voltammetry. In order to evaluate the effect of metal ions upon chelation, both the ligand and its metal complexes were screened for their antibacterial and antifungal activities by minimum inhibitory concentration (MIC) method. The DNA cleavage experiment performed using agarose gel electrophoresis method showed the cleavage of DNA by all the metal complexes. The free radical scavenging activity of newly synthesized compounds has been determined at a different concentration range by means of their interaction with the stable free radical 1,1-diphenyl-2-picrylhydrazyl (DPPH).
Ubiquitous Reassortments in influenza a viruses

The influenza A virus is a negative-stranded RNA virus composed of eight segmented RNA molecules, including polymerases (PB2, PB1, PA), hemagglutinin (HA), nucleoprotein (NP), neuraminidase (NA), matrix protein (MP), and nonstructure gene (NS). The influenza A viruses are notorious for rapid mutations, frequent reassortments, and possible recombinations. Among these evolutionary events, reassortments refer to exchanges of discrete RNA segments between co-infected influenza viruses, and they have facilitated the generation of pandemic and epidemic strains. Thus, identification of reassortments will be critical for pandemic and epidemic prevention and control. This paper presents a reassortment identification method based on distance measurement using complete composition vector (CCV) and segment clustering using a minimum spanning tree (MST) algorithm. By applying this method, we identified 34 potential reassortment clusters among 2,641 PB2 segments of influenza A viruses. Among the 83 serotypes tested, at least 56 (67.46%) exchanged their fragments with another serotype of influenza A viruses. These identified reassortments involve 1,957 H2N1 and 1,968 H3N2 influenza pandemic strains as well as H5N1 avian influenza virus isolates, which have generated the potential for a future pandemic threat. More frequent reassortments were found to occur in wild birds, especially migratory birds. This MST clustering program is written in Java and will be available upon request.