Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of a vraG Mutant in a Genetically Stable Staphylococcus aureus Small-Colony Variant and Preliminary Assessment for Use as a Live-Attenuated Vaccine against Intrammamary Infections

Staphylococcus aureus is a leading cause of bovine intramammary infections (IMIs) that can evolve into difficult-to-treat chronic mastitis. To date, no vaccine formulation has shown high protective efficacy against S. aureus IMI, partly because this bacterium can efficiently evade the immune system. For instance, S. aureus small colony variants (SCVs) have intracellular abilities and can persist without producing invasive infections. As a first step towards the development of a live vaccine, this study describes the elaboration of a novel attenuated mutant of S. aureus taking advantage of the SCV phenotype. A genetically stable SCV was created through the deletion of the hemB gene, impairing its ability to adapt and revert to the invasive phenotype. Further attenuation was obtained through inactivation of gene vraG (SACOL0720) which we previously showed to be important for full virulence during bovine IMIs. After infection of bovine mammary epithelial cells (MAC-T), the double mutant (ΔvraGΔhemB) was less internalized and caused less cell destruction than that seen with ΔhemB and ΔvraG, respectively. In a murine IMI model, the ΔvraGΔhemB mutant was strongly attenuated, with a reduction of viable counts of up to 5-log10 CFU/g of mammary gland when compared to the parental strain. A complete clearance of ΔvraGΔhemB from glands was observed whereas mortality rapidly (48h) occurred with the wild-type strain. Immunization of mice using subcutaneous injections of live ΔvraGΔhemB raised a strong immune response as judged by the high total IgG titers measured against bacterial cell extracts and by the high IgG2a/IgG1 ratio observed against the IsdH protein. Also, ΔvraGΔhemB had sufficient common features with bovine mastitis strains so that the antibody response also strongly recognized strains from a variety of mastitis associated spa types. This double mutant could serve as a live-attenuated component in vaccines to improve cell-mediated immune responses against S. aureus IMIs.
RECOGNITION SYSTEM BASED ON NEURAL NETWORK Neeta

In this paper, we have proposed a novel approach for handwriting recognition system involving segmentation for preprocessing steps and using diagonal based feature extraction technique with neutral network for character recognition. Input is paragraphs of running text, which is preprocessed to segment it into normalized individual words. Further, a diagonal based feature extraction technique is used for extracting the features of handwritten alphabets. A neural network is trained onto the dataset containing 55 samples for each of the 26 alphabets for recognition. A new implicit approach for character recognition is implemented in this paper which segments a character, into parts dynamically for character recognition from the text, which improves the accuracy significantly. A feed forward artificial neural network is being used for character classification, which also helps in deciding the threshold value for the character separation from the running text word. The proposed recognition system performs excellently for separate character written documents with 100% accuracy. It also performs competitively yielding an accuracy of 75% for readable non-cursive handwriting and 60% for cursive handwriting.
Where is home? The lived experiences of Chinese children after their parents have been incarcerated

ABSTRACT This study conducted in-depth interviews to explore the lived experiences of 17 Chinese children with incarcerated parents. These children were under the care of a charitable agency at the time of interview. Narratives of the children revealed a drifting journey that began with ‘feeling like an orphan’, helplessness and abandonment, then progressed to ambivalent dependence on the extended family as ‘extra burdens’, and finally reached to the destination of ‘lucky settlement’ in the charitable agency filled with complex feelings of uncertainty, gratitude and relief. This journey was situated in a cultural context with heavy reliance on informal support and family responsibilities, minimal role of government in child safety and protection, and lack of formal child welfare services. Implications for child welfare practice and policy in China, particularly as related to the well-being of children with incarcerated parents, included supporting the growth of charitable organisations, developing residential care programmes, and establishing a comprehensive formal support system with timely provision of services immediately after the parent is arrested.
Aspect Extraction from Product Reviews Using Category Hierarchy Information

Aspect extraction abstracts the common properties of objects from corpora discussing them, such as reviews of products. Recent work on aspect extraction is leveraging the hierarchical relationship between products and their categories. However, such effort focuses on the aspects of child categories but ignores those from parent categories. Hence, we propose an LDA-based generative topic model inducing the two-layer categorical information (CAT-LDA), to balance the aspects of both a parent category and its child categories. Our hypothesis is that child categories inherit aspects from parent categories, controlled by the hierarchy between them. Experimental results on 5 categories of Amazon.com products show that both common aspects of parent category and the individual aspects of sub-categories can be extracted to align well with the common sense. We further evaluate the manually extracted aspects of 16 products, resulting in an average hit rate of 79.10%.
Efficient On-line Fault Diagnosis for Non-Linear Systems

Fault diagnosis is a critical task for autonomous operation of systems such as spacecraft and planetary rovers, and must often be performed on-board. Unfortunately, these systems frequently also have relatively little computational power to devote to diagnosis. For this reason, algorithms for these applications must be extremely efficient, and preferably anytime. In this paper we introduce the Gaussian particle filter (GPF), an efficient variant on the particle filtering algorithm for non-linear hybrid systems. Each particle samples a discrete mode and approximates the continuous variables by a multivariate Gaussian that is updated at each time-step using an unscented Kalman filter. The algorithm is closely related to Rao-Blackwellized Particle Filtering and equally efficient, but is more broadly applicable. We show that given the same computation time GPF performs diagnosis with a significantly lower rate of incorrect diagnoses and with a much lower error on the continuous parameters. We also use the GPF to diagnose data from the K-9 rover at NASA Ames Research Center.
Discovery and Observations of Two Tree Nests of the Marbled Murrelet

Two nests of the Marbled Murrelet (Brachyramphus marmoratus) were found in old-growth (300 + years) Douglas-fir (Pseudotsuga menziesii) trees in Big Basin Redwoods State Park, Santa Cruz County, California. These were the third and fourth known North American tree nests, and the first to be found by searching from the ground without the use of radio-telemetry. Ground-search techniques for finding nests are presented. Both nests were in the incubation stage when found. Each was observed from a distance for 15 days and 34 days, respectively. Incubation shifts lasted 24 hr with the adults exchanging duties at dawn. Flight behavior near the nest is described. Corvid predation caused both nests to fail, and may be a problem where murrelets nest in areas of high human usage. After nest failure, each tree was climbed. Both nests were located in the inner canopy, mid-crown portion of the trees. Nest branches were large, moss-covered, horizontal branches that were well shaded. One nest was a previously undescribed type of constructed nest made up of small Douglas-fir twigs and foliose lichens. The other nest was a natural depression in a moss-covered limb. Eggshell fragments were similar to previously described eggs. Nest site characteristics are compared to characteristics of the other known Marbled Murrelet tree
Price transmission dynamics between informationally linked securities

The paper examines whether location of trade matters in the pricing of internationally listed securities by examining the price dynamics of stocks listed on the Greek and the two German stock exchanges, Frankfurt and Berlin. Through the investigation of the various possibilities of short-run and long-run arbitrage profits it is found that the prices of stocks in the German markets are priced with reference to the Greek market, implying that the location of trade does not matter and that there is a certain degree of market integration. In contrast, it is found that the price discovery process takes place in the German markets, although most of the trading volume is concentrated in the Greek market.
Response of vegetation to temperature, precipitation and solar radiation time-scales: A case study over mainland Australia

Climate conditions have important influences on vegetation growth and there are also effects of temporal lags of plants growth to climate factors. This paper is based on GIMMS-NDVI (Normalized Difference Vegetation Index) and CRU (Climate Research Unit) climate datasets to analyze the relationship between vegetation and climate factors (temperature, precipitation and solar radiation). Results show that Western Australia responds to climate factors at long time-scales, however, Eastern Australia at short time-scales (with mean value of 6.6 months in totally areas). Moreover, vegetation growth in Australia's coastal areas is mainly influenced by solar radiation, while precipitation and solar radiation jointly play important roles in central Australia.
UCov: a user‐defined coverage criterion for test case intent verification

The goal of regression testing is to ensure that the behaviour of existing code, believed correct by previous testing, is not altered by new program changes. This paper argues that the primary focus of regression testing should be on code associated with (1) earlier bug fixes and (2) particular application scenarios considered to be important by the developer or tester. Existing coverage criteria do not enable such focus, for example, 100% branch coverage does not guarantee that a given bug fix is exercised or a given application scenario is tested. Therefore, there is a need for a new and complementary coverage criterion in which the user can definea test requirement characterizing a given behaviour to be covered as opposed to choosing from a pool of pre‐defined and generic program elements. This paper proposes this new methodology and calls it UCov, a user‐defined coverage criterion wherein a test requirement is an execution pattern of program elements, and possibly predicates, that a test case must satisfy. The proposed criterion is not meant to replace existing criteria, but to complement them as it focuses the testing on important code patterns that could go untested otherwise. UCov supports test case intent verification. For example, following a bug fix, the testing team may augment the regression suite with the test case that revealed the bug. However, this test case might become obsolete due to code modifications not related to the bug. But if a test requirement characterizing the bug was defined by the user, UCov would determine that test case intent verification failed. The UCov methodology was implemented for the Java platform, was successfully applied onto 10 real‐life case studies and was shown to have advantages over JUnit. The implementation comprises the following tools: (1) TRSpec: allows the user to easily specify complex test requirements; (2) TRCheck: checks whether user‐defined test requirements were satisfied, that is, supports test case intent verification; and (3) TRMigrate: migrates user‐defined test requirements to subsequent versions of a given program. Copyright © 2016 John Wiley & Sons, Ltd.
Securing ARP in Software Defined Networks

The mapping of Layer 3 (IP) to Layer 2 (MAC) addresses is a key service in IP networks, and is achieved via the ARP protocol in IPv4, and the NDP protocol in IPv6. Due to their stateless nature and lack of authentication, both ARP and NDP are vulnerable to spoofing attacks, which can enable Denial of Service (DoS) or man-in-the-middle (MITM) attacks. In this paper, we discuss the problem of ARP spoofing in the context of Software Defined Networks (SDNs), and present a new mitigation approach which leverages the centralised network control of SDN.
TRAUCO, a Trithorax-group gene homologue, is required for early embryogenesis in Arabidopsis thaliana

Embryogenesis is a critical stage during the plant life cycle in which a unicellular zygote develops into a multicellular organism. Co-ordinated gene expression is thus necessary for proper embryo development. Polycomb and Trithorax group genes are members of evolutionarily conserved machinery that maintains the correct expression patterns of key developmental regulators by repressing and activating gene transcription. TRAUCO (TRO), a gene homologous to the Trithorax group of genes that can functionally complement a BRE2P yeast mutant, has been identified in Arabidopsis thaliana. It is demonstrated that TRO is a nuclear gene product expressed during embryogenesis, and loss of TRO function leads to impaired early embryo development. Embryos that arrested at the globular stage in the tro-1 mutant allele were fully rescued by a TRO expression clone, a demonstration that the tro-1 mutation is a true loss-of-function in TRO. Our data have established that TRO is the first trithorax-group gene homologue in plants that is required for early embryogenesis.
Modelling for Hardware and Software Partitioning Based on Multiple Properties

In many embedded systems types the separation process for deploying the applications as software and hardware executable units, called partitioning is crucial. This is due to the fact that partitioning decisions impact the overall life cycle of the systems. In industry it is common practice to take partitioning decisions in an early stage of the design, based on hardware and software designers expertise. We propose a new methodology as a combination of model based and component-based approaches which enables a late partitioning decisions based on high level system requirements and project constrains. The final partitioning is decided based on a multi-property analysis approach. Here, we focus on the formalization of the overall process and in particular on the definition of a comprehensive system metamodel. This is meant to support modelling approaches suitable for enabling both the partitioning and reuse. An industrial case study is used to illustrate the approach.
Measurement of surface orientations of transparent objects by use of polarization in highlight

A method is proposed for obtaining surface orientations of transparent objects by use of polarization in highlight. Since the highlight, the specular component of light reflected from objects, is observed only near the specular direction, it reveals only limited parts of an object’s surface. To obtain the orientations of the whole surface of an object, we employ a spherical extended light source. We report the experimental apparatus, a shape recovery algorithm, and a performance evaluation.
Stochastic dynamical systems in neuroscience

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Stochastic dynamical systems in neuroscience Nils Berglund
Super-Resolution of Face Images Using Kernel PCA-Based Prior

We present a learning-based method to super-resolve face images using a kernel principal component analysis-based prior model. A prior probability is formulated based on the energy lying outside the span of principal components identified in a higher-dimensional feature space. This is used to regularize the reconstruction of the high-resolution image. We demonstrate with experiments that including higher-order correlations results in significant improvements
I’m Lost: An Evaluation of an Interactive Wayfinding System

The integration of interactive wayfinding systems, alongside traditional signage and static map displays, has become an increasing trend in hospitals. These systems are aimed at increasing convenience for visitors while lessening the burden on employees often tasked with helping visitors get to their destination. However, in order for an interactive system to be useful, it should first be usable, with a design tailored to the users’ needs, expectations and cognitive abilities. Previous research has consistently demonstrated the difficulty users often experience with these systems, hindering rather than enhancing their ability to get where they need to go. The current research assessed the usability and effectiveness of the interactive wayfinding system at a large hospital complex in Houston, Texas. We recruited 6 participants (5 females and 1 male) from the lobby of the hospital who had no prior interaction with the wayfinding kiosk. The researchers visited the hospital beforehand to review the system, and later developed 5 tasks to be performed on the system. The tasks included, basic navigation to destinations within the hospital, comprehension of orientation in the environment, accessing assistance and relevant information, utilizing the search function and navigating through the hospital based on the route and directions provided. Participants were told it was the system that was being evaluated, as opposed to their performance. The moderator administered instructions, while the other researcher observed the vocal and physical behaviors of the participants, such as asking for help out loud or utilizing signage and maps during the set of tasks. Following the tasks, participants were administered the Systems Usability Scale (Brooke, 1996), as well as a survey assessing general demographic information. There were several problems that participants consistently faced when given these various tasks, which was reflected in the low SUS score. These issues were organized as ineffective organization of information, memory overload on the user, and the inconsideration of user pace. Most importantly, there was a strong mismatch between the wayfinding system and expectations, including the absence of a help option, a lack of a “You Are Here” display, and a system orientation that did not match the real world. Research has shown that if people cannot effectively utilize systems,
Multi-robot odor source search based on Cuckoo search algorithm in ventilated indoor environment

Due to the influence of turbulence, the practical gas plume in ventilated indoor environment is fluctuant and intermittent. In this case, the problem of odor source localization is quite complicated for robots. This paper proposes a novel odor source localization strategy based on cuckoo search algorithm by a group of mobile robots. This proposed algorithm combines the upwind search and local gas concentration optimization mechanism. It utilizes a robot which detects the highest gas concentration among all robots to guide other robots to search odor source in its upwind direction. Simulation results show that the proposed strategy can coordinate multiple robots to search odor source efficiently in dynamic plume environment. Using this strategy, the robots can also escape from both local high concentration and eddy areas.
The web as a resource for WSD

Why general Word Sense Disambiguation (WSD) systems are not (to the best of our knowledge) being used in real-world applications? In our opinion, some plausible reasons are: • General Word Sense Disambiguation, as an intermediate task, is frequently harder than the final application. This is probably the case of the most commonly mentioned WSD applications: mono and multilingual Information Retrieval and Machine Translation. • Different applications demand different sense distinctions and different sense granularities. • Unsupervised systems still have poor performance. • . and supervised systems, in general, hardly have resources to be supervised with. Currently, supervised systems can only attempt an “all-words” WSD task in English, and with very scarce resources. In order to find out whether WSD systems can play a significant role in Human Language Technologies, a necessary step is to make supervised WSD algorithms applicable, finding ways of acquiring lexical information and, in particular, building training corpora at a low cost.
Prosody and the interpretation of tag questions

We provide an account of the alignment of linguistic form and discourse function with respect to English tag questions, adopting as a formal framework Segmented Discourse Representation Theory. SDRT models the discourse function of utterances via their rhetorical connection to the antecedent discourse. We pay particular attention to the prosodic features of tag questions and their contribution to interpretation. This approach to tag questions is appropriate, we argue, as the interpretation of a tag comes down to its rhetorical connection to the host sentence.
The intracellular portion of GITR enhances NGF-promoted neurite growth through an inverse modulation of Erk and NF-κB signalling

Summary NF-&kgr;B transcription factors play a key role in regulating the growth of neural processes in the developing PNS. Although several secreted proteins have been shown to activate NF-&kgr;B to inhibit the growth of developing sympathetic neurons, it is unknown how the endogenous level of NF-&kgr;B activity present in these neurons is restricted to allow neurite growth to occur during their normal development. Here we show that activation of the glucocorticoid-induced tumour necrosis factor receptor (GITR) inhibits NF-&kgr;B activation while promoting the activation of Erk in developing sympathetic neurons. Conversely, inhibition of GITR results in an increase in NF-&kgr;B dependent gene transcription and a decrease in Erk activation leading to a reduction in neurite growth. These findings show that GITR signalling can regulate the extent of sympathetic neurite growth through an inverse modulation of Erk and NF-&kgr;B signalling, which provides an optimal environment for NGF-promoted growth.
Detecting communities in topical semantic networks

With the advance of information technology, online communications between people have increased significantly. These kinds of communications have become more organized subsequent to the emergence of social networks. One of the most important issues in analyzing these kinds of networks is community detection, in which most studies detect communities through analyzing linkages of the networks. The desirable goal in this paper is to reach communities in which the members have the same topic of interest, and where the strength of connections between them is the consequence of their communications' content analysis. Therefore, we propose a new framework which considers the information that is shared by the users, and also the topics they are interested in, in order to find more meaningful communities. While similar studies have only found communities by merely considering the topological structure of the network, and some of the features of semantic information related to the users of the network, like their topics of interest, the proposed framework detects communities through considering topics, communications' content and topological structure of the network. Quantitative evaluations indicate that the proposed framework achieves promising results which are superior in comparison with the other relevant frameworks in the literature.