Miracle-dz/UniFAR-FTUs huggingface dataset:
Prime–Boost with Mycobacterium smegmatis Recombinant Vaccine Improves Protection in Mice Infected with Mycobacterium tuberculosis

The development of a new vaccine as a substitute for Bacillus Calmette–Guerin or to improve its efficacy is one of the many World Health Organization goals to control tuberculosis. Mycobacterial vectors have been used successfully in the development of vaccines against tuberculosis. To enhance the potential utility of Mycobacterium smegmatis as a vaccine, it was transformed with a recombinant plasmid containing the partial sequences of the genes Ag85c, MPT51, and HspX (CMX) from M. tuberculosis. The newly generated recombinant strain mc2-CMX was tested in a murine model of infection. The recombinant vaccine induced specific IgG1 or IgG2a responses to CMX. CD4+ and CD8+ T cells from the lungs and spleen responded ex vivo to CMX, producing IFN-γ, IL17, TNF-α, and IL2. The vaccine thus induced a significant immune response in mice. Mice vaccinated with mc2-CMX and challenged with M. tuberculosis showed better protection than mice immunized with wild-type M. smegmatis or BCG. To increase the safety and immunogenicity of the CMX antigens, we used a recombinant strain of M. smegmatis, IKE (immune killing evasion), to express CMX. The recombinant vaccine IKE-CMX induced a better protective response than mc2-CMX. The data presented here suggest that the expression of CMX antigens improves the immune response and the protection induced in mice when M. smegmatis is used as vaccine against tuberculosis.
Growth Mindset and Persistence in Children's Creative Performance

Motivation literature regarding children’s academic achievement is quite extensive and can typically be separated into two mindsets: growth mindset and fixed mindset, which vary on their level of persistence (i.e., effort toward a task, Dweck, 2006). Individuals with a growth mindset find persistence is useful because they believe their abilities can change through hard work. Individuals with a fixed mindset find persistence is not useful because they believe their abilities cannot change with hard work. In the domain of creative achievement there is a lack of research on mindset and persistence during creative performance. Research shows that adults underestimate the value of persisting in their own creative performance (Lucas & Nordgren, 2015). However, this has not been examined in conjunction with mindset or in a younger sample. The aim of this study was to determine if children also show this underestimation of persistence and if children who are more growth minded will value persistence during their own creative performance. Children of all age groups undervalued their persistence in a creativity task, but children who were more creative did a better job in estimating their persistence. Mindset was not related to children’s value of persistence for their own creative performance, nor did mindset interact with age. These results suggest children are doubtful of persistence as a valuable strategy in their own creative performance for creative achievement.
Two Sustainable and Compliant Robots for Humanitarian Demining

This article, presents two robots developed by IntRoSys, S. A. Poseidon, is a walking robot capable of scanning a large area encompassed by itself with a set of landmine detection sensors. The 3 by 3 m free area encompassed by the structure, plus the wide and accurate mobility of the payload sensors, makes this solution a remarkably useful tool for accurate sensor fusion and consequently for demining, being ideal for open fields. Ares, is a high manoeuvrability, low-cost, and lightweight wheeled robot, suitable for all-terrain environments. Ares carries small and low-cost landmine detection sensors, being targeted for area reduction. The control systems developed for each robot are overviewed. An all-terrain reactive navigation method is revisited for the Ares robot. Some methods for legged robot control systems are discussed and analysed in terms of their applicability in the Poseidon robot.
Inflammation of the brain in Alzheimer's disease: implications for therapy

We briefly describe the similarities and differences between a systemic and a local immune reaction and review the evidence that the latter occurs in Alzheimer's disease (AD) brains. The evidence comes mainly from studies on the complement system, microglia, and cytokines, all of which are important actors in the inflammatory process. The evidence is now overwhelming that the complement proteins and many of the mediators of inflammation are produced locally by brain cells. We will mention briefly the many epidemiological studies indicating that the use of anti‐inflammatory drugs reduces the incidence and slows the progress of AD. Mention will also be made of some recent work on animal models of possible relevance to AD and inflammation. J. Leukoc. Biol. 65: 409–415; 1999.
BR-Tree: A Scalable Prototype for Supporting Multiple Queries of Multidimensional Data

Multidimensional data indexing has received much research attention recently in a centralized system. However, it remains a nascent area of research in providing an integrated structure for multiple queries on multidimensional data in a distributed environment. In this paper, we propose a new data structure, called BR-tree (Bloom-filter-based R-tree), and implement such a prototype in the context of a distributed system. The node in a BR-tree, viewed as an expansion from the traditional R-tree node structure, incorporates space-efficient Bloom filters to facilitate fast membership queries. The proposed BR-tree can simultaneously support not only existing point and range queries, but also cover and bound queries that can potentially benefit various data indexing services. Compared with previous data structures, BR-tree achieves space efficiency and provides quick response (lesO(log n)) on these four types of queries. Our extensive experiments in a distributed environment further validate the practicality and efficiency of the proposed BR-tree structure.
Mammalian Sir2 Homolog SIRT3 Regulates Global Mitochondrial Lysine Acetylation

ABSTRACT Homologs of the Saccharomyces cerevisiae Sir2 protein, sirtuins, promote longevity in many organisms. Studies of the sirtuin SIRT3 have so far been limited to cell culture systems. Here, we investigate the localization and function of SIRT3 in vivo. We show that endogenous mouse SIRT3 is a soluble mitochondrial protein. To address the function and relevance of SIRT3 in the regulation of energy metabolism, we generated and phenotypically characterized SIRT3 knockout mice. SIRT3-deficient animals exhibit striking mitochondrial protein hyperacetylation, suggesting that SIRT3 is a major mitochondrial deacetylase. In contrast, no mitochondrial hyperacetylation was detectable in mice lacking the two other mitochondrial sirtuins, SIRT4 and SIRT5. Surprisingly, despite this biochemical phenotype, SIRT3-deficient mice are metabolically unremarkable under basal conditions and show normal adaptive thermogenesis, a process previously suggested to involve SIRT3. Overall, our results extend the recent finding of lysine acetylation of mitochondrial proteins and demonstrate that SIRT3 has evolved to control reversible lysine acetylation in this organelle.
Excitation of the 3.071 mm Hyperfine Line in Li-like 57Fe in Astrophysical Plasmas

As noted first by Sunyaev & Churazov, the 3.071 mm hyperfine line from 57Fe+23 might be observable in astrophysical plasmas. We assess the atomic processes that might contribute to the excitation of this line. The distorted wave approximation was used to compute the direct electron collision strength between the two hyperfine sublevels of the ground configuration; it was found to be small. Proton collisional excitation was calculated and found to be negligible. We determine the rate of line excitation by electron collisional excitation of more highly excited levels, followed by radiative cascades. The branching ratios for hyperfine sublevels for allowed radiative decays and electron collisional excitation or deexcitation are derived. We show that the dominant line excitation process is electron collisional excitation of the 2p levels followed by radiative decay, as first suggested by Sunyaev & Churazov. We calculate an effective collision strength for excitation of the hyperfine line, including all of these effects and correcting for resonances. Because the hyperfine line is near the peak in the cosmic microwave background radiation spectrum, induced radiative processes are also very important. The effect of background radiation on the level populations and line excitation is determined. We determine the intensity of the hyperfine line from an isothermal, coronal plasma in collisional ionization equilibrium. Because of the variation in the ionization fraction of Fe+23, the emissivity peaks at a temperature of about 1.8 × 107 K. We have also derived the hyperfine line luminosity emitted by a coronal plasma cooling isobarically by its own radiation. Comparisons of the hyperfine line to other lines emitted by the same ion, Fe+23, are shown to be useful for deriving the isotopic fraction of 57Fe. We calculate the ratios of the hyperfine line to the 2s-2p EUV lines at 192 Å and 255 Å and the 2s-3p X-ray doublet at 10.6 Å.
An Optimal Competitive Strategy for Looking Around a Corner

We consider a problem of motion planning under uncertainty. A robot can navigate freely in the plane and, using a built-in vision system, can determine distances and angles. Initially, the robot stands at a point close to a an edge of a polygonal obstacle (e. g. a wall of a huge building) and faces a corner at distance 1 from its position. The other wall which forms the corner is invisible from the starting position and the robot does not know the angle of the corner. The task of the robot is to move on a short path to a point where that wall becomes visible. We show that there is a competitive strategy which guarantees that, for any possible value of the angle, the length of the path the robot walks until it can look around the corner is bounded by the length of the shortest path to do so, times the constant c ≈ 1.21218. Furthermore, we prove that our strategy is optimal in that no smaller competitive factor than c can be achieved. We give a simple formula for the robot to find the optimal path. A more general problem arises if the robot's starting point is not required to lie directly at the visible wall. We provide optimal competitive strategies for all such cases; the competitive factor varies between 1 and c, depending on the angle between the visible wall and the line through the starting point and the corner.
A Study on Seamless Information Sharing between Robots in Identifying the Optimal Path : An Agent based Approach

Developing a concrete agent based architecture model through a heterogeneous agents and designing the best possible lane for a autonomous mobile robots are one of the key area, which gains much attention to the researchers in this field. This paper aim’s the study on behavioural aspects, navigational and optimal path analysis of an autonomous mobile robot, based on agent based system. The key objective of this paper is to find a suboptimal lane for an autonomous mobile robot using master-subordinate architecture in a known environment based on agents. The sub-optimal lane is determined by a heuristics approach, called A Star (A*) algorithm. The communication control between a robot and its server will be accomplished based on the defined open agent architecture, which will be treated as a master-subordinate architecture. The robots used to communicate with its server to update the optimized path details, required to achieve its target position, in an optimized way. The system evaluation was done using a graphical user interface (GUI) based test-bed environment for robots, called MobileSim and the efficiency of the system was measured, via the simulation results.
Performance analysis of eigenvalue-based sensing algorithm with Monte-Carlo threshold

Eigenvalue-based spectrum sensing algorithms, such as the maximum-minimum eigenvalue (MME) algorithm and the Marčhenko-Pastur (MP) law based algorithm, are based on the asymptotic behavior of large random matrices and have very high sensing performance with an appropriate threshold. The advantage of such algorithms is that they can work very well without the estimation of noise variance, and this feature is very attractive for practical applications because of the hardness of obtaining an exact noise variance. In practical applications, threshold-setting is the key problem of such algorithms and it is important to find a simple and efficient way to make it work well with any specific dimensions (i.e. the sizes of samples and transceivers). In this paper, a Monte-Carlo threshold is provided, which shows how eigenvalue-based spectrum sensing algorithm can work well with the new threshold for any specific dimensions. Performance analysis over the E-UTRA channel model in 3GPP LTE demonstrate that, compared with the original MME detection and the MP-law-based detection, as well as the classical energy detection, the improved scheme with Monte-Carlo threshold offers superior detection performance.
OCMiner for Patents . Extracting Chemical Information from Patent Texts

This paper describes OCMiner, a high-performance semantic text processing system for large document collections of scientific publications, and its performance regarding chemical named entity recognition in patent texts within the BioCreative V CHEMDNER-Patents challenge which was set up for this purpose. OCMiner permits adjusting the quality of annotation results by several linguistic options, which can be specialized and fine-tuned for the recognition of chemical and other Life Science terms. Recognized terms are mapped to semantic concepts which are ontologically located within their respective domain taxonomies. If possible, a chemical structure is assigned to chemical compound expression. Annotated document collections, among them US patent applications and grants, can be visualized on a web-based front-end at http://www.ocminer. com/.
Improving clustering of gene expression using functional annotations

Motivation: Biologists active in the field of functional genomics try to find genes that share the same biological properties by means of their mRNA expression. Clustering of genes solely based on measured expression data has proven itself to be useful to direct further research. However, this approach does not always provide grouping of genes when one looks at their biological properties. Combining biological knowledge into the clustering algorithm might solve this problem. Results: We present a vector-based approach of measuring the dissimilarity between genes using the Gene Ontology. This approach uses the GO structure to weigh the GO terms. The weighted GO annotations of a gene are represented as a vector. This allows to compare functional annotations of two genes by calculating vector similarities. This new method is compared to two other methods derived from semantic similarities defined on semantic nets (one also introduced within this paper). Results on clustering genes from different pathways using only their GO annotations showed clear improvements of the proposed vector-based method with respect to the alternative methods. In addition to only clustering genes based on their GO annotations, we also propose a hierarchical clustering based on a combination of GO annotations with measured gene activities (mRNA expressions). This novel combined clustering approach is compared to clusterings based on expert partitionings. Remarkably, the agreement between experts was only moderate. On the other hand, the proposed clustering approach improved clustering based on solely expression data slightly and matched the experts.
LOTTERY SCHEDULING IN THE LINUX KERNEL: A CLOSER LOOK

This paper presents an implementation of a lottery scheduler, presented from design through debugging to performance testing. Desirable characteristics of a general purpose scheduler include low overhead, good overall system performance for a variety of process types, and fair scheduling behavior. Testing is performed, along with an analysis of the results measuring the lottery scheduler against these characteristics. Lottery scheduling is found to provide better than average control over the relative execution rates of processes. The results show that lottery scheduling functions as a good mechanism for sharing the CPU fairly between users that are competing for the resource. While the lottery scheduler proves to have several interesting properties, overall system performance suffers and does not compare favorably with the balanced performance afforded by the standard Linux kernel's scheduler. 11. Using /bin/cat to generate additional CPU load resulted in faster compile times for lottery schedulers; pointing to the lottery scheduler's inability to spawn processes as quickly as the standard Linux kernel. 75 12. Generating additional load with the sh built-in read command results in performance similar to the benchmark with user-mode CPU load. 77 vii LIST OF FIGURES Figure Page 1. Base tickets control global CPU resource rights while process tickets are used to define local resource management policy. Equal base ticket allocations mean that users Fred and John have equal CPU resource rights regardless of process ticket allocation. Process ticket allocation regulating the execution rates of each process relative to others in the same domain, is policy specific to each user that has no effect on overall CPU resource rights. 2. A winning process will be selected from this queue of runnable processes that have had their process tickets scaled into base tickets. The random number selected for this single lottery instance will be between 1 and 400. Only runnable processes are considered in each lottery. viii 20. Two CPU bound processes with a 3 to 1 lottery ticket allocation.
A new technique for high speed decimal logarithm computation of decimal floating-point number

This paper presents a new design and a fast technique for implementation of a 32-bit decimal floating-point (DFP) logarithmic computation to efficiently calculate radix-10 logarithm of a decimal number. Conventional techniques first convert decimal inputs to binary, then perform base-2 logarithm operations, and finally results are converted back to decimal radix. It sometimes causes errors due to the back and forth conversions of the bases. The technique described in this paper uses a 32-bit floating-point arithmetic, and utilizes only addition and subtraction operations. It does not require any decimal to binary conversion, or division operation. As a result, the described algorithm offers a low-cost, hardware-efficient and lower power consumption method for computing decimal floating-point numbers.
A conserved role for the MEK signalling pathway in neural tissue specification and posteriorisation in the invertebrate chordate, the ascidian Ciona intestinalis

Ascidians are invertebrate chordates with a larval body plan similar to that of vertebrates. The ascidian larval CNS is divided along the anteroposterior axis into sensory vesicle, neck, visceral ganglion and tail nerve cord. The anterior part of the sensory vesicle comes from the a-line animal blastomeres, whereas the remaining CNS is largely derived from the A-line vegetal blastomeres. We have analysed the role of the Ras/MEK/ERK signalling pathway in the formation of the larval CNS in the ascidian, Ciona intestinalis. We show evidence that this pathway is required, during the cleavage stages, for the acquisition of: (1) neural fates in otherwise epidermal cells (in a-line cells); and (2) the posterior identity of tail nerve cord precursors that otherwise adopt a more anterior neural character (in A-line cells). Altogether, the MEK signalling pathway appears to play evolutionary conserved roles in these processes in ascidians and vertebrates, suggesting that this may represent an ancestral chordate strategy.
PLANNING FOR THE RANGER TELEROBOTIC SHUTTLE EXPERIMENT ON-ORBIT OPERATIONS

The Ranger Telerobotic Shuttle Experiment is a Space Shuttle based flight experiment to demonstrate on-orbit telerobotic servicing technologies. Ranger will perform a number of activities varying from simple to complex. A task board for calibration and evaluation of basic robotic operations will be the focus of early operations. Extraction and insertion of a robot compatible orbit replaceable unit (ORU) representative of International Space Station ORUs will be performed. As a science focus, numerous repetitions of this task will be executed using different operators, time delays, operator environments, and control station configurations. Demonstration tasks will include change out of a Hubble Space Telescope style ORU and setup of a complex Articulating Portable Foot Restraint. The project is preparing for a launch opportunity in early 2002. The progress of the hardware and software for the flight vehicle and a neutral buoyancy simulator will be discussed as well as the plan for demonstrating the tasks on-orbit and rehearsing them on the ground in a neutral buoyancy environment.
The Big Five personality predictors of academic achievement in gifted students: Mediation by self-regulatory efficacy and academic motivation

ABSTRACT Understanding factors associated with achievement and mechanisms underlying their relationships is critical for planning interventions and services to improve students’ performance and meet their needs. In the present study, the authors examined the predictive role of three Big Five personality traits (conscientiousness, agreeableness, and openness to experience) on academic achievement within the sample of gifted students. Self-regulatory efficacy and autonomous and controlled types of motivation served as mediators in these relationships. Data were collected from 161 gifted middle and high school students. All three personality traits had direct associations with academic achievement. The indirect associations through specific pathways were estimated. Conscientiousness was mediated by self-regulatory efficacy and autonomous motivation, whereas openness was mediated by controlled motivation and autonomous motivation.
Vascular Normalization by Vascular Endothelial Growth Factor Receptor 2 Blockade Induces a Pressure Gradient Across the Vasculature and Improves Drug Penetration in Tumors

Elevated interstitial fluid pressure, a hallmark of solid tumors, can compromise the delivery of therapeutics to tumors. Here we show that blocking vascular endothelial growth factor (VEGF) signaling by DC101 (a VEGF-receptor-2 antibody) decreases interstitial fluid pressure, not by restoring lymphatic function, but by producing a morphologically and functionally “normalized” vascular network. We demonstrate that the normalization process prunes immature vessels and improves the integrity and function of the remaining vasculature by enhancing the perivascular cell and basement membrane coverage. We also show that DC101 induces a hydrostatic pressure gradient across the vascular wall, which leads to a deeper penetration of molecules into tumors. Thus, vascular normalization may contribute to the improved survival rates in tumor-bearing animals and in colorectal carcinoma patients treated with an anti-VEGF antibody in combination with cytotoxic therapies.
LDCnet: Minimizing the cost of supervision for various types of concept drift

Supervision cost is often overlooked when designing decision systems to cope with concept drift. The solution presented in this article utilizes low supervision while achieving similar efficiency to the state-of-the-art methods. Algorithm bases on a net of classification models which cover the whole feature space, preparing the system for every possible concept. The experiments are performed in the simulated environment with four scenarios representing different types of concept drift.