Miracle-dz/UniFAR-FTUs huggingface dataset:
Cloning and Characterization of an Ehrlichia canis Gene Encoding a Protein Localized to the Morula Membrane

ABSTRACT A gene encoding a 23.5-kDa ehrlichial morula membrane protein designated MmpA was cloned by screening an Ehrlichia canis expression library with convalescent dog sera, which resulted in three positive clones. Sequence analysis of the insert DNAs from all three clones indicated an open reading frame with a size of 666 bp that encodes MmpA. The structural analysis of MmpA indicated that it is a transmembrane protein with extreme hydrophobicity. Southern blot analysis of the HindIII-digested chromosomal DNA demonstrated the presence of a single copy of the mmpA gene in E. canis and Ehrlichia chaffeensis but not in the human granulocytic ehrlichiosis agent. The mmpA gene was amplified, cloned, and expressed as a fusion protein. Polyclonal antibodies to the recombinant protein (rMmpA) were raised in rabbits. Western blot analysis of E. canis and E. chaffeensis lysates with the anti-rMmpA serum resulted in the presence of an MmpA band only in E. canis, not in E. chaffeenesis. Sera from dogs which were either naturally or experimentally infected with E. canis recognized the recombinant protein. Double immunofluorescence confocal microscopy studies demonstrated that MmpA was localized mainly on the morula membrane of E. canis. Since the morula membrane is the interface between the ehrlichial growing environment and the host cytoplasm, MmpA may play a role in bacterium-host cell interactions.
HDAC3 Is a Negative Regulator of Cocaine-Context-Associated Memory Formation

Cocaine-induced neuroplasticity mediated by histone acetylating and deacetylating enzymes may contribute to addiction-like behaviors. For example, overexpression of histone deacetylases (HDACs) 4 or 5 in the nucleus accumbens suppresses cocaine-induced conditioned place preference (CPP) acquisition in mice. HDAC4 and HDAC5 are known to interact with HDAC3, but the role of HDAC3 in cocaine-induced behaviors has never been examined. In this study, we address the hypothesis that HDAC3 is a negative regulator of cocaine-context-associated memory formation in mice. We examined the role of HDAC3 during the conditioning phase of CPP, when the mouse has the opportunity to form an associative memory between the cocaine-paired context and the subjective effects of cocaine. To address this hypothesis, Hdac3flox/flox and Hdac3+/+ mice (generated from a C57BL/6 background) were infused into the nucleus accumbens with adeno-associated virus expressing Cre recombinase to create focal, homozygous Hdac3 deletions. Hdac3flox/flox mice exhibit significantly enhanced CPP acquisition, which is correlated with increased gene expression during the consolidation phase of acquisition. Increased gene expression of c-Fos and Nr4a2 is correlated with decreased HDAC3 occupancy and increased histone H4 lysine 8 acetylation at their promoters. The results from this study demonstrate that HDAC3 negatively regulates cocaine-induced CPP acquisition.
Anomaly Detection with Wireless Sensor Networks

The aim of this study is to suggest two automated techniques able to help medical staff to detect earlier than usual some diseases using wireless sensor networks (WSNs). In this context, a patient is equipped with physical sensors which sense health parameters. This WSN will perform some computations and will run an alarm when a disease is suspected. The first technique uses a population protocol to handle data exchanged between motes and provides an efficient algorithm to suggest that a disease is diagnosed on a patient. The algorithm is distributed, i.e., the decision may be done by any sensor dealing with the disease detection. The second technique uses a token algorithm where, some motes are denoted as masters. Each of them is in charge of deciding if a specific disease occurs. This technique is not totally distributed but enhances the network efficiency regarding to the energy consumption, the time execution and the number of exchanged messages.
Dynamic Context-Aware Service Adaptation in a Pervasive Computing System

Pervasive computing requires that devices must be context-aware in order to provide proactively adapted services to both user and applications according to the current context. Most of the proposed approaches of service adaptation in a pervasive computing system are either not context-aware or based on an inappropriate definition of context. In this paper we propose a context-aware dynamic service adaptation approach for a device operating in a pervasive computing system. The approach is then modeled using colored Petri Nets and simulated using the CPN-Tools in order to validate it.
Benchmarking Security Computations on Wireless Devices

Many applications using cryptographic solutions on wireless devices choose one cryptographic technique over another with the assumption of it being more battery power efficient than the other. We present extensive benchmark test results for various cryptography techniques measuring the battery consumption of each technique on wireless devices in terms of number of computations per unit percent battery drain so that many of these assumptions could be better supported with strong evidence. The benchmark tests are performed on two wireless devices: a HP iPaQ PDA and a Dell Inspiron notebook. The cryptography techniques considered include DES, RC2, Rijndael , RSA encryption, MD5 and SHA hashing, and DSA, RSA signature algorithms. We present analysis of our results and a very useful comparison of these techniques enabling future research efforts to make a better decision while selecting cryptographic methods based on concrete results.
Effects of N-Cadherin Disruption on Spine Morphological Dynamics

Structural changes at synapses are thought to be a key mechanism for the encoding of memories in the brain. Recent studies have shown that changes in the dynamic behavior of dendritic spines accompany bidirectional changes in synaptic plasticity, and that the disruption of structural constraints at synapses may play a mechanistic role in spine plasticity. While the prolonged disruption of N-cadherin, a key synaptic adhesion molecule, has been shown to alter spine morphology, little is known about the short-term regulation of spine morphological dynamics by N-cadherin. With time-lapse, confocal imaging in cultured hippocampal neurons, we examined the progression of structural changes in spines following an acute treatment with AHAVD, a peptide known to interfere with the function of N-cadherin. We characterized fast and slow timescale spine dynamics (minutes and hours, respectively) in the same population of spines. We show that N-cadherin disruption leads to enhanced spine motility and reduced length, followed by spine loss. The structural effects are accompanied by a loss of functional connectivity. Further, we demonstrate that early structural changes induced by AHAVD treatment, namely enhanced motility and reduced length, are indicators for later spine fate, i.e., spines with the former changes are more likely to be subsequently lost. Our results thus reveal the short-term regulation of synaptic structure by N-cadherin and suggest that some forms of morphological dynamics may be potential readouts for subsequent, stimulus-induced rewiring in neuronal networks.
Semantic Web techniques for multimedia museum information handling

This paper describes the design and prototype implementation of a novel architecture for integrated concept, metadata and content based browsing and retrieval of museum information. The work is part of a European project involving several major galleries and the aim is to provide more versatile access to digital collections of museum artefacts, including 2-D images, 3-D models and other multimedia representations. An ontology for the museum domain, based on the CIDOC Conceptual Reference Model, is being developed as a semantic layer with references to the digital collection as instance information. The challenges of dealing with the import and management of multimedia museum information through the CIDOC CRM based semantic layer include data aggregation/derivation, cleaning, mapping and augmentation. Knowledge engineering precepts are used to guide the development of tools for data mapping and the organisation of workshops to enhance the museum partners' understanding of the ontology in relation to their legacy data. Augmentation agents for automatically extracting missing metadata instances from the Web are being developed as a way of assisting users to populate the semantic layer. Natural language processing techniques coupled with information retrieval tools are used for identifying information sources and structuring them into welldefined formats to be entered in the ontology. An ontological approach is also taken to the design and implementation of the user-interface of which a graphical concept browser is an integral component. This allows navigation through the semantic layer, display of thumbnails, or full representations of artefacts and textual information in appropriate viewers and the invocation of conventional content based searching or combined querying. Semantic Web technologies are used in system integration to describe how tools for analysis and visualisation can be applied to different data types and sources. This supports flexible and managed formulation, execution and interpretation of the results of distributed multimedia queries. Searches integrating concepts, content and metadata can be initiated from a single user interface. Combining system and data ontologies to define and publish the semantics of data retrieval brings closer the semantic web ideal of a self-describing digital heritage archive, accessible to anyone who can read these published semantics. 2 A. StevensonP1P, M. AddisP1P, M. BonifaceP1P, S. GoodallP2P, P. GrimwoodP1P, S. KimP2P, P. LewisP2P, K. MartinezP2P,
Immunoglobulin: production, mechanisms of action and formulations

Human immunoglobulin (Ig) began to be applied in the clinical practice with the treatment of primary immunodeficiencies. Quickly, applications of Ig increased, as its anti-inflammatory and immunomodulatory functions were elucidated. Currently, Ig is the most commonly used blood product. Ig is obtained by processing plasma; methods, in particular, techniques to reduce plasma viral loads have been evolving over the years and include: pasteurization, solvent/ detergent treatment, caprylic acid treatment and nanofiltration. These methods contribute to increased safety and quality of blood products. The mechanisms of action of Ig not only involve the blockade of Fc receptors of phagocytes, but also control complement pathways, idiotype-anti-idiotype dimer formation, blockage of superantigen binding to T cells, inhibition of dendritic cells and stimulation of regulatory T cells (Tregs). There are several formulations of Ig available, each one with its own peculiar characteristics. In Brazil, there is stringent legislation regulating the quality of Ig. Only Ig products that completely fulfill the quality control criteria are released for use. These standards involve different tests from visual inspection to determination of anti-complementary activity. This paper will further review the history and current status of Ig, including its production and mechanisms of action. The formulations available in Brazil and also the criteria of quality control currently applied will be presented.
Symmetrical charge-charge interactions in ionic solutions: implications for biological interactions

As is well known in electrolyte theory, electrostatic fields are attenuated by the presence of mobile charges in the solution. This seems to limit the possibility of an electrostatic repulsion model of biological interactions such as cell division. Here, a system of two charges in an ionic solution is considered. It is found that in the context of the symmetries of the system, the electrostatic repulsion between the two is considerably increased as compared to the electrostatic repulsion between two bare charges in a dielectric. This increase in repulsion, directly resulting from interactions between the symmetrical parts of the system, was found to be dependent on the magnitude of the charges and the separation between them. It was also found that this increases reaches a steady state for separation greater than a solvent determined length scale related to the Debye length. These findings strongly suggest that electrostatic interactions can play a crucial part in the physical forces that are involved in biological interactions.
Development And Application Of A Bayesian Decision Support Tool To Assist In The Management Of An Endangered Species

Bayesian decision support tools are becoming increasingly popular as a modelling framework that can analyse complex problems, resolve controversies, and support future decision-making in an adaptive management framework. This paper introduces a model designed to assist the management of the endangered Camphora swamp eucalypt (Eucalyptus camphora). This tree species is found in the Yellingbo Nature Conservation Reserve (YNCR), an isolated patch of forest in the Yarra Valley (Victoria, Australia).
Biophysical demand and sustainable water resources management : an Australian perspective

Abstract To develop a sustainable management system of any water resource, it is essential that a balance between the demand of the natural biophysical system and the need of the socio-economic development is achieved. The main challenge that water managers grapple with is how to reconcile the long-term environmental objectives with the short-term political, social and economic needs. Since the biophysical resources underwrite all socio-economic activities, it is imperative that the long-term health of surface water and groundwater systems be the primary driver for sustainable management of water resources. If the environmental need to sustain the ecological values of water is overlooked, then serious water quality problems will arise and the natural aquatic ecosystem will deteriorate to a level such that both social and economic developments become unsustainable. Case studies on water quality and recent water reform initiatives in Australia are discussed in this paper to demonstrate the paramount importa.
Selecting V&V Technology Combinations: How to Pick a Winner?

Numerous software verification and validation (V&V) techniques and tools exist to analyse requirements, designs and implementations of software systems. These V&V technologies range from relatively lightweight ones, such as inspection and testing, to more heavyweight technologies based on formal methods and theorem proving. For complex systems, a significant part of the cost and effort for development and maintenance is associated with V&V activities, and this almost always involves selecting and applying a mix of V&V technologies. Unfortunately, little is known about the cost-effectiveness of individual technologies or how to derive the most cost-effective combination. As such, combinations for particular projects are typically selected in an ad-hoc way. In this paper, several issues related to the selection and evaluation of combinations of V&V technologies are explored, based on personal experiences with the V&V of concurrent Java components. A V&V method is presented that was systematically derived through an analysis of the possible failures that can occur in concurrent Java components. This method combines inspection, static analysis, and dynamic testing. In addition, empirical methods that use analysis of fault data and experiments to evaluate V&V combinations are presented. Finally, ideas are presented for an iterative method that can be used to assist with both the selection and evaluation of cost-effective V&V combinations in a given context.
Metaphorical Perception of Sports Management Students on “Women in Sport” Concept

The purpose of this study was to analyze the perceptions of sports management students in Turkey regarding “women in sport” through metaphorical images. The study group of the research was composed of undergraduate students of Sports Management Department in 2018-2019 academic year. There were fortyfour percent (44%) of these students were female and fiftysix percent (56%) of them were male, which indicated a total of 126 students. Phenomenology approach which is one of the qualitative research methods has been used. The students who participated in the study were selected on voluntary basis and with easily accessible sampling method. Participant opinions were analyzed by using content analysis method. The data of research was derived from the structured forms which included the sentence “Women in sport is like ……. , because…. ”. Findings were showned that female students have produced 31 and male students have produced 52 valid metaphors related to the concept of women in sport. These metaphors were categorized under 6 distinct categories according to their common charecteristics. Female and male students` selecting metaphors was represented themes. According to findings, the theme of “women in sport as a leader” shows similarity in female and male students. In the theme of indivicual empoverment, female students used the concepts of sun, star, plane, female lion but male students stated that the metaphors of earth, gun, tank and warrior. The theme of universal values and contribution to social development in male students was explained as the reasons for selecting the metaphors of “indicator of civilization”, “scale of the nation”, “symbol of the equality”. In conclusion, women’s empoverment through sport was the key element in this study. Women stand to gain specific social benefits from participating in sport. Parents, institutions and government should support and encourage women in all stage of the sports.
Finding Better Candidate Algorithms for Portfolio-Based Planners

In order to construct a high-performance portfolio-based planner, a diverse set of candidate algorithms is needed. In our work, we are looking at the problem of constructing such candidate sets. Below we describe the ArvandHerd planner and use it to demonstrate the importance of selecting a candidate set that uses a variety of heuristic search algorithms. We then describe ways in which candidate algorithms can be constructed when there are atypical requirements on solution quality. Finally, we describe future work into building new candidate algorithms for the inclusion in portfolios.
PhonePaint : Using Smartphones as Dynamic Brushes with Interactive Displays

Copyright is held by the author/owner(s). Abstract We present PhonePaint, a novel technique that allows users to sketch on interactive displays using a smartphone as a configurable paintbrush. PhonePaint provides a casual and ubiquitous painting experience that is suitable for a broad audience, and offers a rich sketching interaction where the stroke parameters are dynamically controlled by the built-in sensors of the phone. We describe a proof-of-concept implementation of PhonePaint with minimal hardware added to a regular smartphone. We conducted a light-weight qualitative evaluation of the prototype. The results show that participants enjoyed the drawing process with PhonePaint and were able to create interesting visuals with minimal training.
Data selection and model combination in connectionist speech recognition

The hybrid connectionist-hidden Markov model (HMM) approach to large vocabulary continuous speech recognition has been shown to be competitive with HMM based systems. However, the recent availability of extremely large amounts of acoustic training data has highlighted a problem with the connectionist acoustic modelling paradigm. The effective use of such large amounts of data is difficult due to the computational requirements of training large connectionist models. This dissertation details research aimed at increasing the performance of connectionist acoustic models through the effective use of available training data. The methods investigated are based on ensembles of models. An ensemble is a collection of models which are combined in a manner such that the performance of the ensemble is greater than that of any of the models which form the ensemble. Most ensemble methods use a simple linear combination of the model estimates to form the ensemble estimate. A data dependent ensemble technique has been developed in which the combination of the ensemble models is dependent on the current input. The use of ensembles for speaker adaptation has been investigated, and a method based on clustering of training data has been developed and implemented. This speaker adaptation scheme does not require additional adaptation data, and can reduce the error rate of a hybrid connectionist-HMM speaker independent recognition system by up to 14.5%. In addition, clustering allows effective use of large amounts of training data. Boosting is a method which makes selective use of training data, and produces an ensemble with each model trained on data drawn from a different distribution. Results on the optical character recognition task suggest that boosting can provide considerable gains in classification performance. The application of boosting to acoustic modelling has been investigated, and a modified boosting procedure developed. The boosting algorithms have been applied to multilayer perceptron acoustic models, and performance of the models assessed on a number of ARPA benchmark tasks. The results show that boosting consistently provides a 14–19% reduction in word error rate. The standard boosting techniques are not suitable for use with recurrent network acoustic models, and three new boosting algorithms have been developed for use with connectionist models with internal memory. These new boosting algorithms have also been evaluated on a number of ARPA benchmark tasks, and have been shown to lead to a reduction in word error rate of 10-18%. ii Acknowledgements There are many of my colleagues in the Speech, …
Row-Buffer Reorganization: Simultaneously Improving Performance and Reducing Energy in DRAMs

In this paper, based on the temporal and spatial locality characteristics of memory accesses in multicores, we propose a re-organization of the existing single large row buffer in a DRAM bank into multiple smaller row-buffers. The proposed configuration helps improve the row hit rates and also brings down the energy required for row-activations. The major contribution of this work is proposing such a reorganization without requiring any significant changes to the existing widely accepted DRAM specifications. Our proposed reorganization improves performance by 35.8%, 14.5% and 21.6% in quad, eight and sixteen core workloads along with a 42%, 28% and 31% reduction in DRAM energy. Additionally, we introduce a Need Based Allocation scheme for buffer management that shows additional performance improvement.
Statistically-based Model for Computer-Aided Transcription Application

The recent implementation of bilingualism in the Common Law system in Hong Kong h as brought about an urgent need to develop a Computer-Aided Transcription (CAT) system to efficiently produce verbatim records of court proceedings conducted in Cantonese Chinese. The Cantonese Chinese CAT system essentially converts phonologically-based shorthand code, or stenograph code, into o rthographic representation in Chinese characters. One big challenge in our development of a Cantonese Chinese CAT system is the ambiguity resolution for homophonous Chinese characters that share identical stenograph code. To solve the problem, the bigram model is used as the language model. We implemented the Viterbi algorithm to efficiently compute the most l ikely Chinese character string for each sequence of stenograph code input. The CAT system is trained with a 0.85 million character corpus. By incorporating enhancement features such as earmarked treatment of numerals, special encoding and d omain-specific transcription, the Cantonese Chinese CAT system achieves as much as 96% transcription accuracy.