Miracle-dz/UniFAR-FTUs huggingface dataset:
A Knowledge Level Analysis of Belief Revision

Revising beliefs is a task any intelligent agent has to perform. For this reason, belief re-vision has received much interest in Arti(cid:12)-cial Intelligence. However, there are serious problems when trying to analyze belief revision techniques developed in the (cid:12)eld of Arti-(cid:12)cial Intelligence on the knowledge level. The symbolic representation of beliefs seems to be crucial. The theory of epistemic change shows that a partial knowledge-level analysis of belief revision is possible, but leaves open the question of how this theory is re-lated to belief revision approaches in Arti(cid:12)-cial Intelligence. In particular, it remains an open question whether the results achieved in the knowledge-level analysis are valid. Furthermore, the idea of reason maintenance, which is considered to be essential in AI, has no counter-part in the theory of epistemic change. Addressing these problems, it is shown how to reconstruct symbol-level belief revision on the knowledge level.
Checking LTL properties of recursive Markov chains

We present algorithms for the qualitative and quantitative model checking of linear temporal logic (LTL) properties for recursive Markov chains (RMCs). Recursive Markov chains are a natural abstract model of procedural probabilistic programs and related systems involving recursion and probability. For the qualitative problem ("given a RMC A and an LTL formula /spl phi/, do the computations of A satisfy /spl phi/ almost surely? ) we present an algorithm that runs in polynomial space in A and exponential time in /spl phi/. For several classes of RMCs, including RMCs with one exit (a special case that corresponds to well-studied probabilistic systems, e.g., multi-type branching processes and stochastic context-free grammars) the algorithm runs in polynomial time in A and exponential time in /spl phi/. On the other hand, we also prove that the problem is EXPTIME-hard, and hence it is EXPTlME-complete. For the quantitative problem ("does the probability that a computation of A satisfies /spl phi/ exceed a given threshold p? ", or approximate the probability within a desired precision) we present an algorithm that runs in polynomial space in A and exponential space in /spl phi/. For linearly-recursive RMCs, we can compute the exact probability in time polynomial in A and exponential in /spl phi/. These results improve by one exponential, in both the qualitative and quantitative case, the complexity that one would obtain if one first translated the LTL formula to a Buchi automaton and then applied the model checking algorithm for Buchi automata from K. Etessami and M. Yannakakis (2005). Our results combine techniques developed in A. Pnueli and L. D. Zuck. (1993) for analysts of RMCs and in C. Courcoubetis and M. Yannakakis (1995) for LTL model checking of flat Markov Chains, and extend them with new techniques.
Robust optimal control of two-level quantum systems

We investigate the time and the energy minimum optimal solutions for the robust control of two-level quantum systems against offset or control field uncertainties. Using the Pontryagin Maximum Principle, we derive the global optimal pulses for the first robustness orders. We show that the dimension of the control landscape is lower or equal to 2N for a field robust to the N th order, which leads to an estimate of its complexity.
Actual-Delay Circuits on FPGA: Trading-Off Luts for Speed

FPGA devices exhibit manufacturing variability. Device ratings and Timing margins are typically used in order to cope with inter-device and intra-device variability respectively. Actual-delay circuits operate according to the actual, physical device delays of the FPGA device components and not according to STA predictions, exhibit data-dependent delay,latency and output completion detection, and can thus detect when their outputs are ready to be latched. In this paper we demonstrate an FPGA flow, based around existing FPGA tools, capable of implementing actual-delay circuits, and through worst-case, upper-bound analysis show that such circuits exhibit reduced delay and higher performance than their conventional counterparts. The FPGA flow incorporates a logic synthesis transformation step for converting a conventional single-rail circuit to monotonic, dual-rail and a LUT mapper for mapping the latter to LUTs while preserving monotonicity. In addition, through our implementation of actual-delay circuits we are able to measure intra and inter-FPGA timing margins and we present results on the STA margin and timing deviation over four devices
Computer Modeling of Microstructural Change and Strength of Low Carbon Steel in Hot Strip Rolling

A calculation model for predicting the strength of hot rolled low carbon steel sheets from their chemical compositions and processing variables has been developed as a combination of the hot deformation model, the transformation model, and the relationship between the strength and the microstructure. To make up a comprehensive model based on the previously reported hot deformation model and transformation model, the effect of stored strain on transformation kinetics and the prediction of ferrite grain size from the transformation model are studied for inclusion in the comprehensive model. Further, the relationships between the microhardnesses and the microstructures are examined. The microhardness of each microconstituent in a mixed microstructure is found dependent on its transformation temperature. These relationships are formulated for the present model. The model has been applied to the calculation of the microstructure and the tensile strength of steels. Good agreement is obtained between the values calculated and observed, and the applicability of the model for hot strip rolling process has been confirmed.
Breast Cancer Histopathology Image Analysis: A Review

This paper presents an overview of methods that have been proposed for the analysis of breast cancer histopathology images. This research area has become particularly relevant with the advent of whole slide imaging (WSI) scanners, which can perform cost-effective and high-throughput histopathology slide digitization, and which aim at replacing the optical microscope as the primary tool used by pathologist. Breast cancer is the most prevalent form of cancers among women, and image analysis methods that target this disease have a huge potential to reduce the workload in a typical pathology lab and to improve the quality of the interpretation. This paper is meant as an introduction for nonexperts. It starts with an overview of the tissue preparation, staining and slide digitization processes followed by a discussion of the different image processing techniques and applications, ranging from analysis of tissue staining to computer-aided diagnosis, and prognosis of breast cancer patients.
Meniscus on a shaped fibre: singularities and hodograph formulation

Using the method of matched asymptotic expansions, the problem of the capillary rise of a meniscus on the complex-shaped fibres was reduced to a nonlinear problem of determination of a minimal surface. This surface has to satisfy a special boundary condition at infinity. The proposed formulation allows one to interpret the meniscus problem as a problem of flow of a fictitious non-Newtonian fluid through a porous medium. As an example, the shape of a meniscus on a fibre of an oval cross section was analysed employing Chaplygin's hodograph transformation. It was discovered that the contact line may form singularities even if the fibre has a smooth profile: this statement was illustrated with an oval fibre profile having infinite curvature at two endpoints.
Controlling Complexity in Part-of-Speech Induction

We consider the problem of fully unsupervised learning of grammatical (part-of-speech) categories from unlabeled text. The standard maximum-likelihood hidden Markov model for this task performs poorly, because of its weak inductive bias and large model capacity. We address this problem by refining the model and modifying the learning objective to control its capacity via para- metric and non-parametric constraints. Our approach enforces word-category association sparsity, adds morphological and orthographic features, and eliminates hard-to-estimate parameters for rare words. We develop an efficient learning algorithm that is not much more computationally intensive than standard training. We also provide an open-source implementation of the algorithm. Our experiments on five diverse languages (Bulgarian, Danish, English, Portuguese, Spanish) achieve significant improvements compared with previous methods for the same task.
Pulsed field magnetization properties for a large single-grain Gd-Ba-Cu-O high-temperature superconductor bulk with a diameter of 140 mm by using a new type of pulsed copper split coil

Pulsed-field magnetization (PFM) was applied to a Gd-Ba-Cu-O high-temperature superconductor (HTS) bulk of 140 mm diameter by using a split-type pulsed current armature coil. Two kinds of split-armature coils with 100 mm and 140 mm diameter were tested. The PFM with the coil of 100 mm diameter is effective to obtain a conical shape of the trapped flux-density distribution. Another coil of 140 mm diameter contributes to enhance the total magnetic flux. We fabricated a single vortex coil which plays a role as 2, those are 100 and 140 mm in one of them, that is a controlled magnetic density distribution coil (CMDC). The CMDC is composed of a vortex-type coil with 100 mm diameter surrounded by additional winding forming an air core solenoid with an outer diameter of 140 mm. We obtained a trapped flux-density distribution with conical shape together with the maximum trapped flux-density up to 0.6 T which is equivalent with 30 % of the value in the field cool magnetization (FCM) and total flux density with 3.1 mWb which is 40 % of the result of the FCM.
Innovation as a nonlinear process, the scientometric perspective, and the specification of an ‘innovation opportunities explorer’

The process of innovation follows nonlinear patterns across the domains of science, technology, and the economy. Novel bibliometric mapping techniques can be used to investigate and represent distinctive, but complementary perspectives on the innovation process (e.g. ‘demand’ and ‘supply’) as well as the interactions among these perspectives using animations. In a map, the different perspectives can be represented as ‘continents’ of data related to varying extents over time. For example, the different branches of Medical Subject Headings (MeSH) in the Medline database provide sources of such perspectives (e.g. ‘Diseases’ vs ‘Drugs and Chemicals’). The multiple-perspective approach enables us to reconstruct facets of the dynamics of innovation, in terms of selection mechanisms shaping localisable trajectories and/or resulting in more globalised regimes. By expanding the data with patents and scholarly publications, we demonstrate the use of this multi-perspective approach in the case of RNA Interference (RNAi). The possibility to develop an ‘Innovation Opportunities Explorer’ is specified.
Patriline Differences Reveal Genetic Influence on Forewing Size and Shape in a Yellowjacket Wasp (Hymenoptera: Vespidae: Vespula flavopilosa Jacobson, 1978)

The wing venation is frequently used as a morphological marker to distinguish biological groups among insects. With geometric morphometrics, minute shape differences can be detected between closely related species or populations, making this technique useful for taxonomy. However, the direct influence of genetic differences on wing morphology has not been explored within colonies of social insects. Here, we show that the father’s genotype has a direct effect on wing morphology in colonies of social wasps. Using geometric morphometrics on the venation pattern, we found significant differences in wing size and shape between patrilines of yellowjackets, taking allometry and measurement error into account. The genetic influence on wing size accounted for a small part of the overall size variation, but venation shape was highly structured by the differences between patrilines. Overall, our results showed a strong genetic influence on wing morphology likely acting at multiple levels of venation pattern development. This confirmed the pertinence of this marker for taxonomic purposes and suggests this phenotype as a potentially useful marker for phylogenies. This also raises doubts about the strength of selective pressures on this phenotype, which highlights the need to understand better the role of wing venation shape in insect flight.
WP Semantics for OO Programs and Its Applications I

For the object oriented (OO) world, developing formal semantics for theoretical study and practical use is still an important topic despite of a decade’s e orts. In this paper, for a su ciently large subset of sequential Java with a pure reference semantics model, we define a Weakest Precondition (WP) semantics, and prove its soundness and completeness. Based on this WP semantics, we study specifications of methods and the refinement relationship between specifications, and we propose new definitions for object invariants and behavioral subtyping notation for general OO programs.
On recent trends in climate dynamics

The dynamics of the atmosphere and the oceans are inherently complex. There are active entangled processes running on spatial scales from millimetres to thousands of kilometres, and temporal scales from seconds to millennia. Capturing the whole range of spatial and temporal scales is impossible given current computer power. A numerical forecaster must decide, depending on their specific objectives, what scales they want to resolve. A corollary of this decision is that each numerical scheme inevitably fails to resolve so-called unresolved scales or subgrid scales. Usually, the interesting information is carried by the slow and large scales. For example, for weather forecasts we want to resolve large-scale highand low-pressure fields rather than small-scale fast oscillations of the stratification surfaces, or for climate prediction in a coupled ocean-atmosphere model we want to learn about the slow dynamics of the ocean that are constantly kicked by fast-evolving weather systems swirling above.
Effect of Eshelby twist on core structure of screw dislocations in molybdenum: atomic structure and electron microscope image simulations

This paper addresses the question as to whether the core structure of screw dislocations in Mo in the bulk can be obtained from high-resolution electron microscopy (HREM) images of such dislocations viewed end-on in a thin foil. Atomistic simulations of the core structure of screw dislocations in elastically anisotropic Mo were carried out using bond order potentials. These simulations take account automatically of the effects of the surface relaxation displacements (anisotropic Eshelby twist). They show that the differential displacements of the atoms at the surface are different with components perpendicular to the Burgers vector about five times larger than those in the middle of the foil, the latter being characteristic of the bulk. Nye tensor plots show that the surface relaxation stresses strongly affect the incompatible distortions. HREM simulations of the computed structure reflect the displacements at the exit surface, modified by interband scattering and the microscope transfer function. Nye tensor plots obtained from the HREM images show that interband scattering also affects the incompatible distortions. It is concluded that it would be very difficult to obtain information on the core structure of screw dislocations in the bulk Mo from HREM images, even under ideal experimental conditions, and that quantitative comparisons between experimental and simulated images from assumed model structures would be essential.
Bio-Encapsulation for the Immune-Protection of Therapeutic Cells

The design of new technologies for treatment of human disorders is a complex and difficult task. The aim of this article is to explore state of art discussion of various techniques and materials involve in cell encapsulations. Encapsulation of cells within semi-permeable polymer shells or beads is a potentially powerful tool, and has long been explored as a promising approach for the treatment of several human diseases such as lysosomal storage disease (LSD), neurological disorders, Parkinsons disease, dwarfism, hemophilia, cancer and diabetes using immune-isolation gene therapy.
LC-VCO design methodology based on evolutionary algorithms

In his paper the design of LC-VCOs is addressed. Due to the high-density integration needs as well as to low cost fabrication, RF applications are usually implemented in CMOS technology. However, this technology development brought up several issues such as the degradation of on-chip LC tank quality factor, yielding VCO's phase noise limitation. To overcome phase-noise limitations, optimization design methodologies are usually used. Since electromagnetic simulations are timely expensive, model based approaches are needed. In this work the characterization of the oscillator behaviour is guaranteed by a set of analytical models describing each circuit element performance. A set of working examples for UMC130 technology, aiming the VCO phase noise and power consumption optimization, is addressed. The results presented, spotlight the potential of the proposed design methodology, combined with a GA optimization procedure, for an accurate and timely efficient oscillator design. The accuracy of the results is checked against HSPICE/RF simulator.
Large-Margin Metric Learning for Constrained Partitioning Problems

We consider unsupervised partitioning problems based explicitly or implicitly on the minimization of Euclidean distortions, such as clustering, image or video segmentation, and other change-point detection problems. We emphasize on cases with specific structure, which include many practical situations ranging from mean-based change-point detection to image segmentation problems. We aim at learning a Mahalanobis metric for these unsupervised problems, leading to feature weighting and/or selection. This is done in a supervised way by assuming the availability of several (partially) labeled datasets that share the same metric. We cast the metric learning problem as a large-margin structured prediction problem, with proper definition of regularizers and losses, leading to a convex optimization problem which can be solved efficiently. Our experiments show how learning the metric can significantly improve performance on bioinformatics, video or image segmentation problems.
The pervasiveness of evolution in GRUMPS software

This paper describes the evolution of the design and implementation of a distributed run‐time system that itself is designed to support the evolution of the topology and implementation of an executing, distributed system. The three different versions of the run‐time architecture that have been designed and implemented are presented, together with how each architecture addresses the problems of topological and functional evolution. In addition, the reasons for the rapid evolution of the design and implementation of the architecture are also described.
In vitro resistance to interferon of hepatitis B virus with precore mutation.

AIM Chronic hepatitis B virus (HBV) infection is predominantly treated with interferon alpha (IFN-alpha), which results in an efficient reduction of the viral load only in 20-40% of treated patients. Mutations at HBV precore prevail in different clinical status of HBV infection. The roles of precore mutation in the progression of chronic hepatitis and interferon sensitivity are still unknown. The aim of this study was to explore if there was any relationship between HBV precore mutation and sensitivity to interferon in vitro. METHODS HBV replication-competent recombinant constructs with different patterns of precore mutations were developed. Then the recombinants were transiently transfected into hepatoma cell line (Huh7) by calcium phosphate transfection method. With or without IFN, viral products in culture medium were collected and quantified 3 d after transfection. RESULTS We obtained 4 recombinant constructs by orientation-cloning 1.2-fold-overlength HBV genome into pUC18 vector via the EcoRI and Hind III and PCR mediated site-directed mutagenesis method. All the recombinants contained mutations within precore region. Huh7 cells transfected with recombinants secreted HBsAg and HBV particles into the cell culture medium, indicating that all the recombinants were replication-competent. By comparing the amount of HBV DNA in the medium, we found that HBV DNA in medium reflecting HBV replication efficiency was different in different recombinants. Recombinants containing precore mutation had fewer HBV DNAs in culture medium than wild type. This result showed that recombinants containing precore mutation had lower replication efficiency than wild type. HBV DNA was decreased in pUC18-HBV1.2-WT recombinants after IFN was added while others with precore mutations were not, indicating that HBV harboring precore mutation was less sensitive to IFN in cell culture system. CONCLUSION These data indicate that HBV harboring precore mutation may be resistant to IFN in vitro.
Expanding the role of community mobilization to accelerate progress towards ending vertical transmission of HIV in Uganda: the Networks model

Efforts to prevent vertical transmission of HIV have gained momentum globally since the launch of the “Global plan towards the elimination of new HIV infections among children by 2015 and keeping their mothers alive”, reflecting the growing consensus that we now have low‐cost, efficacious interventions that promise to end vertical transmission of HIV. Uganda is one of the 22 focus countries in the global plan and one of the 10 countries with the highest need for prevention of vertical transmission globally. In the context of current shortfalls in the prevention of vertical HIV transmission, this paper presents the results of the Networks project, a community mobilisation model implemented by the International HIV/AIDS Alliance in Uganda, and draws out the theoretical foundations and promising community mobilization practices relevant to prevention of vertical transmission.
On the caging region of a third finger with object boundary clouds and two given contact positions

This paper presents a caging approach which deals with planar boundary clouds collected from a laser scanner. Given the boundary clouds of a target object and two fixed finger positions, our aim is to find potential third finger positions that can prevent target from escaping into infinity. The major challenge in working with boundary clouds lies in their uncertainty in geometric model fitting and the failure of critical orientations. In this paper, we track canonical motions according to the rotational intersection of Configuration space fingers and rasterize Work space with grids to compute the third caging positions. Our approach can generate the capture region with max(O(np),O(h2)) ≤ O(n2) cost where n denotes the resolution of grid rasterization, p denotes the resolution of canonical rasterization and h denotes the resolution of boundary rasterization or the number of boundary cloud points. Moreover, we propose a rough approximation which measures a subset of the possible positions by contracting rotations, indicating computational complexity of max(O(n),O(h2)). In the experimental part, our proposal is compared with state-of-the-art works and applied to many other objects. The approach makes caging fast and effective.