Manipulation Strategies for the Rank Maximal Matching Problem

We consider manipulation strategies for the rank-maximal matching problem. In the rank-maximal matching problem we are given a bipartite graph $G = (A \cup P, E)$ such that $A$ denotes a set of applicants and $P$ a set of posts. Each applicant $a \in A$ has a preference list over the set of his neighbours in $G$, possibly involving ties. Preference lists are represented by ranks on the edges - an edge $(a,p)$ has rank $i$, denoted as $rank(a,p)=i$, if post $p$ belongs to one of $a$'s $i$-th choices. A rank-maximal matching is one in which the maximum number of applicants is matched to their rank one posts and subject to this condition, the maximum number of applicants is matched to their rank two posts, and so on. A rank-maximal matching can be computed in $O(\min(c \sqrt{n},n) m)$ time, where $n$ denotes the number of applicants, $m$ the number of edges and $c$ the maximum rank of an edge in an optimal solution. A central authority matches applicants to posts. It does so using one of the rank-maximal matchings. Since there may be more than one rank- maximal matching of $G$, we assume that the central authority chooses any one of them randomly. Let $a_1$ be a manipulative applicant, who knows the preference lists of all the other applicants and wants to falsify his preference list so that he has a chance of getting better posts than if he were truthful. In the first problem addressed in this paper the manipulative applicant $a_1$ wants to ensure that he is never matched to any post worse than the most preferred among those of rank greater than one and obtainable when he is truthful. In the second problem the manipulator wants to construct such a preference list that the worst post he can become matched to by the central authority is best possible or in other words, $a_1$ wants to minimize the maximal rank of a post he can become matched to

Histochemistry and Cell Biology: 61 years and not tired at all.

This is the author accepted manuscript. The final version is available from Springer via the DOI in this record.Isaac Newton is credited with quipping, “If I have seen further it is by standing on the shoulders of Giants”. This remark, made more than 300 years ago is still relevant for today’s scientists. Certainly, in our field of Histochemistry and Cell Biology, many of the insights we enjoy and techniques we apply in our research are the result of contributions to the literature provided by our scientific forebearers. As Editors of Histochemistry and Cell Biology, we are entrusted with maintaining the high quality and continued success of the journal instituted by its founders M. Chèvremont, Liège; H.W. Deane, New York; P.B. Diezel, F. Duspiva and H. Reznik, Heidelberg; O. Eränkö, Helsinki; P. Gedigk and N. Schümmelfelder, Bonn; W. Gössner, Tübingen; W. Graumann, Göttingen; A. G. E. Pearse, London; W. Sandritter, Frankfurt/Main; T.H. Schiebler, Kiel; G. Siebert, Mainz; and M. Wolman, Tel-Hashomer. The list of the international editors represented a virtual list of “Who’s Who” in histochemistry at that time.Biotechnology & Biological Sciences Research Council (BBSRC

An Integer Programming Approach to the Student-Project Allocation Problem with Preferences over Projects

The Student-Project Allocation problem with preferences over Projects (SPA-P) involves sets of students, projects and lecturers, where the students and lecturers each have preferences over the projects. In this context, we typically seek a stable matching of students to projects (and lecturers). However, these stable matchings can have different sizes, and the problem of finding a maximum stable matching (MAX-SPA-P) is NP-hard. There are two known approximation algorithms for MAX-SPA-P, with performance guarantees of 2 and 32 . In this paper, we describe an Integer Programming (IP) model to enable MAX-SPA-P to be solved optimally. Following this, we present results arising from an empirical analysis that investigates how the solution produced by the approximation algorithms compares to the optimal solution obtained from the IP model, with respect to the size of the stable matchings constructed, on instances that are both randomly-generated and derived from real datasets. Our main finding is that the 32 -approximation algorithm finds stable matchings that are very close to having maximum cardinality

A Novel Ultrasonic Method for Accurate Characterization of Microstructural Gradients in Monolithic and Composite Tubular Structures

Prior studies have shown that ultrasonic velocity/time-of-flight imaging that uses back surface echo reflections to gauge volumetric material quality is well suited (perhaps more so than is the commonlyused peak amplitude c-scanning) for quantitative characterization of microstructural gradients. Such gradients include those due to pore fraction, density, fiber fraction, and chemical composition variations [11–15]. Variations in these microstructural factors can affect the uniformity of physical performance (including mechanical [stiffness, strength], thermal [conductivity], and electrical [conductivity, superconducting transition temperature], etc. performance) of monolithic and composite [1,3,6,12]. A weakness of conventional ultrasonic velocity/time-of-flight imaging (as well as to a lesser extent ultrasonic peak amplitude c-scanning where back surface echoes are gated [17] is that the image shows the effects of thickness as well as microstructural variations unless the part is uniformly thick. This limits this type of imaging’s usefulness in practical applications. The effect of thickness is easily observed from the equation for pulse-echo waveform time-of-flight (2τ) between the first front surface echo (FS) and the first back surface echo (B1), or between two successive back surface echoes where: 2τ=(2d)V (1) where d is the sample thickness and V is the velocity of ultrasound in the material. Interpretation of the time-of-flight image is difficult as thickness variation effects can mask or overemphasize the true microstructural variation portrayed in the image of a part containing thickness variations. Thickness effects on time-of-flight can also be interpreted by rearranging equation (1) to calculate velocity: V=(2d)2τ (2) such that velocity is inversely proportional to time-of-flight. Velocity and time-of-flight maps will be affected similarly (although inversely in terms of magnitude) by thickness variations, and velocity maps are used in this investigation to indicate time-of-flight variations.</p

The highly competitive ascidian Didemnum sp. threatens coral reef communities in the Wakatobi Marine National Park, Southeast Sulawesi, Indonesia

Coral reefs in the Wakatobi Marine National Park (WMNP), Indonesia, are protected but have been degrading in several areas due to local anthropogenic stressors. In affected areas, benthic surveys revealed the occurrence of a dominant ascidian species of the genus Didemnum, which may negatively impact the benthic community composition and structure. We quantified the abundance, substrate preference, and growth rate of Didemnum sp. in non-degraded and degraded reefs to assess its impact on the benthic community. While Didemnum sp. occurred in similar high abundances in both, non-degraded (0.66%) and degraded (0.75 %) reef sites, this species showed a substantially (>10-fold) increased growth rate in degrading reefs (2.7 ± 0.98% day−1 increase in colony size, compared to 0.17 ± 0.39 % day −1 in non-degraded reefs). Furthermore, Didemnum sp. colonized many different substrates and showed the ability to overgrow live corals quickly. These observations indicate that Didemnum sp. can be a severe threat to a reef community by outcompeting live corals and call for further studies on the interaction between environmental pollution and Didemnum growth patterns in coral reefs

Registration of the endoluminal surfaces of the colon derived from prone and supine CT colonography

Purpose: Computed tomographic (CT) colonography is a relatively new technique for detecting bowel cancer or potentially precancerous polyps. CT scanning is combined with three-dimensional (3D) image reconstruction to produce a virtual endoluminal representation similar to optical colonoscopy. Because retained fluid and stool can mimic pathology, CT data are acquired with the bowel cleansed and insufflated with gas and patient in both prone and supine positions. Radiologists then match visually endoluminal locations between the two acquisitions in order to determine whether apparent pathology is real or not. This process is hindered by the fact that the colon, essentially a long tube, can undergo considerable deformation between acquisitions. The authors present a novel approach to automatically establish spatial correspondence between prone and supine endoluminal colonic surfaces after surface parameterization, even in the case of local colon collapse.Methods: The complexity of the registration task was reduced from a 3D to a 2D problem by mapping the surfaces extracted from prone and supine CT colonography onto a cylindrical parameterization. A nonrigid cylindrical registration was then performed to align the full colonic surfaces. The curvature information from the original 3D surfaces was used to determine correspondence. The method can also be applied to cases with regions of local colonic collapse by ignoring the collapsed regions during the registration.Results: Using a development set, suitable parameters were found to constrain the cylindrical registration method. Then, the same registration parameters were applied to a different set of 13 validation cases, consisting of 8 fully distended cases and 5 cases exhibiting multiple colonic collapses. All polyps present were well aligned, with a mean (+/- std. dev.) registration error of 5.7 (+/- 3.4) mm. An additional set of 1175 reference points on haustral folds spread over the full endoluminal colon surfaces resulted in an error of 7.7 (+/- 7.4) mm. Here, 82% of folds were aligned correctly after registration with a further 15% misregistered by just onefold.Conclusions: The proposed method reduces the 3D registration task to a cylindrical registration representing the endoluminal surface of the colon. Our algorithm uses surface curvature information as a similarity measure to drive registration to compensate for the large colorectal deformations that occur between prone and supine data acquisitions. The method has the potential to both enhance polyp detection and decrease the radiologist's interpretation time. (C) 2011 American Association of Physicists in Medicine. [DOI: 10.1118/1.3577603

Increased Belief Instability in Psychotic Disorders Predicts Treatment Response to Metacognitive Training

BACKGROUND AND HYPOTHESIS: In a complex world, gathering information and adjusting our beliefs about the world is of paramount importance. The literature suggests that patients with psychotic disorders display a tendency to draw early conclusions based on limited evidence, referred to as the jumping-to-conclusions bias, but few studies have examined the computational mechanisms underlying this and related belief-updating biases. Here, we employ a computational approach to understand the relationship between jumping-to-conclusions, psychotic disorders, and delusions. STUDY DESIGN: We modeled probabilistic reasoning of 261 patients with psychotic disorders and 56 healthy controls during an information sampling task-the fish task-with the Hierarchical Gaussian Filter. Subsequently, we examined the clinical utility of this computational approach by testing whether computational parameters, obtained from fitting the model to each individual's behavior, could predict treatment response to Metacognitive Training using machine learning. STUDY RESULTS: We observed differences in probabilistic reasoning between patients with psychotic disorders and healthy controls, participants with and without jumping-to-conclusions bias, but not between patients with low and high current delusions. The computational analysis suggested that belief instability was increased in patients with psychotic disorders. Jumping-to-conclusions was associated with both increased belief instability and greater prior uncertainty. Lastly, belief instability predicted treatment response to Metacognitive Training at the individual level. CONCLUSIONS: Our results point towards increased belief instability as a key computational mechanism underlying probabilistic reasoning in psychotic disorders. We provide a proof-of-concept that this computational approach may be useful to help identify suitable treatments for individual patients with psychotic disorders

Conductivity Imaging in Plates Using Current Injection Tomography

The task of reconstructing an unknown distribution of electrical conductivity is widely recognized as a central theoretical problem in eddy-current nondestructive evaluation [1]. Rather than using an eddy-current method, we address this problem using DC injection of current into conductive materials. Experimental methods of the magnetic imaging of injected currents using high-resolution SQUID magnetometers have been described elsewhere [2]. In this paper we describe a tomographic method for using magnetically-imaged, injected currents to reconstruct distributions of electrical conductivity. Much of what we describe should also be applicable to data obtained using uniform colinear eddy currents induced by means of planar sheet inducers [4, 5]

A systematic review of biomarkers for disease progression in Parkinson's disease

Peer reviewedPublisher PD