Miracle-dz/UniFAR-FTUs huggingface dataset:
An Exact Connection between Two Solvable SDEs and a Nonlinear Utility Stochastic PDE

Motivated by the work of Musiela and Zariphopoulou \cite{zar-03}, we study the Ito random fields which are utility functions $U(t,x)$ for any $(\omega,t)$. The main tool is the marginal utility $U_x(t,x)$ and its inverse expressed as the opposite of the derivative of the Fenchel conjuguate $\tU(t,y)$. Under regularity assumptions, we associate a $SDE(\mu, \sigma)$ and its adjoint SPDE$(\mu, \sigma)$ in divergence form whose $U_x(t,x)$ and its inverse $-\tU_y(t,y)$ are monotonic solutions. More generally, special attention is paid to rigorous justification of the dynamics of inverse flow of SDE. So that, we are able to extend to the solution of similar SPDEs the decomposition based on the solutions of two SDEs and their inverses. The second part is concerned with forward utilities, consistent with a given incomplete financial market, that can be observed but given exogenously to the investor. As in \cite{zar-03}, market dynamics are considered in an equilibrium state, so that the investor becomes indifferent to any action she can take in such a market. After having made explicit the constraints induced on the local characteristics of consistent utility and its conjugate, we focus on the marginal utility SPDE by showing that it belongs to the previous family of SPDEs. The associated two SDE's are related to the optimal wealth and the optimal state price density, given a pathwise explicit representation of the marginal utility. This new approach addresses several issues with a new perspective: dynamic programming principle, risk tolerance properties, inverse problems. Some examples and applications are given in the last section.
Elevated Homologous Recombination Activity in Fanconi Anemia Fibroblasts*

It is widely believed that Fanconi anemia cells possess a reduced ability to repair inter-strand DNA cross-links. While the mechanism through which inter-strand DNA cross-links are removed from mammalian chromosomes is unknown, these lesions are repaired via homologous recombination in lower eukaryotes and bacteria. Based on the hypothesis that a similar mechanism of DNA repair functions in mammalian somatic cells, we measured homologous recombination activity in diploid fibroblasts from healthy donors, and Fanconi anemia patients. Somewhat surprisingly, homologous recombination levels in nuclear protein extracts prepared from Fanconi anemia cells were nearly 100-fold higher than in extracts prepared from control cells. We observed a similar increase in the activity of a 100-kDa homologous DNA pairing protein in extracts from Fanconi anemia cells. Transfection studies confirmed that plasmid homologous recombination levels in intact Fanconi anemia cells were substantially elevated, compared with control cells. These results suggest that inappropriately elevated levels of homologous recombination activity may contribute to the genomic instability and cancer predisposition that characterize Fanconi anemia.
Finding attractors in Asynchronous Boolean Dynamics

We present a computational method for finding attractors (ergodic sets of states) of Boolean networks under asynchronous update. The approach is based on a systematic removal of state transitions to render the state transition graph acyclic. In this reduced state transition graph, all attractors are fixed points that can be enumerated with little effort in most instances. This attractor set is then extended to the attractor set of the original dynamics. Our numerical tests on standard Kauffman networks indicate that the method is efficient in the sense that the total number of state vectors visited grows moderately with the number of states contained in attractors.
Death receptor‐induced cell death in prostate cancer

Prostate cancer mortality results from metastasis and is often coupled with progression from androgen‐dependent to androgen‐independent growth. Unfortunately, no effective treatment for metastatic prostate cancer increasing patient survival is available. The absence of effective therapies reflects in part a lack of knowledge about the molecular mechanisms involved in the development and progression of this disease. Apoptosis, or programmed cell death, is a cell suicide mechanism that enables multicellular organisms to regulate cell number in tissues. Inhibition of apoptosis appears to be a critical pathophysiological factor contributing to the development and progression of prostate cancer. Understanding the mechanism(s) of apoptosis inhibition may be the basis for developing more effective therapeutic approaches. Our understanding of apoptosis in prostate cancer is relatively limited when compared to other malignancies, in particular, hematopoietic tumors. Thus, a clear need for a better understanding of apoptosis in this malignancy remains. In this review we have focused on what is known about apoptosis in prostate cancer and, more specifically, the receptor/ligand‐mediated pathways of apoptosis as potential therapeutic targets. © 2003 Wiley‐Liss, Inc.
A Survey of Statistical Network Models

Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major topic of interest in diverse areas of study, and most of these involve a form of graphical representation. Probability models on graphs date back to 1959. Along with empirical studies in social psychology and sociology from the 1960s, these early works generated an active "network community" and a substantial literature in the 1970s. This effort moved into the statistical literature in the late 1970s and 1980s, and the past decade has seen a burgeoning network literature in statistical physics and computer science. The growth of the World Wide Web and the emergence of online "networking communities" such as Facebook, MySpace, and LinkedIn, and a host of more specialized professional network communities has intensified interest in the study of networks and network data. Our goal in this review is to provide the reader with an entry point to this burgeoning literature. We begin with an overview of the historical development of statistical network modeling and then we introduce a number of examples that have been studied in the network literature. Our subsequent discussion focuses on a number of prominent static and dynamic network models and their interconnections. We emphasize formal model descriptions, and pay special attention to the interpretation of parameters and their estimation. We end with a description of some open problems and challenges for machine learning and statistics.
Subchondral fracture following arthroscopic knee surgery. A series of eight cases.

BACKGROUND Osteonecrosis has been reported as a rare complication of arthroscopic knee surgery, with the diagnosis based on radiographic findings associated with recurrent or worsening clinical symptoms. The term osteonecrosis has been applied to this clinical entity despite a lack of pathologic evidence to support the diagnosis. The purpose of this study was to document the pathologic changes involved in this rare process. METHODS Patients who had undergone an arthroscopic procedure followed by a total knee replacement within two years were eligible for the study. Inclusion criteria included pre-arthroscopy magnetic resonance imaging findings consistent with a meniscal tear with otherwise normal bone morphology followed by a provisional diagnosis of post-arthroscopy osteonecrosis based on subsequent imaging studies. Patients were excluded if a laser-assisted device had been utilized during the arthroscopy. Seven patients (eight knees) with an average age of sixty-four years met the criteria and were included in the study group. RESULTS All patients had undergone an arthroscopic medial meniscectomy, and two also had had a chondroplasty, with use of a mechanical shaver. Seven of the post-arthroscopy lesions involved the medial femoral condyle, and one lesion involved the medial tibial plateau. Pathologic analysis revealed a subchondral fracture with callus formation, indicated by the presence of woven bone, in all cases. Four patients had essentially intact articular cartilage overlying the lesion, which was characterized by disruption of the trabecular architecture indicative of subchondral bone fracture. The other four patients had an isolated osteochondral defect with reparative tissue within the base of the defect. Only two knees had localized evidence of osteonecrosis, which appeared to be secondary to the fracture. CONCLUSIONS This study provides pathologic evidence supporting the concept that subchondral fracture, and not osteonecrosis, is the major event in this rare complication following arthroscopy. Further investigation into the etiology of this condition is warranted.
ChainCluster: Engineering a Cooperative Content Distribution Framework for Highway Vehicular Communications

The recent advances in wireless communication techniques have made it possible for fast-moving vehicles to download data from the roadside communications infrastructure [e.g., IEEE 802.11b Access Point (AP)], namely, Drive-thru Internet. However, due to the high mobility, harsh, and intermittent wireless channels, the data download volume of individual vehicle per drive-thru is quite limited, as observed in real-world tests. This would severely restrict the service quality of upper layer applications, such as file download and video streaming. On addressing this issue, in this paper, we propose ChainCluster, a cooperative Drive-thru Internet scheme. ChainCluster selects appropriate vehicles to form a linear cluster on the highway. The cluster members then cooperatively download the same content file, with each member retrieving one portion of the file, from the roadside infrastructure. With cluster members consecutively driving through the roadside infrastructure, the download of a single vehicle is virtually extended to that of a tandem of vehicles, which accordingly enhances the probability of successful file download significantly. With a delicate linear cluster formation scheme proposed and applied, in this paper, we first develop an analytical framework to evaluate the data volume that can be downloaded using cooperative drive-thru. Using simulations, we then verify the performance of ChainCluster and show that our analysis can match the simulations well. Finally, we show that ChainCluster can outperform the typical studied clustering schemes and provide general guidance for cooperative content distribution in highway vehicular communications.
Optimal Surface Parameterization Using Inverse Curvature Map

Mesh parameterization is a fundamental technique in computer graphics. Our paper focuses on solving the problem of finding the best discrete conformal mapping that also minimizes area distortion. Firstly, we deduce an exact analytical differential formula to represent area distortion by curvature change in the discrete conformal mapping, giving a dynamic Poisson equation. Our result shows the curvature map is invertible. Furthermore, we give the explicit Jacobi matrix of the inverse curvature map. Secondly, we formulate the task of computing conformal parameterizations with least area distortions as a constrained nonlinear optimization problem in curvature space. We deduce explicit conditions for the optima. Thirdly, we give an energy form to measure the area distortions, and show it has a unique global minimum. We use this to design an efficient algorithm, called free boundary curvature diffusion, which is guaranteed to converge to the global minimum. This result proves the common belief that optimal parameterization with least area distortion has a unique solution and can be achieved by free boundary conformal mapping. Major theoretical results and practical algorithms are presented for optimal parameterization based on the inverse curvature map. Comparisons are conducted with existing methods and using different energies. Novel parameterization applications are also introduced.
Extending Bayesian Logic Programs for Plan Recognition and Machine Reading

Statistical relational learning (SRL) is the area of machine learning that integrates both first-order logic and probabilistic graphical models. The advantage of these formalisms is that they can handle both uncertainty and structured/relational data. As a result, they are widely used in domains like social network analysis, biological data analysis, and natural language processing. Bayesian Logic Programs (BLPs), which integrate both first-order logic and Bayesian networks are a powerful SRL formalism developed in the recent past. In this proposal, we focus on applying BLPs to two real worlds tasks – plan recognition and machine reading. Plan recognition is the task of predicting an agent’s top-level plans based on its observed actions. It is an abductive reasoning task that involves inferring cause from effect. In the first part of the proposal, we develop an approach to abductive plan recognition using BLPs. Since BLPs employ logical deduction to construct the networks, they cannot be used effectively for plan recognition as is. Therefore, we extend BLPs to use logical abduction to construct Bayesian networks and call the resulting model Bayesian Abductive Logic Programs (BALPs). Experimental evaluation on three benchmark data sets demonstrate that BALPs outperform the existing state-of-art methods like Markov Logic Networks (MLNs) for plan recognition. For future work, we propose to apply BLPs to the task of machine reading, which involves automatic extraction of knowledge from natural language text. Present day information extraction (IE) systems that are trained for machine reading are limited by their ability to extract only factual information that is stated explicitly in the text. We propose to improve the performance of an off-the-shelf IE system by inducing general knowledge rules about the domain using the facts already extracted by the IE system. We then use these rules to infer additional facts using BLPs, thereby improving the recall of the underlying IE system. Here again, the standard inference used in BLPs cannot be used to construct the networks. So, we extend BLPs to perform forward inference on all facts extracted by the IE system and then construct the ground Bayesian networks. We initially use an existing inductive logic programming (ILP) based rule learner to learn the rules. In the longer term, we would like to develop a rule/structure learner that is capable of learning an even better set of first-order rules for BLPs.
An Extension Problem Related to the Fractional Laplacian

The operator square root of the Laplacian (− ▵)1/2 can be obtained from the harmonic extension problem to the upper half space as the operator that maps the Dirichlet boundary condition to the Neumann condition. In this article, we obtain similar characterizations for general fractional powers of the Laplacian and other integro-differential operators. From those characterizations we derive some properties of these integro-differential equations from purely local arguments in the extension problems.
Immunoproliferative Effects of Lymphocytic Choriomeningitis Virus in Germfree Mice 1

Summary Mice with congenitally-acquired LCM virus infection were maintained under germfree condtions for 12 months. With advancing age, the mice showed histological evidence of uncontrolled immunoproliferative changes: the enlarged lymph nodes and spleens contained large germinal zones and numerous plasma cells. The cortical cells of the thymus glands were progressively depleted of cortical cells, became shrunken, eventually swollen, and infiltrated with large plasma cells. The visceral organs had perivascular infiltrations of lymphoid and plasma cells which displaced significant amounts of parenchyma. The plasmacytomas which developed differed from the lesions associated with murine leukemia.
Spatial clutter measurement density estimation in nonhomogeneous measurement spaces

Clutter measurement density (CMD) is one of data association parameters, which indicates the number of clutter measurements per unit volume of the measurement space. In probabilistic data association based algorithms, the association probability between a prior estimate and a measurement is proportional to the ratio of target measurement likelihood and CMD. Also the measurement likelihood is used for obtaining the target existence probability for false track discrimination. Although CMD is an important parameter for state estimation as well as track management, it depends on surveillance environments in which the true CMD is rarely known in advance. A clutter measurement density estimator (CMDE) calculates the spatial density of clutter adaptively using measurement information, and provides its estimated CMD to data association algorithms for adaptive target tracking in clutter. A spatial CMDE (SCMDE) selects the measurement with the N-th smallest 2-norm distance from the measurement of interest and evaluates volume of the hypersphere centered at the measurement of interest and touches the selected measurement. The sparsity (inverse of CMD) is obtained from dividing the hypersphere volume by N. It is only applicable to homogeneous measurement spaces of which coordinates have the same unit such as Cartesian coordinates. An improved version of SCMDE which can be utilized in nonhomogeneous measurement spaces with the different coordinate units such as polar coordinates is proposed. By using weighted normal distance that reflects the volume of the nonhomogeneous measurement space, the proposed SCMDE calculates the ellipsoidal volume for each measurement of interest. Performance of the proposed SCMDE is verified by Monte Carlo simulations for various cases.
SeaSpider: Automated Information Gathering on Vessel Movements in Support of Maritime Domain Awareness

Abstract : SeaSpider is an RD another module extracts relevant ship movement information and populates a database; a third module retrieves information from the database in response to user generated queries. In this memorandum, the SeaSpider concept is introduced, the design details of the prototype are presented, and performance is analysed, with a view to future enhancements.
Transient embolization with microspheres of polyhydroxyalkanoate renders efficient adenoviral transduction of pancreatic capillary in vivo

Our previous study showed an efficient targeting of islets of Langerhans by adenoviral injection via the celiac trunk. Unexpectedly, none of the endothelial cells was infected given the direct contact between adenoviruses and the capillary wall. The present study intended to provide an efficient approach for adenoviral targeting of the microcapillary endothelial cells in the pancreas.
Religion, law and human rights in Zimbabwe

This article is an audit of the interplay between religion, law and human rights in Zimbabwe. It examines key issues such as the legal framework in place for the protection of freedom of conscience, including court jurisprudence, the religious demography of Zimbabwe, and the place of religion in politics, education and the Zimbabwean lifestyle. It also scrutinises the co-existence of ideologically antagonistic practices, such as Pentecostal Christianity versus indigenous beliefs and practices. The article argues that the subject of religion is not a sensitive one in Zimbabwe, hence it does not easily occur in political or general debates. Drawing from his own experiences, the author concludes that, apart from looking after spiritual needs, churches play a significant role in subsidising the state's obligations in the provision of socio-economic rights such as health, education and food. For this reason, churches have an important place in national politics as partners in development. The article concludes by citing problematic areas involving religion and politics, such as child marriages practised in certain religious groupings. The author also notes the harassment of church leaders who express their alarm about the political and economic melt-down of the country. This is another problem bedevilling a somewhat previously tranquil relationship between the state and religion.
The impact of bariatric surgery on nutritional status of patients

Introduction Currently, surgical treatment is considered to be the most efficient method of dealing with morbid obesity. Aim To evaluate changes in nutritional status after surgical treatment of obesity in the early postoperative period. Material and methods The study included 50 patients (30 women and 20 men) treated surgically due to morbid obesity. During the preliminary visit and during control visits measurements of body mass, height, and waist and hip circumference were conducted. Also, analysis of body content was performed and blood was taken for biochemical analysis. Statistical analysis was conducted using the program Statistica 10. Results Six months after the surgery, in the group of women, significant reduction of average body mass, average waist circumference, average hip circumference and average body mass index (BMI) was observed. Also, significant reduction of the percentage of body fat and an increase in the percentage of fat-free body mass were observed. A significant decrease in muscle mass was also noted. Both in women and in men, 6 months after the surgery, a significant decrease in fasting glucose concentration, fasting insulin and triglycerides in blood serum was observed. Conclusions Bariatric procedures lead to significant body mass, BMI, waist and hip circumference reduction. Loss of body mass is caused mainly by the reduction of fat tissue. Application of surgical procedures in morbid obesity treatment also allowed us to achieve improvement in insulin, glucose and lipid metabolism.
Comparing Usability Problem Identification and Description by Practitioners and Students

Many studies of usability studies count the number of usability problems identified to measure the effectiveness of an evaluation. However, communicating problems is also important to evaluation effectiveness, because a problem found but poorly explained may not be fixed. This study compared lists of usability problems from 21 practitioners and 23 students watching a pre-recorded usability session. Lists were evaluated for the number of problems reported, and for following six guidelines for describing usability problems: be clear and avoid jargon, describe problem severity, provide backing data, describe problem causes, describe user actions, and provide a solution. There was no difference in the number of problems reported by students and practitioners, but there was a difference in their ratings for following several of the guidelines. Using both measures provides a more complete assessment of usability reports.
Ten-Year Follow-Up of 50 Patients with Bulimia Nervosa

Long-term outcome studies for people suffering from bulimia nervosa are few. Ten years after presentation, we followed up 50 patients (49 women, 1 man) who were originally involved in a double-blind, controlled trial of the antidepressant mianserin. Standardised interviews and questionnaires were used to assess eating attitudes and behaviour, psychiatric status and social functioning. A DSM–III–R diagnosis was given where appropriate. Sufficient information to make a diagnosis was obtained for 44 subjects (88%). Of patients traced, 52% had recovered fully and only 9% continued to suffer the full syndrome; 39% continued to experience some symptoms. Significant predictors of favourable outcome were younger age at onset, higher social class and a family history of alcohol abuse. Outcome for bulimia nervosa continues to improve over ten years with the majority of patients eventually making a full recovery or suffering only moderate abnormalities in eating attitudes. Although predictors of recovery were few, it would appear that intervention has a significant impact on ultimate outcome.