Miracle-dz/UniFAR-FTUs huggingface dataset:
Interactive multi-scale watershed segmentation of tumors in MR brain images

In neurosurgery, determining the position of a tumor during interventions by navigation based on preoperatively acquired (MRI) data is a common approach. In current systems that allow for navigation on preoperative data, it is assumed that no intraoperative tissue deformation occurs. However, in neurosurgical procedures, intraoperative brain deformations of 1 to 10 mm have been reported [1], making the intraoperative deformation the most important cause affecting the overall accuracy of image guided neurosurgery. Information provided by intraoperative imaging devices, which can measure the intraoperative deformation of the soft tissue, is generally less complete and less detailed. One option for solving this problem is the use of intraoperatively acquired data, e.g. ultrasound [2], to correct the preoperative images for deformations that have occurred during surgery. In order to compare tumor localization in preand intraoperative images it is necessary that the tumor is segmented in both modalities. In this paper we focus on the preoperative MR segmentation. The most common way to segment a tumor in MR images is by manual segmentation. The problem with this method is that interobserver variability can be quite large since there is no restriction in choosing the boundary of the tumor. A semi-automatic segmentation method that reduces the degrees of freedom for segmentation, while still maintaining the influence of the surgeon on the segmentation, may improve this. In this paper a semi-automatic multi-scale watershed algorithm [3,4] is evaluated for tumor segmentation in MR brain images in patients scheduled for image-guided neurosurgery, where deformation during the interventions are expected.
Brucella discriminates between mouse dendritic cell subsets upon in vitro infection

Brucella is a Gram-negative bacterium responsible for brucellosis, a worldwide re-emerging zoonosis. Brucella has been shown to infect and replicate within Granulocyte macrophage colony-stimulating factor (GMCSF) in vitro grown bone marrow-derived dendritic cells (BMDC). In this cell model, Brucella can efficiently control BMDC maturation. However, it has been shown that Brucella infection in vivo induces spleen dendritic cells (DC) migration and maturation. As DCs form a complex network composed by several subpopulations, differences observed may be due to different interactions between Brucella and DC subsets. Here, we compare Brucella interaction with several in vitro BMDC models. The present study shows that Brucella is capable of replicating in all the BMDC models tested with a high infection rate at early time points in GMCSF-IL15 DCs and Flt3l DCs. GMCSF-IL15 DCs and Flt3l DCs are more activated than the other studied DC models and consequently intracellular bacteria are not efficiently targeted to the ER replicative niche. Interestingly, GMCSF-DC and GMCSF-Flt3l DC response to infection is comparable. However, the key difference between these 2 models concerns IL10 secretion by GMCSF DCs observed at 48 h post-infection. IL10 secretion can explain the weak secretion of IL12p70 and TNFα in the GMCSF-DC model and the low level of maturation observed when compared to GMCSF-IL15 DCs and Flt3l DCs. These models provide good tools to understand how Brucella induce DC maturation in vivo and may lead to new therapeutic design using DCs as cellular vaccines capable of enhancing immune response against pathogens.
Short-Term Effect of El Niño-Southern Oscillation on Pediatric Hand, Foot and Mouth Disease in Shenzhen, China

Hand, foot and mouth disease (HFMD) was an emerging viral infectious disease in recent years in Shenzhen. The underlying risk factors have not yet been systematically examined. This study analyzed the short-term effect of El Niño-Southern Oscillation on pediatric HFMD in Shenzhen, China. Daily count of HFMD among children aged below 15 years old, Southern Oscillation Index (SOI), and weather variables were collected to construct the time series. A distributed lag non-linear model was applied to investigate the effect of daily SOI on pediatric HFMD occurrence during 2008–2010. We observed an acute effect of SOI variation on HFMD occurrence. The extremely high SOI (SOI = 45, with 0 as reference) was associated with increased HFMD, with the relative risk (RR) being 1.66 (95% Confidence Interval [CI]: 1.34–2.04). Further analyses of the association between HFMD and daily mean temperature and relative humidity supported the correlation between pediatric HFMD and SOI. Meteorological factors might be important predictors of pediatric HFMD occurrence in Shenzhen.
Policy and Party Competition

Policy and Party Competition offers both a theoretical and empirical examination of the subject. The book opens with a theoretical discussion of the nature of political parties, policies and competition. Taking the view that the preferences of the electorate are the logical and ideological starting points of party competition, Laver and Hunt examine the structure of policy preferences, patterns in party systems, parameters of party competition and the role of party policy in government formation. In the second section, they present a unique data set of 24 parliamentary democracies. Party systems analysed include those of the US, Japan, Israel, Canada, France, Britain, Germany, Australia and New Zealand. The authors determine the degree of influence cast by theories of party competition on the actual practice of such competition. This is an important exploration of the methodological issues involved in the application of spatial models of party competition to the real world.
Semi supervised regulatory module discovery

Regulatory modules are sets of co-regulated genes that carry out common functions. A large body of research exists about methods that aim to identify these modules, and this is the first step towards understanding the cellular responses to signals. Its well known that each of the current datasets e.g. microarrays, dna-binding and sequence datasets provide a partial picture of the regulation process and hence integration among them is required in order to obtain more complete picture of the biological processes involved.
Evaluation of different complexity measures for signal detection in genome sequences

Analyzing large amounts of data is one of the most challenging problem in modern molecular biology. In this work, different complexity measures and methods are applied to identify the signals in the whole genome of the three prokaryotic organisms. In addition to previous complexity measures, new measures are introduced for representing Open Reading Frames (ORF). We apply classification algorithms to determine which complexity measures can lead to better predictive performance in discriminating genes from pseudo-genes in ORFs. Also, we investigate whether positions and lengths of windows in ORFs have significant impact on distinguishing between genes and pseudo-genes. Different classification algorithms are applied for classifying ORFs into genes and pseudo-genes.
Content Based Image Retrieval (CBIR) in Remote Clinical Diagnosis and Healthcare

Content-Based Image Retrieval (CBIR) locates, retrieves and displays images alike to one given as a query, using a set of features. It demands accessible data in medical archives and from medical equipment, to infer meaning after some processing. A problem similar in some sense to the target image can aid clinicians. CBIR complements text-based retrieval and improves evidence-based diagnosis, administration, teaching, and research in healthcare. It facilitates visual/automatic diagnosis and decision-making in real-time remote consultation/screening, store-and-forward tests, home care assistance and overall patient surveillance. Metrics help comparing visual data and improve diagnostic. Specially designed architectures can benefit from the application scenario. CBIR use calls for file storage standardization, querying procedures, efficient image transmission, realistic databases, global availability, access simplicity, and Internet-based structures. This chapter recommends important and complex aspects required to handle visual content in healthcare.
MAC approaches for QoS Enhancement in Wireless LANs

José André Moura and Rui Neto Marinheiro ADETTI/ISCTE Av. das Forças Armadas, Edifício ISCTE, 1600-082 Lisboa Telefone: +351.217. 903.099, Fax: +351.217. 903.099 Abstract. Demanding for real-time multimedia applications in wireless access is increasing, and this has driven recent research in QoS. The upcoming IEEE 802.11e standard will give a firm impulse towards QoS provisioning in 802.11 wireless LANs. In parallel, during the last years, other enhanced MAC schemes have also been proposed to improve QoS metrics. Some of these approaches modify the 802.11e Backoff procedure, either by changing the way the Contention Window is determined or by changing the way the backoff timer is decreased. Supported by these previous works, we describe three new approaches. One of them is designated by Differentiated Exponential Collision Recover – DECR, which uses exponential decrease functions in the backoff timer, with different exponential decrease rate for each Access Category. Using simulation results, we conclude that DECR, when compared with other approaches, improves channel utilization without significantly increasing the collision rate.
Husimi transform of an operator product

It is shown that the series derived by Mizrahi, giving the Husimi transform (or covariant symbol) of an operator product, is absolutely convergent for a large class of operators. In particular, the generalized Liouville equation, describing the time evolution of the Husimi function, is absolutely convergent for a large class of Hamiltonians. In contrast, the series derived by Groenewold, giving the Weyl transform of an operator product, is often only asymptotic, or even undefined. The result is used to derive an alternative way of expressing expectation values in terms of the Husimi function. The advantage of this formula is that it applies in many of the cases where the anti-Husimi transform (or contravariant symbol) is so highly singular that it fails to exist as a tempered distribution.
Heterologous Prime-Boost HIV-1 Vaccination Regimens in Pre-Clinical and Clinical Trials

Currently, there are more than 30 million people infected with HIV-1 and thousands more are infected each day. Vaccination is the single most effective mechanism for prevention of viral disease, and after more than 25 years of research, one vaccine has shown somewhat encouraging results in an advanced clinical efficacy trial. A modified intent-to-treat analysis of trial results showed that infection was approximately 30% lower in the vaccine group compared to the placebo group. The vaccine was administered using a heterologous prime-boost regimen in which both target antigens and delivery vehicles were changed during the course of inoculations. Here we examine the complexity of heterologous prime-boost immunizations. We show that the use of different delivery vehicles in prime and boost inoculations can help to avert the inhibitory effects caused by vector-specific immune responses. We also show that the introduction of new antigens into boost inoculations can be advantageous, demonstrating that the effect of ‘original antigenic sin’ is not absolute. Pre-clinical and clinical studies are reviewed, including our own work with a three-vector vaccination regimen using recombinant DNA, virus (Sendai virus or vaccinia virus) and protein. Promising preliminary results suggest that the heterologous prime-boost strategy may possibly provide a foundation for the future prevention of HIV-1 infections in humans.
Technology, Ethical Responsibility, and Blameworthiness in Just War Theory: The Case of Drones

This paper addresses jus in bello challenges posed by technological advances by incorporating blameworthiness into Just War Theory. By involving more individuals with increasingly mundane contributions to the use of force, remotely operated weapons especially those with automated routines threaten to undermine the ability of individuals to adhere to the principles of jus in bello. Recent work has suggested jettisoning the framework of Just War Theory as either impractically stringent or unpalatably permissive as a framework for permissibility of action. I suggest instead incorporating the concept of blameworthiness into the Just War Tradition. Using the illustrative case of unmanned combat aerial vehicles (UCAVs), I argue that the incorporation of more parties does not change the permissibility of any given use of force, but rather has important consequences on the blameworthiness of individual actors and therefore expectations about adherence to Just War Principles. Tags: Just War, technology, drones, ethics
Fast polynomial factorization and modular composition in small characteristic

We obtain randomized algorithms for factoring degree n univariate polynomials over F_q that use O(n1.5 + o(1) + n1 + o(1)log q) field operations, when the characteristic is at most no(1). When log q < n, this is asymptotically faster than the best previous algorithms (von zur Gathen & Shoup (1992) and Kaltofen & Shoup (1998)); for log q ≥ n, it matches the asymptotic running time of the best known algorithms. The improvements come from a new algorithm for modular composition of degree n univariate polynomials, which is the asymptotic bottleneck in fast algorithms for factoring polynomials over finite fields. The best previous algorithms for modular composition use O(n(omega + 1)/2) field operations, where omega is the exponent of matrix multiplication (Brent & Kung (1978)), with a slight improvement in the exponent achieved by employing fast rectangular matrix multiplication (Huang & Pan (1997)). We show that modular composition and multipoint evaluation of multivariate polynomials are essentially equivalent in the sense that an algorithm for one achieving exponent α implies an algorithm for the other with exponent α + o(1), and vice versa. We then give a new algorithm that requires O(n1 + o(1)) field operations when the characteristic is at most no(1), which is optimal up to lower order terms. Our algorithms do not rely on fast matrix multiplication, in contrast to all previous subquadratic algorithms for these problems. The main operations are fast univariate polynomial arithmetic, multipoint evaluation, and interpolation, and consequently the algorithms could be feasible in practice.
Position verification of a mobile robot using standard pattern

As mobile robots are taking on more and more of the tasks that were normally delegated to humans, they need to acquire higher degrees of autonomous operation, which calls for accurate and efficient position determination and/or verification. The critical geometric dimensions of a standard pattern are used here to locate the relative position of the mobile robot with respect to the pattern; by doing so, the method does not depend on values of any intrinsic camera parameters, except the focal length. In addition, this method has the advantages of simplicity and flexibility. This standard pattern is also provided with a unique identification code, using bar codes, that enables the system to find the absolute location of the pattern. These bar codes also assist in the scanning algorithms to locate the pattern in the environment. A thorough error analysis and experimental results obtained through software simulation are presented, as well as the current direction of our work.
Significance of learner dependent features for improving text readability using extractive summarization

Information and Communication Technologies play major role in all types of day to day life activities including Government, public and social domains. The need for HCI aspects to be taken care in these activities has become a predominant one. Especially, incorporating HCI features in the academic environment is getting more attention. In the case of reading materials associated with any type of academic process or content delivery, much focus is to be given so that even people with learning difficulties can get the information to his/her level of ability. Though lot of information is available in the academic scenario in the forms of text books, course ware, on line resources, web documents etc., not all content is readable by all. Tools and technologies must be made available to help people with learning difficulties including dyslexics. The idea is to reduce the burden levels of the learners with the help of assistive technologies. In this direction, this paper focuses on highlighting the importance of various features to be considered for making the text readable by all, using summarization techniques. Text summarization based on both document level and learner level features are discussed for making the content readable for people with learning difficulties. The experiments show that learner dependent features improve the readability of the text through summary as preview of the text.
Frequency Decomposition of Astrometric Signature of Planetary Systems

We present a theoretical analysis of astrometric searches for extrasolar planets with the Space Interferometry Mission (SIM). In particular, we derive a model for future measurements with SIM and discuss the problem of reliable estimation of orbital elements of planets. For this purpose we propose a new method of data analysis and present a numerical test of its application to simulated SIM astrometric measurements of the υ And planetary system. We demonstrate that our approach allows for successful determination of its orbital elements. Most of the proposed approach can be adopted for other astrometric missions.
The structure of political satisfaction

In this paper we use a two-layer model in which we are able to empirically measure direct and indirect effects of satisfaction with public policies based on purely subjective preferences of citizens. We are also able to distinguish which individuals are dissatisfied the most. The estimation results suggest that the specified public policies are all significant except the respondent's attitude with respect to policies regarding social security, the amount of social benefits and immigration policy. Within the political context of 2001 left wing voters are less satisfied with policies aiming to realize a 24 hours economy than right-wing voters. Right wing voters are dissatisfied with immigration policies.
Characterization of Pv92, a Novel Merozoite Surface Protein of Plasmodium vivax

The discovery and understanding of antigenic proteins are essential for development of a vaccine against malaria. In Plasmodium falciparum, Pf92 have been characterized as a merozoite surface protein, and this protein is expressed at the late schizont stage, but no study of Pv92, the orthologue of Pf92 in P. vivax, has been reported. Thus, the protein structure of Pv92 was analyzed, and the gene sequence was aligned with that of other Plasmodium spp. using bioinformatics tools. The recombinant Pv92 protein was expressed and purified using bacterial expression system and used for immunization of mice to gain the polyclonal antibody and for evaluation of antigenicity by protein array. Also, the antibody against Pv92 was used for subcellular analysis by immunofluorescence assay. The Pv92 protein has a signal peptide and a sexual stage s48/45 domain, and the cysteine residues at the N-terminal of Pv92 were completely conserved. The N-terminal of Pv92 was successfully expressed as soluble form using a bacterial expression system. The antibody raised against Pv92 recognized the parasites and completely merged with PvMSP1-19, indicating that Pv92 was localized on the merozoite surface. Evaluation of the human humoral immune response to Pv92 indicated moderate antigenicity, with 65% sensitivity and 95% specificity by protein array. Taken together, the merozoite surface localization and antigenicity of Pv92 implicate that it might be involved in attachment and invasion of a merozoite to a new host cell or immune evasion during invasion process.
Vascular biomarkers derived from dynamic contrast-enhanced MRI predict response of vestibular schwannoma to antiangiogenic therapy in type 2 neurofibromatosis

Background Antiangiogenic therapy of vestibular schwannoma (VS) in type 2 neurofibromatosis can produce tumor shrinkage with response rates of 40%–60%. This study examines the predictive value of parameter-derived MRI in this setting. Methods Twelve patients with 20 VSs were recruited. Each had at least one rapidly growing tumor. Patients were treated with bevacizumab, 5 mg/kg every 2 weeks. Patients with stable or reduced VS volume were maintained at 2.5–5 mg every 4 weeks after 6 months. Those who failed treatment had their bevacizumab discontinued. Dynamic contrast-enhanced (DCE) MRI performed prior to treatment using a high temporal resolution technique, and data were analyzed to allow measurement of contrast transfer coefficient (Ktrans), vascular fraction (vp), extravascular-extracellular fraction (ve). Relaxation rate (R1N) was measured using a variable flip angle technique. Apparent diffusional coefficient (ADC) was calculated from diffusion-weighted imaging. The predictive power of microvascular parameters and ADC were examined using logistic regression modeling. Results Responding tumors were larger (P < .001), had lower R1N (P < .001), and higher Ktrans (P < .05) and ADC (P < .01). They showed increases in R1N (P < .01) and reduction of Ktrans (P < .01) and ADC (P < .01). Modeling to predict response demonstrated significant independent predictive power for R1N (Β = − 0.327, P < .001), and Ktrans (Β = 0.156, P < .05). Modeling to predict percentage change in tumor volume at 90 days identified baseline tumor volume (Β = 5.503, P < .05), R1N (Β = − 5.844, P < .05), and Ktrans (Β = 5.622, P < .05) as independent significant predictors. Conclusions In patients with type 2 neurofibromatosis, biomarkers from DCE-MRI are predictive of VS volume response to inhibition of vascular endothelial growth factor inhibition.
DHT-assisted probabilistic exhaustive search in unstructured P2P networks

Existing replication strategies in unstructured P2P networks, such as square-root principle based replication, can effectively improve search efficiency. How to get optimal replication strategy, however, is not trivial. In this paper we show, through mathematical proof, that random replication strategy achieves the optimal results. By randomly distributing rather small numbers of item and query replicas in the unstructured P2P network, we can guarantee perfect search success rate comparable to exhaustive search with high probability. Our analysis also shows that the cost for such replication strategy is determined by the network size of a P2P system. We propose a hybrid P2P architecture which combines a lightweight DHT with an unstructured P2P overlay to address the problems of network size estimating and random peer sampling. We conduct comprehensive simulation to evaluate this design. Results show that our scheme achieves perfect search success rate with quite small overhead.
Evidence for oscillation of atmospheric neutrinos

We present an analysis of atmospheric neutrino data from a 33.0 kton yr (535-day) exposure of the Super-Kamiokande detector. The data exhibit a zenith angle dependent deficit of muon neutrinos which is inconsistent with expectations based on calculations of the atmospheric neutrino flux. Experimental biases and uncertainties in the prediction of neutrino fluxes and cross sections are unable to explain our observation. The data are consistent, however, with two-flavor ${\ensuremath{\nu}}_{\ensuremath{\mu}}\ensuremath{\leftrightarrow}{\ensuremath{\nu}}_{\ensuremath{\tau}}$ oscillations with ${sin}^{2}2\ensuremath{\theta}g0.82$ and $5\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}4}l\ensuremath{\Delta}{m}^{2}l6\ifmmode\times\else\texttimes\fi{}1{0}^{\ensuremath{-}3}\mathrm{eV}{}^{2}$ at 90% confidence level.